FASTish scenarios.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "from astropy import units as u\n",
    "\n",
    "from astropy.coordinates import SkyCoord, Angle\n",
    "from astropy.table import Table\n",
    "from astropy.wcs import WCS\n",
    "from astropy.visualization import LogStretch, MinMaxInterval, ManualInterval\n",
    "from astropy import modeling\n",
    "from astropy import constants as cnst"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "from matplotlib import pyplot as plt\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "from matplotlib import rcParams, style\n",
    "rcParams['image.cmap'] = 'viridis'\n",
    "rcParams['image.origin'] = 'lower'\n",
    "rcParams['axes.prop_cycle'] = style.library['seaborn-deep']['axes.prop_cycle']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>.container { width:90% !important; }</style>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# a fun trick that makes the notebook always be 90% of the browser window\n",
    "from IPython.core.display import HTML\n",
    "HTML(\"<style>.container { width:90% !important; }</style>\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load relevant data "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import data_loaders"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/erik/miniconda3/envs/anaconda/lib/python3.5/site-packages/astropy/coordinates/angles.py:672: RuntimeWarning: invalid value encountered in less\n",
      "  if np.any(self_angle < wrap_angle_floor) or np.any(self_angle >= wrap_angle):\n",
      "/Users/erik/miniconda3/envs/anaconda/lib/python3.5/site-packages/astropy/coordinates/angles.py:672: RuntimeWarning: invalid value encountered in greater_equal\n",
      "  if np.any(self_angle < wrap_angle_floor) or np.any(self_angle >= wrap_angle):\n",
      "/Users/erik/miniconda3/envs/anaconda/lib/python3.5/site-packages/astropy/coordinates/angles.py:563: RuntimeWarning: invalid value encountered in less\n",
      "  if np.any(angles.value < lower) or np.any(angles.value > upper):\n",
      "/Users/erik/miniconda3/envs/anaconda/lib/python3.5/site-packages/astropy/coordinates/angles.py:563: RuntimeWarning: invalid value encountered in greater\n",
      "  if np.any(angles.value < lower) or np.any(angles.value > upper):\n"
     ]
    }
   ],
   "source": [
    "res = data_loaders.load_galfa_sensitivity('onempc_mass_sens.fits.zip')\n",
    "galfa_sens, galfa_sens_scs, galfa_sens_wcs, galfa_sens_hdu = res"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Fiducial sensitivity senario for FAST"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "* 7e3 solar masses of HI at 1 Mpc / sqrt(cos(dec)) from 0 to 53 degrees\n",
    "* 1e4 solar masses of HI at 1 Mpc / sqrt(cos(dec)) from -14 to 0 degrees\n",
    "* 1e4 solar masses of HI at 1 Mpc / sqrt(cos(dec)) from 53 to 66 degrees\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create a WCS approprate for FAST "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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t6+YA1SKmFRgSRexHmI7Vz5ypjmBsoIG7pzW/soGdQSnmOomKE9aTAlDD12m7\nthrgwA0+MIEBtA3h7b/6Edv9yRprwmxcWjcwiFZGEB04BoVyXuCpA0vJV4TkuBvQ6HKqzrtnWLeL\nwTDT01g4dQILx45i4aj7O34MWaOBxtgYGuvXobFxI/o2bURtyZIygPm6LzA0mzwERW2qzNvN/BeV\naXd4oY2p27/DE//wv6hxxbqp2fsevomZv4+ePC3pgc+zIES0fvDG3XfOPbh39fDrbsbIG25B1uz3\nD38EPFCmNX9OwAgo+3kUsFSlAb7jLAOTZivap6P0IvOaTWtNzmLq4BlMHjiDiYP279z+s2DDGF4/\njJH1wxjeMIwlG4axZP0QRtcPY3BFH7IMEfjEwQcBfMRfJAwEPqDAeLCsiR7KICWMSdhPzdXDDpDq\nEIC3a7vlENYTVr6GmpNUAyoBCI55hWM4QAoLkFotoDDAO//dR23nFwEGqVWm3VYtXVMGBQo66Kan\n9kWvAqBKaRWg0fF8CgQVnbQBw8zOYOHMSbROn3J/J/0WINRXrkRjbA0aa+xffWwM+dBQ6frk3ajy\nR0XXWmVSK21j0OkY/KCvpytQqWueW8DUl7/NE5//GvVt2Xhy9t6HbmbmfejJU5Ie+DwDIaL+wT27\n/mnu+/teNfTKPRj5wVciHxpUL3LotDTrif08QU+AR9IvhPUAyUfgUhBSZrc4ig2+7CxNi/I5VsMG\n7ck5TB+awNShc5g8PIHJQ5OYfNJu2/MFhlYPYmj1AIbHBjG0ehCjYwMYHhvAyFg/lqwZQP9ADiAO\nxdYsBs4El3sTnIkDHJwfBwigJvkyGNQBQFZF8KwnfF6BhPUQrKlOVltIAKjuQA3uvjVgt47IuCg6\nOPOi7RBbBfCj/+6jEbAExhNWO6g+745LzIQ6g5Del0ZUARRQLr8qvcN5026hNTmO9rlxtCbOoj0x\njta5s2ifG/f7lGWoL1uB+vKVqC9X2xUrkA02QZXrxKlrSI791gFSVfCCv38ipEClVF7ZHPeM/UYA\nzMwcJr/wDZ788reosXXjt+bue/gNzDyFnlyQ9MDnaQoR/UBt1fLP19ePYdl734LaCrdCj7wEEbgE\n4JE07b+RT8eUgwwUAMm+BheESaXe/6PZkAIXSUvBJ3csQbMfYR+xSSwEN2gzm/XPAK2pBcwcn8Ls\niWlMHp/GzLEZTB2fwdSJaUwdm8XkiVlkNUJzWR+ay/swtKxht8sbGF7RwNDyBkaWNzC8rIbmaA3N\n4Ry1nBIHBlmFAAAgAElEQVT2AwCFWwQ0+HRssIBlMw3XHgY71mMAhAi3LAIc9gBUc9cPH6Zt7xk7\nPb8OFQkYBbObgfX5vO/jHy2xHGSho/PzfFBhipPjqrwO9br5d0qRZ6gGImYDszCL9vwsitkptGem\n0J6eRHtmEu3pSRQzU2hPTaA9M4ViehLcbqE2PIraklHUR5aitsTtLwn7Wf9AqXPu5qc6L6iUGEm4\n95VAJXUi6FXmj/KWdTqyqm75QCjGJzH+15/D3MP7UZw9907Yyeq9jvU80gOfpyhEtG7gup2PLhw6\nOrDsx34IA9ddjdI3Sxz4BOABgPOzHnRgOKIbfDqijxLghGADa+KKTG6ujTqAQEBF+4QC+EhocjUb\nyhyLkA7bf0IhKtMGIDAbtKbmMXdmDtNn5jB7eh6zp+3+9Ol5zJyex9SZeUyfWcDcRAtzU230NWsY\nHHF/S+xfcyS34DSSY7CZo79J6BvM0BwkDAzl6B8kDDWBwcEMfU3CQD8cWwIyKgLDUQAkJri6//0M\nGmB/jwmMBgV/RsPfOwU+BfCTH/sIkFMEJpF/RMAF1BWkqjpsAwYXBUx7HkV7HkVrHqa9ANOyx6bl\n9lvzKOZnUMzN2u38LIq5Gfs3PwuzMIes0Y+8fwD5QBO15jBqg8PIh4bV/pA7HkHW3w/K1DXpjrqi\nY+/qJxKdUudePcFV7ndVugaJKjbl82rdTswoZUdIAbAbqwoy9/ABnP0ff4d8dGR+7qF91zDzfvSk\no/TA5wKFiGr911z1+wuPHfqpoVe/FCNvfjWyRh3IgvnrKbMenaZYjwejBHw8MAjYIABOOnlUwMSX\nq85rMMoi5hPAMawgoEANISQ6mLyCL4UQJoJqhoUoOMBFksk+wUerSXQbyICMQWtyATMTLcxPLmDu\nXAuzEy3MTixgfqKN6XMtzM8UWJhpY37GYH6mcH92f266wNyMQbvFGBjMUO8j1BsZ6g2g0SDUG4RG\nn/trALUGoU/O1Ql5zqjlsECfAfXM7md52K/l7nfJCK028Nkv3QQ7ome36CWD2dh9YoDDMZs2jGnD\nFG2wKdzWpnFh/4wp7LZowbQWQFmGrN6HrNZAXu9D1mjY43ofsrrbb/RZYOkbRNY/iLx/0B67bdY3\n4Jed6TiRVI47gEzH4IZO7EeldazDn+dyXqXfKf28bCpqRwdmVAFsJRCsAKro3rQLTH7pGzzxz1+l\nxsZ1fzP30KPvY+Y59KQkPfC5ACGiW+rrxr6ejwzR0vf9EOpjK/2DSP5BVqMrxXqEzZyf9UCBT+q7\nkTQNNjFoZaosDT6e+SBEp0VgAkCb2UDwzEUAKQInwAOFn6TqwEbmC4X5Oq5s79NhPw+IyfpobHv1\nZNEY9CSAwbITC1qA8UEArKLajDK1MYAaGXDbYH62QLFQwCwUaC0w2gttmHlGa8GgWDAoFhjthQIL\nCwa8wGi1GMYwyBjAAIVhuzK1YRTs9gsGG8C4PybgH750M4gy94kCsnNSiOI0i1agPEeW1UC1Oiiv\ngfIcVKuBshqyWh3Ia8gkLa8jbzRAeR6b8Pw+/H4nMOg0Z6iyQ+8AEqV8ybluTKQERFVtr8zLHcss\nA5duT4d8qMrXGUzOz4wqWBWA9ulxnP2Lz6J15DjaJ069gZm/gJ5E0gOfLkJEKwZvuHbv/L7Hlo6+\n680Y3HNtcJ5qYAHw1FlPyN8p0CDTOikgobu/R0fAxQAClMFEmeEis1sAlky1VRiMgI1f7cCXpYDE\n6YOCb4YUw8nVvgcpZb4DadBhF3QAAC6IQADI6cUAFMKv4cx/uYt0s3OGbN6GjLbFZwTr6xHTG1MI\nQmDIR+3YR7sZAPNtwr/52IejDjmY1MI8no6rEIDiDrViH5Xpao4QurCZTp17mqeijAsBmacCRCAk\nn2xIrqtrmdy5rg7pJRNdWi9UvU/DRNcRBBmYvf8hnP3zv0d9bNXZ2Qce3sXMh9ETAN7yvDiEiPqI\n6A4iupuI7ndfFQURLSWiLxDRI0T0eSJaovL8gdN/07PYDqIs+2A2PHQyXzKydM1//AiaN+72gQFB\nT3a4nE4ddL1wRZoDH6VT2b5ODeeKfVbJpX3bcZEqNC2CVT5VJOSNMz4feV2AYDjoGmQgtrFmxp0v\nfJV23ypnKECwS3dmTsfe9IIBcnDWdg6UtqszQ4YWZzCwD7RhuxQpgVCwGPoy+6E4x/cknZFhAQRm\nq7MAWw4zYYGtd8hwhgUmFBaK7dYdF66Owtj74Uhass9+n1R6tI/uOiQfeNPp7oYSM8iwrzPSdceS\n5sYB0Q9KSXpUhqpLp+myqJOOic9F6VDXiaQu/Sdlyh8TiAlkKEnvpG/zwFi0l3yl9njMoaDv8uj7\nbv+0TsV1yh+AwV07sObXP4LGxnVLs+bgocbasf9MlPYkl6csOuZDRIPMPOM+N/BNAL8I4B0ATjPz\n7xLRxwAsZeaPPxeftiaikYFrdx5unzk7tPwD70Jj41p3AvoJdbr67ZV0FWjgR1GdTW626PP7ezQb\nioINXP06zDqeXBrKL7Eez1ziiDjPkCAmMHsdYjrLfV0qck75fUgYBmm/kl15AI4p1dwIVpbFkf3M\n5auRLRNkFwiVN7wOO/bNXVi2gV27TdqQuyAJy65cVB602c+uE2fNfprlGP9bNpzZDo4Vyez5BgzY\n3Ycagq+PAcwuEP7tx38xAHP41E+YdHoepuIwFf4XzlR6J/ZSyW6oWrdTvRWDpYh5dKgz1enEViJW\ncCHtQnKuQr+Tea6qTZXpUXs6+4rsWV1WmfWUWRJXpAGtYydx+k/+CqjlM/N7929i5pO4jGXRITAz\nz7jdPtgJ5QzghwD8sUv/YwA/7Paf1U9bE9GLayuXn8tHR4bGPv4hNDYkwBPpVlWXpFW91GmdpWaH\nY//9+g4SsRRPYSrSXaJXcTukdVm1hP3ADQBgQCCXRrCswDMix2isnmVAYPvDZK6HMLAfXit8WyzD\nse0TtgPIWgUE8uyGmNBydwqcoe3aUHimI+zGMqyCMzDDsZIM7BgKOwTwM4c4Q8vtMxMWFCMq2O3D\nto2FASGDYcu4hAUJE2or5kOsWIi7AWFEblmKZxmVjMOBeMoS9Ahfj8Y5Pa+YUBXzqGJDmi2hokxT\nrhMVZVcxoIi9VTAFStulry+5T2l7Qj2BrZTKNUnbKpgMCaNK2YtmYcKi/F9cfjhOWJM7V1+9Eqt/\n+efQt2njYD665AQRvRyXsSw68CGijIjuBnAMwBeZ+bsAVstnDdy3dla7/Ydh5/zdDuCTz6BOaqxf\n+x+yoeZdo295Ay/7sbeDGhf4hfHzmtzOdz4WARES3YrzUYlddKUiedc82NjhfgIwoblGDVcZmc9n\n/SsBpIzbJ9fZQ4ENOaCw9QYzm1HAZTtvW2bh9NiBCYHQYnvOAhA54LMzdQhwpjYxxQnoWdAgB4AB\naOy+cWAm4BI8SZ5PYgHWbChfEjKuTYUywxWJ2a1lstCpAbbzV6awyBTHcOayBJzcfQmddzCpRcDT\nBRDi8y6/BrekY4/AL+3Q03ydzGiJjgedig6/BAopaKlzGoj8oEm3owqwErNYJaCkgJgAUaV5ruIe\nEod6IlCOwE2DFYGyHEt/+E1Y/mPvRDY89PX+bVv/8HI1wy06s5sIEY0A+DtYs9vXmXmZOneamZc/\nW/UM7LJmtpX/6n2or17pzBDyxAPQx2LRSE1ubl+Di1/RwJXRKcQabhtFtyGY4qSsyKyGKrOb3rfl\n6smhwfwWh1SLXrV5DT66DQRvsrP1pya5sHIBYM1lTGqtNzCyzCBjqTuY5iSgQIIJrAkNYDAaZM1g\nsrQOw0aySZm5owfWpBYi6aSXyd1+gyzE2vMBQusADBlvehMzHCMEFxRgH4xgTYGx2W1iivCb//7n\n7UFqcpOHSDBdJpcy3Bo96hyS/AHT5cHrHEBQYXJK86Y6542Uo7gtIh1XT0CX9A75z2uCq9imA7Cq\ntvrrjPKfx8TWIR0I73/pfpDXcMccn6+qj4H22XGc+u//A6jls/N7919xuZnhFi3iMvMEgK8CuA3A\ncSJaDQBENAbgxLNRRzCzLRla87EPBeCJlJA8hEDKZkrCSZY0vzrPHYqXGtKxAaUvntKL85D/cWXU\n6M9Ds49wOQz73rDU401xJN1uYEaQwZ0wDuv4D0EMIZDAsx23HwaKluHYNtgb3WYALmCAGY4BWfZl\nWMxycKYxOLNX5q/Fmv0s0zGO6TjYw4Ir17BNl/LsQFWYUBZMbMjQgjAee1yA0NYsSJhPO3PmNo4Z\njh+5MyTwQEboBHhTHBRD0Q7wEsPxbKjiXIXJKjZjqTZ0Y0/dzGYpA0gY1/nKekpsSqdXMaXkWtP0\nyATo86uABVbp56tTBSFI3krWCSSMiCrYkH0XaktHsfp/+zn0XbFxwJnhXoHLSBYV+BDRColkI6IB\nAK8H8BCAzwL4Saf2EwD+/hnWo8xst/HyH307qF5XCmmOFAHOV8EF6pxHrURKKU7TIMIh0bMlk+pB\ngZTrrLNkeKZBgt1o2ThEFt+H5CWWBWmsf6ftXr4ItFhCFyQv+Yg3bW5ruXM+zflkZJhasN1vsw/g\n9mliOmMPOk7f6bVc51E4QGPOgo8Hki4+IJu3YHL+IgdGzhdkdD4HQgUIrSJXnZ/r5KE6MQ0Azozm\nQUib2cBRp1gFQpFJrgpkqsxn2rTlwY7h/VMVeSrNZmmHj0Sng0mrE8BEAFVlqkvBrQuQpZ18BEAp\n0LlnQgNRycRm4jxx+RSb9ToCEaqBSK43z7H0h96E5e95J7Lhoa/1b9n86cvFDLeozG5EtAs2oCBz\nf3/BzP+JiJYB+EsAGwA8DuBdzDz+NOsYGnjRzqPts+NDK3/amtnC241gcgMCiCQmuCjYQPYzW0bl\nkjoq3/nMboAzW4n5TEBKm9IomHyqFhMlhH3f9WuznWtXjQAbORbP95E69ARUa1ILeXN3TkxeMu8H\n4BBx5vO6ZWycno5+Y8gkU7tfh4soI3bmOTtnx5BdJidjABQWIrWeOflEA2KTG9hHtokZTetJWo44\n6s1GtFkvkMz3MbArMWSw0W8SKed+ZZw40Yf/+ps/oUxp9jcXEFY46vM4+6TSQxwZJ4MBCn9eT5um\nRDcx7XCqp8tK69VldMuj81XpddCJ23oBedP0tLxO+dN0JOcrriu9p/r9r6qzOo/sc2Udvu4on+pn\nALTPnsOpP/pTIMum5vcd2MTMp3EJy6ICn+daiGhZ44oNp+prVtPyd78d1KiXwKWrv8cdE+mHhqMH\nL4RZS74QQh3OB/CRNO/ulnXbKA619noORHy/RcHHEvl69L6UB9f5U6gzy1y94MSXFAOVX/YGAZRq\nbpspsMld51xToCRgI/qhDOMBsOb8MZZX2Lw1YjDHIdg5AWAdLm78ZFEJ5QaMAh0HHCQAY/09BhZA\n7D20H6QryK7bZu+BQcYW9ASQZCFShv3MgvwGhoEjhwfw6f/jx+DQrBpoGM8chNw5n7fUCVM1OHTq\nxGU/Su8OZJ068k5A0rmtcR2pXjcQ7AgKFaBTSpP0pMyOQKTrPF+eqE0dgIg71AWAiwLjf/+PmH3o\nYW4dP7HhUp6UelnQOwAgojX1sdWn+q/cQst/7F0WeLS4B6KjVGE0d9lPyoownsPTHA2ACInvhiry\nChi5POq8zUvxPouJTM2yT3wwSPaNVwx5xRQmM/Fl0igYMM7/ImHNxEDbnbNQQJAwabD2H2UwbMtq\nOROaDWG2EWo26g0ulDoDc47C9aQONpx5jQBnXgt+HBeV5t74BWVSM968Z9PaEB9TFiaQssCg8wWx\nmN9CCLY2u83P16w5y110ZKoCvKnLYXlixuIoMo4Aa5IpUDLHRSY5pOW4H74qyq3CXxIeNERmOUiE\nXTo5NjV5IbmWKnNfqX0Veolp8ry+nw56kdlO161NcPo9knPd/FtRCDeF97WT/ynxL3nTnj4n9aP8\nG2Z5jmVveyuae25AbdmyQ0S0BZeoXGA88QtbiGhzbcXyA80bXsIjP/BqkHjtK0ZonQs5j063slRd\nfu4Ow08o9CMkDSzsMMqnyYEDJWcqMyDLLBhgssHKsg927IUJ7JiPz8uAIZuX1b4BkINgWFgGoSBG\n7reuTrINNBmQMcMQWdbDhIKAnDO0yaDGBCMmPM5gyCBjQosseyg4A2XGghlljm3Y6zBMfsWHNgg5\nS9QbgTkDk73WBQA1N1rP/fXYe7YAW49xQAoSIAVazkRXOHCFB392P2Om8skqC7b3MGrcZgDMt+ph\nMGFcCdJZ6UeAbfuQkZAMsLmAcxns9TrgB+w5d0n+edGPHrvfH85/F59Tz6EehYdH1V1D9zIkgWRf\n2pGWax/W0vMd6enyEOvJOUr00EEPndqq3zFVr7ekV73nUdmkroHjOqVs9xzpdBCpayovEaRfcQAY\nff1rKBvo53Nf+PJ+ItrFzA/gEpNLnvkQ0c58dMmBkVe9kpf8wGuJ1IKMlSARZS6fp27nq8pKytQP\nfic1dg+rPMzRHB7FWuTFsc+5YyryVCvQkiVwPMvhEKVmGCDFcsAhCKCQ3kY6HhZW4gbq7iUzRD6f\nrce9b+yWyGFC212wRKmRYkCFsY9hmwFWDEQmm1oWA4DsORsRZ5e/AYU5OpLPL5njmIpxzEkmjBYu\nwk1YEBAmkLb8vJ7MR7QVDoTaTkfO6Xk+83P1eKRvgDT6zTMafprnhAk5hlUa4XP1KD6NkKuMilN/\nlYyjUxkVzviqeT2kRvz+XdD1dmNXFcwnbWMnhhQxJU7KFn3EYFdZNleUrVhNyuKoS512UFI9j8j/\nARh5+c209K0/yNnw0P1EdCMuMbmkwYeIbsiHhx9c+uY38fArb1FDDycXADbpPp/nvOwLMKSjytSE\nVsrqQENGatIPyTkp13Bors7vuA9AKE3odINPpOa4tmRw4OTNbACMsSM9w45NsIz6VdSaB67MA1fb\nmwwzzwIEbNocwMZ2/LaDJ5CfmGoc6MjEULBMOs0ceIhpTYEOk49YM86kxw5YmDMHHkCLyZkKMx/p\nJhNebb7Mm+K8uc1F14WQawEhuz8zW49Aw3duhQIT6czcb9IVoORclTlOOi0NQih3lClI6Ai5jua0\nxJxXBjZlkjPJeY7zpYBCaaeMqvIrQKSDXkfT14XodTL5qboqQRZVZVMZiC6kTlTkS+7L0PUvoRXv\neReyoeYdRPRqXEJyyYIPEd2aDTW/u/zd78TQnutdT6gUXOd+4QV2OdcJxBxr8Gra86mAxD7wruMn\npec6T5vXFih9m2UmUlao0Ccpf5Fe8kZ8NQEQVFkRYClm4kZqlu24pWwcYygEQFKwEeaEADbirxF/\niwc+38dmYON0HMNhx5qEudhK3MoExi51A/EZEfn5O+KvgQcm2w49X4e9nj0nPivx8RQKyDQLKlhA\nKQDU/FSf6vQ4PBfSARn367hOuxzS3AGE+AJAqHDnE+Do3CEz/AoLqa4ru1MHHvtUAghFjKkqn26L\nLkvfJ5Q76vOxq46h16a8rdRL2qTvYcSG9O+Y5C0BESSEu0udJXbmgEhWVhB9AM1rdmLVT/w4sqHm\nV4jorbhE5JIEHyL6wWyo+dWV738fBnddo06gel+Ek20nwOkENp3KUfuByQTzH6sC0uABgpjSwjmw\n7Uwzik1wAmYmAR4PWD5wwAGLAzoBM2NsWuUkUrb1htWlyb9oEjTQdj4ODzYIc3v8kjcczH1Mmavf\nmcMcALUYsL4ZYVgCiG4law82mQUN2Ou0ZbugCBPMa23PXgILksmlLSbHnOLAghh0Ms98YlNcAKnZ\n6T6QYj1+Dk24kWUQ0h3XhYBQsmSPP4fkfEWHWwk0GoS0ru7sgaijrWIEKZhRVb60LVWmL10+Oujp\ntlUBYmLG6siouLNepVlOv2hJeaWyffkdzHIdri+0R4AopA9cuQ1jP/3TyIeH/56y7MdxCcglBz5E\ndFs+PPQPq3/6pzCwfVt35U4gUmXP0g9fupCa0mOt50fqbpfLWT0oIYBQxHKks/d5yRcbDbBdB619\nPzqfBxlhO2zTvEkNUmZgScKM4ADEuDTxubS9+S74howb9Rm2YGOc38h+cM2tLJCATdvVIZFpxi0O\nCsdE7IoF9pyATeFAT1ZD8AwHjsUQ3EoEYeUC9sASzGvCggRkxK+jFxMtFMh4EELs85mbbsSg0wmE\nog7+KYKQdIQahDTrgAIVb+brYmbjWN/rItatAoBSxy3lyATWKsC7EDaUAhGUXtpurVfVvk6MQ+2n\ngNUxEg+hTlTVKdeB8j3raparaJvPJwM89072bdyIsX/9c8hHRv6EsuxH8QKXSwp8iOjqbKj5T6t+\n8ifQt+mKskIKJhfg4/EjEV+JAhhJ8HkU2OjiIh9OtelNH4vPR8BGpwHSJwnIBJYSAMi2RVhK4f02\nbv6GZxs2TUxqAniBrViwEnAI5sA0ACGY2Apjr9Ob0TiY28THU7jy/OpsYqoz4VzL+WTaDrwK5cNh\nZCAPNjZU2taTeTOd+GOEVcl0W6N0ApsJIdbsmU4IVmhpUxxn8b4DsNmpOmQladuJcdQxehBKO+4q\nEEL5nO6kNAh59iIdaaHyIm1DZzCIWIw2pWkAQHcwqSonqheIO+oubKhUh86fgEbEys7HctD52kum\nvU5tRXxNpd8T3dogZrmK+4fqa9HnG6vHMPYzP4NscPAzL/QghEsGfIhoWW358oeW/eCbuX/LZpvI\nqVKyXwU2QAlsonxpmVyRXgI1Kul40xunOmW2EoGMAolwLlyO3QYmImkStszsB1KQZXeMeynaDqyM\nahO7rTCgADICCsJWApiIH8gCiawcLX4hMY0BMBJgoM1owryE+WUeDGWFavmInHw+Qeb2+IAAMb0B\nkOg8CTKIQAfi/9I+HHvfU59O+Hhc4u9xZc1N9gfQkRuoVqP2nRO6gBBUx18FQtrkVgIGjkxofnQt\n7EcDYwpC6bEJD1aps69iNLo9aTkVbOi8gFN1fUlaRwBFt7Yguu8lxpGymPO0Ndz7Dvr6Pj0VNtSl\nHQDQWLMGK971LuRLltxBROvwApVLYp4PEdX7t2490Vi/HsM33Wh7L0YZWqUnLu2TGsaodNGTtE75\n02oYYQ4FXNkcqmEgsJtMbeFj1ZKoNwKxnYOTeVbkQCpjBw52bC9zcKxJzc5vyXx+CfhjENk8ubAY\n18AC9iMKbdgVBtpMqBGjcFuGmO1sWgZGAYJ8wjp34JV5oGPAZCjIICNCi61OCxnqBBRsvS+G7Nwi\nhp0LRAw4fEPBdsnSNttldwrOUINddSBzEWxExr2f9obKR7VbYOR2hpP9CeXmwyDjzN43YgfCDtTk\nWWCA4OYTuXJliljmAyss2ViYaoCYPeiRGxEwpAMhsHoe/Xws/RDJqDmz833IsT4Wky3bC2C2D4Jv\nln5sidUzA//cAfKswLNfPT9IP/bxox1mPYnVVxg4KWX9zEt7ZQxUWZLoItGRBP0OUXKNqs3yeqX5\nIz1Wesk1dy0jqdvd3riMtHyoOnWbKwa7oQ3k8nOpzQgbNxC0Cc1rXoTWseM8fe89jxHREvUdtBeM\nXBLg09x93QEzP5cve/ObfZoOVwZcp98JOEpMBdVgE4GZepo4efI8wriXUjco65A3etAtCAWQYfsJ\nbwEZ9bKzIVBmOz0m9iwnc51QRjJh1GaSjsc4kJGJowURcnITOwXQXNMM2YmkFmTcRFRXLikbIQvI\ngNCOQMyCgp2MCjex1U4+lYmnSMAmJ4OC7cTVAmSX4YlALQO78gB2pjtjJ6MCaAEWdNgoMyaBWWAp\ncyveGAc6BoYs+BXW4YSCDHJQyAt212DcPCT7oxkGFsTnI4MH92OS/a53dxASfZEUhFxZTO6cQ1Hx\niylsBDJ5ZGUiI4VOVHwXdraxAy41a78KRJCUBweKssSPAEXy6ohUg4kCSKi6KuoO90mVmYKFKEg7\n1LtESqkEiuqadQWVbVJ1y42oArgSyOlGakAjWLZDOj+pa1VApNuh6h999WuodexYLRsc3EtEG/gF\ntlbaC97s1rd23X9cOHpk/ar3vQ+Uqcvp9jNUgY3bRnbcCKAo0qssPs3rX4LwFmu/jc7nRzUIJjVW\nehKJlg7ZrE4cFQfIKJ68Sa3wZVM478qTyDVfjpuVasR/Y2BDrBlRsICUy85kB3I+IOczgWubBCrI\nMjvePOfqKVQoNjO8aaztfVMqLNotwyPpbSZEH4hjBP8N5MumWeTP8V81ZRd44PMGH48ONPDXjDTU\n2i3Fgwyt2Xps0oGMZDn4CZwZKp0jY5+7OFDBm7hSn5A8o75Ml8GwqxOJ34Njc520A0m9vm0CkiiZ\n3FKTnK+jSkcfc3ytvmy5P+gwV6nCpwTdpqo6k3e5ynyXltnVN6Tut65bX1NltJ1RZchLmeZJ2nlB\nviH9jBFhxTvfBZ5fWNe3adMf4wUmL2jwIaLXFJMTv7b6Ax9E1j9gE10n2yVXDBIdwQad9Xxap3oo\nGvGV9DXIuM5bA5Ad2Oo5saEjl+g0exzKkeg2mfsjZaX+H7jO2oMMIRxLpw6U/TceXOyxnNefW/Dl\nAxHItD3IBLARkGGQ/0yCAGZoY1hRQXxBbQcgLZb5QnFev0Ybx/N9NAAVDB9UYI8toATQCZFufkIp\n4m8AhXXe7LY1X4MODoid7S7dAYT8OF1BSD93CQilHSvpegSEpHPznat7SLTfplDlo3rSaNVxVJ9q\nawk8VIfcCUwCwHEMkl06+6hNUieSOtV7F4FolZ6p0Cv9LuX2+zKA0vUgKeOCfEOoyi8gVLGuHANZ\nvY7VP/EBtM+O/zgRvQMvIHnBgg8RXZkPDX151Xt/HI2VK9QJhAcPyb4+ZpwHbCjW75YX59cXM0wE\nMuK3IXhGYlXkk9HSsdsGlqPT9DkNLragMEfHgpYECbBrjzAKIHwGW8BFdPzH2Jg8UPp6nK6dXxNA\nRlY3aEtAAMiX5VclcMEDAnxtV0/bgY1mVBIIYCDh2QpYBIQ4BAbY7leBhStDgELSJUChhfhYggxk\nnkUHgzMAACAASURBVJKezyMfjwsg5FZgmKEEbOTH5CSdQYUs2Ol+beZS51piQtJZdQs+SEFBdXoB\nHNzwImEuaXBCVyZTAimpjxOWh1IbSx1/p7bjwgFMgxRQoavexzSq7emyocq6K/Qq2RBU99HhGqrb\nFUBIl1sbHsHY+38S2WDzr4noxXiByLMGPkT0B0R0nIjuU2m/QUSHiOgu93dbon83Eb3padSVN9at\n3zv6mtfzwLYrO4MNJ/nSA1Z6CjyiByMqh6K80gmXanDlsXoYPWBpkGEof0Ss6+f8SBLb8lnVm04+\n1UxGgwyxZjfkyxEWJWHXIAUyAnDKxNZmWW9NgQy7yDQSYAr5JUKNHBMBwmoJhQJG9iYwWUUhhFHr\nCZ8ebDyokGc0AoaW9cBH3zGyElgsQNZxC6DDFJvRYtCxkXsy6bS8qnUGgnzJFKETPx8I+VG2O2bF\njHzn2AGEpJyq+T4lUOgAUkg6eigg8iDE1dFbSZ3+WIANnXUqO/gKQCN5garqTq7H5xXw0514F5Nc\npIdymd3b2AFku7Gm9DeC6h/0NXD5L+S3zzupMvrXbcDKt76Na8uWf899iHPRy7PJfP4QwBsq0j/B\nzC9xf/8MAER0DYAnANwA+2XSpyQDW7f931lfH43ccgv5BwoogUWnCZ3pg1g67yUGm6q8XFGv31c+\nHsB2zhqA7LsfsxtdJkM6dEQ6xjOYJK/TF5AJbqqY0QChwxcQ834cDwxheR2JAuNoK+Aik0q1aU2F\nZEPCuUOdnv1QzGAgjIZt8AIjgzGBcQljMlDHrD5zzWHejwaXNuSLpgrISK/VZsuSeUGeGQnjUqHW\nwaynPrvNGcD9AUDEh3JeEEIEQv4Lo2KeU7OIfYi2fgY1CHUCmZQpVY78Q34ZfEV+Iahrqqqj8pjD\nw5907JVAlnbcJmm/vr4LALCoXajoxNV9fErzhjiuw5edtukC9OKBAOKBh2pLp/vs50y432roupdQ\n39p11L9p8/+HF4A8a+DDzN8AcLbiVJVjpADQBNBARZffTYhow/zRw/96xdveCSqhi6qRKX7IUoXK\nWpWXJXlAQzlUTouCETRgCdgE3XjdtpBW7f9JzG+qnSWQYUkPW8MSJGDL8pM7WbbBpAbEICPX4jwI\nsQkPqACXACoWIBXIpGYyz1o0oGURCIaygm9GltZpc/iUtU5vaXZE5MFE2lhoEGEJNgjf+BGTWqGD\nCRKQkdWsw/wft+ac6pzhAYdL5qwYhLSDn5VZDdE5n0+XA4T6ihi8fDkRgKCaSaSdfFQXKvxCyfnz\n+omSMtEFPCo72KSslKkl+ToDWKLbhQ2VQEG35QJMcp2YXqSHDm2F6oUu6B6R+gNWvOVtWDhx4h1E\ntBOLXJ4Pn8+HiOgeIvo0EY0CADM/DKAO4HYAn3wqhQ1evfPRJS97OfetWhUBCKl9VO1zokdd9KI8\nVWAT5/XBBVq8vvhIkvIjkEFkfkv9P7aOqnXebBmhI0dgNAqIQp4QsabbFjEZBSoAIpAAVYCKP3Zs\nSZgLhMEEM5y91iwy44WAA1mpQK/fZtNbnqlowLMgZIjcx+bCkjvx5NP48wg+UMCDkAQOZAkIZR6E\nJCjBVICQ+JEoBRzXWVamqc64GoTURFPPWDjqrLxJTLMqxaDEpFZt+hImUxGcAJW/m19I+ak6muC4\nQ5lIOuoUEDp13IrplSIJ03uggSEBlEqwUO9nFbhoUx46tLlSn5N6qsBGl9vJJIdyu0rXCaA2vATL\nXvsG7lu/8S4iWtQ+/ee6cZ8EsIWZrwNwDMB/kRPM/GFmvpGZv3ahhRHRD7dOnepb+qrXEpIHwe+n\neUo7oqv9Myq/YjGeBlfl7cRoqsrmADKAdORBj1X+4P9RZSBmJBpUvL8mARnZsmuP1K99QAB8WDUb\nFZQAQqFABggh1RpU9DmA/JdK/WrUrr42h7BoJlnwUy/gGYAOBMiXUcUc5hmcZyoSRBDAI+zLemsh\nAMH7eziOZGN9zPIdoThwQYNQFROSUG3vJ0mc711BSPmISiCkTXC+wypHyFWZzXwnXGWy4jQvup93\nIAaoEbtmeMov1L2Oiva6Z7Lko1F5SgChO2jtY6ro5LuauTjUmYKFSAqi0Mcop1W2Uad30zNxeyKw\n1GnoUqZjuktuupkA9IHog1jE8pyCDzOfVBOfPgVgz9Mti4iGa0tG/27lD78TVFOfwNbAUGIzFQCD\n5AdFmuc85fjyymk+ok3nSUDGF6kByNenGYyUqc65cn1/UQUyrg4NKkCIdIvABCp0WspjZ8pTZjlZ\n400AqGA4s1YaxWbBxYdhy1ab9TiY92QBUQ0cKVhoc5jM04FiJAJg+rs86JDu5/moSDb98TptTuvG\nhHRknIRha8CJwKYCcKgirQRC0J2UikCT46cDQpV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UO+0GOO02K9f8K4KNiMP0KUcz/5Cz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pAAAg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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x110c7abe0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "wcs = WCS(dict(WCSAXES=2, \n",
    "               CRPIX1=0, CRPIX2=0, \n",
    "               CDELT1=0.2, CDELT2=0.1, \n",
    "               CTYPE1='RA', CTYPE2='DEC', \n",
    "               CUNIT1='deg', CUNIT2='deg',\n",
    "               CRVAL1=0., CRVAL2=-15.0,\n",
    "               LONPOLE=0., LATPOLE=90.,\n",
    "               RADESYS='FK5', EQUINOX=2000))\n",
    "\n",
    "xg, yg = np.mgrid[:1800,:850]\n",
    "ra_g, dec_g = Angle(wcs.wcs_pix2world(xg ,yg, 0), u.deg)\n",
    "\n",
    "plt.subplot(projection='hammer')\n",
    "ptmsk = slice(None, None, 10)\n",
    "plt.scatter(ra_g.wrap_at(180*u.deg).rad[ptmsk], dec_g.rad[ptmsk], c = (xg+yg)[ptmsk], lw=0, alpha=.5)\n",
    "plt.colorbar(orientation='horizontal').set_label('pixel number')\n",
    "\n",
    "# the FAST zone edges\n",
    "lon_all = np.linspace(-np.pi, np.pi, 100)\n",
    "plt.plot(lon_all, [66*u.deg.to(u.rad)]*len(lon_all), c='r')\n",
    "plt.plot(lon_all, [53*u.deg.to(u.rad)]*len(lon_all), c='k')\n",
    "plt.plot(lon_all, [0*u.deg.to(u.rad)]*len(lon_all), c='k')\n",
    "plt.plot(lon_all, [-14*u.deg.to(u.rad)]*len(lon_all), c='r')\n",
    "\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Now generate the sensitivity map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "outermsk = (-14<dec_g.deg)&(dec_g.deg<66)\n",
    "innermsk = (0<dec_g.deg)&(dec_g.deg<53)\n",
    "\n",
    "sens = np.zeros(dec_g.shape)\n",
    "sens[outermsk] = 1e4 * np.cos(dec_g[outermsk]).value**-0.5\n",
    "sens[innermsk] = 7e3 * np.cos(dec_g[innermsk]).value**-0.5\n",
    "\n",
    "sens = sens*u.solMass * u.Mpc**-2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### And plot it like for GALFA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "galfa_min, galfa_max = 0, 5e5\n",
    "galfa_stretch = LogStretch() + ManualInterval(galfa_min, galfa_max)\n",
    "galfa_minst, galfa_maxst = galfa_stretch([galfa_min, galfa_max])\n",
    "\n",
    "def show_sens(sens_arr, name=None, fig=None):\n",
    "    if fig is None:\n",
    "        fig = plt.figure(figsize=(20,6))\n",
    "    else:\n",
    "        plt.figure(fig)\n",
