{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/hep/davide/miniconda3/envs/root_env/lib/ROOT.py:301: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility\n",
" return _orig_ihook( name, *args, **kwds )\n"
]
}
],
"source": [
"import ROOT as r\n",
"import ctypes\n",
"import numpy as np\n",
"from array import array\n",
"import root_numpy as rn\n",
"import matplotlib.pyplot as plt\n",
"import pickle"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"l_flv = ['e','mu']\n",
"data_type = ['MC','small_data']\n",
"mag_status =['Up','Down'] \n",
"tree_name = 'Ds_OfflineTree/DecayTree'"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"l_index = 1\n",
"#data_index = None \n",
"mag_index = 1"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"def find_file_path(l_index, type_index, mag_index): \n",
" return \"/disk/lhcb_data/davide/Rphipi/\"+data_type[type_index]+\"/Ds_phipi_\"+l_flv[l_index]+l_flv[l_index]+\"/Ds_phipi_\"+l_flv[l_index]+l_flv[l_index]+\"_Mag\"+mag_status[mag_index]+\".root\"\n",
"#def find_file_path(l_index, type_index, mag_index): \n",
"# return \"../Desktop/Ds_phipi/\"+data_type[i]+\"/Ds_phipi_\"+l_flv[j]+\"/Ds_phipi_\"+l_flv[j]+\"_\"+mag_status[k]+\".root\""
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"data_mumu = r.TFile(find_file_path(l_index, 1, mag_index))\n",
"MC_mumu = r.TFile(find_file_path(l_index, 0, mag_index))"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<ROOT.TTree object (\"DecayTree\") at 0x55d5d4082200>"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"t_data_mumu = data_mumu.Get(\"Ds_OfflineTree/DecayTree\")\n",
"t_data_mumu"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<ROOT.TTree object (\"DecayTree\") at 0x55d5d40eb6e0>"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"t_MC_mumu = MC_mumu.Get(\"Ds_OfflineTree/DecayTree\")\n",
"t_MC_mumu"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"t_data_mumu.SetBranchStatus(\"*\",0)\n",
"t_data_mumu.SetBranchStatus(\"Ds_ENDVERTEX_CHI2\",1)\n",
"t_data_mumu.SetBranchStatus(\"Ds_ENDVERTEX_NDOF\",1)\n",
"t_data_mumu.SetBranchStatus(\"Ds_OWNPV_CHI2\",1)\n",
"t_data_mumu.SetBranchStatus(\"Ds_OWNPV_NDOF\",1)\n",
"t_data_mumu.SetBranchStatus(\"Ds_IP_OWNPV\",1)\n",
"t_data_mumu.SetBranchStatus(\"Ds_IPCHI2_OWNPV\",1)\n",
"t_data_mumu.SetBranchStatus(\"Ds_DIRA_OWNPV\",1)\n",
"t_data_mumu.SetBranchStatus(\"Ds_ConsD_M\",1)\n",
"\n",
"t_data_mumu.SetBranchStatus(\"mu_plus_MC15TuneV1_ProbNNmu\", 1)\n",
"t_data_mumu.SetBranchStatus(\"Ds_Hlt1TrackMVADecision_TOS\", 1)\n",
"t_data_mumu.SetBranchStatus(\"Ds_Hlt2RareCharmD2PiMuMuOSDecision_TOS\", 1)\n",
"t_data_mumu.SetBranchStatus(\"Ds_Hlt2Phys_TOS\", 1)\n",
"\n",
"\n",
"t_MC_mumu.SetBranchStatus(\"*\",0)\n",
"t_MC_mumu.SetBranchStatus(\"Ds_ENDVERTEX_CHI2\", 1)\n",
"t_MC_mumu.SetBranchStatus(\"Ds_ENDVERTEX_NDOF\", 1)\n",
"t_MC_mumu.SetBranchStatus(\"Ds_OWNPV_CHI2\", 1)\n",
"t_MC_mumu.SetBranchStatus(\"Ds_OWNPV_NDOF\", 1)\n",
"t_MC_mumu.SetBranchStatus(\"Ds_IP_OWNPV\", 1)\n",
"t_MC_mumu.SetBranchStatus(\"Ds_IPCHI2_OWNPV\", 1)\n",
"t_MC_mumu.SetBranchStatus(\"Ds_DIRA_OWNPV\", 1)\n",
"t_MC_mumu.SetBranchStatus(\"Ds_ConsD_M\", 1)\n",
"\n",
"t_MC_mumu.SetBranchStatus(\"mu_plus_MC15TuneV1_ProbNNmu\", 1)\n",
"t_MC_mumu.SetBranchStatus(\"Ds_Hlt1TrackMVADecision_TOS\", 1)\n",
"t_MC_mumu.SetBranchStatus(\"Ds_Hlt2RareCharmD2PiMuMuOSDecision_TOS\", 1)\n",
"t_MC_mumu.SetBranchStatus(\"Ds_Hlt2Phys_TOS\", 1)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"branches_needed = [\n",
" \"Ds_ENDVERTEX_CHI2\",\n",
" \"Ds_ENDVERTEX_NDOF\",\n",
" \"Ds_OWNPV_CHI2\",\n",
" \"Ds_OWNPV_NDOF\",\n",
" \"Ds_IP_OWNPV\",\n",
" \"Ds_IPCHI2_OWNPV\",\n",
" \"Ds_DIRA_OWNPV\",\n",
" \"Ds_ConsD_M\",\n",
" l_flv[l_index]+\"_plus_MC15TuneV1_ProbNN\"+l_flv[l_index],\n",
" \"Ds_Hlt1TrackMVADecision_TOS\",\n",
" \"Ds_Hlt2RareCharmD2PiMuMuOSDecision_TOS\",\n",
" \"Ds_Hlt2Phys_TOS\",\n",
" ] "
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"MC_count=0\n",
"for event in enumerate(t_MC_mumu):\n",
" MC_count+=1\n",
" \n",
"data_count=0\n",
"for event in enumerate(t_data_mumu):\n",
" data_count+=1"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"MC event count 24354, real data event count 93704\n"
]
}
],
"source": [
"print(\"MC event count {0}, real data event count {1}\".format(MC_count,data_count))"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"MC_tuple_dict = {}\n",
"\n",
"for i in range(len(branches_needed)):\n",
" \n",
" MC_tuple_dict[branches_needed[i]] = rn.root2array(\n",
" \n",
" filenames=find_file_path(l_index, 0, mag_index),\n",
" treename = tree_name,\n",
" branches = branches_needed[i],\n",
" start=0,\n",
" stop=MC_count,\n",
" )"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"data_tuple_dict = {}\n",
"\n",
"for i in range(len(branches_needed)):\n",
" \n",
" data_tuple_dict[branches_needed[i]] = rn.root2array(\n",
" \n",
" filenames=find_file_path(l_index, 1, mag_index),\n",
" treename = tree_name,\n",
" branches = branches_needed[i],\n",
" start=0,\n",
" stop=data_count,\n",
" )"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"Ds_constrained_mass_MC = np.array([MC_tuple_dict[\"Ds_ConsD_M\"][i][0] for i in range(len(MC_tuple_dict[\"Ds_ConsD_M\"]))])\n",
"Ds_constrained_mass_data = np.array([data_tuple_dict[\"Ds_ConsD_M\"][i][0] for i in range(len(data_tuple_dict[\"Ds_ConsD_M\"]))])"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1152x432 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.subplot(1,2,1)\n",
"plt.hist(Ds_constrained_mass_MC,bins=70);\n",
"plt.subplot(1,2,2)\n",
"plt.hist(Ds_constrained_mass_data,bins=70);\n",
"fig = plt.gcf()\n",
"fig.set_size_inches(16,6)"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
"data_bkg_indices_over=[]\n",
"data_bkg_indices_under=[]\n",
"\n",
"MC_sig_indices=[]"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
"for i in range(len(data_tuple_dict[\"Ds_ConsD_M\"])):\n",
" #retrieving the Ds reconstructed mass\n",
" Ds_m = data_tuple_dict[\"Ds_ConsD_M\"][i][0]\n",
" \n",
" #selecting the out of signal regions\n",
" if 0<Ds_m<1850:\n",
" data_bkg_indices_under.append(i)\n",
" if 2100 < Ds_m < 2600:\n",
" data_bkg_indices_over.append(i)"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
"for i in range(len(MC_tuple_dict[\"Ds_ConsD_M\"])):\n",
" #retrieving the Ds reconstructed mass\n",
" Ds_m = MC_tuple_dict[\"Ds_ConsD_M\"][i][0]\n",
" \n",
" #selecting the out of signal regions\n",
" if 1850<Ds_m<2100:\n",
" MC_sig_indices.append(i)"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [],
"source": [
"data_tuple_bkg={}\n",
"data_tuple_bkg_under = {}\n",
"data_tuple_bkg_over = {}\n",
"MC_tuple_sig ={}\n",
"\n",
"for label in branches_needed:\n",
" \n",
" data_tuple_bkg[label] = data_tuple_dict[label][data_bkg_indices_under+data_bkg_indices_over]\n",
" data_tuple_bkg_under[label] = data_tuple_dict[label][data_bkg_indices_under]\n",
" data_tuple_bkg_over[label] = data_tuple_dict[label][data_bkg_indices_over]\n",
" MC_tuple_sig[label] = MC_tuple_dict[label][MC_sig_indices]\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [],
"source": [
"nbins=70\n",
"MC_Ds_endvtx_chi2ratio=MC_tuple_dict[\"Ds_ENDVERTEX_CHI2\"]/MC_tuple_dict[\"Ds_ENDVERTEX_NDOF\"]\n",
"data_under_Ds_endvtx_chi2ratio=data_tuple_bkg_under[\"Ds_ENDVERTEX_CHI2\"]/data_tuple_bkg_under[\"Ds_ENDVERTEX_NDOF\"]\n",
"data_over_Ds_endvtx_chi2ratio=data_tuple_bkg_over[\"Ds_ENDVERTEX_CHI2\"]/data_tuple_bkg_over[\"Ds_ENDVERTEX_NDOF\"]"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [],
"source": [
"if np.max(MC_Ds_endvtx_chi2ratio)>np.max(data_under_Ds_endvtx_chi2ratio):\n",
" max_endvchi2_under=np.max(MC_Ds_endvtx_chi2ratio)\n",
"else:\n",
" max_endvchi2_under=np.max(data_under_Ds_endvtx_chi2ratio)\n",
" \n",
"if np.max(MC_Ds_endvtx_chi2ratio)>np.max(data_over_Ds_endvtx_chi2ratio):\n",
" max_endvchi2_over=np.max(MC_Ds_endvtx_chi2ratio)\n",
"else:\n",
" max_endvchi2_over=np.max(data_over_Ds_endvtx_chi2ratio)"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [],
"source": [
"h_mc_under= r.TH1F(\"Ds end vertex MC/data comparison under\", \"Ds end vertex MC/data under Ds mass comparison\",nbins, 0, max_endvchi2_under)\n",
"h_mc_over = r.TH1F(\"Ds end vertex MC/data comparison over\", \"Ds end vertex MC/data over Ds mass comparison\",nbins, 0, max_endvchi2_over)\n",
"\n",
"for i in range(len(MC_Ds_endvtx_chi2ratio)):\n",
" h_mc_under.Fill(MC_Ds_endvtx_chi2ratio[i])\n",
" h_mc_over.Fill(MC_Ds_endvtx_chi2ratio[i])\n",
"\n",
"n1=h_mc_under.Integral(\"width\")\n",
"h_mc_under.Scale(1/n1)\n",
"h_mc_under.Integral(\"width\");\n",
"n2=h_mc_over.Integral(\"width\")\n",
"h_mc_over.Scale(1/n2)\n",
"h_mc_over.Integral(\"width\");"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [],
"source": [
"h_data_under= r.TH1F(\"data below signal\", \"data below signal\",nbins, 0, max_endvchi2_under)\n",
"h_data_over= r.TH1F(\"data over signal\", \"data over signal\",nbins, 0, max_endvchi2_over)\n",
"for i in range(len(data_under_Ds_endvtx_chi2ratio)):\n",
" h_data_under.Fill(data_under_Ds_endvtx_chi2ratio[i])\n",
"for i in range(len(data_over_Ds_endvtx_chi2ratio)):\n",
" h_data_over.Fill(data_over_Ds_endvtx_chi2ratio[i])\n",
" \n",
" \n",
"n2=h_data_under.Integral(\"width\")\n",
"h_data_under.Scale(1/n2)\n",
"h_data_under.Integral(\"width\");\n",
"n3=h_data_over.Integral(\"width\")\n",
"h_data_over.Scale(1/n3)\n",
"h_data_over.Integral(\"width\");"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1152x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"a=[h_mc_under.GetBinContent(i) for i in range(nbins)]\n",
"b=[h_mc_under.GetBinCenter(i) for i in range(nbins)]\n",
"c=[h_data_under.GetBinContent(i) for i in range(nbins)]\n",
"d=[h_data_under.GetBinCenter(i) for i in range(nbins)]\n",
"plt.title(\"Ds End Vertex chisq/ndof Signal MC/ data under peak comparison\", fontsize=20)\n",
"\n",
"plt.bar(b,a,width=0.05,alpha=0.6,label=\"Signal MC\")\n",
"plt.bar(d,c,width=0.06, alpha=0.4, label=\"data under Ds mass peak\")\n",
"plt.legend(fontsize=20)\n",
"fig = plt.gcf()\n",
"fig.set_size_inches(16,8)"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1152x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"a=[h_mc_over.GetBinContent(i) for i in range(nbins)]\n",
"b=[h_mc_over.GetBinCenter(i) for i in range(nbins)]\n",
"c=[h_data_over.GetBinContent(i) for i in range(nbins)]\n",
"d=[h_data_over.GetBinCenter(i) for i in range(nbins)]\n",
"\n",
"plt.title(\"Ds End Vertex chisq/ndof Signal MC/ data over peak comparison\", fontsize=20)\n",
"plt.bar(b,a,width=0.05,alpha=0.6,label=\"Signal MC\")\n",
"plt.bar(d,c,width=0.06, alpha=0.4, label=\"data over Ds mass peak\")\n",
"plt.legend(fontsize=20)\n",
"fig = plt.gcf()\n",
"fig.set_size_inches(16,8)"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [],
"source": [
"nbins=70\n",
"MC_Ds_ownvtx_chi2ratio=MC_tuple_dict[\"Ds_OWNPV_CHI2\"]/MC_tuple_dict[\"Ds_OWNPV_NDOF\"]\n",
"data_under_Ds_ownvtx_chi2ratio=data_tuple_bkg_under[\"Ds_OWNPV_CHI2\"]/data_tuple_bkg_under[\"Ds_OWNPV_NDOF\"]\n",
"data_over_Ds_ownvtx_chi2ratio=data_tuple_bkg_over[\"Ds_OWNPV_CHI2\"]/data_tuple_bkg_over[\"Ds_OWNPV_NDOF\"]"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [],
"source": [
"if np.max(MC_Ds_ownvtx_chi2ratio)>np.max(data_under_Ds_ownvtx_chi2ratio):\n",
" max_ownvchi2_under=np.max(MC_Ds_ownvtx_chi2ratio)\n",
"else:\n",
" max_ownvchi2_under=np.max(data_under_Ds_ownvtx_chi2ratio)\n",
" \n",
"if np.max(MC_Ds_ownvtx_chi2ratio)>np.max(data_over_Ds_ownvtx_chi2ratio):\n",
" max_ownvchi2_over=np.max(MC_Ds_ownvtx_chi2ratio)\n",
"else:\n",
" max_ownvchi2_over=np.max(data_over_Ds_ownvtx_chi2ratio)"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [],
"source": [
"h_mc_under= r.TH1F(\"Ds own PV vertex MC/data comparison under\", \"Ds own PV vertex MC/data under Ds mass comparison\",nbins, 0, max_ownvchi2_under)\n",
"h_mc_over = r.TH1F(\"Ds own PV vertex MC/data comparison over\", \"Ds own PV vertex MC/data over Ds mass comparison\",nbins, 0, max_ownvchi2_over)\n",
"\n",
"for i in range(len(MC_Ds_ownvtx_chi2ratio)):\n",
" h_mc_under.Fill(MC_Ds_ownvtx_chi2ratio[i])\n",
" h_mc_over.Fill(MC_Ds_ownvtx_chi2ratio[i])\n",
"\n",
"n1=h_mc_under.Integral(\"width\")\n",
"h_mc_under.Scale(1/n1)\n",
"h_mc_under.Integral(\"width\");\n",
"n2=h_mc_over.Integral(\"width\")\n",
"h_mc_over.Scale(1/n2)\n",
"h_mc_over.Integral(\"width\");"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"TFile::Append:0: RuntimeWarning: Replacing existing TH1: data below signal (Potential memory leak).\n",
