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@mickypaganini
Created November 6, 2015 14:55
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Old ipynb with results for trained models on centralized HGam h008 MxAODs (modified folder names for root file loading)
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Notes"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"GRL: v71 <br/>\n",
"No fake photons <br/>\n",
"85% b-tagging efficiency point (loose) <br/>"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/usr/local/lib/python2.7/site-packages/IPython/kernel/__init__.py:13: ShimWarning: The `IPython.kernel` package has been deprecated. You should import from ipykernel or jupyter_client instead.\n",
" \"You should import from ipykernel or jupyter_client instead.\", ShimWarning)\n"
]
}
],
"source": [
"import pandas as pd\n",
"import pandautils as pu\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"from sklearn import linear_model\n",
"import cPickle as pickle\n",
"import glob\n",
"from numpy.lib.recfunctions import stack_arrays\n",
"from root_numpy import root2rec\n",
"%matplotlib notebook"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": true
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamPhotons' of branch 'HGamPhotons' with type '' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamPhotonsAux.' of branch 'HGamPhotonsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamElectrons' of branch 'HGamElectrons' with type '' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamElectronsAux.' of branch 'HGamElectronsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4EMTopoJets' of branch 'HGamAntiKt4EMTopoJets' with type '' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4EMTopoJetsAux.' of branch 'HGamAntiKt4EMTopoJetsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuons' of branch 'HGamMuons' with type '' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsAux.' of branch 'HGamMuonsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Reference_AntiKt4EMTopo' of branch 'HGamMET_Reference_AntiKt4EMTopo' with type '' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Reference_AntiKt4EMTopoAux.' of branch 'HGamMET_Reference_AntiKt4EMTopoAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsInJets' of branch 'HGamMuonsInJets' with type '' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsInJetsAux.' of branch 'HGamMuonsInJetsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamEventInfo' of branch 'HGamEventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamEventInfoAux.' of branch 'HGamEventInfoAux.' with type 'xAOD::AuxInfoBase' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamTruthPhotons' of branch 'HGamTruthPhotons' with type '' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamTruthPhotonsAux.' of branch 'HGamTruthPhotonsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamTruthElectrons' of branch 'HGamTruthElectrons' with type '' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamTruthElectronsAux.' of branch 'HGamTruthElectronsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamTruthMuons' of branch 'HGamTruthMuons' with type '' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamTruthMuonsAux.' of branch 'HGamTruthMuonsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4TruthJets' of branch 'HGamAntiKt4TruthJets' with type '' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4TruthJetsAux.' of branch 'HGamAntiKt4TruthJetsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Truth' of branch 'HGamMET_Truth' with type 'DataVector<xAOD::MissingET_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_TruthAux.' of branch 'HGamMET_TruthAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamTruthHiggsBosons' of branch 'HGamTruthHiggsBosons' with type '' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamTruthHiggsBosonsAux.' of branch 'HGamTruthHiggsBosonsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamTruthEventInfo' of branch 'HGamTruthEventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamTruthEventInfoAux.' of branch 'HGamTruthEventInfoAux.' with type 'xAOD::AuxInfoBase' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'EventInfo' of branch 'EventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
" weight_name)\n"
]
}
],
"source": [
"# -- load in MC\n",
"# -- only to be executed once. Pickled version of the dataframes is saved later and can be loaded in\n",
"#X325_df = pu.root2panda('../MxAOD/framework-00-02-30_rel2.3.32/**.root/*', 'CollectionTree')\n",
"H300_df = pu.root2panda('../MxAOD/framework-00-02-30_rel2.3.32/**.root/*', 'CollectionTree')\n",
"# SMhh_df = pu.root2panda('../MxAOD/framework-00-02-30_rel2.3.32/**.root/*', 'CollectionTree')\n",
"# X275_df = pu.root2panda('../MxAOD/framework-00-02-30_rel2.3.32/**.root/*', 'CollectionTree')\n",
"# X350_df = pu.root2panda('../MxAOD/framework-00-02-30_rel2.3.32/**.root/*', 'CollectionTree')\n",
"\n",
"# ybbj_df = pu.root2panda('../MxAOD/framework-00-02-30_rel2.3.32/**.root/*', 'CollectionTree')\n",
"# ybjj_df = pu.root2panda('../MxAOD/framework-00-02-30_rel2.3.32/**.root/*', 'CollectionTree')\n",
"# yjjj_df = pu.root2panda('../MxAOD/framework-00-02-30_rel2.3.32/**.root/*', 'CollectionTree')\n",
"# yybb_df = pu.root2panda('../MxAOD/framework-00-02-30_rel2.3.32/**.root/*', 'CollectionTree')\n",
"# yybj_df = pu.root2panda('../MxAOD/framework-00-02-30_rel2.3.32/**.root/*', 'CollectionTree')"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"['HGamPhotonsAuxDyn.isTight',\n",
" 'HGamPhotonsAuxDyn.isIsoCone20',\n",
" 'HGamPhotonsAuxDyn.topoetcone20',\n",
" 'HGamPhotonsAuxDyn.isIsoCone20Higgs',\n",
" 'HGamPhotonsAuxDyn.isIsoCone40',\n",
" 'HGamPhotonsAuxDyn.isEMTight',\n",
" 'HGamPhotonsAuxDyn.isIsoCone40CaloOnly',\n",
" 'HGamPhotonsAuxDyn.truthOrigin',\n",
" 'HGamPhotonsAuxDyn.pt',\n",
" 'HGamPhotonsAuxDyn.truthType',\n",
" 'HGamPhotonsAuxDyn.eta',\n",
" 'HGamPhotonsAuxDyn.phi',\n",
" 'HGamPhotonsAuxDyn.m',\n",
" 'HGamPhotonsAuxDyn.isTight_nofudge',\n",
" 'HGamPhotonsAuxDyn.eta_s2',\n",
" 'HGamPhotonsAuxDyn.isEMTight_nofudge',\n",
" 'HGamPhotonsAuxDyn.relEreso',\n",
" 'HGamPhotonsAuxDyn.ptcone20',\n",
" 'HGamPhotonsAuxDyn.isConv',\n",
" 'HGamAntiKt4EMTopoJetsAuxDyn.MV2c20_60',\n",
" 'HGamAntiKt4EMTopoJetsAuxDyn.MV2c20_60_Eff',\n",
" 'HGamAntiKt4EMTopoJetsAuxDyn.SF_MV2c20_60',\n",
" 'HGamAntiKt4EMTopoJetsAuxDyn.MV2c20_70',\n",
" 'HGamAntiKt4EMTopoJetsAuxDyn.MV2c20_70_Eff',\n",
" 'HGamAntiKt4EMTopoJetsAuxDyn.pt',\n",
" 'HGamAntiKt4EMTopoJetsAuxDyn.SF_MV2c20_70',\n",
" 'HGamAntiKt4EMTopoJetsAuxDyn.eta',\n",
" 'HGamAntiKt4EMTopoJetsAuxDyn.MV2c20_77',\n",
" 'HGamAntiKt4EMTopoJetsAuxDyn.phi',\n",
" 'HGamAntiKt4EMTopoJetsAuxDyn.MV2c20_77_Eff',\n",
" 'HGamAntiKt4EMTopoJetsAuxDyn.m',\n",
" 'HGamAntiKt4EMTopoJetsAuxDyn.SF_MV2c20_77',\n",
" 'HGamAntiKt4EMTopoJetsAuxDyn.MV2c20_85',\n",
" 'HGamAntiKt4EMTopoJetsAuxDyn.MV2c20_85_Eff',\n",
" 'HGamAntiKt4EMTopoJetsAuxDyn.SF_MV2c20_85',\n",
" 'HGamAntiKt4EMTopoJetsAuxDyn.Jvt',\n",
" 'HGamAntiKt4EMTopoJetsAuxDyn.DetectorEta',\n",
" 'HGamMET_Reference_AntiKt4EMTopoAuxDyn.source',\n",
" 'HGamMET_Reference_AntiKt4EMTopoAuxDyn.name',\n",
" 'HGamMET_Reference_AntiKt4EMTopoAuxDyn.sumet',\n",
" 'HGamMET_Reference_AntiKt4EMTopoAuxDyn.mpx',\n",
" 'HGamMET_Reference_AntiKt4EMTopoAuxDyn.mpy',\n",
" 'HGamMuonsInJetsAuxDyn.pt',\n",
" 'HGamMuonsInJetsAuxDyn.ptvarcone20',\n",
" 'HGamMuonsInJetsAuxDyn.eta',\n",
" 'HGamMuonsInJetsAuxDyn.phi',\n",
" 'HGamMuonsInJetsAuxDyn.topoetcone20',\n",
" 'HGamMuonsInJetsAuxDyn.passIPCut',\n",
" 'HGamEventInfoAuxDyn.selectedVertexZ',\n",
" 'HGamEventInfoAuxDyn.hardestVertexZ',\n",
" 'HGamEventInfoAuxDyn.m_yy_resolution',\n",
" 'HGamEventInfoAuxDyn.truthVertexZ',\n",
" 'HGamEventInfoAuxDyn.NLoosePhotons',\n",
" 'HGamEventInfoAuxDyn.eventShapeDensity',\n",
" 'HGamEventInfoAuxDyn.mu',\n",
" 'HGamEventInfoAuxDyn.TST_met',\n",
" 'HGamEventInfoAuxDyn.TST_sumet',\n",
" 'HGamEventInfoAuxDyn.CST_met',\n",
" 'HGamEventInfoAuxDyn.CST_sumet',\n",
" 'HGamEventInfoAuxDyn.isPassedPreselection',\n",
" 'HGamEventInfoAuxDyn.isPassedPID',\n",
" 'HGamEventInfoAuxDyn.yAbs_yy',\n",
" 'HGamEventInfoAuxDyn.isPassedIsolation',\n",
" 'HGamEventInfoAuxDyn.pTt_yy',\n",
" 'HGamEventInfoAuxDyn.isPassedRelPtCuts',\n",
" 'HGamEventInfoAuxDyn.m_yy',\n",
" 'HGamEventInfoAuxDyn.isPassedMassCut',\n",
" 'HGamEventInfoAuxDyn.pT_yy',\n",
" 'HGamEventInfoAuxDyn.crossSectionBRfilterEff',\n",
" 'HGamEventInfoAuxDyn.cosTS_yy',\n",
" 'HGamEventInfoAuxDyn.Njets',\n",
" 'HGamEventInfoAuxDyn.m_jj',\n",
" 'HGamEventInfoAuxDyn.Dy_j_j',\n",
" 'HGamEventInfoAuxDyn.Dphi_yy_jj',\n",
" 'HGamEventInfoAuxDyn.isPassedBasic',\n",
" 'HGamEventInfoAuxDyn.isPassed',\n",
" 'HGamEventInfoAuxDyn.isPassedEventClean',\n",
" 'HGamEventInfoAuxDyn.isDalitz',\n",
" 'HGamEventInfoAuxDyn.cutFlow',\n",
" 'HGamEventInfoAuxDyn.weightInitial',\n",
" 'HGamEventInfoAuxDyn.weight',\n",
" 'HGamEventInfoAuxDyn.weightCategory',\n",
" 'HGamEventInfoAuxDyn.category',\n",
" 'HGamEventInfoAuxDyn.numberOfPrimaryVertices',\n",
" 'HGamTruthPhotonsAuxDyn.px',\n",
" 'HGamTruthPhotonsAuxDyn.truthOrigin',\n",
" 'HGamTruthPhotonsAuxDyn.pt',\n",
" 'HGamTruthPhotonsAuxDyn.truthType',\n",
" 'HGamTruthPhotonsAuxDyn.py',\n",
" 'HGamTruthPhotonsAuxDyn.eta',\n",
" 'HGamTruthPhotonsAuxDyn.pz',\n",
" 'HGamTruthPhotonsAuxDyn.e',\n",
" 'HGamTruthPhotonsAuxDyn.m',\n",
" 'HGamTruthPhotonsAuxDyn.isIsolated',\n",
" 'HGamTruthPhotonsAuxDyn.etcone20',\n",
" 'HGamTruthPhotonsAuxDyn.etcone40',\n",
" 'HGamAntiKt4TruthJetsAuxDyn.pt',\n",
" 'HGamAntiKt4TruthJetsAuxDyn.eta',\n",
" 'HGamAntiKt4TruthJetsAuxDyn.phi',\n",
" 'HGamAntiKt4TruthJetsAuxDyn.m',\n",
" 'HGamMET_TruthAuxDyn.source',\n",
" 'HGamMET_TruthAuxDyn.name',\n",
" 'HGamMET_TruthAuxDyn.sumet',\n",
" 'HGamMET_TruthAuxDyn.mpx',\n",
" 'HGamMET_TruthAuxDyn.mpy',\n",
" 'HGamTruthHiggsBosonsAuxDyn.pt',\n",
" 'HGamTruthHiggsBosonsAuxDyn.eta',\n",
" 'HGamTruthHiggsBosonsAuxDyn.px',\n",
" 'HGamTruthHiggsBosonsAuxDyn.py',\n",
" 'HGamTruthHiggsBosonsAuxDyn.m',\n",
" 'HGamTruthHiggsBosonsAuxDyn.pz',\n",
" 'HGamTruthHiggsBosonsAuxDyn.e',\n",
" 'HGamTruthEventInfoAuxDyn.Njets',\n",
" 'HGamTruthEventInfoAuxDyn.m_jj',\n",
" 'HGamTruthEventInfoAuxDyn.pT_h1',\n",
" 'HGamTruthEventInfoAuxDyn.Dy_j_j',\n",
" 'HGamTruthEventInfoAuxDyn.pT_h2',\n",
" 'HGamTruthEventInfoAuxDyn.y_h1',\n",
" 'HGamTruthEventInfoAuxDyn.TruthNonInt_met',\n",
" 'HGamTruthEventInfoAuxDyn.y_h2',\n",
" 'HGamTruthEventInfoAuxDyn.TruthInt_sumet',\n",
" 'HGamTruthEventInfoAuxDyn.Dphi_yy_jj',\n",
" 'HGamTruthEventInfoAuxDyn.m_h1',\n",
" 'HGamTruthEventInfoAuxDyn.m_h2',\n",
" 'HGamTruthEventInfoAuxDyn.yAbs_yy',\n",
" 'HGamTruthEventInfoAuxDyn.pTt_yy',\n",
" 'HGamTruthEventInfoAuxDyn.m_yy',\n",
" 'HGamTruthEventInfoAuxDyn.pT_yy',\n",
" 'HGamTruthEventInfoAuxDyn.isFiducial',\n",
" 'HGamTruthEventInfoAuxDyn.cosTS_yy',\n",
" 'HGamTruthEventInfoAuxDyn.isFiducialKinOnly',\n",
" 'EventInfoAuxDyn.passTrig_HLT_g35_loose_g25_loose',\n",
" 'EventInfoAuxDyn.passTrig_HLT_g35_medium_g25_medium',\n",
" 'EventInfoAuxDyn.runNumber',\n",
" 'EventInfoAuxDyn.eventTypeBitmask',\n",
" 'EventInfoAuxDyn.eventNumber',\n",
" 'EventInfoAuxDyn.lumiBlock',\n",
" 'EventInfoAuxDyn.mcChannelNumber',\n",
" 'EventInfoAuxDyn.averageInteractionsPerCrossing',\n",
" 'EventInfoAuxDyn.mcEventWeights',\n",
" 'EventInfoAuxDyn.passTrig_HLT_2g20_tight',\n",
" 'HGamMuonsAuxDyn.pt',\n",
" 'HGamMuonsAuxDyn.ptvarcone20',\n",
" 'HGamMuonsAuxDyn.eta',\n",
" 'HGamMuonsAuxDyn.phi',\n",
" 'HGamMuonsAuxDyn.topoetcone20',\n",
" 'HGamMuonsAuxDyn.passIPCut',\n",
" 'HGamTruthElectronsAuxDyn.pt',\n",
" 'HGamTruthElectronsAuxDyn.eta',\n",
" 'HGamTruthElectronsAuxDyn.px',\n",
" 'HGamTruthElectronsAuxDyn.py',\n",
" 'HGamTruthElectronsAuxDyn.m',\n",
" 'HGamTruthElectronsAuxDyn.pz',\n",
" 'HGamTruthElectronsAuxDyn.e',\n",
" 'HGamElectronsAuxDyn.pt',\n",
" 'HGamElectronsAuxDyn.ptvarcone20',\n",
" 'HGamElectronsAuxDyn.eta',\n",
" 'HGamElectronsAuxDyn.phi',\n",
" 'HGamElectronsAuxDyn.m',\n",
" 'HGamElectronsAuxDyn.topoetcone20',\n",
" 'HGamTruthMuonsAuxDyn.pt',\n",
" 'HGamTruthMuonsAuxDyn.eta',\n",
" 'HGamTruthMuonsAuxDyn.px',\n",
" 'HGamTruthMuonsAuxDyn.py',\n",
" 'HGamTruthMuonsAuxDyn.m',\n",
" 'HGamTruthMuonsAuxDyn.pz',\n",
" 'HGamTruthMuonsAuxDyn.e']"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"[key for key in X325_df.keys()]"
]
},
{
"cell_type": "code",
"execution_count": 261,
"metadata": {
"collapsed": true