    "    plt.imshow(galfa_stretch(sens_arr.value.T), vmin=galfa_minst, vmax=galfa_maxst)\n",
    "    if name is not None:\n",
    "        plt.title(name, fontsize=24)\n",
    "    plt.xlabel('RA arcmin', fontsize=24)\n",
    "    plt.ylabel('Dec arcmin', fontsize=24)\n",
    "    cb = plt.colorbar(orientation='horizontal')\n",
    "    cb.set_label('Log Sensitivity ({})'.format(sens_arr.unit.to_string('latex')), fontsize=24)\n",
    "    ticklocs = cb.formatter.locs\n",
    "    tickdata = galfa_stretch.transform_2.inverse(cb.formatter.locs)*galfa_stretch.transform_1.vmax + galfa_stretch.transform_1.vmin\n",
    "    cb.set_ticks(ticklocs)\n",
    "    cb.set_ticklabels(['{:.1f}'.format(np.log10(d)) for d in tickdata])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/erik/miniconda3/envs/anaconda/lib/python3.5/site-packages/ipykernel/__main__.py:20: RuntimeWarning: divide by zero encountered in log10\n"
     ]
    },
    {
     "data": {
      "image/png": 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PBm4ELgJeWuVfaZIkSdIo8cwCSferqnuT/DGwguYypfcZFEiSJEmjxzMLJEmS\nJElSHwc4lCRJkiRJfQwLJA0syaFJvp/kB0ne0nU96laSa5N8O8mlSS5q5y1JsiLJlUnOS7K4p/0J\nSVYluSLJId1VrrmU5H1J1iT5Ts+8aR8XSfZP8p328+afh/1zaG5NcJycmORHSb7VPg7tWeZxIklD\nZlggaSBJFgDvAp4DPAF4aZJ9uq1KHbsPOKiqnlxVB7TzjgfOr6q9gQuAEwCS7AccBewLHAacmiQd\n1Ky59wGaz4leMzku/gV4VVU9Hnh8krHr1NZtvOME4B1VtX/7+CxAkn3xOJGkoTMskDSoA4BVVXVd\nVW0AzgCO6LgmdSts+u/IEcBp7fRpwJHt9OHAGVV1T1VdC6yiOaY0z1TVhcBtY2ZP67hIsguwQ1Vd\n3Lb7UE8fzQMTHCfQfK6MdQQeJ5I0dIYFkga1G3BDz+sftfM0ugr4XJKLk/xBO29pVa0BqKqbgJ3b\n+WOPn9V4/IySnad5XOxG8xmzkZ83o+OPk1yW5L09l6t4nEhSBwwLJEkzdWBV7Q88F3htkmfQBAi9\nvOWOxuNxofGcCjymqp4E3AT8U8f1SNJIMyyQNKjVwB49r5e18zSiqurG9vkW4FM0lxWsSbIUoD1F\n+Oa2+Wpg957uHj+jZbrHhcfLCKqqW+qBe3r/Gw9cquRxIkkdMCyQNKiLgeVJ9kyyLfAS4NyOa1JH\nkmyf5KHt9CLgEOBymmPimLbZ0cA57fS5wEuSbJvk0cBy4KKhFq1hCv3Xnk/ruGgvVbg9yQHtQHav\n6Omj+aPvOGmDpI1eAHy3nfY4kaQOLOy6AElbh6q6N8kfAytogsb3VdUVHZel7iwFPpmkaP4tOb2q\nViS5BDgzybHAdTQjmFNVK5OcCawENgDH9fwPouaRJB8BDgIenuR64ETgbcBZ0zwuXgt8EHgI8OmN\nI+NrfpjgOPmNJE+iudPKtcAfgseJJHUl/q0mSZIkSZJ6eRmCJEmSJEnqY1ggSZIkSZL6GBZIkiRJ\nkqQ+hgWSJEmSJKmPYYEkSZIkSepjWCBJkiRJkvoYFkiSpK1Kkm2S3Jfk3iS7dl2PJEnzkWGBJEmT\nSPKB9ovp2McdSb6b5N1J9pnmOv+zZz0vmqvaJUmSZsqwQJKkwfwCuKl9rAG2A/YF/gi4LMnvDrKS\nJDsDhwDVPl4xJ9XObwVcCXwf2NBxLZIkzUuGBZIkDearVbVr+3gU8BDgMOAaYFvgA0kePsB6fg/Y\nBvgosA4vKRM0AAAgAElEQVR4ThsgaEBVdV9V7VtVT6iqW7quR5Kk+ciwQJKkGaiqe6tqBc2Xf4BF\nwCBnFxzdPr8X+CRNcPDyzV+hJEnSzBkWSJI0C1X1NeBn7cv9Jmub5FeAJwI/rqovAKcD4YEAYUaS\n7J/k5CRfTnJ9kruT3JrkgiSvTJIJ+v1tO27Ce5IsSPK6JBcl+Wk7f78x7R/e9vlm2+ZnSa5M8pEk\nzx/T9lXtOla0r1+e5GtJbk9yc5Kzkzy+p/2u7fgP1yS5K8kPkrx5vNonG+Cw92dqX7+y/ZnubGs+\nP8lvzvy3LUnSaFjYdQGSJM0DG7/QbjNFu2Norrf/aPv6fJrxD56Y5Feq6tsz3P7ngYe10+vaxxLg\nWcBBwOFJXlBVNU7fovnPg3OA36YZA+BnwH29jZIcBHy8XW/RjOHwM+AxwHLghTSXY2wiyT8Cb2rX\nfTfwcOAFwDOS/BrwoPZneBRwB83v8bHAycCuwBsH/1Xc/zOR5AM0QcwG4C5gB+A3gYOS/E5V/cc0\n1ytJ0sjwzAJJkmYhyYE0lyAA/HCSdtsAL21ffgSaa++BjzH7sws+A7wYeFRVPayqHg48tF3nGuBw\n4HUTlQYcRfMl+jXA4rb/o4Dr2tofRxMm7AhcAhxUVdtV1SPb7RxKc0nFeJ4KvLZ9LK6qxcCTgFXA\nI4C3AR8GrgaeWFVLaIKPE9v+f9J7BsKAQhNevAh4dbvdHWkCiC/T/P3zronOuJAkSYYFkiTNSJKF\nSZ4D/Hs7awPNF/+JHAbsDHy/qi7rmX96+/yyNlCYtqp6WVWdXVU398y7q6o+DLyE5svzcZOsYhFw\nXFW9t6rubvvfUlXr2uUn0/yv/EqaoODLPdv5eVV9rqpePMG6Hwb8TVX9S8+6Lwf+kAe+1O8JPLeq\nVrbL766qvwO+1LZ5wbR+IY3FwDFV9b6e7V4LvIxmXy0DnjaD9UqSNBIMCyRJGsyBSW5sHzfRnE7/\nGWAv4F7gNVX140n6H0NzevzpvTOr6mLgKuCRNIHC5vYl4E5geZJHTNDmZuBD4y1I8jCaMxMKeGtV\nrZ/m9u8G3jlBXb9o1/vunmCi1+dpwoJfmuY2AX5YVWePnVlVq4Fvti9nsl5JkkaCYYEkSYNZSHNm\nwM40X+xD80X3J8DTqmrcL9sASZYAz2tffmScJrMe6DDJUUk+1Q5weFc7yN99NEHGDm2zXSfofvEE\n4xlAcxnBApoxDFbMoLQfVtVdY2e2l2CsbV9+d4K+a9rnJTPY7iWTLFs9i/VKkjQSDAskSRrMF6tq\nm6raBngIzXX3Z9MM1ve+JIsn6fsymsH/LmpPhR9r49kGz0uy43SKai+HOAc4A3g+sBtNiHELcFP7\n2DhY4aJxV9K0ncjS9nntDM4qALhxkmX3TtFm4/IHzWC7d06y7O5ZrFeSpJFgWCBJ0jRV1Yaqury9\nTv884FeA/ztJl1e0z0/b+D/+vQ/gB+3ybWnGGJiOP6IJCX4G/DGwe1VtX1VLq2rXqtqV5jIDeOCu\nDWPdO8F8SZI0ogwLJEmandfRfNl+UZJnjF2YZB+aU/lrgMdMLkV4Ydv3xHYQwb5xE5IsBHaa5jp7\nbbwUYKck289iPZIkaStiWCBJ0ixU1SoeuP3h34/T5Jj2+Us018hP9FhOc7nAAdO8VeCy9vmyCZY/\nk+aMhZm6mCYMWUBzi0RJkjQCDAskSZq9f2yfD0zyzI0zkwR4Oc3//J9VVXdM8rgGuLDtOp2zC25v\nn584dkF7K8a/nfZP06Oq7gDOpQlD/rdnF0iSNBoMCyRJmqWqugw4n+YL9V/1LDqYBwYc/OQAq/pE\nu47fm8bmP9f2OTHJ85IsAEiyH/BpmoEYZzIwYa8TgHXAfsCXkjyzDUJI8pAkz0/yH7PchiRJ2oIY\nFkiStHm8vX1+dpID2ulj2udvVNVkdwXY6BM0wcKyJM8ecLsnAz8EdqQ5A+CuJD+luR3hQcBrgNsG\nXNe4quoHwOHAT4EnA18A1ie5lWZgxXOA58xmGx2YaLBHSZKEYYEkSYPYOADhxA2qzgcubV++NckO\nwJFtv48PtJGqH9GMEQADXopQVWuBpwP/Cvyo3d56mts6PqOqNt6WcaL6p/zZ2u38N7APTSjyXWAD\nzVgIq4AP04QJM1n3IMsnq326fQbdriRJIy1V/lspSZIkSZIe4JkFkiRJkiSpj2GBJEmSJEnqY1gg\nSZIkSZL6GBZIkiRJkqQ+hgWSJEmSJKmPYYEkSZIkSepjWCBJkiRJkvoYFkiSJEmSpD6GBZIkSZIk\nqY9hgSRJkiRJ6mNYIEmSJEmS+iycTeftsqjuZv3mqkWSJEmSJG0+11XVXjPpmKqa8VaT1MF5Yc+M\n/hMVsiBjOkxj+SbLMqbpgkmXM+XyMesbU9tU25/W9qbsO9W2ZlnbNLdXm7Tvfzmdn21a69oM/Tdp\nP+blJu0XTLJsir5j1z1VrVPVNtX2Nl0+5nXPfp2q7Wy3Nev+m+zHSdY/69o29/Lp7se5rGXy5dNe\nH5Mv73097Nrm8nczZdsxhl9r/57ZnMfYtLc11pTbG3NUTaeeKfpOd1tj37rTrm3sO2ST9U+8fLJl\ng9Q2tv+m/3ROr7ZNP8IH396CKdtOXutU/Rcwy/7TWL7ptiZf17RfM7z1Lch9s6ylv/82U/affHvb\nTLd9336Zat1TrWvMcqZYPvZnn6L2qZff17Ns8tqnXesm/af63Uxc23j9N13/A683WfcUtW7ye5ri\nZ9/09zrF727K9lMdk5PV2m+bMZ9D24z5FN20/djl/a837T9m+Sb9F4x5Pbb9ggnbAmzzqFVUTfkv\n+ri8DEGSJEmSJPUxLJAkSZIkSX0MCyRJkiRJUh/DAkmSJEmS1MewQJIkSZIk9TEskCRJkiRJfQwL\nJEmSJElSH8MCSZIkSZLUx7BAkiRJkiT1MSyQJEmSJEl9DAskSZIkSVIfwwJJkiRJktTHsECSJEmS\nJPUxLJAkSZIkSX0MCyRJkiRJUh/DAkmSJEmS1MewQJIkSZIk9TEskCRJkiRJfQwLJEmSJElSH8MC\nSZIkSZLUx7BAkiRJkiT1MSyQJEmSJEl9DAskSZIkSVIfwwJJkiRJktTHsECSJEmSJPUxLJAkSZIk\nSX0MCyRJkiRJUh/DAkmSJEmS1MewQJIkSZIk9TEskCRJkiRJfQwLJEmSJElSH8MCSZIkSZLUx7BA\nkiRJkiT1MSyQJEmSJEl9DAskSZIkSVIfwwJJkiRJktTHsECSJEmSJPUxLJAkSZIkSX0MCyRJkiRJ\nUh/DAkmSJEmS1MewQJIkSZIk9TEskCRJkiRJfQwLJEmSJElSH8MCSZIkSZLUx7BgnvnJ+uu7LkE9\nblv7w65L0Bh33HhV1yWox7rr3B9bmrtWuU+2JHd9z39HtjRrL7uh6xLU49qLb+m6BPW47Ovruy5B\nm5FhwTyz9i7/AduS/PQ2/8jb0tx509Vdl6Ae6673i+mW5u6rfI9sSe5aeU3XJWiM2y77UdclqMd1\nF9/adQnq8W3DgnnFsECSJEmSJPUxLJAkSZIkSX1SVTPvnNwELN185UiSJEmSpM1kTVXtMpOOswoL\nJEmSJEnS/ONlCJIkSZIkqY9hgSRJkiRJ6jOtsCDJ85P8+QDt/r8klyc5eealaSJJliW5IMn32t/z\n68Zp82dJLk3yrbbNPUl27KLe+S7Jg5N8o/19X57kxHHavCzJt9vHhUme2EWto2LAffKsJD9t3yPf\nSvJXXdQ6CgbcHzsm+UT7Hvl6kv26qHWUJFnQHvvnjrPMz6wOTLFP/Mwasin2x8OSnJvksvZz7ZgO\nShwpSa5tP5MuTXLROMv3TvLVJHcneVMXNY6SqfZHT7unJtmQ5AXDrG8UDfAemfb3wzkZsyDJT4El\n5YAIcyLJLsAuVXVZkocC3wSOqKrvT9D+ecAbqurgYdY5SpJsX1Xrk2wDfAV4XVVd1LP86cAVVXV7\nkkOB/1VVT++q3lEwwD55FvCnVXV4Z0WOkAH2x9uBO6vqb5PsDbzbz6y5leSNwFOAh419H/iZ1Y0p\n9omfWUM2xf44oZ1/QpJHAFcCS6vqng5KHQlJfgg8papum2D5I4A9gSOB26rqHcOsb9RMtT/aNguA\nzwF3Ae+vqk8Mq75RNMg+6Wk70PfD6Z5ZcHSS/7+d/kCSdyb5SpKrNqZFSc4BHgp8M8mLprN+Daaq\nbqqqy9rpnwFXALtN0uWlwEeHUduoqqr17eSDgYVAjVn+9aq6vX35dSbfX9oMptonrQyvotE2wP7Y\nD7igbXslsFeSRw6vwtGSZBnwXOC94y33M2v4ptonG5sNqZyRN8D+KGCHdnoH4CcGBXMuTPLdpapu\nrapvAu6H4Zh0f7T+BDgbuHnuyxGD7ZONBvp+OJMxC3r/wNulqg4Eng+cDFBVRwDrq2r/qjprBuvX\nNCTZC3gS8I0Jlm8HHAp8fHhVjZ72VMVLgZuAz1XVxZM0/wPgM8OpbHQNuE9+rT2F9L887X1uDbA/\nvg1sDJ0PAPYAlg23ypFyCvBmxg/RxvIzazgG2Sd+Zg3PVPvjXcB+SX5M8/n1+mEVNsIK+FySi5O8\nuutiNPn+SLIrcGRV/QsGncMy0HtkOt8PZzvA4acAquoKYOdZrkvT1F6CcDbw+vYMg/E8H7iwqn46\nvMpGT1XdV1VPpvly87SJ/ohL8hvAK4G3DLO+UTTAPvkmsEdVPYnmj75PDbvGUTLA/ngbsCTJt4DX\nApcC9w65zJGQ5Ldp7rl8Gc0fcBP+Eedn1nAMuE/8zBqSAffHc4BLq2pX4MnAu9u/yzR3Dqyq/WnO\n+Hhtkv/RdUEjbqr98c/0/9thYDD3Bn2PDPz9cMqwIMlxGwdCAB41ZvHPe5tOtS5tPkkW0gQF/15V\n50zS9CV4CcLQVNUdwH/TpHV9kvwy8B7g8EGuJdLmMdE+qaqfbTw1vqo+AzwoyU4dlDhSJtkfd1bV\nse1ZaUfTBNA/7KLGEXAgcHh7beNHgd9I8qGxjfzMGqop94mfWUM1yHvklcAnAKrqauAaYJ+hVjli\nqurG9vkW4JPAAd1WNNoG2B+/CpyR5BrghTSBmmOuzKFpvEcG/n44ZVhQVadW1ZPblOLGSZpmgmnN\njfcDK6vqnRM1SLIYeBYwWZigWUryiPZ3vfG0nt8Cvj+mzR40p/r8fvtHhebQgPtkac/0ATQDvq4d\naqEjYsD9sTjJg9rpVwNfnOSMKc1CVf1FVe1RVY+h+YPhgqp6RW8bP7OGa8B94mfWkAyyP4DrgIPh\n/n3zeAw450yS7TeeuZFkEXAI8N3JugylsBE1yP6oqse0j0fT/AfncVW1yZ1FtHkM+h6Z7vfDhbOo\naew1XDXJMm1GSQ4EXg5c3l4DXMBf0IwAW1X1nrbpkcB5VXVXN5WOjEcBp7Ujvi4APlZVn07yhzyw\nP94K7AScmiTAhqoyEZ87g+yTFyb5I2ADzSi9L+6u3HlvkP2xb9vmPuB7wKu6K3c0+Zm15fEza8sy\nZn/8HfDBJN9pF/+54c2cWgp8MknRfH85vapW9O6TNrS5hGbAyfuSvB7Yz+B5Tky5P8a097vh3Bt0\nn0zr++Gc3DpRkiRJkiRtvWY7wKEkSZIkSZpnDAskSZIkSVIfwwJJkiRJktTHsECSJEmSJPUxLJAk\nSZIkSX0MCyRJkiRJUh/DAkmSJEmS1MewQJIkSZIk9TEskCRJmoUkv5bkU0nuSLIhyRMmaXtWkvuS\nfDvJPw6zTkmSpsOwQJIkaRaq6mtVdSRwCnAVcMx47ZLsAtwDFPD8qvqzoRUpSdI0GRZIkiRtHvcB\nHwJeliTjLH8u8OnhliRJ0swYFkiSJG0eBXwY2AU4ZJzl2wK/GGpFkiTNkGGBJEnSZlJVNwBfAH6/\nd36S/YFvdVGTJEkzYVggSdI8luQL7YB6r+ii/7DWubkluTDJL5I8ZgbdTwOOTLKoZ97Tq+qizVTe\nlNK4IsmdSR45rO1KkuYPwwJJ0rQk+WD7Re+CrmuZrSTbJDkmyWeS/DjJz5OsTbIyyX8meUuSp3Zd\n5yxV+9hEkqOTnJjkl2fSv8Oa5lSSw4FfBz5aVT+cTtf2+eM0P9+L2vUtZMDLD5LsnOT3khyV5KVJ\n9prG9u9XVQWcBCwC3jqTdUiSRtvCrguQJG115uLL49AleQTwGeApPPDz3N0+Px7Ym2ZAup8COw29\nwM3neuBK4PZxlh0DPBO4BvjODPp3VdOcaQcm/AeawQr/YSbrqKp1ST4BvAL4IPAc4LMDbPtJwP5V\n9f6eeS9OsntVfXkGpZwOnAi8Jsk/VdV1M1iHJGlEeWaBJGkmxhvpfWtzOk1QcAfwZuBRVbWoqnYC\nFgO/BbwbuK27Emevqo6uqv2q6pwu+g9rnZvRocB+wJer6spp9u0N0T4EPDPJ7sBeVfWjyTom2QY4\nqDcoAKiqjwH7JNl+mrVQVffSXBKxLfDH0+0vSRpthgWSpJGTZG+aMKCAV1bVO6rq5o3Lq2pdVV1Q\nVX8C7NtVnerEH9AcF2fMcj0XAD8GXg/cOkD7Xwc+OcGyDzP+3RUG8dH2+ffbQEKSpIEYFkiShibJ\nC5J8NsnNSe5OckOSDyd58hT9FiR5Q5JvJ1nf9v+PJL/eLr8vyb1J9hiwlCf+v/buPVrOqrzj+PdH\nCAEChJTFRS5J6FJKiVyEcisIoghy06BAIYRyEQoWKkvbFIqyrAWtgOVqsUigBDBUEEsEl5AoKVlE\n1HJVsCICAQKEW7iYCyQhT/949pA3kzlzZubMyUnM77PWrJk579773e+cZJ3Z+937eSqvf9SsYEQ0\n3WsuabSkayU9JWmBpNdLcLxTy171+vIzS3/3kTRc0sWl7tuSZkn6jqTNmpxvsKQzJc0o51ooabak\nhyV9S9IedeWXCyZY4gIsAfYlV4nU4lDUHk/3Un+Lyme+XZO+DpH0Ril7WB/79JSkkZX3zc47VNLc\nUm7/nso1qPcnwKHkZMH3W61XMbI2IC8xA24ETgFur5SpffeqX52zRW2bgKQR5Xe6W2lrAdD2yoJS\n9wngEWBj8trMzMxa4skCMzPrd0oTyQHYx4ENgXnA5sBY4H8lndZD3TWBO4CLgQ8Cg8rjYGCapE/3\nsXtbdFpR0hnkQOx4YCQZxG4osCfwbWCKpLXrqtViPmwFPETeed6Y3CP/PvLO9gxJwxqcbxAwFbgE\n2ANYH/gDGVNhe+BzwOd7OF/VAmB26W+QsQNmVx4vNasfEc8D08vbsfX9rDgY2AB4jYwP0Zc+vVwG\n01PL8RObnPdocnA9MyJ+0qRcvf2AwcATEfFaq5Uk7akM+HkC8JCkz5ZDE4FJETG/TGBMAr5Rjk2W\ndFGlmee0NPPCXOAX5OeGMqvC/Dauo94McnKi09UJZma2GvJkgZmZrQhnkXnnlwBfBoZHxEbAlsDN\n5N+jKyTt3aDuueQ+8sXkwHqDUncUGTRuQgf9eaDy+t9LsMO2SBoDXE4O7MYDG0fEMHKQ+gngd+Rd\n8kt6aOIKcnn6nhGxPrAe8CkyoOIo4J8a1BlLBv+bB4wD1i2fxRBysqI2edFURNwcEZsD95UfnRkR\nm1ceezSrX0wiB6BHNykzlhzY3xoRi7vUpwnlvOMk9fQ95sRy3oktXEfVXuX5gaallu/7fRHx0YgY\nFBE7RMQ15eePR8Tnyut5ETE2IkaWcjtFxPhKM/eRgRCJiDkR8amIeLIcOw6Y0ua1VN1fnj/chzbM\nzGw148kCMzPrV+Wu6Nnk4O0bEfGvETEPICJeJAeU95J/k86vq7se8MVS99yI+FZEvFPqPgd8Bmg7\nwntEPE0GoIMc2M+SNFXSeZI+2dvkQRmkXlr6dUSJeTCntL04IqYCB5F3y0+StGl9E2Tmhf0j4pel\n3pKIuKN8BgKOaHDqPco5r4+Im2pbJCLNiohvR8QF7X4eHboFWARsLWn3+oPld3dweXtT/fE+uI2c\nZNkEOKTBeT9A7v8PMhNBO3Yr9VZ4FoaIWALcK+kUSe9tUSgrZ34VEX1ZWVCbQNqu/H80MzPrlScL\nzMysv32cXIq+ELio/mAZJJ1HDpA/LGmTyuEDyGX9b5N34uvrLia3J3Ti5FL3HXLp+UeBL5GD0Zcl\n/UJST0vsPwKMAB7taZl7mZD4OZmm+CP1h4GrIuKNBlVvK89bS1qn7thb5Of0vp4va8WIiNeBu8rb\nYxoUGQOsAzwfEfd08byLyIkeASc1KFL72bQOUgXWPtdWAhJ2XUT8GvghcLyksZKOA34eET/rY9O1\n6xFQP3FlZmbWkCcLzMysv+1cnh+JiDd7KDMdeLeuPEAt8OHDTe6sdpJ/vrYCYDwZO+A08u7378it\nEgHsCtwoqVFU/L8sz9tIerGnR6XcVg3auL/BzwCer7zesO5Ybd//GEmTJR1egvINlNpWhKOqd8OL\nY+lOVoFGaltPDpa0ce2HZcXHceW813TQbm1FyYCly4yIlyLiuoiYFBE3RMQLXWi2ej1tb7kxM7PV\nkycLzMysv9UGc8/3VKBsLajd/dy4cqg2sHmxSft9GkxFxKsRcXVEjIuIbcm7y6cAz5YiR0r6u7pq\ntTvQa5HL4Xt6DCnlGkWy/0MP/Xmn8nZw3bHpZAyHRWRk+1uBVyX9RtJFkt7f2/V22WQyfsKm5MoM\nACRtBHysvO3mFgQAIuK3wM/IVRvjKoc+QQbNfJOe0xA2U/t9Nc2AsQp6u/K6frWKmZlZQ54sMDOz\nFaU+K8BKKSJeiYhrgV1YmhWgfrl77e/n5BKsrrfHv3Sxf18DtiEDIN5JDoz/DPh74DeSxjWp3lUl\npd/k8ra6ZeMociD/eEQ81E+nv5pc1VDNinASuapgUt2kS6vmlOf6FR2ruuGV1y1neTAzs9WbJwvM\nzKy/vVKeR/RUQNIQYKO68rB0tUGzPfr9sn+/pM6bTA5It6k7XJtE6PGa+lNEPBMRF0bEwWTaxP2A\ne8gB+pWdZHfog9pWhMMl1VZCHEMZtPfjeW8mYziMlrRLWc1waDn2nx22Wfv3NrxpqVVP9XoGJB6D\nmZmtejxZYGZm/e3B8vwBST0N7PclB7rV8gC1u9I7SWq0lB/6Nx3cvPJcvyy9lt5vhybXtEKUTAjT\ngcPI7QlDgb9osfqS8lwfb6AdU8i71cOAQyRtydIUhJ1sQWipT2VVQ639k8gYCWuRQSfbSn1Y8Xh5\n3rrD+iurUeX5zYiYPZAdMTOzVYcnC8zMrL9NIe8ADwbG1x8sQenOLW+nR8TLdXXnkVsYTm9QdxDw\nhXY7JGmUpD/tpcw6ZER/gIfrDv8UeA4YRIMMD3XtdG1Je+XOfSMLWRokckiTclVvleeO+1gyUtxC\nDu6PAY4ur++PiCc7aLKdPtW2IhxNxpkIlgY/7MSM0t5yky2Slkh6dyV+LJH07vKXBGSwTsg4D2Zm\nZi3xZIGZmXVqsKSNenmsWbIYfJ0chH1e0jm1XO+SNiej5e9FDnS/XD1BRMwFLil1z5d0hqS1S90R\nZIC/UR30fTTwuKRbJR0pabPaAUnrSjoMuJe8wxzApXX9WgycUd6OlfTfknastDFY0u6S/g14uoP+\n9eR6SddKOkDSepXzjSTTCa4NLKD1DBGPkZ/tpyVt0Id+1bYbHErGEAjgux221XKfIuJBciJnQ/J3\nurAP54X8nQN8qD67Q0Ss0WJ8ioF6rBERg3q4rl3J38n0Pnw2Zma2mvFkgZmZdWovMr5As0ctdeA3\ngYmUQT/whqTXyLvzR5ATBWdExIwG5zkPuIvcpnA58JakOcBM4CDg5ErZVoPaLSL/Bo4Bvge8IGme\npNeBuWSsgp2AxcA5ETG5voGIuJ1c/v4O8EngodLGq8B8cqvCF4D1W+xTK9YGjqcENpQ0R9JcckLi\nqNLfv4mIOU3aqLqBHGDvTWZVmCXpaUltpaOMiHvJ7BHrAH9ObiX4Xjtt9KFPE8h/VwH8sI1rX05E\n3A88RW7l+Ein7axMyuTafuTnc/MAd8fMzFYhniwwM7NORAuPJe8VjlgSESeSEwN3kXnfh5JpD78L\n7BYRVzU8UcQi4BAy2v+vyQHxYuB2MtbB3ZXib7TU+YgpZAaBfyBT7D1R+jy09O0BckXDjhFxQZN2\nJpZ2LgUeLf1anwwiN43cXrFto6qtdLPBz84C/hH4MfAkubVjDeD3wDXAzhHRclDBiHgc2J+cfHiD\nTIE4gkw/2K7/YunvflpEvNRL+W716QeV150GNqy6lqVbG1Y6ko6XdLKkmyQd3kKVQ8h/k9MiYmb/\n9s7MzP6YKKKV7ytmZmYrJ0kfA6YCMyOiaRwC++Mj6VhyNcIsYGT08YtNCVg5k4ydsHmZrFopSNod\nGBYRUyRtSq6CGFEyd/RU51ZyBc0xEeGVBWZm1jKvLDAzs1VdLWjilAHthQ2U08jVDNf0daIAICJe\nBK4iU1Ke2Nf2umwbSqyMsnJjPrBlT4UlvZ/cIvOYJwrMzKxdniwwM7OVmqQ1JN0i6cBqwDtJ20n6\nPnAAucf9igHrpA0ISZ8lY2e8Qw7wu+U8MgvHWSVbB5L2lHSbpLckLZI0ukm/binZCR6R9M1udSoi\nbqBMYEjajoyv8WiTKmeT3/W+1K0+mJnZ6mPN3ouYmZkNKAGfKQ8kvUX+/Vq3HH8XOD0iHhuY7tmK\nJGkLMsXheuTd/wAuiIjZ3TpHRLwi6ThgR/LO/bMRcR8wRtJXyWCSJ9A4FehmZOyKAA6LiGe71a/S\nt9dKpobzgKMjomG6xFLm98D4EozTzMysLY5ZYGZmKz1JpwIHAtsDm5CB/WYD9wCXRcTDA9g9W4FK\nmsinyACazwDfiYgLV+D5v0KuZDkD2LJ+64Okk8hsG9cBW3d7sqCc42zgJyV7g5mZWb/wygIzM1vp\nlUwJ3VxmbquoiHgGGDSQXQBuJFOAHkBm96hai9zC0C8k/RVwR0Q8KulDwIKI+G1/nc/MzFZfniww\nMzMza0NEPCfpf4DjqEwWSNoZeBDYur6OpBPItJcbAacDHwSGA6OAM2tpDSWtCXy1lJsDDAEmRMT/\nSRH5KZkAAAI6SURBVNoPmAAsKNsM1iBX2piZmXWdJwvMzMzM2jcRuFLS0IiorSTYIyKulLTcZEFE\nXCfpJeB2YF5E/DOApL8F7pE0OiLmAtcCr0fEaeX4T4GvkPEJpgHr9/uVmZmZ4WwIZmZmZu1Qeb6V\n3JJwJLy3ImBhL3Xnk/Giflz52QRgQ+BUSTsA44D/qBy/GLisC/02MzNri1cWmJmZmbUpIuZJ+gHw\n12QwwwOBOztoZ6GkXwF7k4ERA3iycvxHXemwmZlZm7yywMzMzKx11ewH1wP7SNoKGBURszpsc1Bp\nt/as5sXNzMz6nycLzMzMzDpzN/ACcCbwaicNSFoHGA1MA2aQEwXb1pXZpW/dNDMza58nC8zMzMxa\nN1LSIICIqKVRPIUMXFhT+37VaIWAJI2pvD8TmAVcHRG/JGMhfLFSeBhwUPe6b2Zm1hrHLDAzMzPr\nhaQ9ga8B+wK7SrosIq4hsyIMj4j5koYCVwN7lWqTJU2NiPF1zW0g6RxgGJn6cJ+IeLscGwucL2kS\nGbtgMXBhv16cmZlZA8pJcTMzMzPrT5L2Be6OiEED3RczM7PeeBuCmZmZ2Yrh711mZrbK8B8tMzMz\ns34m6Vjg8vL6TknbD3CXzMzMmvI2BDMzMzMzMzNbhlcWmJmZmZmZmdkyPFlgZmZmZmZmZsvwZIGZ\nmZmZmZmZLcOTBWZmZmZmZma2DE8WmJmZmZmZmdkyPFlgZmZmZmZmZsvwZIGZmZmZmZmZLcOTBWZm\nZmZmZma2jP8Haa8KUvSf8E0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x110c7a668>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "show_sens(sens)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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xDhzBOjAGIiTW95EY6SW9oY+eTWn6R+L0DZoku3V0VSYVK5ISiMVscIS4qTDF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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x12ef01d68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplot(projection='hammer')\n",
    "ptmsk = slice(None, None, 10)\n",
    "plt.scatter(ra_g.wrap_at(180*u.deg).rad[ptmsk], dec_g.rad[ptmsk], c = sens[ptmsk]/1e4, lw=0, alpha=.1)\n",
    "plt.colorbar(orientation='horizontal').set_label('Sensitivity [$1e4$ {}]'.format(sens.unit.to_string('latex')))\n",
    "\n",
    "# the FAST zone edges\n",
    "lon_all = np.linspace(-np.pi, np.pi, 100)\n",
    "plt.plot(lon_all, [66*u.deg.to(u.rad)]*len(lon_all), c='r')\n",
    "plt.plot(lon_all, [53*u.deg.to(u.rad)]*len(lon_all), c='k')\n",
    "plt.plot(lon_all, [0*u.deg.to(u.rad)]*len(lon_all), c='k')\n",
    "plt.plot(lon_all, [-14*u.deg.to(u.rad)]*len(lon_all), c='r')\n",
    "\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Now compute detectable halos given that sensitivity map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import data_loaders, detectability"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading /Users/erik/projects/m31-galfa/elvis_data/PairedCatalogs/Hall&Oates.txt\n",
      "Loading /Users/erik/projects/m31-galfa/elvis_data/PairedCatalogs/Hamilton&Burr.txt\n",
      "Loading /Users/erik/projects/m31-galfa/elvis_data/PairedCatalogs/Kek&Kauket.txt\n",
      "Loading /Users/erik/projects/m31-galfa/elvis_data/PairedCatalogs/Lincoln&Douglas.txt\n",
      "Loading /Users/erik/projects/m31-galfa/elvis_data/PairedCatalogs/Orion&Taurus.txt\n",
      "Loading /Users/erik/projects/m31-galfa/elvis_data/PairedCatalogs/Romulus&Remus.txt\n",
      "Loading /Users/erik/projects/m31-galfa/elvis_data/PairedCatalogs/Scylla&Charybdis.txt\n",
      "Loading /Users/erik/projects/m31-galfa/elvis_data/PairedCatalogs/Serena&Venus.txt\n",
      "Loading /Users/erik/projects/m31-galfa/elvis_data/PairedCatalogs/Siegfried&Roy.txt\n",
      "Loading /Users/erik/projects/m31-galfa/elvis_data/PairedCatalogs/Sonny&Cher.txt\n",
      "Loading /Users/erik/projects/m31-galfa/elvis_data/PairedCatalogs/Thelma&Louise.txt\n",
      "Loading /Users/erik/projects/m31-galfa/elvis_data/PairedCatalogs/Zeus&Hera.txt\n"
     ]
    }
   ],
   "source": [
    "elvii_pairs = data_loaders.load_elvii_z0(isolated=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading /Users/erik/projects/m31-galfa/elvis_data/PairedTrees/Hall&Oates\n",
      "Loading /Users/erik/projects/m31-galfa/elvis_data/PairedTrees/Hamilton&Burr\n",
      "Loading /Users/erik/projects/m31-galfa/elvis_data/PairedTrees/Kek&Kauket\n",
      "Loading /Users/erik/projects/m31-galfa/elvis_data/PairedTrees/Lincoln&Douglas\n",
      "Loading /Users/erik/projects/m31-galfa/elvis_data/PairedTrees/Orion&Taurus\n",
      "Loading /Users/erik/projects/m31-galfa/elvis_data/PairedTrees/Romulus&Remus\n",
      "Loading /Users/erik/projects/m31-galfa/elvis_data/PairedTrees/Scylla&Charybdis\n",
      "Loading /Users/erik/projects/m31-galfa/elvis_data/PairedTrees/Serena&Venus\n",
      "Loading /Users/erik/projects/m31-galfa/elvis_data/PairedTrees/Siegfried&Roy\n",
      "Loading /Users/erik/projects/m31-galfa/elvis_data/PairedTrees/Sonny&Cher\n",
      "Loading /Users/erik/projects/m31-galfa/elvis_data/PairedTrees/Thelma&Louise\n",
      "Loading /Users/erik/projects/m31-galfa/elvis_data/PairedTrees/Zeus&Hera\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/erik/projects/m31-galfa/data_loaders.py:83: RuntimeWarning: divide by zero encountered in true_divide\n",
      "  coldct['z'] = 1./coldct['scale'] - 1\n"
     ]
    }
   ],
   "source": [
    "elvii_trees = data_loaders.load_elvii_trees('ID,Mvir,Vmax,Rvir,upID,scale')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data_loaders.annotate_z0_from_trees(elvii_pairs, elvii_trees)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#m31 = SkyCoord.from_name('M31')\n",
    "m31 = SkyCoord(10.6847083*u.deg, 41.26875*u.deg, 700*u.kpc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/erik/miniconda3/envs/anaconda/lib/python3.5/site-packages/astropy/units/quantity.py:763: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n",
      "  return super(Quantity, self).__eq__(other)\n"
     ]
    }
   ],
   "source": [
    "detectability.compute_elvis_mgas_bradford_15(elvii_pairs)\n",
    "\n",
    "for tab in elvii_pairs.values():\n",
    "    #these add host{n}_lat/host{n}_lon/host{n}_dist\n",
    "    data_loaders.add_oriented_radecs(tab, 0, 1, target_coord=m31)\n",
    "    data_loaders.add_oriented_radecs(tab, 1, 0, target_coord=m31)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "detectability.compute_elvis_detectability(sens, wcs, 'fast', elvii_pairs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "detectability.compute_elvis_detectability(galfa_sens, galfa_sens_wcs, 'galfadr1', elvii_pairs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "wakker_hvcs = Table.read('wakk.fits')\n",
    "wakker_scs = SkyCoord(l=wakker_hvcs['L'], b=wakker_hvcs['B'], unit=u.deg, frame='galactic')\n",
    "\n",
    "detectability.compute_elvis_findable(elvii_pairs, wakker_scs, wakker_hvcs['VLSR']*u.km/u.s)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Produce a summary table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "&lt;Table length=24&gt;\n",
       "<table id=\"table5079001632-606939\" class=\"table table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>host name</th><th>nfast z0</th><th>ngalfa z0</th><th>nfast/galfa z0</th><th>nfast ever</th><th>ngalfa ever</th><th>nfast/galfa ever</th></tr></thead>\n",
       "<tr><td>Siegfried</td><td>148</td><td>36</td><td>4.11111111111</td><td>75</td><td>17</td><td>4.41176470588</td></tr>\n",
       "<tr><td>Roy</td><td>154</td><td>29</td><td>5.31034482759</td><td>76</td><td>13</td><td>5.84615384615</td></tr>\n",
