{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "41c42cae",
   "metadata": {},
   "source": [
    "# hist031_TRatioPlot_residual_fit\n",
    "Example which shows how you can get the graph of the lower plot and set the y axis range for it.\n",
    "\n",
    "Since the lower plot is not created until `TRatioPlot::Draw` is called, you can only use the method\n",
    "afterwards.\n",
    "Inspired by the tutorial of Paul Gessinger.\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "**Author:** Alberto Ferro  \n",
    "<i><small>This notebook tutorial was automatically generated with <a href= \"https://github.com/root-project/root/blob/master/documentation/doxygen/converttonotebook.py\">ROOTBOOK-izer</a> from the macro found in the ROOT repository  on Tuesday, May 19, 2026 at 08:12 PM.</small></i>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "5f79a247",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:12:41.576967Z",
     "iopub.status.busy": "2026-05-19T20:12:41.576838Z",
     "iopub.status.idle": "2026-05-19T20:12:42.915114Z",
     "shell.execute_reply": "2026-05-19T20:12:42.914537Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "****************************************\n",
      "Minimizer is Minuit2 / Migrad\n",
      "Chi2                      =      22.1778\n",
      "NDf                       =           33\n",
      "Edm                       =  6.53577e-08\n",
      "NCalls                    =           55\n",
      "Constant                  =      158.988   +/-   4.47298     \n",
      "Mean                      =   0.00662197   +/-   0.0225355   \n",
      "Sigma                     =     0.993481   +/-   0.0169678    \t (limited)\n"
     ]
    },
    {
     "data": {
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').then(json => {\n",
       "   const obj = Core.parse(json);\n",
       "   Core.draw('root_plot_1779221562896', obj, '');\n",
       "});\n",
       "\n",
       "      }\n",
       "      const servers = ['/static/', 'https://root.cern/js/7.11.0/', 'https://jsroot.gsi.de/7.11.0/'],\n",
       "            path = 'build/jsroot';\n",
       "      if (typeof JSROOT !== 'undefined')\n",
       "         execCode(JSROOT);\n",
       "      else if (typeof requirejs !== 'undefined') {\n",
