nexrad_display_notebook_v1.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# This notebook will display any NEXRAD site Reflectivity file from the Level II data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pyart\n",
    "\n",
    "import os\n",
    "import cartopy.crs as ccrs\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--------------------------------------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "dadash='-------------------------------------'\n",
    "print(dadash+dadash)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [],
   "source": [
    "list_of_lats = np.arange(0.0,90.0,1.0)\n",
    "#\n",
    "list_of_lons =np.arange(-179.0,181.0,1.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'PHMO'"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ALL_call_signs= \\\n",
    "[\"PGUA\",\"RKSG\",\"RKJK\",\"RODN\",\"KABR\",\"KENX\",\"KABX\",\"KFDR\",\"KAMA\",\"PAHG\", \\\n",
    "\"KEWX\",\"KBBX\",\"PABC\",\"KBLX\",\"KBGM\",\"KBMX\",\"KBIS\",\"KCBX\",\"KBOX\",\"KBRO\", \\\n",
    "\"KBUF\",\"KCXX\",\"KFDX\",\"KICX\",\"KCLX\",\"KRLX\",\"KCYS\",\"KLOT\",\"KILN\",\"KCLE\", \\\n",
    "\"KCAE\",\"KGWX\",\"KCRP\",\"KFWS\",\"KDVN\",\"KFTG\",\"KDMX\",\"KDTX\",\"KDDC\",\"KDOX\", \\\n",
    "\"KDLH\",\"KDYX\",\"KEYX\",\"KEVX\",\"KEPZ\",\"KLRX\",\"KBHX\",\"PAPD\",\"KFSX\",\"KHPX\", \\\n",
    "\"KGRK\",\"KPOE\",\"KEOX\",\"KSRX\",\"KIWX\",\"KAPX\",\"KGGW\",\"KGLD\",\"KMVX\",\"KGJX\", \\\n",
    "\"KGRR\",\"KTFX\",\"KGRB\",\"KGSP\",\"KRMX\",\"KUEX\",\"KHDX\",\"KCBW\",\"KHGX\",\"KHTX\", \\\n",
    "\"KIND\",\"KJKL\",\"KJAN\",\"KJAX\",\"PHKN\",\"KEAX\",\"KBYX\",\"PAKC\",\"KMRX\",\"KARX\", \\\n",
    "\"LPLA\",\"KLCH\",\"KESX\",\"KDFX\",\"KILX\",\"KLZK\",\"KVTX\",\"KLVX\",\"KLBB\",\"KMQT\", \\\n",
    "\"KMXX\",\"KMAX\",\"KMLB\",\"KNQA\",\"KAMX\",\"PAIH\",\"KMAF\",\"KMKX\",\"KMPX\",\"KMBX\", \\\n",
    "\"KMSX\",\"KMOB\",\"PHMO\",\"KVAX\",\"KMHX\",\"KOHX\",\"KLIX\",\"KOKX\",\"PAEC\",\"KAKQ\", \\\n",
    "\"KLNX\",\"KTLX\",\"KOAX\",\"KPAH\",\"KPDT\",\"KDIX\",\"KIWA\",\"KPBZ\",\"KSFX\",\"KGYX\", \\\n",
    "\"KRTX\",\"KPUX\",\"KRAX\",\"KUDX\",\"KRGX\",\"KRIW\",\"KFCX\",\"KJGX\",\"KDAX\",\"KLSX\", \\\n",
    "\"KMTX\",\"KSJT\",\"KNKX\",\"KMUX\",\"KHNX\",\"TJUA\",\"KSOX\",\"KATX\",\"KSHV\",\"KFSD\", \\\n",
    "\"PACG\",\"PHKI\",\"PHWA\",\"KOTX\",\"KSGF\",\"KCCX\",\"KLWX\",\"KTLH\",\"KTBW\",\"KTWX\", \\\n",
    "\"KEMX\",\"KINX\",\"KVNX\",\"KVBX\",\"KICT\",\"KLTX\",\"KFFC\",\"KYUX\",\"KLGX\",\"PHMO\"]\n",
    "#\n",
    "CALL_SIGN=ALL_call_signs[-1]\n",
    "CALL_SIGN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Molokai HI'"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dict_call_signs={\"KABR\":\"Aberdeen_SD\", \"KABX\":\"Albuquerque_NM\", \"KAKQ\":\"Norfolk-VA\", \\\n",
    "\"KAMA\":\"Amarillo_TX\", \"KBBX\":\"Beale-AFB_CA\", \\\n",
    "\"KAMX\":\"Miami-FL\", \"KAPX\":\"Gaylord_MI\", \"KARX\":\"La-Crosse_WI\", \"KATX\":\"Seattle-Tacoma_WA\", \\\n",
    "\"KBGM\":\"Binghamton_NY\", \"KBHX\":\"Eureka_CA\", \"KBIS\":\"Bismarck_ND\", \"KBLX\":\"Billings_MT\", \\\n",
    "\"KBMX\":\"Birmingham_AL\", \"KCAE\":\"Columbia_SC\", \\\n",
    "\"KBOX\":\"Boston-MA\", \"KBRO\":\"Brownsville-TX\", \"KBUF\":\"Buffalo_NY\", \"KBYX\":\"Key-West-FL\", \\\n",
    "\"KCBW\":\"Houlton-Maine\", \"KCBX\":\"Boise_ID\", \"KCCX\":\"State-College_PA\", \"KCLE\":\"Cleveland_OH\", \\\n",
    "\"KCLX\":\"Charleston-SC\", \"KDDC\":\"Dodge-City_KS\", \\\n",
    "\"KCRP\":\"Corpus-Christi-TX\", \"KCXX\":\"Burlington_VT\", \"KCYS\":\"Cheyenne_WY\", \"KDAX\":\"Sacramento_CA\", \\\n",
    "\"KDFX\":\"Laughlin-AFB_TX\", \"KDIX\":\"Philadelphia-PA\", \"KDLH\":\"Duluth_MN\", \"KDMX\":\"Des-Moines_IA\", \\\n",
    "\"KDOX\":\"Dover-AFB-DE\", \"KEMX\":\"Tucson_AZ\", \\\n",
    "\"KDTX\":\"Detroit_MI\", \"KDVN\":\"Davenport_IA\", \"KDYX\":\"Dyess-AFB_TX\", \"KEAX\":\"Kansas-City_MO\", \\\n",
    "\"KENX\":\"Albany_NY\", \"KEOX\":\"Fort-Rucker_AL\", \"KEPZ\":\"El-Paso_TX\", \"KESX\":\"Las-Vegas_NV\", \\\n",
    "\"KEVX\":\"Eglin-AFB-FL\", \"KFDX\":\"Cannon-AFB_NM\", \\\n",
    "\"KEWX\":\"Austin-San-Antonio_TX\", \"KEYX\":\"Edwards-AFB_CA\", \"KFCX\":\"Roanoke_VA\", \"KFDR\":\"Altus-AFB_OK\", \\\n",
    "\"KFFC\":\"Atlanta_GA\", \"KFSD\":\"Sioux-Falls_SD\", \"KFSX\":\"Flagstaff_AZ\",\"KFTG\":\"Denver_CO\", \\\n",
    "\"KFWS\":\"Dallas-Ft.Worth_TX\", \"KGRK\":\"Fort-Hood_TX\", \\\n",
    "\"KGGW\":\"Glasgow_MT\", \"KGJX\":\"Grand-Junction_Co\", \"KGLD\":\"Goodland_KS\", \"KGRB\":\"Green-Bay_WI\", \\\n",
    "\"KGRR\":\"Grand-Rapids_MI\", \"KGSP\":\"Greer_SC\", \"KGWX\":\"Columbus-AFB,_ MS\", \"KGYX\":\"Portland-Maine\", \\\n",
    "\"KHDX\":\"Holloman-AFB_NM\", \"KHTX\":\"Huntsville_AL\",  \\\n",
    "\"KHGX\":\"Houston-Galveston-TX\", \"KHNX\":\"San-Joaquin-Valley_CA\", \"KHPX\":\"Fort-Campbell_KY\", \\\n",
    "\"KICT\":\"Wichita_KS\", \"KICX\":\"Cedar-City_UT\", \"KILN\":\"Cincinnati_OH\", \"KILX\":\"Lincoln_IL\", \\\n",
    "\"KIND\":\"Indianapolis_IN\", \"KJAX\":\"Jacksonville-FL\", \\\n",
    "\"KINX\":\"Tulsa_OK\", \"KIWA\":\"Phoenix_AZ\", \"KIWX\":\"Fort-Wayne_IN\", \"KJAN\":\"Jackson_MS\", \\\n",
    "\"KJGX\":\"Robins-AFB_GA\", \"KJKL\":\"Jackson_KY\", \"KLBB\":\"Lubbock_TX\", \"KLCH\":\"Lake-Charles-LA\", \\\n",
    "\"KLIX\":\"New-Orleans-LA\", \"KLTX\":\"Wilmington-NC\", \\\n",
    "\"KLNX\":\"North-Platte_NE\", \"KLOT\":\"Chicago_IL\", \"KLRX\":\"Elko_NV\", \"KLSX\":\"Saint-Louis_ MO\", \\\n",
    "\"KLVX\":\"Louisville_KY\", \"KLWX\":\"Sterling-VA\", \"KLZK\":\"Little-Rock_AR\", \"KMAF\":\"Midland-Odessa_TX\", \\\n",
    "\"KMAX\":\"Medford_OR\", \"KMOB\":\"Mobile-AL\", \\\n",
    "\"KMBX\":\"Minot-AFB_ND\", \"KMHX\":\"Morehead-City-NC\", \"KMKX\":\"Milwaukee_WI\", \"KMLB\":\"Melbourne-FL\", \\\n",
