notebook_analysis_CVS_to_ROOT_cpp.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<CENTER><img src=\"opendata-top-transblack.png\" style=\"width:40%\"></CENTER>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<CENTER><h1>Simple CVS to ROOT C++ notebook example</h1></CENTER>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false,
    "inputHidden": false,
    "outputHidden": false
   },
   "outputs": [],
   "source": [
    "//%jsroot on"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#include \"Riostream.h\"\n",
    "#include \"TString.h\"\n",
    "#include \"TFile.h\"\n",
    "#include \"TTree.h\"\n",
    "#include \"TSystem.h\"\n",
    "#include <stdio.h>\n",
    "#include <stdlib.h>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Download the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "--2018-08-21 18:09:54--  https://docs.google.com/spreadsheets/d/1nH8J5PViu8yRVMAY5q3ydS6Onqv5ZOh3tdeM5MP9YQo/export?format=csv\r\n",
      "Resolving docs.google.com (docs.google.com)... 216.58.205.174, 2a00:1450:4002:801::200e\r\n",
      "Connecting to docs.google.com (docs.google.com)|216.58.205.174|:443... connected.\r\n",
      "HTTP request sent, awaiting response... 200 OK\r\n",
      "Length: unspecified [text/csv]\r\n",
      "Saving to: ‘ages.csv’\r\n",
      "\r\n",
      "\r",
      "ages.csv                [<=>                   ]       0  --.-KB/s             \r",
      "ages.csv                [ <=>                  ]     463  --.-KB/s   in 0s     \r\n",
      "\r\n",
      "2018-08-21 18:09:55 (24.9 MB/s) - ‘ages.csv’ saved [463]\r\n",
      "\r\n"
     ]
    }
   ],
   "source": [
    "//This two lines can be commented out. You just need it once, and in case the CVS file was not provided already\n",
    "system(\"wget https://docs.google.com/spreadsheets/d/1nH8J5PViu8yRVMAY5q3ydS6Onqv5ZOh3tdeM5MP9YQo/export?format=csv -O ages.csv\");\n",
    "\n",
    "//If the file is downloaded with the line above, you *need* to remove the first line of the CSV file"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create a ROOT file to save the data that now is in the CSV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "TString dir = gSystem->UnixPathName(__FILE__);\n",
    "dir.ReplaceAll(\"ages.C\",\"\");\n",
    "dir.ReplaceAll(\"/./\",\"/\");\n",
    "\n",
    "TFile *f = new TFile(\"ages.root\",\"RECREATE\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Read the CSV file and save the values into a ROOT file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "TTree::ReadStream:0: RuntimeWarning: Couldn't read formatted data in \"room1\" for branch room1 on line 1; ignoring line\n",
