{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# II - Accessing Astronomical Data From Python\n",
    "\n",
    "## 0.- Installing necessary packages\n",
    "* ``conda install astropy``\n",
    "* ``conda install -c astropy aplpy astroquery``\n",
    "\n",
    "Before doing to data analysis, we need to find, load and pre-process data!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.- Astronomical Data from WebPages"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Function to retrieve the tarball and the fits file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import urllib\n",
    "import tarfile\n",
    "import sys\n",
    "#%matplotlib inline\n",
    "%matplotlib notebook\n",
    "global DOWNLOADS_DIR \n",
    "DOWNLOADS_DIR= '.'\n",
    "\n",
    "def download_and_extract(url):\n",
    "    # Obtain the filename\n",
    "    name = url.rsplit('/', 1)[-1]\n",
    "    filename = os.path.join(DOWNLOADS_DIR, name)\n",
    "    # Download the file if not found\n",
    "    if not os.path.isfile(filename):\n",
    "        urllib.urlretrieve(url, filename)\n",
    "    # Decompress (if needed) and copy the selected file to the DOWNLOADS_DIR\n",
    "    sdir=filename.rsplit('ReferenceImages',1)[0]+\"ReferenceImages\"\n",
    "    if not os.path.isdir(sdir):\n",
    "        tar = tarfile.open(filename)\n",
    "        tar.extractall(path=DOWNLOADS_DIR)\n",
    "        tar.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TWHydra_CO3_2line.image.fits\r\n",
      "TWHydra_CO3_2line.image.mom.weighted_coord.fits\r\n",
      "TWHydra_CO3_2line.image.mom.weighted_dispersion_coord.fits\r\n",
      "TWHydra_CO3_2line.image.mom0.fits\r\n",
      "TWHydra_HCOplusline.image.fits\r\n",
      "TWHydra_HCOplusline.image.mom.weighted_coord.fits\r\n",
      "TWHydra_HCOplusline.image.mom.weighted_dispersion_coord.fits\r\n",
      "TWHydra_HCOplusline.image.mom0.fits\r\n",
      "TWHydra_contall_apcal.image.fits\r\n"
     ]
    }
   ],
   "source": [
    "# Data from ALMA science verification \n",
    "twhydra_url = 'https://almascience.nrao.edu/almadata/sciver/TWHya/TWHYA_BAND7_ReferenceImages.tgz'\n",
    "download_and_extract(twhydra_url)\n",
    "\n",
    "!ls TWHYA_BAND7_ReferenceImages"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.- Loading and a Quick Look at the Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2.0'"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from astropy.io import fits\n",
    "import logging\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "# Load File\n",
    "hdulist = fits.open(\"TWHYA_BAND7_ReferenceImages/TWHydra_CO3_2line.image.mom0.fits\")\n",
    "twhydra = hdulist[0]\n",
    "import astropy\n",
    "astropy.version.version"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Show the header"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SIMPLE  =                    T /Standard FITS                                   \n",
       "BITPIX  =                  -32 /Floating point (32 bit)                         \n",
       "NAXIS   =                    4                                                  \n",
       "NAXIS1  =                  100                                                  \n",
       "NAXIS2  =                  100                                                  \n",
       "NAXIS3  =                    1                                                  \n",
       "NAXIS4  =                    1                                                  \n",
       "BSCALE  =   1.000000000000E+00 /PHYSICAL = PIXEL*BSCALE + BZERO                 \n",
       "BZERO   =   0.000000000000E+00                                                  \n",
       "BMAJ    =   4.668472210566E-04                                                  \n",
       "BMIN    =   4.255372948117E-04                                                  \n",
       "BPA     =   2.230152130127E+01                                                  \n",
       "BTYPE   = 'Intensity'                                                           \n",
       "OBJECT  = 'TW Hya  '                                                            \n",
       "                                                                                \n",
       "BUNIT   = 'JY/BEAM.KM/S'       /Brightness (pixel) unit                         \n",
       "EQUINOX =   2.000000000000E+03                                                  \n",
       "LONPOLE =   1.800000000000E+02                                                  \n",
       "LATPOLE =  -3.470476691248E+01                                                  \n",
       "PC001001=   1.000000000000E+00                                                  \n",
       "PC002001=   0.000000000000E+00                                                  \n",
       "PC003001=   0.000000000000E+00                                                  \n",
       "PC004001=   0.000000000000E+00                                                  \n",
       "PC001002=   0.000000000000E+00                                                  \n",
       "PC002002=   1.000000000000E+00                                                  \n",
       "PC003002=   0.000000000000E+00                                                  \n",
       "PC004002=   0.000000000000E+00                                                  \n",
       "PC001003=   0.000000000000E+00                                                  \n",
       "PC002003=   0.000000000000E+00                                                  \n",
       "PC003003=   1.000000000000E+00                                                  \n",
       "PC004003=   0.000000000000E+00                                                  \n",
       "PC001004=   0.000000000000E+00                                                  \n",
       "PC002004=   0.000000000000E+00                                                  \n",
       "PC003004=   0.000000000000E+00                                                  \n",
       "PC004004=   1.000000000000E+00                                                  \n",
       "CTYPE1  = 'RA---SIN'                                                            \n",
       "CRVAL1  =   1.654660207616E+02                                                  \n",
       "CDELT1  =  -8.333333333333E-05                                                  \n",
       "CRPIX1  =   5.100000000000E+01                                                  \n",
       "CUNIT1  = 'deg     '                                                            \n",
       "CTYPE2  = 'DEC--SIN'                                                            \n",
       "CRVAL2  =  -3.470476691248E+01                                                  \n",
       "CDELT2  =   8.333333333333E-05                                                  \n",
       "CRPIX2  =   5.100000000000E+01                                                  \n",
       "CUNIT2  = 'deg     '                                                            \n",
       "CTYPE3  = 'FREQ    '                                                            \n",
       "CRVAL3  =   3.458006038050E+11                                                  \n",
       "CDELT3  =  -1.384141518555E+05                                                  \n",
       "CRPIX3  =  -3.900000000000E+01                                                  \n",
       "CUNIT3  = 'HZ      '                                                            \n",
       "CTYPE4  = 'STOKES  '                                                            \n",
       "CRVAL4  =   1.000000000000E+00                                                  \n",
       "CDELT4  =   1.000000000000E+00                                                  \n",
       "CRPIX4  =   1.000000000000E+00                                                  \n",
       "CUNIT4  = '        '                                                            \n",
       "PV2_1   =   0.000000000000E+00                                                  \n",
       "PV2_2   =   0.000000000000E+00                                                  \n",
       "RESTFRQ =   3.457959900000E+11 /Rest Frequency (Hz)                             \n",
       "SPECSYS = 'LSRK    '           /Spectral reference frame                        \n",
       "ALTRVAL =  -3.999999947043E+03 /Alternate frequency reference value             \n",
       "ALTRPIX =  -3.900000000000E+01 /Alternate frequency reference pixel             \n",
       "VELREF  =                  257 /1 LSR, 2 HEL, 3 OBS, +256 Radio                 \n",
       "COMMENT casacore non-standard usage: 4 LSD, 5 GEO, 6 SOU, 7 GAL                 \n",
       "TELESCOP= 'ALMA    '                                                            \n",
       "OBSERVER= 'Unknown '                                                            \n",
       "DATE-OBS= '2011-04-22T00:15:41.760000'                                          \n",
       "TIMESYS = 'UTC     '                                                            \n",
       "OBSRA   =   1.654660207616E+02                                                  \n",
       "OBSDEC  =  -3.470476691248E+01                                                  \n",
       "OBSGEO-X=   2.225142180269E+06                                                  \n",
       "OBSGEO-Y=  -5.440307370349E+06                                                  \n",
       "OBSGEO-Z=  -2.481029851874E+06                                                  \n",
       "DATE    = '2011-05-30T22:09:28.571000' /Date FITS file was written              \n",
       "ORIGIN  = 'CASA casacore alma-evla '                                            \n",
       "HISTORY CASA START LOGTABLE                                                     \n",
       "HISTORY 2011-05-27T17:37:11 INFO SRCCODE='imager::clean()'                      \n",
       "HISTORY 2011-05-27T17:37:11 INFO SRCCODE='imager::clean()'                      \n",
       "HISTORY Tue May 24 20:37:43 2011  HISTORY calibrater::setdata [Beginning selectv\n",
       "HISTORY >is--(MSSelection version)-------, chanmode=none nchan=1 start=0 step=1 \n",
       "HISTORY >Start='0km/s' mStep='0km/s' msSelect='']                               \n",
       "HISTORY Tue May 24 20:38:01 2011  HISTORY calibrater::correct [] Beginning corre\n",
       "HISTORY >ct---------------------------                                          \n",
       "HISTORY Tue May 24 20:38:04 2011  HISTORY applycal [] taskname = applycal       \n",
       "HISTORY Tue May 24 20:38:04 2011  HISTORY applycal [] vis         = \"X3c1.ms\"   \n",
       "HISTORY Tue May 24 20:38:04 2011  HISTORY applycal [] msselect    = \"\"          \n",
       "HISTORY Tue May 24 20:38:04 2011  HISTORY applycal [] gaintable   = \"['X3c1.tsys\n",
       "HISTORY >.fdm', 'wvr_X3c1.cal']\"                                                \n",
       "HISTORY Tue May 24 20:38:04 2011  HISTORY applycal [] gainfield   = \"['0']\"     \n",
       "HISTORY Tue May 24 20:38:04 2011  HISTORY applycal [] interp      = \"['nearest',\n",
       "HISTORY > 'nearest']\"                                                           \n",
       "HISTORY Tue May 24 20:38:04 2011  HISTORY applycal [] spwmap      = []          \n",
       "HISTORY Tue May 24 20:38:04 2011  HISTORY applycal [] calwt       = True        \n",
       "HISTORY Tue May 24 20:38:04 2011  HISTORY applycal [] gaincurve   = False       \n",
       "HISTORY Tue May 24 20:38:04 2011  HISTORY applycal [] opacity     = 0.0         \n",
       "HISTORY Tue May 24 20:38:05 2011  HISTORY calibrater::setdata [Beginning selectv\n",
       "HISTORY >is--(MSSelection version)-------, chanmode=none nchan=1 start=0 step=1 \n",
       "HISTORY >Start='0km/s' mStep='0km/s' msSelect='']                               \n",
       "HISTORY Tue May 24 20:38:21 2011  HISTORY calibrater::correct [] Beginning corre\n",
       "HISTORY >ct---------------------------                                          \n",
       "HISTORY Tue May 24 20:38:24 2011  HISTORY applycal [] taskname = applycal       \n",
       "HISTORY Tue May 24 20:38:24 2011  HISTORY applycal [] vis         = \"X3c1.ms\"   \n",
       "HISTORY Tue May 24 20:38:24 2011  HISTORY applycal [] msselect    = \"\"          \n",
       "HISTORY Tue May 24 20:38:24 2011  HISTORY applycal [] gaintable   = \"['X3c1.tsys\n",
       "HISTORY >.fdm', 'wvr_X3c1.cal']\"                                                \n",
       "HISTORY Tue May 24 20:38:24 2011  HISTORY applycal [] gainfield   = \"['1']\"     \n",
       "HISTORY Tue May 24 20:38:24 2011  HISTORY applycal [] interp      = \"['nearest',\n",
       "HISTORY > 'nearest']\"                                                           \n",
       "HISTORY Tue May 24 20:38:24 2011  HISTORY applycal [] spwmap      = []          \n",
       "HISTORY Tue May 24 20:38:24 2011  HISTORY applycal [] calwt       = True        \n",
       "HISTORY Tue May 24 20:38:25 2011  HISTORY applycal [] gaincurve   = False       \n",
       "HISTORY Tue May 24 20:38:25 2011  HISTORY applycal [] opacity     = 0.0         \n",
       "HISTORY Tue May 24 20:38:25 2011  HISTORY calibrater::setdata [Beginning selectv\n",
       "HISTORY >is--(MSSelection version)-------, chanmode=none nchan=1 start=0 step=1 \n",
       "HISTORY >Start='0km/s' mStep='0km/s' msSelect='']                               \n",
       "HISTORY Tue May 24 20:38:42 2011  HISTORY calibrater::correct [] Beginning corre\n",
       "HISTORY >ct---------------------------                                          \n",
       "HISTORY Tue May 24 20:39:46 2011  HISTORY applycal [] taskname = applycal       \n",
       "HISTORY Tue May 24 20:39:46 2011  HISTORY applycal [] vis         = \"X3c1.ms\"   \n",
       "HISTORY Tue May 24 20:39:46 2011  HISTORY applycal [] msselect    = \"\"          \n",
       "HISTORY Tue May 24 20:39:46 2011  HISTORY applycal [] gaintable   = \"['X3c1.tsys\n",
       "HISTORY >.fdm', 'wvr_X3c1.cal']\"                                                \n",
       "HISTORY Tue May 24 20:39:46 2011  HISTORY applycal [] gainfield   = \"['2']\"     \n",
       "HISTORY Tue May 24 20:39:46 2011  HISTORY applycal [] interp      = \"['nearest',\n",
       "HISTORY > 'nearest']\"                                                           \n",
       "HISTORY Tue May 24 20:39:46 2011  HISTORY applycal [] spwmap      = []          \n",
       "HISTORY Tue May 24 20:39:46 2011  HISTORY applycal [] calwt       = True        \n",
       "HISTORY Tue May 24 20:39:46 2011  HISTORY applycal [] gaincurve   = False       \n",
       "HISTORY Tue May 24 20:39:46 2011  HISTORY applycal [] opacity     = 0.0         \n",
       "HISTORY Tue May 24 20:39:47 2011  HISTORY calibrater::setdata [Beginning selectv\n",
       "HISTORY >is--(MSSelection version)-------, chanmode=none nchan=1 start=0 step=1 \n",
       "HISTORY >Start='0km/s' mStep='0km/s' msSelect='']                               \n",
       "HISTORY Tue May 24 20:40:04 2011  HISTORY calibrater::correct [] Beginning corre\n",
       "HISTORY >ct---------------------------                                          \n",
       "HISTORY Tue May 24 20:40:27 2011  HISTORY applycal [] taskname = applycal       \n",
       "HISTORY Tue May 24 20:40:27 2011  HISTORY applycal [] vis         = \"X3c1.ms\"   \n",
       "HISTORY Tue May 24 20:40:27 2011  HISTORY applycal [] msselect    = \"\"          \n",
       "HISTORY Tue May 24 20:40:27 2011  HISTORY applycal [] gaintable   = \"['X3c1.tsys\n",
       "HISTORY >.fdm', 'wvr_X3c1.cal']\"                                                \n",
       "HISTORY Tue May 24 20:40:27 2011  HISTORY applycal [] gainfield   = \"['4']\"     \n",
       "HISTORY Tue May 24 20:40:27 2011  HISTORY applycal [] interp      = \"['nearest',\n",
       "HISTORY > 'nearest']\"                                                           \n",
       "HISTORY Tue May 24 20:40:27 2011  HISTORY applycal [] spwmap      = []          \n",
       "HISTORY Tue May 24 20:40:27 2011  HISTORY applycal [] calwt       = True        \n",
       "HISTORY Tue May 24 20:40:27 2011  HISTORY applycal [] gaincurve   = False       \n",
       "HISTORY Tue May 24 20:40:27 2011  HISTORY applycal [] opacity     = 0.0         \n",
       "HISTORY Tue May 24 20:51:12 2011  HISTORY calibrater::setdata [Beginning selectv\n",
       "HISTORY >is--(MSSelection version)-------, chanmode=none nchan=1 start=0 step=1 \n",
       "HISTORY >Start='0km/s' mStep='0km/s' msSelect='']                               \n",
       "HISTORY Tue May 24 20:51:26 2011  HISTORY calibrater::correct [] Beginning corre\n",
       "HISTORY >ct---------------------------                                          \n",
       "HISTORY Tue May 24 20:51:37 2011  HISTORY applycal [] taskname = applycal       \n",
       "HISTORY Tue May 24 20:51:37 2011  HISTORY applycal [] vis         = \"X3c1.ms\"   \n",
       "HISTORY Tue May 24 20:51:37 2011  HISTORY applycal [] msselect    = \"\"          \n",
       "HISTORY Tue May 24 20:51:37 2011  HISTORY applycal [] gaintable   = \"['X3c1.tsys\n",
       "HISTORY >.fdm', 'wvr_X3c1.cal']\"                                                \n",
       "HISTORY Tue May 24 20:51:37 2011  HISTORY applycal [] gainfield   = \"['4', '3']\"\n",
       "HISTORY Tue May 24 20:51:37 2011  HISTORY applycal [] interp      = \"['nearest',\n",
       "HISTORY > 'nearest']\"                                                           \n",
       "HISTORY Tue May 24 20:51:37 2011  HISTORY applycal [] spwmap      = []          \n",
       "HISTORY Tue May 24 20:51:37 2011  HISTORY applycal [] calwt       = True        \n",
       "HISTORY Tue May 24 20:51:37 2011  HISTORY applycal [] gaincurve   = False       \n",
       "HISTORY Tue May 24 20:51:37 2011  HISTORY applycal [] opacity     = 0.0         \n",
       "HISTORY Tue May 24 20:56:25 2011  HISTORY ms::split() [fieldids= spwids=17,19,21\n",
       "HISTORY >,23 step=[1] which='corrected'] X3c1_wvrtsys.ms split from /export/data\n",
       "HISTORY >1/data_2/SV_data/test_TWHydra_may24/X3c1.ms                            \n",
       "HISTORY Tue May 24 20:56:25 2011  HISTORY split [] taskname=split               \n",
       "HISTORY Tue May 24 20:56:25 2011  HISTORY split [] vis         = \"X3c1.ms\"      \n",
       "HISTORY Tue May 24 20:56:25 2011  HISTORY split [] outputvis   = \"X3c1_wvrtsys.m\n",
       "HISTORY >s\"                                                                     \n",
       "HISTORY Tue May 24 20:56:25 2011  HISTORY split [] datacolumn  = \"corrected\"    \n",
       "HISTORY Tue May 24 20:56:25 2011  HISTORY split [] field       = \"\"             \n",
       "HISTORY Tue May 24 20:56:25 2011  HISTORY split [] spw         = \"17,19,21,23\"  \n",
       "HISTORY Tue May 24 20:56:25 2011  HISTORY split [] width       = 1              \n",
       "HISTORY Tue May 24 20:56:25 2011  HISTORY split [] antenna     = \"\"             \n",
       "HISTORY Tue May 24 20:56:25 2011  HISTORY split [] timebin     = \"0.0s\"         \n",
       "HISTORY Tue May 24 20:56:25 2011  HISTORY split [] timerange   = \"\"             \n",
       "HISTORY Tue May 24 20:56:25 2011  HISTORY split [] scan        = \"\"             \n",
       "HISTORY Tue May 24 20:56:25 2011  HISTORY split [] array       = \"\"             \n",
       "HISTORY Tue May 24 20:56:25 2011  HISTORY split [] uvrange     = \"\"             \n",
       "HISTORY Tue May 24 20:56:25 2011  HISTORY split [] correlation = \"\"             \n",
       "HISTORY Tue May 24 20:56:25 2011  HISTORY split [] combine     = \"\"             \n",
       "HISTORY Tue May 24 20:56:25 2011  HISTORY split [] keepflags   = True           \n",
       "HISTORY Tue May 24 22:01:42 2011  HISTORY flagdata [] taskname = flagdata       \n",
       "HISTORY Tue May 24 22:01:42 2011  HISTORY flagdata [] vis      = \"X3c1_wvrtsys.m\n",
       "HISTORY >s\"                                                                     \n",
       "HISTORY Tue May 24 22:01:42 2011  HISTORY flagdata [] mode     = \"manualflag\"   \n",
       "HISTORY Tue May 24 22:02:43 2011  HISTORY flagdata [] taskname = flagdata       \n",
       "HISTORY Tue May 24 22:02:43 2011  HISTORY flagdata [] vis      = \"X3c1_wvrtsys.m\n",
       "HISTORY >s\"                                                                     \n",
       "HISTORY Tue May 24 22:02:43 2011  HISTORY flagdata [] mode     = \"manualflag\"   \n",
       "HISTORY Wed May 25 14:40:38 2011  HISTORY flagdata [] taskname = flagdata       \n",
       "HISTORY Wed May 25 14:40:38 2011  HISTORY flagdata [] vis      = \"X3c1_wvrtsys.m\n",
       "HISTORY >s\"                                                                     \n",
       "HISTORY Wed May 25 14:40:38 2011  HISTORY flagdata [] mode     = \"manualflag\"   \n",
       "HISTORY Wed May 25 14:40:58 2011  HISTORY flagdata [] taskname = flagdata       \n",
       "HISTORY Wed May 25 14:40:58 2011  HISTORY flagdata [] vis      = \"X3c1_wvrtsys.m\n",
       "HISTORY >s\"                                                                     \n",
       "HISTORY Wed May 25 14:40:58 2011  HISTORY flagdata [] mode     = \"shadow\"       \n",
       "HISTORY Wed May 25 14:41:19 2011  HISTORY flagdata [] taskname = flagdata       \n",
       "HISTORY Wed May 25 14:41:19 2011  HISTORY flagdata [] vis      = \"X3c1_wvrtsys.m\n",
       "HISTORY >s\"                                                                     \n",
       "HISTORY Wed May 25 14:41:19 2011  HISTORY flagdata [] mode     = \"manualflag\"   \n",
       "HISTORY Wed May 25 22:02:19 2011  HISTORY concat [] taskname=concat             \n",
       "HISTORY Wed May 25 22:02:19 2011  HISTORY concat [] vis         = \"Band7multi_ap\n",
       "HISTORY >ril22.ms\"                                                              \n",
       "HISTORY Wed May 25 22:02:19 2011  HISTORY concat [] concatvis   = \"X5d8_wvrtsys.\n",
       "HISTORY >ms\"                                                                    \n",
       "HISTORY Wed May 25 22:02:19 2011  HISTORY concat [] freqtol     = \"\"            \n",
       "HISTORY Wed May 25 22:02:19 2011  HISTORY concat [] dirtol      = \"\"            \n",
       "HISTORY Wed May 25 22:05:04 2011  HISTORY concat [] taskname=concat             \n",
       "HISTORY Wed May 25 22:05:04 2011  HISTORY concat [] vis         = \"Band7multi_ap\n",
       "HISTORY >ril22.ms\"                                                              \n",
       "HISTORY Wed May 25 22:05:04 2011  HISTORY concat [] concatvis   = \"X7ef_wvrtsys.\n",
       "HISTORY >ms\"                                                                    \n",
       "HISTORY Wed May 25 22:05:04 2011  HISTORY concat [] freqtol     = \"\"            \n",
       "HISTORY Wed May 25 22:05:04 2011  HISTORY concat [] dirtol      = \"\"            \n",
       "HISTORY Wed May 25 22:34:09 2011  HISTORY im::calc_uvw() (file /var/rpmbuild/BUI\n",
       "HISTORY >LD/casapy/casapy-32.0.15111/code/synthesis/implement/Utilities/FixVis.c\n",
       "HISTORY >, line 435) [] UVWs calculated for fields [-1, 1, -1, -1, -1]          \n",
       "HISTORY Wed May 25 22:39:41 2011  HISTORY flagdata [] taskname = flagdata       \n",
       "HISTORY Wed May 25 22:39:41 2011  HISTORY flagdata [] vis      = \"Band7multi_apr\n",
       "HISTORY >il22.ms\"                                                               \n",
       "HISTORY Wed May 25 22:39:41 2011  HISTORY flagdata [] mode     = \"manualflag\"   \n",
       "HISTORY Wed May 25 22:40:40 2011  HISTORY flagdata [] taskname = flagdata       \n",
       "HISTORY Wed May 25 22:40:40 2011  HISTORY flagdata [] vis      = \"Band7multi_apr\n",
       "HISTORY >il22.ms\"                                                               \n",
       "HISTORY Wed May 25 22:40:40 2011  HISTORY flagdata [] mode     = \"manualflag\"   \n",
       "HISTORY Wed May 25 22:40:44 2011  HISTORY imager::data selection [mode=channel n\n",
       "HISTORY >chan=[0] start=[0] step=[1] mstart='Radialvelocity: 0' mstep='Radialvel\n",
       "HISTORY >city: 0' spectralwindowids=[0] fieldids=[1] msselect=]                 \n",
       "HISTORY Wed May 25 22:40:47 2011  HISTORY imager::data selection [mode=channel n\n",
       "HISTORY >chan=[0] start=[0] step=[1] mstart='Radialvelocity: 0' mstep='Radialvel\n",
       "HISTORY >city: 0' spectralwindowids=[1] fieldids=[1] msselect=]                 \n",
       "HISTORY Wed May 25 22:40:49 2011  HISTORY imager::data selection [mode=channel n\n",
       "HISTORY >chan=[0] start=[0] step=[1] mstart='Radialvelocity: 0' mstep='Radialvel\n",
       "HISTORY >city: 0' spectralwindowids=[2] fieldids=[1] msselect=]                 \n",
       "HISTORY Wed May 25 22:40:51 2011  HISTORY imager::data selection [mode=channel n\n",
       "HISTORY >chan=[0] start=[0] step=[1] mstart='Radialvelocity: 0' mstep='Radialvel\n",
       "HISTORY >city: 0' spectralwindowids=[3] fieldids=[1] msselect=]                 \n",
       "HISTORY Wed May 25 22:40:51 2011  HISTORY imager::data selection [] Selecting da\n",
       "HISTORY >ta                                                                     \n",
       "HISTORY Wed May 25 22:40:52 2011  HISTORY setjy::imager::data selection [] Selec\n",
       "HISTORY >ted 810 out of 188460 visibilities.                                    \n",
       "HISTORY Wed May 25 22:40:54 2011  HISTORY setjy [] taskname = setjy             \n",
       "HISTORY Wed May 25 22:40:54 2011  HISTORY setjy [] vis         = \"Band7multi_apr\n",
       "HISTORY >il22.ms\"                                                               \n",
       "HISTORY Wed May 25 22:40:54 2011  HISTORY setjy [] field       = \"1\"            \n",
       "HISTORY Wed May 25 22:40:54 2011  HISTORY setjy [] spw       =                  \n",
       "HISTORY Wed May 25 22:40:54 2011  HISTORY setjy [] modimage =                   \n",
       "HISTORY Wed May 25 22:40:54 2011  HISTORY setjy [] fluxdensity = -1             \n",
       "HISTORY Wed May 25 22:40:54 2011  HISTORY setjy [] standard    = \"Butler-JPL-Hor\n",
       "HISTORY >izons 2010\"                                                            \n",
       "HISTORY Wed May 25 22:43:43 2011  HISTORY calibrater::setdata [Beginning selectv\n",
       "HISTORY >is--(MSSelection version)-------, chanmode=none nchan=1 start=0 step=1 \n",
       "HISTORY >Start='0km/s' mStep='0km/s' msSelect='']                               \n",
       "HISTORY Wed May 25 22:43:44 2011  HISTORY calibrater::correct [] Beginning corre\n",
       "HISTORY >ct---------------------------                                          \n",
       "HISTORY Wed May 25 22:43:50 2011  HISTORY applycal [] taskname = applycal       \n",
       "HISTORY Wed May 25 22:43:50 2011  HISTORY applycal [] vis         = \"Band7multi_\n",
       "HISTORY >april22.ms\"                                                            \n",
       "HISTORY Wed May 25 22:43:50 2011  HISTORY applycal [] msselect    = \"\"          \n",
       "HISTORY Wed May 25 22:43:50 2011  HISTORY applycal [] gaintable   = \"['bandpass.\n",
       "HISTORY >bcal', 'intphase.gcal', 'flux.cal']\"                                   \n",
       "HISTORY Wed May 25 22:43:50 2011  HISTORY applycal [] gainfield   = \"['0', '0', \n",
       "HISTORY > '0']\"                                                                 \n",
       "HISTORY Wed May 25 22:43:50 2011  HISTORY applycal [] interp      = \"['nearest',\n",
       "HISTORY > 'nearest', 'nearest']\"                                                \n",
       "HISTORY Wed May 25 22:43:50 2011  HISTORY applycal [] spwmap      = []          \n",
       "HISTORY Wed May 25 22:43:50 2011  HISTORY applycal [] calwt       = True        \n",
       "HISTORY Wed May 25 22:43:50 2011  HISTORY applycal [] gaincurve   = False       \n",
       "HISTORY Wed May 25 22:43:50 2011  HISTORY applycal [] opacity     = 0.0         \n",
       "HISTORY Wed May 25 22:44:10 2011  HISTORY calibrater::setdata [Beginning selectv\n",
       "HISTORY >is--(MSSelection version)-------, chanmode=none nchan=1 start=0 step=1 \n",
       "HISTORY >Start='0km/s' mStep='0km/s' msSelect='']                               \n",
       "HISTORY Wed May 25 22:44:10 2011  HISTORY calibrater::correct [] Beginning corre\n",
       "HISTORY >ct---------------------------                                          \n",
       "HISTORY Wed May 25 22:44:15 2011  HISTORY applycal [] taskname = applycal       \n",
       "HISTORY Wed May 25 22:44:15 2011  HISTORY applycal [] vis         = \"Band7multi_\n",
       "HISTORY >april22.ms\"                                                            \n",
       "HISTORY Wed May 25 22:44:15 2011  HISTORY applycal [] msselect    = \"\"          \n",
       "HISTORY Wed May 25 22:44:15 2011  HISTORY applycal [] gaintable   = \"['bandpass.\n",
       "HISTORY >bcal', 'intphase.gcal', 'flux.cal']\"                                   \n",
       "HISTORY Wed May 25 22:44:15 2011  HISTORY applycal [] gainfield   = \"['0', '1', \n",
       "HISTORY > '1']\"                                                                 \n",
       "HISTORY Wed May 25 22:44:15 2011  HISTORY applycal [] interp      = \"['nearest',\n",
