{
 "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",
    "import seaborn as sns\n",
    "from scipy.optimize import curve_fit\n",
    "from utils.components import unique_name_ext_re\n",
    "\n",
    "mplhep.style.use([\"LHCbTex2\"])\n",
    "plt.rcParams[\"savefig.dpi\"] = 600\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "38525"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "file = uproot.open(\n",
    "    \"/work/cetin/LHCb/reco_tuner/data/tracking_losses_ntuple_B_upstream.root:PrDebugTrackingLosses.PrDebugTrackingTool/Tuple;1\"\n",
    "    # \"/work/cetin/LHCb/reco_tuner/data/tracking_losses_ntuple_B_def.root:PrDebugTrackingLosses.PrDebugTrackingTool/Tuple;1\"\n",
    ")\n",
    "\n",
    "# selektiere nur elektronen von B->K*ee\n",
    "allcolumns = file.arrays()\n",
    "electrons = allcolumns[(allcolumns.isElectron) & (allcolumns.fromB)]\n",
    "\n",
    "ak.num(electrons, axis=0)\n",
    "# ak.count(found, axis=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# electrons.type.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "cut_prop: bool = electrons.p_end_velo > 0  # 3e3\n",
    "found = electrons[~electrons.lost]\n",
    "lost = electrons[electrons.lost]\n",
    "\n",
    "eloss_found = (found[\"p\"] - found[\"p_upstream\"]) / found[\"p\"]\n",
    "eloss_lost = (lost[\"p\"] - lost[\"p_upstream\"]) / lost[\"p\"]\n",
    "\n",
    "eloss = (electrons[\"p\"] - electrons[\"p_upstream\"]) / electrons[\"p\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "eloss_velo_found = (found[\"p\"] - found[\"p_end_velo\"]) / found[\"p\"]\n",
    "eloss_velo_lost = (lost[\"p\"] - lost[\"p_end_velo\"]) / lost[\"p\"]\n",
    "\n",
    "eloss_velo = (electrons[\"p\"] - electrons[\"p_end_velo\"]) / electrons[\"p\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1200x900 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nbins = 50\n",
    "plt.hist(\n",
    "    ak.to_numpy(eloss_lost),\n",
    "    bins=nbins,\n",
    "    density=True,\n",
    "    alpha=0.5,\n",
    "    histtype=\"bar\",\n",
    "    color=\"#F05342\",\n",
    "    label=\"lost\",\n",
    "    range=[0.001, 1],\n",
    ")\n",
    "# #2A9D8F another teal color\n",
    "plt.hist(\n",
    "    ak.to_numpy(eloss_found),\n",
    "    bins=nbins,\n",
    "    density=True,\n",
    "    alpha=0.5,\n",
    "    histtype=\"bar\",\n",
    "    color=\"#107E7D\",\n",
    "    label=\"found\",\n",
    "    range=[0.001, 1],\n",
    ")\n",
    "\n",
    "plt.xlabel(r\"$E_\\gamma/E_0$\")\n",
    "plt.ylabel(\"Number of Tracks (normalised)\")\n",
    "mplhep.lhcb.text(\"Simulation\")\n",
    "plt.legend(loc=\"upper center\")\n",
    "plt.show()\n",
    "# plt.savefig(\n",
    "#     \"/work/cetin/Projektpraktikum/thesis/emitted_energy_beginVelo2endT.pdf\",\n",
    "#     format=\"PDF\",\n",
    "# )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "sorted_eloss_found = ak.to_numpy(ak.sort(eloss_found))\n",
    "sorted_eloss_lost = ak.to_numpy(ak.sort(eloss_lost))\n",
    "sorted_eloss = ak.to_numpy(ak.sort(eloss))\n",
    "sorted_eloss_velo = ak.to_numpy(ak.sort(eloss_velo))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x900 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nbins = 50\n",
    "plt.hist(\n",
    "    ak.to_numpy(eloss_velo),\n",
    "    bins=nbins,\n",
    "    density=True,\n",
    "    alpha=0.6,\n",
    "    histtype=\"bar\",\n",
    "    color=\"#2A9D8F\",\n",
    "    label=\"electrons\",\n",
    "    range=[0.001, 1],\n",
    ")\n",
    "mean_eloss = np.mean(ak.to_numpy(eloss_velo))\n",
    "plt.vlines(\n",
    "    mean_eloss,\n",
    "    ymin=0,\n",
    "    ymax=3.5,\n",
    "    colors=\"#F05342\",\n",
    "    label=f\"mean: {np.round(mean_eloss,2)} $E_0$\",\n",
    ")\n",
    "median_eloss = np.median(sorted_eloss_velo)\n",
    "plt.vlines(\n",
    "    median_eloss,\n",
    "    ymin=0,\n",
    "    ymax=3.5,\n",
    "    colors=\"#0B3954\",\n",
    "    label=f\"median: {np.round(median_eloss,2)} $E_0$\",\n",
    ")\n",
    "\n",
    "plt.xlabel(r\"$E_\\gamma/E_0$\")\n",
    "plt.ylabel(\"Number of Tracks (normalised)\")\n",
    "mplhep.lhcb.text(\"Simulation\", loc=0)\n",
    "plt.legend()  # loc=\"upper center\")\n",
    "# plt.show()\n",
    "plt.savefig(\n",
    "    \"/work/cetin/Projektpraktikum/thesis/emitted_energy_velo_mean.pdf\",\n",
    "    format=\"PDF\",\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x900 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nbins = 50\n",
    "plt.hist(\n",
    "    ak.to_numpy(eloss_magnet_lost),\n",
    "    bins=nbins,\n",
    "    density=True,\n",
    "    alpha=0.5,\n",
    "    histtype=\"bar\",\n",
    "    color=\"#F05342\",\n",
    "    label=\"lost\",\n",
    "    range=[0.001, 1],\n",
    ")\n",
    "# #2A9D8F another teal color\n",
    "plt.hist(\n",
    "    ak.to_numpy(eloss_magnet_found),\n",
    "    bins=nbins,\n",
    "    density=True,\n",
    "    alpha=0.5,\n",
    "    histtype=\"bar\",\n",
    "    color=\"#107E7D\",\n",
    "    label=\"found\",\n",
    "    range=[0.001, 1],\n",
    ")\n",
    "\n",
    "plt.xlabel(r\"$E_\\gamma/E_{VELO}$\")\n",
    "plt.ylabel(\"Number of Tracks (normalised)\")\n",
    "# plt.title(r'$B\\rightarrow K^\\ast ee$, $p>5$GeV, photons w/ brem_vtx_z$<9500$mm')\n",
    "plt.legend(loc=\"best\")\n",
    "mplhep.lhcb.text(\"Simulation\", loc=0)\n",
    "plt.show()\n",
    "# plt.savefig(\n",
    "#     \"/work/cetin/Projektpraktikum/thesis/emitted_energy_endVelo2endT.pdf\",\n",