      "TTree::ReadStream:0: RuntimeWarning: Read too few columns (2 < 11) in line 1; ignoring line\n",
      "TTree::ReadStream:0: RuntimeWarning: Read too few columns (10 < 11) in line 7; ignoring line\n",
      "TTree::ReadStream:0: RuntimeWarning: Read too few columns (10 < 11) in line 8; ignoring line\n",
      "TTree::ReadStream:0: RuntimeWarning: Read too few columns (10 < 11) in line 9; ignoring line\n",
      "TTree::ReadStream:0: RuntimeWarning: Read too few columns (10 < 11) in line 10; ignoring line\n",
      "TTree::ReadStream:0: RuntimeWarning: Read too few columns (10 < 11) in line 11; ignoring line\n",
      "TTree::ReadStream:0: RuntimeWarning: Read too few columns (10 < 11) in line 12; ignoring line\n",
      "TTree::ReadStream:0: RuntimeWarning: Read too few columns (10 < 11) in line 13; ignoring line\n"
     ]
    }
   ],
   "source": [
    "TTree *tree = new TTree(\"data\",\"data from csv file\");\n",
    "// The file inside has -------->   \"Room\",\"room1\",\"room2\",\"room3\",\"room4\",\"room5\",\"room6\",\"room7\",\"room8\",\"room9\",\"room10\"\n",
    "tree->ReadFile(\"ages.csv\",\"Room/C:room1/f:room2/F:room3/F:room4/F:room5/F:room6/F:room7/F:room8/F:room9/F:room10/F\",',');\n",
    "f->Write();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's plot some stats of the files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-rw-r--r-- 1 summerstudent users  463 Aug 21 18:09 ages.csv\r\n",
      "-rw-r--r-- 1 summerstudent users 6.5K Aug 21 18:10 ages.root\r\n",
      "\r\n",
      "This dataset contains the below number of data points / rows\r\n",
      "12 ages.csv\r\n"
     ]
    }
   ],
   "source": [
    "system(\"ls -lhrt ages*\");\n",
    "system(\"echo\");\n",
    "system(\"echo 'This dataset contains the below number of data points / rows'\");\n",
    "system(\"wc -l ages.csv\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's open the new root file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "TFile *_file0 = TFile::Open(\"ages.root\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Let's do some visualisations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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r+99+L8gFM3Umo67r8/k8eMT/Z9M05/PZPyhtVmP+2OLDdwgkNnZEcgI3aU1pOINLyvhb\nuVOfnVoi/eoSX9d1g0fatj2dTu6fdj4lapvwGImN5e4q9wEGlM3xX0s8J6mfiEzZW3mXxEGGX+zp\nF4G2bWv/OUh1+DMmSItQY4D5DgSS3RC1PJgYnBG5dHC17N7K7dJnMi6Xy/F4rOv6eDy6pIVdrWqM\naZrmcDi4w/R0OhFkiOKHGiWcNiQnkJDAIWrf5ITADgZSzlVCykTRYFHJiif4IkyA6d4nY7VK1wYb\n48oJlIC3e1KS4omY74W7qse8kqu/yEhZwnozgCCBkYWsi0MpxkR2Ao1Mcoox1ddOquyUT0qQAU0G\nOU9RZ9E4kiCkQL62j8Fy4ol5ApuEJZQEGeon8DLlJzaSXCOWRBJcvKDAkmgjl3hintaUhlbpCz93\noXv5U+5CF4dSjAk4LqrWulg0UHGoX2a3435cUJLJgHx7zaGQnACcawNtCaeA+nINHQgyENtdcyhU\nTgDW6skO9WMw0YZkBBlIY3IdCiEFYPYunihnDNbdu0wRZCC2yXXhg8QGFwukErmKPGYxZjnRhvoO\nZkRJ4acQlAs59xZjhi4OBXxLjk+zd8AhpxgzUO2kHOo7mBEyGWsQTAzsVYy5V3Eo4Ft9fG4pT97x\n1cIR2KR9lZO8EUtJkEG4GlOEyom7ikMBE3ibNTafyB3RRipKpktSrfxWfLMSCZtPMIeCa5Ycljse\nny5qETLfsbty5hdyfHeypiSTgY0kbz7BHAriLzu6mZ/Q+oG4nE/86jsoBEFGQYLmkyPw51CM7KZi\nhSTH5+rNrNQPxnQQuyDIUEtycmILEhs6xD8+lxdP3DVloP4IpIPYQklNRkJCyjISVk6k4ldspG4L\nboh8fCYpnlB/HKrv4INnqRugCpmMnOQ+3xECcyhyyJnvSHIYqE+/q+/gg5f2/7R3MxKCDLm0zneE\nwBxKfJLnO9JSPxir76BVSDdDUxJk5JvHIzmxLxIb+0p1fOYST8xTP0qp76CluGsRKAkyBgeB2JiD\n5EQcJDbWSXJ86ogn5inrzpj6Dlq6Y6lAlAQZMpGcSM5PbPA3HxC4+YR66kcp3R0sJHOzLymrS9q2\n3fgEAd7WJJezviMX/joUsVmuQMbLOiIcn5OLOyKs75BvkGPTJ9MOjm9HNX+Dqky7mUT6IKNt26qq\njsdjVVWTkYT/hKZpYrfvsdlD6m1NcmnXzVy4UU1xqLEkkti9GHNhMMF54VM/SqnvoFVIN7dIH2Qc\nj8fT6dT3/eVyOR6Pk0+4XC72CefzOUKTlnz4Q75yDzWSJCeM6jt3JKR+lFLfQauQbq6QOMiwqQub\nn6jr2oymRew/7bfqur5cLru3If6HP0iQyxxKkuOTeCI+9X9M9R20CunmcrIKPw+HQ9u2NqSw2rY9\nHA5N09hoY3VlRsVKUUwZfP5IfgzEPz4nA6zkf4eSVdqLCtV30Cqkmzelz2QcDofBI4PndF3Xtq3N\ndvif6ma4n42fnJgvF4JYMRMbzHdghvrEu/oOWoV086bEQUZd113XDR4ZP82mN/y5lckr4/gSGeZK\nTRihljuEdgw1mO/AOupHKfUdtArp5jXpCz99g4DD8lMdg7RHcgQcWq0ONSInJwzxRAHUj1LqO2gV\n0s2B9JNGVVVdLhebqDgej7Y9fr2nP7PlnnzzNcP1ywUWff9ZVb2y/+s/Qch9WbGXcbhQXS/xidMS\nX/JTWB9m00sz+XExwpV8MLqpPOrSZzLsytW6ru1aVvugDTjs16fTyX0+O51ONyMMYHeDxEbo+Y7J\n5AT5CTjqPwqr76BVwvkrJXQaLCpZ8QRftEzG4JHB48jI8uTEOLGx8feOHxRyVhYro8+UGTV1nVg5\nwjSZDK8BIla3hSBlCevNAIIEBnY0jiSWJycGE6vLrwvEE9id+mS7+g5aNlGauhVBSAkygHCWhBQr\nuNccvw7xBCJTf3QVEm3ooyTI0BoDYrmZ+Y6g6zv8UGPwIBCf+jFYd+/0SV/4uQtK4UqTZPOJGS6a\n4QhEWuWsk1TfQR2UBBlQaRxJRNt8Asid+mhDfQd1IMiAFNKSE4AO6gdj9R3MGkEG0iA5AUSm/sza\nN9pgQ+ddKCn8hEypijHlY28VmdRXTVrqu3lX7wgmgiLIwG62bD5RAq5l0swcsYMnKFPOclD1HZSP\nIAMrkZxYiNgirS3pNPVHsvpo464Ojm9Ehe2U1GQMbvGQujl6sL4DeQlUPqz+qqK+dlJ9B8VSkslY\nst8ibmK+IwK//IKPTRtFS6ep/8Tv6O6dKemtFEJJJiOaJaOC8JGD5EQqff8ZBZ4riDpiy/lArL6D\nXOXiIMhQjs0nkJdcjlj10Yb6Dnqeua/4GLA7goyVZB6LEj7qAcspOGJzaedqBUQbL1M3QDOCjB1E\nDjhEZY+xC+FTbBsVcsTqHYPfKiDa8D27/RQsQJAhXS7ZY8Aq9ogtZwxW+faNvE1vqH83QyPIEKGQ\nj3pQgyN2RjnRhvoOmoIP470oCTLy2iej2I96BdIxD8IRu476aEN9B30l9DEEJUFG/1jq5jzCRz3k\nhSN2d+r/biVEGyX0MQQlQYYkb8uFuEBDMuY7klA/PpUwEpfQxx1JCTLatk3dhL28LRfiAg05mO8Q\nopzxqYTDqZx3c4v0QUbbtlVVHY/HqqpmQg37NAGxCOuaIB3JCfnKGZ/Ud9BwWs1KH2Qcj8fT6dT3\n/eVyOR6PM0+L1qSZTDLbtmC1cRHolh1WmO/QQX20ob6DvhL6eK/EQYbNTDRNY4yp69pcmTep6/p0\nOu37q++6RnOxRlocpeqpf/tyjDbuXR2WYx9DS5/J8B0Oh3GQ0bZt13U2EFmNazQyQnKiZOrHJ1Ej\ncaBF5qL6mFb6TMbhcBg8MnjO8XgcX1irWf7T7BdcoyEYK5LwTjnjUwmHdznv5jWJg4y6rruuGzwy\n+KdNb9jgw4Ug/Sz34yUcxJBtSaUwK5IwoZzxSUIH+/6zqnoVbve