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'EventInfo' of branch 'EventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4EMTopoJets' of branch 'HGamAntiKt4EMTopoJets' with type 'DataVector<xAOD::Jet_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamElectrons' of branch 'HGamElectrons' with type 'DataVector<xAOD::Electron_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamEventInfo' of branch 'HGamEventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Reference_AntiKt4EMTopo' of branch 'HGamMET_Reference_AntiKt4EMTopo' with type 'xAOD::MissingETContainer_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuons' of branch 'HGamMuons' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsInJets' of branch 'HGamMuonsInJets' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamPhotons' of branch 'HGamPhotons' with type 'DataVector<xAOD::Photon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'EventInfo' of branch 'EventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4EMTopoJets' of branch 'HGamAntiKt4EMTopoJets' with type 'DataVector<xAOD::Jet_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamElectrons' of branch 'HGamElectrons' with type 'DataVector<xAOD::Electron_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamEventInfo' of branch 'HGamEventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Reference_AntiKt4EMTopo' of branch 'HGamMET_Reference_AntiKt4EMTopo' with type 'xAOD::MissingETContainer_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuons' of branch 'HGamMuons' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsInJets' of branch 'HGamMuonsInJets' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamPhotons' of branch 'HGamPhotons' with type 'DataVector<xAOD::Photon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamPhotons' of branch 'HGamPhotons' with type 'DataVector<xAOD::Photon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamPhotonsAux.' of branch 'HGamPhotonsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamElectrons' of branch 'HGamElectrons' with type 'DataVector<xAOD::Electron_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamElectronsAux.' of branch 'HGamElectronsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4EMTopoJets' of branch 'HGamAntiKt4EMTopoJets' with type 'DataVector<xAOD::Jet_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4EMTopoJetsAux.' of branch 'HGamAntiKt4EMTopoJetsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuons' of branch 'HGamMuons' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsAux.' of branch 'HGamMuonsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Reference_AntiKt4EMTopo' of branch 'HGamMET_Reference_AntiKt4EMTopo' with type 'xAOD::MissingETContainer_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Reference_AntiKt4EMTopoAux.' of branch 'HGamMET_Reference_AntiKt4EMTopoAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsInJets' of branch 'HGamMuonsInJets' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsInJetsAux.' of branch 'HGamMuonsInJetsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamEventInfo' of branch 'HGamEventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamEventInfoAux.' of branch 'HGamEventInfoAux.' with type 'xAOD::AuxInfoBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'EventInfo' of branch 'EventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'EventInfo' of branch 'EventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4EMTopoJets' of branch 'HGamAntiKt4EMTopoJets' with type 'DataVector<xAOD::Jet_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamElectrons' of branch 'HGamElectrons' with type 'DataVector<xAOD::Electron_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamEventInfo' of branch 'HGamEventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Reference_AntiKt4EMTopo' of branch 'HGamMET_Reference_AntiKt4EMTopo' with type 'xAOD::MissingETContainer_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuons' of branch 'HGamMuons' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsInJets' of branch 'HGamMuonsInJets' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamPhotons' of branch 'HGamPhotons' with type 'DataVector<xAOD::Photon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'EventInfo' of branch 'EventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4EMTopoJets' of branch 'HGamAntiKt4EMTopoJets' with type 'DataVector<xAOD::Jet_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamElectrons' of branch 'HGamElectrons' with type 'DataVector<xAOD::Electron_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamEventInfo' of branch 'HGamEventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Reference_AntiKt4EMTopo' of branch 'HGamMET_Reference_AntiKt4EMTopo' with type 'xAOD::MissingETContainer_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuons' of branch 'HGamMuons' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsInJets' of branch 'HGamMuonsInJets' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamPhotons' of branch 'HGamPhotons' with type 'DataVector<xAOD::Photon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'EventInfo' of branch 'EventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4EMTopoJets' of branch 'HGamAntiKt4EMTopoJets' with type 'DataVector<xAOD::Jet_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamElectrons' of branch 'HGamElectrons' with type 'DataVector<xAOD::Electron_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamEventInfo' of branch 'HGamEventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Reference_AntiKt4EMTopo' of branch 'HGamMET_Reference_AntiKt4EMTopo' with type 'xAOD::MissingETContainer_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuons' of branch 'HGamMuons' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsInJets' of branch 'HGamMuonsInJets' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamPhotons' of branch 'HGamPhotons' with type 'DataVector<xAOD::Photon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamPhotons' of branch 'HGamPhotons' with type 'DataVector<xAOD::Photon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamPhotonsAux.' of branch 'HGamPhotonsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamElectrons' of branch 'HGamElectrons' with type 'DataVector<xAOD::Electron_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamElectronsAux.' of branch 'HGamElectronsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4EMTopoJets' of branch 'HGamAntiKt4EMTopoJets' with type 'DataVector<xAOD::Jet_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4EMTopoJetsAux.' of branch 'HGamAntiKt4EMTopoJetsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuons' of branch 'HGamMuons' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsAux.' of branch 'HGamMuonsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Reference_AntiKt4EMTopo' of branch 'HGamMET_Reference_AntiKt4EMTopo' with type 'xAOD::MissingETContainer_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Reference_AntiKt4EMTopoAux.' of branch 'HGamMET_Reference_AntiKt4EMTopoAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsInJets' of branch 'HGamMuonsInJets' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsInJetsAux.' of branch 'HGamMuonsInJetsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamEventInfo' of branch 'HGamEventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamEventInfoAux.' of branch 'HGamEventInfoAux.' with type 'xAOD::AuxInfoBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'EventInfo' of branch 'EventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamPhotons' of branch 'HGamPhotons' with type 'DataVector<xAOD::Photon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamPhotonsAux.' of branch 'HGamPhotonsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamElectrons' of branch 'HGamElectrons' with type 'DataVector<xAOD::Electron_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamElectronsAux.' of branch 'HGamElectronsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4EMTopoJets' of branch 'HGamAntiKt4EMTopoJets' with type 'DataVector<xAOD::Jet_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4EMTopoJetsAux.' of branch 'HGamAntiKt4EMTopoJetsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuons' of branch 'HGamMuons' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsAux.' of branch 'HGamMuonsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Reference_AntiKt4EMTopo' of branch 'HGamMET_Reference_AntiKt4EMTopo' with type 'xAOD::MissingETContainer_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Reference_AntiKt4EMTopoAux.' of branch 'HGamMET_Reference_AntiKt4EMTopoAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsInJets' of branch 'HGamMuonsInJets' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsInJetsAux.' of branch 'HGamMuonsInJetsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamEventInfo' of branch 'HGamEventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamEventInfoAux.' of branch 'HGamEventInfoAux.' with type 'xAOD::AuxInfoBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'EventInfo' of branch 'EventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamPhotons' of branch 'HGamPhotons' with type 'DataVector<xAOD::Photon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamPhotonsAux.' of branch 'HGamPhotonsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamElectrons' of branch 'HGamElectrons' with type 'DataVector<xAOD::Electron_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamElectronsAux.' of branch 'HGamElectronsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4EMTopoJets' of branch 'HGamAntiKt4EMTopoJets' with type 'DataVector<xAOD::Jet_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4EMTopoJetsAux.' of branch 'HGamAntiKt4EMTopoJetsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuons' of branch 'HGamMuons' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsAux.' of branch 'HGamMuonsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Reference_AntiKt4EMTopo' of branch 'HGamMET_Reference_AntiKt4EMTopo' with type 'xAOD::MissingETContainer_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Reference_AntiKt4EMTopoAux.' of branch 'HGamMET_Reference_AntiKt4EMTopoAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsInJets' of branch 'HGamMuonsInJets' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsInJetsAux.' of branch 'HGamMuonsInJetsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamEventInfo' of branch 'HGamEventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamEventInfoAux.' of branch 'HGamEventInfoAux.' with type 'xAOD::AuxInfoBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'EventInfo' of branch 'EventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamPhotons' of branch 'HGamPhotons' with type 'DataVector<xAOD::Photon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamElectrons' of branch 'HGamElectrons' with type 'DataVector<xAOD::Electron_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamElectronsAux.' of branch 'HGamElectronsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4EMTopoJets' of branch 'HGamAntiKt4EMTopoJets' with type 'DataVector<xAOD::Jet_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4EMTopoJetsAux.' of branch 'HGamAntiKt4EMTopoJetsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuons' of branch 'HGamMuons' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsAux.' of branch 'HGamMuonsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Reference_AntiKt4EMTopo' of branch 'HGamMET_Reference_AntiKt4EMTopo' with type 'xAOD::MissingETContainer_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Reference_AntiKt4EMTopoAux.' of branch 'HGamMET_Reference_AntiKt4EMTopoAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsInJets' of branch 'HGamMuonsInJets' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsInJetsAux.' of branch 'HGamMuonsInJetsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamEventInfo' of branch 'HGamEventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamEventInfoAux.' of branch 'HGamEventInfoAux.' with type 'xAOD::AuxInfoBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'EventInfo' of branch 'EventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamPhotons' of branch 'HGamPhotons' with type 'DataVector<xAOD::Photon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamPhotonsAux.' of branch 'HGamPhotonsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamElectrons' of branch 'HGamElectrons' with type 'DataVector<xAOD::Electron_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamElectronsAux.' of branch 'HGamElectronsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4EMTopoJets' of branch 'HGamAntiKt4EMTopoJets' with type 'DataVector<xAOD::Jet_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4EMTopoJetsAux.' of branch 'HGamAntiKt4EMTopoJetsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuons' of branch 'HGamMuons' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsAux.' of branch 'HGamMuonsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Reference_AntiKt4EMTopo' of branch 'HGamMET_Reference_AntiKt4EMTopo' with type 'xAOD::MissingETContainer_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Reference_AntiKt4EMTopoAux.' of