       "HISTORY > 'nearest', 'nearest']\"                                                \n",
       "HISTORY Wed May 25 22:44:15 2011  HISTORY applycal [] spwmap      = []          \n",
       "HISTORY Wed May 25 22:44:15 2011  HISTORY applycal [] calwt       = True        \n",
       "HISTORY Wed May 25 22:44:15 2011  HISTORY applycal [] gaincurve   = False       \n",
       "HISTORY Wed May 25 22:44:15 2011  HISTORY applycal [] opacity     = 0.0         \n",
       "HISTORY Wed May 25 22:44:44 2011  HISTORY calibrater::setdata [Beginning selectv\n",
       "HISTORY >is--(MSSelection version)-------, chanmode=none nchan=1 start=0 step=1 \n",
       "HISTORY >Start='0km/s' mStep='0km/s' msSelect='']                               \n",
       "HISTORY Wed May 25 22:44:44 2011  HISTORY calibrater::correct [] Beginning corre\n",
       "HISTORY >ct---------------------------                                          \n",
       "HISTORY Wed May 25 22:45:05 2011  HISTORY applycal [] taskname = applycal       \n",
       "HISTORY Wed May 25 22:45:05 2011  HISTORY applycal [] vis         = \"Band7multi_\n",
       "HISTORY >april22.ms\"                                                            \n",
       "HISTORY Wed May 25 22:45:05 2011  HISTORY applycal [] msselect    = \"\"          \n",
       "HISTORY Wed May 25 22:45:05 2011  HISTORY applycal [] gaintable   = \"['bandpass.\n",
       "HISTORY >bcal', 'intphase.gcal', 'flux.cal']\"                                   \n",
       "HISTORY Wed May 25 22:45:05 2011  HISTORY applycal [] gainfield   = \"['0', '3', \n",
       "HISTORY > '3']\"                                                                 \n",
       "HISTORY Wed May 25 22:45:05 2011  HISTORY applycal [] interp      = \"['nearest',\n",
       "HISTORY > 'nearest', 'nearest']\"                                                \n",
       "HISTORY Wed May 25 22:45:05 2011  HISTORY applycal [] spwmap      = []          \n",
       "HISTORY Wed May 25 22:45:05 2011  HISTORY applycal [] calwt       = True        \n",
       "HISTORY Wed May 25 22:45:05 2011  HISTORY applycal [] gaincurve   = False       \n",
       "HISTORY Wed May 25 22:45:05 2011  HISTORY applycal [] opacity     = 0.0         \n",
       "HISTORY Wed May 25 22:45:46 2011  HISTORY calibrater::setdata [Beginning selectv\n",
       "HISTORY >is--(MSSelection version)-------, chanmode=none nchan=1 start=0 step=1 \n",
       "HISTORY >Start='0km/s' mStep='0km/s' msSelect='']                               \n",
       "HISTORY Wed May 25 22:45:47 2011  HISTORY calibrater::correct [] Beginning corre\n",
       "HISTORY >ct---------------------------                                          \n",
       "HISTORY Wed May 25 22:46:56 2011  HISTORY applycal [] taskname = applycal       \n",
       "HISTORY Wed May 25 22:46:56 2011  HISTORY applycal [] vis         = \"Band7multi_\n",
       "HISTORY >april22.ms\"                                                            \n",
       "HISTORY Wed May 25 22:46:56 2011  HISTORY applycal [] msselect    = \"\"          \n",
       "HISTORY Wed May 25 22:46:56 2011  HISTORY applycal [] gaintable   = \"['bandpass.\n",
       "HISTORY >bcal', 'intphase.gcal', 'flux.cal']\"                                   \n",
       "HISTORY Wed May 25 22:46:56 2011  HISTORY applycal [] gainfield   = \"['0', '4', \n",
       "HISTORY > '4']\"                                                                 \n",
       "HISTORY Wed May 25 22:46:56 2011  HISTORY applycal [] interp      = \"['nearest',\n",
       "HISTORY > 'nearest', 'nearest']\"                                                \n",
       "HISTORY Wed May 25 22:46:56 2011  HISTORY applycal [] spwmap      = []          \n",
       "HISTORY Wed May 25 22:46:56 2011  HISTORY applycal [] calwt       = True        \n",
       "HISTORY Wed May 25 22:46:56 2011  HISTORY applycal [] gaincurve   = False       \n",
       "HISTORY Wed May 25 22:46:56 2011  HISTORY applycal [] opacity     = 0.0         \n",
       "HISTORY Wed May 25 22:47:14 2011  HISTORY calibrater::setdata [Beginning selectv\n",
       "HISTORY >is--(MSSelection version)-------, chanmode=none nchan=1 start=0 step=1 \n",
       "HISTORY >Start='0km/s' mStep='0km/s' msSelect='']                               \n",
       "HISTORY Wed May 25 22:47:15 2011  HISTORY calibrater::correct [] Beginning corre\n",
       "HISTORY >ct---------------------------                                          \n",
       "HISTORY Wed May 25 22:52:06 2011  HISTORY applycal [] taskname = applycal       \n",
       "HISTORY Wed May 25 22:52:06 2011  HISTORY applycal [] vis         = \"Band7multi_\n",
       "HISTORY >april22.ms\"                                                            \n",
       "HISTORY Wed May 25 22:52:06 2011  HISTORY applycal [] msselect    = \"\"          \n",
       "HISTORY Wed May 25 22:52:06 2011  HISTORY applycal [] gaintable   = \"['bandpass.\n",
       "HISTORY >bcal', 'scanphase.gcal', 'flux.cal']\"                                  \n",
       "HISTORY Wed May 25 22:52:06 2011  HISTORY applycal [] gainfield   = \"['0', '3,4'\n",
       "HISTORY >, '3,4']\"                                                              \n",
       "HISTORY Wed May 25 22:52:06 2011  HISTORY applycal [] interp      = \"['nearest',\n",
       "HISTORY > 'linear', 'linear']\"                                                  \n",
       "HISTORY Wed May 25 22:52:06 2011  HISTORY applycal [] spwmap      = []          \n",
       "HISTORY Wed May 25 22:52:06 2011  HISTORY applycal [] calwt       = True        \n",
       "HISTORY Wed May 25 22:52:06 2011  HISTORY applycal [] gaincurve   = False       \n",
       "HISTORY Wed May 25 22:52:06 2011  HISTORY applycal [] opacity     = 0.0         \n",
       "HISTORY Wed May 25 23:09:03 2011  HISTORY ms::split() [fieldids=2 spwids=* step=\n",
       "HISTORY >[1] which='corrected'] TWHydra_corrected.ms split from /export/data_1/d\n",
       "HISTORY >ta_2/SV_data/test_TWHydra_may24/Band7multi_april22.ms                  \n",
       "HISTORY Wed May 25 23:09:03 2011  HISTORY split [] taskname=split               \n",
       "HISTORY Wed May 25 23:09:03 2011  HISTORY split [] vis         = \"Band7multi_apr\n",
       "HISTORY >il22.ms\"                                                               \n",
       "HISTORY Wed May 25 23:09:03 2011  HISTORY split [] outputvis   = \"TWHydra_correc\n",
       "HISTORY >ted.ms\"                                                                \n",
       "HISTORY Wed May 25 23:09:03 2011  HISTORY split [] datacolumn  = \"corrected\"    \n",
       "HISTORY Wed May 25 23:09:03 2011  HISTORY split [] field       = \"2\"            \n",
       "HISTORY Wed May 25 23:09:03 2011  HISTORY split [] spw         = \"\"             \n",
       "HISTORY Wed May 25 23:09:03 2011  HISTORY split [] width       = 1              \n",
       "HISTORY Wed May 25 23:09:03 2011  HISTORY split [] antenna     = \"\"             \n",
       "HISTORY Wed May 25 23:09:03 2011  HISTORY split [] timebin     = \"0.0s\"         \n",
       "HISTORY Wed May 25 23:09:04 2011  HISTORY split [] timerange   = \"\"             \n",
       "HISTORY Wed May 25 23:09:04 2011  HISTORY split [] scan        = \"\"             \n",
       "HISTORY Wed May 25 23:09:04 2011  HISTORY split [] array       = \"\"             \n",
       "HISTORY Wed May 25 23:09:04 2011  HISTORY split [] uvrange     = \"\"             \n",
       "HISTORY Wed May 25 23:09:04 2011  HISTORY split [] correlation = \"\"             \n",
       "HISTORY Wed May 25 23:09:04 2011  HISTORY split [] combine     = \"\"             \n",
       "HISTORY Wed May 25 23:09:04 2011  HISTORY split [] keepflags   = True           \n",
       "HISTORY Thu May 26 18:08:07 2011  HISTORY calibrater::setdata [Beginning selectv\n",
       "HISTORY >is--(MSSelection version)-------, chanmode=none nchan=1 start=0 step=1 \n",
       "HISTORY >Start='0km/s' mStep='0km/s' msSelect='']                               \n",
       "HISTORY Thu May 26 18:08:08 2011  HISTORY calibrater::correct [] Beginning corre\n",
       "HISTORY >ct---------------------------                                          \n",
       "HISTORY Thu May 26 18:12:43 2011  HISTORY applycal [] taskname = applycal       \n",
       "HISTORY Thu May 26 18:12:43 2011  HISTORY applycal [] vis         = \"TWHydra_cor\n",
       "HISTORY >rected.ms\"                                                             \n",
       "HISTORY Thu May 26 18:12:43 2011  HISTORY applycal [] msselect    = \"\"          \n",
       "HISTORY Thu May 26 18:12:43 2011  HISTORY applycal [] gaintable   = \"['self_2.pc\n",
       "HISTORY >al', 'self_ap.cal']\"                                                   \n",
       "HISTORY Thu May 26 18:12:43 2011  HISTORY applycal [] gainfield   = \"['']\"      \n",
       "HISTORY Thu May 26 18:12:43 2011  HISTORY applycal [] interp      = \"['linear']\"\n",
       "HISTORY Thu May 26 18:12:43 2011  HISTORY applycal [] spwmap      = []          \n",
       "HISTORY Thu May 26 18:12:43 2011  HISTORY applycal [] calwt       = False       \n",
       "HISTORY Thu May 26 18:12:43 2011  HISTORY applycal [] gaincurve   = False       \n",
       "HISTORY Thu May 26 18:12:43 2011  HISTORY applycal [] opacity     = 0.0         \n",
       "HISTORY Thu May 26 21:55:23 2011  HISTORY calibrater::setdata [Beginning selectv\n",
       "HISTORY >is--(MSSelection version)-------, chanmode=none nchan=1 start=0 step=1 \n",
       "HISTORY >Start='0km/s' mStep='0km/s' msSelect='']                               \n",
       "HISTORY Thu May 26 21:55:24 2011  HISTORY calibrater::correct [] Beginning corre\n",
       "HISTORY >ct---------------------------                                          \n",
       "HISTORY Thu May 26 21:59:16 2011  HISTORY applycal [] taskname = applycal       \n",
       "HISTORY Thu May 26 21:59:16 2011  HISTORY applycal [] vis         = \"TWHydra_cor\n",
       "HISTORY >rected.ms\"                                                             \n",
       "HISTORY Thu May 26 21:59:16 2011  HISTORY applycal [] msselect    = \"\"          \n",
       "HISTORY Thu May 26 21:59:16 2011  HISTORY applycal [] gaintable   = \"['self_2.pc\n",
       "HISTORY >al', 'self_ap.cal']\"                                                   \n",
       "HISTORY Thu May 26 21:59:16 2011  HISTORY applycal [] gainfield   = \"['']\"      \n",
       "HISTORY Thu May 26 21:59:16 2011  HISTORY applycal [] interp      = \"['linear']\"\n",
       "HISTORY Thu May 26 21:59:16 2011  HISTORY applycal [] spwmap      = []          \n",
       "HISTORY Thu May 26 21:59:16 2011  HISTORY applycal [] calwt       = False       \n",
       "HISTORY Thu May 26 21:59:16 2011  HISTORY applycal [] gaincurve   = False       \n",
       "HISTORY Thu May 26 21:59:16 2011  HISTORY applycal [] opacity     = 0.0         \n",
       "HISTORY Fri May 27 14:46:25 2011  HISTORY calibrater::setdata [Beginning selectv\n",
       "HISTORY >is--(MSSelection version)-------, chanmode=none nchan=1 start=0 step=1 \n",
       "HISTORY >Start='0km/s' mStep='0km/s' msSelect='']                               \n",
       "HISTORY Fri May 27 14:46:26 2011  HISTORY calibrater::correct [] Beginning corre\n",
       "HISTORY >ct---------------------------                                          \n",
       "HISTORY Fri May 27 14:49:55 2011  HISTORY applycal [] taskname = applycal       \n",
       "HISTORY Fri May 27 14:49:55 2011  HISTORY applycal [] vis         = \"TWHydra_cor\n",
       "HISTORY >rected.ms\"                                                             \n",
       "HISTORY Fri May 27 14:49:55 2011  HISTORY applycal [] msselect    = \"\"          \n",
       "HISTORY Fri May 27 14:49:55 2011  HISTORY applycal [] gaintable   = \"['self_2.pc\n",
       "HISTORY >al', 'self_ap.cal']\"                                                   \n",
       "HISTORY Fri May 27 14:49:55 2011  HISTORY applycal [] gainfield   = \"['']\"      \n",
       "HISTORY Fri May 27 14:49:55 2011  HISTORY applycal [] interp      = \"['linear']\"\n",
       "HISTORY Fri May 27 14:49:55 2011  HISTORY applycal [] spwmap      = []          \n",
       "HISTORY Fri May 27 14:49:55 2011  HISTORY applycal [] calwt       = False       \n",
       "HISTORY Fri May 27 14:49:55 2011  HISTORY applycal [] gaincurve   = False       \n",
       "HISTORY Fri May 27 14:49:55 2011  HISTORY applycal [] opacity     = 0.0         \n",
       "HISTORY Fri May 27 14:55:23 2011  HISTORY ms::split() [fieldids= spwids=2 step=[\n",
       "HISTORY >1] which='corrected'] TWHydra_CO3_2.ms split from /export/data_1/data_2\n",
       "HISTORY >SV_data/test_TWHydra_may24/TWHydra_corrected.ms                        \n",
       "HISTORY Fri May 27 14:55:23 2011  HISTORY split [] taskname=split               \n",
       "HISTORY Fri May 27 14:55:23 2011  HISTORY split [] vis         = \"TWHydra_correc\n",
       "HISTORY >ted.ms\"                                                                \n",
       "HISTORY Fri May 27 14:55:23 2011  HISTORY split [] outputvis   = \"TWHydra_CO3_2.\n",
       "HISTORY >ms\"                                                                    \n",
       "HISTORY Fri May 27 14:55:24 2011  HISTORY split [] datacolumn  = \"corrected\"    \n",
       "HISTORY Fri May 27 14:55:24 2011  HISTORY split [] field       = \"\"             \n",
       "HISTORY Fri May 27 14:55:24 2011  HISTORY split [] spw         = \"2\"            \n",
       "HISTORY Fri May 27 14:55:24 2011  HISTORY split [] width       = 1              \n",
       "HISTORY Fri May 27 14:55:24 2011  HISTORY split [] antenna     = \"\"             \n",
       "HISTORY Fri May 27 14:55:24 2011  HISTORY split [] timebin     = \"0.0s\"         \n",
       "HISTORY Fri May 27 14:55:24 2011  HISTORY split [] timerange   = \"\"             \n",
       "HISTORY Fri May 27 14:55:24 2011  HISTORY split [] scan        = \"\"             \n",
       "HISTORY Fri May 27 14:55:24 2011  HISTORY split [] array       = \"\"             \n",
       "HISTORY Fri May 27 14:55:24 2011  HISTORY split [] uvrange     = \"\"             \n",
       "HISTORY Fri May 27 14:55:24 2011  HISTORY split [] correlation = \"\"             \n",
       "HISTORY Fri May 27 14:55:24 2011  HISTORY split [] combine     = \"\"             \n",
       "HISTORY Fri May 27 14:55:24 2011  HISTORY split [] keepflags   = True           \n",
       "HISTORY Fri May 27 15:28:58 2011  HISTORY calibrater::setdata [Beginning selectv\n",
       "HISTORY >is--(MSSelection version)-------, chanmode=none nchan=1 start=0 step=1 \n",
       "HISTORY >Start='0km/s' mStep='0km/s' msSelect='']                               \n",
       "HISTORY Fri May 27 15:29:02 2011  HISTORY calibrater::solve [] Beginning solve--\n",
       "HISTORY >---------------------------                                            \n",
       "HISTORY Fri May 27 15:31:11 2011  HISTORY calibrater::setdata [Beginning selectv\n",
       "HISTORY >is--(MSSelection version)-------, chanmode=none nchan=1 start=0 step=1 \n",
       "HISTORY >Start='0km/s' mStep='0km/s' msSelect='']                               \n",
       "HISTORY Fri May 27 15:31:12 2011  HISTORY calibrater::correct [] Beginning corre\n",
       "HISTORY >ct---------------------------                                          \n",
       "HISTORY Fri May 27 15:37:15 2011  HISTORY ms::split() [fieldids= spwids=* step=[\n",
       "HISTORY >1] which='corrected'] TWHydra_CO3_2.ms.contsub split from /export/data_\n",
       "HISTORY >/data_2/SV_data/test_TWHydra_may24/TWHydra_CO3_2.ms.contsubxS1huJ      \n",
       "HISTORY Fri May 27 15:37:15 2011  HISTORY uvcontsub2 [] taskname = uvcontsub2   \n",
       "HISTORY Fri May 27 15:37:15 2011  HISTORY uvcontsub2 [] vis       = TWHydra_CO3_\n",
       "HISTORY >2.ms                                                                   \n",
       "HISTORY Fri May 27 15:37:15 2011  HISTORY uvcontsub2 [] field     = \"\"          \n",
       "HISTORY Fri May 27 15:37:15 2011  HISTORY uvcontsub2 [] fitspw    = \"0:20~2000,0\n",
       "HISTORY >:2400~3800\"                                                            \n",
       "HISTORY Fri May 27 15:37:15 2011  HISTORY uvcontsub2 [] solint    = int         \n",
       "HISTORY Fri May 27 15:37:15 2011  HISTORY uvcontsub2 [] fitorder  = 1           \n",
       "HISTORY Fri May 27 15:37:16 2011  HISTORY uvcontsub2 [] spw       = \"\"          \n",
       "HISTORY Fri May 27 15:37:16 2011  HISTORY uvcontsub2 [] want_cont = False       \n",
       "HISTORY Fri May 27 16:15:09 2011  HISTORY imager::data selection [mode=none ncha\n",
       "HISTORY >n=[-1] start=[0] step=[1] mstart='Radialvelocity: 0' mstep='Radialveloc\n",
       "HISTORY >ty: 0' spectralwindowids=[] fieldids=[] msselect=]                     \n",
       "HISTORY Fri May 27 16:15:13 2011  HISTORY imager::defineimage() [Defining image \n",
       "HISTORY > properties:nx=100 ny=100 cellx='0.3arcsec' celly='0.3arcsec' stokes=I'\n",
       "HISTORY > mode=RADIOVELOCITY nchan=118 start=-1 step=0 spwids=[-1] fieldid=0 fac\n",
       "HISTORY >ts=1 frame=1 distance='0',  phaseCenter='field-0 ' mStart='Radialveloci\n",
       "HISTORY >y: -4000' qStep='0.12 km/s'' mFreqStart='Frequency: 0]                 \n",
       "HISTORY Fri May 27 16:15:15 2011  HISTORY imager::data selection [mode=none ncha\n",
       "HISTORY >n=[-1] start=[0] step=[1] mstart='Radialvelocity: 0' mstep='Radialveloc\n",
       "HISTORY >ty: 0' spectralwindowids=[] fieldids=[] msselect=]                     \n",
       "HISTORY Fri May 27 16:15:16 2011  HISTORY imager::data selection [mode=none ncha\n",
       "HISTORY >n=[-1] start=[0] step=[1] mstart='Radialvelocity: 0' mstep='Radialveloc\n",
       "HISTORY >ty: 0' spectralwindowids=[] fieldids=[] msselect=]                     \n",
       "HISTORY Fri May 27 16:15:16 2011  HISTORY imager::weight() [] Weighting MS: Imag\n",
       "HISTORY >ing weights will be changed                                            \n",
       "HISTORY Fri May 27 16:15:16 2011  HISTORY imager::weight() [] Briggs weighting: \n",
       "HISTORY > sidelobes will be suppressed over full image                          \n",
       "HISTORY Fri May 27 16:15:23 2011  HISTORY imager::clean() [] Using multifield Cl\n",
       "HISTORY >ark clean                                                              \n",
       "HISTORY Fri May 27 16:15:23 2011  HISTORY imager::clean() [] Clean gain = 0.1, N\n",
       "HISTORY >iter = 0, Threshold = 1 mJy                                            \n",
       "HISTORY Fri May 27 16:15:23 2011  HISTORY imager::clean() [] Continuing deconvol\n",
       "HISTORY >ution                                                                  \n",
       "HISTORY Fri May 27 16:16:48 2011  HISTORY imager::clean() [] Threshhold not reac\n",
       "HISTORY >hed yet.                                                               \n",
       "HISTORY Fri May 27 16:16:48 2011  HISTORY imager::clean() [] Fitted beam used in\n",
       "HISTORY > restoration: 1.68065 by 1.53193 (arcsec) at pa 22.3015 (deg)          \n",
       "HISTORY Fri May 27 16:17:45 2011  HISTORY imager::clean() [] Clean gain = 0.1, N\n",
       "HISTORY >iter = 500, Threshold = 1 mJy                                          \n",
       "HISTORY Fri May 27 16:17:45 2011  HISTORY imager::clean() [] Starting deconvolut\n",
       "HISTORY >ion                                                                    \n",
       "HISTORY Fri May 27 16:23:21 2011  HISTORY imager::clean() [] Threshhold not reac\n",
       "HISTORY >hed yet.                                                               \n",
       "HISTORY Fri May 27 16:23:21 2011  HISTORY imager::clean() [] Beam used in restor\n",
       "HISTORY >ation: 1.68065 by 1.53193 (arcsec) at pa 22.3015 (deg)                 \n",
       "HISTORY Fri May 27 16:26:42 2011  HISTORY imager::clean() [] Clean gain = 0.1, N\n",
       "HISTORY >iter = 300, Threshold = 1 mJy                                          \n",
       "HISTORY Fri May 27 16:26:42 2011  HISTORY imager::clean() [] Continuing deconvol\n",
       "HISTORY >ution                                                                  \n",
       "HISTORY Fri May 27 16:28:52 2011  HISTORY imager::clean() [] Threshhold not reac\n",
       "HISTORY >hed yet.                                                               \n",
       "HISTORY Fri May 27 17:35:52 2011  HISTORY imager::clean() [] Clean gain = 0.1, N\n",
       "HISTORY >iter = 300, Threshold = 1 mJy                                          \n",
       "HISTORY Fri May 27 17:35:52 2011  HISTORY imager::clean() [] Continuing deconvol\n",
       "HISTORY >ution                                                                  \n",
       "HISTORY Fri May 27 17:37:10 2011  HISTORY imager::clean() [] Threshhold not reac\n",
       "HISTORY >hed yet.                                                               \n",
       "HISTORY CASA END LOGTABLE                                                       "
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "twhydra.header"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Quick Look\n",
    "We can use matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"639.4444613839378\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x1145c8be0>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "plt.imshow(twhydra.data.sum(axis=(0,1)))\n",
    "#plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO: Setting slices=[0, 0] [aplpy.core]\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"999.4444709206812\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO: Auto-setting vmin to -9.227e-01 [aplpy.core]\n",
      "INFO: Auto-setting vmax to  7.636e+00 [aplpy.core]\n"
     ]
    }
   ],
   "source": [
    "import aplpy \n",
    "fig = aplpy.FITSFigure(twhydra)\n",
    "fig.show_grayscale()\n",
    "fig.show_grid()\n",
    "fig.show_contour()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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xwt1aiKAAAIIOCKwafcBdXxtqvYePBqar3yB7Br5YJNQEMSBAAIIIIAAAkr8dyJ/OQb8gqCBAW+gx8sn/PG4AZRHAAEEEIhN4NDR47rqrelatvXvf03w8/2NVblQztgmZRQCCCCAAAKGCXDnjzkNJfwxp5de7ITwxwt1aiKAAAIIpFrgiW8W6eu5m/9vnjuallT3DhVSPT8TIIAAAgggYIIA4Y8JXTy1B8Ifc3rpxU4If7xQpyYCCCCAQKoEvpy9UU99tyTJOQrkyKJpT7VU+nT8iJQqZAYjgAACCBghQPhjRBsJf8xpo2c7IfzxjJ7CCCCAAAKxCCzZvFdXvT1dR46dsIdnSp9OR44nfP357fXUsFTeWKZnDAIIIIAAAkYJEP6Y005+rWVOL73YCeGPF+rURAABBBCISeCvf46EHvC8Zc9Be3z1Irl0Te0i6v59wp1AnWsX0XNXV42pBoMQQAABBBAwSYDwx5xuEv6Y00svdkL444U6NRFAAAEEohY4fuKkun04R5NW7bDH5s6WSdYDnrNnyaDaA8bqcPhuIOvrOT1aKUvG9FHXYQACCCCAAAImCRD+mNNNwh9zeunFTgh/vFCnJgIIIIBA1AJDfl2lV8attsdZj/T5uFs9NS5z6uNd9342X78s2WZ//+0ba6pd5YJR12EAAggggAACJgkQ/pjTTcIfc3rpxU4If7xQpyYCCCCAQFQCU1fv1I3DZv1rzONty+neFqXtPxuz7A/d8ck8++v2lQvorRtrRVWHkxFAAAEEEDBNgPDHnI4S/pjTSy92QvjjhTo1EUAAAQSiErjp/dmanOjjXq0qXKChXWorXaI3elkPgK4zcKz2HjwamjtThnSa27OVcmTJGFUtTkYAAQQQQMAkAcIfc7pJ+GNOL73YCeGPF+rURAABBBCISqD58xO0YdeB0JjsmTNo6lMtlfPc/w91nv5usb6Yvcmee/BVVXVNnSJR1eJkBBBAAAEETBIg/DGnm4Q/5vTSi50Q/nihTk0EEEAAgagErIc579x/ODSmRN5smvBY8yTHz1y3S9cOnWl/r2GpPPr89vpR1eJkBBBAAAEETBIg/DGnm4Q/5vTSi50Q/nihTk0EEEAAgagEKvQapYNHj4fGVLowh355oEmS40+cOKnGz43X1r2HQt8/5xxpxlMXqUDOLFHV42QEEEAAAQRMESD8MaWTEuGPOb30YieEP16oUxMBBBBAIGIB6xXvpbqPsM+vWyK3vr6zwVnH/2fkb3pn0jr7+z06VNDtTUtGXI8TEUAAAQQQMEmA8MecbhL+mNNLL3ZC+OOFOjURQAABBCIW2HfoqKr0GWOf37L8BXq/a52zjv9t299q/8oU+/uVC+XQz/cnfadQxIvgRAQQQAABBAIqQPgT0MYlsWzCH3N66cVOCH+8UKcmAggggEDEAn/sPaT6/xlnn9+xakG9fn3NZMe3HTJZK7fvs88Z+0gzlb7gvIhrciICCCCAAAKmCBD+mNJJPvZlTie92QnhjzfuVEUAAQQQiFBgzZ/71eqlSfbZ19Ypomevqprs6DcnrtHgUSvtc+5vWVqPtikXYUVOQwABBBBAwBwBwh+DemnOVtiJBwKEPx6gUxIBBBBAIHKBxZv36NLXp9kDbm1cQr06Vkx2gs1/HVDj5ybY5xTNnVWTHm+uRD8AR74AzkQAAQQQQCDAAoQ/AW7eGUvnY1/m9NKLnRD+eKFOTQQQQACBiAWmr92p69+dZZ//wEVl9EjrsimO7/T2dM3Z8Jd93rd3N1StYuenOI4TEEAAAQQQMEmA8MecbhL+mNNLL3ZC+OOFOjURQAABBCIW+HX5dt3+8Vz7/Kfbl9edzUqlOP7Tmb+r53+X2ufd1KCY+l1WOcVxnIAAAggggIBJAoQ/5nST8MecXnqxE8IfL9SpiQACCCAQscB/F2zRQ18ttM8fcHll3Vi/WIrj//rniOoMHKtjJ0J/1Ym3fqVIxgkIIIAAAgYKEP6Y01TCH3N66cVOCH+8UKcmAggggEDEAp/N+l09vk+4g+flztV1eY1CEY2vN2istv99OHSu9dyfyU+0iGgcJyGAAAIIIGCKAOGPKZ3kbV/mdNKbnRD+eONOVQQQQACBCAWGTl6rQSNW2GcP7VJLbSoViGh0yxcnat2Of0Ln5smWSfN6tY5oHCchgAACCCBgigDhjymdJPwxp5Pe7ITwxxt3qiKAAAIIRCjw0q+r9Oq41fbZn99WTw1L541o9GWvT9WizXtD52bOkE4rB7SPaBwnIYAAAgggYIoA4Y8pnST8MaeT3uyE8Mcbd6oigAACCEQoMODn5Xpv6nr77B/ubaRqRXJFNPr6d2dq+tpd9rmrB7ZXxvTpIhrLSQgggAACCJggQPhjQhdP7YFn/pjTSy92QvjjhTo1EUAAAQQiFnj6u8X6YvYm+/yxjzRT6QvOi2i89ZYw621hp4+FvVsrV9ZMEY3lJAQQQAABBEwQIPwxoYuEP+Z00budEP54Z09lBBBAAIEIBO7/YoF+WrTVPnPG0y1VMOe5EYyUHv5qob5fsMU+d+qTLVT4/KwRjeUkBBBAAAEETBAg/DGhi4Q/5nTRu50Q/nhnT2UEEEAAgQgEun04R+NX/GmfubhPG+XIkjGCkVKv/y7VJzN/t88d9VATlS+QI6KxnIQAAggggIAJAoQ/JnSR8MecLnq3E8If7+ypjAACCCAQgUDnd2Zo1vrd9plrB3VQ+nSRfer92ZEr9PaktfbYb+9uoFrFckdQlVMQQAABBBAwQ4Dwx4w+WruI7Kcfc/bLTpwVIPxx1pPZEEAAAQQcFuj42hQt3fJ3aNYsGdNpRf/I39j1+vjVemHMKntFH3Wrq2Zl8zm8QqZDAAEEEEDAvwKEP/7tTbQrI/yJVozzEwsQ/nA9IIAAAgj4WqDFCxO1fuc/oTXmPS+T5vZsHfF6P5y2Xn1+Wm6f/8b1NXVx1YIRj+dEBBBAAAEEgi5A+BP0Diasn/DHnF56sRPCHy/UqYkAAgggELFA3YFj9ee+w6Hzi+XJqkmPt4h47PC5m/T4N4vt8wdfVVXX1CkS8XhORAABBBBAIOgChD9B7yDhjzkd9HYnhD/e+lMdAQQQQCAFgUq9R+mfI8dDZ1UsmEMjHmwSsdnIJdt092fz7fN7d6yobo1LRDyeExFAAAEEEAi6AOFP0DtI+GNOB73dCeGPt/5URwABBBBIRuDEiZMq2X2EfUad4udr+F0NIzabsnqHugybbZ//SOuyeuCiMhGP50QEEEAAAQSCLkD4E/QOEv6Y00Fvd0L4460/1RFAAAEEkhHYf/iYKj8z2j6jebl8+vCWuhGbzd/4l658c7p9/p1NS+rpDhUiHs+JCCCAAAIIBF2A8CfoHST8MaeD3u6E8Mdbf6ojgAACCCQj8Offh1R30Dj7DOthzdZDmyM9Vm3fpzZDJtun31CvqAZeUSXS4ZyHAAIIIIBA4AUIfwLfQnsDPPDZnF56sRPCHy/UqYkAAgggEJHAuh371fLFSfa519QurMFXV4torHXS1j0H1fDZ8fb5l1W/UK9cWyPi8ZyIAAIIIIBA0AUIf4LewYT1E/6Y00svdkL444U6NRFAAAEEIhJYsnmvLnl9qn3uLY2K65lLKkU01jpp78GjqtZ3jH1+qwoX6L2b60Q8nhMRQAABBBAIugDhT9A7SPhjTge93Qnhj7f+VEcAAQQQSEZg5rpdunboTPuM+1uW1qNtykVsduz4CZXuMdI+v37J3PryjgYRj+dEBBBAAAEEgi5A+BP0DhL+mNNBb3dC+OOtP9URQAABBJIRGPfbdt360Vz7jKfal9ddzUpFZVah1ygdPHrqVfFVCuXUT/c3jmo8JyOAAAIIIBBkAcKfIHfv32vnY1/m9NKLnRD+eKFOTQQQQACBiAR+WLhFD3650D63/2WV1KVB8YjGnj6p9oCx2rn/cOjLEnmzacJjzaMaz8kIIIAAAggEWYDwJ8jdI/w5W/eySmomqZYk61Ug1r+Lhk/uK6lPMm0vJOkySS0kWU+CtL62jj8kWfebvysp4YmRZ58ov6QnJHUM1z4oaZmkjyQNkxQKW5I5rF9nWuPbSCooaZ+k+ZKGSvo2Dpct4U8cUJkSAQQQQMAZgc9nbVT375fYk710TTVdWbNwVJM3f36CNuw6EBqTL3tmzenRKqrxnIwAAggggECQBQh/gty9f6+dO38SPKxf5U04S2uTC3+KSPpdUmJL66dE6+tzE833vqQ7JJ26d/z/DytsGi0pT/hb+yVlkZQh/LX1vUslHTnL+A6ShkuyQizr+FvSeZLShb/+QNKtEQRI0VzdhD/RaHEuAggggICrAu9NWacBv/xm13ynSy21rVQgqjVc/OoULdtq/ZUqZc2UXsv7tYtqPCcjgAACCCAQZAHCnyB3799rJ/xJ8LDCn+/Cd8pYd8tY/wyRZP2UmFz4Y90/vl7SOEkfSxprvR02HLqUlzQofFeQVWmApF5JXD45Ja0I17L+3UWS9ZCCTJJuD68jo6S3JN2TxPgSkqxfbWaTNE1SN0mrwuHP45J6h8c8KWmwg5cv4Y+DmEyFAAIIIOCswMtjV+nlsavtST+9tZ4al8kbVZHO78zQrPW77TFrB3VQ+nT8+BQVIicjgAACCARWgPAnsK37v4Xz00sCSfok7srZIKlYCuGPFdxYH7eywqKkDst4hCTrV4XW3Tz5JB0648T+knpKsj7mZb2D1gqTEh9Ph0Mk666hiuFgJ/H3P5F0Y/hjZhUk7Tlj/Dvhu46sX11aYdVfDl3ChD8OQTINAggggIDzAgN/Wa53pyT8lfr9PQ1Vo+j5URW69cM5GrfiT3vM4j5tlCOL9fsYDgQQQAABBMwXIPwxp8eEP8n3MpLwJ5KroZOkr8MnWs8TWnDGIOtjY9bzhayPZll37Zx5WB/f2ha+k6efpGcSnWDd7bMj/BEz68+t7595nL47yfpza36rjhMH4Y8TisyBAAIIIBAXAet5P9Zzf04fvz7cVGXyZ4+q1gNfLNCPi6wbek8dM55uqYI5E3+qO6rpOBkBBBBAAIFACRD+BKpdyS6W8Cf5XjoV/lwi6cdwqTrhj3Sdrlwu/JEv6+trws/tSWpV1t1D7cMPkG6Q6IS2kkaFv64rac5ZtrRcknVX0JeSrnPoEib8cQiSaRBAAAEEnBd48MsF+mFhQnAz/amWujBXdMGNEwGS8ztjRgQQQAABBNwRIPxxx9mNKoQ/7oQ/L0p6JPywZutjX6eeHHnquErSN+H/tj7SlfBkyn+vzXpWj/X8Hmus9VGz08ejkl4If2E97Nn66FhSh3XnkXUHkvVsoKoOXVyEPw5BMg0CCCCAgPMCt300R2N/S/jI1qLebZQza3Qf2Ro04jcNnbzOXlwsHx1zfmfMiAACCCCAgDsChD/uOLtRhfAneWUn7vyxHsa8NPwWLuvZPDedUfJ+Sa+G/8wKdRIHQ4lPfVDSy+E/sO5Zt54fZB2ngyXrOT65k9mO9fDqhyTtkhTd0y7PPinhjxv/l1IDAQQQQCAmgeuGztSMddZfe6eONQPbK0P60y/BjGzKV8au1pCx1jsUTh2xPDQ6skqchQACCCCAgP8ECH/815NYV0T4k7xcasMf697yKZKs17jvlFQt/CawxFW7SxoY/gPr15HHzrIk661fQ8PfuzD8DCDrS+vPrO9tkVQ4me1YNaxa1qviM0d4wYTCnZSOkycjOi2lafg+AggggAACjgpc+vpULd68NzRn5gzptHKA9enp6I5hU9er/8/WJ6dPHW/fWFPtKheMbhLORgABBBBAIKAChD8BbVwSyyb8Sb6XqQl/MoSf33O5pKOSOkoak0Q5wh9z/n9iJwgggAACPhJo+eJErdvxT2hFubNl0vxeraNe3VdzNurJb61PTJ86XuhUTVfXSu53LVGXYAACCCCAAAK+FSD88W1rol4Y4U98wh/rtfGfhx/gbN3JYz1g+fRzfc6syMe+or5sGYAAAggggEDKAvUGjdX2vw+HTiyS+3Lr78EAACAASURBVFxNeaJlyoPOOOPnxVt13+cJL+nse2kl3dzQeokmBwIIIIAAAuYLEP6Y02PCH+fDHyv4+VTStZKOS7pB0lfJlOGBz+b8/8ROEEAAAQR8JFDlmdHad/jUp6nLF8iuUQ81jXp1E1f+qa4fJLxI8/G25XRvi9JRz8MABBBAAAEEgihA+BPEriW9ZsIfZ8MfK/j5TFLncPBzY/jV6slV4VXv5vz/xE4QQAABBHwiYD2PrlT3EToRfixd7WLn65u7G0a9urkbduvqt2fY4+5uXkpPtisf9TwMQAABBBBAIIgChD9B7BrhTyxdi+aZP4k/6mXd8RNJ8GOtyQrgrDpFJb0v6dYkFppN0h+SzpPUT9Izic6xvrdDkvVw6d6S+icxvli4hvWtbpI+iAUjiTG87cshSKZBAAEEEHBW4MCRY6rYe7Q9adOy+fRxt7pRF/lt299q/4r17oZTx00NiqnfZZWjnocBCCCAAAIIBFGA8CeIXUt6zdz5k3wvIw1/Et/xY91fbgU/yX3U68yqVmDTU9IBSZUSBTWnz3tC0nPhu4kqSkp45+ypM6xXyFs1t0mqIOnUq00Sjjcl3S1pnyQrCLJeC+/EQfjjhCJzIIAAAgg4LrBj32HVGTjWnrdDlQJ68wbr5ZvRHZt2H1CTwRPsQVfWLKSXrqke3SScjQACCCCAQEAFCH8C2rgklk3482+U8yVZQc7pY771jEhJz0sanOjPD0naH/468TN+rODn+vBbvqK5SnJKWiGpgCTrfbI3SZonKVP4TqCXw//9lqR7kpi4hCTrVSTWXUDWryetu4dWh79+VFKf8B1GT56xj2jWmNS5hD+pFWQ8AggggEBcBDbs/EfNX5hoz92pVmE936la1LX++ueIavT/1R7XpmJ+Db2pdtTzMAABBBBAAIEgChD+BLFrSa+Z8OffLqfv9Empwx9J6ho+yXp65KTwf1uvdN+dwuAHz3JXkPXrSOv+9Dzh8dZdOlkkZQx/bb0m/lJJp15b8v9Hh3DolDX8LevuH+tjYqfDLOujXlYoFH76QUpbjOj7hD8RMXESAggggIDbAku37FXH16baZbs2LK4+l1o310Z3HDl2QmV7jrQHNSqdR5/dVj+6STgbAQQQQACBgAoQ/gS0cUksm/Dn3yixhD/NJSXcD57ytXGLpA/Pclp+SdbdOR3DdxxZdxgtlWSFTdbzgE6kMH2p8PjWkgqGP+ZlvZ/2HUnfpry0qM8g/ImajAEIIIAAAm4IzFq