8Ys/u76ZuwCNd1w2CDPugq/o8\nn8/moYYjLXcsyrwdK2KqqspeQcZfUCmM7fxoQ+VYpb6DvhL66EufyTAP+Qm/CNRPXfj5icvlIiHC\n8E1Gvjo2k8Yk6nuQivrjqoTkTQl99KUv/LQrV+u6tmtZ7YNt28Zcs7oQoUOBqMGEQOrHpyQnV99/\nFjMzXUi0kT7IqOu67/umaez/2gftPwfP7Pt+PJmSCrMkmkjYc4IQFssVMj6ZAjpotH9ckVKTISd6\nWMJGGMQZmRpXTjDfgUypr2ZQ30H10mcygKCY70AJ1Oc21HdQKyVBxrV9MlAICfMdgATqj3Oijbwo\nCTKu7ZMBlVjfAdykfgzmHM+CkiADiuWbnKCWEwmV84lffQezRpABEZjvAAJRH22o72DWCDKQAPMd\nQHzqB2P1HcwRQQaCIzmBLPiV47pHKfXnHdGGHFL2yUDuZu7fQUgxwI1v0ro+8Ly70Uzff2afpvug\nVb/5hO7eZYEgA2uwn9VqVIPGdCWeuH3Xuqp6ZZ+mO9QoZ6sr9R0US0mQQU4sKJITkG91PHHLu1DD\n6D3g1Ucbkx1cEvFX1SsyjlsoCTIGZwUxxwrMd0TGlWudJZMdAbz0f7viE0Fx16zH5RpBjxkYoybI\nwL2Y70iF2GK5YMmJLYpIbBi9KQ2n73uqoyIgyCgCyQkIJzKemKE/saF+AuWavv+MwqkdEWTowXwH\n5Es02TFtj+GE4lBgDkHGPsZXq9DlQsx36KOsxExOcsL+VcfxxPII41Y4UsQcCtEGViDIWCptAo3k\nBCSTE09MuuvknYwnlr3Cy4cf15zYMKq7NvJMzmGcKYIMQZjvgHC7T3YInP/emN6wG2y4UMOoPmcL\nSGm8K77R3tNQlAQZMdes7pXQZr6jQOMJEYGjrLV7cmJDhkComca7vbx0JzbKmUDR3buglAQZ8vfJ\nIDkBseJMdmQdT6zGzqHKqO/g7pQEGfI8c1cWQgoISVeIWtmxnZC/6mIUh2qgvoO7kxJktG1b1/WW\nJwjz9qrNUYgkhFdi3iX82pCY9G+wYSnumkW0sVD6W723bVtV1fF4rKqqbdvxE5qmcU9omiZ2+4wx\nIudfIFy0Ua2aYszLqf8WkbaMtqpe3RVPTL7Clh8P46UxL/2by2ulu3eG28rfkj6TcTweT6dT0zRt\n2x6Px0FI2Lbt+Xz238W6rkOnNCbrJ8R8EkKhQkx2bCzGlJQheGuPtSEx6U9slPOJX3fvVkscZNjU\nhc1P2NBhMC3Stu3hcHD/PBwOe82bsF4Ucaz4cBxtsiO3IXlPwhpPcage6jt4l/SZDN84hhjMj3Rd\nt27GhPWiEO+ZMaaqnhljBBZPCBuSJdp3k3Kj94qkPtpQ38G7pM9k+IkK85DbmHymnVixIcjC2S+S\nE8iHuMAiKIFTLcsFnmbSP4diyelaoNuxEm2Y5IWfdV13XTd4ZPJpx+Pxcrm4NEY/y/1gse8rNJFW\niXmXvv8sn2LMpWIVor4rDl3ctCzJ6eDkW7M9Gi65ODT96hLfIOCwbLFn3/dylrDacve7it5Rgoej\nwo4Kz3Z82eVPljYkx1wbItAejde/DiXJGJzkuCrwc2/6TIZ5mCLxi0DbtvX/mWrlKnCNCyYeX/2f\nPezDdseS0dVKzhCU52UJiY1Un/jjnwuK38SB9IWfl8vleDweDoeu606nk33QrVy1oYb/ftj1rila\ninItW+4R+4aNJa8NWSjfyo9rW5BRHBrgd31moscZ5ZRrSOnevht6hnjbblYGjS8HAj8pYt62vSim\ng4zBaDE+KjIdBUXZHkzkGI7ovvtaaHedkhEu5lqjjfSZDEtOvcWOxrfchByaNt6OT9qQfG/Zio4t\nyAq5+5qldQxWT0qQAQRSVa+u1GAST9ym674hb2mcZtI/h1LO/IIySoKM0EU02z8nIQJldxmVIGaG\nQKDcGl/EBhtEG3lREmQMDrVyCneLxWSHQLkNyQnE+gSiP7FhiDYyoSTIiIYai8j2Sk5kml7KtNl7\nybr7Aio/ikhsGNVdU4AgA1LslZzQlLTPuvRhuWuNz7r70So/FvSd4lAkQ5CB2EJXTkgbbHa3PYqS\nNiSXuTbEiRWO6J9DYQJFIIIMBKSgciL3MWny+QzJmdppk3L7UpoTG0QbchBkYB9a4wkyBLu2KKqs\nGx9eEXMoRBvJEWTgPjtOdpQzJA8e9/8pp5RY1Hshk7Qj9i5XGq9/DsVS3DXhlAQZrFkNYcdKTFNq\n0l5ODBGfwHdtucIqP16aYjYpJ6URmZIgg30ythBViakvaa8ea0N0HLGDTcqN0mhDZackUxJkYCH5\nlRM5Xp1vGoxDG9Mb0oZk1oakbsLuCkpsILTvpG6AQhIuOtUVxryc+k8tgbMVy2/w2PefTX7r3tUl\nomxsvISTKzQh79pDYuPlw6WjINwqeUdkMrK3Y3JC4MfE5VgboiNp72Td+CXyqVVSOIei/uiSgyBj\nNxFO+NDxBEPyri26/Rt3JOq9kKnkI5ZNypEKQYZEEe4mGnNDJ4Gybnwc0obkuwgYkncmqRBVVWJD\nyOSUYgQZiVGJqcBDHPYsdUPWYG0IAfQqRSU2nom6JudFSZAhti