branch 'HGamMET_Reference_AntiKt4EMTopoAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsInJets' of branch 'HGamMuonsInJets' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsInJetsAux.' of branch 'HGamMuonsInJetsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamEventInfo' of branch 'HGamEventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamEventInfoAux.' of branch 'HGamEventInfoAux.' with type 'xAOD::AuxInfoBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'EventInfo' of branch 'EventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamPhotons' of branch 'HGamPhotons' with type 'DataVector<xAOD::Photon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamPhotonsAux.' of branch 'HGamPhotonsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamElectrons' of branch 'HGamElectrons' with type 'DataVector<xAOD::Electron_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamElectronsAux.' of branch 'HGamElectronsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4EMTopoJets' of branch 'HGamAntiKt4EMTopoJets' with type 'DataVector<xAOD::Jet_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4EMTopoJetsAux.' of branch 'HGamAntiKt4EMTopoJetsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuons' of branch 'HGamMuons' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsAux.' of branch 'HGamMuonsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Reference_AntiKt4EMTopo' of branch 'HGamMET_Reference_AntiKt4EMTopo' with type 'xAOD::MissingETContainer_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Reference_AntiKt4EMTopoAux.' of branch 'HGamMET_Reference_AntiKt4EMTopoAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsInJets' of branch 'HGamMuonsInJets' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsInJetsAux.' of branch 'HGamMuonsInJetsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamEventInfo' of branch 'HGamEventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamEventInfoAux.' of branch 'HGamEventInfoAux.' with type 'xAOD::AuxInfoBase' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'EventInfo' of branch 'EventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'EventInfo' of branch 'EventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4EMTopoJets' of branch 'HGamAntiKt4EMTopoJets' with type 'DataVector<xAOD::Jet_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamElectrons' of branch 'HGamElectrons' with type 'DataVector<xAOD::Electron_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamEventInfo' of branch 'HGamEventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Reference_AntiKt4EMTopo' of branch 'HGamMET_Reference_AntiKt4EMTopo' with type 'xAOD::MissingETContainer_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuons' of branch 'HGamMuons' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsInJets' of branch 'HGamMuonsInJets' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamPhotons' of branch 'HGamPhotons' with type 'DataVector<xAOD::Photon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'EventInfo' of branch 'EventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4EMTopoJets' of branch 'HGamAntiKt4EMTopoJets' with type 'DataVector<xAOD::Jet_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamElectrons' of branch 'HGamElectrons' with type 'DataVector<xAOD::Electron_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamEventInfo' of branch 'HGamEventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Reference_AntiKt4EMTopo' of branch 'HGamMET_Reference_AntiKt4EMTopo' with type 'xAOD::MissingETContainer_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuons' of branch 'HGamMuons' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsInJets' of branch 'HGamMuonsInJets' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamPhotons' of branch 'HGamPhotons' with type 'DataVector<xAOD::Photon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'EventInfo' of branch 'EventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4EMTopoJets' of branch 'HGamAntiKt4EMTopoJets' with type 'DataVector<xAOD::Jet_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamElectrons' of branch 'HGamElectrons' with type 'DataVector<xAOD::Electron_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamEventInfo' of branch 'HGamEventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Reference_AntiKt4EMTopo' of branch 'HGamMET_Reference_AntiKt4EMTopo' with type 'xAOD::MissingETContainer_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuons' of branch 'HGamMuons' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsInJets' of branch 'HGamMuonsInJets' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamPhotons' of branch 'HGamPhotons' with type 'DataVector<xAOD::Photon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'EventInfo' of branch 'EventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4EMTopoJets' of branch 'HGamAntiKt4EMTopoJets' with type 'DataVector<xAOD::Jet_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamElectrons' of branch 'HGamElectrons' with type 'DataVector<xAOD::Electron_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamEventInfo' of branch 'HGamEventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Reference_AntiKt4EMTopo' of branch 'HGamMET_Reference_AntiKt4EMTopo' with type 'xAOD::MissingETContainer_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuons' of branch 'HGamMuons' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsInJets' of branch 'HGamMuonsInJets' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamPhotons' of branch 'HGamPhotons' with type 'DataVector<xAOD::Photon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'EventInfo' of branch 'EventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4EMTopoJets' of branch 'HGamAntiKt4EMTopoJets' with type 'DataVector<xAOD::Jet_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamElectrons' of branch 'HGamElectrons' with type 'DataVector<xAOD::Electron_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamEventInfo' of branch 'HGamEventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Reference_AntiKt4EMTopo' of branch 'HGamMET_Reference_AntiKt4EMTopo' with type 'xAOD::MissingETContainer_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuons' of branch 'HGamMuons' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsInJets' of branch 'HGamMuonsInJets' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamPhotons' of branch 'HGamPhotons' with type 'DataVector<xAOD::Photon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'EventInfo' of branch 'EventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4EMTopoJets' of branch 'HGamAntiKt4EMTopoJets' with type 'DataVector<xAOD::Jet_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamElectrons' of branch 'HGamElectrons' with type 'DataVector<xAOD::Electron_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamEventInfo' of branch 'HGamEventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Reference_AntiKt4EMTopo' of branch 'HGamMET_Reference_AntiKt4EMTopo' with type 'xAOD::MissingETContainer_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuons' of branch 'HGamMuons' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsInJets' of branch 'HGamMuonsInJets' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
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"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamPhotons' of branch 'HGamPhotons' with type 'DataVector<xAOD::Photon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamPhotons' of branch 'HGamPhotons' with type 'DataVector<xAOD::Photon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamPhotonsAux.' of branch 'HGamPhotonsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamElectrons' of branch 'HGamElectrons' with type 'DataVector<xAOD::Electron_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamElectronsAux.' of branch 'HGamElectronsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4EMTopoJets' of branch 'HGamAntiKt4EMTopoJets' with type 'DataVector<xAOD::Jet_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4EMTopoJetsAux.' of branch 'HGamAntiKt4EMTopoJetsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuons' of branch 'HGamMuons' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsAux.' of branch 'HGamMuonsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Reference_AntiKt4EMTopo' of branch 'HGamMET_Reference_AntiKt4EMTopo' with type 'xAOD::MissingETContainer_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Reference_AntiKt4EMTopoAux.' of branch 'HGamMET_Reference_AntiKt4EMTopoAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsInJets' of branch 'HGamMuonsInJets' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsInJetsAux.' of branch 'HGamMuonsInJetsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamEventInfo' of branch 'HGamEventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamEventInfoAux.' of branch 'HGamEventInfoAux.' with type 'xAOD::AuxInfoBase' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'EventInfo' of branch 'EventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'EventInfo' of branch 'EventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4EMTopoJets' of branch 'HGamAntiKt4EMTopoJets' with type 'DataVector<xAOD::Jet_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamElectrons' of branch 'HGamElectrons' with type 'DataVector<xAOD::Electron_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamEventInfo' of branch 'HGamEventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Reference_AntiKt4EMTopo' of branch 'HGamMET_Reference_AntiKt4EMTopo' with type 'xAOD::MissingETContainer_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuons' of branch 'HGamMuons' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsInJets' of branch 'HGamMuonsInJets' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamPhotons' of branch 'HGamPhotons' with type 'DataVector<xAOD::Photon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'EventInfo' of branch 'EventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4EMTopoJets' of branch 'HGamAntiKt4EMTopoJets' with type 'DataVector<xAOD::Jet_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamElectrons' of branch 'HGamElectrons' with type 'DataVector<xAOD::Electron_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamEventInfo' of branch 'HGamEventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Reference_AntiKt4EMTopo' of branch 'HGamMET_Reference_AntiKt4EMTopo' with type 'xAOD::MissingETContainer_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuons' of branch 'HGamMuons' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsInJets' of branch 'HGamMuonsInJets' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamPhotons' of branch 'HGamPhotons' with type 'DataVector<xAOD::Photon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'EventInfo' of branch 'EventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4EMTopoJets' of branch 'HGamAntiKt4EMTopoJets' with type 'DataVector<xAOD::Jet_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamElectrons' of branch 'HGamElectrons' with type 'DataVector<xAOD::Electron_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamEventInfo' of branch 'HGamEventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Reference_AntiKt4EMTopo' of branch 'HGamMET_Reference_AntiKt4EMTopo' with type 'xAOD::MissingETContainer_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuons' of branch 'HGamMuons' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsInJets' of branch 'HGamMuonsInJets' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamPhotons' of branch 'HGamPhotons' with type 'DataVector<xAOD::Photon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'EventInfo' of branch 'EventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4EMTopoJets' of branch 'HGamAntiKt4EMTopoJets' with type 'DataVector<xAOD::Jet_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamElectrons' of branch 'HGamElectrons' with type 'DataVector<xAOD::Electron_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamEventInfo' of branch 'HGamEventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Reference_AntiKt4EMTopo' of branch 'HGamMET_Reference_AntiKt4EMTopo' with type 'xAOD::MissingETContainer_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuons' of branch 'HGamMuons' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsInJets' of branch 'HGamMuonsInJets' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamPhotons' of branch 'HGamPhotons' with type 'DataVector<xAOD::Photon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'EventInfo' of branch 'EventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4EMTopoJets' of branch 'HGamAntiKt4EMTopoJets' with type 