3S52HzrRL3duilB5vG9uDmsv2GKkjx0/9FVytSC79cG8jN7ZADQQQQAABBDwXIPzxvAWOLYDwxzHKNDkR4U+abDubRgABBPwvMGHFn7rlw4RXtD/RrpzuaR7bK9pr9v9Vu/85Etp0qXzZNO5R6/c+HAgggAACCJgvQPhjTo8Jf8zppRc7IfzxQp2aCCCAAAIpCvy0aKvu/8K6+fXU0e+ySrqpQfEUxyV1QpPB47Vp98HQtwrkyKKZ3S+KaR4GIYAAAgggEDQBwp+gdezs6yX8MaeXXuyE8McLdWoigAACCKQo8OXsjXrqO+tdCKeOFzpV09W1Cqc4LqkT2r08WSv+sB7FJ2XPnEFL+raNaR4GIYAAAgggEDQBwp+gdYzwx5yO+WsnhD/+6gerQQABBBAICwybul79f7ZeoHnqePvGmmpX2XocXvRHp7ena86Gv0IDzzlHWjeogxL9MBz9hIxAAAEEEEAgIAKEPwFpVATL5M6fCJA45awChD9cHAgggAACvhR4ddxqvfTrKnttn9xaV03K5ItprV0/mK2JK3fYY5f1batsmTPENBeDEEAAAQQQCJIA4U+QupX8Wgl/zOmlFzsh/PFCnZoIIIAAAikK/GfEb3pn8jr7vO/uaaiaRc9PcVxSJ9z7+Xz9snib/a3Z3S/SBTmyxDQXgxBAAAEEEAiSAOFPkLpF+GNOt/y3E8If//WEFSGAAAIISOrx/RJ9NmujbTH6oaYqVyB7TDZPfbtYX87ZZI8d92gzlcp3XkxzMQgBBBBAAIEgCRD+BKlbhD/mdMt/OyH88V9PWBECCCCAgKSHv1qo7xdssS2mPtlChc/PGpON9ewg6xlCp48f72ukqoVzxTQXgxBAAAEEEAiSAOFPkLpF+GNOt/y3E8If//WEFSGAAAIISLr947n6dfl222Jh79bKlTVTTDbWs4OsZwidPj6/vZ4alsob01wMQgABBBBAIEgChD9B6hbhjznd8t9OCH/81xNWhAACCCAg6fp3Z2r62l22xaoB7ZUpQ7qYbIZOXqtBI1bYY4d2qaU2lQrENBeDEEAAAQQQCJIA4U+QukX4Y063/LcTwh//9YQVIYAAAghIuuyNaVq0aU/IIlP6dFo1sH3MLp/P2qju3y+xxw/pXE1X1Cgc83wMRAABBBBAICgChD9B6VTK6+RtXykbccbZBQh/uDoQQAABBHwp0OqlSVrz5/7Q2s7PmlELereJeZ0/LNyiB79caI/vf3lldalfLOb5GIgAAggggEBQBAh/gtKplNdJ+JOyEWcQ/nANIIAAAggETKDBf8Zp295DoVUXPv9cTX2yZcw7GPfbdt360Vx7/FPty+uuZqVino+BCCCAAAIIBEWA8CconUp5nYQ/KRtxBuEP1wACCCCAQMAEqvQZrX2HjoVWXS5/do1+uGnMO5i1bpc6D51pj7+vRWk91rZczPMxEAEEEEAAgaAIEP4EpVMpr5PwJ2UjziD84RpAAAEEEAiQwMmTJ1W6x0gdPxH6dLJqFs2l7+5pFPMOlm7Zq46vTbXHd21YXH0urRTzfAxEAAEEEEAgKAKEP0HpVMrrJPxJ2YgzCH+4BhBAAAEEAiRw6Ohxle81yl5xkzJ59cmt9WLewYad/6j5CxPt8Z1qFdbznarFPB8DEUAAAQQQCIoA4U9QOpXyOgl/UjbiDMIfrgEEEEAAgQAJ7Nx/WLUHjLVX3K5SAb3dpVbMOzhzvvaVC+itG2OfL+aFMBABBBBAAAGXBQh/XAaPYznCnzjipoGpedtXGmgyW0QAAQSCJrBx1wE1fX6CveyrahbWi9fEfqeO03cSBc2T9SKAAAIIpF0Bwh9zek/4Y04vvdgJ4Y8X6tREAAEEEEhWYPnWv9Xh1Sn2OTc3KKa+l1WOWc3pZwjFvBAGIoAAAggg4LIA4Y/L4HEsR/gTR9w0MDXhTxpoMltEAAEEgiYwZ8NudXp7hr3se5qX0hPtyqdqG9X6jtHeg0dDc5TNf57GPNwsVfMxGAEEEEAAgSAIEP4EoUuRrZHwJzInzkpagPCHKwMBBBBAwHcCE1b+qVs+mGOv6/G25XRvi9KpWmejZ8dry56DoTkK5TpX055qmar5GIwAAggggEAQBAh/gtClyNZI+BOZE2cR/nANIIAAAggEROCXxdt07+fz7dX2uaSiujYqkarVtxkySau27w/NkfPcjFr0TJtUzcdgBBBAAAEEgiBA+BOELkW2RsKfyJw4i/CHawABBBBAICACX8/ZpCe+XWyv9vmrq6pT7SKpWv2Vb07T/I17QnOkT3eO1gxsr0Q/EKdqbgYjgAACCCDgVwHCH792Jvp1Ef5Eb8aIBAE+9sXVgAACCCDgO4H3p65Xv5+X2+t684aa6lClYKrW2WXYLE1ZvdOeY0X/dsqSMX2q5mQwAggggAACfhcg/PF7hyJfH+FP5Fac+f8ChD9cFQgggAACvhN4ffxqvTBmlb2uj7rVVbOy+VK1zrs/naeRS/+w55jbs5Xynpc5VXMyGAEEEEAAAb8LEP74vUORr4/wJ3IrziT84RpAAAEEEAiAwLMjV+jtSWvtlX57dwPVKpY7VSt/bPgifTNvsz3HxMeaq3jebKmak8EIIIAAAgj4XYDwx+8dinx9hD+RW3Em4Q/XAAIIIIBAAAR6/XepPpn5u73SUQ81UfkCOVK18j4/LtOH0zfYc/x8f2NVLpQzVXMyGAEEEEAAAb8LEP74vUORr4/wJ3IrziT84RpAAAEEEAiAwCNfLdR3C7bYK53yRAsVyZ01VSt/YfRKvT5hjT3HV3fUV72SeVI1J4MRQAABBBDwuwDhj987FPn6CH8it+JMwh+uAQQQQACBAAjc+clcjV623V7p/F6tlTtbplSt/K2Ja/XcqBX2HO93ra2W5fOnak4GI4AAAggg4HcBwh+/dyjy9RH+RG7FmYQ/XAMIIIAAAgEQuPG9WZq6JuHNXCsHtFPmDKl7M5f1MTLr42Snj1eura7LqhcKgAZLRAABBBBAIHYBwp/Y7fw2kvDHbx0J1np421ew+sVqEUAAgTQhcPkb07Rw057QXjOkO0erB7ZXoh9eYzL4fsFmPfzVInvsoCuq6Pp6RWOai0EIIIAAAggERYDwJyidSnmdhD8pG3HG2QUIf7g6EEAAAQR8J9BmyCSt2r4/tK6c52bUomfapHqNY5b9oTs+mWfP06NDBd3etGSq52UCBBBAAAEE/CxA+OPn7kS3NsKf6Lw4+98ChD9cEQgggAACvhNo9Ox4bdlzMLSuQrnO1bSnWqZ6jdPX7tT1786y53ngojJ6pHXZVM/LBAgggAACCPhZgPDHz92Jbm2EP9F5cTbhD9cAAggggIDPBar1HaO9B4+GVlk2/3ka83CzVK948eY9uvT1afY8tzYuoV4dK6Z6XiZAAAEEEEDAzwKEP37uTnRrI/yJzouzCX+4BhBAAAEEfCxw8uRJlekxUsdOhG5OVfUiufTfexulesVrd+zXRS9Osue5tk4RPXtV1VTPywQIIIAAAgj4WYDwx8/diW5thD/ReXE24Q/XAAIIIICAjwUOHzuucj1H2StsXDqvPr2tXqpX/Offh1R30Dh7nourFtQb19dM9bxMgAACCCCAgJ8FCH/83J3o1kb4E50XZxP+cA0ggAACCPhYYPc/R1Sz/6/2CttWyq93utRO9Yr/OXxMlZ4Zbc/TvFw+fXhL3VTPywQIIIAAAgj4WYDwx8/diW5thD/ReXE24Q/XAAIIIICAjwU27T6gJoMn2Cu8skYhvdS5eqpXbH2crGT3ETp56tNkqlP8fA2/q2Gq52UCBBBAAAEE/CxA+OPn7kS3NsKf6Lw4m/CHawABBBBAwMcCK/74W+1enmKvsEv9Yup/eWVHVlz5mdHaf/hYaK7yBbJr1ENNHZmXSRBAAAEEEPCrAOGPXzsT/boIf6I3Y0SCAK9652pAAAEEEPCVwLzfd+uqt2bYa7qrWSk91b68I2usP2ic/vj7UGiuIrnP1ZQnUv8KeUcWxiQIIIAAAgjESYDwJ06wHkxL+OMBukElCX8MaiZbQQABBEwQmLRqh25+f7a9lcfalNV9Lcs4srWLXpyotTv+Cc2VO1smze/V2pF5mQQBBBBAAAG/ChD++LUz0a+L8Cd6M0YkCBD+cDUggAACCPhKYMSSbbrns/n2mnp3rKhujUs4ssbLXp+qRZv3hubKlD6dVg1s78i8TIIAAggggIBfBQh//NqZ6NdF+BO9GSMIf7gGEEAAAQR8KjB87iY9/s1ie3WDr6qqa+oUcWS1N7w3U9PW7LLnWjWgvTJlSOfI3EyCAAIIIICAHwUIf/zYldjWRPgTmxujTglw5w9XAgIIIICArwQ+nLZefX5abq/pjetr6uKqBR1Z4x0fz9WY5dvtuRb0aq3zs2VyZG4mQQABBBBAwI8ChD9+7EpsayL8ic2NUYQ/XAMIIIAAAj4UeGPCGj0/eqW9sg9uqaMW5S5wZKWPfLVQ3y3YYs815YkWKpI7qyNzMwkCCCCAAAJ+FCD88WNXYlsT4U9sbowi/OEaQAABBBDwocDgUSv05sS19sqG39VAdYrndmSlvX9Yqo9n/G7PNfLBJqpQMIcjczMJAggggAACfhQg/PFjV2JbE+FPbG6MIvzhGkAAAQQQ8KHAMz8s1UeJApoRDzRRxQudCWieG7VCbyUKlr65q4FqOxQs+ZCSJSGAAAIIICDCH3MuAsIfc3rpxU545o8X6tREAAEEEDirwKNfL9K38zfb35/8eAsVzePMR7PO/EjZh7fUUXOHPlJGSxFAAAEEEPCjAOGPH7sS25oIf2JzY9QpAcIfrgQEEEAAAV8J3P3pPI1c+oe9prk9WynveZkdWeNH0zfomR+X2XO9fn0Ndax6oSNzMwkCCCCAAAJ+FCD88WNXYlsT4U9sbowi/OEaQAABBBDwoUCXYbM0ZfVOe2Ur+rdTlozpHVnpN/M267Hhi+y5nruqijrXKerI3EyCAAIIIICAHwUIf/zYldjWRPgTmxujCH+4BhBAAAEEfChw5ZvTNH/jntDK0qc7R2sGtk/8vIJUrXjU0m2669P59hy9OlbUrY1LpGpOBiOAAAIIIOBnAcIfP3cnurUR/kTnxdn/FuBjX1wRCCCAAAK+Emg7ZLJWbt8XWlP2LBm0pE9bx9Y3ZfUOdRk2257v4VZl9WCrMo7Nz0QIIIAAAgj4TYDwx28diX09hD+x2zGSZ/5wDSCAAAII+Eyg8XPjtfmvg6FVFcyZRTOevsixFS7Y+JeueHO6Pd8dTUuqe4cKjs3PRAgggAACCPhNgPDHbx2JfT2EP7HbMZLwh2sAAQQQQMBnAjX6jdFfB46GVlX6gvM09pFmjq1w9fZ9aj1ksj3f9fWKatAVVRybn4kQQAABBBDwmwDhj986Evt6CH9it2Mk4Q/XAAIIIICAzwTK9hipI8dPhFZVrUgu/XBvI8dWuHXPQTV8drw936XVLtSr19VwbH4mQgABBBBAwG8ChD9+60js6yH8id2OkYQ/XAMIIIAAAj4SOHLshMr2HGmvqGGpPPr89vqOrfDvQ0dVtc8Ye76Lyl+gYV3rODY/EyGAAAIIIOA3AcIfv3Uk9vUQ/sRux0jCH64BBBBAAAEfCew5cETV+/1qr6h1xfx696bajq3w+ImTKtV9hD1fvRK59dWdDRybn4kQQAABBBDwmwDhj986Evt6CH9it2Mk4Q/XAAIIIICAjwQ2/3VAjZ+bYK/oihqFNKRzdUdXWKHXKB08ejw0Z6ULc+iXB5o4Oj+TIYAAAggg4CcBwh8/dSN1ayH8SZ1fWh/Nq97T+hXA/hFAAAEfCaz8Y5/avpzwQOYb6hXVQIcfyFxn4Fjt2Hc4tOviebJq4uMtfCTAUhBAAAEEEHBWgPDHWU8vZyP88VI/+LUJf4LfQ3aAAAIIGCMwf+NfujLRq9jvbFpSTzv8KvYWL0zU+p3/hMzynpdZc3u2MsaPjSCAAAIIIHCmAOGPOdcE4Y85vfRiJ4Q/XqhTEwEEEEAgSYEpq3eoy7DZ9vceaV1WD1xUxlGtjq9N0dItf4fmPDdjev3Wv52j8zMZAggggAACfhIg/PFTN1K3FsKf1Pml9dGEP2n9CmD/CCCAgI8ERi3dprs+nW+vqFfHirq1cQlHV3jt0BmauW63Peeage2VIX06R2swGQIIIIAAAn4RIPzxSydSvw7Cn9QbpuUZCH/ScvfZOwIIIOAzgW/nbdajwxfZq3r2yiq6tm5RR1d520dzNPa3P+05Fz3TRjnPzehoDSZDAAEEEEDALwKEP37pROrXQfiTesO0PAPhT1ruPntHAAEEfCbw8YwN6v3DMntVr11XQ5dUu9DRVT745QL9sHCrPef0p1rqwlznOlqDyRBAAAEEEPCLAOGPXzqR+nUQ/qTeMC3PQPiTlrvP3hFAAAGfCbw5cY0Gj1ppr+qDrnXUovwFjq6yx/dL9NmsjfacYx5uqrL5sztag8kQQAABBBDwiwDhj186kfp1EP6k3jAtz0D4k5a7z94RQAABnwk8P3qF3piw1l7VV3fUV72SeRxd5X9G/KZ3Jq+z5/zunoaqWfR8R2swGQIIIIAAAn4RIPzxSydSvw7Cn9QbpuUZCH/ScvfZOwIIIOAzgT4/LtOH0zfYq/r5/saqXCino6t8ddxqvfTrKnvOT26tqyZl8jlag8kQQAABBBDwiwDhj186kfp1EP6k3jAtz0D4k5a7z94RQAABnwk8PnyRhs/bbK9q4mPNVTxvNkdXOWzqevX/ebk951s31FT7KgUdrcFkCCCAAAII+EWA8McvnUj9Ogh/Um+Ylmcg/EnL3WfvCCCAgM8E7vlsnkYs+cNe1ZwerZQve2ZHV/n1nE164tvF9pzPX11VnWoXcbQGkyGAAAIIIOAXAcIfv3Qi9esg/Em9YVqegfAnLXefvSOAAAI+E7j5/dmatGqHvarl/doqa6YMjq7yl8XbdO/n8+05+1xSUV0blXC0BpMhgAACCCDgFwHCH790IvXrIPxJvWFanoHwJy13n70jgAACPhO4+q3pmvv7X6FVpTtHWjuogxL90OrIaieu/FNdP5hjz/VYm7K6r2UZR+ZmEgQQQAABBPwmQPjjt47Evh7Cn9jtGCkR/nAVIIAAAgj4RqDdy5O14o99ofVkz5xBS/q2dXxt837fravemmHPe1ezUnqqfXnH6zAhAggggAACfhAg/PFDF5xZA+GPM45pdRbCn7TaefaNAAII+FCgyeDx2rT7YGhl+XNk1qzurRxf5Yo//la7l6fY83apX0z9L6/seB0mRAABBBBAwA8ChD9+6IIzayD8ccYxrc5C+JNWO8++EUAAAR8K1Or/q3b9cyS0spL5smn8o80dX+Wm3QfUZPAEe94raxTSS52rO16HCRFAAAEEEPCDAOGPH7rgzBoIf5xxTKuzEP6k1c6zbwQQQMCHAuV6jtThYydCK6taOKd+vK+x46vcc+CIqvf71Z63dcX8evem2o7XYUIEEEAAAQT8IED444cuOLMGwp8Ex6ySmkmqJalm+N9Fw9/uK6lPBOT5JT0hqaMka6x17/kySR9JGqbwM3KSmadUeHwbSQUlWQ8usF4pMlTStxHUt9b9iCTrV535JO2WNFPSa5LGRzA+2lMIf6IV43wEEEAAgbgIHDt+QqV7jLTnblAyj764o77jtY4eP6Eyieo0LJVHn9/ufB3HF86ECCCAAAIIxCBA+BMDmk+HEP4kNMYKTBLu4/53wyIJf6zQaLSkPOGh+yVlkXT6HbPW9y6VdOp+9P8/OkgaLskKoazjb0nnWS8sCX/9gaRbkwmQbpP0VqJ6eyXlkHS6x5HsIdrLlPAnWjHORwABBBCIi8Deg0dVre8Ye+5WFS7QezfXiUutsj1H6kj4DqNqhXPqhzjcYRSXhTMpAggggAACUQoQ/kQJ5uPTCX8SmmOFP9+F77Sx7rax/hkiqYCklIKTnJJWhM+1/t1F0lxJmSTdHp4nYzicuSeJ66GEpCWSskmaJqmbpFXh8OdxSb3DY56UNDiJ8Q0kWU+fTC/pv5Lul7Q5HEQNlHRneExnSV87eD0S/jiIyVQIIIAAArELbN1zUA2fTbjJ9bLqF+qVa2vEPmEyI914tlBcFs6kCCCAAAIIRClA+BMlmI9PJ/xJaI4VnBw/o1cbJBWLIPzpL6ln+GNelSStP2OepyUNCs9fMRzsJD7lE0k3SvpDUgVJe84Y/46kO8J3AxWX9NcZ37eCH+vBBlaAZN2BdPSM74+SZL3v1tpP6ST2GeslSvgTqxzjEEAAAQQcFVi9fZ9aD5lsz3l9vaIadEUVR2ucnqzp4AnauPtA6Mt4vVUsLgtnUgQQQAABBKIUIPyJEszHpxP+JN+cSMOf38PP+LE+mmXdtXPmYX18a1v4Tp5+kp5JdIJ1t88OSeeG/9z6/pmHFficDpSs+a06p4+SktaGv7hZ0sdJjLeeZTQx/Octk/l4W7SXKuFPtGKcjwACCCAQF4EFG//SFW9Ot+e+vUkJ9bjY+n2L80f7V6bot23Wp7Ol8zJn0NK+1u9XOBBAAAEEEDBPgPDHnJ4S/iTfy0jCn3Lhj3xZM10Tfm5PUrOOkNQ+/ABm62Napw/rJ0brzhzrqCtpzlmWtDx8V9CXkq5LdI71ka63w19bD5z+M4nx1l1N1t1C2SU9K8m6E8mJg/DHCUXmQAABBBBItcC0NTt1w3uz7HkealVGD7Uqm+p5k5qg09vTNWdDwk246wZ1ULp0/EgVF2wmRQABBBDwVIDwx1N+R4vzk0rynJGEP1dJ+iY8jfUrxt/OMqX1rB7r+T3WrwqtZwSdPh6V9EL4C+thz9YbwpI6rGf1dAp/tKtqohOsN3ndFw59rPDnbMdsSdaTL38KP3jaiQuJ8McJReZAAAEEEEi1wOhlf+jOT+bZ8/S8uIJua2LdHOv8ccsHszVhpXXT7qnDuvPHugOIAwEEEEAAAdMECH/M6SjhT/K9jCT8sR6u/Gp4GivUOXUf+P8fD0p6OfzH1h041tvArOPF8OvZrV8h5k5mOdbDpx+StEtS3kTnWa+Av1LSgvAr6s82xfeSLpdk/WRcO8JLOBTupHScPBnRaSlNw/cRQAABBBCIWeC7+Zv1yNeL7PH/ubKKrqtbNOb5kht43+fz9fNi69Pcp45Z3S9S/hzWCz45EEAAAQQQMEuA8MecfhL+JN/LSMKf7pKsN2pZh/VGr2NnmdJ669fQ8PcuDD8DyPrS+jPre1skFU5mOVYNq5b1qvjMic6z3mvbOvyWMOuhz2c7PpN0ffhh09ZH1SI5Ikp1CH8ioeQcBBBAAIF4Cnwy83f1+u9Su8Qr11bXZdULxaXkU98u1pdzNtlzj32kmUpfYD3ejwMBBBBAAAGzBAh/zOkn4U/yvUzr4U9KVzof+0pJiO8jgAACCLgi8PaktXp25Aq71rCba+uiCsl9Gjr2ZQ34ebnem5rwYs8f7m2kakVyxT4hIxFAAAEEEPCpAOGPTxsTw7IIf1If/pj8sa+ULinCn5SE+D4CCCCAgCsCL45ZqdfGr7FrfXlHfdUvmScutYf8ukqvjFttz/35bfXUsHTiT2THpSyTIoAAAggg4LoA4Y/r5HErSPiT+vCHBz7zzJ+4/Q/KxAgggAACkQn0/WmZPphm3bB76vjpvsaqUjjx+xUimyeSs96dvE4DRyS83+GdDCnIFQAAIABJREFULrXUtlKBSIZyDgIIIIAAAoESIPwJVLuSXSzhT+rDHz+96v0CSQmvH0nYG696N+f/WXaCAAIIIJCEwJPfLNZXcxOewzP+0WYqmS8+z+H5YvZGPf3dEnsVL11TTVfWTO6xfbQMAQQQQACBYAoQ/gSzb0mtmvAn9eGPZWj9qtF6pcj7km5NYspskv6QZP0U2k/SM4nOsb5nBTbnSuotqX8S44uFa1jf6ibpg0TnWO+xXRv++iZJnyQxvqmkSeE/bylpgkOXMB/7cgiSaRBAAAEEUidw7+fz9UuiN3DN7n6RLojTG7h+XLRVD3xhvWTz1NH/skrq0qB46jbAaAQQQAABBHwoQPjjw6bEuCTCn+ThInngc+jnPkk9JR2QVClRUHN69ickPSfpuKSK4TduJa5sBTY3ht8AVkHS3jOW9aakuyXtk2QFQdZr4RMfUyRZb/qy3nFbR9LRM74/QlJ7Sb9LKhVeR4yXzL+GEf44ocgcCCCAAAKpFuj6wWxNXJlw8+uyvm2VLXOGVM+b1ATjV2xXtw/n2t96sl153d3c+uuVAwEEEEAAAbMECH/M6Sfhz797eb4k6yNSp4/5kopIel7S4ER/fkjS/kRfWw8VsF4xYn3gf7kk6w6ceZIyhe8Eejn8329JuieJy6eEJOv+cesuICvIse4esp4kaX39qKQ+kqxePXnGOk5P1VDS5PDav5P0QPjV8bklDQgHR9a5nSV97eDlS/jjICZTIYAAAgjELnDN2zM0e8Nue4J1gzooXbr4/Jgze/1uXfPODLvWvS1K6fG25WNfPCMRQAABBBDwqQDhj08bE8Oy4vNTUQwL8cmQ03f6pLScjyR1PeOkWpJGSzr9ahHrLp0skjKGzxsj6VJJh88yeQdJwyVlDX/fuvvH+pjY6TDK+qiXFQqFApckjtskWeHS6V9z7pFkhVKne9w3HCKltLdovk/4E40W5yKAAAIIxE3g4lenaNnWv0PzZ8uUXsv6tYtbrWVb9+riV6fa83dtWFx9LrVu/OVAAAEEEEDALAHCH3P6Sfjz716mJvyxZsofvjunY/iOIesOoaWSrLDIeh7QiRQuHeuecevuntaSCoY/5mU9VOAdSd9GcNnVDN8p1ExSvvDHw6xfTb4maXwE46M9hfAnWjHORwABBBCIi0CLFyZq/c5/QnPny55Zc3q0iksda9Lfd/2jZs9PtOe/ulZhvdCpWtzqMTECCCCAAAJeCRD+eCXvfF3CH+dN09KMhD9pqdvsFQEEEPCxQN2BY/XnvlM31xbPk1UTH28Rt9Xu2n9YtQaMtedvV6mA3u5i3QDMgQACCCCAgFkChD/m9JPwx5xeerETwh8v1KmJAAIIIPB/ApWfGa39h4+F/rxiwRwa8WCTuCkdOnpc5XuNsudvUiavPrm1XtzqMTECCCCAAAJeCRD+eCXvfF3CH+dN09KMhD9pqdvsFQEEEPCpwMmTJ1Wy+widDD8Vr07x8zX8LutdCPE5rHpleozUsROnCtYomkvf39MoPsWYFQEEEEAAAQ8FCH88xHe4NOGPw6BpbDrCnzTWcLaLAAII+FHg4JHjqtA74U6cZmXz6aNudeO61Gp9x2jvwaOhGmXzn6cxD1uP2+NAAAEEEEDALAHCH3P6SfhjTi+92Anhjxfq1EQAAQQQ+JfAzv2HVTvRM3g6VCmgN2+I7zN4Gj07Xlv2HAyto1CuczXtqZZ0BQEEEEAAAeMECH/MaSnhjzm99GInhD9eqFMTAQQQQOBfAht3HVDT5yfYf+bG27faDJmkVdv3h2rmyJJBi/u0pSsIIIAAAggYJ0D4Y05LCX/M6aUXOyH88UKdmggggAAC/xL4bdvfav/KFPvPbm5QTH0vqxxXpSvenKYFG/eEaqRPd47WDGyvRD8gx7U2kyOAAAIIIOCWAOGPW9Lxr0P4E39jkysQ/pjcXfaGAAIIBERg3u+7ddVbM+zV3t28lJ5sVz6uq+8ybJamrN5p11jRv52yZEwf15pMjgACCCCAgNsChD9ui8evHuFP/GzTwsyEP2mhy+wRAQQQ8LnA5FU7dNP7s+1VPtamrO5rWSauq77rk3katewPu8bcnq2U97zMca3J5AgggAACCLgtQPjjtnj86hH+xM82LcxM+JMWusweEUAAAZ8LjFq6TXd9Ot9eZe+OFdWtcYm4rvqx4Yv0zbzNdo1JjzdXsTzZ4lqTyRFAAAEEEHBbgPDHbfH41SP8iZ9tWpiZ8CctdJk9IoAAAj4X+HbeZj06fJG9yueuqqLOdYrGddV9flymD6dvsGv88kBjVbowZ1xrMjkCCCCAAAJuCxD+uC0ev3qEP/GzTQszE/6khS6zRwQQQMDnAp/M2KBePyyzV/nadTV0SbUL47rq50ev0BsT1to1vr6zgeqWyB3XmkyOAAIIIICA2wKEP26Lx68e4U/8bNPCzIQ/aaHL7BEBBBDwucDbk9bq2ZEr7FW+37W2WpbPH9dVvzlxjQaPWmnX+KBrHbUof0FcazI5AggggAACbgsQ/rgtHr96hD/xs00LMxP+pIUus0cEEEDA5wIvjVmpV8evsVf55R31Vb9knriu+uMZG9Tb5buN4rohJkcAAQQQQCAJAcIfcy4Lwh9zeunFTgh/vFCnJgIIIIDAvwT6/7xcw6aut//sp/saq0rh+D5/58znDD17ZRVdWze+zxmi7QgggAACCLgtQPjjtnj86hH+xM82LcxM+JMWusweEUAAAZ8LPP3dYn0xe5O9ynGPNlOpfOfFddWjlv6huz6dZ9foeXEF3dakZFxrMjkCCCCAAAJuCxD+uC0ev3qEP/GzTQszE/6khS6zRwQQQMDnAg98sUA/Ltpqr3Lm0xepQM4scV311NU7deOwWXaNh1qV0UOtysa1JpMjgAACCCDgtgDhj9vi8atH+BM/27QwM+FPWugye0QAAQR8LnDbR3M09rc/7VUu7tNGObJkjOuqF2z8S1e8Od2ucXuTEupxccW41mRyBBBAAAEE3BYg/HFbPH71CH/iZ5sWZib8SQtdZo8IIICAzwWuGzpTM9btsle5ZmB7ZUifLq6rXr19n1oPmWzXuK5uUf3nyipxrcnkCCCAAAIIuC1A+OO2ePzqEf7EzzYtzEz4kxa6zB4RQAABnwtc9vpULdq8N7TKzBnSaeWA9nFf8dY9B9Xw2fF2nUurXahXr6sR97oUQAABBBBAwE0Bwh83teNbi/Anvr6mz074Y3qH2R8CCCAQAIFWL03Smj/3h1aaO1smze/VOu6r3nvwqKr1HWPXuaj8BRrWtU7c61IAAQQQQAABNwUIf9zUjm8twp/4+po+O+GP6R1mfwgggEAABBr+Z5y27j0UWmnh88/V1Cdbxn3Vx0+cVKnuI+w69Urk1ld3Noh7XQoggAACCCDgpgDhj5va8a1F+BNfX9NnJ/wxvcPsDwEEEAiAgHUHjnUnjnWUy59dox9u6sqqK/QapYNHj4dqVS6UQz/f38SVuhRBAAEEEEDALQHCH7ek41+H8Cf+xiZXIPwxubvsDQEEEAiIQJkeI3T0eOivJNUomkvf39PIlZXXHjBWO/cfDtUqkTebJjzW3JW6FEEAAQQQQMAtAcIft6TjX4fwJ/7GJlcg/DG5u+wNAQQQCIDAkWMnVLbnSHuljUvn1ae31XNl5c2fn6ANuw6EauXLnllzerRypS5FEEAAAQQQcEuA8Mct6fjXIfyJv7HJFQh/TO4ue0MAAQQCILDnwBFV7/ervdI2FfNr6E21XVn5xa9O0bKtf4dqZc2UXsv7tXOlLkUQQAABBBBwS4Dwxy3p+Nch/Im/sckVCH9M7i57QwABBAIgsGXPQTVK9Mr1K2oU0pDO1V1Z+TXvzNDs9bvtWmsHdVD6dPxo5Qo+RRBAAAEEXBEg/HGF2ZUi/ITiCrOxRQh/jG0tG0MAAQSCIbB6+z61HjLZXuwN9Ypq4BVVXFl8tw/naPyKP+1ai/u0UY4sGV2pTREEEEAAAQTcECD8cUPZnRqEP+44m1qF8MfUzrIvBBBAICACCzft0eVvTLNXe0fTkureoYIrq7//iwX6adFWu9aMp1uqYM5zXalNEQQQQAABBNwQIPxxQ9mdGoQ/7jibWoXwx9TOsi8EEEAgIALT1+zU9e/Nslf7UKsyeqhVWVdW//R3i/XF7E12rbGPNFXpC7K7UpsiCCCAAAIIuCFA+OOGsjs1CH/ccTa1CuGPqZ1lXwgggEBABH5dvl23fzzXXm2PDhV0e9OSrqx+wM/L9d7U9Xat/97bSNWL5HKlNkUQQAABBBBwQ4Dwxw1ld2oQ/rjjbGoVwh9TO8u+EEAAgYAI/LBwix78cqG92oFXVNYN9Yq5svohv67SK+NW27U+u62eGpXO60ptiiCAAAIIIOCGAOGPG8ru1CD8ccfZ1CqEP6Z2ln0hgAACARH4fNZGdf9+ib3alztX1+U1Crmy+vemrNOAX36za73TpZbaVirgSm2KIIAAAggg4IYA4Y8byu7UIPxxx9nUKoQ/pnaWfSGAAAIBETgzgBnapZbauBTAfDF7o57+LiF4eumaarqyZuGAyLFMBBBAAAEEUhYg/EnZKChnEP4EpVP+XCfhjz/7wqoQQACBNCPwytjVGjJ2lb1fNz969eOirXrgiwV27f6XVVKXBsXTjD0bRQABBBAwX4Dwx5weE/6Y00svdkL444U6NRFAAAEEbIH/jPhN70xeZ3/9/T0NVaPo+a4IjV+xXd0+THjY9JPtyuvu5qVcqU0RBBBAAAEE3BAg/HFD2Z0ahD/uOJtahfDH1M6yLwQQQCAgAj3/u0Sfztxor3bMw01VNr87r1uftW6XOg+dade+r0VpPda2XEDkWCYCCCCAAAIpCxD+pGwUlDMIf4LSKX+uk/DHn31hVQgggECaEXjkq4X6bsEWe79Tn2yhwudndWX/S7fsVcfXptq1ujYsrj6XVnKlNkUQQAABBBBwQ4Dwxw1ld2oQ/rjjbGoVwh9TO8u+EEAAgYAI3PnJXI1ett1e7YJerXV+tkyurH7Dzn/U/IWJdq1OtQrr+U7VXKlNEQQQQAABBNwQIPxxQ9mdGoQ/7jibWoXwx9TOsi8EEEAgIAJdhs3SlNU77dWuHNBOmTOkd2X1O/YdVp2BY+1a7SsX0Fs31nKlNkUQQAABBBBwQ4Dwxw1ld2oQ/rjjbGoVwh9TO8u+EEAAgYAIXPnmNM3fuCe02gzpztHqge2V6AfVuO7i4JHjqtB7lF2jSZm8+uTWenGtyeQIIIAAAgi4KUD446Z2fGsR/sTX1/TZCX9M7zD7QwABBHwu0O7lyVrxx77QKnNkyaDFfdq6tuKTJ0+qVPcROhH621CqWTSXvrunkWv1KYQAAggggEC8BQh/4i3s3vyEP+5Zm1iJ8MfErrInBBBAIEACTQaP16bdB0MrLpgzi2Y8fZGrq6/SZ7T2HToWqlkuf3aNfripq/UphgACCCCAQDwFCH/iqevu3IQ/7nqbVo3wx7SOsh8EEEAgYAK1+v+qXf8cCa26VL5sGvdoc1d30OA/47Rt76FQzUK5ztW0p1q6Wp9iCCCAAAIIxFOA8Ceeuu7OTfjjrrdp1Qh/TOso+0EAAQQCJlC+10gdOnoitOqqhXPqx/sau7qD1i9N0uo/94dq5sqaUQt7t3G1PsUQQAABBBCIpwDhTzx13Z2b8Mddb9OqEf6Y1lH2gwACCARI4PiJU8/cOX3UL5lbX97RwNUdXP7GNC3cdOqB0xnTWw+c7uBqfYohgAACCCAQTwHCn3jqujs34Y+73qZVI/wxraPsBwEEEAiQwL5DR1Wlzxh7xReVv0DDutZxdQc3vjdLU9d486p5VzdKMQQQQACBNClA+GNO2wl/zOmlFzsh/PFCnZoIIIAAAiGB7X8fUr1B42yNS6pdqNeuq+Gqzp2fzNXoZdvtmvN7tVbubJlcXQPFEEAAAQQQiJcA4U+8ZN2fl/DHfXOTKhL+mNRN9oIAAggETGDdjv1q+eIke9XX1imiZ6+q6uouHvl6ob6bv8WuOeWJFiqSO6ura6AYAggggAAC8RIg/ImXrPvzEv64b25SRcIfk7rJXhBAAIGACSzdslcdX5tqr7pboxLqfUlFV3fR+4el+njG73bNkQ82UYWCOVxdA8UQQAABBBCIlwDhT7xk3Z+X8Md9c5MqEv6Y1E32ggACCARMYNa6Xeo8dKa96vtbltajbcq5uovnRq3QWxPX2jWH39VAdYrndnUNFEMAAQQQQCBeAoQ/8ZJ1f17CH/fNTapI+GNSN9kLAgggEDCBCSv+1C0fzrFX/WS78rq7eSlXd/HGhDV6fvRKu+YHt9RRi3IXuLoGiiGAAAIIIBAvAcKfeMm6Py/hj/vmJlUk/DGpm+wFAQQQCJjAz4u36r7PF9ir7ndZJd3UoLiru/hw2nr1+Wm5XfP162uoY9ULXV0DxRBAAAEEEIiXAOFPvGTdn5fwx31zkyoS/pjUTfaCAAIIBEzg6zmb9MS3i+1Vv9Cpmq6uVdjVXQyfu0mPf5OwhueuqqLOdYq6ugaKIYAAAgggEC8Bwp94ybo/L+GP++YmVST8Mamb7AUBBBAImMAH09arb6K7bt66oabaVyno6i5GLtmmuz+bb9fs1bGibm1cwtU1UAwBBBBAAIF4CRD+xEvW/XkJf9w3N6ki4Y9J3WQvCCCAQMAEznzezkfd6qpZ2Xyu7mLK6h3qMmy2XfOR1mX1wEVlXF0DxRBAAAEEEIiXAOFPvGTdn5fwx31zkyoS/pjUTfaCAAIIBExg8KgVejPRm7a+uauBarv8pq35G//SlW9Ot+XubFpST3eoEDBJlosAAggggEDSAoQ/5lwZhD/m9NKLnRD+eKFOTQQQQACBkECfH5fpw+kbbI0RDzRRxQtzuKqzavs+tRky2a55Q72iGnhFFVfXQDEEEEAAAQTiJUD4Ey9Z9+cl/HHf3KSKhD8mdZO9IIAAAgETeHz4Ig2ft9le9aTHm6tYnmyu7mLLnoNq9Ox4u+bl1S/Uy9fWcHUNFEMAAQQQQCBeAoQ/8ZJ1f17CH/fNTapI+GNSN9kLAgggEDCBez+br1+WbLNXPadHK+XLntnVXew9cFTV+o2xa7aqkF/v3Vzb1TVQDAEEEEAAgXgJEP7ES9b9eQl/3Dc3qSLhj0ndZC8IIIBAwAS6fjBbE1fusFe9vF9bZc2UwdVdHDt+QqV7jLRrNiiZR1/cUd/VNVAMAQQQQACBeAkQ/sRL1v15CX/cNzepIuGPSd1kLwgggEDABK55e4Zmb9gdWvU550hrB3ZQunTu/2hTrudIHT52IrSOKoVy6qf7GwdMkuUigAACCCCQtADhjzlXhvs/IZljx04kwh+uAgQQQAABzwQufnWKlm39O1Q/W6b0WtavnSdrqdX/V+3650iodsm82TT+seaerIOiCCCAAAIIOC1A+OO0qHfzEf54Z29CZcIfE7rIHhBAAIGACrR4YaLW7/wntHrrWT/WM3+8OJoOnqCNuw+ESl+QPbNme7QOL/ZOTQQQQAABswUIf8zpL+GPOb30YieEP16oUxMBBBBAICRQd+BY/bnvcOi/i+fJqomPt/BEpv0rU/TbNu/vQPJk8xRFAAEEEDBagPDHnPYS/pjTSy92QvjjhTo1EUAAAQRCApWfGa39h4+F/rtiwRwa8WATT2Q6vT1dczb8ZddeN8ibZw95snmKIoAAAggYLUD4Y057CX/M6aUXOyH88UKdmggggAACOnnypEp2H6GTob+JpDrFz9fwuxp6InPLB7M1IdFbx5b2bavzMrv71jFPNk5RBBBAAAHjBQh/zGkx4Y85vfRiJ4Q/XqhTEwEEEEBAB48cV4Xeo2yJZmXz6aNudT2Rue/z+fp58Ta79qzuFyl/jiyerIWiCCCAAAIIOClA+OOkprdzEf546x/06oQ/Qe8g60cAAQQCKrBz/2HVHjDWXn2HKgX05g21PNnNU98u1pdzNtm1xz3aTKXynefJWiiKAAIIIICAkwKEP05qejsX4Y+3/kGvTvgT9A6yfgQQQCCgAht3HVDT5yfYq7+6VmG90KmaJ7vp//NyDZu63q79432NVLVwLk/WQlEEEEAAAQScFCD8cVLT27kIf7z1D3p1wp+gd5D1I4AAAgEVsN6uZb1l6/Rxc4Ni6ntZZU9289Kvq/TquNV27c9vr6eGpfJ6shaKIoAAAggg4KQA4Y+Tmt7ORfjjrX/QqxP+BL2DrB8BBBAIqMC833frqrdm2Ku/u3kpPdmuvCe7GTp5rQaNWGHXfvem2mpdMb8na6EoAggggAACTgoQ/jip6e1chD/e+ge9OuFP0DvI+hFAAIGACkxetUM3vT/bXv1jbcrqvpZlPNnNZ7N+V4/vl9q1X+5cXZfXKOTJWiiKAAIIIICAkwKEP05qejsX4Y+3/kGvTvgT9A6yfgQQQCCgAiOXbNPdn823V9+7Y0V1a1zCk938sHCLHvxyoV27/+WV1aV+MU/WQlEEEEAAAQScFCD8cVLT27kIf5z1by3pdkn1JFn3e1vhiPXuV+u+9KGSJiVTLrukRyVdJcn66fW4pFWSvpT0mqQjKSzVqveEpI6Siko6KGmZpI8kDQuvxdndntqfTp4M/YsDAQQQQAAB1wS+mbdZjw1fZNd77qoq6lzH+uvP/WPs8u267eO5duGn2pfXXc1Kub8QKiKAAAIIIOCwAOGPw6AeTkf44wy+5fiWpDsTTWeFL9ZxbqI/GyLpkSRKWr8enCipePh7BySll5Q5/PUCSRdJ+ussy7XebTtaUp7w9/dLyiIpQ/hr63uXRhAgRatB+BOtGOcjgAACCDgi8PGMDer9g/U7jlPHa9fV0CXVLnRk7mgnmbF2l657d6Y97P6WpfVom3LRTsP5CCCAAAII+E6A8Md3LYl5QYQ/MdP9a+Atkt4P/8k3krpLOv3aD+unv+ckXRb+/pWSvk802gporPvWq4TvErpJ0lhJ6SR1kvSuJOuuoBGSLk5iuTklWU+ZLBD+dxdJ1q8fM4XvQrICp4zhcOoeZ7Zrz0L44zAo0yGAAAIIRCbw1sS1em5UwkOW3+9aWy3Le/OQ5SWb9+qS16faC7+lUXE9c0mlyDbCWQgggAACCPhYgPDHx82JcmmEP1GCneX0CZKaS1ojqYKkY2ecZ4Uv1k+oJcMf47ou0fdvlfRe+OuG4Y+IJR5unft5+A9aSRp3xtz9JfUMf8zL+klz/Rnff1rSoPDHyCqGP0rmzK752JdTjsyDAAIIIBClwItjVuq18dZfu6eOL++or/olT98AG+VkqTx93Y79avliwie7r6ldWIOvrpbKWRmOAAIIIICA9wKEP973wKkVEP44I2kFO9YdPt9KuvosU1rfs+76+VnSJYnOmSypiSQrQGqZxFirR2vDzwH6WNLNZ5zze/gZPx9I6pbE+PPCdxRZ/+4n6RlnthyahTt/HMRkKgQQQACByAX6/bRc709L+H3HT/c1VpXC1s2w7h9/7jukugMTfjdzcZWCeuOGmu4vhIoIIIAAAgg4LED44zCoh9MR/jiDb30kq32Ed/70kdQ3XDar/sfefUBXUW5tHH8EpIgUpXekS0eQGnoxcAU7VopY7lXsqEgTpFnwUhSvWMEG8tmwEXpHqlJCRzoIgoCAIp1vvScnk4hATpKTzMx7/rPWXVdzZubd+7fPWmY9mSIdCd7iZR7WPOQC5fxP0kOS9kgqlGgfEzjFX/PeXtJnFzg+vj7zQIJ64WmZ8CeMjpwKAQQQQCCZAs99sVKfLtnhHDW9W2OVzmf+zpH+29ETp1TxefN4vbitcbl8+qBL7fQvhBURQAABBBAIswDhT5hBXTwd4U948M2VPN8ET2We+WNutYq/Ft0ENC9JujF4BY/5U+Dh4L7mQc3xrwdpIynmAuWYZ/W8EfzMXNN+IPjP5s1gZj2zmVu61l7g+FckPRNcN5x/FuXKn/B8fzgLAggggEAyBR4dt0zfrvjFOWphj+YqmMu86yD9N/PWy9I9J+pM8OWXtUpcoc8fMndysyGAAAIIIOBvAcIff88vcfWEP+Gb5RPBBzubBy2bLfHbvn6XNC74bJ744Mbskzg0Mg8HWHmBcszDoicEPzMPhl4V/OdHJb0W/GcT6sSHSuee5nFJw4M/NA+PNm8DC2UL6R3uvOo9FEr2QQABBBAIp8B9Y5Zo+rq9zilX9mulnFnNI/bc2ar0nawjx+Me+VehYA5NeqKRO4WwKgIIIIAAAmEUIPwJI6bLpyL8Ce8AzNu4zFu/8p9zWvPqdvPMH/O8ncQPZL5L0ifBfcsmulro3KpaSpoS/GHih0Kbt4oNCv7c/MZ77oOm48/zgKS3g/9i3oO7O8S2CX9ChGI3BBBAAIH0Fbjj7QVauDnh7yk/D2qtTBnNizLd2eoOnq49h48FFi92ZTbNffZ8j/FzpzZWRQABBBBAIKUChD8plfPecYQ/4ZmJeXaPeeCyee6OuY3LhDLLgqeuEXzbVi1Jv0lqnugKH6+HP0npcNtXUkJ8jgACCCCQJgLtRs7Typ2HAufOkimD1g80j95zb2v+31natO/PQAFXZs+sn/qYv9uwIYAAAggg4G8Bwh9/zy9x9YQ/4ZmleR6PeS7PeknVJcX96S9hyyZpuaRykuYF3+5lPvX6bV9J6RD+JCXE5wgggAACaSLgtbDlhpHztCIYRmXOmEEbBrkbRqUJOidFAAEEEIg4AcIfe0ZO+JP6WZpn6JjrzjNJekzS6xc4ZeLn8xSQZB5UwAOfU+/PGRBAAAEEIlCg3ovTtftQ3N9ail6RTfO6u3ub1V3vLNQPm/Y7k9gwsLUyZ3LvNrQI/ErQMgIIIIBAGggQ/qQBqkunJPxJPXziAMc888e8Vv18W3Sit3nVlbRIEq96T70/Z0AAAQQQiECBqv0m6/CxuEfdlS+QQ5OfdPcByw98uFRT1/zqTGJZn5a6Inv8OyAicEC0jADpDfwFAAAgAElEQVQCCCBghQDhjxVjDDRB+JP6WZpn+vwUPI259evNC5yyk6Qxwc8qSVoT/Oc5wdvAZgSfB3Tu4WZG5rXxpSR9KMmcJ34zn22VVDz4oOn7zrN2dkl7JF0uqX/wodOp7zruDNz2FS5JzoMAAgggELKAectk2V4xOhV8t3qN4rn11cMNQj4+LXZ8cvxyfbVsl3Pquc82VbErzd942BBAAAEEEPCvAOGPf2d3vmDBnm7c6cQ8z8dc523+34RAdc7z1q2MkkzIY97UdVBSPkmng+WawObdYJBSL3hFUOJOzEOkxwd/0ELS9HPaHBB8hbx5o5gJlUwYlHh7NvgKerNeRUkbwshE+BNGTE6FAAIIIBCawPFTp1W+9yRn56gyefXx/eY/v+5tvSfE6uOF250CJj3RUBUK5nSvIFZGAAEEEEAgDAKEP2FA9MgpuPInPIN4TZJ5po/ZzG+jJnBZHfz3ypKGSGoV/HfzundzBU78Zp4VZEKjKpLMnwzNlT0m4DEPCrglGAyZ3x5jJLU5T7m5JK2TVDB4NVFHST9KMteam2BpePCfzRVJ5sqkcG6EP+HU5FwIIIAAAiEJHPzzhGoMmOrs26piAb3d0bxU073tpZh1GjV7k1PAFw/VU80SV7pXECsjgAACCCAQBgHCnzAgeuQUhD/hGYS56udLSea5PvHb8eA/ZEn0s3GSOiS66if+o5KSZkoy/282cxWPCX+yBv/dvDbevCLeXDV0vs08d2iypDzBD48Ej700+O9TJLWTFF9TeLrmtq9wOXIeBBBAAIFkCOw8eFRRL5v/bMZtN9UoomG3m5dtureNnLFRr05JuLj2gy611bicudCXDQEEEEAAAf8KEP74d3bnVk74E75ZGktzpc49wbd45Q/eymXe6rVY0mhJ319kOfPWsKcl3SzpKklngrdomcDIvEHsRBKlmjeIdZd0vaRiwdfNr5L0QfB5QOZ84d648ifcopwPAQQQQCBJgQ2/HlGrYeZu6rjt7jrFNegmcwGte9vo+Vv0wrfxj/OT/nf3NWpTpZB7BbEyAggggAACYRAg/AkDokdOQfjjkUH4tAzCH58OjrIRQAABPwss235QN/3vB6eFBxuVUs82V7va0v8t3aFnP1/p1PDKrVXVvpb5WwwbAggggAAC/hUg/PHv7M6tnPDHnlm60QnhjxvqrIkAAghEuMD8n3/T3e8uchSeaFFWT7Qo56rKxNjdeviT+Jd/Sn3bVtS9DcyFvGwIIIAAAgj4V4Dwx7+zI/yxZ3Ze6ITwxwtToAYEEEAgwgSmrN6jBz8y7zaI23q1uVoPNCrlqsLsDfvU6X1zl3fc9nSrcnqkWVlXa2JxBBBAAAEEUitA+JNaQe8cz5U/3pmFHysh/PHj1KgZAQQQ8LnAhGW79MT45U4Xg26qrLvrlHC1qx+3HdAtby5wavh341Lq0drdW9FcBWFxBBBAAAErBAh/rBhjoAnCH3tm6UYnhD9uqLMmAgggEOECnyzapl5fmXcaxG3Db6+uG2sUcVVl3Z7Dih4+16nhnrrFNfBGdx9C7SoIiyOAAAIIWCFA+GPFGAl/7Bmja50Q/rhGz8IIIIBA5Aq8M2ezBk1c6wC83aGmWlUq6CrIjgNH1fAVb71+3lUQFkcAAQQQsEKA8MeKMRL+2DNG1zoh/HGNnoURQACByBUYPm2Dhk/b6AB8cn8dNSiT11WQg3+eUI0BU50aWlYsoHc61nK1JhZHAAEEEEAgtQKEP6kV9M7x3PblnVn4sRLCHz9OjZoRQAABnwsMnrhWb8/Z7HTx1cP1VaP4Fa52deLUGZXrHePUUL90Ho19oK6rNbE4AggggAACqRUg/EmtoHeOJ/zxziz8WAnhjx+nRs0IIICAzwV6fRWrTxZtd7qY8mQjlSuQw/WuyvWK0YnTZwJ1VCuaS18/EuV6TRSAAAIIIIBAagQIf1Kj561jCX+8NQ+/VUP447eJUS8CCCBggcCT45frq2W7nE7mdW+qoldc5npn1wyYqgN/ngjUUTpfdk3v1sT1migAAQQQQACB1AgQ/qRGz1vHEv54ax5+q4bwx28To14EEEDAAoEHP1yqKWt+dTpZ1qelrsie2fXOGr4yQzsO/BWoo2DOrFrYs7nrNVEAAggggAACqREg/EmNnreOJfzx1jz8Vg3hj98mRr0IIICABQL3vLtI837+zelk/cBoZcmU0fXOoofP0bo9RwJ15MiSSbEvXOd6TRSAAAIIIIBAagQIf1Kj561jCX+8NQ+/VUP447eJUS8CCCBggcBN/5uvZdt/D3SSKcMl2jiotRL9cupah7e++YOWbjsYWD/DJdKmwW08UZdrICyMAAIIIOB7AcIf34/QaYDwx55ZutEJ4Y8b6qyJAAIIRLjAdcPmaP2vcVfY5MyaSSv7eeMKm07vL9bsDfuc6azpf50uy5wpwqdF+wgggAACfhYg/PHz9P5eO+GPPbN0oxPCHzfUWRMBBBCIcIGol2do58G4Z+sUypVVC3p449k6XT/5Sd/H7nams7hXc+XPkTXCp0X7CCCAAAJ+FiD88fP0CH/smZ77nRD+uD8DKkAAAQQiTsCrb9V69vMV+r+lO515zOjWWKXyXR5x86FhBBBAAAF7BAh/LJqlPa3QiQsChD8uoLMkAgggEOkC5XvH6PipMwGGqkVz6ZtHojxB8sK3qzV6/lanlm8fiVKVork8URtFIIAAAgggkBIBwp+UqHnzGG778uZc/FIV4Y9fJkWdCCCAgCUCp06fUZleMU43dUtdqU8frOeJ7v47Zb1en/GzU8u4B+qqXuk8nqiNIhBAAAEEEEiJAOFPStS8eQzhjzfn4peqCH/8MinqRAABBCwROHzspKr2m+J007xCfr3X+VpPdDdq9ia9FLPOqeXdjrXUomIBT9RGEQgggAACCKREgPAnJWrePIbwx5tz8UtVhD9+mRR1IoAAApYI7Dl0THVfnO5007ZaYb1+Zw1PdPfRwm3qM2GVU8uIO6rrhupFPFEbRSCAAAIIIJASAcKflKh58xjCH2/OxS9VEf74ZVLUiQACCFgisGnfH2r+39lON3fWLqYXb67qie4mLNulJ8Yvd2oZdFNl3V2nhCdqowgEEEAAAQRSIkD4kxI1bx5D+OPNufilKsIfv0yKOhFAAAFLBGJ3HlLbkfOcbu6Lukp9rq/oie6mrvlVD3y41KmlZ5sKerBRaU/URhEIIIAAAgikRIDwJyVq3jyG8Mebc/FLVYQ/fpkUdSKAAAKWCCzcvF93vL3Q6eaxZmX0VKvynujuh02/6a53FiXU1rysnmpZzhO1UQQCCCCAAAIpESD8SYmaN48h/PHmXPxSFeGPXyZFnQgggIAlAjPW/aouYxKurnmudQX9p7E3rq5ZufN3tRs535H20lVJloyfNhBAAAEE0lmA8CedwdNwOcKfNMSNgFMT/kTAkGkRAQQQ8JLAtyt+0aPjljklDbihkjrUK+mJEs99HtEd1xbTS7d443lEngCiCAQQQAAB3wkQ/vhuZBcsmPDHnlm60QnhjxvqrIkAAghEsMD4JdvV/YtYR+C/t1XTLTWLekLk18PHVGdwwpvIrq9aSCPvusYTtVEEAggggAACKREg/EmJmjePIfzx5lz8UhXhj18mRZ0IIICAJQLvz9ui/t+tcboZdc81iq5cyBPd/XH8lCr3nezU0qR8Po25t7YnaqMIBBBAAAEEUiJA+JMSNW8eQ/jjzbn4pSrCH79MijoRQAABSwRGztioV6dscLr5sEttNSqXzxPdnTlzVqV6TnRqubbkFfrsP/U9URtFIIAAAgggkBIBwp+UqHnzGMIfb87FL1UR/vhlUtSJAAIIWCLw8qR1enPWJqebLx6qp5olrvRMd5Wen6Q/T5wO1HN1oZyKebyhZ2qjEAQQQAABBJIrQPiTXDHv7k/4493Z+KEywh8/TIkaEUAAAYsE+n69Sh8s2OZ0ZMIVE7J4Zas9aJr2HjkeKKf4lZdpzrNNvVIadSCAAAIIIJBsAcKfZJN59gDCH8+OxheFEf74YkwUiQACCNgj8PRnK/T5jzudhuY801TF81zmmQabvTpLm3/7M1BPnuyZ9WOflp6pjUIQQAABBBBIrgDhT3LFvLs/4Y93Z+OHygh//DAlakQAAQQsEnj4kx81MXaP09HS3i2U9/Isnumw3ch5WrnzUKCeLJkyaP3A1p6pjUIQQAABBBBIrgDhT3LFvLs/4Y93Z+OHygh//DAlakQAAQQsEuj0/mLN3rDP6Wht/2hly5zRMx3e+fZCLdi836nn50GtlSljBs/URyEIIIAAAggkR4DwJzla3t6X8Mfb8/F6dYQ/Xp8Q9SGAAAKWCdw26gct2Xow0NUll0ibB7dRol9MXe/2/g+WatraX506VjzfSrkuu9T1uigAAQQQQACBlAgQ/qREzZvHEP54cy5+qYrwxy+Tok4EEEDAEoE2I+Zqze7DgW4uz5JJq164zlOdPfHpMk1Y/otT0/znmqlI7myeqpFiEEAAAQQQCFWA8CdUKe/vR/jj/Rl5uULCHy9Ph9oQQAABCwWaDJmprfuPBjrLnyOLFvdq4akue30Vq08WbXdqmvJkI5UrkMNTNVIMAggggAACoQoQ/oQq5f39CH+8PyMvV0j44+XpUBsCCCBgocC1g6ZpX/BV6lflza6ZTzfxVJcvTlyrt+Zsdmr68uH6uqb4FZ6qkWIQQAABBBAIVYDwJ1Qp7+9nQ/iTV9Jv3qe2skLCHyvHSlMIIICAdwUqPT9Jf544HSiwUuGc+v6xhp4q9rXpGzV06ganpg+71Fajcvk8VSPFIIAAAgggEKoA4U+oUt7fz2vhT4ykDskIc1pK+kBSYe9TW1kh4Y+VY6UpBBBAwJsCZ86cVeleE3U28F8fqXbJK/V//6nnqWLfm7dFA75b49T05t3XqHWVQp6qkWIQQAABBBAIVYDwJ1Qp7+/ntfDnjKQ9kjpJmnoRvkySBkt6yrzsQ5J33vHq/ZmHs0LCn3Bqci4EEEAAgYsKHD1xShWfn+zs06R8Po25t7an1MYv2a7uX8Q6NQ25tapuq1XMUzVSDAIIIIAAAqEKEP6EKuX9/bwW/myUVFqSCYGGSeoh6dQ5jObzcZJqBoOf8ZLu9D61lRUS/lg5VppCAAEEvClgnvVjnvkTv/2rSiG9cfc1nir2u5W/6JGxy5ya+rWtqM4NrvJUjRSDAAIIIIBAqAKEP6FKeX8/r4U/l0t6U9Ldkkyw8JOkOyRtClJ2lPS6JPPajD8lPSZptPeZra2Q8Mfa0dIYAggg4D2Bbfv/VOMhs5zCbqtZVENuq+apQmeu36t7Ry9xanrmuvLq2rSMp2qkGAQQQAABBEIVIPwJVcr7+3kt/IkXMyHPSEkmDPpD0tOSGgWv8DE1mz+pmat9Ep6o6H1rGysk/LFxqvSEAAIIeFRgzS+H1ea1uU51neuXVL92lTxV7ZKtB3TbqAVOTQ81Ka3u0RU8VSPFIIAAAgggEKoA4U+oUt7fz6vhj5EzfyYbK6lW8CqgeM0RkrpLOul9XusrJPyxfsQ0iAACCHhHYOnWA7o1UbDycJPSetZjwcra3YfVekRCQNWxXgn1v6GydxCpBAEEEEAAgWQIEP4kA8vju3o5/DF0z0vqFzQ0QYN5gmKLZLwNzOP8vi+P8Mf3I6QBBBBAwD8CszfsU6f3FzsFe/GWqh0HjqrhKzOdGm++poiGtq/uH2QqRQABBBBAIJEA4Y89Xwevhj8FJH0kqXnwoc5LJZmb+s1bvuLfBpbwxEd75uG3Tgh//DYx6kUAAQR8LBATu1sPfWIeBxi39W1bUfd67GHKB/48oWsGJLywtFXFAnq7o7mImQ0BBBBAAAH/CRD++G9mF6rYi+FPa0ljJOUN3trVU9JQSeZdruYtX+aVGeZtYOZn5rNz3wZmz3S83wnhj/dnRIUIIICANQKf/7hTT3+2wunnlVuqqv213nqN+vFTp1W+9ySnxgZl8uiT++taMwMaQQABBBCILAHCH3vm7bXwx7ze3bzBy9T1c/BNXwl/4ot7y9eo4MOe498GZh78bPZlS38Bwp/0N2dFBBBAIGIFPlywVc9/vdrpf+RdNXR91cKe8yjXK0YnTpu/U0nViuXW110beK5GCkIAAQQQQCAUAcKfUJT8sY/Xwp+435Tibvl6OPg69/NJdgq+8t28DeyIpFz+4LauSsIf60ZKQwgggIB3Bd6ctUkvT1rnFDi687VqWiG/5wo2t32Z27/MVjpfdk3v1sRzNVIQAggggAACoQgQ/oSi5I99vBb+HAqGPp+EwGfeBmZuA7tGUsYQ9meX8AsQ/oTflDMigAACCFxA4L9T1uv1GQkX+45/sK7qlMrjOa9Gr8zU9gNHA3UVyJlFi3qad1WwIYAAAggg4D8Bwh//zexCFXst/CktaVMyeM0DoAdLejYZx7Br+AQIf8JnyZkQQAABBJIQ6P/tGr0/f4uz13ePRqlyEe9d/Gte9W5e+W62y7Nk0qoXrmO2CCCAAAII+FKA8MeXYztv0V4Lf+yRjYxOCH8iY850iQACCHhC4LkvVurTJTucWmZ0a6xS+cwd4N7a2o9aoMVbDzhFbR7cRhky8CuXt6ZENQgggAACoQgQ/oSi5I99+E3EH3PyapWEP16dDHUhgAACFgo8Om6Zvl3xi9PZop7NVSBnVs912mXMEs1Yt9epK7ZfK+XIeqnn6qQgBBBAAAEEkhIg/ElKyD+fey38KZ5Cuu0pPI7DUidA+JM6P45GAAEEEEiGwLmhysp+rZTTg6HKuSHVwh7NVTCX90KqZNCzKwIIIIBAhAoQ/tgzeK+FP6dTQGsCCPPsH7b0FyD8SX9zVkQAAQQiVqD9Wwu0eEvC7VSbBrdRRg/eTtXjy1iNW5zwd6lpTzVSmfw5InZuNI4AAggg4F8Bwh//zu7cyr0W/sS/6j25whmSewD7h0WA8CcsjJwEAQQQQCAUgX+9Nlerf4l7kPJlmTNqTf/oUA5L930GT1yrt+dsdtb96uH6qlH8inSvgwURQAABBBBIrQDhT2oFvXO818KfEknQmFd61JH0pKR8kjpIWitpm3dII6oSwp+IGjfNIoAAAu4KNB4yU9v2x71CPX+OLFrcy5uvUH9t+kYNnbrBwfr4vjqKKpvXXTxWRwABBBBAIAUChD8pQPPoIV4Lf0JlMjfOT5dUUlINSQlPVQz1DOwXDgHCn3Aocg4EEEAAgZAEag2cqt/+OBHYt1Te7JrxdJOQjkvvnd6bt0UDvlvjLDvqnmsUXblQepfBeggggAACCKRagPAn1YSeOYFfwx8DWFPSEkmvS3rcM6KRVQjhT2TNm24RQAABVwXK947R8VNxd4hXLZpL3zwS5Wo9F1r8/5bs0LNfrHQ+HnJrVd1Wq5gna6UoBBBAAAEELiZA+GPP98PP4Y+ZwhFJ+8wfAO0Zia86Ifzx1bgoFgEEEPCvwMnTZ1S2V4zTQL1SeTTuwbqebGhi7G49/MlPTm1921bUvQ2u8mStFIUAAggggADhT2R8B/wc/piHPP8hyfSQLTLG5bkuCX88NxIKQgABBOwU+P3oCVXvP9VprmXFAnqnYy1PNjt7wz51en+xU9vTrcrpkWZlPVkrRSGAAAIIIED4ExnfAT+HP80lmd8Cf5XEjfTufF8Jf9xxZ1UEEEAg4gR2HjyqqJdnOn3fVKOIht1e3ZMOP247qFve/MGp7d+NS6lH66s9WStFIYAAAgggQPgTGd8BP4Y/l0q6SdLQYOjzqaS7I2NcnuuS8MdzI6EgBBBAwE6BdXsOK3r4XKe5DnVLaMCNlT3Z7IZfj6jVsDlObXfXKa5BN1XxZK0UhQACCCCAAOFPZHwHvBb+bE6C3bzlK3/wVi9T+6Hgq98T3qcaGXPzSpeEP16ZBHUggAAClgv8uO2AbnlzgdPlfxqX1nOtK3iy612//6UGL81waruxemENv8O8nJQNAQQQQAABfwnwwGd/zeuiQZ7HWol7hUdo2zxJj0paEdru7JUGAoQ/aYDKKRFAAAEE/ikwa/1edR5tXvIZtz1zXXl1bVrGk1SH/jqpai9McWprcXV+vdvpWk/WSlEIIIAAAghcTIDwx57vh9eu/OmUBO0pSQeDgc8ue8bg204If3w7OgpHAAEE/CXw/crd6jo24Q1a/dpWVGePvkHr9JmzKt1zogNc56orNf7f9fwFTrUIIIAAAgiYW24ucSIDr2UHzCeZAgwwmWDs/jcBwh++EAgggAAC6SIwfsl2df8i1lnr1duq6daaRdNl7ZQscnWfSfrr5OnAoZWL5NR3jzZMyWk4BgEEEEAAAVcFCH9c5Q/r4oQ/YeWMuJMR/kTcyGkYAQQQcEfgvXlbNOC7Nc7io+65RtGVvfuyz2sHTdO+I8cD9ZbMc5lmPdPUHThWRQABBBBAIBUChD+pwPPYoYQ/HhuIz8oh/PHZwCgXAQQQ8KvAiGkbNWxawvsdPr6vjqLK5vVsO81enaXNv/0ZqC/v5Zm1tHdLz9ZKYQgggAACCFxIgPDHnu+Gm+FP8TAybg/juThV6AKEP6FbsScCCCCAQCoEBk9cq7fnJLwU9KuH66tG8StScca0PbTt6/MUu8u8lFTKemkGrRvQOm0X5OwIIIAAAgikgQDhTxqgunRKN8OfuBvhU7+ZACJT6k/DGVIgQPiTAjQOQQABBBBIvkCPL2M1bnHC33qmPdVIZfLnSP6J0umIO99eqAWb9zurbRzUWpdmzJBOq7MMAggggAAC4REg/AmPoxfO4mb4k5zXuidlxW9TSQmlzeeEP2njylkRQAABBM4ReGzcMn2z4hfnpwt6NFOhXNk86/TAh0s1dc2vTn3Ln2+p3Jdl9my9FIYAAggggMD5BAh/7PleuBn+lAgj47YwnotThS5A+BO6