{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "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",
    "from mpl_toolkits import mplot3d\n",
    "import itertools\n",
    "import awkward as ak\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'\\n#cut \\ntcut = ((tracked[\"eta\"]<5.0) & (tracked[\"eta\"]>1.9))\\nlcut = ((lost[\"eta\"]<5.0) & (lost[\"eta\"]>1.9))\\n\\ntracked = tracked[tcut]\\nlost = lost[lcut]\\n'"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#file = uproot.open(\"tracking_losses_ntuple_Bd2KstEE.root:PrDebugTrackingLosses.PrDebugTrackingTool/Tuple;1\")\n",
    "file = uproot.open(\"tracking_losses_ntuple_Dst0ToD0EE.root:PrDebugTrackingLosses.PrDebugTrackingTool/Tuple;1\")\n",
    "\n",
    "\n",
    "\"\"\"\n",
    "#file.keys()\n",
    "#file.show()\n",
    "vertices = file.arrays([\"all_endvtx_x\", \"all_endvtx_y\", \"all_endvtx_z\"])\n",
    "vt_length = file.arrays([\"all_endvtx_x_length\", \"all_endvtx_y_length\", \"all_endvtx_z_length\"])\n",
    "vert_len = vt_length[\"all_endvtx_x_length\"]\n",
    "\n",
    "vtx = vertices[\"all_endvtx_x\"]\n",
    "vty = vertices[\"all_endvtx_y\"]\n",
    "vtz = vertices[\"all_endvtx_z\"]\n",
    "\n",
    "isElectron = file[\"isElectron\"].array()\n",
    "lost = file[\"lost_in_track_fit\"].array()\n",
    "\n",
    "fromPairProd = file[\"fromPairProd\"].array()\n",
    "\n",
    "#vt_length[\"all_endvtx_y_length\"]\n",
    "#vertices\n",
    "\n",
    "#array[array.isElectron]\n",
    "\"\"\"\n",
    "\n",
    "allcolumns = file.arrays()\n",
    "tracked = allcolumns[(allcolumns.isElectron) & (~allcolumns.lost)] #D: 42422\n",
    "lost = allcolumns[(allcolumns.isElectron) & (allcolumns.lost)] #D: 27072\n",
    "\n",
    "#n_cuts = []\n",
    "#n_cuts.append(ak.num(allcolumns, axis=0))\n",
    "\n",
    "\"\"\"\n",
    "#cut \n",
    "tcut = ((tracked[\"eta\"]<5.0) & (tracked[\"eta\"]>1.9))\n",
    "lcut = ((lost[\"eta\"]<5.0) & (lost[\"eta\"]>1.9))\n",
    "\n",
    "tracked = tracked[tcut]\n",
    "lost = lost[lcut]\n",
    "\"\"\"\n",
    "\n",
    "#n_cuts.append(ak.num(tracked, axis=0) + ak.num(lost, axis=0))\n",
    "\n",
    "#~ := logical not \n",
    "#allc_isE= allcolumns[(~allcolumns.isElectron) & (bool 2)]\n",
    "\n",
    "#ak.num(lost, axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "#CutFlow\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "colors = ['blue', 'darkorange']\n",
    "labels = [\"tracked\", \"lost\"]\n",
    "#ak.num(ctracked, axis=0)\n",
    "\n",
    "plt.hist(ak.ravel(tracked[\"eta\"]), bins=100, density=True, alpha=0.4, label=\"tracked\")\n",
    "plt.hist(ak.ravel(lost[\"eta\"]), bins =100, density=True, alpha=0.4, label=\"lost\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#vtx[particle][index of vertex]\n",
    "\n",
    "vtx_x = ak.ravel(allcolumns.all_endvtx_x)\n",
    "vtx_y = ak.ravel(allcolumns.all_endvtx_y)\n",
    "vtx_z = ak.ravel(allcolumns.all_endvtx_z)\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(projection='3d')\n",
    "\n",
    "ax.scatter(vtx_x, vtx_y, vtx_z, marker=\".\", s=1)\n",
    "\n",
    "ax.set_xlabel('X')\n",
    "ax.set_ylabel('Y')\n",
    "ax.set_zlabel('Z')\n",
    "ax.view_init(15, 35)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#create an array with all electron indices\n",
    "electron = allcolumns[(allcolumns.isElectron)]\n",
    "#electron.show()\n",
    "#electron_ind = electron[electron.]\n",
    "#electron_ind = electron_ind.to_numpy()\n",
    "e_vtx_x = ak.ravel(electron.all_endvtx_x)\n",
    "e_vtx_y = ak.ravel(electron.all_endvtx_y)\n",
    "e_vtx_z = ak.ravel(electron.all_endvtx_z)\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(projection='3d')\n",
    "\n",
    "ax.scatter(e_vtx_x, e_vtx_y, e_vtx_z, marker=\".\", s=1)\n",
    "\n",
    "ax.set_xlabel('X')\n",
    "ax.set_ylabel('Y')\n",
    "ax.set_zlabel('Z')\n",
    "ax.view_init(15, 35)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 4000x2000 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ((ax0, ax1, ax2), (ax3, ax4, ax5)) = plt.subplots(nrows=2, ncols=3, figsize=(40,20))\n",
    "\n",
    "colors = ['blue', 'darkorange']\n",
    "labels = [\"tracked\", \"lost\"]\n",
    "\n",
    "ax0.hist([ak.ravel(tracked[\"energy\"]),ak.ravel(lost[\"energy\"])], 1000, density=True, histtype='bar', color=colors, label=labels)\n",
    "ax0.legend()\n",
    "ax0.set_xlim(0,40000)\n",
    "ax0.set_title('energy')\n",
    "\n",
    "ax1.hist([ak.ravel(tracked[\"eta\"]), ak.ravel(lost[\"eta\"])], bins=100, density=True, color=colors, label=labels)\n",
    "ax1.legend()\n",
    "ax1.set_title('eta')\n",
    "\n",
    "ax2.hist([ak.ravel(tracked[\"p\"]),ak.ravel(lost[\"p\"])], 500, density=True, histtype='bar', color=colors, label=labels)\n",
    "ax2.legend()\n",
    "ax2.set_xlim(0,50000)\n",
    "ax2.set_title('p')\n",
    "\n",
    "ax3.hist([ak.ravel(tracked[\"pt\"]),ak.ravel(lost[\"pt\"])], 500, density=True, histtype='bar', color=colors, label=labels)\n",
    "ax3.legend()\n",
    "ax3.set_xlim(0,3000)\n",
    "ax3.set_title('pt')\n",
    "\n",
    "ax4.hist([ak.ravel(tracked[\"tx\"]),ak.ravel(lost[\"tx\"])], 100, density=True, histtype='bar', color=colors, label=labels)\n",
    "ax4.legend()\n",
    "ax4.set_title('tx')\n",
    "\n",
    "ax5.hist([ak.ravel(tracked[\"ty\"]),ak.ravel(lost[\"ty\"])], 100, density=True, histtype='bar', color=colors, label=labels)\n",
    "ax5.legend()\n",
    "ax5.set_title('ty')\n",
    "\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 4500x3000 with 9 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ((ax0, ax1, ax2), (ax3, ax4, ax5), (ax6, ax7, ax8)) = plt.subplots(nrows=3, ncols=3, figsize=(45,30))\n",
    "\n",
    "colors = ['blue', 'darkorange']\n",
    "labels = [\"tracked\", \"lost\"]\n",
    "n_bins=75\n",
    "\n",
    "ax0.hist([ak.ravel(tracked[\"velo_hit_pos_x\"]),ak.ravel(lost[\"velo_hit_pos_x\"])], n_bins, density=True, histtype='bar', color=colors, label=labels)\n",
    "ax0.legend()\n",
    "ax0.set_title('velo x')\n",
    "\n",
    "ax1.hist([ak.ravel(tracked[\"velo_hit_pos_y\"]),ak.ravel(lost[\"velo_hit_pos_y\"])], n_bins, density=True, histtype='bar', color=colors, label=labels)\n",
    "ax1.legend()\n",
    "ax1.set_title('velo y')\n",
    "\n",
