UE_in_pp/plotting/dijet_QA_calo_input_comparison.ipynb

0001 {
0002  "cells": [
0003   {
0004    "cell_type": "code",
0005    "execution_count": 1,
0006    "id": "0727af2b-0e8b-44b8-af33-eeeb6ffc8f85",
0007    "metadata": {},
0008    "outputs": [
0009     {
0010      "name": "stdout",
0011      "output_type": "stream",
0012      "text": [
0013       "Welcome to JupyROOT 6.26/06\n"
0014      ]
0015     }
0016    ],
0017    "source": [
0018     "import ROOT\n",
0019     "from ROOT import TCanvas, TFile, TProfile, TNtuple, TH1I, TH1F, TH2F, TH3F, TColor, TEfficiency\n",
0020     "from ROOT import gROOT, gBenchmark, gRandom, gSystem\n",
0021     "import numpy as np\n",
0022     "import pdb"
0023    ]
0024   },
0025   {
0026    "cell_type": "code",
0027    "execution_count": 2,
0028    "id": "09dbc289-1f1f-4b62-9c83-efd18859c012",
0029    "metadata": {},
0030    "outputs": [
0031     {
0032      "name": "stdout",
0033      "output_type": "stream",
0034      "text": [
0035       "/direct/sphenix+u/egm2153/spring_2023\n"
0036      ]
0037     },
0038     {
0039      "data": {
0040       "text/plain": [
0041        "0"
0042       ]
0043      },
0044      "execution_count": 2,
0045      "metadata": {},
0046      "output_type": "execute_result"
0047     },
0048     {
0049      "name": "stdout",
0050      "output_type": "stream",
0051      "text": [
0052       "sPhenixStyle: Applying nominal settings.\n",
0053       "sPhenixStyle: ROOT6 mode\n"
0054      ]
0055     }
0056    ],
0057    "source": [
0058     "%cd /sphenix/u/egm2153/spring_2023\n",
0059     "gROOT.LoadMacro(\"sPhenixStyle.C\");\n",
0060     "gROOT.ProcessLine(\"SetsPhenixStyle()\")"
0061    ]
0062   },
0063   {
0064    "cell_type": "code",
0065    "execution_count": 3,
0066    "id": "34ddc2fe-b709-44e8-ad2c-2800084add08",
0067    "metadata": {},
0068    "outputs": [
0069     {
0070      "name": "stdout",
0071      "output_type": "stream",
0072      "text": [
0073       "/gpfs/mnt/gpfs02/sphenix/user/egm2153/calib_study/JetValidation/analysis\n"
0074      ]
0075     }
0076    ],
0077    "source": [
0078     "%cd /sphenix/user/egm2153/calib_study/JetValidation/analysis"
0079    ]
0080   },
0081   {
0082    "cell_type": "code",
0083    "execution_count": 10,
0084    "id": "82cc2d24-9155-4d3e-ac61-ee100dcb2ec3",
0085    "metadata": {},
0086    "outputs": [
0087     {
0088      "name": "stdout",
0089      "output_type": "stream",
0090      "text": [
0091       "144950.0\n",
0092       "554588.0\n",
0093       "856646.0\n",
0094       "644670.0\n",
0095       "621570.0\n"
0096      ]
0097     }
0098    ],
0099    "source": [
0100     "direct = 'results_11_11'\n",
0101     "\n",
0102     "f1 = ROOT.TFile.Open(\"ue_unfolding/dijet_calo_analysis_data_topo_pt7cut_wAj_wntopo.root\")\n",
0103     "h_jetspectra = TH1F(f1.Get(\"h_pass_spectra\"))\n",
0104     "h_deltaphi = TH1F(f1.Get(\"h_deltaphi\"))\n",
0105     "h_xj = TH1F(f1.Get(\"h_pass_xj\"))\n",
0106     "h_jetspectra.Scale(1.0/h_jetspectra.Integral())\n",
0107     "h_deltaphi.Scale(1.0/h_deltaphi.Integral())\n",
0108     "h_xj.Scale(1.0/h_xj.Integral())\n",
0109     "h_jetspectra.SetDirectory(0)\n",
0110     "h_deltaphi.SetDirectory(0)\n",
0111     "h_xj.SetDirectory(0)\n",
0112     "f1.Close()\n",
0113     "f2 = ROOT.TFile.Open(\"ue_unfolding/dijet_calo_analysis_waveform_topocluster_simulation_pt7cut_wAj_wntopo.root\")\n",
0114     "h_mc_jetspectra = TH1F(f2.Get(\"h_pass_spectra\"))\n",
0115     "h_mc_deltaphi = TH1F(f2.Get(\"h_deltaphi\"))\n",
0116     "h_mc_xj = TH1F(f2.Get(\"h_pass_xj\"))\n",
0117     "h_mc_jetspectra.Scale(1.0/h_mc_jetspectra.Integral())\n",
0118     "h_mc_deltaphi.Scale(1.0/h_mc_deltaphi.Integral())\n",
0119     "h_mc_xj.Scale(1.0/h_mc_xj.Integral())\n",
0120     "h_mc_jetspectra.SetDirectory(0)\n",
0121     "h_mc_deltaphi.SetDirectory(0)\n",
0122     "h_mc_xj.SetDirectory(0)\n",
0123     "f2.Close()\n",
0124     "f2 = ROOT.TFile.Open(\"ue_unfolding/dijet_calo_analysis_cluster_topocluster_simulation_pt7cut_wAj_wntopo.root\")\n",
0125     "h_clus_jetspectra = TH1F(f2.Get(\"h_pass_spectra\"))\n",
0126     "h_clus_deltaphi = TH1F(f2.Get(\"h_deltaphi\"))\n",
0127     "h_clus_xj = TH1F(f2.Get(\"h_pass_xj\"))\n",
0128     "h_clus_jetspectra.Scale(1.0/h_clus_jetspectra.Integral())\n",
0129     "h_clus_deltaphi.Scale(1.0/h_clus_deltaphi.Integral())\n",
0130     "h_clus_xj.Scale(1.0/h_clus_xj.Integral())\n",
0131     "h_clus_jetspectra.SetDirectory(0)\n",
0132     "h_clus_deltaphi.SetDirectory(0)\n",
0133     "h_clus_xj.SetDirectory(0)\n",