FXsigAACCKRCoMuYJZqxbq9zhth+rZQj66WpOGPaHvrU+OX6ctkuZ5F53Zuq6BWXpe2inB0BBBBAAIEwCxD+hBnUxdO5Gf642DZLh0mA8CdMkJwGAQQQQODiAu3fWqDFWw44O20e3EYZMnj315g+E1bpo4UJf5ua9ERDVSiYkzEjgAACCCDgKwHCH1+N66LFeve3Jv8am9/sHpJ0g6Syksy/75O0UdJsScMl/X6e9syDC7pJukXSVZLMM5HMa00+lfS6pBNJkBSQ9Kyk6yWZh2n/JWm1pA8kvScpENSEeSP8CTMop0MAAQQQOL/Av16bq9W/HA58eFnmjFrTP9rTVC9PWqc3Z21yavz8P/VUq+SVnq6Z4hBAAAEEEDhXgPDHnu+E2+GPee7PbklFzkN6tSRzPfdKH3E3lTROkglizGYCm6OScifqoYak5ef0ZG6BmyWpZPDn5piMkrIE/32ZpOaSDl7AoqakyZLyBD//w7xcJNGDsM1n7UIIkJJLTfiTXDH2RwABBBBIkUDjITO1bb/5z6OUP0cWLe7VIkXnSa+D3pj5s4ZMXu8sN+bea9WkfP70Wp51EEAAAQQQCIsA4U9YGD1xEi+EP3skFT6PhgmF8vnoTV4NJE2VZJ4++aWkFyX9GLzixtzkXyl4NZC5CmdLon7Nm8p+klQlGIR1lDRNknmI9W2S3pFkrgqaKOlf53HKJWmdpILB/+8gaakk81TJByQNC4Zob0p6OMzfOsKfMINyOgQQQACB8wvUGjhVv/0RdxFsqbzZNePpJp6m+uCHrer7jbkAN24beVcNXV/1fL/ueLoNikMAAQQQiHABwh97vgBeD3/Mn8jMFTBe30y4E2t+Hw3eovVYMgq+T9K7wf3rS1pwzrF3Shob/Jn5M+f0cz4fIKl38DYvEzAlDpbMrj0kDQ7eRlYxeCtZMsq76K6EP+GS5DwIIIAAAhcVKN87RsdPxb0otGrRXPrmkShPi33x4051+2yFU+NLN1fRHbXNXdlsCCCAAAII+EeA8Mc/s0qqUsKfpIRC+/zfkkZJMlcxmef1HAvtsMBecyQ1lDRTUrPzHGdmZB4aYM77oaRO5+xjniZpfpscLanLeY6/PHhFkfn//pL6JqO2pHYl/ElKiM8RQAABBFItcPL0GZXtFeOcp16pPBr3YN1UnzctTzB59R79+yNzAXDc1vtfV+v+huZvRGwIIIAAAgj4R4Dwxz+zSqpSwp+khEL7fL4kc9WOeTBzcq76MVcMHQne4mUe1jzkAsv9L/gQaRMuFUq0T/ngrV7mR+0lfXaB480tY60lLZRUL7SWQtqL8CckJnZCAAEEEEiNwO9HT6h6f3NnddzWsmIBvdOxVmpOmebHzv/5N9397iJnnSdalNUTLcql+bosgAACCCCAQDgFCH/CqenuuQh/Uu9vHspsXj9inrHTOXgFj7kNy4Qt5sHP5iHNi4NXBn1/znLmQc3m+TxmayMp4c+af9/RPKvnjeCPzEOd4991a94M9nnw5+aWrrUXaOcVSc8E6zTPCArXRvgTLknOgwACCCBwQYGdB48q6mVzgWzcdlONIhp2e3VPi63Y8btueMP8bShuuz/qKvW+3vynmg0BBBBAAAH/CBD++GdWSVVK+JOUUNKfJ776xtxW9WTwAc3ne9OXebbPg4leu95W0jfBJapd5M1m5rXxE4L7mQdDrwr+86OSXgv+swl14t6B+8/t8eAr5s0n5uHR5m1g4dgIf8KhyDkQQAABBC4qsG7PYUUPn+vs06FuCQ24sbKn1Tbt+0PN/zvbqfGOa4vppVuqerpmikMAAQQQQOBcAcIfe74ThD+pn6V56ED8Q5rNkyh/l2SeAfS1pJPB5/G8Gnxzl1mtm6ShwWXvkvRJ8J/LSvr5AuW0lDQl+Fnih0L3lDQo+PNLJZ26wPHmrV9vBz8zrxoxb1ILZQuEO0ltZ8+GtFtSp+FzBBBAAAEEzivw47YDuuXNhPch/KdxaT3XuoKntX49fEx1Bie8o+H6qoU08q5rPF0zxSGAAAIIIHCuAOGPPd8JLwF2DdUAACAASURBVIQ/qU0OzPHmdelubSaMSbiuW7op0VU68TWZ17ab17mbq3v2B1/LboIawh+3psa6CCCAAAK+EZi1fq86j17i1PvMdeXVtWkZT9f/5/FTqtR3slNjk/L5NObe2p6umeIQQAABBBAg/LH3O+CF8Ce1uib8cfN18OY2rJXBJjZKutDTHO+R9FFwP3O1kHkKJLd9pXb6HI8AAgggYL3A9yt3q+tY8zeUuK1f24rq3MC8BNO7m7kqtlTPiYq/OLZWiSv0+UPm70VsCCCAAAII+EeAK3/8M6ukKnU7/AnXa8dfSKrRNPz8yuDVPGaJbyW1u8Ba5lrv+He+3i7p/yTxwOc0HAynRgABBBCwQ2D8ku3q/kWs08yrt1XTrTWLer65Kn0n68jxuDuyKxTMoUlPNPJ8zRSIAAIIIIBAYgHCH3u+D26HP7ZI7pRUJInwJ3HQE/9adl71bss3gD4QQAABBNJM4L15WzTguzXO+Ufdc42iKxdKs/XCdeJ6L07X7kPHAqcrekU2zeveLFyn5jwIIIAAAgikiwDhT7owp8sihD/hYX5f0r3BBzabBzefb+sg6cPgB9cmesX7HEkNJc2Q1Pw8B5oZmQdBlwoe3ynRPuazrcGHSpsa7jvP8dkl7ZF0uSTzNrJwXW1lluJtX+H5/nAWBBBAAIGLCIyYtlHDpm1w9vj4vjqKKpvX82Yth87Wxr1xL9jMfdmlWv58K8/XTIEIIIAAAggkFiD8sef7QPgTnlma8MaEOGa70AOfl0ky73jdFQxrzJvBzGYCG/MKeBOk1As+CyhxVeYqofHBH7SQlPDqkLgfDpDUW9JRSZWCYVDi45+V9LKk05IqSkr47Tn1vRP+pN6QMyCAAAIIJCEweOJavT1ns7PXVw/XV43iV3je7ab/zdey7eYloNKlGS/RhoGtleiXaM/XT4EIIIAAAggQ/tjzHSD8Cd8sP5N0a/D5P/Gvejc3+heXNESSCXHM1lnSB4mWNW8qM0+xNA+ONsGQubLHBDzmDWG3BIOhnJJiJLU5T7m5JK0LvkHMXBPfMfhsoczBYGm4JPPPb0p6OHztBs5E+BNmUE6HAAIIIPBPgR5fxmrc4u3OB9OeaqQy+XN4nqrDe4s0d+NvTp3rBkQr66VuvqPC82QUiAACCCDgMQHCH48NJBXlEP6kAu+cQ83tVRMlxT/N8XjwapzEf5o0D6bud54lS0qaKcn8v9nMVTwm/Mka/Hdz1ZC5JezgBco1zxMy75PNE/z8SPDYS4P/PiX4IGpTUzg3wp9wanIuBBBAAIHzCjw2bpm+WfGL89mCHs1UKFc2z2s99PGPilll7ryO25b2bqG8l2fxfN0UiAACCCCAQLwA4Y893wXCn/DO0gQ2XSSZ5/tUlmT+LLlX0lxJr0v64SLLmX2flnSzJPP+WnNbmLlFa1zw2BNJlFpAUndJ10sqJsk8YXJV8Coj8zyg+NvMwtkx4U84NTkXAggggMB5BbqMWaIZ68x/TuO22H6tlCNr/N83vIv2zGcr9NmP5p0QcdvsZ5qoRB7ztyI2BBBAAAEE/CFA+OOPOYVSJeFPKErscyEBwh++GwgggAACaS7Q/q0FWrzlgLPO5sFtlCGD93+F6ffNao35wbyXIW777tEoVS5i7tZmQwABBBBAwB8ChD/+mFMoVXr/N6dQumAftwQIf9ySZ10EEEAgggTajJirNbsPBzrOnjmjVveP9kX3/52yXq/PMC/sjNs+fbCu6paKv0PbFy1QJAIIIIBAhAsQ/tjzBSD8sWeWbnRC+OOGOmsigAACESbQeMhMbdtvHocn5c+RRYt7mZdfen97a/YmvRhj3skQt73XqZaaX23u0mZDAAEEEEDAHwKEP/6YUyhVEv6EosQ+FxIg/OG7gQACCCCQ5gI1B0zV/j/jHn1XKl92zejWJM3XDMcCHy/cpt4TzOP34rYRd1TXDdWLhOPUnAMBBBBAAIF0ESD8SRfmdFmE8CddmK1dhPDH2tHSGAIIIOAdgfK9Y3T8VNx7C6oWzaVvHonyTnEXqeTr5bv0+KfLnT0G3lhZ99Qt4YvaKRIBBBBAAAEjQPhjz/eA8MeeWbrRCeGPG+qsiQACCESQwMnTZ1S2V4zTcf3SeTT2gbq+EJi+9lfd98FSp9bnWlfQfxqX9kXtFIkAAggggADhj13fAcIfu+aZ3t0Q/qS3OOshgAACESbw+9ETqt5/qtN1y4oF9E7HWr5QWLh5v+54e6FT66PNyqhbq/K+qJ0iEUAAAQQQIPyx6ztA+GPXPNO7G8Kf9BZnPQQQQCDCBHYePKqol2c6Xd9co4iG3l7dFwqrdh3S9a/Pc2rtXL+k+rWr5IvaKRIBBBBAAAHCH7u+A4Q/ds0zvbsh/ElvcdZDAAEEIkxg3Z7Dih4+1+m6Q90SGnBjZV8obNv/pxoPmeXUemvNonr1tmq+qJ0iEUAAAQQQIPyx6ztA+GPXPNO7G8Kf9BZnPQQQQCDCBH7cdkC3vLnA6do8M8c8O8cP229/HFetgdOcUltXLqg376nph9KpEQEEEEAAgYAAD3y254tA+GPPLN3ohPDHDXXWRAABBCJIYNb6veo8eonT8TPXlVfXpmV8IXDs5GlV6DPJqbVh2bz66L46vqidIhFAAAEEECD8ses7QPhj1zzTuxvCn/QWZz0EEEAgwgS+X7lbXcf+5HTdr21FdW5wlS8Uzp49q3K9Y3TydOA/l6peLLcmdG3gi9opEgEEEEAAAcIfu74DhD92zTO9uyH8SW9x1kMAAQQiTGD8ku3q/kWs07V5Zo55do5fthr9p+jg0ZOBcsvmv1xTn2rsl9KpEwEEEEAAAW77sug7QPhj0TBdaIXwxwV0lkQAAQQiSeC9eVs04Ls1Tsuj7rlG0ZUL+YYg6uUZ2nnwr0C9hXJl1YIezX1TO4UigAACCCDAM3/s+Q4Q/tgzSzc6IfxxQ501EUAAgQgSGDFto4ZN2+B0/PF9dRRVNq9vBKKHz9G6PUcC9ebIkkmxL1znm9opFAEEEEAAAcIfe74DhD/2zNKNTgh/3FBnTQQQQCCCBAZPXKu352x2Ov7q4fqqUfwK3wjcNuoHLdl6MFDvJZdImwe3SXwJvW/6oFAEEEAAgcgUIPyxZ+6EP/bM0o1OCH/cUGdNBBBAIIIEenwZq3GLtzsdT3uqkcrkz+Ebgc6jF2vW+n1OvatfuE7Zs2TyTf0UigACCCAQ2QKEP/bMn/DHnlm60QnhjxvqrIkAAghEkMBj45bpmxW/OB0v6NFMhXJl843AI2N/0ncrdzv1LurZXAVyZvVN/RSKAAIIIBDZAoQ/9syf8MeeWbrRCeGPG+qsiQACCESQQJcxSzRj3V6n49h+rZQj66W+Eejx5UqNW7zDqXd6t8Yqne9y39RPoQgggAACkS1A+GPP/Al/7JmlG50Q/rihzpoIIIBABAm0f2uBFm854HRsnpmTIYN/fn0Z+N0avTtvi1P/110bqFqx3BE0QVpFAAEEEPCzAOGPn6f399r989uTPeY2dUL4Y9M06QUBBBDwoECbEXO1ZvfhQGXZM2fU6v7RHqzywiUNn7ZBw6dtdHb45P46alDGP28r8xU2xSKAAAIIhF2A8CfspK6dkPDHNXorFib8sWKMNIEAAgh4V6DxkJnatv9ooMD8ObJoca8W3i32PJW9O3ezBn6/1vnkrQ41dV2lgr7qgWIRQAABBCJXgPDHntkT/tgzSzc6IfxxQ501EUAAgQgSqDlgqvb/eSLQcal82TWjWxNfdf/p4u167stYp+b/3lZNt9Qs6qseKBYBBBBAIHIFCH/smT3hjz2zdKMTwh831FkTAQQQiCCB8r1jdPzUmUDHVYvm0jePRPmq++9W/qJHxi5zan6hXSV1ql/SVz1QLAIIIIBA5AoQ/tgze8Ife2bpRieEP26osyYCCCAQIQInT59R2V4xTrf1S+fR2Afq+qr7Wev3qvPoJU7Nz1xXXl2blvFVDxSLAAIIIBC5AoQ/9sye8MeeWbrRCeGPG+qsiQACCESIwO9HT6h6/6lOty0rFtA7HWv5qvulWw/o1lELnJofalJa3aMr+KoHikUAAQQQiFwBwh97Zk/4Y88s3eiE8McNddZEAAEEIkRgx4GjavjKTKfbm2sU0dDbq/uq+3V7Dit6+Fyn5g51S2jAjZV91QPFIoAAAghErgDhjz2zJ/yxZ5ZudEL444Y6ayKAAAIRImBDcLLz4FFFvZwQYN1Uo4iG+SzAipCvG20igAACCJxHgPDHnq8F4Y89s3SjE8IfN9RZEwEEEIgQARtumTp09KSq9Z/iTMyPt65FyNeNNhFAAAEECH+s/g4Q/lg93jRvjvAnzYlZAAEEEIhcARselnzq9BmVSfTQ6nql8mjcg/56aHXkfgPpHAEEEECAK3/s+Q4Q/tgzSzc6IfxxQ501EUAAgQgRsOU16RX6xOjYybjX1VcpkkvfPuqv19VHyNeNNhFAAAEEziNA+GPP14Lwx55ZutEJ4Y8b6qyJAAIIRIjA+CXb1f2LWKfbV2+rpltrFvVd97UGTtNvfxwP1F0qb3bNeLqJ73qgYAQQQACByBQg/LFn7oQ/9szSjU4If9xQZ00EEEAgQgTem7dFA75b43Q76p6aiq5c0HfdNxkyU1v3Hw3UnS9HFi3p1cJ3PVAwAggggEBkChD+2DN3wh97ZulGJ4Q/bqizJgIIIBAhAiOmbdSwaRucbj++r46iyub1XffXvz5Xq3YdDtSd7dKMWjsg2nc9UDACCCCAQGQKEP7YM3fCH3tm6UYnhD9uqLMmAgggECECgyeu1dtzNjvdTujaQNWL5fZd93e8vUALNx9w6t40uI0yZuBXMN8NkoIRQACBCBQg/LFn6PzmYc8s3eiE8McNddZEAAEEIkSgx5exGrd4u9PttKcaqUz+HL7r/v4Plmja2r1O3Sv6tlKubJf6rg8KRgABBBCIPAHCH3tmTvhjzyzd6ITwxw111kQAAQQiROCxccv0zYpfnG4X9miugrmy+q77Jz5dpgnLE/qY/1wzFcmdzXd9UDACCCCAQOQJEP7YM3PCH3tm6UYnhD9uqLMmAgggECECXcYs0Yx1CVfMxPZrpRxZ/XfFTO8Jsfp4YcIVTFOebKRyBfx3BVOEfO1oEwEEEEAgkQDhjz1fB8Ife2bpRieEP26osyYCCCAQIQLt31qgxVsSnpWzeXAbZfDhs3JejFmrt2YnPLvoi4fqq2aJKyJkirSJAAIIIOBnAcIfP0/v77UT/tgzSzc6IfxxQ501EUAAgQgRaDNirtbsjntLVvbMGbW6vz/fkjVyxka9OiXhrWUfdKmtxuXyRcgUaRMBBBBAwM8ChD9+nh7hjz3Tc78Twh/3Z0AFCCCAgLUCjYfM1Lb9RwP95c+RRYt7tfBlr2Pmb1G/b9c4tf/v7mvUpkohX/ZC0QgggAACkSVA+GPPvLnyx55ZutEJ4Y8b6qyJAAIIRIhAzQFTtf/PE4FuS+XLrhndmviy88+W7tAzn690an/llqpqf20xX/ZC0QgggAACkSVA+GPPvAl/7JmlG50Q/rihzpoIIIBAhAiU7x2j46fOBLqtWjSXvnkkypedT1q1W//5+Cen9j7XV9R9UVf5sheKRgABBBCILAHCH3vmTfhjzyzd6ITwxw111kQAAQQiQODk6TMq2yvG6bR+6Twa+0BdX3Y+b+Nvuue9RU7tT7Yop8dblPVlLxSNAAIIIBBZAoQ/9syb8MeeWbrRCeGPG+qsiQACCESAwO9HT6h6/6lOpy0rFtA7HWv5svPlO37XjW/Md2p/sFEp9WxztS97oWgEEEAAgcgSIPyxZ96EP/bM0o1OCH/cUGdNBBBAIAIEdhw4qoavzHQ6vblGEQ29vbovO/957xG1GDrHqf3O2sX14s1VfNkLRSOAAAIIRJYA4Y898yb8sWeWbnRC+OOGOmsigAACESCwbs9hRQ+f63TaoW4JDbixsi8733PomOq+ON2pvW21wnr9zhq+7IWiEUAAAQQiS4Dwx555E/7YM0s3OiH8cUOdNRFAAIEIEFi69YBuHbXA6fShJqXVPbqCLzv/4/gpVe472am9WYX8er/ztb7shaIRQAABBCJLgPDHnnkT/tgzSzc6IfxxQ501EUAAgQgQmLV+rzqPXuJ0+sx15dW1aRlfdn7mzFmV6jnRqb12ySv1f/+p58teKBoBBBBAILIECH/smTfhjz2zdKMTwh831FkTAQQQiACB71b+okfGLnM6faFdJXWqX9K3nZsrf8wVQGa7ulBOxTze0Le9UDgCCCCAQOQIEP7YM2vCH3tm6UYnhD9uqLMmAgggEAEC45dsV/cvYp1OX72tmm6tWdS3ndcdPF17Dh8L1F/8yss059mmvu2FwhFAAAEEIkeA8MeeWRP+2DNLNzoh/HFDnTURQACBCBB4d+5mDfx+rdPpqHtqKrpyQd923vy/s7Rp35+B+q/Mnlk/9Wnp214oHAEEEEAgcgQIf+yZNeGPPbN0oxPCHzfUWRMBBBCIAIER0zZq2LQNTqcf31dHUWXz+rbzG96YrxU7fg/UnzljBm0Y1Nq3vVA4AggggEDkCBD+2DNrwh97ZulGJ4Q/bqizJgIIIBABAoO+X6N35m5xOp3QtYGqF8vt287veXeR5v38m1P/+oHRypIpo2/7oXAEEEAAgcgQIPyxZ86EP/bM0o1OCH/cUGdNBBBAIAIEenwZq3GLtzudTnuqkcrkz+Hbzv/90VJNXv2rU7+57cvc/sWGAAIIIICAlwUIf7w8neTVRviTPC/2/rsA4Q/fCAQQQACBNBF4dNwyfbviF+fcC3s0V8FcWdNkrfQ4abf/W6EvftrpLDXnmaYqnuey9FiaNRBAAAEEEEixAOFPiuk8dyDhj+dG4quCCH98NS6KRQABBPwj0GXMEs1Yt9cpOLZfK+XIeql/Gjin0n7frNaYH7Y6P534WENVLJzTt/1QOAIIIIBAZAgQ/tgzZ8Ife2bpRieEP26osyYCCCAQAQLt31qgxVsOOJ1uHtxGGTL499eWIZPX6Y2Zm5x+/u/f9VT7qisjYJK0iAACCCDgZwHCHz9P7++1+/e3KHtm4OdOCH/8PD1qRwABBDws0GbEXK3ZfThQYfbMGbW6f7SHq026tDdnbdLLk9Y5O77fuZaaVSiQ9IHsgQACCCCAgIsChD8u4od5acKfMING2OkIfyJs4LSLAAIIpJdA4yEztW3/0cByBXJm0aKeLdJr6TRZ56OF29Rnwirn3CPuqK4bqhdJk7U4KQIIIIAAAuESIPwJl6T75yH8cX8Gfq6A8MfP06N2BBBAwMMCNQdM1f4/TwQqLJUvu2Z0a+LhapMubcKyXXpi/HJnx8E3VdFddYonfSB7IIAAAggg4KIA4Y+L+GFemvAnzKARdjrCnwgbOO0igAAC6SVQvneMjp86E1iuWtFc+vqRqPRaOk3WmbrmVz3w4VLn3D3bVNCDjUqnyVqcFAEEEEAAgXAJEP6ES9L98xD+uD8DP1dA+OPn6VE7Aggg4FGBk6fPqGyvGKe6+qXzaOwDdT1abWhlLdi0X3e+s9DZ+bFmZfRUq/KhHcxeCCCAAAIIuCRA+OMSfBosS/iTBqgRdErCnwgaNq0igAAC6SXw+9ETqt5/qrNcq4oF9HbHWum1fJqss2rXIV3/+jzn3F0aXKXn21ZMk7U4KQIIIIAAAuESIPwJl6T75yH8cX8Gfq6A8MfP06N2BBBAwKMCOw4cVcNXZjrV3VyjiIbeXt2j1YZW1pbf/lTTV2c5O7evVVSv3FottIPZCwEEEEAAAZcECH9cgk+DZQl/0gA1gk5J+BNBw6ZVBBBAIL0E1u05rOjhc53lOtQtoQE3Vk6v5dNknX1HjuvaQdOcc7epUlD/u7tmmqzFSRFAAAEEEAiXAOFPuCTdPw/hj/sz8HMFhD9+nh61I4AAAh4VWLr1gG4dtcCp7qEmpdU9uoJHqw2trGMnT6tCn0nOzo3K5dOHXWqHdjB7IYAAAggg4JIA4Y9L8GmwLOFPGqBG0CkJfyJo2LSKAAIIpJfArPV71Xn0Eme5Z64rr65Ny6TX8mmyztmzZ1WmV4xOnwn8p1PXFM+tLx9ukCZrcVIEEEAAAQTCJUD4Ey5J989D+OP+DPxcAeGPn6dH7QgggIBHBb5b+YseGbvMqe6FdpXUqX5Jj1YbelnVXpiiQ3+dDBxQrsDlmvJk49APZk8EEEAAAQRcECD8cQE9jZYk/Ekj2Ag5LeFPhAyaNhFAAIH0FBi/ZLu6fxHrLPnqbdV0a82i6VlCmqzV4KUZ2vX7X4FzF8mdTfOfa5Ym63BSBBBAAAEEwiVA+BMuSffPQ/jj/gz8XAHhj5+nR+0IIICARwXenbtZA79f61Q36p6aiq5c0KPVhl7WdcPmaP2vRwIH5MyaSSv7XRf6weyJAAIIIICACwKEPy6gp9GShD9pBBshpyX8iZBB0yYCCCCQngIjpm3UsGkbnCU/vq+OosrmTc8S0mStW978QT9uOxg4d4ZLpE2D2yjRL9VpsiYnRQABBBBAIDUChD+p0fPWsYQ/3pqH36oh/PHbxKgXAQQQ8IHAoO/X6J25W5xKJ3RtoOrFcvug8ouX2On9xZq9YZ+z09r+0cqWOaPv+6IBBBBAAAF7BQh/7Jkt4Y89s3SjE8IfN9RZEwEEELBcoMeXsRq3eLvT5bSnGqlM/hy+77rrJz/p+9jdTh+LezVX/hxZfd8XDSCAAAII2CtA+GPPbAl/0naWz0l6MdESF/M2v9V2k3SLpKsknZZkrnn/VNLrkk4kUWoBSc9Kul5ScUnmiZKrJX0g6T1Jce+WDe9G+BNeT86GAAIIICDp0XHL9O2KXxyLhT2aq2Au/4ck3T9fqfFLdzh9zejWWKXyXc7MEUAAAQQQ8KwA4Y9nR5Pswgh/kk0W8gHlJS2XlPi31Qt5l5A0S1L8e2yPSjLXgWcJrmbed9tcUtyDAv651ZQ0WVKe4Ed/BNfNFPx381m7EAKkkJsL7kj4k1wx9kcAAQQQSFKgy5glmrFur7NfbL9WypH10iSP8/oOA75bo/fmJdzO9u0jUapSNJfXy6Y+BBBAAIEIFiD8sWf4hD9pM8sMkuZKqi9pgaR6wWXO520Cmp8kVZFkrgXvKGmaeRakpNskvSPJXBU0UdK/zlOu+a1xnSTzGhTz/x0kLZWUWdIDkoZJMr8xvynp4TC3S/gTZlBOhwACCCAgtR+1QIu3HnAoNg9uowzmCck+34ZN3aAR0zc6XYx9oI7ql/b/g6x9PhbKRwABBBC4iADhjz1fD///JuXNWTwuabikTyT9LKnvRcKf+yS9G/w8PixK3NWdksYGf9BC0vRzWh4gqXfwNq9KkhL+pBi3Yw9Jg4O3kVUM3koWLjXCn3BJch4EEEAAAUegzYi5WrP7cODfs2fOqNX9o63QeWfOZg2amPAK+7c71FSrSv5/hb0Vw6EJBBBAAIHzChD+2PPFIPwJ/yzN83piJR2TdLWkrkmEP3MkNZQ0U1Kz85RjZrQp+BygDyV1OmefbcFn/IyW1OU8x5uHCZgrisz/909USzg6J/wJhyLnQAABBBD4m0CjV2Zq+wFzB7RUIGcWLepp/vbh/808xNo8zDp+G9q+mm6+pqj/G6MDBBBAAAFrBQh/7Bkt4U/4Z2lu2TLP5zEhjQlr+l0k/LlM0pHgLV7mYc1DLlDO/yQ9JGmPpEKJ9jHPFTK3epmtvaTPLnC8uWWstaSFiW5BC0fnhD/hUOQcCCCAAAJ/E6g5YKr2/xn3noNS+bJrRrcmVgiZh1ibh1nHbwNuqKQO9eIf92dFizSBAAIIIGCZAOGPPQMl/AnvLM0zdt4OPrOnZfDUFwt/zIOazfN5zNZGUswFyjHP6nkj+Jl5qHP8gxDMm8E+D/7c3NKVcC3530/0iqRnJJlr6MP5ZEnCn/B+fzgbAggggICkcr1jdOLUmYBFtaK59PUjUVa4zFy3V/eOWeL08mx0eT3cpIwVvdEEAggggICdAoQ/9syV8Cd8sywSfLW6edByZUmbQwh/2kr6JrhfNUkrL1DODZImBD8zD4ZeFfznRyW9FvxnE+rEPSDhn1v8M4jMJ+bh0eZtYOHYCH/Cocg5EEAAAQQcgZOnz6hsr4S/hdQvnUdjH6hrhdCSrQd02yjzHoi47eEmpfVsdAUreqMJBBBAAAE7BQh/7Jkr4U/4Zvld8G1c3SWZK23it4td+XNX8KHQZt+ywYdDn68icxXRlOAHiR8K3VPSoODPzRu9Tl2gnfgrkszHhYPPAAql80C4k9R29mxIuyV1Gj5HAAEEEEBAvx89oer9pzoSrSoW0Nsda1khs3b3YbUeYV4GGrd1qldCL9xg/l7EhgACCCCAgDcFCH+8OZeUVEX4kxK1fx5zj6SPJC2XdO05IQzhT3iMOQsCCCCAQAQI7DhwVA1fMe9AiNturlFEQ2+vbkXn5/Z2U40iGmZJb1YMiCYQQAABBP4hQPhjz5eC8Cf1sywQvN0rtyRzXXr8M3ziz3yx8IfbvlLvzxkQQAABBCwSWLfnsKKHJ1wd07FeCfW35OqYI8dOqkq/+At5pSbl82nMvbUtmh6tIIAAAgjYJkD4Y89ECX9SP0vzivXOkt6UZN7Yde5mbs3qEfyhed6O2cwrTMz/eOBz6v05AwIIIICARQJLtx7QrYmei/NQk9Lqbslzccxt0uZ5RqfOxN0uXa1Ybn3dtYFF06MVBBBAAAHbBAh/7Jko4U/qZzlLUuNknmaEpCck8ar3ZMKxOwIIIICA3QKz1u9V59EJb8R65rry6trUnjdi1Ro4Tb/9cTwwxBJ5LtPsZ5raPVC6QwABBBDwtQDhj6/H97fiCX9SP8vUhD9m9TmSGkqaIan5ecoxM/pZUilJH5rnQybax3y2VVJxSe9Luu88x2eXtEfS5ZL6S+qb+padM/C2rzBicioEEEAAAem7lP+qsQAAIABJREFUlb/okbHLHIoX2lVSp/olraFpOXS2Nu6Ne+lmzqyZtLLfddb0RiMIIIAAAvYJEP7YM1PCn7Sf5cWe+WNWN4HNu5JMkFJP0qJzSmovaXzwZy0kTT/n8wGSeks6KqlSMAxKvIu5Fe1lSaclVZS0IYwtE/6EEZNTIYAAAghI45dsV/cvYh2K/95WTbfULGoNTftRC7R46wGnn58HtVamjBms6Y9GEEAAAQTsEiD8sWeehD9pP8ukwp9Mkn6SVEXSruCVPSbgMb8J3hIMhnJKipHU5jzl5pK0TlJBSWskdZT0o6TMwWBpePCfzTOJHg5zu4Q/YQbldAgggECkC7w7d7MGfr/WYRh1T01FVzb/ibNje/DDpZqy5lenmR97t1Cey7PY0RxdIIAAAghYJ0D4Y89ICX/SfpZJhT+mAnM9u3mvbfx17eYqHhP+ZA2WZ65/N7eEHbxAuebB0ZMl5Ql+fiR47KXBfzevFmknKe4hA+HbCH/CZ8mZEEAAAQQkjZi2UcOmJVyk+sn9ddSgTF5rbLp/vlLjl+5w+pn2VGOVyW/uzGZDAAEEEEDAewKEP96bSUorIvxJqVzox4US/pizmTeBPS3pZklXSToTvEVrnKTXg28Hu9iq5pXz3SVdL6mYpGOSVkn6IPg8IHO+cG+EP+EW5XwIIIBAhAsM+n6N3pm7xVGY0LWBqhfLbY3KizFr9dbszU4/XzxUTzVLXGlNfzSCAAIIIGCXAOGPPfMk/LFnlm50QvjjhjprIoAAAhYL9PgyVuMWb3c6nPZUI5XJb/4+Ysc2avYmvRRj7taO297tWEstKpq/37AhgAACCCDgPQHCH+/NJKUVEf6kVI7jjADhD98DBBBAAIGwCnQd+5O+X7nbOeeins1VIGf8XdBhXcqVk537QOsht1bVbbXMBbtsCCCAAAIIeE+A8Md7M0lpRYQ/KZXjOMIfvgMIIIAAAmEXuOudhfph037nvOsHRitLpoxhX8etE05evUf//si8lyFu69Xmaj3QqJRb5bAuAggggAACFxUg/LHnC0L4Y88s3eiEK3/cUGdNBBBAwGKB6OFztG6PeW+BdHmWTFr1wnVWdbt4ywG1f2uB09PDTUrr2egKVvVIMwgggAAC9ggQ/lg0S3taoRMXBAh/XEBnSQQQQMBmgbqDp2vPYfPOAqnoFdk0r3szq9rd+OsRtRw2x+npztrF9eLNVazqkWYQQAABBOwRIPyxaJb2tEInLggQ/riAzpIIIICArQJnz55V+T6TdOJU3AsqqxbNpW8eibKq3X1HjuvaQdOcnlpXLqg376lpVY80gwACCCBgjwDhj0WztKcVOnFBgPDHBXSWRAABBGwV+PP4KVXqO9lpr3G5fPqgS22r2j15+ozK9opxeqpb6kp9+mA9q3qkGQQQQAABewQIfyyapT2t0IkLAoQ/LqCzJAIIIGCrwM6DRxX18kynvRurF9bwO2pY126VvpN15PipQF8VCubQpCcaWdcjDSGAAAII2CFA+GPHHE0XPPDZnlm60QnhjxvqrIkAAghYKhC785DajpzndHdvg5Lq27aSdd02fGWGdhz4K9BXgZxZtKhnC+t6pCEEEEAAATsECH/smCPhjz1zdKsTwh+35FkXAQQQsFBg9oZ96vT+Yqezbi3L6dHmZa3rtN3IeVq581Cgr8yZMmj9gGgl+uXaun5pCAEEEEDAvwKEP/6d3bmVc+WPPbN0oxPCHzfUWRMBBBCwVGDCsl16Yvxyp7sBN1ZWh7olrOu24/uLNWfDPqevNf2v02WZM1nXJw0hgAACCPhfgPDH/zOM74Dwx55ZutEJ4Y8b6qyJAAIIWCowev4WvfDtGqe7N+66Rv+qWsi6bh//dJm+Xv6L09f855qpSO5s1vVJQwgggAAC/hcg/PH/DAl/7Jmhm50Q/ripz9oIIICAZQJDp6zXazN+droa+0Ad1S+d17Iupb5fr9IHC7Y5fX33aJQqF8llXZ80hAACCCDgfwHCH//PkPDHnhm62Qnhj5v6rI0AAghYJtB7Qqw+Xrjd6Srm8Ya6ulBOy7qUhk3doBHTNzp9fXxfHUWVtS/ksm5wNIQAAghEoADhjz1D57Yve2bpRieEP26osyYCCCBgqUDXsT/p+5W7ne4W9WyuAjmzWtftmPlb1C/R7W2v31lDbasVtq5PGkIAAQQQ8L8A4Y//ZxjfAeGPPbN0oxPCHzfUWRMBBBCwVOCudxbqh037ne7WD4xWlkwZrev26+W79PiniR5sfUMldahX0ro+aQgBBBBAwP8ChD/+nyHhjz0zdLMTwh839VkbAQQQsEwgevgcrdtzJNBV9swZtbp/tGUdxrVz7ivtn2pZTo9Z+Ep7K4dHUwgggECECRD+2DNwrvyxZ5ZudEL444Y6ayKAAAKWCtQdPF17Dh8LdFf0imya172ZlZ2u3Pm72o2c7/R2b4OS6tu2kpW90hQCCCCAgL8FCH/8Pb/E1RP+2DNLNzoh/HFDnTURQAABCwXOnj2r8n0m6cSpM4HuqhbNpW8eibKwU2nHgaNq+MpMp7ebahTRsNurW9krTSGAAAII+FuA8Mff8yP8sWd+bndC+OP2BFgfAQQQsETgz+OnVKnvZKebRuXy6cMutS3p7u9tHDl2UlX6TXF+2LR8Po2+185erRwgTSGAAAIRJED4Y8+wufLHnlm60QnhjxvqrIkAAghYKLDz4FFFvZxwNcyN1Qtr+B01LOxUMlc5le0Vo1NnAv8ZVfViuTWhawMre6UpBBBAAAF/CxD++Ht+iasn/LFnlm50QvjjhjprIoAAAhYKxO48pLYj5zmd2f4cnFoDp+m3P44H+i2Z5zLNeqaphVOlJQQQQAABvwsQ/vh9ggn1E/7YM0s3OiH8cUOdNRFAAAELBSLtDVgth87Wxr1/BCaZK9ulWtG3lYVTpSUEEEAAAb8LEP74fYKEP/ZM0N1OCH/c9Wd1BBBAwBqBr5fv0uOfLnf6GXBjZXWoW8Ka/s5tpP2oBVq89UDgx5dcIv08qI0yZuBvctYOnMYQQAABnwoQ/vh0cOcpm98y7JmlG50Q/rihzpoIIICAhQKj52/RC9+ucTp7465r9K+qhSzsNK6lBz9cqilrfnX6+6lPS12ZPbO1/dIYAggggIA/BQh//Dm381VN+GPPLN3ohPDHDXXWRAABBCwUGDplvV6b8bPT2dj766h+mbwWdhrXUvfPV2r80h1Of9O7NVbpfJdb2y+NIYAAAgj4U4Dwx59zI/yxZ25e6YTwxyuToA4EEEDA5wJ9JqzSRwu3OV3EPN5QVxfK6fOuLlz+izFr9dbszc4OXzxUTzVLXGltvzSGAAIIIOBPAcIff86N8MeeuXmlE8Ifr0yCOhBAAAGfC3Qd+5O+X7nb6WJRz+YqkDOrz7u6cPmjZm/SSzHrnB3e7VhLLSoWsLZfGkMAAQQQ8KcA4Y8/50b4Y8/cvNIJ4Y9XJkEdCCCAgM8F7npnoX7YtN/pYv3AaGXJlNHnXV24/PFLtqv7F7HODkNurarbahWztl8aQwABBBDwpwDhjz/nRvhjz9y80gnhj1cmQR0IIICAzwVaj5irtbsPB7rInjmjVveP9nlHFy9/8uo9+vdHPzo79WpztR5oVMrqnmkOAQQQQMB/AoQ//pvZhSrmgc/2zNKNTgh/3FBnTQQQQMBCgbqDp2vP4WOBzopekU3zujezsMuElhZvOaD2by1wfvBwk9J6NrqC1T3THAIIIICA/wQIf/w3M8Ife2bmpU4If7w0DWpBAAEEfCpw9uxZle8zSSdOnQl0UKVILn37aJRPuwmt7I2/HlHLYXOcne+sXVwv3lwltIPZCwEEEEAAgXQSIPxJJ+h0WIYrf9IB2eIlCH8sHi6tIYAAAuklcPTEKVV8frKzXKNy+fRhl9rptbwr6+w7clzXDprmrN26ckG9eU9NV2phUQQQQAABBC4kQPhjz3eD8MeeWbrRCeGPG+qsiQACCFgmsPPgUUW9PNPp6sbqhTX8jhqWdfn3dk6ePqOyvWKcH9YtdaU+fbCe1T3THAIIIICA/wQIf/w3swsGefa0QicuCBD+uIDOkggggIBtArE7D6ntyHlOW53rl1S/dpVsa/Mf/VTuO1l/HD8V+HmFgjk06YlG1vdMgwgggAAC/hIg/PHXvC5WLVf+2DNLNzoh/HFDnTURQAABywTmbNinju8vdrp6qmU5Pda8rGVd/rOdqJdnaOfBvwIfFMiZRYt6trC+ZxpEAAEEEPCXAOGPv+ZF+GPPvLzWCeGP1yZCPQgggIAPBb5evkuPf7rcqXzAjZXVoW4JH3aSvJLbvj5PsbsOBQ7KnCmD1g+IVqJfspN3MvZGAAEEEEAgDQQIf9IA1aVTcuWPS/CWLEv4Y8kgaQMBBBBwU2D0/C164ds1Tgkj76qh66sWdrOkdFm7w3uLNHfjb85aa/pfp8syZ0qXtVkEAQQQQACBUAQIf0JR8sc+hD/+mJNXqyT88epkqAsBBBDwkcDQqRv02vSNTsVj76+j+mXy+qiDlJX62Lhl+mbFL87BPzzXTIVzZ0vZyTgKAQQQQACBNBAg/EkDVJdOSfjjErwlyxL+WDJI2kAAAQTcFOgzYZU+WrjNKSHm8Ya6ulBON0tKl7X7fr1KHyxI6Pv7x6JUqXCudFmbRRBAAAEEEAhFgPAnFCV/7EP44485ebVKwh+vToa6EEAAAR8JdB37k75fudupeFHP5iqQM6uPOkhZqcOmbtCIRFc8fXJ/HTWIgCueUqbFUQgggAACbggQ/rihnjZrEv6kjWuknJXwJ1ImTZ8IIIBAGgrc/e5Czf95v7PC+oHRypIpYxqu6I1Tj5m/Rf0i8FlH3tCnCgQQQACBUAQIf0JR8sc+hD/+mJNXqyT88epkqAsBBBDwkUDrEXO1dvfhQMXZM2fU6v7RPqo+5aVG6lvOUi7GkQgggAAC6S1A+JPe4mm3HuFP2tlGwpkJfyJhyvSIAAIIpLFA3cHTtefwscAqRa/Ipnndm6Xxit44/ewN+9Tp/cVOMd1altOjzct6oziqQAABBBBAQBLhjz1fA8Ife2bpRieEP26osyYCCCBgkcDZs2dVoc8kHT91JtBVlSK59O2jURZ1eOFWVu78Xe1Gznd26NLgKj3ftmJE9E6TCCCAAAL+ECD88cecQqmS8CcUJfa5kADhD98NBBBAAIFUCRw9cUoVn5/snKNRuXz6sEvtVJ3TLwfvOHBUDV+Z6ZR7c40iGnp7db+UT50IIIAAAhEgQPhjz5AJf+yZpRudEP64oc6aCCCAgEUCOw8eVdTLCQHIjdULa/gdNSzq8MKtHDl2UlX6TXF2aFo+n0bfGxnBV0QMmCYRQAABCwQIfywYYrAFwh97ZulGJ4Q/bqizJgIIIGCRQOzOQ2o7cp7TUef6JdWvXSWLOrxwK+aWt7K9YnTqTOA/p6peLLcmdG0QEb3TJAIIIICAPwQIf/wxp1CqJPwJRYl9LiRA+MN3AwEEEEAgVQJzNuxTx0QPPX6qZTk9FkEPPa41cJp+++N4wLBknss065mmqfLkYAQQQAABBMIpQPgTTk13z0X4466/31cn/PH7BKkfAQQQcFkg0l933nLobG3c+0dgCrmyXaoVfVu5PBGWRwABBBBAIEGA8MeebwPhjz2zdKMTwh831FkTAQQQsEhg9PwteuHbNU5HI++qoeurFraow4u30n7UAi3eeiCw0yWXSD8PaqOMGfj1LGK+ADSKAAIIeFyA8MfjA0pGefx2kQwsdv2HAOEPXwoEEEAAgVQJDJ26Qa9N3+icY+z9dVS/TN5UndNPBz/44VJNWfOrU/JPfVrqyuyZ/dQCtSKAAAIIWCxA+GPPcAl/7JmlG50Q/rihzpoIIICARQJ9JqzSRwu3OR3FPN5QVxfKaVGHF2+l++crNX7pDmen6d0aq3S+yyOmfxpFAAEEEPC2AOGPt+eTnOoIf5Kjxb7nChD+8J1AAAEEEEiVQNexP+n7lbudcyzs0VwFc2VN1Tn9dPCLMWv11uzNTslfPFRPNUtc6acWqBUBBBBAwGIBwh97hkv4Y88s3eiE8McNddZEAAEELBK4+92Fmv/zfqejdQOilfXSjBZ1ePFWRs3epJdi1jk7vduxllpULBAx/dMoAggggIC3BQh/vD2f5FRH+JMcLfY9V4Dwh+8EAggggECqBFqPmKu1uw8HzpE9c0at7h+dqvP57eDxS7ar+xexTtlDbq2q22oV81sb1IsAAgggYKkA4Y89gyX8sWeWbnRC+OOGOmsigAACFgnUHTxdew4fC3RUJHc2zX+umUXdJd3KpFV79J+Pf3R27NXmaj3QqFTSB7IHAggggAAC6SBA+JMOyOm0BOFPOkFbugzhj6WDpS0EEEAgPQTOnj2rCn0m6fipM4HlqhTJpW8fjUqPpT2zxqLN+3X72wudeh5uUlrPRlfwTH0UggACCCAQ2QKEP/bMn/DHnlm60QnhjxvqrIkAAghYInD0xClVfH6y002jcvn0YZfalnQXWhsbfj2iVsPmODvfVae4Bt9UJbSD2QsBBBBAAIE0FiD8SWPgdDw94U86Ylu4FOGPhUOlJQQQQCC9BHYePKqol2c6y91QvbBG3FEjvZb3xDp7jxxT7UHTnVraVCmo/91d0xO1UQQCCCCAAAKEP/Z8Bwh/7JmlG50Q/rihzpoIIICAJQKrdh3S9a/Pc7rpXL+k+rWrZEl3obVx4tQZlesd4+xcr1QejXuwbmgHsxcCCCCAAAJpLED4k8bA6Xh6wp90xLZwKcIfC4dKSwgggEB6CczZsE8d31/sLPdUy3J6rHnZ9FreM+tU7jtZfxw/FainQsEcmvREI8/URiEIIIAAApEtQPhjz/wJf+yZpRudEP64oc6aCCCAgCUCXy/fpcc/Xe50M+CGSupQr6Ql3YXeRtTLM7Tz4F+BAwrmzKqFPZuHfjB7IoAAAgggkIYChD9piJvOpyb8SWdwy5Yj/LFsoLSDAAIIpKfAmPlb1O/bNc6SI++qoeurFk7PEjyxVtvX5yl216FALVkyZdD6ga09URdFIIAAAgggQPhjz3eA8MeeWbrRCeGPG+qsiQACCFgiMHTqBr02faPTzdj766h+mbyWdBd6Gx3eW6S5G39zDljbP1rZMmcM/QTsiQACCCCAQBoJEP6kEawLpyX8cQHdoiUJfywaJq0ggAAC6S3QZ8IqfbRwm7PsxMcaqmLhnOldhuvrPTZumb5Z8YtTxw/PNVPh3Nlcr4sCEEAAAQQQIPyx5ztA+GPPLN3ohPDHDXXWRAABBCwReGTsT/pu5W6nm4U9mqtgrqyWdBd6G32/XqUPFiSEYN8/FqVKhXOFfgL2RAABBBBAII0ECH/SCNaF0xL+uIBu0ZKEPxYNk1YQQACB9Ba4+92Fmv/zfmfZdQOilfXSyLvdadjUDRqR6Pa3T+6vowYRePtben//WA8BBBBAIGkBwp+kjfyyB+GPXyblzToJf7w5F6pCAAEEfCHQesRcrd19OFDrZZkzak3/aF/UHe4iefB1uEU5HwIIIIBAuAQIf8Il6f55CH/cn4GfKyD88fP0qB0BBBBwWaDei9O1+9CxQBVFcmfT/OeauVyRO8v/45X3N1ZWh7ol3CmGVRFAAAEEEEgkQPhjz9eB8MeeWbrRCeGPG+qsiQACCFggcPbsWVXoM0nHT50JdFOlSC59+2iUBZ0lv4XZG/ap0/uLnQO7tSynR5uXTf6JOAIBBBBAAIEwCxD+hBnUxdMR/riIb8HShD8WDJEWEEAAATcEjp44pYrPT3aWblg2rz66r44bpbi+5sqdv6vdyPlOHV0aXKXn21Z0vS4KQAABBBBAgPDHnu8A4Y89s3SjE8IfN9RZEwEEELBAYNfvf6nBSzOcTm6oXlgj7qhhQWfJb2HHgaNq+MpM58CbaxTR0NurJ/9EHIEAAggggECYBQh/wgzq4ukIf1zEt2Bpwh8LhkgLCCCAgBsCq3Yd0vWvz3OW7ly/pPq1q+RGKa6veeTYSVXpN8Wpo2n5fBp9b23X66IABBBAAAEECH/s+Q4Q/tgzSzc6IfxxQ501EUAAAQsE5mzYp46JnnPzZItyerxFZD7nxjz/qGyvGJ06E/jPqqoXy60JXRtYMGVaQAABBBDwuwDhj98nmFA/4U/4ZplHUjtJzSVdI8m8piOTpH2Slkr6QNJXSSyXQ1I3SbdIukrSaUkbJH0q6XVJJ5I4voCkZyVdL6m4pL8krQ6u/Z6kuN8qw7cR/oTPkjMhgAACESXwjzdc3VBJHeqVjCiDxM3WGjhNv/1xPPCj/2/vPMDlqqr3/aXf9B4CBBJCS2ih914EEURAUCyAiF30rwiKoqKoqCgi/MQWRbGAAnaRTgzSSwyGAAECCQES0nu9N//nO3NmMhnm3jv9lHl3nvvMnTvn7L32u1bmnPPtvdceM7SPJl10VNOyoOMQgAAEIBAfAog/8fFFtZYg/lRLcNP560OxJ/sX711r8aZvXhP/kvROSauKNGuxaJLv+cLPfEw3Sb3C91NCYWlxOybvI8mZMy1CuayQ1JJnkz+zONWZgFQOEcSfcmhxLAQgAAEI5Aj86oGXdNnfp+fe/9979tJJe2zVtISOu+rfev4NX7qlgb17aOpX39K0LOg4BCAAAQjEhwDiT3x8Ua0liD/VEtx0voUQ79P6q1CEmRl+ZDHnUkkfDN//VtL7C5r1DKEnvdOtpNclnS3pbkldJZ0h6eeSPCvoNklvK2LyQEnPShoZvrp+zzbqKelDkn4gqYekH0v6eO26nJlJ5OnqFAhAAAIQgEA5BK66a4auuef53Cm/O/8AHbLDsHKqSNWxZ/zkQT32cmZ8p0sX6YVvnqhuXblNS5WT6QwEIACBBBJA/Emg09oxmbuK2vnS87M3bdXx5np/Iukj4Z+9JOuVvEMsDE0M3x8s6aGC08+S9Pvwb8dKuqfg88tDgcnLvJwt86WCzy+R9K1wJpL3jvVSsloUxJ9aUKQOCEAAAk1I4Ct/naYbHpqV6/ltnzpMu2w1oAlJZLr8oRse113T5+X6P+XLx2lwX4/hUCAAAQhAAALREUD8iY59rVtG/Kk10fbr2y+cGeQjTivI/zNZ0mGheHR0kSrspxfDPEA3SDqn4BjfPVtQul7SeUXO7xfOKPLr1yV9tUbdRvypEUiqgQAEINBsBD75+yf1j6c82TVTHr7kGI0c6NXKzVkuvmWq/vj4nFzn773wCI0d7ss2BQIQgAAEIBAdAcSf6NjXumXEn1oTbb8+L+l6KvzYS7luCX/vI2l5uMTLyZqvbKeK6yR9TNJcSVvmHbNzuNTLfzpT0s3tnO8lY2/1/bWkg2rUbcSfGoGkGghAAALNRuC9Ex/WAy8szHX72ctPUEsPp7prznLFbc/op5OzK8alWz92sPYZPbg5YdBrCEAAAhCIDQHEn9i4ompDEH+qRlhyBRdIuiY8epyk58LfnajZ+XlcTpTkpNDFinP1/Cj8wEmdF4W/e2ewrJDkJV3PtHP+dyVdJGmZc0mWbHXHByL+1Agk1UAAAhBoNgJv/eH9euZ1X5KkPj27afrXT2g2BJv198eTXtR3bnf6vkz5xTn76pjx3sSTAgEIQAACEIiOAOJPdOxr3TLiT62JFq9vkCRvaeIZO/dLOjzvsJMl/S18PyFvdlBhTadI+kv4R88imhb+ni8qWdTJ3Em/uXxa0tXhn508OrOlSMelpEzOJHzuDCOfQwACEIBAIYGDrrhHry/1xpjS1oN664EvFFv13Dzcbnp0tr7wp//lOvy9MybonfuMah4A9BQCEIAABGJJAPEnlm6pyCjEn4qwlXWSd+z6q6STJPku94ACgec9kn4X1rijpBfaqf04SXeGn+Unhf6ipG+Gf/eOXhvaOd+7fv0s/Mx76W5KtNB+dxB/ynI1B0MAAhCAQCkEPGgw7su3a+2GtuDw3bYeoH9c4NR3zVtunzZXH/3tEzkAl75tvM4/bGzzAqHnEIAABCAQCwKIP7FwQ02MQPypCcYOK7lW0ifDI7yr1y8Ljo6z+NMZHZZ9dUaIzyEAAQhA4E0EVq3boF2+ckfu74ftOEy/+aDHRpq3PDJzod71M6fly5SPH7m9Lj7Bq8QpEIAABCAAgegIIP5Ex77WLSP+1Jro5vV9T9KF4Z8+k7fsKv+oOC/76owO4k9nhPgcAhCAAATeRODVJat1yLfvzf39lD230g/fvVdTk3ppwUod9b1JOQZvn7CVrjmruZk0dUDQeQhAAAIxIYD4ExNH1MAMxJ8aQGynimyCZX/8OUnfb+c4Ej7XzwfUDAEIQAACMSQw7dWlOuna/+QsO/fgMbrs7bvG0NLGmbS+tU3jv3y7NrRlVlyzFK5x7GkJAhCAAATaJ4D4k57oQPypjy+9XbsFH5eOtm/352z1Xh8fUCsEIAABCMSUwOQZ83X2Lx/NWfeZY3fSp4912rvmLkd/f5Jmzl8ZQOjbs5umfe145d10Nzcceg8BCEAAApEQQPyJBHtdGkX8qT3W/KVenQk/2dYnS3KmS8+BP6aISfaTE0E78+MNks7JO8afvSxp2zCfkPMKFZa+kuZK6ifp65K+WqNus+yrRiCpBgIQgEAzEfjrf1/Vp2/6b67Ll5+yq95/0JhmQlC0r+f/+nHd/cy83GcPX3KMRg5saXouAIAABCAAgegIIP5Ex77WLSP+1JZovvDT0VKvwlYt2EyUZDHlIEmPFBxwpqQ/hH87VtI9BZ9fLulSSasked68xaD8YhHqO5JaJe0iaUaNuo34UyOQVAMBCECgmQj86oGXdNnfp+e6fO1Ze+nkCd6IsrnLFbc9o59OnpmD8PvzD9DBOwxrbij0HgIQgAAEIiWA+BMp/po2jvhTO5z5OX4+K+kHZVTdXdKTknaX9Go4s8cCj7eJPz0UhgZI+pekE4vUO1DSs5JGSvLd9NmSvF9sT0kWlq4Of/9dkZtvAAAgAElEQVSxNxApw67ODkX86YwQn0MAAhCAwJsIXHXXDF1zz/O5v//u/AN0CCKH/vDYbH3+1v/luFz+jt30/gNHE0EQgAAEIACByAgg/kSGvuYNI/7UBqmXXM0Kq2qTNL+Taj1DyD/5xfPd75OUnffuWTwWf7LzvaeES8IWt1O3E0d739yh4efLw3N7hO/vlPR2SWtr0+WgFsSfGsKkKghAAALNQuALtz6lmx57Jdfd2z51mHbZymMczV0ee3mRzvjJQzkIHzhkjL56cnMnwm7uiKD3EIAABKIngPgTvQ9qZQHiT21IWrB5qYyqvibpsiLH9w8TRZ8maTtJFpK8ROtGSddKWtdJG1tI+rykkyRtI2mNpGmSfh3mA3J9tSyIP7WkSV0QgAAEmoTAadc9oCdnL8n1dvrXj1efnp4E29xl4Yq12ucbd+cgHLHTcP36vP2bGwq9hwAEIACBSAkg/kSKv6aNI/7UFGfTVYb403Qup8MQgAAEqiOwceNG7XHZnVq+dkNQ0TZDeuv+i4+urtKUnG02e379Li1dvR42KfEp3YAABCCQdAKIP0n34Cb7EX/S48soeoL4EwV12oQABCCQYAJzl67RgVds2rfgmHEj9Itz90twj2pr+qnXPaAp4ayoLl2kZy8/Qb26d6ttI9QGAQhAAAIQKJEA4k+JoBJwGOJPApwUYxMRf2LsHEyDAAQgEEcCk2fM19m/fDRn2keOGKtL3jo+jqZGYtOFf5yqW5+ck2v7zs8crp228KpwCgQgAAEIQKDxBBB/Gs+8Xi0i/tSLbHPUi/jTHH6mlxCAAARqRmDi/TP1jX8+k6vv+2dM0On7jKpZ/Umv6Ef3vaAr73gu142fvG9vnbDblknvFvZDAAIQgEBCCSD+JNRxRcxG/EmPL6PoCeJPFNRpEwIQgECCCXz+lqf0h8c37fT1908eqt1HDUxwj2pr+u3TXtdHf/tkrtKLjt9Znzhqh9o2Qm0QgAAEIACBEgkg/pQIKgGHIf4kwEkxNhHxJ8bOwTQIQAACcSSQv9OXc9pM/9oJ6t2TnDZZX82Yt1xv+cHknOtO33uUvn/mhDi6EpsgAAEIQKAJCCD+pMfJiD/p8WUUPUH8iYI6bUIAAhBIKIHCnb62HdJHky8+KqG9qY/Zaze0avyXb1dbcIWV9tp2kP788UPq0xi1QgACEIAABDohgPiTnhBB/EmPL6PoCeJPFNRpEwIQgEBCCby+dLUOuuLenPXs9FXckYd/9z7NXrQq+HBg7x7671eOU97Nd0K9j9kQgAAEIJBEAog/SfRacZsRf9Ljyyh6gvgTBXXahAAEIJBQAv+eMV/n5O309dEjttcX3jouob2pn9nnXv+oJj03P9fAE5ceq6H9etWvQWqGAAQgAAEItEMA8Sc9oYH4kx5fRtETxJ8oqNMmBCAAgYQSKNzp66ozJ+i0vdnpq9CdX/v707r+gZdzf775owdpvzFDEup1zIYABCAAgSQTQPxJsvc2tx3xJz2+jKIniD9RUKdNCEAAAgklULjT1z8uOFS7bc1OX4Xu/M3Ds/Tlv0zL/fk7p++ud+23bUK9jtkQgAAEIJBkAog/SfYe4k96vBd9TxB/ovcBFkAAAhBIDIFTr3tAU2YvCexlp6/23fbgCwv0nomP5A74yOFjdcmJ4xPjZwyFAAQgAIH0EED8SZEv09MVehIBAcSfCKDTJAQgAIEkEmCnr9K9NnfpGh14xT25E44dv4UmnrNv6RVwJAQgAAEIQKBGBBB/agQyBtWw7CsGTkiwCYg/CXYepkMAAhBoJIHCnb6OHT9CE8/Zr5EmJKYtC2W7ffUOrVzXGtg8dnhf3XvhkYmxH0MhAAEIQCA9BBB/UuTL9HSFnkRAAPEnAug0CQEIQCCJBAp3+vrYkdvr8yew01d7vjzp2vs17dVlwcfdu3bRM5efoB7duibR9dgMAQhAAAIJJoD4k2DnFZjOzJ/0+DKKniD+REGdNiEAAQgkkAA7fZXntE/dOEV/m/pa7qR7LzxCY4f3K68SjoYABCAAAQhUSQDxp0qAMTod8SdGzkigKYg/CXQaJkMAAhCIgsDFt0zVHx+fk2uanb469sLVd8/Q1Xc/nzto4tn76thdtojCdbQJAQhAAAJNTADxJz3OR/xJjy+j6AniTxTUaRMCEIBAAgmw01d5TvOsH8/+yZYvnjhOHz58+/Iq4WgIQAACEIBAlQQQf6oEGKPTEX9i5IwEmoL4k0CnYTIEIACBRhMo3Olr9NA++vdFRzXajES1N+3VpTrp2v/kbH73ftvo26fvkag+YCwEIAABCCSfAOJP8n2Y7QHiT3p8GUVPEH+ioE6bEIAABBJG4LUlq3Xwt+/NWc1OX507cNW6DdrlK3fkDtx/zBD98aMHdX4iR0AAAhCAAARqSADxp4YwI64K8SdiByS8ecSfhDsQ8yEAAQg0gsCk597Qudc/lmuKnb5Ko37QFffo9aVrgoOH9eupxy89rrQTOQoCEIAABCBQIwKIPzUCGYNqEH9i4IQEm4D4k2DnYToEIACBRhEo3OnrB++aoFP3GtWo5hPbznsnPqwHXliYs3/qV9+igb17JLY/GA4BCEAAAskjgPiTPJ+1ZzHiT3p8GUVPEH+ioE6bEIAABBJGgJ2+KnPYl/8yTb95eFbu5L984hDtuc2gyirjLAhAAAIQgEAFBBB/KoAW01MQf2LqmISYhfiTEEdhJgQgAIEoCbzjRw/ov68sCUzo0kV65usnqKVHtyhNSkTb1z/wkr729+k5W686c4JO25sZU4lwHkZCAAIQSAkBxJ+UONL3YOnpCj2JgADiTwTQaRICEIBAkgh4p6/dL7tTK9ZuCMxmp6/SvVeYK+mTR+2gzx2/c+kVcCQEIAABCECgSgKIP1UCjNHpiD8xckYCTUH8SaDTMBkCEIBAIwm8eaevLTTxnH0baUJi23pl0Sod9t37cvafuPtIXffefRLbHwyHAAQgAIHkEUD8SZ7P2rMY8Sc9voyiJ4g/UVCnTQhAAAIJIlA4e+XjR26vi08Yl6AeRGdqa9tGjf/K7Vq3oS0wYtzI/rr9/x0enUG0DAEIQAACTUcA8Sc9Lkf8SY8vo+gJ4k8U1GkTAhCAQIII/HzyTH3ztmdyFl/9rj31jr22TlAPojX1+B9M1nPzlgdG9OreNciX1LUrt2/ReoXWIQABCDQPAcSf9Piau4f0+DKKniD+REGdNiEAAQgkiMBFN0/VzU/MyVn8jwsO1W5bD0xQD6I19WO/fUL/mjY3Z8T9Fx+lbYb0idYoWocABCAAgaYhgPiTHlcj/qTHl1H0BPEnCuq0CQEIQCBBBPJ3+vKElens9FWW966841n96L4Xc+f8+rz9dcROw8uqg4MhAAEIQAAClRJA/KmUXPzOQ/yJn0+SZBHiT5K8ha0QgAAEGkygcKevMUP7aNJFRzXYimQ3d+sTc3ThzVNznfjqybvoA4dsl+xOYT0EIAABCCSGAOJPYlzVqaGIP50i4oAOCCD+EB4QgAAEINAugVeXrNYh37439/lxu2yhn5/NTl/lhMyU2Yt16nUP5k55/4Gjdfk7diunCo6FAAQgAAEIVEwA8adidLE7EfEndi5JlEGIP4lyF8ZCAAIQaCyB+557Qx+4/rFco+z0VT7/pavXa8LX7sydeMgOQ/W78w8svyLOgAAEIAABCFRAAPGnAmgxPQXxJ6aOSYhZiD8JcRRmQgACEIiCwM8mv6hv3fZsrml2+qrMC/t+4y4tWLEuOHnLgS166JJjKquIsyAAAQhAAAJlEkD8KRNYjA9H/ImxcxJgGuJPApyEiRCAAASiIlC409c/P3Wodt2Knb7K9ceZP3lIj768KHfa9K8frz49u5dbDcdDAAIQgAAEyiaA+FM2stiegPgTW9ckwjDEn0S4CSMhAAEIREPglB89oKmvLAkaZ6evyn3whVuf0k2PvZKr4B8XHKrdtkZEq5woZ0IAAhCAQKkEEH9KJRX/4xB/4u+jOFuI+BNn72AbBCAAgQgJeKev3b56h1auaw2sYKevyp1RuHzumrP20tsnbFV5hZwJAQhAAAIQKJEA4k+JoBJwGOJPApwUYxMRf2LsHEyDAAQgECWBOYtX6dDv3JczgZ2+KvfG3dPn6fwbHs9V8N4DttU3T9298go5EwIQgAAEIFAiAcSfEkEl4DDEnwQ4KcYmIv7E2DmYBgEIQCBKAoU7fX3iqO110fHjojQpsW0vXrlO+3/rbq1vDS676t+rux750jHk/UmsRzEcAhCAQHIIIP4kx1edWYr40xkhPu+IAOIP8QEBCEAAAkUJXHPP87rqrhm5z3747j11yp5bQ6tCAp/4/ZP651Ov586+8p176Ix9t6mwNk6DAAQgAAEIlEYA8ac0Tkk4CvEnCV6Kr42IP/H1DZZBAAIQiIxAa9tGHXHlfZqzeHXOhnsuPELbD+8XmU1Jb/g/zy/Q+37xSK4b+4werFs/dnDSu4X9EIAABCAQcwKIPzF3UBnmIf6UAYtD30QA8YeggAAEIACBNxG499l5Ou9Xm3LUIFRUHyRtFtS+d59eWbRJULvzM4drpy36V185NUAAAhCAAATaIYD4k57QQPxJjy+j6AniTxTUaRMCEIBAzAmce/2jmvTc/JyVLPmqjcN+dN8LuvKO53KVnXfIdvrKybvUpnJqgQAEIAABCBQhgPiTnrBA/EmPL6PoCeJPFNRpEwIQgECMCcxauFJHfm+SNmZyE2to35568JKj1at7txhbnQzT3li2Rgd9+155WZ3LoD499PAlx6ilB2yT4UGshAAEIJA8Aog/yfNZexYj/qTHl1H0BPEnCuq0CQEIQCDGBK647Rn9dPLMnIUfP3J7XXwCu3zVymUfuuFx3TV9Xq46ZlXViiz1QAACEIBAMQKIP+mJC8Sf9Pgyip4g/kRBnTYhAAEIxJTAmvWtOvCKe7Rk1frAwq5dpMkXH6VRg/vE1OLkmVWYT+nAsUN004cPSl5HsBgCEIAABBJBAPEnEW4qyUjEn5IwcVA7BBB/CA0IQAACEMgRuOWJOfrczVNz748dv4UmnrMvhGpIwEu+Dv3OvXp96Zpcrfd97khtN6xvDVuhKghAAAIQgECGAOJPeiIB8Sc9voyiJ4g/UVCnTQhAAAIxJXDKjx7Q1FeW5Kz79Xn764idhsfU2uSaddVdM3TNPc/nOvCRI8bqkreOT26HsBwCEIAABGJLAPEntq4p2zDEn7KRcUIeAcQfwgECEIAABAICT81Zorf/3wM5GmOG9tG9Fx6prl77RakpgTmLV+mw796XS6o9rF9PPfiFY9Sze9eatkNlEIAABCAAAcSf9MQAd2Tp8WUUPUH8iYI6bUIAAhCIIYGLb5mqPz4+J2fZpW8br/MPGxtDS9Nh0rnXP6pJz83PdebH791bb919y3R0jl5AAAIQgEBsCCD+xMYVVRuC+FM1wqauAPGnqd1P5yEAAQhkCCxdtV77f+turd3QFrzv1b2rHvniMRrUpyeI6kTg9mlz9dHfPpGr/fCdhuuG8/avU2tUCwEIQAACzUoA8Sc9nkf8SY8vo+gJ4k8U1GkTAhCAQMwITLx/pr7xz2dyVp2xzyhdecaEmFmZLnPWt7bpoCvu1YIVa4OOdfHOahcdpW2GsLNaujxNbyAAAQhESwDxJ1r+tWwd8aeWNJuvLsSf5vM5PYYABCCwGYG2to06+vuT9PLCVbm//+2Th2iPUYMgVWcC37n9Wf140ou5Vj519A767Ft2rnOrVA8BCEAAAs1EAPEnPd5G/EmPL6PoCeJPFNRpEwIQgECMCEyeMV9n//LRnEUTthmkv37ikBhZmF5TZi1cqSOunJTr4MgBLfrP549S924kfk6v1+kZBCAAgcYSQPxpLO96tob4U0+66a8b8Sf9PqaHEIAABDok8KEbHtdd0+fljvneGRP0zn1GQa1BBN7z84f14IsLc61dfsquev9BYxrUOs1AAAIQgEDaCSD+pMfDiD/p8WUUPUH8iYI6bUIAAhCICYHn5y3X8VdPVltwNZAG9emhhy85Ri09usXEwvSb8bepr+lTN07JdbRHty668UMHat8xQ9LfeXoIAQhAAAJ1J4D4U3fEDWsA8adhqFPZEOJPKt1KpyAAAQh0TuCFN5brrJ8/ovnLMwmHXT58+Fh98cTxnZ/METUjsKG1TWf89CFNmb0kV+fw/r30jwsO1RYDWmrWDhVBAAIQgEBzEkD8SY/fEX/S48soeoL4EwV12oQABCAQMYHn5i7Xeyc+rAUr1uUsaenRVXd95gh2m4rAN/OWrdFJ1/5nMyFur20H6aYPH6he3ZmFFYFLaBICEIBAaggg/qTGlUL8SY8vo+gJ4k8U1GkTAhCAQIQEnn5tqd438REtXrU+Z0XP7l310/fto6PGjYjQsuZu+olZi/Tunz2s9a3hGjxJZ+2/ja44bY/mBkPvIQABCECgKgKIP1Xhi9XJiD+xckfijEH8SZzLMBgCEIBA5QT+N2ep3veLR7R09Sbhp1f3rvr52fvq8J2GV14xZ9aEwO8emaUv/XnaZnV989Td9N4DRtekfiqBAAQgAIHmI4D4kx6fI/6kx5dR9ATxJwrqtAkBCEAgAgJTZi8OtnRfvmZDrvXePbrpF+fsq4N3GBaBRTRZjMAlf3pKNz76Su4jEkATJxCAAAQgUA0BxJ9q6MXrXMSfePkjadYg/iTNY9gLAQhAoAICXlJ0zi8f04q1m4SfPj276fpz99MBY4dWUCOn1IvA2g2twfIvEkDXizD1QgACEGguAog/6fE34k96fBlFTxB/oqBOmxCAAAQaRKC1baMm3j9TV901Q2s3tOVa7deru3593n7aZzTbiTfIFWU1UywB9K5bDdBVZ+6pnUf2L6suDoYABCAAgeYmgPiTHv8j/qTHl1H0BPEnCuq0CQEIQKABBJ6ft1yfu+UpTX1l0xbibrZ/S3fdcN7+2mvbwQ2wgiYqJVAsAXTXLgry/3zmuJ00pG/PSqvmPAhAAAIQaCICiD/pcTbiT3p8GUVPEH+ioE6bEIAABOpIYH1rm342eaZ+ePfzWte6abaPmxzUp4d+c94B2n3UwDpaQNW1IlAsAbTrHtDSXZ8+die9/8DR8k5tFAhAAAIQgEB7BBB/0hMbiD/p8WUUPUH8iYI6bUIAAhCoE4FnXl+mi26ZqmmvLntTC97N64rTdtfWg3rXqXWqrQeB3zw8S9/917NanpevKdvO2GF9delJ43XUziOUd3NfDzOoEwIQgAAEEkoA8SehjitiNuJPenwZRU8Qf6KgTpsQgAAEakzAuX2uu+8F/fCe57WhLfhqzxUv8/rySbvojH1GIRDUmHujqluwYq2+f+cM/eGx2Spwb2DCAdsN0UeP3F5H7jQcHzfKKbQDAQhAICEEEH8S4qgSzET8KQESh7RLAPGH4IAABCCQcAIWBv7fTf/Vf15Y8KaeHDNuhL556u4aObAl4b3EfBOY/toyXf6P6Xpo5sKiQMaN7K8PHz5WJ0/YSj26sRyMqIEABCAAAeUPCqAdJDwgcGDCHRix+Yg/ETuA5iEAAQhUQ+DRlxbpghuf1Lxlazerxrl9Ljt5V52y51bMBKkGcAzP3bhxo+6cPk/fuu0ZzVq4qqiFWw1s0XmHbqd377+tvLMbBQIQgAAEmpcAM3/S43vEn/T4MoqeIP5EQZ02IQABCFRJoK1to352/0xdecdz8pKv/HLs+BH61mm7a0R/ZvtUiTnWp6/d0KobHpwVxMH85ZuLf1nDnRj6I0dsrw8dNpbE0LH2JsZBAAIQqB8BxJ/6sW10zYg/jSaervYQf9LlT3oDAQg0AYElq9bpczdP1d3PvLFZb7t17aIvnDBO5x+2HbN9miAOsl20CPSXKa/qp5Nnaub8lUV7vsOIfvrGO3bTgWOHNhEZugoBCEAAAiaA+JOeOED8SY8vo+gJ4k8U1GkTAhCAQIUEHn95kT5903/16pLVm9UwckCL/u89e2nfMUMqrJnTkk7As8HufmZeIAI9MWtx0e6cvvcoffHEcRrar1fSu4v9EIAABCBQIgHEnxJBJeAwxJ8EOCnGJiL+xNg5mAYBCEAgS+B/c5bqB3fP0L3Pbj7bx58ftuMwXf2uPXmgJ1xyBCwSXnvvC/r3jPlvouJ8UJe8dZzO2Gcbde3KbSRhAwEIQCDtBBB/0uNhrtrp8WUUPUH8iYI6bUIAAhAokcDTry3V1Xc/r7umz3vTGV26SJ85did94qgd5CVfFAjkE8gmhr7sb0/r9aVr3gRnvzGD9cmjd9RBY4eSD4jQgQAEIJBiAog/6XEud3vp8aV70l/ShZJOl7SdpFZJMyTdJOlaSetq3F3EnxoDpToIQAACtSDw3NzluvruGfrXtLlFqxvWr5d++O49dcgOw2rRHHWkmMCKtRt09V0zdP2DL78pOXhw49Gru44aN0Jv2XULHbnzCHYHS3Es0DUIQKA5CSD+pMfviD/p8eVoSZMkjQm75P1bu0nKLsyfIukYScUX8lfGAfGnMm6cBQEIQKBmBDxD46UFKzVl9hI9OXuxnpy9RM/OXaaNm2/iFbTXv6V7sHPTBw4Zo/4tPWpmAxWln4BnkX3xz9M09ZUl7Xa2Z7euOmSHoTp2ly2061YDNXZ4Xw0gztIfHPQQAhBINQHEn/S4F/EnHb7sLulJSbtLel3S2ZLultRV0hmSfh7OCrpN0ttq2GXEnxrCpCoIQAACHRHwluzzlq0JkjW/uni1Zi1cpalzlmjK7MVavGp9h/D69equ8w7dTh88dDsN7I3oQ6RVRsAxeOOjs/Xd25/VsjUbSqpkeP9e2n54X20/vF/ws9MW/bX36EHq09O3LhQIQAACEIg7AcSfuHuodPsQf0pnFecjPyhpYmjgwZIeKjD2LEm/D/92rKR7atQZxJ8agaQaCEAAAlkCC1aslZdtPfP6suD1lcWrAsHn9SVrtKGtyHSeDtD16dlN5x48JpjtM7hvTyBDoCYEvBTMycPvfHquJj03X35fTunRrYv23nZwsOzQPxNGDVT3bh6vokAAAhCAQNwIIP7EzSOV24P4Uzm7OJ052Ru2SLpP0tFFDLOfXwzzAN0g6ZwaGY/4UyOQVFMZAW9NPH/FWr2yaFXwgPzKotVatHKdRg5s0XbD+mrssL7admgf9eruFZAUCMSLwLoNbXr+DYs8y/Xc3GV6NhB8lsviTzXFuZt3HjlAR48brvMO2Y5dvKqBybmdEli7oVUPvbhQdzw9L0gsXkn8Om/QAWOHykmk/f3tnFSZn54a1KdnLiG5/8949pt/nIQ6+7pq3QZtaN0Y5CSyQJp5bQteh/TtGQhNe48erB2G92OHsk49ygEQgAAENieA+JOeiED8Sb4v+0haHi7xuljSle106TpJH5Pk7J9b1qjbiD81AllKNc7rYXHj8VmL9MSsTF6PRSvXqmuXLsGPd+vxjx/8/Dqod0/tstUA7Rr8DNSOW/RTjzqOrG5obdPClev0xrK1emP5Gr2xfG3w+8KVa9W7ZzcN69tLQ/v1DG7o/Tq8X69gJkJ7Nrm/S1at19xla4KfeUvD1/Cm34LPnMWrtXZDW4f4zGPrwb01ZmhGDNppZH+NGzlAO4/sH7vEpGvWtwYzPJauXq+169u0rrVNa9e3Bn3M/LSqd49uwcPRlgN7a+SAloBtuWV9a5tWrWvV6nWt8kOTl2+4zeBn1brg1eyXrVkfHLdmfZtsW/CzIfPeD2F+qBo1uLe2GdIn8zo482re1Qhu9v385Wv1whsr9OL8FcHra0vXyDHWulFqbWsLHvTaNmYe9Lp37aJRg/sEPh4zLPvat+jyJtdtlivXbtDyNRu0aNU6LV65LhANF6/y6/rgvdn37dVNfXt1DxLa+jX7+8A+Pcrib94LV6wL+uHZPP6Z/vqy4H25M3mK+TrzcDtIe207WHttO0h7jBoUu9guN0Y5PpkELMhPeWWJnpqzRDPnrwz+//pn3rLKBU1/hw/p6/SFG7VgRXX7VjjnVSAEbTtY+4weHFwfvXV93oNNp+D9PeTvjuBn7fpNv69ZH3yvdO3aJfj+69W9q1p6bP7as3vX4Jrnz7K/+9W5krLX73Js6dTYKg7wd2VWTPN32PrWjfKMLXKFVQGVU6si4Jj0/crcpWv02tLVwevrS1YHg4COyy0G+N6oJffqJaf1vO+tqjMJOxnxJ2EO68BcxJ/k+3IfSY+H3ThR0r/a6dLHJf0o/GyopEU16HpsxR+LD39+8tXg4c8/A7KvLZn3vgH0DVp+8U3r+nCk0Dc83bv6Ji0jqDT6ZswP1q8vzeT1ePq1ZaHgs6SiEdVsH32DufMW/bXb1gM0fssBGjusX5CM0xfKcvvnC/DsRav04IsL9cALCwIxygJNsQSzncWZ3eD27Q1vPR381kVyG77ZrGfZZkjvQAgaP7K/th/RL7gh79bVP9pMULNNjokgPlozI8p+aLcA4X++0ffNe68emZv4Xj0y7x07vmn2sZmb54xoEYgBK9dpTjBjaXUwc8k8LZiVW/zgYhHIfrQdgWC0oTVPPMq8X73eQk9GwKk3V/txq4G9g9lXFmO2c6wN6xu8tzDkByTPDpi/fF0gDi5YvjZ4qPNIfvZh0Q9W1ZbBfTI3g1mxx/232FXmyqkOzcjnP3Jg70CICvq0Yp0WrrD4uS4Q0qotQ/v2DNgF4tqg8GdwH+04op9GD+1T9v/hau3hfAiUQ2D5mvWBGGTB8/FZi4Prhr/z4lCcD8v/rzI/oYA9qHfwveHvpLlLV2dePRCxdE3woFnJta7UvmYHcrp16RJ8n3Tv1iUYKPHAiQdN/EDrGVF+HZw3K6qwfttYOAsq+97XAecJC4TvAgHc373Bdaqtrd2k8fmcsuxGDGhRS/duaumRuQa25Ilftm3V+uyAQ+Z7ODP40Cpf5bNimK+bPr9nt27B9dT1eYDD9y/tFd8vWbj3NcT5CwQAACAASURBVMUivn8sEKxauyG41qxY2xq8rly3IWjP9Q3p0zNg6u9Vv/q9v8tdstfPtcHgS+b66TYcJ56FNrhvj4C77yUt7tWi+J4gM8CSebXvhvTrWbaIb1tfW7JGc8KZ0MHr4tXB+xVrNmzG1PcLZu0+OM58XxDc27RuDO4jLHI6Xnx/1rtH1yBHl4/1UmIPQpmj49GDjB5crGbApz2GvoY+NHNhcK/5xMuLg36sXOeNjEsrvhfJ/r8Z5v839nk///QKfO+BE/fbzH2PlHv1vdKG/EEmzyKU/JzQunHjpteNmb95IMr3iH6174J72WBgNnMvmX3v+1x/nj3Or74f8f1u9vdr37NXLJPkI/6UFnNJOArxJwle6tjGkyX9LTxkgqSn2jn8FEl/CT9zYuhpJXS9pCdvf2nFrTz28iKd8ZPC1EebrPQXcd+e3TMCQ/AQ39buA6GP7REKQT3CETpf9H3x981C8Nq3RzDTxu99YfQF0hfH7Gvvnl2DC4BvPJwbwTc+uRuStRuCB0QLPZ714YubRYBGYbWdfii3+OEHdM8qyV7cfbH3Bd7vPXoy7dWlwU27L8S2lQIBCNSWgG9Ux2/p2WmbZqg5SW4lM7xqaxm1QaC2BGYvXKUHXlyg//ia8sKCTpOW17Z1aksSAYsT2XuRrAjhB3ULPrUYKKiUhe+fLCD4vqmYgGjB4Y1la4JZ25ml6Znl6f7ds+GyYoOFg2LF914j+mcEvxH9W4LXAS3dA3Fryap1WhLO0s3M1s28b9S9Y769HijdcUT/YCbdblsPDF49u7rcWWKebfzozEXBPeaDLy4IlkI3W3n80mMDwSpuBfEnbh6p3B7En8rZxeXM90j6XWjMjpJeaMew4yTdGX5WLCl0sdNKUnXiKP7cPX2ezr8hOyEqLq6qrR3Z5Uyuta3NS2GyIweZpTC1mG1QW4trW5uX4owa0kfbhMuOsq8e0bGQ9tKCFZq5YGWwBbZ/0s6jtnSL1+aYs6CZHSm0aNneTWuj7PEMvfZGqBthQ6Vt+GZ5hxH9A6Fnly0HBDPQxm3ZP5Y3fZX2kfMgUCoBj54/M3dZsIOdH+g9G3D+isxsDo/+eyadZ1luOaC3tgiWvbYEMx790O0fD8h4kKZbt8xsGc+e8av/vTB/eWap9KwlemL24mBJKQUCEKg/Ac+ucd7F0UP6aPTQvsEsVf94RlU2T2NOFFu8mv+bkh790jGB0Be3gvgTN49Ubg/iT+Xs4nJmPcWfzvoY22Vff3pyjj77x6md2Z+oz7O5CpynYN/RgzVhm0FBDpL2ikeCpr+2TE+/tjRYOuZZO15SU8slL9m2+/bspnFbDghGqIKfAS25V09P9/Ru37xnbuTD15WZ3y0eOJAsImZendkhWPkVTMv1jX5wkz+gZbPfB/TuXtZSF09vf2H+imAk6dlwFyX/Xu4uNfUIGs8u26J/i7wMzXlzPLrnafOeCr/pJzP1fflar3cPlyEESxIyiU89ZTm/uE5Pmc8uRfOoaXaq9qZp292D6dwenRvkpZF9Mssi/ePp7X61b4Mp/OGStvwlgp4x57Z98+b8S17G5lcv53h54cqK8nNYYHIOISdm9Wy0zKtvGvsG9mcf6vKXY3pKvm2YtdBC3yq9vGBl0L5/Fq9cv9mIsftjFp755/8/QzyFP5z2H7x6GUCfngF3LxPIXzbgWPHUeS8ryCwDyfjBu3AV8rcvvOwsO73cI3lbDWoJllz6x7N5OlrKUI84o04INDsBX2f8HfXk7MWaMntJ8J0RfHctXl30/3A+Lwu2Xkbqa5G/K3xNHtCSWUae+ekRLNPx8o3sciEvHfPsjuyrl5j4d39neWnN+vDV730t9JKS4DXvx8dZAPMyrXoW2+4lTe6TZ/q6v371Lmw9wuVnnr3sWb8eYOks3149baXu8gj4uur0B44zX6uimB1UnsVvPtpirmepbzmot7YK8x5aBN5ykO83W+SlpdmlmcF9UbhM0797KbaX1CWhPPLFY4LvmbgVxJ+4eaRyexB/KmcXlzPrueyrsz7GVvzxl/3/Xl0aJK5dlk1k69/XbHrvqcLBg2TejY1vdIL19l26ZHK6tPnmLFz/HP7uC2c2OW5ngMr93A/svrEMcnqEuT08SrLnNoOD3B6FeYrKrd8ijEdXnXfB+Rdmzs/MjvENcDl5YPzQuk+wTe9QHbT9MO0xamAik+plHwQsAr22ZHXg8+ya7mAmVbhzjAPdN78eVQ5Gl7v6ptijy5k8BOucEyCXH2BTombfyGduojM30tk8Un7fr8V5JjIzl2qRIHnZ6g3Bg0M2d0Iw6u2AirD4/4mFmOzsK7/6/6YflIKdfPpnE4BnclhYODSTWuVRaFTX85NQ+sHPOQWcQ4KtqxvlAdqBQHUE/H/Yom5WCPL1wMJ5Jp9a72B2kQcjqr0GV2NlNnF8Jl+aZ0atDZb6dFR8zXHOoE2ieddgRpSvQRZ6smK3l6yXk7PFvDyg42XqmeXqq4P8QYViV1b4so3BoIOXkof5Y4JlXD26BflQLEo4x07wGopj2bqyGxMEmxSEuev8N1/rgu/aIHdPZiOJzO89A6EjK/Bb1OrTq1sgzLnNVWtb8xL8ZxP9Z3KzeXm+/Z4ZdAkHYHpY/MoMvJi38wv5WP/4dw9izVteXs5D5zZyTNmmbN6dbJoAt+9ivl4yZl97lm17xf60/zxYk9mEYfMNGDyY4rayiY/tO9+vWAzxhhJm6vudjNC36T7F1y/XbaHIxwQ/4UYR/t2DI76+T3s1M8j4/BsrajoT2HGx21YDdfD2vs/0ToBDOhzw7Oj/gfvs+AkGH8OBx6yg6nuz3OCYB7rCgbLsDGfHhLnkNlZxLp+umY1V/Kzg+6xssnZ/PwR5fbIDmWFOn2yOH9uRPSa7WUuXMMekz/PfHA9R37sVY4n4U823d7zOjfbJIF4skmoNCZ8j8pwvln643XQjkNklyRfUXOK48GYluLi2bszdgHjNer9wJyHPPvBImwUfX6CjmA3gGRxOCuilUr6h2bQTVKtWrc8kZvSPRyN8Efbso6Q9oEcUJjQLAQhAAAIQgECKCVi08sCGxbCMgJh5XbByXZAUOTur10KMf/dM33KERAt/Fv28g6pno1rcsuDjGbqezRoHscBC33NzlwczzS0GBbNvF6wKNi/pbMa5ZyZZZHXeJOe786DigWOHBP2jxIMA4k88/FALKxB/akEx2jrY6j1a/rQOAQhAAAIQgAAEIAABCBQQ8A5kwXLwhZml2R5o9MyqQAjz7OchvQPhJ4qBT5xVOgHEn9JZxf1IxJ+4e6g0+yZLOkzSvZKOKXKK/exE0GMl3SDpnNKq7fSo2C776tRyDoAABCAAAQhAAAIQgAAEIACBDgkg/qQnQBB/0uHLD0qaGC4zPUjSIwXdOlPSH8K/HSvpnhp1G/GnRiCpBgIQgAAEIAABCEAAAhCAQNwIIP7EzSOV24P4Uzm7OJ3pLZ+elLS7pFfDmT0WeJw17vRQGBog6V+STqyh4Yg/NYRJVRCAAAQgAAEIQAACEIAABOJEAPEnTt6ozhbEn+r4xensMZLuk+RXl1Wh+JPdL3BKuCRscQ2NRvypIUyqggAEIAABCEAAAhCAAAQgECcCiD9x8kZ1tiD+VMcvbmf3l/Q5SadJ2k5Sm6QZkm6UdK13pK6xwYg/NQZKdRCAAAQgAAEIQAACEIAABOJCAPEnLp6o3g7En+oZNnMNiD/N7H36DgEIQAACEIAABCAAAQikmgDiT3rci/iTHl9G0RPEnyio0yYEIAABCEAAAhCAAAQgAIEGEED8aQDkBjWB+NMg0CltBvEnpY6lWxCAAAQgAAEIQAACEIAABBB/0hMDiD/p8WUUPUH8iYI6bUIAAhCAAAQgAAEIQAACEGgAAcSfBkBuUBOIPw0CndJmEH9S6li6BQEIQAACEIAABCAAAQhAAPEnPTGA+JMeX0bRE8SfKKjTJgQgAAEIQAACEIAABCAAgQYQQPxpAOQGNYH40yDQKW0G8SeljqVbEIAABCAAAQhAAAIQgAAEEH/SEwOIP+nxZRQ9QfyJgjptQgACEIAABCAAAQhAAAIQaAABxJ8GQG5QE4g/DQKd0mYQf1LqWLoFAQhAAAIQgAAEIAABCEAA8Sc9MYD4kx5fRtETxJ8oqNMmBCAAAQhAAAIQgAAEIACBBhBA/GkA5AY1gfjTINApbQbxJ6WOpVsQgAAEIAABCEAAAhCAAAQQf9ITA4g/6fFlFD1B/ImCOm1CAAIQgAAEIAABCEAAAhBoAAHEnwZAblATiD8NAp3SZhB/UupYugUBCEAAAhCAAAQgAAEIQADxJz0xgPiTHl9G0RPEnyio0yYEIAABCEAAAhCAAAQgAIEGEED8aQDkBjWB+NMg0CltBvEnpY6lWxCAAAQgAAEIQAACEIAABBB/0hMDiD/p8WUUPUH8iYI6bUIAAhCAAAQgAAEIQAACEGgAAcSfBkBuUBOIPw0CndJmEH9S6li6BQEIQAACEIAABCAAAQhAAPEnPTGA+JMeX0bRE8SfKKjTJgQgAAEIQAACEIAABCAAgQYQQPxpAOQGNYH40yDQKW0G8SeljqVbEIAABCAAAQhAAAIQgAAEEH/SEwOIP+nxZRQ9QfyJgjptQgACEIAABCAAAQhAAAIQaAABxJ8GQG5QE4g/DQKd0mYQf1LqWLoFAQhAAAIQgAAEIAABCEAA8Sc9MYD4kx5fRtETxJ8oqNMmBCAAAQhAAAIQgAAEIACBBhBA/GkA5AY1gfjTINApbSYQfygQgAAEIAABCEAAAhCAAAQgkGoCaAcJdy8OTLgDIzYf8SdiB9A8BCAAAQhAAAIQgAAEIACBBhBAO2gA5Ho2gQPrSZe640AgK1AR63HwRnxtIE7i65u4WUasxM0j8bWHWImvb+JmGbESN4/E0x7iJJ5+iaNVxEocvRIDm3ggjoETMKGuBPjyqyve1FROnKTGlXXvCLFSd8SpaYBYSY0r694RYqXuiFPRAHGSCjc2pBPESkMwJ68RxJ/k+QyLyyPAl195vJr1aOKkWT1ffr+JlfKZNesZxEqzer78fhMr5TNrxjOIk2b0emV9JlYq45b6sxB/Uu/ipu8gX35NHwIlASBOSsLEQZKIFcKgVALESqmkOI5YIQZKIUCclEKJY0yAWCEOihJA/CEw0k6AL7+0e7g2/SNOasOxGWohVprBy7XpI7FSG47NUAux0gxerr6PxEn1DJulBmKlWTxdZj8Rf8oExuGJI8CXX+JcFonBxEkk2BPZKLGSSLdFYjSxEgn2RDZKrCTSbQ03mjhpOPLENkisJNZ19TUc8ae+fKk9egJ8+UXvgyRYQJwkwUvxsJFYiYcfkmAFsZIEL8XDRmIlHn6IuxXESdw9FB/7iJX4+CJWliD+xModGFMHAnz51QFqCqskTlLo1Dp1iVipE9gUVkuspNCpdeoSsVInsCmrljhJmUPr2B1ipY5wk1w14k+SvYftEIAABCAAAQhAAAIQgAAEIAABCECgEwKIP4QIBCAAAQhAAAIQgAAEIAABCEAAAhBIMQHEnxQ7l65BAAIQgAAEIAABCEAAAhCAAAQgAAHEH2IAAhCAAAQgAAEIQAACEIAABCAAAQikmADiT4qdS9cgAAEIQAACEIAABCAAAQhAAAIQgADiDzEAAQhAAAIQgAAEIAABCEAAAhCAAARSTADxJ8XOpWsQgAAEIAABCEAAAhCAAAQgAAEIQADxhxiAAAQgAAEIQAACEIAABCAAAQhAAAIpJoD4k2Ln0jUIQAACEIAABCAAAQhAAAIQgAAEIID4QwykkUB/SRdKOl3SdpJaJc2QdJOkayWtS2On6dNmBIZKerukYyTtLWm0pO6S5kt6XNKvJf25E2bEUfMG1RckXZHX/Y6ulcRJc8bJAEkfk3SKpB0l+b2/X56X9G9JV0taUgQN8dI88XKcpA9JOkDSFpI2Snpd0kOSfhbGSXs0iJN0xEkfSUdI2ie8F/HrtmHXvibpshK66di5WNJJ4bmrJT0d3sf8IoyrjqrZPjz/LZK2lLRc0pNhDN5aQvsc0hgC1cTK1uG16ChJe0nye5e5kh6W9HNJ95bQjWpjrYQmOCRqAog/UXuA9mtNwA/5kySNCSteJambpF7h+ymhILC41g1TX6wIrA/FnqxRa0IRsG+elf+S9E5JjpHCQhzFyp0NNWZnSf+V1JLXanvXSuKkoa6JTWO+wb4xfKC3UR5Q8PfIoDwLfQPuOMovxEtsXFhXQ/x98WNJH8lrxQ/sLr3z/vYDSZ/l+lNXX0Rd+ZGS7mvHiFLEH4tFd0jygJbLivDa5MEsF3/mga72BjVPlHSzJAsLLssk9ZPUNXx/vaQPliAgRc2xGdqvNFa2kTRLUv59iq9Hfp//ffNLSR8O74WL8aw21prBR6noI+JPKtxIJ0ICvhh6NGP3cHTtbEl3hxe5M0Ll26Npt0l6G9RSTcAjrI9K+lV4czQz7K1FwUvDmx3/6beS3l9AgjhKdWh02DnfEN8v6eBwdP6g8Ohi10ripDnj5BBJd4U31X8KZ4g9ET48+QFr13AE1iPyL+UhIl6aJ14+IMkPWi63SPpiOCPM7y0ufyeMEb8/rWAWKnGSrjjxA72/J3xvmv2x6DdSUmfiz0BJz4bH+tX3Kp653DOcUeZ6eoRC48eLYPPM9/9J8qDXA5LOC2fBW/y5SNJXwnM+L+m76cKeyN5UGiu+r/W15h5JN4TPPa+Fzz7jJH0r7/vmG5K+XIROtbGWSODNajTiT7N6Pp399ujFxLBr2Ye3/J6eJen34R+ODb8o00mCXnlkvr3RNtP5Sd6orKdgv5KHjDhq3vj5dLhc53eSXpD01Q7EH+Kk+eLE4o4fpsaGS4g/VQYC4qUMWAk/1NceP8j5O2S8pA0F/fEDux/mHUdeju57k2whThLu/ALzPfPcqQfyy8vhUvTOxJ/Lw8EqzxqzqJwvJru+S8IHe9e/Syjs5LfzG0nvC5f+OA4Ll6H+NJwJ4tlAFhCYER9t7FUaKxZuvLTP4mKx4md9D3qfEM4cGy7Js+HzS7WxFi05Wi+LAOJPWbg4OOYEJks6LHzoP7qIrY73F8M8QFbHz4l5fzCvfgT2C2cGuYXCkVfiqH7c41xzdpTUN0W+Uf5EJ+IPcRJnb9bHNi/jsXDsPAqOl8Ib6I5aJV7q45M41mphxzN8nE/FS4uLFX/ma88/JJ2cdwBxEkeP1tamUsUfL+Xx4JSXZnnWTmHxDB7nkPLr1/OuVz7Os32cg8zLfjyI4c8LS3bGiP/u+t0OJV4ESo2Vzqz26oc/hgc5D6ZTYOSXamKts7b5PGYEEH9i5hDMqZiAR2SdxM7LNpwY78p2arouTNLpm3cnvqM0JwEvDXwq7Lovip6a70IcNWc8uNdeIuoE4RaFLQ47EWd7M3+Ik+aMEy+d8KxSbxxQzqwf4qW54sWj7G8tceaPv2c8A4TrT/PESCkP9BYPLSK6nBnm7SlGKBtrTuqbXabs446XdHt4wv6SHmsH7/RwsKNwBlrzeCPePS0lVkrpgQXmv4UHevDTywezpdpYK6V9jokRAcSfGDkDU6oi4ERl2S8zJ7hzMt9ixeuifxR+4AR6i6pqlZOTSuACSdeExntN9HPh78RRUj1and3ekce771gA8g49Lh2JP8RJdbyTeLY3DfDyCOfbODecYer8YX7I9w4pXjLhPGOeGfTPgg4SL0n0eOU25z9oeWDBy3O8BMzFD1rflvSOcCayR+EdVy7ESeXMk3RmKQ/03q02OyjlJV3PtNNB5+px/h7HkJf/ZIt3vP1e+MbiczbheGE1ng3iATAvZ90jSRCbxNZSYqUUFN8Pk8s7MbiXfWW/c3xutbFWSvscEyMCiD8xcgamVEUg/2ZrQt6sjsJKvS3vX8I/evbHtKpa5eQkEvCOPB7t8swvJ/c9PK8TxFESPVqdzd4S1dvm+qF+N0nZ5OAdiT/ESXXMk3h2/uiol1B8RpI3ECi205dzz3lXFSeedyFekujx6mz+f2FiZ3+vuOTv9uXcK94tzuJh/gAUcVId86ScXcoDff4AlUWd/If1/H5m89T5b/4+8m5gLtmHfYvSQzoA46TRjtWFkoYlBWAT2VlKrHSGw0uU/axjEdB5oLwZTn6pNtY6a5/PY0YA8SdmDsGcigm8R5KTtLrsmDfKVlihR/XvDP9YLCl0xQZwYiIIeFngXyWdFObrOKBAKCSOEuHGmhrpnBve/a9wx5OOxB/ipKYuSERlB4Y7wNnYtjB5qnMA+ftkfZibwyPtHkV38cj7VeHvxEsiXFxzI/294l2/RhTU7G2YnfPHy0rzk/gSJzV3QSwrLOWB3jvEfTO03gnCC5OGZzuWnbXq91uFOYD8u2ey+rNXJY3qgILbcFsWsT27kRIvAqXESkcWO+eTBzk9q3CBJA+Oeyew/FJtrMWLGNZ0SgDxp1NEHJAQAtw0JcRREZvpXB2fDG3wrirZ7XizZhFHETuowc17JxSPhP1XktfB599gI/402Bkxb86DBc75ky2n5s0izf7N4rJ3XPENtkfSvZ2zY4rvlZg7t8bmeYTdyXOdq8XL0f1wlU2wule4Q9O+4cOY84xl888RJzV2REyrK+WBvtoHcsSfmDq/TLNKiZX2quwe5oryElMPUHjQMzv4jfhTpiPSdDjiT5q82dx9Ybp0c/u/lN57VN6j8S5esnF1kZOIo1JIpuMY52nxci8vA/SsjvwEiO4hy77S4eda9SI/SfzzknZqp+KsoOiPHVePsOyrVi5ITD3OK+j8gs4lt2eRXeE8Gm/B2TH0n3CXUneO609iXFyVoaU80Fe7FIdlX1W5KDYnlxIrxYz1tvG/DwVoD0CclZdDqvD4amMtNrAwpDQCiD+lceKo+BMgUWL8fRSlhdmkiLbhc+F6+GL2EEdReqmxbXtk3ol7fxzuEFjYukdenajVxbkUXDw13j/ESWN9FYfWnDfDs3lc/i7p7e0Y5QS+T4SfvSvcXpd4iYMHG2ODvyucx8ej7t4RzrNNi5X8By4L0W/wvdIYB8WglVIe6KtNwkvC5xg4ugYmlBIrhc1Y+PmtpHdLapX0Xkl/6MCWamOtBt2kikYSQPxpJG3aqicBttKtJ91k131lKPi4FxdL8vv2CnGUbF+XY/0kSUeUc4KkH4bJMYmTMsGl5PA5kpwgvCPxJ1/oyW7RTLykJABK6Ea+/53zx1txFysn5O1Kmp0hRpyUADgFh5TyQF/t9tts9Z6CQJFUSqzk99TCj/OfeuDBwo9not7UCYpqYy0dpJuoF4g/TeTsJujq5HD69L2SvI6+sDjevd3qWEk3SDqnCZg0exfzl3p1JvxkWRFHzRE11Yg/JkScNEec5PfSOcI+EF5HvLFAsfL+8Priz5xHKruckHhpjnhxTh/nfXLx0i/PLCxWfP/xq/CDXcMdKPleaY4YKeWB3verPm7bMDehcxQWlr6S5krqJ8k7EDqBeLb4s/mSvMTwK5IuL3L+6LANf3RemKeqOTyQnF6WEivZ3uQv9SpV+PG51cZacmhiaUAA8YdASBMBXxy9xa631z0ozLWQ3z+PwmanPh4r6Z40dZ6+vIlAvvDT0VKvwhOJI4LJBDrK+ePPiZPmi5PDQtHPPW8v4bMT++4R7rLjBzfvDEa8NE+s+GHbywP9ahHIO0oW7tTkhzSLgU4i7q24h4ej9MRJc8RJqQ/0FmwuleTd4SwQ+rz84gGt74Sxs4ukGQWfezMDz/x4XdJ4SUsLPr9O0sckLZdkIcixSIkXgVJjJX/Gj79v7PeOlnoV9rLaWIsXNazpkADiDwGSJgJeY++bLSfm9PaWHlmzwOMdWLym1cLQgHCq9Ylp6jh9eROB/Bw/n5X0gzIYEUdlwErxoZ2JP8RJip3fQddulvTO8AE/u9W7b7Yt9HhJqQcZXJxP6td59RAvzRMv10hyTh+X28Plxk4u77JbGCdvCd97toZnbWQLcZK+OBksyQ/n2eL71G3COPC9SraskbQi7/1ASc+GuwZOl3R2mE+sZzj44E0r/Ltnl3mWWWHZTtL/JHkWkLf79oCFk9X7vXMC+Rrn58DPS8q3I30eSE6PKomV/Bw/2d0lfZ0qp1Qba+W0xbERE0D8idgBNF9zAmMk3SfJry4eMbH40xK+96isl4QxwlFz9LGp0A9hs0JrPOruqc8dFc8Q8k9+IY5i487IDOlM/LFhxElk7omsYT84OY/L4aEFa8PrjG/as+Vr4YNVoZHES2Rua2jDnvXzJ0nO65MtjhOXXnl/u1GSlwl6iQbXn4a6qKGNZWdvdNaoxWKLxvnFOaTukDQ0/KNn6fh+tkf43lt3O/l8Nr4K2/BAp4UA55Ny8ewfLxPLilHe+MCikGfMU6InUEms+Fr079B0b+nuhPMdlU+3Myuo2liLnh4WlEQA8ackTByUMALebcPLfE6T5JEPCwCeDusbLe+84d16KOkl4Aesl8roXnsPasRRGRBTeGgp4o+7TZyk0PmddMkDCs6R4Qd3z+RwDHi3Jo+u+xrzYAfnEy/NES++v/aMYy+/8EPViPAB23HyaJhf5Z/ESVMEQyUP9PlgvBucZ+ecFM4Y8gyhaeHMQuchyy4tbQ/m9uH5x0naMlzm5YHQn0q6tSk8kJxOVhIrR4aD3qX20nnrsvnGCs+pNtZKtYHjIiSA+BMhfJqGAAQgAAEIQAACEIAABCAAAQhAAAL1JoD4U2/C1A8BCEAAAhCAAAQgAAEIQAACEIAABCIkgPgTIXyahgAEIAABCEAAAhCAAAQgAAEIQAAC9SaA+FNvwtQPAQhAAAIQgAAEIAABCEAAAhCAAAQiJID4EyF8moYABCAAAQhAAAIQgAAEIAABCEAAAvUmgPhTb8LUDwEIQAACEIAABCAAAQhAAAIQgAAEIiSA+BMhfJqGAAQgAAEIQAACEIAABCAAAQhAAAL1JoD4U2/Cj5EnyAAACulJREFU1A8BCEAAAhCAAAQgAAEIQAACEIAABCIkgPgTIXyahgAEIAABCEAAAhCAAAQgAAEIQAAC9SaA+FNvwtQPAQhAAAIQgAAEIAABCEAAAhCAAAQiJID4EyF8moYABCAAAQhAAAIQgAAEIAABCEAAAvUmgPhTb8LUDwEIQAACEIAABCAAAQhAAAIQgAAEIiSA+BMhfJqGAAQgAAEIQAACEIAABCAAAQhAAAL1JoD4U2/C1A8BCEAAAhCAAAQgAAEIQAACEIAABCIkgPgTIXyahgAEIAABCEAAAhCAAAQgAAEIQAAC9SaA+FNvwtQPAQhAAAIQgECtCJwr6XpJsySNqVWlTVLPxrCfR0ma1CR9ppsQgAAEIAABCIQEEH8IBQhAAAIQgAAEoiDQTdLpkk6SdKCkEZL6SFoiaYak+yX9TtK0POMQfyr3FOJP5ew4EwIQgAAEIJB4Aog/iXchHYAABCAAAQgkjoDFnl9L2inP8vWSlksaJKlr3t//JOksSeskIf5U7mrEn8rZcSYEIAABCEAg8QQQfxLvQjoAAQhAAAIQSBSBkyXdLKmXpIWSvifpVknPh73wjKC9wllBH5c0QNLgcEYQ4k/lrkb8qZwdZ0IAAhCAAAQSTwDxJ/EupAMQgAAEIACBxBDYUdLjoaAzXdLxkuZ0YP0QSb8MZ/x4ORjiT+WuRvypnB1nQgACEIAABBJPAPEn8S6kAxCAAAQgAIHEEPiDpDMlrZE0IcztU4rxvl+xeFEo/uwj6fOSDpNkoehVSX+RdLmkxUUq7iHprWGeob0lbS1paDiraIqkX0m6KWyr8PQjJd0X/tH27CDpi5KOC/MVzZf0L0mXhXYUnl+t7dn6+kv6hKRTJO0sqa+kNyQ9IOmHkh5qByjiTymRxjEQgAAEIACBlBJA/EmpY+kWBCAAAQhAIGYEtpD0WpjP5xeSzq/AvnwBxcKLxRoLOkslWRTJ5gp6OkwivaKgjXwBxx8tk+R7IZ+bLV6S9m5JbR2ce7Skv0nqF+Yp6i2pe3i8+7h/EQGoWttd/Z6S/i5pVNhWq6RVefZb4PmSpCuKsEX8qSDgOAUCEIAABCCQFgKIP2nxJP2AAAQgAAEIxJuABZUbQxO9w9c/KzA3K6BY8HBuoN9I+rqkV8Kdwj4g6QehIOTZP18paMOizHmSbpH0aCj++BDPGnpfOGPIOYY+LemaDsQfzyrybmSedfSspJ6S3iFpYijE2K6zC86v1vYtJf03nGXkJNjfkvSUJCfK9k5pn5R0SShCnRrOgMo3AfGngoDjFAhAAAIQgEBaCCD+pMWT9AMCEIAABCAQbwIWYy4NTfRyK8+QKbdkBRSf593C/L6wfF/SZyW9IMk5hsop7wyTUb8YLuvKPzd/1pCXfx1bZHbQBaFotDrMa7Qhr4JqbfdsKQtXv5f03nY69RlJV0maGs4Syj8M8aecSOBYCEAAAhCAQMoIIP6kzKF0BwIQgAAEIBBTAtdJ+lhom5dJOe9PuSVfQLGwY4GnsBwu6d/hH50Px7OESi22K3u8Z9rMzTsxX/xxnp+7i1S6raRZ4d93kfRM3jHV2N4S5jDyq3MlecZPseL8RQvCD0ZKmpd3EOJPqVHAcRCAAAQgAIEUEkD8SaFT6RIEIAABCEAghgRqKf4sChM1F+umEzFnt413bhwngc4vzu/z0TDp83hJg8JlYoV17RfuTJb9e77446Vhy4s07rw/XoblcmiYhDl7WFb8qcT2QyT9J6woX9Ap1n/nVnI5IFzalj0G8SeG/ykwCQIQgAAEINAoAog/jSJNOxCAAAQgAIHmJlDLZV+eXTOmHZz++0vhZ9tJejnvuJ0k3ZOXMNkfeabPyrwlXFnxxGJPdgaRjyvc7as9b7YnspSyTX17tp8h6Y9lhs9RkiblnYP4UyZADocABCAAAQikiQDiT5q8SV8gAAEIQAAC8SVQy4TPlYo/3g794FAQukjSvZI8EydbnEQ6m6enUDyJUvzJZ1fpkjnEn/j+38AyCEAAAhCAQN0JIP7UHTENQAACEIAABCAgqdZbvZc782cbSbNDTxwk6eEiXnEi6jnh3+Mk/uQLT+MkPVdBRCH+VACNUyAAAQhAAAJpIYD4kxZP0g8IQAACEIBA/Al46ZKXMHk3rD0lzSjRZN+vWLyoZumUZ/x45o+LEyevLdL2OZJ+FUPxx4mrPUPJW8p7xtL3SuSWfxjiTwXQOAUCEIAABCCQFgKIP2nxJP2AAAQgAAEIxJ+Ac+48IamfpKclHV8kIXN+LwZLmijpg5KWVCn+7CppWlh5YTJk/9mJoJ/M2+I9TjN/bN/1Yf+9m9c+ebOYinl9SMFyNh+D+BP//x9YCAEIQAACEKgbAcSfuqGlYghAAAIQgAAEihB4h6Q/hLNYLGR4Fsutedu2O+/OHpJOlXRBuBuXRaBqxZ+uYSJob8du4cmzfCxEuXgZ2P9JGp23i1jcxB9vPf+4pK0kvSbpC5L+krfr2HBJ3ub+fZL6hMJaPn7EH/47QgACEIAABJqYAOJPEzufrkMAAhCAAAQiIuCty728ytuyZ8s6SStCscdCjYsFi5tCocZbqFez7Mv1nSTpz5K8JbuLd/pysVjiHb9OkXR3+Le4iT82y1vTW/DxDCqXtlAU6yXJS8OyxX04rsC3iD8RBTvNQgACEIAABOJAAPEnDl7ABghAAAIQgEDzEfAMH+f/sSDjZVgjJHknq6WSng23Wf9NQXLjasUfU/Ysny9JsgBl0WduuP37d8K22hNJotztKz86LPR41tLpYd4kL/GycObZQFMk3SXpFkmLEX+a7z8VPYYABCAAAQi0RwDxh9iAAAQgAAEIQAACEIAABCAAAQhAAAIpJoD4k2Ln0jUIQAACEIAABCAAAQhAAAIQgAAEIID4QwxAAAIQgAAEIAABCEAAAhCAAAQgAIEUE0D8SbFz6RoEIAABCEAAAhCAAAQgAAEIQAACEED8IQYgAAEIQAACEIAABCAAAQhAAAIQgECKCSD+pNi5dA0CEIAABCAAAQhAAAIQgAAEIAABCCD+EAMQgAAEIAABCEAAAhCAAAQgAAEIQCDFBBB/UuxcugYBCEAAAhCAAAQgAAEIQAACEIAABBB/iAEIQAACEIAABCAAAQhAAAIQgAAEIJBiAog/KXYuXYMABCAAAQhAAAIQgAAEIAABCEAAAog/xAAEIAABCEAAAhCAAAQgAAEIQAACEEgxAcSfFDuXrkEAAhCAAAQgAAEIQAACEIAABCAAAcQfYgACEIAABCAAAQhAAAIQgAAEIAABCKSYAOJPip1L1yAAAQhAAAIQgAAEIAABCEAAAhCAAOIPMQABCEAAAhCAAAQgAAEIQAACEIAABFJMAPEnxc6laxCAAAQgAAEIQAACEIAABCAAAQhAAPGHGIAABCAAAQhAAAIQgAAEIAABCEAAAikmgPiTYufSNQhAAAIQgAAEIAABCEAAAhCAAAQggPhDDEAAAhCAAAQgAAEIQAACEIAABCAAgRQTQPxJsXPpGgQgAAEIQAACEIAABCAAAQhAAAIQQPwhBiAAAQhAAAIQgAAEIAABCEAAAhCAQIoJIP6k2Ll0DQIQgAAEIAABCEAAAhCAAAQgAAEIIP4QAxCAAAQgAAEIQAACEIAABCAAAQhAIMUEEH9S7Fy6BgEIQAACEIAABCAAAQhAAAIQgAAEEH+IAQhAAAIQgAAEIAABCEAAAhCAAAQgkGIC/x+lcjnkLX6gGAAAAABJRU5ErkJggg==\" width=\"639.4444613839378\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Load Data Cube\n",
    "hdulist = fits.open(\"TWHYA_BAND7_ReferenceImages/TWHydra_CO3_2line.image.fits\")\n",
    "twhydra_cube = hdulist[0]\n",
    "\n",
    "def show_spectra(cube):\n",
    "    spec = cube.sum(axis=(0,2,3))\n",
    "    plt.plot(spec)\n",
    "    plt.ylabel('Flux')\n",
    "    plt.xlabel('Channel')\n",
    "\n",
    "show_spectra(twhydra_cube.data)\n",
    "#plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Interactivity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'float'>\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'7.0.0'"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import ipywidgets\n",
    "from ipywidgets import interact\n",
    "threshold=0.\n",
    "print(type(threshold))\n",
    "ipywidgets.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "8.64718 -0.488696\n"
     ]
    }
   ],
   "source": [
    "mmax = twhydra_cube.data.max()\n",
    "mmin = twhydra_cube.data.min()\n",
    "print(mmax,mmin)\n",
    "interact?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f20a466dc67e43eaa8952efd043df460",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "A Jupyter Widget"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "#@interact.options(manual=True)\n",
    "def interactive_denoising(threshold=0.):\n",
    "    threshold=float(threshold)\n",
    "    #print type(threshold)\n",
    "    cube=twhydra_cube.data.copy()\n",
    "    cube[cube < threshold] = 0\n",
    "    show_spectra(cube)\n",
    "    plt.show()\n",
    "res=interact(interactive_denoising,threshold=(mmin,mmax))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'threshold': 4.5113}"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "limits = res.widget.kwargs\n",
    "limits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1a494857eda44d67b1c435b8e8c1ab55",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "A Jupyter Widget"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<function __main__.explore_channels>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cube=twhydra_cube.data[0]\n",
    "def explore_channels(chan=50):\n",
    "    plt.imshow(cube[chan])\n",
    "    plt.colorbar()\n",
    "    plt.show()\n",
    "\n",
    "interact(explore_channels,chan=(0,cube.shape[0]-1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3 Catalog Access"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'All:GOODS/HDF/CDF': ['GOODS: Chandra ACIS HB',\n",
      "                       'GOODS: Chandra ACIS FB',\n",
      "                       'GOODS: Chandra ACIS SB',\n",
      "                       'GOODS: VLT VIMOS U',\n",
      "                       'GOODS: VLT VIMOS R',\n",
      "                       'GOODS: HST ACS B',\n",
      "                       'GOODS: HST ACS V',\n",
      "                       'GOODS: HST ACS I',\n",
      "                       'GOODS: HST ACS Z',\n",
      "                       'Hawaii HDF U',\n",
      "                       'Hawaii HDF B',\n",
      "                       'Hawaii HDF V0201',\n",
      "                       'Hawaii HDF V0401',\n",
      "                       'Hawaii HDF R',\n",
      "                       'Hawaii HDF I',\n",
      "                       'Hawaii HDF z',\n",
      "                       'Hawaii HDF HK',\n",
      "                       'GOODS: HST NICMOS',\n",
      "                       'GOODS: VLT ISAAC J',\n",
      "                       'GOODS: VLT ISAAC H',\n",
      "                       'GOODS: VLT ISAAC Ks',\n",
      "                       'HUDF: VLT ISAAC Ks',\n",
      "                       'GOODS: Spitzer IRAC 3.6',\n",
      "                       'GOODS: Spitzer IRAC 4.5',\n",
      "                       'GOODS: Spitzer IRAC 5.8',\n",
      "                       'GOODS: Spitzer IRAC 8.0',\n",
      "                       'GOODS: Spitzer MIPS 24',\n",
      "                       'GOODS: Herschel 100',\n",
      "                       'GOODS: Herschel 160',\n",
      "                       'GOODS: Herschel 250',\n",
      "                       'GOODS: Herschel 350',\n",
      "                       'GOODS: Herschel 500',\n",
      "                       'CDFS: LESS',\n",
      "                       'GOODS: VLA North'],\n",
      " 'GammaRay': ['Fermi 5',\n",
      "              'Fermi 4',\n",
      "              'Fermi 3',\n",
      "              'Fermi 2',\n",
      "              'Fermi 1',\n",
      "              'EGRET (3D)',\n",
      "              'EGRET <100 MeV',\n",
      "              'EGRET >100 MeV',\n",
      "              'COMPTEL'],\n",
      " 'HardX-ray': ['INT GAL 17-35 Flux',\n",
      "               'INT GAL 17-60 Flux',\n",
      "               'INT GAL 35-80 Flux',\n",
      "               'INTEGRAL/SPI GC',\n",
      "               'GRANAT/SIGMA',\n",
      "               'RXTE Allsky 3-8keV Flux',\n",
      "               'RXTE Allsky 3-20keV Flux',\n",
      "               'RXTE Allsky 8-20keV Flux'],\n",
      " 'IR:2MASS': ['2MASS-J', '2MASS-H', '2MASS-K'],\n",
      " 'IR:AKARI': ['AKARI N60', 'AKARI WIDE-S', 'AKARI WIDE-L', 'AKARI N160'],\n",
      " 'IR:IRAS': ['IRIS  12',\n",
      "             'IRIS  25',\n",
      "             'IRIS  60',\n",
      "             'IRIS 100',\n",
      "             'SFD100m',\n",
      "             'SFD Dust Map',\n",
      "             'IRAS  12 micron',\n",
      "             'IRAS  25 micron',\n",
      "             'IRAS  60 micron',\n",
      "             'IRAS 100 micron'],\n",
      " 'IR:Planck': ['Planck 857',\n",
      "               'Planck 545',\n",
      "               'Planck 353',\n",
      "               'Planck 217',\n",
      "               'Planck 143',\n",
      "               'Planck 100',\n",
      "               'Planck 070',\n",
      "               'Planck 044',\n",
      "               'Planck 030'],\n",
      " 'IR:UKIDSS': ['UKIDSS-Y', 'UKIDSS-J', 'UKIDSS-H', 'UKIDSS-K'],\n",
      " 'IR:WISE': ['WISE 3.4', 'WISE 4.6', 'WISE 12', 'WISE 22'],\n",
      " 'IR:WMAP&COBE': ['WMAP ILC',\n",
      "                  'WMAP Ka',\n",
      "                  'WMAP K',\n",
      "                  'WMAP Q',\n",
      "                  'WMAP V',\n",
      "                  'WMAP W',\n",
      "                  'COBE DIRBE/AAM',\n",
      "                  'COBE DIRBE/ZSMA'],\n",
      " 'Optical:DSS': ['DSS',\n",
      "                 'DSS1 Blue',\n",
      "                 'DSS1 Red',\n",
      "                 'DSS2 Red',\n",
      "                 'DSS2 Blue',\n",
      "                 'DSS2 IR'],\n",
      " 'Optical:SDSS': ['SDSSg',\n",
      "                  'SDSSi',\n",
      "                  'SDSSr',\n",
      "                  'SDSSu',\n",
      "                  'SDSSz',\n",
      "                  'SDSSdr7g',\n",
      "                  'SDSSdr7i',\n",
      "                  'SDSSdr7r',\n",
      "                  'SDSSdr7u',\n",
      "                  'SDSSdr7z'],\n",
      " 'OtherOptical': ['Mellinger Red',\n",
      "                  'Mellinger Green',\n",
      "                  'Mellinger Blue',\n",
      "                  'NEAT',\n",
      "                  'H-Alpha Comp',\n",
      "                  'SHASSA H',\n",
      "                  'SHASSA CC',\n",
      "                  'SHASSA C',\n",
      "                  'SHASSA Sm'],\n",
      " 'ROSATDiffuse': ['RASS Background 1',\n",
      "                  'RASS Background 2',\n",
      "                  'RASS Background 3',\n",
      "                  'RASS Background 4',\n",
      "                  'RASS Background 5',\n",
      "                  'RASS Background 6',\n",
      "                  'RASS Background 7'],\n",
      " 'ROSATw/sources': ['RASS-Cnt Soft',\n",
      "                    'RASS-Cnt Hard',\n",
      "                    'RASS-Cnt Broad',\n",
      "                    'PSPC 2.0 Deg-Int',\n",
      "                    'PSPC 1.0 Deg-Int',\n",
      "                    'PSPC 0.6 Deg-Int',\n",
      "                    'HRI'],\n",
      " 'Radio:GHz': ['CO',\n",
      "               'GB6 (4850MHz)',\n",
      "               'VLA FIRST (1.4 GHz)',\n",
      "               'NVSS',\n",
      "               'Stripe82VLA',\n",
      "               '1420MHz (Bonn)',\n",
      "               'HI4PI',\n",
      "               'EBHIS',\n",
      "               'nH'],\n",
      " 'Radio:MHz': ['SUMSS 843 MHz',\n",
      "               '0408MHz',\n",
      "               'WENSS',\n",
      "               'TGSS ADR1',\n",
      "               'VLSSr',\n",
      "               '0035MHz'],\n",
      " 'SoftX-ray': ['SwiftXRTCnt', 'SwiftXRTExp', 'SwiftXRTInt', 'HEAO 1 A-2'],\n",
      " 'UV': ['GALEX Near UV',\n",
      "        'GALEX Far UV',\n",
      "        'ROSAT WFC F1',\n",
      "        'ROSAT WFC F2',\n",
      "        'EUVE 83 A',\n",
      "        'EUVE 171 A',\n",
      "        'EUVE 405 A',\n",
      "        'EUVE 555 A'],\n",
      " 'X-ray:SwiftBAT': ['BAT SNR 14-195',\n",
      "                    'BAT SNR 14-20',\n",
      "                    'BAT SNR 20-24',\n",
      "                    'BAT SNR 24-35',\n",
      "                    'BAT SNR 35-50',\n",
      "                    'BAT SNR 50-75',\n",
      "                    'BAT SNR 75-100',\n",
