{
 "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": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "\n",
       "require(['notebook'],\n",
       "  function() {\n",
       "    IPython.CodeCell.config_defaults.highlight_modes['magic_text/x-c++src'] = {'reg':[/^%%cpp/]};\n",
       "    console.log(\"JupyROOT - %%cpp magic configured\");\n",
       "  }\n",
       ");\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Welcome to JupyROOT 6.08/04\n"
     ]
    }
   ],
   "source": [
    "import ROOT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "bgs= ROOT.TFile.Open(\"http://opendata.atlas.cern/release/samples/MC/mc_105985.WW.root\")\n",
    "sig = ROOT.TFile.Open(\"http://opendata.atlas.cern/release/samples/MC/mc_161005.ggH125_WW2lep.root\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "c = ROOT.TCanvas(\"testCanvas\",\"a first way to plot a variable\",800,600)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "t_bgs = bgs.Get(\"mini\")\n",
    "t_sig = sig.Get(\"mini\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "h_bgs = ROOT.TH1F(\"variable_bgs\",\"Example plot: Number of Leptons\",4,0,4)\n",
    "h2_bgs = ROOT.TH1F(\"variable2_bgs\",\"Example plot: Number of Jets\",10,0,10)\n",
    "\n",
    "h_sig = ROOT.TH1F(\"variable_sig\",\"Example plot: Number of Leptons\",4,0,4)\n",
    "h2_sig = ROOT.TH1F(\"variable2_sig\",\"Example plot: Number of Jets\",10,0,10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Done!\n"
     ]
    }
   ],
   "source": [
    "for event in t_bgs:\n",
    "    h_bgs.Fill(t_bgs.lep_n)\n",
    "    h2_bgs.Fill(t_bgs.jet_n)\n",
    "for event in t_sig:\n",
    "    h_sig.Fill(t_sig.lep_n)\n",
    "    h2_sig.Fill(t_sig.jet_n)\n",
    "        \n",
    "print \"Done!\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "scale_sig = h_sig.Integral()\n",
    "h_sig.Scale(1/scale_sig)\n",
    "\n",
    "scale2_sig = h2_sig.Integral()\n",
    "h2_sig.Scale(1/scale2_sig)\n",
    "\n",
    "#h_sig.Draw()\n",
    "#h2_sig.Draw(\"same\")\n",
    "#c.Draw()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ILlSJTQDAIxj+AwBIQKgCAEhAqAIASECoAgBIQKgCAEhAqAIASECoAgBIQKgC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\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "scale_bgs = h_bgs.Integral()\n",
    "h_bgs.Scale(1/scale_bgs)\n",
    "\n",
    "scale2_bgs= h2_bgs.Integral()\n",
    "h2_bgs.Scale(1/scale2_bgs)\n",
    "\n",
    "\n",
    "h_bgs.SetFillStyle(3008)\n",
    "h_bgs.SetFillColor(4)\n",
    "h_sig.SetFillStyle(3003)\n",
    "h_sig.SetFillColor(2)\n",
    "\n",
    "legend=ROOT.TLegend(0.75,0.7,0.9,0.9)\n",
    "legend.AddEntry(h_bgs,\"Background(WW)\",\"f\")\n",
    "legend.AddEntry(h_sig,\"Signal(Higgs)\",\"f\")\n",
    "\n",
    "h_sig.SetLineColor(2)\n",
    "h_sig.SetStats(0)\n",
    "h_bgs.SetStats(0)\n",
    "\n",
    "h_bgs.Draw()\n",
    "h_sig.Draw(\"same\")\n",
    "legend.Draw()\n",
    "c.Draw()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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OWgrBw+3MBqZRDE3HX14jVAEHsbX5qD4wT9XsbNrDCQiaprlerw/D07NvnZh3NEt7XLCd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\na3MEAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "h2_bgs.SetFillStyle(3008)\n",
    "h2_bgs.SetFillColor(4)\n",
    "h2_sig.SetFillStyle(3003)\n",
    "h2_sig.SetFillColor(2)\n",
    "\n",
    "legend=ROOT.TLegend(0.5,0.7,0.9,0.9)\n",
    "legend.AddEntry(h2_bgs,\"Background(WW)\",\"f\")\n",
    "legend.AddEntry(h2_sig,\"Signal(Higgs)\",\"f\")\n",
    "\n",
    "\n",
    "h2_sig.SetLineColor(2)\n",
    "h2_sig.SetStats(0)\n",
    "h2_bgs.SetStats(0)\n",
    "h2_sig.Draw()\n",
    "h2_bgs.Draw(\"same\")\n",
    "legend.Draw()\n",
    "c.Draw()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "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": "2.7.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}