    "ax2.hist([ak.ravel(tracked[\"velo_hit_pos_z\"]),ak.ravel(lost[\"velo_hit_pos_z\"])], n_bins, density=True, histtype='bar', color=colors, label=labels)\n",
    "ax2.legend()\n",
    "ax2.set_title('velo z')\n",
    "\n",
    "ax3.hist([ak.ravel(tracked[\"ut_hit_pos_x\"]),ak.ravel(lost[\"ut_hit_pos_x\"])], n_bins, density=True, histtype='bar', color=colors, label=labels)\n",
    "ax3.legend()\n",
    "ax3.set_title('ut x')\n",
    "\n",
    "ax4.hist([ak.ravel(tracked[\"ut_hit_pos_y\"]),ak.ravel(lost[\"ut_hit_pos_y\"])], n_bins, density=True, histtype='bar', color=colors, label=labels)\n",
    "ax4.legend()\n",
    "ax4.set_title('ut y')\n",
    "\n",
    "ax5.hist([ak.ravel(tracked[\"ut_hit_pos_z\"]),ak.ravel(lost[\"ut_hit_pos_z\"])], n_bins, density=True, histtype='bar', color=colors, label=labels)\n",
    "ax5.legend()\n",
    "ax5.set_title('ut z')\n",
    "\n",
    "ax6.hist([ak.ravel(tracked[\"scifi_hit_pos_x\"]),ak.ravel(lost[\"scifi_hit_pos_x\"])], n_bins, density=True, histtype='bar', color=colors, label=labels)\n",
    "ax6.legend()\n",
    "ax6.set_title('scifi x')\n",
    "\n",
    "ax7.hist([ak.ravel(tracked[\"scifi_hit_pos_y\"]),ak.ravel(lost[\"scifi_hit_pos_y\"])], n_bins, density=True, histtype='bar', color=colors, label=labels)\n",
    "ax7.legend()\n",
    "ax7.set_title('scifi y')\n",
    "\n",
    "ax8.hist([ak.ravel(tracked[\"scifi_hit_pos_z\"]),ak.ravel(lost[\"scifi_hit_pos_z\"])], n_bins, density=True, histtype='bar', color=colors, label=labels)\n",
    "ax8.legend()\n",
    "ax8.set_title('scifi z')\n",
    "\n",
    "\n",
    "#fig.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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AQN0yxujo0aMKDw9XgwaX5t4vgfks3333nSIiIup6GAAAADiPAwcO/OLf3FqNwHyWgIAASWd+AYGBgXU8GgAAAJyrrKxMERERjtx2KRCYz1L9GEZgYCCBGQAAoB67lI/P8qE/AAAAwAKBGQAAALBAYAYAAAAs8AwzAACApKqqKp06daquhwFJPj4+8vLyquthOBCYAQDAVc0Yo+LiYh05cqSuh4KzXHPNNQoNDa0X341BYAYAAFe16rAcHByshg0b1ouAdjUzxuinn35SSUmJJCksLKyOR0RgBgAAV7GqqipHWG7WrFldDwf/4u/vL0kqKSlRcHBwnT+ewYf+AADAVav6meWGDRvW8UhwrurfSX14rpzADAAArno8hlH/1KffCYEZAAAAsEBgBgAAQI3Wr18vm812UVcR2bdvn2w2m7Zv337R+vwlEZgBAADcsNku3VYbPXr0UGpq6kW9ZrhHYAYAALgCGWNUWVlZ18O4IhCYAQAALjOjRo1Sbm6unnnmGdlsNtlsNr300kuy2Wx69913FRcXJ7vdrg0bNuirr77S4MGDFRISosaNG6tLly5at26dU3/l5eV65JFHFBERIbvdrrZt22rx4sVuz33ixAkNGDBAN998s3788UdJ0tKlS9W+fXv5+fmpXbt2WrBggdMxn3zyiTp16iQ/Pz/FxcUpPz//l5mYXwjrMAMAAFxmnnnmGX3xxReKiYnRrFmzJEm7du2SJD3yyCOaM2eOWrdurWuuuUbffPON+vfvr8cff1x+fn7661//qkGDBmnv3r1q2bKlJOnuu+9WXl6enn32WXXs2FEFBQU6ePCgy3lLS0s1cOBA+fn56b333lOjRo30wgsvaPr06Zo/f746deqk/Px8jR49Wo0aNdLIkSN1/PhxDRw4UL169dLy5ctVUFCgCRMmXLrJuggIzAAAAJeZoKAg+fr6qmHDhgoNDZUk/eMf/5AkzZo1S71793bUNmvWTB07dnS8fvzxx7V69WqtWbNG48aN0xdffKFXX31VOTk5uu222yRJrVu3djnn999/r+TkZLVp00YrVqyQr6+vJOlPf/qTnn76aQ0dOlSSFBUVpd27d+svf/mLRo4cqZdffllVVVVasmSJGjZsqBtvvFHffPON/vCHP/wyk/MLIDADAABcQeLi4pxeHz9+XDNnztRbb72l7777TpWVlTpx4oQKCwslSdu3b5eXl5e6d+9u2e9tt92mLl266NVXX3V8894PP/ygAwcO6N5779Xo0aMdtZWVlQoKCpIk7dmzRx07dnT6cpiEhISLcq2XCoEZAADgCtKoUSOn13/84x/17rvvas6cOfrVr34lf39/3XHHHaqoqJD076+hPp8BAwYoKytLu3fv1k033SRJOn36tCTphRdeUHx8vFN9dag2xvys66kPCMwAAACXIV9fX1VVVZ23bsOGDRo1apRuv/12SdKxY8e0b98+x/6bbrpJp0+fVm5uruORDHeefPJJNW7cWLfeeqvWr1+v6OhohYSE6LrrrtPXX3+tu+66y+1x0dHR+tvf/qYTJ044wvnHH3/swZXWPVbJqK2n68/XNQIAgKtPq1attHnzZu3bt08HDx503O09169+9SutWrVK27dv144dOzRixAin2latWmnkyJG655579Prrr6ugoEDr16/Xq6++6tLXnDlzdNddd6lXr16OZ6ZnzJih9PR0xwcRd+7cqaVLl2ru3LmSpBEjRqhBgwa69957tXv3bmVnZ2vOnDm/wIz8cgjMAAAAl6GHH35YXl5eio6O1rXXXut4Jvlc//M//6MmTZooMTFRgwYNUp8+fdS5c2enmoULF+qOO+7QAw88oHbt2mn06NE6fvx4jf0NHz5cvXr10hdffKH77rtPL774ol566SXddNNN6t69u1566SVFRUVJkho3bqw333xTu3fvVqdOnTR16lRlZGRc3Mn4hdnMlfBgyUVSVlamoKAglZaWKjAw0Lr4aZv0EFMHAMDl7OTJkyooKFBUVJT8/Pzqejg4S02/G4/y2kXCHWYAAADAAoEZAAAAsEBgBgAAACwQmAEAAAALBGYAAADAAoEZAAAAsEBgBgAAACwQmAEAAAALBGYAAADAAoEZAADgMtSjRw+lpqbW9TCuCt51PQAAAIB66WnbpTvXQ+bSnesc69evV8+ePXX48GFdc801dTaO+ow7zAAAAIAFAjMAAMBl7vDhw7r77rvVpEkTNWzYUP369dOXX37p2L9//34NGjRITZo0UaNGjXTjjTcqOztb+/btU8+ePSVJTZo0kc1m06hRo+roKuovHskAAAC4zI0aNUpffvml1qxZo8DAQE2aNEn9+/fX7t275ePjo7Fjx6qiokIffvihGjVqpN27d6tx48aKiIhQVlaWhg0bpr179yowMFD+/v51fTn1DoEZAADgMlYdlD/66CMlJiZKkl5++WVFRETo9ddf1+9+9zsVFhZq2LBhuummmyRJrVu3dhzftGlTSVJwcDDPMNeARzIAAAAuY3v27JG3t7fi4+Mdbc2aNdMNN9ygPXv2SJLGjx+vxx9/XL/5zW80ffp0ffbZZ3U13MsSgRkAAOAyZoz7FTaMMbLZzqz0cd999+nrr79WSkqKdu7cqbi4OP3v//7vpRzmZY3ADAAAcBmLjo5WZWWlNm/e7Gg7dOiQvvjiC7Vv397RFhERoTFjxmjVqlV66KGH9MILL0iSfH19JUlVVVWXduCXEQJzLdgu4bKMAAAAVtq2bavBgwdr9OjR2rhxo3bs2KHf//73uu666zR48GBJUmpqqt59910VFBTo008/1fvvv+8I05GRkbLZbHrrrbf0ww8/6NixY3V5OfUSgRkAAOAyt3TpUsXGxmrgwIFKSEiQMUbZ2dny8fGRdObu8dixY9W+fXv17dtXN9xwgxYsWCBJuu666zRz5kw9+uijCgkJ0bhx4+ryUuolm6npwZerUFlZmYKCglRaWqrAwMAa62w2ycyx1em38gAAgJ/v5MmTKigoUFRUlPz8/Op6ODhLTb+bC81rFxN3mAEAAAALBGYAAADAAoEZAAAAsFCrwLxgwQLH8ySxsbHasGGDZX1ubq5iY2Pl5+en1q1ba9GiRS41WVlZio6Olt1uV3R0tFavXu20f+HCherQoYMCAwMVGBiohIQEvfPOO041xhjNmDFD4eHh8vf3V48ePbRr167aXCIAAAAgqRaBOTMzU6mpqZo6dary8/PVtWtX9evXT4WFhW7rCwoK1L9/f3Xt2lX5+fmaMmWKxo8fr6ysLEdNXl6ekpOTlZKSoh07diglJUXDhw93Wk+wRYsWevLJJ7V161Zt3bpVvXr10uDBg50C8VNPPaW5c+dq/vz52rJli0JDQ9W7d28dPXrU08sEAAAAJNVilYz4+Hh17txZCxcudLS1b99eQ4YMUXp6ukv9pEmTtGbNGsdXM0rSmDFjtGPHDuXl5UmSkpOTVVZW5nTHuG/fvmrSpIlWrFhR41iaNm2qP//5z7r33ntljFF4eLhSU1M1adIkSVJ5eblCQkKUkZGh+++//7zXxioZAABcXapXYoiMjFTDhg3rejg4y08//aT9+/fXi1UyvD0prqio0LZt2/Too486tSclJWnTpk1uj8nLy1NSUpJTW58+fbR48WKdOnVKPj4+ysvL08SJE11q5s2b57bPqqoqvfbaazp+/LgSEhIknbmTXVxc7HQuu92u7t27a9OmTW4Dc3l5ucrLyx2vy8rKar54AABwxfH19VWDBg303Xff6dprr5Wvr6/j66RRN4wxqqio0A8//KAGDRo4vomwLnkUmA8ePKiqqiqFhIQ4tYeEhKi4uNjtMcXFxW7rKysrdfDgQYWFhdVYc26fO3fuVEJCgk6ePKnGjRtr9erVio6Odpyn+rhz+9m/f7/bsaWnp2vmzJnnuWoAAHClatCggaKiolRUVKTvvvuuroeDszRs2FAtW7ZUgwZ1v0aFR4G52rl/eRljLP8ac1d/bvuF9HnDDTdo+/btOnLkiLKysjRy5Ejl5uY6QrOnY5s8ebLS0tIcr8vKyhQREVHjdQAAgCuPr6+vWrZsqcrKSlVVVdX1cCDJy8tL3t7e9eZuv0eBuXnz5vLy8nK581tSUuJyZ7daaGio23pvb281a9bMsubcPn19ffWrX/1KkhQXF6ctW7bomWee0V/+8heFhoZKOnOnOSws7ILGZrfbZbfbz3fZAADgCmez2eTj4+P4KmngbB7d4/b19VVsbKxycnKc2nNycpSYmOj2mISEBJf6tWvXKi4uzvGmrKmmpj6rGWMczyBHRUUpNDTUqZ+Kigrl5uaetx8AAACgJh4/kpGWlqaUlBTFxcUpISFBzz//vAoLCzVmzBhJZx5z+Pbbb7Vs2TJJZ1bEmD9/vtLS0jR69Gjl5eVp8eLFTqtfTJgwQd26dVNGRoYGDx6sN954Q+vWrdPGjRsdNVOmTFG/fv0UERGho0ePauXKlVq/fr3+/ve/Szrzl2Fqaqpmz56ttm3bqm3btpo9e7YaNmyoESNG/KxJAgAAwNXL48CcnJysQ4cOadasWSoqKlJMTIyys7MVGRkpSSoqKnJakzkqKkrZ2dmaOHGinnvuOYWHh+vZZ5/VsGHDHDWJiYlauXKlHnvsMU2bNk1t2rRRZmam4uPjHTXff/+9UlJSVFRUpKCgIHXo0EF///vf1bt3b0fNI488ohMnTuiBBx7Q4cOHFR8fr7Vr1yogIKBWkwMAAAB4vA7zlYx1mAEAAOq3uliHue7X6QAAAADqMQIzAAAAYIHADAAAAFggMAMAAAAWCMwAAACABQIzAAAAYIHADAAAAFggMAMAAAAWCMwAAACABQIzAAAAYIHADAAAAFggMAMAAAAWCMwAAACABQIzAAAAYIHADAAAAFggMAMAAAAWCMwAAACABQIzAAAAYIHADAAAAFggMAMAAAAWCMwAAACABQIzAAAAYIHADAAAAFggMAMAAAAWCMwAAACABQIzAAAAYIHADAAAAFggMAMAAAAWCMwAAACABQIzAAAAYIHADAAAAFggMAMAAAAWCMwAAACABQIzAAAAYIHADAAAAFggMAMAAAAWCMwAAACABQIzAAAAYIHADAAAAFggMAMAAAAWCMwAAACABQIzAAAAYIHADAAAAFggMAMAAAAWCMwAAACABQIzAAAAYIHADAAAAFggMAMAAAAWCMwAAACABQIzAAAAYIHADAAAAFggMAMAAAAWCMwAAACABQIzAAAAYIHADAAAAFggMAMAAAAWCMwAAACAhVoF5gULFigqKkp+fn6KjY3Vhg0bLOtzc3MVGxsrPz8/tW7dWosWLXKpycrKUnR0tOx2u6Kjo7V69Wqn/enp6erSpYsCAgIUHBysIUOGaO/evU41o0aNks1mc9puvvnm2lwiAAAAIKkWgTkzM1OpqamaOnWq8vPz1bVrV/Xr10+FhYVu6wsKCtS/f3917dpV+fn5mjJlisaPH6+srCxHTV5enpKTk5WSkqIdO3YoJSVFw4cP1+bNmx01ubm5Gjt2rD7++GPl5OSosrJSSUlJOn78uNP5+vbtq6KiIseWnZ3t6SUCAAAADjZjjPHkgPj4eHXu3FkLFy50tLVv315DhgxRenq6S/2kSZO0Zs0a7dmzx9E2ZswY7dixQ3l5eZKk5ORklZWV6Z133nHU9O3bV02aNNGKFSvcjuOHH35QcHCwcnNz1a1bN0ln7jAfOXJEr7/+uieX5FBWVqagoCCVlpYqMDCwxjqbTTJzbNJDHk0dAAAAfqYLzWsXk0d3mCsqKrRt2zYlJSU5tSclJWnTpk1uj8nLy3Op79Onj7Zu3apTp05Z1tTUpySVlpZKkpo2berUvn79egUHB+v666/X6NGjVVJSUmMf5eXlKisrc9oAAACAs3kUmA8ePKiqqiqFhIQ4tYeEhKi4uNjtMcXFxW7rKysrdfDgQcuamvo0xigtLU233HKLYmJiHO39+vXTyy+/rPfff19PP/20tmzZol69eqm8vNxtP+np6QoKCnJsERER1hMAAACAq453bQ6y2WxOr40xLm3nqz+33ZM+x40bp88++0wbN250ak9OTnb8HBMTo7i4OEVGRurtt9/W0KFDXfqZPHmy0tLSHK/LysoIzQAAAHDiUWBu3ry5vLy8XO78lpSUuNwhrhYaGuq23tvbW82aNbOscdfngw8+qDVr1ujDDz9UixYtLMcbFhamyMhIffnll2732+122e12yz4AAABwdfPokQxfX1/FxsYqJyfHqT0nJ0eJiYluj0lISHCpX7t2reLi4uTj42NZc3afxhiNGzdOq1at0vvvv6+oqKjzjvfQoUM6cOCAwsLCLuj6AAAAgHN5vKxcWlqaXnzxRS1ZskR79uzRxIkTVVhYqDFjxkg685jD3Xff7agfM2aM9u/fr7S0NO3Zs0dLlizR4sWL9fDDDztqJkyYoLVr1yojI0P/+Mc/lJGRoXXr1ik1NdVRM3bsWC1fvlyvvPKKAgICVFxcrOLiYp04cUKSdOzYMT388MPKy8vTvn37tH79eg0aNEjNmzfX7bffXtv5AQAAwFXO42eYk5OTdejQIc2aNUtFRUWKiYlRdna2IiMjJUlFRUVOazJHRUUpOztbEydO1HPPPafw8HA9++yzGjZsmKMmMTFRK1eu1GOPPaZp06apTZs2yszMVHx8vKOmehm7Hj16OI1n6dKlGjVqlLy8vLRz504tW7ZMR44cUVhYmHr27KnMzEwFBAR4epkAAACApFqsw3wlYx1mAACA+q3er8MMAAAAXG0IzAAAAIAFAjMAAABggcAMAAAAWCAwAwAAABYIzAAAAIAFAjMAAABggcAMAAAAWCAwAwAAABYIzAAAAIAFAjMAAABggcAMAAAAWCAwAwAAABYIzAAAAIAFAjMAAABggcAMAAAAWCAwAwAAABYIzAAAAIAFAjMAAABggcAMAAAAWCAwAwAAABYIzAAAAIAFAjMAAABggcAMAAAAWCAwAwAAABYIzAAAAIAFAjMAAABggcAMAAAAWCAwAwAAABYIzAAAAIAFAvPF8LTtzAYAAIArDoEZAAAAsEBgBgAAACwQmAEAAAALBGYAAADAAoEZAAAAsEBgBgAAACwQmAEAAAALBGYAAADAAoEZAAAAsEBgBgAAACwQmH8mG9+IDQAAcEUjMAMAAAAWCMwAAACABQIzAAAAYIHADAAAAFggMAMAAAAWCMwAAACABQIzAAAAYIHADAAAAFggMAMAAAAWCMwAAACABQIzAAAAYIHADAAAAFggMAMAAAAWCMwAAACABQIzAAAAYKFWgXnBggWKioqSn5+fYmNjtWHDBsv63NxcxcbGys/PT61bt9aiRYtcarKyshQdHS273a7o6GitXr3aaX96erq6dOmigIAABQcHa8iQIdq7d69TjTFGM2bMUHh4uPz9/dWjRw/t2rWrNpcIAAAASKpFYM7MzFRqaqqmTp2q/Px8de3aVf369VNhYaHb+oKCAvXv319du3ZVfn6+pkyZovHjxysrK8tRk5eXp+TkZKWkpGjHjh1KSUnR8OHDtXnzZkdNbm6uxo4dq48//lg5OTmqrKxUUlKSjh8/7qh56qmnNHfuXM2fP19btmxRaGioevfuraNHj3p6mQAAAIAkyWaMMZ4cEB8fr86dO2vhwoWOtvbt22vIkCFKT093qZ80aZLWrFmjPXv2ONrGjBmjHTt2KC8vT5KUnJyssrIyvfPOO46avn37qkmTJlqxYoXbcfzwww8KDg5Wbm6uunXrJmOMwsPDlZqaqkmTJkmSysvLFRISooyMDN1///3nvbaysjIFBQWptLRUgYGBNdbZbJKZY5MeMv/+WZIe8mgqAQAA4KELzWsXk0d3mCsqKrRt2zYlJSU5tSclJWnTpk1uj8nLy3Op79Onj7Zu3apTp05Z1tTUpySVlpZKkpo2bSrpzJ3s4uJip37sdru6d+9u2Q8AAABgxduT4oMHD6qqqkohISFO7SEhISouLnZ7THFxsdv6yspKHTx4UGFhYTXW1NSnMUZpaWm65ZZbFBMT4zhP9XHn9rN//363/ZSXl6u8vNzxuqyszG0dAAAArl61+tCfzWZzem2McWk7X/257Z70OW7cOH322WduH9fwpJ/09HQFBQU5toiIiBqvAQAAAFcnjwJz8+bN5eXl5XLnt6SkxOXObrXQ0FC39d7e3mrWrJlljbs+H3zwQa1Zs0YffPCBWrRo4XQeSR6NbfLkySotLXVsBw4ccFsHAACAq5dHgdnX11exsbHKyclxas/JyVFiYqLbYxISElzq165dq7i4OPn4+FjWnN2nMUbjxo3TqlWr9P777ysqKsqpPioqSqGhoU79VFRUKDc3t8ax2e12BQYGOm0AAADA2Tx6hlmS0tLSlJKSori4OCUkJOj5559XYWGhxowZI+nMXdtvv/1Wy5Ytk3RmRYz58+crLS1No0ePVl5enhYvXuz0OMWECRPUrVs3ZWRkaPDgwXrjjTe0bt06bdy40VEzduxYvfLKK3rjjTcUEBDguJMcFBQkf39/2Ww2paamavbs2Wrbtq3atm2r2bNnq2HDhhoxYsTPmiQAAABcvTwOzMnJyTp06JBmzZqloqIixcTEKDs7W5GRkZKkoqIipzWZo6KilJ2drYkTJ+q5555TeHi4nn32WQ0bNsxRk5iYqJUrV+qxxx7TtGnT1KZNG2VmZio+Pt5RU72MXY8ePZzGs3TpUo0aNUqS9Mgjj+jEiRN64IEHdPjwYcXHx2vt2rUKCAjw9DIBAAAASbVYh/lKxjrMAAAA9Vu9X4cZAAAAuNoQmAEAAAALBGYAAADAAoEZAAAAsEBgBgAAACwQmAEAAAALBGYAAADAAoEZAAAAsEBgBgAAACwQmAEAAAALBGYAAADAAoEZAAAAsEBgBgAAACwQmAEAAAALBGYAAADAAoEZAAAAsEBgBgAAACwQmAEAAAALBGYAAADAAoEZAAAAsEBgBgAAACwQmAEAAAALBGYAAADAAoEZAAAAsEBgBgAAACwQmAEAAAALBGYAAADAAoEZAAAAsEBgBgAAACwQmAEAAAALBGYAAADAAoEZAAAAsEBgBgAAACwQmAEAAAALBGYAAADAAoEZAAAAsEBgBgAAACwQmH8JT9vqegQAAAC4SAjMAAAAgAUCMwAAAGCBwAwAAABYIDADAAAAFgjMF5HNdmYDAADAlYPADAAAAFggMAMAAAAWCMwAAACABQIzAAAAYIHADAAAAFggMAMAAAAWCMwAAACABQIzAAAAYIHADAAAAFggMAMAAAAWCMwAAACABQIzAAAAYIHADAAAAFggMAMAAAAWahWYFyxYoKioKPn5+Sk2NlYbNmywrM/NzVVsbKz8/PzUunVrLVq0yKUmKytL0dHRstvtio6O1urVq532f/jhhxo0aJDCw8Nls9n0+uuvu/QxatQo2Ww2p+3mm2+uzSUCAAAAkmoRmDMzM5WamqqpU6cqPz9fXbt2Vb9+/VRYWOi2vqCgQP3791fXrl2Vn5+vKVOmaPz48crKynLU5OXlKTk5WSkpKdqxY4dSUlI0fPhwbd682VFz/PhxdezYUfPnz7ccX9++fVVUVOTYsrOzPb1EAAAAwMFmjDGeHBAfH6/OnTtr4cKFjrb27dtryJAhSk9Pd6mfNGmS1qxZoz179jjaxowZox07digvL0+SlJycrLKyMr3zzjuOmr59+6pJkyZasWKF66BtNq1evVpDhgxxah81apSOHDni9u7zhSgrK1NQUJBKS0sVGBhYY53NJpk5Nukh8++fJdkePjOV1fsAAABwcV1oXruYPLrDXFFRoW3btikpKcmpPSkpSZs2bXJ7TF5enkt9nz59tHXrVp06dcqypqY+raxfv17BwcG6/vrrNXr0aJWUlHjcBwAAAFDN25PigwcPqqqqSiEhIU7tISEhKi4udntMcXGx2/rKykodPHhQYWFhNdbU1GdN+vXrp9/97neKjIxUQUGBpk2bpl69emnbtm2y2+0u9eXl5SovL3e8Lisr8+h8AAAAuPJ5FJir2Ww2p9fGGJe289Wf2+5pn+4kJyc7fo6JiVFcXJwiIyP19ttva+jQoS716enpmjlzpkfnAAAAwNXFo0cymjdvLi8vL5c7vyUlJS53iKuFhoa6rff29lazZs0sa2rq80KFhYUpMjJSX375pdv9kydPVmlpqWM7cODAzzofAAAArjweBWZfX1/FxsYqJyfHqT0nJ0eJiYluj0lISHCpX7t2reLi4uTj42NZU1OfF+rQoUM6cOCAwsLC3O632+0KDAx02gAAAICzefxIRlpamlJSUhQXF6eEhAQ9//zzKiws1JgxYySduWv77bffatmyZZLOrIgxf/58paWlafTo0crLy9PixYudVr+YMGGCunXrpoyMDA0ePFhvvPGG1q1bp40bNzpqjh07pn/+85+O1wUFBdq+fbuaNm2qli1b6tixY5oxY4aGDRumsLAw7du3T1OmTFHz5s11++2313qCAAAAcHXzODAnJyfr0KFDmjVrloqKihQTE6Ps7GxFRkZKkoqKipzWZI6KilJ2drYmTpyo5557TuHh4Xr22Wc1bNgwR01iYqJWrlypxx57TNOmTVObNm2UmZmp+Ph4R83WrVvVs2dPx+u0tDRJ0siRI/XSSy/Jy8tLO3fu1LJly3TkyBGFhYWpZ8+eyszMVEBAgOczAwAAAKgW6zBfyViHGQAAoH6r9+swAwAAAFcbAjMAAABggcAMAAAAWCAwAwAAABYIzAAAAIAFAjMAAABggcAMAAAAWCAwAwAAABYIzAAAAIAFAjMAAABggcAMAAAAWCAwAwAAABYIzAAAAIAFAjMAAABggcD8S3vadmYDAADAZYnADAAAAFggMAMAAAAWCMwAAACABQIzAAAAYIHADAAAAFggMAMAAAAWCMy/IBuryQEAAFz2CMwAAACABQIzAAAAYIHADAAAAFggMAMAAAAWCMwAAACABQIzAAAAYIHADAAAAFggMAMAAAAWCMwAAACABQIzAAAAYIHADAAAAFggMAMAAAAWCMwAAACABQIzAAAAYIHADAAAAFggMAMAAAAWCMwAAACABQIzAAAAYIHADAAAAFggMAMAAAAWCMwAAACABQIzAAAAYIHADAAAAFggMAMAAAAWCMwAAACABQIzAAAAYIHADAAAAFggMAMAAAAWCMyXiM12ZtPTtroeCgAAADxAYAYAAAAsEJgBAAAACwRmAAAAwAKBGQAAALBAYAYAAAAsEJgBAAAAC7UKzAsWLFBUVJT8/PwUGxurDRs2WNbn5uYqNjZWfn5+at26tRYtWuRSk5WVpejoaNntdkVHR2v16tVO+z/88EMNGjRI4eHhstlsev311136MMZoxowZCg8Pl7+/v3r06KFdu3bV5hIBAAAASbUIzJmZmUpNTdXUqVOVn5+vrl27ql+/fiosLHRbX1BQoP79+6tr167Kz8/XlClTNH78eGVlZTlq8vLylJycrJSUFO3YsUMpKSkaPny4Nm/e7Kg5fvy4OnbsqPnz59c4tqeeekpz587V/PnztWXLFoWGhqp37946evSop5cJAAAASJJsxhjjyQHx8fHq3LmzFi5c6Ghr3769hgwZovT0dJf6SZMmac2aNdqzZ4+jbcyYMdqxY4fy8vIkScnJySorK9M777zjqOnbt6+aNGmiFStWuA7aZtPq1as1ZMgQR5sxRuHh4UpNTdWkSZMkSeXl5QoJCVFGRobuv//+815bWVmZgoKCVFpaqsDAwBrrbDbJzLFJD5l//yzJ9vCZqbyQfQAAAPDchea1i8mjO8wVFRXatm2bkpKSnNqTkpK0adMmt8fk5eW51Pfp00dbt27VqVOnLGtq6tOdgoICFRcXO/Vjt9vVvXt3j/oBAAAAzubtSfHBgwdVVVWlkJAQp/aQkBAVFxe7Paa4uNhtfWVlpQ4ePKiwsLAaa2rqs6bzVB93bj/79+93e0x5ebnKy8sdr8vKyi74fAAAALg61OpDfzabzem1Mcal7Xz157Z72ufFGFt6erqCgoIcW0REhMfnAwAAwJXNo8DcvHlzeXl5udz5LSkpcbmzWy00NNRtvbe3t5o1a2ZZU1OfNZ1Hkkf9TJ48WaWlpY7twIEDF3w+AAAAXB08Csy+vr6KjY1VTk6OU3tOTo4SExPdHpOQkOBSv3btWsXFxcnHx8eypqY+3YmKilJoaKhTPxUVFcrNza2xH7vdrsDAQKcNAAAAOJtHzzBLUlpamlJSUhQXF6eEhAQ9//zzKiws1JgxYySduWv77bffatmyZZLOrIgxf/58paWlafTo0crLy9PixYudVr+YMGGCunXrpoyMDA0ePFhvvPGG1q1bp40bNzpqjh07pn/+85+O1wUFBdq+fbuaNm2qli1bymazKTU1VbNnz1bbtm3Vtm1bzZ49Ww0bNtSIESNqPUEAAAC4unkcmJOTk3Xo0CHNmjVLRUVFiomJUXZ2tiIjIyVJRUVFTmsyR0VFKTs7WxMnTtRzzz2n8PBwPfvssxo2bJijJjExUStXrtRjjz2madOmqU2bNsrMzFR8fLyjZuvWrerZs6fjdVpamiRp5MiReumllyRJjzzyiE6cOKEHHnhAhw8fVnx8vNauXauAgABPLxMAAACQVIt1mK9krMMMAABQv9X7dZgBAACAqw2BuY7UYsU8AAAA1AECMwAAAGCBwAwAAABYIDADAAAAFgjMdelp25kNAAAA9RaBGQAAALBAYAYAAAAsEJgBAAAACwRmAAAAwAKBGQAAALBAYAYAAAAsEJgBAAAACwRmAAAAwAKBGQAAALBAYAYAAAAsEJgBAAAACwRmAAAAwAKBGQAAALBAYAYAAAAsEJjrAZvtzKanbXU9FAAAAJyDwAwAAABYIDADAAAAFgjMAAAAgAUCMwAAAGCBwAwAAABYIDADAAAAFgjMAAAAgAUCMwAAAGCBwAwAAABYIDADAAAAFgjMAAAAgAUCMwAAAGCBwFwP2Wx1PQIAAABUIzADAAAAFgjMAAAAgAUCMwAAAGCBwAwAAABYIDADAAAAFgjM9dXTtjMbAAAA6hSBGQAAALBAYAYAAAAsEJgBAAAACwRmAAAAwAKBGQAAALBAYAYAAAAsEJjrOZvtzAYAAIC6QWC+XLAmMwAAQJ0gMAMAAAAWCMwAAACABQIzAAAAYIHADAAAAFggMAMAAAAWCMwAAACABQLzZYY1mQEAAC4tAjMAAABggcB8OeJLTAAAAC4ZAjMAAABgoVaBecGCBYqKipKfn59iY2O1YcMGy/rc3FzFxsbKz89PrVu31qJFi1xqsrKyFB0dLbvdrujoaK1evdrj844aNUo2m81pu/nmm2tziQAAAICkWgTmzMxMpaamaurUqcrPz1fXrl3Vr18/FRYWuq0vKChQ//791bVrV+Xn52vKlCkaP368srKyHDV5eXlKTk5WSkqKduzYoZSUFA0fPlybN2/2+Lx9+/ZVUVGRY8vOzvb0EgEAAAAHjwPz3Llzde+99+q+++5T+/btNW/ePEVERGjhwoVu6xctWqSWLVtq3rx5at++ve677z7dc889mjNnjqNm3rx56t27tyZPnqx27dpp8uTJuvXWWzVv3jyPz2u32xUaGurYmjZt6uklAgAAAA4eBeaKigpt27ZNSUlJTu1JSUnatGmT22Py8vJc6vv06aOtW7fq1KlTljXVfXpy3vXr1ys4OFjXX3+9Ro8erZKSkhqvp7y8XGVlZU4bAAAAcDaPAvPBgwdVVVWlkJAQp/aQkBAVFxe7Paa4uNhtfWVlpQ4ePGhZU93nhZ63X79+evnll/X+++/r6aef1pYtW9SrVy+Vl5e7HVt6erqCgoIcW0RExAXMAgAAAK4m3rU5yHbOt2cYY1zazld/bvuF9Hm+muTkZMfPMTExiouLU2RkpN5++20NHTrUZVyTJ09WWlqa43VZWdnlF5qrl5h7yNTtOAAAAK5QHgXm5s2by8vLy+VucklJicvd32qhoaFu6729vdWsWTPLmuo+a3NeSQoLC1NkZKS+/PJLt/vtdrvsdnuNx9d3Nptk5py/DgAAALXn0SMZvr6+io2NVU5OjlN7Tk6OEhMT3R6TkJDgUr927VrFxcXJx8fHsqa6z9qcV5IOHTqkAwcOKCws7MIuEAAAADiHx6tkpKWl6cUXX9SSJUu0Z88eTZw4UYWFhRozZoykM4853H333Y76MWPGaP/+/UpLS9OePXu0ZMkSLV68WA8//LCjZsKECVq7dq0yMjL0j3/8QxkZGVq3bp1SU1Mv+LzHjh3Tww8/rLy8PO3bt0/r16/XoEGD1Lx5c91+++21nZ/LD98CCAAAcFF5/AxzcnKyDh06pFmzZqmoqEgxMTHKzs5WZGSkJKmoqMhpbeSoqChlZ2dr4sSJeu655xQeHq5nn31Ww4YNc9QkJiZq5cqVeuyxxzRt2jS1adNGmZmZio+Pv+Dzenl5aefOnVq2bJmOHDmisLAw9ezZU5mZmQoICKj1BAEAAODqVqsP/T3wwAN64IEH3O576aWXXNq6d++uTz/91LLPO+64Q3fccUetz+vv7693333X8ngAAADAU7X6amzUTxYLlQAAAKCWCMwAAACABQIzAAAAYIHADAAAAFggMAMAAAAWCMxXKJtNZ9ZkZl1mAACAn4XADAAAAFggMAMAAAAWCMwAAACABQIzAAAAYIHADAAAAFggMF8FbLazVs0AAACARwjMAAAAgAUCMwAAAGCBwAwAAABYIDBfhWw8ygwAAHDBCMxXOT4QCAAAYI3ADAAAAFjwrusBoI447iibOh0GAABAfccdZrh62sYjGgAAAP9CYAYAAAAsEJgBAAAACwRmODl7yTnHChoAAABXMQIzAAAAYIHADAAAAFggMOP8/rViBo9nAACAqxGBGQAAALBAYMbPw3rNAADgCkdgBgAAACwQmOGZf30LIEvOAQCAqwWBGQAAALBAYAYAAAAsEJhxUZz7DYHVj24AAABc7gjMAAAAgAUCMy6eGu4oO+44AwAAXIYIzAAAAIAFAjMuKZ5vBgAAlxsCM+oMazkDAIDLAYEZde9fd5vPvvtMmAYAAPUFgRkAAACwQGBG/Xb23WcAAIA6QGDG5ePcxzX44CAAALgECMy47HH3GQAA/JIIzLgysFQdAAD4hRCYceUjSAMAgJ+BwIwritXzzTy6AQAAaoPAjCuaS0g+99GNc39mDWgAAHAOAjOuWmeHYrcBuYa71IRpAACuLgRm4DzO/gZCB9aHBgDgqkFgBi6Sc5+fdhu0AQDAZYfADPxcFxCK+bIVAAAuXwRmoA5c6J1oHvkAAKDuEZiBeoaQDABA/UJgBuqjC1ju7uw70273nfUzj4MAAFB7BGbgcmMVfN0E7XPVdtWPmvax1B4A4EpHYAauYm7D7oU+W81z1wCAqwSBGcCF8/DuttVSe273/cv59p0d1s/7BTQAAPxMtQrMCxYsUFRUlPz8/BQbG6sNGzZY1ufm5io2NlZ+fn5q3bq1Fi1a5FKTlZWl6Oho2e12RUdHa/Xq1R6f1xijGTNmKDw8XP7+/urRo4d27dpVm0sEUBesluirbVj/F4/vivPMNwDgXzwOzJmZmUpNTdXUqVOVn5+vrl27ql+/fiosLHRbX1BQoP79+6tr167Kz8/XlClTNH78eGVlZTlq8vLylJycrJSUFO3YsUMpKSkaPny4Nm/e7NF5n3rqKc2dO1fz58/Xli1bFBoaqt69e+vo0aOeXiaAK4XVV5zX9sOV594xVw13vi/0zvoF7Dv3emrzvPnPxh8RAK5SHgfmuXPn6t5779V9992n9u3ba968eYqIiNDChQvd1i9atEgtW7bUvHnz1L59e91333265557NGfOHEfNvHnz1Lt3b02ePFnt2rXT5MmTdeutt2revHkXfF5jjObNm6epU6dq6NChiomJ0V//+lf99NNPeuWVVzy9TACoV2p83txN0Hbs00UO8meN5Wf9AXCecbm9trPPfe6cWP1R5Ga+3M6Rm/7Pt+/sPgBc2bw9Ka6oqNC2bdv06KOPOrUnJSVp06ZNbo/Jy8tTUlKSU1ufPn20ePFinTp1Sj4+PsrLy9PEiRNdaqoD84Wct6CgQMXFxU7nstvt6t69uzZt2qT777/fZWzl5eUqLy93vC4tLZUklZWVWU3DmZqTkv5VV3bS0Xrp9p1bZ7WPcTEuxsW4LqNxBQVJpY+f08cTQdKDpf/+WZJU6ua4c/b967iz+wyynemz9PGzzu2u/wdLa9wX9FipUx9nn/vf+84+98/Yd06d1b6Lfu66Glfpv35X/+q6VuP6Vx/V/Vy0/s96b7j072afS13Nu6X/vbA+JOdrsOyzFi5onBZj/KVV5zRjzKU7qfHAt99+aySZjz76yKn9iSeeMNdff73bY9q2bWueeOIJp7aPPvrISDLfffedMcYYHx8f8/LLLzvVvPzyy8bX1/eCz1vd57fffutUM3r0aJOUlOR2bNOnTzeS2NjY2NjY2NjYLrPtq6++soqtF5VHd5ir2c75/1LGGJe289Wf234hfV6smmqTJ09WWlqa4/WRI0cUGRmpwsJCBVX/CYfzKisrU0REhA4cOKDAwMC6Hs5lgTmrHebNc8xZ7TBvnmPOaod581xpaalatmyppk2bXrJzehSYmzdvLi8vLxUXFzu1l5SUKCQkxO0xoaGhbuu9vb3VrFkzy5rqPi/kvKGhoZKk4uJihYWFXdDY7Ha77Ha7S3tQUBBv2loIDAxk3jzEnNUO8+Y55qx2mDfPMWe1w7x5rkGDS7c6skdn8vX1VWxsrHJycpzac3JylJiY6PaYhIQEl/q1a9cqLi5OPj4+ljXVfV7IeaOiohQaGupUU1FRodzc3BrHBgAAAJyPx49kpKWlKSUlRXFxcUpISNDzzz+vwsJCjRkzRtKZxxy+/fZbLVu2TJI0ZswYzZ8/X2lpaRo9erTy8vK0ePFirVixwtHnhAkT1K1bN2VkZGjw4MF64403tG7dOm3cuPGCz2uz2ZSamqrZs2erbdu2atu2rWbPnq2GDRtqxIgRP2uSAAAAcBWrzYPPzz33nImMjDS+vr6mc+fOJjc317Fv5MiRpnv37k7169evN506dTK+vr6mVatWZuHChS59vvbaa+aGG24wPj4+pl27diYrK8uj8xpjzOnTp8306dNNaGiosdvtplu3bmbnzp0XfF0nT54006dPNydPnrzgY8C81QZzVjvMm+eYs9ph3jzHnNUO8+a5upgzmzGXck0OAAAA4PJy6Z6WBgAAAC5DBGYAAADAAoEZAAAAsEBgBgAAACwQmM+yYMECRUVFyc/PT7GxsdqwYUNdD+mS+fDDDzVo0CCFh4fLZrPp9ddfd9pvjNGMGTMUHh4uf39