    "\"KMPX\":\"Minneapolis-St.Paul_MN\", \"KMQT\":\"Marquette_MI\", \"KMRX\":\"Knoxville-Tri-Cities_TN\", \\\n",
    "\"KMSX\":\"Missoula_MT\", \"KNKX\":\"San-Diego-CA\", \\\n",
    "\"KMTX\":\"Salt-Lake-City_UT\", \"KMUX\":\"San-Francisco_CA\", \"KMVX\":\"Grand-Forks_ND\", \"KMXX\":\"Maxwell-AFB_AL\", \\\n",
    "\"KNQA\":\"Memphis_TN\", \"KOAX\":\"Omaha_NE\", \"KOHX\":\"Nashville_TN\", \"KOKX\":\"New-York-City-NY\", \\\n",
    "\"KOTX\":\"Spokane_WA\", \"KPAH\":\"Paducah_KY\", \\\n",
    "\"KPBZ\":\"Pittsburgh_PA\", \"KPDT\":\"Pendleton_OR\", \"KPOE\":\"Fort-Polk_LA\", \"KPUX\":\"Pueblo_CO\", \\\n",
    "\"KRAX\":\"Raleigh-Durham_NC\", \"KRGX\":\"Reno-NV\", \"KSFX\":\"Pocatello-Idaho-Falls_ID\", \\\n",
    "\"KRIW\":\"Riverton_WY\", \"KRLX\":\"Charleston_WV\", \"KRMX\":\"Griffiss-AFB_NY\", \"KRTX\":\"Portland_OR\", \\\n",
    "\"KSGF\":\"Springfield_MO\", \"KSHV\":\"Shreveport_LA\", \"KSJT\":\"San-Angelo_TX\", \\\n",
    "\"KSOX\":\"Santa-Ana_Mountains_CA\", \"KTLX\":\"Oklahoma-City_OK\", \\\n",
    "\"KSRX\":\"Fort-Smith_AR\", \"KTBW\":\"Tampa-FL\", \"KTFX\":\"Great-Falls_MT\", \"KTLH\":\"Tallahassee-FL\", \\\n",
    "\"KTWX\":\"Topeka_KS\", \"KUDX\":\"Rapid-City_SD\", \"KUEX\":\"Hastings_NE\", \"KVAX\":\"Moody-AFB_GA\", \\\n",
    "\"KVBX\":\"Vandenberg-AFB_CA\", \"PABC\":\"Bethel_AK\", \\\n",
    "\"KVNX\":\"Vance-AFB_OK\", \"KVTX\":\"Los_Angeles_CA\", \"KYUX\":\"Yuma_AZ\", \"LPLA\":\"Lajes-AB_Azores\", \\\n",
    "\"PACG\":\"Sitka_AK\", \"PAEC\":\"Nome_AK\", \"PAHG\":\"Anchorage_AK\", \"PAIH\":\"Middleton-Island_AK\",\n",
    "\"PAKC\":\"King-Salmon_AK\", \"PHKM\":'Kamuela-Kohala-HI', \\\n",
    "\"PAPD\":\"Fairbanks_AK\", \"PGUA\":\"Anderson-AFB-Guam\", \"PHKI\":\"South-Kauai-HI\", \\\n",
    "\"PHKN\":\"Kamuela_HI\", \"PHMO\":\"Molokai-HI\", \"PHWA\":\"South-Shore-HI\", \"RKJK\":\"Kunsan-AB-Korea\", \\\n",
    "\"RKSG\":\"Camp-Humphreys-Korea\", \"RODN\":\"Kadena_Okinawa\", \"TJUA\":\"San-Juan-Puerto-Rico\", \\\n",
    "\"KLGX\":\"Langley-Hill_WA\", \"PHMO\":'Molokai HI'}\n",
    "\n",
    "PlaceName = dict_call_signs[CALL_SIGN]\n",
    "PlaceName"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "\n",
    "\n",
    "#CALL_SIGN=\"PHMO\"\n",
    "data_dir='/u/curr/etc/dynamic/obs_data/met/cqc/radar/'+CALL_SIGN\n",
    "\n",
    "data_dir='/satdat/curr/m4b/radar/nexrad/'+CALL_SIGN+'/'\n",
    "\n",
    "\n",
    "list_of_files= []\n",
    "list_of_files=os.listdir(data_dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Next \n",
    "list_of_files.sort()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [],
   "source": [
    "derivedatafrom =list_of_files[-1]\n",
    "#derivedatafrom =list_of_files[15]\n",
    "\n",
    "#derivedatafrom ='20161223135600.compress.raw'\n",
    "#\n",
    "#\n",
    "filename = data_dir+derivedatafrom\n",
    "#filename"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SUCCESS: Read in Level II RADAR  datafile: /satdat/curr/m4b/radar/nexrad/PHMO/20210413225650.compress.raw\n"
     ]
    }
   ],
   "source": [
    "read_radar_ok = 1\n",
    "\n",
    "#\n",
    "\n",
    "try:\n",
    "    radar = pyart.io.read(filename)\n",
    "except:\n",
    "    read_radar_ok = 0\n",
    "    print(\"WARNING: Error reading LevelII  datafile: \"+filename)\n",
    "    #=================================================================#\n",
    "\n",
    "if (read_radar_ok  == 1):\n",
    "    print(\"SUCCESS: Read in Level II RADAR  datafile: \"+filename)\n",
    "    #\n",
    "    #====================================="
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [],
   "source": [
    "SITE_latitude = radar.latitude['data'][0]\n",
    "\n",
    "SITE_longitude  = radar.longitude['data'][0]\n",
    "\n",
    "minlon = SITE_longitude - 4.5\n",
    "maxlon = SITE_longitude + 4.5\n",
    "#\n",
    "minlat = SITE_latitude - 3.5\n",
    "maxlat = SITE_latitude + 3.5\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "List of lats for grid plotting:\n",
      "[18.0, 19.0, 20.0, 21.0, 22.0, 23.0, 24.0]\n"
     ]
    }
   ],
   "source": [
    "local_lats=[]\n",
    "local_lons=[]\n",
    "\n",
    "for item in list_of_lats:\n",
    "    #\n",
    "    if (item > mnnlat ) & (item < mxxlat):\n",
    "        local_lats.append(item)\n",
    "        #---------------------------------\n",
    "        # END OF IF LOOP\n",
    "        #---------------------------------\n",
    "    #---------------------------------\n",
    "    # END OF FOR LOOP\n",
    "    #---------------------------------\n",
    "\n",
    "print('List of lats for grid plotting:')\n",
    "print(local_lats)\n",
    "\n",
    "for item in list_of_lons:\n",
    "    #\n",
    "    if (item > mnnlon ) & (item < mxxlon):\n",
    "        local_lons.append(item)\n",
    "        #---------------------------------\n",
    "        # END OF IF LOOP\n",
    "        #---------------------------------\n",
    "    #---------------------------------\n",
    "    # END OF FOR LOOP\n",
    "    #---------------------------------\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "List of lons for grid plotting:\n",
      "[-161.0, -160.0, -159.0, -158.0, -157.0, -156.0, -155.0, -154.0, -153.0]\n"
     ]
    }
   ],
   "source": [
    "print('List of lons for grid plotting:')\n",
    "print(local_lons)\n",
    "\n",
    "CallSign =CALL_SIGN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [],
   "source": [
    "#PlaceName = 'Molokai HI'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The year-month-day     is: d20210413\n",
      "The hour-minute-second is: s225650\n",
      "The year-month-day -2-     is: 2021-04-13\n",
      "The hour-minute-second -2- is: 22:56:50\n",
      "Formatted Date-time String:\n",
      "2021-04-13---22:56:50 UTC\n"
     ]
    }
   ],
