Occupancy Rates Analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "b468a964",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import relevant packages\n",
    "import uproot\n",
    "import vector\n",
    "import awkward as ak\n",
    "import numpy as np\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "import math\n",
    "import matplotlib.colors as colors\n",
    "from scipy.stats import norm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "50ebf9d7",
   "metadata": {},
   "outputs": [],
   "source": [
    "tree=uproot.open(\"/Users/isaac/Desktop/mucolstudies/ntup_collectionsNoBIB.root\")[\"tracks_tree\"]\n",
    "treeBIB=uproot.open(\"/Users/isaac/Desktop/mucolstudies/ntup_hitsBIB1[123]0.root\")[\"tracks_tree\"]\n",
    "treeNOBIB=uproot.open(\"/Users/isaac/Desktop/mucolstudies/ntup_hitsNoBIB.root\")[\"tracks_tree\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "51f197a9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['x', 'y', 'z', 't', 'barOrEnd', 'location', 'module', 'layer', 'side']\n"
     ]
    }
   ],
   "source": [
    "print(treeBIB.keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b14477e3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# a handy plotting function\n",
    "def plot1DHistogram(data,bins,scale='linear',label=\"\", savefig=False, dpi=300):\n",
    "    \n",
    "    # handle data, there must be a smarter way to do this...\n",
    "    if type(data[0])==np.int64 : data_flat=data\n",
    "    elif type(data[0])==np.float32 : data_flat=data\n",
    "    elif type(data[0])==np.float64 : data_flat=data\n",
    "    else: data_flat = ak.flatten(data)\n",
    "    \n",
    "    fig = plt.figure(figsize=(15,10))\n",
    "    ax = fig.add_subplot(111)\n",
    "    \n",
    "    ax.hist(data_flat, bins=bins)\n",
    "    \n",
    "    # handle labels\n",
    "    title  = \"\" if len(label.split(\";\")) < 1 else label.split(\";\")[0]  \n",
    "    xlabel = \"\" if len(label.split(\";\")) < 2 else label.split(\";\")[1]  \n",
    "    ylabel = \"\" if len(label.split(\";\")) < 3 else label.split(\";\")[2] \n",
    "    \n",
    "    ax.set_title(title)\n",
    "    ax.set_xlabel(xlabel)\n",
    "    ax.set_ylabel(ylabel)\n",
    "    plt.yscale(scale)\n",
    "    if savefig:\n",
    "        plt.savefig(title + \".png\", dpi=dpi)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e2fe3da7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# a handy plotting function\n",
    "def plot2DHistogram(datax, datay, bins=100, norm=\"log\", label=\"\", savefig=False, dpi=300):\n",
    "    \n",
    "    data_flatx = np.array(np.ravel(datax)).T\n",
    "    data_flaty = np.array(np.ravel(datay)).T\n",
    "    #print(len(data_flatx),data_flatx)\n",
    "    #print(len(data_flaty),data_flaty)\n",
    "    \n",
    "    fig = plt.figure(figsize=(15,10))\n",
    "    ax = fig.add_subplot(111)\n",
    "    \n",
    "    hh = ax.hist2d(data_flatx, data_flaty, bins=bins, norm=norm, cmap=\"plasma\")\n",
    "    \n",
    "    title  = \"\" if len(label.split(\";\")) < 1 else label.split(\";\")[0]  \n",
    "    xlabel = \"\" if len(label.split(\";\")) < 2 else label.split(\";\")[1]  \n",
    "    ylabel = \"\" if len(label.split(\";\")) < 3 else label.split(\";\")[2]  \n",
    "    zlabel = \"\" if len(label.split(\";\")) < 4 else label.split(\";\")[3] \n",
    "    \n",
    "    ax.set_title(title)\n",
    "    ax.set_xlabel(xlabel)\n",
    "    ax.set_ylabel(ylabel)\n",