/9ejRQ7t27XKqKS8v14MPPqjmzZurUaNG+u1vf6tvvvnGqebw4cNKSUlRUFCQgoKClJKSoiNHjvzCV/fLSE9PV5cuXRQQEKDg4GANGTJEe/fudaph3pwtXLhQHTp0cCzQn5CQoHfeecexn/k6v/T0dMcymtWYN1czZsyQzWZz2qq/4Epizqx8++23+v3vf69mzZqpYcOG+o//+A9t27bNsZ+5c9aqVSuX95rNZtPYsWMlMV81qays1GOPPaaoqCj5+/urdevWmjVrlk6fPu2oqVdzd8nW46jnVq5caXx8fMwLL7xgdu/ebSZMmGAaNWpk9u/fX9dDuySys7PN1KlTTVZWlpFkVq9e7bT/ySefNAEBASYrK8vs3LnTJCcnm7CwMFNWVuaoGTNmjLnuuutMTk6O+fTTT03Pnj1Nx44dTWVlpaOmb9++JiYmxmzatMls2rTJxMTEmIEDB16qy7yo+vTpY5YuXWo+//xzs337djNgwADTsmVLc+zYMUcN8+ZszZo15u233zZ79+41e/fuNVOmTDE+Pj7m888/N8YwX+fzySefmFatWpkOHTqYCRMmONqZN1fTp083N954oykqKnJsJSUljv3MmXs//vijiYyMNKNGjTKbN282BQUFZt26deaf//yno4a5c1ZSUuL0PsvJyTGSzAcffGCMYb5q8vjjj5tmzZqZt956yxQUFJjXXnvNNG7c2MybN89RU5/mjsD8L7/+9a/NmDFjnNratWtnHn300ToaUd05NzCfPn3ahIaGmieffNLRdvLkSRMUFGQWLVpkjDHmyJEjxsfHx6xcudJR8+2335oGDRqYv//978YYY3bv3m0kmY8//thRk5eXZySZf/zjH7/wVf3ySkpKjCTH+uDM24Vp0qSJefHFF5mv8zh69Khp27atycnJMd27d3cEZubNvenTp5uOHTu63cec1WzSpEnmlltuqXE/c3d+EyZMMG3atDGnT59mviwMGDDA3HPPPU5tQ4cONb///e+NMfXvvcYjGTrzFdrbtm1TUlKSU3tSUpI2bdpUR6OqPwoKClRcXOw0P3a7Xd27d3fMz7Zt23Tq1CmnmvDwcMXExDhq8vLyFBQUpPj4eEfNzTffrKCgoCtinktLSyVJTZs2lcS8nU9VVZVWrlyp48ePKyEhgfk6j7Fjx2rAgAG67bbbnNqZt5p9+eWXCg8PV1RUlP7zP/9TX3/9tSTmzMqaNWsUFxen3/3udwoODlanTp30wgsvOPYzd9YqKiq0fPly3XPPPbLZbMyXhVtuuUXvvfeevvjiC0nSjh07tHHjRvXv319S/XuvefzV2FeigwcPqqqqSiEhIU7tISEhKi4urqNR1R/Vc+Bufvbv3++o8fX1VZMmTVxqqo8vLi5WcHCwS//BwcGX/TwbY5SWlqZbbrlFMTExkpi3muzcuVMJCQk6efKkGjdurNWrVys6OtrxLy7my9XKlSv16aefasuWLS77eJ+5Fx8fr2XLlun666/X999/r8cff1yJiYnatWsXc2bh66+/1sKFC5WWlqYpU6bok08+0fjx42W323X33Xczd+fx+uuv68iRIxo1apQk/vm0MmnSJJWWlqpdu3by8vJSVVWVnnjiCd15552S6t/cEZjPYrPZnF4bY1zarma1mZ9za9zVXwnzPG7cOH322WfauHGjyz7mzdkNN9yg7du368iRI8rKytLIkSOVm5vr2M98OTtw4IAmTJigtWvXys/Pr8Y65s1Zv379HD/fdNNNSkhIUJs2bfTXv/5VN998syTmzJ3Tp08rLi5Os2fPliR16tRJu3bt0sKFC3X33Xc76pg79xYvXqx+/fopPDzcqZ35cpWZmanly5frlVde0Y033qjt27crNTVV4eHhGjlypKOuvswdj2RIat68uby8vFz+0igpKXH5y+ZqVP3Jcqv5CQ0NVUVFhQ4fPmxZ8/3337v0/8MPP1zW8/zggw9qzZo1+uCDD9SiRQtHO/Pmnq+vr371q18pLi5O6enp6tixo5555hnmqwbbtm1TSUmJYmNj5e3tLW9vb+Xm5urZZ5+Vt7e345qYN2uNGjXSTTfdpC+//JL3moWwsDBFR0c7tbVv316FhYWS+Pealf3792vdunW67777HG3MV83++Mc/6tFHH9V//ud/6qabblJKSoomTpyo9PR0SfVv7gjMOvMf8NjYWOXk5Di15+TkKDExsY5GVX9ERUUpNDTUaX4qKiqUm5vrmJ/Y2Fj5+Pg41RQVFenzzz931CQkJKi0tFSffPKJo2bz5s0qLS29LOfZGKNx48Zp1apVev/99xUVFeW0n3m7MMYYlZeXM181uPXWW7Vz505t377dscXFxemuu+7S9u3b1bp1a+btApSXl2vPnj0KCwvjvWbhN7/5jcvymF988YUiIyMl8e81K0uXLlVwcLAGDBjgaGO+avbTTz+pQQPnGOrl5eVYVq7ezd0FfzzwCle9rNzixYvN7t27TWpqqmnUqJHZt29fXQ/tkjh69KjJz883+fn5RpKZO3euyc/Pdyyr9+STT5qgoCCzatUqs3PnTnPnnXe6XdqlRYsWZt26debTTz81vXr1cru0S4cOHUxeXp7Jy8szN91002W7LM4f/vAHExQUZNavX++0pNBPP/3kqGHenE2ePNl8+OGHpqCgwHz22WdmypQppkGDBmbt2rXGGObrQp29SoYxzJs7Dz30kFm/fr35+uuvzccff2wGDhxoAgICHP9OZ87c++STT4y3t7d54oknzJdffmlefvll07BhQ7N8+XJHDXPnqqqqyrRs2dJMmjTJZR/z5d7IkSPNdddd51hWbtWqVaZ58+bmkUcecdTUp7kjMJ/lueeeM5GRkcbX19d07tzZsTzY1eCDDz4wkly2kSNHGmPOLO8yffp0Exoaaux2u+nWrZvZuXOnUx8nTpww48aNM02bNjX+/v5m4MCBprCw0Knm0KFD5q677jIBAQEmICDA3HXXXebw4cOX6CovLnfzJcksXbrUUcO8Obvnnnsc/4xde+215tZbb3WEZWOYrwt1bmBm3lxVr9fq4+NjwsPDzdChQ82uXbsc+5mzmr355psmJibG2O12065dO/P888877WfuXL377rtGktm7d6/LPubLvbKyMjNhwgTTsmVL4+fnZ1q3bm2mTp1qysvLHTX1ae5sxhhz4fejAQAAgKsLzzADAAAAFgjMAAAAgAUCMwAAAGCBwAwAAABYIDADAAAAFgjMAAAAgAUCMwAAAGCBwAwAAABYIDADAAAAFgjMAAAAgAUCMwAAAGCBwAwAAABY+P/OY9ekfrOVRwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,6))\n",
    "plt.hist([ak.ravel(tracked[\"brem_photons_pe\"]), ak.ravel(lost[\"brem_photons_pe\"])], 5000, density=True, histtype=\"bar\", color=colors, label=labels)\n",
    "plt.xlim(0,8000)\n",
    "plt.title(\"brem photons abs(p)\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 4000x2000 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ((ax0, ax1, ax2), (ax3, ax4, ax5)) = plt.subplots(nrows=2, ncols=3, figsize=(40,20))\n",
    "\n",
    "colors = ['blue', 'darkorange']\n",
    "labels = [\"tracked\", \"lost\"]\n",
    "n_bins=200\n",
    "\n",
    "ax0.hist([ak.ravel(tracked[\"brem_photons_px\"]),ak.ravel(lost[\"brem_photons_px\"])], 500, density=True, histtype='bar', color=colors, label=labels)\n",
    "ax0.legend()\n",
    "ax0.set_xlim(-1500,1500)\n",
    "ax0.set_title('brem photon px')\n",
    "\n",
    "ax1.hist([ak.ravel(tracked[\"brem_photons_py\"]),ak.ravel(lost[\"brem_photons_py\"])], 1000, density=True, histtype='bar', color=colors, label=labels)\n",
    "ax1.legend()\n",
    "ax1.set_xlim(-500,500)\n",
    "ax1.set_title('brem photon py')\n",
    "\n",
    "ax2.hist([ak.ravel(tracked[\"brem_photons_pz\"]),ak.ravel(lost[\"brem_photons_pz\"])], 1000, density=True, histtype='bar', color=colors, label=labels)\n",
    "ax2.legend()\n",
    "ax2.set_xlim(0,10000)\n",
    "ax2.set_title('brem photon pz')\n",
    "\n",
    "ax3.hist([ak.ravel(tracked[\"brem_vtx_x\"]),ak.ravel(lost[\"brem_vtx_x\"])], n_bins, density=True, histtype='bar', color=colors, label=labels)\n",
    "ax3.legend()\n",
    "ax3.set_title('brem vtx x')\n",
    "\n",
    "ax4.hist([ak.ravel(tracked[\"brem_vtx_y\"]),ak.ravel(lost[\"brem_vtx_y\"])], n_bins, density=True, histtype='bar', color=colors, label=labels)\n",
    "ax4.legend()\n",
    "ax4.set_title('brem vtx y')\n",
    "\n",
    "ax5.hist([ak.ravel(tracked[\"brem_vtx_z\"]),ak.ravel(lost[\"brem_vtx_z\"])], n_bins, density=True, histtype='bar', color=colors, label=labels)\n",
    "ax5.legend()\n",
    "ax5.set_title('brem vtx z')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ((ax0, ax1)) = plt.subplots(nrows=1, ncols=2, figsize=(20,6))\n",
    "\n",
    "ax0.hist([ak.ravel(tracked[\"velo_track_x\"]), ak.ravel(lost[\"velo_track_x\"])], bins=150, density=True, histtype='bar', color=colors, label=labels)\n",
    "ax0.legend()\n",
    "ax0.set_title('velo track x')\n",
    "\n",
    "ax1.hist([ak.ravel(tracked[\"velo_track_y\"]), ak.ravel(lost[\"velo_track_y\"])],bins=150, density=True, histtype='bar', color=colors, label=labels)\n",
    "ax1.legend()\n",
    "ax1.set_title('velo track y')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\"\"\"\n",
    "#cut experimentation\n",
    "\n",
    "zcut = (ak.any(tracked[\"velo_hit_pos_z\"]<200, axis=-1) & ak.any(tracked[\"velo_hit_pos_z\"]>-200, axis=-1))\n",
    "zlc = (ak.any(lost[\"velo_hit_pos_z\"]<200, axis=-1) & ak.any(lost[\"velo_hit_pos_z\"]>-200, axis=-1))\n",
    "ztr = tracked[zcut]\n",
    "zlo = lost[zlc]\n",
    "\n",