       "<tr><td>Orion</td><td>36</td><td>10</td><td>3.6</td><td>16</td><td>3</td><td>5.33333333333</td></tr>\n",
       "<tr><td>Taurus</td><td>80</td><td>14</td><td>5.71428571429</td><td>40</td><td>8</td><td>5.0</td></tr>\n",
       "<tr><td>Kek</td><td>78</td><td>17</td><td>4.58823529412</td><td>32</td><td>10</td><td>3.2</td></tr>\n",
       "<tr><td>Kauket</td><td>114</td><td>30</td><td>3.8</td><td>76</td><td>16</td><td>4.75</td></tr>\n",
       "<tr><td>Romulus</td><td>61</td><td>9</td><td>6.77777777778</td><td>25</td><td>1</td><td>25.0</td></tr>\n",
       "<tr><td>Remus</td><td>60</td><td>19</td><td>3.15789473684</td><td>24</td><td>6</td><td>4.0</td></tr>\n",
       "<tr><td>Lincoln</td><td>75</td><td>26</td><td>2.88461538462</td><td>25</td><td>9</td><td>2.77777777778</td></tr>\n",
       "<tr><td>Douglas</td><td>88</td><td>20</td><td>4.4</td><td>39</td><td>6</td><td>6.5</td></tr>\n",
       "<tr><td>Sonny</td><td>43</td><td>11</td><td>3.90909090909</td><td>19</td><td>5</td><td>3.8</td></tr>\n",
       "<tr><td>Cher</td><td>47</td><td>11</td><td>4.27272727273</td><td>12</td><td>4</td><td>3.0</td></tr>\n",
       "<tr><td>Zeus</td><td>101</td><td>12</td><td>8.41666666667</td><td>56</td><td>6</td><td>9.33333333333</td></tr>\n",
       "<tr><td>Hera</td><td>81</td><td>21</td><td>3.85714285714</td><td>39</td><td>7</td><td>5.57142857143</td></tr>\n",
       "<tr><td>Scylla</td><td>89</td><td>17</td><td>5.23529411765</td><td>58</td><td>10</td><td>5.8</td></tr>\n",
       "<tr><td>Charybdis</td><td>81</td><td>21</td><td>3.85714285714</td><td>54</td><td>14</td><td>3.85714285714</td></tr>\n",
       "<tr><td>Serena</td><td>102</td><td>19</td><td>5.36842105263</td><td>71</td><td>12</td><td>5.91666666667</td></tr>\n",
       "<tr><td>Venus</td><td>164</td><td>43</td><td>3.81395348837</td><td>95</td><td>19</td><td>5.0</td></tr>\n",
       "<tr><td>Hamilton</td><td>60</td><td>9</td><td>6.66666666667</td><td>34</td><td>6</td><td>5.66666666667</td></tr>\n",
       "<tr><td>Burr</td><td>87</td><td>25</td><td>3.48</td><td>47</td><td>13</td><td>3.61538461538</td></tr>\n",
       "<tr><td>Thelma</td><td>56</td><td>8</td><td>7.0</td><td>18</td><td>1</td><td>18.0</td></tr>\n",
       "<tr><td>Louise</td><td>50</td><td>11</td><td>4.54545454545</td><td>16</td><td>2</td><td>8.0</td></tr>\n",
       "<tr><td>Hall</td><td>64</td><td>12</td><td>5.33333333333</td><td>30</td><td>7</td><td>4.28571428571</td></tr>\n",
       "<tr><td>Oates</td><td>42</td><td>17</td><td>2.47058823529</td><td>18</td><td>5</td><td>3.6</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",
       "require.config({paths: {\n",
       "    datatables: 'https://cdn.datatables.net/1.10.9/js/jquery.dataTables.min'\n",
       "}});\n",
       "require([\"datatables\"], function(){\n",
       "    console.log(\"$('#table5079001632-606939').dataTable()\");\n",
       "    $('#table5079001632-606939').dataTable({\n",
       "        \"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": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "summary_tab = Table(names=['host name', 'nfast z0', 'ngalfa z0', 'nfast/galfa z0', 'nfast ever', 'ngalfa ever', 'nfast/galfa ever'], \n",
    "                    dtype=['S10', int, int, float, int, int, float])\n",
    "\n",
    "for names in elvii_pairs:\n",
    "    cat = elvii_pairs[names]\n",
    "    ns = names.split('&')\n",
    "    for i in (0, 1):\n",
    "        findable_fast = cat['findable_fast_host'+str(i)]\n",
    "        findable_galfa = cat['findable_galfadr1_host'+str(i)]\n",
    "        \n",
    "        nfast0 = np.sum(findable_fast&~cat['sat_of_either'])\n",
    "        ngalfa0 = np.sum(findable_galfa&~cat['sat_of_either'])\n",
    "        nfastever = np.sum(findable_fast&~cat['upIDever_either'])\n",
    "        ngalfaever = np.sum(findable_galfa&~cat['upIDever_either'])\n",
    "        summary_tab.add_row([ns[i], nfast0, ngalfa0, nfast0/ngalfa0, nfastever, ngalfaever, nfastever/ngalfaever])\n",
    "        \n",
    "summary_tab.show_in_notebook()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# now add in a reionization cut for Tvir @ z=6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# values from the \"Probabilistic Experiments\" notebook\n",
    "lmvirtolrvir =  modeling.models.Linear1D(slope=0.3332146169115156, intercept=-1.4803268453825718)\n",
    "\n",
    "vtoltvir = lambda v: np.log10((0.6 * cnst.m_p*v**2 / 2 / cnst.k_B)/u.K)\n",
    "def lmtoltvir(lmvir):\n",
    "    lrvir = lmvirtolrvir(lmvir)\n",
    "    vsq = cnst.G * 10**lmvir/10**lrvir * (u.solMass/u.kpc)\n",
    "    return np.log10((0.6 * cnst.m_p*vsq / 2 / cnst.k_B)/u.K)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/erik/miniconda3/envs/anaconda/lib/python3.5/site-packages/ipykernel/__main__.py:8: RuntimeWarning: divide by zero encountered in log10\n",
      "/Users/erik/miniconda3/envs/anaconda/lib/python3.5/site-packages/astropy/units/quantity.py:822: RuntimeWarning: invalid value encountered in true_divide\n",
      "  return super(Quantity, self).__truediv__(other)\n"
     ]
    }
   ],
   "source": [
    "for name, tree in elvii_trees.items():\n",
    "    for z_re in (6,7,8,9):\n",
    "        idxzre = np.argmin(np.abs(tree[0]['z']-z_re))    \n",
    "        elvii_pairs[name]['Mviratz{}'.format(z_re)] = tree['Mvir'][:, idxzre]\n",
    "        elvii_pairs[name]['Rviratz{}'.format(z_re)] = tree['Rvir'][:, idxzre]\n",
    "        elvii_pairs[name]['Vmatz{}'.format(z_re)] = tree['Vmax'][:, idxzre]\n",
    "        elvii_pairs[name]['Tviratz{}'.format(z_re)] = 10**lmtoltvir(np.log10(tree['Mvir'][:, idxzre]/u.solMass))*u.K"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Produce a summary table *including* the reionization cut"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/erik/miniconda3/envs/anaconda/lib/python3.5/site-packages/ipykernel/__main__.py:8: RuntimeWarning: invalid value encountered in greater\n",
      "/Users/erik/miniconda3/envs/anaconda/lib/python3.5/site-packages/ipykernel/__main__.py:16: RuntimeWarning: divide by zero encountered in long_scalars\n",
      "/Users/erik/miniconda3/envs/anaconda/lib/python3.5/site-packages/ipykernel/__main__.py:16: RuntimeWarning: invalid value encountered in long_scalars\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "&lt;Table length=24&gt;\n",
       "<table id=\"table5069720096-16078\" class=\"table table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>host name</th><th>nfast z0</th><th>ngalfa z0</th><th>nfast/galfa z0</th><th>nfast ever</th><th>ngalfa ever</th><th>nfast/galfa ever</th></tr></thead>\n",
       "<tr><td>Siegfried</td><td>25</td><td>9</td><td>2.77777777778</td><td>15</td><td>4</td><td>3.75</td></tr>\n",
       "<tr><td>Roy</td><td>20</td><td>4</td><td>5.0</td><td>10</td><td>1</td><td>10.0</td></tr>\n",