    "    \n",
    "    # colorbars are annoying\n",
    "    cbar = fig.colorbar(hh[3])\n",
    "    #cbar.ax.tick_params(labelsize=tick_font_size)\n",
    "    cbar.set_label(zlabel, fontsize=15)\n",
    "\n",
    "    if savefig:\n",
    "        plt.savefig(title + \".png\", dpi=dpi)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "ca660603",
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.rcParams.update({'font.size': 20,\n",
    "                    'xtick.labelsize' : 50,\n",
    "                    'ytick.labelsize' : 50,\n",
    "                    'xtick.major.size' : 10,\n",
    "                    'ytick.major.size' : 10,\n",
    "                    'xtick.minor.size' : 5,\n",
    "                    'ytick.minor.size' : 5,\n",
    "                    'axes.labelsize' : 50,\n",
    "                    'axes.titlesize' : 50}) "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2624fc79",
   "metadata": {},
   "source": [
    "# Investigating per layer occupancy rates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "d6f24460",
   "metadata": {},
   "outputs": [],
   "source": [
    "layerPerModule={\n",
    "    1 : 8,\n",
    "    2 : 8,\n",
    "    3 : 3,\n",
    "    4 : 7,\n",
    "    5 : 3,\n",
    "    6 : 4\n",
    "} #dictionairy to help loop over all layers later"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "db62b63f",
   "metadata": {},
   "outputs": [],
   "source": [
    "layersBeforeModule={\n",
    "    1 : 0,\n",
    "    2 : 8,\n",
    "    3 : 24,\n",
    "    4 : 27,\n",
    "    5 : 41,\n",
    "    6 : 44\n",
    "}#Function to help with hashing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "804fa6b4",
   "metadata": {},
   "outputs": [],
   "source": [
    "surfacearea=layer_area = np.array([270.40, 270.40, 448.50, 448.50, 655.20, 655.20, 904.80, 904.80,  # VXD barrel\n",
    "                      389.00, 389.00, 378.96, 378.96, 364.36, 364.36, 312.48, 312.48,  # VXD endcaps\n",
    "                      389.00, 389.00, 378.96, 378.96, 364.36, 364.36, 312.48, 312.48,\n",
    "                      8117.85, 22034.16, 51678.81,  # IT barrel\n",
    "                      6639.65, 10611.59, 10078.04, 9900.19, 9307.37, 8595.98, 8299.56,  # IT endcaps\n",
    "                      6639.65, 10611.59, 10078.04, 9900.19, 9307.37, 8595.98, 8299.56,\n",
    "                      140032.91, 194828.39, 249623.88,  # OT barrel\n",
    "                      69545.45, 69545.45, 69545.45, 69545.45,  # OT endcaps\n",
    "                      69545.45, 69545.45, 69545.45, 69545.45])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "54533b76",
   "metadata": {},
   "outputs": [
    {
     "data": {
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AgxAAAQAABiEAAgAADEIABAAAGIQACAAAMAgBEAAAYBACIAAAwCAEQAAAgEEIgAAAAIMQAAEAAAYhAAIAAAxCAAQAABiEAAgAADAIARAAAGAQAiAAAMAgBEAAAIBBCIAAAACDEAABAAAGIQACAAAMQgAEAAAYhAAIAAAwCAEQAABgEAIgAADAIARAAACAQQiAAAAAgxAAAQAABiEAAgAADEIABAAAGIQACAAAMAgBEAAAYBACIAAAwCAEQAAAgEEIgAAAAIMQAAEAAAYhAAIAAAxCAAQAABiEAAgAADAIARAAAGAQAiAAAMAgBEAAAIBBCIAAAACDEAABAAAGsW8dg1TVsUlOTnL7JCckuWGSY5JcnuSSJJ9L8s7u/tg65gMAAGBxCwfAqrpuktOS3D/J/ZLcK8mds4XVxKq6OMnLkvx+d//donMDAACwvGVWAL8lyduWnO/mSf5dkn9XVX+e5And/cklxwIAAGABu/kM4A8neVdV7d/FGgAAAIaxjmcAO8n7k7wnyUeSfDzJV5JckeQGmT0TeGqS0zc+b3bTJK+rqu/o7g+uoRYAAAAOYpkA2Ek+mORVSV6d5C3d/aXD3VRVxyT5xSRPSXL0pq4bJfl/quqB3d1L1AMAAMAWLBwAN1bqTlnivsuS/HpVvTnJXyU5alP3/ZM8KMl5i44LAADA1uz4M4Dd/aYkvzXR9aidrgUAAGAku/USmBdPtN1tx6sAAAAYyG4FwH+YaLvNjlcBAAAwkN0KgEdPtF2x41UAAAAMZB3HQCzjPhNtU6uCAAd10tnnHrTvomedsYOVAADsDbu1AvgfJ9pes+NVAAAADGRHA2BVXa+qfjfJQ+e6Ppfkj3ayFgAAgNHsyBbQqjopyRmZHQR/l7nuTvKz3X3pTtQCAAAwqrUFwI0D3o/d3JTkuCS3THLDg9x2RZKf6+6Xr6sOAAAApq1zBfCemQW+rfrrJL/c3e9cYw0AAAAcxG68BfTdSR7f3W/ahbkBAACGtRsB8J5JXl9Vf57kGd39rq3cVFVnJjnzcNedeOKJK5YHAABwZFpbAOzuG2z+XFX7khyf5ITMzv17VJLvzezZwOtufP7XVfWU7n7GFsY/J8k5h7tu//79vXDxAAAAA9i2YyC6+6ruvri739Xd/3d3n57k25NsXvHbl+TpVfXc7aoDAACAmR09B3DjhS8PSPK2ua5fqqpH7WQtAAAAo9nRAJgk3f3VJD+W5LK5rudsbBsFAABgG+x4AEyS7v5Ykj+aa75DktN3oRwAAIAh7EoA3PCqibYH73QRAAAAo9jNAHjRRNuddroIAACAUexmALx8ou2GO14FAADAIHYzAN5you3iHa8CAABgELsZAO870fbpHa8CAABgELsSAKuqkvz4RNdbdroWAACAUezWCuDjkpw61/b1TL8ZFAAAgDVYKABW1alV9R+r6thlJ6yqRyX53Ymu3984JB4AAIBtsOgK4I2TPDvJR6vqOVW1f6s3VtU9quolSV6a5Hpz3Z9J8qQFawEAAGAB+5a875ZJzkpyVlV9Jsnbk7wzyaeSXJLka0lukOQmSe6R5Ds3/nfKl5L8UHdfsmQtAAAAbMGyAXCzWyV52MbXoj6Z5Ie7+/w11AEAAMAhLLoF9PIkV69h3iuT/JckdxX+AAAAdsZCK4Dd/daqumWS70vy0MzO8rtrthYkL8tsq+ifJnlJd39+wVoBAABYwcJbQLv7C0n++8ZXquq4JN+S5I5Jbp3Zs39HJ7k0yZczeybwA0ne393rWD0EAABgCSs/A9jdl2b2Aph3rjoWAAAA22e3DoIHAABghwmAAAAAgxAAAQAABiEAAgAADEIABAAAGIQACAAAMAgBEAAAYBACIAAAwCAEQAAAgEEIgAAAAIMQAAEAAAYhAAIAAAxCAAQAABiEAAgAADAIARAAAGAQAiAAAMAgBEAAAIBBCIAAAACDEAABAAAGIQACAAAMQgAEAAAYhAAIAAAwCAEQAABgEAIgAADAIARAAACAQQiAAAAAgxAAAQAABiEAAgAADEIABAAAGIQACAAAMAgBEAAAYBACIAAAwCAEQAAAgEEIgAAAAIMQAAEAAAYhAAIAAAxCAAQAABiEAAgAADAIARAAAGAQAiAAAMAgBEAAAIBBCIAAAACDEAABAAAGIQACAAAMQgAEAAAYhAAIAAAwCAEQAABgEAIgAADAIARAAACAQQiAAAAAgxAAAQAABiEAAgAADEIABAAAGIQACAAAMAgBEAAAYBACIAAAwCAEQAAAgEEIgAAAAIMQAAEAAAYhAAIAAAxCAAQAABiEAAgAADAIARAAAGAQAiAAAMAgBEAAAIBBCIAAAACDEAABAAAGIQACAAAMQgAEAAAYhAAIAAAwCAEQAABgEAIgAADAIARAAACAQexb10BVdfskd09yuyTHJzkqyRc3vj6Q5O+7++p1zQcAAMBilg6AVXVKktOTPCTJgzILfYdyaVW9IcnvJXlld39j2bkBAABY3EIBsKqOSXJWkh9Nco8F5zouyRkbX++tqn/b3RcsOAYAAABLWvQZwFsleVoWD3/z7p7kLVX1+BXHAQAAYIvW9gxgko8kOS/Jh5N8NsmlSW6a5N5JHp7k9hNzP6+qrujuc9ZYBwAAABNWDYDvS/KiJC/p7n862EVVtS/JY5M8N8kN5rqfV1Vv6O4PrVgLAAAAh7DsMRCvT/Ld3X337n7OocJfknT3Vd39giT3T3LJXPdRSX5zyToAAADYokUD4JeSPLi7H9Ldb1x0su5+d5LHTXQ9rKpuvuh4AAAAbN1CAbC7v9jd560yYXe/LMm755qvm+Rhq4wLAADAoS27BXRVr5pou9OOVwEAADCQ3QqAH59ou/WOVwEAADCQ3QqAx060XbbjVQAAAAxktwLgyRNtn9rxKgAAAAay4wFw40zAH5zoOn+nawEAABjJbqwA/qsc+LzfF5L8zS7UAgAAMIwdDYBVdXSSZ050vbC7r9rJWgAAAEaz0yuAz0xyl7m2Lyb59R2uAwAAYDj7dmqiqvqRJE+c6Dqruz+3hfvPTHLm4a478cQTFy8OAABgADsSAKvqtCR/ONH1su7+/a2M0d3nJDnncNft37+/FywPAABgCNu+BbSq7pTkFTnw7L8PJHnsds8PAADAzLYGwKo6Iclf5cC3fn4iyfd391e2c34AAAD+xbYFwKq6ZWbh745zXZ9O8tDu/th2zQ0AAMCBtiUAVtXNkrwuySlzXRdnFv4+tB3zAgAAcHBrD4BVdZMkr01yj7muL2QW/t677jkBAAA4vLUGwKq6cWbh79S5rkuSfF93v2ud8wEAALB1awuAVXWjJK9Jctpc15eTnN7dF65rLgAAABa3lgBYVTdM8uok3zHX9ZXMwt/frWMeAAAAlrdyAKyqGyT5yyT3nev6apKHdfdbV50DAACA1a0UAKvquCSvTHK/ua5Lkzy8u/92lfEBAABYn6UDYFUdm+QVSR441/W1JGd095tWKQwAAID1WioAVtXRSV6e5MFzXZcl+YHuPm/FugAAAFizhQNgVR2V5M+TPHSu67Ikj+ju16+jMAAAANZroQBYVfuSvDTJw+a6Lk/yQ939unUVBgAAwHrtW/D6H0vygxPtlyd5dlU9e4VaLujux61wPwAAAIewaAC83kHaj9/4WsUlK94PAADAIazlIHgAAACu/QRAAACAQSy0BbS7X5TkRdtSCQAAANvKCiAAAMAgBEAAAIBBCIAAAACDEAABAAAGIQACAAAMQgAEAAAYhAAIAAAwCAEQAABgEAIgAADAIARAAACAQQiAAAAAgxAAAQAABiEAAgAADEIABAAAGIQACAAAMAgBEAAAYBACIAAAwCAEQAAAgEEIgAAAAIPYt9sFAHBkO+nscw/Zf9GzztihSgAAK4AAAACDEAABAAAGIQACAAAMQgAEAAAYhAAIAAAwCAEQAABgEAIgAADAIARAAACAQQiAAAAAgxAAAQAABiEAAgAADEIABAAAGIQACAAAMAgBEAAAYBACIAAAwCAEQAAAgEEIgAAAAIMQAAEAAAYhAAIAAAxCAAQAABiEAAgAADAIARAAAGAQAiAAAMAgBEAAAIBBCIAAAACDEAABAAAGIQACAAAMQgAEAAAYhAAIAAAwCAEQAABgEAIgAADAIARAAACAQQiAAAAAgxAAAQAABiEAAgAADEIABAAAGIQACAAAMAgBEAAAYBACIAAAwCAEQAAAgEEIgAAAAIMQAAEAAAYhAAIAAAxCAAQAABiEAAgAADAIARAAAGAQAiAAAMAgBEAAAIBBCIAAAACDEAABAAAGIQACAAAMQgAEAAAYhAAIAAAwCAEQAABgEPvWMUhV3TTJ/k1fpyU5cf667q51zAcAAMDilgqAVXWPJGdkFvT2J7njOosCAABg/ZZdAXxckiessxAAAAC2l2cAAQAABrHuAHhFkrcnOSfJJWseGwAAgBWs8hKYq5K8L8kFm77e1d1XJElVnZ7k+FULBAAAYD2WDYC/nuRXu/uydRYDAADA9lkqAHb3p9ZdCAAAANvLS2AAAAAGIQACAAAMQgAEAAAYhAAIAAAwCAEQAABgEAIgAADAIARAAACAQQiAAAAAg1jqIPjdUFVnJjnzcNedeOKJO1ANAADA3rNnAmB3n5PknMNdt3///t6BcgAAAPYcW0ABAAAGIQACAAAMQgAEAAAYhAAIAAAwCAEQAABgEAIgAADAIARAAACAQQiAAAAAgxAAAQAABiEAAgAADEIABAAAGIQACAAAMIh9u10AAHDtd9LZ5x6y/6JnnbFDlQCwCiuAAAAAg1h6BbCqXpnktoe45IC+qnrnYYZ9eHf/87I1AQAAcHCrbAG9W5I7LHjPvQ7Tf9SStQAAAHAYtoACAAAMQgAEAAAYxNJbQLv7pDXWAQAAwDazAggAADAIARAAAGAQAiAAAMAgBEAAAIBBCIAAAACDEAABAAAGIQACAAAMQgAEAAAYhAAIAAAwiH27XQAAAOtz0tnnHrTvomedsYOVANdGVgABAAAGIQACAAAMQgAEAAAYhAAIAAAwCAEQAABgEAIgAADAIARAAACAQQiAAAAAgxAAAQAABiEAAgAADEIABAAAGIQACAAAMAgBEAAAYBACIAAAwCAEQAAAgEEIgAAAAIPYt9sFAADAaE46+9xD9l/0rDN2qBJGYwUQAABgEAIgAADAIARAAACAQQiAAAAAgxAAAQAABiEAAgAADEIABAAAGIQACAAAMAgBEAAAYBACIAAAwCAEQAAAgEEIgAAAAIMQAAEAAAYhAAIAAAxCAAQAABiEAAgAADAIARAAAGAQAiAAAMAgBEAAAIBBCIAAAACDEAABAAAGIQACAAAMQgAEAAAYhAAIAAAwCAEQAABgEAIgAADAIPbtdgEAAADXViedfe5B+y561hk7WMl6WAEEAAAYhAAIAAAwCAEQAABgEAIgAADAIARAAACAQQiAAAAAgxAAAQAABiEAAgAADEIABAAAGIQACAAAMAgBEAAAYBACIAAAwCAEQAAAgEEIgAAAAIMQAAEAAAYhAAIAAAxCAAQAABiEAAgAADCIfescrKpukeQ+Se6c5EZJrkzy+STvS3JBd1+5zvkAAADYurUEwKp6ZJInJLl/kjrIZV+pqpcmeXZ3f2gd8wIAALB1K20BraoTquoNSf5Hkgfk4OEvSW6Y5GeS/H1VPbmqDnUtAAAAa7Z0AKyquyQ5P8l3L3jrUUmeluSPq+q6y84PAADAYpbaAlpVN0vy2iS3mei+MMnLk3w0yTFJ7pLkJ5Lcdu66Ryf5bJInLlMDAAAAi1n2GcBzkpw41/aVJD/Z3f9z/uKqelKSJyV5ylzXE6rq1d39qiXrAAAAYIsW3gJaVd+b5Ifnmq9I8pCp8Jck3X1ldz8106t9/7Wq1vo2UgAAAA60zDOAT55oe2p3X3C4G7v7tzPbOrrZyZltEQUAAGAbLRQAq+ruSR4413xxkt9YYJhfnWj7+UXqAAAAYHGLrgD++ETbC7v7iq0O0N0XZvaimM3uW1V3XLAWAAAAFrBoAPz+ibY/W2LeqXumxgYAAGBNthwAq+q4JN8+1/y1JG9fYt43TbTNby0FAABgjRZZAbz3xPUXdPdVS8x7fpIr59pOW2IcAAAAtmiRAHjKRNtHlpl045nBT84139lxEAAAANtnkQB40kTbx1aY++Nzn6+bAw+XBwAAYE0WCYC3nmj7xApzT917qxXGAwAA4BAWCYA3nWj76gpzT917sxXGAwAA4BAWCYDHTbRdtsLcU/ceu8J4AAAAHEJ199YurHpdkofMNX9vd//VUhNXPSPJk+aaf6q7X3yQ689McuYWhv7WJB9cpqZtdvMkF+92EXCE830G28v3GGw/32eswx26+xZTHau+dXNr6XHr99ZBL+4+J8k5K8y3q6rqgu7ev9t1wJHM9xlsL99jsP18n7HdFtkCOn9uX5Ics8LcU/descJ4AAAAHMIiAfBrE23rDoCXrjAeAAAAh7BIAPz8RNsNVph76t6pOQAAAFiDRQLgZybabrfC3Lff4hwAAACswSIB8KMTbXdYYe4T5z5fneTjK4wHAADAISwSAKeOVjh5mUmr6qgcuAL4D9191TLjAQAAcHiLBMB3JPnGXNv+qlrmKIn9Sa431/b2JcYBAABgi7YcALv70sxC4GbHJTl1iXkfMNH2xiXGAQAAYIsWWQFMkr+caHvkEvNO3TM19pFkzx5iD3uI7zPYXr7HYPv5PmNbVXdv/eKqeyT5+7nmzyW5XXdv6RD3qjo1B273fFt333fLhQAAALCwhVYAu/s9Sf5mrvkWSX5pgWGeOdH2/EXqAAAAYHELrQAmSVWdngO3a349yf26+5Avcqmqxyd53lzzPyY5pbuvXKgQAAAAFrLoM4Dp7lcneflc8/WTvL6qHjF1T1Vdr6qenAPDX5L8ovAHAACw/RZeAUySqrpFZs/x3W6i+4LMAuJHkxyT5FuSPCbJCRPX/k53/8LCBewRG/+c7pPkzklulOTKJJ9P8r4kFwi+sLyqun2Su2f2/0PHJzkqyRc3vj6Q5O+7++pdKxAAFlBV101yzySnJLl1Zm/b/3qSLye5KMmHuvuju1YgR4ylAmCSVNVdk/x1Zv+BLuOlSX7iSPwBraoemeQJSe6fpA5y2Vcy+2fw7O7+0E7VBntVVZ2S5PQkD0nyoMxC36FcmuQNSX4vySu7e/4cU2AJVVVJXp/kuye6z+vuB+9sRbC3VdX/luTMJA/PbMHgUC5O8uYkr0zyZ939+W0ujyPQ0gEw+V+/gX9Jps/1O5grk/znJE870n4gq6oTkvxxpv9QPJgrkjw9ydN7lX8ZcASqqmOSnJXkR5PcY4Wh3pvk33b3BWspDAZWVb+Y5LcP0i0AwhZtLKY8P4v93LjZT3X3i9dYEoNY+BnAzbr7E5n9Jv7HMvttxKECzFeTvDDJPbv7KUdg+LtLkvOz+DfxUUmeluSPN5b+gX9xq8y+P1YJf8lsq+hbNl5EBSypqk7O9Nu8gQVU1b9JcmGWD3+wtH2rDrCxavXSJC+tqlsm+Y4kd8psCfuqzJaq35/k/K2eFbjXVNXNkrw2yW0mui/MNZ+JvEuSn0hy27nrHp3ks0meuG2FwpHlI0nOS/LhzL53Lk1y0yT3zmwbze3nrt+X5HlVdUV3O2QXFlRV18nsF7nH7nYtsJdV1S8lee