    "colors = ['blue', 'darkorange']\n",
    "labels = [\"tracked\", \"lost\"]\n",
    "n_bins=200\n",
    "\n",
    "plt.hist([ak.ravel(ztr[\"velo_hit_pos_z\"]),ak.ravel(zlo[\"velo_hit_pos_z\"])], bins=n_bins, density=True, histtype='bar', color=colors, label=labels)\n",
    "plt.legend()\n",
    "plt.title('velo z')\n",
    "plt.show()\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'all_endvtx_types_length': 3,\n",
       " 'all_endvtx_types': [101.0, 104.0, 0.0],\n",
       " 'all_endvtx_x_length': 3,\n",
       " 'all_endvtx_x': [14.989899635314941, 15.055899620056152, 1996.3660888671875],\n",
       " 'all_endvtx_y_length': 3,\n",
       " 'all_endvtx_y': [-30.541900634765625,\n",
       "  -30.669300079345703,\n",
       "  -396.27178955078125],\n",
       " 'all_endvtx_z_length': 3,\n",
       " 'all_endvtx_z': [935.5191040039062, 939.534423828125, 12658.6591796875],\n",
       " 'brem_photons_pe_length': 1,\n",
       " 'brem_photons_pe': [151.66514587402344],\n",
       " 'brem_photons_px_length': 1,\n",
       " 'brem_photons_px': [2.450000047683716],\n",
       " 'brem_photons_py_length': 1,\n",
       " 'brem_photons_py': [-4.78000020980835],\n",
       " 'brem_photons_pz_length': 1,\n",
       " 'brem_photons_pz': [151.57000732421875],\n",
       " 'brem_vtx_x_length': 1,\n",
       " 'brem_vtx_x': [14.989899635314941],\n",
       " 'brem_vtx_y_length': 1,\n",
       " 'brem_vtx_y': [-30.541900634765625],\n",
       " 'brem_vtx_z_length': 1,\n",
       " 'brem_vtx_z': [935.5191040039062],\n",
       " 'endvtx_type': 0,\n",
       " 'endvtx_x': nan,\n",
       " 'endvtx_y': nan,\n",
       " 'endvtx_z': nan,\n",
       " 'energy': 5565.570363846007,\n",
       " 'eta': 4.08326911379515,\n",
       " 'event_count': 0,\n",
       " 'fromB': False,\n",
       " 'fromD': False,\n",
       " 'fromDecay': False,\n",
       " 'fromHadInt': False,\n",
       " 'fromPV': False,\n",
       " 'fromPairProd': True,\n",
       " 'fromSignal': False,\n",
       " 'fromStrange': False,\n",
       " 'isElectron': True,\n",
       " 'isKaon': False,\n",
       " 'isMuon': False,\n",
       " 'isPion': False,\n",
       " 'isProton': False,\n",
       " 'lost': False,\n",
       " 'lost_in_track_fit': False,\n",
       " 'match_fraction': 1.0,\n",
       " 'mcp_idx': 2608,\n",
       " 'mother_id': 22,\n",
       " 'mother_key': 2607,\n",
       " 'originvtx_type': 102,\n",
       " 'originvtx_x': 6.2875000000000005,\n",
       " 'originvtx_y': -13.276200000000001,\n",
       " 'originvtx_z': 385.07070000000004,\n",
       " 'p': 5565.570340387407,\n",
       " 'phi': -1.129423972793533,\n",
       " 'pid': -11,\n",
       " 'pt': 187.531879156585,\n",
       " 'px': 80.11,\n",
       " 'py': -169.56,\n",
       " 'pz': 5562.41,\n",
       " 'scifi_hit_pos_x_length': 12,\n",
       " 'scifi_hit_pos_x': [748.9720458984375,\n",
       "  765.9661254882812,\n",
       "  783.1256103515625,\n",
       "  800.260009765625,\n",
       "  918.012451171875,\n",
       "  935.6343383789062,\n",
       "  953.3908081054688,\n",
       "  971.0899047851562,\n",
       "  1092.497802734375,\n",
       "  1110.47998046875,\n",
       "  1128.590087890625,\n",
       "  1146.6357421875],\n",
       " 'scifi_hit_pos_y_length': 12,\n",
       " 'scifi_hit_pos_y': [-243.1846160888672,\n",
       "  -245.28126525878906,\n",
       "  -247.38218688964844,\n",
       "  -249.4748992919922,\n",
       "  -263.50482177734375,\n",
       "  -265.5829772949219,\n",
       "  -267.6712341308594,\n",
       "  -269.77069091796875,\n",
       "  -284.1728210449219,\n",
       "  -286.2898864746094,\n",
       "  -288.4374694824219,\n",
       "  -290.5879821777344],\n",
       " 'scifi_hit_pos_z_length': 12,\n",
       " 'scifi_hit_pos_z': [7825.2236328125,\n",
       "  7895.0166015625,\n",
       "  7965.20947265625,\n",
       "  8035.00244140625,\n",
       "  8507.150390625,\n",
       "  8576.943359375,\n",
       "  8647.13671875,\n",
       "  8716.9296875,\n",
       "  9192.076171875,\n",
       "  9261.869140625,\n",
       "  9332.0615234375,\n",
       "  9401.8544921875],\n",
       " 'track_p': 5280.022074225443,\n",
       " 'track_pt': 183.50043288509636,\n",
       " 'tx': 0.014402030774430507,\n",
       " 'ty': -0.030483189840374948,\n",
       " 'ut_hit_pos_x_length': 5,\n",
       " 'ut_hit_pos_x': [40.90873718261719,\n",
       "  42.1309814453125,\n",
       "  47.45195007324219,\n",
       "  48.83097457885742,\n",
       "  48.83406066894531],\n",
       " 'ut_hit_pos_y_length': 5,\n",
       " 'ut_hit_pos_y': [-73.33869934082031,\n",
       "  -75.0264892578125,\n",
       "  -81.90847778320312,\n",
       "  -83.59490203857422,\n",
       "  -83.59870147705078],\n",
       " 'ut_hit_pos_z_length': 5,\n",
       " 'ut_hit_pos_z': [2321.846435546875,\n",
       "  2376.846435546875,\n",
       "  2601.846435546875,\n",
       "  2656.765380859375,\n",
       "  2656.888916015625],\n",
       " 'velo_hit_pos_x_length': 7,\n",
       " 'velo_hit_pos_x': [6.313237190246582,\n",
       "  6.5126190185546875,\n",
       "  7.8375444412231445,\n",
       "  9.391555786132812,\n",
       "  10.16195011138916,\n",
       "  10.950575828552246,\n",
       "  11.7467041015625],\n",
       " 'velo_hit_pos_y_length': 7,\n",
       " 'velo_hit_pos_y': [-13.330745697021484,\n",
       "  -13.751118659973145,\n",
       "  -16.4586124420166,\n",
       "  -19.542583465576172,\n",
       "  -21.095014572143555,\n",
       "  -22.661531448364258,\n",
       "  -24.2331485748291],\n",
       " 'velo_hit_pos_z_length': 7,\n",
       " 'velo_hit_pos_z': [386.8590087890625,\n",
       "  400.6409912109375,\n",
       "  486.8590087890625,\n",
       "  586.8590087890625,\n",
       "  636.8590087890625,\n",
       "  686.8590087890625,\n",
       "  736.8590087890625],\n",
       " 'velo_track_idx': 17,\n",
       " 'velo_track_tx': 0.015615668147802353,\n",
       " 'velo_track_ty': -0.03123132698237896,\n",
       " 'velo_track_x': 12.28200912475586,\n",
       " 'velo_track_y': -25.28349494934082,\n",