    "#     format=\"PDF\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x900 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nbins = 50\n",
    "plt.hist(\n",
    "    ak.to_numpy(eloss_velo_lost),\n",
    "    bins=nbins,\n",
    "    density=True,\n",
    "    alpha=0.5,\n",
    "    histtype=\"bar\",\n",
    "    color=\"#F05342\",\n",
    "    label=\"lost\",\n",
    "    range=[0.001, 1],\n",
    ")\n",
    "# #2A9D8F another teal color\n",
    "plt.hist(\n",
    "    ak.to_numpy(eloss_velo_found),\n",
    "    bins=nbins,\n",
    "    density=True,\n",
    "    alpha=0.5,\n",
    "    histtype=\"bar\",\n",
    "    color=\"#107E7D\",\n",
    "    label=\"found\",\n",
    "    range=[0.001, 1],\n",
    ")\n",
    "\n",
    "plt.xlabel(r\"$E_\\gamma/E_0$\")\n",
    "# plt.ylabel(\"a.u.\")\n",
    "plt.ylabel(\"Number of Tracks (normalised)\")\n",
    "\n",
    "# plt.title(r'$B\\rightarrow K^\\ast ee$, $p>5$GeV, photons w/ brem_vtx_z$<9500$mm')\n",
    "plt.legend(loc=\"best\")\n",
    "mplhep.lhcb.text(\"Simulation\", loc=0)\n",
    "plt.show()\n",
    "# plt.savefig(\n",
    "#     \"/work/cetin/Projektpraktikum/thesis/emitted_energy_beginVelo2endVelo.pdf\",\n",
    "#     format=\"PDF\",\n",
    "# )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "### --- ### above should be correct"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x900 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nbins = 50\n",
    "plt.hist(\n",
    "    ak.to_numpy(lost[\"eta\"]),\n",
    "    bins=nbins,\n",
    "    density=True,\n",
    "    alpha=0.5,\n",
    "    histtype=\"bar\",\n",
    "    color=\"#F05342\",\n",
    "    label=\"lost\",\n",
    "    range=[2, 5],\n",
    ")\n",
    "# #2A9D8F another teal color\n",
    "plt.hist(\n",
    "    ak.to_numpy(found[\"eta\"]),\n",
    "    bins=nbins,\n",
    "    density=True,\n",
    "    alpha=0.5,\n",
    "    histtype=\"bar\",\n",
    "    color=\"#107E7D\",\n",
    "    label=\"found\",\n",
    "    range=[2, 5],\n",
    ")\n",
    "# plt.xlim(2, 5)\n",
    "plt.xlabel(r\"$\\eta$\")\n",
    "plt.ylabel(\"Number of Tracks (normalised)\")\n",
    "plt.legend(loc=\"best\")\n",
    "mplhep.lhcb.text(\"Simulation\", loc=0)\n",
    "# plt.show()\n",
    "plt.savefig(\n",
    "    \"/work/cetin/Projektpraktikum/thesis/eta_found_lost.pdf\",\n",
    "    format=\"PDF\",\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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MRqPI5/Px6tWrW+8PAAAA4L4Iwm6o1WpNb+/u7p67XZIk0W63I+LTNMLt7e1zt61Wq1Gv12Nvby+KxeLcIvd3NXa/34/19fXI5XJRrVYvnG45Go2mXXVv3761UD4AAACwUgRhN1QoFKbdVoPBIPb29s7c7unTpxHx6cIAs91ZZzk51fGbb76587E7nc40cOv3+1Eul+emX87WVi6XY2NjI4bDYZRKpQuPBQAAAGDZCMJuYWtrK3q9XuTz+Wg0GlGr1WIwGESSJNPgaDAYRKlUiu++++7SDqqTPy8UCnc+dq1WO/VYu92O9fX1qNVqUa/Xo1wuR7Vaje3t7djf37+wLgAAAIBlJQi7pUqlEoeHh9FsNmM0GsXTp0+nIdLGxkZ0Op3Y39+/0jTCTqcThUIh8vl87OzsXLqw/SLGrlQqMRwOY3t7ezr2xGAwiI8fP8arV6+m45gOCQAAAKyq3Hg8HqddBNm2ubkZHz58iEePHsX79+/TLuda/uf/+ou0SwAAACCj/sd/++9pl3AjaeYAOsIAAAAAyARBGAAAAACZIAgDAAAAIBMEYQAAAABkgiAMAAAAgEwQhAEAAACQCYIwAAAAADJBEAYAAABAJgjCAAAAAMgEQRgAAAAAmSAIAwAAACATBGEAAAAAZIIgDAAAAIBMEIQBAAAAkAmCMAAAAAAyQRAGAAAAQCYIwgAAAADIhC/SLgAmDg4OYnNz88JtXr58GS9fvrynigAAAIDreP36dbx+/frCbQ4ODu6pmtMEYSyN4+Pj+PDhw4XbHB0d3VM1AAAAwHUdHR1dem6fJkEYS+PBgwfx8OHDC7dZW1u7p2oAAACA61pbW4tHjx5duM3BwUEcHx/fU0XzBGEsjYcPH8b79+/TLgMAAAC4oassabS5uZla15jF8gEAAADIBEEYAAAAAJkgCAMAAAAgEwRhAAAAAGSCIAwAAACATBCEAQAAAJAJgjAAAAAAMkEQBgAAAEAmCMIAAAAAyARBGAAAAACZIAgDAAAAIBMEYQAAAABkgiAMAAAAgEwQhAEAAACQCYIwAAAAADJBEAYAAABAJgjCAAAAAMgEQRgAAAAAmSAIAwAAACATBGEAAAAAZIIgDAAAAIBMEIQBAAAAkAmCMAAAAAAyQRAGAAAAQCYIwgAAAADIBEEYAAAAAJkgCAMAAAAgEwRhAAAAAGSCIAwAAACATPgi7QJg4uDgIDY3Ny/c5uXLl/Hy5ct7qggAAAC4jtevX8fr168v3Obg4OCeqjlNEMbSOD4+jg8fPly4zdHR0T1VAwAAAFzX0dHRpef2aRKEsTQePHgQDx8+vHCbtbW1e6oGAAAAuK61tbV49OjRhdscHBzE8fHxPVU0TxDG0nj48GG8f/8+7TIAAACAG7rKkkabm5updY1ZLB8AAACATBCEAQAAAJAJgjAAAAAAMkEQBgAAAEAmCMIAAAAAyARBGAAAAACZIAgDAAAAIBMEYQAAAABkgiAMAAAAgEwQhAEAAACQCYIwAAAAADJBEAYAAABAJgjCAAAAAMgEQRgAAAAAmSAIAwAAACATBGEAAAAAZIIgDAAAAIBMEIQBAAAAkAmCMAAAAAAyQRAGAAAAQCYIwgAAAADIBEEYAAAAAJkgCAMAAAAgEwRhAAAAAGSCIAwAAACATBCEAQAAAJAJgjAAAAAAMkEQBgAAAEAmCMIAAAAAyIQv0i4AJg4ODmJzc/PCbV6+fBkvX768p4oAAACA63j9+nW8fv36wm0ODg7uqZrTBGEsjePj4/jw4cOF2xwdHd1TNQAAAMB1HR0dXXpunyZBGEvjwYMH8fDhwwu3WVtbu6dqAAAAgOtaW1uLR48eXbjNwcFBHB8f31NF8wRhLI2HDx/G+/fv0y4DAAAAuKGrLGm0ubmZWteYxfIBAAAAyARBGAAAAACZIAgDAAAAIBMEYQAAAABkgiAMAAAAgEwQhAEAAACQCYIwAAAAADJBEAYAAABAJgjCAAAAAMgEQRgAAAAAmSAIAwAAACATBGEAAAAAZIIgDAAAAIBMEIQBAAAAkAmCMAAAAAAyQRAGAAAAQCYIwgAAAADIBEEYAAAAAJkgCAMAAAAgEwRhAAAAAGSCIAwAAACATBCEAQAAAJAJgjAAAAAAMkEQBgAAAEAmCMIAAAAAyARBGAAAAACZIAgDAAAAIBMEYQAAAABkgiAMAAAAgEz4Iu0CYOLg4CA2Nzcv3Obly5fx8uXLe6oIAAAAuI7Xr1/H69evL9zm4ODgnqo5TRDG0jg+Po4PHz5cuM3R0dE9VQMAAABc19HR0aXn9mkShLE0Hjx4EA8fPrxwm7W1tXuqBgAAALiutbW1ePTo0YXbHBwcxPHx8T1VNE8QxtJ4+PBhvH//Pu0yAAAAgBu6ypJGm5ubqXWNWSwfAAAAgEwQhAEAAACQCYIwAAAAADJBEAYAAABAJgjCAAAAAMgEQRgAAAAAmSAIAwAAACATBGEAAAAAZIIgDAAAAIBMEIQBAAAAkAmCMAAAAAAy4Yu0CwD+w//55d/G//vXf43/9OWX8Z//639Juxw+A95TLJL3E4vmPcUieT+xaN5TLJL30/IQhMES+b9/87/j6PvvY+2HP/ThyEJ4T7FI3k8smvcUi+T9xKJ5T7FI3k/Lw9RIAAAAADJBEAYAAABAJgjCAAAAAMgEQdiC7O3tRbVajfX19cjlclEsFqNWq0W/31/JsdM8HgAAAIC7IAi7pX6/H+vr69FoNCIiotPpxHA4jGazGYPBIKrValSr1UiSZCXGTvN4AAAAAO6Sq0beQr/fj2q1GhER29vb0Wq1pj8rFAqxtbUV5XI5+v1+lMvl2N/fj3w+v7Rjp3k8AAAAAHdNR9gNJUkStVotIj6FRLOh0axOpxMREaPRaLr9Mo6d5vEAAAAA3AcdYTdUq9Wm0wMn0wjPMumk6na70e/3o91ux/b29tKNnebxXOb169dxdHQUa2tr8fLlyzsdaxnGTcP/+eXfxv/713+N//Tll/Gf/+t/+azHzdKxpiVrr3HWxk1Dll7jLB1rWrL2Gmdt3DRk6TXO0rGmJWuvcdbGTYPz6dMEYTcwGo3mFo1/9uzZhds/f/48ut1uRHwKmW4THN3F2Gkez1W8fv06Pnz4EI8ePbr3/7hpjJuG//s3/zuOvv8+1n74w3v9RZDGuFk61rRk7TXO2rhpyNJrnKVjTUvWXuOsjZuGLL3GWTrWtGTtNc7auGlwPn2aqZE30Gw2p7crlcql62RtbW1NbydJMg2RlmXsNI8HAAAA4L4Iwm6g3W5Pb5dKpSs9p1AoTG+/efNmqcZO83gAAAAA7osg7JoGg8Hc/SdPnlzpebMB0007qO5i7DSPBwAAAOA+CcKuaXYtrYj5zqiLnNzuZACV1thpHg8AAADAfRKEXdO33347d/+y9bQmfvSjH83df/fu3VKMnebxAAAAANwnQdg1jUajufs37aAaDodLMXaaxwMAAABwnwRh13QyOLqpJEmWYuw0jwcAAADgPuXG4/E47SJWSS6Xm7t/1Zev3+9HtVqd3t/a2opOp5P62Gkez8Tv/u7vxr//+79HRMSDB6ez2ePj4+nts35+0g9+8IP4vd/7vRvVMuvg4CCOj4/jwYMH8fDhwzO3+aff/ObW48zt7+goxuNx5HK5+MHa2kL3bdz0xszauFk61qyNm6VjTWvcLB1rWuNm6VizNm6WjjWtcbN0rGmNm6Vjzdq4dzXmDy45973Kee11/OY3v4l/+qd/unS7y87jJz//nd/5nfi3f/u3W9d1HV/c62hMpdlBdRdj32afv/3tb6e3Z/+znOWyn0dEfP/99/H999/fuJ6zxvzw4cPC9ncV4/E4jhZ4DMZdjjGzNm6WjjVr42bpWNMaN0vHmta4WTrWrI2bpWNNa9wsHWta42bpWLM27qLHvOq+0jivnR37PLN5wH0RhF1TPp9fSJB01UXp73rsNI9n4ssvv4x/+Zd/ifF4fKWOr8ssqiMMAAAA+A9X7Qi7zPHxceRyufjyyy8XUNX1CMKuaWNjYyHB0cbGxlKMnebxTPzzP//zrccHAAAAuIzF8q/ppp1PJ8Omm3aELXrsNI8HAAAA4D4Jwq7p8ePHc/ev2k318ePHufvFYnEpxk7zeAAAAADukyDsmsrl8tz90Wh0pecNh8O5+5VKZSnGTvN4AAAAAO6TIOyaTnZQXTU4mu20yufzUSgUlmLsNI8HAAAA4D4Jwq6pVCrNrYf17bffXul57969m94+GT6lOXaaxwMAAABwnwRhN/Ds2bPp7cFgcKXnzG7XaDSWauw0jwcAAADgvuTG4/E47SJWzWAwmFtb67KXsN/vR7VajYiIQqFwan2ttMdO83gAAAAA7ouOsBsolUpzi8N3u90Lt+90OtPbl3VPtdvtaDQa567VdRdj3+XxAAAAACwLHWE3NBqNolgsRsSnIGl/f//M7ZIkifX19Yj4dGXFXq937j6r1Wr0+/3p/cPDw7n1u+5y7LvYJwAAAMAy0RF2Q4VCYdoZNRgMYm9v78ztnj59GhGfrqw420l1ltkQLCLim2++ubex72KfAAAAAMtEEHYLW1tb0ev1Ip/PR6PRiFqtFoPBIJIkiX6/H+VyOQaDQZRKpfjuu+/O7O6adfLnhULh3sa+q30CAAAALAtB2C1VKpU4PDyMZrMZo9Eonj59Guvr61Gr1WJjYyM6nU7s7+9fKTTqdDpRKBQin8/Hzs7O3Lpddz32Xe6TxRmNRlGv16NYLEYul4v19fUol8tRr9fPXVcOzjMYDObeT7lcLorFYjQajUiSJO3y+AyMRqOoVquXrj1Jtuzt7UW1Wo319fXp506tVjvVGQ9X4XOGRfG9iEVz7rbExsBKaDab44i48F+z2Uy7TFbA4eHheGtr69L3U6vVSrtUVtTJ95j3EuPxeNzr9cb5fH4cEeNKpTLu9Xrj4XA47nQ640KhMH388PAw7VJZAT5nWBTfi7gLzt2W2xd3GbIBizG5kEI+n49KpRKFQiFGo1EMBoO5vyY0Go0oFAqxtbWVYrUssyRJolwuX+mvUPV6Pfb396PVat1DZXwOkiSJ3d3dc9eZJLv6/X5Uq9WIiNje3p77XJn83iqXy9OlGHSfcx6fMyyS70XcBeduy8/USFhyjUYj+v1+NJvNODw8jE6nE81mMzqdTgyHw2g2m3Pb12q1lCplFdRqtRiNRlEqlabvoeFwGJ1OJ3Z2dk5t3263TTfhSvb29qZrScKsJEmmv5sKhcK5J5GTi/CMRiO/yziTzxkWzfciFs2524pIuyUNON9wOBxHxLjX61243fb29lyb7f7+/j1VyCpptVrjiBjv7Oycu81wOByXSqW591M+n7/HKllF+/v7c587k/damE7CeDyuVCpXfi+Y6sZ5fM6waL4XsWjO3VZHbjwej+8rdAOup1arxZMnT878i9SsJElifX19er/ZbF76HLKnWCxGoVCIXq934Xaj0SiKxeLcY71e79ILeMDEYDCIcrk8vd9qtWJ7ezvFikjLyc+Tw8PDC6c8drvd6V/H8/l8HB4e3nWJrCifM9yW70UsmnO31WFqJCyxJEmu9KGYz+ejUCjM3YdZkzUJJlOPLlIoFE61bZuGwnX4DGJi9rOkUqlc+t6YXSclSRJTkDiXzxluw/ci7oJzt9UhCIMldtlfqGZ9/Phxevvx48d3UQ4r7M2bN7G9vX3lX7Qn/8r5j//4j3dQFfC5a7fb09ulUulKz5k9OXjz5s3CawLwvYi74NxtdbhqJHwGkiSJJEki4tMv6quebJAdz58/nzu5vMzJ99DJKQEAlznZMfHkyZMrPa9UKk2vqqUjDLgLvheRJudu6dMRBp+Bb775JiI+/RX9Ki3eZE+pVLpW2/Xkl/PEdb4sAkRE9Pv9uftX/Rw5uZ0pSMCi+V5Empy7pU8QBisuSZKo1+tRKpWi1+uZY85CTLoxJiwIC1zXt99+O3f/qr+ffvSjH83df/fu3aJKArgR34tYFOduy0EQBitsNBpFuVyOfD4fb9++9dcpFmb2xNNVuICbOHnieNOOsOFwuLCaAG7C9yIWwbnb8hCEwYrqdrtRLBZjNBpNL8G7t7eXdll8Jlqt1vR2o9FIsRJgVZ0Mwm7q5JQkgPvmexG35dxtuQjCYIUkSRJ7e3tRLBajVqud+nmj0TjzcbiO0Wg0XZOn2Wz6axVwIzcNsE5OE5m9shbAffO9iJty7ra8BGGwQvr9fgyHw6hUKueuTdDtdv11gVtpNpsR8Wl60s7OTsrVAFmnIwxIk+9F3JRzt+UlCIMVsrW1Fa1WK1qtVvR6vRiPx9FqtU799bzRaDhx4EYGg0G02+3I5/PR6/XSLgdYYYtaANhCwkBafC/iNpy7LS9BGNxAu92OXC630H/lcvlGtWxvb8f+/v6pD9R2u72AI+U+LNP76cWLFxERFvBcccv0niK7NjY2lmo/ANflexGL5txtOQjC4DNQKBTi7du3c4+dvGw9XKZer8dgMIhOpxOlUintcoAVd9NOrpN/FdcRBqTB9yLuinO39H2RdgGwiiqVSnQ6nYXu87Zf9EulUmxtbUW3242IxV2ti7u3DO+ndrsd7XY7Wq1WbG1tLbQW7t8yvKfg8ePH0wWmIz4FXFd5H51cHL9YLC66NIAL+V7EXXPuli5BGNxAoVBYyvbo58+fTz9MzTNfHWm/n/r9ftTr9Wi1WrG9vZ1aHSxO2u8piIhT02lHo9GVuiqGw+Hc/fMWGAa4C74XcV+cu6XH1Ej4jMyeYOje4CoGg0FUq9VoNpu+7AEL9fjx47n7V/1r9+zJQD6fF+oC98b3Iu6Tc7f0CMLgM3XyBAROGo1G8fTp09jZ2XE5cGDhSqXS3Bf7q65/8u7du+ltv8uA++J7EWny++5+CcLgMzL71/ZqtZpiJSy70WgU5XI5tre3o9lsXvk5e3t7d1wZ8Dl59uzZ9PbsemEXmd2u0WgsvCaAk3wvIg3O3dIjCIPPyOTkIZ/PW9iTcyVJEtVqNZ49e3blL3sREbVazVo9wLXU6/Xp7X6/f+n2s9sUCgWfOcCd872ItDh3S4/F8uEzsru7GxERX3/9dcqVsKySJIlyuRyFQiEajcaV1uwZjUbTrgyXD+cqLPjKRKlUikqlMg24ut3uhV/2Z692qhuMi/icYRF8LyJNzt3SIwiDJba3txdv3ryJSqUSr169unARxUajEUmSxM7Ojr8ocK6nT5/GaDSK0WgUxWLxWs9ttVp3VBWfm5MnEk5Ys63Vak0/b3Z3d8/9HZUkSbTb7Yj4dKVIC1VzEZ8zLILvRSySc7fVkRuPx+O0iwBOS5Ik1tfX5x7b2dk5s2W7VqtFt9uNZrNpcU/OVS6Xr7xGz1n8uuAqJn9dnz1JLZVKsb+/n2JVpK3b7UatVouIOPd31eQzKp/Px3fffecKWpzL5wyL4HsRi+TcbbVYIwyW1FmXjN/b24v19fWo1WrRaDSiWq1OP3CHw6EPUs5Vq9Vu9WVPZwYXSZIkarXa9DPpZKfGYDCIXC4X1Wr11u9FVtPW1lb0er3I5/PRaDSm74MkSaLf709PSEulkhCMM/mcYZF8L2LRnLutFh1hsMSSJInd3d3o9/sxGo0iSZLI5/OxsbERpVJpurCnEwYAVsVk6sjs77XHjx9HvV43PQSAleXcbXUIwgAAAADIBFMjAQAAAMgEQRgAAAAAmSAIAwAAACATBGEAAAAAZIIgDAAAAIBMEIQBAAAAkAmCMAAAAAAyQRAGAAAAQCYIwgAAAADIBEEYAAAAAJkgCAMAAAAgE75IuwAAAAAAltdgMIg3b95EkiTRarXSLudWBGEAAAAAzOn3+9HpdKLf78doNIqIiEqlknJVt2dqJAAAAMAlkiSJXC536b/BYJB2qbdWrVaj0WhEu92ehmDn2dvbu/Q1KRaL91T55QRhAAAAANdUKpVif38/Dg8P5/6VSqW0S7u1Xq8X+/v70ev1Lt12Z2dn7viHw+FST580NRIAAAD4LHS73ej1evHu3btIkiSGw+GdjfXq1avPIvS6yFWnQubz+bnb29vb0ev1otvt3lFlNycIAwAAAD4LjUZjOpVve3v7TseaDX84rVAopF3CmUyNBAAAAFZekiRz61nVarU7HW9jY+NO98/dEIQBAAAAK6/f78/d/xyucMjiCcIAAACAlTe7sPvW1laKlbDMBGEAAADAypvtCHv+/HmKlbDMBGEAAADASju5PtgyTotMkiT29vaiWCzOPT55LJfLRbVajSRJzt1Ht9uNWq0W5XI5crlc5HK5KBaLUa/XYzAY3Kiubrcb1Wo11tfXI5fLRblcjnq9Pvd6fk4EYQAAAMBKm+0Gq1QqS3VFx36/H7VaLdbX1+euahkRUa1W5x7r9/vRaDRO7aPb7cb6+nrUarUoFArR6XTi8PBwOh203W5HuVyOvb29K9c1Go2iWCxGrVaLjx8/RrPZjF6vF8+fP49+vx/FYvFa+1sVX6RdAAAAAMBNjEajGAwGsbu7O/d4v99PvStsb28vdnd3z+zwSpIkXrx4cWqB/4g41Yk16QKLiGg2m7GzszP9WaVSieFwGOvr65EkSTQajSgUCpeukTYYDKJcLp+7z52dnajX62eGcqtORxgAAACwMiZTDNfX16NYLEaj0ZibFtjv96NarUYul4tarXbhVMO7tL29HYeHh7G/v3/qZ998802MRqMYDocxHo/ngqtqtTq9nSTJNASLOP8iANvb29PbrVbrwrpGo9E0BNva2poLwWa1Wq0olUoX7msVCcIAAACAlTAJwBqNxjRomr1aZKlUisPDw2lg1O1246uvvjqz8+quTaZnlkqlU91pzWYz3r59G4VCISIiOp1O9Hq96HQ6c8HUN998M/e889btml137LJjnQ3Wms3mhdte9vNVZGokAAAAsNSSJImnT5/GYDCIQqEQvV5vGiKdvFpkPp+PTqcT9Xo92u32tKvqu+++S23tsJPjNhqNU4+dNZXzqt1sk9diYjQanXos4lMwOOmeK5VKZ24z6/Hjx1caf5XoCAMAAACW1mg0iq+++moagu3v788FOLMdYbNTB1ut1jRsmqzJtSyePXt2pe22t7cv7Cw7z3kB2uxaavV6/dL9LNNFBxZFEAYAAAAspSRJolqtToOdXq93KpyZdIQVCoVTHU6za2elMT3yPFcNmPL5/HSdsbPWGps4GXx9/Pjx1DaTCwtMXNYN9rkShAEAAABLqVarTdfFajabp8KbJEmmPz9rIfknT56cue2qOW/R+tFoFPV6fW7dr/OcDAKzGoRZIwwAAABYOt1udy68OevqhifXBzvprM6oz0G/349mszk9/nw+f+l6Yic7yrIahOkIAwAAAJZOo9GY3p6d4jhrsj5YPp8/s2vqZDi06uFPt9uNcrkc1Wo1+v1+bG9vx3A4jE6nc+lzV7UbbtEEYQAAAMBSGQwGc8HNeVP/Jh1R5y0+PxwOp7dXeeH30WgU1Wo1arVaDAaD2N7ejsPDw2i1WlcO9052x2U1GDM1EgAAAFgqb968mbv/+PHjU9vMrvl1WVAWcfUrNS6bfr8f1Wp1en9/f//cNcOu47KplJ8rHWEAAADAUpkNsPL5/JndXLPbVCqVUz8/uTj+VRaUXzaTTrCJTqdz4xBsY2Pj1L6zSBAGAAAALJXZbqWTAc7EZH2ws0KwiIh2uz29XSqVzt1umdXr9entUql05pUxr+rkFMrJ65c1gjAAAABgqcyuZ3Xe2l6TjrDzOr12d3ent5vN5uKKuydJksx1vZ01PfQ6ZjvLIiK++eabW+1vVQnCAAAAgKUy27101hS+2WmPZ6391Wg0pl1lOzs7S9cNdpX1ud69e7fQ/Z18DZIkiW63e+UxIk4vuL+KBGEAAADAUpkNwk6u9RXxH91gpVLpVMfYYDCIvb29iPgU/qxiN9hZZrvDTrrKNMd8Pn9qauWLFy8uDNEGg8Hc/c9hgX1BGAAAALBUXr16NXf/ZJg1CX6eP38+9/hgMIhyuRwRn0KwZVkH62SQd5Vur5Nreo1Go2nAN/tYvV6fWw8tYj7Amg2vvv7667ntkiSJp0+fnhlwjUajU9NOR6PRhYHcKhCEAQAAAEvl5MLw7XZ7LuyZhDEnt5mEYDs7O0sTgrXb7VOdVY1G49KrNhYKhVNXiGw0GlEul6Ner0e5XI5isRij0Sj29/fnttvd3Z1uM7tWWj6fj06nM7ftYDCI9fX1qNfr0e12o91uR71ej2KxeOaU0mq1Grlcbm4h/1WSG4/H47SLAAAAAJiVJEnUarW5DqStra149epVlMvlKBQKsb+/H/1+P3Z3d2MwGESpVIqvv/76VIC0qHrW19en9/f39y8c56xOrZMKhUJUKpVotVpn/nw0GkW5XD53SmKz2YydnZ2IiGkoNqtUKp0KySI+BYm1Wu3CqY7b29vRarUil8vN1Vuv12Nra+tUx9pJjUZj2sFWKBRiOBxeuP19EYQBAAAAS6vb7U6DrrPk8/l49uxZ1Ov1OwnAJq4bhC1y3BcvXsRgMIjRaBSFQmEaCM6ujzYYDKbb5fP52N7evnR9tL29vXjz5k2MRqNIkiTy+XxUKpWo1+vTbrBisRhbW1vx/Pnzax2vIAwAAADghiaL5jcajej3+9HpdKJSqZxaLP8ux08jCFtVyxqEfZF2AQAAAACXyefzUSqV4uPHj9OuKLgui+UDAAAAK2MwGCxFCPbx48e0S+AGBGEAAADASpgsnP/8+fOUK4lLr/qYdRctxJ8mUyMBAACAldDr9aZTJNPWaDSiUCjE48eP5x6/rzXLlsnJ0Ovdu3eXXjEzLYIwAAAAYCX0+/149uxZ2mVExKfwp1qtnno8a4vo7+3tRaPRSLuMK3PVSAAAAGAl5HK56PV6UalU0i6FFSUIAwAAAJbeYDCIcrkcYgxuw2L5AAAAwNLr9/tLcbVIVpuOMAAAAAAyQUcYAAAAAJkgCAMAAAAgEwRhAAAAAGSCIAwAAACATBCEAQAAAJAJgjAAAAAAMkEQBgAAAEAmCMIAAAAAyARBGAAAAACZIAgDAAAAIBMEYQAAAABkgiAMAAAAgEwQhAEAAACQCYIwAAAAADJBEAYAAABAJgjCAAAAAMgEQRgAAAAAmSAIAwAAACATBGEAAAAAZIIgDAAAAIBMEIQBAAAAkAmCMAAAAAAyQRAGAAAAQCYIwgAAAADIBEEYAAAAAJkgCAMAAAAgEwRhAAAAAGSCIAwAAACATBCEAQAAAJAJ/x8/R+kKCvQjeAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1200x900 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nbins = 50\n",
    "plt.hist(\n",
    "    ak.to_numpy(lost[\"phi\"]),\n",
    "    bins=nbins,\n",
    "    density=True,\n",
    "    alpha=0.5,\n",
    "    histtype=\"bar\",\n",
    "    color=\"#F05342\",\n",
    "    label=\"lost\",\n",
    "    range=[-3.142, 3.142],\n",
    ")\n",
    "# #2A9D8F another teal color\n",
    "plt.hist(\n",
    "    ak.to_numpy(found[\"phi\"]),\n",
    "    bins=nbins,\n",
    "    density=True,\n",
    "    alpha=0.5,\n",
    "    histtype=\"bar\",\n",
    "    color=\"#107E7D\",\n",
    "    label=\"found\",\n",
    "    range=[-3.142, 3.142],\n",
    ")\n",
    "# plt.xlim(2, 5)\n",
    "plt.xlabel(r\"$\\phi$ [rad]\")\n",
    "plt.ylabel(\"Number of Tracks (normalised)\")\n",
    "plt.legend(loc=\"best\")\n",
    "mplhep.lhcb.text(\"Simulation\", loc=0)\n",
    "plt.show()\n",
    "# plt.savefig(\n",
    "#     \"/work/cetin/Projektpraktikum/thesis/phi_found_lost.pdf\",\n",
    "#     format=\"PDF\",\n",
    "# )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# magnet kick position\n",
    "input_tree = uproot.open({\n",
    "    \"/work/cetin/LHCb/reco_tuner/data/tracking_losses_ntuple_B_upstream.root\":\n",
    "    \"PrDebugTrackingLosses.PrDebugTrackingTool/Tuple;1\"\n",
    "})\n",
    "array = input_tree.arrays()\n",
    "\n",
    "array[\"dSlope_yEndT\"] = array[\"ideal_state_9410_ty\"] - array[\n",
    "    \"ideal_state_770_ty\"]\n",
    "array[\"dSlope_yEndT_abs\"] = abs(array[\"dSlope_yEndT\"])\n",
    "\n",
    "array[\"dSlope_xEndT\"] = array[\"ideal_state_9410_tx\"] - array[\n",
    "    \"ideal_state_770_tx\"]\n",
    "array[\"dSlope_xEndT_abs\"] = abs(array[\"dSlope_xEndT\"])\n",
    "array[\"x_EndT_abs\"] = abs(array[\"ideal_state_9410_x\"])\n",
    "array[\"x_EndVelo_abs\"] = abs(array[\"ideal_state_770_x\"])\n",
    "\n",
    "array[\"y_EndT_abs\"] = abs(array[\"ideal_state_9410_y\"])\n",
    "array[\"y_EndVelo_abs\"] = abs(array[\"ideal_state_770_y\"])\n",
    "\n",
    "array[\"z_mag_xEndT\"] = (\n",
    "    array[\"ideal_state_770_x\"] - array[\"ideal_state_9410_x\"] -\n",
    "    array[\"ideal_state_770_tx\"] * array[\"ideal_state_770_z\"] +\n",
    "    array[\"ideal_state_9410_tx\"] *\n",
    "    array[\"ideal_state_9410_z\"]) / array[\"dSlope_xEndT\"]\n",
    "\n",
    "# array[\"yStraightOut\"] = array[\n",
    "#     \"ideal_state_770_y\"] + array[\"ideal_state_770_ty\"] * (\n",
    "#         array[\"ideal_state_10000_z\"] - array[\"ideal_state_770_z\"])\n",
    "# array[\"yDiffOut\"] = array[\"ideal_state_10000_y\"] - array[\"yStraightOut\"]\n",
    "\n",
    "not_e = array[(array.isProton)]\n",
    "\n",
    "array = array[(array.isElectron) & (array.fromB)]\n",
    "stretch_factor = ak.num(array[array.lost], axis=0) / ak.num(array[~array.lost],\n",
    "                                                            axis=0)\n",
    "# stretch_factor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# not_e"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 1200x900 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "xmin: float = 5100\n",
