{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "3b83038a",
   "metadata": {},
   "source": [
    "# hist033_TRatioPlot_fit_confidence\n",
    "Example that shows how you can set the colors of the confidence interval bands by using\n",
    "the method `TRatioPlot::SetConfidenceIntervalColors`.\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": "bc48b225",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:12:46.506230Z",
     "iopub.status.busy": "2026-05-19T20:12:46.506098Z",
     "iopub.status.idle": "2026-05-19T20:12:47.832972Z",
     "shell.execute_reply": "2026-05-19T20:12:47.832567Z"
    }
   },
   "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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       "\n",
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').then(json => {\n",
       "   const obj = Core.parse(json);\n",
       "   Core.draw('root_plot_1779221567822', 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_1779221567822();\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",
    "\n",
    "c1 = ROOT.TCanvas(\"c1\", \"fit residual simple\")\n",
    "h1 = ROOT.TH1D(\"h1\", \"h1\", 50, -5, 5)\n",
    "h1.FillRandom(\"gaus\", 2000)\n",
    "h1.Fit(\"gaus\")\n",
    "h1.GetXaxis().SetTitle(\"x\")\n",
    "h1.GetYaxis().SetTitle(\"y\")\n",
    "\n",
    "rp1 = ROOT.TRatioPlot(h1)\n",
    "rp1.SetConfidenceIntervalColors(\"kBlue\", \"kRed\")\n",
    "rp1.Draw()\n",
    "c1.Update()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ddf6356b",
   "metadata": {},
   "source": [
    "Draw all canvases "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3cdb22e8",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:12:47.850309Z",
     "iopub.status.busy": "2026-05-19T20:12:47.850154Z",
     "iopub.status.idle": "2026-05-19T20:12:47.966055Z",
     "shell.execute_reply": "2026-05-19T20:12:47.965494Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "<div id=\"root_plot_1779221567964\" style=\"width: 700px; height: 500px; position: relative\">\n",
       "</div>\n",
       "\n",
       "</div>\n",
       "<script>\n",
       "   function process_root_plot_1779221567964() {\n",
       "      function execCode(Core) {\n",
       "         Core.settings.HandleKeys = false;\n",
       "         \n",
       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').then(json => {\n",
       "   const obj = Core.parse(json);\n",
       "   Core.draw('root_plot_1779221567964', 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_1779221567964();\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
}