       " 'velo_track_z': 770.0}"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tracked[1].tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'lost' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m/work/cetin/Projektpraktikum/wetest.ipynb Cell 16\u001b[0m line \u001b[0;36m1\n\u001b[0;32m----> <a href='vscode-notebook-cell://ssh-remote%2Blhcba1.physi.uni-heidelberg.de/work/cetin/Projektpraktikum/wetest.ipynb#X21sdnNjb2RlLXJlbW90ZQ%3D%3D?line=0'>1</a>\u001b[0m lost[\u001b[39m1\u001b[39m]\u001b[39m.\u001b[39mtolist()\n",
      "\u001b[0;31mNameError\u001b[0m: name 'lost' is not defined"
     ]
    }
   ],
   "source": [
    "lost[1].tolist()"
   ]
  },
  {
   "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": []
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name                 | typename                 | interpretation                \n",
      "---------------------+--------------------------+-------------------------------\n",
      "all_endvtx_types_... | int32_t                  | AsDtype('>i4')\n",
      "all_endvtx_types     | float[]                  | AsJagged(AsDtype('>f4'))\n",
      "all_endvtx_x_length  | int32_t                  | AsDtype('>i4')\n",
      "all_endvtx_x         | float[]                  | AsJagged(AsDtype('>f4'))\n",
      "all_endvtx_y_length  | int32_t                  | AsDtype('>i4')\n",
      "all_endvtx_y         | float[]                  | AsJagged(AsDtype('>f4'))\n",
      "all_endvtx_z_length  | int32_t                  | AsDtype('>i4')\n",
      "all_endvtx_z         | float[]                  | AsJagged(AsDtype('>f4'))\n",
      "brem_photons_pe_l... | int32_t                  | AsDtype('>i4')\n",
      "brem_photons_pe      | float[]                  | AsJagged(AsDtype('>f4'))\n",
      "brem_photons_px_l... | int32_t                  | AsDtype('>i4')\n",
      "brem_photons_px      | float[]                  | AsJagged(AsDtype('>f4'))\n",
      "brem_photons_py_l... | int32_t                  | AsDtype('>i4')\n",
      "brem_photons_py      | float[]                  | AsJagged(AsDtype('>f4'))\n",
      "brem_photons_pz_l... | int32_t                  | AsDtype('>i4')\n",
      "brem_photons_pz      | float[]                  | AsJagged(AsDtype('>f4'))\n",
      "brem_vtx_x_length    | int32_t                  | AsDtype('>i4')\n",
      "brem_vtx_x           | float[]                  | AsJagged(AsDtype('>f4'))\n",
      "brem_vtx_y_length    | int32_t                  | AsDtype('>i4')\n",
      "brem_vtx_y           | float[]                  | AsJagged(AsDtype('>f4'))\n",
      "brem_vtx_z_length    | int32_t                  | AsDtype('>i4')\n",
      "brem_vtx_z           | float[]                  | AsJagged(AsDtype('>f4'))\n",
      "endvtx_type          | int32_t                  | AsDtype('>i4')\n",
      "endvtx_x             | double                   | AsDtype('>f8')\n",
      "endvtx_y             | double                   | AsDtype('>f8')\n",
      "endvtx_z             | double                   | AsDtype('>f8')\n",
      "energy               | double                   | AsDtype('>f8')\n",
      "eta                  | double                   | AsDtype('>f8')\n",
      "event_count          | int32_t                  | AsDtype('>i4')\n",
      "fromB                | bool                     | AsDtype('bool')\n",
      "fromD                | bool                     | AsDtype('bool')\n",
      "fromDecay            | bool                     | AsDtype('bool')\n",
      "fromHadInt           | bool                     | AsDtype('bool')\n",
      "fromPV               | bool                     | AsDtype('bool')\n",
      "fromPairProd         | bool                     | AsDtype('bool')\n",
      "fromSignal           | bool                     | AsDtype('bool')\n",
      "fromStrange          | bool                     | AsDtype('bool')\n",
      "isElectron           | bool                     | AsDtype('bool')\n",
      "isKaon               | bool                     | AsDtype('bool')\n",
      "isMuon               | bool                     | AsDtype('bool')\n",
      "isPion               | bool                     | AsDtype('bool')\n",
      "isProton             | bool                     | AsDtype('bool')\n",
      "lost                 | bool                     | AsDtype('bool')\n",
      "lost_in_track_fit    | bool                     | AsDtype('bool')\n",
      "match_fraction       | float                    | AsDtype('>f4')\n",
      "mcp_idx              | int32_t                  | AsDtype('>i4')\n",
      "mother_id            | int32_t                  | AsDtype('>i4')\n",
      "mother_key           | int32_t                  | AsDtype('>i4')\n",
      "originvtx_type       | int32_t                  | AsDtype('>i4')\n",
      "originvtx_x          | double                   | AsDtype('>f8')\n",
      "originvtx_y          | double                   | AsDtype('>f8')\n",
      "originvtx_z          | double                   | AsDtype('>f8')\n",
      "p                    | double                   | AsDtype('>f8')\n",
      "phi                  | double                   | AsDtype('>f8')\n",
      "pid                  | int32_t                  | AsDtype('>i4')\n",
      "pt                   | double                   | AsDtype('>f8')\n",
      "px                   | double                   | AsDtype('>f8')\n",
      "py                   | double                   | AsDtype('>f8')\n",
      "pz                   | double                   | AsDtype('>f8')\n",
      "scifi_hit_pos_x_l... | int32_t                  | AsDtype('>i4')\n",
      "scifi_hit_pos_x      | float[]                  | AsJagged(AsDtype('>f4'))\n",
      "scifi_hit_pos_y_l... | int32_t                  | AsDtype('>i4')\n",
      "scifi_hit_pos_y      | float[]                  | AsJagged(AsDtype('>f4'))\n",
      "scifi_hit_pos_z_l... | int32_t                  | AsDtype('>i4')\n",
      "scifi_hit_pos_z      | float[]                  | AsJagged(AsDtype('>f4'))\n",
      "track_p              | double                   | AsDtype('>f8')\n",
      "track_pt             | double                   | AsDtype('>f8')\n",
      "tx                   | double                   | AsDtype('>f8')\n",
      "ty                   | double                   | AsDtype('>f8')\n",
      "ut_hit_pos_x_length  | int32_t                  | AsDtype('>i4')\n",
      "ut_hit_pos_x         | float[]                  | AsJagged(AsDtype('>f4'))\n",
      "ut_hit_pos_y_length  | int32_t                  | AsDtype('>i4')\n",
