{
"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 numpy as np\n",
"from array import array\n",
"import root_numpy as rn\n",
"import matplotlib.pyplot as plt\n",
"import pickle\n",
"import math\n",
"import os\n",
"\n",
"from tools.data_processing import *\n",
"from tools.kinematics_fix import *\n",
"from tools.preselector import *\n"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"l_index = 1\n",
"mother_index = 1\n",
"data_index = 1\n",
"apply_phi_mass_cut = True\n",
"n_cats=6\n",
"data_type = ['MC','data']\n",
"mother_ID=['Dplus','Ds']\n",
"l_flv = ['e','mu']\n",
"PATH='/disk/lhcb_data/davide/Rphipi_new/'\n",
"\n",
"save_path_presel_data=PATH+data_type[data_index]+'/'+l_flv[l_index]+'_tuples/presel/'\n",
"save_path_trigged_data=PATH+data_type[data_index]+'/'+l_flv[l_index]+'_tuples/trigged/'\n",
"save_path_trigCats_data=save_path_trigged_data+'trigCats/'\n",
"save_path_BDT_for_data=PATH+data_type[data_index]+'/'+l_flv[l_index]+'_tuples/for_BDT_training/'"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"#retrieve files\n",
"\n",
"def find_file_path(l_index=l_index, mother_index=mother_index): \n",
" return \"/disk/lhcb_data/davide/Rphipi/data/\"+mother_ID[mother_index]+\"_phipi_\"+l_flv[l_index]+l_flv[l_index]+\"/\"+mother_ID[mother_index]+\"_phipi_\"+l_flv[l_index]+l_flv[l_index]+\".root\"\n",
"\n",
"data = r.TFile(find_file_path(l_index=l_index, mother_index=mother_index))\n",
"tree_name_Ds = mother_ID[mother_index]+'_OfflineTree/DecayTree'\n",
"t_data = data.Get(tree_name_Ds)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Converting tuples to dictionary"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"#Switch on only the branches that you need\n",
"data_tuple_dict = {}\n",
"\n",
"t_data.SetBranchStatus(\"*\",0)\n",
"\n",
"for branch in return_branches(data_index=data_index, mother_index=mother_index, l_index=l_index):\n",
" if branch!='cos_thetal':\n",
" t_data.SetBranchStatus(branch, 1)\n",
"\n",
"branches_needed=return_branches(data_index=data_index, mother_index=mother_index, l_index=l_index)\n",
"for branch in branches_needed:\n",
" if branch!='cos_thetal':\n",
" data_tuple_dict[branch] = rn.root2array(\n",
" \n",
" filenames=find_file_path(l_index, mother_index=mother_index),\n",
" treename = tree_name_Ds,\n",
" branches = branch,\n",
" start=0,\n",
" stop=t_data.GetEntries(),\n",
" )\n",
" \n",
"data_tuple_dict = fix_mass_vector(data_tuple_dict, 'Ds_ConsD_M')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Phi Mass Cut "
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"#for plot purposes\n",
"#data_tuple_dict_phi_cut=data_tuple_dict\n",
"\n",
"if apply_phi_mass_cut:\n",
" \n",
" if l_flv[l_index]=='mu':\n",
" lower_phi_mass = 990\n",
" upper_phi_mass = 1050\n",
" \n",
" if l_flv[l_index]=='e':\n",
" lower_phi_mass = 870\n",
" upper_phi_mass = 1110\n",
" \n",
" data_tuple_dict =filter_tuple_mass_cut(locals(), data_tuple_dict, l_index, \n",