       "         servers.forEach((s,i) => { servers[i] = s + path; });\n",
       "         requirejs.config({ paths: { 'jsroot' : servers } })(['jsroot'],  execCode);\n",
       "      } else {\n",
       "         const config = document.getElementById('jupyter-config-data');\n",
       "         if (config)\n",
       "            servers[0] = (JSON.parse(config.innerHTML || '{}')?.baseUrl || '/') + 'static/';\n",
       "         else\n",
       "            servers.shift();\n",
       "         function loadJsroot() {\n",
       "            return !servers.length ? 0 : import(servers.shift() + path + '.js').catch(loadJsroot).then(() => execCode(JSROOT));\n",
       "         }\n",
       "         loadJsroot();\n",
       "      }\n",
       "   }\n",
       "   process_root_plot_1779221562896();\n",
       "</script>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import ROOT\n",
    "\n",
    "ROOT.gStyle.SetOptStat(0)\n",
    "c1 = ROOT.TCanvas(\"c1\", \"fit residual simple\")\n",
    "c1.SetLogy()\n",
    "\n",
    "h1 = ROOT.TH1D(\"h1\", \"h1\", 50, -5, 5)\n",
    "h1.FillRandom(\"gaus\", 2000)\n",
    "h1.Fit(\"gaus\")\n",
    "h1.SetMinimum(0.001)\n",
    "h1.GetXaxis().SetTitle(\"x\")\n",
    "h1.GetYaxis().SetTitle(\"y\")\n",
    "\n",
    "rp1 = ROOT.TRatioPlot(h1)\n",
    "rp1.Draw()\n",
    "rp1.GetLowerRefGraph().SetMinimum(-2)\n",
    "rp1.GetLowerRefGraph().SetMaximum(2)\n",
    "\n",
    "c1.Update()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "20dfe083",
   "metadata": {},
   "source": [
    "Draw all canvases "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c54b7f70",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:12:42.923859Z",
     "iopub.status.busy": "2026-05-19T20:12:42.923667Z",
     "iopub.status.idle": "2026-05-19T20:12:43.039648Z",
     "shell.execute_reply": "2026-05-19T20:12:43.039227Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "<div id=\"root_plot_1779221563037\" style=\"width: 700px; height: 500px; position: relative\">\n",
       "</div>\n",
       "\n",
       "</div>\n",
       "<script>\n",
       "   function process_root_plot_1779221563037() {\n",
       "      function execCode(Core) {\n",
       "         Core.settings.HandleKeys = false;\n",
       "         \n",
