NK_1.ipynb

{
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  {
   "cell_type": "code",
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   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import gps_particle_data\n",
    "import wget\n",
    "import os\n",
    "import numpy as np \n",
    "import time\n",
    "import json\n",
    "import sys\n",
    "import math\n",
    "from datetime import datetime, timedelta, date\n",
    "from itertools import compress\n",
    "from random import randint\n",
    "import urllib2\n",
    "import aacgmv2\n",
    "\n",
    "import matplotlib\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "====================================\n",
      "Loading data for satellite  53\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns53/ns53_061008_v1.03.ascii\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns53/ns53_061015_v1.03.ascii\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns53/ns53_061022_v1.03.ascii\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns53/ns53_061029_v1.03.ascii\n"
     ]
    }
   ],
   "source": [
    "#Script simple plots for NK nuclear tests on the following dates:\n",
    "#9 October 2006, 25 May 2009, 12 February 2013, 6 January 2016, 9 September 2016\n",
    "\n",
    "start_date = datetime(2006,10,7,0,0,0);\n",
    "end_date = datetime(2006,10,30,0,0,0);\n",
    "ms = gps_particle_data.meta_search();\n",
    "ms.load_data(start_date,end_date);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
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     "name": "stdout",
     "output_type": "stream",
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      "Burst # 6000 / 6053\n",
      "Date :  2006-11-04 17:08:00\n",
      "L-shell :  5.594766\n",
      "Burst # 6020 / 6053\n",
      "Date :  2006-11-04 18:28:00\n",
      "L-shell :  4.209228\n",
      "Burst # 6040 / 6053\n",
      "Date :  2006-11-04 19:48:00\n",
      "L-shell :  6.184149\n"
     ]
    }
   ],
   "source": [
    "output_data = ms.get_all_data_by_satellite();\n",
    "burst_events = ms.get_burst_events(output_data);\n",
    "\n",
    "eq_s = gps_particle_data.earthquake_search(start_date,end_date, min_magnitude=6,min_lat=-90,max_lat=90,min_lon=90,max_lon=180);\n",
    "\n",
    "L_shells = eq_s.get_L_shells(500.0);\n",
    "eq_datetimes = eq_s.get_datetimes();\n",
    "\n",
    "datetimes_small_del_L = [];\n",
    "eq = []\n",
    "\n",
    "for ib, be in enumerate(burst_events):\n",
    "    if(ib%20==0):\n",
    "        print 'Burst #', ib, '/', len(burst_events);\n",
    "        print 'Date : ', be.date;\n",
    "        print 'L-shell : ', be.data['L_shell'];\n",
    "   \n",
    "    # Get the datetime spread\n",
    "    pre_gap = timedelta(hours=-12);\n",
    "    post_gap = timedelta(hours=12);\n",
    "   \n",
    "    start_date = be.date+pre_gap;\n",
    "    end_date = be.date+post_gap;\n",
    "\n",
    "    # Compare with EQs\n",
    "    for i,info in enumerate(eq_s.earthquake_information):\n",
    "        # Print the details of the Sumatran earthquake\n",
    "        del_L = math.fabs(be.data['L_shell'] - L_shells[i]);\n",
    "        del_time = eq_datetimes[i] - be.data['datetime'];\n",
    "        time_test = (del_time<timedelta(days=10)) and (del_time>timedelta(days=-10));\n",
    "\n",
    "        if( (del_L<0.1) and time_test):\n",
    "            #print 'Matching EQ... '\n",
    "            #print info;\n",
    "            eq.append([be.data['datetime'], eq_datetimes[i], info[1]])\n",
    "            #print 'L_shell: ', be.data['L_shell'], L_shells[i];\n",