'DataVector<xAOD::Jet_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamElectrons' of branch 'HGamElectrons' with type 'DataVector<xAOD::Electron_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamEventInfo' of branch 'HGamEventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Reference_AntiKt4EMTopo' of branch 'HGamMET_Reference_AntiKt4EMTopo' with type 'xAOD::MissingETContainer_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuons' of branch 'HGamMuons' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsInJets' of branch 'HGamMuonsInJets' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamPhotons' of branch 'HGamPhotons' with type 'DataVector<xAOD::Photon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamPhotons' of branch 'HGamPhotons' with type 'DataVector<xAOD::Photon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamPhotonsAux.' of branch 'HGamPhotonsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamElectrons' of branch 'HGamElectrons' with type 'DataVector<xAOD::Electron_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamElectronsAux.' of branch 'HGamElectronsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4EMTopoJets' of branch 'HGamAntiKt4EMTopoJets' with type 'DataVector<xAOD::Jet_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4EMTopoJetsAux.' of branch 'HGamAntiKt4EMTopoJetsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuons' of branch 'HGamMuons' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsAux.' of branch 'HGamMuonsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Reference_AntiKt4EMTopo' of branch 'HGamMET_Reference_AntiKt4EMTopo' with type 'xAOD::MissingETContainer_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Reference_AntiKt4EMTopoAux.' of branch 'HGamMET_Reference_AntiKt4EMTopoAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsInJets' of branch 'HGamMuonsInJets' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsInJetsAux.' of branch 'HGamMuonsInJetsAux.' with type 'xAOD::AuxContainerBase' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamEventInfo' of branch 'HGamEventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamEventInfoAux.' of branch 'HGamEventInfoAux.' with type 'xAOD::AuxInfoBase' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'EventInfo' of branch 'EventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'EventInfo' of branch 'EventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4EMTopoJets' of branch 'HGamAntiKt4EMTopoJets' with type 'DataVector<xAOD::Jet_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamElectrons' of branch 'HGamElectrons' with type 'DataVector<xAOD::Electron_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamEventInfo' of branch 'HGamEventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Reference_AntiKt4EMTopo' of branch 'HGamMET_Reference_AntiKt4EMTopo' with type 'xAOD::MissingETContainer_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuons' of branch 'HGamMuons' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsInJets' of branch 'HGamMuonsInJets' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamPhotons' of branch 'HGamPhotons' with type 'DataVector<xAOD::Photon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'EventInfo' of branch 'EventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamAntiKt4EMTopoJets' of branch 'HGamAntiKt4EMTopoJets' with type 'DataVector<xAOD::Jet_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamElectrons' of branch 'HGamElectrons' with type 'DataVector<xAOD::Electron_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamEventInfo' of branch 'HGamEventInfo' with type 'xAOD::EventInfo_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMET_Reference_AntiKt4EMTopo' of branch 'HGamMET_Reference_AntiKt4EMTopo' with type 'xAOD::MissingETContainer_v1' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuons' of branch 'HGamMuons' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamMuonsInJets' of branch 'HGamMuonsInJets' with type 'DataVector<xAOD::Muon_v1>' (skipping)\n",
" weight_name)\n",
"/usr/local/lib/python2.7/site-packages/root_numpy/_tree.py:205: RootNumpyUnconvertibleWarning: cannot convert leaf 'HGamPhotons' of branch 'HGamPhotons' with type 'DataVector<xAOD::Photon_v1>' (skipping)\n",
" weight_name)\n"
]
}
],
"source": [
"# -- load in data if you want to test models on data\n",
"datafiles = glob.glob('../MxAOD/HGamma_MxAODs/data/data15_13TeV.0027*.root')\n",
"ss = stack_arrays([root2rec(fpath, 'CollectionTree') for fpath in datafiles])\n",
"data_df = pd.DataFrame(ss.data)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[ 8.62502812e+04 1.19836781e+05 2.18938798e-01 7.86869062e+04\n",
" -5.50082803e-01 0.00000000e+00 -1.07864094e+00 -1.34915781e+00\n",
" 2.90111995e+00 1.25000000e+05 1.25000000e+05 5.49923599e-01\n",
" 2.89044766e+04 1.24590945e+05 1.17273297e+05 6.71235984e-03]\n"
]
}
],
"source": [
"# -- truth variables\n",
"# -- not used for anything now, really. I was just playing around.\n",
"truth_event_vars = [key for key in X325_df.keys() if all( (s in key for s in['Event','Truth']) )]\n",
"# -- remove mismodeled variables\n",
"truth_event_vars.remove('HGamTruthEventInfoAuxDyn.Njets')\n",
"truth_event_vars.remove('HGamTruthEventInfoAuxDyn.isFiducial')\n",
"truth_event_vars.remove('HGamTruthEventInfoAuxDyn.isFiducialKinOnly')\n",
"print (np.array(X325_df[truth_event_vars])[0]) # -- quantities for the first event"
]
},
{
"cell_type": "code",
"execution_count": 276,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# -- interesting variables to use for learning purposes\n",
"reco_event_vars = [key for key in X325_df.keys() if all( (s in key for s in['HGamEventInfoAuxDyn']) )]\n",
"# -- remove mismodeled ones, weights and things that cannot be used for learning\n",
"reco_event_vars = [i for i in reco_event_vars if i not in ['HGamEventInfoAuxDyn.truthVertexZ',\n",
" 'HGamEventInfoAuxDyn.crossSectionBRfilterEff', \n",
" 'HGamEventInfoAuxDyn.Njets', \n",
" 'HGamEventInfoAuxDyn.cutFlow',\n",
" 'HGamEventInfoAuxDyn.weightInitial',\n",
" 'HGamEventInfoAuxDyn.weight',\n",
" 'HGamEventInfoAuxDyn.weightCategory',\n",
" 'HGamEventInfoAuxDyn.category',\n",
" 'HGamEventInfoAuxDyn.isDalitz',\n",
" 'HGamEventInfoAuxDyn.isPassedBasic']]"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"dataframes = [X325_df,\n",
"H300_df,\n",
"SMhh_df,\n",
"X275_df,\n",
"X350_df,\n",
"ybbj_df,\n",
"ybjj_df,\n",
"yjjj_df,\n",
"yybb_df,\n",
"yybj_df]\n",
"\n",
"dataframe_names = ['X325',\n",
"'H300',\n",
"'SMhh',\n",
"'X275',\n",
"'X350',\n",
"'ybbj',\n",
"'ybjj',\n",
"'yjjj',\n",
"'yybb',\n",
"'yybj']"
]
},
{
"cell_type": "code",
"execution_count": 277,
"metadata": {
"collapsed": true
},
"outputs": [
{
"ename": "NameError",
"evalue": "name 'dataframes' is not defined",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-277-9872cfe605f1>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m# -- slice dataframes by reducing columns to only useful event info\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mdataframes\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mreco_event_vars\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mdf\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mdataframes\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m;\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;31mNameError\u001b[0m: name 'dataframes' is not defined"
]
}
],
"source": [
"# -- slice dataframes by reducing columns to only useful event info\n",
"dataframes = [df[reco_event_vars] for df in dataframes];"
]
},
{
"cell_type": "code",
"execution_count": 263,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"data_df = data_df[reco_event_vars] \n",
"\n",
"# 'HGamEventInfoAuxDyn.truthVertexZ'\n",
"# 'HGamEventInfoAuxDyn.crossSectionBRfilterEff', \n",
"# 'HGamEventInfoAuxDyn.isDalitz'\n",
"# are not in the data files so cannot be used for classification!"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/usr/local/lib/python2.7/site-packages/ipykernel/__main__.py:3: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
" app.launch_new_instance()\n"
]
}
],
"source": [
"# -- add a column called 'class' to each dataframe which will contain a string with the name of the sample\n",
"for _df, _n in zip(dataframes, dataframe_names):\n",
" _df['class'] = [_n] * _df.shape[0]"
]
},
{
"cell_type": "code",
"execution_count": 230,
"metadata": {
"collapsed": true
},
"outputs": [
{
"ename": "NameError",
"evalue": "name '_df' is not defined",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-230-a03112b6dd63>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m# -- list all the event level features\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mfeatures\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mc\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mc\u001b[0m \u001b[0;32min\u001b[0m \u001b[0m_df\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mc\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0;34m'class'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfeatures\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mNameError\u001b[0m: name '_df' is not defined"
]
}
],
"source": [
"# -- list all the event level features\n",
"features = [c for c in _df.columns if c != 'class']"
]
},
{
"cell_type": "code",
"execution_count": 281,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# -- concatenate all dataframes into one big one\n",
"ALREADY_MADE = True\n",
"if ALREADY_MADE:\n",
" mc_df_ALL = pickle.load(open('./mc-h008-ALL.pkl', 'rb'))\n",
"else:\n",
" mc_df_ALL = pd.concat(dataframes)\n",
" mc_df_ALL.to_pickle('./mc-h008-ALL.pkl')\n",
"features = [a for a in mc_df_ALL.columns if ((a != 'class'))]"
]
},
{
"cell_type": "code",
"execution_count": 282,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"['HGamEventInfoAuxDyn.selectedVertexZ',\n",
" 'HGamEventInfoAuxDyn.hardestVertexZ',\n",
" 'HGamEventInfoAuxDyn.m_yy_resolution',\n",
" 'HGamEventInfoAuxDyn.NLoosePhotons',\n",
" 'HGamEventInfoAuxDyn.eventShapeDensity',\n",
" 'HGamEventInfoAuxDyn.mu',\n",
" 'HGamEventInfoAuxDyn.TST_met',\n",
" 'HGamEventInfoAuxDyn.TST_sumet',\n",
" 'HGamEventInfoAuxDyn.CST_met',\n",
" 'HGamEventInfoAuxDyn.CST_sumet',\n",
" 'HGamEventInfoAuxDyn.isPassedPreselection',\n",
" 'HGamEventInfoAuxDyn.isPassedPID',\n",
" 'HGamEventInfoAuxDyn.yAbs_yy',\n",
" 'HGamEventInfoAuxDyn.isPassedIsolation',\n",
" 'HGamEventInfoAuxDyn.pTt_yy',\n",
" 'HGamEventInfoAuxDyn.isPassedRelPtCuts',\n",
" 'HGamEventInfoAuxDyn.m_yy',\n",
" 'HGamEventInfoAuxDyn.isPassedMassCut',\n",
" 'HGamEventInfoAuxDyn.pT_yy',\n",
" 'HGamEventInfoAuxDyn.cosTS_yy',\n",
" 'HGamEventInfoAuxDyn.m_jj',\n",
" 'HGamEventInfoAuxDyn.Dy_j_j',\n",
" 'HGamEventInfoAuxDyn.Dphi_yy_jj',\n",
" 'HGamEventInfoAuxDyn.isPassedBasic',\n",
" 'HGamEventInfoAuxDyn.isPassed',\n",
" 'HGamEventInfoAuxDyn.isPassedEventClean',\n",
" 'HGamEventInfoAuxDyn.numberOfPrimaryVertices']"
]
},
"execution_count": 282,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"features"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# -- separate training features from target \n",
"X = mc_df_ALL[features].values\n",
"y = mc_df_ALL['class'].values"
]
},
{
"cell_type": "code",
"execution_count": 266,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"coarse_labels = np.array(map(make_label, mc_df_ALL['class']))\n",
"SM_df = mc_df_ALL.ix[coarse_labels == 'SMhh'].copy()\n",
"Signal_df = mc_df_ALL.ix[coarse_labels == 'Signal'].copy()\n",
"Background_df = mc_df_ALL.ix[coarse_labels == 'Background'].copy()"
]
},
{
"cell_type": "code",
"execution_count": 272,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"Background_df[key].values\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 280,
"metadata": {
"collapsed": false,
"scrolled": false
},
"outputs": [
{
"data": {
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PY5slBWMKU6MN3Huv/3BFP/j7HNi6+fTw1HTQvGhHW2nUqVOHxYsXIyLcdtttNGnShEGD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\nF/ASkBam7SpgCDAFY0z0dao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"text/plain": [
