pyROOT3.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<CENTER><img src=\"opendata-top-transblack.png\" style=\"width:60%\"></CENTER>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<CENTER><h1>Simple pyROOT notebook example</h1></CENTER>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "require(['codemirror/mode/clike/clike'], function(Clike) { console.log('ROOTaaS - C++ CodeMirror module loaded'); });"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "IPython.CodeCell.config_defaults.highlight_modes['magic_text/x-c++src'] = {'reg':[/^%%cpp/]};"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Welcome to ROOTaaS 6.06/08\n"
     ]
    }
   ],
   "source": [
    "import ROOT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Read signal (f1) and background (f2) data\n",
    "f1 = ROOT.TFile.Open(\"mc_105985.WW.root\")\n",
    "f2 = ROOT.TFile.Open(\"mc_161005.ggH125_WW2lep.root\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# c = ROOT.TCanvas(\"testCanvas\",\"a first way to plot a variable\",800,600)\n",
    "c = ROOT.TCanvas(\"compare\")\n",
    "legend = ROOT.TLegend(0.1,0.7,0.48,0.9)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "t1 = f1.Get(\"mini\")\n",
    "t2 = f2.Get(\"mini\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "TFile::Append:0: RuntimeWarning: Replacing existing TH1: variable (Potential memory leak).\n"
     ]
    }
   ],
   "source": [
    "bg = ROOT.TH1F(\"variable\",\"Background Vs Signal\",4,0,8)\n",
    "sig = ROOT.TH1F(\"variable\",\"Background  Vs Signal\",4,0,8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Done\n"
     ]
    }
   ],
   "source": [
    "for event in t1:\n",
    "    bg.Fill(t1.jet_n)\n",
    "for event in t2:\n",
    "    sig.Fill(t2.jet_n, weight)\n",
    "print \"Done\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "bg.Draw()\n",
    "sig.Draw(\"same\")\n",
    "sig.SetLineColor(2)\n",
    "legend.AddEntry(bg,\"Background(WW)\");\n",
    "legend.AddEntry(sig,\"Signal(Higgs)\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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wpbu5txOSA25OCim3pfBW7t7kALs6GIICAGClFg3d68ttmVpfkpJ4+EM8BJnIufWlNE1l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\n/wDbOTJM/9Tg/wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "c.Draw()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "scale = bg.Integral()\n",
    "bg.Scale(1/scale)\n",
    "scale2 = sig.Integral()\n",
    "sig.Scale(1/scale2)\n",
    "sig.SetLineColor(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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QRFAAAABBBAUAABBEUAAAAEEEBQAAEJTg9EjWUQAAYCwJBgUCAQAAY6HrAQAA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\nAABA0P8DW/m/72Q1h6kAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "legend.AddEntry(bg,\"Background(WW)\");\n",
    "legend.AddEntry(sig,\"Signal(Higgs)\");\n",
    "sig.Draw()\n",
    "bg.Draw(\"same\")\n",
    "c.Draw()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}