" 'phi_M', lower_bound=lower_phi_mass, upper_bound=upper_phi_mass, \n",
" cut_kind='inside', include_costhetal = False)\n",
" \n",
"##nice plot\n",
"#for i in range(20):\n",
"# \n",
"# upper_cut=np.arange(800+5*i,1100-5*i).max()\n",
"# lower_cut=np.arange(800+5*i,1100-5*i).min()\n",
"# plt.clf()\n",
"# data_tuple_dict_phi_cut=filter_tuple_mass_cut(globals(), data_tuple_dict_phi_cut, l_index, 'phi_M', lower_bound=lower_cut, upper_bound=upper_cut)\n",
"# plt.hist(data_tuple_dict_phi_cut['Ds_ConsD_M'],bins=40);\n",
"# plt.savefig('plot_{0}.png'.format(i))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# PID Cut "
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"if l_flv[l_index]=='mu':\n",
" lPID_cut = 0.4\n",
" piPID_cut = 0.6\n",
" \n",
" \n",
"if l_flv[l_index]=='e':\n",
" lPID_cut = 0.2\n",
" piPID_cut = 0.6\n",
" \n",
"data_tuple_dict_eplusPID =filter_tuple_cond(locals(), data_tuple_dict, l_index, l_flv[l_index]+\"_plus_MC15TuneV1_ProbNN\"+l_flv[l_index], cmp_gte, lPID_cut, include_costhetal=False)\n",
"data_tuple_dict_eminusPID =filter_tuple_cond(locals(), data_tuple_dict_eplusPID, l_index, l_flv[l_index]+\"_minus_MC15TuneV1_ProbNN\"+l_flv[l_index], cmp_gte, lPID_cut, include_costhetal=False)\n",
"data_tuple_dict_presel =filter_tuple_cond(locals(), data_tuple_dict_eminusPID, l_index, 'pi_MC15TuneV1_ProbNNpi', cmp_gte, piPID_cut, include_costhetal=False)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Add cos_thetal branch & save preselection"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"costheta_Ds=get_costheta_list(data_tuple_dict_presel, l_index=l_index, mother_index=mother_index)\n",
"data_tuple_dict_presel[\"cos_thetal\"]=costheta_Ds\n",
"\n",
"save_tuples(locals(), data_tuple_dict_presel, l_index, save_path_presel_data, file_format='pickle')\n",
"save_tuples(locals(), data_tuple_dict_presel, l_index, save_path_presel_data, file_format='root')\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Get Hlt cuts "
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Hlt1\n",
"Overwriting pickle file at/disk/lhcb_data/davide/Rphipi_new/data/mu_tuples/trigged/Ds_phipi_mumu_Hlt1.pickle\n",
"Hlt1\n",
"Saving root file at/disk/lhcb_data/davide/Rphipi_new/data/mu_tuples/trigged/Ds_phipi_mumu_Hlt1.root\n",
"Hlt2\n",
"Overwriting pickle file at/disk/lhcb_data/davide/Rphipi_new/data/mu_tuples/trigged/Ds_phipi_mumu_Hlt2.pickle\n",
"Hlt2\n",
"Saving root file at/disk/lhcb_data/davide/Rphipi_new/data/mu_tuples/trigged/Ds_phipi_mumu_Hlt2.root\n",
"FullHlt\n",
"Overwriting pickle file at/disk/lhcb_data/davide/Rphipi_new/data/mu_tuples/trigged/Ds_phipi_mumu_FullHlt.pickle\n",
"FullHlt\n",
"Saving root file at/disk/lhcb_data/davide/Rphipi_new/data/mu_tuples/trigged/Ds_phipi_mumu_FullHlt.root\n"
]
}
],
"source": [
"data_tuple_dict_presel_Hlt1 = filter_tuple_cond(locals(), data_tuple_dict_presel, l_index, 'Ds_Hlt1TrackMVADecision_TOS', cmp_eq, True)\n",
"\n",