"<matplotlib.figure.Figure at 0x2037cb710>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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0rGY9+2jdOijtVQCz393FtAc2VvlrQuPtdZyR8uCDD7Jt2zbGjx8f7VBCstdx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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x161653a50>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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mZllQXl5OeXn5bpdXRM2dd0ltgUXA6cAqYC4wMvcAraS+wF+BSyPibznp+wAl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\nwd7MLAMc7M3MMuD/B+ugZvyxDpOgAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1f1dbb450>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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IRClBi4hElBK0iEhEKUGLiESUErSISEQpQYuIRJQStIhIRClBi4hElBK0iEhE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\nRClBi4hElBK0iEhE/R8eODvnlqNkaAAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x133e12bd0>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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IbRHJ9uMHAacCX7D3glKIvKB0kIhUF5FD2HtB6Wpgk4j0\nEBHBXVD6BuWvPOKaFLCsc4H/lFeQ/stQ7CzcNk1pnH65TwOLVPWRkKK02qZlxZlO21REGhUfVhKR\nWsApwDzSb1sGxlm80/ZS/vlU1VtVtbWqHoI7b/Keql5MKrfn/pxISscBd2hqCa4nxC1JXvchuN4Y\n84Evi9cPNMCdcPsamAHkhNS51cf6FXBayPRjcB/UpbhHEhxobC/i7qSwA3fs9JLyjAuoAbyMe5zW\nx8DB5RTnpbi7Zn8OLPBfiqZpEOfxuOPb83E7w3lA73TbpmXEeXo6bVOgM+4B0/N9TDeW9/emnLZl\nWXGmzbYMiLkXe3uRpWx72oWWxhhjEqKyHCIzxhiTZizBGGOMSQhLMMYYYxLCEowxxpiEsARjjDEm\nISzBGGOMSQhLMMYYYxLCEowxxpiE+P8A2sftOfPQ+wAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1176d5890>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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"text/plain": [
"<matplotlib.figure.Figure at 0x12ae13d10>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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DgV7AogxtTKzrO0QTJ0REpB5KO1Jy91IzuwR4FsgFprj7O2Z2Udh+r7vPM7Mh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\nRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1176f5dd0>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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GNm3asHLlSqZNm1a6/o9//CO/+c1vaNmyJYsXL+Zb3/pWmboS64svT506lYUL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\n+pDPAp40sw8l3RTWP25meZL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im5lrs8putk52g3RieoU3WwOpbrbOIRoJui9JXdVC0cjT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\nnHMZz4OVc865jPf/AXrJ5zcbySn7AAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x161709450>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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06cPXvvY17r///iC8qOt9LrjgArKzs2OWldm1JGXR5eoKHl+Nfh5RQQGcc07wN9rkybBh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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1c2ab84d0>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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LlvDXv/71QN/CWuPByjlX67LgqfYAXHLJJbRu3Zq2bdvyk5/8hAcffJA+ffpw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\nXbvDepmikJ6wfzMrlbRdUkf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ir9cDAzLI0xXoUkXZzmZW9lu6GOgc1rsAz6eoa3dYL1MU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\nRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1119852d0>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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maaGk6elwcvGLa2ZmtWnwhc7AJ8CYiJghqTPwN0nPAgGMi4hxRS2hmZk1qMFg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\nAxzMzcwywMHczCwD/j9qYt9cmETH2wAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1616c8e10>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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BDnMzswxwmJuZZYDD3MwsAxzmZmYZ4DA3M8sAh7mZWQY4zM3MMsBhbmaWAQ5z\nM7MMcJibmWWAw9zMLAMc5mZmGeAwNzPLAIe5mVkGOMzNzDKg1jCX9JCkUkmz88Z1k/S8pHckTZPU\ntWmLaWZmNSmkZT4eOKXKuO8Bz0fE/sAf0+dmZtZCag3ziJgOlFUZfTowIR2eAJzRyOUyM7M6qG+f\nec+IKE2HS4GejVQeMzOrh3YNXUFEhKSoblpRUVHFcC6XI5fLNXRzZmaZUlxcTHFxMQAfzCiteeYa\n1DfMSyXtFhGLJe0OLKlupvwwNzOzzeU3dEtWvcH4l++r13rq283yJDAyHR4JPFHP9ZiZWSMo5NTE\nx4GXgP6SFki6BPgJcKKkd4Avp8/NzKyF1NrNEhHDtzDpK41cFjMzqydfAWpmlgEOczOzDHCYm5ll\ngMPczCwDHOZmZhngMDczywCHuZlZBjjMzcwywGFuZpYBDnMzswxwmJuZZYDD3MwsAxzmZmYZ4DA3\nM8sAh7mZWQY4zM3MMsBhbmaWAQ5zM7MMcJibmWWAw9zMLAMc5mZmGeAwNzPLAIe5mVkGtGvIwpLe\nB1YBXwCfR8SRjVEoMzOrmwaFORBALiKWN0ZhzMysfhqjm0WNsA4zM2uAhoZ5AC9IelXS5Y1RIDMz\nq7uGdrMcGxGLJO0CPC/p7YiYXj6xqKioYsZcLkcul2vg5szMsqW4uJji4mIAPphRWu/1NCjMI2JR\n+vdjSX8AjgSqDXMzM9tcfkO3ZNUbjH/5vnqtp97dLJI6SOqUDu8EnATMru/6zMys/hrSMu8J/EFS\n+Xp+HRHTGqVUZmZWJ/UO84iYBxzeiGUxM7N68hWgZmYZ4DA3M8sAh7mZWQY4zM3MMsBhbmaWAQ5z\nM7MMcJibmWWAw9zMLAMc5mZmGeAwNzPLAIe5mVkGOMzNzDLAYW5mlgEOczOzDHCYm5llgMPczCwD\nHOZmZhngMDczywCHuZlZBjjMzcwywGFuZpYBDnMzswyod5hLOkXS25LelXR9YxbKzMzqpl5hLqkt\ncDdwCnAQMFzSgY1ZsCwpLi5u6SK0Gq6LTVwXm7guGq6+LfMjgb9HxPsR8TkwERjWeMXKFr9QN3Fd\nbOK62MR10XD1DfNewIK85x+m48zMrAW0q+dy0ZCNvruxF6dt/0pDVrFVmbvhI/77x9vO/tbEdbGJ\n62KTbaku1kcboF+103baZbt6r1cRdc9lSYOAoog4JX3+fWBjRPw0b54GBb6Z2bYqIlTXZeob5u2A\nucAJwEIh6N+1AAADYklEQVTgFWB4RLxV55WZmVmD1aubJSI2SPom8BzQFhjnIDczazn1apmbmVnr\n0uArQAu5eEjSXen01yUNaOg2W6va6kLSBWkdvCHpL5IObYlyNodCLyqTdISkDZLOas7yNacC3yM5\nSa9JelNScTMXsdkU8B7pIWmqpFlpXYxqgWI2OUkPSSqVNLuGeeqWmxFR7wdJF8vfgb2A9sAs4MAq\n8wwFnkmHjwJebsg2W+ujwLo4GuiSDp+yLddF3nx/Ap4Gzm7pcrfg66Ir8Ddgz/R5j5YudwvWRRHw\n4/J6AJYB7Vq67E1QF8cDA4DZW5he59xsaMu8kIuHTgcmAETETKCrpJ4N3G5rVGtdRMSMiFiZPp0J\n7NnMZWwuhV5UdjXwO+Dj5ixcMyukLkYA/xkRHwJExNJmLmNzKaQuFgGd0+HOwLKI2NCMZWwWETEd\nKKthljrnZkPDvJCLh6qbJ4shVtcLqS4DnmnSErWcWutCUi+SN/K96aisHrwp5HWxH9BN0ouSXpV0\nUbOVrnkVUhcPAv8kaSHwOnBNM5Wttalzbtb3oqFyhb4Bq54zmcU3bsH7JGkIcClwbNMVp0UVUhd3\nAt+LiJAkNn+NZEUhddEe+GeSU307ADMkvRwR7zZpyZpfIXVxAzArInKS9gWel3RYRKxu4rK1RnXK\nzYaG+UdA77znvUk+QWqaZ890XNYUUhekBz0fBE6JiJq+Zm3NCqmLfwEmJjlOD+Crkj6PiCebp4jN\nppC6WAAsjYhPgU8l/RdwGJC1MC+kLo4BfgQQEf+QNA/oD7zaLCVsPeqcmw3tZnkV2E/SXpK2A84D\nqr4ZnwQuhoorR1dERGkDt9sa1VoXkvoAvwcujIi/t0AZm0utdRER+0TE3hGxN0m/+TcyGORQ2Htk\nMnCcpLaSOpAc8JrTzOVsDoXUxdvAVwDSPuL+wHvNWsrWoc652aCWeWzh4iFJV6TT74+IZyQNlfR3\n4BPgkoZss7UqpC6Am4GdgXvTFunnEXFkS5W5qRRYF9uEAt8jb0uaCrwBbAQejIjMhXmBr4vbgPGS\nXidpbI6OiOUtVugmIulxYDDQQ9IC4BaS7rZ656YvGjIzywDfNs7MLAMc5mZmGeAwNzPLAIe5mVkG\nOMzNzDLAYW5mlgEOczOzDHCYm5llwP8CK3wQpeFHVnwAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x12b0454d0>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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U7EVEYkDBXkQkBhTsRURiQMFeRCQGFOxFRGIgbbA3s35mttzMVprZ6BLyTzez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\nHW/7ccm+ctQAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1c27d7550>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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"text/plain": [
"<matplotlib.figure.Figure at 0x21330edd0>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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FRGoyBY+qsh3YS/Sw+VjPA59XfXNERA6HgkdVakjpnscsoucKi4jUIjrnISIi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\neqyceUrV5+5uZuVdT63VukM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"text/plain": [
"<matplotlib.figure.Figure at 0x1c2739550>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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MzGqST838Y2BsRHwKGApcLelQ4Abg2Yg4GHg+nTYzs1ZQbzCPiOURMS8d3wD8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\nzDLAwdzMLAMczM3MMsDB3MwsA/4/cGyd7Mv5k9UAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1c277f310>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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t9DCzgaFMj1D+bHf/LPC9g+wLERHJs2wjpTOBFe5e7u67gRlAaVqeS4GpAO6+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\nXoehj94DitLSfgHcFJZvBu6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"text/plain": [
"<matplotlib.figure.Figure at 0x1c1b18610>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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r4I/A7e6+3cxKx7m7m5lXNF9BQUFpfywWIxaLpVtWEZFIisfjxOPx8NWutJZh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\nMBcRiYD/Dz7VpNJ78AbpAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x117934fd0>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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DDd19Qcg3JanMSqBxmG8CLM/pk4uISOxkeyBrW2Bp0vIyoFcOedoCbTKUbenu\nq8P8aqBlmG8DvJKmrp1hPmF5SAf4NfCymV0F1AfOyPKZREQkprIFJc+xHsueBUtXn7u7meW6nXRu\nB/7k7v9jZr2Bh4Evpcs4duzY0vmioiKKior2Y7P76aWX4MX5MOl35dfdcw/071/1bRKRg15xcTHF\nxcV52362oLQcaJ+03J6yPZZ0edqFPLXTpCdOra02s1buviqcmluTpa7lYT41HeCrwBgAd3/FzOqZ\nWQt3X5v6YZKDUt7t2AHdu8PjC8qmX345fPFFftokIge91C/s48aNq9LtZ7um9CrRoIKOZlaHaBDC\nrJQ8s4BhAKGnsjGcmstUdhYwPMwPB55ISh9qZnXMrBPQBVjg7quAzWbWKwx8uBSYGcosAs4M2+8G\n1EsXkGKpbl1o27bsdMgh+W6ViEjeZOwpuXuJmV0JPAMUApPc/V0zuzysn+jus82sn5ktBrYCl2Uq\nG6q+FZhuZiOBJcDgUGahmU0HFgIlwCh3T5zaGwU8CBwCzHb3p0P6NcAkM/sJ0enBRLATEZFqJuub\nZ939KeCplLSJKctX5lo2pK8n9G7SrLsFuCVN+mtAjzTp/wGKKvwAIiJSbeiJDiIiEhsKSiIiEhsK\nSiIiEhsKSiIiEhsKSiIiEhsKSiIiEhtZh4RLTKxaBaNugoYpD9QoKIAnnkhfRkSkmlFQqi62bYVT\nT4WvNNiTtmsXfPvb+WuTiMgBpqBUnfTqBecetWd51678tUVEpBLompKIiMSGgpKIiMSGgpKIiMSG\ngpKIiMSGgpKIiMSGgpKIiMSGgpKIiMSGgpKIiMSGbp7Nly3AJuBPKekfAaurvjkiInGgoJQva4FP\ngVdS0t8FPqz65oiIxIGCUj41o3xP6el8NEREJB50TUlERGJDQUlERGJDQUlERGIja1Ays75mtsjM\nPjCzayvIc1dY/6aZ9cxW1syamdlcM3vfzOaYWZOkddeH/IvM7Oyk9BPN7K2w7s6U7Q82s3fM7G0z\ne2Rvd0LsbN0AK1eWndzz3SoRkUqXMSiZWSEwHugLdAcuNLNuKXn6AZ3dvQvwfeDuHMpeB8x196OB\n58IyZtYdGBLy9wUmmJmFMncDI8N2uphZ31CmSyj/VXc/Frh6H/dFPNRpAtPHwAknlJ12OxQW5rt1\nIiKVKtvou5OBxe6+BMDMpgEDiQYuJwwAJgO4+3wza2JmrYBOGcoOAPqE8pOBYqLAMhB41N13AkvM\nbDHQy8zzS36ZAAAWR0lEQVQ+Bhq6+4JQZgowiGis2veA8e6+KbRh7d7vhhg58T4YDHwnJb0b0LHq\nmyMiUpWynb5rCyxNWl4W0nLJ0yZD2ZbunrhFdDXQMsy3CfnS1ZWcvjypri5AVzObZ2Yvm9k3s3wm\nERGJqWw9pVwvZFj2LFi6+tzdzWx/LpjUBjoT9bzaA/8wsx6JnlOysWPHls4XFRVRVFS0H5sVEal5\niouLKS4uztv2swWl5UQH+oT2lO2xpMvTLuSpnSZ9eZhfbWat3H2VmbUG1mSpa3mYT02HqDc23913\nEZ3ye58oSL2W+mGSg5KIiJSX+oV93LhxVbr9bKfvXiUaVNDRzOoQDUKYlZJnFjAMwMx6AxvDqblM\nZWcBw8P8cOCJpPShZlbHzDoRnZpb4O6rgM1m1isMfLgUmBnKPAEUhe23AI5GD+oREamWMvaU3L3E\nzK4EngEKgUnu/q6ZXR7WT3T32WbWLwxK2ApclqlsqPpWYLqZjQSWEF3ax90Xmtl0YCFQAoxyLx0L\nPQp4EDgEmO3uT4cyz5jZ2Wb2DrAL+C9337Dfe0ZERKqc+UFy/4uZeZw+602diinZBTd9UlR2xXdI\nO/quWzd4/PHoZ6ldu6BOneiniEglMDPcPZdxAweEnuggIiKxoaeEV3fusGVL+fSCAqhfv+rbIyKy\nHxSUqrv69aFNm7Jpu3ZBly7w5pv5aZOIyD7S6bvqrLAw6iWlTi+/nO+WiYjsE/WUqpFXX4W1aR6i\ndNppVd8WEZHKoKBUTZx4Itx7b9k096hTpMF3IlJTKChVEw8/XD4tMSJcRKSm0DUlERGJDQUlERGJ\nDQUlERGJDQUlERGJDQUlERGJDQUlERGJDQUlERGJDQUlERGJDQUlERGJDQUlERGJDQUlERGJDQUl\nERGJDQUlERGJDQUlERGJDQUlERGJDQUlERGJjaxBycz6mtkiM/vAzK6tIM9dYf2bZtYzW1kza2Zm\nc83sfTObY2ZNktZdH/IvMrOzk9JPNLO3wro707ThAjPbbWYn7M0OqJEWA+8Ah6eZRuWxXSIiWWQM\nSmZWCIwH+gLdgQvNrFtKnn5AZ3fvAnwfuDuHstcBc939aOC5sIyZdQeGhPx9gQlmZqHM3cDIsJ0u\nZtY3qQ0NgauBV/ZlJ9Q4u4jeKfx2yjQG2JzHdomIZJGtp3QysNjdl7j7TmAaMDAlzwBgMoC7zwea\nmFmrLGVLy4Sfg8L8QOBRd9/p7kuIvvP3MrPWQEN3XxDyTUkqA3AzcCuwHTAk2gupvaTGeW2RiEhW\n2YJSW2Bp0vKykJZLnjYZyrZ099VhfjXQMsy3CfnS1ZWcvjxRVzhd19bdZ4d1nuUziYhITNXKsj7X\nA3wuvRNLV5+7u5ntUyAJp/ZuB4bn0paxY8eWzhcVFVFUVLQvmxURqbGKi4spLi7O2/azBaXlQPuk\n5faU7bGky9Mu5KmdJn15mF9tZq3cfVU4NbcmS13Lw3xqekPgS0BxuPTUCphlZv3d/V+pHyY5KImI\nSHmpX9jHjRtXpdvPdvruVaJBBR3NrA7RIIRZKXlmAcMAzKw3sDGcmstUdhZ7ejfDgSeS0oeaWR0z\n6wR0ARa4+ypgs5n1Cr2jS4GZ7r7Z3Q9z907u3olooEPagCQiIvGXsafk7iVmdiXwDFAITHL3d83s\n8rB+orvPNrN+ZrYY2ApclqlsqPpWYLqZjQSWAINDmYVmNh1YCJQAo9w9cWpvFPAgcAgw292fPiB7\noDpL7JntKek7q7ohIiIHRrbTd7j7U8BTKWkTU5avzLVsSF8PnFlBmVuAW9Kkvwb0yNLW0zOtr3F2\nh6lRmvTaFZR5G/h1mvQi4JQD1jIRkX2SNShJNZDaU3qTcEI1xZeAcyh/r9LfiIaHKCiJSJ4pKB1M\neoYp1XVV3RARkfT07DsREYkNBSUREYkNBSUREYkNBSUREYkNBSUREYkNBSUREYkNBSUREYkNBSUR\nEYkNBSUREYkNBSUREYkNBSUREYkNBSUREYkNPZBVImuBD9KktwHqV3FbROSgpaBUXfw3sDolreQA\n1d0cuBeYmZK+HJgOnHuAtiMikoWCUnXxCHA+0CopbTfRe5D21zVhSqVgJCJVTEGpOrkE6Ja0vAv4\naZ7aIiJSCRSUqrndu6Fx49TEYzl294O8mJcWiYjsOwWlaqygADZuLJ/+1v99xBU/PLTqGyQisp8U\nlKoxszS9JKDhobuqvjEiIgeAglJNtWs3zJ5dPr1NGzj++Kpvj4hIDhSUaqL69aHeDhg/vmz68uXQ\nowc8/HB+2iUikkVOT3Qws75mtsjMPjCzayvIc1dY/6aZ9cxW1syamdlcM3vfzOaYWZOkddeH/IvM\n7Oyk9BPN7K2w7s6k9J+a2Tth28+aWYe93RE1Srt20OnIqKeUPF2Tbty3iEh8ZA1KZlYIjAf6At2B\nC82sW0qefkBnd+8CfB+4O4ey1wFz3f1o4LmwjJl1B4aE/H2BCWaWuBvnbmBk2E4XM+sb0v8FnOju\nxwF/Bm7b2x0hIiL5l0tP6WRgsbsvcfedwDRgYEqeAcBkAHefDzQxs1ZZypaWCT8HhfmBwKPuvtPd\nlwCLgV5m1hpo6O4LQr4piTLuXuzuX4T0+UC7nD69iIjESi7XlNoCS5OWlwG9csjTlujJaRWVbenu\niQfnrAZahvk2wCtp6toZ5hOWh/RUI4E0V/hln/yb9M++OwWoV8VtEZEaL5eg5DnWlcsDbyxdfe7u\nZpbrdiqu3OwS4ATgJ+nWjx07tnS+qKiIoqKi/d1kzdYDmBumZC8B7wNHVHmLRKSSFRcXU1xcnLft\n5xKUlgPtk5bbU7bHki5Pu5Cndpr05WF+tZm1cvdV4dTcmix1LafsabnkujCzM4EbgK+HU4XlJAcl\nycGvK0hXMBKpsVK/sI8bN65Kt5/LNaVXiQYVdDSzOkSDEGal5JkFDAMws97AxnBqLlPZWcDwMD8c\neCIpfaiZ1TGzTkAXYIG7rwI2m1mvMPDh0kSZMNrvHqC/u6/du10gIiJxkbWn5O4lZnYl8AxQCExy\n93fN7PKwfqK7zzazfma2GNgKXJapbKj6VmC6mY0ElgCDQ5mFZjYdWEj0coZR7p44tTcKeBA4BJjt\n7k+H9NuIrnz8OQzU+9jdEwMnRESkmsjp5ll3fwp4KiVtYsrylbmWDenrgTMrKHMLcEua9NeIrnSk\npp+VofkiIlJN6HXoIiISGwpKIiISG3r2XRxdDdyYkvZhPhoiIlK1FJTi5g5gSwXrOlVlQ7J4j/Lt\nLCB6OJSIyD5SUIqbdM+oiJujKf8a9l1Ed5NVFFBFRHKgoCR7L/UJDxAFozZV3RARqWk00EFERGJD\nQUlERGJDp+9qqLfeggYNUhJLhjCkXTsm5aVFIiLZKSjVQMceC5s3l0+f9uPXKH6udtU3SEQkRwpK\nNVBhYZpeElCv9i5Ytw6uvrr8yv794cy0T30SEakyCkoHk06d4OjmcORHZdNnzYLWrfc/KH1G+hF4\nJwJ/2b+qReTgoKB0MGnTBo5pA1cfUzZ95cr9r7s+SW+3SvIqFb+XSUQkhYKSHBgFpO8lHVbVDRGR\n6kxDwkVEJDbUU5LKt4bo1YypugBfq9qmiEi8KShJ5ToMOA0oTkl/H/gSCkoiUoaC0kHmww/h4YdT\nEt85nuPfm86xrw8pX2D0aDjxxH3fYGfS95LuAxbse7UiUjMpKB1EOnWCI4+Ep58um/76wkFc2qsb\nxw5cVHbFb35zYEbmVWQD8E6a9FZA88rbrIjEl4LSQeRrX4umVNddVw+aHAdDjiu74qGHKq8xTYB3\ngcEp6SuBscCPKm/TIhJfCkqS2eTJ8NJL5dOvuQaaNt33er8TplQ/ArYC69OsawjoKUkiNZqGhEvF\nhg2Dnj2jZxYlTxMmpH+43oFwKPBbomtRydPhwAuVs0kRiY+sPSUz60v0