QSO_CRTS_stats_before_day-avg.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Calculating statistics for the CRTS QSO that are longer than 10 lines, that were extracted from  QSO_CRTS.tar, to ~/Desktop/SDSS/QSO_CRTS_LC_longer_10   ( code below based on qso_lc_stats.py) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt \n",
    "from os import listdir"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "u'/astro/users/suberlak/Desktop/SDSS'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pwd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "directory = 'QSO_CRTS_LC_longer_10/'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "\n",
    "lc_stat_files = np.array(listdir(dir))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# make an array for storing total timespan of obs per object, \n",
    "# as well as the total number of nights per object\n",
    "#nobs_object = np.zeros_like(lc_stat_files, dtype=float) # store how many nights per object\n",
    "timespan_obs = np.zeros_like(lc_stat_files, dtype=float) # store what was the total  timespan of observations per object\n",
    "lc_length=np.zeros_like(lc_stat_files, dtype=float)\n",
    "avg_N_day = np.zeros_like(lc_stat_files, dtype=float)\n",
    "avg_mag_ttl= np.zeros_like(lc_stat_files, dtype=float)\n",
    "avg_err_ttl= np.zeros_like(lc_stat_files, dtype=float)\n",
    "avg_mjd_diff= np.zeros_like(lc_stat_files, dtype=float)\n",
    "mean_time_betw_obs = np.zeros_like(lc_stat_files, dtype=float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Loop over the files to get all the values from each file... "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "for i in range(len(lc_stat_files)):\n",
    "    address=directory+lc_stat_files[i]  \n",
    "    data=np.loadtxt(address)     \n",
    "    lc_length[i] = sum(1 for line in open(address))\n",
    "    avg_mag_ttl[i] = np.mean(data[:,1])\n",
    "    avg_err_ttl[i] = np.mean(data[:,2])\n",
    "    \n",
    "    timespan_obs[i] = data[-1,0]-data[0,0]  # gives number of days between first and last obs\n",
    "    \n",
    "    \n",
    "    # the \n",
    "    mjd_diff = np.zeros(len(data[:,0]))\n",
    "    for j in range(len(data)-1):\n",
    "        mjd_diff[j] = data[j+1,0] - data[j,0]\n",
    "    avg_mjd_diff[i] = np.mean(mjd_diff)     # avg span between obs in MJD      \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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s4GZgUWY+2OhzJHAR1TlUplKdkf7ozNwyKlslSZIkaYe0JaBk5oHD6La0vgy1jo3AyfVl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\ngiAIgmDA8B8rfPW1bvSV8gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7b942082d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "sns.set_context('poster')\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "ax.set_ylabel('N')\n",
    "ax.set_xlabel('Number of observations per CRTS Quasar')\n",
    "ax.hist(lc_length)\n",
    "plt.savefig('QSO_CRTS_stats_lc_length.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "208.657584015\n"
     ]
    }
   ],
   "source": [
    "# What is the mean number of observation points per Quasar ? \n",
    "print(np.mean(lc_length))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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VlyRJkrQe1O4hOQ/YD9grM29oWb6oud8GuLVl+Vzgrsx8LCIWAZtGxEBmrmgrc3vLfnYb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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7b935f1090>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "ax.set_ylabel('mag')\n",
    "ax.set_xlabel('Average magnitude: CRTS Quasars')\n",
    "ax.hist(avg_mag_ttl)\n",
    "plt.savefig('QSO_CRTS_stats_avg_mag.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "19.5065692892\n",
      "19.6611904762\n"
     ]
    }
   ],
   "source": [
    "# What is the mean and median magnitude ? \n",
    "print(np.mean(avg_mag_ttl))\n",
    "print(np.median(avg_mag_ttl))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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m3t9UZy1wWIfaLUmSJGmKSg4qu9XPF1Ethj+X6pStC+oF8nOAkcx8oGm/ofp5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\nBEEQBEEQBEGXIxSVIAiCIAiCIAi6HP8P8mt/v1pvTSYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7b93975450>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "ax.set_ylabel('mag')\n",
    "ax.set_xlabel('Average original error: CRTS Quasars')\n",
    "ax.hist(avg_err_ttl)\n",
    "plt.savefig('QSO_CRTS_stats_avg_err.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.220691330566\n",
      "0.216234939759\n"
     ]
    }
   ],
   "source": [
    "# What is the median CRTS error and mean\n",
    "print np.mean(avg_err_ttl)\n",
    "print np.median(avg_err_ttl)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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JxRhAJEmSJBVjAJEkSZJUjAFEkiRJUjEGEEmSJEnFGEAkSZIkFWMAkSRJklRM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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7b937a69d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "ax.set_ylabel('mag')\n",
    "ax.set_xlabel('Observations timespan : first to last day, CRTS Quasars [years]')\n",
    "ax.hist(timespan_obs / 365.0)\n",
    "plt.savefig('QSO_CRTS_stats_obs_timespan.png')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.96120410016867786"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# What percentage of observations of quasars span the period of more than 7 years \n",
    "np.sum(timespan_obs > 7*365) / float(len(timespan_obs))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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RJEmSVBRDiiRJkqSiGFIkSZIkFcWQIkmSJKkohhRJkiRJRTGkSJIkSSqKIUWS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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7b93693810>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "ax.set_ylabel('mag')\n",
    "ax.set_xlabel('Average timespan between consecutive observations: CRTS Quasars [days]')\n",
    "ax.hist(avg_mjd_diff)\n",
    "plt.savefig('QSO_CRTS_stats_observations_cadence.png')"
   ]
  },
  {
   "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": "2.7.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}