       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eKYPmBqIMMAzA1kGH6oEEgaMwzAqqBnGH6otY0K25O4oaJEFayPI9jWCnuTyFChklinGQZg20HPMADbDnqGgQ1OEUo8wwBUjFLrqoKKUhLA7zpUVPpgBCuWxZaG0Q4YhC/AGKMgGBOMVd1IwByh9b4XLNDJOJtpjwUTi/QExwaXCcYsYyRULOK0zwpHhqMwXAWyY5yN1Ks5VSLjARbb15EVKygKqhuDWtdjTG+2ErHiFWQsWhsUZCie2thj0mEkCibAxECwOGLAw544gUVBhqG1tceax6pgYnRWn1XrIKDQEeSssqbOMUjcH5UlU1FXza1SWTJkXTfCzAlpFxsk1IlhqxFvhBmoirvNzVEZCyYjRg790sE09FcaSfcoYBW3jZFC/x6JZYTpHyUM15J6JYCxMDabYmE8HlvsCDMej3LY7KLYJ61Xj4DaSZslN0N4BfNsYTV8gSzjuIGCi4W80z8w44HA03+j92Ih8fQPTP8QefqHA9B/8DCLZsdkPUKAlTSY8YQIoxHoeab/kGBDUlhz+g8ZJtVg7b/Awpq3ivUIFQbXYNYjWtifut8S44kCc1SzaKL/6GCkDab/USZWHxf7EUMfeR6GTv/IxdlIQXGg/5h6eKTC2l/uE+OhXvsrPbijMPOPtcfFhd1XTeXJYkFsMP0l6bFZUx/oL6nDsMH0l3zP2uChC/SXQo9rUWH6S7GnL4XpLyU1dCvM/FLu1WqPHKH9lR7nH7Ca41PtK94/YPrLFq9Sg1lf2IJlwNA7OoQxoOBoAT2qzMwSKUWkIPSwkVZAn7AHDk2p6iYUC4PAykqB014hLHRLgXaLW4BuKdBu8dtxRq0628TCKByuRQrYWVgFqKsFdAuzUI8jLcAt2AXIiOcTO7+FYYCNtBC6hWWAfrsCbPJ4LWnB+sM2QDAtYGAwjjCOA2+BhXWAYtqCgcE8kM60gAWabHBawEjVCDeuhzBStYeM66GUXpkIa4rHgqErGxnXVGk5jEQxjxaMFFYCWdICRgozaXQGVyMFCATj3lKgTiClBMUIZFbdQBxtLcDrMnmCtEA9NPgdpnfgSoGnqCOiGOgp3iDFZmB8K+p6YGrFQFDVIcRClIyjVNQhpA70bCCweISkgm/ZQGDxCUllWtlAYHELCX4cYPUSYcZhQBPcLFUKM2B1QzAlRDxgNBfGk9Rjg2sIryXtIcD4hnAJK8z4cA4pMhecjIJ3CCcL84Hg4iByitvFFMaHLQWKjzuX/rHujagOwVUXERS+WgPBxUukPmdg+se6B8WvYjLrhT1FD4IYCC5eIgeFB9b+8TCC085AcAX7HhQemPXBqKLHxBsIrsBgcG1Vb5ojzfVOT00wEFxRBgPCBwPBFRiMHiKEfuDYOw/+oxIApx4fpsL0D4PRI5UMBFdgMIH+Eo5ZEd9iF9hTCK4E2zs9YNlAcAWXPBQcmP7xyet5KwYCLOgRetyKgQALmkRQ7cBE+keX0NNXDQRY0CZUQFEVUwR9Qu0M1kTWA41CYWcgyIJOobA3gf7RKhSOBoIsER0V0SIZCLJErKQqgBkIskSst0gi1QTGE/HZIjiKulYlMj5gbyDQgste4WAg0BIZH/XJQKAlMj7gjDNbJDI+4Go840mMD23FGui1JMYH7AzkWhLjAw7GM57E+ICjgVhLYnzA2XjWI7X1A4dwUkpifNY4RGPGkxgfsBgotyTGB+yN0/EwPmDc5rhaGR9wMpBtwSSjMNoQMOOjHkkcmP2tBpyBiEtu+0usizCeHMd6ziBwGmEkEmD0RZ5H6gIG/4Bx7hJI9PnrQ2LJ/kkj9Ga3j1bzjXczMzvS6LEYzeyHWf9ddcFUh+qXTHXQlmKqq6Z6ayouXu9M9d5UH0z10VSfTPXQqGKqr6YGa2oQU4MzNXhTQzA1oDwSIwJtK6aGamq0pkYxNTpTozc1BlPxgcdkaoQmFlNjNTVZU5OYmpypyZuaCDSJpqZkaoKWFlNTNTVbU7OYmp2p2Zuag6kZVTSZmrOpGTpcTS3W1CKmFmdq8aaWYAgWrtBJaKnS72pqtabig67O1OpNJcClRlMrKmw2tUL31a+OHQZKbNUSYvFAqGXU4ouBBFvEBgvxtQTsWMiuhdZaCKxFrraQVgs9taoVQ0kt5NMiJVsIp0VOsJBIiyRsIY4WimgRDyy00EIALVTPIsxa6J2FyBEvjczMB09AyCwSgYWEWeiWRfy0UCwLylmkTQuyWaiSBc1sC97hCbDKYpix0BwbeUKtcgiVFh5vMb9YZEoLh7dIkxbWbrG2WHi6xdJi0UgsHN1iXLGwcosoaeHhFgXBwrwtJhSLDGlh3RZJ3cKzLTK4JYDAIkFaRGoLq7YIkBYebREdLbKnRWC0SIFWWbsKDbBli7BkYcgWudHCim3lCcRGCye2CIyWPcdqgdDAB0EO7HmLamLPMUTA7/lA42fPVVDEyiAqIbZ4CPZc5UNhz1tgAHuu8VKYBuCqfGggBX2w5+j9sEc+6IM9V4GwRWSx5yoOCnuOsg7v4oMn2HOUcPgRhgz6YM9V+EOhhrHwwRPsuQZsqZyHegxb4IMn2HM1Bgp7rvFxGvEi7LkGuKHGQqj54An2XCPsVAttkWHsuYpvGiGncpsqhSqwtRAS9lzFNdXOVE5TvUty+f7nn382HyuakxDxa6M52yWLt8RxjhGbxG2vT2g4hTq3ks+2L7hwuwNw7wbHxcsbu2stQvz95Xst9+brV4v13j2ZVrD3yrFge/fj8eLN5ubJC+KwCU0GbJW2sxomT/3R8sXJDKtIa7D3fqpvrwhvTxphPH+zvBwsfnOzuUk54dsHyx+WZ8vVydmsj0KP1Oy98O782WK6u0N/CrceAj0o/ODw8Gyhl2qgs2Phdthex718/uru4uQFV4JsZwly1j2YHtW5EH9+8bHN0RRuvm0ydU9g8tM/zQx1O/+OGf77n2aG2w36hXv4+Xy9dyXq8/l6QgqWTHGRY3r08FE7E1+s5z+2exgNfnC62d35aMB4FaQB482PB6ebL1q8fbsWRxD89gUjPWAGD043t/UO2dju9nJsdil8ngZaeLDccBFugh+vVkcaPU9Bu7Bya3WyWb1en40XF25uxrFcIJc3NxtOsFKotxCCdmHm/SkBB4W5j/eSRojrEJ1ev/vy5ODL9Xo1XkHjWCuozTm8t1+fPB9pApWAeyQMcNw/arkAMzZm/oBjYw494N5m3128WJwc7N+yYXStdI+88qJd4dT3dHeQV0w0YduQ5Rnx0MwO73ARYnF2gYCPpY9O58+5CKB9by/07c1he5tvLGOM23bnR7NtOhVPTS90re0uznuvcHfF6M7yDITcHw9FvG8cTrJMe2o3ddxWZ2o6lY4NL4yGVveWJ8vj18f/vlivdvc8qDh3x1Lpe7vy8nC9OFys/3J317qV7y1cK9ifJiPdL93Ns5V+sTi8M+ujZdO2Jd/O+ny+5MkMJ8Bek6djwcP5PvI9nJ/DLTrfFu161qLLd0sfzg/OTZ21ezg/uHxX9eH84Irrqg/nByD7k93yjCVPz5XAGMeLSnS4fP5qvKb0cH7aLoU+GYnGtuDpDN/k7PDR8/VicXJ7/lypD8ODpu0tPyDnYA9tKdrfj+mpvfNDE8Dd6aFkQqCGVq3N+hgSOktd0Fs0FCrNqFwfBVISg2bawG+ny07U3QEQncdmvTz9YvF8eTw/OtveKFKSPIo6bisv7M1OG1yYnpbtzw8k0cK9CW7hLZ9qEgrSR7vDvH1qSwL1mTadum3NfKb3M51GfFZfnZws1l8zPVpy1PS1Z7P+O24RffYZH+I+EzT+z8JnZYLTZ+EzSUDO0iCMTXaQFu2XO3u++bau2LGu2M+C/Sx8FrSl9v2RPr6HuCzmB4s1rFovTOmybaHby83tCWniiDR6DYtd3NYoLumqPZ8f6cPs/v9ZLU8onKSAW/PTffDx8ngrS+ZSqpSgFOOr4/mLBS/aEvhb85ODo8W3L5dnrxbrr+cnL8Zb163889WbsaztXivVkexd2vzrcnW0PJlKx7uLremt5fr50UVqP1Zx25RB7zHAJ8jbX745fbIv80yFT/cLn17Vcio815KG9+Zvvli+0KwAIOGD9ebl6tb8eLGej9TnI+pqSlOmVAUXRRzlcdfpatANFmiPYAFOtGes3Vu+C4zxsgam1+ZZgXZPnluXrl1F5ib8FfeQ94kHHTZ4ZBa/16LdkS+uW7KoN2FHBffluXu8DdpbzyYo/MoV/eU67f3niyMIu17lv0YlHfXRqy5iOqvpCMYpvlF1aKK6s372BuBPrccy/mdLVcFhIU92t+ifbC/OP2kNuMx9eHu5PtuMF9vnfNPHSAHiJoZ0vPhieXZ6NN+7eg6F3NJY1kxV991V8Hurg7vzZyP8FtX6LTvF6Mdt+uniNv30h9qmLdveigCjleIt5obdNkEX2i61/SKlgZZd3iQatE3i2wffo2uMA++3R3+7uEd/qC1iQVV8+JNv0QV7xp6xw6qE8uXJZr1EOHQNfnz2+vjH8xCcaq+SXBqdpFxc9bEmG4KKxzz3RpvG0jlnXa7RZXxJh/fmb9DtZv0NtXvPDkdlTy0AagK4v1ofT5oEmDoaLFr6iMNHr48ZhFKfcxmF0P1JMHTZyPi2jBQXrB63lWtdRfrVYbKlKS/mr9VoqVgx67fwHofjkF7P36jdkxguGm2Z9y/nbleS6/unZE9gW+4fLI8bdbh/CpnQPX/80+lo4L1/eqhCmkcRuv/F7RmRTbPDWy+XZ//1er4mlZHrJOdcg88x4Cfa273tdl7c34fztZpw0DlCF7KruZTQEtIY21nnoo/R+RpriVzG7aykmnIJPgXvcvAwmofz9T0yunyn+QymEqidlojtcHtYn8gllBINHs1JE3Hes5lweapnE+eMejZDV+i5kIYo1VQXN4IpnfUWz5Cn3GmZ7awVLz6klF3xxRWnZU5cytEWEVIQtTIfbCm1WMm5eC4kY40OtlRXeUmqOnNbQo2l4DXzlgAFpu4dfsGaQvA+J4qc9d7bYKVGjzMIm7WtRVys2RfnU6EopOxqrbZ6ax23oztS8mSfs3WFRWcUuP68LcGikzgtibbUEmJwgU0wtnNSYooSbCwSqxjbefG+BJIHhZBrMLYLIRRbxLuQo9Onkgu1eO9dcSyPsV1J1ZWScpbk8ORKJzVVcj0lX9Xx0yUvPpecc0gJH37nLE6kklzJOHZdV32tJWQfvMVL5rtSsnPFWl5aTOxsySUmYbw5epO6WJ2UlIu1Ac9e6ZiX9a4WG5r/sMs+BpusjznipvNdIIeVVJGirqTU5VK8zTUXyZlYhi7lnHyNNgWvN/87B7oV670UIgdsF1y1KZVUa4lifOo8q5ghipnYCN9Za7NLXmLEnRVt50MKJdN1KM7E0vnoSs21Zo/nL6WuRptTijVmV4LJqbOBfnOMydtgSuxCjeJzkOyLes87ifwryfmgDsvQFV+rLz4Ej59WQudDjMHWUhx+TedZouJ8yBaPt3jpaiiu1sRh8gTKdcl6n0IuyeM9DKlz4tly5yJOzihdrF6K9yEXHMsxdrEkb1ORQmiHxNLZHEDPmCv+zli6WoKPzpZQ8DzCKUqWJCnWjEMzps7awEnKJeFUjSBISNGWEsFMCZlFjXhRbcC9HWwXA2e0OgJOxHuSU1XrOBN6Nz50yfE8XmD1qcYu5prEJby86nzucIeKc67g109d0LUScCSJKanLKQXJIYaaCNrPncsxRPE1S6nVpNKJK/yT4osVE2sXYg0xVmiT465C57PFkZ+8lBTAjup9tT75mEsktKXjuBcXQ82RWBXpJLuawOzqM1c/u5Kcq0WiS3hKnXQuWJuVymQNiu1cUuqSU3B4Wn1XavaVk+IJhBDpbBZMFJLFcWe/y16qS07Ix2aLSV2RbHOu1gXCeiKvDNWxnIFYiQAxSsH5kiUS1OQ7G10M0boUJHKnoHOlhOqrDdURJiJdqsWXGpNI1Vi1zoWcgxSXk+eWUFdtDi6nUqy3Walgit5lBp+zEH9mu5BiJKlbsIE5Q6dcCdFVqSmGSD6QzrnqC4tUgg8pQgFjibl6yaW4HBpNLNHFIolQAg+9s9lD1RL+cp/1RUqiU8reRYiLtvIuex+ij1JGuu8kipQIvZRAjgnoea0hWy+x1kQik87aaoXXiE/FZqXC1sYMfkQfSg7EudDOJxerr5KhqnnkNi6xzMHaFJUUWysBTlKcZJ9craZ0McfirUSfIGIwtNhJzUSdlJylJi27EU3UPFwIXPOj5d/2zUqUfXWyWbxYk+IKcQSF7fXR/LIVZSy/xuetASnvlJtuYRR7OCcF4WahokIjEBDizGdbuZQcu+thcjmxSrX6UGyCcdvkK3z/5tHR7k2PSBK2S+qlFUgi/z37p1NNtjbjP//rMYbfkxdmebIxj8cZadsH5EP830yuabqzW6uTs838BMfY2eL5iiyWlliDv/N19xZzogCmV8mveNWj5Yvj+d673M+sxrQ9/ey7aejf/+vizek/37Bd/Nd//uc3N75jDN//y//9n9/pG77/l6tL/2VUySYRcsx+16RIBN35+uF8Te5Plc3/usAXsIdU6PHT8o8p326tjk9XZ8uWFpQyRtwSxAEpcrYcbTsHwJSzTTv5fHmC/f7L9foBaeVAU+AHPyzWh0erH9FkQIj1GuvDdZIgtqDTGUm6CHQjdZDeuue+m3Em6f80Zw1ZWmLgllaLG9KrNlNyJQ1HIZKFqBdinByBYlzNisVwk80aDTs1Ekw2yXijSYpaXx81XgXt9VobqOYzfHi0ujaRK3bQh/P14