0134     "f2.Close()\n",
0135     "f2 = ROOT.TFile.Open(\"ue_unfolding/dijet_calo_analysis_nozero_topocluster_simulation_pt7cut_wAj_wntopo.root\")\n",
0136     "h_nz_jetspectra = TH1F(f2.Get(\"h_pass_spectra\"))\n",
0137     "h_nz_deltaphi = TH1F(f2.Get(\"h_deltaphi\"))\n",
0138     "h_nz_xj = TH1F(f2.Get(\"h_pass_xj\"))\n",
0139     "h_nz_jetspectra.Scale(1.0/h_nz_jetspectra.Integral())\n",
0140     "h_nz_deltaphi.Scale(1.0/h_nz_deltaphi.Integral())\n",
0141     "h_nz_xj.Scale(1.0/h_nz_xj.Integral())\n",
0142     "h_nz_jetspectra.SetDirectory(0)\n",
0143     "h_nz_deltaphi.SetDirectory(0)\n",
0144     "h_nz_xj.SetDirectory(0)\n",
0145     "f2.Close()\n",
0146     "f2 = ROOT.TFile.Open(\"ue_unfolding/dijet_calo_analysis_detroit_jet10_topocluster_simulation_pt7cut_wAj_wntopo.root\")\n",
0147     "h_dt_jetspectra = TH1F(f2.Get(\"h_pass_spectra\"))\n",
0148     "h_dt_deltaphi = TH1F(f2.Get(\"h_deltaphi\"))\n",
0149     "h_dt_xj = TH1F(f2.Get(\"h_pass_xj\"))\n",
0150     "h_dt_jetspectra.Scale(1.0/h_dt_jetspectra.Integral())\n",
0151     "h_dt_deltaphi.Scale(1.0/h_dt_deltaphi.Integral())\n",
0152     "h_dt_xj.Scale(1.0/h_dt_xj.Integral())\n",
0153     "h_dt_jetspectra.SetDirectory(0)\n",
0154     "h_dt_deltaphi.SetDirectory(0)\n",
0155     "h_dt_xj.SetDirectory(0)\n",
0156     "f2.Close()\n",
0157     "print(h_jetspectra.GetEntries())\n",
0158     "print(h_mc_jetspectra.GetEntries())\n",
0159     "print(h_clus_jetspectra.GetEntries())\n",
0160     "print(h_nz_jetspectra.GetEntries())\n",
0161     "print(h_dt_jetspectra.GetEntries())"
0162    ]
0163   },
0164   {
0165    "cell_type": "code",
0166    "execution_count": 11,
0167    "id": "376a07a6-8017-4dd2-a57e-9f6492409b98",
0168    "metadata": {},
0169    "outputs": [
0170     {
0171      "name": "stderr",
0172      "output_type": "stream",
0173      "text": [
0174       "Warning in <TCanvas::Constructor>: Deleting canvas with same name: canvas\n",
0175       "Info in <TCanvas::Print>: png file /sphenix/u/egm2153/fall_2024/results_11_11/h_jetspectra.png has been created\n"
0176      ]
0177     },
0178     {
0179      "data": {
0180       "image/png": 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\n",
0181       "text/plain": [
0182        "<IPython.core.display.Image object>"
0183       ]
0184      },
0185      "metadata": {},
0186      "output_type": "display_data"
0187     }
0188    ],
0189    "source": [
0190     "canvas = ROOT.TCanvas(\"canvas\", \"\", 600, 800)\n",
0191     "pad1 = ROOT.TPad(\"pad1\", \"\", 0, 0.3, 1, 1.0)\n",
0192     "pad1.SetBottomMargin(0.02)  # Adjust the margin for better separation\n",
0193     "pad1.Draw()\n",
0194     "pad1.cd()\n",
0195     "pad1.SetLogy(1)  # Set logarithmic scale for the spectra plot\n",
0196     "\n",
0197     "# Customize the histograms (color, marker, etc.)\n",
0198     "h_jetspectra.SetStats(0)\n",
0199     "h_mc_jetspectra.SetStats(0)\n",
0200     "h_clus_jetspectra.SetStats(0)\n",
0201     "h_nz_jetspectra.SetStats(0)\n",
0202     "h_mc_jetspectra.SetLineColor(2)\n",
0203     "h_mc_jetspectra.SetMarkerColor(2)\n",
0204     "h_clus_jetspectra.SetLineColor(4)\n",
0205     "h_clus_jetspectra.SetMarkerColor(4)\n",
0206     "h_nz_jetspectra.SetLineColor(6)\n",
0207     "h_nz_jetspectra.SetMarkerColor(6)\n",
0208     "h_dt_jetspectra.SetLineColor(7)\n",
0209     "h_dt_jetspectra.SetMarkerColor(7)\n",
0210     "\n",
0211     "h_mc_jetspectra.GetXaxis().SetLabelSize(0)\n",
0212     "h_jetspectra.GetXaxis().SetLabelSize(0)\n",
0213     "h_clus_jetspectra.GetXaxis().SetLabelSize(0)\n",
0214     "h_nz_jetspectra.GetXaxis().SetLabelSize(0)\n",
0215     "h_dt_jetspectra.GetXaxis().SetLabelSize(0)\n",
0216     "\n",
0217     "h_mc_jetspectra.Draw()\n",
0218     "h_dt_jetspectra.Draw(\"same\")\n",
0219     "h_clus_jetspectra.Draw(\"same\")\n",
0220     "h_nz_jetspectra.Draw(\"same\")  # Uncomment if needed\n",
0221     "h_jetspectra.Draw(\"same\")\n",
0222     "\n",
0223     "# Add legend\n",
0224     "leg = ROOT.TLegend(.17, .08, .55, .35)\n",
0225     "leg.AddEntry(\"\",\"Dijet Events |#Delta#phi| > 2.75\",\"\")\n",
0226     "leg.AddEntry(h_jetspectra,\"Jet Trig. Data\",\"l\")\n",
0227     "leg.AddEntry(h_mc_jetspectra,\"Calo Waveform\",\"l\")\n",
0228     "leg.AddEntry(h_clus_jetspectra,\"Calo Cluster\",\"l\")\n",
0229     "leg.AddEntry(h_nz_jetspectra,\"Calo No ZS\",\"l\")\n",
0230     "leg.AddEntry(h_dt_jetspectra,\"Detriot Waveform\",\"l\")\n",
0231     "leg.Draw()\n",
0232     "leg.SetTextSize(0.04)\n",
0233     "\n",
0234     "canvas.cd()\n",