      "                    'BAT SNR 100-150',\n",
      "                    'BAT SNR 150-195'],\n",
      " 'overlay_blue': ['Fermi 5',\n",
      "                  'Fermi 4',\n",
      "                  'Fermi 3',\n",
      "                  'Fermi 2',\n",
      "                  'Fermi 1',\n",
      "                  'EGRET (3D)',\n",
      "                  'EGRET <100 MeV',\n",
      "                  'EGRET >100 MeV',\n",
      "                  'COMPTEL',\n",
      "                  'INT GAL 17-35 Flux',\n",
      "                  'INT GAL 17-60 Flux',\n",
      "                  'INT GAL 35-80 Flux',\n",
      "                  'INTEGRAL/SPI GC',\n",
      "                  'GRANAT/SIGMA',\n",
      "                  'RXTE Allsky 3-8keV Flux',\n",
      "                  'RXTE Allsky 3-20keV Flux',\n",
      "                  'RXTE Allsky 8-20keV Flux',\n",
      "                  'BAT SNR 14-195',\n",
      "                  'BAT SNR 14-20',\n",
      "                  'BAT SNR 20-24',\n",
      "                  'BAT SNR 24-35',\n",
      "                  'BAT SNR 35-50',\n",
      "                  'BAT SNR 50-75',\n",
      "                  'BAT SNR 75-100',\n",
      "                  'BAT SNR 100-150',\n",
      "                  'BAT SNR 150-195',\n",
      "                  'SwiftXRTCnt',\n",
      "                  'SwiftXRTExp',\n",
      "                  'SwiftXRTInt',\n",
      "                  'HEAO 1 A-2',\n",
      "                  'RASS-Cnt Soft',\n",
      "                  'RASS-Cnt Hard',\n",
      "                  'RASS-Cnt Broad',\n",
      "                  'PSPC 2.0 Deg-Int',\n",
      "                  'PSPC 1.0 Deg-Int',\n",
      "                  'PSPC 0.6 Deg-Int',\n",
      "                  'HRI',\n",
      "                  'RASS Background 1',\n",
      "                  'RASS Background 2',\n",
      "                  'RASS Background 3',\n",
      "                  'RASS Background 4',\n",
      "                  'RASS Background 5',\n",
      "                  'RASS Background 6',\n",
      "                  'RASS Background 7',\n",
      "                  'GALEX Near UV',\n",
      "                  'GALEX Far UV',\n",
      "                  'ROSAT WFC F1',\n",
      "                  'ROSAT WFC F2',\n",
      "                  'EUVE 83 A',\n",
      "                  'EUVE 171 A',\n",
      "                  'EUVE 405 A',\n",
      "                  'EUVE 555 A',\n",
      "                  'DSS',\n",
      "                  'DSS1 Blue',\n",
      "                  'DSS1 Red',\n",
      "                  'DSS2 Red',\n",
      "                  'DSS2 Blue',\n",
      "                  'DSS2 IR',\n",
      "                  'SDSSg',\n",
      "                  'SDSSi',\n",
      "                  'SDSSr',\n",
      "                  'SDSSu',\n",
      "                  'SDSSz',\n",
      "                  'SDSSdr7g',\n",
      "                  'SDSSdr7i',\n",
      "                  'SDSSdr7r',\n",
      "                  'SDSSdr7u',\n",
      "                  'SDSSdr7z',\n",
      "                  'Mellinger Red',\n",
      "                  'Mellinger Green',\n",
      "                  'Mellinger Blue',\n",
      "                  'NEAT',\n",
      "                  'H-Alpha Comp',\n",
      "                  'SHASSA H',\n",
      "                  'SHASSA CC',\n",
      "                  'SHASSA C',\n",
      "                  'SHASSA Sm',\n",
      "                  'IRIS  12',\n",
      "                  'IRIS  25',\n",
      "                  'IRIS  60',\n",
      "                  'IRIS 100',\n",
      "                  'SFD100m',\n",
      "                  'SFD Dust Map',\n",
      "                  'IRAS  12 micron',\n",
      "                  'IRAS  25 micron',\n",
      "                  'IRAS  60 micron',\n",
      "                  'IRAS 100 micron',\n",
      "                  '2MASS-J',\n",
      "                  '2MASS-H',\n",
      "                  '2MASS-K',\n",
      "                  'UKIDSS-Y',\n",
      "                  'UKIDSS-J',\n",
      "                  'UKIDSS-H',\n",
      "                  'UKIDSS-K',\n",
      "                  'WISE 3.4',\n",
      "                  'WISE 4.6',\n",
      "                  'WISE 12',\n",
      "                  'WISE 22',\n",
      "                  'AKARI N60',\n",
      "                  'AKARI WIDE-S',\n",
      "                  'AKARI WIDE-L',\n",
      "                  'AKARI N160',\n",
      "                  'Planck 857',\n",
      "                  'Planck 545',\n",
      "                  'Planck 353',\n",
      "                  'Planck 217',\n",
      "                  'Planck 143',\n",
      "                  'Planck 100',\n",
      "                  'Planck 070',\n",
      "                  'Planck 044',\n",
      "                  'Planck 030',\n",
      "                  'WMAP ILC',\n",
      "                  'WMAP Ka',\n",
      "                  'WMAP K',\n",
      "                  'WMAP Q',\n",
      "                  'WMAP V',\n",
      "                  'WMAP W',\n",
      "                  'COBE DIRBE/AAM',\n",
      "                  'COBE DIRBE/ZSMA',\n",
      "                  'CO',\n",
      "                  'GB6 (4850MHz)',\n",
      "                  'VLA FIRST (1.4 GHz)',\n",
      "                  'NVSS',\n",
      "                  'Stripe82VLA',\n",
      "                  '1420MHz (Bonn)',\n",
      "                  'HI4PI',\n",
      "                  'EBHIS',\n",
      "                  'nH',\n",
      "                  'SUMSS 843 MHz',\n",
      "                  '0408MHz',\n",
      "                  'WENSS',\n",
      "                  'TGSS ADR1',\n",
      "                  'VLSSr',\n",
      "                  '0035MHz',\n",
      "                  'GOODS: Chandra ACIS HB',\n",
      "                  'GOODS: Chandra ACIS FB',\n",
      "                  'GOODS: Chandra ACIS SB',\n",
      "                  'GOODS: VLT VIMOS U',\n",
      "                  'GOODS: VLT VIMOS R',\n",
      "                  'GOODS: HST ACS B',\n",
      "                  'GOODS: HST ACS V',\n",
      "                  'GOODS: HST ACS I',\n",
      "                  'GOODS: HST ACS Z',\n",
      "                  'Hawaii HDF U',\n",
      "                  'Hawaii HDF B',\n",
      "                  'Hawaii HDF V0201',\n",
      "                  'Hawaii HDF V0401',\n",
      "                  'Hawaii HDF R',\n",
      "                  'Hawaii HDF I',\n",
      "                  'Hawaii HDF z',\n",
      "                  'Hawaii HDF HK',\n",
      "                  'GOODS: HST NICMOS',\n",
      "                  'GOODS: VLT ISAAC J',\n",
      "                  'GOODS: VLT ISAAC H',\n",
      "                  'GOODS: VLT ISAAC Ks',\n",
      "                  'HUDF: VLT ISAAC Ks',\n",
      "                  'GOODS: Spitzer IRAC 3.6',\n",
      "                  'GOODS: Spitzer IRAC 4.5',\n",
      "                  'GOODS: Spitzer IRAC 5.8',\n",
      "                  'GOODS: Spitzer IRAC 8.0',\n",
      "                  'GOODS: Spitzer MIPS 24',\n",
      "                  'GOODS: Herschel 100',\n",
      "                  'GOODS: Herschel 160',\n",
      "                  'GOODS: Herschel 250',\n",
      "                  'GOODS: Herschel 350',\n",
      "                  'GOODS: Herschel 500',\n",
      "                  'CDFS: LESS',\n",
      "                  'GOODS: VLA North',\n",
      "                  'None '],\n",
      " 'overlay_green': ['None \\n'\n",
      "                   ' Fermi 5Fermi 4Fermi 3Fermi 2Fermi 1EGRET (3D)EGRET <100 '\n",
      "                   'MeVEGRET >100 MeVCOMPTELINT GAL 17-35 FluxINT GAL 17-60 '\n",
      "                   'FluxINT GAL 35-80 FluxINTEGRAL/SPI GCGRANAT/SIGMARXTE '\n",
      "                   'Allsky 3-8keV FluxRXTE Allsky 3-20keV FluxRXTE Allsky '\n",
      "                   '8-20keV FluxBAT SNR 14-195BAT SNR 14-20BAT SNR 20-24BAT '\n",
      "                   'SNR 24-35BAT SNR 35-50BAT SNR 50-75BAT SNR 75-100BAT SNR '\n",
      "                   '100-150BAT SNR '\n",
      "                   '150-195SwiftXRTCntSwiftXRTExpSwiftXRTIntHEAO 1 A-2RASS-Cnt '\n",
      "                   'SoftRASS-Cnt HardRASS-Cnt BroadPSPC 2.0 Deg-IntPSPC 1.0 '\n",
      "                   'Deg-IntPSPC 0.6 Deg-IntHRIRASS Background 1RASS Background '\n",
      "                   '2RASS Background 3RASS Background 4RASS Background 5RASS '\n",
      "                   'Background 6RASS Background 7GALEX Near UVGALEX Far '\n",
      "                   'UVROSAT WFC F1ROSAT WFC F2EUVE 83 AEUVE 171 AEUVE 405 '\n",
      "                   'AEUVE 555 ADSSDSS1 BlueDSS1 RedDSS2 RedDSS2 BlueDSS2 '\n",
      "                   'IRSDSSgSDSSiSDSSrSDSSuSDSSzSDSSdr7gSDSSdr7iSDSSdr7rSDSSdr7uSDSSdr7zMellinger '\n",
      "                   'RedMellinger GreenMellinger BlueNEATH-Alpha CompSHASSA '\n",
      "                   'HSHASSA CCSHASSA CSHASSA SmIRIS  12IRIS  25IRIS  60IRIS '\n",
      "                   '100SFD100mSFD Dust MapIRAS  12 micronIRAS  25 micronIRAS  '\n",
      "                   '60 micronIRAS 100 '\n",
      "                   'micron2MASS-J2MASS-H2MASS-KUKIDSS-YUKIDSS-JUKIDSS-HUKIDSS-KWISE '\n",
      "                   '3.4WISE 4.6WISE 12WISE 22AKARI N60AKARI WIDE-SAKARI '\n",
      "                   'WIDE-LAKARI N160Planck 857Planck 545Planck 353Planck '\n",
      "                   '217Planck 143Planck 100Planck 070Planck 044Planck 030WMAP '\n",
      "                   'ILCWMAP KaWMAP KWMAP QWMAP VWMAP WCOBE DIRBE/AAMCOBE '\n",
      "                   'DIRBE/ZSMACOGB6 (4850MHz)VLA FIRST (1.4 '\n",
      "                   'GHz)NVSSStripe82VLA1420MHz (Bonn)HI4PIEBHISnHSUMSS 843 '\n",
      "                   'MHz0408MHzWENSSTGSS ADR1VLSSr0035MHzGOODS: Chandra ACIS '\n",
      "                   'HBGOODS: Chandra ACIS FBGOODS: Chandra ACIS SBGOODS: VLT '\n",
      "                   'VIMOS UGOODS: VLT VIMOS RGOODS: HST ACS BGOODS: HST ACS '\n",
      "                   'VGOODS: HST ACS IGOODS: HST ACS ZHawaii HDF UHawaii HDF '\n",
      "                   'BHawaii HDF V0201Hawaii HDF V0401Hawaii HDF RHawaii HDF '\n",
      "                   'IHawaii HDF zHawaii HDF HKGOODS: HST NICMOSGOODS: VLT '\n",
      "                   'ISAAC JGOODS: VLT ISAAC HGOODS: VLT ISAAC KsHUDF: VLT '\n",
      "                   'ISAAC KsGOODS: Spitzer IRAC 3.6GOODS: Spitzer IRAC '\n",
      "                   '4.5GOODS: Spitzer IRAC 5.8GOODS: Spitzer IRAC 8.0GOODS: '\n",
      "                   'Spitzer MIPS 24GOODS: Herschel 100GOODS: Herschel '\n",
      "                   '160GOODS: Herschel 250GOODS: Herschel 350GOODS: Herschel '\n",
      "                   '500CDFS: LESSGOODS: VLA North\\n',\n",
      "                   'Fermi 5',\n",
      "                   'Fermi 4',\n",
      "                   'Fermi 3',\n",
      "                   'Fermi 2',\n",
      "                   'Fermi 1',\n",
      "                   'EGRET (3D)',\n",
      "                   'EGRET <100 MeV',\n",
      "                   'EGRET >100 MeV',\n",
      "                   'COMPTEL',\n",
      "                   'INT GAL 17-35 Flux',\n",
      "                   'INT GAL 17-60 Flux',\n",
      "                   'INT GAL 35-80 Flux',\n",
      "                   'INTEGRAL/SPI GC',\n",
      "                   'GRANAT/SIGMA',\n",
      "                   'RXTE Allsky 3-8keV Flux',\n",
      "                   'RXTE Allsky 3-20keV Flux',\n",
      "                   'RXTE Allsky 8-20keV Flux',\n",
      "                   'BAT SNR 14-195',\n",
      "                   'BAT SNR 14-20',\n",
      "                   'BAT SNR 20-24',\n",
      "                   'BAT SNR 24-35',\n",
      "                   'BAT SNR 35-50',\n",
      "                   'BAT SNR 50-75',\n",
      "                   'BAT SNR 75-100',\n",
      "                   'BAT SNR 100-150',\n",
      "                   'BAT SNR 150-195',\n",
      "                   'SwiftXRTCnt',\n",
      "                   'SwiftXRTExp',\n",
      "                   'SwiftXRTInt',\n",
      "                   'HEAO 1 A-2',\n",
      "                   'RASS-Cnt Soft',\n",
      "                   'RASS-Cnt Hard',\n",
      "                   'RASS-Cnt Broad',\n",
      "                   'PSPC 2.0 Deg-Int',\n",
      "                   'PSPC 1.0 Deg-Int',\n",
      "                   'PSPC 0.6 Deg-Int',\n",
      "                   'HRI',\n",
      "                   'RASS Background 1',\n",
      "                   'RASS Background 2',\n",
      "                   'RASS Background 3',\n",
      "                   'RASS Background 4',\n",
      "                   'RASS Background 5',\n",
      "                   'RASS Background 6',\n",
      "                   'RASS Background 7',\n",
      "                   'GALEX Near UV',\n",
      "                   'GALEX Far UV',\n",
      "                   'ROSAT WFC F1',\n",
      "                   'ROSAT WFC F2',\n",
      "                   'EUVE 83 A',\n",
      "                   'EUVE 171 A',\n",
      "                   'EUVE 405 A',\n",
      "                   'EUVE 555 A',\n",
      "                   'DSS',\n",
      "                   'DSS1 Blue',\n",
      "                   'DSS1 Red',\n",
      "                   'DSS2 Red',\n",
      "                   'DSS2 Blue',\n",
      "                   'DSS2 IR',\n",
      "                   'SDSSg',\n",
      "                   'SDSSi',\n",
      "                   'SDSSr',\n",
      "                   'SDSSu',\n",
      "                   'SDSSz',\n",
      "                   'SDSSdr7g',\n",
      "                   'SDSSdr7i',\n",
      "                   'SDSSdr7r',\n",
      "                   'SDSSdr7u',\n",
      "                   'SDSSdr7z',\n",
      "                   'Mellinger Red',\n",
      "                   'Mellinger Green',\n",
      "                   'Mellinger Blue',\n",
      "                   'NEAT',\n",
      "                   'H-Alpha Comp',\n",
      "                   'SHASSA H',\n",
      "                   'SHASSA CC',\n",
      "                   'SHASSA C',\n",
      "                   'SHASSA Sm',\n",
      "                   'IRIS  12',\n",
      "                   'IRIS  25',\n",
      "                   'IRIS  60',\n",
      "                   'IRIS 100',\n",
      "                   'SFD100m',\n",
      "                   'SFD Dust Map',\n",
      "                   'IRAS  12 micron',\n",
      "                   'IRAS  25 micron',\n",
      "                   'IRAS  60 micron',\n",
      "                   'IRAS 100 micron',\n",
      "                   '2MASS-J',\n",
      "                   '2MASS-H',\n",
      "                   '2MASS-K',\n",
      "                   'UKIDSS-Y',\n",
      "                   'UKIDSS-J',\n",
      "                   'UKIDSS-H',\n",
      "                   'UKIDSS-K',\n",
      "                   'WISE 3.4',\n",
      "                   'WISE 4.6',\n",
      "                   'WISE 12',\n",
      "                   'WISE 22',\n",
      "                   'AKARI N60',\n",
      "                   'AKARI WIDE-S',\n",
      "                   'AKARI WIDE-L',\n",
      "                   'AKARI N160',\n",
      "                   'Planck 857',\n",
      "                   'Planck 545',\n",
      "                   'Planck 353',\n",
      "                   'Planck 217',\n",
      "                   'Planck 143',\n",
      "                   'Planck 100',\n",
      "                   'Planck 070',\n",
      "                   'Planck 044',\n",
      "                   'Planck 030',\n",
      "                   'WMAP ILC',\n",
      "                   'WMAP Ka',\n",
      "                   'WMAP K',\n",
      "                   'WMAP Q',\n",
      "                   'WMAP V',\n",
      "                   'WMAP W',\n",
      "                   'COBE DIRBE/AAM',\n",
      "                   'COBE DIRBE/ZSMA',\n",
      "                   'CO',\n",
      "                   'GB6 (4850MHz)',\n",
      "                   'VLA FIRST (1.4 GHz)',\n",
      "                   'NVSS',\n",
      "                   'Stripe82VLA',\n",
      "                   '1420MHz (Bonn)',\n",
      "                   'HI4PI',\n",
      "                   'EBHIS',\n",
      "                   'nH',\n",
      "                   'SUMSS 843 MHz',\n",
      "                   '0408MHz',\n",
      "                   'WENSS',\n",
      "                   'TGSS ADR1',\n",
      "                   'VLSSr',\n",
      "                   '0035MHz',\n",
      "                   'GOODS: Chandra ACIS HB',\n",
      "                   'GOODS: Chandra ACIS FB',\n",
      "                   'GOODS: Chandra ACIS SB',\n",
      "                   'GOODS: VLT VIMOS U',\n",
      "                   'GOODS: VLT VIMOS R',\n",
      "                   'GOODS: HST ACS B',\n",
      "                   'GOODS: HST ACS V',\n",
      "                   'GOODS: HST ACS I',\n",
      "                   'GOODS: HST ACS Z',\n",
      "                   'Hawaii HDF U',\n",
      "                   'Hawaii HDF B',\n",
      "                   'Hawaii HDF V0201',\n",
      "                   'Hawaii HDF V0401',\n",
      "                   'Hawaii HDF R',\n",
      "                   'Hawaii HDF I',\n",
      "                   'Hawaii HDF z',\n",
      "                   'Hawaii HDF HK',\n",
      "                   'GOODS: HST NICMOS',\n",
      "                   'GOODS: VLT ISAAC J',\n",
      "                   'GOODS: VLT ISAAC H',\n",
      "                   'GOODS: VLT ISAAC Ks',\n",
      "                   'HUDF: VLT ISAAC Ks',\n",
      "                   'GOODS: Spitzer IRAC 3.6',\n",
      "                   'GOODS: Spitzer IRAC 4.5',\n",
      "                   'GOODS: Spitzer IRAC 5.8',\n",
      "                   'GOODS: Spitzer IRAC 8.0',\n",
      "                   'GOODS: Spitzer MIPS 24',\n",
      "                   'GOODS: Herschel 100',\n",
      "                   'GOODS: Herschel 160',\n",
      "                   'GOODS: Herschel 250',\n",
      "                   'GOODS: Herschel 350',\n",
      "                   'GOODS: Herschel 500',\n",
      "                   'CDFS: LESS',\n",
      "                   'GOODS: VLA North'],\n",
      " 'overlay_red': ['None \\n'\n",
      "                 ' Fermi 5Fermi 4Fermi 3Fermi 2Fermi 1EGRET (3D)EGRET <100 '\n",
      "                 'MeVEGRET >100 MeVCOMPTELINT GAL 17-35 FluxINT GAL 17-60 '\n",
      "                 'FluxINT GAL 35-80 FluxINTEGRAL/SPI GCGRANAT/SIGMARXTE Allsky '\n",
      "                 '3-8keV FluxRXTE Allsky 3-20keV FluxRXTE Allsky 8-20keV '\n",
      "                 'FluxBAT SNR 14-195BAT SNR 14-20BAT SNR 20-24BAT SNR 24-35BAT '\n",
      "                 'SNR 35-50BAT SNR 50-75BAT SNR 75-100BAT SNR 100-150BAT SNR '\n",
      "                 '150-195SwiftXRTCntSwiftXRTExpSwiftXRTIntHEAO 1 A-2RASS-Cnt '\n",
      "                 'SoftRASS-Cnt HardRASS-Cnt BroadPSPC 2.0 Deg-IntPSPC 1.0 '\n",
      "                 'Deg-IntPSPC 0.6 Deg-IntHRIRASS Background 1RASS Background '\n",
      "                 '2RASS Background 3RASS Background 4RASS Background 5RASS '\n",
      "                 'Background 6RASS Background 7GALEX Near UVGALEX Far UVROSAT '\n",
      "                 'WFC F1ROSAT WFC F2EUVE 83 AEUVE 171 AEUVE 405 AEUVE 555 '\n",
      "                 'ADSSDSS1 BlueDSS1 RedDSS2 RedDSS2 BlueDSS2 '\n",
      "                 'IRSDSSgSDSSiSDSSrSDSSuSDSSzSDSSdr7gSDSSdr7iSDSSdr7rSDSSdr7uSDSSdr7zMellinger '\n",
      "                 'RedMellinger GreenMellinger BlueNEATH-Alpha CompSHASSA '\n",
      "                 'HSHASSA CCSHASSA CSHASSA SmIRIS  12IRIS  25IRIS  60IRIS '\n",
      "                 '100SFD100mSFD Dust MapIRAS  12 micronIRAS  25 micronIRAS  60 '\n",
      "                 'micronIRAS 100 '\n",
      "                 'micron2MASS-J2MASS-H2MASS-KUKIDSS-YUKIDSS-JUKIDSS-HUKIDSS-KWISE '\n",
      "                 '3.4WISE 4.6WISE 12WISE 22AKARI N60AKARI WIDE-SAKARI '\n",
      "                 'WIDE-LAKARI N160Planck 857Planck 545Planck 353Planck '\n",
      "                 '217Planck 143Planck 100Planck 070Planck 044Planck 030WMAP '\n",
      "                 'ILCWMAP KaWMAP KWMAP QWMAP VWMAP WCOBE DIRBE/AAMCOBE '\n",
      "                 'DIRBE/ZSMACOGB6 (4850MHz)VLA FIRST (1.4 '\n",
      "                 'GHz)NVSSStripe82VLA1420MHz (Bonn)HI4PIEBHISnHSUMSS 843 '\n",
      "                 'MHz0408MHzWENSSTGSS ADR1VLSSr0035MHzGOODS: Chandra ACIS '\n",
      "                 'HBGOODS: Chandra ACIS FBGOODS: Chandra ACIS SBGOODS: VLT '\n",
      "                 'VIMOS UGOODS: VLT VIMOS RGOODS: HST ACS BGOODS: HST ACS '\n",
      "                 'VGOODS: HST ACS IGOODS: HST ACS ZHawaii HDF UHawaii HDF '\n",
      "                 'BHawaii HDF V0201Hawaii HDF V0401Hawaii HDF RHawaii HDF '\n",
      "                 'IHawaii HDF zHawaii HDF HKGOODS: HST NICMOSGOODS: VLT ISAAC '\n",
      "                 'JGOODS: VLT ISAAC HGOODS: VLT ISAAC KsHUDF: VLT ISAAC '\n",
      "                 'KsGOODS: Spitzer IRAC 3.6GOODS: Spitzer IRAC 4.5GOODS: '\n",
      "                 'Spitzer IRAC 5.8GOODS: Spitzer IRAC 8.0GOODS: Spitzer MIPS '\n",
      "                 '24GOODS: Herschel 100GOODS: Herschel 160GOODS: Herschel '\n",
      "                 '250GOODS: Herschel 350GOODS: Herschel 500CDFS: LESSGOODS: '\n",
      "                 'VLA North\\n',\n",
      "                 'Fermi 5',\n",
      "                 'Fermi 4',\n",
      "                 'Fermi 3',\n",
      "                 'Fermi 2',\n",
      "                 'Fermi 1',\n",
      "                 'EGRET (3D)',\n",
      "                 'EGRET <100 MeV',\n",
      "                 'EGRET >100 MeV',\n",
      "                 'COMPTEL',\n",
      "                 'INT GAL 17-35 Flux',\n",
      "                 'INT GAL 17-60 Flux',\n",
      "                 'INT GAL 35-80 Flux',\n",
      "                 'INTEGRAL/SPI GC',\n",
      "                 'GRANAT/SIGMA',\n",
      "                 'RXTE Allsky 3-8keV Flux',\n",
      "                 'RXTE Allsky 3-20keV Flux',\n",
      "                 'RXTE Allsky 8-20keV Flux',\n",
      "                 'BAT SNR 14-195',\n",
      "                 'BAT SNR 14-20',\n",
      "                 'BAT SNR 20-24',\n",
      "                 'BAT SNR 24-35',\n",
      "                 'BAT SNR 35-50',\n",
      "                 'BAT SNR 50-75',\n",
      "                 'BAT SNR 75-100',\n",
      "                 'BAT SNR 100-150',\n",
      "                 'BAT SNR 150-195',\n",
      "                 'SwiftXRTCnt',\n",
      "                 'SwiftXRTExp',\n",
      "                 'SwiftXRTInt',\n",
      "                 'HEAO 1 A-2',\n",
      "                 'RASS-Cnt Soft',\n",
      "                 'RASS-Cnt Hard',\n",
      "                 'RASS-Cnt Broad',\n",
      "                 'PSPC 2.0 Deg-Int',\n",
      "                 'PSPC 1.0 Deg-Int',\n",
      "                 'PSPC 0.6 Deg-Int',\n",
      "                 'HRI',\n",
      "                 'RASS Background 1',\n",
      "                 'RASS Background 2',\n",
      "                 'RASS Background 3',\n",
      "                 'RASS Background 4',\n",
      "                 'RASS Background 5',\n",
      "                 'RASS Background 6',\n",
      "                 'RASS Background 7',\n",
      "                 'GALEX Near UV',\n",
      "                 'GALEX Far UV',\n",
      "                 'ROSAT WFC F1',\n",
      "                 'ROSAT WFC F2',\n",
      "                 'EUVE 83 A',\n",
      "                 'EUVE 171 A',\n",
      "                 'EUVE 405 A',\n",
      "                 'EUVE 555 A',\n",
      "                 'DSS',\n",
      "                 'DSS1 Blue',\n",
      "                 'DSS1 Red',\n",
      "                 'DSS2 Red',\n",
      "                 'DSS2 Blue',\n",
      "                 'DSS2 IR',\n",
      "                 'SDSSg',\n",
      "                 'SDSSi',\n",
      "                 'SDSSr',\n",
      "                 'SDSSu',\n",
      "                 'SDSSz',\n",
      "                 'SDSSdr7g',\n",
      "                 'SDSSdr7i',\n",
      "                 'SDSSdr7r',\n",
      "                 'SDSSdr7u',\n",
      "                 'SDSSdr7z',\n",
      "                 'Mellinger Red',\n",
      "                 'Mellinger Green',\n",
      "                 'Mellinger Blue',\n",
      "                 'NEAT',\n",
      "                 'H-Alpha Comp',\n",
      "                 'SHASSA H',\n",
      "                 'SHASSA CC',\n",
      "                 'SHASSA C',\n",
      "                 'SHASSA Sm',\n",
      "                 'IRIS  12',\n",
      "                 'IRIS  25',\n",
      "                 'IRIS  60',\n",
      "                 'IRIS 100',\n",
      "                 'SFD100m',\n",
      "                 'SFD Dust Map',\n",
      "                 'IRAS  12 micron',\n",
      "                 'IRAS  25 micron',\n",
      "                 'IRAS  60 micron',\n",
      "                 'IRAS 100 micron',\n",
      "                 '2MASS-J',\n",
      "                 '2MASS-H',\n",
      "                 '2MASS-K',\n",
      "                 'UKIDSS-Y',\n",
      "                 'UKIDSS-J',\n",
      "                 'UKIDSS-H',\n",
      "                 'UKIDSS-K',\n",
      "                 'WISE 3.4',\n",
      "                 'WISE 4.6',\n",
      "                 'WISE 12',\n",
      "                 'WISE 22',\n",
      "                 'AKARI N60',\n",
      "                 'AKARI WIDE-S',\n",
      "                 'AKARI WIDE-L',\n",
      "                 'AKARI N160',\n",
      "                 'Planck 857',\n",
      "                 'Planck 545',\n",
      "                 'Planck 353',\n",
      "                 'Planck 217',\n",
      "                 'Planck 143',\n",
      "                 'Planck 100',\n",
      "                 'Planck 070',\n",
      "                 'Planck 044',\n",
      "                 'Planck 030',\n",
      "                 'WMAP ILC',\n",
      "                 'WMAP Ka',\n",
      "                 'WMAP K',\n",
      "                 'WMAP Q',\n",
      "                 'WMAP V',\n",
      "                 'WMAP W',\n",
      "                 'COBE DIRBE/AAM',\n",
      "                 'COBE DIRBE/ZSMA',\n",
      "                 'CO',\n",
      "                 'GB6 (4850MHz)',\n",
      "                 'VLA FIRST (1.4 GHz)',\n",
      "                 'NVSS',\n",
      "                 'Stripe82VLA',\n",
      "                 '1420MHz (Bonn)',\n",
      "                 'HI4PI',\n",
      "                 'EBHIS',\n",
      "                 'nH',\n",
      "                 'SUMSS 843 MHz',\n",
      "                 '0408MHz',\n",
      "                 'WENSS',\n",
      "                 'TGSS ADR1',\n",
      "                 'VLSSr',\n",
      "                 '0035MHz',\n",
      "                 'GOODS: Chandra ACIS HB',\n",
      "                 'GOODS: Chandra ACIS FB',\n",
      "                 'GOODS: Chandra ACIS SB',\n",
      "                 'GOODS: VLT VIMOS U',\n",
      "                 'GOODS: VLT VIMOS R',\n",
      "                 'GOODS: HST ACS B',\n",
      "                 'GOODS: HST ACS V',\n",
      "                 'GOODS: HST ACS I',\n",
      "                 'GOODS: HST ACS Z',\n",
      "                 'Hawaii HDF U',\n",
      "                 'Hawaii HDF B',\n",
      "                 'Hawaii HDF V0201',\n",
      "                 'Hawaii HDF V0401',\n",
      "                 'Hawaii HDF R',\n",
      "                 'Hawaii HDF I',\n",
      "                 'Hawaii HDF z',\n",
      "                 'Hawaii HDF HK',\n",
      "                 'GOODS: HST NICMOS',\n",
      "                 'GOODS: VLT ISAAC J',\n",
      "                 'GOODS: VLT ISAAC H',\n",
      "                 'GOODS: VLT ISAAC Ks',\n",
      "                 'HUDF: VLT ISAAC Ks',\n",
      "                 'GOODS: Spitzer IRAC 3.6',\n",
      "                 'GOODS: Spitzer IRAC 4.5',\n",
      "                 'GOODS: Spitzer IRAC 5.8',\n",
      "                 'GOODS: Spitzer IRAC 8.0',\n",
      "                 'GOODS: Spitzer MIPS 24',\n",
      "                 'GOODS: Herschel 100',\n",
      "                 'GOODS: Herschel 160',\n",
      "                 'GOODS: Herschel 250',\n",
      "                 'GOODS: Herschel 350',\n",
      "                 'GOODS: Herschel 500',\n",
      "                 'CDFS: LESS',\n",
      "                 'GOODS: VLA North']}\n"
     ]
    }
   ],
   "source": [
    "from astroquery.skyview import SkyView\n",
    "SkyView.list_surveys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['https://skyview.gsfc.nasa.gov/tempspace/fits/skv15640288189951.fits']\n"
