{
"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\""
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"data = r.TFile(find_file_path(l_index, 1, mag_index))\n",
"MC = 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 0x5564ed7eb1e0>"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"t_data = data.Get(\"Ds_OfflineTree/DecayTree\")\n",
"t_data"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<ROOT.TTree object (\"DecayTree\") at 0x5564ed7d2e50>"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"t_MC = MC.Get(\"Ds_OfflineTree/DecayTree\")\n",
"t_MC"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"t_data.SetBranchStatus(\"*\",0)\n",
"t_data.SetBranchStatus(\"Ds_ENDVERTEX_CHI2\",1)\n",
"t_data.SetBranchStatus(\"Ds_ENDVERTEX_NDOF\",1)\n",
"t_data.SetBranchStatus(\"Ds_OWNPV_CHI2\",1)\n",
"t_data.SetBranchStatus(\"Ds_OWNPV_NDOF\",1)\n",
"t_data.SetBranchStatus(\"Ds_IP_OWNPV\",1)\n",
"t_data.SetBranchStatus(\"Ds_IPCHI2_OWNPV\",1)\n",
"t_data.SetBranchStatus(\"Ds_DIRA_OWNPV\",1)\n",
"t_data.SetBranchStatus(\"Ds_ConsD_M\",1)\n",
"\n",
"t_data.SetBranchStatus(l_flv[l_index]+\"_plus_MC15TuneV1_ProbNN\"+l_flv[l_index], 1)\n",
"t_data.SetBranchStatus(\"Ds_Hlt1TrackMVADecision_TOS\", 1)\n",
"t_data.SetBranchStatus(\"Ds_Hlt2RareCharmD2Pi\"+l_flv[l_index].capitalize()+l_flv[l_index].capitalize()+\"OSDecision_TOS\", 1)\n",
"t_data.SetBranchStatus(\"Ds_Hlt2Phys_TOS\", 1)\n",
"\n",
"\n",
"t_MC.SetBranchStatus(\"Ds_ENDVERTEX_CHI2\", 1)\n",
"t_MC.SetBranchStatus(\"Ds_ENDVERTEX_NDOF\", 1)\n",
"t_MC.SetBranchStatus(\"Ds_OWNPV_CHI2\", 1)\n",
"t_MC.SetBranchStatus(\"Ds_OWNPV_NDOF\", 1)\n",
"t_MC.SetBranchStatus(\"Ds_IP_OWNPV\", 1)\n",
"t_MC.SetBranchStatus(\"Ds_IPCHI2_OWNPV\", 1)\n",
"t_MC.SetBranchStatus(\"Ds_DIRA_OWNPV\", 1)\n",
"t_MC.SetBranchStatus(\"Ds_ConsD_M\", 1)\n",
"\n",
"t_MC.SetBranchStatus(l_flv[l_index]+\"_plus_MC15TuneV1_ProbNN\"+l_flv[l_index], 1)\n",
"t_MC.SetBranchStatus(\"Ds_Hlt1TrackMVADecision_TOS\", 1)\n",
"t_MC.SetBranchStatus(\"Ds_Hlt2RareCharmD2Pi\"+l_flv[l_index].capitalize()+l_flv[l_index].capitalize()+\"OSDecision_TOS\", 1)\n",
"t_MC.SetBranchStatus(\"Ds_Hlt2Phys_TOS\", 1)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"\n",
"t_data.SetBranchStatus(\"phi_ENDVERTEX_CHI2\",1)\n",
"t_data.SetBranchStatus(\"phi_ENDVERTEX_NDOF\",1)\n",
"t_data.SetBranchStatus(\"phi_OWNPV_CHI2\",1)\n",
"t_data.SetBranchStatus(\"phi_OWNPV_NDOF\",1)\n",
"t_data.SetBranchStatus(\"phi_IP_OWNPV\",1)\n",
"t_data.SetBranchStatus(\"phi_IPCHI2_OWNPV\",1)\n",
"t_data.SetBranchStatus(\"phi_DIRA_OWNPV\",1)\n",
"\n",
"\n",
"t_MC.SetBranchStatus(\"phi_ENDVERTEX_CHI2\", 1)\n",
"t_MC.SetBranchStatus(\"phi_ENDVERTEX_NDOF\", 1)\n",
"t_MC.SetBranchStatus(\"phi_OWNPV_CHI2\", 1)\n",
"t_MC.SetBranchStatus(\"phi_OWNPV_NDOF\", 1)\n",
"t_MC.SetBranchStatus(\"phi_IP_OWNPV\", 1)\n",
"t_MC.SetBranchStatus(\"phi_IPCHI2_OWNPV\", 1)\n",
"t_MC.SetBranchStatus(\"phi_DIRA_OWNPV\", 1)\n"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"branches_needed = [\n",
" \"Ds_ENDVERTEX_CHI2\",\n",
" \"Ds_ENDVERTEX_NDOF\",\n",
" \"Ds_OWNPV_CHI2\",\n",
" \"Ds_OWNPV_NDOF\",\n",
" \"Ds_IPCHI2_OWNPV\",\n",
" \"Ds_IP_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_Hlt2RareCharmD2Pi\"+l_flv[l_index].capitalize()+l_flv[l_index].capitalize()+\"OSDecision_TOS\",\n",
" \"Ds_Hlt2Phys_TOS\",\n",
" \n",
" \"phi_ENDVERTEX_CHI2\",\n",
" \"phi_ENDVERTEX_NDOF\",\n",
" \"phi_OWNPV_CHI2\",\n",
" \"phi_OWNPV_NDOF\",\n",
" \"phi_IP_OWNPV\",\n",
" \"phi_IPCHI2_OWNPV\",\n",
" \"phi_DIRA_OWNPV\",\n",
"\n",
" ] "
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"MC_count=0\n",
"for event in enumerate(t_MC):\n",
" MC_count+=1\n",
" \n",
"data_count=0\n",
