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notebooks/thesis_efficiencies.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import uproot\n",
+    "import numpy as np\n",
+    "import sys\n",
+    "import os\n",
+    "import matplotlib\n",
+    "import matplotlib.pyplot as plt\n",
+    "import mplhep\n",
+    "from mpl_toolkits import mplot3d\n",
+    "import itertools\n",
+    "import awkward as ak\n",
+    "from scipy.optimize import curve_fit\n",
+    "from utils.components import unique_name_ext_re\n",
+    "mplhep.style.use([\"LHCbTex2\"])\n",
+    "plt.rcParams[\"savefig.dpi\"] = 600\n",
+    "%matplotlib inline"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "file = uproot.open(\n",
+    "    \"/work/cetin/LHCb/reco_tuner/data/resolutions_and_effs_B_thesis.root:Track/MatchTrackChecker_8319528f/Match;1\",\n",
+    ")\n",
+    "\n",
+    "P_recoed = file[\"01_long_P_reconstructed;1\"].to_numpy()\n",
+    "P_recoable = file[\"01_long_P_reconstructible;1\"].to_numpy()\n",
+    "\n",
+    "Pt_recoed = file[\"01_long_Pt_reconstructed;1\"].to_numpy()\n",
+    "Pt_recoable = file[\"01_long_Pt_reconstructible;1\"].to_numpy()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "control eff:  0.8626619913200968\n",
+      "new eff:  0.8626619913200968\n"
+     ]
+    }
+   ],
+   "source": [
+    "P_Velo_recoed = file[\"01_long_EndVelo_P_reconstructed;1\"].to_numpy()\n",
+    "P_Velo_recoable = file[\"01_long_EndVelo_P_reconstructible;1\"].to_numpy()\n",
+    "\n",
+    "print(\"control eff: \", np.sum(P_recoed[0]) / np.sum(P_recoable[0]))\n",
+    "print(\"new eff: \", np.sum(P_Velo_recoed[0]) / np.sum(P_Velo_recoable[0]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "control eff:  0.8629752409817771\n",
+      "new eff:  0.8629752409817771\n"
+     ]
+    }
+   ],
+   "source": [
+    "Pt_Velo_recoed = file[\"01_long_EndVelo_Pt_reconstructed;1\"].to_numpy()\n",
+    "Pt_Velo_recoable = file[\"01_long_EndVelo_Pt_reconstructible;1\"].to_numpy()\n",
+    "\n",
+    "print(\"control eff: \", np.sum(Pt_recoed[0]) / np.sum(Pt_recoable[0]))\n",
+    "print(\"new eff: \", np.sum(Pt_Velo_recoed[0]) / np.sum(Pt_Velo_recoable[0]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
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+       "        3.49000e+02, 3.05000e+02, 3.24000e+02, 2.83000e+02, 3.18000e+02]),\n",
+       " array([     0.,   1000.,   2000.,   3000.,   4000.,   5000.,   6000.,\n",
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+       "         98000.,  99000., 100000.]))"
+      ]
+     },
+     "execution_count": 27,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "P_recoable"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "tuner",
+   "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": "3.10.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}