    "            datetimes_small_del_L.append(be.data['datetime'] - eq_datetimes[i]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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AAEAXhBcAAKALwgsAANAF4QUAAOiC8AIAAHRBeAEAALogvAAAAF0QXgAAgC4ILwAAQBeE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\nhBcAAKALwgsAANAF4QUAAOjC/w+9AMF1wH6N5wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ffa62a022d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "delta_times_seconds = [];\n",
    "for tdelta in datetimes_small_del_L:\n",
    "    delta_times_seconds.append(tdelta.seconds);\n",
    "#print delta_times_seconds\n",
    "fig = plt.figure(figsize=(8, 6), dpi=120)\n",
    "ax = fig.add_subplot(111)\n",
    "plt.hist(delta_times_seconds)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "====================================\n",
      "Loading data for satellite  53\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns53/ns53_090524_v1.03.ascii\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns53/ns53_090531_v1.03.ascii\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns53/ns53_090607_v1.03.ascii\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns53/ns53_090614_v1.03.ascii\n"
     ]
    }
   ],
   "source": [
    "#25 May 2009\n",
    "start_date = datetime(2009,5,23,0,0,0);\n",
    "end_date = datetime(2009,6,14,0,0,0);\n",
    "ms = gps_particle_data.meta_search();\n",
    "ms.load_data(start_date,end_date);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Burst # 0 / 1571\n",
      "Date :  2009-05-24 01:08:00\n",
      "L-shell :  6.257951\n",
      "Burst # 20 / 1571\n",
      "Date :  2009-05-24 03:24:00\n",
      "L-shell :  4.859455\n",
      "Burst # 40 / 1571\n",
      "Date :  2009-05-24 08:32:00\n",
      "L-shell :  4.557583\n",
      "Burst # 60 / 1571\n",
      "Date :  2009-05-24 10:36:00\n",
      "L-shell :  6.338222\n",
      "Burst # 80 / 1571\n",
      "Date :  2009-05-24 15:48:00\n",
      "L-shell :  4.693186\n",
      "Burst # 100 / 1571\n",
      "Date :  2009-05-24 19:16:00\n",
      "L-shell :  5.415369\n",
      "Burst # 120 / 1571\n",
      "Date :  2009-05-24 21:48:00\n",
      "L-shell :  5.89078\n",
      "Burst # 140 / 1571\n",
      "Date :  2009-05-25 02:00:00\n",
      "L-shell :  4.441067\n",
      "Burst # 160 / 1571\n",
      "Date :  2009-05-25 07:44:00\n",
      "L-shell :  6.004877\n",
      "Burst # 180 / 1571\n",
      "Date :  2009-05-25 09:52:00\n",
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      "Date :  2009-06-12 06:36:00\n",
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      "Date :  2009-06-12 23:52:00\n",
      "L-shell :  5.856372\n",
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      "Date :  2009-06-13 09:00:00\n",
      "L-shell :  5.724199\n",
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      "Date :  2009-06-13 17:44:00\n",
      "L-shell :  5.967232\n",
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      "Date :  2009-06-14 06:28:00\n",
      "L-shell :  5.74331\n"
     ]
    }
   ],
   "source": [
    "output_data = ms.get_all_data_by_satellite();\n",
    "burst_events = ms.get_burst_events(output_data);\n",
    "\n",
    "eq_s = gps_particle_data.earthquake_search(start_date,end_date, min_magnitude=6,min_lat=-90,max_lat=90,min_lon=90,max_lon=180);\n",
    "\n",
    "L_shells = eq_s.get_L_shells(500.0);\n",
    "eq_datetimes = eq_s.get_datetimes();\n",
    "\n",
    "datetimes_small_del_L = [];\n",
    "eq = []\n",
    "\n",
    "for ib, be in enumerate(burst_events):\n",
    "    if(ib%20==0):\n",
    "        print 'Burst #', ib, '/', len(burst_events);\n",
    "        print 'Date : ', be.date;\n",
    "        print 'L-shell : ', be.data['L_shell'];\n",
    "   \n",
    "    # Get the datetime spread\n",
    "    pre_gap = timedelta(hours=-12);\n",
    "    post_gap = timedelta(hours=12);\n",
    "   \n",
    "    start_date = be.date+pre_gap;\n",
    "    end_date = be.date+post_gap;\n",
    "\n",
    "    # Compare with EQs\n",