     ]
    }
   ],
   "source": [
    "res=SkyView.get_image_list(position='M100',survey=['DSS2 Red'])\n",
    "print(res)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('opt2.fits', <http.client.HTTPMessage at 0x1158bff98>)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "urllib.request.urlretrieve(res[0],'opt2.fits')\n",
    "#urllib.parse(res[0],'opt2.fits')\n",
    "#urllib.urlretrieve(res[0],'opt2.fits')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(300, 300)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hdulist = fits.open(\"opt2.fits\")\n",
    "imagen=hdulist[0]\n",
    "imagen.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO: Auto-setting vmin to  2.697e+03 [aplpy.core]\n",
      "INFO: Auto-setting vmax to  2.446e+04 [aplpy.core]\n"
     ]
    },
    {
     "data": {
      "image/png": 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TPXnw+VNfVup7TOML5+rqKny5mx2+UKKg6l5Wb/tam4mKiqHa4H2C6hivC7alpXrBslRb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\n+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z+2Uk81/808L2KYfJ7yKXktNyb5TDvGiBksWKc8V+cTNwczs8TFxYX1K3RST+rvdnR0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6sT6PVC+KM4wjPigvvxYHny/Xgz8E/n2qgOsRp6RSzUWHGR+BQHFbKs9gfl9cN+VpbnNxY2Nj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\nNdkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1158e3208>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "opt = hdulist[0] \n",
    "fig = aplpy.FITSFigure(opt)\n",
    "fig.show_grayscale()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "23a0eea67df24918bbe43126f46e37ef",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "A Jupyter Widget"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "from astropy.wcs import WCS\n",
    "from matplotlib.patches import Circle\n",
    "ra=opt.header['CRVAL1']\n",
    "dec=opt.header['CRVAL2']\n",
    "mywcs=WCS(opt.header)\n",
    "max_radius=0.09\n",
    "\n",
    "def select_radius(radius=max_radius):\n",
    "    ax=plt.subplot(111,projection=mywcs)\n",
    "    ax.imshow(opt.data,cmap=\"gray\",origin='lower')\n",
    "    cc=Circle((ra,dec),radius=radius,edgecolor=\"green\",facecolor=\"none\",transform=ax.get_transform('fk5'))\n",
    "    ax.add_patch(cc)\n",
    "    \n",
    "mycirc=interact(select_radius,radius=(0.0,max_radius,max_radius/1000))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "185.728 15.8218\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0.03618"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "limits = mycirc.widget.kwargs\n",
    "rad    = limits['radius']\n",
    "print(ra,dec)\n",
    "rad"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I/324 : The Initial Gaia Source List (IGSL) (Smart, 2013)\n",
      "I/337 : Gaia DR1 (Gaia Collaboration, 2016)\n",
      "I/339 : Hot Stuff for One Year (HSOY) (Altmann+, 2017)\n",
      "I/340 : UCAC5 Catalogue (Zacharias+ 2017)\n",
      "VI/137 : GaiaSimu Universe Model Snapshot (Robin+, 2012)\n",
      "J/ApJ/811/85 : RVs & V-band LCs of probable members of Cyg OB2 (Kiminki+, 2015)\n",
      "J/ApJ/831/L6 : Eclipsing binary parallaxes with Gaia data (Stassun+, 2016)\n",
      "J/ApJ/832/L18 : Gaia's DR1 parallaxes vs previous measurements (Jao+, 2016)\n",
      "J/ApJ/833/119 : Distances of Gaia DR1 TGAS sources (Astraatmadja+, 2016)\n",
      "J/A+A/366/1003 : 8500-8750{AA} high resolution spectroscopy. III. (Munari+, 2001)\n",
      "J/A+A/406/751 : Close encounters of asteroids 2003-2020 (Fienga+, 2003)\n",
      "J/A+A/406/995 : 8500-8750{AA} high resolution spectroscopy. IV. (Marrese+, 2003)\n",
      "J/A+A/520/A113 : VLBI detection of 398 extragalactic radio sources (Bourda+, 2010)\n",
      "J/A+A/523/A48 : Gaia photometry (Jordi+, 2010)\n",
      "J/A+A/526/A102 : VLBI imaging of 105 extragalactic radio sources (Bourda+, 2011)\n",
      "J/A+A/538/A38 : Synthetic galaxy spectra (Karampelas+, 2012)\n",
      "J/A+A/546/A61 : Radial velocities for XHIP catalogue (de Bruijne+, 2012)\n",
      "J/A+A/550/A103 : Model 1D (LHD) and 3D (CO5BOLD) spectra (Allende Prieto+, 2013)\n",
      "J/A+A/552/A64 : Gaia-RVS standards (Soubiran+, 2013)\n",
      "J/A+A/552/A98 : Optical monitoring of extragalactic sources (Taris+, 2013)\n",
      "J/A+A/561/A94 : Velocities and photometry in Trumpler 20 (Donati+, 2014)\n",
      "J/A+A/563/A94 : Kinematics of the Gamma Vel cluster (Jeffries+, 2014)\n",
      "J/A+A/564/A133 : Gaia FGK benchmark stars: metallicity (Jofre+, 2014)\n",
      "J/A+A/565/A11 : Gaia photometry for white dwarfs (Carrasco+, 2014)\n",
      "J/A+A/566/A50 : Classification of stellar spectra 644-681nm (Damiani+, 2014)\n",
      "J/A+A/566/A98 : The Gaia Benchmark Stars - Library (Blanco-Cuaresma+, 2014)\n",
      "J/A+A/567/A55 : Metallicity of the {gamma} Vel cluster (Spina+, 2014)\n",
      "J/A+A/569/A17 : Gaia-ESO Survey: NGC6705 (Cantat-Gaudin+, 2014)\n",
      "J/A+A/572/A33 : Abundances from Gaia-ESO Survey (Mikolaitis+, 2014)\n",
      "J/A+A/573/A55 : Gaia-ESO Survey: Tr 20, NGC4815, NGC6705 (Tautvaisiene+, 2015)\n",
      "J/A+A/573/A115 : Radial velocities in seven globular clusters (Lardo+, 2015)\n",
      "J/A+A/574/L7 : Gaia-ESO Survey: Li-rich stars in NGC2547 (Sacco+, 2015)\n",
      "J/A+A/575/A4 : Activity and accretion in {gamma} Vel and Cha I (Frasca+, 2015)\n",
      "J/A+A/575/A26 : Properties of the Population II star HD 140283 (Creevey+, 2015)\n",
      "J/A+A/580/A75 : Velocity precision in the Gaia-ESO Survey (Jackson+, 2015)\n",
      "J/A+A/581/A52 : Gaia-ESO Survey: H{alpha} emission stars catalogue (Traven+, 2015)\n",
      "J/A+A/582/A81 : Gaia FGK benchmark stars: abundances (Jofre+, 2015)\n",
      "J/A+A/583/A59 : Gaia-FUN-SSO network. Apophis campaign (Thuillot+, 2015)\n",
      "J/A+A/586/A52 : NGC 2264, NGC 2547 and NGC 2516 stellar radii (Jackson+, 2016)\n",
      "J/A+A/587/A112 : Long term R and V band monitoring of AGN (Taris+, 2016)\n",
      "J/A+A/589/A70 : Gamma Vel cluster membership and IMF (Prisinzano+, 2016)\n",
      "J/A+A/589/A115 : Na and Al abundances of 1303 stars (Smiljanic+, 2016)\n",
      "J/A+A/590/A78 : NGC2264 weak-line T Tauri lithium abundances (Bouvier+, 2016)\n",
      "J/A+A/591/A37 : Gaia-ESO Survey. Parameters for cluster members (Jacobson+, 2016)\n",
      "J/A+A/591/A74 : Nebular emission lines towards NGC3372 center (Damiani+, 2016)\n",
      "J/A+A/592/A70 : Gaia FGK stars: low-metallicities candidates (Hawkins+, 2016)\n",
      "J/A+A/594/A120 : Gaia-ESO Survey: Hydrogen lines in red giants (Bergemann+, 2016)\n",
      "J/A+A/597/A10 : SEP stars radial velocities (Fremat+, 2017)\n",
      "J/A+A/598/A5 : Gaia-ESO Survey iDR4 calibrators (Pancino+, 2017)\n",
      "J/A+A/598/A68 : Gaia-ESO Survey. Trumpler 23 (Overbeek+, 2017)\n",
      "J/A+A/600/A50 : Catalog of hot subdwarf stars (Geier+, 2017)\n",
      "J/A+A/601/A9 : HD17674, HD29021, and HD42012 radial velocities (Rey+, 2017)\n",
      "J/A+A/601/A19 : Gaia DR1 open cluster members (Gaia Collaboration+, 2017)\n",
      "J/A+A/601/A56 : NGC 6802 dwarf cluster members and non-members (Tang+, 2017)\n",
      "J/A+A/601/A70 : GES: pre-main-sequence clusters [Fe/H] (Spina+, 2017)\n",
      "J/A+A/601/A97 : Gaia-ESO Survey: Cha I members (Sacco+, 2017)\n",
      "J/A+A/601/A112 : GES iDR4 Mg-Al anticorrelation in GCs (Pancino+, 2017)\n",
      "J/A+A/603/A2 : Gaia-ESO Survey abundances radial distribution (Magrini+, 2017)\n",
      "J/A+A/603/A81 : Trumpler 14 and 16 in the Carina nebula (Damiani+, 2017)\n",
      "J/A+A/604/A128 : S abundances for 1301 stars from GES (Duffau+, 2017)\n",
      "J/A+AS/141/141 : 8500-8750{AA} high resolution spectroscopy. II. (Munari+, 2000)\n",
      "J/AJ/140/1758 : Spectral atlas of peculiar stars (Tomasella+, 2010)\n",
      "J/AJ/151/79 : Radio fluxes of 195 ICRF2-Gaia transfer sources (Le Bail+, 2016)\n",
      "J/AJ/152/180 : Bolometric fluxes of eclipsing binaries in Tycho-2 (Stassun+, 2016)\n",
      "J/MNRAS/418/863 : NLTE corrections for Mg and Ca lines (Merle+ 2011)\n",
      "J/MNRAS/426/1767 : Gaia spectrophotometric standard stars I. (Pancino+, 2012)\n",
      "J/MNRAS/430/2797 : ICRF2 sources of the Rio survey (Assafin+, 2013)\n",
      "J/MNRAS/441/3127 : FeI oscillator strengths for Gaia-ESO (Ruffoni+, 2014)\n",
      "J/MNRAS/458/3272 : Gaia SB2 radial velocity curves (Kiefer+, 2016)\n",
      "J/MNRAS/462/3616 : Gaia SPSS variability monitoring (Marinoni+, 2016)\n",
      "J/MNRAS/465/3203 : GALAH observational overview ((Martell+, 2017)\n",
      "J/MNRAS/471/770 : Parameters and IR excesses of Gaia DR1 stars (McDonald+, 2017)\n",
      "J/AcA/62/219 : OGLE: Gaia South Ecliptic Pole Field (Soszynski+, 2012)\n"
     ]
    }
   ],
   "source": [
    "from astroquery.vizier import Vizier\n",
    "catalog_list = Vizier.find_catalogs(keywords=['GAIA'])\n",
    "for key,item in catalog_list.items():\n",
    "    print(key+\" : \"+item.description)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from astropy.coordinates import SkyCoord\n",
    "import astropy.units as u\n",
    "\n",
    "c = SkyCoord(ra=ra*u.deg, dec=dec*u.deg)\n",
    "#res=Vizier.query_region(c, radius=rad*u.deg, catalog='J/A+A/601/A19')\n",
    "res=Vizier.query_region(c, radius=rad*u.deg, catalog='I/337')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "&lt;Table masked=True length=47&gt;\n",
       "<table id=\"table4512663704-731401\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>idx</th><th>RA_ICRS</th><th>e_RA_ICRS</th><th>DE_ICRS</th><th>e_DE_ICRS</th><th>Source</th><th>Plx</th><th>pmRA</th><th>pmDE</th><th>RADEcor</th><th>Dup</th><th>__FG_</th><th>e__FG_</th><th>__Gmag_</th><th>Var</th></tr></thead>\n",
       "<thead><tr><th></th><th>deg</th><th>mas</th><th>deg</th><th>mas</th><th></th><th>mas</th><th>mas / yr</th><th>mas / yr</th><th></th><th></th><th>e-/s</th><th>e-/s</th><th>mag</th><th></th></tr></thead>\n",
       "<tr><td>0</td><td>185.7381227640</td><td>4.936</td><td>15.8019286598</td><td>3.374</td><td>3945390050828621056</td><td>--</td><td>--</td><td>--</td><td>-0.832</td><td>1</td><td>211</td><td>2.497</td><td>19.714</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>1</td><td>185.7461790790</td><td>48.893</td><td>15.8020492870</td><td>15.002</td><td>3945390149615599488</td><td>--</td><td>--</td><td>--</td><td>-0.939</td><td>0</td><td>166.3</td><td>3.524</td><td>19.972</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>2</td><td>185.7477853061</td><td>54.062</td><td>15.8152513394</td><td>26.222</td><td>3945390153907852032</td><td>--</td><td>--</td><td>--</td><td>-0.974</td><td>0</td><td>190</td><td>3.344</td><td>19.828</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>3</td><td>185.7493264663</td><td>43.634</td><td>15.8153906916</td><td>13.363</td><td>3945390153907852288</td><td>--</td><td>--</td><td>--</td><td>-0.898</td><td>1</td><td>129.7</td><td>3.444</td><td>20.242</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>4</td><td>185.7610081654</td><td>0.842</td><td>15.8251025328</td><td>0.583</td><td>3945390183975337984</td><td>--</td><td>--</td><td>--</td><td>-0.825</td><td>0</td><td>465.3</td><td>3.111</td><td>18.855</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>5</td><td>185.7602402653</td><td>1.023</td><td>15.8141218175</td><td>0.644</td><td>3945390188267574656</td><td>--</td><td>--</td><td>--</td><td>-0.832</td><td>0</td><td>303.8</td><td>2.25</td><td>19.318</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>6</td><td>185.7547099397</td><td>18.597</td><td>15.8133937553</td><td>7.070</td><td>3945390188268042496</td><td>--</td><td>--</td><td>--</td><td>-0.988</td><td>0</td><td>139.6</td><td>2.659</td><td>20.162</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>7</td><td>185.7046419813</td><td>1.077</td><td>15.7980288546</td><td>0.835</td><td>3945576211891358208</td><td>--</td><td>--</td><td>--</td><td>-0.831</td><td>0</td><td>370.4</td><td>3.398</td><td>19.103</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>8</td><td>185.7249346415</td><td>0.286</td><td>15.8110037272</td><td>0.221</td><td>3945577719426402304</td><td>--</td><td>--</td><td>--</td><td>-0.838</td><td>0</td><td>4131</td><td>11.52</td><td>16.485</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>9</td><td>185.6935893549</td><td>34.529</td><td>15.8085003134</td><td>13.298</td><td>3945577758080100224</td><td>--</td><td>--</td><td>--</td><td>-0.956</td><td>0</td><td>93.43</td><td>2.199</td><td>20.599</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>10</td><td>185.7144300294</td><td>5.239</td><td>15.8287362894</td><td>3.651</td><td>3945577788146583936</td><td>--</td><td>--</td><td>--</td><td>-0.872</td><td>0</td><td>233.7</td><td>3.495</td><td>19.603</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>11</td><td>185.7107618637</td><td>20.559</td><td>15.8279136508</td><td>9.692</td><td>3945577792439834624</td><td>--</td><td>--</td><td>--</td><td>-0.875</td><td>0</td><td>126.1</td><td>3.201</td><td>20.273</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>12</td><td>185.7091650094</td><td>19.897</td><td>15.8238360430</td><td>9.647</td><td>3945577792439835264</td><td>--</td><td>--</td><td>--</td><td>-0.761</td><td>0</td><td>122.5</td><td>3.399</td><td>20.304</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>13</td><td>185.7125174610</td><td>6.460</td><td>15.8153320445</td><td>3.725</td><td>3945577792439836800</td><td>--</td><td>--</td><td>--</td><td>-0.872</td><td>0</td><td>156.5</td><td>2.68</td><td>20.038</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>14</td><td>185.7288799555</td><td>2.617</td><td>15.8223057192</td><td>1.787</td><td>3945577822505627392</td><td>--</td><td>--</td><td>--</td><td>-0.845</td><td>0</td><td>6631</td><td>92.66</td><td>15.971</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>15</td><td>185.7291598632</td><td>10.521</td><td>15.8209660196</td><td>7.341</td><td>3945577826799080576</td><td>--</td><td>--</td><td>--</td><td>-0.951</td><td>0</td><td>666.1</td><td>11.77</td><td>18.466</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>16</td><td>185.7311103092</td><td>15.548</td><td>15.8226291091</td><td>9.829</td><td>3945577826799113728</td><td>--</td><td>--</td><td>--</td><td>-0.913</td><td>0</td><td>721.4</td><td>13.99</td><td>18.379</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>17</td><td>185.7298748680</td><td>24.151</td><td>15.8227207079</td><td>20.424</td><td>3945577826799114240</td><td>--</td><td>--</td><td>--</td><td>-0.682</td><td>0</td><td>1458</td><td>129.1</td><td>17.615</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>18</td><td>185.7299880347</td><td>2.100</td><td>15.8235963137</td><td>1.496</td><td>3945577826799116800</td><td>--</td><td>--</td><td>--</td><td>-0.846</td><td>0</td><td>917.4</td><td>9.068</td><td>18.118</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>19</td><td>185.7288343051</td><td>2.505</td><td>15.8236041007</td><td>1.823</td><td>3945577826799117440</td><td>--</td><td>--</td><td>--</td><td>-0.828</td><td>0</td><td>1142</td><td>14.15</td><td>17.881</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>20</td><td>185.7298563452</td><td>2.526</td><td>15.8226395563</td><td>1.986</td><td>3945577826799118336</td><td>--</td><td>--</td><td>--</td><td>-0.791</td><td>0</td><td>1230</td><td>16.33</td><td>17.800</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>21</td><td>185.7310268714</td><td>6.672</td><td>15.8216778623</td><td>3.243</td><td>3945577826799120000</td><td>--</td><td>--</td><td>--</td><td>-0.462</td><td>0</td><td>923.3</td><td>20.75</td><td>18.111</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>22</td><td>185.7272939312</td><td>6.152</td><td>15.8223442651</td><td>4.287</td><td>3945577826799123200</td><td>--</td><td>--</td><td>--</td><td>-0.697</td><td>0</td><td>1226</td><td>18.78</td><td>17.803</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>23</td><td>185.7303901421</td><td>2.904</td><td>15.8203739070</td><td>2.110</td><td>3945577826799124608</td><td>--</td><td>--</td><td>--</td><td>-0.836</td><td>0</td><td>648.8</td><td>9.996</td><td>18.494</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>24</td><td>185.7274235898</td><td>7.388</td><td>15.8213335361</td><td>4.267</td><td>3945577826799125504</td><td>--</td><td>--</td><td>--</td><td>-0.790</td><td>0</td><td>1170</td><td>18.87</td><td>17.854</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>25</td><td>185.7289857557</td><td>11.968</td><td>15.8204863518</td><td>7.489</td><td>3945577826799125888</td><td>--</td><td>--</td><td>--</td><td>-0.635</td><td>0</td><td>1033</td><td>23.09</td><td>17.989</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>26</td><td>185.7279152967</td><td>1.630</td><td>15.8206376009</td><td>1.169</td><td>3945577826799126016</td><td>--</td><td>--</td><td>--</td><td>-0.831</td><td>0</td><td>1032</td><td>10.68</td><td>17.990</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>27</td><td>185.7287936912</td><td>7.507</td><td>15.8199017421</td><td>5.085</td><td>3945577826799126272</td><td>--</td><td>--</td><td>--</td><td>-0.847</td><td>0</td><td>831.6</td><td>14.22</td><td>18.225</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>28</td><td>185.7281439375</td><td>1.486</td><td>15.8199615908</td><td>1.008</td><td>3945577826799126528</td><td>--</td><td>--</td><td>--</td><td>-0.838</td><td>0</td><td>1122</td><td>10.42</td><td>17.900</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>29</td><td>185.7291425473</td><td>3.214</td><td>15.8194398746</td><td>2.148</td><td>3945577826799126656</td><td>--</td><td>--</td><td>--</td><td>-0.840</td><td>0</td><td>818.7</td><td>10.23</td><td>18.242</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>30</td><td>185.7292969571</td><td>17.158</td><td>15.8192959165</td><td>8.867</td><td>3945577826799126912</td><td>--</td><td>--</td><td>--</td><td>-0.536</td><td>0</td><td>597.7</td><td>23.53</td><td>18.584</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>31</td><td>185.7427640272</td><td>1.149</td><td>15.8196351546</td><td>0.815</td><td>3945577826799128576</td><td>--</td><td>--</td><td>--</td><td>-0.835</td><td>0</td><td>419.8</td><td>2.932</td><td>18.967</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>32</td><td>185.7384854704</td><td>11.933</td><td>15.8178840149</td><td>5.432</td><td>3945577826799250432</td><td>--</td><td>--</td><td>--</td><td>-0.816</td><td>0</td><td>156.8</td><td>2.57</td><td>20.037</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>33</td><td>185.7321600040</td><td>8.776</td><td>15.8269611876</td><td>5.756</td><td>3945577826799570176</td><td>--</td><td>--</td><td>--</td><td>-0.860</td><td>0</td><td>170.6</td><td>3.076</td><td>19.945</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>34</td><td>185.7177958034</td><td>1.937</td><td>15.8284410777</td><td>1.390</td><td>3945577891225799168</td><td>--</td><td>--</td><td>--</td><td>-0.822</td><td>0</td><td>493</td><td>4.501</td><td>18.793</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>35</td><td>185.7269771900</td><td>12.013</td><td>15.8236578342</td><td>6.172</td><td>3945577895518595584</td><td>--</td><td>--</td><td>--</td><td>-0.878</td><td>0</td><td>1355</td><td>30.72</td><td>17.695</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>36</td><td>185.7265760498</td><td>2.128</td><td>15.8228438865</td><td>1.566</td><td>3945577895518599424</td><td>--</td><td>--</td><td>--</td><td>-0.820</td><td>0</td><td>1300</td><td>14.52</td><td>17.740</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>37</td><td>185.7298085359</td><td>44.482</td><td>15.8258010445</td><td>18.743</td><td>3945577895519047680</td><td>--</td><td>--</td><td>--</td><td>0.480</td><td>0</td><td>172.7</td><td>14.15</td><td>19.932</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>38</td><td>185.7261105274</td><td>18.517</td><td>15.8271936695</td><td>7.678</td><td>3945577895519085440</td><td>--</td><td>--</td><td>--</td><td>-0.933</td><td>0</td><td>199.5</td><td>3.381</td><td>19.775</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>39</td><td>185.7327383120</td><td>1.704</td><td>15.8400740498</td><td>1.258</td><td>3945577925585845376</td><td>--</td><td>--</td><td>--</td><td>-0.839</td><td>0</td><td>173.6</td><td>1.923</td><td>19.926</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>40</td><td>185.7010753166</td><td>0.214</td><td>15.8219485143</td><td>0.140</td><td>3945577994304258048</td><td>--</td><td>--</td><td>--</td><td>-0.864</td><td>0</td><td>8078</td><td>14.76</td><td>15.757</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>41</td><td>185.7063017712</td><td>5.543</td><td>15.8250243577</td><td>4.036</td><td>3945577994306659712</td><td>--</td><td>--</td><td>--</td><td>-0.881</td><td>0</td><td>158.1</td><td>2.026</td><td>20.028</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>42</td><td>185.7039766223</td><td>2.192</td><td>15.8365807798</td><td>1.524</td><td>3945577998597820288</td><td>--</td><td>--</td><td>--</td><td>-0.828</td><td>0</td><td>429.5</td><td>3.843</td><td>18.942</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>43</td><td>185.7063460319</td><td>22.513</td><td>15.8373811347</td><td>8.713</td><td>3945578097384524288</td><td>--</td><td>--</td><td>--</td><td>-0.965</td><td>0</td><td>145.1</td><td>2.8</td><td>20.120</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>44</td><td>185.7048880607</td><td>0.205</td><td>15.8441178343</td><td>0.125</td><td>3945578166102958208</td><td>--</td><td>--</td><td>--</td><td>-0.875</td><td>0</td><td>1.098e+04</td><td>23.43</td><td>15.424</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>45</td><td>185.7098855725</td><td>0.196</td><td>15.8491427290</td><td>0.121</td><td>3945578166102970112</td><td>--</td><td>--</td><td>--</td><td>-0.874</td><td>0</td><td>1.545e+04</td><td>17.83</td><td>15.052</td><td>NOT_AVAILABLE</td></tr>\n",
       "<tr><td>46</td><td>185.7335162746</td><td>2.238</td><td>15.8510338988</td><td>1.496</td><td>3945578509700404480</td><td>--</td><td>--</td><td>--</td><td>-0.833</td><td>0</td><td>211.7</td><td>1.935</td><td>19.710</td><td>NOT_AVAILABLE</td></tr>\n",
       "</table><style>table.dataTable {clear: both; width: auto !important; margin: 0 !important;}\n",
       ".dataTables_info, .dataTables_length, .dataTables_filter, .dataTables_paginate{\n",
       "display: inline-block; margin-right: 1em; }\n",
       ".paginate_button { margin-right: 5px; }\n",
       "</style>\n",
       "<script>\n",
       "\n",
       "var astropy_sort_num = function(a, b) {\n",
       "    var a_num = parseFloat(a);\n",
       "    var b_num = parseFloat(b);\n",
       "\n",
       "    if (isNaN(a_num) && isNaN(b_num))\n",
       "        return ((a < b) ? -1 : ((a > b) ? 1 : 0));\n",
       "    else if (!isNaN(a_num) && !isNaN(b_num))\n",
       "        return ((a_num < b_num) ? -1 : ((a_num > b_num) ? 1 : 0));\n",
       "    else\n",
       "        return isNaN(a_num) ? -1 : 1;\n",
       "}\n",
       "\n",
       "require.config({paths: {\n",
       "    datatables: 'https://cdn.datatables.net/1.10.12/js/jquery.dataTables.min'\n",
       "}});\n",
       "require([\"datatables\"], function(){\n",
       "    console.log(\"$('#table4512663704-731401').dataTable()\");\n",
       "    \n",
       "jQuery.extend( jQuery.fn.dataTableExt.oSort, {\n",
       "    \"optionalnum-asc\": astropy_sort_num,\n",
       "    \"optionalnum-desc\": function (a,b) { return -astropy_sort_num(a, b); }\n",
       "});\n",
       "\n",
       "    $('#table4512663704-731401').dataTable({\n",
       "        order: [],\n",
       "        pageLength: 50,\n",
       "        lengthMenu: [[10, 25, 50, 100, 500, 1000, -1], [10, 25, 50, 100, 500, 1000, 'All']],\n",
       "        pagingType: \"full_numbers\",\n",
       "        columnDefs: [{targets: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13], type: \"optionalnum\"}]\n",
       "    });\n",
       "});\n",
       "</script>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "restab=res[0]\n",
    "#restab=res[0]\n",
    "restab.show_in_notebook()\n",
    "#restab"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO: Auto-setting vmin to  2.697e+03 [aplpy.core]\n",
      "INFO: Auto-setting vmax to  2.446e+04 [aplpy.core]\n"
     ]
    },
    {
     "data": {
      "image/png": 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qz1mW3OXh7vTwyPE/Ednckwef3/Rlxb7HNLpwDg4O3Je7yPoLxQuqrmXVtq+0mbCoGKwN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\nBUEQBEEQjBH/D7fZGXOdP+DYAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10d00a898>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = aplpy.FITSFigure(opt)\n",
    "fig.show_grayscale()\n",
    "#fig.show_markers(restab['ra'],restab['dec'])\n",
    "fig.show_markers(restab['RA_ICRS'],restab['DE_ICRS'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### With ALMA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['https://skyview.gsfc.nasa.gov/tempspace/fits/skv15372982969808.fits']"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res=SkyView.get_image_list(position='Galactic Center',survey=['NVSS'])\n",
    "res"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO: Auto-setting vmin to -1.796e+00 [aplpy.core]\n",
      "INFO: Auto-setting vmax to  3.434e+00 [aplpy.core]\n"
     ]
    },
    {
     "data": {
      "image/png": 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IVOnlz7PM2b2KKcqly+its3Bx4tUdmZFHP6pR0uwRsPvN3iH63THF5GuZkb22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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10cb736d8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "urllib.request.urlretrieve(res[0],'opt.fits')\n",
    "#urllib.urlretrieve(res[0],'opt.fits')\n",
    "hdulist = fits.open(\"opt.fits\")\n",
    "opt = hdulist[0] \n",
    "fig = aplpy.FITSFigure(opt)\n",
    "fig.show_grayscale()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ab8b097436184105ad469e865305d7d7",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "A Jupyter Widget"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mycirc=interact(select_radius,radius=(0.0,0.9,0.9/100))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "266.417 -29.0078\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0.0279"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "limits = mycirc.widget.kwargs\n",
    "ra=opt.header['CRVAL1']\n",
    "dec=opt.header['CRVAL2']\n",
    "rad    = limits['radius']\n",
    "print(ra,dec)\n",
    "rad"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'{\\n    \"title\": \"ChiVO ALMA\",\\n    \"url\": \"http://vo.chivo.cl/archive_alma/q/scs-archive-alma/scs.xml?\"\\n}'"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from astropy.vo.client import vos_catalog\n",
    "catalog=vos_catalog.VOSCatalog.create(\"ChiVO ALMA\",\n",
    "                                      \"http://vo.chivo.cl/archive_alma/q/scs-archive-alma/scs.xml?\")\n",
    "catalog.dumps()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Trying http://vo.chivo.cl/archive_alma/q/scs-archive-alma/scs.xml?\n"
     ]
    },
    {
     "ename": "VOSError",
     "evalue": "None of the available catalogs returned valid results.",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mVOSError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-54-69de20788817>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m res=vos_catalog.call_vo_service('conesearch_good',\n\u001b[1;32m      2\u001b[0m                             \u001b[0mcatalog_db\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcatalog\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m                             kwargs={'RA': ra, 'DEC': dec,'SR': rad})\n\u001b[0m",
      "\u001b[0;32m/usr/local/lib/python3.5/site-packages/astropy/utils/decorators.py\u001b[0m in \u001b[0;36mdeprecated_func\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    119\u001b[0m             \u001b[0mwarnings\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwarn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmessage\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcategory\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstacklevel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    120\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 121\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    122\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    123\u001b[0m         \u001b[0;31m# If this is an extension function, we can't call\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.5/site-packages/astropy/vo/client/vos_catalog.py\u001b[0m in \u001b[0;36mcall_vo_service\u001b[0;34m(service_type, catalog_db, pedantic, verbose, cache, kwargs)\u001b[0m\n\u001b[1;32m    894\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mn_timed_out\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    895\u001b[0m         \u001b[0merr_msg\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0;34m' ({0} URL(s) timed out.)'\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn_timed_out\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 896\u001b[0;31m     \u001b[0;32mraise\u001b[0m \u001b[0mVOSError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0merr_msg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    897\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    898\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mVOSError\u001b[0m: None of the available catalogs returned valid results."