"for event in enumerate(t_data):\n",
" data_count+=1"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"MC event count 24354, real data event count 106404\n"
]
}
],
"source": [
"print(\"MC event count {0}, real data event count {1}\".format(MC_count,data_count))"
]
},
{
"cell_type": "code",
"execution_count": 13,
"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": 14,
"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": 15,
"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": 16,
"metadata": {},
"outputs": [
{
"data": {
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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, range=(0,3000));\n",
"plt.subplot(1,2,2)\n",
"plt.hist(Ds_constrained_mass_data,bins=70, range=(0,3000));\n",
"fig = plt.gcf()\n",
"fig.set_size_inches(16,6)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
"data_bkg_indices_over=[]\n",
"data_bkg_indices_under=[]\n",
"\n",
"MC_sig_indices=[]"
]
},
{
"cell_type": "code",
"execution_count": 18,
"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 2050 < Ds_m < 2600:\n",
" data_bkg_indices_over.append(i)"
]
},
{
"cell_type": "code",
"execution_count": 19,
"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 signal regions\n",
" if 1850<Ds_m<2050:\n",
" MC_sig_indices.append(i)"
]
},
{
"cell_type": "code",
"execution_count": 20,
"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",
"\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": 21,
"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": 22,
"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": 23,
"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": 24,
"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": 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_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": 26,
"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": 27,
"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": 28,
"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": 29,
"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": 30,
"metadata": {},
"outputs": [],
"source": [
"h_data_under= r.TH1F(\"data below signal_1\", \"data below signal_1\",nbins, 0, max_ownvchi2_under)\n",
"h_data_over= r.TH1F(\"data over signal_1\", \"data over signal_1\",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": 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_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": 32,
"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": 33,
"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": 34,
"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": 35,
"metadata": {},
"outputs": [],
"source": [
"min_DIRA_under=0.99980\n",
"min_DIRA_over=0.99980"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [],
"source": [
"h_mc_under= r.TH1F(\"Ds DIRA own PV MC/data comparison below\", \"Ds DIRAown PV MC/data below 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": 37,
"metadata": {},
"outputs": [],
"source": [
"h_data_under= r.TH1F(\"data below signal_2\", \"data below signal_2\",nbins, min_DIRA_under, 1)\n",
"h_data_over= r.TH1F(\"data over signal_2\", \"data over signal_2\",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": 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_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": 39,
"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": 40,
"metadata": {},
"outputs": [],
"source": [
"nbins=70\n",
"MC_probNNmu=MC_tuple_dict[l_flv[l_index]+\"_plus_MC15TuneV1_ProbNN\"+l_flv[l_index]]\n",
"data_probNNmu_under=data_tuple_bkg_under[l_flv[l_index]+\"_plus_MC15TuneV1_ProbNN\"+l_flv[l_index]]\n",