    "    for i,info in enumerate(eq_s.earthquake_information):\n",
    "        # Print the details of the Sumatran earthquake\n",
    "        del_L = math.fabs(be.data['L_shell'] - L_shells[i]);\n",
    "        del_time = eq_datetimes[i] - be.data['datetime'];\n",
    "        time_test = (del_time<timedelta(days=10)) and (del_time>timedelta(days=-10));\n",
    "\n",
    "        if( (del_L<0.1) and time_test):\n",
    "            #print 'Matching EQ... '\n",
    "            #print info;\n",
    "            eq.append([be.data['datetime'], eq_datetimes[i], info[1]])\n",
    "            #print 'L_shell: ', be.data['L_shell'], L_shells[i];\n",
    "            datetimes_small_del_L.append(be.data['datetime'] - eq_datetimes[i]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ryQ0rjC+NPWiNuZetMffK6Xaz48u3/a61FllVhye5/7LhI9eaBwAALIZ5h9AhSe5cYfyO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\nI4QAAIB2hBAAANCOEAIAANr5/9gIGVoL/uxwAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ffa62b1a890>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "delta_times_seconds = [];\n",
    "for tdelta in datetimes_small_del_L:\n",
    "    delta_times_seconds.append(tdelta.seconds);\n",
    "#print delta_times_seconds\n",
    "fig = plt.figure(figsize=(8, 6), dpi=120)\n",
    "ax = fig.add_subplot(111)\n",
    "plt.hist(delta_times_seconds)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "====================================\n",
      "Loading data for satellite  53\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns53/ns53_130210_v1.03.ascii\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns53/ns53_130217_v1.03.ascii\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns53/ns53_130224_v1.03.ascii\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns53/ns53_130303_v1.03.ascii\n"
     ]
    }
   ],
   "source": [
    "#12 Feb 2013\n",
    "start_date = datetime(2013,2,10,0,0,0);\n",
    "end_date = datetime(2013,3,3,0,0,0);\n",
    "ms = gps_particle_data.meta_search();\n",
    "ms.load_data(start_date,end_date);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "Date :  2013-03-09 17:58:00\n",
      "L-shell :  6.363461\n",
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      "Date :  2013-03-09 20:54:00\n",
      "L-shell :  5.129294\n",
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      "Date :  2013-03-09 22:14:00\n",
      "L-shell :  4.163171\n",
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      "Date :  2013-03-09 23:34:00\n",
      "L-shell :  6.798836\n"
     ]
    }
   ],
   "source": [
    "output_data = ms.get_all_data_by_satellite();\n",
    "burst_events = ms.get_burst_events(output_data);\n",
    "\n",
    "eq_s = gps_particle_data.earthquake_search(start_date,end_date, min_magnitude=6,min_lat=-90,max_lat=90,min_lon=90,max_lon=180);\n",
    "\n",
    "L_shells = eq_s.get_L_shells(500.0);\n",
    "eq_datetimes = eq_s.get_datetimes();\n",
    "\n",
    "datetimes_small_del_L = [];\n",
    "eq = []\n",
    "\n",
    "for ib, be in enumerate(burst_events):\n",
    "    if(ib%20==0):\n",
    "        print 'Burst #', ib, '/', len(burst_events);\n",
    "        print 'Date : ', be.date;\n",
    "        print 'L-shell : ', be.data['L_shell'];\n",
    "   \n",
    "    # Get the datetime spread\n",
    "    pre_gap = timedelta(hours=-12);\n",
    "    post_gap = timedelta(hours=12);\n",
    "   \n",
    "    start_date = be.date+pre_gap;\n",
    "    end_date = be.date+post_gap;\n",
    "\n",
    "    # Compare with EQs\n",
    "    for i,info in enumerate(eq_s.earthquake_information):\n",
    "        # Print the details of the Sumatran earthquake\n",
    "        del_L = math.fabs(be.data['L_shell'] - L_shells[i]);\n",
    "        del_time = eq_datetimes[i] - be.data['datetime'];\n",
    "        time_test = (del_time<timedelta(days=10)) and (del_time>timedelta(days=-10));\n",
