{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Event file Header information ##\n",
    "\n",
    "Header information is stored in a class called Head,\n",
    "in a way that derives directly from the ascii (.evt) event files. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "start_run:  1\n",
      "PDF: 4      58\n",
      "XSecFile:  \n",
      "aashowerfit_detector: /pbs/throng/km3net/detectors/KM3NeT_-00000001_20171212.detx\n",
      "can:  0 1027 888.4\n",
      "can_user: 0.00 1027.00  888.40\n",
      "coord_origin:  0 0 0 \n",
      "cut_in:  0 0 0 0\n",
      "cut_nu:  100 1e+08 -1 1\n",
      "cut_primary:  0 0 0 0\n",
      "cut_seamuon:  0 0 0 0\n",
      "decay: doesnt happen\n",
      "detector:  NOT\n",
      "drawing: Volume\n",
      "genhencut:  2000 0\n",
      "genvol:  0 1027 888.4 2.649e+09 100000\n",
      "kcut: 2\n",
      "livetime:  0 0\n",
      "model: 1       2       0       1      12\n",
      "muon_desc_file:  \n",
      "ngen: 0.1000E+06\n",
      "norma:  0 0\n",
      "nuflux: 0       3       0 0.500E+00 0.000E+00 0.100E+01 0.300E+01\n",
      "physics:  GENHEN 7.2-220514 180825 0833\n",
      "seed: GENHEN 3  347108279         0         0\n",
      "simul:  JSirene 11012 11/15/18 16:25:55\n",
      "sourcemode: diffuse\n",
      "spectrum:  -1.4\n",
      "target:  isoscalar\n",
      "usedetfile: false\n",
      "xlat_user: 0.63297\n",
      "xparam: OFF\n",
      "zed_user: 0.00 3450.00\n",
      "end_event:\n",
      "\n",
      "EventFile io / wall time = 0.698964 / 60.4094 (1.15705 % spent on io.)\n"
     ]
    }
   ],
   "source": [
    "import ROOT\n",
    "import aa\n",
    "from math import *\n",
    "f = ROOT.EventFile(\"../../data/mc5.1.numuCC.nohits.aa.root\")\n",
    "\n",
    "print (f.header)\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The for statement loops over all the events in the file. EventFile::index counts the events, which is usefull since we only want to process a few events here. \n",
    "Of course, we can do much more complicated things in the event loop.\n",
    "\n",
    "\n",
    "The following exmple makes a plot of the energy of the neutrino, for all events, for an E^-2 neutrino spectrum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "h = ROOT.TH1D(\"h\",\"h\",28,1,8)\n",
    "\n",
    "for event in f :\n",
    "         \n",
    "    h.Fill( log10(event.mc_trks[0].E) ,event.w[1] * event.mc_trks[0].E**-2 )\n",
    "        \n",
    "h.Draw()\n",
    "ROOT.gPad.Draw()        \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}