{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<CENTER><h1>Dimuon spectrum | CMS pyROOT notebook example</h1></CENTER>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p><b>Reference:</b> https://swan.web.cern.ch/notebook-galleries</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "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": true
   },
   "outputs": [],
   "source": [
    "inputFileName = 'MuRun2010B.csv'\n",
    "import os\n",
    "if not os.path.exists(inputFileName):\n",
    "    import urllib2\n",
    "    ##response = urllib2.urlopen('https://raw.githubusercontent.com/dpiparo/swanExamples/master/notebooks/MuRun2010B.csv')\n",
    "    response = urllib2.urlopen('./MuRun2010B.csv')\n",
    "    filecontent = response.read()   \n",
    "    with open(inputFileName,\"w\") as f_out:\n",
    "        f_out.write(filecontent)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "100000L"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dimuons = ROOT.TTree(\"MuonPairs\",\"MuonPairs\")\n",
    "dimuons.ReadFile(inputFileName)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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KT2g9pN8Q1yGifnPZSUWhdIhEEAQT+rMEAHRkUVC9vyzCVPpQdVs4NrKUlFJKlpF0bTfn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\nAKNS+s/2p59+evbZZ/WvUlG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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "invMass = ROOT.TH1F(\"invMass\",\"CMS Opendata: #mu#mu mass;#mu#mu mass [GeV];Events\",512, 2, 110)\n",
    "invMassFormula = \"sqrt((E1 + E2)^2 - ((px1 + px2)^2 + (py1 + py2)^2 + (pz1 + pz2)^2))\"\n",
    "cut = \"Q1*Q2==-1\"\n",
    "c = ROOT.TCanvas()\n",
    "dimuons.Draw(invMassFormula + \" >> invMass\",cut,\"hist\")\n",
    "c.SetLogx()\n",
    "c.SetLogy()\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": "2.7.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}