mTzcH6gi7heHM40H9zhN6eni/VYfC5NLGXX0AOiU/a0JAZ3vZZE7Z6WpGTow2RsbX6WTylbW8pW7xDLc0HI85pw9W0pWyWFUEpESYN9v0fK1tS5pMlifSmVI/lkTICq+VuDhTtKsSkHtY+fy5gqSbrskeeSs0Gzi+7lb5Vkuxi1NqQiZNqbakn/qcJ+rCGH6LymZDyfv5VXkzy2JiLzKhrtW9K5ui5i/LA251zo6nxuV+9tp28LPnvvmOdeolfvauek1hp8rWiAu1pyrF6u3eVonVLAFrQccQWNgnX/RSlgiyXHqUWyT5pod/f+lgNWCopYsM7HhgRTktdXmgP2Eo5M1WMOWJUvXEEb0Ry3u8ytnbUu6CrXEMQR1DnbSwrbeV1Tq9IgMcWzbZJY+HtuaYZtjCVTNyWNvaquZYOlZnyI6MnIUy01rO1SzQylFJQExnEux+yVIz2XdfaKwW6z0F7V7zYr7RVdf0pS++dJUnvBTvg2k+JWhmnCdUtr+xpW+R+njS9OVkOVqN4zlS3i093Vj39Wfqtm4X12qwz4HzVFeglJoq/YsrhE8NYU6a7zNqfqvPMxeTW6vjNF+q/ht76gwqOFRnG+7nPUVzhOu4TdjEBxmx1cbI/fOtdh8IlYi/jX2OnEaF6RbfgD8tuQbVcaQ3bJZ6j5Hr/FGBSojSl67h/sanE+XK6dhrnLqf4x+a1aGTN2yew8ZqMtOx/57SUcOc9vA+bYmLCaZ24vzH4Bw72KH0952a9iqzuWe5lVv5vlusbCRWpOxSJd/lKee9V435frXu79KraLrHZFbnj8fh8rGTzKzKdk8BeTwf9aPnsEi/y1fPbx6vQXarUZIv6B1NrQ/KuXgzuviOz89EMkHCO0WP6L1opeRDzVZb30Ct4zqaGvxue3Wmm6rOud10qv4D0TH3w160OqHTZauI9TxjRV8gMflyo/ok56xTj3eOTloUyVV47zAodUdSmKi8nlmJPLGmy7p5SyJxM4+vdDCDjvJIvg4bv4SyQCrd+9klM1sb1xjyawaZ14X3GqRocNQX8O6P31zqvYyvuxwcta6bvZ4GWd9Ldkg5d7H9kgezT+Qop+bT+Qwun55qdtNNEnJvib/iLKr2WCm9Xpr2WBd2TP1htRPu+47U+1cBWDq08P16s3zbDebMKt3X7lo838+avdJYMWu4ooriEhDQTXzkXy3BFerhb92cv2azKHd9yuDLX5L+v56ctd0d0nFN5e6rDakxQ8Oj1abm6v5xoYBAWCoKjJW5+/5MvS0ptnPx0fjyErHIMrft3sfDAQrfZV+g8kB4xBWb88DOj+6Wp5giNGI3meXO/5oB6fx43QeXPDd5EPMTdcV/nIfEQ+PB9ibggVQoVQIVQIFZYKSwWx6jdYaNhDM/pN//DXaTyJoRGteYzneRFv5NX0QWf0SveMgwExMoYYOlHDytN3z8t2FW9trc76GFPChZpKShJrkkxcSGKY5+JSrM5BgnM+lpBctaEw4JI0TikmbMlR5+gCxkVHpAy/fsVSVOy+ws+NEehkhHgnWyyBRZ7L8SxKcC7GZFPyKVQtiiW4GrJEolTUIRyIJbBc3E+RS+a2K1JDTAT8WJt80HETP+OKRiOo45oooZxtDrEKCTZsJ75wGZswnRhFdzBYYW7OxYC/isApT4BNwfnsPZsgPmTvE0EMUd3YjtCmIq5moid0H/EXeB8Dz3AhvHM+R1+TDy6T5+AG2jcufUnF+cildhBEQiWkoaaaUilaFInoYIUIn2hY5bDQOuJegnM08p4ILWJ4YuRHRwhB8iGUGmMQKY55xOJSTMnGFEqsOIx9zd55YsmkkvDBdrm4mG2M5FRIok7lVMUXG4PjmroHL4v1taSSS46ZqAjbBRIJMI1IlJDu2X7IAqFI0klBpCHMkYgWcDtll1IkykdcLYq1f1+U4nmTIhR29WI9P75Ev+7I7etIVhSkrdEa2ajf9WTrd47OJ3vC7O8Iz0eAuS42n9n+fxKa31zuU7BnpxfwxvD8zqol6DcP/r7m7vv7BX9fCtD/Q+0VSPVBgr/RN5z32VXnIUHqzWr75rrLFb/5Hn4K4Ndt3rudOV6FUVOC3oQBF9qOadlvvkXvHcCvSNui97dfpxs5GpzfDB7bQH0abSO3r8DGc0H6l7H4Nw3ZP88MP1Z80C4Hllj3MwrQdg2uDXU/p8V8iSHinTKq/sTwCaI6XXz55OXyhaol++m4dkHro8B+4SF+E/U9Oopmr6On79nR9iGGd2t1crg8WJw8XxAauP5hfqRa4rnQHxUtfg/tqV2yPR8e1ND6lya++aQ/KTJ+YFF1jPn7xafonZj951Rfv3wv/dXaIE41reQ0OovA4ESoVpaYY/ZZb2hI9aV6V2KoPkXUI42IKqi9XkPj0XJjiVI1jiZGFCZHAHlJPkQnSfU8X4stQaq1LueEAukS9wjwPztLsBdR1jF7orWIVtewa1SnHK0PIerND4+2JF59hUXf4q0NNROxnF3U8XmJoQZfUshE/ugtExKwhcqLCKKkJ++qRFtR6fjNmo4fFBcdSQpJo7eJ/o0+5xZOr+/xNaQSPeppu2jjQwkSYgjO+9ZV4LoMlwQkkBKOKy7otaVKdi5ZFtA7L87jPSbcHrVQHfDO4fiukV8m7Ly3rjpHQLwnsSEDjETkc+0lt/hs7iIkZ2t1LBHKpPdZqi3ohMFpULr3thA6noUVHBfZh3Z3xDZd1pXEhYDKIhOeZTtXHenznGdgaiNwxNER7x6CtGWWWi0IIEECtz243uPBEUIKclY04AfYqxBZbfmge2trluoxUqRabfDfX0P/3SUV9Pej/5rA4xP9/yD2M7j9B6b/F4za/+CmindkEvhDacDoOr9CA1YpbLJWbBUo/XZZgaKvdkm9PffBr6l/slS8U8vFmh+5fBawnQs31ia198qay7uI3P0p1UBLa3ExZ8CHTz6JZbPtwT+cpeKcWq4L8VsmD/j9LRG6ANONe4ALJoh/cOWpuFAlc5G0VG7R2k5IVBFysSXZ2gR9LqCX5ELhhgRtQpDqMvcni21PcWG9xlyCXivHbRSzCwEiyZP8QGPHLWI8irihvOov0aWaEwGvOTWNi3v1KVqyWafg6SuVgKrGlXdiailxqEbV+WRj0SbW1uKt5Ro3CZhtl7ytORbuogc8djzkJDnH7fDIzy/YLoUU6b5avGII9Vm4O5xYCL3qzI2EZKt31QqeQ+08l+q8JAmSouOpVLlWU2zNVTy/1dmlYtE8vBCCqhpgcrgSa/XRche19e68Q220iQvyjCeT8CPl5EtLIoCrLpOCvMRU9GosQUGhxBLYMc1hkGqJ3FTnfv/4nhx8IgVFKdxm4c2JS+Mpp5LxWFISbcqF1ApSs84rZl9qspp+oe0Nam4tOSYbSGNtu+Cllpy4IhtS4sVow9GlkkSdvLRxuaQAXyzWqTJH6vZCGmpchZ4ltMLgvPNWUvRpUp2WMmYSa3aqW0s3wS3x4MvVj5fNa7sUhLcwtbH2GnJ9C8ULXqz3pW5JC3e7NYa93V5uvl6cvT7abAM2Hr2crxcHmsvtksL2nk6aT8mupmRXH1m40UuVf7k6N9lfpjRJVwWl/OKMdSSkIyfIeP0qVEvaiTGcsvNe71CJlMD9fkRARboyhnO0g6nXA7T8cntSKV6XQJzntP59Eohreu9vd7nIvt3mIiOt6TaXt6opz1/tBC6VQp8t3poUfNJtpvyG1yg7uI6nvOTvSkR+f5u/jLffeqk3mmf/4xtV6tp1IL6qHL5NTnkhI9qkfO+1375Vb0ozN2Kd/wCYYmvDIAJYYtRw17ejyhUP/ClwpdtLzfbx8eXRNfiiWQYvpdB7H4RppOVqDfiPQFquIEWNz43XTjSXi8axfAx0wezJ6W/Uxbvc5VJD9oho+gMHv57YXIVAWwq0o1vo27+e4Dz6yzUIpPkP/y4EahTn90egKwhIozjXYZArIzPjZ3X0/vHHwCBVxxr6oIu9FV8q6kWA3b7/71ZsjrZk56NhzY3ryE5jWX8Hm9oTaO4tye2/FUv3GNiFmj1KdaFmDwUv1HxzejVivqeAeykK6VOa0I+RJvTu6scPu01K5P4ovx1zzbFUUW8vk/Q7TbB/+GAxaNvR8kQzyV/w7BD+zqb8ch0FosnTe1m1zyXNVvPmXs5szZZ0Lvrk4/XNzu73rUmffqO+b1yc+A3R3E7TJjwckyiRe4msQjdE81++XP04tdgZEu4sDxbKcdrlC5b8m9NzN/Pp7JvTizcL9b7+3dWP55pOhRcbq+a1ONzcm69fkLVTA5auur/41cnZYjNut+J8vJzX/OH84NvFs20Go2swi/158Ow/F883X30xKlXnbKH/tiRVFwPbvomMUHpxxQXUqZvPN0syhh7Oj87ITPH1Yn7w4OTop+3PQHy73Lxcvd48XC+PlzQ927W9Mz/78s3i+W6Z9xtdPCAfbDbs1P5szqHjp+z2++bwm9NFooYHF1due4HpQ/9s3Nn8eDGc6s/T/MfZ/IeF5sV62xjch8/s/+zo/he3WI2r+z2HNQ/nP+gPmVx3zMhT8IHuNylFJf