       "<tr><td>Orion</td><td>7</td><td>2</td><td>3.5</td><td>1</td><td>0</td><td>inf</td></tr>\n",
       "<tr><td>Taurus</td><td>13</td><td>1</td><td>13.0</td><td>6</td><td>1</td><td>6.0</td></tr>\n",
       "<tr><td>Kek</td><td>8</td><td>3</td><td>2.66666666667</td><td>3</td><td>1</td><td>3.0</td></tr>\n",
       "<tr><td>Kauket</td><td>16</td><td>5</td><td>3.2</td><td>15</td><td>4</td><td>3.75</td></tr>\n",
       "<tr><td>Romulus</td><td>7</td><td>0</td><td>inf</td><td>4</td><td>0</td><td>inf</td></tr>\n",
       "<tr><td>Remus</td><td>6</td><td>3</td><td>2.0</td><td>2</td><td>1</td><td>2.0</td></tr>\n",
       "<tr><td>Lincoln</td><td>7</td><td>3</td><td>2.33333333333</td><td>2</td><td>1</td><td>2.0</td></tr>\n",
       "<tr><td>Douglas</td><td>5</td><td>0</td><td>inf</td><td>2</td><td>0</td><td>inf</td></tr>\n",
       "<tr><td>Sonny</td><td>2</td><td>0</td><td>inf</td><td>1</td><td>0</td><td>inf</td></tr>\n",
       "<tr><td>Cher</td><td>4</td><td>4</td><td>1.0</td><td>1</td><td>1</td><td>1.0</td></tr>\n",
       "<tr><td>Zeus</td><td>16</td><td>3</td><td>5.33333333333</td><td>10</td><td>2</td><td>5.0</td></tr>\n",
       "<tr><td>Hera</td><td>8</td><td>6</td><td>1.33333333333</td><td>4</td><td>3</td><td>1.33333333333</td></tr>\n",
       "<tr><td>Scylla</td><td>20</td><td>4</td><td>5.0</td><td>15</td><td>3</td><td>5.0</td></tr>\n",
       "<tr><td>Charybdis</td><td>9</td><td>4</td><td>2.25</td><td>6</td><td>3</td><td>2.0</td></tr>\n",
       "<tr><td>Serena</td><td>8</td><td>3</td><td>2.66666666667</td><td>5</td><td>2</td><td>2.5</td></tr>\n",
       "<tr><td>Venus</td><td>17</td><td>4</td><td>4.25</td><td>10</td><td>2</td><td>5.0</td></tr>\n",
       "<tr><td>Hamilton</td><td>12</td><td>2</td><td>6.0</td><td>9</td><td>2</td><td>4.5</td></tr>\n",
       "<tr><td>Burr</td><td>15</td><td>10</td><td>1.5</td><td>10</td><td>6</td><td>1.66666666667</td></tr>\n",
       "<tr><td>Thelma</td><td>3</td><td>1</td><td>3.0</td><td>0</td><td>0</td><td>nan</td></tr>\n",
       "<tr><td>Louise</td><td>4</td><td>0</td><td>inf</td><td>0</td><td>0</td><td>nan</td></tr>\n",
       "<tr><td>Hall</td><td>7</td><td>1</td><td>7.0</td><td>2</td><td>0</td><td>inf</td></tr>\n",
       "<tr><td>Oates</td><td>4</td><td>3</td><td>1.33333333333</td><td>1</td><td>0</td><td>inf</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",
       "require.config({paths: {\n",
       "    datatables: 'https://cdn.datatables.net/1.10.9/js/jquery.dataTables.min'\n",
       "}});\n",
       "require([\"datatables\"], function(){\n",
       "    console.log(\"$('#table5069720096-16078').dataTable()\");\n",
       "    $('#table5069720096-16078').dataTable({\n",
       "        \"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": 136,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "summary_tab_re = Table(names=['host name', 'nfast z0', 'ngalfa z0', 'nfast/galfa z0', 'nfast ever', 'ngalfa ever', 'nfast/galfa ever'], \n",
    "                    dtype=['S10', int, int, float, int, int, float])\n",
    "\n",
    "for names in elvii_pairs:\n",
    "    cat = elvii_pairs[names]\n",
    "    ns = names.split('&')\n",
    "    for i in (0, 1):\n",
    "        tvirmsk = np.isfinite(cat['Tviratz8'])&(cat['Tviratz8']>10**3.*u.K)\n",
    "        findable_fast = cat['findable_fast_host'+str(i)]&tvirmsk\n",
    "        findable_galfa = cat['findable_galfadr1_host'+str(i)]&tvirmsk\n",
    "        \n",
    "        nfast0 = np.sum(findable_fast&~cat['sat_of_either'])\n",
    "        ngalfa0 = np.sum(findable_galfa&~cat['sat_of_either'])\n",
    "        nfastever = np.sum(findable_fast&~cat['upIDever_either'])\n",
    "        ngalfaever = np.sum(findable_galfa&~cat['upIDever_either'])\n",
    "        summary_tab_re.add_row([ns[i], nfast0, ngalfa0, nfast0/ngalfa0, nfastever, ngalfaever, nfastever/ngalfaever])\n",
    "        \n",
    "summary_tab_re.show_in_notebook()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Some comparisons "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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ZQ1hYGMHBwQwdOpRLly65HJ/b96RBgwa59p3beXO7Do0aNeK5554r1PV1V33X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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x12cd55b38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 7))\n",
    "plt.scatter(np.arange(len(summary_tab)), summary_tab['nfast/galfa z0'], c='r', lw=0, s=40, alpha=.5, \n",
    "            label='not sat at z=0')\n",
    "plt.scatter(np.arange(len(summary_tab)), summary_tab['nfast/galfa ever'], c='b', lw=0, s=40, alpha=.5, \n",
    "            label=' never sat')\n",
    "\n",
    "plt.scatter(np.arange(len(summary_tab)), summary_tab_re['nfast/galfa z0'], c='m', marker='s', s=60, lw=0, alpha=.5, \n",
    "            label='not sat at z=0, reionization cut: $T_{vir}@z=8 > 10^{3} M_{\\\\odot}$')\n",
    "plt.scatter(np.arange(len(summary_tab)), summary_tab_re['nfast/galfa ever'], c='c', marker='s', s=60, lw=0, alpha=.5, \n",
    "            label='never sat, reionization cut: $T_{vir}@z=8 > 10^{3} M_{\\\\odot}$')\n",
    "\n",
    "plt.xlim(-.2, 23.2)\n",
    "plt.ylim(0,25.5)\n",
    "plt.ylabel('$n_{fast}/n_{galfa}$', fontsize=36)\n",
    "plt.xticks(np.arange(len(summary_tab)), list(summary_tab['host name'].astype('U')), rotation=45)\n",
    "plt.legend(loc=0)\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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ITU1l4MCBbN68maFDh2KtZcWKFTz99NNMnTqVyZMn4+Hh4bw+LSIigl69etGh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\niIiISIP+Hy55h7PvZX5rAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x12e30c710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 7))\n",
    "plt.scatter(np.arange(len(summary_tab)), summary_tab['nfast z0'], c='r', lw=0, s=40, alpha=.5, \n",
    "            label='not sat at z=0')\n",
    "plt.scatter(np.arange(len(summary_tab)), summary_tab['nfast ever'], c='b', lw=0, s=40, alpha=.5, \n",
    "            label=' never sat')\n",
    "\n",
    "plt.scatter(np.arange(len(summary_tab)), summary_tab_re['nfast z0'], c='m', marker='s', s=60, lw=0, alpha=.5, \n",
    "            label='not sat at z=0, reionization cut: $T_{vir}@z=8 > 10^{3} M_{\\\\odot}$')\n",
    "plt.scatter(np.arange(len(summary_tab)), summary_tab_re['nfast ever'], c='c', marker='s', s=60, lw=0, alpha=.5, \n",
    "            label='never sat, reionization cut: $T_{vir}@z=8 > 10^{3} M_{\\\\odot}$')\n",
    "\n",
    "plt.xlim(-.2, 23.2)\n",
    "plt.ylim(0,180)\n",
    "plt.ylabel('$n_{fast}$', fontsize=36)\n",
    "plt.xticks(np.arange(len(summary_tab)), list(summary_tab['host name'].astype('U')), rotation=45)\n",
    "plt.legend(loc='upper center')\n",
    "plt.tight_layout()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}