5EVyd5R2Y/U/5TZn+27Utyk8yeC7x3ku/MGn5+Z2xr/Q+ouz+b5BXrHHOPOCfJiXNtX0nyk939P+cvrqonJXlSkqfMdT2hql7d3a/aliph73tfkhcleUl3/9PBLqqqfUkem9kfsDeY635eVb3Bs7ewsCfmmo98vC2zH0aBLaqqRyf5zYmulyY5+3AveamqG2X2S87HJTmidtOxc1Z6BpCkqr43yWvmmq9Icv/DPW9UVU9I8l/mmj+S5K7dfdXaioQ9qqpOymz1/PVJntLdb1zw/ntmtkp4/FzXK7p78tga4EAbjzm8M7OdLMnsjdYPzywEbuYZQDiIje+jC3PNX0xemeQx3f0/lhivvD+CZaz0DCBJkidPtD11Ky+b6O7fzmyZf7OTM9siCiRfSvLg7n7IouEvSbr73Zn9lnTew6rq5itXBwPY2Pr5ovxL+Etmq4Gf3Y16YA97fg7clfLoZcJf8r8ew4KFCYArqKq7J3ngXPPFSX5jgWF+daLt55cuCo4g3f3F7j5vxTFeluTdc83XTfKwVcaFgZyV5Ls2fT7XmwdhMVX1A5kdY7TZH278GQU7SgBczY9PtL1wkZfddPeFmW0H2Oy+VXXHlSoDNpt6rvZOO14F7DEbr6l/2qamLyf5uV0qB/ay/2Pu89cz++UK7DgBcDXfP9H2Z0uMM3XP1NjAcj4+0XbrHa8C9pCNo4n+IMn1NzWf1d2f3KWSYE+qqm/NgWdmv6K7P7cb9YAAuKSqOi7Jt881fy3J25cY7k0TbfNbS4HlTb22/rIdrwL2ll9Jcp9Nn1/X3S/YrWJgD3vURNuf7HgVsEEAXN69c+A/vwuWfHvn+Zm9BWqz05YpCph08kTbp3a8CtgjNp5xf8qmpkuT/OzuVAN73vdOtL11x6uADQ6SXN4pE20fWWag7r6iqj6ZZPNzf3euqn2Og4DVbJwJ+IMTXefvdC2wF2x8z/xBkqM2NT/pcOeTAQfa2Eo9f17mxZvPsq2qGyf5ycyOVrlnkltmtjBwcWa/rHxjZkeOvb67nf3HyqwALu+kibaPrTDe/DNK182Bh8sDi/tXOfB5vy8k+ZtdqAX2gl/NNXehvDnJ7+xSLbDX3SXXfI42ST78zb+oqjOTfCKz77GHJ7ldZr98OS7JHZLcN7Pt2H+V5N1V9cM7UDNHOAFweVMvkPjECuNN3XurFcaD4VXV0UmeOdH1QqvrcKCqumeueb7t5Ul+2qoDLG3qjdNfqqrrV9X/l+T/SnLDLY519yQvq6pzqup6a6uQ4QiAy7vpRNtXVxhv6t6brTAeMAt/d5lr+2KSX9+FWuBabeMHyj9IsvkHy6d29wd3qSQ4Etxmou2rSf4oyQ/MtXeSzyR5f2ZbPw/2i5efTfIXVeXneJbiP5zlHTfRtspbBafunXpzIbAFVfUjSZ440XWWV2/DpF/L7AVn33RhkufsTilwxLjJRNsZueabQT+f5D8kuV1337q779bdt81sJ9iZSf7pIGM8Zc21MggBcHlTS++XrzDeVAA8aqINOIyqOi3JH050vay7f3+n64Fru6o6NcmTNjVdmdnWz6t3qSQ4Usw//5ckx2z663cmuXt3/1Z3//Pmi7r74o2jV+6a5PUT4/xaVd1tbZUyDAFwvXrN99YK48GQqupOSV6RA1fQP5DksTtfEVy7VdVRmW393Pxm8Gd297t3qSQ4khzqZ7nPJvm+7v7MoQbo7q9ktl30QxNjn71aeYxIAFze/Ll9yTV/o7OoqXuvWGE8GE5VnZDZm9LmX9L0iSTfv/GHKHBN/ynJt236/J4kz9ilWuBIM/Xz4jf9ylYfSejuryX59xNdj66qrb5EBpIIgKv42kTbugPgpSuMB0OpqltmFv7uONf16SQP7e5VjmmBI1JV7c/sFfPfdHVmWz/9AhLW42A/y12c5E8WGai7X5fZC2I225fk/kvUxcAEwOV9fqLtBiuMN3Xv1BzAnKq6WZLXJTllruvizMLf/LYZGF5VXT/Ji3LNrZ/P7e7zd6ciOCId7Ge585b8RctrJ9oesMQ4DEwAXN7Ufu3brTDe7bc4B7BJVd0ksz8Q7zHX9YXMwt97d74q2BOekNm5Yt/04cy2gwLr86mDtL9jyfGm7rvtkmMxqH2Hv4SD+OhE2x1WGO/Euc9XJ/n4CuPBEa+qbpxZ+Dt1ruuSzB6sf9eOFwV7x/wPjTdM8paqLb9/bOpN1fur6p3zjd1974UqgyPHPx6kfdldXlP3OTeahQiAy5s6GPfkZQbaeAPb/ArgP3T3VcuMByOoqhsleU2S0+a6vpzk9O6+cOergj3t1jnwBUqLOi7JvdZQCxwpPpHZwe/zj/p8fcnxpo4cO3rJsRiULaDLe0eSb8y17a+qZUL1/hx4ruDbl6oKBrDxxrNXJ/mOua6vZBb+/m7nqwKAa+rub2T6Z7obLznk8RNt3hnBQgTAJXX3pTlwH/ZxOXAr2lZMPbz7xiXGgSNeVd0gyV8mue9c11eTPKy737rzVQHAQb1hom3+jdVbddJE25aOkoBvEgBX85cTbY9cYpype6bGhqFV1XFJXpnkfnNdlyZ5eHf/7c5XBXtTdz+xu2vZr0z/AHveQa6FkZ070Tb/59hWTd237AtlGJQAuJr/PtH22I1n+rakqk5Ncp+55rd199RLZmBYVXVsklckeeBc19eSnNHdb9r5qgDg0DYeS/jwXPP+qrrrIuNU1c2TPGyi63XL1saYBMAVdPd7kvzNXPMtkvzSAsM8c6Lt+UsXBUegqjo6ycuTPHiu67IkP9Dd5+14UQCwdc+baHvqgmP8n0muP9f2d939ieVKYlQC4OqePtH21Kr69sPdWFWPT3L6XPM/JnnJOgqDI8HGivqfJ3noXNdlSR7R3a/f+aoAYCEvyOyNoJs9qqp+fis3V9UPZnZ257ynrVoY4xEAV9Tdr85sZWKz6yd5fVU9YuqeqrpeVT05078N+sXuvnLNZcKetPFW3ZfmwC0vlyf5oe627QWAa73uvjzJ4ye6/ltVPaOqjpm6b+Nnxl9O8mdJ5p+nfU13Tz1fCIdU3b3bNex5VXWLzF7xe7uJ7gsyC4gfTXJMkm9J8pgkJ0xc+zvd/QvbVSfsNVX1mCQvnui6JMnHVhz+gu5+3IpjwLCq6qTM/mzb7LzufvDOVwN7Q1U9N9OPCn0ms58X357kC5kd93CPJD+U5MSJ6y9Ksr+7HQHBwhwEvwbd/bmq+r4kf50DD9Hdv/F1OC9N8sQ1lwZ73fz5mN90fKbPQlrEJSveDwCLOiuzMwB/eq79VknO3OIYH8zsEQjhj6XYArom3f3+zA6lnn8pzOFcmdlDwI/u7qvXXhgAANcK3f2N7v6ZzJ7nu3TR25P8aZLv7O75t4rClgmAa7TxFqYHJfmxJG/O7Bv1YL6a5IVJ7tndT+nub+xAiQAA7LLu/q9J7pLkNzLb/nkoX0zyJ0lO7e4f7+4vbXd9HNk8A7iNquqWma0K3inJjZJcleTiJO9Pcn53X7GL5QEAsMuqqjJ73u/bktwms3dGfCmznxk/nOTtFgpYJwEQAABgELaAAgAADEIABAAAGIQACAAAMAgBEAAAYBACIAAAwCAEQAAAgEEIgAAAAIMQAAEAAAYhAAIAAAxCAAQAABiEAAgAADAIARAAAGAQAiAAAMAgBEAAAIBBCIAAAACD+P8BR/eEBEI0ItsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot1DHistogram(treeBIB[\"layer\"].array(), bins=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "e841285d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "i:\n",