"data_probNNmu_over=data_tuple_bkg_over[l_flv[l_index]+\"_plus_MC15TuneV1_ProbNN\"+l_flv[l_index]]"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {},
"outputs": [],
"source": [
"h_mc= r.TH1F(\"ProbNN e MC/data comparison below\", \"ProbNN e MC/data below 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": 42,
"metadata": {},
"outputs": [],
"source": [
"h_data_under= r.TH1F(\"data below signal_3\", \"data below signal_3\",nbins, 0, 1)\n",
"h_data_over= r.TH1F(\"data over signal_3\", \"data over signal_3\",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": 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_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": 44,
"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": 45,
"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": 46,
"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": 47,
"metadata": {},
"outputs": [],
"source": [
"h_data_under= r.TH1F(\"data below signal_4\", \"data below signal_4\",nbins, 0, 2)\n",
"h_data_over= r.TH1F(\"data over signal_4\", \"data over signal_4\",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": 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_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 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": 49,
"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": 50,
"metadata": {},
"outputs": [],
"source": [
"nbins=4\n",
"MC_Hlt2RareCharm_TOS=MC_tuple_dict[\"Ds_Hlt2RareCharmD2Pi\"+l_flv[l_index].capitalize()+l_flv[l_index].capitalize()+\"OSDecision_TOS\"]\n",
"data_Hlt2RareCharm_TOS_under=data_tuple_bkg_under[\"Ds_Hlt2RareCharmD2Pi\"+l_flv[l_index].capitalize()+l_flv[l_index].capitalize()+\"OSDecision_TOS\"]\n",
"data_Hlt2RareCharm_TOS_over=data_tuple_bkg_over[\"Ds_Hlt2RareCharmD2Pi\"+l_flv[l_index].capitalize()+l_flv[l_index].capitalize()+\"OSDecision_TOS\"]"
]
},
{
"cell_type": "code",
"execution_count": 51,
"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": 52,
"metadata": {},
"outputs": [],
"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": 53,
"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 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 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": [
{
"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": 55,
"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": 56,
"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": 57,
"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": 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_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": 59,
"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": 60,
"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": 61,
"metadata": {},
"outputs": [],
"source": [
"with open('/disk/lhcb_data/davide/Rphipi/NN/'+l_flv[l_index]+l_flv[l_index]+'/MC_for_NN_'+l_flv[l_index]+l_flv[l_index]+'_Mag'+mag_status[mag_index]+'.pickle', 'wb') as handle:\n",
" pickle.dump(MC_tuple_sig, handle, protocol=pickle.HIGHEST_PROTOCOL)\n",
"with open('/disk/lhcb_data/davide/Rphipi/NN/'+l_flv[l_index]+l_flv[l_index]+'/data_for_NN_'+l_flv[l_index]+l_flv[l_index]+'_Mag'+mag_status[mag_index]+'.pickle', 'wb') as handle:\n",
" pickle.dump(data_tuple_bkg, handle, protocol=pickle.HIGHEST_PROTOCOL)\n",
"with open('/disk/lhcb_data/davide/Rphipi/NN_for_selection/'+l_flv[l_index]+l_flv[l_index]+'/data_for_NN_'+l_flv[l_index]+l_flv[l_index]+'_Mag'+mag_status[mag_index]+'.pickle', 'wb') as handle:\n",
" pickle.dump(data_tuple_dict, handle, protocol=pickle.HIGHEST_PROTOCOL)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 2",
"language": "python",
"name": "python2"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.15"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
Davide Lancierini