"data_tuple_dict_presel_Hlt2 = filter_tuple_cond(locals(), data_tuple_dict_presel, l_index, \"Ds_Hlt2RareCharmD2Pi\"+l_flv[l_index].capitalize()+l_flv[l_index].capitalize()+\"OSDecision_TOS\",cmp_eq, True)\n",
"\n",
"data_tuple_dict_presel_FullHlt = filter_tuple_cond(locals(), data_tuple_dict_presel_Hlt1, l_index, \"Ds_Hlt2RareCharmD2Pi\"+l_flv[l_index].capitalize()+l_flv[l_index].capitalize()+\"OSDecision_TOS\",cmp_eq, True)\n",
"\n",
"save_tuples(locals(), data_tuple_dict_presel_Hlt1, l_index, save_path_trigged_data, file_format='pickle')\n",
"save_tuples(locals(), data_tuple_dict_presel_Hlt1, l_index, save_path_trigged_data, file_format='root')\n",
"\n",
"save_tuples(locals(), data_tuple_dict_presel_Hlt2, l_index, save_path_trigged_data, file_format='pickle')\n",
"save_tuples(locals(), data_tuple_dict_presel_Hlt2, l_index, save_path_trigged_data, file_format='root')\n",
"\n",
"save_tuples(locals(), data_tuple_dict_presel_FullHlt, l_index, save_path_trigged_data, file_format='pickle')\n",
"save_tuples(locals(), data_tuple_dict_presel_FullHlt, l_index, save_path_trigged_data, file_format='root')\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Split in trigger categories\n",
"\n",
" if trig_cat == 0:\n",
" #Exclusive L0_Lepton_TOS \n",
" \n",
" if trig_cat == 1:\n",
" #Exclusive L0_Global_TIS\n",
" \n",
" if trig_cat == 2:\n",
" #L0_Lepton_TOS and L0_Global_TIS\n",
" \n",
" if trig_cat == 3:\n",
" #Either L0_Lepton_TOS or L0_Global_TIS\n",
" \n",
" if trig_cat == 4:\n",
" #TOS and TOSandTIS\n",
"\n",
" if trig_cat == 5:\n",
" #TIS and TOSandTIS\n",
"\n",
" \n",
" "
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The counts are coming back\n",
"Overwriting pickle file at/disk/lhcb_data/davide/Rphipi_new/data/mu_tuples/trigged/trigCats/0/Ds_phipi_mumu_trigCat0.pickle\n",
"Overwriting pickle file at/disk/lhcb_data/davide/Rphipi_new/data/mu_tuples/trigged/trigCats/1/Ds_phipi_mumu_trigCat1.pickle\n",
"Overwriting pickle file at/disk/lhcb_data/davide/Rphipi_new/data/mu_tuples/trigged/trigCats/2/Ds_phipi_mumu_trigCat2.pickle\n",
"Overwriting pickle file at/disk/lhcb_data/davide/Rphipi_new/data/mu_tuples/trigged/trigCats/3/Ds_phipi_mumu_trigCat3.pickle\n",
"Overwriting pickle file at/disk/lhcb_data/davide/Rphipi_new/data/mu_tuples/trigged/trigCats/4/Ds_phipi_mumu_trigCat4.pickle\n",
"Overwriting pickle file at/disk/lhcb_data/davide/Rphipi_new/data/mu_tuples/trigged/trigCats/5/Ds_phipi_mumu_trigCat5.pickle\n",
"Saving root file at/disk/lhcb_data/davide/Rphipi_new/data/mu_tuples/trigged/trigCats/0/Ds_phipi_mumu_trigCat0.root\n",
"Saving root file at/disk/lhcb_data/davide/Rphipi_new/data/mu_tuples/trigged/trigCats/1/Ds_phipi_mumu_trigCat1.root\n",
"Saving root file at/disk/lhcb_data/davide/Rphipi_new/data/mu_tuples/trigged/trigCats/2/Ds_phipi_mumu_trigCat2.root\n",
"Saving root file at/disk/lhcb_data/davide/Rphipi_new/data/mu_tuples/trigged/trigCats/3/Ds_phipi_mumu_trigCat3.root\n",