ku5C4E/u/ps0ee4CzgG2\nASPc/fVMZc2sGfAYcASwBBjs7hvDuuuB7xK9y/RH7j4npJ9IdMm8HjDb3a8O6XWBKcAJwDpgiLt/\nvA/74qD2y1/Cf/93aupgZsyAc85JSZ44MRoxsX172XQz6NJl/xpya5hSfQP4Belvxp1MdDpQRKq9\njD0lMysExgN9ge7AhWbWLSVPP6Czu3cBvg/cnUPZ64C57n408FxYxsy6A0NC/r7ABDOzUOZuYGTY\nTpcQ8ABGAutC+v8A5YJmXC354o18NwGAceNg/XpYtQpmzChm1apo/tRTYdeuNAU6dYLLL4dzz90z\n9esHJ5xQKe0rLi6Gm4Frib6uJE/FwJ3A7SnTPZXSlPLtihm1KTdqU3xl6ymdDCx29yUAZjYNGEh0\niTphANF3Vdx9vpk1MbNWQKcMZQcAfUL5yUSHluvC+kfdfSewxMwWA73M7GOgobsnBhFPAQYBT4e6\nxoT0/yUKhNXCx9vjEZTq1o0mgPnziznnnCIAatWCUaPg2mtTSxQztzh6lF6pLVugUaM9FSXs2AH1\n6sFjj5XfcIcOcPzxWdtXXFxM0dii9CuvBjaFKWEr0V9V6qWwXUBj4Idp6jkUaJ0mvQ4V/pcUFxdT\nVFRBu/JEbcqN2hRf2YJSW2Bp0vIyoFcOedoSPQmtorIt3X11mF8NtAzzbYBX0tS1M8wnLA/pZbbv\n7iVmtsnMmrl7ukvlshf++Ef47LPy6WeeGV1qqpX017NzZwM+xbn/DzvLZl65knr/+whnT0gJSi+9\nRN0tn9KgfbOy6WvXRj2uAQP2pL34Itx0EzRvHgWyZF03Q48eZYPhF8CRwGGdyub9J/C/Bi+kjJZ4\nO/w8JOWDfg50JDoxnewz4CjgDcLXsWA1cAzlB2PUIrqBONkOYDvpz1XUI3rArchBKFtQ8hzrsexZ\nsHT1ububWa7bqTFatyqgwfZcdlv+HHFE+vTXXy9/Wu/zz43rroN/vFz2iLxoUQdeeet6mqU8QXz9\nluhn081lK9rweSG8CF96b1Vp2pqta5hQfCW1Cp129daVyf/RpqZ0rLOC+oUbS9N2lhgf72zDMVZ2\nZMQXXpfVtOSodWUvOW6nkJW05shdy8rmp4A1Sw7niPvLbnPjjnrssHps4hNenT2vNP29na3pVPgp\nhbZ7T1t2F7Bsd3M6s6ZMHTsoYAVN6Wgbyu4Y30UUrQ5NaUshn9KIDuXy7wAMCupEbdi9jNdufgV2\nb4WC+mX/M3fvjOovTOnN7t4F7Ijyl6l7N+z+AmodWj6/74RaKVG8ZCsU1gNLirTuvFfyEa/dkuZO\n6V1EV5v3h5fA7hKoVa98WwoOgYL0VyjeK1nOa78Obdq1GzzN53Rg9160sWRb+c8PUPI5FNYBy1xR\nmTal2kX0BSb1kLFrG1APClO3uSPKH/4uEi7ouoMRr50a71Gs7l7hBPQGnk5avh64NiXPPcDQpOVF\nRD2fCsuGPK3CfGtgUZi/DrguqczTRL2rVsC7SekXAncn5ekd5msBn1bwWVyTJk2aNO39lClOHOgp\nW0/pVaJBBR2BFUSDEC5MyTMLuBKYZma9gY3uvtrM1mUoOwsYTjQoYTjwRFL6VDO7nei0XBdgQehN\nbTazXkQPp7kUuCulrleAbxMNnCjH3ePdLRERkcxBKVyjuRJ4hqgTO8nd3zWzy8P6ie4+28z6hUEJ\nW4HLMpUNVd8KTDezkYQh4aHMQjObDiwESoBRHro5wCiiIeGHEA0JTzwsZxLwkJl9QDQkfOh+7RER\nEckb23PMFxERybOqPFe4PxPRff7vAm8CjwONU65XfUB0rerspPQTgbfCujuT0usS3bz7AdFpvyOS\n1g0nerHC+8CwpPROwPxQZhpQez8/T9/Q3g9IuU63j/W1B/5G9IjTt4luPAZoBswNn2cO0KQq91tY\nVwi8DvwlDm0iutX2z+HvaSHRdct8t+n68Lt7C5ga6shHm/5ONI7wraT1+d4304lG4G4n/O+R/+NB\nuTYlrfsZ0RCJZnFoE3BV2FdvA7+J+3Ez78Em1wk4CygI87cCt4b57kSDc2sTDeBdzJ4e4ALg5DA/\nG+gb5kcBE8L8EGBa0j/ff4gOWk3CfOOkX/jgMH838IP9+CyFoZ0dQ7vfALrt5/5pBRwf5hsA7wHd\ngNuA0SH92ircb8kHrp8CjwCzwnJe20Q0kPu7Yb4W0d1LeWtTqPdDoG7I9xjRP3k+2rScaAB7clDK\n175J/O89D4wmOlDeDfyA/B8PyrUppLcnGnz1ESEo5Xk/nU70hSIRoA6L+3Ez78FmHw/A5wEPh/ky\nIwLDH0RvolF9ySP2hgL3JOXplXRQ+jTMl47qC8v3hHIGfMqef4IyIwv3of2nUHZkYplRhwdoHz0B\nnEkYDRnSWrFnpGOl77cw3w54NvxzJHpKeWsTUQD6MM3+ymebmhF9iWga8v+F6KCbrzZdRdmglM99\nk/jf60R0sC33v0f+jgfl2gTMAL5M2aCUtzYRBYVvpPl7j+1xs7o+kPW7RBEcohtuk28wSb55N6cb\nboFNZtY8Q13NiEYV7k5T176o6IbjAyKMeOxJ1G3OdKNyZe83iB79dA3R6YyEfLapE/CpmT1gZv8y\ns/vMrH4+2+TRjd6/Bz4hGqm60d3n5rFNLSkrn7+vZsBGoqHJqXUl5OV4kNomMxsILHP3f6e0L5/7\nqQvwdTN7xcyKzeykqm7T3h43YxWUzGyumb2VZuqflOfnwA53n1pFzfLsWWJRJwBm1oDocUtXu/uW\nMhuNvq5U2rbTtOVcYI1HD+hNOyS/qttE9A3vBKLTECcQjRi9Lp9tMrOjgB8TnUZpAzQws0vy2aaK\nVHE7sm4nRscDA25gzyPPEmlVIdN+qgU0dffeRF8Op1dNk/b9byRWQcndz3L3HmmmvwCY2QigH3Bx\nUrHlROdxE9oRRerlYT41PVGmQ6izFtH5z3Vp6mof0tYDTcxKb9VuF9L3VbrtLKsgb87MrDZRQHrI\n3RP3fq0OzyLEzFpD6aMFKnu/LQO+Cgwws4+AR4FvmNlDeW7TMqJvs/8M6X8mClKr8timk4CX3H1d\n+Ab6ONEp3ny1aRVl5ev3Vfq/x54DfOn/Xr6PBylt2kj0peLN8PfeDnjNzFrmeT8tI/p7IvzN7zaz\nFlXZpr0+bmY7vxeXiWi02jtAi5T0xAW7OkSnZv7Dngt284lGVhnlL9glnggxlLIX7D4Mv9ymifmw\nbjrRazEgOme6PwMdaoV2dgztPhADHYzoQbX/k5J+G3uepHEd5S8IV+p+S2pHH/ZcU8prm4B/AEeH\n+bGhPXlrE3Ac0cioQ0Jdk4Er8timL1N+oEM+f1/TiW7Qf4vwv0c8jgdl2pTSjuRrSvncT5cD48L6\no4FP4n7czHuw2YuD7gfAx0RDi18njAIJ624gGj2yCPhmUnpiaONi4K6k9LphZyWGNnZMWndZSP8A\nGJ6Unjy08TH2f0j4OUQXtxcD1x+A/XMq0XWbN5L2Ud/wB/Ms6YfzVvp+S1rfhz2j7/LaJqIg8E+S\nhhPHoE2j2TMkfDLRqKh8tOkVoutaO4iuH1wWg30zK7THid7Z9j3yfzxItGl3aNP/S/l7/5CyQ8Lz\n0qbwd/RQ2MZrQFHcj5u6eVZERGIjVteURETk4KagJCIisaGgJCIisaGgJCIisaGgJCIisaGgJCIi\nsaGgJCIisaGgJCIisfH/AVrqAWD1vV3mAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x117b52a90>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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BDvZmZiXAwd7MrAQ42JuZlQAHezOzEuBgb2ZWAhzszcxKgIO9mVkJcLA3MysB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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x21367fe10>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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PeuVASUbbn89SJi1YOeec21PmH/Jjx46t1ePnGwZ8hWgyQ3dJTYkm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\nrWmFE9JWM9ttZicR/XFyjqRzM/YnoZ2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"text/plain": [
"<matplotlib.figure.Figure at 0x21365c7d0>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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ul5mZ5WhdIL8XsCRneylwbJH7rlPdtWvh7LPhxhurpv/nf8L8+UUe0czMqlUo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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x213690150>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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HxDpJhwCPSVoWEU/ue3PNzGxfFAv2a4D8pwD0Ixnd1yginpTUXlKPiNgYEevS9Lcl/Y5k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\nMDL5Vzdk7QAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x117b30a10>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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f+LKIGJs3/9Z03i2SvgGURcQ3am0bdZXfR0uY9Qz0OX73ZgVtZrZN6zYEbrm1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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x32b23f810>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
"<matplotlib.figure.Figure at 0x119679ad0>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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bNmwoGD506BC7du0iNTWVGjVqABTMH4i496wmTZqwZ8+egGl/+OGHMj+MY8ne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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1199a0e10>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"for key in features:\n",
" if (key != 'HGamEventInfoAuxDyn.isPassedBasic'):\n",
" bins = np.linspace(mc_df_ALL[key].min(), mc_df_ALL[key].max(), 50)\n",
" plt.hist(SM_df[key].values, bins=bins,color = 'magenta', histtype='step', normed=True, label = 'SM hh')\n",
" plt.hist(Signal_df[key].values, bins=bins,color = 'red', histtype='step', normed=True, label = 'Signal')\n",
" plt.hist(Background_df[key].values, bins=bins,color = 'blue', histtype='step', normed=True, label = 'Background')\n",
" plt.title(key)\n",
" plt.legend()\n",
" plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 283,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"X_data = data_df[features].values"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# -- get number of available examples\n",
"ix = range(X.shape[0])"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# -- shuffle the indices to shuffle X and y\n",
"np.random.shuffle(ix)\n",
"X, y = X[ix], y[ix]\n",
"# -- divide the sample in half for training and testing\n",
"n = X.shape[0] / 2"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
},
"source": [
"# Classifiers"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# -- Logistic Regression with Cross Validation\n",
"classifier = linear_model.LogisticRegressionCV(Cs=10, cv=5, verbose=True, \n",
" penalty='l2', max_iter=10000, solver='liblinear',\n",
" n_jobs=6)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"classifier.fit(X[:n], y[:n]) # Training"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"yhat = classifier.predict(X[n:]) # Testing"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"print 'Prediction Accuracy: {}%'.format((yhat == y[n:]).mean())"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# -- count how many training and testing samples we have for each class\n",
"cts = {k : 0 for k in set(y)}\n",
"for _y in y[:n]:\n",
" cts[_y] += 1\n",
"print 'Training'\n",
"for k, v in cts.iteritems():\n",
" print '{}: {}'.format(k, v)\n",
"print 'Testing'\n",
"cts = {k : 0 for k in set(y)}\n",
"for _y in y[n:]:\n",
" cts[_y] += 1\n",
"for k, v in cts.iteritems():\n",
" print '{}: {}'.format(k, v)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# -- make different labels (3 classes instead of 10)\n",
"import string\n",
"def make_label(l):\n",
" if l[0] == 'S':\n",
" return 'SMhh'\n",
" elif l[0] in string.uppercase:\n",
" return 'Signal'\n",
" return 'Background'\n",
"labels = map(make_label, y) # labels = 3 class equivalent to y"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SMhh: 70611\n",
"Signal: 251655\n",
"Background: 285981\n"
]
}
],
"source": [
"# -- count how many events you have in each class\n",
"cts = {k : 0 for k in set(labels)}\n",
"for _y in labels:\n",
" cts[_y] += 1\n",
"for k, v in cts.iteritems():\n",
" print '{}: {}'.format(k, v)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# -- 3 class Logistic Regression with Cross Validation\n",
"triclassifier = linear_model.LogisticRegressionCV(Cs=20, cv=5, verbose=True, \n",
" penalty='l2', max_iter=10000, solver='liblinear',\n",
" n_jobs=6)"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"[Parallel(n_jobs=6)]: Done 1 out of 15 | elapsed: 4.8min remaining: 66.5min\n",
"[Parallel(n_jobs=6)]: Done 15 out of 15 | elapsed: 23.6min finished\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"[LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear]"
]
},
{
"data": {
"text/plain": [
"LogisticRegressionCV(Cs=20, class_weight=None, cv=5, dual=False,\n",
" fit_intercept=True, intercept_scaling=1.0, max_iter=10000,\n",
" multi_class='ovr', n_jobs=6, penalty='l2', refit=True,\n",
" scoring=None, solver='liblinear', tol=0.0001, verbose=True)"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"[LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear][LibLinear]"
]
}
],
"source": [
"triclassifier.fit(X[:n], labels[:n])"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"min = 0.0, max = 0.985\n"
]
},
{
"ename": "KeyboardInterrupt",
"evalue": "",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m/usr/local/lib/python2.7/site-packages/matplotlib/backends/backend_macosx.pyc\u001b[0m in \u001b[0;36mclose\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 380\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshow\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 381\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 382\u001b[0;31m \u001b[0;32mdef\u001b[0m \u001b[0mclose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 383\u001b[0m \u001b[0mGcf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdestroy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnum\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 384\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mKeyboardInterrupt\u001b[0m: "
]
}
],
"source": [
"# yhat = triclassifier.predict_proba(X[n:])\n",
"# print triclassifier.classes_\n",
"\n",
"# -- plot some results\n",
"sb = yhat[:, 2]\n",
"bins = np.linspace(sb.min(), np.percentile(sb, 95), 50)\n",
"print 'min = {}, max = {}'.format(sb.min(), sb.max())\n",
"plt.hist(sb[np.array(labels[n:]) == 'Signal'], bins=bins, label='Signal', color='red', histtype='step', normed=True)\n",
"plt.hist(sb[np.array(labels[n:]) == 'Background'], bins=bins, label='Background', color='blue', histtype='step', normed=True)\n",
"plt.legend()\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Prediction Accuracy: 0.560090620931%\n"
]
}
],
"source": [
"print 'Prediction Accuracy: {}%'.format((yhat == labels[n:]).mean())"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"{'H300': 0.04455768623737374,\n",
" 'X275': 0.042133240431882026,\n",
" 'X325': 0.049255783420138886,\n",
" 'X350': 0.05711412109375,\n",
" 'sm': 0.08734294921875,\n",
" 'ybbj': 1.9344743909269427e-05,\n",
" 'ybjj': 0.0,\n",
" 'yjjj': 0.0,\n",
" 'yybb': 0.0053058220722953684,\n",
" 'yybj': 0.0020889803856347336}"
]
},
"execution_count": 34,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# -- Get cutflow from HH2yybb analysis\n",
"with open('../cutflow_percentages.pickle', 'rb') as handle:\n",
" cutflow_percent_dict = pickle.load(handle)\n",
"cutflow_percent_dict"
]
},
{
"cell_type": "code",
"execution_count": 95,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'SMhh': 0.08734294921875, 'Signal': 0.19306083118314465, 'Background': 0.007414147201839371}\n",
"\n",
"S / sqrt(B) = 2.24214435139\n"
]
}
],
"source": [
"# -- get figure of merit from cutflow\n",
"sig_value = 0; sm_value = 0; bkg_value = 0;\n",
"for key, value in cutflow_percent_dict.iteritems():\n",
" if (any( signal in key for signal in ['H300', 'X275', 'X325', 'X350'])):\n",
" sig_value += value\n",
" elif(key == 'sm'): \n",
" sm_value += value\n",
" else:\n",
" bkg_value += value\n",
"cutflow3_dict = {'Signal' : sig_value, 'SMhh' : sm_value, 'Background': bkg_value} \n",
"print cutflow3_dict\n",
"\n",
"\n",
"print '\\nS / sqrt(B) = {}'.format(cutflow3_dict['Signal'] / np.sqrt(cutflow3_dict['Background']))\n",
"# note: we are ignoring SMhh completely here!"