0235     "pad2 = ROOT.TPad(\"pad2\", \"\", 0, 0.05, 1, 0.3)\n",
0236     "pad2.SetTopMargin(0.02)\n",
0237     "pad2.SetBottomMargin(0.4)\n",
0238     "pad2.Draw()\n",
0239     "pad2.cd()\n",
0240     "ratio1 = h_mc_jetspectra.Clone(\"ratio1\")\n",
0241     "ratio1.Divide(h_jetspectra)\n",
0242     "ratio2 = h_clus_jetspectra.Clone(\"ratio2\")\n",
0243     "ratio2.Divide(h_jetspectra)\n",
0244     "ratio3 = h_nz_jetspectra.Clone(\"ratio3\")\n",
0245     "ratio3.Divide(h_jetspectra)\n",
0246     "ratio4 = h_dt_jetspectra.Clone(\"ratio4\")\n",
0247     "ratio4.Divide(h_jetspectra)\n",
0248     "\n",
0249     "ratio1.GetYaxis().SetTitle(\"MC/Data Ratio\")\n",
0250     "ratio1.GetYaxis().SetNdivisions(208)\n",
0251     "ratio1.GetYaxis().SetRangeUser(0.5,1.5)\n",
0252     "ratio1.GetYaxis().SetTitleSize(25)\n",
0253     "ratio1.GetYaxis().SetTitleFont(43)\n",
0254     "ratio1.GetYaxis().SetTitleOffset(1.5)\n",
0255     "ratio1.GetYaxis().SetLabelFont(43)\n",
0256     "ratio1.GetYaxis().SetLabelSize(25)\n",
0257     "ratio1.GetXaxis().SetTitle(\"p_{T,reco jet} [GeV]\")\n",
0258     "ratio1.GetXaxis().SetTitleSize(25)\n",
0259     "ratio1.GetXaxis().SetTitleFont(43)\n",
0260     "ratio1.GetXaxis().SetTitleOffset(0)\n",
0261     "ratio1.GetXaxis().SetLabelFont(43)\n",
0262     "ratio1.GetXaxis().SetLabelSize(25)\n",
0263     "\n",
0264     "# Draw ratio plots\n",
0265     "ratio1.Draw(\"ep\")\n",
0266     "ratio2.Draw(\"same ep\")\n",
0267     "ratio3.Draw(\"same ep\")  # Uncomment if needed\n",
0268     "ratio4.Draw(\"same ep\")\n",
0269     "\n",
0270     "# Update canvas\n",
0271     "canvas.Update()\n",
0272     "canvas.Draw()\n",
0273     "canvas.SaveAs(\"/sphenix/u/egm2153/fall_2024/\"+direct+\"/h_jetspectra.png\")"
0274    ]
0275   },
0276   {
0277    "cell_type": "code",
0278    "execution_count": 12,
0279    "id": "638bcad9-11c2-48d0-a0bf-8c92bd3d1262",
0280    "metadata": {},
0281    "outputs": [
0282     {
0283      "name": "stderr",
0284      "output_type": "stream",
0285      "text": [
0286       "Warning in <TCanvas::Constructor>: Deleting canvas with same name: canvas\n",
0287       "Info in <TCanvas::Print>: png file /sphenix/u/egm2153/fall_2024/results_11_11/h_deltaphi.png has been created\n"
0288      ]
0289     },
0290     {
0291      "data": {
0292       "image/png": 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\n",
0293       "text/plain": [
0294        "<IPython.core.display.Image object>"
0295       ]
0296      },
0297      "metadata": {},
0298      "output_type": "display_data"
0299     }
0300    ],
0301    "source": [
0302     "canvas = ROOT.TCanvas(\"canvas\",\"\",600,500)\n",
0303     "leg = ROOT.TLegend(.6,.65,.85,.89)\n",
0304     "leg.AddEntry(h_deltaphi,\"Jet Trig. Data\",\"l\")\n",
0305     "leg.AddEntry(h_mc_deltaphi,\"Calo Waveform\",\"l\")\n",
0306     "leg.AddEntry(h_clus_deltaphi,\"Calo Cluster\",\"l\")\n",
0307     "leg.AddEntry(h_nz_deltaphi,\"Calo No ZS\",\"l\")\n",
0308     "leg.AddEntry(h_dt_deltaphi,\"Detroit Waveform\",\"l\")\n",
0309     "leg.SetTextSize(0.04)\n",
0310     "h_deltaphi.SetStats(0)\n",
0311     "h_mc_deltaphi.SetStats(0)\n",
0312     "h_clus_deltaphi.SetStats(0)\n",
0313     "h_nz_deltaphi.SetStats(0)\n",
0314     "h_dt_deltaphi.SetStats(0)\n",
0315     "h_mc_deltaphi.SetLineColor(2)\n",
0316     "h_mc_deltaphi.SetMarkerColor(2)\n",
0317     "h_clus_deltaphi.SetLineColor(4)\n",
0318     "h_clus_deltaphi.SetMarkerColor(4)\n",
0319     "h_nz_deltaphi.SetLineColor(6)\n",
0320     "h_nz_deltaphi.SetMarkerColor(6)\n",
0321     "h_dt_deltaphi.SetLineColor(7)\n",
0322     "h_dt_deltaphi.SetMarkerColor(7)\n",
0323     "h_mc_deltaphi.GetYaxis().SetRangeUser(0,0.16)\n",
0324     "h_mc_deltaphi.GetXaxis().SetRangeUser(-3.2,3.2)\n",
0325     "h_mc_deltaphi.Draw('hist')\n",
0326     "h_dt_deltaphi.Draw('hist,same')\n",
0327     "h_clus_deltaphi.Draw('hist,same')\n",
0328     "h_nz_deltaphi.Draw('hist,same')\n",
0329     "h_deltaphi.Draw('hist,same')\n",
0330     "h_mc_deltaphi.SetXTitle(\"#Delta#phi\") \n",
0331     "canvas.SetLogy(0)\n",
0332     "leg.Draw()\n",
0333     "canvas.Draw()\n",
0334     "canvas.SaveAs(\"/sphenix/u/egm2153/fall_2024/\"+direct+\"/h_deltaphi.png\")"
0335    ]
0336   },
0337   {
0338    "cell_type": "code",
0339    "execution_count": 13,
0340    "id": "7e191391-06d1-4ac5-9801-b7c1f022ebff",
0341    "metadata": {},
0342    "outputs": [
0343     {
0344      "name": "stderr",
0345      "output_type": "stream",
0346      "text": [
0347       "Warning in <TCanvas::Constructor>: Deleting canvas with same name: canvas\n",