    "\n",
    "        if( (del_L<0.1) and time_test):\n",
    "            #print 'Matching EQ... '\n",
    "            #print info;\n",
    "            eq.append([be.data['datetime'], eq_datetimes[i], info[1]])\n",
    "            #print 'L_shell: ', be.data['L_shell'], L_shells[i];\n",
    "            datetimes_small_del_L.append(be.data['datetime'] - eq_datetimes[i]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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qUVUvPsi+p077fX7a981VdczSswYAAHaFjTxD8vAk5yQ5NclfHGynqnp0kj9JcnKSs5O8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\nI0gAAIA2/x9MX8vXP87b0wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ffa6054a310>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "delta_times_seconds = [];\n",
    "for tdelta in datetimes_small_del_L:\n",
    "    delta_times_seconds.append(tdelta.seconds);\n",
    "#print delta_times_seconds\n",
    "fig = plt.figure(figsize=(8, 6), dpi=120)\n",
    "ax = fig.add_subplot(111)\n",
    "plt.hist(delta_times_seconds)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "====================================\n",
      "Loading data for satellite  53\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns53/ns53_151227_v1.03.ascii\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns53/ns53_160103_v1.03.ascii\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns53/ns53_160110_v1.03.ascii\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns53/ns53_160117_v1.03.ascii\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns53/ns53_160124_v1.03.ascii\n"
     ]
    }
   ],
   "source": [
    "#6 Jan 2016\n",
    "start_date = datetime(2015,12,25,0,0,0);\n",
    "end_date = datetime(2016,1,25,0,0,0);\n",
    "ms = gps_particle_data.meta_search();\n",
    "ms.load_data(start_date,end_date);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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      "L-shell :  4.498708\n"
     ]
    }
   ],
   "source": [
    "output_data = ms.get_all_data_by_satellite();\n",
    "burst_events = ms.get_burst_events(output_data);\n",
    "\n",
    "eq_s = gps_particle_data.earthquake_search(start_date,end_date, min_magnitude=6,min_lat=-90,max_lat=90,min_lon=90,max_lon=180);\n",
    "\n",
    "L_shells = eq_s.get_L_shells(500.0);\n",
    "eq_datetimes = eq_s.get_datetimes();\n",
    "\n",
    "datetimes_small_del_L = [];\n",
    "eq = []\n",
    "\n",
    "for ib, be in enumerate(burst_events):\n",
    "    if(ib%20==0):\n",
    "        print 'Burst #', ib, '/', len(burst_events);\n",
    "        print 'Date : ', be.date;\n",
    "        print 'L-shell : ', be.data['L_shell'];\n",
    "   \n",
    "    # Get the datetime spread\n",
    "    pre_gap = timedelta(hours=-12);\n",
    "    post_gap = timedelta(hours=12);\n",
    "   \n",
    "    start_date = be.date+pre_gap;\n",
    "    end_date = be.date+post_gap;\n",
    "\n",
    "    # Compare with EQs\n",
    "    for i,info in enumerate(eq_s.earthquake_information):\n",
    "        # Print the details of the Sumatran earthquake\n",
    "        del_L = math.fabs(be.data['L_shell'] - L_shells[i]);\n",
    "        del_time = eq_datetimes[i] - be.data['datetime'];\n",
    "        time_test = (del_time<timedelta(days=10)) and (del_time>timedelta(days=-10));\n",
    "\n",
    "        if( (del_L<0.1) and time_test):\n",
    "            #print 'Matching EQ... '\n",
    "            #print info;\n",
    "            eq.append([be.data['datetime'], eq_datetimes[i], info[1]])\n",
    "            #print 'L_shell: ', be.data['L_shell'], L_shells[i];\n",
    "            datetimes_small_del_L.append(be.data['datetime'] - eq_datetimes[i]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