+U7VwuwbVsqbkIhiyu9Lou5yjRhRz41UK6blL+Fc3drPedeM0Q5XwJZEOdHT4RZt7bLuScXcTMrjdWtIOxqrZ7utZXPAAt+dVYFZ1zOVhSGhGvrTeLp6fGDEOYqr3mO9r/tQam9tUJv9aliPZyfoB19wjRl4JbqzU/yzI/WL4+a4G4W1K13avR8LNB6GczrtdXpspmSdO0UzTe6w9wL6xZyf9II++uTl4sSNwPI9iR60bYG3+/xN7PwI6TZsiaMuHor8deJHR355uFWiuuEgUY9551a7KGjb8bca3p8PxsJ3Cc7AS2yQKNv2c0/pDRe2Nuk0SOl5uWiLyp5qDNg/XyxfJkq6oHUj9zoRk/SgwX8xf+/PP3lwjKb8DO8id2plv9wX6sBXTYF/6A9887h/rj/jrLcu6vp+CNewXC1C8c1l8pary7zw/PrY6UYlzNqtpEvf/gE33X2sb023eZf/suy+9DsLxmN/vzy98NPeOHPxPvRM8Pf/Tf2aX89ujpr0LPX0nitgLX1RTnDyAc+2CjZBdSiD5Ik11VOK4IpoWL3VWjAppwfEXzJhxnwi1q9S67qGLuJAGH7DK/GGBTqUl/pOXpVPVW4Ti7IJ5k6ta3vK2fhOO35YW8wJo/Ccdqw3r0fL08JVmFUpw7yxcvj5YvXm5urU5OFs83OwvL7eWbxUGTu9VA8/P/AxujZJg=').then(json => {\n",
       "   const obj = Core.parse(json);\n",
       "   Core.draw('root_plot_1779221563037', obj, '');\n",
       "});\n",
       "\n",
       "      }\n",
       "      const servers = ['/static/', 'https://root.cern/js/7.11.0/', 'https://jsroot.gsi.de/7.11.0/'],\n",
       "            path = 'build/jsroot';\n",
       "      if (typeof JSROOT !== 'undefined')\n",
       "         execCode(JSROOT);\n",
       "      else if (typeof requirejs !== 'undefined') {\n",
       "         servers.forEach((s,i) => { servers[i] = s + path; });\n",
       "         requirejs.config({ paths: { 'jsroot' : servers } })(['jsroot'],  execCode);\n",
       "      } else {\n",
       "         const config = document.getElementById('jupyter-config-data');\n",
       "         if (config)\n",
       "            servers[0] = (JSON.parse(config.innerHTML || '{}')?.baseUrl || '/') + 'static/';\n",
       "         else\n",
       "            servers.shift();\n",
       "         function loadJsroot() {\n",
       "            return !servers.length ? 0 : import(servers.shift() + path + '.js').catch(loadJsroot).then(() => execCode(JSROOT));\n",
       "         }\n",
       "         loadJsroot();\n",
       "      }\n",
       "   }\n",
       "   process_root_plot_1779221563037();\n",
       "</script>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from ROOT import gROOT \n",
    "gROOT.GetListOfCanvases().Draw()"
   ]
  }
 ],
 "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": "3.12.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