]
},
{
"cell_type": "code",
"execution_count": 89,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"2.4315383267405926"
]
},
"execution_count": 89,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"labels = np.array(labels)\n",
"# -- Function to compute S/sqrt(B) for trained models\n",
"def s_over_rootB(labels, disc):\n",
" # -- initiate dictionaries to 0 for all 3 labels\n",
" passed = {k : 0 for k in set(labels)}\n",
" totals = {k : 0 for k in set(labels)}\n",
"\n",
" for lab in (labels):\n",
" totals[lab] += 1.0\n",
"\n",
" for lab in (labels)[disc]:\n",
" passed[lab] += 1.0\n",
"\n",
" pcts_passed = {k : passed[k] / totals[k] for k in passed.keys()}\n",
"# pcts_passed = {k : passed[k] for k in passed.keys()}\n",
"# print pcts_passed\n",
"\n",
" return pcts_passed['Signal'] / np.sqrt(pcts_passed['Background'])\n",
"\n",
"\n",
"s_over_rootB(labels[n:], yhat[:, 2] > 0.45) # simple, just using yhat[:,2] --> can do better with lr"
]
},
{
"cell_type": "code",
"execution_count": 74,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"labels = np.array(labels)"
]
},
{
"cell_type": "code",
"execution_count": 87,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<__main__.Likelihood2D at 0x1d7914a50>"
]
},
"execution_count": 87,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"lh = Likelihood2D(np.linspace(0, 1, 10), np.linspace(0, 1, 10))\n",
"\n",
"lh.fit(\n",
" (yhat[labels[n:] == 'Signal', 0], yhat[labels[n:] == 'Signal', 2]), \n",
" (yhat[labels[n:] == 'Background', 0], yhat[labels[n:] == 'Background', 2])\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 88,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"y_lh = lh.predict((yhat[:, 0], yhat[:, 2]))\n",
"# plt.hist(y_lh, histtype='step', bins=30)\n",
"# plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 93,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"bins = np.linspace(y_lh.min(), np.percentile(y_lh, 98), 50)\n",
"plt.hist(y_lh[np.array(labels[n:]) == 'Signal'], bins=bins, label='Signal', color='red', histtype='step', normed=True)\n",
"plt.hist(y_lh[np.array(labels[n:]) == 'Background'], bins=bins, label='Background', color='blue', histtype='step', normed=True)\n",
"plt.legend()\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 104,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1.07506072376\n"
]
}
],
"source": [
"best = -999\n",
"for cut in bins:\n",
" val = s_over_rootB(labels[n:], y_lh > cut)\n",
" if val > best:\n",
" best = val\n",
"print best"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Scikit Learn BDT"
]
},
{
"cell_type": "code",
"execution_count": 66,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"[Parallel(n_jobs=6)]: Done 1 out of 200 | elapsed: 9.7s remaining: 32.1min\n",
"[Parallel(n_jobs=6)]: Done 200 out of 200 | elapsed: 15.3min finished\n"
]
},
{
"data": {
"text/plain": [
"RandomForestClassifier(bootstrap=True, class_weight=None, criterion='gini',\n",
" max_depth=None, max_features='auto', max_leaf_nodes=None,\n",
" min_samples_leaf=1, min_samples_split=2,\n",
" min_weight_fraction_leaf=0.0, n_estimators=200, n_jobs=6,\n",
" oob_score=False, random_state=None, verbose=True,\n",
" warm_start=False)"
]
},
"execution_count": 66,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from sklearn import ensemble\n",
"# -- train \n",
"#clf = pickle.load(open('./random-forest.pkl', 'rb'))\n",
"clf = ensemble.RandomForestClassifier(n_estimators=200, n_jobs=6, verbose=True)\n",
"# # ensemble.GradientBoostingClassifier(verbose=1)\n",
"clf.fit(X[:n], labels[:n]) # if you put y: 10 class model\n",
" # if you put labels: 3 class model"
]
},
{
"cell_type": "code",
"execution_count": 67,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"[Parallel(n_jobs=6)]: Done 1 out of 200 | elapsed: 0.5s remaining: 1.7min\n",
"[Parallel(n_jobs=6)]: Done 200 out of 200 | elapsed: 21.1s finished\n"
]
}
],
"source": [
"# -- test\n",
"yhat = clf.predict_proba(X[n:])"
]
},
{
"cell_type": "code",
"execution_count": 68,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"[Parallel(n_jobs=6)]: Done 1 out of 160 | elapsed: 0.4s remaining: 1.1min\n",
"[Parallel(n_jobs=6)]: Done 200 out of 200 | elapsed: 18.4s finished\n"
]
},
{
"data": {
"text/plain": [
"0.80973550262392968"
]
},
"execution_count": 68,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"clf.score(X[n:],labels[n:]) # accuracy"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"pickle.dump(clf, open('./random-forest.pkl', 'wb'), pickle.HIGHEST_PROTOCOL)"
]
},
{
"cell_type": "code",
"execution_count": 322,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"from sklearn.metrics import confusion_matrix"
]
},
{
"cell_type": "code",
"execution_count": 323,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"def plot_confusion_matrix(cm, classes, title='Confusion matrix', cmap=plt.cm.Blues):\n",
" plt.imshow(cm, interpolation='nearest', cmap=cmap)\n",
" plt.title(title)\n",
" plt.colorbar()\n",
" tick_marks = np.arange(len(classes))\n",
" plt.xticks(tick_marks, classes, rotation=45)\n",
" plt.yticks(tick_marks, classes)\n",
" plt.tight_layout()\n",
" plt.ylabel('True label')\n",
" plt.xlabel('Predicted label')"
]
},
{
"cell_type": "code",
"execution_count": 73,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"[Parallel(n_jobs=6)]: Done 1 out of 200 | elapsed: 0.8s remaining: 2.8min\n",
"[Parallel(n_jobs=6)]: Done 200 out of 200 | elapsed: 19.2s finished\n"
]
}
],
"source": [
"confmat = confusion_matrix(labels[n:], clf.predict(X[n:]))"
]
},
{
"cell_type": "code",
"execution_count": 74,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/usr/local/lib/python2.7/site-packages/matplotlib/tight_layout.py:225: UserWarning: tight_layout : falling back to Agg renderer\n",
" warnings.warn(\"tight_layout : falling back to Agg renderer\")\n"
]
}
],
"source": [
"plot_confusion_matrix(confmat, clf.classes_)\n"
]
},
{
"cell_type": "code",
"execution_count": 75,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"3.1081673044\n"
]
}
],
"source": [
"best = -999\n",
"for cut in np.linspace(0, 1, 20):\n",
" val = s_over_rootB(labels[n:], yhat[:, 2] > cut)\n",
" if val > best:\n",
" best = val\n",
"print best"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
},
"source": [
"## Keras NN"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"from keras.models import Sequential \n",
"from keras.layers.core import *"
]
},
{
"cell_type": "code",
"execution_count": 57,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"pup = Sequential()"
]
},
{
"cell_type": "code",
"execution_count": 58,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"luke = Sequential()\n",
"luke.add(MaxoutDense(40, nb_feature=10, input_dim=X.shape[1]))\n",
"luke.add(Dropout(0.2))\n",
"\n",
"micky = Sequential()\n",
"micky.add(MaxoutDense(40, nb_feature=10, input_dim=X.shape[1]))\n",
"micky.add(Dropout(0.2))\n"
]
},
{
"cell_type": "code",
"execution_count": 59,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"pup.add(Merge([micky, luke], mode='concat'))\n",
"\n",
"pup.add(MaxoutDense(40, nb_feature=10))\n",
"pup.add(Dropout(0.2))\n",
"\n",
"pup.add(Dense(30))\n",
"pup.add(Activation('relu'))\n",
"pup.add(Dropout(0.2))\n",
"\n",
"pup.add(Dense(10))\n",
"pup.add(Activation('relu'))\n",
"pup.add(Dropout(0.2))\n",
"\n",
"pup.add(Dense(3))\n",
"pup.add(Activation('softmax'))\n",
"\n",
"pup.compile('adam', 'categorical_crossentropy')"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"from sklearn.preprocessing import LabelEncoder"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['Background' 'SMhh' 'Signal']\n",
"[0 1 2 2 0 0 0 2 1 0]\n",
"[[ 1. 0. 0.]\n",
" [ 0. 1. 0.]\n",
" [ 0. 0. 1.]\n",
" [ 0. 0. 1.]\n",
" [ 1. 0. 0.]\n",
" [ 1. 0. 0.]\n",
" [ 1. 0. 0.]\n",
" [ 0. 0. 1.]\n",
" [ 0. 1. 0.]\n",
" [ 1. 0. 0.]]\n"
]
}
],
"source": [
"encoder = LabelEncoder()\n",
"labels_digits = encoder.fit_transform(labels)\n",
"print encoder.classes_\n",
"print labels_digits[:10]\n",
"\n",
"from keras.utils import np_utils\n",
"labels_matrix = np_utils.to_categorical(labels_digits, 3)\n",
"print labels_matrix[:10]"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"array([ 1.00000119, 0.99998903, 1.00762343, 0.99853259, 1.00000656,\n",
" 0.99848211, 1.00001681, 0.9999994 , 1.00000286, 0.99997175,\n",
" 1.00201488, 0.99952447, 1.00142848, 1.00363255, 1.00092053,\n",
" 0.99626333, 1.00047231, 1.00028539, 0.99836016, 0.99833989,\n",
" 1.00108528, 1.00187516, 1.00229931, 0. , 0.99238223,\n",
" 1.00110435, 0.99956542], dtype=float32)"
]
},
"execution_count": 36,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from sklearn.preprocessing import StandardScaler\n",
"scaler = StandardScaler()\n",
"Z = scaler.fit_transform(X)\n",
"Z.var(axis=0)"
]
},
{
"cell_type": "code",
"execution_count": 61,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Train on 304123 samples, validate on 304124 samples\n",
"Epoch 1/7\n",
"304123/304123 [==============================] - 43s - loss: 0.4893 - acc: 0.7969 - val_loss: 0.4682 - val_acc: 0.8012\n",
"Epoch 2/7\n",
"304123/304123 [==============================] - 45s - loss: 0.4872 - acc: 0.7973 - val_loss: 0.4654 - val_acc: 0.8034\n",
"Epoch 3/7\n",
"304123/304123 [==============================] - 45s - loss: 0.4853 - acc: 0.7987 - val_loss: 0.4613 - val_acc: 0.8055\n",
"Epoch 4/7\n",
"304123/304123 [==============================] - 42s - loss: 0.4833 - acc: 0.7986 - val_loss: 0.4657 - val_acc: 0.8029\n",
"Epoch 5/7\n",
"304123/304123 [==============================] - 40s - loss: 0.4829 - acc: 0.7992 - val_loss: 0.4626 - val_acc: 0.8038\n",
"Epoch 6/7\n",
"304123/304123 [==============================] - 44s - loss: 0.4813 - acc: 0.7997 - val_loss: 0.4588 - val_acc: 0.8060\n",
"Epoch 7/7\n",
"304123/304123 [==============================] - 45s - loss: 0.4810 - acc: 0.8004 - val_loss: 0.4620 - val_acc: 0.8034\n"
]
},
{
"data": {
"text/plain": [
"<keras.callbacks.History at 0x119b57990>"
]
},
"execution_count": 61,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pup.fit([Z[:n], np.power(Z[:n], 2)], labels_matrix[:n], verbose=True, batch_size=128, show_accuracy=True,\n",
" nb_epoch=7, validation_data=([Z[n:], np.power(Z[n:], 2)], labels_matrix[n:]))\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 77,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"304124/304124 [==============================] - 9s \n"
]
}
],
"source": [
"yhat_NN = pup.predict([Z[n:], np.power(Z[n:], 2)], verbose=True)"
]
},
{
"cell_type": "code",
"execution_count": 96,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"def bestS2B(labels, yhat, nbins=100):\n",
" best = -9999\n",
" ideal_cut = 0\n",
" for cut in np.linspace(yhat.min(), yhat.max(), nbins):\n",
" temp = s_over_rootB(labels, yhat > cut)\n",
" if (temp > best) & (not np.isinf(temp)):\n",
" best = temp\n",
" ideal_cut = cut\n",
" return best, ideal_cut"
]
},
{
"cell_type": "code",
"execution_count": 157,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# -- best Random Forest\n",
"SB_RF, cut_RF = bestS2B(labels[n:], yhat[:,2])"
]
},
{
"cell_type": "code",
"execution_count": 158,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# -- best NN\n",
"SB_NN, cut_NN = bestS2B(labels[n:], np.log(yhat_NN[:,2]/yhat_NN[:,0]))"
]
},
{
"cell_type": "code",
"execution_count": 120,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"bdt = ensemble.GradientBoostingClassifier(loss='deviance', learning_rate=0.1, n_estimators=500, subsample=1.0, \n",
" min_samples_split=3, min_samples_leaf=2, min_weight_fraction_leaf=0.0, \n",
" max_depth=5, init=None, random_state=None, \n",
" max_features=None, verbose=1, max_leaf_nodes=None, warm_start=False)"
]
},
{
"cell_type": "code",
"execution_count": 121,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" Iter Train Loss Remaining Time \n",
" 1 286876.5754 194.16m\n",
" 2 263878.5972 216.36m\n",
" 3 245128.1536 205.55m\n",
" 4 229616.9332 201.87m\n",
" 5 216694.3636 190.67m\n",
" 6 205852.2271 184.52m\n",
" 7 196714.5394 179.27m\n",
" 8 188950.2319 174.05m\n",
" 9 182283.3901 174.73m\n",
" 10 176633.8797 177.55m\n",
" 20 148960.9458 192.55m\n",
" 30 141212.0303 186.20m\n",
" 40 137915.0303 169.38m\n",
" 50 136042.6415 157.67m\n",
" 60 134763.7914 148.90m\n",
" 70 133803.8605 141.56m\n",
" 80 133003.3481 135.25m\n",
" 90 132420.8445 129.42m\n",
" 100 131906.4769 124.09m\n",
" 200 128155.6996 85.01m\n",
" 300 125399.0827 54.35m\n",
" 400 123073.5278 26.54m\n",
" 500 120928.3260 0.00s\n"