"Saving root file at/disk/lhcb_data/davide/Rphipi_new/data/mu_tuples/trigged/trigCats/4/Ds_phipi_mumu_trigCat4.root\n",
"Saving root file at/disk/lhcb_data/davide/Rphipi_new/data/mu_tuples/trigged/trigCats/5/Ds_phipi_mumu_trigCat5.root\n"
]
}
],
"source": [
"data_tuple_dict_presel_trigCats = {}\n",
"\n",
"for i in range(n_cats):\n",
" \n",
" data_tuple_dict_presel_trigCats[i] = filter_tuple_L0TrigCat(locals(), data_tuple_dict_presel_FullHlt, l_index, trig_cat=i)\n",
" \n",
"n_0=data_tuple_dict_presel_trigCats[0]['Ds_ConsD_M'].shape[0]\n",
"n_1=data_tuple_dict_presel_trigCats[1]['Ds_ConsD_M'].shape[0]\n",
"n_2=data_tuple_dict_presel_trigCats[2]['Ds_ConsD_M'].shape[0]\n",
"n_3=data_tuple_dict_presel_trigCats[3]['Ds_ConsD_M'].shape[0]\n",
"n_4=data_tuple_dict_presel_trigCats[4]['Ds_ConsD_M'].shape[0]\n",
"n_5=data_tuple_dict_presel_trigCats[5]['Ds_ConsD_M'].shape[0]\n",
"\n",
"sanity=np.array_equal([n_0+n_2+n_1==n_3,n_0+n_5==n_3,n_4+n_1==n_3],[True,True,True])\n",
"\n",
"if sanity:\n",
" print('The counts are coming back')\n",
" \n",
" save_tuples(locals(), data_tuple_dict_presel_trigCats, l_index, save_path_trigCats_data, file_format='pickle')\n",
" save_tuples(locals(), data_tuple_dict_presel_trigCats, l_index, save_path_trigCats_data, file_format='root')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Prepare Bkg Sets for BDT"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"for_BDT\n",
"Saving pickle file at/disk/lhcb_data/davide/Rphipi_new/data/mu_tuples/for_BDT/Ds_phipi_mumu_for_BDT.pickle\n",
"for_BDT\n",
"Saving root file at/disk/lhcb_data/davide/Rphipi_new/data/mu_tuples/for_BDT/Ds_phipi_mumu_for_BDT.root\n"
]
}
],
"source": [
"if l_flv[l_index]=='mu':\n",
" \n",
" lower_Dplus_mass_data=1830\n",
" upper_Dplus_mass_data=1910\n",
" \n",
" lower_Ds_mass_data=1930\n",
" upper_Ds_mass_data=2010\n",
" \n",
" \n",
"if l_flv[l_index]=='e':\n",
" \n",
" lower_Dplus_mass_data=1810\n",
" upper_Dplus_mass_data=1920\n",
"\n",
" lower_Ds_mass_data=1920\n",
" upper_Ds_mass_data=2020\n",
" \n",
"data_Ds_tuple_dict_bkg_1 = filter_tuple_mass_cut(locals(), data_tuple_dict_presel_FullHlt, l_index, 'Ds_ConsD_M', lower_bound=lower_Dplus_mass_data, upper_bound=upper_Dplus_mass_data, cut_kind='outside')\n",
"data_Ds_tuple_dict_bkg_for_BDT = filter_tuple_mass_cut(locals(), data_Ds_tuple_dict_bkg_1, l_index, 'Ds_ConsD_M', lower_bound=lower_Ds_mass_data, upper_bound=upper_Ds_mass_data, cut_kind='outside')\n",
" \n",
"save_tuples(locals(), data_Ds_tuple_dict_bkg_for_BDT, l_index, save_path_BDT_for_data, file_format='pickle')\n",
"save_tuples(locals(), data_Ds_tuple_dict_bkg_for_BDT, l_index, save_path_BDT_for_data, file_format='root') \n"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.hist(data_Ds_tuple_dict_bkg_for_BDT['Ds_ConsD_M'], bins=70);"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.hist(data_Ds_tuple_dict_bkg_for_BDT['cos_thetal'], bins=70);"
]
},
{
"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