0348       "Info in <TCanvas::Print>: png file /sphenix/u/egm2153/fall_2024/results_11_11/h_xj.png has been created\n"
0349      ]
0350     },
0351     {
0352      "data": {
0353       "image/png": 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L/inRPQshzLrKdHeO/d0+ow/FrUkZuaZSudSz3EVw0HEu2pZPjPSlcEcpaKpJAZeAzb1y6qqU54AtToqbk+wuwgW9uBdEYZNfQQghQjfY1Wo1nrHy+PX19U/s7p5vt82FS/X6a+bmzpw6lVdU49iQcsfIfMqqlA7ASQFzweSXDya/ZHq8bDVfvOquws6W5dHtdt9y7Fhvefnhvfx3U73unD37wNbW4uJivrEli81jUtrbJuOWs99oxrK7CLPDC43OdV01lJqqY/Q8j5mvVBYWFh7Y2vpnjuM4DgDHcX5hbq74mS9W8kWW34NnC0s2SVjyIxrQbDSyVqTs2Up4TsxyyhpLfkRUaDOQ+QCsAKv6Urt3/0xdSt4rOHuY/IiInrIGfLXbvXljA5UKXBeVys3r63/V7Y56ryAVF5PftFJ3iKv584ZqaRvhPgTrIeIWDrvz8SMhSs2FC2JlRRoDtsndXXH8uLhwIe/IKG0Z3T84Gwp7fqKv4yCz6Mn4ifQGOZy5RN9jHl2Y3UR66oi8dZ2ys76+vnLHHaEP1+odd5w4cSLv0Eoqu4twQS/uBVHM5Kc+kNFRVwbJCqMlv2hW0wO7RAMbas+DU5FntHMqmzQKDsj0DU9KdmeY1Z5TRtUrep5n9i9oNpvVajW7wTyjEzjoEahDlZCh0deIiIqJyW/KmINZm5rNpq6KhDG/nZLQTqaGn1biWuxCyU/9ERplOzq6mBlAaIo+c+d64vVoPOZW6m56M0jzOYbm1FXT2+rlqmXU3HNoc7Yjlo1tWiRI4BAOWdd/Jg7FbULTKqMS5Wwo4PnBANWbuhZUDfpsDjAdqvZU7wFztbidmzvRY1tHF1r3HKqVDR3F3ImOQW+l2zJD+09YU5c+9Qx/6l+1gh4Fu1qtmoNiJ59SmjWw/5zACet08Hfj7rhNKFPZfTb50iUp2ncF68QLUWpag9BWKg2Yf8e15MXtUz8USiRqD6FtVWrR/5rJKXQm9TNKnkEi1OYXOg/RSEJHD8WW8C+Vgi2NBQjO4/xtuC00HfytuPURPBIgYPLL1IRLaKz27KP/yxM31dn4PxED3kds3g+g7oiwrhad5yHhRoVQzaeuTtQLzXlosX+8j9BuzepZM4ZoPHGTxQ+yZuhcJTRGzsbd2TQcWw2mkOIQjlqngz+MBft08Kz3TM9QGXF8TH7TJ66Bysx5un2rVquZE72GWFOCdf96ylyzwU/tQXe0MbOISn4qhlBPHLOx0JyDV+3ZbCmMTm9rRhhNWmy6ozF95eZLXz/0w9B08N849MOHb7qUd2iUMia/scU2H4z9E8OazJrNps4xQohOp6NrBa0zxybsKq4kVK1WzXnbzZWjnV9U3go10Zm7UtGqOM1dRb/6RcujcRGyDEdj+qnNg9devehf//9ibzp4//pvXXv10vPbB3OOjNLG5DdlVKqI5oNQL9BBZpS1dhntu36oelMttJbtzJrPUJa1psxo1WXcWMnm5npN6zMiGsqNLz6w8McH5E88q4cgQNBDIJ/37KP/6cDRl/BSOXPSajycScU8P+qF010Zox01YfQu0cW+aIcX65oJvWlCuwrFY3axCXWlCfXGjNtKLzRDRUyHF7NXS2jNaAeW0IFCK5jdaoi0h+69nMp+/CBIZT/llN1ncwY/86rvu84Nw25rXiULe02MttWZScvsUaIyhP4jlPxCNaJ9x0izfmGy3iMR2q1aJ5qBQq9RtIY29FDcIRCpYg2tyeRHE7YdBOtBMB8ECIL5IDgRBNvMgsPL7rM5a/PViUgnyaGeoOu6nU5Hb1Lw+fxCfS+tj5p3ncfVCmZUZxgNYMCjJD+v0dYkmqSulMeBJWBz74q0KuU5YAtY4LyAw8juIlzoi/uwVOqqVqu6MUk1NQ34HHWfkWlJfkRUTBtS7hiZT1mV0gFOMvkNg8mvP93D0HxGqiAYGgkzuqFOkwqTHxENIjaPSWm9VTd2Oe8YjMGZ3PtTpb1Qc1dc30iT7/sJd8IREQ0n+WLN79PFMDslm7hCnlo+4NMMrcySHxGNoCJlz1bCc2KWUxxWe/YXl+SY/Ihowtal3AXa+/NcXco54BST3zBY7UlENDXWgHPAqrpqdzoA6lKeBdbyDYsMTH59iP3yDudpqp+OmqluqDEt+478MshxleieObomEYAFIVrd7lfe+U5UKnBdVCoPbWy0ut3FIl1DciQGlmEQGd0/OHlxT2eopxlaubDnJ/o69r0/XYlOGzQ46xih5r3tGGC6pb6HGC02okLZ3t5+9atfvbKyoj8pq6urt9122/b2dt6hTZnsLsIs+U0f3bVHv4qNRiM65HS6zDtJNDU+dYqlvVqtlumzIJqMM2fOLC0tbW5u6iXtdnt5efn06dM5RkX7ZJRUJ089nWi5YainGVq5gOcnOgOtMuCMrCOX/OL2j/2z1I5Z8sPARViiIuClOGvZnZnZKfmprBAqhahiRMJEplMnNHuD1mw2zXscm82mWW+eUDjTs+4JIRJKXebcQ6a4AQRCB/V936y+Nw+qN1crdDqduDXN8NT+1aNsaCSioWWUVHMRfUZqiVnQ8fYMsocCnh8MULpSWUoN7a3nfFAPRWd1wN6A19bxqc0d9i0vYv/MEqGKWR2DPpAaglxvpWKrVqsJ4YUeqlarY5Y1ibIwPz9vvd46jpN3aFMmu4vwlWkl0SJQs62qDpCITBSnqJHMqtXqNBYXBo9ZD3AKoNls1mq16MDWagVddFMrtFqtuPJfWoNHm+OvmvvUf5vT9cm9PKfCq9Vq0sh80/giUhmsrKxc+Nq3PvgHD5gL3/LLb33O856dV0gUMlPJT10fO52O6pqhyIzvUs+uL2408AHTT2iW17hkFp1mQaXJIUIciZ4R3nVd/U0lLjyTenHNf7MKkWg8r/vH/83rfvcdr7nmzZ+6+CG15PZr7vg//+hrH/vDX883MNJmp81P8X0/NJ9fdAUpZVyJQRe0iywuePM2O91UVqvVEkYutbaGWrNO3HETkmsc3/dVN9FarWa2+YWosM2Wy9B88Ux+VFifaVx6/1VnfnhxwYEDwIFz6eKNH7jqzGf+50t5h0Z7MqpOnQ0FPD9xr5rZLKfW0Y1hZjuf+Xe0A2d0wljzuNZ+mOZOMFibn3k4nX2jR4k7onX/RLkA7D+/hcunEUhICenBU3+8F8G7cDluE7LK7iI8ayW/mRc3T0WoF2ij0ehbILN2GY1bWdVVhhaqCTHiOtOGenuax9U1rr7vWzuRWo+oakrjIiSavLjstwFR35vvyIWr/liDWIeI24QmLaOkOhuKeX7UC6frdaMdNWGUmfSwLNGSn3XNhM6T+rihPZsrJMdg7ifuIbO0lxAeWPKjIoDlJ0AQ7BX7Bn+IrLK7CPOUJylm8pN7lY0mM2mFylJm/gslv9CIZck3mFuHNzMzkBmGdWLFuP3onYRqQRPCY/KjIvu7Ky5ZM9zfXXEp79CmTHYXYU7Zk6TgUxqZ3VviHtUPRW91iFtzwIMOsknCnuOCj26S/DSJCmj3bY9/9iPf/8WL+25s+Pg1337Ff3vt/AOH84pqGnE+v3xExxTn6SKivmRXPvmGi//5G9992XcW1JL/+8e2f+551z/jI9eIRU7sYBc3hwOTXw4KXvIjosKSXYnTQBtyVwpHYAVYAzPfsFjyyweTHxGNSfpSuMx5I2LyyweTHxFRjrK7CPM+PyIiKp2ZGtuzVPw97p4BN2w2myNMGKuH4oyGgeH7YarI4w5kXY2T3FKZdaSsZjeOcDlldAvFbCjs+Ym+jgPOATvyZLbqKNa5gkeYfrbvG9J6TyFnL6Ky2Q6C9SCYDwIEwXwQnAiC7SDIO6iJyu4izGrP6aM6BIdGzlTzJGR96LTmfIi+EfVkfuaBzBXUWNicw4jKoyvlcWAH6AkBIXpC7ALHgC47IqSByW/KhCbh0wtVbsj00CozZZRiVbZTuU39Do0RYz5EVAZngCVg06jtbAuxDJzOLaKZwuQ3ZUIDWGvNZtPMFs1m05wMKCFn6MmPhBDJic113UajkVz8Mo87eEOgKsvKft9nQymfaGYI28/J/ZlPaQtxKmZ9NgkOJ6Pq1NlQwPODAZq+VBZUI1/rYa/VQ9GBrbE35mdodOy444beNjDa/ELHHfANpo4bak1U21arVQ7gSWVgGQc0CBAE1hGwEx6aPdldhGfydKWmaMmv78QLSqPRMDuhxM3nZ04BqERn+NP0caOzK8TNwDdI5xqdL6MPhQbvZm8XKpv5mAznlKnPC5NfPoqW/ORgJT+TLtKNP5mtPm5oAluV8