    "xmax: float = 5800\n",
    "nbins = 100\n",
    "\n",
    "fig = plt.figure()\n",
    "# plt.hist(\n",
    "#     array[\"match_zMag\"],\n",
    "#     bins=nbins,\n",
    "#     range=[xmin, xmax],\n",
    "#     color=\"#712F79\",\n",
    "#     alpha=0.5,\n",
    "#     label=\"e pred\",\n",
    "#     density=True,\n",
    "# )\n",
    "# plt.hist(\n",
    "#     not_e[\"match_zMag_def\"],\n",
    "#     bins=nbins,\n",
    "#     range=[xmin, xmax],\n",
    "#     color=\"#107E7D\",\n",
    "#     alpha=0.5,\n",
    "#     label=\"K pred\",\n",
    "#     density=True,\n",
    "# )\n",
    "# 87A330\n",
    "plt.hist(\n",
    "    not_e[\"z_mag_xEndT\"],\n",
    "    bins=nbins,\n",
    "    range=[xmin, xmax],\n",
    "    color=\"#F05342\",\n",
    "    alpha=0.5,\n",
    "    label=\"proton\",\n",
    "    density=True,\n",
    ")\n",
    "plt.hist(\n",
    "    array[\"z_mag_xEndT\"],\n",
    "    bins=nbins,\n",
    "    range=[xmin, xmax],\n",
    "    color=\"#87A330\",\n",
    "    alpha=0.5,\n",
    "    label=\"electron\",\n",
    "    density=True,\n",
    ")\n",
    "plt.xlabel(r\"$z_{\\mathrm{Mag}}$ [mm]\")\n",
    "plt.ylabel(\"Number of Tracks (normalised)\")\n",
    "plt.legend(loc=\"best\")\n",
    "mplhep.lhcb.text(\"Simulation\", loc=0)\n",
    "plt.show()\n",
    "# plt.savefig(\n",
    "#     \"/work/cetin/Projektpraktikum/thesis/match_true_zmag_e_kaon.pdf\", format=\"PDF\"\n",
    "# )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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zQVhC/ZvI3717d6j7dYdWF70S4ziPDQAAADDtBGEJde/PFdG72mqQ/nEXuSrjOI8NAAAAMO0EYQk9e/as5/aw+2i9/fbbPbefP38+VccGAAAAmHaCsIQajUbP7YuuyqrX61N1bAAAAIBpJwhLqD+MuqhmszlVxwYAAACYdoKwhC4aIvWfxvj69eupOjYAAADAtPvUuAuYVeNclTWpK8IODg7i9u3bl55nfX091tfXR1ARAAAA0La9vR3b29uXnufg4GAE1VyMICyhTCYzkiBp2I3uJ+XYV+H4+DhevXp16XmOjo5GUA0AAADQ7ejoaCTv28dJEJbQ4uLiSMKoxcXFqTr2Vbhx40bcvHnz0vPMz8+PoBoAAACg2/z8fNy6devS8xwcHMTx8fEIKkpOEJbQRVdT9QdYF10RNq5jX4WbN2/Gy5cvx10GAAAAcIpRbUV0+/btsa0ss1l+Qnfu3Om5PewKrf4N6peWlqbq2AAAAADTzoqwhPL5fM/tRqMRuVzu3PvV6/We24VCYaqODcBk+/njbww99tP3v5JiJQAAMLmsCEuof1VWo9EY6n7dq7cymUxks9mpOjYAAADAtBOEJZTL5Xr22Hr27NlQ93v+/Hnn8/5AaxqODQAAADDtBGEX8N5773U+r9VqQ92ne1ypVJrKYwMAAABMM0HYBaytrXU+r1ar547vHpPNZi+1R9c4jw0AAAAwzQRhF5DL5XoCpb29vYHjy+Vy5/PzVmTt7u5GqVQ6c/+vNI/db9irUgIAAABMA1eNvKCdnZ1YWlqKiIiHDx/GysrKqeOazWbs7u5GxJurNa6urp455/LycmcF19bWVhweHvbsCZbmsU/TH8YJxoBp85Nv188f1C33K+kUAgAATAQrwi4om812VlvVarXY2to6ddy9e/ci4s3VGrtXZ52m/1THJ0+eXNmx+zWbzRMryB4/fpxoDoBpU/3ujxJ9AAAA00UQdgkrKytRqVQik8lEqVSKYrEYtVotms1mVKvVyOfzUavVIpfLxYsXL05d3dWt//vZbPbKjh3xJvwqFouxvLwcCwsLJ1aE1Wq1mJubi+Xl5c7xAC7rJ9+uJ/oAAAC4KKdGXlKhUIjDw8PY2tqKx48fx71796LZbEYmk4k7d+5EuVw+89TFfuVyOdbW1uL169exurp67sb2ozx2xMVWjgFcNWEYAABwUXOtVqs17iKYbbdv345Xr17FrVu34uXLl+MuB7ikP/7r7yQaP0nB1n/306NE4wtf+kJKlaTr0/e/Mu4SAACYYePMAZwaCQAAAMBMEIQBAAAAMBMEYQAAAADMBJvlAzBSk7TnV9qq3/3R0GOndT8xAAC4TqwIAwAAAGAmCMIAAAAAmAmCMAAAAABmgiAMAAAAgJkgCAMAAABgJgjCAAAAAJgJnxp3AQAwC6rf/VGi8YUvfSGlSgAAYHZZEQYAAADATLAijIlxcHAQt2/fHjhmfX091tfXr6giAAAAIInt7e3Y3t4eOObg4OCKqjlJEMbEOD4+jlevXg0cc3R0dEXVAAAAAEkdHR2d+95+nARhTIwbN27EzZs3B46Zn5+/omoAAACApObn5+PWrVsDxxwcHMTx8fEVVdRLEMbEuHnzZrx8+XLcZQCn+OO//s64S7gS3/vpJ4nG//Zn30qpEgAAmE7DbGl0+/btsa0as1k+AAAAADNBEAYAAADATBCEAQAAADATBGEAAAAAzASb5QPABKp+90eJxhe+9IWUKgEAgOtDEAbAuX7y7fq4SwAAALg0p0YCAAAAMBMEYQAAAADMBEEYAAAAADNBEAYAAADATBCEAQAAADATXDUSgGvr+Ic/GHcJAADABLEiDAAAAICZIAgDAAAAYCY4NRJgBn37a9Vxl8AY/fzxNxKN//T9r6RUCQAAXC0rwgAAAACYCVaEAcA1UP3uj4YeW/jSF1KsBAAAJpcVYQAAAADMBEEYAAAAADNBEAYAAADATBCEAQAAADATBGEAAAAAzARBGAAAAAAzQRAGAAAAwEwQhAEAAAAwEz417gKg7eDgIG7fvj1wzPr6eqyvr19RRQAAAEAS29vbsb29PXDMwcHBFVVzkiCMiXF8fByvXr0aOObo6OiKqgEAAACSOjo6Ove9/TgJwpgYN27ciJs3bw4cMz8/f0XVAJzvez/9ZOixv/3Zt1KsBAAAJsP8/HzcunVr4JiDg4M4Pj6+oop6zbVardZYjgz/6vbt2/Hq1au4detWvHz5ctzlwEz49teqicb/zYcvUqokXcc//MG4S+iY5iCs8KUvJBr/6ftfSakSAACug3HmADbLBwAAAGAmCMIAAAAAmAmCMAAAAABmgs3yAa6BpHt+AQAAzCIrwgAAAACYCYIwAAAAAGaCUyMBmCrHP/zBuEsAAACmlBVhAAAAAMwEQRgAAAAAM0EQBgAAAMBMsEcYADBQ9bs/SjT+d++nVAgAAFySFWEAAAAAzAQrwgAm1Le/Vh13CQAAANeKFWEAAAAAzAQrwgDgCnzvp58kGv/bn30rpUoAAGB2CcIAgJH6+eNvDD320/e/kmIlAADQy6mRAAAAAMwEQRgAAAAAM8GpkQCM1fEPfzDuEhix6nd/NPTY372fYiEAANDHijAAAAAAZoIVYQDA2Hz7a9VE43/nDwopVQIAwCwQhAFckaRv+AEAABgtp0YCAAAAMBOsCAOYQX/z4YtxlwAAAHDlrAgDAAAAYCZYEcbEODg4iNu3bw8cs76+Huvr61dUEQAAAJDE9vZ2bG9vDxxzcHBwRdWcJAhjYhwfH8erV68Gjjk6OrqiagDG63s//STR+N/+7FspVQIAAMM7Ojo69739OAnCmBg3btyImzdvDhwzPz9/RdUAF3X8wx+MuwSmyD9//+8S3qOQSh0AAIzG/Px83Lp1a+CYg4ODOD4+vqKKegnCmBg3b96Mly9fjrsMAAAA4IKG2dLo9u3bY1s1ZrN8AAAAAGaCIAwAAACAmSAIAwAAAGAm2CMMgHPZAJ9J8e2vVRON/50/sLk+AAC/ZEUYAAAAADPBijAA4NpKsoLM6jEAgOtPEAZwCUlP0wIAAGB8BGEAM8ieXwAAwCyyRxgAAAAAM0EQBgAAAMBMcGokAFwD3/vpJ0OP/e3PvpViJdMr6Z5/NtcHAJg+gjAAmDFJQrOIyQrO/vn7f5do/Kd+49+mVAkAANPIqZEAAAAAzARBGAAAAAAzwamRAAAXYE8xAIDpIwgD6JL0je2k+JsPX4y7BAAAgIknCAO4Bo5/+INxlwATKcnm+jbWBwC4/gRhABMq6dXxIC3TfJVJAADoJggDrrVpPdURAACA0ROEAQBcgSTBvI31AQDScWPcBQAAAADAVbAiDOCK2PMLGFbS07qtIAMAGI4VYQAAAADMBCvCAC7BKi84KclVJifpCpNJ+/lTv/FvU6okOSvIAACGY0UYAAAAADPBijAmxsHBQdy+fXvgmPX19VhfX7+iiphUSVc+AAAAcDW2t7dje3t74JiDg4MrquYkQRgT4/j4OF69ejVwzNHR0RVVw6xyqiOQliS/X9I+7TLJHxScRgkAJHF0dHTue/txEoQxMW7cuBE3b94cOGZ+fv6KquG6mOZgK8k+S8DVm+bfLwAAaZmfn49bt24NHHNwcBDHx8dXVFGvuVar1RrLkeFf3b59O169ehW3bt2Kly9fjrscpkCSlQzT/EZVEMYsmKTN8qfZJG3cbwUZAHCeceYAVoQBY2fPL5hdSQNfwRkAAJchCAMApobg7HRJV7+muYIs6R83rCADAK6SIAwYu0l6AwfA1bJxPwBwlQRhwNSZ5n2/ACbBJF3BEgDgKgnCgJH7+eNvjLuEiWTze5hsTru8fpymCQD0E4TBjEoaVn36/leGHlv97o+SlgOQCgE0AADdBGFwQdvb23F0dBTz8/Oxvr4+7nJSZ5UX0+Zvv/9f4xf/+Iv41V/51fit3/h34y4Hplaa+zh+6+le/OyTn8Vn3vpM/M/3Vs4dP0lXGU67FqvTmASz9noXpo0evRhBGFzQ9vZ2vHr1Km7duuWXDkygv/3+9+LHPzuKz31mXhDG1JmV0zS/9fSb8VHzR/H2Zz8f/+N/+8Vzx6e9X9kkBW0wCbzehcmmRy9GEAYMxemOAL1mJayaJS4iAADXnyAMJliS0xGT7OEVIdg6i/2EABhGmqeMRiRbneY0SgAYniAMrgl7eAFMtlkJ2hMFRP/0T+nNzZnSvJqmK3UCMOkEYSOytbUVlUolnj9/Hs1mM7LZbORyuVhbW4tCId0n+DSOPc7HAwAk4zTN2TbNe5sJzgC4aoKwS6pWq1EsFqPZbEahUIhyuRzZbDZqtVqUSqVYXl7ufD2TyUz8scf5eAAArqs0T6VM+zTN/+t/+bNE45OYlb3Wkq7cT7rlBQDDE4RdQrVajeXl5YiIWF1djZ2dnc73stlsrKysRD6fj2q1Gvl8Pvb390cWHqVx7HE+nmnW+uRnTksEYKqkeZqm1WajkeZpoNN8immSUO53/8//LcVKAJhWgrALajabUSwWI+JNSNQdGnUrl8uxtLQUjUYjisViVCqViTz2OB8PZ7Oh/eXNyp48AJMiye/df2y1Ov9N4/e1UG7yTVIol3TlW5LVbP9+MWk1yaR5gSWA60YQdkHt0wcjIkql0pnj2iup9vb2olqtxu7ubqyurk7cscf5eH7yk5/0/Pc6m5Rg6z9/8F/iZ//48/jMr3w6/qff/O/HXU4i01r7337/v8Yv/vEX8au/8qvxW7/x78ZdTiLTXPu0muZ/82mtfVrrjpju2qfVtD4XRcxW7ZOyd9q3nu7F38T/F5/7zFvxv/4PvzPUfZLW/s/fT/Aa87vDB34/b755fZ7kDIhJCdq2t7fj6Ogo5ufnY319/dzxk3L6atK6J4naSWKcOYAg7AIajUZUq798cnrvvfcGjr9//37s7e1FxJuQ6TLBURrHHufjiYj48Y9/3PPfafOLXxxPTMA1rP/8wf8dH/3043j7s5+fwhfBb2r/3Gfm47/54m+Nu5yh/e33vxc//tlRfO4z81P3RnWaa59W0/xvPq21T2vdEdNde9rSWhX85P/5L/Hjnx1N9fOo2i9v2NVs3/r2X3Tq/o35O0POPl2vLbslCZSSvoYufOkLQ4/9s//jf4//9/Vh3Lp1K5VgI2lY+e8XXw01Lu2607S9vR2vXr1SO0MZZw4gCLuAzc3NzueFQuHcfbJWVlY6nzebzdjb2+v52riPPc7HAxEXO40GAMYtrVM6I9I/rTNJ7dN6iukknXY57SblD79JavjFL44j4s2qtnQu+JDw3yNBiBcR8fOf/mLosC3Nq6kmCTZbn/wstToiJmfVHtNPEHYBu7u7nc9zudxQ98lms9FoNCIi4vHjxxcOjtI49jgfD9eTfbkA4HLSei69Dn9QGjbEm9YAD5JK8zTgSdrfLs250w7xmCyCsIRqtVrP7bt37w51v1wu1wmO2qcVTsKxx/l4mC7CLQCYTa4yCpc37Gq29kq2+Kd/mohVjUkits4qvASr2dIO2tKSZoCXhADvYgRhCXXvpRXxZmXUMPrH1Wq1oVdfpXnscT4eAABmW5rbI0zKH/Eusgovae0CRSZKghAvzUtaJNlTrm3YEG9aAzzeEIQl9OzZs57b5+2n1fb222/33H7+/Hni4CiNY4/z8TB+ae5tAgDAL03z6660ar+KAM+ptLPrInvKDRviTcY1abvqJhFBWELt0wHbLrqCql6vT8Sxx/l4ZtGkvPi5DvuDAADwxrTuKZfma+NJW0GYNGibhQtawLgIwhLqD44uqtlsTsSxx/l4rotp/useAACQvmHfL1zFqbRJXCRkSyvEc8owozLXalkaksTc3FzP7WH/+arVaiwvL3dur6ysRLlcHvuxx/l42rpruHHjxoXm6Pa5z30ufu3Xfu3S85zn4OAgjo+PY25uLn7trc+lfrxR+sknP45Wq6X2KzStdUdMb+3TWneE2sdhWuuOUPs4TGvdEWofh2mtO0Lt4zCtdUdMXu2/0vded5DDnx3FcYq1J6kliXbdN27ciJs3b6ZyjH4/+clP4sc//vGl5zk+/uVpnVcdS1kRNibjXEGVxrEvM+fc3FznB7+7GS7q448/jo8//vjS8wyr1WrFj392dGXHGyW1X71prTtiemuf1roj1D4O01p3hNrHYVrrjlD7OExr3RFqH4dprTtC7eNwfHwcr169GncZF9K/OOcqCMISymQyIwmSht2UPu1jj/PxtL311lvxySefROtfk+zLuqoVYQAAADBLRrkibG5uLt566+pPYRWEJbS4uDiS4GhxMfn1VtM49jgfT9tPf/rTSx8fAAAA4DyXX34zYy668qk/bLroirBRH3ucjwcAAADgKgnCErpz507P7WFXU71+/brn9tLS0kQce5yPBwAAAOAqCcISyufzPbcbjcZQ96vX6z23C4XCRBx7nI8HAAAA4CoJwhLqX0E1bHDUvdIqk8lENpudiGOP8/EAAAAAXCVBWEK5XK5nP6xnz54Ndb/nz593Pu8Pn8Z57HE+HgAAAICrJAi7gPfee6/zea1WG+o+3eNKpdJEHXucjwcAAADgqsy1Wq3WuIuYNrVarWdvrfP+CavVaiwvL0dERDabPbG/1riPPc7HAwAAAHBVrAi7gFwu17M5/N7e3sDx5XK58/l5q6d2d3ejVCqduVdXGsdO8/EAAAAATAorwi6o0WjE0tJSRLwJkvb3908d12w2Y2FhISLeXFmxUqmcOefy8nJUq9XO7cPDw579u9I8dhpzAgAAAEwSK8IuKJvNdlZG1Wq12NraOnXcvXv3IuLNlRW7V1KdpjsEi4h48uTJlR07jTkBAAAAJokg7BJWVlaiUqlEJpOJUqkUxWIxarVaNJvNqFarkc/no1arRS6XixcvXpy6uqtb//ez2eyVHTutOQEAAAAmhSDskgqFQhweHsbm5mY0Go24d+9eLCwsRLFYjMXFxSiXy7G/vz9UaFQulyObzUYmk4mNjY2efbvSPnaac45Do9HobOh/nlqtFmtra7G0tBRzc3MxNzcXS0tLUSqVotlsXriGra2tWF5ejoWFhc6cxWLxxMq/cc8J45CkRxuNRk+PLiwsRD6fj7W1tTP3UxyGHoWzJenRQdp9e97+o6fRozDYqPr0MnPqUzjbqHu0VqvF3t5ebG1tDd0PevQMLZgih4eHrYgY6mN1dfXcuVZWVs6dZ2dnJ1GNlUqllclkWhHRKhQKrUql0qrX661yudzKZrOdrx8eHo51TkjDKHu01Wq1Njc3z51nc3MzUY16lFk26h4dZGNjozNXuVwe+n56lFmXRp+Oek59yiy7qufSw8PD1ubmZiuXy7UiopXJZFobGxutSqVybh/o0cEEYUyVYd4Utz/q9fqZ8xweHnaadZS/wCqVyrn3af8iy2azQ/2SSGNOSMuoerTVarUKhULnSX9lZaW1sbHRWllZObV3h32TrUeZdaPs0UG6+0KPQjJp9Oko59SnzLq0n0sPDw9bq6urnTlyuVyrUqkMfX89ej5BGFOlnUCf91EoFAbO036DncvlWuVyuVWv1ztpdvdfsJO8iD88POzUl81mzxxXr9eHrjONOSFNo+rRdh+etdrrtBcg59GjMLoeHaS7L5IEYXoU3kijT0c1pz6FdJ9Ld3Z2euZPenaSHh2OIIypsbOz04qIznLQQR+DEujuec5Sr9c7iXb7I5PJDKyvHa4N8wur+5TMQWPTmBPSMqoebT+JnveXr+6/lEVEa39/f+B4PcqsG1WPnqe9crP7hfwwQZgehXT6dJRz6lNmXZrPpd0LMrLZ7IVWk+nR4QjCmBrZbHZgAp1knmES6u5Eu/1x1hvz/rHn/dIrl8vnBmxpzAlpGlWPrqysDLXvV//+DIPuo0dhdD06SPsNwv7+fqIgTI/CG2n06ajm1KeQ3nNpd4CUyWQu9AcpPTo8QRhTod1Ql02V9/f3h2rgtv7Tr856o929MmXYZaDd8572BiGNOSEto+rRVquVaCl1935hg46tR5l1o+zRs7RfLLdXXCcJwvQopNOno5xTnzLr0nou7V5xFXHxPTr16PBuBEyBhw8fRiaTiffee+9S8zx+/DhWV1cjk8kMNb5QKPTc/uijj04dt7u72/k8l8sNNXc2m+2p6yrmhLSMqkcjIiqVytBjX79+3fn8zp07Z47To8y6UfboWYrFYuRyudjc3Ex8Xz0K6fTpKOfUp8y6NHp0d3c3qtVq5/bOzk7Pz3jSudr06GCCMCZerVaLWq0WzWYzFhYWYmlpKdbW1mJvby/xXPfv30/0Ar2/2ZeWlk6tr9vdu3cTz93/WNKYE9Iyyh5NotlsRrPZjIg3ofVZT856lFl3FT1aKpWiVqtFuVy+UH3d9CizKI0+HeWc+pRZl0aPNhqNWFtb69zO5XKxurp64fq66dHBBGFMvFKp1HO70WjE7u5uFIvFmJubi2KxeKJJz5LL5YZeDRYRnTfZbael890J/lljTtM/rvsxpDEnpGWUPZrEkydPIuLNz/2gN996lFmXdo/WarXY2tq68F+x9Sik06ejnFOfMuvS6NFisdhz+/33379wfXo0GUEYE63RaJxowH57e3uRz+d70vRRHr9b/6mSERHPnj3ruT1s0Pb222/33H7+/Hmqc0IaxtWjzWYz1tbWIpfLRaVSGdgjepRZdhU9eu/evVhZWbnwX7H1KLMujT4d9Zz6lFmWVo92B0SZTCZWVlYuXKMeTeZT4y4ABslms7GzsxPNZjPq9XpUq9UT4VTb7u5uPH/+PPb390d2/O6mPesFfn89F03K6/V6qnNCGsbRo41GI5aXlyOTycTTp0/PfVLWo8yytHu0/dfsR48eXbhGPcqsS6NPRz2nPmWWpdGjOzs7PbfbCy729vbi8ePHUavVotFoRCaTiWw2G/fv3x+417UeTUYQxsTrD6CazWbs7u7Gw4cPT5y6WKvVYnl5OdFm24N0/4LqXw7bdtYvwaS6H0sac0JarrJH9/b2epaRLywsxObmZmxsbJx5Hz3KrEurR/f29mJvb+/cVZnn0aOQTp+Ock59yqwbdY92b0IfEbG4uBj5fP7EaYTNZrOzP1mpVIpyuXzqyjE9moxTI5k6mUwmNjY24vDwMMrl8okX39VqNba2ti59nO7lqpubm2cm4Bdt7P66u69+l8accFVG3aPNZjO2trZiaWnpxF4KEW9C6tO+3n3/i9CjXFej6NFmsxnFYjFWV1dP3TYgCT0KJ6Xxevcyc+pT6HWZfmo0Gid+/p88eRJra2txeHgYrVYrWq1W1Ov1EwFcsVg8dQN6PZqMIIyptrKyEi9evDhxtbiHDx9eeu721SWz2ezA1SajkkZSPonpO7NlFD1arVajXq9HoVA48w333t7eSALwQfQo19FFe/TevXudU0UmhR7lukrj9W6ar6EH0adcR0n7qX+lVSaTiRcvXpw49bH9PNv/XPvgwYPUfu5npUcFYUy9TCYT+/v7Pb94ms3muRsaDlKr1WJ3dzcymcy5y84vczrIWfOkMSeMy2V7dGVlpfMioFKpRKvVip2dnRM/36VS6dQnWj0KgyXt0a2trajVagOv1pr0+KOeR49y3aTxejfJnPoUBkvST/1B2KC9v9rf714Z1mw2T4RsejQZQRjXRv9GvZfZJ+zBgwcREfH06dNzNwVcXFy88HHOmieNOWHcRtmjq6ursb+/f+KJtX+/hQg9CsMapkfbe5Rsbm6e+Mv3RelRGN4on0uTzKlPYTjD9FP/5vF37949d97+/ar7z4TQo8kIwrg2crlcz2lTF93cb21trfOX7mFe5F804e5fuTKK9H3QnDBuo+rRtmw2G0+fPu35Wv9lniP0KAxrmB4tFouRy+VGumWAHoXhjfq5dNg59SkMZ5h+usjPcDabPfHetHtjfT2ajCCMa2V5eflS99/d3Y3d3d3Y2dk59Wocp7lz507P7WHPge7fNHBpaSnVOWESXLZH++VyuZ5ePe3Fhh6F4Q3q0a2trWg0GrG4uBjFYvHcj+6+ePjwYc/3ujf61aOQzKifS4eZU5/C8M7rp4v+zPb3TPfrXj2azKfGXQCMUvdpjEmXYFar1VhbW4udnZ0TV+cYJJ/P99xuNBpDrSTrXxLb/ZeDNOaESXCZHj3L/fv3O2+qT3uC1qMwvEE9+tFHH0VEXGhPoval37uP0w6x9Sgkk8Zz6Xlz6lMY3nn91L9CatiAqT9Q6g6c9GgyVoRxrXT/0kmyBLNWq8Xy8nJsbm4mCsEiBifzg3T/wstkMj21pzEnTIKL9ugg3U/Ip82pR2F4afToefQoJJNGn543pz6F4aXVT/1zdYdsejQZQRjXyvPnzzufD7tsvNFoxL1792JjY+NCe57kcrmeX0qn7VF0mu5a+3/JpDEnTIKL9GgSp/3c61EY3qAe3dzcjFarNfRH9wvfcrnc873Nzc3O9/QoJJPGc+l5c+pTGN4w/dStfwXVsLqfZ/VoMoIwrpXuXyLDLMFsNBqRz+djdXW150X5effpv0rHe++91/m8+9SPQbrH9V8FJK05YdyS9ugwuv86ddYbAj0Kw0mjR4ehR2F4afTpMHPqUxjOMP3U/fVhtxzoP4WyP1DTowm04BrJZrOtiGhtbGycO/bw8LCVzWZbq6uriY6Ry+Va+/v7PV/b399vRUTn4zyVSqUzNpvNnjomjTlh3JL06LA2NzdbEdHKZDJnjtGjMJxR9mh7roholcvlgWP1KAwvjefSYebUpzCcYfqp+2c5IlqHh4fnzru6utoZXygUTnxfjw5PEMa1US6XO2+Gz/tF0g7BCoVCq16vD/VRqVRauVyulcvlTp2zUCgM/YK/+5fYzs7OmePSmBPGJUmPJpHJZIbqET0Kg426R5MEYa2WHoVhpPFcmmROfQqDJemn7ufJYYLt7vH9CzPa9OhwBGFMrEql0nmDWygUzmz2VqvVqtfrnbGDxrXlcrmeZDvJx1kNXa/XO2POCstarTch3KAkP+05YVTS6tHNzc1WLpdrbWxsnPsCYmNjY+gXD3qUWZPm8+gwkgZhepRZlEafptn7+pRZk2Y/9a+2qtfrA+tojxt0RpMeHY4gjInVnSYPavr2L6dsNjvwl0fbZUKwiMEt0/4LQES0Njc3Bx5/2L/kpTEnjEIaPdr9BHreX8hWVlYG9sVp9CizJK3n0WElDcJaLT3K7EmjT9PufX3KLEm7n3Z2djrzZrPZU3+222cznRdEtenR8wnCmFj95023PzKZTGtlZaW1urraabZhVo60Wr9843zRj2H2E+v+q8HKykprf3+/dXh42Dm1sv0LLMkvhzTmhMtKo0dbrd43z/1zbmxstAqFQuf2Rd6061FmRVo9OqyLBGHtuvUosyKNPr2K3tenzIqr7qdMJtPa3Nxs7e/vt/b391ubm5ud7yXZ21qPDiYIY6LV6/XW6upqK5vN9vxyyGazrZWVlVa5XJ7YRmuf3tVdd6FQSPRm4CrmhMtIo0cPDw9bGxsbJ37W23Pu7OyMpO/1KLPA82j6c8JlpdGnV9X7+pRZcFX9tLOz0/mDb/sY7e1CLrpiW4+ebq7VarUCAAAAAK65G+MuAAAAAACugiAMAAAAgJkgCAMAAABgJgjCAAAAAJgJgjAAAAAAZoIgDAAAAICZIAgDAAAAYCYIwgAAAACYCYIwAAAAAGaCIAwAAACAmSAIAwAAAGAmCMIAAAAAmAmCMAAAAABmgiAMAAAAgJkgCAMAAABmVrPZjLm5uXM/arXauEudWFtbW+f++y0tLY27zIiImGu1Wq1xFwEAAAAwDs1mMxYWFjq3c7lcPHr0KLLZbM+4TCZzxZVNl2az2fn89evXUa1WY21trfO1bDYb9Xp9DJX1EoQBAAAAM6s/CCuXy7GysjLGiq6PYrEYe3t7ETE5QZhTIwEAAAD+lZVfo9O/qm4SCMIAAAAA/tXi4uK4SyBFgjAAAAAAZoIgDAAAAICZIAgDAAAAYCYIwgAAAAAuqNlsxtbWVuTz+c4VEtv29vZieXk5FhYWYm5uLvL5fOzu7p45T6lUinw+3zO+f85Jr2PSfWrcBQAAAABMk1qtFtVqNR4/fhy1Wu3E9xuNRhSLxRPfq9Vqsba2Fvv7+7Gzs9P5+tbWVpRKpVOPUywWY2NjIzY3Nye2jmky12q1WuMuAgAAADhfqVSKRqMx9Pi7d+/GxsZGihVNv2azGQsLC53b+/v7kcvlzhzfaDQ6YVH/KqlyuRyvX7+OtbW1yOVycf/+/chms9FoNOLhw4fRbDY7YyuVShQKhVheXo7nz5/He++9F/l8PhYXF+PZs2extbXVM3e9Xo9sNjtxdQxSKpU6989ms1Gv14e6X5oEYQAAADAF+gObYbRDDs6WNAjr1r+CKpvNxuvXr+PRo0exsrLSM7bRaMTS0lLndvsYi4uLUS6XI5PJ9IyvVquxvLzcub26utqzemsS6+g3iUGYPcIAAABgClSr1UTjd3Z2hGApOy0wOzw8PBE+RbwJgrr/f9RqtWg2m1GpVE6ETxERhUKhZ+XVoP//k1LHNBCEAQAAwBSoVCqRzWajUqlEq9U68yOXy8XGxkasrq6Ou+Rrb3Fxsef2acFTt+6VVRFx6n5c3boDrkGnxE5KHdNAEAYAAABToFqtnnuqY7FYjGw227OhefuKgXNzcz0f+Xz+QnUUi8VT5+rfS4qT+ldc9QdY/fr34hpVCDUpdYyDq0YCAADAFCiVSgM3Kd/a2opGoxH7+/s9X19ZWYmVlZUTe2HVarWo1WpD74cV8WY/rf6N2Tc3N23IP6TzAqfzdG9yfx3qGAcrwgAAAGAKDDrVsVqtxs7OTjx9+vTMMZlM5sRqsocPHyaq4bTxTsFMz9tvvz3uEiJicuoYBUEYAAAATLFGoxHFYvHMzc679X9/b28v0Wluu7u7J8K0844Jk0QQBgAAAFOq2WzG8vJylMvlgadNti0uLp64CmD3fmKD7O3tRbPZPHdjdZhkgjAAAACYUsViMUql0sAN9E/THWbt7u4OtefTw4cPo1AoxJ07d5KWCRNDEAYAAABTaG1tLXK53IX26FpdXe05pXF3d3fg+PbG+laDMe0EYQAAADBldnd34/Xr10Of1nia7gDtvE3zHz58GNlsNvHKs0ajEWtra5HP52N5eTmWlpZieXn5xJUnz1IqlWJpaSkWFhYin8/H2tpa1Gq1RDVAN0EYAAAATJFarRY7OztRLpcvNc/777/f+bzZbJ4ZTrW/l3Q12N7eXiwtLcXr169jf38/KpVK1Ov1iPjlKZ1naTQasbS0FLVaLfb39+PFixcR8SYAzOfzsbW11VmlNsxpndAmCAMAAIAp0Wg04sGDB/H06dNLz5XJZIZaFba7u3ti7DCKxWJERNy/f7/n6+1VbFtbW2eGWMViMRqNRuzs7EQmk4lMJtMT/JVKpcjn85HP589dzQbdBGEAAAAwJYrFYpTL5Z79vS6je1VWe4VVv4cPHyYOwRqNxpnf6679+fPnJ76/t7cXtVotstlsz9Uts9lsTx31ej1ardalTg8dt9evX4+7hIiYnDqugiAMAAAApsDy8nK8//77PeHQZfXv+9V/uuLe3l40m82e0yiHnXdnZyc2NzdjZWWl53uLi4udz09bEfb48ePOHP266xt2n7FJ0h84nXda50cffXSt6xgHQRgAAABMuFKpFNVqNYrFYiwvL0e1Wh3p3G3VarVnNdfDhw9jZWXlQivQVldXY2Njo3O72WzG7u5uzxUqT1uJ1F6Vdtqqsu5wbBLCmf4azwuU+r/f3jNt2PFnrbSblDqmgSAMAAAAJtje3l5sbW11bler1VheXk68ef1ZCoVCT8DUPtWwfapk0tVg/Wq1WqytrcWTJ09idXX13NMs27WcFba0v3/37t1L1TUK/fuTPXny5MwQqtlsxs7Ozonxg8KtJ0+e9Hyt//6TVsc0EIQBAADAhKrVap1N5/ttbW31BGRt+Xw+FhYWelZenac7VNvd3Y1msxkPHz6MXC4XuVwueeHxJnBZXl6OYrEYm5ubQ+8ztra21vn8tMfXaDROnNJ5lWq1WiwvL8fCwsKJPdWazWYsLCxEPp/vnLpZq9U6/09OW7m1tLQU+Xy+8/+rWq3G0tJSLC0tnQizqtVqLCwsxPLycvzlX/7lRNQxbavD5lqtVmvcRQAAAAAntYOkbDYbtVotHj9+fCL0qFQqPaHQ0tJSJ5zof8u/trYWjUYjKpXKiWMtLCx0Ao/V1dXY3d2Ncrl8Yo+vdsjSdlqs0Gw245133olmsxn1er1nxVn3/Xd2dk4NyHZ3dzuBWHeI9uDBg6jValGpVEa2V1r/49nf379w+EevUqnUCTOz2ey5p2BeBSvCAAAAYEJVKpVYXV2NQqEQGxsbsb+/H5VKpSeoKRaLPSt22qHYaUHRoKsDdgdSu7u7kclkToRgwyqVStFsNiOTyZyoY5grFK6urka5XI5sNhvPnj2Le/fuxYMHD2J5eflEsAZJfGrcBQAAAADDKxQKsb+/H7u7u53AKZ/Pn1glVS6XT9y32WyeGUS9//77PacinrU32DBB1vPnzzvHO62G8+zt7UWlUpmIFURcL1aEAQAAwBRaXV2Nw8PD2NnZiWw2G/l8PpaWluL169dRr9dPPb3v9evXZ+7plMlkelaFnbWnV3+QdVqwtbi42Pm8O1yr1Wrx4MGDzu120NU9x97eXufqmOMwTNDH9BKEAQAAwBRbXV2NSqUSh4eHUa/XO6cU9qtWq1Gr1aLZbJ65kX570/zV1dXIZDKnjnn8+HHP7f4rCkb0bnhfKpViaWkpFhYW4sGDBz0r1ba2tmJpaannqoft+YvFYszNzcXCwkJnI/d8Pt+5Ymb/XmmjMm2bv0+yYVb/XTWb5QMAAMA1tru7Gzs7OyeCo1wuF2traydWfi0vL3dWmXVbW1uLarV6alCUy+Xi/v37sbGx0XPczc3NzlUeS6VS51jt0zoXFxdjbW2t537NZjOKxWJUq9VzH9vm5mbPfS+if7P8TCYT5XI57ty50zPurGCQN/pDr+fPn/es6puUzfIFYQAAAMDEaAdhm5ubkclkotFo9Oxt1mw246OPPuqscDs8PLxUSNUfhJ3F1STPtrW11VlNeBZBGAAAAECX9sb//avEzpLP5+PRo0cCKoZmjzAAAABgIhSLxWg0Gmdu1H8aIRhJCMIAAACAsWs2m519wYbZH2x3dzcKhULaZXHNODUSAAAAmAhLS0udzfhXV1djbW0tstlsZDKZzj5h1Wo1yuVyZ1N7SEIQBgAAAEyERqMRy8vLp16Zsi2Xy9kXjAsThAEAAAATpb3q6/Xr19FsNiOTycTdu3ejUCgIwLgUQRgAAAAAM8Fm+QAAAADMBEEYAAAAADNBEAYAAADATBCEAQAAADATBGEAAAAAzARBGAAAAAAzQRAGAAAAwEwQhAEAAAAwEwRhAAAAAMwEQRgAAAAAM0EQBgAAAMBMEIQBAAAAMBMEYQAAAADMBEEYAAAAADNBEAYAAADATBCEAQAAADATBGEAAAAAzARBGAAAAAAzQRAGAAAAwEwQhAEAAAAwEwRhAAAAAMwEQRgAAAAAM0EQBgAAAMBMEIQBAAAAMBMEYQAAAADMBEEYAAAAADNBEAYAAADATBCEAQAAADATBGEAAAAAzIT/H1duSCgnJx5BAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1200x900 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "xmin: float = 5200\n",
    "xmax: float = 5600\n",
    "\n",
    "fig = plt.figure()\n",
    "plt.hist(\n",
    "    array[\"match_zMag\"],\n",
    "    bins=80,\n",
    "    range=[xmin, xmax],\n",
    "    color=\"#F05342\",\n",
    "    alpha=0.5,\n",
    "    label=\"new\",\n",
    "    density=True,\n",
    ")\n",
    "plt.hist(\n",
    "    array[\"match_zMag_def\"],\n",
    "    bins=80,\n",
    "    range=[xmin, xmax],\n",
    "    color=\"#107E7D\",\n",
    "    alpha=0.5,\n",
    "    label=\"default\",\n",
    "    density=True,\n",
    ")\n",
    "plt.hist(\n",
    "    array[\"z_mag_xEndT\"],\n",
    "    bins=80,\n",
    "    range=[xmin, xmax],\n",
    "    color=\"#712F79\",\n",
    "    alpha=0.5,\n",
    "    label=\"true\",\n",
    "    density=True,\n",
    ")\n",
    "plt.xlabel(r\"$z_{\\mathrm{Mag}}$ [mm]\")\n",
    "plt.ylabel(\"Number of Tracks (normalised)\")\n",
    "plt.legend(loc=\"best\")\n",
    "mplhep.lhcb.text(\"Simulation\", loc=0)\n",
    "plt.show()\n",
    "# plt.savefig(\n",
    "#     \"/work/cetin/Projektpraktikum/thesis/match_zmag_lost_found.pdf\", format=\"PDF\"\n",
    "# )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x900 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bins = np.linspace(5150, 5700, 50)\n",
    "ax = sns.regplot(\n",
    "    x=ak.to_numpy(array[\"z_mag_xEndT\"]),\n",
    "    y=ak.to_numpy(array[\"z_mag_xEndT\"]) - ak.to_numpy(array[\"match_zMag\"]),\n",
    "    x_bins=bins,\n",
    "    fit_reg=None,\n",
    "    x_estimator=np.mean,\n",
    "    label=\"bla\",\n",
    ")\n",
    "ax.set_ylim(-150, 175)\n",
    "ax2 = ax.twinx()\n",
    "ax2.hist(\n",
    "    ak.to_numpy(array[\"z_mag_xEndT\"]),\n",
    "    bins=50,\n",
    "    range=[5150, 5700],\n",
    "    color=\"#2A9D8F\",\n",
    "    alpha=0.5,\n",
    "    align=\"mid\",\n",
    "    density=True,\n",
    ")\n",
    "ax.set_xlabel(r\"$z_{\\mathrm{Mag}}$ [mm]\")\n",
    "ax.set_ylabel(\n",
    "    r\"$\\left\\langle z_{\\mathrm{Mag}}-z_{\\mathrm{Mag}}^{\\mathrm{pred}}\\right\\rangle$ [mm]\"\n",
    ")\n",
    "ax2.set_ylabel(\"Number of Tracks (normalised)\")\n",
    "mplhep.lhcb.text(\"Simulation\", loc=0)\n",
    "plt.show()\n",
    "# plt.savefig(\n",
    "#     \"/work/cetin/LHCb/reco_tuner/parameterisations/plots/magnet_kink_regression_plot.pdf\",\n",
    "#     format=\"PDF\",\n",
    "# )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1200x900 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bins = np.linspace(-40, 40, 41)\n",
    "ax = sns.regplot(\n",
    "    x=ak.to_numpy(array[\"yDiffOut\"]),\n",
    "    y=ak.to_numpy(array[\"yDiffOut\"]) - ak.to_numpy(array[\"match_yCorr\"]),\n",
    "    x_bins=bins,\n",
    "    fit_reg=None,\n",
    "    x_estimator=np.mean,\n",
    "    label=\"bla\",\n",
    ")\n",
    "ax2 = ax.twinx()\n",
    "ax2.hist(\n",
    "    ak.to_numpy(array[\"yDiffOut\"]),\n",
    "    bins=30,\n",
    "    range=[-40, 40],\n",
    "    color=\"#2A9D8F\",\n",
    "    alpha=0.5,\n",
    "    align=\"mid\",\n",
    "    density=True,\n",
    ")\n",
    "ax.set_xlabel(r\"$y_{\\mathrm{corr}}$ [mm]\")\n",
    "ax.set_ylabel(\n",
    "    r\"$\\left\\langle y_{\\mathrm{corr}}-y_{\\mathrm{corr}}^{\\mathrm{pred}}\\right\\rangle$ [mm]\"\n",
    ")\n",
    "ax2.set_ylabel(\"Number of Tracks (normalised)\")\n",
    "mplhep.lhcb.text(\"Simulation\", loc=0)\n",
    "plt.show()\n",
    "# plt.savefig(\n",
    "#     \"/work/cetin/LHCb/reco_tuner/parameterisations/plots/bend_y_regression_plot.pdf\",\n",
    "#     format=\"PDF\",\n",
    "# )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x900 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "xmin: float = -30\n",
    "xmax: float = 30\n",
    "\n",
    "fig = plt.figure()\n",
    "plt.hist(\n",
    "    array[\"match_yCorr\"],\n",
    "    bins=80,\n",
    "    range=[xmin, xmax],\n",
    "    color=\"#F05342\",\n",
    "    alpha=0.5,\n",
    "    label=\"new\",\n",
    "    density=True,\n",
    ")\n",
    "plt.hist(\n",
    "    array[\"match_yCorr_def\"],\n",
    "    bins=80,\n",
    "    range=[xmin, xmax],\n",
    "    color=\"#107E7D\",\n",
    "    alpha=0.5,\n",
    "    label=\"default\",\n",
    "    density=True,\n",
    ")\n",
    "plt.hist(\n",
    "    array[\"yDiffOut\"],\n",
    "    bins=80,\n",
    "    range=[xmin, xmax],\n",
    "    color=\"#712F79\",\n",
    "    alpha=0.5,\n",
    "    label=\"true\",\n",
    "    density=True,\n",
    ")\n",
    "plt.xlabel(r\"$y_{\\mathrm{corr}}$ [mm]\")\n",
    "plt.ylabel(\"Number of Tracks (normalised)\")\n",
    "plt.legend(loc=\"best\")\n",
    "mplhep.lhcb.text(\"Simulation\", loc=0)\n",
    "plt.show()\n",
    "# plt.savefig(\n",
    "#     \"/work/cetin/Projektpraktikum/thesis/match_zmag_lost_found.pdf\", format=\"PDF\"\n",
    "# )"
   ]
  },
  {
   "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
}