      "0\n",
      "j:\n",
      "0\n",
      "-1\n",
      "1\n",
      "i:\n",
      "1\n",
      "j:\n",
      "0\n",
      "-1\n",
      "1\n",
      "i:\n",
      "2\n",
      "j:\n",
      "0\n",
      "-1\n",
      "1\n"
     ]
    }
   ],
   "source": [
    "hits=[] #initializing a array to keep track of hits for each layer\n",
    "area=[]\n",
    "for i in range(3):\n",
    "    inLoc=treeBIB[\"location\"].array()==i\n",
    "    print(\"i:\")\n",
    "    print(i)\n",
    "    print(\"j:\")\n",
    "    for j in [0,-1,1]:\n",
    "        print(j)\n",
    "        inSide=treeBIB[\"side\"].array()==j\n",
    "        for k in range(layerPerModule[2*i+abs(j)+1]):\n",
    "            data=inLoc & inSide & (treeBIB[\"layer\"].array()==k)\n",
    "            hits.append(np.sum(data))\n",
    "            r=np.sqrt(treeBIB[\"x\"].array()[data]**2+treeBIB[\"y\"].array()[data]**2)\n",
    "            z=treeBIB[\"z\"].array()[data]\n",
    "            if j==0:\n",
    "                area.append(np.pi*2*max(r)*(max(z)-min(z)))\n",
    "            else:\n",
    "                area.append((max(r)**2-min(r)**2)*np.pi)\n",
    "hits=np.array(hits)\n",
    "area=np.array(area)/100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "d9a07c3e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 477.469  406.739  188.642  190.321  141.395  135.427  117.899  117.392\n",
      "  106.053  107.591  135.96   133.475  155.364  150.637  111.583  109.685\n",
      "  111.986  111.197  136.425  134.508  152.561  148.619  112.484  112.079\n",
      " 1849.853  869.475  770.45   413.128  430.024  350.945  263.579  208.396\n",
      "  144.422  118.169  418.29   430.11   353.456  265.026  219.133  149.629\n",
      "  122.798  903.139  645.786  457.817  190.64   348.919  339.232  333.929\n",
      "  190.433  349.249  331.369  321.783]\n"
     ]
    }
   ],
   "source": [
    "print(hits/1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "bd7fe66e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "52\n"
     ]
    }
   ],
   "source": [
    "print(len(hits))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "0ee080ba",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[   255.92438854    272.06850491    432.20276703    448.26775572\n",
      "    616.2538621     632.84695175    842.20015906    858.53372906\n",
      "    379.7963455     380.90452116    378.50975547    373.90174554\n",
      "    362.30180466    362.42929527    320.29576101    318.95665313\n",
      "    380.31092517    380.54593236    375.60353404    376.46707713\n",
      "    363.82916878    360.04323106    319.50348149    320.57760688\n",
      "   7888.13520706  20745.83676522  48428.05608966   5523.03618676\n",
      "   9121.44592116   8590.22807636   8534.08660966   8001.54133097\n",
      "   7485.80030063   7278.63289228   5513.53796838   9121.81834087\n",
      "   8573.99984009   8519.84117963   7954.20471606   7430.60621772\n",
      "   7280.53858944 130710.48054044 183762.5671909  237247.67279816\n",