      "ut_hit_pos_y         | float[]                  | AsJagged(AsDtype('>f4'))\n",
      "ut_hit_pos_z_length  | int32_t                  | AsDtype('>i4')\n",
      "ut_hit_pos_z         | float[]                  | AsJagged(AsDtype('>f4'))\n",
      "velo_hit_pos_x_le... | int32_t                  | AsDtype('>i4')\n",
      "velo_hit_pos_x       | float[]                  | AsJagged(AsDtype('>f4'))\n",
      "velo_hit_pos_y_le... | int32_t                  | AsDtype('>i4')\n",
      "velo_hit_pos_y       | float[]                  | AsJagged(AsDtype('>f4'))\n",
      "velo_hit_pos_z_le... | int32_t                  | AsDtype('>i4')\n",
      "velo_hit_pos_z       | float[]                  | AsJagged(AsDtype('>f4'))\n",
      "velo_track_idx       | int32_t                  | AsDtype('>i4')\n",
      "velo_track_tx        | double                   | AsDtype('>f8')\n",
      "velo_track_ty        | double                   | AsDtype('>f8')\n",
      "velo_track_x         | double                   | AsDtype('>f8')\n",
      "velo_track_y         | double                   | AsDtype('>f8')\n",
      "velo_track_z         | double                   | AsDtype('>f8')\n"
     ]
    }
   ],
   "source": [
    "file.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'\\nvar=\"energy\"\\n#plt.hist(tracked[var], bins=1000, label=\"tracked\",edgecolor=\"blue\", fill=False, density=True)\\n#plt.hist(lost[var], bins=1000, label=\"lost\",edgecolor=\"darkorange\", fill=False, density=True)\\nplt.hist([tracked[var], lost[var]],bins=1000,label=[\"tracked\", \"lost\"], density=True)\\nplt.title(var)\\nplt.xlim([0,40000])\\nplt.xlabel(var+\" [MeV]\")\\nplt.ylabel(\"scaled\")\\nplt.legend()\\nplt.show()\\n\\nvar=\"eta\"\\nplt.hist(tracked[var], bins=100, label=\"tracked\", edgecolor=\"blue\", fill=False, density=True)\\nplt.hist(lost[var], bins=100, label=\"lost\", edgecolor=\"orange\", fill=False, density=True)\\n#plt.hist([tracked[var], lost[var]],bins=150,label=[\"tracked\", \"lost\"], density=True)\\nplt.title(var)\\nplt.xlabel(var)\\nplt.ylabel(\"scaled\")\\nplt.legend()\\nplt.show()\\n\\nvar=\"p\"\\n#plt.hist(tracked[var], bins=100, label=\"tracked\")\\n#plt.hist(lost[var], bins=100, label=\"lost\")\\nplt.hist([tracked[var], lost[var]],bins=200,label=[\"tracked\", \"lost\"], density=True)\\nplt.title(var)\\nplt.xlabel(var+f\" [MeV/$c^2$]\")\\nplt.ylabel(\"scaled\")\\nplt.xlim([0,150000])\\nplt.legend()\\nplt.show()\\n\\nvar=\"pt\"\\n#plt.hist(tracked[var], bins=200, label=\"tracked\",density=True)\\n#plt.hist(lost[var], bins=200, label=\"lost\", density=True)\\nplt.hist([tracked[var], lost[var]],bins=200,label=[\"tracked\", \"lost\"], density=True)\\nplt.title(var)\\nplt.xlabel(f\"p transversal [MeV/$c^2$]\")\\nplt.ylabel(\"counts\")\\nplt.xlim([0,6000])\\nplt.legend()\\nplt.show()\\n\\nvar=\"tx\"\\n#plt.hist(tracked[var], bins=100, label=\"tracked\")\\n#plt.hist(lost[var], bins=100, label=\"lost\")\\nplt.hist([tracked[var], lost[var]],bins=100,label=[\"tracked\", \"lost\"], density=True)\\nplt.title(var)\\nplt.xlabel(f\"tx [MeV/$c^2$]\")\\nplt.ylabel(\"counts\")\\n#plt.xlim([0,6000])\\nplt.legend()\\nplt.show()\\n\\nvar=\"ty\"\\n#plt.hist(tracked[var], bins=100, label=\"tracked\")\\n#plt.hist(lost[var], bins=100, label=\"lost\")\\nplt.hist([tracked[var], lost[var]],bins=100,label=[\"tracked\", \"lost\"], density=True)\\nplt.title(var)\\nplt.xlabel(f\"ty [MeV/$c^2$]\")\\nplt.ylabel(\"counts\")\\n#plt.xlim([0,6000])\\nplt.legend()\\nplt.show()\\n'"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\"\n",
    "var=\"energy\"\n",
    "#plt.hist(tracked[var], bins=1000, label=\"tracked\",edgecolor=\"blue\", fill=False, density=True)\n",
    "#plt.hist(lost[var], bins=1000, label=\"lost\",edgecolor=\"darkorange\", fill=False, density=True)\n",
    "plt.hist([tracked[var], lost[var]],bins=1000,label=[\"tracked\", \"lost\"], density=True)\n",
    "plt.title(var)\n",
    "plt.xlim([0,40000])\n",
    "plt.xlabel(var+\" [MeV]\")\n",
    "plt.ylabel(\"scaled\")\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n",
    "var=\"eta\"\n",
    "plt.hist(tracked[var], bins=100, label=\"tracked\", edgecolor=\"blue\", fill=False, density=True)\n",
    "plt.hist(lost[var], bins=100, label=\"lost\", edgecolor=\"orange\", fill=False, density=True)\n",
    "#plt.hist([tracked[var], lost[var]],bins=150,label=[\"tracked\", \"lost\"], density=True)\n",
    "plt.title(var)\n",
    "plt.xlabel(var)\n",
    "plt.ylabel(\"scaled\")\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n",
    "var=\"p\"\n",
    "#plt.hist(tracked[var], bins=100, label=\"tracked\")\n",
    "#plt.hist(lost[var], bins=100, label=\"lost\")\n",
    "plt.hist([tracked[var], lost[var]],bins=200,label=[\"tracked\", \"lost\"], density=True)\n",
    "plt.title(var)\n",
    "plt.xlabel(var+f\" [MeV/$c^2$]\")\n",
    "plt.ylabel(\"scaled\")\n",
    "plt.xlim([0,150000])\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n",
    "var=\"pt\"\n",
    "#plt.hist(tracked[var], bins=200, label=\"tracked\",density=True)\n",
    "#plt.hist(lost[var], bins=200, label=\"lost\", density=True)\n",
    "plt.hist([tracked[var], lost[var]],bins=200,label=[\"tracked\", \"lost\"], density=True)\n",
    "plt.title(var)\n",
    "plt.xlabel(f\"p transversal [MeV/$c^2$]\")\n",
    "plt.ylabel(\"counts\")\n",
    "plt.xlim([0,6000])\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n",
    "var=\"tx\"\n",
    "#plt.hist(tracked[var], bins=100, label=\"tracked\")\n",
    "#plt.hist(lost[var], bins=100, label=\"lost\")\n",
    "plt.hist([tracked[var], lost[var]],bins=100,label=[\"tracked\", \"lost\"], density=True)\n",
    "plt.title(var)\n",
    "plt.xlabel(f\"tx [MeV/$c^2$]\")\n",
    "plt.ylabel(\"counts\")\n",
    "#plt.xlim([0,6000])\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n",
    "var=\"ty\"\n",
    "#plt.hist(tracked[var], bins=100, label=\"tracked\")\n",
    "#plt.hist(lost[var], bins=100, label=\"lost\")\n",
    "plt.hist([tracked[var], lost[var]],bins=100,label=[\"tracked\", \"lost\"], density=True)\n",
    "plt.title(var)\n",
    "plt.xlabel(f\"ty [MeV/$c^2$]\")\n",
    "plt.ylabel(\"counts\")\n",
    "#plt.xlim([0,6000])\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\"\"\""
   ]
  }
 ],
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