     ]
    }
   ],
   "source": [
    "res=vos_catalog.call_vo_service('conesearch_good',\n",
    "                            catalog_db=catalog,\n",
    "                            kwargs={'RA': ra, 'DEC': dec,'SR': rad})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "&lt;Table masked=True length=43&gt;\n",
       "<table id=\"table4554426384-604693\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>idx</th><th>obsURL</th><th>project_code</th><th>source_name</th><th>s_ra</th><th>s_dec</th><th>band</th><th>spatial_resolution</th><th>frequency_resolution</th><th>integration</th><th>release_date</th><th>frequency_support</th><th>velocity_resolution</th><th>pol_products</th><th>observation_date</th><th>pi_name</th><th>pwv</th><th>group_ous_id</th><th>member_ous_id</th><th>asdm_uid</th><th>project_title</th><th>project_type</th><th>scan_intent</th><th>largest_angular_scale</th><th>qa2_status</th><th>pub</th></tr></thead>\n",
       "<tr><td>0</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/Xa25bbf/Xc8cf&amp;mous=uid://A001/X197/X33</td><td>2013.1.01242.S</td><td>SiO_15_16</td><td>266.416</td><td>-29.017600000000002</td><td>7.0</td><td>0.26793301</td><td>488.28101</td><td>151.2</td><td>2016-11-23</td><td>[289.54..289.78GHz,976.56kHz,null]_U_[290.52..290.76GHz,976.56kHz,null]_U_[291.14..291.37GHz,976.56kHz,null]_U_[291.28..291.51GHz,976.56kHz,null]_U_[291.49..292.43GHz,976.56kHz,null]_U_[300.74..300.97GHz,976.56kHz,null]_U_[303.47..304.41GHz,488.28kHz,null]</td><td>973.12201</td><td>XX_YY</td><td>2015-06-08_03:41:01</td><td>Yusef-Zadeh,_Farhad</td><td>0.4868778</td><td>uid://A001/X197/X32</td><td>uid://A001/X197/X33</td><td>uid://A002/Xa25bbf/Xc8cf</td><td>SiO_Observations_of_the_Circumnuclear_Molecular_Ring_and_Its_Interior</td><td>S</td><td>TARGET</td><td>15.236022735724893</td><td>Y</td><td>0.0</td></tr>\n",
       "<tr><td>1</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/Xa77ec0/X26e&amp;mous=uid://A001/X197/X27</td><td>2013.1.01242.S</td><td>Circumnuclear_Ring</td><td>266.416</td><td>-29.0124</td><td>3.0</td><td>0.48200601</td><td>244.14101</td><td>124.993</td><td>2016-12-07</td><td>[84.40..84.64GHz,244.14kHz,null]_U_[86.73..86.96GHz,244.14kHz,null]_U_[96.50..96.97GHz,488.28kHz,null]_U_[99.61..99.84GHz,244.14kHz,null]</td><td>854.23297</td><td>XX_YY</td><td>2015-08-06_00:59:26</td><td>Yusef-Zadeh,_Farhad</td><td>4.1887031</td><td>uid://A001/X197/X26</td><td>uid://A001/X197/X27</td><td>uid://A002/Xa77ec0/X26e</td><td>SiO_Observations_of_the_Circumnuclear_Molecular_Ring_and_Its_Interior</td><td>S</td><td>TARGET</td><td>250.92385860193491</td><td>Y</td><td>0.0</td></tr>\n",
       "<tr><td>2</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/Xa25bbf/Xc8cf&amp;mous=uid://A001/X197/X33</td><td>2013.1.01242.S</td><td>SiO_17</td><td>266.42200000000003</td><td>-29.017099999999999</td><td>7.0</td><td>0.26793301</td><td>488.28101</td><td>151.2</td><td>2016-11-23</td><td>[289.54..289.78GHz,976.56kHz,null]_U_[290.52..290.76GHz,976.56kHz,null]_U_[291.14..291.37GHz,976.56kHz,null]_U_[291.28..291.51GHz,976.56kHz,null]_U_[291.49..292.43GHz,976.56kHz,null]_U_[300.74..300.97GHz,976.56kHz,null]_U_[303.47..304.41GHz,488.28kHz,null]</td><td>973.12201</td><td>XX_YY</td><td>2015-06-08_03:41:01</td><td>Yusef-Zadeh,_Farhad</td><td>0.4868778</td><td>uid://A001/X197/X32</td><td>uid://A001/X197/X33</td><td>uid://A002/Xa25bbf/Xc8cf</td><td>SiO_Observations_of_the_Circumnuclear_Molecular_Ring_and_Its_Interior</td><td>S</td><td>TARGET</td><td>15.2372831514159</td><td>Y</td><td>0.0</td></tr>\n",
       "<tr><td>3</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/Xa25bbf/Xc8cf&amp;mous=uid://A001/X197/X33</td><td>2013.1.01242.S</td><td>SiO_30_31</td><td>266.41000000000003</td><td>-29.011099999999999</td><td>7.0</td><td>0.26793599</td><td>488.28101</td><td>151.2</td><td>2016-11-23</td><td>[289.54..289.78GHz,976.56kHz,null]_U_[290.52..290.76GHz,976.56kHz,null]_U_[291.14..291.37GHz,976.56kHz,null]_U_[291.28..291.51GHz,976.56kHz,null]_U_[291.49..292.43GHz,976.56kHz,null]_U_[300.74..300.97GHz,976.56kHz,null]_U_[303.47..304.41GHz,488.28kHz,null]</td><td>973.12201</td><td>XX_YY</td><td>2015-06-08_03:41:01</td><td>Yusef-Zadeh,_Farhad</td><td>0.4868778</td><td>uid://A001/X197/X32</td><td>uid://A001/X197/X33</td><td>uid://A002/Xa25bbf/Xc8cf</td><td>SiO_Observations_of_the_Circumnuclear_Molecular_Ring_and_Its_Interior</td><td>S</td><td>TARGET</td><td>15.233305658622868</td><td>Y</td><td>0.0</td></tr>\n",
       "<tr><td>4</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/X83b318/X971&amp;mous=uid://A001/X122/X160</td><td>2013.1.01058.S</td><td>SgrA_star</td><td>266.41699999999997</td><td>-29.0107</td><td>7.0</td><td>3.60624</td><td>976.56201</td><td>2373.361</td><td>2016-09-23</td><td>[344.78..346.84GHz,976.56kHz,null]_U_[346.17..348.22GHz,976.56kHz,null]_U_[356.21..358.26GHz,976.56kHz,null]_U_[356.91..358.96GHz,976.56kHz,null]</td><td>831.138</td><td>XX_YY</td><td>2014-06-09_07:57:38</td><td>Goicoechea,_Javier</td><td>--</td><td>uid://A001/X122/X15d</td><td>uid://A001/X122/X160</td><td>uid://A002/X83b318/X971</td><td>Irradiated_Shocks_and_Ionisation_Sources_in_the_Central_Parsec_of_the_Milky_Way</td><td>S</td><td>TARGET</td><td>196.10165749058791</td><td>Y</td><td>0.0</td></tr>\n",
       "<tr><td>5</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/Xa16f89/X10bb&amp;mous=uid://A001/X121/X2de</td><td>2013.1.00857.S</td><td>Circumnuclear_Disk</td><td>266.41399999999999</td><td>-29.009499999999999</td><td>6.0</td><td>20.1436</td><td>1953.12</td><td>11354.112</td><td>2016-10-16</td><td>[251.50..253.49GHz,1953.12kHz,null]_U_[253.74..255.73GHz,1953.12kHz,null]_U_[265.74..267.74GHz,1953.12kHz,null]_U_[268.73..270.72GHz,1953.12kHz,null]</td><td>2245.6599</td><td>XX_YY</td><td>2015-05-24_01:31:48</td><td>Mills,_Elisabeth</td><td>1.3583895</td><td>uid://A001/X121/X2d9</td><td>uid://A001/X121/X2de</td><td>uid://A002/Xa16f89/X10bb</td><td>The_Density_(and_Destiny)_of_the_Circumnuclear_Disk</td><td>S</td><td>TARGET_WVR</td><td>357.05621696406217</td><td>Y</td><td>0.0</td></tr>\n",
       "<tr><td>6</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/Xa916fc/X8ac&amp;mous=uid://A001/X121/X2e7</td><td>2013.1.00857.S</td><td>Circumnuclear_Disk</td><td>266.41399999999999</td><td>-29.009499999999999</td><td>3.0</td><td>56.254002</td><td>1953.12</td><td>1876.992</td><td>2016-12-16</td><td>[85.50..87.50GHz,1953.12kHz,null]_U_[87.46..89.45GHz,1953.12kHz,null]_U_[97.50..99.50GHz,1953.12kHz,null]_U_[99.50..101.50GHz,1953.12kHz,null]</td><td>6263.7798</td><td>XX_YY</td><td>2015-08-28_23:06:17</td><td>Mills,_Elisabeth</td><td>2.1332936</td><td>uid://A001/X121/X2e0</td><td>uid://A001/X121/X2e7</td><td>uid://A002/Xa916fc/X8ac</td><td>The_Density_(and_Destiny)_of_the_Circumnuclear_Disk</td><td>S</td><td>TARGET_WVR</td><td>997.13033003618864</td><td>Y</td><td>0.0</td></tr>\n",
       "<tr><td>7</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/X87544a/X222e&amp;mous=uid://A001/X121/X2e5</td><td>2013.1.00857.S</td><td>Circumnuclear_Disk</td><td>266.41199999999998</td><td>-29.008500000000002</td><td>3.0</td><td>14.1329</td><td>1953.12</td><td>329.575</td><td>2016-01-02</td><td>[85.49..87.49GHz,1953.12kHz,null]_U_[87.43..89.43GHz,1953.12kHz,null]_U_[97.49..99.49GHz,1953.12kHz,null]_U_[99.49..101.49GHz,1953.12kHz,null]</td><td>6264.9399</td><td>XX_YY</td><td>2014-07-21_04:36:00</td><td>Mills,_Elisabeth</td><td>--</td><td>uid://A001/X121/X2e0</td><td>uid://A001/X121/X2e5</td><td>uid://A002/X87544a/X222e</td><td>The_Density_(and_Destiny)_of_the_Circumnuclear_Disk</td><td>S</td><td>TARGET</td><td>142.26084610942709</td><td>Y</td><td>0.0</td></tr>\n",
       "<tr><td>8</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/X88cee1/Xa4e&amp;mous=uid://A001/X121/X2ee</td><td>2013.1.00857.S</td><td>Circumnuclear_Disk</td><td>266.41199999999998</td><td>-29.008500000000002</td><td>3.0</td><td>13.5999</td><td>1953.12</td><td>511.455</td><td>2016-03-02</td><td>[89.70..91.69GHz,1953.12kHz,null]_U_[91.59..93.61GHz,1953.12kHz,null]_U_[101.76..103.75GHz,1953.12kHz,null]_U_[103.59..105.61GHz,1953.12kHz,null]</td><td>5994.23</td><td>XX_YY</td><td>2014-08-06_04:06:46</td><td>Mills,_Elisabeth</td><td>--</td><td>uid://A001/X121/X2e9</td><td>uid://A001/X121/X2ee</td><td>uid://A002/X88cee1/Xa4e</td><td>The_Density_(and_Destiny)_of_the_Circumnuclear_Disk</td><td>S</td><td>TARGET</td><td>254.19514498336727</td><td>Y</td><td>0.0</td></tr>\n",
       "<tr><td>9</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/X9d6f4c/X29a9&amp;mous=uid://A001/X121/X2da</td><td>2013.1.00857.S</td><td>Circumnuclear_Disk</td><td>266.41399999999999</td><td>-29.008500000000002</td><td>6.0</td><td>0.72804701</td><td>1953.12</td><td>87.67</td><td>2016-06-03</td><td>[251.57..253.45GHz,1953.12kHz,null]_U_[253.82..255.69GHz,1953.12kHz,null]_U_[265.82..267.69GHz,1953.12kHz,null]_U_[268.80..270.68GHz,1953.12kHz,null]</td><td>2245.54</td><td>XX_YY</td><td>2015-04-06_08:48:26</td><td>Mills,_Elisabeth</td><td>1.7634906</td><td>uid://A001/X121/X2d9</td><td>uid://A001/X121/X2da</td><td>uid://A002/X9d6f4c/X29a9</td><td>The_Density_(and_Destiny)_of_the_Circumnuclear_Disk</td><td>S</td><td>TARGET</td><td>17.023126503812875</td><td>Y</td><td>0.0</td></tr>\n",
       "<tr><td>10</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/X9d6f4c/X2c6e&amp;mous=uid://A001/X121/X2f3</td><td>2013.1.00857.S</td><td>Circumnuclear_Disk</td><td>266.41399999999999</td><td>-29.008500000000002</td><td>6.0</td><td>0.71946698</td><td>1953.12</td><td>87.581</td><td>2016-06-03</td><td>[255.74..257.62GHz,1953.12kHz,null]_U_[257.80..259.67GHz,1953.12kHz,null]_U_[270.60..272.47GHz,1953.12kHz,null]_U_[272.60..274.47GHz,1953.12kHz,null]</td><td>2208.4399</td><td>XX_YY</td><td>2015-04-06_10:06:34</td><td>Mills,_Elisabeth</td><td>1.8867824</td><td>uid://A001/X121/X2f2</td><td>uid://A001/X121/X2f3</td><td>uid://A002/X9d6f4c/X2c6e</td><td>The_Density_(and_Destiny)_of_the_Circumnuclear_Disk</td><td>S</td><td>TARGET</td><td>20.251467019075601</td><td>Y</td><td>0.0</td></tr>\n",
       "<tr><td>11</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/X95e355/X1d46&amp;mous=uid://A001/X121/X2e3</td><td>2013.1.00857.S</td><td>Circumnuclear_Disk</td><td>266.41399999999999</td><td>-29.008500000000002</td><td>3.0</td><td>1.96306</td><td>1953.12</td><td>68.203</td><td>2016-03-30</td><td>[85.56..87.43GHz,1953.12kHz,null]_U_[87.50..89.37GHz,1953.12kHz,null]_U_[97.56..99.43GHz,1953.12kHz,null]_U_[99.56..101.43GHz,1953.12kHz,null]</td><td>6264.75</td><td>XX_YY</td><td>2014-12-06_13:29:22</td><td>Mills,_Elisabeth</td><td>5.1424727</td><td>uid://A001/X121/X2e0</td><td>uid://A001/X121/X2e3</td><td>uid://A002/X95e355/X1d46</td><td>The_Density_(and_Destiny)_of_the_Circumnuclear_Disk</td><td>S</td><td>TARGET</td><td>154.92024716586798</td><td>Y</td><td>0.0</td></tr>\n",
       "<tr><td>12</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/X87f18c/X116b&amp;mous=uid://A001/X121/X2f5</td><td>2013.1.00857.S</td><td>Circumnuclear_Disk</td><td>266.41399999999999</td><td>-29.008500000000002</td><td>6.0</td><td>4.9456301</td><td>1953.12</td><td>195.117</td><td>2016-07-22</td><td>[255.64..257.64GHz,1953.12kHz,null]_U_[257.69..259.69GHz,1953.12kHz,null]_U_[270.50..272.49GHz,1953.12kHz,null]_U_[272.50..274.49GHz,1953.12kHz,null]</td><td>2208.77</td><td>XX_YY</td><td>2014-07-28_03:51:47</td><td>Mills,_Elisabeth</td><td>--</td><td>uid://A001/X121/X2f2</td><td>uid://A001/X121/X2f5</td><td>uid://A002/X87f18c/X116b</td><td>The_Density_(and_Destiny)_of_the_Circumnuclear_Disk</td><td>S</td><td>TARGET</td><td>228.77213359477034</td><td>Y</td><td>0.0</td></tr>\n",
       "<tr><td>13</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/X87544a/X22d1&amp;mous=uid://A001/X121/X2e1</td><td>2013.1.00857.S</td><td>Circumnuclear_Disk</td><td>266.41399999999999</td><td>-29.008500000000002</td><td>3.0</td><td>0.84987801</td><td>1953.12</td><td>68.205</td><td>2015-09-23</td><td>[85.56..87.43GHz,1953.12kHz,null]_U_[87.49..89.37GHz,1953.12kHz,null]_U_[97.56..99.43GHz,1953.12kHz,null]_U_[99.56..101.43GHz,1953.12kHz,null]</td><td>6264.9399</td><td>XX_YY</td><td>2014-07-21_04:50:50</td><td>Mills,_Elisabeth</td><td>2.2471156</td><td>uid://A001/X121/X2e0</td><td>uid://A001/X121/X2e1</td><td>uid://A002/X87544a/X22d1</td><td>The_Density_(and_Destiny)_of_the_Circumnuclear_Disk</td><td>S</td><td>TARGET</td><td>51.044266780887156</td><td>Y</td><td>0.0</td></tr>\n",
       "<tr><td>14</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/X85f3e3/X23e&amp;mous=uid://A001/X121/X2ea</td><td>2013.1.00857.S</td><td>Circumnuclear_Disk</td><td>266.41399999999999</td><td>-29.008500000000002</td><td>3.0</td><td>0.81297898</td><td>1953.12</td><td>144.674</td><td>2015-09-23</td><td>[89.76..91.64GHz,1953.12kHz,null]_U_[91.66..93.53GHz,1953.12kHz,null]_U_[101.82..103.70GHz,1953.12kHz,null]_U_[103.66..105.53GHz,1953.12kHz,null]</td><td>5994.4502</td><td>XX_YY</td><td>2014-07-04_04:02:49</td><td>Mills,_Elisabeth</td><td>2.5834188</td><td>uid://A001/X121/X2e9</td><td>uid://A001/X121/X2ea</td><td>uid://A002/X85f3e3/X23e</td><td>The_Density_(and_Destiny)_of_the_Circumnuclear_Disk</td><td>S</td><td>TARGET</td><td>44.597254493987869</td><td>Y</td><td>0.0</td></tr>\n",
       "<tr><td>15</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/X87c075/X2c43&amp;mous=uid://A001/X121/X2dc</td><td>2013.1.00857.S</td><td>Circumnuclear_Disk</td><td>266.41399999999999</td><td>-29.008500000000002</td><td>6.0</td><td>5.0497398</td><td>1953.12</td><td>193.153</td><td>2016-06-06</td><td>[251.47..253.47GHz,1953.12kHz,null]_U_[253.72..255.71GHz,1953.12kHz,null]_U_[265.72..267.71GHz,1953.12kHz,null]_U_[268.70..270.70GHz,1953.12kHz,null]</td><td>2245.8799</td><td>XX_YY</td><td>2014-07-27_02:55:06</td><td>Mills,_Elisabeth</td><td>--</td><td>uid://A001/X121/X2d9</td><td>uid://A001/X121/X2dc</td><td>uid://A002/X87c075/X2c43</td><td>The_Density_(and_Destiny)_of_the_Circumnuclear_Disk</td><td>S</td><td>TARGET</td><td>59.446455025808007</td><td>Y</td><td>0.0</td></tr>\n",
       "<tr><td>16</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/X95e355/X1c09&amp;mous=uid://A001/X121/X2ec</td><td>2013.1.00857.S</td><td>Circumnuclear_Disk</td><td>266.41399999999999</td><td>-29.008500000000002</td><td>3.0</td><td>1.86115</td><td>1953.12</td><td>72.335</td><td>2016-01-27</td><td>[89.76..91.64GHz,1953.12kHz,null]_U_[91.66..93.53GHz,1953.12kHz,null]_U_[101.83..103.70GHz,1953.12kHz,null]_U_[103.66..105.53GHz,1953.12kHz,null]</td><td>5994.4199</td><td>XX_YY</td><td>2014-12-06_12:57:33</td><td>Mills,_Elisabeth</td><td>5.1178575</td><td>uid://A001/X121/X2e9</td><td>uid://A001/X121/X2ec</td><td>uid://A002/X95e355/X1c09</td><td>The_Density_(and_Destiny)_of_the_Circumnuclear_Disk</td><td>S</td><td>TARGET</td><td>112.22753745719854</td><td>Y</td><td>0.0</td></tr>\n",
       "<tr><td>17</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/Xa916fc/Xcb3&amp;mous=uid://A001/X197/X2f</td><td>2013.1.01242.S</td><td>Sources_1_11</td><td>266.41699999999997</td><td>-29.009699999999999</td><td>6.0</td><td>0.197446</td><td>976.56201</td><td>967.68</td><td>2016-12-22</td><td>[216.62..217.56GHz,976.56kHz,null]_U_[217.97..218.44GHz,1953.12kHz,null]_U_[218.23..218.70GHz,1953.12kHz,null]_U_[218.51..218.98GHz,1953.12kHz,null]_U_[230.06..230.99GHz,976.56kHz,null]_U_[231.48..233.48GHz,31250.00kHz,null]</td><td>1348.04</td><td>XX_YY</td><td>2015-08-29_00:11:53</td><td>Yusef-Zadeh,_Farhad</td><td>1.6833909</td><td>uid://A001/X197/X2e</td><td>uid://A001/X197/X2f</td><td>uid://A002/Xa916fc/Xcb3</td><td>SiO_Observations_of_the_Circumnuclear_Molecular_Ring_and_Its_Interior</td><td>S</td><td>TARGET</td><td>37.578527193335773</td><td>Y</td><td>0.0</td></tr>\n",
       "<tr><td>18</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/Xa25bbf/Xc8cf&amp;mous=uid://A001/X197/X33</td><td>2013.1.01242.S</td><td>SiO_1_11</td><td>266.41699999999997</td><td>-29.009699999999999</td><td>7.0</td><td>0.267937</td><td>488.28101</td><td>151.2</td><td>2016-11-23</td><td>[289.54..289.78GHz,976.56kHz,null]_U_[290.52..290.76GHz,976.56kHz,null]_U_[291.14..291.37GHz,976.56kHz,null]_U_[291.28..291.51GHz,976.56kHz,null]_U_[291.49..292.43GHz,976.56kHz,null]_U_[300.74..300.97GHz,976.56kHz,null]_U_[303.47..304.41GHz,488.28kHz,null]</td><td>973.12201</td><td>XX_YY</td><td>2015-06-08_03:41:01</td><td>Yusef-Zadeh,_Farhad</td><td>0.4868778</td><td>uid://A001/X197/X32</td><td>uid://A001/X197/X33</td><td>uid://A002/Xa25bbf/Xc8cf</td><td>SiO_Observations_of_the_Circumnuclear_Molecular_Ring_and_Its_Interior</td><td>S</td><td>TARGET</td><td>15.23484242904191</td><td>Y</td><td>0.0</td></tr>\n",
       "<tr><td>19</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/Xa657ad/X1e3e&amp;mous=uid://A001/X122/X1b</td><td>2013.1.00111.S</td><td>sgra_star</td><td>266.41699999999997</td><td>-29.0078</td><td>6.0</td><td>0.182265</td><td>3906.25</td><td>2419.2</td><td>2016-10-16</td><td>[228.91..230.91GHz,31250.00kHz,null]_U_[230.30..232.30GHz,31250.00kHz,null]_U_[230.47..230.94GHz,3906.25kHz,null]_U_[231.66..232.13GHz,3906.25kHz,null]_U_[231.80..233.80GHz,31250.00kHz,null]</td><td>5079.0298</td><td>XX_YY</td><td>2015-07-22_04:55:05</td><td>Scoville,_Nick</td><td>3.0631948</td><td>uid://A001/X122/X1a</td><td>uid://A001/X122/X1b</td><td>uid://A002/Xa657ad/X1e3e</td><td>The_extreme_UV_through_ALMA&amp;apos;s_eyes:_a_unique_probe_of_the_ionizing_power_of_starbursts_and_super_massive_black_holes</td><td>S</td><td>TARGET</td><td>20.329169040277733</td><td>Y</td><td>1.0</td></tr>\n",
       "<tr><td>20</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/X9f852b/Xe6e&amp;mous=uid://A002/X82316f/X7</td><td>2013.1.00071.S</td><td>SgrA_star</td><td>266.41699999999997</td><td>-29.0078</td><td>8.0</td><td>0.368449</td><td>3906.25</td><td>40.946</td><td>2016-08-10</td><td>[477.32..479.20GHz,3906.25kHz,null]_U_[479.15..481.03GHz,3906.25kHz,null]_U_[489.33..491.20GHz,3906.25kHz,null]_U_[491.32..493.19GHz,3906.25kHz,null]</td><td>2413.6899</td><td>XX_YY</td><td>2015-04-30_06:48:16</td><td>Liu,_Hauyu_Baobab</td><td>0.88422066</td><td>uid://A002/X82316f/X6</td><td>uid://A002/X82316f/X7</td><td>uid://A002/X9f852b/Xe6e</td><td>Resolving_the_atomic_gas_accretion_flow_surrounding_the_SgrA*</td><td>S</td><td>TARGET</td><td>8.7433018103528184</td><td>Y</td><td>1.0</td></tr>\n",
       "<tr><td>21</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/Xa657ad/Xd3b&amp;mous=uid://A001/X122/X2b</td><td>2013.1.00111.S</td><td>sgra_star</td><td>266.41699999999997</td><td>-29.0078</td><td>6.0</td><td>0.20477401</td><td>976.56201</td><td>1905.12</td><td>2016-10-07</td><td>[214.96..216.83GHz,976.56kHz,null]_U_[216.07..217.94GHz,976.56kHz,null]_U_[217.06..218.94GHz,976.56kHz,null]</td><td>1349.12</td><td>XX_YY</td><td>2015-07-22_00:09:50</td><td>Scoville,_Nick</td><td>2.8489859</td><td>uid://A001/X122/X2a</td><td>uid://A001/X122/X2b</td><td>uid://A002/Xa657ad/Xd3b</td><td>The_extreme_UV_through_ALMA&amp;apos;s_eyes:_a_unique_probe_of_the_ionizing_power_of_starbursts_and_super_massive_black_holes</td><td>S</td><td>TARGET</td><td>45.291562261139653</td><td>Y</td><td>1.0</td></tr>\n",
       "<tr><td>22</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/X9dcf39/X256f&amp;mous=uid://A001/X121/X448</td><td>2013.1.00834.S</td><td>Sgr_A_star</td><td>266.41699999999997</td><td>-29.0078</td><td>3.0</td><td>2.0715201</td><td>976.56201</td><td>1965.6</td><td>2016-07-31</td><td>[84.85..85.79GHz,976.56kHz,null]_U_[85.78..86.72GHz,976.56kHz,null]_U_[86.71..87.65GHz,976.56kHz,null]_U_[87.64..88.58GHz,976.56kHz,null]</td><td>3376.1299</td><td>XX_YY</td><td>2015-04-10_06:21:25</td><td>Darling,_Jeremy</td><td>2.6007774</td><td>uid://A001/X121/X447</td><td>uid://A001/X121/X448</td><td>uid://A002/X9dcf39/X256f</td><td>High_Velocity_Masers_in_the_Galactic_Center:_A_New_Probe_of_General_Relativity</td><td>S</td><td>TARGET</td><td>47.766593687972609</td><td>Y</td><td>0.0</td></tr>\n",
       "<tr><td>23</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/X9f852b/Xaf1&amp;mous=uid://A002/X82316f/X9</td><td>2013.1.00071.S</td><td>SgrA_star</td><td>266.41699999999997</td><td>-29.0078</td><td>8.0</td><td>2.6322401</td><td>3906.25</td><td>68.721</td><td>2016-08-13</td><td>[477.27..479.26GHz,3906.25kHz,null]_U_[479.09..481.09GHz,3906.25kHz,null]_U_[489.27..491.26GHz,3906.25kHz,null]_U_[491.26..493.25GHz,3906.25kHz,null]</td><td>2413.6899</td><td>XX_YY</td><td>2015-04-30_05:34:42</td><td>Liu,_Hauyu_Baobab</td><td>--</td><td>uid://A002/X82316f/X6</td><td>uid://A002/X82316f/X9</td><td>uid://A002/X9f852b/Xaf1</td><td>Resolving_the_atomic_gas_accretion_flow_surrounding_the_SgrA*</td><td>S</td><td>TARGET</td><td>16.953078893658457</td><td>Y</td><td>1.0</td></tr>\n",
       "<tr><td>24</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/Xb54d65/X29ac&amp;mous=uid://A001/X85a/X28</td><td>2015.A.00021.S</td><td>SgrA_star</td><td>266.41699999999997</td><td>-29.0078</td><td>6.0</td><td>0.31667301</td><td>976.56201</td><td>10281.6</td><td>2016-09-01</td><td>[217.44..219.31GHz,3906.25kHz,null]_U_[219.26..221.14GHz,976.56kHz,null]_U_[231.26..233.14GHz,976.56kHz,null]_U_[233.14..235.01GHz,3906.25kHz,null]</td><td>1326.73</td><td>XX_YY</td><td>2016-07-12_22:43:19</td><td>Witzel,_Gunther</td><td>0.88808626</td><td>uid://A001/X85a/X27</td><td>uid://A001/X85a/X28</td><td>uid://A002/Xb54d65/X29ac</td><td>Sgr_A*_multi-wavelength_monnitoring</td><td>S</td><td>TARGET</td><td>122.01467720100837</td><td>Y</td><td>0.0</td></tr>\n",
       "<tr><td>25</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/Xb58d4d/X1137&amp;mous=uid://A001/X85a/X2c</td><td>2015.A.00021.S</td><td>SgrA_star</td><td>266.41699999999997</td><td>-29.0078</td><td>6.0</td><td>0.25685799</td><td>976.56201</td><td>11612.16</td><td>2016-09-01</td><td>[217.43..219.31GHz,3906.25kHz,null]_U_[219.26..221.13GHz,976.56kHz,null]_U_[231.26..233.13GHz,976.56kHz,null]_U_[233.13..235.01GHz,3906.25kHz,null]</td><td>1326.74</td><td>XX_YY</td><td>2016-07-18_22:59:50</td><td>Witzel,_Gunther</td><td>1.5089086</td><td>uid://A001/X85a/X2b</td><td>uid://A001/X85a/X2c</td><td>uid://A002/Xb58d4d/X1137</td><td>Sgr_A*_multi-wavelength_monnitoring</td><td>S</td><td>TARGET</td><td>101.71570374164331</td><td>Y</td><td>0.0</td></tr>\n",
       "<tr><td>26</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/X7fb89e/Xa06&amp;mous=uid://A002/X7d1738/X42</td><td>2012.1.00635.S</td><td>SgrA_star</td><td>266.41699999999997</td><td>-29.0078</td><td>7.0</td><td>0.39289501</td><td>31250.0</td><td>1028.16</td><td>2015-05-16</td><td>[215.03..217.03GHz,31250.00kHz,null]_U_[217.03..219.03GHz,31250.00kHz,null]_U_[230.99..232.86GHz,976.56kHz,null]_U_[232.80..234.80GHz,31250.00kHz,null]_U_[338.66..340.66GHz,31250.00kHz,null]_U_[340.64..342.64GHz,31250.00kHz,null]_U_[350.76..352.76GHz,31250.00kHz,null]_U_[352.70..354.58GHz,976.56kHz,null]</td><td>1258.27</td><td>XX_YY</td><td>2014-04-25_06:35:44</td><td>Bower,_Geoffrey</td><td>1.2224643</td><td>uid://A002/X7d1738/X41</td><td>uid://A002/X7d1738/X42</td><td>uid://A002/X7fb89e/Xa06</td><td>The_G2_Gas_Cloud_Encounter_with_Sagittarius_A*:_Accretion_Structure_on_Scales_of_3000_to_1_Schwarzschild_Radii</td><td>S</td><td>TARGET_WVR</td><td>11.186309647433838</td><td>Y</td><td>1.0</td></tr>\n",
       "<tr><td>27</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/X828760/X60f&amp;mous=uid://A002/X7d1738/X45</td><td>2012.1.00635.S</td><td>SgrA_star</td><td>266.41699999999997</td><td>-29.0078</td><td>7.0</td><td>0.33941799</td><td>31250.0</td><td>1209.6</td><td>2015-07-28</td><td>[215.02..217.02GHz,31250.00kHz,null]_U_[217.02..219.02GHz,31250.00kHz,null]_U_[230.98..232.85GHz,976.56kHz,null]_U_[232.79..234.79GHz,31250.00kHz,null]_U_[338.62..340.62GHz,31250.00kHz,null]_U_[340.62..342.62GHz,31250.00kHz,null]_U_[350.75..352.75GHz,31250.00kHz,null]_U_[352.69..354.56GHz,976.56kHz,null]</td><td>1258.3199</td><td>XX_YY</td><td>2014-05-26_04:09:05</td><td>Bower,_Geoffrey</td><td>0.73699152</td><td>uid://A002/X7d1738/X44</td><td>uid://A002/X7d1738/X45</td><td>uid://A002/X828760/X60f</td><td>The_G2_Gas_Cloud_Encounter_with_Sagittarius_A*:_Accretion_Structure_on_Scales_of_3000_to_1_Schwarzschild_Radii</td><td>S</td><td>TARGET_WVR</td><td>19.969546448988897</td><td>Y</td><td>1.0</td></tr>\n",
       "<tr><td>28</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/X40d164/X1b3&amp;mous=uid://A002/X391d0b/X23d</td><td>2011.0.00887.S</td><td>Sagittarius_A*</td><td>266.41699999999997</td><td>-29.0078</td><td>7.0</td><td>0.70037502</td><td>31250.0</td><td>2419.2</td><td>2013-10-01</td><td>[91.99..93.99GHz,31250.00kHz,null]_U_[93.93..95.93GHz,31250.00kHz,null]_U_[103.99..105.99GHz,31250.00kHz,null]_U_[105.99..107.99GHz,31250.00kHz,null]_U_[244.00..246.00GHz,31250.00kHz,null]_U_[246.00..248.00GHz,31250.00kHz,null]_U_[259.50..261.50GHz,31250.00kHz,null]_U_[261.50..263.50GHz,31250.00kHz,null]_U_[334.99..336.99GHz,31250.00kHz,null]_U_[336.93..338.93GHz,31250.00kHz,null]_U_[346.99..348.99GHz,31250.00kHz,null]_U_[348.99..350.99GHz,31250.00kHz,null]</td><td>31306.9</td><td>XX_YY</td><td>2012-05-18_03:36:32</td><td>Falcke,_Heino</td><td>0.50392938</td><td>-</td><td>uid://A002/X391d0b/X23d</td><td>uid://A002/X40d164/X1b3</td><td>Monitoring_fast_variations_of_event-horizon_scale_gas_in_Sgr_A*_with_frequency_switching</td><td>S</td><td>TARGET</td><td>21.944484358557393</td><td>Y</td><td>1.0</td></tr>\n",
       "<tr><td>29</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/X7d80c7/X1324&amp;mous=uid://A002/X5a9a13/X79b</td><td>2012.1.00628.T</td><td>Sgr_A_star</td><td>266.41699999999997</td><td>-29.0078</td><td>6.0</td><td>0.541996</td><td>244.14101</td><td>756.0</td><td>2016-10-28</td><td>[260.05..260.52GHz,244.14kHz,null]_U_[260.31..260.78GHz,244.14kHz,null]_U_[261.80..262.26GHz,244.14kHz,null]_U_[263.54..264.01GHz,244.14kHz,null]</td><td>280.12</td><td>XX_YY</td><td>2014-03-26_08:00:12</td><td>Ott,_Juergen</td><td>0.66332996</td><td>uid://A002/X5a9a13/X79a</td><td>uid://A002/X5a9a13/X79b</td><td>uid://A002/X7d80c7/X1324</td><td>Molecular_Absorption_Survey_against_the_G2_Cloud_Sgr_A*_Accretion_Event</td><td>T</td><td>TARGET_WVR</td><td>15.819548375912355</td><td>Y</td><td>0.0</td></tr>\n",
       "<tr><td>30</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/X7b13df/Xf8a&amp;mous=uid://A002/X79f8ed/X3f</td><td>2012.1.00635.S</td><td>SgrA_star</td><td>266.41699999999997</td><td>-29.0078</td><td>7.0</td><td>0.54589498</td><td>31250.0</td><td>907.2</td><td>2015-03-17</td><td>[215.03..217.03GHz,31250.00kHz,null]_U_[217.03..219.03GHz,31250.00kHz,null]_U_[230.99..232.86GHz,976.56kHz,null]_U_[232.80..234.80GHz,31250.00kHz,null]_U_[338.66..340.66GHz,31250.00kHz,null]_U_[340.64..342.64GHz,31250.00kHz,null]_U_[350.77..352.77GHz,31250.00kHz,null]_U_[352.71..354.58GHz,976.56kHz,null]</td><td>1258.26</td><td>XX_YY</td><td>2014-02-22_08:59:36</td><td>Bower,_Geoffrey</td><td>0.68189752</td><td>uid://A002/X5d7935/X2fa</td><td>uid://A002/X79f8ed/X3f</td><td>uid://A002/X7b13df/Xf8a</td><td>The_G2_Gas_Cloud_Encounter_with_Sagittarius_A*:_Accretion_Structure_on_Scales_of_3000_to_1_Schwarzschild_Radii</td><td>S</td><td>TARGET_WVR</td><td>15.868455107956496</td><td>Y</td><td>1.0</td></tr>\n",
       "<tr><td>31</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/X7d80c7/X108d&amp;mous=uid://A002/X5a9a13/X79f</td><td>2012.1.00628.T</td><td>Sgr_A_star</td><td>266.41699999999997</td><td>-29.0078</td><td>7.0</td><td>0.23474699</td><td>244.14101</td><td>2963.52</td><td>2016-10-29</td><td>[330.36..330.86GHz,244.14kHz,null]_U_[332.55..333.05GHz,244.14kHz,null]_U_[342.66..343.16GHz,244.14kHz,null]_U_[345.57..346.06GHz,244.14kHz,null]</td><td>216.625</td><td>XX_YY</td><td>2014-03-26_06:42:00</td><td>Ott,_Juergen</td><td>0.67400306</td><td>uid://A002/X5a9a13/X79e</td><td>uid://A002/X5a9a13/X79f</td><td>uid://A002/X7d80c7/X108d</td><td>Molecular_Absorption_Survey_against_the_G2_Cloud_Sgr_A*_Accretion_Event</td><td>T</td><td>TARGET</td><td>12.706184307459052</td><td>Y</td><td>0.0</td></tr>\n",
       "<tr><td>32</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/X7d80c7/X14a8&amp;mous=uid://A002/X5a9a13/X797</td><td>2012.1.00628.T</td><td>Sgr_A_star</td><td>266.41699999999997</td><td>-29.0078</td><td>6.0</td><td>0.62992901</td><td>244.14101</td><td>756.0</td><td>2016-10-28</td><td>[218.55..219.02GHz,244.14kHz,null]_U_[219.35..219.82GHz,244.14kHz,null]_U_[230.33..230.80GHz,244.14kHz,null]_U_[231.11..231.58GHz,244.14kHz,null]</td><td>325.19299</td><td>XX_YY</td><td>2014-03-26_08:39:23</td><td>Ott,_Juergen</td><td>0.65146077</td><td>uid://A002/X5a9a13/X796</td><td>uid://A002/X5a9a13/X797</td><td>uid://A002/X7d80c7/X14a8</td><td>Molecular_Absorption_Survey_against_the_G2_Cloud_Sgr_A*_Accretion_Event</td><td>T</td><td>TARGET_WVR</td><td>18.715344585514305</td><td>Y</td><td>0.0</td></tr>\n",
       "<tr><td>33</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/X7d2ec1/Xbf7&amp;mous=uid://A002/X7d1738/X3f</td><td>2012.1.00635.S</td><td>SgrA_star</td><td>266.41699999999997</td><td>-29.0078</td><td>7.0</td><td>0.497491</td><td>31250.0</td><td>604.8</td><td>2015-05-09</td><td>[215.03..217.03GHz,31250.00kHz,null]_U_[217.03..219.03GHz,31250.00kHz,null]_U_[230.99..232.87GHz,976.56kHz,null]_U_[232.80..234.80GHz,31250.00kHz,null]_U_[338.66..340.66GHz,31250.00kHz,null]_U_[340.65..342.65GHz,31250.00kHz,null]_U_[350.77..352.77GHz,31250.00kHz,null]_U_[352.71..354.58GHz,976.56kHz,null]</td><td>1258.25</td><td>XX_YY</td><td>2014-03-21_08:53:07</td><td>Bower,_Geoffrey</td><td>0.63449371</td><td>uid://A002/X7d1738/X3e</td><td>uid://A002/X7d1738/X3f</td><td>uid://A002/X7d2ec1/Xbf7</td><td>The_G2_Gas_Cloud_Encounter_with_Sagittarius_A*:_Accretion_Structure_on_Scales_of_3000_to_1_Schwarzschild_Radii</td><td>S</td><td>TARGET_WVR</td><td>15.116660343333201</td><td>Y</td><td>1.0</td></tr>\n",
       "<tr><td>34</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/X7c6ce6/X11d4&amp;mous=uid://A002/X684eb5/X20e</td><td>2012.1.00543.S</td><td>SgrAstar</td><td>266.41899999999998</td><td>-29.008600000000001</td><td>7.0</td><td>0.419505</td><td>3906.25</td><td>167.14</td><td>2016-11-01</td><td>[341.09..342.99GHz,3906.25kHz,null]_U_[343.04..344.94GHz,3906.25kHz,null]_U_[353.09..354.99GHz,3906.25kHz,null]_U_[355.04..356.94GHz,3906.25kHz,null]</td><td>3355.22</td><td>XX_YY</td><td>2014-03-11_08:55:20</td><td>Martin,_Sergio</td><td>0.65702772</td><td>uid://A002/X684eb5/X20d</td><td>uid://A002/X684eb5/X20e</td><td>uid://A002/X7c6ce6/X11d4</td><td>Fuelling_the_Galactic_center_super_massive_black_hole</td><td>S</td><td>TARGET</td><td>60.786696636575428</td><td>Y</td><td>0.0</td></tr>\n",
       "<tr><td>35</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/X6f4350/X85&amp;mous=uid://A002/X684eb5/X210</td><td>2012.1.00543.S</td><td>SgrAstar</td><td>266.41899999999998</td><td>-29.0075</td><td>7.0</td><td>3.6629601</td><td>3906.25</td><td>189.393</td><td>2016-02-26</td><td>[340.98..342.97GHz,3906.25kHz,null]_U_[340.98..343.04GHz,3906.25kHz,null]_U_[342.91..344.91GHz,3906.25kHz,null]_U_[343.01..345.00GHz,3906.25kHz,null]_U_[352.98..355.04GHz,3906.25kHz,null]_U_[354.98..357.04GHz,3906.25kHz,null]</td><td>3355.22</td><td>XX_YY</td><td>2013-10-07_20:50:49</td><td>Martin,_Sergio</td><td>--</td><td>uid://A002/X684eb5/X20d</td><td>uid://A002/X684eb5/X210</td><td>uid://A002/X6f4350/X85</td><td>Fuelling_the_Galactic_center_super_massive_black_hole</td><td>S</td><td>TARGET</td><td>40.863503725726204</td><td>Y</td><td>0.0</td></tr>\n",
       "<tr><td>36</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/Xa25bbf/Xc8cf&amp;mous=uid://A001/X197/X33</td><td>2013.1.01242.S</td><td>Northern_Arm</td><td>266.41899999999998</td><td>-29.005600000000001</td><td>7.0</td><td>0.26793799</td><td>488.28101</td><td>151.2</td><td>2016-11-23</td><td>[289.54..289.78GHz,976.56kHz,null]_U_[290.52..290.76GHz,976.56kHz,null]_U_[291.14..291.37GHz,976.56kHz,null]_U_[291.28..291.51GHz,976.56kHz,null]_U_[291.49..292.43GHz,976.56kHz,null]_U_[300.74..300.97GHz,976.56kHz,null]_U_[303.47..304.41GHz,488.28kHz,null]</td><td>973.12201</td><td>XX_YY</td><td>2015-06-08_03:41:01</td><td>Yusef-Zadeh,_Farhad</td><td>0.4868778</td><td>uid://A001/X197/X32</td><td>uid://A001/X197/X33</td><td>uid://A002/Xa25bbf/Xc8cf</td><td>SiO_Observations_of_the_Circumnuclear_Molecular_Ring_and_Its_Interior</td><td>S</td><td>TARGET</td><td>15.234635175739298</td><td>Y</td><td>0.0</td></tr>\n",
       "<tr><td>37</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/Xa25bbf/Xc8cf&amp;mous=uid://A001/X197/X33</td><td>2013.1.01242.S</td><td>SiO_34_35</td><td>266.40800000000002</td><td>-29.000299999999999</td><td>7.0</td><td>0.267941</td><td>488.28101</td><td>151.2</td><td>2016-11-23</td><td>[289.54..289.78GHz,976.56kHz,null]_U_[290.52..290.76GHz,976.56kHz,null]_U_[291.14..291.37GHz,976.56kHz,null]_U_[291.28..291.51GHz,976.56kHz,null]_U_[291.49..292.43GHz,976.56kHz,null]_U_[300.74..300.97GHz,976.56kHz,null]_U_[303.47..304.41GHz,488.28kHz,null]</td><td>973.12201</td><td>XX_YY</td><td>2015-06-08_03:41:01</td><td>Yusef-Zadeh,_Farhad</td><td>0.4868778</td><td>uid://A001/X197/X32</td><td>uid://A001/X197/X33</td><td>uid://A002/Xa25bbf/Xc8cf</td><td>SiO_Observations_of_the_Circumnuclear_Molecular_Ring_and_Its_Interior</td><td>S</td><td>TARGET</td><td>15.231194433924157</td><td>Y</td><td>0.0</td></tr>\n",
       "<tr><td>38</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/Xa25bbf/Xc8cf&amp;mous=uid://A001/X197/X33</td><td>2013.1.01242.S</td><td>SiO_24</td><td>266.41500000000002</td><td>-28.997499999999999</td><td>7.0</td><td>0.26794201</td><td>488.28101</td><td>151.2</td><td>2016-11-23</td><td>[289.54..289.78GHz,976.56kHz,null]_U_[290.52..290.76GHz,976.56kHz,null]_U_[291.14..291.37GHz,976.56kHz,null]_U_[291.28..291.51GHz,976.56kHz,null]_U_[291.49..292.43GHz,976.56kHz,null]_U_[300.74..300.97GHz,976.56kHz,null]_U_[303.47..304.41GHz,488.28kHz,null]</td><td>973.12201</td><td>XX_YY</td><td>2015-06-08_03:41:01</td><td>Yusef-Zadeh,_Farhad</td><td>0.4868778</td><td>uid://A001/X197/X32</td><td>uid://A001/X197/X33</td><td>uid://A002/Xa25bbf/Xc8cf</td><td>SiO_Observations_of_the_Circumnuclear_Molecular_Ring_and_Its_Interior</td><td>S</td><td>TARGET</td><td>15.232193849435397</td><td>Y</td><td>0.0</td></tr>\n",
       "<tr><td>39</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/Xa25bbf/Xc8cf&amp;mous=uid://A001/X197/X33</td><td>2013.1.01242.S</td><td>SiO_21_22</td><td>266.43200000000002</td><td>-29.005600000000001</td><td>7.0</td><td>0.26793799</td><td>488.28101</td><td>151.2</td><td>2016-11-23</td><td>[289.54..289.78GHz,976.56kHz,null]_U_[290.52..290.76GHz,976.56kHz,null]_U_[291.14..291.37GHz,976.56kHz,null]_U_[291.28..291.51GHz,976.56kHz,null]_U_[291.49..292.43GHz,976.56kHz,null]_U_[300.74..300.97GHz,976.56kHz,null]_U_[303.47..304.41GHz,488.28kHz,null]</td><td>973.12201</td><td>XX_YY</td><td>2015-06-08_03:41:01</td><td>Yusef-Zadeh,_Farhad</td><td>0.4868778</td><td>uid://A001/X197/X32</td><td>uid://A001/X197/X33</td><td>uid://A002/Xa25bbf/Xc8cf</td><td>SiO_Observations_of_the_Circumnuclear_Molecular_Ring_and_Its_Interior</td><td>S</td><td>TARGET</td><td>15.237782423568659</td><td>Y</td><td>0.0</td></tr>\n",
       "<tr><td>40</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/Xa25bbf/Xc8cf&amp;mous=uid://A001/X197/X33</td><td>2013.1.01242.S</td><td>SiO_23</td><td>266.42399999999998</td><td>-28.996600000000001</td><td>7.0</td><td>0.26794201</td><td>488.28101</td><td>151.2</td><td>2016-11-23</td><td>[289.54..289.78GHz,976.56kHz,null]_U_[290.52..290.76GHz,976.56kHz,null]_U_[291.14..291.37GHz,976.56kHz,null]_U_[291.28..291.51GHz,976.56kHz,null]_U_[291.49..292.43GHz,976.56kHz,null]_U_[300.74..300.97GHz,976.56kHz,null]_U_[303.47..304.41GHz,488.28kHz,null]</td><td>973.12201</td><td>XX_YY</td><td>2015-06-08_03:41:01</td><td>Yusef-Zadeh,_Farhad</td><td>0.4868778</td><td>uid://A001/X197/X32</td><td>uid://A001/X197/X33</td><td>uid://A002/Xa25bbf/Xc8cf</td><td>SiO_Observations_of_the_Circumnuclear_Molecular_Ring_and_Its_Interior</td><td>S</td><td>TARGET</td><td>15.234260245688519</td><td>Y</td><td>0.0</td></tr>\n",
       "<tr><td>41</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/X960614/X1181&amp;mous=uid://A001/X11f/X4c</td><td>2013.1.01194.S</td><td>G-0.02-0.07</td><td>266.46499999999997</td><td>-28.997199999999999</td><td>3.0</td><td>1.87749</td><td>244.14101</td><td>1814.4</td><td>2016-12-22</td><td>[88.58..88.70GHz,488.28kHz,null]_U_[89.14..89.26GHz,488.28kHz,null]_U_[89.44..89.56GHz,244.14kHz,null]_U_[89.91..90.03GHz,488.28kHz,null]_U_[90.61..90.73GHz,488.28kHz,null]_U_[91.44..91.56GHz,488.28kHz,null]_U_[92.44..92.56GHz,488.28kHz,null]_U_[101.00..103.01GHz,31250.00kHz,null]_U_[102.15..102.29GHz,244.14kHz,null]_U_[102.52..102.66GHz,122.07kHz,null]</td><td>817.86499</td><td>XX_YY</td><td>2014-12-07_13:21:35</td><td>Gerin,_Maryvonne</td><td>4.4712744</td><td>uid://A001/X11f/X4b</td><td>uid://A001/X11f/X4c</td><td>uid://A002/X960614/X1181</td><td>A_CF+_survey_of_the_diffuse_medium_in_the_inner_galaxy</td><td>S</td><td>TARGET</td><td>1400.8330419870572</td><td>Y</td><td>0.0</td></tr>\n",
       "<tr><td>42</td><td>http://vo.chivo.cl:9000/tarball?asdm=uid://A002/X651f57/Xade&amp;mous=uid://A002/X6444ba/X10</td><td>2012.1.00080.S</td><td>GC50MC</td><td>266.46499999999997</td><td>-28.9893</td><td>3.0</td><td>13.8147</td><td>488.28101</td><td>1523.741</td><td>2016-11-23</td><td>[85.21..86.23GHz,488.28kHz,null]_U_[86.40..87.42GHz,488.28kHz,null]_U_[96.15..97.18GHz,488.28kHz,null]_U_[96.15..97.18GHz,488.28kHz,null]_U_[96.15..97.18GHz,488.28kHz,null]_U_[96.15..97.16GHz,488.28kHz,null]_U_[97.47..98.49GHz,488.28kHz,null]</td><td>1594.77</td><td>XX_YY</td><td>2013-05-31_09:13:20</td><td>Tsuboi,_Masato</td><td>--</td><td>uid://A002/X6444ba/Xd</td><td>uid://A002/X6444ba/X10</td><td>uid://A002/X651f57/Xade</td><td>Core_Mass_Function_of_the_Galactic_Center_50_km/s_Molecuar_Cloud</td><td>S</td><td>TARGET</td><td>949.78474555833873</td><td>Y</td><td>1.0</td></tr>\n",
       "</table><style>table.dataTable {clear: both; width: auto !important; margin: 0 !important;}\n",
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       "display: inline-block; margin-right: 1em; }\n",
       ".paginate_button { margin-right: 5px; }\n",
       "</style>\n",
       "<script>\n",
       "require.config({paths: {\n",
       "    datatables: 'https://cdn.datatables.net/1.10.9/js/jquery.dataTables.min'\n",
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       "require([\"datatables\"], function(){\n",
       "    console.log(\"$('#table4554426384-604693').dataTable()\");\n",
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       "        \"order\": [],\n",
       "        \"iDisplayLength\": 50,\n",
       "        \"aLengthMenu\": [[10, 25, 50, 100, 500, 1000, -1], [10, 25, 50, 100, 500, 1000, 'All']],\n",
       "        \"pagingType\": \"full_numbers\"\n",
       "    });\n",
       "});\n",
       "</script>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "almatab=res.to_table()\n",
    "almatab.show_in_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO: Auto-setting vmin to -1.796e+00 [aplpy.core]\n",
      "INFO: Auto-setting vmax to  3.434e+00 [aplpy.core]\n"
     ]
    },
    {
     "data": {
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Pxs7m/TO6fd4cu3ynHwzMs7FT1HreHLsXtn6fLwH7PBvLPBs7Za1/GX5z7Kze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\nJEmSJID/D4RtaZqYkqhqAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10f5cba90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#%matplotlib notebook\n",
    "fig = aplpy.FITSFigure(opt)\n",
    "fig.show_grayscale()\n",
    "fig.show_markers(almatab['s_ra'],almatab['s_dec'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# http://vo.chivo.cl:9000/tarball?asdm=uid://A002/Xa657ad/Xd3b&mous=uid://A001/X122/X2b"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "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": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}