   "source": [
    "yymmdd='d'+derivedatafrom[0:8]\n",
    "hhmmss='s'+derivedatafrom[8:14]\n",
    "#\n",
    "print('The year-month-day     is: '+yymmdd)\n",
    "print('The hour-minute-second is: '+hhmmss)\n",
    "#\n",
    "#\n",
    "#yyyy_mm_dd = derivedatafrom[0:4]+'_'+derivedatafrom[4:2]+'_'+derivedatafrom[6:2]\n",
    "yyyy_mm_dd = derivedatafrom[0:4]+'-'+derivedatafrom[4:6]+'-'+derivedatafrom[6:8]\n",
    "#\n",
    "#hh_MM_sec  = derivedatafrom[8:2]+':'+derivedatafrom[10:2]+':'+derivedatafrom[12:2]\n",
    "hh_MM_sec  = derivedatafrom[8:10]+':'+derivedatafrom[10:12]+':'+derivedatafrom[12:14]\n",
    "#\n",
    "print('The year-month-day -2-     is: '+yyyy_mm_dd)\n",
    "#\n",
    "print('The hour-minute-second -2- is: '+hh_MM_sec)\n",
    "#\n",
    "ymdhms_formatted = yyyy_mm_dd+'---'+hh_MM_sec+' UTC'\n",
    "#\n",
    "print('Formatted Date-time String:')\n",
    "\n",
    "print(ymdhms_formatted)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [],
   "source": [
    "display = pyart.graph.RadarMapDisplay(radar)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [],
   "source": [
    "GIS_shapefile = '/satdat/m4b/NEXRAD/python/shape/cb_2015_us_state_500k'\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [],
   "source": [
    "projection = ccrs.LambertConformal(central_latitude=radar.latitude['data'][0], \\\n",
    "    central_longitude=radar.longitude['data'][0])\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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bLW6oH8LQBCK0rjugu7yoFtIxrPc8DDgjat2Hw4ntvjtWeePFHQLsUMObZIdQY4GaV9kl+M7C8JFjl8cwhBPmbywPtTFJ8l8NwZj8Z4dBwHptu97BWgytKcJ6HHotjgDIPJsxPuoI0YtYN2CYdyJUJEjrLaC/6bf9LAyBEOFpDG1giKqWYDiyi+Wqej2Gk7h+FmFVrKqJVkGzYrej1nrdeuCJKAFZoKq32kgnUdz1QN84i/LYKeffgLNE5NsYztni+ViKldY/MVxqj8NYw6IjwiPRf7We+O6ro8uxCRhi+omKMBSjXydR2R16CY4AyDzPApeIyB7m0ndXR51fBPxERLzm6linx0tIVQMYy17egdGf8JbldBFGa7hZRCZiaAix0tiM4c73LhEpFhGXiIwQkXbmojhUYiyg3hGeBE42fRu5RSTXHKZpZ32DuHHNe3kdeEBESs1neKSlnGUiUpIg7dcwNIwbgb9r/JXD2t2zaU55DqMy/1RV19m4lwiJ/qungGNE5EwR8YhImSnwY5XjEwzvpVea9z4Jw2VIxkccOWQHjgBIHy9HzQN40Qz/E8ZSjIsx3C6/EBXvWowWXzVwA21b9bF4GmOkzD+07fDKC4EbRaQOY6nCZxOkcS5Gp+FyM9/nsGeOAZgDnC4i1SJia0y7qq4HIusfb8No5f4OG++njbjnYHRar8ToiP2tGW8lRgv/G9N0NChG2i0Y/8cxJH7ufwHGmOn80xL+GEZnrm3zj0nc/8oUJD8ApmIsurKIXQultCmHqvoxKvwTMEaZPQCca967g4PjCyjbEJHhGEMrvZp8fLxDFiMiQzEET4W2XXHNwSErcDQAB4cuwLS7Xw4841T+DtmKMxPYwSHFmOvZVmKMuDk+w8VxcIiLYwJycHBwMNlfROtsXrsa3lDVbi3gHQ3AwcHBwaQOuNnmtWfFnkfTrXD6ABwcHBx6KVmvAQwfPlzXrt2dybEODg69BVWNNbnRNkLs2ZE9lawXAGvXrsXpp3BwcEiGSGqq7t5kFsl6AeDg4OCQTnqTBtCbhJ2Dg4NDUsTmZistkT4i8pyIrBSRFSLybRHpKyJvicgq87e0K+7DDo4AcHBwcOg65gD/VtXRGC47VmD4+3pbVUcCb9Pe/1facASAg4ODg4nd1r8dDcB0NHgkho8mzDUZdmL4rnrMvOwx4EcpvIUO4QgABwcHBwsum5sN9sRwUPiIiHwuIn82Z4kPMD3VgrG2RkcXU0oZjgBwcHBwsNABDaCfiMy3bBdEJeUBDgIeVNUDMdb2aGPuUWOIY8aGOTqjgBwcHBwsdGAU0HZVPTjB+Q0Y605/Yh4/hyEAKkVkoKpuNpct3drZsu4ujgbg4ODg0AWo6hZgvYjsYwZ9D2ONjX8B55lh52Gs5Z0RHA3AwcHBwaQLZgJfDDwlIj7gG+DnGA3vZ0XkfAyPsWemNkv7OALAwcHBwUIqBYCqLgJimYm+l8JsOo0jABwcHBws9Ca7uCMAHBwcHCw4riAcHBwcHHo8SQWAiAwRkXdEZLmILBORS6POTxURFZF+5rFLRB4XkQ9FZKwZNsm85mRLvFdEZFKK78fBwcGh06RyJnB3wI4GEASmquoY4FBgioiMAUM4AMcC6yzXHwt8ApwKTLWEbwB+n4pCOzg4OHQVjgCwoKqbVXWhuV+H4cxosHn6buBK2s5kcwNhc7M+p8VAjYh8PwXldnBwcHDYTTrUCSwiw4EDgU9E5BRgo6oujlqI4Q3gSeBcIHpq9E3ATOCtJPlcECOug4NDN0NVCYfDhEIhQqEQwWCQYDDYehwKhRg0aFCmi9mG3tQxalsAiEgh8DzwWwyz0DQMc08bVDUI/CRWGqr6roggIocnyktVHwYeNvNNm5+Mbdu2sWTJEtxuNwAulwu3243H48HtdifdItfHC4vsp2rlIgeHzqKqhEKhNpWzdT9RWKwtUqmHw+F2eVm/o8i3FPmtq6sjEAgwbNiwDDwFB1sCQES8GJX/U6r6goh8C8PTXaT1vwewUEQmmtOfE3ETMB1DiGQV1dXVjB49msGDB7druVhfcuvHEQwGCYfDBAKBuB9O9H5kiUu/34/P52vNX0RwuVytH0xk3yo44v1ar3W5XO3CIsemAI4bHn3s0DFUtXWL/NeR38h+dHisX+sWCoXaxI8cR96nWNdHfuMR+Z9jNU6qqqoYNGhQu3M5OTm2GkEdeW/WrVtHIBBIxaNPGb3prU8qAMT4N/8CrFDV2QCquhQot1yzBjhYVbcnS09V3xSRmcDAzha6qwiFQng8xiOJVK4RbaArmDt3LpMmTWo9jvVRx/vIY22BQKBdBRI5bmlpob6+nuLi4riVU3T47hAKhdoIGaDNb3QlYT2Ot5+IiDCNXj86cmwNt4bF2k9G5NlG3pVorEI0nvCN/k0ktDds2MDgwYPJz89vJ+ijGwmxGg0dQVWZN28eY8aM6VC8zuLxeGhqakpLXnYQwPYjy4KlykXEhbHQzCCgCfhCVW07l7OjARwGnAMsFZFFZtg0VX2to4W1cBMZdIAUj1Ao1KUVfjJEJG6lsrvs2LGD9evXs//++3dJ+tEsXbqUgQMHUlZW1q6ijfWbaD8Wqtqmcvvwww+ZOHEiYE+YWIVQ9H4yKisrqaqqSlslWV1dTXl5OcXFxV2eV7q1Po/Hk1BTyQRitwrIoA1DREYAVwHHAKsw1h3IBUaJSCPwEPCYqiZsySWtbVT1fZJoRao6PMn5ucBcy/G/kqWZCTItALoSVcXlSl/3ViS/dJmSXC4Xubm5XZ4PGJWkXW0hFbhcrt3WyLIVt9tNMJhF1mABsdsGy2yxZwEPAr/WqJdRRMqBn2I03B+LEbcVxxWEhWAw2GMFQDgcTmvrLp0VZLpJtwAQkR4rALJOA5AOaAAZRFXPSnBuK3CPnXR604inpFj7AHoa6dYAIP3mhHThaACpI+s0AEjpmpBdhYj8TUT2jXPuCbvpOALAQjo1gHS3kDOhATgCIDX0ZAGQlRqAy96WYY4B/i0iU2KcG2s3kczfRhaRzj6AcDicEZt8OvPrqfR0AZBOk5PH48kqDUDoNgJgA3AI8EPTr1q/ziSS+dvIItItANLZ35AJgeNoAKkh3QLA7XanrVWedSYgwXBmY2fLLKqqW1T1OOC/wHwROd48Z/vD65kG790gXZVWZJx8uki3CQicPoBU4XK50pqf2+1Om8DJxnfE1c1qRVWdLSJvA0+KyImAL1mcCI4GkCHSrQE4JqDUke4KOd0agMvlyi67fDrpPhpAG8mpqouBCRh1+mi7iTgCIEP0dA2gJ5uAIL0CriebgLKRbtIHMD46QFWbVXUKhmseW3QzZafn0NM7gSE71ftU0Bv6ANI96ihrGgxCt2gWq2pYRL4LVKvqEhE5EzgS+Bp4wG46jgAwSXcLOd2zjjNhcsqKD7oLSLcJKN0TwdKtAUQETrZMwsyC1n1SROQPwH5Ajoh8BRQC/8Zw3fNX4Gw76TgCwCTdk8CcPoDuS7o1ALfbTUtLS1rzS7cAyJpZ+JE+gOznKFUdIyK5wEagXFVDIvIQsMRuIo4AMMlEizzdfQDOMNDU0NNdQaS7EzibJoNJR3wBZZZmMOz+IrJWVUPmsYqIbf/a3eNW00C6WyCZEDjOMNDU4PQBpD6/bJoL0B18AQHlInI5hs4S2cc87m83EUcAmGTCBNSTO4EdDSB19PRRQFk1G1i6Rx8A8CegKMY+wJ/tJuIIAJN0t8h7wzDQnkpvmAjWW01AQHcZBXRDKtJxBIBJuk1APb0TGBwTUKpIt03e5XKldZnGrDMBdQMBICL3JjqvqpfYSacb3Gp6SLcJKBMagGMCSg2OBpBaskoDEBCvvS3DLDC3XOAgjFXBVgEH0AFXEI4GYNIbNABnJnBq6A19AOnML9v6ALpDs1hVHwMQkd8Ah6tq0Dz+I/Ce3XQcAWDSG/oA0m0C6qk4w0BTS7rnOSRC6DajgCKUAsXADvO40AyzhSMATEKhEF5v+vS6TLiDdjSA1JCJiWA9fRRQY2Nj2vJLSDfRACzcCnwuIu9glP5IYIbdyI4AMAkGg+Tl5aUtP2cYaPelp2sAmZoJnC10h07gCKr6iIi8jrE4DMBVqrrFbvyktyoiQ0TkHRFZLiLLRORSM3ymiCwRkUUi8qaIDDLDXSLyuIh8KCJjzbBJIqIicrIl3VdEZFIH7rVLcUxAqaUnDwNNN04fQBrpJktCisjwyL65MMxL5rbFPC8iktQrqJ3bCAJTVXUMcCgwRUTGAHeo6n6qegDwCnCdef2xwCfAqcBUSzobgN/byC8j9AZfQI4JqHvijAJKIwJ4bW6Z5Q4ReV5EzhWRsSJSLiJDReRoEZkJfADEXDTeStIaT1U3A5vN/ToRWQEMVtXllssKgMgb6gbC5matARYDXhH5vqq+ZecO04mjAaQeRwCkhp6+IExWaQBkvnVvB1U9w2yInw38AhgINAIrgNeAm1S1OVk6HWrymmrHgRgtfETkJuBcoAY4yrzsDeBJM/yCqCRuAmYCCQWAiFwQI26X0tOHgTozgbsvmRiV01X5qSrhcJhQKEQwGCQYDNLc3Izf7++S/DpFCgWAiLiB+cBGVT1JRPYEngHKMMbxn6Oqnbp5sxG+W1YV2wJARAqB54HfqmqtWYDfA78XkWuAi4DrzfGoP4lT4HdFBBE5PFFeqvow8LCZb1pqkqamJhYsWIDP58PtdrfZPB5Pu7DozeVyxTyO1+pOtwbgzATuvqTrOVor5kAgQF1dHaFQqDU83hYMBgmHwwSDwZjh0UR/W+meeZwQSfkw0EsxWuXF5vFtwN2q+ow5Zv984MGU5tgBbAkAEfFiVP5PqeoLMS55CkPtuN5GcjcB0zH6FrIGEeGQQw5pbf3Ee5kj+y0tLXE/COsHE68l3NDQwKefftoqXFwuV5stVpidTURihkVaW6YAbt0c0ouqtm7hcLjdb/R+ZAsEAmzevLlNWORdi7VFn7O+l/HeSRFpfe8aGxv58ssv2zVqrI0hr9cbszFkvSby/iV7JvPmzeuKx905UtROMjthT8So8y4X40EcDfzUvOQxjCGb2SsAzEL/BVihqrMt4SNVdZV5eAqw0k6Gqvqm2UkxsBPl7TLC4XBr6z8dzJs3j0MOOQQRafNxJvuQI5VBdFh0pRF93NDQwPz589tUOB3FKjgi2kQsgSIiNDY2Mn/+/DZhiX6tecQKT0ZTUxNLly5td1/W48i+9TdeWKxj61ZfX8+8efM6/RyjhXWsMOu5UChEbW1tu0aC1+tN2HiIbkgk0kqtzJ07l4MPPrjD99YZsqkhIqn1BnoPcCW7PHWWATsjs3YxBsYM7mziZt28h6qu72wadjSAw4BzgKUissgMmwacLyL7YHT2rgUmdyDfm4CXOlLQriYTwyR9Pl/aXv65c+dy+OEJLW8JiVR0EeGRrKL8+OOPGT16tO1KN1ZeycIiiAiVlZUMGjSoXXj0fnSYNTzecayw9957jyOOOCJtmtS2bdvYZ599ujyfXk/HFoTpJyLzLccPm+ZrROQkYKuqLuiq4e7m4i+vAd/qbBp2RgG9T9vRPBFes5uJqs4F5lqO/xUnzYyS7pZINrV8khEpq10Nye12U1hY2JVFaoPH46GsrCxt+Vm1IIcehn0jwHZVjacmHQb8UER+gOGwrRiYA/QREY+pBeyBsZzj7rBQRCao6mediey8wQ4ODllBVowci7iCsLMlQFWvUdU9VHU4xqCY/6rq2cA7wOnmZeex+5aQQ4CPRORrc2LuUhFx1gR2cHDYPdI5mS8yGSydkzHj0cXzAK4CnhGRWcDnGP2ru8NxuxM58087C8iKloeDQxYRmXyWrkEREX9AGRcAXeAMzmoCV9VvgIkpTHutiOwPHGEGvaeqi+3Gd0xAOK6SHbIf6eEeSLPGHUT3WRAGADF8sz0FlJvbkyJysd34jgZA+t1AOBqHQ0eJzAZOVws5Mh8mXS7Ss8kdRHdwBWHhfOAQVW0AEJHbgI+A++xEdgQA6XcEl4lZuQ6pJ5028nQ7hMuE+4lsEQDdzC4igPWPCtGBEZaOACD9foDSrXE4pJ6ISSadAqAnrwmQLSagFE8ESwePAJ+IyIvm8Y+Av9qN7AgA0l8hO775u0yxMJAAACAASURBVD/ptsn3dAGQVRpAN2qbqepsEZkLRGZ5/lxVP7cb3xEAZGYtAGd1ru5NbxAAvXJRmG62JKSIPKGq5wALY4QlxREAZGYtgHR3Ojt9DqklEzb5nr4mQDaYgDroCiIbGGs9MN1Pj7cb2akVyMxaAD19MZjegLMucGrzywoNAFIyE7irEZFrRKQO2E9Eas2tDthKB2YXO7UC6TcBZUIDcExAqaU3mIB6pQZA91gTWFVvUdUijKV5i82tSFXLVPUau+k4AgBHA3DoOJkwAfXkdYGzRgMQjE5gO1t28KmIlEQORKSPiPzIbmSnVqB3rAfsaACppTdoAL2yExi6hQnIwvWqWhM5UNWd2FuYC3A6gYHMDAN1OoG7Pz1ZAKR7mcasMQF1v07gWB+27TvoXrfaRaTbCVUmNABHAKSWnj4KKBN9AFmhAXS/iWDzRWQ28AfzeArGYvO26F632kX0Bg0gnSag3jDxrDeYgHplHwB0NxPQxYAf+Lu5tWAIAVs4GgCZGQXkaADdm94gAHqrN9As6uBNiukE7urOxncEAJnRANI98zjdGkBP7XRe0nwZLgkD5/ZoAZDuiWDpvr94CN3LBCQi/TEWnh+LsfQkAKp6tJ34jgAgM87gfD6frWu3bt3KCy+8wMCBAxk+fDjDhw+npKQkeUQL6e4E7skCYL/cuwH43PV5jxYA6TYBZRXdSABgrAXwd+AkYDLGMpPb7EZ2BACZ8QWUTOCoKk899RRTp07lqKOOoqGhgTVr1rBmzRo8Hg/Dhg1jxIgRPPLIIxQXFyfNz1nwPjkLm6YyOKeKAa5Hk16bbhOQiKTdJp8NLfK00/1GAZWp6l9E5FJVnQfMExHbC8QnvVURGQI8DgwAFHhYVeeIyB3AyRgdEF9jeKHbaca5AzgKmKqq80RkOLAauERV7zOvuR+Yr6qP2r7VLiLb5gGsW7eOyZMns3HjRl599VUOPvjg1nOqyo4dO1izZg2nnHIKL7/8MmeffXbC/BwNwB4H5d0FwKeNVzIx/3b+57+QvX0PxLw2E30A6ewk7bUaQDdzBgdExupuFpETgU1AX7uR7dxqEKMiHwMcCkwRkTHAW8A4Vd0P+Aq4BkBERpvxjqRtb/RW4FIRsWf7SCPZNDP3+eefZ/z48XznO99h/vz5bSp/MCqesrIyxo8fz0knnURNTU3MdKLz60mjgD6ov5p3665p/d0UOp8ga3i3LvkM+IVNU/nKn3iQxJ76JV/5pxBOsq6GYwJKLen2dxSX7jUKaJY5E3gqcAXwZ+Ayu5GT3oaqblbVheZ+HbACGKyqb6pqpEnyMbCHue8GwhjagvUL2ga8jWGj6tXE0zhWrVrF5MmT+fe//8306dOTLsdXUlJiWwCkexRQVwmcr/xTqG3x0tfXCECuO8QXtQNRfyNuSV4hH5R3F8Wb3mFu7bSY5z9tvJJAbj88EmKU7w8xr4GePwoo3Z3AkD0jgbqDLyBz6UeAPFWtUdUvVPUoVR2vqv+ym06HbsM05RwIfBJ16hfA6wCqugzIB94HHoy67jbgCtNlaa8lVh+AqnLOOecwffp0xo+35821pKSE2trapNdl0gS0vOWSlKW7vOUSRvn+wAllMxmXM4dA2EVj0MOxpbPw+sZwWOGtSdP4yj+FdeUnMbZwY8zzE/NvZ4u/D0FN/Io6E8G6Js+MzwXoPr6AfiDGR2bb8VssbHd3iEgh8DzwW1WttYT/HsNM9FQkTFVjrkqvqt+IyCfAT5PkdQFwgd2y7S6BQIAVK1bgdrtxu914PJ7W/cixy+Vqt+92uzvV0o3VIg+FQvTr14+HH36Ygw46iCOOOCJpOiUlJWzYsMFWfpkyAY3JuTfmNXNrpzGp+Gbbab66/VpcUsKYnF1hHYkfYZTvDxBlhHyzejrHls5qLVN90EeuK8BX/ilxtYCergHEel9UlVAoZGsLBoNxj637VgKBQFZoAFlk3knEv4FqoFBErK1AAVRVE48MMbElAETEi1H5P6WqL1jCf4Yx/Oh7av9ruBl4DpgX7wJVfRh42MyjS7+ySOu4tLS0zQsbCATavcTRWzgcjlkJiAhut7uNoIjsu1wuqqurWbNmDTk5Oa1hLpeLBx98kM8++4xZs2ZxwAEHcMEFF9C3b9/W89FbtpqAEnUCv151LW6XEgi5E3ayRnNiv5mpLGIr64K/ItfTD9glUI4susVW3HSPAgoGgwQCAcLhcNwt8l7GOo61b/217qsqdXV1zJ07t005rA2j6C3SOPJ4PHi9XvLy8mJeY73W+p4sWrQoKzSA7jAKSFV/B/xORF5S1VM6m46dUUAC/AVYoaqzLeHHY0xA+K6qNtrNUFVXishyjBFEtocrdRXhcBifz0dFRUXK0rS2lGJ9bDt27KCkpKRVzY6cCwQCjB07lttuu4333nuPOXPmcNhhhzFy5EhUtd3Hnp+fz1FHHdXuI43G7/cDsGHDhtaPLiJERKT1ONa+3Q1o3Q8GgzQ3N7Nu3brW8MhvqL6UocHP8RePYMX2EeQXb2p3TYQVzY8yJu/ntp55IBBgy5Yt7f4H62+s/R1Lv8K7z16sq17X5nrrFiusurqapqYmtm/f3u5c5L+K3o/3a0eQRN6P+vr6Ng2MRJu14RGpcOM1SqzpRfbnzp3LpEmTbD3/VJA1JqDuoQEAsDuVP9jTAA4DzgGWisgiM2wacC+QA7xlfrQfq+pkm/neBNheuLgr6YpJYCKCx+OJO7fA4/FQUVGRcDLYAQccwMKFC5k8eTK5ubk8+OCDjB27a/W3t956i8mTJ/Pggw8m/Ui/+eYbXC4XQ4YMSVgxJQoH2l2XqIJU1TbeJCPXDar7H5X5B7NH8wkUhl6nrq6u3TWR3wpOYUfTDgBWNc5lZP6kNtdahUUoFKK6urr1+UdItC8iFI78C5saXqda/sno/JPaCCKrILTGERFqa2spKCigrKwMIKbQjCVUo8OiW8HxqKmp4ZtvvuHAAw9Mem13JZs6gXsLSQWAqr4PMcfDvWY3E1VdA4yzHC8mS+RsuucAgH1ncAcddBAfffQRDz30EJMmTeL888/n2muv5cknn+T666/n+eeft9VXEDFzRVp+XU1jYyPV1dWMGDGiNezV7ddyYr+ZfFBfTKFrI6PyRzGKUbbTbGr6M8tqKjm9YkbM85WVley7776dKu/eXMwH9VezV+FetuPU1dVRVFREeXl5p/LsKFkzRLILcTSA9NMNrF1dS7pnAUfytGuTd7vdXHjhhZx22mlMnTqV4cOH07dvX95//3323ntvW2lkwzDQiA3fzkidaB5bN5Pzht7FQXkpKVpM4pVr646j8H/5HuEJP2eo50+t4eme6JYJXzmRju503WvWuITuRgJARE4GXlXVTr0cvV4ApNsPUISOflQVFRU89dRTfP755+y555706dPHdtxsnQn8ZvV0+ua2cHDeHQmvO2/otZ0qx4uV1xMIuRhc3NQpwQPgLx6B95Bh/K+xjKGFu8J7+iigSJ7pbCBlw+xj6SadwBb+D7hHRJ4H/qqqKzsSuRvJuq4hEyag3eHAAw/sUOUP2ekN9NXt11KR1xC38n+x8nperLS9sl1rvmDM9n2x8noKfCH2Kq1nlKzgzerpceN9UH8121rOYH7T79qdywnV8L/GinYCJBMCIJ35QS9eFKYbzQRW1f+HMTfra+BREflIRC4QkSI78bPkNjJHJkxA6SaeBrAt3DWTsu1UVCf2m9nqWTOa16uuZWezl1MH3NCp/Lc351HgCxEICdsacwluWsKg/LqYriJe3X4tee4AK/x70xhs/x70z/kHXlf7lne6bfKZ0AB65brAkT6AbiIAAMx5Wc8BzwADgVOBhSIScz6WlSy6jczQ3