KypLjnaQUqHnueZ1bksCFJ5nAiCVZ3/fF/9UQ+Cu5n80sA2v7HF1b6P/xMj4Q45cwIE1fBWq9Wik9Bq1nlo+3YqGXkWiBDdpTNhc9d1m82m3MuUaXU3JSq+NeCr3e7NGxuoVOC6qFRuXl//q253Le/AZgOTXx9iv7zDAQBrMms2m7q3pxCi0+lEZ50dcFeDZDXP88a8uUIdxRqbytzRhXFTxhPNpgsXxMqK3NlBrwcAvZ7c3RXHj4sLF/KOLBPCJrvDMfn1ES2DR9bI7MdG1QFGs06oF2ij0eibmaxdRpM3MbcN3Vyh9hYt51lTabPZVOnZ+mjcrohK5cyZM89fWnp4c1Mvebjd/vvLy6dPz+bNDnHVnhM9HinFPD/qhVOdKqXRqmfthGJO4y5tvT1Da/bt7RmNRO8h1G8z7g2mQ2rYhJ6j3iqhawzRtOP1PE52T2oGT1aKCvtmilYARvOEZua/UPIL1TomDFRmTTzqQOZWocCs/VNC4Vk/vTqjxz1HolkyaHLrJ+/nkb7snhSn7ElS8CmNzO4tcY/qh9QQ2An7Sev+8eSo8t0b0RSpzFd6u73ocuewY10+kzifXz4KnvyIaIatv3z90W8/+r5vvs9ceOffu+u6Hzty6gun8opqwpj88sHkR0STYOvVuI3t4zi+jOU22mpJHfWzOHs/7l/Ckn0/M3e54mS2REQlIiEXsLCFLQeOAweAA2cOc1vYWsSinL0sN3Es2SRhyY+IJsB6P9t3ERzZK5/48F246u8dY3nI7F2usrsIcyZ3IqICkpuAA7kGAUBnvvdCfg8AJGdxGBOrPYmIcmYbv1p8CLvLwGmjhvO9kH8P+CAel1JY53ugwbHkN2V83zeHPnFdd5L3ADSbzb6jwFhvnGg2m9FQrQtTlPX+iTL12pd+5fOPHZz7Ly/bgXSAXeB7wOd/6gv/1fwlgIPcji2j+wdnQwHPT9wd4oNPd6BudR/h0KE5H+J2EjdZRGhhdEKldKkj8r54ml7n/+zCbTd8afUFHiBfgQCQ9Z/xbr3+S498sZt3aJOT3UWY1Z5TyXwJ9XQHAw6GOUjpzUrN5K7/jTtidGROfThzYbp31oeonXueN87Q20T5Wnzxjfd/asGZkw56n4V00Jt7prz/k0eXXnI079BmAZNfHwWc1SHEdV31/WgCF/pBDhFNfp1ORxUHQwtTDi4mEqLptfjiG09+odaT8//Xvf+5J+dPfbE2w5mPszoUS7QMXkyNRsNMJ77vm28gnXXUbEedTke9q1SrmF5ZrdNsNq3bqtXMP2q1WjTBWOdkaDab1Wo1tNAsR5pHNIdkMwPQa+ocbIaqt2o2m2rav9DC6JqhM6CWqxkEzfVDm3O6CZq82jtuyjuEzMVVe070eKQU8PyohBFdbp2uQTXvRWdyVw9JowXRnCPC3NZ8k5htfnoKCGujndnspwM2I49Gi71xt0ODZcM2Zrd5FBVDaKvQFBD63+iT0sNn6+eilpjT08edEKKp40/bLPDZfdz4MU5SwMvcIMkv2uUE+yceCiUJM4FFL+46i4Q6vCC+u4q5Wx1MQoQ6GUcjDK2ZkBejudm6lTWS0NFDsZn/xp1/oiLbDoL1IJgPAgTBfBCcCILtKcmC2X3cWO05LpHZz8h0G5tWrVYT2thCVZehDqXR6sq+VLWk2kpNWquPoh4KBWPOOOH7vvmouSv121wyyHy85lZKtGI2tB9OGU+zpLJ1uDcAACAASURBVCvlcWAH6AkBIXpC7ALHgG6B23EmgMlvRoSSgWrV04bqXRLNKKN1TtG3JOodmjnYTLEq+alQVXNdKBgz+ZlLarWafo6hDQcJb9hnRDSNzgBLwKbReaQtxDIwm/PBD2wKbnI3r6GD998zbwZP6KOoHxr5buiCfHeK9iUZufNndOa/EUpCKs+Fkp/qiqICM4t6tVpN1XzqLiehXbVarWaz2Wq1QqVSWe6vrkSmpOqiSLfJthCQMm5ipFJ8rjKqTk3LaAFH7wSPm4XcFJ3HvIDnx9rmpLufqH+jbX6NRsN8NNTmZ64ZPQ/Y3/vDXJ5wi7o+vdG9hV7HaAxmhOazM1cLdZmRe5O/m4+aBw29AfSS6LkKHZ1tfjQtrIOkIQgQBMM+VBzZfdwK9TTDdL87s9di33MR6sGo/zUvlKF1zE595q4KeJnTHRc1s3eiEsqFoa6PyckvujLie5Ekj89i/doRPc+hTjf6pUneSi8MdRm1hhrq1WKuyeRHM28+JsM509DnpYzJz9qtPJrGouJSnXlFs+7HeriR48+IdXizvuVacwXzO4T1Uh6q5NRnKZr8ognJFD2fMpJczTX1DqOvV7RPZnTDhFATnhSTH828E0GwGsl/9SC4u9zJr7jz1bmuqzoKmm1XquEnof+hakBCpDVI3aqsF4b+NY+oW54w/fP5xXWJHGRosbTWGZB+Qc3+LIPsObRhKmsSzZKulMeAZdXOBwCoS3kW2AIWCzlqlSnDi3BGSXV8Kry4L/txW1kLFjKx4ivhiEU+P0REA9oOghNB4AQBgsAJgruD4Pw0FPtkme/zG/ZL+oD911WONIeqUgeqVqssFhDRjFkQ4qQQPSE8oCfEKSGKX+bLWtGT32j6DjjZbDZV/tM3iqkbw3nvFxHNsn+b+YDy02I2k19fvu+3Wi31t+4Koe9LM01siHEiooxsP7i98fKNyoFK7R21yoHK+svWtx/czjEeMbDsYihL8gtlNdUpRjUN+r4v42fFi1ZAE82S9/2Gl3cIlK3tB7dXbrvrsa99tSd7AHqy1/v63xy/9c4c89/gLXPZxTBryc86n07oUdV9tFqthsZ7VBWhnP6UyuDLnzz/3y2sz4vKXe995byovOnoiS9/8nzeQVEmzqzet3jpwP2Pfkwv2Xz0Yz/+gytOr9ybY1S5K3ryy6IRLq4bvVoygUlWifL15U+ef/svrTzx3W/togdgF73vP/btt//Scea/qRZXc3jqz999/xOfDq28+cSnf/uheydf2VgcxU1+qhwWnRMViUNNqgSm2/M0ldKsQ0eGcER/mnn33vXe6+WRj198QC/5o4sfuEFe9+47/12OURFNVHp3TaQvGqFaEhrRUUlYJzRiSNyUpNW9yVHNXaXzTIjyUJILBT0FiP4EwDwc62vq4HBg20QW6eXO7r1XoCcZNcjYnnEjW2L/zODWrRAZ/xORXJvl8yPKFpMfSSnfKN7yWrw+9IK+Fm94o7gj79D6K2nyk5EhGaMnIpr8pG0AzOhIMVM6qwPREGKKAg7mrRnuMJziFwUoTtxL9yw88iLcdgtW9Qt9C+ovxK3Pwrniv9rZXYSnYOzK0ebzw14DYfJWaudxbYHTPrYnkdWbDrz1+/LiH+Gj5sLX4vXXioMfDh6I24oKLqafigTwLHR/Cme+gvbj2D0M5+ew8jeofweLajvLNoW57GV3EebFPQmTH82kL//yv377xz5/Q1DR+e+1eP3fHnjsvv/6n/z8H1imDaGpVqnIXu+pDPez8P4CNfW34zy9vLCyuwhPwUzuRJSuF973a+/55tl3f/Waw993VFHg2msr9z3/GS++79fyDo3St7KC3V3ZbgsAOvPV63JuLtew8lbcWx2IKCNiYeGFf/Rb//E3Kz0H9+N1PQf/8TfmX/zx/0UsLuYdGqVvbQ3nzmF19enyU70uz57F2lqOQeWP1XpJWO1JM0/6vuBMJrOu25WnT6Pdxu4uHAcrK1hbw+Ji0es8wTa/vDD5EdEs8X3pulOQ8zQmv3zEDfPDk0ZElK4JX2/Z4aUP5jkiogmwXmyzG2iUHV6IiKh0mPyIiKh0mPyIiGgInZloDGLyIyKi/rpSbkhZkdIFKlKuS9md5izI5EdERH10pTwO7AA9ISBET4hd4BgwvfmPyY+o1GajCouydgZYAjaNvpdtIZaB07lFNC7e55eEN7nTrOpKeQZoAz1gHlgB1oCFzLqV0xSJu9vOPm1E3HI1ncT4wWR2EWbJj6h0Zq8Ki7IVemN0OkmPTgkmP6LSmb0qLEqRZXJbIeYBdLvY2EClAtdFpYL1dXS7DiCFsE6JW3BMfkQzS8T8nNyf+ZS2EKfiN6GSe1O3u3T8OHZ20OsBQK+H3d2lY8fe1O3mHdqImPyISia5kmo6q7Aoawfabbm0hM3Npxe123J5WZw5k19QY2GHjiTs8EIzqSJlz9ZJwYlZTqWS1nCaqVw8OZN7bqzvA2ZEmmorwK6U7f3v7bqU5Z7Zm3KW3RjWVqz27EPa5B0U0VjWgHPAqvFOrkt5Fij3zN70FOtFb35+3rqy4zjW9Ue4Tk74YsuSH1HpLAixJeVpwJFyF3CAOWALWGSdJ8VYWVnpfe1bm3/wgLlw9Zffevh5z84rpDGxTSsJ2/xo5vlSusx51M/5T375rl96x6ErnvuHFz+klvzSNXd87/I3/v0fvufHb39RdsflTe5ElAlmPhqE07j0xqvOPP/iggMHgAPnJy/e+CtXnZlvXMo7tBGxZJOEJT8iKh3rKGaQYu8BH74LN7o8uk0KsWR2EebFPQmTHxGVTiSXSUgA1iSX8FDBkx+rPYmI6GnR8X0OADsxqawHeWA6RwVib08iInqaraAl3n3lDw9evmptf1J7L+QPrviR/NHVkwotTSz5ERFRHxff/OQrrvnOaaP8915I95rvXHzTkzlGNQ4mPyIi6uMtv3X4t286/LxnXdiBDCB3IH/yx7qnfu7wHe86nHdoI2LyIyKiPhYWxKmPPqPzq0ef66CG4LkOvF9dOPnRZywuFr91z469GZOwtycRUYjvS9edUM7jrQ75YPIjIsoRZ3XIDWd1ICKaAM7qUCyc1YGIKAud/dfSCV9smfyIiGhyulJuSFmR0gUqUq5L2c2jRMHkR0REE9KV8jiwA/SEgBA9IXaBY8Dk8x+THxERTcgZYAnYNJr32kIsA6cnHgl7MyZhb08iohHE9l2REtaOLXHL0xkf24IlPyIimojkssRkSxpTcKuD7/u+7wNwXdd13WG3AtBsNtPdORERJbDnMSEqUvZsjziqFdCyhcgoKRa9Wi9658cgATebzVarZS5pNBrRFNh356z2JCJK0bqUu0B7/7W3LuUccCom+ZVxPj9VFKtWq57neZ5XrVYxwI2QOvM1Gg3P8xqNBoBWq6ULgoraz7A7JyKika0B54BVKQHc0pEA6lKeBdYmH4r1vsIi8DwvGqFa4nlewobRdVT+q1arCUusGxb5/BARTaML5y9/Zv3yY/OXLyN4bP7yZ05c7p6/HLdydhfh4lbrua7b6XRC1ZWqVFetVkPFOM33/VqtBlsFprkw9K/e1vd9s/GP1Z5ERCmSXYnjwBLEpuigU0VVrkqcA7YgFljtCQDodDrYq/nUVCJUD1mppKgKdiZVqxmXMhXXdZvNJru9EBFl5Qy6R7rv3HxnBRUXbgWVjfZG9/ru5G/0K27yU4ZNRcnpzVxHpUOV7VTaGz46IiKyEfaf7snuyodWdrDTQw9AD71d7B7/4PHuqa51fZnVbX6FT36jiaZMtUSlPZ0ghRCtVqvT6XQ6nVarJYQYJHcSEdEIJGQb7SUsbWJTL2yjvYzlMziTXZ6zms3kNwhVd6q7t6iaUtVeaBIDy+E5EBEVkoCI/hzAgZM4aWY+pY32KZw6gAPWrTKKsCzJz1qk8zxPlxGbzaauCDXXGbzvUNZPgYiI0jJryc+s3ox7VCc8a28a1nwSEY1J2n4CwMEV1vUP44rAtkl2ip78sktFqpwXldCVlIiIBiJl9EdI+dNXVG9CuHXpZrzyp694hbBtkl2AxU1+qhEulPxU4Swub2GvMBca2wz7b5xQv+OSXMLOiYhoEJa2OwEh8IXL738Y1wCrxrr1h3D1Fy+/37p+dsW/4iY/ledCaUz9azbL+XvUv7om08ya0ZRpbd5TvV14nx8RUTYksABsAQ7gAAAcYA7YAhYzruaMxlJgKkWFht8MxazX0Uv0uGhqK33Du7mVXscc/xO2Ac8yfHpERCUzP2827Xn6b8cJrOtndxEu+vBdapAzc0koYLVCaMCz6KwOZsdORQ+EpkVHTePwZkREKVpfl7u7aLf3z+pQl3NzOHVqosObTcHFfeQp91StZvJWejxP2Co8mfyIiFLU7cpjx7C8/HT+q9fl2bPY2sLiIpNfYTD5ERGlq9uVp0+j3cbuLhwHKytYW7NnPjD55YXJj4goI74vXbfPAC5Mfvlg8iMiylEZpzQiIiLKCJMfERGVzpV5B1B01ukaWBdKRJSuCc+Nw+TXB/McEdEEWC+22WVEVnsSEVHpMPkREVHpMPkREVHpMPkREVHpMPkREVHpMPkREVHpMPkREVHpMPkREVHpMPkREVHpMPkREVHpMPkREVHpMPkREVHpcGDrPjirAxHRBHBWh2JhniMimgDO6kBERJQtJj8iIiodJj8iIiodJj+iaSU7bJAmGhGTH9GUkV0pN6SsSLiQFSnXpewyCxINh8mPaJrIrsRxYAeiJwSE6AnsAsfA/Ec0FCY/oqlyBk9cJ8Xm0/2/RVs8cb3E6RxjIpo+gvexJRCC54dyEnN3k4QUtsfiloPvX5pm2V2EWfIjmhoyMZUlP0pEJiY/oiIStp8DEDtGhuugo//uQR6AiG5CRFYc3oxoishNIMD299Fuo91Dbx7zK1i5FvUrcRSQzHdEA2LyIyoiaW/Yw/Px/8zj7muw1EMPQA+9z2P3Io738DsB/iEb/YgGxA4dSeLGVOVJo7y8/MpXXbx8+WH45sKbUbv6CvGFH30mp6CIUjDh6y2TXxL29qS8pDWYPd/ANNXY25OIiCg1TH5ERSRjzM/PW9d3HMe6/oTDJpoW7PBCNE1WVlZ2d3fb7ba5sF6vz83N5RUS0TRiyY9omqytrZ07d251dVUvqdfrZ8+eXVtbyzEqoqlT9JKf7/u+7wNwXdd13WG3AtBsNvuur9YZZE2ifC0sLGxtbZ0+fdpxnN3dXcdx5ubmtra2FhcX8w6NaJoUujdjtMPbINE2m81Wq2UuaTQaCYlNrV+tVnW+NAMo8vmhkvN9f/BvhETTqIy9PdWnulqtep7neV61WsUA/b915ms0Gp7nNRoNAK1WK5rYFN/3Q5mSaFow8xGNrKAlG9/3a7Ua9hf1VObzPC/hMx9dJ6FgByObsuRHRFQ0pSv5qVpKVW7T1L8JFZg6e5nZUa3f6XSi66vVQkchIqKZV9Dkp3JVqISXkMYUlfyiyUxVmYYKds1ms9PpNBoN1h3RlOqwWoJoVAVNfsqwaSmuYc+6pmrqYw9PmjpdKTekrEjpAhUp16XsMgsSDanQyW800ZSplpipMdqgSDQVulIeB3aAnhAQoifELnAMYP4jGsoMJr++VC70PG+QlcXAsg2aCABwBlgCNo33W1uIZeB0bhERDa0I19Wi3+SeCrPM5/t+p9OpVqsD1qmydEi5SPrQR64IbSEg5Snbunz7UgENfl3NLv/NVPJzXbfT6cTd+asWqgpP13V1a59KjZ1Oh+O8UNElXzKkjOZFIrIqdPLLbgAL643t7AJDxWHPckJUpOzZHnFUKyARDaagbX7qdoXozQnYu2/BSmXKaGIzb5zwIvStEerftJ4CURZWgNVI+a8u5Uou0RBNreKOYKKqepNHeIne1T7sCC/YG02GI7zQVOhKeQxYVu18AIC6lGeBLWCRJT+aOaUb4QV7JTzXddUUDTqZhUZvqdVqZkWlKrrVajW1lR7qc/BbAImKbEGILcABHCkhpSPlHDMf0fCK2+anEl6n01FdVJS+XwFc1200Gq1Wy9yKlZk0SxaEOAmcBHwpXeY8opEUvVpvtPn8sNdAOOxWIaz2JCLKUXYXYV7ckzD5ERHlqIxtfkRERBlh8iMiotJh8iMiotJh8iMiotIp7q0OBWEdVpW9YIiI0jXhuXGY/PpgniMimgDrxTa7jMhqTyIiKh0mPyIiKh0mPyIiKh0mPyIiKh0mPyIiKh0mPyIiKh0mPyIiKh0mPyIiKh0mPyIiKh0mPyIiKh0mPyIiKh0mPyIiKh0ObN0HZ3UgIpoAzupQLMxzREQTwFkdiIiIssXkR0REpcPkR0REpcPkR0REpcPkR0REpcPkR0REpcPkR0REpcPkR0REpcPkR0REpcPkR0REpcPkRzRpssMx84hyxuRHNCGyK+WGlBUJF7Ii5bqUXWZBonww+fUhbPIOiqaP7EocB3YgekJAiJ7ALnAMzH9EyoQvtoKzFiQQgueH0iE3JHYgNvd9mOWqhANxkl+niOyyuwjz4p6EyY+GFpPIJKSwPRa3XD1GVHLZXYRZ7UmUOZmYx5IfJaIsMPkRpUpafoQUgWPPcMFhKaSwbkVE2WHyI5qEz/7EJf/QN9XfHXTUH/6hs5/9iUv5BUVUXlPQpuX7vu/7AFzXdV132K0ANJvNuNX0Q9ads82PhhXXPe1GBPfgwofR/jO0e+jNY/7FWHkz6hs4eiHmOyjfekTl7fAS7eo6SMDNZrPVaplLGo1GKAW6rtvpdEIbep5npkAmPxpWTPKTQPcgVv4Rlv4Mm2rRS7D6FZy7hPuBBWs/Gb71iEra4UXloWq16nme53nVahW2dBiiM1+j0fA8r9FoAGi1WrogqNZRmU+to3deq9Uyei5UEhIi+hPgwEG8+5KR+QB8Ce1LWD6Idwc4YN0qx2dBNPtkUXmeF41QLfE8L2HD6Doq/1Wr1eT9qPzXaDTM1cZ4BlRGZfhsEk1Mdh+E4pb8VC2lylua+jehDU8X78zaS7W+ruS0rqNXMwuIREQ0k4qb/FSusuanaFudplJXKGUCUKU6M7FF1yEaX9zXzHnHsa7vHD4ct8mEIycqlSvzDqCPwbt3KoOU21zXtV5ZVGYd9ohEg1hZXd29cKH9wQ+aC+tvecvcc56TV0hEZVbckt84oglMLUlIjboLTEKdKtHI1tbWzj366Orqql5Sr9fP/u3frq2t5RgVUWnNZvIbiu/7QgjVQVT3stGsA41zqgca1sLCwtbWluM4juMAcBxnbm5ua2trcXEx79CIJq0I19WiV3umJa7Mp+/2q1ar1nXY9EKpOXpU3HOPuOce+L5wXRE7CDbRjBv8uppd/pu1kl9y9aZZHaoKfCrzeZ7HTp