6pql49jEDBkxO5EDgmLVf4mFRy\nhqBYt961EnYOfRdR6e1jKEqCDKn7ZDwz7z7gFhdMGMYkdUrOECwk8KBdbsO7pmoO5Ro2KV+BJay3\nrbhkPMzzRV0mKnByMeZ6RYHdL1m+A+1CLDCeevilMS/7vle/6pUIY7lsgoy2bVM3QRB9Q/L2xqsf\n1Qon8IiNFkNL67uZbbzdYMOFGrqjDd2920UGQUbbtlVVHY/HqqoihxoPZ8jbgj45p/pdlyd9Q3LW\njY9DzrG6QlFD8oCas9Xt5aU7seFPoKRtiVgZBBnH4/F0OvV9f7lcjsdjoN9ya3/MXN31eatMAsek\n5a41niE5U1k3flIhO4cSbVwjvfDTpi6apjHG1HVtH7FfbDF1HGQcScRUal3b3CskJHwLstCybnwc\nko5YikNLJD3IGDgcDvcGGfI3ohCr5LUhbEFWJoEH7XKZnLClbLChuGt3kR5ktG17OBwGj5gFKalB\nvCz/wiHw6hZzvaK07mfd+Diy7nU+9w25Q24LjKVssOF3PMTsYeEpDek1GfB725AAABeySURBVHVd\nd103eMQY019hn+N/LRBrQza+gjTXGi/tbVpN5RHL2hAZ3pVraK1mKLxcQ3qQMTAIOHz2GB2HGm6F\nyPZTfa8zk7UhqZuA+8QMIrMekvWdrQttftdeUhyqVQZpnKqqLpdLXddt2x6Px8kG38xH7Tt74p9R\nJVxBJJOUtR7e4GBw5XXtHF+RV3dBUvfvlnXjy3RtmumuV1jw427XgFDD08zJOHiCE3omReusSgaZ\nDLtyta5ru5Z18jk3Iww3n/KQ8PjsWpJgCZtrzXF1qMCPicvpS9rfRd+n5KwbH4e0IzbWNJPEDTZC\nHK4qo4qBDIKMuq77vm+axv7vilfw30g/1HDRxvUflHWG30XfkMw0U+omSCftiL0L00xTPy4u1AhE\ncQczCDKs7Xtj+FzpxnyoUfIZvssrpJJjkikyaW/ZXThht/y4QDc3Kd+3OFTgZy3FKQ0RQYY7evxI\nwj3493//94F+6WAOZWFxaMkZAqPxAreEtLfsLiqPWNaGlKeI4lB90gcZdV3bXcP7vu+6zm6D8f77\n7z958sQ++OWXX/77v//77r93PIdio42boQZJ+9RNCKvwt6zkIVnfW7+QwHdt1m6Jjdw6nqX05ayT\nJbVVVf3617/+q7/6K2PM+++/b4z54x//GK099ou+70u4vqSV9fqCUeMTrC5JKOv3rkyx1oZE9szc\nOd1wc2nJ4DlLnr8dq0uCsHkLu1O4XaTqvmUjDGPMkydPorVnMIdizDO3mEqCrONulUn71E1IqfDu\nLyHwiNU4zcQcimgigoymaZqmsYtU27YdT4588803cdozOYdiQ43I14uSh2SV00y4SdoRe5d8huSl\ncptm0r9zaKbS12SYh0xG0zT2/mcuh+HETGaMuXUoMRMbMdeGSMPakJsEjknLsTZky48LJKnxFIeK\nkzjIGCxM9WdMQhR7ruPPoaRKbMyQdIYLJefNsiIndQR2nyEZM/Y4YklsSCEiyHCBxfl8ttttPXny\n5JtvvrHHx5dffvnTn/40WRNHJUWDdSjSruDbZd2jvIZkt2/sTDqKtSGpmyCdwHdtucBHLImN9NJP\nl9hdw+1BcDgcbNjxJ3/yJ19++aWdJXny5Mmf/dmfHQ6H58+f/+53v0vc3Af+Xl75Rhslj0lxkvbu\n1caRRIjhs+QMwUICD9qFmGba8OOEGsmkDzLsruGXy6Xve5fS6Lqu7/uf/vSnfd9/+OGHH3300dOn\nT40xH330kYQ442Gf0Hcy3aQ85pgkrfsk7VM3IazC97ElHJnyNtTYq0lYQuLC3KZp2rZ1AUdVVb/9\n7W9/9KMfGWOeP3/+5s2bmRu+RzCzmnnHPTZErkdfZPta/GxN7JPhEhj2i5nF97n/xfI9Ys3mxpfc\n96wt2Sdj4fO3Y5+MeFxlhjHm+fPnT58+tRGGMebp06dv3rxxX1dV9fTp0//6r/+K1rb548B+a+HO\noQ8/wtoQzdz7O36j+223Ak6FpP2WHxco68ZDPolBxul0cqtO3rx5YydKBv+0OYPf/OY3T58+/cu/\n/MtobVtyT3nzuDh0ftUrZ/hNAsekJfZqtrTuM82UugnSSTti19HRCwmk52cG8yN26qTrup///Oeu\n5U+fPn369Ok//dM/vX79uuu6zz///Nqr/fKXv3Rff/LJJwHb/djDNMrLG8/bQ9bJz+2NT9r9G9uK\nG3U7i2O7kk/Y5H2/9zZVTJesIDGT4fviiy/evHljl5bYyZEf/ehHP//5z//xH/9x/OTPP//8iy++\nsDWYr1+/Hnz3z//8zz/1uIDDraV2czQhuA02dn3NorPW+rqPm/J911QesSXntLCQ9CDDGNP3vZ0i\nsTkM++Bf/MVfuCf84Q9/sP988+bN73//+77vnz9//uGHH75+/frFixcu2vjf//3fr776yq0HsZmM\nuq4Ph4N95Hw++zdP2ctgDuUh1Ngh2mBtyMInl3mBk/aW3YW1IZOvsOXH09JxuunoRWRZ5mdszGEr\nQJ8+ffqHP/yh7/sXL150XWejkNevX3/44YfPnz83xnzxxRe///