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AUlV3rKpXVdXnquorVfWxqjqtqm6+jPEBAICtaduiB6iqY5K8J8lVSZ6X5Mok90xyRpLv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\nBzHTgAWi8o0NAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ffa5be05090>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "delta_times_seconds = [];\n",
    "for tdelta in datetimes_small_del_L:\n",
    "    delta_times_seconds.append(tdelta.seconds);\n",
    "#print delta_times_seconds\n",
    "fig = plt.figure(figsize=(8, 6), dpi=120)\n",
    "ax = fig.add_subplot(111)\n",
    "plt.hist(delta_times_seconds)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "====================================\n",
      "Loading data for satellite  53\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns53/ns53_160904_v1.03.ascii\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns53/ns53_160911_v1.03.ascii\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns53/ns53_160918_v1.03.ascii\n",
      "File : https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/data/ns53/ns53_160925_v1.03.ascii\n"
     ]
    }
   ],
   "source": [
    "#9 Sept Jan 2016\n",
    "start_date = datetime(2016,9,4,0,0,0);\n",
    "end_date = datetime(2016,9,28,0,0,0);\n",
    "ms = gps_particle_data.meta_search();\n",
    "ms.load_data(start_date,end_date);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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   ],
   "source": [
    "output_data = ms.get_all_data_by_satellite();\n",
    "burst_events = ms.get_burst_events(output_data);\n",
    "\n",
    "eq_s = gps_particle_data.earthquake_search(start_date,end_date, min_magnitude=6,min_lat=-90,max_lat=90,min_lon=90,max_lon=180);\n",
    "\n",
    "L_shells = eq_s.get_L_shells(500.0);\n",
    "eq_datetimes = eq_s.get_datetimes();\n",
    "\n",
    "datetimes_small_del_L = [];\n",
    "eq = []\n",
    "\n",
    "for ib, be in enumerate(burst_events):\n",
    "    if(ib%20==0):\n",
    "        print 'Burst #', ib, '/', len(burst_events);\n",
    "        print 'Date : ', be.date;\n",
    "        print 'L-shell : ', be.data['L_shell'];\n",
    "   \n",
    "    # Get the datetime spread\n",
    "    pre_gap = timedelta(hours=-12);\n",
    "    post_gap = timedelta(hours=12);\n",
    "   \n",
    "    start_date = be.date+pre_gap;\n",
    "    end_date = be.date+post_gap;\n",
    "\n",
    "    # Compare with EQs\n",
    "    for i,info in enumerate(eq_s.earthquake_information):\n",
    "        # Print the details of the Sumatran earthquake\n",
    "        del_L = math.fabs(be.data['L_shell'] - L_shells[i]);\n",
    "        del_time = eq_datetimes[i] - be.data['datetime'];\n",
    "        time_test = (del_time<timedelta(days=10)) and (del_time>timedelta(days=-10));\n",
    "\n",
    "        if( (del_L<0.1) and time_test):\n",
    "            #print 'Matching EQ... '\n",
    "            #print info;\n",
    "            eq.append([be.data['datetime'], eq_datetimes[i], info[1]])\n",
    "            #print 'L_shell: ', be.data['L_shell'], L_shells[i];\n",
    "            datetimes_small_del_L.append(be.data['datetime'] - eq_datetimes[i]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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1yaq6o6purKqzqmqflc4dAADYMazmHZoDkpye5NFJ/mahTlV1SJKPJ3lkklOT/EGS45N8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\npUh7AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ffa5e21ab90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "delta_times_seconds = [];\n",
    "for tdelta in datetimes_small_del_L:\n",
    "    delta_times_seconds.append(tdelta.seconds);\n",
    "#print delta_times_seconds\n",
    "fig = plt.figure(figsize=(8, 6), dpi=120)\n",
    "ax = fig.add_subplot(111)\n",
    "plt.hist(delta_times_seconds)\n",
    "plt.show()"
   ]
  }
 ],
 "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": 2
}