6Uqa6Ux4EdoCcEarWeELvAMaDLb1dEeSh68ssoJ/m+r+5nV3f1sZMLZe0MsARsGl9j20IsA6dzi4io1Iqb/NStCKHkp3qjqPsWrFQaC41thsiNEyrzeZ7H7i2ULhHzc3J/5lPaQpyK34SIslPosStVba8ZoVpijsAZvWM9uo4a8Ey36qliX1wjXyiAIp8fKqCYoT0lEDPuZ/xDfOcRlXRsT1XCc11XTdGgk1lo9JZarWYW4FSPzVqtprbSQ33qVKf+6HQ61s5FrAKlcVgn5pNCzMes7wBSCE7nRzRhhe7tqRJep9Mxx5vu+y3Add1Go9FqtcytzHsY2LeFJm8F2JWyvb+EV5dyLq+AiMptCqr1RpvPD8aILSMX5ljtSWnpSnkMWAZ0/qtLeRbYAhZ5kyhRjPLO55cvJj9KUVfK00Ab2AUcYAVYY+YjSsTklw8mP8qCL6XLnEc0ACa/fDD5ERHlqKS9PYmIiLLA5EdERKVT6FsdisA6rCrrQomI0jXhuXGY/PpgniMimgDrxZazOhAREaWGyY+IiEqHyY+IiEqHyY+IiEqHyY+IiEqHyY+IiEqHyY+IiEqHyY+IiEqHyY9oUP57/LxDIKJ0MPkR9bH94PbGyzcqByq1d9QqByrrL1vffnA776CIaCxMfkRJth/cvuu2la9+7bGe7AHoyd7ffL13563Hmf+IphqTH1GS+1bPHLi48LFH79dLPvbo5hUXl+5dOZ1jVEQ0Jk7WmiRuTFWetJmU1hC6fHsQjWDC11vO6tAHL2RERBPAWR2I8iIjP4GDeeuqh+EAgW0TflsimgIs+RE9RSL8HVMCr8J//0N8/3Nom8tvQf0qPONPcSDmSynzH1HRseRHtEfK0I+Q8kVXXS/x17dgVa91C+oSf/nCq64TkfWf+iGiwmPyI0ry63cFh29szT3zisNwAByGc+iZ4vCN//rX72SSI5pi7O2ZRAien7Lb/ta33vrn3+7979c9/Kmln931/sKp3fSa886vPPbAzT+2ePRo3tERzbjsLsK8uCdh8qMNKXeeeGJzbg4AfAlXAFh9/HFnbu5kZv3QiEhh8ssHk1+pxN1kBGuSi1vO7i5E6cnuIsw2P6J4yZ86fjEimlpMfkRPsdyyJ4T9Lj/AAaQQvMuPaErxPj+iJCvArpTt/TWcdSnn8gqIiNLAkh9RkjXgHLBq1HDWpTwLrOUXEhGNj8mPKMmCEFuAAzhSQkpHyjlgC1hkV0+iacbejEk4q8PMkB0pquOmK19KlzmPKBsTvt6y5NeHtMk7KBqU7Eq5IWVF+m5HVqRcl7I7+svHzEeUnQlfbJn8aGbJrvz6G7bf9nsbR3pHXonakd6Rt/5v619//fY4+Y+IZgOTH82sv/6ftt/058ev/U6vhx6AHnqHvvP4Gx869tf/43beoRFRztjml4QjvEyHmMrIDWzsYGcTm+bCVaw6cE7ipH0bvtpERcLhzfLB5DcVUpzrmS83UaFkdxEu9U3uvu/7vg/AdV3XdXOOhoiIJqW8JZtocSF6Kljyy53/Ht99u9tnJVvJTwLPxPyT6EUfugbO97EbO4w1ERUGB7ZOmSrnVatVz/M8z6tWq0i19ozGtP3g9sbLNyoHKrV31CoHKusvW99+MLaXipAy+nNAyituPv7qQyuhlV9zaPXKm44fsG0imPmISqOMyc/3/U6no/5QFZ6q8lMtyTGwgvjovzqfyn6av/LR0TbcfnD7n/+zY3/+l9/pyR6Anuw99Ff/36/9wl0J+c9Cyifa9c9c/chLrn86/730+tU/veqbT5yps4RHVHJlTH7NZhNAo9EwF6p/1UPl9NCnvv3+F+w8JoJf/jcLj4ng/S/YeehT3x5hP5/+wEO33/Av50Wl9ZE3zIvK7df/i09/4KGh9vA7//w9P7y48CeP/55e8ieP/4fLl5Z++9fus65vnVpBCjH/wqOX/vj+L/3EPOAAAJwvPu/wpU/f77x4gRMyEJVcGdu0VPWm53mhTi5quXlCytPm99Cnvv3omyvfdX7wxkeemq7g95e/d33v4HUfeuzm1zx78P18+gMPNe985+Frjv7pE/9BLXnV3J27T2633nfPbW+9Obp+WlXN1pdpXcrdJ55oq0nY7/PwjhqA+uOPz83NnWIVN9E04K0OaYomubjl5Ul+73/BzsG/u1JnPuX3l7936dofve0vK4Pv5/Yb/uWli4/rzKe8au7Og1cf+uSj90bXzzT5daU8BiwDekIiNSEDh6UmmhZMfmkqdfKLueZLSGF7LG65deGoQmdYOjiya+uleRjO49ixPoe4V6kr5WmgDewCDrACrDHzEU0PJr80DZX8Bt/tdJxJ2xOSkIjJZ3EPpZj8oueteuUJefnxz6FtLrwFdXHgUOfyb492FE7IQFQcRbi0lrHDy1CsA41P8VQPtm4eQoqdmN4ePUghRXSTuJPgYN66n8NwBj9vV/3T1/3g6m/cglW95BbUf3D116/6p68b+Xkz8xEVRxGuq0x+BAAf/+nd31/+Xmjhh5/7vY//g8eH2s8/ue5tr5q7M7TwVXN33XLdrw6+k3vetbT7U7/7zMo1h+EAOAznmZWre8//3d96148PFQwRUZzyJj/e0mf62d+5dH3voJn/Pvzc792wc/BnfufiUPtZ+907dp/cNvPfq+bu2n3y/Or/+ubBd/LzL3rOB37vut6tv/n44cd+Fp95/PBjO7e+/f2/d91LX/ycoYIhIopTxuSnbukLJT91h58a6qWEbn7Ns6/70GOXrv3RDoIAwQ6CH15z+cgHH3vh7UPc5wDgtrfe3HrfPQevPqQLbQevfmZj612v+dUXDrWfn3/Rc77w4WW5e+BtWwty98AXP7zMzEdEKSpjhxfE920J3fw3g709B/DR/+H86//N0vj7abzhI62PvGH8/RBRabG3Z8pc1+10OtVqVRX4ms2mGvAsdDYKlfwYTBwGE4fBxClUMChYPCUJpkBPcsJU/jOXRE9FSd4EI2AwcRhMHAaToFDxlCSYAj3Jyes7n19J3gQjYDBxGEwcBpOgUPGUJJgCPckCKsmbYAQMJg6DicNgEhQqnpIEU8benkREVHJMfiNKHp4n4dGRN2QwIwQz8hEZTBYbMhgGk2IwY2LyIyKi0mHyIyKi0rky7wCKzlokL05rMBHRbJhw/SeTXx/Mc0REE2C92GaXEVntSUREpVOg+zkKKK9uSEREpPAmdyIionSw2pOIiEqHyY+IiEqHyY+IiEqHtzrY9Z3woYDH9X2/2WyGZqifZBj+HnfP+JGMGYz6O/dgTK7rNpvNVOIZNhj1DokLacLBjL9hWvtM/tTkeHLM9/D4MRQzmAHpiVfT3KmkiLzO0pjHrVarqYQ6Whjq6KZqtZpLMJ7nRbfKK5gQdZYajUYuwTQajehWoz2R8YORtlcql5cp+tYtwskpzgfKGkwq7+HBpfX09+0z3d3NAPUyV6tVz/M8z9OvesGPq69ruYShV/M8T+6/qE0+GH2lUMHoMzPmx3X8N0ZakYwcjAqg0Wh4EZMPRr9JdDypXOJHCCZ6Nsxtc3nbmB8o8+TkEoz5gfI8T7+Nx3zbDE6H29P8vAAABfJJREFUne5umfz20W8yc+EEXumRj2u+g8dPNqOFYd1qkA2zCyb0OYmLMOtgrHsY/xI2cjBp1Q2kGExondxfphSDGSee6FZ5vYet36qtn7LUNRoN8+LG5Jct63c99fJn+kqPfNxoRdbkw4hbQZczJh9M9KBjnpzx3xg67Y2f/EYOZvx3SNbBqILF5IOJ29XIkYwTT1xqyeU9bP2OMn4wgwh9rWfyy1bc96CsX+lUjjt+kKOFoT4/0a3GvNCPFkzc1XPMkzPmC6SvIKkkv5GDMVdIqyZjnPdM6u1GaX1+VfoZP7yR38PWFXJ5D8dtFZcUs5BRQZPJb5+498Fkkt+Yx00r+aW157iPzeSDGb/xZpxgzAt9islvhGDUCqEv1GNev0YLJnROqtVqtVpNK9kMG8z466ceT6iVK5U2v9GCiUtyqTSIDojJbxKY/NLNN+PEM34w5lU+r3wTWifH5Gc2OqpMo89PXpfUUBouyBs4xVLpOPFET04ubxtrvWhaHXAGxOQ3CSle/Sd/3IJcO7yUunqOH0yKXYFGDia0Qu7JL/WuQKMFY7403l4P4SJ8YRp25YziCX1TCZ2rCQejwwj19hz/nTygjJIfR3ihNLmuW6vVsPepyDcY3/fVu1x9XCc/R4e6Jzfh7rpJcl1XShm6m9t1XXVtnfxty4qUUt1n7bquji2VgRpGU4SXzPd99SFSqU69jVVIavmEqdzT6XRqtVqtVmu1WqqaevKRpCzdXDrt4s5J1ucqleOOH+Q4YejrRVpf0NJ9LcZsnx8tGPVow6Cr+9S/kwwmzpidmUcLJq7FKJVOUsMGM9qa2cUTd3LGbGYb8+SoMl+j0VAfInZ4mTXqfcDensPuWWe+FD8MowUTl1Ry6XqKfiYZTJxczkzcQVPJxCOfmdQvsuO8beK6T+d1clLZajSs9pwE9fYK1bqompBMi/l5HTetMFqtFowqrByD8X2/1WpF6830YIaTDMaL0CU/9e8kg3FdVwgRd2ZGNnIw1kPn8jKF1kyxBni0eJJDnfDJUUP15lgRnaF0c+kMiJ4WtSTrAv4gx9XX0AH3MJkwMrpna5xgUr9BeLRgotI6VzNwZqwfq3xfpiwuiam/UuNciEYIxrN1iZrkfQ6S1Z4TE/puPn4PtBSPG7r7JySVOEcII/mL6jifkNHOiVon2jltzM/q+C+QTC/5zcCZMY+eezAyjY6vKcZjfnzMkzNmAhgtmLwuiRqT3+REr+YFOe4Ekt8IYSBRKteyoc6JZ6tOTOVb6pgvkEy1lDwDZybaqTL3YFK/wo4cT3SrVGJLK5jxIxlcRslPyLz7oxdTFnOMFfm4xQxjnGAyego8M6nvVjU7FSSYjIz8SmGv1S33k1O0Uzo+Jj8iIiod9vYkIqLSYfIjIqLSYfIjIqLSYfIjIqLSYfIjIqLSYfIjIqLSYfIjIqLSYfIjIqLSYfIjIqLSYfIjIqLSYfIjIqLSYfIjIqLSYfIjIqLSYfIjIqLSYfIjIqLSYfIjIqLSYfIjIqLSYfIjIqLSYfIjIqLSYfIjIqKJajabzWZzkIXZuXJiRyIiIgLg+36n0wGgs53v+61Wq1qtTiwGIaWc2MGIiIgACCEAeJ7nuq7+d5L5iNWeREQ0aZ7nAajVagBU/lNLJobJj4iIJs113Uajof7odDrValWlwIlhtScREeVD1XZishWeCkt+RESUj0n2cAlh8iMiohw0m03V5xNGt8+JYbUnERHlQPfwDPX8BOD7ftZNgCz5ERHRpOmEh/09P5Vareb7fqYBMPkREdFEqUpO3cPTdV3V+KcrP81SYEZY7UlERJPj+74q5IWyj1n5OYFqTyY/IiIqFiFE1oU/VnsSEVHpMPkREVHpMPkREVHpMPkREVHpMPkREVHpMPkREVHpMPkREVHpMPkREVHpMPkREVGBCCEmMLctR3ghIqLSYcmPiIhKh8mPiIhKh8mPiIhKh8mPiIhKh8mPiIhKh8mPiIhKh8mPiIhKh8mPiIhKh8mPiIhKh8mPiIhKh8mPiIhK5/8HGG9n302OolkAAAAASUVORK5CYII=\n",
0354       "text/plain": [
0355        "<IPython.core.display.Image object>"
0356       ]
0357      },
0358      "metadata": {},
0359      "output_type": "display_data"
0360     }
0361    ],
0362    "source": [
0363     "canvas = ROOT.TCanvas(\"canvas\",\"\",600,500)\n",
0364     "leg = ROOT.TLegend(.17,.67,.45,.92)\n",
0365     "leg.AddEntry(\"\",\"Dijet Events |#Delta#phi| > 2.75\",\"\")\n",
0366     "leg.AddEntry(h_xj,\"Jet Trig. Data\",\"l\")\n",
0367     "leg.AddEntry(h_mc_xj,\"Calo Waveform\",\"l\")\n",
0368     "leg.AddEntry(h_clus_xj,\"Calo Cluster\",\"l\")\n",
0369     "leg.AddEntry(h_nz_xj,\"Calo No ZS\",\"l\")\n",
0370     "leg.AddEntry(h_dt_xj,\"Detroit Waveform\",\"l\")\n",
0371     "leg.SetTextSize(0.04)\n",
0372     "h_xj.SetStats(0)\n",
0373     "h_mc_xj.SetStats(0)\n",
0374     "h_clus_xj.SetStats(0)\n",
0375     "h_nz_xj.SetStats(0)\n",
0376     "h_dt_xj.SetStats(0)\n",
0377     "h_mc_xj.SetLineColor(2)\n",
0378     "h_mc_xj.SetMarkerColor(2)\n",
0379     "h_clus_xj.SetLineColor(4)\n",
0380     "h_clus_xj.SetMarkerColor(4)\n",
0381     "h_nz_xj.SetLineColor(6)\n",
0382     "h_nz_xj.SetMarkerColor(6)\n",
0383     "h_dt_xj.SetLineColor(7)\n",
0384     "h_dt_xj.SetMarkerColor(7)\n",
0385     "h_mc_xj.Draw()\n",
0386     "h_dt_xj.Draw('same')\n",
0387     "h_clus_xj.Draw('same')\n",
0388     "h_nz_xj.Draw('same')\n",
0389     "h_xj.Draw('same')\n",
0390     "h_mc_xj.SetXTitle(\"x_{j}\") \n",
0391     "canvas.SetLogy(0)\n",
0392     "leg.Draw()\n",
0393     "canvas.Draw()\n",
0394     "canvas.SaveAs(\"/sphenix/u/egm2153/fall_2024/\"+direct+\"/h_xj.png\")"
0395    ]
0396   },
0397   {
0398    "cell_type": "code",
0399    "execution_count": null,
0400    "id": "81e8e143-5617-4c19-8e26-732f75a6ec7c",
0401    "metadata": {},
0402    "outputs": [],
0403    "source": []
0404   },
0405   {
0406    "cell_type": "code",
0407    "execution_count": null,
0408    "id": "952b99ba-7d45-4704-a4b2-b57ef08cb0b1",
0409    "metadata": {},
0410    "outputs": [],
0411    "source": []
0412   },
0413   {
0414    "cell_type": "code",
0415    "execution_count": null,
0416    "id": "62dd15d6-ef7d-420f-a870-3b463765dfb3",
0417    "metadata": {},
0418    "outputs": [],
0419    "source": []
0420   },
0421   {
0422    "cell_type": "code",
0423    "execution_count": null,
0424    "id": "75c4b3e9-4bdc-44b9-9fae-aa5f528f1167",
0425    "metadata": {},
0426    "outputs": [],
0427    "source": []
0428   },
0429   {
0430    "cell_type": "code",
0431    "execution_count": null,
0432    "id": "41902062-03ea-4ba4-9b10-cdf86957453b",
0433    "metadata": {},
0434    "outputs": [],
0435    "source": []
0436   },
0437   {
0438    "cell_type": "code",
0439    "execution_count": null,
0440    "id": "1bee6f28-f7c0-42e5-b90b-f43e30a60aad",
0441    "metadata": {},
0442    "outputs": [],
0443    "source": []
0444   },
0445   {
0446    "cell_type": "code",
0447    "execution_count": null,
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0450    "outputs": [],
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0452   },
0453   {
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0458    "outputs": [],
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0460   },
0461   {
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0464    "id": "59ae0a66-34d4-4a5c-9bce-4748fe721315",
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0468   },
0469   {
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0499 }