3vP/jgAz8ZZe+WYoypqupyudgS\nkMHOYKHZORRp93rVsdIhkUfTJfPjxL7TJZlPM22Ve9J+i6wbv8UuHb9zuuTu273eRet0Sa698tc6\n/+Y3v/n444+rqrLBhDHmcDgcDgdbnHE4HIwxXdf5P/KTn/zkX//1X83j93WwdDZCFx6KQ42RF23g\nmutXt2RBxnLbg8isR7WsG1+s7UGkWbUkdXLBebhQQ2uQ8d3UDVip73u7cvXjjz82xtg5ERthGGP8\nWtE3b97YlIYx5quvvvq///u/733ve59++un3v//9733ve4OXjbYDhz+H4h4xGkONrC/rk43Ptzvm\n/jmykrtfJoEn7F3zROGP2JfGu1zv+so6ZVCTcc3HH39sIwxjTNd1LpJ48eKFW/Vqgw+b0nB1GDbC\n+Ld/+7fB7dnMQ9ojgvHRqeCWKCorP1I3IaXCu7+EtCP2LoVXfmxrP/uUL5VxkOH7/PPP3crVL774\n4sWLF+5xF3zY5STn8/l0Ovk/G21+ZCG3Sfn8dl5Zn+EqK+1xU9bvmr4jltLpzbjX620KJ4Fev37t\n5k3crMQvf/nLTz/91N6MzY7iX3311SeffFLXdV3X4yLQJMZzcnvNoQhMgS6XT+MzqMmIg0LUfBtf\njpth35WajKuvtnEORWtNhpJMhs9FGK9fv3bzJp988sn3v//94/FojKmq6ic/+YmdOmnb9nw+13Xt\n3wM2lfk5lCWrXrdnCATKuvFxSPuUvD1rXUiGoFgC37Xlrh+xL708NN7SGTpd4xIYg8fbtk0bXszw\no+OYO4dqFfJTZvBMBmtD8m38Fll3XOwC430zGYNX9pcNLvwpMhnZa9v2cDhM7iYuM8LwbyhvH9l9\nO6+blH7g2PQKCRW+BVnWjV9CZa1SgVuQ2awGiQ2roCCjrmtpNZ4zBuGFz21aum+ooXJIXv5khuQC\nCTxiCxySHX0BNHMoprTpEk1cbi3+BhvsCnqF8sJPkvY7tiemrBsfWtx4ZW4jL63TJbluxlU4/3B8\nXK5hIlRscMHS7dqYtHFPpLSEbegUVdaND83+cWIdse828jLF7OVV0HSJJtfWoRhj7ByKwFzojLxa\nO5B14ycxzZS6CdJlfcwLmGZ6WdReXgQZAQ1uHx/6nvKujOOuVa+RCTjDdxZzTCq8+5kS+K4tV/IJ\nGzqAdtdq3aEGQUYogxUrEe4p76c3BsWhck71mGe4nF7vRf2InvVbxtqQ3X88rZinm+I4gyAjCJur\n8O+E0nWdS2AcDodAyYwxr2LjRqgh7STPOmm/5Y8p7Y0IRF8QydqQhc+UdrZG9Mz/z9+k4NpaQgUo\n/Nyf3UW07/txMsN9EfmG8u5r+8XkUpSsT/KsGz8QbushUX+lmPeDldZ3QyGqWnaJ2fQ8tZ0c0RpM\nXEMmY3/H4/FyufiPjEOKaPeUn5xDWZLYKFmEv0y46+y1xvMpOVNZNz6OpEfss8f/GWOe9Veka2RK\nBBk7a5rGzpK0bWsjick9y6PdU36SP4eyvThU4Ji0nJyk/V6vk/U003ZZNz6Okk/YbX1/Nv7v3kji\n4TNeQZgu2V/XdfZObMYYW+NpMxly7pAySNktvyVK4VnryedvT/snJKoxMkl7y+5S+Am7tu9XJzvM\ngi2zis1YXFPc/FBM/n3kRd1TftK+d18r8mbf73b8nPnAlPWmn/MyfMve4eZz+TZ+g7l44prtdRVF\nVWaQyYikbduqquwcSvJ7yk/ydtewNkUbMcv6EN/2t0zaqEYhauomhDYRT6zb4Xt7fFBOhGHIZEQm\nZ8ZkwL+hvP8It5W/R8BMhsBhaTnuG5K6FQkk7fiNeKKoREJy/K0xd8rFvCXKXtJd3URMl2Q9qmXd\n+DKlnmaajifmw4hUQcZ//ud/Dh758Y9/HL8ZkTFdUrqbiUH7BJmJDclJe/9llywrXVH3rm+aKevG\nxyEtDos1zbSmeOJ6MxJEGD/72c/++Z//2X/k/ffft0GG+yz3t3/7t//yL/8Sv21BkcnAnCvrUIy0\naOOmKLenf5TJuBZA+JmMwXNEDR46ZP1XLXWaaVHxxM1shPA5kaqq/uM//uPHP/7xkydPjDHffPON\nffDrr7/+67/+69St2xOZjOwFrfMYnKWDzUMndw59eKasC5yoxsgk7S27y/YFxgK7r31X0BvJCeFR\nwhY/+9nPXBrj22+//frrr+3j77333i9+8QtlQYbad7EETdOcz2f79el0cvdDcfkG/8F9+XMoM6GG\nYi454fVdRE3GEkUuMH4n68bn6eqOf0ErJ8SGKYO7Pbiv/+7v/u7bb7/90z/9U2PMixcvfvjDHyZr\n4n7IZGTM3iHFGNO27fF4dBtyHA4Hu/1XVVV2f459f687K7ydQ63M5lAWyvNj4hyWa6ZugnQb3rX7\nVorOtkHnStEf/OAH//AP/2C//tWvfjX47rfffvvixQtjzAcffPD69WsFcYbQQA83tW3bNI27K4rb\n4Mvf6cv+b8ybsRljNoYaAsekxbLJZASS83u3Sb4d31arxErRNcaFboNMhq3POJ1OXddFu3qHQyYj\nV+5Wrm7bcv8ur4PnROBNnSxNbEheG4IV1L8X1463fPM6ixtzNZ6YiSTKvOnoPFuN4f5pr8+/+tWv\nxnUYdtvGmG0LhCAje/Y+KafTyaS73at/KRndWf5qqBH5viHITrZDsjG5TjPtuVJ0yw9u5z7tuOlj\n/8Fw9Woz2rb9n//5nx/84Ae2GafT6Xw+v/fee99+++2rV6/atv3FL37x9ddf//d///cHH3xgIiah\ngyLIyJ77PDFZfhEnFp68lDyu2Ii3SXmZpI3Hd2FtSIoAep+VojLTFXVduzDC3s/BXh5D16v5bKmc\n/dpNYf/xj3/86KOP+r63ZfvuIvnee+/Z/7UpjdevX3ddJ/APu4KGPpTJzpK4YNzdgM2vybBFGwnD\n4RVzKHGEGZMi1WSwNiTfxicyF09s33BC4Fg42aTd69Xc9gH+Qj/3K9yvG8QTk3/5yRkTGxW5V87U\nd1I3AOv5B1/XdfbI9nOD5/M5fkrQsaeQW4fy8PWzmfVsIUyO9/fmvfdrzg6/cXvj752oEoUIY9az\nqf/enYDemfjW488AE24GEDdfITJXrGY/evmRxLhwbZ2qqpqmsYmKtm3P5/Plcun7/nQ62QebpnE3\nwrRfz1+K/+Zv/sYYczqdZN7cagumS3Jlg9yqqg6Hg39nVzm3e10wh2IiJDa2p9zvHdW2D8w7jqPi\nk/bp5Zkaua94oqjbitqoomkam8o9Ho+Xy2X8tI31am3b2l43TeOCA5u0GCdI/FjH3z5x8PX5fK6q\n6nQ62au6jtUlZDIyZo/ypmn6vvePxckHpfETG0I+LgtPb4SW4UB7nyV3kFn3CoFNJCfGaYlBfmJA\nVBAQhx2/bRZhclvkjfVq1z6/uV83GcT4mebJr201xgcffNB1nY53jUxG9iaPdbE5t8E95fPdzkv9\nkLydtAxBDmtD1qwUNUmrLycnI9Kq69qfSr6WRdjCD1AmdwpweWX7xfl8tgsAB8/x0xj2ix/+8IcK\nNuDyiSvYgWJLKshMxvuUvy38XFhRMVP4KW14npf6Zt+J7R5PXCOwvnLwed2vebSPJFkpah7XeLqv\nXXX84Akr2Bex/+tmZGy0MfjaPt9PWpSGTAYimb9E+hmO7O6+Fpm07sfMEAh0q/FLiydE1U4u1HXd\neKiOvFJ00uVy8Qf4EPVqLmiwy2Xdr3P1GXVd2zlrIQmeVMSFxijQtfVmD1/msk95oZkMPNi0zTYr\nRXc3OcDvMuoP7uqw4yvrQ+Enlgp3pbi2DuWuVa99/5m+5Zq4SVQxphktFl3+itmtFLWqB/60yF4r\nRTcKV682U4eBAYIM3Gb3+Doejzb56R6fvL7syL7441DjarRRVa82xhPqkwdZR1Hp1obcXtyxMJ5Q\ntlLUsvtDXC4Xu3Qz1Z0NIJa4/BsEGlRR2WIuPxG6sYrq2i+dPDh32ac8jN2mS7ZjV9D7G7+oeELg\nnIUQft2D+xMl33QYyVH4iRsGt3h1JV225ss9OJ6h3OjapfzxqleBocZSVfUqXGoh5s3nBIYjK4ox\n3fFGGLHctSoEqhPgMF2CG2yNtPun27/cJJp5vWsOZXdBZxySTGdon2babbLDSh5/DGYnQ09ZzvCX\naBpjuq6zbZBzZwNIQCYDS9lryrWkRfx7ypt7biu/XwO2DqgCP/cvJ7vlS28rOv8qCTe2uknUYlF3\nZwP7T7d0U86dDSABQQYWsbvuDFam+RLeU968K7x3w0zG0yhFCVE8IXZzzI1cnsA9EnrK8ib/VmT+\n4+wPAYcgA7fZ27CNr8tCriODrcqNiooNZdbefG46ObExjFi4WFRUIGLvntX3/TiZ4b5IVV+Z150N\nEBlBBm5wH1YGj/u3HbJ3Oo7dsgfjwWDhzqGKSZuUWdCYO7bZ3h5G3CQqwjDGjG8lymJRZIEgAze4\nGV/3iA0v5M+8Pl6HYq4lNvYdj/cq3lzYqjzXhtyOJ24mEqQFAUHZW4kaY+zpZpMWqaYsgbsQZOCG\npmmu1YcLn3kdTKNcm0PZfuuNwavFXCQi+74hc8UTWisnAum6zi3l8Le9knwCAobNuKDSuEpj8C1j\nzM2Kjfs/4i/ajMvovH3J0tuA+cSGEZJHbv9WojveVhQIhH0yoI23i8YEd4OJmxtsZDXGx7TzzhOi\n+DvoC9mOYoatBq3r2pZmE2FAIKGfJIAQrq9DMXssRXlmzMslcyWZZDJuJyc23jhUYCbDNcnuCmO/\nDr2D/kaS8y4ANRkoyLV1KEbeqte4EcbVSsyNccDN4k1RcUbbtq520gUWbocY+3iS7SjmEWFAMoIM\n4K3+3a2014caKwo/t8QTqwpHxi+ycphXtlLUbTXhyiond9AXFWEAwhFkQBw77T2YEbdf2BvA7vvr\n/DmUhateb73gxGzIqq2oHrl/bcgO22yLCgKises4TqeTYTsKYBuCDAjStm3TNF3X2eu7FfoGDeHm\nUPad8rj+apu22caYizUnDza2owCWY3UJZBlf093dHc3DjHiclngZjtj3er1uYmWHMcaYl5neVlTU\n1IONcd0//buJimonkBGCDAhiF/2PPynGv6e8vw7WG7ZjhhqT8cTLcTxhbu3M4dWaCOIvFvXf1rSL\nRc/ns/va7q1puHc5sAHTJRAt1Yz45Of7xxUbV+dQdi/GVLk5pr3fjR3FbUjRNI2Qe5cfDgd/s3z5\nO+gDYhFkQDRpM+LeTdeuFoeuKJ4o7baig7UbLrBIvliUe5cD+yLIQAaEXN/9cfpWceh9K0W3hxE3\nyYkwjDF1Xfvt8Ut9JSwW5d7lwF4IMiCd5HvKm+EciosthjcxuVkVISoIiMZurHktacFiUSB3BBmQ\nLpcZ8flshLQJCwncZpr2PZU2NQZgO4IMiDP+RCt5Rnzmjq8DRBg+W185/puIfaMBrMASVuRB5sAz\nuOOrzMWixhi7dsN/JO1KUVdfOXicxaKAMgQZwEpZTH/YxIC//YN5WKtpw6Pz+Ry/vtItUnXcYlHu\nXQ5oQpABrHStDlRaMkPOJqpO0zSDLcVcoNP3vf0um2wCChBkAI9sH9tEpTfkbKK6nMAmAViHIAN4\nyy5jsRtdK/4YzUpRANEQZABvHY/H0+nU9/3lcrE3+1aJlaIAoiHIAIx5+HxvqxNcEeL2FxRLePMA\n6ECQAUzw11LeS/60CytFAcRBkAEYY0zbtoNZg9XxgfxpF1aKAogjg4X+QAT2JhrudLA3GV/xEX/w\nOlVVuW2zpWFvTQChkckAJuy14GLLtEtoRBgAQiPIAIx5XOzpF4Hea8dpFwDIHUEG8JYtoajr2hZV\nrHsRe2fRwSM7NA4AMsRdWIG36rre/XavXdcRZAAoFoWfwM5cseegCBQASkMmA9iZnXY5HA5d162e\ndgEABchkAEGwQBQACDIAAEAQrC4BAABBEGQAAIAgCDIAAEAQBBkAACAIggwAABAEQQYAAAiCIAMA\nAARBkAEAAIIgyAAAAEEQZAAAgCAIMgAAQBAEGQAAIAiCDAAAEARBBgAACIIgAwAABEGQAQAAgiDI\nAAAAQRBkAACAIAgyAABAEP8PJAI3MXEmWxsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "TCanvas *example3Dplot = new TCanvas(\"example3Dplot\",\"example 3D plot\",10,10,720,420);\n",
    "data->Draw(\"room1:room3\",\"room2>-1\",\"SURF\");\n",
    "example3Dplot->Draw();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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JYk3TjOO49RCnLTJq+fmppZ2lkI9AOBr5CISjVZTPl37xP279lFSXWGsX0yxu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\ngiIDAABkQZEBAACy+H8iGbTF1+G26QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "TCanvas *example2Dplot = new TCanvas(\"example2Dplot\",\"example 2D plot\",10,10,720,420);\n",
    "data->Draw(\"room1:room2\",\"room2>-100\",\"textcolz\");\n",
    "example2Dplot->SetGrid();\n",
    "example2Dplot->Draw();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<CENTER><h2>this is my title</h2>\n",
    "<p>...write more documentation</p></CENTER>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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GSVkiI24V2XzI5iOSjZICII2SskRG3Cqy+ZDNRyQbJWWJjLhVZPMhm49INkoKgDRKyhIZ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\nYxW8Onr6LgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "TCanvas *example1Dplot = new TCanvas(\"example1Dplot\",\"example 1D plot\",10,10,400,400);\n",
    "data->Draw(\"room1\");\n",
    "example1Dplot->SetGrid();\n",
    "example1Dplot->Draw();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernel_info": {
   "name": "root"
  },
  "kernelspec": {
   "display_name": "ROOT Prompt",
   "language": "c++",
   "name": "root"
  },
  "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"
  },
  "nteract": {
   "version": "0.3.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}