      "  52616.44657461  52660.13020855  52617.33421175  52683.13047985\n",
      "  52581.39427642  52591.75805121  52679.3450718   52625.56710041]\n"
     ]
    }
   ],
   "source": [
    "print(area)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "b5a5792e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot1DHistogram(100*abs(surfacearea-area)/surfacearea,bins=20, label=\"Comparison between recorded and measured surface area; Relative error (percent); Count\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "7d7f33ea",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[   270.4     270.4     448.5     448.5     655.2     655.2     904.8\n",
      "    904.8     389.      389.      378.96    378.96    364.36    364.36\n",
      "    312.48    312.48    389.      389.      378.96    378.96    364.36\n",
      "    364.36    312.48    312.48   8117.85  22034.16  51678.81   6639.65\n",
      "  10611.59  10078.04   9900.19   9307.37   8595.98   8299.56   6639.65\n",
      "  10611.59  10078.04   9900.19   9307.37   8595.98   8299.56 140032.91\n",
      " 194828.39 249623.88  69545.45  69545.45  69545.45  69545.45  69545.45\n",
      "  69545.45  69545.45  69545.45]\n"
     ]
    }
   ],
   "source": [
    "print(surfacearea)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "c3c0a553",
   "metadata": {},
   "outputs": [],
   "source": [
    "label=[]\n",
    "for i in range(6):\n",
    "    #Adding the SI tracker type to the label\n",
    "    if i//2==0:\n",
    "        cur=\"V\"\n",
    "    elif i//2 ==1:\n",
    "        cur=\"I\"\n",
    "    else:\n",
    "        cur=\"O\"\n",
    "    \n",
    "    #Adding if its an endcap or a barrel to label\n",
    "    if (i %2)==0:\n",
    "        cur+=\"B\"\n",
    "    else:\n",
    "        cur+=\"E\"\n",
    "        \n",
    "    for j in range(layerPerModule[i+1]):\n",
    "        label.append(cur+str(j))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "ad810574",
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.rcParams.update({'font.size': 20,\n",
    "                    'xtick.labelsize' : 50,\n",
    "                    'ytick.labelsize' : 50,\n",
    "                    'xtick.major.size' : 10,\n",
    "                    'ytick.major.size' : 10,\n",
    "                    'xtick.minor.size' : 5,\n",
    "                    'ytick.minor.size' : 5,\n",
    "                    'axes.labelsize' : 50,\n",
    "                    'axes.titlesize' : 50}) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "f66ae4cd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2160x1440 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(30,20))\n",
    "ax = fig.add_subplot(111)\n",
    "\n",
    "ax.bar(range(52), (hits/surfacearea)/30, fill=False, linewidth=4, edgecolor=\"blue\")\n",
    "\n",
    "ax.vlines(7.5, ymin=0, ymax=30, colors=\"grey\", linestyle=\"dashed\", linewidth=4)\n",
    "ax.text(2.3,21, \"VX barrel\", fontsize=30, alpha=0.5)\n",
    "ax.vlines(15.50, ymin=0, ymax=30, colors=\"grey\", linestyle=\"dashed\", linewidth=4)\n",
    "ax.text(13.5,31, \"VX disks\", fontsize=30, alpha=0.5)\n",
    "ax.vlines(23.50, ymin=0, ymax=30, colors=\"grey\", linestyle=\"dashed\", linewidth=4)\n",
    "ax.text(11,21, \"+z\", fontsize=30, alpha=0.5)\n",
    "ax.text(19,21, \"-z\", fontsize=30, alpha=0.5)\n",
    "ax.vlines(26.5, ymin=0, ymax=30, colors=\"grey\", linestyle=\"dashed\", linewidth=4)\n",
    "ax.text(24.5,16, \"IT barrel\", fontsize=30, rotation=90, va='center', alpha=0.5)\n",