"TFile::Append:0: RuntimeWarning: Replacing existing TH1: data over signal (Potential memory leak).\n"
]
}
],
"source": [
"h_data_under= r.TH1F(\"data below signal\", \"data below signal\",nbins, 0, max_ownvchi2_under)\n",
"h_data_over= r.TH1F(\"data over signal\", \"data over signal\",nbins, 0, max_ownvchi2_over)\n",
"for i in range(len(data_under_Ds_ownvtx_chi2ratio)):\n",
" h_data_under.Fill(data_under_Ds_ownvtx_chi2ratio[i])\n",
"for i in range(len(data_over_Ds_ownvtx_chi2ratio)):\n",
" h_data_over.Fill(data_over_Ds_ownvtx_chi2ratio[i])\n",
" \n",
" \n",
"n2=h_data_under.Integral(\"width\")\n",
"h_data_under.Scale(1/n2)\n",
"h_data_under.Integral(\"width\");\n",
"n3=h_data_over.Integral(\"width\")\n",
"h_data_over.Scale(1/n3)\n",
"h_data_over.Integral(\"width\");"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1152x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"a=[h_mc_under.GetBinContent(i) for i in range(nbins)]\n",
"b=[h_mc_under.GetBinCenter(i) for i in range(nbins)]\n",
"c=[h_data_under.GetBinContent(i) for i in range(nbins)]\n",
"d=[h_data_under.GetBinCenter(i) for i in range(nbins)]\n",
"plt.title(\"Ds Own PV Vertex chisq/ndof Signal MC/ data under peak comparison\", fontsize=20)\n",
"\n",
"plt.bar(b,a,width=0.015,alpha=0.4,label=\"Signal MC\")\n",
"plt.bar(d,c,width=0.01, alpha=0.6, label=\"data under Ds mass peak\")\n",
"plt.legend(fontsize=20)\n",
"fig = plt.gcf()\n",
"fig.set_size_inches(16,8)"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1152x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"a=[h_mc_over.GetBinContent(i) for i in range(nbins)]\n",
"b=[h_mc_over.GetBinCenter(i) for i in range(nbins)]\n",
"c=[h_data_over.GetBinContent(i) for i in range(nbins)]\n",
"d=[h_data_over.GetBinCenter(i) for i in range(nbins)]\n",
"\n",
"plt.title(\"Ds Own PV Vertex chisq/ndof Signal MC/ data over peak comparison\", fontsize=20)\n",
"plt.bar(b,a,width=0.014,alpha=0.4,label=\"Signal MC\")\n",
"plt.bar(d,c,width=0.01, alpha=0.6, label=\"data over Ds mass peak\")\n",
"plt.legend(fontsize=20)\n",
"fig = plt.gcf()\n",
"fig.set_size_inches(16,8)"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [],
"source": [
"nbins=70\n",
"MC_Ds_DIRA_ownpv=MC_tuple_dict[\"Ds_DIRA_OWNPV\"]\n",
"data_under_Ds_DIRA_ownpv=data_tuple_bkg_under[\"Ds_DIRA_OWNPV\"]\n",
"data_over_Ds_DIRA_ownpv=data_tuple_bkg_over[\"Ds_DIRA_OWNPV\"]"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [],
"source": [
"if np.min(MC_Ds_DIRA_ownpv)<np.min(data_under_Ds_DIRA_ownpv):\n",
" min_DIRA_under=np.min(MC_Ds_DIRA_ownpv)\n",
"else:\n",
" min_DIRA_under=np.min(data_under_Ds_DIRA_ownpv)\n",
" \n",
"if np.min(MC_Ds_DIRA_ownpv)<np.min(data_over_Ds_DIRA_ownpv):\n",
" min_DIRA_over=np.min(MC_Ds_DIRA_ownpv)\n",
"else:\n",
" min_DIRA_over=np.min(data_over_Ds_DIRA_ownpv)"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [],
"source": [
"min_DIRA_under=0.99980\n",
"min_DIRA_over=0.99980"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [],
"source": [
"h_mc_under= r.TH1F(\"Ds DIRA own PV MC/data comparison under\", \"Ds DIRAown PV MC/data under Ds mass comparison\",nbins, min_DIRA_under, 1)\n",
"h_mc_over = r.TH1F(\"Ds DIRA own PV MC/data comparison over\", \"Ds DIRA own PV MC/data over Ds mass comparison\",nbins, min_DIRA_over, 1)\n",
"\n",
"for i in range(len(MC_Ds_DIRA_ownpv)):\n",
" h_mc_under.Fill(MC_Ds_DIRA_ownpv[i])\n",
" h_mc_over.Fill(MC_Ds_DIRA_ownpv[i])\n",
"\n",
"n1=h_mc_under.Integral(\"width\")\n",
"h_mc_under.Scale(1/n1)\n",
"h_mc_under.Integral(\"width\");\n",
"n2=h_mc_over.Integral(\"width\")\n",
"h_mc_over.Scale(1/n2)\n",
"h_mc_over.Integral(\"width\");"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"TFile::Append:0: RuntimeWarning: Replacing existing TH1: data below signal (Potential memory leak).\n",
"TFile::Append:0: RuntimeWarning: Replacing existing TH1: data over signal (Potential memory leak).\n"
]
}
],
"source": [
"h_data_under= r.TH1F(\"data below signal\", \"data below signal\",nbins, min_DIRA_under, 1)\n",
"h_data_over= r.TH1F(\"data over signal\", \"data over signal\",nbins, min_DIRA_over, 1)\n",
"for i in range(len(data_under_Ds_DIRA_ownpv)):\n",
" h_data_under.Fill(data_under_Ds_DIRA_ownpv[i])\n",
"for i in range(len(data_over_Ds_DIRA_ownpv)):\n",
" h_data_over.Fill(data_over_Ds_DIRA_ownpv[i])\n",
" \n",
"n2=h_data_under.Integral(\"width\")\n",
"h_data_under.Scale(1/n2)\n",
"h_data_under.Integral(\"width\");\n",
"n3=h_data_over.Integral(\"width\")\n",
"h_data_over.Scale(1/n3)\n",
"h_data_over.Integral(\"width\");"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1152x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"a=[h_mc_under.GetBinContent(i) for i in range(nbins)]\n",
"b=[h_mc_under.GetBinCenter(i) for i in range(nbins)]\n",
"c=[h_data_under.GetBinContent(i) for i in range(nbins)]\n",
"d=[h_data_under.GetBinCenter(i) for i in range(nbins)]\n",
"plt.title(\"Ds Own PV Vertex chisq/ndof Signal MC/ data under peak comparison\", fontsize=20)\n",
"\n",
"plt.bar(b,a,width=0.000001,alpha=0.6,label=\"Signal MC\")\n",
"plt.bar(d,c,width=0.0000015, alpha=0.4, label=\"data under Ds mass peak\")\n",
"plt.legend(fontsize=20)\n",
"fig = plt.gcf()\n",
"fig.set_size_inches(16,8)"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1152x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"a=[h_mc_over.GetBinContent(i) for i in range(nbins)]\n",
"b=[h_mc_over.GetBinCenter(i) for i in range(nbins)]\n",
"c=[h_data_over.GetBinContent(i) for i in range(nbins)]\n",
"d=[h_data_over.GetBinCenter(i) for i in range(nbins)]\n",
"\n",
"plt.title(\"Ds Own PV Vertex chisq/ndof Signal MC/ data over peak comparison\", fontsize=20)\n",
"plt.bar(b,a,width=0.000001,alpha=0.6,label=\"Signal MC\")\n",
"plt.bar(d,c,width=0.0000015, alpha=0.4, label=\"data over Ds mass peak\")\n",
"plt.legend(fontsize=20)\n",
"fig = plt.gcf()\n",
"fig.set_size_inches(16,8)"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [],
"source": [
"nbins=70\n",
"MC_probNNmu=MC_tuple_dict[\"mu_plus_MC15TuneV1_ProbNNmu\"]\n",
"data_probNNmu_under=data_tuple_bkg_under[\"mu_plus_MC15TuneV1_ProbNNmu\"]\n",
"data_probNNmu_over=data_tuple_bkg_over[\"mu_plus_MC15TuneV1_ProbNNmu\"]"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {},
"outputs": [],
"source": [
"h_mc= r.TH1F(\"ProbNN mu MC/data comparison under\", \"ProbNN mu MC/data under Ds mass comparison\",nbins, 0, 1)\n",
"\n",
"for i in range(len(MC_probNNmu)):\n",
" h_mc.Fill(MC_probNNmu[i]) \n",
"\n",
"n1=h_mc.Integral(\"width\")\n",
"h_mc.Scale(1/n1)\n",
"h_mc.Integral(\"width\");"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"TFile::Append:0: RuntimeWarning: Replacing existing TH1: data below signal (Potential memory leak).\n",
"TFile::Append:0: RuntimeWarning: Replacing existing TH1: data over signal (Potential memory leak).\n"
]
}
],
"source": [
"h_data_under= r.TH1F(\"data below signal\", \"data below signal\",nbins, 0, 1)\n",
"h_data_over= r.TH1F(\"data over signal\", \"data over signal\",nbins, 0, 1)\n",
"for i in range(len(data_probNNmu_under)):\n",
" h_data_under.Fill(data_probNNmu_under[i])\n",
"for i in range(len(data_probNNmu_over)):\n",
" h_data_over.Fill(data_probNNmu_under[i])\n",
" \n",
"n2=h_data_under.Integral(\"width\")\n",
"h_data_under.Scale(1/n2)\n",
"h_data_under.Integral(\"width\");\n",
"n3=h_data_over.Integral(\"width\")\n",
"h_data_over.Scale(1/n3)\n",
"h_data_over.Integral(\"width\");"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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XbV5e6mRyzr1pZu9L6mRRRjcMqm5Ajin2H/sCGanVv3t/nbwEu56ZlQtvshkh1Dwz1iAXMQe/yKNu8i7k/s8598fwGf5T1twutvPMOXfYzJ6Tl2hUk9dM9u1cqoUG82in2E/zszFvtOJWkp6J0UIgmvBjKssAReZdQZdR9ov7h+X1if61i3jtipn9XV7CmRd3y0t4rvabb4Yvr6u8hDNeoc8d7QZXQY1CHO95KFqd0tGaIwckL+e8vfL6esaqEyk/x9Jv5R0PQ8wsyTn3UJzrlH6+KVUhjrL5+XtR0Mop6yA8sWI4buco59wXkq73j/Pz5Q049EdJD8m7MXZPWGyl/e8qy3kl7BxxvPZp4KRFH07gxBHqg9k2xvzQSJL/jTIv20WwPzJqM3l3s9fFsf6B8poEP6a8nxvyU7eg7ZbXPC7aDbXGBbieg/r5LnfMJ9z+BfgXks6O0eczt1Fq4xV6XUJkX1cp9j5VEEKjOlaTNDFKk7VIT/u/B+TWBzai7/EV8m4kxNucVvr5WImWJDaWd+EZqa6kjyOTTV+s7XhMsfeBgvxeQk/Moj1xKah9O+Y2CzunRAo9cY7WnDYo58TYf9r4v8P7tC+TVNbMLohz2fn5zvbI6/qwUNJgM8utj3a49X79iy3Kq1oibJDX3LOpmUU20ZZy/ntR0KLtK1XkbcdNoea0SsA5ynnWOOeekPe9SFLXsCKr5DVxj7ZfN5V3jjge2xA4qSX6whDAzxbLu4ho7zfry+T/v6O84fAXRal7o5lF9jMZIa8Z3+TIwSei8QcdelFSPXkj98UtP3UD8IG8C4gscfjD/Ue+RiQmMytlZoNzSIpulncHf22o31cOXpCXLD1mYZ3I/EFw7os3plyE+rO1CZ/oX/g9VkDryMY5t1FeP84e8poZ51Z+sbxmt+UlzbIo75c17714feXtUyE95F2Mv5+H8Cb5v4eZWeaTID9xGh2jznZJ55v3HtbwmO5V7KbT3yt237NY30sreYPt5EVoUK1+FvZ+QD/Wgno6NF1eYtvfzBpGzAudUyKNl9cs8vFoAyr532fTAoovpIi/vvDtUEvSvZKOKOu+87j/+xkzK68IZpZsZo3CJuXrWPIHpekk7wn+vWY2NpcqoXpH5Q0kVVLSs5GDvZn3fs7yftlD+vn1So9ElKsjbzsclvfKjqDda2Znhq0/Sd4rWooo6wBix+UcZWYXxDhvh5ohhzd1nuj/fsx/nUpoGSUl/d3/77MFFRtwqqJJLXCC8PuU9ZPXb2yqmU2Xd8f7HHmDpeyTdH2M5oTvSlpsZq/q53fmtZT3io7c+lWFe0DeawLO+gUfIT91C9IT8kYnfdbMQu+yqyfvLvwb8vr0xCNZ0nB5TeM+kDfo0vfyBrloLu+J0o/yEs/c/E3ed3itpAvM7B15Fz9XyxvM4nL93Fzyl/qPH++fzOxCP97K8vqZzlGA34tz7p08VvmjvD6MN0taZ2bzJH0k74lxVXk3BqrJ60spf8TH9pL+E9b3Kp64FpvZE5Juk/SpmU3Vz+/h3K2IZra+sfIuflf55X+S9+SugbzmwtH6Kc+RN3DSa/K2+zFJC5xzC+QlEH0kvW5mr8gbufR8eU9Zpuvn94rG83mWm9kCedtisd+UvZx+/o7r5FQ/znX8YGYD5PWvW+THHDqn/EregGWtI+qsN+89nBMlrTezN+W9hqWIvBGeW8t/rUV+4wvzsbzjcKV/PIXew1lG3us7Mpt4OufmmPcu30ckbTSzN+SdG1PkvULkEnkj1Xbyq+T7WHLO7TezLv6ybvdvctwcPppsDMPkPVnrKekzP9bd8o6LDvLOs5P8soPk7Zt3mFkzeTdjQu/hTJV0a4wn9QVtmaTV/r6yV97N0XryBiAKf8J7vM5R7SWNMrPF8s4rGfJaBfSUd2xmvqPVOfeymXWTt83WmNnr8lpsdJe3777inHtJAPKFhBM4gfgXlI3lvX7gUnnNCL+T9+Lqh51zG2JUfVxeU8M75Y0U+oO8i5I/R76mIJf1f21mY5S3JDXfdQuSc26t35d0pLwLmSPymre1kHfBEW/CmSEvKegk7wKwj7yLuJ8kfSkvMRnjDyiUW0w/mVlbeRdb6fKG2/9S3utx3paXcOarn5Bzbq+ZtZaXLP1G3v6z0V/HY/LeTXhC8JPGP5jZJEkD5F00N5OX5O+QN4rmQPkJp7wkr7i8V9Tk1R3yWgb8UdLv5d00mCbpz/IuRiNjG21mByXdKu8JZIa8/aelvP0hWsJ5h7yL1HbyktkkeYnDAufcMjPr7P+/t7z98SN5+9NO5SHh9HWTd8HcTd4Im//zP8s78i6a8805N9XMOsl7anq1vBsBC+SN9jpIUZqBO+deNLOP5H1vbf34jsobzXeWfn7FUUHZLe+7+Ju8G0xpktZKesw5l21dzrm/+gnI7fKOj4r+59okaYqk58PKFsix5I/q28Nf/gBJKWZ2Y059kJ1zh/xtf7O8V5r0kzdK8jfykrLFYWV3mTc4zp/k7Ud3yzs/fSDvVSV5vRH0S90lrwXCTfIGwvpe3vnxIee9gigU7/E6R70j7+ZLC3n7Rkl5+8tiSaOdc5GtJPrIG2n3RnnnCMnrhjJa3jtOAeST5X6zDQAQFDO7Xt7F7s3OuacSHc+JyLx323aX99L7/YmOB4llZk7SfOdcm0THcirzbxj1k1QrnhtvAE5d9OEEgOMgWp8if9qD8p56zTzuQRUC5r3g/nJ57xsk2QQAoJChSS0AHB/T/ME0lsvrj1tdXrPD0pL+5Jz7JpHBnaj8wVFivkcWAACc2Eg4AeD4mCKvT1Z/eS+Yz5A33P5459wv6ZsIAABwwqMPJwAAAAAgEPThBAAAAAAEIpAmtRUqVHA1a9YMYtEAAAAAgARauXLld865ivGUDSThrFmzplasWBHEogEAAAAACWRmX8Vblia1AAAAAIBAkHACAAAAAAJBwgkAAAAACAQJJwAAAAAgECScAAAAAIBAkHACAAAAAAJBwgkAAAAACAQJJwAAAAAgEEUTHcDBgwe1a9cu7du3T0ePHk10OACQUEWKFFFqaqrKlSunlJSURIcDAACQLwlNOA8ePKjNmzerbNmyqlmzppKTk2VmiQwJABLGOafDhw8rIyNDmzdvVo0aNUg6AQBAoZbQJrW7du1S2bJlVaFCBRUrVoxkE8ApzcxUrFgxVahQQWXLltWuXbsSHRIAAEC+JDTh3Ldvn9LS0hIZAgCckNLS0rRv375EhwEAAJAvCU04jx49quTk5ESGAAAnpOTkZPq1AwCAQi/ho9TSjBYAsuPcCAAATgYJTzgBAAAAACcnEk4AAAAAQCBIOAuhSZMmycw0adKkRIcSFzNTmzZtEh0GAAAAgOMsoe/hzM3LyzcnOoQc9W1ao0CWc/ToUU2cOFEvvviiPvnkE2VkZKhkyZKqXr26GjRooCuvvFI9evQokHUVBqG+a2am//3vf6pTp07Ucm3bttW8efMkSc8995z69++frcyPP/6oZ555RjNmzNCnn36qPXv2qGTJkqpbt67at2+v3/72t6pdu3ZQHwUAAAA4pZ3QCeep4OjRo+rSpYtmzZqlihUrqlu3bqpatar279+vNWvW6LXXXtOmTZuyJJw9evRQs2bNVKVKlQRGHqyiRYvqyJEjevbZZzVy5Mhs8//3v/9p3rx5meWiWbZsmdLT07V161ZVq1ZNl112mc444wzt379fq1ev1qhRozRq1CgtW7ZMF110UdAfCQAAADjlkHAm2OTJkzVr1iw1adJE7733nlJTU7PM379/v5YvX55lWunSpVW6dOnjGeZxV6lSJVWpUkXPPfechg8frqJFs+6q//znPyVJV1xxhaZNm5at/vr169WxY0f98MMPevTRRzVw4MBsy9i8ebPuu+8+ZWRkBPdBAAAAgAi5teQsqJaUJwL6cCbYkiVLJEn9+/fPlmxKUsmSJdW2bdss03Lqwzl79my1aNFCpUqVUrly5dS9e3d9+umn6t+/v8xMmzZtyiy7adMmmZn69++vTZs2qXfv3qpQoYKKFy+uRo0a6Y033si2/L1792rEiBG65JJLVL58eRUtWlQVK1ZU165dtXTp0vxtjAg33XSTtm/fni2Ow4cPa9KkSWrevLnOP//8qHVvu+02ZWRk6P7779f999+fLdmUpBo1amjKlCm6+OKLCzRuAAAAAB4SzgQrXry4JK+JaH5NmTJFnTt31qpVq3TVVVfp97//vXbv3q2WLVtq48aNMet99dVXatKkibZt26abbrpJ119/vdavX69u3brp/fffz1J23bp1GjlypEqUKKF+/fpp0KBBuuyyy7RgwQK1bt1as2bNyvfnCOnTp49KlSqV+TQzZMaMGdqxY4duuummqPW+/PJLvffeeypevLjuu+++XNeTkpJSIPECAAAAyIomtQl21VVXacyYMRozZox27typHj16qGHDhjrzzDPztJx9+/bpD3/4g4oXL66lS5eqXr16mfMeeOCBqP0gQ+bNm6fRo0fr7rvvzpx23XXXqXXr1ho1alSWJ6znn3++tm/frrS0tCzL2L59uxo3bqy77rpLnTp1ylPssaSmpqp3796aNGmStmzZomrVqkmSnnnmGaWlpenqq6+O+rkWLVokSWrYsKHKlClTILEAAAAAyDuecCbYxRdfrJdfflmVKlXSiy++qCuvvFI1a9ZU+fLl1aNHD82cOTOu5UyfPl179uzRjTfemCXZlKQhQ4aofPnyMeueddZZWZJNSWrVqpXOOussffDBB1mmp6WlZUs2Jaly5crq1auX1q9fr82bC2504ZtuuilzFF/Jexr77rvv6pprrlHJkiWj1tm2bZskZSaoAAAAABKDhPME0Lt3b23evFmzZ8/W4MGD1aVLFxUpUkSvv/66unbtqn79+sk5l+MyVq1aJclLFCMVK1ZMTZs2jVm3UaNGUadXqVJFu3fvzjZ98eLFuvrqq1W9enWlpKTIzGRmGj16tCRp69atOcaaF02bNtWvf/