]
},
{
"data": {
"text/plain": [
"GradientBoostingClassifier(init=None, learning_rate=0.1, loss='deviance',\n",
" max_depth=5, max_features=None, max_leaf_nodes=None,\n",
" min_samples_leaf=2, min_samples_split=3,\n",
" min_weight_fraction_leaf=0.0, n_estimators=500,\n",
" random_state=None, subsample=1.0, verbose=1,\n",
" warm_start=False)"
]
},
"execution_count": 121,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"bdt.fit(X[:n], labels[:n])"
]
},
{
"cell_type": "code",
"execution_count": 122,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"yhat_BDT = bdt.predict_proba(X[n:])"
]
},
{
"cell_type": "code",
"execution_count": 310,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
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AeRWsPwaYF/fYgXfM7Cgw2d2fr1KVUi3f+x48+mimqxCRTEoU9knPj2pmlwA/Ai6MW3yh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\nAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x213332ad0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"bins = np.linspace(-15,15, 50)\n",
"plt.hist(np.log(yhat_BDT[:,2]/yhat_BDT[:,0])[np.array(labels[n:]) == 'Signal'], bins=bins, label='Signal', color = 'red', histtype='step', normed=True)\n",
"plt.hist(np.log(yhat_BDT[:,2]/yhat_BDT[:,0])[np.array(labels[n:]) == 'Background'], bins=bins, label='Background', color = 'blue', histtype='step', normed=True)\n",
"plt.axvline(cut_BDT, color='green', linewidth=2)\n",
"plt.legend()\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 305,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"4.72053573676 3.24703050232\n"
]
}
],
"source": [
"SB_BDT, cut_BDT = bestS2B(labels[n:], np.log(yhat_BDT[:,2]/yhat_BDT[:,0]))\n",
"print SB_BDT, cut_BDT"
]
},
{
"cell_type": "code",
"execution_count": 186,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"disc_RF = yhat[:,2] > cut_RF\n",
"disc_NN = np.log(yhat_NN[:,2]/yhat_NN[:,0]) > cut_NN\n",
"disc_BDT = np.log(yhat_BDT[:,2]/yhat_BDT[:,0]) > cut_BDT"
]
},
{
"cell_type": "code",
"execution_count": 217,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"disc_final = disc_BDT.copy()\n",
"disc_final[(disc_RF == disc_NN)] = disc_RF[(disc_RF == disc_NN)]\n"
]
},
{
"cell_type": "code",
"execution_count": 218,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"SB_committee = s_over_rootB(labels[n:], disc_final)"
]
},
{
"cell_type": "code",
"execution_count": 219,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"RF: S/root(b) = 3.06490189892\n",
"NN: S/root(b) = 4.03753025318\n",
"BDT: S/root(b) = 4.72053573676\n",
"Committee of Experts: S/root(b) = 4.28494942637\n"
]
}
],
"source": [
"print 'RF: S/root(b) = {}'.format(SB_RF)\n",
"print 'NN: S/root(b) = {}'.format(SB_NN)\n",
"print 'BDT: S/root(b) = {}'.format(SB_BDT)\n",
"print 'Committee of Experts: S/root(b) = {}'.format(SB_committee)"
]
},
{
"cell_type": "code",
"execution_count": 286,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"947\n"
]
}
],
"source": [
"data_pred = bdt.predict_proba(X_data) \n",
"print (np.log(data_pred[:,2]/data_pred[:,0]) > cut_BDT).sum()"
]
},
{
"cell_type": "code",
"execution_count": 321,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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+0EvJpKV3zA477FBz+hlnnMG+++47rgFZLY3uWfD9DP2n3WM23u8Dv3f6nXol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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x213564a10>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# -- m_yy for selected events in region [110,140] GeV\n",
"plt.hist(np.array(data_df.ix[np.log(data_pred[:,2]/data_pred[:,0]) > cut_BDT]['HGamEventInfoAuxDyn.m_yy']), \n",
" np.linspace(110000, 140000, 50))\n",
"plt.xlabel(r'm$_{\\gamma\\gamma}$ (MeV)')\n",
"plt.ylabel('Number of Events')\n",
"plt.title(r'm$_{\\gamma\\gamma}$ of BDT selected events in range [110,140] GeV')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 314,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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JdRCHiIikqcqGcq7o+RkHcPe7Q4lIRETSSmU1mgMc+brP44BJQFtAiUZERKpU\n2VDOM0vnzSwLuBW4DngCeCD80EREJB1Ueo/GzI4HfgBcDcwHznT3/LoITERE0kNl92hmApcDjwKn\nuXthnUUlIiJpo7IHNm8DOgM/BXabWWHMVFA34YmISKqr7B5Ntd4aICIiEo+SiYiIhEqJRkREQqVE\nIyIioVKiERGRUCnRiIhIqJRoREQkVEo0IiISKiUaEREJlRKNiIiESolGRERCpUQjIiKhUqIREZFQ\nKdGIiEiolGhERCRUSjQiIhIqJRoREQmVEo2IiIQqaYnGzHaY2UYzW29muUFZGzN73szeNbNVZtYq\nZv1pZvaemb1jZsOSFbeIiFRPMms0DmS7+wB3HxiUTQWed/fewOrgM2bWDxgD9AOGAw+bmWpjIiIp\nINl/rK3c5xHAvGB+HjAymL8MWOjuRe6+A9gGDEREROq9ZNdoXjCzdWZ2Q1DW3t33BvN7gfbBfCdg\nV8y2u4DOdROmiIgcjSZJPPZ57v6RmZ0APG9m78QudHc3M69k+zjLZsTMZweTiIgclhNMdSdpicbd\nPwq+fmJmTxFpCttrZh3cfY+ZdQQ+DlbPA7rGbN4lKCtnRpghi4ikgWzK/hP+89CPmJSmMzNrYWaZ\nwfxxwDBgE7AcuDZY7VpgaTC/HBhrZk3NrAfQC8it26hFRKQmklWjaQ88ZWalMfzR3VeZ2TpgsZlN\nAnYAowHcfYuZLQa2AN8AN7t7Zc1qIiJST1i6/L2O3M+Jdy73AdOIvwwiHd9qc1lt708x1t9l9SUO\nxagYj25/7l6+B3CtSnb3ZhERSXNKNCIiEiolGhERCZUSjYiIhEqJRkREQqVEIyIioVKiERGRUCnR\niIhIqJRoREQkVEo0IiISKiUaEREJlRKNiIiESolGRERCpUQjIiKhUqIREZFQKdGIiEiolGhERCRU\nSjQiIhIqJRoREQmVEo2IiIRKiUZEREKlRCMiIqFSohERkVAp0YiISKiUaEREJFRKNCIiEiolGhER\nCZUSjYiIhKpJsgMQSW0WwjKR9KJEI5KQ+InBK1m7pstE0o0SjUgC4iWG8JKC0o2kFyUakXpGtR1J\nN+oMICIioVKNRiRKdQaRMCjRiARSo8mqfkUjkoiUaTozs+Fm9o6ZvWdmtyc7HpFk8AomkfosJRKN\nmTUG/gsYDvQDxplZ3+RGVddykh1AyHKSHUCocpIdQKhykh1AyHKSHUDKS4lEAwwEtrn7DncvAp4A\nLktyTHUyIPE0AAAHOElEQVQsJ9kBhCynjo5jFUzhygn9CJCM84rIqaPjJEtOsgNIeamSaDoDH8Z8\n3hWUicRRcTJJ56andD0vSX2p0hkgod8Zs6ZHbujFtR6M1LbS/7x/XkF5ZdscKTVu6telMF6FU367\n8tdO5DBzr///95jZucAMdx8efJ4GlLj7L2PWqf8nIiJSD7l7qP+HpUqiaQL8HbgI2A3kAuPcfWtS\nAxMRkSqlRNOZu39jZpOBlUBjYLaSjIhIakiJGo2IiKSupPc6M7PHzWyvmW2KKRtlZpvNrNjMziy3\n/rTgoc13zGxYTPlZZrYpWPbbmPJmZrYoKF9rZifGLLvWzN4Npv+b7PMzs+5mdtDM1gfTwyl6fveb\n2VYze8vM/mRmLWOWpcz1q865pdG1+/fg3DaY2Woz6xqzLGWuXXXPL12uX8yyH5pZiZm1iSlL3vVz\n96ROwFBgALAppuwUoDfwEnBmTHk/YANwDNAd2MbhWlkuMDCYXwEMD+ZvBh4O5scATwTzbYDtQKtg\n2g60SvL5dY9dr9x+Uun8LgYaBfP3Afel4vWr5rmly7XLjJm/BXgsFa9dDc4vLa5fUN4VeA74B9Cm\nPly/pNdo3P0VIL9c2Tvu/m6c1S8DFrp7kbvvIPLNOsfMOhL5AcoN1psPjAzmRwDzgvkniXQoAPhn\nYJW7f+HuXwDPE3nzQK2q5vnFlYLn97y7lwQfXwe6BPMpdf2qeW5x1ddzgwrPrzDmYwbwaTCfUtcu\nOJfqnF9cqXZ+gV8DPylXltTrl/REU02diDysWar0wc3y5XkcfqAz+rCnu38D7DOz4yvZV7L1CKru\nOWY2JCjrTOqe3/VE/kuC9Lt+secGaXLtzOwXZvYBMBG4NyhOm2sXc37XEqmVlkr562dmlwG73H1j\nuUVJvX6plmjS3W6gq7sPAG4DFphZZpJjqjEzuxP42t0XJDuW2hbn3NLm2rn7ne7eDZgD/CbZ8dS2\nmPObC/xnUJzy18/MWgB3AHfFFicpnDJSLdHkEWl/LNWFSDbNo2wTRml56TbdIPo8Tkt3/yzOvrpS\nNkvXOXf/2t3zg/m/EWn77EUKnp+ZTQT+Fbg6pjgtrl+8c0unaxdjAXB2MJ8W166c6PmlyfU7icj9\nl7fM7B9BrG+aWfs4MdXt9avtG1Q1vKnVnTg34ojcLD8r5nPpDa2mQA8iPwylN7ReB84hksHL39D6\nXTA/lrI3tN4ncjOrdel8ks+vLdA4mO8ZXLxWqXZ+RNprNwNty62XctevGueWLteuV8z8LcDvU/Xa\nVfP80uL6lVsWrzNAUq5frZ94Db5RC4lUW78m0h54PZGbUR8CB4E9wLMx699B5EbWO8A/x5SfBWwK\nlj0YU94MWAy8B6wFuscsuy4ofw+4NtnnB1wJvA2sB94ELknR83sP2Bmcx3qCniupdv2qc25pdO3+\nN4h1A5EbwO1S8dpV9/yAK1L4+h0Kzu+6csvfJ0g0yb5+emBTRERClWr3aEREJMUo0YiISKiUaERE\nJFRKNCIiEiolGhERCZUSjYiIhEqJRkREQqVEIyIioVKiEQlBMGjUGjOz4HOJmf0+ZnkTM/vEzP5c\nyT5ejB2gKij7vpk9bGZNzexlM9PvsNR7+iEVCcfVwNN++NUbB4BTzezY4PPFRN6nVdmrORYSecdU\nrDHAAnf/GniFw2OHiNRbSjTS4AXD+L5jZnPM7O9m9kczG2ZmfwmGqj276r0cYRywrFzZCuCSmOUL\nCV7jbmbXmNnrwXgos4KaypPAJcGbczGz7kAnd3812MfyYD8i9ZoSjUjEScBMIsNs9wHGuPt5wI+I\nvIwwYWbWGPg/fuQoqouAsWbWDOhP5K25mNkpwGhgsEfGQykBrnb3z4kMs/uvwfZjg32U2gAMrk5s\nIsnQJNkBiNQT/3D3zQBmthl4ISh/m8ir2KujLVBYvtDdNwW1knHAMzGLLiLyBt11wS2d5kTe6g2H\nm8+WE2k2uz5mf4fMrJGZHevuX1UzRpE6o0QjEnEoZr6EyKvlS+dr8ntS0ciGy4nUnM4nkpBK153n\n7vFqTsuB/zSzAUALd18f5zh6BbvUa2o6E6l9nwIZFSx7HJgR1J5Kk9Fq4CozOwHAzNqYWTcAd99P\nZIC8OURGhIwKmuCK3T02SYrUO6rRiESUrxXEfnYzuwQYCDwLfAO0j/3s7uuiK7sXm9nbZtbH3f8e\nuz93zwP+K6bM3X2rmf0UWBV0AigiMrrhB8F6C4E/EbmPE2sA8FpNT1ikrmjgM5EEmFkLd//SzEYB\nLwIHYz97ZCz12PUnAu3d/ZchxnQP8Ia7PxXWMURqg5rORBLg7l8Gs5+4+2flP8fZZAGRrskV3as5\nKkGz2RBgaRj7F6lNajoTqZ7yvzNxf4eCByq/HVYQwX2Z0PYvUpvUdCYiIqFS05mIiIRKiUZEREKl\nRCMiIqFSohERkVAp0YiISKiUaEREJFRKNCIiEiolGhERCdX/BwtkFZyXjFUrAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x12f6fa910>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# -- m_yy for all data in region [110,140] geV\n",
"plt.hist(np.array(data_df['HGamEventInfoAuxDyn.m_yy']), \n",
" np.linspace(110000, 140000, 50), label = 'All Events')\n",
"plt.hist(np.array(data_df.ix[np.log(data_pred[:,2]/data_pred[:,0]) > cut_BDT]['HGamEventInfoAuxDyn.m_yy']), \n",
" np.linspace(110000, 140000, 50), color = 'red', label = 'BDT Selected Events')\n",
"plt.xlabel(r'm$_{\\gamma\\gamma}$ (MeV)')\n",
"plt.ylabel('Number of Events')\n",
"plt.legend()\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 311,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"(1239196, 27)"
]
},
"execution_count": 311,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data_df.shape"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Others"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"print 'Types = {}'.format(set(pu.flatten(X325_df['HGamPhotonsAuxDyn.truthType'])))\n",
"print 'Origins = {}'.format(set(pu.flatten(X325_df['HGamPhotonsAuxDyn.truthOrigin'])))\n",
"# Particle truthType and truthOrigin are defined here: \n",
"# https://svnweb.cern.ch/trac/atlasoff/browser/PhysicsAnalysis/MCTruthClassifier/trunk/MCTruthClassifier/MCTruthClassifierDefs.h\n",
"\n",
"# truthType:\n",
"# 0 = Unknown\n",
"# 3 = NonIsoElectron\n",
"# 4 = BkgElectron\n",
"# 14 = IsoPhoton\n",
"# 15 = NonIsoPhoton\n",
"# 16 = BkgPhoton\n",
"# 17 = Hadron\n",
"\n",
"# truthOrigin:\n",
"# 0 = NonDefined\n",
"# 5 = PhotonConv\n",
"# 9 = TauLep\n",
"# 14 = Higgs\n",
"# 23 = LightMeson\n",
"# 25 = CharmedMeson\n",
"# 26 = BottomMeson\n",
"# 27 = CCbarMeson\n",
"# 38 = UndrPhot\n",
"# 40 = FSRPhot\n",
"# 42 = PiZero"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 70,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"--2015-10-30 18:45:29-- https://raw.githubusercontent.com/ml-slac/deep-jets/test-code/likelihood.py\n",
"Resolving raw.githubusercontent.com... 23.235.47.133\n",
"Connecting to raw.githubusercontent.com|23.235.47.133|:443... connected.\n",
"HTTP request sent, awaiting response... 200 OK\n",
"Length: 1687 (1.6K) [text/plain]\n",
"Saving to: 'likelihood.py'\n",
"\n",
"likelihood.py 100%[=====================>] 1.65K --.-KB/s in 0s \n",
"\n",
"2015-10-30 18:45:29 (76.6 MB/s) - 'likelihood.py' saved [1687/1687]\n",
"\n"
]
}
],
"source": [
"!wget https://raw.githubusercontent.com/ml-slac/deep-jets/test-code/likelihood.py"
]
},
{
"cell_type": "code",
"execution_count": 71,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"%run likelihood.py"
]
},
{
"cell_type": "code",
"execution_count": 256,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"HGamEventInfoAuxDyn.TST_sumet: 0.0974025488097\n",
"HGamEventInfoAuxDyn.m_yy: 0.0939963144843\n",
"HGamEventInfoAuxDyn.pT_yy: 0.0829551429091\n",
"HGamEventInfoAuxDyn.m_jj: 0.0804275883303\n",
"HGamEventInfoAuxDyn.CST_sumet: 0.0760380727805\n",
"HGamEventInfoAuxDyn.eventShapeDensity: 0.0641393479107\n",
"HGamEventInfoAuxDyn.TST_met: 0.0559665012045\n",
"HGamEventInfoAuxDyn.CST_met: 0.0509480369719\n",
"HGamEventInfoAuxDyn.Dy_j_j: 0.0500850913014\n",
"HGamEventInfoAuxDyn.pTt_yy: 0.0424038800992\n",
"HGamEventInfoAuxDyn.m_yy_resolution: 0.0394142904453\n",
"HGamEventInfoAuxDyn.Dphi_yy_jj: 0.0383577779491\n",
"HGamEventInfoAuxDyn.hardestVertexZ: 0.0349086734168\n",
"HGamEventInfoAuxDyn.selectedVertexZ: 0.0348643706821\n",
"HGamEventInfoAuxDyn.cosTS_yy: 0.0346988600924\n",
"HGamEventInfoAuxDyn.yAbs_yy: 0.0336816297308\n",
"HGamEventInfoAuxDyn.mu: 0.0262469569262\n",
"HGamEventInfoAuxDyn.numberOfPrimaryVertices: 0.0213167528802\n",
"HGamEventInfoAuxDyn.isPassedMassCut: 0.0112232526883\n",
"HGamEventInfoAuxDyn.NLoosePhotons: 0.00864043845855\n",
"HGamEventInfoAuxDyn.isPassedIsolation: 0.00703468884202\n",
"HGamEventInfoAuxDyn.isPassedPID: 0.00572237739075\n",
"HGamEventInfoAuxDyn.isPassedRelPtCuts: 0.00404916201392\n",
"HGamEventInfoAuxDyn.isPassed: 0.00335304814304\n",
"HGamEventInfoAuxDyn.isPassedEventClean: 0.00166009531659\n",
"HGamEventInfoAuxDyn.isPassedPreselection: 0.000465100222338\n",
"HGamEventInfoAuxDyn.isPassedBasic: 0.0\n"
]
}
],
"source": [
"ix = np.argsort(bdt.feature_importances_)[::-1]\n",
"for i, f in zip(bdt.feature_importances_[ix], np.array(features)[ix]):\n",
" print '{}: {}'.format(f, i)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 2",
"language": "python",
"name": "python2"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.10"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
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