    "ax.vlines(33.5, ymin=0, ymax=30, colors=\"grey\", linestyle=\"dashed\", linewidth=4)\n",
    "ax.text(32,31, \"IT disks\", fontsize=30, alpha=0.5)\n",
    "ax.vlines(40.5, ymin=0, ymax=30, colors=\"grey\", linestyle=\"dashed\", linewidth=4)\n",
    "ax.text(29.5,21, \"+z\", fontsize=30, alpha=0.5)\n",
    "ax.text(36.5,21, \"-z\", fontsize=30, alpha=0.5)\n",
    "ax.vlines(43.5, ymin=0, ymax=30, colors=\"grey\", linestyle=\"dashed\", linewidth=4)\n",
    "ax.text(41.5,16, \"OT barrel\", fontsize=30, rotation=90, va='center', alpha=0.5)\n",
    "ax.vlines(47.5, ymin=0, ymax=30, colors=\"grey\", linestyle=\"dashed\", linewidth=4)\n",
    "ax.text(46,31, \"OT disks\", fontsize=30, alpha=0.5)\n",
    "ax.text(45,21, \"+z\", fontsize=30, alpha=0.5)\n",
    "ax.text(49,21, \"-z\", fontsize=30, alpha=0.5)\n",
    "\n",
    "\n",
    "ax.set_ylabel(f\"Average number of hits / cm$^2$\")\n",
    "ax.set_xlabel(\"Layer\")\n",
    "ax.set_title(\"Background hits occupancy rate for time window $[-3\\sigma_t,+5\\sigma_t]$\")\n",
    "plt.savefig(\"occupancy.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "6b3b8e9b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Background hits for time window $[-3\\\\sigma_t,+5\\\\sigma_t]$')"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2160x1440 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(30,20))\n",
    "ax = fig.add_subplot(111)\n",
    "ax.bar(range(52), hits/30000, fill=False, linewidth=4, edgecolor=\"blue\")\n",
    "\n",
    "ax.vlines(7.5, ymin=0, ymax=20, colors=\"grey\", linestyle=\"dashed\", linewidth=4)\n",
    "ax.vlines(15.5, ymin=0, ymax=20, colors=\"grey\", linestyle=\"dashed\", linewidth=4)\n",
    "ax.vlines(23.5, ymin=0, ymax=20, colors=\"grey\", linestyle=\"dashed\", linewidth=4)\n",
    "ax.vlines(26.5, ymin=0, ymax=20, colors=\"grey\", linestyle=\"dashed\", linewidth=4)\n",
    "ax.vlines(33.5, ymin=0, ymax=20, colors=\"grey\", linestyle=\"dashed\", linewidth=4)\n",
    "ax.vlines(40.5, ymin=0, ymax=20, colors=\"grey\", linestyle=\"dashed\", linewidth=4)\n",
    "ax.vlines(43.5, ymin=0, ymax=20, colors=\"grey\", linestyle=\"dashed\", linewidth=4)\n",
    "\n",
    "ax.set_ylabel(f\"Average number of hits (Thousands)\")\n",
    "ax.set_xlabel(\"Layer\")\n",
    "ax.set_title(\"Background hits for time window $[-3\\sigma_t,+5\\sigma_t]$\")\n",
    "#plt.savefig(\"hits.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "92b9b89c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Area of tracker layers')"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2160x1440 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use('seaborn-v0_8-colorblind')\n",
    "plt.rcParams.update({'font.size': 20})\n",
    "plt.rcParams.update({'xtick.major.size' : 10}) \n",
    "plt.rcParams.update({'ytick.major.size' : 10}) \n",
    "plt.rcParams.update({'xtick.minor.size' : 5}) \n",
    "plt.rcParams.update({'ytick.minor.size' : 5}) \n",
    "#plt.rcParams.update({'axes.labelsize' : \"large\"}) \n",
    "\n",
    "fig = plt.figure(figsize=(30,20))\n",
    "ax = fig.add_subplot(111)\n",
    "ax.bar(range(52), surfacearea, fill=False, linewidth=4, edgecolor=\"blue\")\n",
    "ax.set_ylabel(f\"Area (cm$^2)$\")\n",
    "ax.set_xlabel(\"Layer\")\n",
    "ax.set_title(\"Area of tracker layers\")\n",
    "#plt.savefig(\"area.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e1e4c218",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}