1rTZw4UceOHdM///lPHTt2LGZzWgAAAAAnDprUniCSk5PVoUMHdejQQZJ07NgxTZ8+XTfccINeeOEF9ejRQ927d49Zf+/evZIUswlp2bJlY9aN1YcxKSlJx44dyzJt2rRpSk9PV/HixdW+fXvVqVNHpUqVUlJSkubNm6f58+fr4MGDOX7WvLrpppt0++236+2339Zzzz2nhg0bqkGDBjHLh14XU5CJLwAAAIC8I+E8QSUlJalHjx5as2aNBg8erLlz5+aYcIaaue7Zsyfq/FjT82rw4MEqUaKEPvnkE9WqVSvLvLvvvlvz588vkPWEu+6663T//ffr5ptv1tatW/XQQw/lWL5ly5aSpBUrVmjv3r0n/StkAAAAgBMVTWpPcKFEMrcmtaEnfgsXLsw279ChQ1q2bFmBxPPZZ5/pwgsvzJZsSso2om1BKVOmjNLT07VlyxaVKlVKffr0ybF8rVq1dOmll+rAgQMaNWpUrssv6CeyAAAAADwknAk2efJkvfvuu9markrSd999p6eeekqS1Lp16xyX061bN5UuXVoTJ07URx99lGXesGHD9P333xdIvJUrV9batWu1Y8eOLNNHjRql1atXF8g6ohkxYoSmTZum2bNnR31faaRx48YpLS1NjzzyiEaPHq0jR45kK7N582b16tWrwN8fCgAAAMBDk9oEW758ucaOHavKlSurZcuWqlWrlpKTk/Xll1/qrbfe0t69e9WtWzelp6fnuJy0tDQ9+eSTuu6669S8eXNdffXVqlKlipYsWaLVq1erZcuWWrRokZKS8neP4Y477tA999yjBg0aKD09XSVKlNDChQu1atUqde7cWW+//Xa+lh9LjRo1VKNGjbjLn3feeZo9e7bS09N1zz33aOzYsWrXrp3OOOMM/fjjj/roo4+0ePFimZkGDRoUSMwAAADAqY6EM8HuvvtuVa9eXfPmzdOHH36oGTNmyDmn8uXLq3nz5urbt6/69u0rM8t1Wddcc43KlSunhx9+WK+88opSUlLUunVrLVq0SMOHD5ekqK80yYuBAwcqJSVF48eP14QJE5SWlqZWrVpp0aJFmjFjRmAJ5y/RrFkzrV+/Xs8884xmzJihN998U7tG/wNjAAAgAElEQVR371bJkiV11llnaeDAgRowYEDU5sEAAAAA8s9y6xv4SzRq1MitWLEi13Lr1q3TeeedV+DrR1bOOZ111lnav39/5jsqAZz4OEcCAHByenl5zu+t79s0/pZ9iWBmK51z0d+tGIE+nCeRvXv3Rh0AZ8yYMfriiy/Uo0ePBEQFAAAA4FRFk9qTyNKlS3Xttdeqffv2ql27tg4ePKjFixdr2bJlql69uoYOHZroEAEAAACcQkg4TyLnnHOO2rRpo0WLFuk///mPzEzVqlXT7bffrj//+c86/fTTEx0iAAAAgFMICedJpFatWpo6dWqiwwAAAAAASfThBAAAAAAEhIQTAAAAABAIEk4AAAAAQCDiSjjNbJiZ/c/MNpjZf8ysVNCBAQAAAAAKt1wTTjM7S9L1ki50zp0j6aikPkEHBgAAAAAo3OJ5wrlL0mFJJcysqKSSkjYHGhUAAAAAoNDLNeF0zu2S9Ji8JHObpL3OuXciy5nZADNbYWYrdu7cWfCRAgAAAAAKlXia1NaRdJekWpLOkFTKzK6NLOece9o518g516hixYoFHykAAAAAoFCJp0ltE0lLnHM7nXOHJb0mqWWwYQEAAAAACrt4Es6NkpqZWUkzM0nt/Gk4DmrWrKmaNWsmOoxCpX///jIzbdq0KdGh4BQ1b948mZmGDh2a6FAAAAASqmhuBZxzH5jZVEkfSzomabWkJ4MOTJI0847jsppf7IqxiY4gbmamSy65RPPmzUt0KKeEmjVr6quvvsr8f1JSkkqVKqWqVauqfv366tKli9LT05WSkpLAKAEAAIBg5ZpwSpJzboikIQHHApx07rjjDpUpU0bHjh1TRkaGNmzYoJkzZ2rKlCl64IEHNGXKFDVr1izRYQIAAACBiCvhBPDL3HnnndmaRO/du1eDBw/WE088oU6dOmnZsmU699xzExMgAAAAEKB4+nAiYM45jR8/XhdccIGKFy+uqlWr6tZbb9XevXujlt+7d69GjBihSy65ROXLl1fRokVVsWJFde3aVUuXLs1SdtKkSfK63krz58+XmWX+hPcve/rpp3XFFVeoWrVqSk5OVlpamlq0aKEXX3wxT59l6NChMrOoTXc3bdokM1P//v2zTA/vc/nUU0/p17/+tYoXL65KlSppwIABMbfDe++9p1atWqlUqVIqV66cunfvrvXr1+cY3/Lly5Wenq7KlSurWLFiql69un7/+9/rm2++yVa2TZs2MjMdOnRIw4cP1znnnKOUlJRs8edV6dKlNW7cOF1//fXau3evBg0alGX+9u3b9Yc//EFnnnmmihUrpuLFi+uss85S7969tXFjfN2nQ31/9+7dqzvvvFPVq1dXsWLFdP755+uVV16RJB08eFAPPfSQatasqeTkZNWpU0fjx4/PtqxDhw5p9OjR6tChgypVqqTk5GSVK1dOl156qd5+++2o61+5cqW6d++u008/XUWLFlVqaqrq1aunW265RYcPH84sl5GRofvvv19nn322UlJSlJKSojPPPFPdu3fXihUr4vqsoe/p4MGDevDBB1WrVi2lpKSoTp06GjZsmA4dOhS13vr169W/f//MbVOpUiX17dtXGzZsyFZ2w4YNuvPOO9WgQQOlpqaqWLFiOvPMMzVgwABt2bIlrjgl6cCBA0pPT5eZ6Y9//KOOHTsWd10AAIDCiCecJ4A777xT48aNU5UqVTRgwAAlJydr+vTpWr58uQ4dOqRixYplKb9u3TqNHDlSrVu3Vr9+/VSyZEl9/fXXmj59ut5++23NnDlTnTp1kiTVr19fQ4YM0bBhw3TmmWdmSZbatGmT+e+77rpLF154obp27ary5ctr9+7deuutt3Tddddpw4YNevjhhwPfDvfdd5/mzp2rnj176oorrtDcuXP1zDPP6PPPP9fcuXOzlJ06dap69eqlYsWKqVevXqpSpYoWLVqkiy++WBdeeGHU5U+cOFEDBgxQamqqunfvrjPOOENffPGFJk2apJkzZ2rZsmWqUaNGtnpXXnmlVq1ape7duystLU2nn356gXzehx56SC+88ILeeOMNZWRkKC0tTfv371fLli31xRdfqFOnTurTp4+SkpL05Zdf6v3339e6detUp06duJZ/6NAhXXrppfrpp5/Uu3dvHThwQC+99JL69OmjUqVKacKECVqzZo26deumokWL6pVXXtFtt92mkiVL6sYbb8xczq5du/SnP/1JLVq0UK9evVS6dGl9++23mjlzpi677DI988wz+t3vfpdZ/uOPP1bLli2VlJSkHj16qGbNmjpw4IDWrVunF154QX/729+UnJws55w6d+6sJUuWqFWrVurRo4eSk5O1ZcsWzZ8/X8uWLVOjRo3i3p5XX321PvzwQ6Wnp2ceQ0OHDtWKFSs0Y8aMzBsvkjRr1iz17NlTktStWzfVrl1b27Zt07///W+9+eabev/993XRRRdllp82bZpefvlltWnTRh06dFCRIkW0Zs0aTZw4UTNnztSKFStUtWrVHOPbvXu3unbtqsWLF+uRRx7JdqMBAADgZETCmWBLlizRuHHjVLduXS1dulTlypWTJP3lL39R+/bttW3bNp155plZ6px//vnavn270tLSskzfvn27GjdurLvuuitLwlm/fn0NGzZMNWvWjDlq5vr161W9evUs0w4fPqxu3brp0Ucf1c0335zrBXV+rVq1SmvWrFGlSpUkSceOHVPHjh313nvv6YMPPlCTJk0kST/88IN+//vfKzk5WYsWLVLDhg0zl3HPPfdo9OjR2Zb92Wef6eabb9Z5552nOXPmZEkalyxZorZt2+qOO+7QtGnTstXdtm2b1q1bp9TU1AL9vHXq1FG1atW0ZcsWrVy5Um3bttWcOXO0ceNGDRo0SI888kiW8kePHtX+/fvjXv62bdvUokULTZkyRUWKFJEkXX/99WrSpIn69OmjevXqae3atSpZsqQk78ZH3bp19dhjj2VJOMuWLastW7ZkS7T37dunSy65RPfdd5+uueYalShRQpL0/PPP68CBA5o1a5Y6duyYpU5GRkbm+j799FMtWbJEvXv31uTJk7OUc84pIyMj7s8qed/xmjVrVLZsWUk/H0NvvPGGXnzxRV133XWSvMSvT58+Klu2rObNm6ezzz47cxmDBg1Ss2bN9Lvf/U7//e9/M6f369dP99xzj4oWzXrKXLBggdq2basRI0ZowoQJMWP76quv1LlzZ33++ef617/+pWuuuSZPnw0AAKCwokltgj333HOSpGHDhmUmm5JUvHjxqImTJKWlpWVLNiWpcuXK6tWrl9avX6/NmzfnKY7IZFOSkpOTdcstt+jIkSOaM2dOnpb3SwwZMiQz2ZS8kV1DT2Q/+OCDzOnTp0/Xrl271L9//yzJpiSNGDEiM+EIN2HCBB0+fFhjxozJljg1b95cPXr00MyZM7Vv375sdf/yl78UeLIZEkrid+7cKclr5iopy9O4kCJFiuQ5jscffzwz2ZSkxo0bq27duvrhhx/017/+NTP5k7x9oHXr1lq3bl2W7ZCSkhL1qW5qaqpuvPFG7d69Wx9++GHm9Jw+Q1pampKSknItZ2YqXbp0nj7rww8/nOW7Dz+GJk6cmDn9hRde0J49ezR8+PAsyaYk1a1bVwMGDNCqVau0du3azOlVqlTJlmxKUuvWrdWgQQPNnj07ZlyrV6/WxRdfrK1bt+rtt98m2QQAAKcUnnAmWOgpyiWXXJJtXuPGjVWqVKmo9RYvXqyxY8dq6dKl2rFjR7Z+alu3bo3aPDSWzZs3669//avmzJmjzZs366effsq2vKA1btw427QqVapI8p5KheS0zYoXL65mzZpl61sY6tv63nvvaeHChdnqffPNNzp69Kg+++yzbElskKPIOuckSUeOHJEktWvXTqeffroeffRRffTRR+rcubMuvvhi1a9fP0viGI9KlSqpWrVqUad/9tlnUZurhhL+PXv2ZElu16xZo1GjRmnBggXatm2bDhw4kKVe+P7Rq1cvTZgwQT179lR6erratWun5s2bZ2sKXL9+fZ133nmaPHmytm7dqiuuuELNmzdXo0aNsjUjj0dOx9CqVasyp4X2hRUrVujrr7/OVieUaK5bt07nn3++JO97eumllzRp0iR99NFH2r17t44ePZpZJ1a8ixYt0t///nelpqZqwYIFqlevXp4/FwAAQGFGwplgoQFxwp9uhpiZypQpk236tGnTlJ6eruLFi6t9+/aqU6eOSpUqpaSkJM2bN0/z58/PfHoUjy+++EJNmjTR7t271apVK3Xo0EGlS5dWkSJFtGnTJj3//PN5Wt4vFe2dlKGnYeEX9zlts1jTv//+e0nSo48+mmMMP/zwQ7ZpeX3SlhehwYpCiV7ZsmW1dOlSDR06VG+88YbeeustSVKFChV0yy236MEHH1RycnJcyy5evHjU6aFtGu/2XrZsmX7zm9/oyJEjateunbp27Zr5pHL16tWaPn16lv2jVatWmjNnjh555BFNmTJFzz//vCTpnHPO0ZAhQ9SnTx9JUtGiRTVv3jwNHz5cU6dO1YIFCyR5T0779eunkSNH5umJbk7HUPigUKF94R//+EeOywvfF+6++26NGTNGVapUUceOHVW1atXMJsSTJk3K8s7VcKtWrdK+ffvUvHlzRiIGAACnJBLOBAslM7t27cp8mhfinNOePXtUoUKFLNMHDx6sEiVK6JNPPlGtWrWyzLv77rs1f/78PMXw97//Xd9//71effVVXXXVVVnmzZgxIzNhiEcoYQk9uQsX+VTslwrfZtFEmx6qs3fv3qjNkRPh888/15YtW5SUlKT69etnTq9du7ZeeOEFOee0du1azZ07V08++aSGDx+uH3/8UY899thxjXPEiBE6cOCAli1bltmPNmTcuHGaPn16tjpt2rRRmzZtdPDgQa1cuVKzZs3SE088ob59+yo1NVVdunSRJJ1++ukaP368xo8fr88//1zz58/XU089pfHjx2vbtm2aOnVq3HHu2rVLFStWzDItdAyFf+ehfeGjjz6KOcBUuB07dmjcuHFq2LChFi5cmJlohsyYMSNmwnnrrbdqx44d+sc//qGuXbvq9ddfz1YfAADgZEYfzgQLjYQZLUn88MMP9eOPP2ab/tlnn+nCCy/MlmxK0vvvvx91PUlJSVGTwNDyJG+0zniXF0uoD12014yE9/PLj5y2WSgxihRqFhutOW2iDB8+XJLUuXNnlS9fPtt8M9MFF1yg2267Te+++64kL7k53j777DNVrlw5W7Ip5b5/pKSkqHnz5ho+fLjGjRsnKfZnOOuss/Tb3/5W8+fP12mnnaaZM2fmKc6cjqEGDRpkTsvrvvD555/r2LFj6tChQ7ZkcefOnfr0009j1jUzTZgwQXfeeafeeecdXX755VGPaQAAgJMVCWeChQbFGTJkSJYncwcOHNDAgQOj1qlcubLWrl2rHTt2ZJk+atQorV69Omqd8uXLx+yHWblyZUnK9u7MhQsX5jjyZjShpOT555/P8o7BHTt2aNiwYXlaVizdunVT2bJlNWnSJK1cuTLLvAcffDBLf8+QW2+9VcnJybrrrruiDqh07NgxLV++vEDiy01GRoZuv/12/etf/9Jpp52mUaNGZc5bs2aNvv3222x1Qs2Iow2IFLTKlSvr22+/1bp167JMf/XVV6M+3VyyZEm2PsBS9s/w5Zdf6osvvshWbt++fTp69GjU5uQ5GTx4cJbvPvwYuuGGGzKn33DDDSpTpoyGDRumjz/+OOqywt9nGzo+Fi5cmKWp8aFDhzRgwIAs7xWN5fHHH9ef/vQnvf/+++rYsWOeR+AFAAAorGhSm2AtWrTQbbfdpieeeEK/+tWvsrxDsGzZstma2UrSHXfcoXvuuUcNGjRQenq6SpQooYULF2rVqlXq3LlztgFzJG8wmilTpqhnz56qX7++kpKS1Lp1a7Vu3Vq33HKLJk+erO7du6tXr16qWrWq1q5dqxkzZqhbt2567bXX4v48TZs2VevWrfXuu++qRYsWatu2rXbt2qWpU6eqXbt22rhxY762lySddtppevrpp9WrVy+1bNkyy3s4P/30U7Vu3TqzP2DIueeeq4kTJ+rGG2/Uueeeq8svv1xnn322jh49qi+//FILFixQmTJltH79+nzHF27MmDEqU6ZM5ms+NmzYoAULFujHH39UzZo1NXnyZJ133nmZ5d99913de++9atGiherVq6e0tDR98803eu2115SUlKR77723QOOLx+23366FCxdmvoezbNmyWrlypebMmaNu3brp9ddfz1L+b3/7m+bOnau2bdvqnHPOUbFixTL3p7Jly2rAgAGSvCatPXv2VJMmTdSwYUOVK1dO3333nV5//XX99NNPGjFiRJ7irFu3ri644IIsx9DGjRt1+eWXZ74SRfJuvkydOlU9evRQw4YN1bFjR/3qV7+Smenrr7/WokWLtH379swm4LVr11aXLl30xhtvqHHjxurQoYMOHDigmTNnysx04YUXxkxcw40cOVLFixfXkCFD1L59e82aNSshNxAAAACOJxLOE8DYsWNVt25dPfnkk3rqqadUvnx59ejRQyNHjow6quXAgQOVkpKi8ePHa8KECUpLS1OrVq20aNEizZgxI2rCOXbsWJmZ5syZo+nTp+vYsWMaMmSIWrdunTmq65AhQzRlyhQVLVpU9erV0+TJk1WxYsU8JZyS99qSe++9V9OnT9d///tfnX322Ro5cqQ6dOigV1999Rdvp3Dp6emaNWuWhg0bpldffVUpKSlq3bq1li5dqkcffTRbwilJ1157rerVq6fRo0fr/fff1/Tp01WkSBHVqFFDnTp1Ut++fQsktnBjx46V5DWtLFWqlKpVq6YrrrhCXbp0UXp6eraBezp06KCNGzdq8eLFeu6557R//36VLVtWLVq00MCBA9W2bdsCjzE36enpmjJlih599FFNnDhRJUqUUJMmTTR79mx9/fXX2RLOm2++Wampqfrggw/0zjvv6MiRIzrjjDPUr18/PfDAA6pdu7YkqVGjRrrnnnu0YMECvfzyy8rIyFBaWpouuugiPfnkk+rZs2ee4nz11Vf18MMP66WXXtI333yjqlWraujQoRo0aFC2V6+0a9dOH3/8sR577DHNnj1b7733npxzqlq1qpo2baorr7wyS/kpU6bogQce0Kuvvqq///3vqlSpkrp06aJhw4bp6quvjjvGhx56SCVKlNB9992ndu3a6Z133snWRxsAAOBkYrH69eVHo0aN3IoVK3Itt27duixPdwAgr9q0aaP58+fH7KNcmHGOBADg5PTy8uxdvML1bRr/6w0TwcxWOueyv2MvCvpwAgAAAAACQcIJAAAAAAgECScAAAAAIBAMGgSgUIt8nQ8AAABOHDzhBAAAAAAEgoQTAAAAABAIEk4AAAAAQCASnnCejO/OA4D84twIAABOBglNOIsUKaLDhw8nMgQAOCEdPnxYRYoUSXQYAAAA+ZLQhDM1NVUZGRmJDAEATkgZGRlKTU1NdBgAAAD5ktCEs1y5ctq9e7e+++47HTp0iCZkAE5pzjkdOnRI3333nXbv3q1y5colOiQAAIB8Seh7OFNSUlSjRg3t2rVLmzZt0tGjRxMZDgAkXJEiRZSamqoaNWooJSUl0eEAAADkS0ITTslLOqtUqaIqVaokOhQAAAAAQAFK+Ci1AAAAAICTEwknAAAAACAQJJwAAAAAgECQcAIAAAAAAkHCCQAAAAAIBAknAAAAACAQJJwAAAAAgECQcAIAAAAAAkHCCQAAAAAIBAknAAAAACAQJJwAAAAAgECQcAIAAAAAAkHCCQAAAAAIBAknAAAAACAQuSacZnaOma0O+8kwszuPR3AAAAAAgMKraG4FnHMbJNWXJDMrImmrpGkBxwUAAAAAKOTy2qS2naSNzrmvgggGAAAAAHDyyGvC2VvS5GgzzGyAma0wsxU7d+7Mf2QAAAAAgEIt7oTTzIpJ6irp39HmO+eeds41cs41qlixYkHFBwAAAAAopPLyhLOzpP86574NKhgAAAAAwMkjLwlnH8VoTgsAAAAAQKS4Ek4zKyWpvaTXgg0HAAAAAHCyyPW1KJLknPtRUvmAYwEAAAAAnETyOkotAAAAAABxIeEEAAAAAASChBMAAAAAEAgSTgAAAABAIEg4AQAAAACBIOEEAAAAAASChBMAAAAAEAgSTgAAAABAIEg4AQAAAACBIOEEAAAAAASChBMAAAAAEAgSTgAAAABAIEg4AQAAAACBIOEEAAAAAASChBMAAAAAEAgSTgAAAABAIEg4AQAAAACBIOEEAAAAAASChBMAAAAAEAgSTgAAAABAIEg4AQAAAACBIOEEAAAAAASChBMAAAAAEAgSTgAAAABAIEg4AQAAAACBIOEEAAAAAASChBMAAAAAEAgSTgAAAABAIEg4AQAAAACBIOEEAAAAAASChBMAAAAAEAgSTgAAAABAIEg4AQAAAACBIOEEAAAAAASChBMAAAAAEAgSTgAAAABAIEg4AQAAAACBIOEEAAAAAASChBMAAAAAEIi4Ek4zK2Nm/zazj81svZk1DzowAAAAAEDhVjTOcs9Iet0595KZFZVUKsCYAAAAAAAngVwTTjMrL6mBc+4qSXLOHZG0N+jAAAAAAACFWzxNas+WtNNvUrvGzP5lZqlBBwYAAAAAKNziSTiTJDWW9Jhz7gJJuyQNjixkZgPMbIWZrdi5c2cBhwkAAAAAKGziSTi/lrTVObfc//9USfUjCznnnnbONXLONapYsWJBxggAAAAAKIRyTTidc19L+s7MzvEntZO0PtCoAAAAAACFXryj1P5W0ktmVlLSZknXBBcSAAAAAOBkEFfC6ZxbLalRwLEAAAAAAE4i8fThBAAAAAAgz0g4AQAAAACBIOEEAAAAAASChBMAAAAAEAgSTgAAAABAIEg4AQAAAACBIOEEAAAAAASChBMAAAAAEAgSTgAAAABAIEg4AQAAAACBIOEEAAAAAASChBMAAAAAEAgSTgAAAABAIEg4AQAAAACBIOEEAAAAAASiaKIDAAAAAIDC7OXlm3Oc37dpjeMUyYmHJ5wAAAAAgECQcAIAAAAAAkHCCQAAAAAIBAknAAAAACAQJJwAAAAAgECQcAIAAAAAAkHCCQAAAAAIBAknAAAAACAQJJwAAAAAgEAUTXQAAAAAAHAqafzpsJwLNH32+ARyHPCEEwAAAAAQCBJOAAAAAEAgSDgBAAAAAIEg4QQAAAAABIKEEwAAAAAQCBJOAAAAAEAgSDgBAAAAAIEg4QQAAAAABIKEEwAAAAAQCBJOAAAAAEAgSDgBAAAAAIEg4QQAAAAABIKEEwAAAAAQCBJOAAAAAEAgisZTyMw2Sdon6aikI865RkEGBQAAAAAo/OJKOH1tnXPfBRYJAAAAAOCkQpNaAAAAAEAg4k04naR3zewTM7styIAAAAAAACeHeJvUXuyc225mp0uaZWbrnXPvhhcwswGSBkhSjRo1CjhMAAAAAEBhE9cTTufcdv/3DklTJTWOUuZp51wj51yjihUrFmyUAAAAAIBCJ9eE08xKmVnJ0L8ldZK0NujAAAAAAACFWzxNaitJet3MnKSSkl6RND3QqAAAAAAAhV6uCadz7gtJFx6HWAAAAAAAJxFeiwIAAAAACAQJJwAAAAAgECScAAAAAIBAkHACAAAAAAJBwgkAAAAACAQJJwAAAAAgECScAAAAAIBAkHACAAAAAAJBwgkAAAAACAQJJwAAAAAgECScAAAAAIBAkHACAAAAAAJBwgkAAAAACAQJJwAAAAAgECScAAAAAIBAkHACAAAAAAJBwgkAAAAACAQJJwAAAAAgECScAAAAAIBAkHACAAAAAAJBwgkAAAAACAQJJwAAAAAgECScAAAAAIBAkHACAAAAAAJBwgkAAAAACAQJJwAAAAAgECScAAAAAIBAkHACAAAAAAJBwgkAAAAACAQJJwAAAAAgECScAAAAAIBAkHACAAAAAAJBwgkAAAAACAQJJwAAAAAgECScAAAAAIBAkHACAAAAAAJBwgkAAAAACAQJJwAAAAAgECScAAAAAIBAkHACAAAAAAIRd8JpZkXMbJWZvRFkQAAAAACAk0NennDeIWldUIEAAAAAAE4ucSWcZlZN0uWS/hlsOAAAAACAk0W8TzjHSLpP0rEAYwEAAAAAnERyTTjNrIukHc65lbmUG2BmK8xsxc6dOwssQAAAAABA4RTPE84Wkrqa2SZJUyT9xsxejCzknHvaOdfIOdeoYsWKBRwmAAAAAKCwyTXhdM79yTlXzTlXU1JvSXOdc9cGHhkAAAAAoFDjPZwAAAAAgEAUzUth59w8SfMCiQQAAAAAcFLhCScAAAAAIBAknAAAAACAQJBwAgAAAAACQcIJAAAAAAgECScAAAAAIBAknAAAAACAQJBwAgAAAAACQcIJAAAAAAgECScAAAAAIBAknAAAAACAQJBwAgAAAAACUTTRAQAAAADAieTl5ZtzLdO3aY3jEEnhxxNOAAAAAEAgSDgBAAAAAIEg4QQAAAAABIKEEwAAAAAQCBJOAAAAAEAgSDgBAAAAAIHgtSgAAAAAkA+NPx2Wc4Gmzx6fQE5APOEEAAAAAASChBMAAAAAEAgSTgAAAABAIEg4AQAAAACBIOEEAAAAAPx/e/cXa9lV1wH8+6PTQA08yUS0w1BjGgySSshMRkPRVmNSbIh/0gSp6YNpLGAw+AYm/kl90gcTNFFJdZCYphUFYiSA1Wi0NoHiWGsZqLYaSdsY0qIRpQlY5OfDvZhxGO7Zhzlr333u+XySSebcvXLznTtrzp3vXWuvPYTCCQAAwBAKJwAAAEMonAAAAAyhcAIAADCEwgkAAMAQCicAAABDKJwAAAAMoXACAAAwhMIJAADAEAonAAAAQyicAAAADKFwAgAAMP2ji84AAAw0SURBVITCCQAAwBAKJwAAAEMonAAAAAyhcAIAADDEysJZVS+oqnNV9XBVPV5V76yqmiMcAAAA2+vYhDFfTPK93f1sVV2Z5IEkNyb5i6HJAAAA2GorC2d3d5Jn919emeSKJE+PDAUAAMD2m3QPZ1VdUVUPZ69o/mV3n7/EmDv2t96ee+aZZzadEwAAgC0zqXB29/9096uSnEjy2qq68RJj7uruU9196vjx45vOCQAAwJZZ65Ta7v6PJB9K8l1j4gAAAHBUTDml9sVV9aL931+V5AeSfNWWWgAAALjQlFNqvyXJ7+0/CuUFSe7t7g+OjQUAAMC2m3JK7SNJXjVDFgAAgCHuefCJA6/feubkTEl2y1r3cAIAAMBUCicAAABDKJwAAAAMoXACAAAwhMIJAADAEAonAAAAQyicAAAADKFwAgAAMITCCQAAwBAKJwAAAEMonAAAAAyhcAIAADCEwgkAAMAQCicAAABDKJwAAAAMoXACAAAwhMIJAADAEAonAAAAQyicAAAADKFwAgAAMITCCQAAwBDHDjsAAADAkpw+f+fqQWfOjg9yBFjhBAAAYAiFEwAAgCEUTgAAAIZQOAEAABhC4QQAAGAIhRMAAIAhFE4AAACGUDgBAAAY4thhBwAAAFjXPQ8+ceD1W8+cnCkJB7HCCQAAwBAKJwAAAEMonAAAAAyhcAIAADCEwgkAAMAQCicAAABDKJwAAAAMoXACAAAwxMrCWVUvrar7q+p8VT1WVW+fIxgAAADb7diEMc8leWt3P1JVL0ryUFXd190PD84GAADAFlu5wtndn+nuR/Z//19JHkly9ehgAAAAbLe17uGsqmuSnE7ywIgwAAAAHB1TttQmSarqhUnel+Rnuvtzl7h+R5I7kuTkyZMbCwgAAHC5Tp+/8+ABZ87OE2THTFrhrKork7w/yb3d/YFLjenuu7r7VHefOn78+CYzAgAAsIWmnFJbSc4mebS7f3V8JAAAAI6CKSucr0lyW5Lvq6qH93/94OBcAAAAbLmV93B29wNJaoYsAADAjrrnwSdWjrn1jLNits1ap9QCAADAVAonAAAAQyicAAAADKFwAgAAMITCCQAAwBAKJwAAAEMonAAAAAyhcAIAADCEwgkAAMAQxw47AAAAcDTd8+ATB16/9czJmZJwWKxwAgAAMIQVTgAAYOucPn/nwQPOnJ0nCAeywgkAAMAQCicAAABDKJwAAAAMoXACAAAwhMIJAADAEAonAAAAQyicAAAADKFwAgAAMITCCQAAwBAKJwAAAEMonAAAAAxx7LADAAAA2+GeB5848PqtZ07OlIRtYYUTAACAIaxwAgAAh+70+TtXDzpzdnwQNsoKJwAAAEMonAAAAAyhcAIAADCEwgkAAMAQCicAAABDOKUWAAB21KrnaiaercnlscIJAADAEAonAAAAQyicAAAADOEeTgAAYIjT5+88eMCZs/ME4dBY4QQAAGAIK5wAAHCErDp59nJOnbViyboUTubxwbcdfP31vzZPDgAAYDa21AIAADDEysJZVe+uqqer6vwcgQAAADgapqxwvifJTYNzAAAAcMSsvIezu++vqmvGR4ELuOcTAAC2nns4AQAAGGJjhbOq7qiqc1V17plnntnUpwUAAGBLbeyxKN19V5K7kuTUqVO9qc8Lk9iCCwAcUYf6XM3EszW5LLbUAgAAMMSUx6Lcm+SjSV5eVU9V1e3jYwEAALDtppxS+8Y5ggAAAJdv5TZZW2SZ0cbu4YSt4X5PAACYhcIJqyioAMAhsmLJNlM4AQDgMo08SRa2mcIJm7bOiug2r55uc3YAAGahcMI22WSZvXj8SEvKAgBL4Ae37AiFE9izpG98S8oCAAM8/vTnD7x+7Uw5YLSVz+EEAACAr4cVTgAAuExOkoVLUziB7WcLLgDAIimcAABwEY85gc1QOIHdYjUUAGA2CicAADvBqiXMT+EEOIgVUYCd5BAg2AyFE2CT1imo65ZZ5Rc46ga/zymRMD+FEwCArfT42dsPvH7t7QokHDaFEwCAydwHCaxD4QTAdl3YZav+/SfeA4Cvm8IJcFTtSonclT8nrGNJ/y7WyPL4058/cOi1m8gDzErhBGB9mzwc6eLxXNqSCgQ7zcE7wDoUTgBgdyyluK/5g5iR902uWlVMLm9l0aol7DaFE4BlWUohSHbn0TWj/5wjvy7b+jUH2BEKJwC7Y0nbe0dn2dYitqTcS8qyJquKwFIonAAAmzCwoLpvEthWzzvsAAAAABxNCicAAABD2FILADCz0SfDAiyFwgkAcAnrHrzjoB6Ar6ZwAgCLMbrkKYUA81I4AeAIUqwAWAKFEwB2nFVFAEZROAFgQ9YpVg6NAWAXeCwKAAAAQ1jhBNgSI7cxHubnvtTnX4ftmgCwXAonAIsyskCuW36XVGaXlAUAplI4gST+kw8AwOYpnLBFllTElpRlHaNzj9zGCgCwbRROOKJ26QTMw1ydPSpfQwCAERROZrHNz3hb0kEtAACwTRROdo6SBwAA8/AcTgAAAIaYVDir6qaqOl9Vj1bVO0aHAgAAYPutLJxV9fwk70ryuiTXJbmlql49OhgAAADbbcoK55kkn+zuJ7v7uSTvTXLz2FgAAABsuymF80SSJy94/dT+xwAAAOBrqu4+eEDVrUm+p7vfvP/6jUlu6O43XTTujiR37L98eZJ/3Hzc2b04yWcPOwTEXGQ5zEWWwlxkKcxFlmLOufiy7j4+ZeCUx6I8leSlF7w+sf+x/6e770py16R4W6KqznX3qcPOAeYiS2EushTmIkthLrIUS52LU7bUfjzJK6vqRFVdmeQNST4yNhYAAADbbuUKZ3d/oarekuS+7BXUu7v73PBkAAAAbLUpW2rT3R9O8uHBWZboSG0RZquZiyyFuchSmIsshbnIUixyLq48NAgAAAC+HlPu4QQAAIC1KZxJquqmqjpfVY9W1Tsucb2q6ter6lNV9XdV9erDyMnRN2Eu3lZVn9gf87dVtbiTyDgaVs3FC8adrqovVdUtc+Zjd0yZi1V1Q1X9TVX9fVXdP3dGdsOE79Evqao/3///4mNV9ebDyMnRVlXvrqqnq+r817i+uN6y84Wzqp6f5F1JXpfkuiS3XOIv5keTvCzJdyS5PcnvzhqSnTBxLj6W5PrufmWSn0vyO/OmZBdMnIupqiuS/EqSP503Ibtiylysqpck+Y0kr+/u78ze92zYqInvi29Ncq67X5HkNUl+uaqumjcpO+A9SW464PriesvOF84kZ5J8sruf7O7nkrw3yc0Xjbk5e6fzdnc/lORYVb304k8El2nlXOzuB7v7c/svH0hy9cwZ2Q1T3heT5KeTvD/J03OGY6dMmYs/luQPuvszSdLdcz30nN0yZS4+leRFVVVJXpjks0m+OG9Mjrruvj/Jvx8wZHG9ReFMTiR58oLXT+1/bN0xcLnWnWdvSvLHQxOxq1bOxaq6OsmPJPmtGXOxe6a8L357km+uqo/t33Lwk7OlY5dMmYu/neQVSf41ySeSvK27vzxPPPg/i+stkx6LAixLVd2QvW0S1x9yFHbXO5O8vbu/vPfDfDg0z8veFsfvT3JVko9V1Ue7+5L3N8FAP5vkkSQ3Jvm2JH9WVX/d3f95uLHgcFnh3Gv9Fy4zn9j/2Lpj4HJNmmdVdV2Ss0l+qLv/baZs7JYpc/FUkt+vqk8nuSXJb1bVD88Tjx0yZS4+meS+7n52fzvtX2WvgMImTZmLr03yh/tbGf8pyb9kb8UT5rS43qJwJh9P8sqqOlFVVyZ5Q5KPXDTmw0l+PEn2bxD/cnc/GdislXOxqk4m+UCS27r7sUPIyG5YORe7+1u7+5ruvibJ+5L8VHf/0fxROeKmfI/+UJLrq+pYVX1Dku9O8g8z5+TomzIX/zl7K+2pqm/KXtn89JwhIQvsLTu/pba7v1BVb0lyX/YK+N3dfe4rR1l397uydyjGjVX1qST/neQnDi0wR9bEufgLSb4xe6tJSfKl7vZoFDZq4lyE4abMxe5+qKr+JHtbGa9Mcnb/oAzYmInvi7+U5O6qejTJFUl+/iuHWcGmVNW9SW5I8uKqeirJL2bvvW+xvaW6+7AzAAAAcATZUgsAAMAQCicAAABDKJwAAAAMoXACAAAwhMIJAADAEAonAAAAQyicAAAADKFwAgAAMMT/ApPMNfuuS/0LAAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 1152x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"a=[h_mc.GetBinContent(i) for i in range(nbins)]\n",
"b=[h_mc.GetBinCenter(i) for i in range(nbins)]\n",
"c=[h_data_under.GetBinContent(i) for i in range(nbins)]\n",
"d=[h_data_under.GetBinCenter(i) for i in range(nbins)]\n",
"plt.title(\"ProbNN mu Signal MC/ data under peak comparison\", fontsize=20)\n",
"\n",
"plt.bar(b,a,width=0.01,alpha=0.4,label=\"Signal MC\")\n",
"plt.bar(d,c,width=0.01, alpha=0.6, label=\"data under Ds mass peak\")\n",
"plt.legend(fontsize=20)\n",
"fig = plt.gcf()\n",
"fig.set_size_inches(16,8)"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1152x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"a=[h_mc.GetBinContent(i) for i in range(nbins)]\n",
"b=[h_mc.GetBinCenter(i) for i in range(nbins)]\n",
"c=[h_data_over.GetBinContent(i) for i in range(nbins)]\n",
"d=[h_data_over.GetBinCenter(i) for i in range(nbins)]\n",
"plt.title(\"Prob NN mu Signal MC/ data under peak comparison\", fontsize=20)\n",
"\n",
"plt.bar(b,a,width=0.01,alpha=0.4,label=\"Signal MC\")\n",
"plt.bar(d,c,width=0.01, alpha=0.6, label=\"data under Ds mass peak\")\n",
"plt.legend(fontsize=20)\n",
"fig = plt.gcf()\n",
"fig.set_size_inches(16,8)"
]
},
{
"cell_type": "code",
"execution_count": 44,
"metadata": {},
"outputs": [],
"source": [
"nbins=4\n",
"MC_Hlt1TrackMVA_TOS=MC_tuple_dict[\"Ds_Hlt1TrackMVADecision_TOS\"]\n",
"data_Hlt1TrackMVA_TOS_under=data_tuple_bkg_under[\"Ds_Hlt1TrackMVADecision_TOS\"]\n",
"data_Hlt1TrackMVA_TOS_over=data_tuple_bkg_over[\"Ds_Hlt1TrackMVADecision_TOS\"]"
]
},
{
"cell_type": "code",
"execution_count": 45,
"metadata": {},
"outputs": [],
"source": [
"h_mc= r.TH1F(\"Hlt1 TrackMVA TOS MC/data comparison under\", \"Hlt1 TrackMVA TOS MC/data under Ds mass comparison\",nbins, 0, 2)\n",
"\n",
"for i in range(len(MC_Hlt1TrackMVA_TOS)):\n",
" h_mc.Fill(MC_Hlt1TrackMVA_TOS[i]) \n",
"\n",
"n1=h_mc.Integral(\"width\")\n",
"h_mc.Scale(1/n1)\n",
"h_mc.Integral(\"width\");"
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"TFile::Append:0: RuntimeWarning: Replacing existing TH1: data below signal (Potential memory leak).\n",
"TFile::Append:0: RuntimeWarning: Replacing existing TH1: data over signal (Potential memory leak).\n"
]
}
],
"source": [
"h_data_under= r.TH1F(\"data below signal\", \"data below signal\",nbins, 0, 2)\n",
"h_data_over= r.TH1F(\"data over signal\", \"data over signal\",nbins, 0, 2)\n",
"for i in range(len(data_Hlt1TrackMVA_TOS_under)):\n",
" h_data_under.Fill(data_Hlt1TrackMVA_TOS_under[i])\n",
"for i in range(len(data_Hlt1TrackMVA_TOS_over)):\n",
" h_data_over.Fill(data_Hlt1TrackMVA_TOS_over[i])\n",
" \n",
"n2=h_data_under.Integral(\"width\")\n",
"h_data_under.Scale(1/n2)\n",
"h_data_under.Integral(\"width\");\n",
"n3=h_data_over.Integral(\"width\")\n",
"h_data_over.Scale(1/n3)\n",
"h_data_over.Integral(\"width\");"
]
},
{
"cell_type": "code",
"execution_count": 47,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1152x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"a=[h_mc.GetBinContent(i) for i in range(nbins)]\n",
"b=[h_mc.GetBinCenter(i) for i in range(nbins)]\n",
"c=[h_data_under.GetBinContent(i) for i in range(nbins)]\n",
"d=[h_data_under.GetBinCenter(i) for i in range(nbins)]\n",
"plt.title(\"Hlt1 TrackMVA TOS Signal MC/ data under peak comparison\", fontsize=20)\n",
"\n",
"plt.bar(b,a,width=0.5,alpha=0.4,label=\"Signal MC\")\n",
"plt.bar(d,c,width=0.5, alpha=0.6, label=\"data under Ds mass peak\")\n",
"plt.legend(fontsize=20)\n",
"fig = plt.gcf()\n",
"fig.set_size_inches(16,8)"
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1152x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"a=[h_mc.GetBinContent(i) for i in range(nbins)]\n",
"b=[h_mc.GetBinCenter(i) for i in range(nbins)]\n",
"c=[h_data_over.GetBinContent(i) for i in range(nbins)]\n",
"d=[h_data_over.GetBinCenter(i) for i in range(nbins)]\n",
"plt.title(\"Hlt1 TrackMVA TOS Signal MC/ data under peak comparison\", fontsize=20)\n",
"\n",
"plt.bar(b,a,width=0.5,alpha=0.4,label=\"Signal MC\")\n",
"plt.bar(d,c,width=0.5, alpha=0.6, label=\"data under Ds mass peak\")\n",
"plt.legend(fontsize=20)\n",
"fig = plt.gcf()\n",
"fig.set_size_inches(16,8)"
]
},
{
"cell_type": "code",
"execution_count": 49,
"metadata": {},
"outputs": [],
"source": [
"nbins=4\n",
"MC_Hlt2RareCharm_TOS=MC_tuple_dict[\"Ds_Hlt2RareCharmD2PiMuMuOSDecision_TOS\"]\n",
"data_Hlt2RareCharm_TOS_under=data_tuple_bkg_under[\"Ds_Hlt2RareCharmD2PiMuMuOSDecision_TOS\"]\n",
"data_Hlt2RareCharm_TOS_over=data_tuple_bkg_over[\"Ds_Hlt2RareCharmD2PiMuMuOSDecision_TOS\"]"
]
},
{
"cell_type": "code",
"execution_count": 50,
"metadata": {},
"outputs": [],
"source": [
"h_mc= r.TH1F(\"Hlt2 RareCharm TOS MC/data comparison under\", \"Hlt2 RareCharm TOS MC/data under Ds mass comparison\",nbins, 0, 2)\n",
"\n",
"for i in range(len(MC_Hlt2RareCharm_TOS)):\n",
" h_mc.Fill(MC_Hlt2RareCharm_TOS[i]) \n",
"\n",
"n1=h_mc.Integral(\"width\")\n",
"h_mc.Scale(1/n1)\n",
"h_mc.Integral(\"width\");"
]
},
{
"cell_type": "code",
"execution_count": 51,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"TFile::Append:0: RuntimeWarning: Replacing existing TH1: data below signal (Potential memory leak).\n",
"TFile::Append:0: RuntimeWarning: Replacing existing TH1: data over signal (Potential memory leak).\n"
]
}
],
"source": [
"h_data_under= r.TH1F(\"data below signal\", \"data below signal\",nbins, 0, 2)\n",
"h_data_over= r.TH1F(\"data over signal\", \"data over signal\",nbins, 0, 2)\n",
"for i in range(len(data_Hlt2RareCharm_TOS_under)):\n",
" h_data_under.Fill(data_Hlt2RareCharm_TOS_under[i])\n",
"for i in range(len(data_Hlt2RareCharm_TOS_over)):\n",
" h_data_over.Fill(data_Hlt2RareCharm_TOS_over[i])\n",
" \n",
"n2=h_data_under.Integral(\"width\")\n",
"h_data_under.Scale(1/n2)\n",
"h_data_under.Integral(\"width\");\n",
"n3=h_data_over.Integral(\"width\")\n",
"h_data_over.Scale(1/n3)\n",
"h_data_over.Integral(\"width\");"
]
},
{
"cell_type": "code",
"execution_count": 52,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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g2t0o33wvUoajC0g1pdZwSZdI6mFmQ+XLzXQXv5lmKnSQ//1Ntj/pqcHf2OBKzrmVZrZOPpjKwcwaybeEaCbfTDB2+qFqCppQJsPMqsjXgLWT/96Ifc9UX5d4ki1HeZ2zfWY2Q77rQLQzg7/NzexPcd7nmODvifI1eNESfifn47sEn6epwd+GMflzkjpanL6W8rXgJSXVlK/tLcxn6Ur5crpQ0vkuif7rEWZWTf6hx4IgwMkrbQ350cg/Ch4QxZoc/G0YZ128kccj+VzkYgbGc85tN7OfFfN9EyVeWdlifpqkMxXV/aEQ57Ug5WSWfJPz683sOPmHt7MlfRL9ECMQKe+5BvBzzi01s/WS6plZWsyDsC8SPNCN/kwV+MEb8FsQlAJ/TPGmPYkEDuPkawlWyvd1+V7+KbTkbyijb0wjU9kUtG9lM/lmezOTCUijjJBvPnuN/NNkp7xroyRl/6jOCt63lXyfoZPkbxSWOefiBURdJVWUb5YZO2DPC/L9hXrr1/5cqfS9/LFlmFmlvGpLgz69kZqXXNOSBDesq6LS15TvP3WepP+TPx9JCW4Qnw9ekSlr/iFfG/OCmR0TFfDHKiX/m5Fovs54NzbR4vWvitwcFYksCMrwu/LXZ4V8E/AN+rUM91Hu4Kqwpsif46vla60rKnEf5Yh18rWlvyUQ6yrfvHByfgkDkZYeiWriNiomQDSzs+XP4z75vrJvyNce7ZdvTt9OBTiPQUD6iXxwO1v+nG2Wrw2rIl8bn+rrEk9S5UjJnbNYkQFtbs0nD/EGCIr7nZyE/PIX3cqngnzgk9f0WFKQv0J+lprLP8ycUZCANFCQ35X8rlMkUI037drOOMsiZSFRP9n9yllOoiV1LQp5XpMuJ865X8ysuXxrr876dVqpTWb2nHzz5Mg5KCNpp3NuR4Ld/ST/OS0dk4e8zpOU+FwBKUdQChxazpIPSEdLujQ6wAiCnz4x6SMBRtwRPPNwm/zUKjcG+70xj2Amm3NurZlNkK+V2ivpA+fcV0m+57PyQWkv+RvihLWkgcgAR93MrFuCNBea2c2FaHYXV/B0fbH8QBxnK6qmNo7T5W8UNsn3B8pv32vM7DL5G74WZpbu8h5IKa99/WB+lM/z5Gu+jpYfCCqeHfIBTqI5eQs6V28ikUFQXpF0eUwZLqKcoxSnhHPOBTd5j0oaKH8txuSz2Uz52ok28n0akxIM6tJO0liX/GBNkZvI8vq1JihavKbcDwR/G8XWppvZ/Sp4E+gb5YPw3s65HJ85M2spH5QmK3LDG695RPEC5iuR6HMWT7zlkW1qOefWxFl/IOSXv+gAYot8zVWxJJt9F+azdLN8k9Bbg9q1uM3EEyjI70qy1+m3Bv0FkWwefrfvKOfcWkm9zKy3/IBWreRbQv0tyFekSe4WSRXMrGSCwLS8/Pd3sgNwAb87+pQCuUWa/CQ9xcFBpG7wd3ycIPFMxTy9DZ6Ar5Z0StCMKlk75Ef1e1v+B3J4EJwmY7j8k/yE020k8B/5m52uZlZVfu7RSH/THIKmTq3kA7fnE7zmy98AX16APBREpAb47ug+XnHcG/x9PskbTcnfWOxTCspo0MQt0ucr4f6CvH0qqUrQpDhWy8LmJRApw+PilOHmOnAPU0fK96+qLj+ibrxamGiRAVCusDhThUQLmvpFtJNUQgWYCka+hlKKMx9yMDJq1djl8udxVYLm3a3jLJPyLlOR6xJvNOJE+0skUqser29mfqM4Jyuvc1ZEfhCZWJGmlfHWHShHJfg8tQr+Rs9hO1e+5urMXKnjK8xnKTK68wRJN5vZM9F9KvMStMhYKz+9ULxrHG2t/Pd0/aCvdaw/B3+T7YdZGPHKShn5gZU2yjellUL4jnLecufc00E+90nqGJUkUk5axW5rfh7qqpI+i23SDBxMCEqB3CLNhX6P/lGptj742yp6YTAoztAE2wyRv9EZaWalYrYzSzD/X1DL01W+WeDVkl4Mbvby8458U6QuSjzdRrz3+0V+oJEM+SH7K0h6I0E/pOxaVOfcNfFe8kP9R6dNtWfk+7/Vl/SKxcwRa2bFzM8BeZ587eTDUesqm5/zMNf8eIG/SSomaU4ytaRm9nDQzyveuu7yNaRr5UfQzUvkAcDj0dc6KCP35ZePJCUqwxXky+oBETygaSdfLh9JIv1iSf+Ub9Y80fy8pTkEn58u8p+RiC7yD1MmFCB7L8nXLt4TNKON7D9dUqIpG9ZLOtrMcvSlN7NeStzk+ydJVRMEH4muy6nyg8EUxEfB38stav5EMysrP7BNKrwv3xQ7y8xig42/yz98iPW0/AO3R4NgP4fgeiYbEBbEoJjzUFX+8+TkB2aLGCxfDp6KLgdR2xUxs+hBfAr1WQoezHSWH2G4t6QRBXj4OEQ+OBsZtA6Ifv+0yO9KENS9IP+9/kR02Qu+s+6TP+aRSb5vYdxoZsdHvb/Jf8ZLyA9QFAlAf5fvKDOra/EHGor0X43uMhEZ7OuRIJCO7KNYVJ6eT1XegAOB5rtAblPkfwQfMz/YxTZJcs5l3yyZ2cio9CcEfx8zs23Bv59zzs38HfIaa5J8H5deZnaM/NQBFeSDx8WK3+9vsHyz2AslrTKzcfLzyVWRb6b0lPwPcy7OuT1B09gX5ZvzFjOzy+IMwhC9zT4VIBiN8ax8M8IWUf/PIbhR7yF/Q5fwR9g5t8D8ABYNzM89mN/owQXinNtlfjCSt+QHw2htZu/KB38V5YfwryF/vTrE9HstIT9NwsNmNle+hnKTfL+hlvKB7mYlPy/k/5P0dzObL1/j8KN8H8Qm8td+l3yzzPxqav8vOJaOkj4NjqdksOxj+SbAydb2JvKufP/O64MapI/lz1dX+WlqtuWxbaE456YUcJM+8g9375A/HzPkayx2yNdMtJIP+D+QsstmB/lm60kfh3PuczN7WP4G/XMzez14j/ODJKvkB4uJNli+tv7jIP02+b6kzeTn7ow3UM5k+Yc175jZPAXTjzjn3pf/rPWS9O+gXH8t6Tj5oOVt+euT7PGsMLNIHj4ys0nyN9pd5ft410t2X3m8x24zu1r+WN83s+h5Ss8MjrVNzDZrzexS+eb2n5vvarBMPgCoJf+9U1R5zC35G6ySH0DpMzN7R/7zdLF8mR/g/Ki/kfx9bGY3SnpS0v/M7G35AY2KSaojX4O2Sv46Syn4LAXn8SL5pqo95fvJX5HXd3zgCfmppzrr19+VH+XP3dny07AMCtL2C5b1lK8xfV++PFws3+z0Hudc0gNyFcI0SfPN7LUgr3+Wr7lfpl+bw0u/33dUU0nPm9kc+e+VTfLnr4v8985jkYTOuXfNbLj8Z3Spmf1Xvo/rBfI1uxOUc/5h4ODjDoJ5aXjxKsxLwXxl+aRZHaSrHWfbqXHS/0X+x+WXePuPLMvj1fM3HEerRPmJShOZp3RoHmmOkr+B+Ek+2FgpP71ACfkf2sVxtjH5/kOz5If/3yM/T95oSfWi0uWYpzRqeZr8k1onH4QVC5Znz1OaxPHHnac0TrrI/J0rEqy/KFj/YRLveUOQ9sUCXqs85ymNSVtEvonwRPnBMPYE12ZacD4z4mxTVP4G5xn5m5Et8gHC1uD//5B0VAHye658kDIveO+98s3zlso/dDg+zja55ikNlpcK3v+boHytkh+Io1ZwTkYmOFcN4uwrcs0HxSyvJh8YbJQfzGSF/I1rccWZS1OFmKc0yfS55imNWV9f/oZvmfwN6W75WrrxwbUvGqQ7J3jfqwpS3qLe52r5Ea93yfctfV7+ZjjRtbpS/mHU7uC6vyN/oxv3fMk3qR8hP4jTvthrE2w7RT4g/jkoTz0SXcd8jqWUfHC1Ljie5fLT25RTzHyNv7UcBeuay49Iul3+czQhSJ/X/urKB+FfBnnbGZTzlyV1jEkbmae07G+4npuDa1dR/gHC+uD9PpfUK4/tGst/x38TXNvtQdl7TrnnZE3JZ0n+eywyndZ/JaUncXxp8n0eZ+vX35U1QX5OiUl7hKT+QTnYGaSfIqlTAa933HluY895orIl6Xr5z8zO4HoMk1Qhzn5S+h0VL9/yDxoi04Ftkf/e/kn+t6R9gv1cJd/M+2f5+5dP5R+a5bpe8fKZzOeNF68D9TLnYpvDAwBQMGbWUb4GvI9z7rH80h+OzOz/5JtBVnHOFXTEaxxizGyzpNXOuQZh5+VwFnSjuEVSQxdVMw3g90WfUgBA0szPbRu7rJx8LUGkphwxgv5pneSnUSIgBQAgCn1KAQAFMTIYpGSOfPOvavJ9TCtIesw5tyLMzB2snG+W9EccPA0AgAOOoBQAUBD/lR9M43L5+VV/lu+39Ixz7pUwMwYAAP6Y8u1TamYj5EcL3OCcyzXkfZCmlfyE48UkbXHOpWq+OgAAAADAISyZoLSl/JPwl+IFpcFcWZMltXHOrTezivSXAQAAAAAkI9/mu8656WZWO48kl0h63Tm3PkifVEBasWJFV7t2XrsFAAAAAPxRLViw4EfnXOxc2rmkok/pCZIUTPBeStIQ59zweAnNrLf8cPiqWbOm5s+fn4K3BwAAAAAcbMzs62TSpWJKmDT5CYfbSGot6W4zi9v31Dn3rHOusXOucaVK+QbMAAAAAIBDXCpqSr+RtM45t13SdjObJqmepMUp2DcAAAAA4BCWiprSdyQ1N7OiZlZS0pmSlqdgvwAAAACAQ1y+NaVmNkpSK0kVzWytpL6S0iXJOfe0c+4TM5so6bNg+fPOuU8OXJYBAAAAAIeKZEbf7Z5EmoHy85QCAAAAAJC0VDTfBQAAAADgNyEoBQAAAACEhqAUAAAAABCaVEwJAwAAcMjZtWuXNm7cqG3btmnfvn1hZwcAQlWkSBGVLl1a5cuXV0ZGRkr3TVAKAAAQY9euXVqzZo3KlSun2rVrKz09XWYWdrYAIBTOOe3Zs0dbt27VmjVrVLNmzZQGpjTfBQAAiLFx40aVK1dOFStWVLFixQhIARzWzEzFihVTxYoVVa5cOW3cuDGl+ycoBQAAiLFt2zZlZmaGnQ0AOOhkZmZq27ZtKd0nQSkAAECMffv2KT09PexsAMBBJz09PeX97AlKAQAA4qDJLgDkdiC+GwlKAQAAAAChISgFAAAAAISGoBQAAAApMXLkSJmZRo4cGXZWkmJmatWqVdjZAA57zFMKAABQQK/OWxN2FvJ06ek1U7Kfffv2acSIEXr55Zf1+eefa+vWrSpZsqRq1Kihhg0b6sILL1SXLl1S8l5/BJG+dGam//3vf6pTp07cdK1bt9bUqVMlSS+88IJ69uyZK8327ds1fPhwjRs3TosXL9bmzZtVsmRJ1a1bV+ecc46uvvpqHXPMMQfqUICDCkEpAAAActm3b586dOigiRMnqlKlSurUqZOqVaumHTt2aMmSJXrjjTe0evXqHEFply5ddMYZZ6hq1aoh5vzAKlq0qPbu3avnn39eAwYMyLX+f//7n6ZOnZqdLp65c+cqKytL3377rapXr67zzjtPRx11lHbs2KFFixZp4MCBGjhwoObOnatTTz31QB8SEDqCUgCFdrDXGAAHi1TVXgG/h1GjRmnixIlq0qSJPvjgA5UuXTrH+h07dmjevHk5lpUpU0ZlypT5PbP5u6tcubKqVq2qF154Qf3791fRojlvp5977jlJ0gUXXKA333wz1/bLly9Xu3bt9PPPP+vRRx/VHXfckWsfa9as0V133aWtW7ceuAMBDiL0KQUAAEAus2fPliT17NkzV0AqSSVLllTr1q1zLMurT+mkSZPUrFkzlSpVSuXLl1fnzp21ePFi9ezZU2am1atXZ6ddvXq1zEw9e/bU6tWrdckll6hixYoqXry4GjdurLfffjvX/rds2aKHHnpIZ511lipUqKCiRYuqUqVK6tixo+bMmVO4kxGjV69eWr9+fa587NmzRyNHjlTTpk110kknxd32pptu0tatW3X33Xfr7rvvzhWQSlLNmjU1evRonXnmmSnNN3CwIigFAABALsWLF5fkm6MW1ujRo9W+fXstXLhQF110ka699lpt2rRJzZs31xdffJFwu6+//lpNmjTRunXr1KtXL11xxRVavny5OnXqpClTpuRIu2zZMg0YMEAlSpRQjx491KdPH5133nmaPn2t+0UwAAAgAElEQVS6WrZsqYkTJxb6OCK6d++uUqVKZdeKRowbN04bNmxQr1694m731Vdf6YMPPlDx4sV111135fs+GRkZKckvcLCj+S4AAAByueiiizRo0CANGjRIP/zwg7p06aJGjRqpVq1aBdrPtm3bdP3116t48eKaM2eO6tevn73unnvuidsvM2Lq1Kl6/PHHdfvtt2cvu/zyy9WyZUsNHDgwR03tSSedpPXr1yszMzPHPtavX6/TTjtNt912m84999wC5T2R0qVL65JLLtHIkSO1du1aVa9eXZI0fPhwZWZm6uKLL457XDNnzpQkNWrUSGXLlk1JXoBDATWlAAAAyOXMM8/Uq6++qsqVK+vll1/WhRdeqNq1a6tChQrq0qWLxo8fn9R+xo4dq82bN+uqq67KEZBKUt++fVWhQoWE2x577LE5AlJJatGihY499lh99NFHOZZnZmbmCkglqUqVKurWrZuWL1+uNWtSNwZCr169skcnlnyt7vvvv6/LLrtMJUuWjLvNunXrJCk7iAXgEZQCAAAgrksuuURr1qzRpEmTdN9996lDhw4qUqSI3nrrLXXs2FE9evSQcy7PfSxcuFCSDyZjFStWTKeffnrCbRs3bhx3edWqVbVp06Zcy2fNmqWLL75YNWrUUEZGhsxMZqbHH39ckvTtt9/mmdeCOP300/WnP/1JI0aM0P79+/Xcc89p//79CZvuAkiM5rsAAABIKD09XW3btlXbtm0lSfv379fYsWN15ZVX6qWXXlKXLl3UuXPnhNtv2bJFkhI2Vy1XrlzCbRP1qUxLS9P+/ftzLHvzzTeVlZWl4sWL65xzzlGdOnVUqlQppaWlaerUqZo2bZp27dqV57EWVK9evXTzzTdrwoQJeuGFF9SoUSM1bNgwYfrIVDmpDI6BQwFBKQAAAJKWlpamLl26aMmSJbrvvvv04Ycf5hmURprUbt68Oe76RMsL6r777lOJEiX0+eef6+ijj86x7vbbb9e0adNS8j7RLr/8ct1999267rrr9O233+r+++/PM33z5s0lSfPnz9eWLVsO+elzgGTRfBcAAAAFFgk282u+G6k5nDFjRq51u3fv1ty5c1OSn5UrV6pevXq5AlJJuUbqTZWyZcsqKytLa9euValSpdS9e/c80x999NE6++yztXPnTg0cODDf/ae6Zhc4WBGUAgAAIJdRo0bp/fffz9VMVpJ+/PFHPfPMM5Kkli1b5rmfTp06qUyZMhoxYoQ+/fTTHOv69eunn376KSX5rVKlipYuXaoNGzbkWD5w4EAtWrQoJe8Rz0MPPaQ333xTkyZNijufa6whQ4YoMzNTjzzyiB5//HHt3bs3V5o1a9aoW7duKZ9fFThY0XwXAAAAucybN0+DBw9WlSpV1Lx5cx199NFKT0/XV199pXfffVdbtmxRp06dlJWVled+MjMz9dRTT+nyyy9X06ZNdfHFF6tq1aqaPXu2Fi1apObNm2vmzJlKSytcXcktt9yiO++8Uw0bNlRWVpZKlCihGTNmaOHChWrfvr0mTJhQqP0nUrNmTdWsWTPp9CeeeKImTZqkrKws3XnnnRo8eLDatGmjo446Stu3b9enn36qWbNmyczUp0+fA5Jn4GBDUAoAAIBcbr/9dtWoUUNTp07Vxx9/rHHjxsk5pwoVKqhp06a69NJLdemll8rM8t3XZZddpvLly+vBBx/Ua6+9poyMDLVs2VIzZ85U//79JSnudC4FcccddygjI0NDhw7VsGHDlJmZqRYtWmjmzJkaN27cAQtKf4szzjhDy5cv1/DhwzVu3Di988472rRpk0qWLKljjz1Wd9xxh3r37h23KTJwKLL8+gEcKI0bN3bz588P5b0BpNar81I37xtwKLv09ORrUxCuZcuW6cQTTww7G4c855yOPfZY7dixI3sOTwAHv2S/I81sgXMu/txOUehTCgAAgANqy5YtcQftGTRokL788kt16dIlhFwBOFjQfBcAAAAH1Jw5c/SXv/xF55xzjo455hjt2rVLs2bN0ty5c1WjRg098MADYWcRQIgISgEAAHBAHX/88WrVqpVmzpyp//73vzIzVa9eXTfffLP+3//7fzryyCPDziKAEBGUAgAA4IA6+uijNWbMmLCzAeAgRZ9SAAAAAEBoCEoBAAAAAKEhKAUAAAAAhIagFAAAAAAQGoJSAAAAAEBoCEoBAAAAAKEhKAUAAAAAhIagFAAAAAAQGoJSAAAAAEBoCEoBAABQYLVr11bt2rXDzsYfSs+ePWVmWr16ddhZwWFq6tSpMjM98MADYWclh6JhZwAAAOAPZ/wtYecgbxcMDjsHSTMznXXWWZo6dWrYWTks1K5dW19//XX2/9PS0lSqVClVq1ZNDRo0UIcOHZSVlaWMjIwQc4nDDUEpAAAAcJi55ZZbVLZsWe3fv19bt27VihUrNH78eI0ePVr33HOPRo8erTPOOCPsbOIwQVAKAAAAHGZuvfXWXM2vt2zZovvuu09PPvmkzj33XM2dO1cnnHBCOBnEYYU+pQAAAIjLOaehQ4fq5JNPVvHixVWtWjXdeOON2rJlS9z0W7Zs0UMPPaSzzjpLFSpUUNGiRVWpUiV17NhRc+bMyZF25MiRMjNJ0rRp02Rm2a/o/m7PPvusLrjgAlWvXl3p6enKzMxUs2bN9PLLLxfoWB544AGZWdxmwqtXr5aZqWfPnjmWR/cBfeaZZ/SnP/1JxYsXV+XKldW7d++E5+GDDz5QixYtVKpUKZUvX16dO3fW8uXL88zfvHnzlJWVpSpVqqhYsWKqUaOGrr32Wn333Xe50rZq1Upmpt27d6t///46/vjjlZGRkSv/BVWmTBkNGTJEV1xxhbZs2aI+ffrkWL9+/Xpdf/31qlWrlooVK6bixYvr2GOP1SWXXKIvvvgiqfeI9EXesmWLbr31VtWoUUPFihXTSSedpNdee02StGvXLt1///2qXbu20tPTVadOHQ0dOjTXvnbv3q3HH39cbdu2VeXKlZWenq7y5cvr7LPP1oQJE+K+/4IFC9S5c2cdeeSRKlq0qEqXLq369evrhhtu0J49e7LTbd26VXfffbeOO+44ZWRkKCMjQ7Vq1VLnzp01f/78pI41cp127dqle++9V0cffbQyMjJUp04d9evXT7t374673fLly9WzZ8/sc1O5cmVdeumlWrFiRa60K1as0K233qqGDRuqdOnSKlasmGrVqqXevXtr7dq1SeVTknbu3KmsrCyZmf76179q//79SW+bCvnWlJrZCEkdJG1wzp2SR7rTJM2RdIlzbkzqsggAAIAw3HrrrRoyZIiqVq2q3r17Kz09XWPHjtW8efO0e/duFStWLEf6ZcuWacCAAWrZsqV69OihkiVL6ptvvtHYsWM1YcIEjR8/Xueee64kqUGDBurbt6/69eunWrVq5QioWrVqlf3v2267TfXq1VPHjh1VoUIFbdq0Se+++64uv/xyrVixQg8++OABPw933XWXPvzwQ3Xt2lUXXHCBPvzwQw0fPlyrVq3Shx9+mCPtmDFj1K1bNxUrVkzdunVT1apVNXPmTJ155pmqV69e3P2PGDFCvXv3VunSpdW5c2cdddRR+vLLLzVy5EiNHz9ec+fOVc2aNXNtd+GFF2rhwoXq3LmzMjMzdeSRR6bkeO+//3699NJLevvtt7V161ZlZmZqx44dat68ub788kude+656t69u9LS0vTVV19pypQpWrZsmerUqZPU/nfv3q2zzz5bv/zyiy655BLt3LlTr7zyirp3765SpUpp2LBhWrJkiTp16qSiRYvqtdde00033aSSJUvqqquuyt7Pxo0b9fe//13NmjVTt27dVKZMGX3//fcaP368zjvvPA0fPlzXXHNNdvrPPvtMzZs3V1pamrp06aLatWtr586dWrZsmV566SX94x//UHp6upxzat++vWbPnq0WLVqoS5cuSk9P19q1azVt2jTNnTtXjRs3Tvp8Xnzxxfr444+VlZWV/Rl64IEHNH/+fI0bNy774YwkTZw4UV27dpUkderUScccc4zWrVun//znP3rnnXc0ZcoUnXrqqdnp33zzTb366qtq1aqV2rZtqyJFimjJkiUaMWKExo8fr/nz56tatWp55m/Tpk3q2LGjZs2apUceeSTXw4jfQzLNd0dKGirppUQJzKyIpMckvZeabAEAACBMs2fP1pAhQ1S3bl3NmTNH5cuXlyQ9/PDDOuecc7Ru3TrVqlUrxzYnnXSS1q9fr8zMzBzL169fr9NOO0233XZbjqC0QYMG6tevn2rXrp1wNNDly5erRo0aOZbt2bNHnTp10qOPPqrrrrsu35vuwlq4cKGWLFmiypUrS5L279+vdu3a6YMPPtBHH32kJk2aSJJ+/vlnXXvttUpPT9fMmTPVqFGj7H3ceeedevzxx3Pte+XKlbruuut04oknavLkyTkCy9mzZ6t169a65ZZb9Oabb+badt26dVq2bJlKly6d0uOtU6eOqlevrrVr12rBggVq3bq1Jk+erC+++EJ9+vTRI488kiP9vn37tGPHjqT3v27dOjVr1kyjR49WkSJFJElXXHGFmjRpou7du6t+/fpaunSpSpYsKck/HKlbt67++c9/5ghKy5Urp7Vr1+YKxrdt26azzjpLd911ly677DKVKFFCkvTiiy9q586dmjhxotq1a5djm61bt2a/3+LFizV79mxdcsklGjVqVI50zjlt3bo16WOV/DVesmSJypUrJ+nXz9Dbb7+tl19+WZdffrkkHxx2795d5cqV09SpU3Xcccdl76NPnz4644wzdM011+iTTz7JXt6jRw/deeedKlo0Z1g3ffp0tW7dWg899JCGDRuWMG9ff/212rdvr1WrVunf//63LrvssgIdW6rk23zXOTdd0sZ8kt0k6b+SNqQiUwAAAAjXCy+8IEnq169fdkAqScWLF48bXElSZmZmroBUkqpUqaJu3bpp+fLlWrNmTYHyERuQSlJ6erpuuOEG7d27V5MnTy7Q/n6Lvn37Zgekkh+xNlKz+9FHH2UvHzt2rDZu3KiePXvmCEgl6aGHHsoOSqINGzZMe/bs0aBBg3IFV02bNlWXLl00fvx4bdu2Lde2Dz/8cMoD0ohIoP/DDz9I8k1qJeWo1YsoUqRIgfPxr3/9KzsglaTTTjtNdevW1c8//6zHHnssO0CUfBlo2bKlli1bluM8ZGRkxK0dLl26tK666ipt2rRJH3/8cfbyvI4hMzNTaWlp+aYzM5UpU6ZAx/rggw/muPbRn6ERI0ZkL3/ppZe0efNm9e/fP0dAKkl169ZV7969tXDhQi1dujR7edWqVXMFpJLUsmVLNWzYUJMmTUqYr0WLFunMM8/Ut99+qwkTJoQWkEopGOjIzKpJ6iKptaTTCp0jAAAAhC5SG3PWWWflWnfaaaepVKlScbebNWuWBg8erDlz5mjDhg25+s19++23cZuiJrJmzRo99thjmjx5stasWaNffvkl1/4OtNNOy32LW7VqVUm+disir3NWvHhxnXHGGbn6Okb62n7wwQeaMWNGru2+++477du3TytXrswV6B7I0XGdc5KkvXv3SpLatGmjI488Uo8++qg+/fRTtW/fXmeeeaYaNGiQI7hMRuXKlVW9evW4y1euXBm3aWzkocDmzZtzBMBLlizRwIEDNX36dK1bt047d+7MsV10+ejWrZuGDRumrl27KisrS23atFHTpk1zNTtu0KCBTjzxRI0aNUrffvutLrjgAjVt2lSNGzfO1WQ9GXl9hhYuXJi9LFIW5s+fr2+++SbXNpFgdNmyZTrppJMk+ev0yiuvaOTIkfr000+1adMm7du3L3ubRPmdOXOmnnjiCZUuXVrTp09X/fr1C3xcqZSK0XcHSbrbObc/3tOEaGbWW1JvSQX6MgIAAMDvKzKIT3QtaYSZqWzZsrmWv/nmm8rKylLx4sV1zjnnqE6dOipVqpTS0tI0depUTZs2LbsWKhlffvmlmjRpok2bNqlFixZq27atypQpoyJFimj16tV68cUXC7S/3yrenJ2RWrXoACCvc5Zo+U8//SRJevTRR/PMw88//5xrWUFr7AoiMsBSJBgsV66c5syZowceeEBvv/223n33XUlSxYoVdcMNN+jee+9Venp6UvsuXrx43OWRc5rs+Z47d67+/Oc/a+/evWrTpo06duyYXeO5aNEijR07Nkf5aNGihSZPnqxHHnlEo0eP1osvvihJOv7449W3b191795dklS0aFFNnTpV/fv315gxYzR9+nRJvga2R48eGjBgQIFqhvP6DEUPZBUpC08//XSe+4suC7fffrsGDRqkqlWrql27dqpWrVp2c+WRI0fmmJM22sKFC7Vt2zY1bdr0oBhhORVBaWNJo4OAtKKk88xsr3PurdiEzrlnJT0rSY0bN3YpeG8AAAAcAJGAZ+PGjdm1ghHOOW3evFkVK1bMsfy+++5TiRIl9Pnnn+voo4/Ose7222/XtGnTCpSHJ554Qj/99JNef/11XXTRRTnWjRs3LjuoSEYkqInUAEaLrV37raLPWTzxlke22bJlS9ymz2FYtWqV1q5dq7S0NDVo0CB7+THHHKOXXnpJzjktXbpUH374oZ566in1799f27dv1z//+c/fNZ8PPfSQdu7cqblz52b3640YMmSIxo4dm2ubVq1aqVWrVtq1a5cWLFigiRMn6sknn9Sll16q0qVLq0OHDpKkI488UkOHDtXQoUO1atUqTZs2Tc8884yGDh2qdevWacyY5Md13bhxoypVqpRjWeQzFH3NI2Xh008/TTgoVrQNGzZoyJAhatSokWbMmJEdjEaMGzcuYVB64403asOGDXr66afVsWNHvfXWW7m2/z0VekoY59zRzrnazrnaksZIuiFeQAoAAIA/jsgIn/ECyY8//ljbt2/PtXzlypWqV69eroBUkqZMmRL3fdLS0uIGipH9SX4U0mT3l0ikT1+8KVai+x0WRl7nLBI8xYo0wY3XdDcs/fv3lyS1b99eFSpUyLXezHTyySfrpptu0vvvvy/JB0C/t5UrV6pKlSq5AlIp//KRkZGhpk2bqn///hoyZIikxMdw7LHH6uqrr9a0adN0xBFHaPz48QXKZ16foYYNG2YvK2hZWLVqlfbv36+2bdvmCih/+OEHLV68OOG2ZqZhw4bp1ltv1Xvvvafzzz8/7mf695JvUGpmo+SnejnezNaa2dVmdp2ZXXfgswcAAIAwRAby6du3b44avp07d+qOO+6Iu02VKlW0dOlSbdiQc+zLgQMHatGiRXG3qVChQsJ+oVWqVJGkXHOLzpgxI88RReOJBC4vvvhijjkYN2zYoH79+hVoX4l06tRJ5cqV08iRI7VgwYIc6+69994c/U8jbrzxRqWnp+u2226LOwjU/v37NW/evJTkLz9bt27VzTffrH//+9864ogjNHDgwOx1S5Ys0ffff59rm0iT5XiDOB1oVapU0ffff69ly5blWP7666/HrSWdPXt2rj7JUu5j+Oqrr/Tll1/mSrdt2zbt27cvbtP1vNx33305rn30Z+jKK6/MXn7llVeqbNmy6tevnz777LO4+4qe7zfy+ZgxY0aOZs27d+9W7969c8y7msi//vUv/f3vf9eUKVPUrl27Ao8snCr5Nt91znVPdmfOuZ6Fyg0AAAAOCs2aNdNNN92kJ598UqecckqOORbLlSuXq0mvJN1yyy2688471bBhQ2VlZalEiRKaMWOGFi5cqPbt2+ca5EfyA+iMHj1aXbt2VYMGDZSWlqaWLVuqZcuWuuGGGzRq1Ch17txZ3bp1U7Vq1bR06VKNGzdOnTp10htvvJH08Zx++ulq2bKl3n//fTVr1kytW7fWxo0bNWbMGLVp00ZffPFFoc6XJB1xxBF69tln1a1bNzVv3jzHPKWLFy9Wy5Yts/snRpxwwgkaMWKErrrqKp1wwgk6//zzddxxx2nfvn366quvNH36dJUtW1bLly8vdP6iDRo0SGXLls2e4mTFihWaPn26tm/frtq1a2vUqFE68cQTs9O///77+tvf/qZmzZqpfv36yszM1Hfffac33nhDaWlp+tvf/pbS/CXj5ptv1owZM7LnKS1XrpwWLFigyZMnq1OnTnrrrZyNN//xj3/oww8/VOvWrXX88cerWLFi2eWpXLly6t27tyTffLZr165q0qSJGjVqpPLly+vHH3/UW2+9pV9++UUPPfRQgfJZt25dnXzyyTk+Q1988YXOP//87OlgJP+AZsyYMerSpYsaNWqkdu3a6ZRTTpGZ6ZtvvtHMmTO1fv367ObmxxxzjDp06KC3335bp512mtq2baudO3dq/PjxMjPVq1cvYXAbbcCAASpevLj69u2rc845RxMnTvzdHzKkok8pAAAADkGDBw9W3bp19dRTT+mZZ55RhQoV1KVLFw0YMCDuaJ133HGHMjIyNHToUA0bNkyZmZlq0aKFZs6cqXHjxsUNSgcPHiwz0+TJkzV27Fjt379fffv2VcuWLbNHq+3bt69Gjx6tokWLqn79+ho1apQqVapUoKBU8lO2/O1vf9PYsWP1ySef6LjjjtOAAQPUtm1bvf7667/5PEXLysrSxIkT1a9fP73++uvKyMhQy5YtNWfOHD366KO5glJJ+stf/qL69evr8ccf15QpUzR27FgVKVJENWvW1LnnnqtLL700JXmLNnjwYEm+GWepUqVUvXp1XXDBBerQoYOysrJyDTbUtm1bffHFF5o1a5ZeeOEF7dixQ+XKlVOzZs10xx13qHXr1inPY36ysrI0evRoPfrooxoxYoRKlCihJk2aaNKkSfrmm29yBaXXXXedSpcurY8++kjvvfee9u7dq6OOOko9evTQPffco2OOOUaS1LhxY915552aPn26Xn31VW3dulWZmZk69dRT9dRTT6lr164Fyufrr7+uBx98UK+88oq+++47VatWTQ888ID69OmTa9qZNm3a6LPPPtM///lPTZo0SR988IGcc6pWrZpOP/10XXjhhTnSjx49Wvfcc49ef/11PfHEE6pcubI6dOigfv366eKLL046j/fff79KlCihu+66S23atNF7772Xq8/4gWSJ2vAfaI0bN3bz588P5b0BpNar8wo25xxwuLr0dEae/6NYtmxZjloiACioVq1aadq0aQn7TP+RJfsdaWYLnHO55/iJUeiBjgAAAAAA+K0ISgEAAAAAoSEoBQAAAACEhoGOAAAAACDFYqcyQmLUlAIAAAAAQkNQCgAAAAAIDUEpAAAAACA0BKUAAABxHIpzCwJAYR2I70aCUgAAgBhFihTRnj17ws4GABx09uzZoyJFiqR0nwSlAAAAMUqXLq2tW7eGnQ0AOOhs3bpVpUuXTuk+CUoBAABilC9fXps2bdKPP/6o3bt305QXwGHNOafdu3frxx9/1KZNm1S+fPmU7p95SgEAAGJkZGSoZs2a2rhxo1avXq19+/aFnSUACFWRIkVUunRp1axZUxkZGSndN0EpAABAHBkZGapataqqVq0adlYA4JBG810AAAAAQGgISgEAAAAAoSEoBQAAAACEhqAUAAAAABAaglIAAAAAQGgISgEAAAAAoSEoBQAAAACEhqAUAAAAABAaglIAAAAAQGgISgEAAAAAoSEoBQAAAACEhqAUAAAAABAaglIAAAAAQGgISgEAAAAAoSEoBQAAAACEhqAUAAAAABAaglIAAAAAQGgISgEAAAAAoSEoBQAAAACEhqAUAAAAABAaglIAAAAAQGgISgEAAAAAoSEoBQAAAACEhqAUAAAAABAaglIAAAAAQGgISgEAAAAAoSEoBQAAAACEhqAUAAAAABAaglIAAAAAQGgISgEAAAAAock3KDWzEWa2wcwWJ1h/uZl9bmaLzWyBmTVOfTYBAAAAAIeiZGpKR0o6N4/1KyU1d86dIuleSc+lIF8AAAAAgMNA0fwSOOemm1ntPNbPi/rvTEnVCp8tAAAAAMDhINV9Sq+VNC7F+wQAAAAAHKLyrSlNlpm1knS1pOZ5pOktqbck1axZM1VvDQAAAAD4g0pJTamZ1ZP0vKROzrmfEqVzzj3rnGvsnGtcqVKlVLw1AAAAAOAPrNBBqZnVlPSGpMudcysLnyUAAAAAwOEi3+a7ZjZKUitJFc1sraS+ktIlyTn3tKT7JVWQ9H9mJkl7nXNMCwMAAAAAyFcyo+92z2f9NZKuSVmOAAAAAACHjVSPvgsAAAAAQNIISgEAAAAAoSEoBQAAAACEhqAUAAAAABAaglIAAAAAQGgISgEAAAAAoSEoBQAAAACEhqAUAAAAABAaglIAAAAAQGgISgEAAAAAoSEoBQAAAACEhqAUAAAAABAaglIAAAAAQGgISgEAAAAAoSEoBQAAAACEhqAUAAAAABAaglIAAAAAQGgISgEAAAAAoSEoBQAAAACEhqAUAAAAABAaglIAAAAAQGgISgEAAAAAoSEoBQAAAACEhqAUAAAAABAaglIAAAAAQGgISgEAAAAAoSEoBQAAAACEhqAUAAAAABAaglIAAAAAQGgISgEAAAAAoSEoBQAAAACEhqAUAAAAABAaglIAAAAAQGgISgEAAAAAoSEoBQAAAACEhqAUAAAAABAaglIAAAAAQGgISgEAAAAAoSEoBQAAAACEhqAUAAAAABAaglIAAAAAQGgISgEAAAAAoSEoBQAAAACEpmjYGQAAAAByGH9L2DkADn4XDA47BylDTSkAAAAAIDT5BqVmNsLMNpjZ4gTrzcyGmNlSM1toZqemPpsAAAAAgENRMjWlIyWdm8f6rpJqSTpZ0tWSXih8tgAAAAAAh4N8g1Ln3HRJG/NIcr6kl533iaSiZlYjVRkEAAAAABy6UtGntLqkb6L+vzZYBgAAAABAnn7XgY7MrLeZzTez+T/88MPv+dYAAAAAgINQKoLStZKim+tWD5bl4px71jnX2DnXuNAYdOMAABKsSURBVFKlSil4awAAAADAH1kqgtJ3JV0mScHIu/udc9/kvQkAAAAAAFLR/BKY2ShJrSRVNLO1kvpKSpck59zTkv4rqbWZLZW0W9KVByy3AAAAAIBDSr5BqXOuez7rnaS/pixHAAAAAIDDxu860BEAAAAAANHyrSkFgPyctrhf2FkA/hhOfz7sHAAAcNChphQAAAAAEBqCUgAAAABAaAhKAQAAAAChISgFAAAAAISGoBQAAAAAEBqCUgAAAABAaAhKAQAAAAChISgFAAAAAISGoBQAAAAAEBqCUgAAAABAaAhKAQAAAAChISgFAAAAAISGoBQAAAAAEBqCUgAAAABAaAhKAQAAAAChISgFAAAAAISGoBQAAAAAEBqCUgAAAABAaAhKAQAAAAChISgFAAAAAISGoBQAAAAAEBqCUgAAAABAaAhKAQAAAAChISgFAAAAAISGoBQAAAAAEBqCUgAAAABAaAhKAQAAAAChISgFAAAAAISGoBQAAAAAEBqCUgAAAABAaAhKAQAAAAChISgFAAAAAISGoBQAAAAAEBqCUgAAAABAaAhKAQAAAAChISgFAAAAAISGoBQAAAAAEBqCUgAAAABAaAhKAQAAAAChISgFAAAAAISGoBQAAAAAEBqCUgAAAABAaAhKAQAAAAChSSooNbNzzWyxmS0zsz5x1lcxs8lmttTMVprZdanPKgAAAADgUJNvUGpmGZKeltReUj1JWfb/27v/WMnOsg7g30d2beSHRugCwt2iJiYGm6apSxoCaAkktmyMQYgFoYkILm2Q+CMaqkYk+o+GaEwV3FRAE9dgFQgQ3NJiiBIMUC+ltNsWi0birrp0waQRTG1rH/+YWZledvfOvZ277+zs55NM9vx4z8x759lz3nznnDlTddmGZj+bZL27n5vkBUl+u6q+bdGdBQAAYLXMc6b08iR3d/fR7n44yU1J9m9ocyzJU6qqkjw5yVeS/M9CewoAAMDKmSeUriU5OjN/bLps1h8neW6Sf09yV5Kf6+5HF9JDAAAAVtaibnT0K0nuTPKsJJcm+cOq+vaNjarqQFWtV9X6iRMnFvTSAAAAnKvmCaXHkuydmV+bLpv1oiR/1RP/lORfMjlz+hjdfWN37+vufXv27NlunwEAAFgR84TS25JcXFVrVbU7ydVJbt7Q5p+TvCRJquoZmQTSLy2wnwAAAKygXZs16O4Hq+q6JLdkEmIPdff6yZ996e6DSX4zyaGqujfJE5L8encf38F+AwAAsAI2DaVJ0t2HkxzesOzgzPTxJC9dbNcAAABYdYu60REAAABsmVAKAADAMEIpAAAAwwilAAAADCOUAgAAMIxQCgAAwDBCKQAAAMMIpQAAAAwjlAIAADCMUAoAAMAwQikAAADDCKUAAAAMI5QCAAAwjFAKAADAMEIpAAAAwwilAAAADCOUAgAAMIxQCgAAwDBCKQAAAMMIpQAAAAwjlAIAADCMUAoAAMAwQikAAADDCKUAAAAMI5QCAAAwjFAKAADAMEIpAAAAwwilAAAADCOUAgAAMIxQCgAAwDBCKQAAAMMIpQAAAAwjlAIAADCMUAoAAMAwQikAAADDCKUAAAAMI5QCAAAwjFAKAADAMEIpAAAAwwilAAAADCOUAgAAMIxQCgAAwDBCKQAAAMMIpQAAAAwjlAIAADCMUAoAAMAwc4XSqrqyqo5U1b1Vdf1p2lxRVf9QVZ+vqk8stpsAAACsol2bNaiqC5IcTPKiJMeTfKqqbu3u22faPDPJO5K8pLuPV9WFO9VhAAAAVsc8Z0ovT3J3dx/t7oeT3JRk/4Y2r0ryl919PEm6+yuL7SYAAACraJ5Qupbk6Mz8semyWd+f5Luq6tNVdVdV/cypnqiqDlTVelWtnzhxYns9BgAAYGUs6kZH35Lk0iQvSfLiJG+pqos3NuruG7t7X3fv27Nnz4JeGgAAgHPVpt8pzeTM6N6Z+bXpsllHk/xHd389yder6u+SXJLkyEJ6CQAAwEqa50zpbUkurqq1qtqd5OokN29o89dJXlhVu6rqiUmen+QLi+0qAAAAq2bTM6Xd/WBVXZfklkxC7KHuXq+qa6frD3b37VX10SR3Jtmd5N2zd+cFAACAU5nn8t109+EkhzcsO7hh/u1J3r64rgEAALDqFnWjIwAAANgyoRQAAIBhhFIAAACGEUoBAAAYRigFAABgGKEUAACAYYRSAAAAhhFKAQAAGEYoBQAAYBihFAAAgGGEUgAAAIYRSgEAABhGKAUAAGAYoRQAAIBhhFIAAACGEUoBAAAYRigFAABgGKEUAACAYYRSAAAAhhFKAQAAGEYoBQAAYBihFAAAgGGEUgAAAIYRSgEAABhGKAUAAGAYoRQAAIBhhFIAAACGEUoBAAAYRigFAABgmF2jOwAAALO+eP/XRncBlt73je7AAjlTCgAAwDBCKQAAAMMIpQAAAAwjlAIAADCMUAoAAMAwQikAAADDCKUAAAAMI5QCAAAwjFAKAADAMEIpAAAAwwilAAAADCOUAgAAMIxQCgAAwDBCKQAAAMMIpQAAAAwzVyitqiur6khV3VtV15+h3fOq6pGqeuXiuggAAMCq2jSUVtUFSQ4muSrJJUleWVWXnaLdE5L8TpJbF91JAAAAVtM8Z0ovT3J3dx/t7oeT3JRk/ynavTnJ+5Pcv8D+AQAAsMLmCaVrSY7OzB+bLvt/VfXsJC9P8kdneqKqOlBV61W1fuLEia32FQAAgBWzqBsd/X6St3T3o2dq1N03dve+7t63Z8+eBb00AAAA56pdc7Q5lmTvzPzadNmsfUn+oqqS5MIkL6uqR7r7gwvpJQAAACtpnlB6W5KLq2otyZeTXJ3k2tkG3f09J6er6k+TfEQgBQAAYDObhtLufrCqrktySyaX+x7q7vWquna6/uAO9xEAAIAVNc+Z0nT34SSHNyw7ZRjt7p96/N0CAADgfLCoGx0BAADAlgmlAAAADCOUAgAAMIxQCgAAwDBCKQAAAMMIpQAAAAwjlAIAADCMUAoAAMAwQikAAADDCKUAAAAMI5QCAAAwjFAKAADAMEIpAAAAwwilAAAADCOUAgAAMIxQCgAAwDBCKQAAAMMIpQAAAAwjlAIAADCMUAoAAMAwQikAAADDCKUAAAAMI5QCAAAwjFAKAADAMEIpAAAAwwilAAAADCOUAgAAMIxQCgAAwDBCKQAAAMMIpQAAAAwjlAIAADCMUAoAAMAwQikAAADDCKUAAAAMI5QCAAAwjFAKAADAMEIpAAAAwwilAAAADCOUAgAAMIxQCgAAwDBCKQAAAMMIpQAAAAwjlAIAADCMUAoAAMAwQikAAADDzBVKq+rKqjpSVfdW1fWnWH9NVd01bfPZqtq3+K4CAACwanZt1qCqLkhyMMmLkhxP8qmqurW7b59pdl+SF3b3A1V1VZJ3Jbl0JzoMAADA6pjnTOnlSe7u7qPd/XCSm5Lsn23Q3Z/p7gems59M8uzFdhMAAIBVNE8oXUtydGb+2HTZ6bwxyYcfT6cAAAA4P2x6+e5WVNUVSV6f5IWnWX8gyYEkueiiixb50gAAAJyD5jlTeizJ3pn5temyx6iqS5K8O8mPdfdXT/VE3X1jd+/r7n179uzZTn8BAABYIfOE0tuSXFxVa1W1O8nVSW6ebVBVFyX5QJJruvu+xXcTAACAVbTp5bvd/WBVXZfklkxC7KHuXq+qa6frDyZ5a5KnJXlnVSXJI93tZ2EAAAA4o7m+U9rdh5Mc3rDs4Mz0G5K8YbFdAwAAYNXNc/kuAAAA7AihFAAAgGGEUgAAAIYRSgEAABhGKAUAAGAYoRQAAIBhhFIAAACGEUoBAAAYRigFAABgGKEUAACAYYRSAAAAhhFKAQAAGEYoBQAAYBihFAAAgGGEUgAAAIYRSgEAABhGKAUAAGAYoRQAAIBhhFIAAACGEUoBAAAYRigFAABgGKEUAACAYYRSAAAAhhFKAQAAGEYoBQAAYBihFAAAgGGEUgAAAIYRSgEAABhGKAUAAGAYoRQAAIBhhFIAAACGEUoBAAAYRigFAABgGKEUAACAYYRSAAAAhhFKAQAAGEYoBQAAYBihFAAAgGGEUgAAAIYRSgEAABhGKAUAAGAYoRQAAIBhhFIAAACGEUoBAAAYRigFAABgmLlCaVVdWVVHqureqrr+FOurqm6oqnuq6nNVddniuwoAAMCq2TSUVtUFSQ4muSrJJUleeYrQ+eNJnpPkB5K8PsmfLLifAAAArKB5zpRenuTu7j7a3Q8nuSnJ/g1t9ic51BO3J9lVVXsX3FcAAABWzDyhdC3J0Zn5Y9NlW20DAAAAj7HrbL5YVR1IcmA6+7Wq+sez+frbcGGSr4zuBI+hJstJXZaPmiyjN7xHXZaPmiwndVk+arJszo0x5TnzNJonlB5LMnsp7tp02anafPoMbdLdNya5cZ6OLYOqWu/ufaP7wTeoyXJSl+WjJstJXZaPmiwndVk+arJ8Vqkm81y+e1uSi6tqrap2J7k6yc0b2hxO8pokmd4E6dHuPhoAAAA4g03PlHb3g1V1XZJbMgmxh7p7vaquna4/mOT9SV5cVfckeSjJ63awzwAAAKyIub5T2t2HMzkbOrvs4Mx0J3nTYru2FM6ZS43PI2qynNRl+ajJclKX5aMmy0ldlo+aLJ+VqUlN8iQAAACcffN8pxQAAAB2xHkfSqvqqVX1saq6q6purarvPE27L03b3FFV61vdnvnN855W1d6q+kRVHamq+6rqLTPr3lZV/zat1R1V9bKz+xesjqq6cvoe31tV159ifVXVDVV1T1V9bnqjs7m2ZfvmqMs10/3nSFV9tqr2zaw75bGMx2eOmlxRVQ/MHJfeOu+2bM8cNfnlmXocqar/raqnTtfZT3ZAVb2nqu6vqiOnWW9MGWCOuhhTzrI5arJ6Y0p3n9ePJH+Q5Ben07+Q5IbTtPtSkgu3u73HYmuS5JlJLplOPyXJF5NcOp1/W5JfGv13nOuPJBdM/9/vTbI7yXqSyza0eUWSDyWpJJcl+fy823rsaF0uT/Id0+mrktwxs+6UxzKPHa/JFUk+sp1tPXamJhva/2iSj8/M2092pi4/NB0rjpxmvTFlOetiTFm+mqzcmHLenylNsj/Jn02nD03nz+b2fLNN39PuPt7dd06n/yvJnUmefdZ6eH64PMnd3X20ux9OclO+uRb7M7kjd3f37Ul2VdXeObdlezZ9b7v7M939wHT2k7Fv7LTH8//dvrIztvq+vjrJe89Kz85j3f2JJP95hibGlAE2q4sx5eybY185nXN2XxFKkz3dfSJJpv8+/TTtOsnJS0rfvI3tmd+W3tOq+u4kz8vkQHnSm6rqC1X151X1tJ3q6IpbSzL7e8PHpsvmaTPPtmzPVt/bNyb58Mz86Y5lbN+8NXn+9JKqj1fVpVvclq2Z+32tqicmuTKTn7c7yX4yhjFl+RlTlsdKjSlz/STMua6q/iaTyz03+rUtPM3zu/t4VT09yUer6gvd/bHF9PD8s6CapKqenOR9SX5+5lO8dyT5rUwOlG9LckOS12y7s3COqqorkrw+yQtnFjuWjfHZJHu7+7+r6keSfLCqvnd0p0gyuXT377t79qyE/QQ2MKYslZUbU86LUNrdLz3duqo6UVV7uvtEVe1Jcv9pnuP49N/7q+p9mZyZ+1iSubbnsRZRk6ranckn2+/t7g/MPPeJmTYHk/ztwjp+fjmWyXcSTlqbLjtVm09vaLN7jm3Znnnqkqq6JMm7k1zV3V89ufwMxzK2b9OaTL9mcHL6lqp6KJMP5uaqJ1u2lff1Vdlw6a79ZBhjypIypiyXVRxTXL6bHE7y2un0a5PcvLFBVT1penlPqupJmVzmc8+827Nl89SkMjk43tvdv7th3ezlvq/IN2rF1tyW5OKqWpt+AHB1vrkWhzM9Cz29S+Kj3X10zm3Znk3f26q6KMkHklzT3ffNLD/TsYztm6cme2amfzDJkzP5wM2+sjPmel+r6juS/HAmN9c5ucx+Mo4xZQkZU5bPKo4p58WZ0k38RpKbquqnk3w5yU8kSVU9K8m7uvtlSZ6RyWnxTvLETL40/KEzbc/jMk9NXpDkmiR3VdUd0+1+tbsPJ/m96Sd635rkXzO51IQt6u4Hq+q6JLdk8gHWoe5er6prp+sPZnKm+sVVdU+Sh5K87kzbjvg7Vs2cdXlrkqcleefk85s80t37cuZjGds0Z01eXVUHpps8lOQnu/uRJI/YVxZvzpokycuT3NrdX5/Z3H6yQ6rqvZncNfTCqjqWyXi/OzGmjDRHXYwpZ9kcNVm5MaV6cvtgAAAAOOtcvgsAAMAwQikAAADDCKUAAAAMI5QCAAAwjFAKAADAMEIpAAAAwwilAAAADCOUAgAAMMz/ARw+/7jAbtweAAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 1152x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"a=[h_mc.GetBinContent(i) for i in range(nbins)]\n",
"b=[h_mc.GetBinCenter(i) for i in range(nbins)]\n",
"c=[h_data_under.GetBinContent(i) for i in range(nbins)]\n",
"d=[h_data_under.GetBinCenter(i) for i in range(nbins)]\n",
"plt.title(\"Hlt1 TrackMVA TOS Signal MC/ data under peak comparison\", fontsize=20)\n",
"\n",
"plt.bar(b,a,width=0.5,alpha=0.4,label=\"Signal MC\")\n",
"plt.bar(d,c,width=0.5, alpha=0.6, label=\"data under Ds mass peak\")\n",
"plt.legend(fontsize=20)\n",
"fig = plt.gcf()\n",
"fig.set_size_inches(16,8)"
]
},
{
"cell_type": "code",
"execution_count": 53,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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rd5N8871IGY4uINWUWsMkXSqpu5kNkS8301z8Zpqp0F7+9zfZ/qSnBn9jgys551aY2Vr5YCoHM2sk3xKimXwzwdjph6opaEKZDDOrIl8D1lb+eyP2PVN9XeJJthzldc72mtl0+a4D0c4M/jY3sz/FeZ9jgr8nytfgRUv4nZyP7xN8nqYEfxvG5M9J6mBx+lrK14KXlFRTvra3MJ+lq+TL6QJJF7gk+q9HmFk1+Yce84MAJ6+0NeRHI/84eEAUa1Lwt2GcdfFGHo/kc6GLGRjPObfNzH5RzPdNlHhlZbP5aZLOVFT3h0Kc14KUk5nyTc5vMLPj5B/ezpL0afRDjECkvOcawM85t8TM1kmqZ2ZpMQ/CvkzwQDf6M1XgB2/A70FQChyc4k17EgkcxsrXEqyQ7+vyg/xTaMnfUEbfmEamsilo38pm8s32ZiQTkEYZLt989lr5p8lOeddGScr+UZ0ZvG9L+T5DJ8nfKCx1zsULiLpIqijfLDN2wJ4X5fsL9dJv/blS6Qf5Y8sws0p51ZYGfXojNS+5piUJblhXRqWvKd9/6nxJ/yd/PpIS3CC+ELwiU9b8Q7425kUzOyYq4I9VSv43I9F8nfFubKLF618VuTkqElkQlOH35K/Pcvkm4Ov1WxnurdzBVWFNlj/H18jXWldU4j7KEWvla0t/TyDWRb554aT8EgYiLT0S1cRtUEyAaGbnyJ/HvfJ9Zd+Urz3aJ9+cvq0KcB6DgPRT+eB2lvw52yRfG1ZFvjY+1dclnqTKkZI7Z7EiA9rclk8e4g0QFPc7OQn55S+6lU8F+cAnr+mxpCB/hfwsNZd/mDm9IAFpoCC/K/ldp0igGm/atR1xlkXKQqJ+svuUs5xES+paFPK8Jl1OnHO/mllz+dZenfTbtFIbzex5+ebJkXNQRtIO59z2BLv7Wf5zWjomD3mdJynxuQJSjqAUOLScLR+QjpJ0WXSAEQQ/vWPSRwKMuCN45uF2+alVbgr2e1MewUw259waMxsvXyu1R9KHzrmvk3zP5+SD0p7yN8QJa0kDkQGOuppZ1wRpLjKzWwrR7C6u4On6IvmBOM5RVE1tHKfL3yhslO8PlN++V5vZ5fI3fGeZWbrLeyClvPb1o/lRPs+Xr/k6Wn4gqHi2ywc4iebkLehcvYlEBkF5VdIVMWW4iHKOUpwSzjkX3OQ9JmmA/LUYnc9mM+RrJ1rL92lMSjCoS1tJY1zygzVFbiLL67eaoGjxmnI/GPxtFFubbmYPqOBNoG+SD8J7OedyfObMrIV8UJqsyA1vvOYRxQuYr0Siz1k88ZZHtqnlnFsdZ/3+kF/+ogOIzfI1V8WSbPZdmM/SLfJNQm8LatfiNhNPoCC/K8lep98b9BdEsnn4w76jnHNrJPU0s17yA1q1lG8J9bcgX5EmuZslVTCzkgkC0/Ly39/JDsAF/OHoUwrkFmnyk/QUBweQusHfcXGCxDMV8/Q2eAK+StIpQTOqZG2XH9XvHfkfyGFBcJqMYfJP8hNOt5HAf+RvdrqYWVX5uUcj/U1zCJo6tZQP3F5I8JonfwN8RQHyUBCRGuB7ovt4xXFf8PeFJG80JX9jsVcpKKNBE7dIn6+E+wvy9pmkKkGT4lgtCpuXQKQMj41Thptr/z1MHSHfv6q6/Ii68WphokUGQLnS4kwVEi1o6hfRVlIJFWAqGPkaSinOfMjByKhVY5fLn8eVCZp3t4qzTMq7TEWuS7zRiBPtL5FIrXq8vpn5jeKcrLzOWRH5QWRiRZpWxlu3vxyV4PPUMvgbPYftHPmaqzNzpY6vMJ+lyOjO4yXdYmbPRvepzEvQImON/PRC8a5xtDXy39P1g77Wsf4c/E22H2ZhxCsrZeQHVtog35RWCuE7ynnLnHPPBPncK6lDVJJIOWkZu635eairSvo8tkkzcCAhKAVyizQX+iP6R6XauuBvy+iFwaA4QxJsM1j+RmeEmZWK2c4swfx/QS1PF/lmgddIeim42cvPu/JNkTor8XQb8d7vV/mBRjLkh+yvIOnNBP2QsmtRnXPXxnvJD/UfnTbVnpXv/1Zf0qsWM0esmRUzPwfk+fK1k49Eratsfs7DXPPjBf4mqZik2cnUkprZI0E/r3jrusnXkK6RH0E3L5EHAE9EX+ugjNyfXz6SlKgMV5Avq/tF8ICmrXy5fDSJ9Isk/VO+WfME8/OW5hB8fjrLf0YiOss/TBlfgOy9LF+7eG/QjDay/3RJiaZsWCfpaDPL0ZfezHoqcZPvnyVVTRB8JLoup8oPBlMQHwd/r7Co+RPNrKz8wDap8IF8U+wsM4sNNv4u//Ah1jPyD9weC4L9HILrmWxAWBADY85DVfnPk5MfmC1ikHw5eDq6HERtV8TMogfxKdRnKXgw00l+hOFekoYX4OHjYPngbETQOiD6/dMivytBUPei/Pf6k9FlL/jOul/+mEck+b6FcZOZHR/1/ib/GS8hP0BRJAD9Q76jzKyuxR9oKNJ/NbrLRGSwr0eDQDqyj2JReXohVXkD9gea7wK5TZb/EXzc/GAXWyXJOZd9s2RmI6LSnxD8fdzMtgb/ft45N+MPyGusifJ9XHqa2THyUwdUkA8eFyl+v79B8s1iL5K00szGys8nV0W+mdLT8j/MuTjndgdNY1+Sb85bzMwujzMIQ/Q2e1WAYDTGc/LNCM+K+n8OwY16d/kbuoQ/ws65+eYHsGhgfu7B/EYPLhDn3E7zg5G8LT8YRisze08++KsoP4R/Dfnr1T6m32sJ+WkSHjGzOfI1lBvl+w21kA90Nyn5eSH/n6S/m9k8+RqHn+T7IDaRv/Y75Ztl5ldT+3/BsXSQ9FlwPCWDZZ/INwFOtrY3kffk+3feENQgfSJ/vrrIT1OzNY9tC8U5N7mAm/SWf7h7p/z5mC5fY7FdvmaipXzA/6GUXTbbyzdbT/o4nHNfmNkj8jfoX5jZG8F7XBAkWSk/WEy0QfK19Z8E6bfK9yVtJj93Z7yBcibJP6x518zmKph+xDn3gfxnraekfwfl+htJx8kHLe/IX59kj2e5mUXy8LGZTZS/0e4i38e7XrL7yuM9dpnZNfLH+oGZRc9TemZwrK1jtlljZpfJN7f/wnxXg6XyAUAt+e+dospjbsnfYaX8AEqfm9m78p+nS+TLfH/nR/2N5O8TM7tJ0lOS/mdm78gPaFRMUh35GrSV8tdZSsFnKTiPF8s3Ve0h30/+yry+4wNPyk891Um//a78JH/uzpGfhmVgkLZvsKyHfI3pB/Ll4RL5Zqf3OueSHpCrEKZKmmdmrwd5/bN8zf1S/dYcXvrjvqOaSnrBzGbLf69slD9/neW/dx6PJHTOvWdmw+Q/o0vM7L/yfVwvlK/ZHa+c8w8DBx53AMxLw4tXYV4K5ivLJ82qIF3tONtOiZP+L/I/Lr/G239kWR6vHr/jOFomyk9Umsg8pUPySHOU/A3Ez/LBxgr56QVKyP/QLoqzjcn3H5opP/z/bvl58kZJqheVLsc8pVHL0+Sf1Dr5IKxYsDx7ntIkjj/uPKVx0kXm71yeYP3FwfqPknjPG4O0LxXwWuU5T2lM2iLyTYQnyA+GsTu4NlOD85kRZ5ui8jc4z8rfjGyWDxC2BP//h6SjCpDf8+SDlLnBe++Rb563RP6hw/Fxtsk1T2mwvFTw/t8G5Wul/EActYJzMiLBuWoQZ1+Raz4wZnk1+cBgg/xgJsvlb1yLK85cmirEPKVJps81T2nM+vryN3xL5W9Id8nX0o0Lrn3RIN25wfteXZDyFvU+18iPeL1Tvm/pC/I3w4mu1VXyD6N2Bdf9Xfkb3bjnS75J/XD5QZz2xl6bYNvJ8gHxL0F56p7oOuZzLKXkg6u1wfEsk5/eppxi5mv8veUoWNdcfkTSbfKfo/FB+rz2V1c+CP8qyNuOoJy/IqlDTNrIPKVlf8f13BRcu4ryDxDWBe/3haSeeWzXWP47/tvg2m4Lyt7zyj0na0o+S/LfY5HptP4rKT2J40uT7/M4S7/9rqwO8nNKTNojJPULysGOIP1kSR0LeL3jznMbe84TlS1JN8h/ZnYE12OopApx9pPS76h4+ZZ/0BCZDmyz/Pf2z/K/Je0S7Odq+Wbev8jfv3wm/9As1/WKl89kPm+8eO2vlzkX2xweAICCMbMO8jXgvZ1zj+eX/nBkZv8n3wyyinOuoCNe4xBjZpskrXLONQg7L4ezoBvFrZIauqiaaQB/LPqUAgCSZn5u29hl5eRrCSI15YgR9E/rKD+NEgEpAABR6FMKACiIEcEgJbPlm39Vk+9jWkHS48655WFm7kDlfLOkg3HwNAAA9juCUgBAQfxXfjCNK+TnV/1Fvt/Ss865V8PMGAAAODjl26fUzIbLjxa43jmXa8j7IE1L+QnHi0na7JxL1Xx1AAAAAIBDWDJBaQv5J+EvxwtKg7myJklq7ZxbZ2YV6S8DAAAAAEhGvs13nXPTzKx2HkkulfSGc25dkD6pgLRixYqudu28dgsAAAAAOFjNnz//J+dc7FzauaSiT+kJkhRM8F5K0mDn3LB4Cc2sl/xw+KpZs6bmzZuXgrcHAAAAABxozOybZNKlYkqYNPkJh1tLaiXpHjOL2/fUOfecc66xc65xpUr5BswAAAAAgENcKmpKv5W01jm3TdI2M5sqqZ6kRSnYNwAAAADgEJaKmtJ3JTU3s6JmVlLSmZKWpWC/AAAAAIBDXL41pWY2UlJLSRXNbI2kPpLSJck594xz7lMzmyDp82D5C865T/dflgEAAAAAh4pkRt/tlkSaAfLzlAIAAAAAkLRUNN8FAAAAAOB3ISgFAAAAAISGoBQAAAAAEJpUTAkDAABwyNm5c6c2bNigrVu3au/evWFnBwBCVaRIEZUuXVrly5dXRkZGSvdNUAoAABBj586dWr16tcqVK6fatWsrPT1dZhZ2tgAgFM457d69W1u2bNHq1atVs2bNlAamNN8FAACIsWHDBpUrV04VK1ZUsWLFCEgBHNbMTMWKFVPFihVVrlw5bdiwIaX7JygFAACIsXXrVmVmZoadDQA44GRmZmrr1q0p3SdBKQAAQIy9e/cqPT097GwAwAEnPT095f3sCUoBAADioMkuAOS2P74bCUoBAAAAAKEhKAUAAAAAhIagFAAAACkxYsQImZlGjBgRdlaSYmZq2bJl2NkADnvMUwoAAFBAr81dHXYW8nTZ6TVTsp+9e/dq+PDheuWVV/TFF19oy5YtKlmypGrUqKGGDRvqoosuUufOnVPyXgeDSF86M9P//vc/1alTJ266Vq1aacqUKZKkF198UT169MiVZtu2bRo2bJjGjh2rRYsWadOmTSpZsqTq1q2rc889V9dcc42OOeaY/XUowAGFoBQAAAC57N27V+3bt9eECRNUqVIldezYUdWqVdP27du1ePFivfnmm1q1alWOoLRz584644wzVLVq1RBzvn8VLVpUe/bs0QsvvKD+/fvnWv+///1PU6ZMyU4Xz5w5c5SVlaXvvvtO1atX1/nnn6+jjjpK27dv18KFCzVgwAANGDBAc+bM0amnnrq/DwkIHUEpgEI70GsMgANFqmqvgD/CyJEjNWHCBDVp0kQffvihSpcunWP99u3bNXfu3BzLypQpozJlyvyR2fzDVa5cWVWrVtWLL76ofv36qWjRnLfTzz//vCTpwgsv1FtvvZVr+2XLlqlt27b65Zdf9Nhjj+nOO+/MtY/Vq1fr7rvv1pYtW/bfgQAHEPqUAgAAIJdZs2ZJknr06JErIJWkkiVLqlWrVjmW5dWndOLEiWrWrJlKlSql8uXLq1OnTlq0aJF69OghM9OqVauy065atUpmph49emjVqlW69NJLVbFiRRUvXlyNGzfWO++8k2v/mzdv1sMPP6yzzz5bFSpUUNGiRVWpUiV16NBBs2fPLtzJiNGzZ0+tW7cuVz52796tESNGqGnTpjrppJPibnvzzTdry5Ytuueee3TPPffkCkglqWbNmho1apTOPPPMlOYbOFARlAIAACCX4sWLS/LNUQtr1KhRateunRYsWKCLL75Y1113nTZu3KjmzZvryy+/TLjdN998oyZNmmjt2rXq2bOnrrzySi1btkwdO3bU5MmTc6RdunSp+vfvrxIlSqh79+7q3bu3zj//fE2bNk3xBVFAAAAgAElEQVQtWrTQhAkTCn0cEd26dVOpUqWya0Ujxo4dq/Xr16tnz55xt/v666/14Ycfqnjx4rr77rvzfZ+MjIyU5Bc40NF8FwAAALlcfPHFGjhwoAYOHKgff/xRnTt3VqNGjVSrVq0C7Wfr1q264YYbVLx4cc2ePVv169fPXnfvvffG7ZcZMWXKFD3xxBO64447spddccUVatGihQYMGJCjpvakk07SunXrlJmZmWMf69at02mnnabbb79d5513XoHynkjp0qV16aWXasSIEVqzZo2qV68uSRo2bJgyMzN1ySWXxD2uGTNmSJIaNWqksmXLpiQvwKGAmlIAAADkcuaZZ+q1115T5cqV9corr+iiiy5S7dq1VaFCBXXu3Fnjxo1Laj9jxozRpk2bdPXVV+cISCWpT58+qlChQsJtjz322BwBqSSdddZZOvbYY/Xxxx/nWJ6ZmZkrIJWkKlWqqGvXrlq2bJlWr07dGAg9e/bMHp1Y8rW6H3zwgS6//HKVLFky7jZr166VpOwgFoBHUAoAAIC4Lr30Uq1evVoTJ07U/fffr/bt26tIkSJ6++231aFDB3Xv3l3OuTz3sWDBAkk+mIxVrFgxnX766Qm3bdy4cdzlVatW1caNG3Mtnzlzpi655BLVqFFDGRkZMjOZmZ544glJ0nfffZdnXgvi9NNP15/+9CcNHz5c+/bt0/PPP699+/YlbLoLIDGa7wIAACCh9PR0tWnTRm3atJEk7du3T2PGjNFVV12ll19+WZ07d1anTp0Sbr9582ZJSthctVy5cgm3TdSnMi0tTfv27cux7K233lJWVpaKFy+uc889V3Xq1FGpUqWUlpamKVOmaOrUqdq5c2eex1pQPXv21C233KLx48frxRdfVKNGjdSwYcOE6SNT5aQyOAYOBQSlAAAASFpaWpo6d+6sxYsX6/7779dHH32UZ1AaaVK7adOmuOsTLS+o+++/XyVKlNAXX3yho48+Ose6O+64Q1OnTk3J+0S74oordM899+j666/Xd999pwceeCDP9M2bN5ckzZs3T5s3bz7kp88BkkXzXQAAABRYJNjMr/lupOZw+vTpudbt2rVLc+bMSUl+VqxYoXr16uUKSCXlGqk3VcqWLausrCytWbNGpUqVUrdu3fJMf/TRR+ucc87Rjh07NGDAgHz3n+qaXeBARVAKAACAXEaOHKkPPvggVzNZSfrpp5/07LPPSpJatGiR5346duyoMmXKaPjw4frss89yrOvbt69+/vnnlOS3SpUqWrJkidavX59j+YABA7Rw4cKUvEc8Dz/8sN566y1NnDgx7nyusQYPHqzMzEw9+uijeuKJJ7Rnz55caVavXq2uXbumfH5V4EBF810AAADkMnfuXA0aNEhVqlRR8+bNdfTRRys9PV1ff/213nvvPW3evFkdO3ZUVlZWnvvJzMzU008/rSuuuEJNmzbVJZdcoqpVq2rWrFlauHChmjdvrhkzZigtrXB1JbfeeqvuuusuNWzYUFlZWSpRooSmT5+uBQsWqF27dho/fnyh9p9IzZo1VbNmzaTTn3jiiZo4caKysrJ01113adCgQWrdurWOOuoobdu2TZ999plmzpwpM1Pv3r33S56BAw1BKQAAAHK54447VKNGDU2ZMkWffPKJxo4dK+ecKlSooKZNm+qyyy7TZZddJjPLd1+XX365ypcvr4ceekivv/66MjIy1KJFC82YMUP9+vWTpLjTuRTEnXfeqYyMDA0ZMkRDhw5VZmamzjrrLM2YMUNjx47db0Hp73HGGWdo2bJlGjZsmMaOHat3331XGzduVMmSJXXsscfqzjvvVK9eveI2RQYORZZfP4D9pXHjxm7evHmhvDeA1HptburmfQMOZZednnxtCsK1dOlSnXjiiWFn45DnnNOxxx6r7du3Z8/hCeDAl+x3pJnNd87Fn9spCn1KAQAAsF9t3rw57qA9AwcO1FdffaXOnTuHkCsABwqa7wIAAGC/mj17tv7yl7/o3HPP1THHHKOdO3dq5syZmjNnjmrUqKEHH3ww7CwCCBFBKQAAAPar448/Xi1bttSMGTP03//+V2am6tWr65ZbbtH/+3//T0ceeWTYWQQQIoJSAAAA7FdHH320Ro8eHXY2AByg6FMKAAAAAAgNQSkAAAAAIDQEpQAAAACA0BCUAgAAAABCQ1AKAAAAAAgNQSkAAAAAIDQEpQAAAACA0BCUAgAAAABCQ1AKAAAAAAgNQSkAAAAKrHbt2qpdu3bY2Tio9OjRQ2amVatWhZ0VHKamTJkiM9ODDz4YdlZyKBp2BgAAAA46424NOwd5u3BQ2DlImpnp7LPP1pQpU8LOymGhdu3a+uabb7L/n5aWplKlSqlatWpq0KCB2rdvr6ysLGVkZISYSxxuCEoBAACAw8ytt96qsmXLat++fdqyZYuWL1+ucePGadSoUbr33ns1atQonXHGGWFnE4cJglIAAADgMHPbbbflan69efNm3X///Xrqqad03nnnac6cOTrhhBPCySAOK/QpBQAAQFzOOQ0ZMkQnn3yyihcvrmrVqummm27S5s2b46bfvHmzHn74YZ199tmqUKGCihYtqkqVKqlDhw6aPXt2jrQjRoyQmUmSpk6dKjPLfkX3d3vuued04YUXqnr16kpPT1dmZqaaNWumV155pUDH8uCDD8rM4jYTXrVqlcxMPXr0yLE8ug/os88+qz/96U8qXry4KleurF69eiU8Dx9++KHOOusslSpVSuXLl1enTp20bNmyPPM3d+5cZWVlqUqVKipWrJhq1Kih6667Tt9//32utC1btpSZadeuXerXr5+OP/54ZWRk5Mp/QZUpU0aDBw/WlVdeqc2bN6t379451q9bt0433HCDatWqpWLFiql48eI69thjdemll+rLL79M6j0ifZE3b96s2267TTVq1FCxYsV00kkn6fXXX5ck7dy5Uw888IBq166t9PR01alTR0OGDMm1r127dumJJ55QmzZtVLlyZaWnp6t8+fI655xzNH78+LjvP3/+fHXq1ElHHnmkihYtqtKlS6t+/fq68cYbtXv37ux0W7Zs0T333KPjjjtOGRkZysjIUK1atdSpUyfNmzcvqWONXKedO3fqvvvu09FHH62MjAzVqVNHffv21a5du+Jut2zZMvXo0SP73FSuXFmXXXaZli9fnivt8uXLddttt6lhw4YqXbq0ihUrplq1aqlXr15as2ZNUvmUpB07digrK0tmpr/+9a/at29f0tumQr41pWY2XFJ7Seudc6fkke40SbMlXeqcG526LAIAACAMt912mwYPHqyqVauqV69eSk9P15gxYzR37lzt2rVLxYoVy5F+6dKl6t+/v1q0aKHu3burZMmS+vbbbzVmzBiNHz9e48aN03nnnSdJatCggfr06aO+ffuqVq1aOQKqli1bZv/79ttvV7169dShQwdVqFBBGzdu1HvvvacrrrhCy5cv10MPPbTfz8Pdd9+tjz76SF26dNGFF16ojz76SMOGDdPKlSv10Ucf5Ug7evRode3aVcWKFVPXrl1VtWpVzZgxQ2eeeabq1asXd//Dhw9Xr169VLp0aXXq1ElHHXWUvvrqK40YMULjxo3TnDlzVLNmzVzbXXTRRVqwYIE6deqkzMxMHXnkkSk53gceeEAvv/yy3nnnHW3ZskWZmZnavn27mjdvrq+++krnnXeeunXrprS0NH399deaPHmyli5dqjp16iS1/127dumcc87Rr7/+qksvvVQ7duzQq6++qm7duqlUqVIaOnSoFi9erI4dO6po0aJ6/fXXdfPNN6tkyZK6+uqrs/ezYcMG/f3vf1ezZs3UtWtXlSlTRj/88IPGjRun888/X8OGDdO1116bnf7zzz9X8+bNlZaWps6dO6t27drasWOHli5dqpdffln/+Mc/lJ6eLuec2rVrp1mzZumss85S586dlZ6erjVr1mjq1KmaM2eOGjdunPT5vOSSS/TJJ58oKysr+zP04IMPat68eRo7dmz2wxlJmjBhgrp06SJJ6tixo4455hitXbtW//nPf/Tuu+9q8uTJOvXUU7PTv/XWW3rttdfUsmVLtWnTRkWKFNHixYs1fPhwjRs3TvPmzVO1atXyzN/GjRvVoUMHzZw5U48++miuhxF/hGSa746QNETSy4kSmFkRSY9Lej812QIAAECYZs2apcGDB6tu3bqaPXu2ypcvL0l65JFHdO6552rt2rWqVatWjm1OOukkrVu3TpmZmTmWr1u3Tqeddppuv/32HEFpgwYN1LdvX9WuXTvhaKDLli1TjRo1cizbvXu3OnbsqMcee0zXX399vjfdhbVgwQItXrxYlStXliTt27dPbdu21YcffqiPP/5YTZo0kST98ssvuu6665Senq4ZM2aoUaNG2fu466679MQTT+Ta94oVK3T99dfrxBNP1KRJk3IElrNmzVKrVq1066236q233sq17dq1a7V06VKVLl06pcdbp04dVa9eXWvWrNH8+fPVqlUrTZo0SV9++aV69+6tRx99NEf6vXv3avv27Unvf+3atWrWrJlGjRqlIkWKSJKuvPJKNWnSRN26dVP9+vW1ZMkSlSxZUpJ/OFK3bl3985//zBGUlitXTmvWrMkVjG/dulVnn3227r77bl1++eUqUaKEJOmll17Sjh07NGHCBLVt2zbHNlu2bMl+v0WLFmnWrFm69NJLNXLkyBzpnHPasmVL0scq+Wu8ePFilStXTtJvn6F33nlHr7zyiq644gpJPjjs1q2bypUrpylTpui4447L3kfv3r11xhln6Nprr9Wnn36avbx79+666667VLRozrBu2rRpatWqlR5++GENHTo0Yd6++eYbtWvXTitXrtS///1vXX755QU6tlTJt/muc26apA35JLtZ0n8lrU9FpgAAABCuF198UZLUt2/f7IBUkooXLx43uJKkzMzMXAGpJFWpUkVdu3bVsmXLtHr16gLlIzYglaT09HTdeOON2rNnjyZNmlSg/f0effr0yQ5IJT9ibaRm9+OPP85ePmbMGG3YsEE9evTIEZBK0sMPP5wdlEQbOnSodu/erYEDB+YKrpo2barOnTtr3Lhx2rp1a65tH3nkkZQHpBGRQP/HH3+U5JvUSspRqxdRpEiRAufjX//6V3ZAKkmnnXaa6tatq19++UWPP/54doAo+TLQokULLV26NMd5yMjIiFs7XLp0aV199dXauHGjPvnkk+zleR1DZmam0tLS8k1nZipTpkyBjvWhhx7Kce2jP0PDhw/PXv7yyy9r06ZN6tevX46AVJLq1q2rXr16acGCBVqyZEn28qpVq+YKSCWpRYsWatiwoSZOnJgwXwsXLtSZZ56p7777TuPHjw8tIJVSMNCRmVWT1FlSK0mnFTpHAAAACF2kNubss8/Ote60005TqVKl4m43c+ZMDRo0SLNnz9b69etz9Zv77rvv4jZFTWT16tV6/PHHNWnSJK1evVq//vprrv3tb6edlvsWt2rVqpJ87VZEXuesePHiOuOMM3L1dYz0tf3www81ffr0XNt9//332rt3r1asWJEr0N2fo+M65yRJe/bskSS1bt1aRx55pB577DF99tlnateunc4880w1aNAgR3CZjMqVK6t69epxl69YsSJu09jIQ4FNmzblCIAXL16sAQMGaNq0aVq7dq127NiRY7vo8tG1a1cNHTpUXbp0UVZWllq3bq2mTZvmanbcoEEDnXjiiRo5cqS+++47XXjhhWratKkaN26cq8l6MvL6DC1YsCB7WaQszJs3T99++22ubSLB6NKlS3XSSSdJ8tfp1Vdf1YgRI/TZZ59p48aN2rt3b/Y2ifI7Y8YMPfnkkypdurSmTZum+vXrF/i4UikVo+8OlHSPc25fvKcJ0cysl6Rekgr0ZQQAAIA/VmQQn+ha0ggzU9myZXMtf+utt5SVlaXixYvr3HPPVZ06dVSqVCmlpaVpypQpmjp1anYtVDK++uorNWnSRBs3btRZZ52lNm3aqEyZMipSpIhWrVqll156qUD7+73izdkZqVWLDgDyOmeJlv/888+SpMceeyzPPPzyyy+5lhW0xq4gIgMsRYLBcuXKafbs2XrwwQf1zjvv6L333pMkVaxYUTfeeKPuu+8+paenJ7Xv4sWLx10eOafJnu85c+boz3/+s/bs2aPWrVurQ4cO2TWeCxcu1JgxY3KUj7POOkuTJk3So48+qlGjRumll16SJB1//PHq06ePunXrJkkqWrSopkyZon79+mn06NGaNm2aJF8D2717d/Xv379ANcN5fYaiB7KKlIVnnnkmz/1Fl4U77rhDAwcOVNWqVdW2bVtVq1Ytu7nyiBEjcsxJG23BggXaunWrmjZtekCMsJyKoLSxpFFBQFpR0vlmtsc593ZsQufcc5Kek6TGjRu7FLw3AAAA9oNIwLNhw4bsWsEI55w2bdqkihUr5lh+//33q0SJEvriiy909NFH51h3xx13aOrUqQXKw5NPPqmff/5Zb7zxhi6++OIc68aOHZsdVCQjEtREagCjxdau/V7R5yyeeMsj22zevDlu0+cwrFy5UmvWrFFaWpoaNGiQvfyYY47Ryy+/LOeclixZoo8++khPP/20+vXrp23btumf//znH5rPhx9+WDt27NCcOXOy+/VGDB48WGPGjMm1TcuWLdWyZUvt3LlT8+fP14QJE/TUU0/psssuU+nSpdW+fXtJ0pFHHqkhQ4ZoyJAhWrlypaZOnapnn31WQ4YM0dq1azV6dPLjum7YsEGVKlXKsSzyGYq+5pGy8NlnnyUcFCva+vXrNXjwYDVq1EjTp0/PDkYjxo4dmzAovemmm7R+/Xo988wz6tChg95+++1c2/+RCj0ljHPuaOdcbedcbUmjJd0YLyAFAADAwSMywme8QPKTTz7Rtm3bci1fsWKF6tWrlysglaTJkyfHfZ+0tLS4gWJkf5IfhTTZ/SUS6dMXb4qV6H6HhZHXOYsET7EiTXDjNd0NS79+/SRJ7dq1U4UKFXKtNzOdfPLJuvnmm/XBBx9I8gHQH23FihWqUqVKroBUyr98ZGRkqGnTpurXr58GDx4sKfExHHvssbrmmms0depUHXHEERo3blyB8pnXZ6hhw4bZywpaFlauXKl9+/apTZs2uQLKH3/8UYsWLUq4rZlp6NChuu222/T+++/rggsuiPuZ/qPkG5Sa2Uj5qV6ON7M1ZnaNmV1vZtfv/+wBAAAgDJGBfPr06ZOjhm/Hjh268847425TpUoVLVmyROvX5xz7csCAAVq4cGHcbSpUqJCwX2iVKlUkKdfcotOnT89zRNF4IoHLSy+9lGMOxvXr16tv374F2lciHTt2VLly5TRixAjNnz8/x7r77rsvR//TiJtuuknp6em6/fbb4w4CtW/fPs2dOzcl+cvPli1bdMstt+jf//63jjjiCA0YMCB73eLFi/XDDz/k2ibSZDneIE77W5UqVfTDDz9o6dKlOZa/8cYbcWtJZ82alatPspT7GL7++mt99dVXudJt3bpVe/fujdt0PS/3339/jmsf/Rm66qqrspdfddVVKlu2rPr27avPP/887r6i5/uNfD6mT5+eo1nzrl271KtXrxzzribyr3/9S3//+981efJktW3btsAjC6dKvs13nXPdkt2Zc65HoXIDAACAA0KzZs10880366mnntIpp5ySY47FcuXK5WrSK0m33nqr7rrrLjVs2FBZWVkqUaKEpk+frgULFqhdu3a5BvmR/AA6o0aNUpcuXdSgQQOlpaWpRYsWatGihW688UaNHDlSnTp1UteuXVWtWjUtWbJEY8eOVceOHfXmm28mfTynn366WrRooQ8++EDNmjVTq1attGHDBo0ePVqtW7fWl19+WajzJUlHHHGEnnvuOXXt2lXNmzfPMU/pokWL1KJFi+z+iREnnHCChg8frquvvlonnHCCLrjgAh133HHau3evvv76a02bNk1ly5bVsmXLCp2/aAMHDlTZsmWzpzhZvny5pk2bpm3btql27doaOXKkTjzxxOz0H3zwgf72t7+pWbNmql+/vjIzM/X999/rzTffVFpamv72t7+lNH/JuOWWWzR9+vTseUrLlSun+fPna9KkSerYsaPefjtn481//OMf+uijj9SqVSsdf/zxKlasWHZ5KleunHr16iXJN5/t0qWLmjRpokaNGql8+fL66aef9Pbbb+vXX3/Vww8/XKB81q1bVyeffHKOz9CXX36pCy64IHs6GMk/oBk9erQ6d+6sRo0aqW3btjrllFNkZvr22281Y8YMrVu3Lru5+THHHKP27dvrnXfe0WmnnaY2bdpox44dGjdunMxM9erVSxjcRuvfv7+KFy+uPn366Nxzz9WECRP+8IcMqehTCgAAgEPQoEGDVLduXT399NN69tlnVaFCBXXu3Fn9+/ePO1rnnXfeqYyMDA0ZMkRDhw5VZmamzjrrLM2YMUNjx46NG5QOGjRIZqZJkyZpzJgx2rdvn/r06aMWLVpkj1bbp08fjRo1SkWLFlX9+vU1cuRIVapUqUBBqeSnbPnb3/6mMWPG6NNPP9Vxxx2n/v37q02bNnrjjTd+93mKlpWVpQkTJqhv37564403lJGRoRYtWmj27Nl67LHHcgWlkvSXv/xF9evX1xNPPKHJkydrzJgxKlKkiGrWrKnzzjtPl112WUryFm3QoEGSfDPOUqVKqXr16rrwwgvVvn17ZWVl5RpsqE2bNvryyy81c+ZMvfjii9q+fbvKlSunZs2a6c4771SrVq1Snsf8ZGVladSoUXrsscc0fPhwlShRQk2aNNHEiRP17bff5gpKr7/+epUuXVoff/yx3n//fe3Zs0dHHXWUunfvrnvvvVfHHHOMJKlx48a66667NG3aNL322mvasmWLMjMzdeqpp+rpp59Wly5dCpTPN954Qw899JBeffVVff/996pWrZoefPBB9e7dO9e0M61bt9bnn3+uf/7zn5o4caI+/PBDOedUrVo1nX766broootypB81apTuvfdevfHGG3ryySdVuXJltW/fXn379tUll1ySdB4feOABlShRQnfffbdat26t999/P1ef8f3JErXh398aN27s5s2bF8p7A0it1+YWbM454HB12emMPH+wWLp0aY5aIgAoqJYtW2rq1KkJ+0wfzJL9jjSz+c653HP8xCj0QEcAAAAAAPxeBKUAAAAAgNAQlAIAAAAAQsNARwAAAACQYrFTGSExakoBAAAAAKEhKAUAAAAAhIagFAAAAAAQGoJSAACAOA7FuQUBoLD2x3cjQSkAAECMIkWKaPfu3WFnAwAOOLt371aRIkVSuk+CUgAAgBilS5fWli1bws4GABxwtmzZotKlS6d0nwSlAAAAMcqXL6+NGzfqp59+0q5du2jKC+Cw5pzTrl279NNPP2njxo0qX758SvfPPKUAAAAxMjIyVLNmTW3YsEGrVq3S3r17w84SAISqSJEiKl26tGrWrKmMjIyU7pugFAAAII6MjAxVrVpVVatWDTsrAHBIo/kuAAAAACA0BKUAAAAAgNAQlAIAAAAAQkNQCgAAAAAIDUEpAAAAACA0BKUAAAAAgNAQlAIAAAAAQkNQCgAAAAAIDUEpAAAAACA0BKUAAAAAgNAQlAIAAAAAQkNQCgAAAAAIDUEpAAAAACA0BKUAAAAAgNAQlAIAAAAAQkNQCgAAAAAIDUEpAAAAACA0BKUAAAAAgNAQlAIAAAAAQkNQCgAAAAAIDUEpAAAAACA0BKUAAAAAgNAQlAIAAAAAQkNQCgAAAAAIDUEpAAAAACA0BKUAAAAAgNAQlAIAAAAAQkNQCgAAAAAIDUEpAAAAACA0BKUAAAAAgNDkG5Sa2XAzW29mixKsv8LMvjCzRWY238wapz6bAAAAAIBDUTI1pSMknZfH+hWSmjvnTpF0n6TnU5AvAAAAAMBhoGh+CZxz08ysdh7r50b9d4akaoXPFgAAAADgcJDqPqXXSRqb4n0CAAAAAA5R+daUJsvMWkq6RlLzPNL0ktRLkmrWrJmqtwYAAAAAHKRSUlNqZvUkvSCpo3Pu50TpnHPPOecaO+caV6pUKRVvDQAAAAA4iBU6KDWzmpLelHSFc25F4bMEAAAAADhc5Nt818xGSmopqaKZrZHUR1K6JDnnnpH0gKQKkv7PzCRpj3OOaWEAAAAAAPlKZvTdbvmsv1bStSnLEQAAAADgsJHq0XcBAAAAAEgaQSkAAAAAIDQEpQAAAACA0BCUAgAAAABCQ1AKAAAAAAgNQSkAAAAAIDQEpQAAAACA0BCUAgAAAABCQ1AKAAAAAAgNQSkAAAAAIDQEpQAAAACA0BCUAgAAAABCQ1AKAAAAAAgNQSkAAAAAIDQEpQAAAACA0BQNOwMAAABADuNuDTsHwIHvwkFh5yBlqCkFAAAAAISGoBQAAAAAEBqCUgAAAABAaAhKAQAAAAChISgFAAAAAISGoBQAAAAAEBqCUgAAAABAaAhKAQAAAAChISgFAAAAAISGoBQAAAAAEBqCUgAAAABAaAhKAQAAAAChISgFAAAAAISGoBQAAAAAEBqCUgAAAABAaAhKAQAAAAChISgFAAAAAISGoBQAAAAAEBqCUgAAAABAaAhKAQAAAAChISgFAAAAAISGoBQAAAAAEBqCUgAAAABAaAhKAQAAAAChISgFAAAAAISGoBQAAAAAEBqCUgAAAABAaAhKAQAAAAChISgFAAAAAIQm36DUzIab2XozW5RgvZnZYDNbYmYLzOzU1GcTAAAAAHAoSqamdISk8/JY30VSLUknS7pG0ouFzxYAAAAA4HCQb1DqnJsmaUMeSS6Q9IrzPpVU1MxqpCqDAAAAAIBDVyr6lFaX9G3U/9cEywAAAAAAyNMfOtCRmfUys3lmNu/HH3/8I98aAAAAAHAASkVQukZSdHPd6sGyXJxzzznnGjvnGouebRsAABKtSURBVFeqVCkFbw0AAAAAOJilIih9T9LlkhSMvLvPOfdt3psAAAAAACAVzS+BmY2U1FJSRTNbI6mPpHRJcs49I+m/klqZ2RJJuyRdtd9yCwAAAAA4pOQblDrnuuWz3kn6a8pyBAAAAAA4bPyhAx0BAAAAABCNoBQAAAAAEBqCUgAAAABAaAhKAQAAAAChISgFAAAAAISGoBQAAAAAEBqCUgAAAABAaAhKAQAAAAChISgFAAAAAISGoBQAAAAAEBqCUgAAAABAaAhKAQAAAAChISgFAAAAAISGoBQAAAAAEBqCUgAAAABAaAhKAQAAAAChISgFAAAAAISGoBQAAAAAEBqCUgAAAABAaAhKAQAAAAChISgFAAAAAISGoBQAAAAAEBqCUgAAAABAaAhKAQAAAAChISgFAAAAAISGoBQAAAAAEBqCUgAAAABAaAhKAQAAAAChISgFAAAAAISmaNgZAHDwO21R37CzABwcTn8h7BwAAHDAoaYUAAAAABAaglIAAAAAQGgISgEAAAAAoSEoBQAAAACEhqAUAAAAABAaglIAAAAAQGgISgEAAAAAoSEoBQAAAACEhqAUAAAAABAaglIAAAAAQGgISgEAAAAAoSEoBQAAAACEhqAUAAAAABAaglIAAAAAQGgISgEAAAAAoUkqKDWz88xskZktNbPecdZXMbNJZrbEzFaY2fWpzyoAAAAA4FCTb1BqZhmSnpHUTlI9SVn2/9u7/1jJzrIO4N9Hdm3kh0boAsLdoiYmBpumqUsaAmgJJLZsjEGIBaGJCC5tkPgjGqpGJPqPhmhMFdxUQBPXYBUIENzSYogSDFAvpbTbFotG4q66dMGkEUxtax//mFmZXnb3zr2du+/s7OeTTPb8eM/Me+fZc95855w5U3XZhmY/m2S9u5+b5AVJfruqvm3RnQUAAGC1zHOm9PIkd3f30e5+OMlNSfZvaHMsyVOqqpI8OclXkvzPQnsKAADAypknlK4lOTozf2y6bNYfJ3lukn9PcleSn+vuRxfSQwAAAFbWom509CtJ7kzyrCSXJvnDqvr2jY2q6kBVrVfV+okTJxb00gAAAJyr5gmlx5LsnZlfmy6b9aIkf9UT/5TkXzI5c/oY3X1jd+/r7n179uzZbp8BAABYEfOE0tuSXFxVa1W1O8nVSW7e0Oafk7wkSarqGZkE0i8tsJ8AAACsoF2bNejuB6vquiS3ZBJiD3X3+smffenug0l+M8mhqro3yROS/Hp3H9/BfgMAALACNg2lSdLdh5Mc3rDs4Mz08SQvXWzXAAAAWHWLutERAAAAbJlQCgAAwDBCKQAAAMMIpQAAAAwjlAIAADCMUAoAAMAwQikAAADDCKUAAAAMI5QCAAAwjFAKAADAMEIpAAAAwwilAAAADCOUAgAAMIxQCgAAwDBCKQAAAMMIpQAAAAwjlAIAADCMUAoAAMAwQikAAADDCKUAAAAMI5QCAAAwjFAKAADAMEIpAAAAwwilAAAADCOUAgAAMIxQCgAAwDBCKQAAAMMIpQAAAAwjlAIAADCMUAoAAMAwQikAAADDCKUAAAAMI5QCAAAwjFAKAADAMEIpAAAAwwilAAAADCOUAgAAMIxQCgAAwDBCKQAAAMMIpQAAAAwjlAIAADCMUAoAAMAwQikAAADDCKUAAAAMI5QCAAAwjFAKAADAMHOF0qq6sqqOVNW9VXX9adpcUVX/UFWfr6pPLLabAAAArKJdmzWoqguSHEzyoiTHk3yqqm7t7ttn2jwzyTuSvKS7j1fVhTvVYQAAAFbHPGdKL09yd3cf7e6Hk9yUZP+GNq9K8pfdfTxJuvsri+0mAAAAq2ieULqW5OjM/LHpslnfn+S7qurTVXVXVf3MqZ6oqg5U1XpVrZ84cWJ7PQYAAGBlLOpGR9+S5NIkL0ny4iRvqaqLNzbq7hu7e19379uzZ8+CXhoAAIBz1abfKc3kzOjemfm16bJZR5P8R3d/PcnXq+rvklyS5MhCegkAAMBKmudM6W1JLq6qtaraneTqJDdvaPPXSV5YVbuq6olJnp/kC4vtKgAAAKtm0zOl3f1gVV2X5JZMQuyh7l6vqmun6w929+1V9dEkdybZneTds3fnBQAAgFOZ5/LddPfhJIc3LDu4Yf7tSd6+uK4BAACw6hZ1oyMAAADYMqEUAACAYYRSAAAAhhFKAQAAGEYoBQAAYBihFAAAgGGEUgAAAIYRSgEAABhGKAUAAGAYoRQAAIBhhFIAAACGEUoBAAAYRigFAABgGKEUAACAYYRSAAAAhhFKAQAAGEYoBQAAYBihFAAAgGGEUgAAAIYRSgEAABhGKAUAAGAYoRQAAIBhhFIAAACGEUoBAAAYRigFAABgGKEUAACAYYRSAAAAhhFKAQAAGEYoBQAAYJhdozsAAACzvnj/10Z3AZbe943uwAI5UwoAAMAwQikAAADDCKUAAAAMI5QCAAAwjFAKAADAMEIpAAAAwwilAAAADCOUAgAAMIxQCgAAwDBCKQAAAMMIpQAAAAwjlAIAADCMUAoAAMAwQikAAADDCKUAAAAMM1coraorq+pIVd1bVdefod3zquqRqnrl4roIAADAqto0lFbVBUkOJrkqySVJXllVl52i3ROS/E6SWxfdSQAAAFbTPGdKL09yd3cf7e6Hk9yUZP8p2r05yfuT3L/A/gEAALDC5gmla0mOzswfmy77f1X17CQvT/JHZ3qiqjpQVetVtX7ixImt9hUAAIAVs6gbHf1+krd096NnatTdN3b3vu7et2fPngW9NAAAAOeqXXO0OZZk78z82nTZrH1J/qKqkuTCJC+rqke6+4ML6SUAAAAraZ5QeluSi6tqLcmXk1yd5NrZBt39PSenq+pPk3xEIAUAAGAzm4bS7n6wqq5Lcksml/se6u71qrp2uv7gDvcRAACAFTXPmdJ09+EkhzcsO2UY7e6fevzdAgAA4HywqBsdAQAAwJYJpQAAAAwjlAIAADCMUAoAAMAwQikAAADDCKUAAAAMI5QCAAAwjFAKAADAMEIpAAAAwwilAAAADCOUAgAAMIxQCgAAwDBCKQAAAMMIpQAAAAwjlAIAADCMUAoAAMAwQikAAADDCKUAAAAMI5QCAAAwjFAKAADAMEIpAAAAwwilAAAADCOUAgAAMIxQCgAAwDBCKQAAAMMIpQAAAAwjlAIAADCMUAoAAMAwQikAAADDCKUAAAAMI5QCAAAwjFAKAADAMEIpAAAAwwilAAAADCOUAgAAMIxQCgAAwDBCKQAAAMMIpQAAAAwjlAIAADCMUAoAAMAwQikAAADDCKUAAAAMI5QCAAAwjFAKAADAMEIpAAAAw8wVSqvqyqo6UlX3VtX1p1h/TVXdNW3z2arat/iuAgAAsGp2bdagqi5IcjDJi5IcT/Kpqrq1u2+faXZfkhd29wNVdVWSdyW5dCc6DAAAwOqY50zp5Unu7u6j3f1wkpuS7J9t0N2f6e4HprOfTPLsxXYTAACAVTRPKF1LcnRm/th02em8McmHH0+nAAAAOD9sevnuVlTVFUlen+SFp1l/IMmBJLnooosW+dIAAACcg+Y5U3osyd6Z+bXpsseoqkuSvDvJj3X3V0/1RN19Y3fv6+59e/bs2U5/AQAAWCHzhNLbklxcVWtVtTvJ1Ulunm1QVRcl+UCSa7r7vsV3EwAAgFW06eW73f1gVV2X5JZMQuyh7l6vqmun6w8meWuSpyV5Z1UlySPd7WdhAAAAOKO5vlPa3YeTHN6w7ODM9BuSvGGxXQMAAGDVzXP5LgAAAOwIoRQAAIBhhFIAAACGEUoBAAAYRigFAABgGKEUAACAYYRSAAAAhhFKAQAAGEYoBQAAYBihFAAAgGGEUgAAAIYRSgEAABhGKAUAAGAYoRQAAIBhhFIAAACGEUoBAAAYRigFAABgGKEUAACAYYRSAAAAhhFKAQAAGEYoBQAAYBihFAAAgGGEUgAAAIYRSgEAABhGKAUAAGAYoRQAAIBhhFIAAACGEUoBAAAYRigFAABgGKEUAACAYYRSAAAAhhFKAQAAGEYoBQAAYBihFAAAgGGEUgAAAIYRSgEAABhGKAUAAGAYoRQAAIBhhFIAAACGEUoBAAAYRigFAABgGKEUAACAYYRSAAAAhhFKAQAAGEYoBQAAYJi5QmlVXVlVR6rq3qq6/hTrq6puqKp7qupzVXXZ4rsKAADAqtk0lFbVBUkOJrkqySVJXnmK0PnjSZ6T5AeSvD7Jnyy4nwAAAKygec6UXp7k7u4+2t0PJ7kpyf4NbfYnOdQTtyfZVVV7F9xXAAAAVsw8oXQtydGZ+WPTZVttAwAAAI+x62y+WFUdSHJgOvu1qvrHs/n623Bhkq+M7gSPoSbLSV2Wj5osoze8R12Wj5osJ3VZPmqybM6NMeU58zSaJ5QeSzJ7Ke7adNmp2nz6DG3S3TcmuXGeji2Dqlrv7n2j+8E3qMlyUpfloybLSV2Wj5osJ3VZPmqyfFapJvNcvntbkouraq2qdie5OsnNG9ocTvKaJJneBOnR7j4aAAAAOINNz5R294NVdV2SWzIJsYe6e72qrp2uP5jk/UleXFX3JHkoyet2sM8AAACsiLm+U9rdhzM5Gzq77ODMdCd502K7thTOmUuNzyNqspzUZfmoyXJSl+WjJstJXZaPmiyflalJTfIkAAAAnH3zfKcUAAAAdsR5H0qr6qlV9bGququqbq2q7zxNuy9N29xRVetb3Z75zfOeVtXeqvpEVR2pqvuq6i0z695WVf82rdUdVfWys/sXrI6qunL6Ht9bVdefYn1V1Q1VdU9VfW56o7O5tmX75qjLNdP950hVfbaq9s2sO+WxjMdnjppcUVUPzByX3jrvtmzPHDX55Zl6HKmq/62qp07X2U92QFW9p6rur6ojp1lvTBlgjroYU86yOWqyemNKd5/XjyR/kOQXp9O/kOSG07T7UpILt7u9x2JrkuSZSS6ZTj8lyReTXDqdf1uSXxr9d5zrjyQXTP/f702yO8l6kss2tHlFkg8lqSSXJfn8vNt67GhdLk/yHdPpq5LcMbPulMcyjx2vyRVJPrKdbT12piYb2v9oko/PzNtPdqYuPzQdK46cZr0xZTnrYkxZvpqs3Jhy3p8pTbI/yZ9Npw9N58/m9nyzTd/T7j7e3XdOp/8ryZ1Jnn3Wenh+uDzJ3d19tLsfTnJTvrkW+zO5I3d39+1JdlXV3jm3ZXs2fW+7+zPd/cB09pOxb+y0x/P/3b6yM7b6vr46yXvPSs/OY939iST/eYYmxpQBNquLMeXsm2NfOZ1zdl8RSpM93X0iSab/Pv007TrJyUtK37yN7Znflt7TqvruJM/L5EB50puq6gtV9edV9bSd6uiKW0sy+3vDx6bL5mkzz7Zsz1bf2zcm+fDM/OmOZWzfvDV5/vSSqo9X1aVb3Jatmft9raonJrkyk5+3O8l+MoYxZfkZU5bHSo0pc/0kzLmuqv4mk8s9N/q1LTzN87v7eFU9PclHq+oL3f2xxfTw/LOgmqSqnpzkfUl+fuZTvHck+a1MDpRvS3JDktdsu7NwjqqqK5K8PskLZxY7lo3x2SR7u/u/q+pHknywqr53dKdIMrl09++7e/ashP0ENjCmLJWVG1POi1Da3S893bqqOlFVe7r7RFXtSXL/aZ7j+PTf+6vqfZmcmftYkrm257EWUZOq2p3JJ9vv7e4PzDz3iZk2B5P87cI6fn45lsl3Ek5amy47VZtPb2ize45t2Z556pKquiTJu5Nc1d1fPbn8DMcytm/Tmky/ZnBy+paqeiiTD+bmqidbtpX39VXZcOmu/WQYY8qSMqYsl1UcU1y+mxxO8trp9GuT3LyxQVU9aXp5T6rqSZlc5nPPvNuzZfPUpDI5ON7b3b+7Yd3s5b6vyDdqxdbcluTiqlqbfgBwdb65FoczPQs9vUvio919dM5t2Z5N39uquijJB5Jc0933zSw/07GM7ZunJntmpn8wyZMz+cDNvrIz5npfq+o7kvxwJjfXObnMfjKOMWUJGVOWzyqOKefFmdJN/EaSm6rqp5N8OclPJElVPSvJu7r7ZUmekclp8U7yxEy+NPyhM23P4zJPTV6Q5Jokd1XVHdPtfrW7Dyf5veknet+a5F8zudSELeruB6vquiS3ZPIB1qHuXq+qa6frD2ZypvrFVXVPkoeSvO5M2474O1bNnHV5a5KnJXnn5PObPNLd+3LmYxnbNGdNXl1VB6abPJTkJ7v7kSSP2FcWb86aJMnLk9za3V+f2dx+skOq6r2Z3DX0wqo6lsl4vzsxpow0R12MKWfZHDVZuTGlenL7YAAAADjrXL4LAADAMEIpAAAAwwilAAAADCOUAgAAMIxQCgAAwDBCKQAAAMMIpQAAAAwjlAIAADDM/wEnjP+4hGAzJQAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 1152x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"a=[h_mc.GetBinContent(i) for i in range(nbins)]\n",
"b=[h_mc.GetBinCenter(i) for i in range(nbins)]\n",
"c=[h_data_over.GetBinContent(i) for i in range(nbins)]\n",
"d=[h_data_over.GetBinCenter(i) for i in range(nbins)]\n",
"plt.title(\"Hlt1 TrackMVA TOS Signal MC/ data under peak comparison\", fontsize=20)\n",
"\n",
"plt.bar(b,a,width=0.5,alpha=0.4,label=\"Signal MC\")\n",
"plt.bar(d,c,width=0.5, alpha=0.6, label=\"data under Ds mass peak\")\n",
"plt.legend(fontsize=20)\n",
"fig = plt.gcf()\n",
"fig.set_size_inches(16,8)"
]
},
{
"cell_type": "code",
"execution_count": 54,
"metadata": {},
"outputs": [],
"source": [
"nbins=4\n",
"MC_Hlt2Phys_TOS=MC_tuple_dict[\"Ds_Hlt2Phys_TOS\"]\n",
"data_Hlt2Phys_TOS_under=data_tuple_bkg_under[\"Ds_Hlt2Phys_TOS\"]\n",
"data_Hlt2Phys_TOS_over=data_tuple_bkg_over[\"Ds_Hlt2Phys_TOS\"]"
]
},
{
"cell_type": "code",
"execution_count": 55,
"metadata": {},
"outputs": [],
"source": [
"h_mc= r.TH1F(\"Hlt2 Phys TOS MC/data comparison under\", \"Hlt2 Phys TOS MC/data under Ds mass comparison\",nbins, 0, 2)\n",
"\n",
"for i in range(len(MC_Hlt2Phys_TOS)):\n",
" h_mc.Fill(MC_Hlt2Phys_TOS[i]) \n",
"\n",
"n1=h_mc.Integral(\"width\")\n",
"h_mc.Scale(1/n1)\n",
"h_mc.Integral(\"width\");"
]
},
{
"cell_type": "code",
"execution_count": 56,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"TFile::Append:0: RuntimeWarning: Replacing existing TH1: data below signal (Potential memory leak).\n",
"TFile::Append:0: RuntimeWarning: Replacing existing TH1: data over signal (Potential memory leak).\n"
]
}
],
"source": [
"h_data_under= r.TH1F(\"data below signal\", \"data below signal\",nbins, 0, 2)\n",
"h_data_over= r.TH1F(\"data over signal\", \"data over signal\",nbins, 0, 2)\n",
"for i in range(len(data_Hlt2Phys_TOS_under)):\n",
" h_data_under.Fill(data_Hlt2Phys_TOS_under[i])\n",
"for i in range(len(data_Hlt2Phys_TOS_under)):\n",
" h_data_over.Fill(data_Hlt2Phys_TOS_under[i])\n",
" \n",
"n2=h_data_under.Integral(\"width\")\n",
"h_data_under.Scale(1/n2)\n",
"h_data_under.Integral(\"width\");\n",
"n3=h_data_over.Integral(\"width\")\n",
"h_data_over.Scale(1/n3)\n",
"h_data_over.Integral(\"width\");"
]
},
{
"cell_type": "code",
"execution_count": 57,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1152x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"a=[h_mc.GetBinContent(i) for i in range(nbins)]\n",
"b=[h_mc.GetBinCenter(i) for i in range(nbins)]\n",
"c=[h_data_under.GetBinContent(i) for i in range(nbins)]\n",
"d=[h_data_under.GetBinCenter(i) for i in range(nbins)]\n",
"plt.title(\"Hlt2 Phys TOS Signal MC/ data below peak comparison\", fontsize=20)\n",
"\n",
"plt.bar(b,a,width=0.5,alpha=0.4,label=\"Signal MC\")\n",
"plt.bar(d,c,width=0.5, alpha=0.6, label=\"data below Ds mass peak\")\n",
"plt.legend(fontsize=20)\n",
"fig = plt.gcf()\n",
"fig.set_size_inches(16,8)"
]
},
{
"cell_type": "code",
"execution_count": 58,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1152x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"a=[h_mc.GetBinContent(i) for i in range(nbins)]\n",
"b=[h_mc.GetBinCenter(i) for i in range(nbins)]\n",
"c=[h_data_over.GetBinContent(i) for i in range(nbins)]\n",
"d=[h_data_over.GetBinCenter(i) for i in range(nbins)]\n",
"plt.title(\"Hlt1 TrackMVA TOS Signal MC/ data over peak comparison\", fontsize=20)\n",
"\n",
"plt.bar(b,a,width=0.5,alpha=0.4,label=\"Signal MC\")\n",
"plt.bar(d,c,width=0.5, alpha=0.6, label=\"data over Ds mass peak\")\n",
"plt.legend(fontsize=20)\n",
"fig = plt.gcf()\n",
"fig.set_size_inches(16,8)"
]
},
{
"cell_type": "code",
"execution_count": 59,
"metadata": {},
"outputs": [],
"source": [
"#h_data_under.SetLineColor(38)\n",
"#h_mc_under.SetLineColor(46)\n",
"#\n",
"#c1=r.TCanvas(\"c1\",\"c1\",1200,700)\n",
"#r.gStyle.SetOptStat(0)\n",
"#h_mc_under.Draw()\n",
"#h_data_under.Draw(\"same\")\n",
"#\n",
"#legend = r.TLegend(0.9,0.8,0.6,0.9)\n",
"#legend.SetHeader(\"Ds End vertex chi2\")\n",
"#legend.AddEntry(h_mc_under,\"Signal MC\",\"L\")\n",
"#legend.AddEntry(h_data_under,\"data below Ds reco mass MC\",\"L\")\n",
"#legend.Draw()\n",
"#c1.Update()\n",
"#c1.SaveAs(\"/home/hep/davide/Rphipi/plt.pdf\")"
]
},
{
"cell_type": "code",
"execution_count": 63,
"metadata": {},
"outputs": [],
"source": [
"with open('/disk/lhcb_data/davide/Rphipi/NN_test/MC_for_NN.pickle', 'wb') as handle:\n",
" pickle.dump(MC_tuple_sig, handle, protocol=pickle.HIGHEST_PROTOCOL)\n",
"with open('/disk/lhcb_data/davide/Rphipi/NN_test/data_for_NN.pickle', 'wb') as handle:\n",
" pickle.dump(data_tuple_bkg, handle, protocol=pickle.HIGHEST_PROTOCOL)\n",
" "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.5"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
Davide Lancierini