TSAzhBPA6gJFqR0pq6V3dE4Tiibyc+HxW+xJ8rvga9vZo/8WgblG6OLttTn4NnjQApfvJcGv6edJnBiv5kMzqnCLRrXlcTE/Ntj5tfTTUCZ0AAybQKC7uEKIoKInCIiLwJzAS8wUVVPAPbH8A+UkJ7d9LVBpvoA0km8TuDi+hXUF+2T8vzerb6XcEsF42nr0uK5LTM4vWIGT264kf+3x3W20nrom5vZo7iJ1dX5XDSyfQv+/lW34HUr5YHh/GHVrZQXBlpnH4/Lgbm+abyy9SBc3zmQYd4mGvxunt10Ay6XUXmfXjGDAa5HGVBolI/CdlnEpDd0AqfbH1DWjALqXtXBacDdqvquNVBVG0Xk/GSRs0SOZY7eagLa+LnRj7CX94980XJpa/j//BfyP/+FncrH7/dz33338fDFn1K9rb6dTb3AG+LFyuvbVP6PrJ0VN71H1s4ipLC2Jo+LRl7DkxtubD33wNc38+SGG/nOHtspy/cTDAtTRl7NmYPa9htEZveeN/RaJhXfTHWzF687zMDC5nYt/uIc+5VPuk1AmRgG2ls1gG5mAtoSXflHHMWp6tvJIvfsms8GwWCQvLwuHF8YRSYWZ4mVp2fgaCSnmC9aLmVczpzWcLuuGaLTf+aZZ5g+fTqjR4/mhBNOYPH7X/O/zStZf+r1rbZ8t0s5dcANvLrdGNXTFHTz82Ez4qb782HTeXbTDWxt8HH/qlsoytl1D+UFftbtzGNL3QCKcoKMzhnE3Stv5/J9r4qZToQ2mkdUa//Y0vjCKJpMCIB00ysXhu9+o4C+D0S/9CfECItJ9sixDJGJ9YDTbXKKpQHU9B2PBlsYwCa2hc9jYVNSc2HMdN944w3Gjx/PnDlz+Otf/8prr73G2NNqOOh7I/nLHZ/yyRPv8NyWGbxbdw2BkLCwaSpet+IS4k7qinDb8js4c9D1NAQ8XDTyGupaPK3hp1fMoLywhYqiZgCqAxv57T7tR/F0FenuA8gEvbITGLqFBiAivxGRpcBoEVli2VYDS+ym071kXReQCQGQ7klZsTSAUk894ZY6mguGUBvI73Can332GVdddRUbN27klltu4dRTT23Nw+cKU97Pw6znzuay4x7hkqHD2e/Ivahr8eB1K1sbfDT4PWB4UeD+VbdQXuBna4OPi0Zew50rjE7XisIW7lxxO24xKv1AyMcja2fhFuO3qjGX5qCbfG+QxoC7Na1YfQWppjcIgHT3AWSFCUiyp4M3CU9juOC/BbjaEl6nqjvsJtI9brULCQaDae0DyMSoo1gaQGWgD65+e1MbMir/Qdvesp3ePffcw/HHH89ZZ53FsmXLOO2009oImMr6XFrCLk7caxVT/nAG91/0PP7KSgYXN+NzhwmEdpXlga9vpqKohe1NXgp8IWavvI3hpY1cse+VnDf0Wq7Y90oa/B7coowqq8cfchFSYWNtHrUtXnI9IYb2acLrDvPA/26jObjr2d62PPEEs92hNwiAdFfIWfNMU6QBiMgQEXlHRJaLyDIRudQM7ysib4nIKvO3tBOlVNPFzhSgzrIhIildErJH01s0gOg8x+XMob/rMfp66hmXM4eKoba1Ro455hg8Hg/77rtvG+EZ6Tw+quyXBMPwbtOhXHrsZn4wZRLXnf08TfV+1u7M47CBmwGYvfI28jxhttTl0Bxw43WHKfCFqGvxcMPi2VyzYA43LJ5NUU6A5qCb+RtLWVNdwM4mH6GwUJwToCzfz4KNpSjgEgipcMPi2cxaelfM8fupImsqqy4kE6uCZQWpMwHFW073auBtVR2JsUri1QnSiMfT5u8CYL75u8BybAtHAKR5FFCmNIB4nYjbA8VUhn/WofTGjRvHfffdx29/+1tUlS9aLmVh01S+rC3juS0zmFf1Z/bKP4R++X60qIKTfzmBgw8u5t5LXyIUhkXbyynL93PQoBpc5kgcnzvMxto8djZ7WV1dQEiFwcXmso/eEDubDM+po/vX0r+gmeagm6rGHNbtzKdPnp+wCvUtu5bQ9LrD5HpDzFp6VyeeWHJ6gwDIBtcMaSeFE8E0znK6wCnAY+ZljwE/6mgxVfUk83dPVd3L/I1str0a9noBkO55ANmiAewup59+Ojv967n1mR+zvr4Yj4Txuo0KsTgnyObgB3hdYVbUD+Logas566YzWLO6gUWP/5vtTV7W7cxj/sY+DCxqoSFgCODmgJvmgJtAyIXPHWZns4+inAD98gL0yTPWNGgIuAmEXTT4PeR6QoRUqGrIIaSCxxWmKCdASIWKwmYuHDGN6d8yOrcj/Qr3r7K32EsyeosA6OkeSNshIB63rQ3oJyLzLVvcVQyl7XK6A1R1s3lqCzCg08UV+ZeInCUiHe/IwxEAaW+RZ8r9dKJhhHXBjr87LpeL2bP+xN9u+R+lOc3kuvzUtngIh4X98n5FbYuHhoCHQm+AZfWD2dhcxO3P/IgnHljK1k+WsEdxM0cO205ti4cCb7C1sm8OuhnSpwGA2mYva6oLWbGtiCEljYwdUENdi5cGv4exA2oYXmpcF1bBI2E21+XxTVUR5QXNrKku4JoFxvDW25bfwRX7XgmQsg7iTAmAdM8+TrcGkIkJb20RcLntbbBdVQ+2bA/HTDHOcrpgGPKB3flT7wKOAFaIyHMicrqI5NqN7AiANJuAMqEBJPIGul/u3Z0a+w9w8skn0+zeziv/+IYlO/oztLiRPnnGIjBhjHH1w/ia7Y0+ygv87Dk0h+mPnMbsi19h6+qtNAY91LV4KMoJ0r+ghUDYRf+CZvrlBeib38LQPg2MLq+hwBekqtHHym3FFHiDHL3XNrbU5bKssgSfO8zIfnUoRqvfH3LhcikNfg9l+S0ABEIuZq+8LeGks46SCQGQbodwvXZhePsCICkSezndShEZaJ4fCGztbFFVdZ6qXgjsBTwEnNmR9Hq9AEinv3PInAbQFUJHRJhz8194+va5lOc10tdTTyBkVIw5HqMVN69mP+paPEz47AYWby1l2IHD+cW13+X+899me1WAUWX1rK/JZ0tdLoOLm9hSl8fWBh87GnNYua2ENTsKqWrMoSzfz9gBNZQX+Hl/bRm53hATh+zAH3KxrLIEgGGljQzt08DKrSWEVbhi3yt5bssM/CEXZfl+qhp9bUxBEXNQIk+hie49EwIgna3jTAiATM8FEBHE5ba12Ugr5nK6wL+AiCfG84CXdrPMecCPgcnABHb1LySl1wuAdJMt8wBSxfHHH09F6T588a+PqQ3l4Q+5+LL5z+R5Q7xZPZ3inCBed5jV372G/curqWvxsP+p36b0gFLu+M1LLNhYRJ9cPyEVttbn0Bx0s7PZR64nxAmjNjO8bz11LV7WVBfw1fYiVmwrIt8bZGeTjyVbSli+pQ8+d5gcT4jKuhy21OUxuKSROycajhC3Nvi48YDLWFNdQFm+n/4FLTy2bib+kIsRfRt54Oub2VhrW2NuJRMCIN2zjzPRB5D5uQAdMgElI7Kc7tEissjcfgDcCnxfRFYBx5jHnSutyLMYnctHA/cDI1Q1qRfQCL1+Ili6yZT30a4SACLCzJkz+enPTuPHKxrRvhUMHjSGPfrm0eyDYQOEXE+YfE8Qj4SpbvIytE8Tv5x1LDcffycf/ONz9jnpMAp8QbY15DK6vMbQAupzafB7aA666V/QTK43xIeryxlmCoT1OwsYVlpPnzw/+b4gNc1elm8toSA3wJodho+HWUvvYvq3pgGGG4p1O/MpygngcxuV2uqdeYTDwuDiZp7ccCOluYHWlcvs3HdP1wAy0QeQaQ0AEcTjTX6dDRIspwvwvZRkYmgYZ6lqp/4oRwCkmUxoAF3N0UcfzTnXH4drw1esXbaKrUuFDYXbeeSvT+DL9VA6sIS+g/rQd1AJe+5VxB77bmTR+mE0hbwM+fY43KJsq8+lKMeovN0uZXBJY+uEsaWbSxlU0shLJ7Zfv+A37z/I+p0FDA27KPCFaAx4KPAFueLT+3CJl4e+uZk11QXkeoTr97+c25bfweWjr+LFyuvZ2Wx86MeWzoJS0zFdP3v33BsEQK/uA8hyRORoVf0vUACcEt3As/Q3JKRXC4BMjOLoiesPiAhn/nQ4a3aO5ZTiJvaqu5QPN7zEWbeUs3yN0lBZzdrV9QSqqmjetJmZcxqpr57PZY+ey+++O8Nw9+BScj0htjUYgmBbfS5VjTmMLq/hueN/HjfvBw//DQAPvfQ8XleY8RU72dqQQ1VDDhVFTexs9lLgM8xQAFeNMfwFxVpspiNrEDgCoGvIuAlIpFsIAOC7wH+Bk2OcU8ARAMnIhCvocDiMz+dLa57pYGNdHl53mMMKb2VT7SbGFR/Fh9X/4Df7TefTxitZsc8Qqhp97NOvnmOaveR6wjQHXTzw9c1srS9k4pAdLKssJhQW+uT5qWrIAWBbvWGfb2lp4corr0RVGTBgABUVFQwYMKB1y/f6GdWvlqWVJRTlBNjRmEOBL8jw0gbKC/x8tN727Hhb9BYBkAkX1I4GkBxVjfg9v1FVV1vPiciedtNJWvuJyBDgcYzJCgo8rKpzROQMYAawL8YqNPMtce4AjsKYBj3PnASxGrhEVe8zr7kfmK+qj9otbKrJRGs8FAr1OBMQtG9Ri0hri7ox6MHtUgp8ITbU5lFe0EIg5GJLneHMrbywmSVbSijwBSnKCbB+Z0GrSSjSmXvPPfewdOlSfvjDH1JZWckHH3zAli1bqKyspLKykilTpnD7eXfhKvCR37cIb0kJhWVFDBvqo2TMaA79rjHXYfbK27h8tC1PuQnpDcNAe20fQDcQABaeBw6KCnsOolZjioOd5m/En8VCc6HhBSLyFvAFxmo0D1kvFpHR5u6RwKPAPPN4K3CpiDykqn47hetqMrEaWCbcQaeDJc2XsaWpgGNLZ7WrpL6oLKLAF2JoSRMrthWylRxyPSH6F7RQ1+JhY63hzmFceS2fb+7D2AE1LKssYUejoQVs3ryZO+64g48//pi99947Zv7vvfcex3hu5OHhk6nc3ITW7SRYs5Mt32zhlbvv4wlLS/ahb26mwBe0vSpZLDKxSHsmOoEzMQrI789k9dA9TEBmPTsWKBGR0yynigHbw9qSCgBzyvJmc79ORFYAg1X1LbMg0VHcGPOAlLY94NuADzDGvf7JbgG7kp40Jj/T7Jd7N/uZr1303IoCX4iinCBVTV7TxYOXQCiHwcVNrd47qxpy+GJrMX1y/bzx5SCuOHw5Ty8dDsC0adM4//zz41b+YLyHpQPg+uFz+MuoWVQUlbOssoTcd+dTs7W2tTzHDN/ClqYCdjYZHcQAv95rWqfuuacLgEwtQpNxDcDdLUy0+wAnAX1o2w9QB/zKbiIdMoBH+bOIiaouM/1SvA9Er9BxG/C6iPw1ST4XAHH9aqSKiHrb1NSE2+3G7Xbjcrm69MXviZ3AAB/UX83m+tzWRV6sz7DB76a6ycukYVt5a3UF48prGVJYz/sb+1PVmEMg5KJPnp9t9blsDLnoW9DCa/8bhNcdpq6ujqeeeorS0lJeeeUVSkpKKC4ubv2N7I8aNYr5leW8s/l7/PBb71Kp/alvHMBX85Yx6tsjWtcJaA572btwO/ObBlLgCzKqb32n7rc39AHsDqpKOBwmFAoRCoUIBoPt9mP91tfXk5/fKbc2KULAlf1do6r6EvCSiHxbVT/qbDq27zSRP4sYhYs5EUFVvxGRT4CfJon/MPCwmW+XfWXBYJC6ujqWLFnS+gLG+sBEpFVARG8ulyvmfnRY5LelpYVAIIDf728Ny0RLK9UcVnhr6xKL0RrARSOv4bF1M1m6zViH+MvthXyxtbjVBXQoLITCQv/C5lYXzssr+5DrDVFUVERVVRXV1dXU1tZSU1MT87e5uZlHPhhGoO4zpv89iKtlAeGmJhoaQxx07vGtPoDeX1fGuAE+isz1fzfW5UEn6pvuZgJSVUKhEOFwuLVijvdr3W9paWHlypXtzkdvsZ5F5P32eDyt30P0vsfjIS8vrzW8qKiI6urq3X1Uu0c3MAFZmCwiK1R1J4C5tsBdqvoLO5FtCYA4/iw6y80YnRTzkl3Y1YRCISoqKhg9enTC6yIfj50tHA7T0tIS9wOrrq6mpaWldVZnsk42l8uVcBORuGEigojg9/tZt25du3Oxro11HL1FTFjR4ZGwWJXBeUOvbXMcccngFqW80FjWMaRGGnUtXg7ao4qlm0u55KM/cO+3p1BUVJTwOT3++t+ZdMVZ9C1qoignwOFDq3h80XCG9GmgqiGHR9bOYvyAKsYNKOCTdzdx8IBKGoYexOmDbuCRtbNiDgGN3IeqttsCgQDBYJCmpqaY58PhsK39yHH0vjUsslVXV1NVVcX69evbnYtXCUewviexGiaR/ehGjIhQUlLSrlFjrchT2YipqamhqqoqJWl1iu4zDDTCfpHKH0BVq0XkQLuR7YwCiufPolOo6koRWY5ht/psd9PbHeyaY0SktbWyu3z22WeMGTOGgoKCpNdGVxTJtlgVSUTABAKBmJWL3Yor0WYtK4Df70dVWb9+fZv72dayBYD+ORUczEQAtrdsoSXkQs3KX4EKl+IR5bCQixxPiLlz5yZ8Tmvrt1MU9nFkYynaUIoIbFw/lGNdSlNtGcMBqgaw6ssRNO+sp6SyH19vdBH8JMQfCx4gp3Agb331Fl6vMTFsR2Azfb0DAWIKuIiQq6urY/HixXGFpjUs0X7k2Ov1thPo1mOAgoICBgwY0KbCtl6bam1y9erVVFRUpE1Lzfg8AATpBiYgCy4RKVXVamhdDcz2Ddi5MOLPYqmILDLDpgE5wH1Af+BVEVmkqsfZzPcm4HO7hewqMjEKqCPDQKNb3J0hGAyyYcMGRowY0ek0OsratWsJh8PsuWfy4cizlt5Fg99DKCyUFbTgdRmrgoUUdjTm8Nm6fhBcy4Sh21t9+1u54tP7IB8O2NGft2jkRwesZXV1PrneEN9UFVGUE+D6/S8H4AeXn8DiFz/m+Yd95B/xUz5ZAfPeWM/Kf37Fmo83MWDAAI477jhGHrWaURP7M64kpndfAJqbm1m0aBGHHnpo5x9UB9mxYwc5OTlJtaFUEjE7phGu3AAAIABJREFUpes7yfwwULqbBnAX8JGI/MM8PgOjfrWFnVFAifxZvGgnEzXWrhxnOV5MFjiiy9QooHTmmcgVdFfmabfFGKnUr1t0d5vw8gI/a3YU8tKJ53H6vx+httnLDYtns6a6kFxPiJomH/6QC7ergB+M3oi3powT99nIqysHMaRPA6u2F9Mnz0//wmZuWDyboQtL+eKVz3j1nyMYNKSI2gfv4fgD4FdXG1pLKBRi4cKFvPHGG/zh5ue4/KxKxkz4D9dMuR09bClnDGw/z2FncCXGSn/pIROdwJHJYOl6ZzO9CpkgiKdbjAICQFUfF5H5GM7gAE5T1eV243crXSfVhEIhcnJy0p5nOivkrvQEmkpuPOAyZq+8jU21+a0uHG6fcAkABb4gOxpzWFtdSKPfwx59Gqhr8XLxYV9R2+JhyZYSxomyb99qigr8bG3wMby0ga93FFJe4OfCEdO4+LWjOea4CvL3PQQJbabgpOG8mfMLBlZP59jSWbjdbiZMmMCECRMY/rMwPn8dS99bzQ033MDAgQPZ//6vGDVqVGt5RYRi16h4t9MlZKrjORQKtZrHuppsGAbaHUYBRdEXaFDVR0Skv4jsGT07OB4Zb4Vnkt4wESzbNYAI1yyYw+Wjr+LOiRezbmdBqyuISz76Ay6X4nWHGVZaT9/8llYhsLE2ly11OazfWUBz0M36hmLW1eRx1KB1HFaxmQJfkAUbSwEoHjqQd97cxLp1TWyWYdQ+sYZhfZrY2tC+tVfgDeH3FbH/ceN49MOjGHqE8u3v7Md1111HU1MT0HuGgaa7RZ75xoqAuO1tWYCIXA9cBUSWuvMCT9qN36sFQLYt0N4VZEID6Mw93jL+Um5YPJtrFsyhwBdsbf0HQi5GlNXhdYfZ1pBLvi9ISZ6fsQN2UtXooznopigngMelLNtaRF2Lh3c2DcX39oOUF7Rw1F7b2BQ6n5lnPcH4Hx3MGd95lvde/5q+vz+d1dX5hMJty7m85RLK8v2UF/gpzgnSQAG3XNmHZz45h3lLn2Ps2LG8+uqrjgDoqUT6AFK0IlgaOBX4IdAAoKqbANudRN1O10klmXAGl24ypQF0hohH0EinLRjePq/49D5yPUYlFFahrsVLVWNO6/rABb4ggZBQ0+yjWWG/ilpeGXUTBCEQEp5ZNYpxA67jsmsPYuD+I7jxkqd5+z9juPWufozKfbBNGZrDXrY25FDgDbFP8TbC6mJZ80j2HLKTK//0Y3Z+9hkXXnw24/bvz2W/aRu3q3EEQDrodqOA/KqqkflSIpJ8eKGFXq0BZMIElG4y5XqioxrADYtnt6v8wRgldOfEi7l9wiXc++0pAAzp08C2hlzunHgxDx7+G/Yqq6MwJ8jefevxusMs2VLMtvpc3GK4odinXz21LR62NuTw6x/7mP7yFDYtUJ6bPaRNXkuaLyOMi6HFjbhdSmHdl+St+Dv5niCbWkooygly9gn/5t+fn05OcR5LlizZvYfUQTIhADI1+zgTrtoBEBd4fPa27OBZEXkI6CMivwL+Qwdc7XQrUZdqeoMG0B1MQA98fTP9C41hn69uv7bNqlzRQz/v/86FrfvXLJgDQFm+h/oWD5vrchlc3Ehz0E2BL8jOZi9fbi+kwe/G5w5TXuBneVVfLj7gek57fiMTJkzg4IMP5thjj+XZTTcwuDiHIk8Lg3zbUK2j+dO5uPqUMDH/dhY2TaU+aHz0YW8e2zfWMOi4QbvzmDpMb9EAInlm7NvMHvNOUlT1ThH5PlCL4R/ouoifNjv07NovCT3VL4+V7mACavR7yPcFmf6tqdy54na2N86kX74/4fKM1y26m1yPtmoMf9/4FFPHTOGWFfdTlt9CgS/Ez4dNN1b5MhtrDQF364zfwYMH8/TTT3PKGSex+LMvGNyviRx3iNKP7qGhBpoXQt8Z5zK/eiiDgYPy7mrNe9Hzh1JT+S4DBgzo2IPZTSKzx9NJJheFyYgAkG5nAsKs8G1X+la6152mmN4gALqDBuASJRwWZq+8jSv23eWr/6FvbmZLXW47sxAYw0atDMk3Jp1dv//lPLnhRgIhF7NX3kaBz0VpboAzB13fLo1JkyZxwq8P5/TTT2fGy8dwSN81+PuUEKqsoeisQWjtJoYVlrCk+TL2y70bVWXZsmVMnTqVl19+mYaGBtv3mAoyOQ8g3XkGg8G0D9E2EDRLRvgkQkTq2OVx2driEkBVtdhOOo4ASPOQzExUxtneBxBvgZZYbppnLb2LfG+QuhZvO8Ggqqavf6hq9HHFvlcmzftvM1/nyKVjeebqJznkke/h3etQtPk/qL+ZLd59WLmgkv++s4OtC07j/fffJz8/n9/97ndMmDAhqYuKVJPJeQDpJJPuIBQIx533mlXsr6r/v71zj5OiuBb/98zO7LLLQ2QFBERRAyhGBEUJmigmEROjEVG84COaa1QS349ojCQaFY1GUbw+ggGMXPKLwVfw3vhCL4gPFEUBBUWID+S5gLyXfczM+f3R3Uvv7MxOz+zM1M52fz+f+nR3dVefrumeOlWnqk593tKb+LoTuNAFsonVwEy1ABKZufYPzFzbdB3eTBl/+HWUlsSTtgoeXvEQ7cIx1u9o56nwB3hj52+55L7TeWtBDfdNWs3b70V58NlujLymE9/tMZ3bLlmKrP4WZ511FgsXLuRvH4/huuuauqQoBCYKYz8uDB9X8RQM8xSAiLzWkpv4ugVQaEysBlYsE8HScfeyPzUs6O64dnYjIlzW93L+6/NJngr/J1ZZ/Qwdy2Bw72ru/ftpXH7aU7zWq5xDhh3I2F/txwUn/oXKyspG6Xrzx9xkKAtMtAAcF+aFxKQ/IFUhpq3fBITlBO63QD8RaVIb8uq4M1AABcQvLQBoagJKZoPPhBsH/LphUZfm8Frzb18ao0f7ajZUVwAV9O5Xxj+WXcF+7bawqb4Tx1Tc06LnzQd+GQVk2iNokZiAxgAjscrwrL0DBgqggJgYk29CZr5Ma+kK/2TMWH1bw9q/n9ePIywxtscqKA934vNtHWkfiTU05/ct287WaPtWWfiD/zqBTRHX1m8ZV9XlwN0iskRVX8z2Pr5VACY6ZE25nmjtw0DzKdcp/J9efyvl4a7077SZFVs707/zFqpqOxASpSZawvBOrbPQd2NqIpiJFoAxExBF0wJw+EBEpgI9VfXHIjIAGKaqU70kbv2qLk/4wRGcI7O1DwP1wiP/vpMZq29rOH5iVeo5Aom8tfM37FNRR6RE2RprzxFdNhDVEjpFajm+412M2PuOnD5rvghMQIVAiGvIU2gl/BV4GXBmJX4GXO01cavJRaExMdHELyYgyL1Xxx4dahtq89B0icnm+GJrBVU7yxix9x20C9XRLlRPVEONJncVA36ZCGbSBOS0ALyEVsI+qjoTiAOoahTw/MJ8awIyYY4x0Qlsau5BrmWe0b35IaTNySsNaUMn9LfLLPcRPctz92yFwpQ9vtAyza4KJkSLYxSQwy4RqcSeDCYi3wG2eU3s2xaAn0xAbaEP4LkN2Y8iaukIpNaCCRfUfjMBFWEL4FrgeeBgEXkLmA5c4TVx0AIosMx8FMaro78AYL/wlCbnimEmsBfStQCSsaD6hlY7oqdYMDX5LBgFlB4RCQHtgBOwHMEJsFxV673ew7cKIBqNGukDyIfSSVbwu2W2BROQV7lu1uwoh4rCyK6pqeGUU06he/fuHH/88YwaNargzuLygV9bAMWAqsZF5GFVHQwszeYexaHq8kBbagE0h5+GgSaSTashW+6//37Ky8sZ8sO1vPjGJPoecgC/+MUvWLo0q/9lq8F3fQAe3UC0AlcQDq+JyJmSZY0rbckgIr1FZI6ILBORpSJylR3fRURmi8gKe7u3HR8Skeki8raIHGbHDRcRFZHTXPf9XxEZns1D5wJTo4D8MAwUWsParoVBVVm3bh333Xcft9xTz+j95vHQBctZsGg4++w7hxN/eAzHj9if2bNntxrFmAmm+h1MjgKKaomn0Eq4FMsvUK2IbBeRHSKy3WtiL1XDKHCdqg4AvgNcZk82+A3wmqr2BV6zjwFGAO9irVXp9pq1GrjZ64PlGxMtAFMdsn4YeWRKyakq06dP5yc/+QkH9ikn1KmEdt85mc6RTVz/h2Es+L+e/PTsA7n22msZOHAgjz/+eMF96xQbplYhsxDihDyF1oCqdlTVkKqWqmon+9iTK2jwoABUdZ2qfmDv7wA+AXoBpwNP2Jc9geWXAqAEa0xqHBoZ0xYD2+zVa4xjYhSQKaXjlz6AQuMogGOPPZaFCxeyLdKLskE/pdteL7Fvz/cBKO13PBeM7cySJUuYOHEiM2fOpE+fPtx+++1s2rTJcA5aJya/HQVicW+hLZCRGhORPsBgrBp+d1VdZ59aDzg9Xi9j9Uo/DyR6pJsAjM/yWXNKMBEsfxSjqSMbHAVw3HHHsW3bNpZ/vBnKOrI2dhEA+5TMoCYeoWv7WYgIJ510Ei+++CKvvvoqX331FX379mXcuHGsXLnScE5aD6pKNBo1+g3FVDwFL4jIj0RkuYisFJHfpE9RWDyXgCLSAXgGuFpVt7u1tHtVensm2phk91DVeSKCiHw3jaxLgEu8Pls21NbWsnnzZjZv3kxJSQnhcJiSkpJGwYkLhUJNzjnxmeCnTmA/tQBCoRBjxozh7WdKOXxgFWWhejbGL2B3vJSDIk3X5z7ssMOYMmUKEyZM4OGHH2bYsGGMGDGCm2++mQEDBqSVa/L3jcfjxGKxhm00Gm3Yd46d/VRxzrGTNpGSkhLq6uoM5A5UyVkHr4iUAA8DJ2GZwN8TkedVdVlOBOQATwpARCJYhf/fVPVZO3qDiPRQ1XUi0gOo8ijTaQWk7OVR1ceAx2zZeakKqCr77rsvHTt2bPJx1tbWNvmIk4VUtRS3wnD2Q6EQW7duZffu3WzevJlQKNQQnPOpjtOF5gqDTE1AK+t+RRyhX+nDGf+mbvykAADGjh3L6NGjueOOlWyqHgnlndOm7969O7fddhvXX389Dz/8MCeeeCInnHAC48ePZ+DAgY2uVdWGd1lTUwNY7zZdcBfWzcW7t86+w86dOxtWPxORpJWhZCESiVBeXp60UuXsp/p+X3/9dWOKLhbPmcxjgJXOyl0i8iSW6TxnCkBE/ltVz08Xl4q0CsAeXjQV+CRhkYHngQuAP9rbWV4EquorInI70MPL9fkiHo/TuXNn9t5775ze1/mjJvtjLV++nMrKSioqKpr8Ievr65P+QdMFVW22uVxdXd3QynErDGebuC/yC3bofHaHF7vivAWwCogdO3awZs0aysvLG+ISt+4/duKfPNWfPlm8k/eamhqqqqooLS1tFJ94XbJtqrhkx+746upqPv30U0KhEJFIhDPPPJPZs2fTrdsfGr6Dr+MPUcrQRu/K2XfeIcCwYcMYOnQoGzduZO7cuXz44Yf07t27ofXmvKedO3fywQcfJK00OIVzYgXBKYwTKxjJtonfCcAbb7zBsGHDCmoydUYCRSKRgskEq/ZfF/PcYt5HRN53HT9mV14degFfu45XA0Nb+IiJHOY+sFsdR3lN7OWNHgecD3wkIovsuN9iFfwzReQi4CvgbK9CsVoBnhRGvshXH4C7hpRIJBKhsrKSTp08d9K3mIULF9K3b186duzYqOBxbxMLJtWDGgqmxGuSFYSJcU7B4aR1rmlu29y+F6LRKNu3b29QAG6SKaDErXvfXeimUnIiwvr166msrKSsrIx4PM6aNWtYuXIlxxxzjEu59mfTulOQcJhIt4MguotdkUo61q8jWt6FstBudPsa6jod3DChr7q6mosvvpgVK1Ywa9YsevTYU1d6++23GTJkSNJ85gtTcwFisVjBFQBA3Punt0lVh+TxUVIiIjdhlcPlrmGfAtRhW0+8kLYEVNU3IeXUuB94EaKqc4G5ruPnm7lnQTA1CshUH4CjmApBVVUVvXv3pn379gWRB7Bt2zYOPvhgKioKNPUX+Oqrr+jSpQtlZWVcdNFFrF+/np///OcNLR+Hne2rqVu6kJL2tUi4lPZr5xHv9yNQpZZ2lAIlX7wGfa3rKyoqmDFjBnfeeSdDhw5l1qxZDB48GPCPS2hTcwEUPHfwemAN0Nt1vJ8d12JU9S7gLhG5S1UzXynJxreuIEwNyfTL3AM/9AGA9R1deumlfP7557zwwgtNCv+Nu063hoT2hA1Vx9GtyxzWbuhFzxLXeh1d7OBCRLj55ps55JBDGDFiBJMnT2bUqFG+WhTGiDsIzWkfwHtAXxE5EKvgHwOck6ubA6jqTSLSCzgAV3muqvO8pPe1Aij0MNDAHXT+MDUR7JZbbmHZsmW89NJLTVo8G+IXEmu3Dxt3j6Jr+bN07/YWAKG9erB2+f6Eux5Mty5zmpVx5plncuCBBzJy5Ei++eYbBg0aFLQA8kguWwCqGhWRy7GGxpcA01Q1p75BROSPWIplGXvWAVAgUADNYWqBdj+0APyAqrJo0SKWLVvGiy++SMeOTdfl7h76Kxt3j2J3pLJRfLj7IdRtW0fNe3Ph5PSyjjzySF599VWOO+44nnzySV8oAFP+gBSoj+WuMqGqLwAv5OyGTTkD6K+qWU0v93XJUOhaoyml44dWR6GZPHkyVVVVTJ06tdlO/a7l1qjpdZ/3b4jbp2QGkT6ZDQbp168f9957L3PmzKG6ujq7h84Sk53ABcfjJLAc9hO0lM+BrHvKfa0ACo1fJmWZmsVZKLmqyqRJkzjqqKPo0KGDpzThXgPZEL+QjbWj2RC/EOIx9j85s+f92c9+RufOnXnggQeyeOrs8dOaAJYrCPEUWgnVwCIRmSwiDzrBa2LfmoD8QltZE7g1MXfuXEpKSujevbsnpbN/+C97/mll9jaLAVIiwoknnsiNN97Is88+y6hRozK/SRb4zQTUilw9e+F5O2RFoADaOH5xBldIeZMnT+aXv/wloVAo41bHpth51H02h56HZjcasF27dvz+979n9OjRHH300fTu3Tt9ohZiSgGYcgfRisw7aVHVJ0SkHNhfVZdnmt6XJiBTPvJN4QcFUGii0WhWvvL3KZmRdeEPljmmX79+XHPNNZx77rkFKZhNLUZvpAWgxWUCEmuNlUXAS/bxIBHx3CLwpQIwMQTUT7R1b6BXXXUVkyZNSuuGIx84rY4bbriB0tJSJkyYUBCZfpkHoAj1MW+hlXArls+hrQCqugg4yGtiXyoAE7OA/UZbbgEMGzaMfffdly+++MKIAnD6daZPn84jjzzCm2++mVeZfuoDQHPrDroA1KvqtoQ4z801XyoAEy0AP5hFHEzltZCF8bXXXsvChQszlrk2dhGbYudlLdc9E7hnz55MmTKFc889ly1btmR9z3T4biJYEZmAgKUicg5QIiJ9ReS/gLe9JvatAggmZOUPEyagQiuckSNHsmPHjowWfd9YO5rQhsXEd2ygamt2C+MluoI49dRTGTlyJBdffHHefndTLQAj8wCg2BaFvwLLI2gt8HdgO3C118S+NISbMAH5TQG09dZOOBzmqKOO4plnnuGEE07wlKZr2VOsx3Ie2a3z7KzkJvMF9Lvf/Y6ePXtSU1PTxBdRLjA1EazYXUEUAlWtxlprPav11n2pAPziB8gkbV0BAAwcOJBp06bx5Zdf0qdPH09pnLWCsyUUCjUqGFWVxx9/nFNOOSUvhb8j0zcmIG1V5p2UiMj/YOmrpKjqT73cx5cKwFQLwC8dz219FJBDu3btOPnkk3nwwQeZODFx+ev84G4BfPHFF1x55ZWsWLGCmTNn5k2mCRNQNnMscoHlC6goKmr35uImRZHTXGOiD8CETJO09U5gsPJ46qmn8sQTT7BtW+JAjPzJrK+v54477uDoo4/m2GOPZcmSJU2WkMwlJhSAMYpkFJCqvt5c8HofX7YATJiATDllC8gfIkJlZSUnn3wyU6ZM4brrrsu7zMWLF/Ovf/2LNWvWsHDhQg444IC8yzTRB2AKBeJFYAJyEJG+wF3AAKCdE6+qnuYCBC2AAsr0gyM4P+HMBL722muZNGlSXm3Wa9as4eyzz2bSpEmMGDGC5557riCFP/isBUDReQN9HHgUiAInAtOBGV4T+1IB+KUPwE8jj0wtCKOqDBkyhJqaGjZu3JhzGfX19UycOJEjjjiCQw45hKlTp3LQQZ4neuYEE53AYP2+hW55FJsrCKBcVV8DRFW/UtVbgZ94TRyYgAoo09R6wAH5wVEAqsrWrVuprKxMnygD3njjDX71q1/Rs2dP5s+fT9++ffnmm2/YtGlTTuWkw8QylLBnLkAhv+Ei6gR2qBWRELDCXn1sDeDNRzk+VgB+aQEEJqD84dRQt27dSkVFBaWlpTm576pVqxg/fjxz5sxh4sSJnHXWWQ3v0URhbOobcuYCRCJZr3eSFa3IvOOFq4AK4Ergdiwz0AVeE/tSAZgwAQUtgPxjYhQQQFVVFd26dWvx/b755hvuuusupk2bxrhx41i2bFmTpSZNDY80gYm5ANq6Zvl6IaaqO4GdwM8zTZy2dBCRaSJSJSIfu+KOEJH5IvKRiPyPiHRynfuTiLwvIifYx31EREXkCtc1D4nIhZk+bK4IWgABucAxAW3cuJGuXbtmfZ/du3dz9913079/f3bu3MnHH3/MhAkTkq4zbMocYwJT7iCKrA/gPhH5RERuF5FvZ5rYS/Xwr8CPEuKmAL9R1cOB54BfA4jIIfb544HLXNdXAVeJSG7ayC3EL30AfuoENoFjAspWAUSjUaZOnUq/fv147733ePPNN3n00Ufp0aNHyjR+UwAFbwFQHPMAHFT1RCyzz0Zgsl0pH+81fdrSQVXnAd8kRPcD5tn7s4Ez7f0SLFekCrh/oY3Aa2Rgm8onfhkF5DcTUKFxWgBVVVUZKQBVZdasWQwcOJDp06fz1FNP8fTTT9O/f/+0aU2MjDGFEXcQas0D8BJaC6q6XlUfBMZhLQ7ze69ps60GLwVOB/4JjAZ62w+yVEQqgDexWwUu7gZeFJFp6W4uIpcAl2T5bGnxUwsgMAHlD+e3zaQFsGXLFk4//XS2bt3Kvffey49//OOM3pGpFoCjeHL5DcfjcWKxGNFoNOl2165ddOrUKf2Ncoi1IEzxVJpE5FDgP7Aq4ZuBfwCeZyRmWwr+J/CgiPwOa0HihsU7VfWKZAlU9XMReRc4J93NVfUx4DEAEcl5j1dNTQ3z5s1rOC4pKWkI4XC40bETQqFQ0vhk50KhEKFQqNEf29RMYL+0AEzOA9i2bRurV69m9+7dzTpki8VijB07lkGDBnH//fdn1SLMtwJQVeLxeEPh7ASnr0NEGsW7r4tGo02O3dcmIiIN/7fErTP72JQJqIiYhlXon6yqazNNnJUCUNVPgREAItIP7xMP7gSeBjz7qsgHpaWlDB8+HLA+ePdHmuxDdoe6urqkH3/iceKftKamhnA4zPLlyxsUhqMonJAsLpMgIo32q6uricVi1NbWNsQ51wQtg5bj1IqvvvpqrrrqKgYMGMDEiRMZOXJk0t93/Pjx1NfXc9999yEiRKPRRgWul/1oNEpNTQ2rVq1qiEsXnO8xcT8V7gqNs19bW8vatWspLS1tUgGKRCIpK0dOoZ7NN7dq1Srq6+szfi8tQovLFYSqDmtJ+qwUgIh0U9UqewLCeODPXtKp6qcisgw4DXgvG9m5xqmF5Nsk9NFHH9GzZ0+6dOnS7B802bE71NfXN4lLVVjU1NRQU1PTsHKV+1w2OAokMSSe27VrFwsWLGhyvrlt4n6y4+bYsmULn332WZMx4+4hk85+c9vEfXdIjK+rqyMajdKuXTsuv/xyduzYwddff82UKVPo3bs37do1uGZhy5Yt9OrVi5tuuom33norqcJOFZeo5GOxGPX19Q2FcyQSSVkpcBfi7jj3u/HCggUL6N+/PxUVFZ7TtJRwOExNTU3B5EHxtABEZKaqni0iH9HYLbQAqqqevAOmLfVE5O/AcGAfEVkN3AJ0EBFnlM+zWP4ovDIB+DCD69sEjglIRBpqRvlm48aNVFVVcdhhh7X4Xu4C0FE0znFiITl//vwGmYmFZ7Jtqrh0z+MuwHbt2kW3bt3o0GHPJEgvyiaZEkt2PpnS27BhA9u2bePQQw9tuG99fT2PPvoo559/Pueddx633HILq1atYvTo0bzyyisMHjzYU/6aY926dRx88MEtvk8m+GVdYGdJyCLgKnt7aktuklYBqOrYFKcmeRGgql8C33YdL8agDyJTk2hMzT3IlanHXSCm61cIhUK0b98+J3K9UlZWxl577cVee+1VMJnJfodIJMKVV17J2LFjGT9+PIceeiiRSIRJkyblpPA3halFYQo+D6BIJoKp6jp7+1VL7uO7mcCmxsYHncD5xWQncDK6du3K5MmTufTSS1myZAnnnJN27EOrxk8tgCIbBbSDPSagUiAC7FJVT8OnfKcATAwBdeQGw0DbFs0pAIcjjzySI488skBPlD9MKAAzriCKxgQEgKo2TBcX689+OvAdr+mLR9XlCBOTwCCYCNYW8aIA2gqmFoYvvCsIb5PAWuNIIbX4J3Cy1zS+bAGYUABBC6Dt4ScFYKIPwKQriGJBREa5DkPAEMDz0ClfKgATJqBgQZj8Y8IbqF8UgCkTUOE7gYtrHgDWkHqHKPAllhnIE75TACZNQIWujZtYEtIvBSIECiDfmPh9Fagrok5gVc3YBbQb3ykAUyYgKPxIFROtDjA3IseETBMKwJFbyDyXlJRQV1eX/sIiRymOYaAOIvJgc+dV9crmzgcKoA1jqgXgl34HUwrA8QdUyO/YNwvDF9koIKAdMADLHxBYzjmXAfO9JPadAohGo0b6AExgau6BX/CTAjC1MDwUtlKhUJAWgIj8Cct+Xwf8G/i5qm61z90EXATEgCtV9eVmbjUQ+K6qRu20fwbeUNVxXp6jeIxdOcJPLQBTCsBUC8AvncAmXEKbGAY5C4XSAAANAElEQVQKZvJaoBXBZgPftn32fAbcBCAiA4AxwGFYC3E9IiLNFVh7A+5JXx3sOE/4oyrsIhaLNXLS1ZYxVRgHJqD8YkoBmGgBOHMBClVpUy1MC0BVX3EdvgOcZe+fDjypqrXAFyKyEjiG1CadPwIfisgcLEdwxwO3en0OXyoAExOyTOC3FkChMdkJ7CcFEI1GKS0tzGqyhhaE+U/22PB7YSkEh9V2XFJU9XEReREYakfdqKrrvQr2nQIwtRykifH4fiuMC00oFDKiAEyYY0z1ARTcHYRCBj/tPiLyvuv4MXsxKwBE5FVg3yTpblbVWfY1N2ON3/9bNo9ru3/4IXCQqt4mIvuLyDGqusBLet8pABMTwUwNxwxaAPklaAHkn0LPBs5wJvAmVR2S8l6qP2wusYhciOXO+Qe650Nag73Ers1+dlwqHsFah/37wG3ADuAZ4Oh0Dw9BJ3DBZJpqAQQKIL/4qQ/ARCewCX9AhfAFJCI/Am4Afqqq1a5TzwNjRKRMRA4E+gLN1eaHqupl2O4fVHULlldQT/iuBeAnE5Cp2cemKLRsUyYgP3UCF9oEVEBvoA8BZcBs+z/6jqqOU9WlIjITayx/FLhMVZv74evtUUIKICJdsVoEnvCdAjBhAjI19NSU4vFLC8DkKKBCyzU9CqhwFGYmsKp+q5lzE7BWTvTCg8BzQDcRmYA1mmi81+fwpQLwSwsgmAmcX/w0DNRUXk20AIppQRhV/ZuILAR+gDUMdKSqfuI1ve8UgCkTkF9aAMFM4PxjQgGYIhwOF9QHkVJ03kBR1U+BT7NJ6zsFYKJj1E+dwBCYgPKNnxSAiVXBimk9gJbiOwVgApMtgMAElD8CBZB/Cj4MVFvnal/5IlAABcBUC8BP8wD85g46UAD5o8i8gbaItKWDiEwTkSoR+dgVN0hE3hGRRSLyvogcY8eHRGS6iLwtIofZccNFREXkNFf6/xWR4XnIT6vEVAvA1DwAv+DHFkCh81voUUBWJ7B4Cm0BL6XDX7G80rm5B/iDqg4Cfm8fA4wA3gXOAK5zXb8auLlFT5oDTBVOJlsAgQmo7WFKAZiYDFbwUUBYzuC8hLZA2lJJVecB3yRGs8cF6V7AWnu/BGsSQhxrSJLDYmCbiJzUoqdtISbH4/ulBQDmOoH90vowpQBMLQzfFmcCtxay7QO4GnhZRO7FUiLH2vEvAzOAnwGXJKSZANyO5Qe7WUTkkiTpW4yjAApdS43FYkQikYLJc/DbTGC/YLIFkIvCWFWJRqPEYrGGEI1GG+Lc2/r6+oLmVZFgFJAHfglco6rPiMjZwFTgh/aqNGOSJVDVeSKCiHw33c1tj3qPAYhIzkqUkpISIpEI8+bNS1pQlZSUeA6hUCjtsRNncg0Cv5iA/GR2yvVMYFVFVYnFYsTj8UZb935dXR2rV68mEok0uaa5kIiINPqvhMPhpNuysjIqKiro06dPzvKa/sfIyBto0ZOtArgAuMrefwqY4jHdBKxpyoXt1rcJh8McfXRyJ3nOHyAxxOPxhhqJsx+Px6mvr0/6J3D/gZz9+vp6RIQVK1Y0kesoCkdZuI+9BBFJGReNRtm6dSu24m1y3olPPG4pfiqMm8MpWOPxeLP7zreSGOc+5w7bt2+nurqa5cuXJz3vfHfuQt0JqUj8BhMrNaFQiK5duzbkKxwOEw6Hm1R8nALcHV9s30NbMe94IVsFsBY4AZiL5Ya0acmWBFV9RURuB3pkKTdviEjDR10oEmte7j+vu1Bw/5nd28SCI/G4c+fOfPnllykLl2QFUS7yFI1GmTdvXiOFkmrb3L6bdIXIrl272L59e6P3564lO/up4lLtp6Ouro65c+emPJ9M4SbbT1TmyeKcQrWyspKuXbs2OucUtKkqEc75YiuMC44CbWSEjxfSlnYi8ndgONbiB6uBW4CLgUkiEsZyQ5qJvX4CMCvzR217uAuBtkC6AjXZucS0qY69kE55JFM07m1zCivARwR9AHtQ1bEpTh3lRYCqzsVqKTjHz9N4hFBAGyEoNAPaBIEJKCAgIMCHKBl40y9+AgUQEBAQ0IAEJqCAgIAAXxJ0AgcEBAT4mKAPICAgIMCnBAogICAgwIeoHXxCMSiAr0TkANMPERAQ0Or5Kid3CVoArQdV7ZPL+4nI+6o6JJf3bK1y/ZRXv8n1U14LKzcYBRQQEBDgT6o+fZkHj93H49Wb8vosBSBQAAEBAQE2qpq4+FWbpm04ocmMx3wk10959ZtcP+XVpNw2jQQLeAQEBAT4Ez+2AAICAgICKEIFICLTRKRKRD5OiL9CRD4VkaUico8dVykic0Rkp4g8lHD9cBF533Xt6SLyT9f5m0Rkpet4tojUepHrTi8iy0XkZFf8GBH5QESuto+vEpEHXOcni8irrrzuEJHNrvO3isgaEVlkh1Ps+FIReVxEPhKRxSIyPJd5bUZuRESesOV+IiI3ZZNX+3i+iFR7lHuuK26RiMRFZFC+82ufG2g/61I73+0ylWu/260ist1DXvuIyG5X/J8L8W5d5/cX6z90fYHe7TGuuMUickYL5F4hIg8SkBz3wiDFEIDjgSOBj11xJwKvAmX2cTd72x74LjAOeCjhPv8AyoH7gEOArsB61/nngQ9c95oBPOhR7gBgMVAGHAj8Gyixz/0TKAGeBDoAQ4AFrnu+A7xnX3M88BLwtev8rcD1SX6Xy4DHnecAFgKhHOY1ldxzgCft/QrgS6BPpnm1j18FfuNFbsIzHA78O8fvNlV+w8AS4Aj7uNL1/J7l2u92WsL5VDL7uJ8tD99xs78x8DTWyn/Xu+Ly9m7t7yhs7/cAqlzHmcr9OzCmUOVTsYWiawGo6jzgm4ToXwJ/VNVa+5oqe7tLVd/EWrQmkRB7nL+Kqm4EtovIt+zzvYBn2LPgfW/gDS9ygdOxCsVaVf0CWAkcY59zBhmrvb8I6Cci5SKyF7Dbjjvczuu3gV3pfxkGAP/neo6tWH+OXOU1FQq0F2txoHKgDnBqtZ7zal/XF3jdo1w3Y7EKBId85ncEsERVFwOo6mZVdRa+9SzXfrcDgOqMctqUfOYVERkJfAEsTTxlb3P+blW1Wq31xQHa0XhubqZyjwXe8iLXjxSdAkhBP+B7IvKuiLwuIskX/m3MFOBtrFryJ3bcW8CxItIfa5nLd+zjMHAEVs3Pi9xewNeu61bbcQDPAu8D76vqDvtD/xA4GvgO8K5Lbi+sjzxxDeXLRWSJbUbY245bDPxURMIiciDWgj29c5jXVHKfxlJQ64BVwL2q6ijobPK6zqNcN/+BVdNzyGd++wEqIi/bpogbWiB3AFaB5SWvB4rIh/Z39r1C5FVEOgA3An9Icn1e362IDBWRpcBHwDiXQshYrqq6/4sBLtqKAggDXbA+gF8DM0WaX5ZKVV9W1SNV9TpX9NtYNYZjgfnAAmAoMBj4FKjNgdwnVHWwqt7XjNz5ruMPEm7xKHAwMAjrD+XcZxqWonkfeMC+ZyyHeU0l9xhbTk8sc9d1InJQlnl9O8lPlkouYBUUQLWqNtiW85zfMJZZ8Vx7e4aI/CBLuf+mce02lcx1wP6qOhi4Fvh/ItKpAHm9FbhfVXcmXJ/3d6uq76rqYVgF+01i97PkSG6ATVtRAKuBZ9ViAVZz2OtsPjdv4fqQVHUHVhN0OMk/pFRy17Cn9g2wnx2XTu4wrI/3E6za4bFYtvwGVHWDqsZUNQ78Bdu0pKpRVb1GVQep6ulAZ+CzXOU1lVysPoCXVLXeNj29xR7TU6Z5zUSuwxga1/7znd/VwDxV3aSq1cALWH1S2cj1+m5rVXWzvb8QS3H0K0BehwL3iMiXwNXAb0Xkcg9yc/VusVs1O7FMoTmRG7CHtqIA/onVIYuI9ANKyW6a9idYNdnvYjUrwbInjiO5HTGV3OeBMSJSZptj+mLVwlIxH6sV0VVVq1RVgY1YfQnvuy8UkR6uwzOAj+34ChFpb++fBERVdVmu8ppKLpbZ5/v2Ne3tfHyaZV4zkYuIhICzaWz/T0Wu8vsycLj9e4eBE4Bsf2ev77ariJTY+wdhfU+f5zuvqvo9Ve2jlj+uB4A7VfWhxPQucvJuReRA+7dFLEeQh2ANLsiJ3AAX2gp6ojMJWLW9dUA9Vm3sIqyCdwbWB/QB8H3X9V9idRrvtK8fkOb+/wLedB1fiNVMfy5DuTdj1dSWAz/2kK+lwAzX8a22rESZ/41lF12CpWh62Nf3sWV9gjXi4gAPMjPJayq5HbBGiCzFKgh/nWVed2IV5J7k2umGA+9k8O20OL92uvPsPHwM3NMCuRs8/sZn2vIW2d/ZaYXKa8I7anY0Vq7eLXB+Qn5HtkBuONdlUFsKwUzggICAAJ/SVkxAAQEBAQEZEiiAgICAAJ8SKICAgIAAnxIogICAgACfEiiAgICAAJ8SKICAgIAAnxIogICAgACfEiiAgICAAJ/y/wH/S3d2agIdGwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "display.plot_ppi_map('reflectivity', 1, vmin=-32, vmax=64, min_lon=minlon, max_lon=maxlon, \\\n",
    "    min_lat=minlat, max_lat=maxlat, \\\n",
    "    lat_lines = local_lats, lon_lines = local_lons, \\\n",
    "    #shapefile=GIS_shapefile, \\\n",
    "    projection=projection, \\\n",
    "    lat_0=radar.latitude['data'][0],lon_0=radar.longitude['data'][0])\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.6.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}