Visibility_Radio_Astronomy.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Observe NGC 1052 with the VLA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "import astroplan\n",
    "from astroplan.plots import plot_altitude\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as mpl\n",
    "import numpy as np\n",
    "from astropy.time import Time\n",
    "from astropy import coordinates\n",
    "from astropy import units as u\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['',\n",
       " '',\n",
       " '',\n",
       " 'ALMA',\n",
       " 'ATST',\n",
       " 'Anglo-Australian Observatory',\n",
       " 'Apache Point',\n",
       " 'Apache Point Observatory',\n",
       " 'Atacama Large Millimeter Array',\n",
       " 'BAO',\n",
       " 'BBSO',\n",
       " 'Beijing XingLong Observatory',\n",
       " 'Black Moshannon Observatory',\n",
       " 'CHARA',\n",
       " 'Canada-France-Hawaii Telescope',\n",
       " 'Catalina Observatory',\n",
       " 'Cerro Pachon',\n",
       " 'Cerro Paranal',\n",
       " 'Cerro Tololo',\n",
       " 'Cerro Tololo Interamerican Observatory',\n",
       " 'DCT',\n",
       " 'DKIST',\n",
       " 'Discovery Channel Telescope',\n",
       " 'Dominion Astrophysical Observatory',\n",
       " 'GBT',\n",
       " 'Gemini South',\n",
       " 'Green Bank Telescope',\n",
       " 'Hale Telescope',\n",
       " 'Haleakala Observatories',\n",
       " 'Happy Jack',\n",
       " 'IAO',\n",
       " 'JCMT',\n",
       " 'James Clerk Maxwell Telescope',\n",
       " 'Jansky Very Large Array',\n",
       " 'Keck Observatory',\n",
       " 'Kitt Peak',\n",
       " 'Kitt Peak National Observatory',\n",
       " 'La Silla Observatory',\n",
       " 'Large Binocular Telescope',\n",
       " 'Las Campanas Observatory',\n",
       " 'Lick Observatory',\n",
       " 'Lowell Observatory',\n",
       " 'MWA',\n",
       " 'Manastash Ridge Observatory',\n",
       " 'McDonald Observatory',\n",
       " 'Medicina',\n",
       " 'Medicina Dish',\n",
       " 'Michigan-Dartmouth-MIT Observatory',\n",
       " 'Mount Graham International Observatory',\n",
       " 'Mt Graham',\n",
       " 'Mt. Ekar 182 cm. Telescope',\n",
       " 'Mt. Stromlo Observatory',\n",
       " 'Multiple Mirror Telescope',\n",
       " 'Murchison Widefield Array',\n",
       " 'NOV',\n",
       " 'NST',\n",
       " 'National Observatory of Venezuela',\n",
       " 'Noto',\n",
       " 'Observatorio Astronomico Nacional, San Pedro Martir',\n",
       " 'Observatorio Astronomico Nacional, Tonantzintla',\n",
       " 'Palomar',\n",
       " 'Paranal Observatory',\n",
       " 'Roque de los Muchachos',\n",
       " 'SAAO',\n",
       " 'SALT',\n",
       " 'SPO',\n",
       " 'SRT',\n",
       " 'Sac Peak',\n",
       " 'Sacramento Peak',\n",
       " 'Siding Spring Observatory',\n",
       " 'Southern African Large Telescope',\n",
       " 'Subaru',\n",
       " 'Subaru Telescope',\n",
       " 'Sunspot',\n",
       " 'Sutherland',\n",
       " 'TUG',\n",
       " 'UKIRT',\n",
       " 'United Kingdom Infrared Telescope',\n",
       " 'Vainu Bappu Observatory',\n",
       " 'Very Large Array',\n",
       " 'W. M. Keck Observatory',\n",
       " 'Whipple',\n",
       " 'Whipple Observatory',\n",
       " 'aao',\n",
       " 'alma',\n",
       " 'apo',\n",
       " 'bbso',\n",
       " 'bmo',\n",
       " 'cfht',\n",
       " 'ctio',\n",
       " 'dao',\n",
       " 'dct',\n",
       " 'dkist',\n",
       " 'ekar',\n",
       " 'example_site',\n",
       " 'flwo',\n",
       " 'gbt',\n",
       " 'gemini_north',\n",
       " 'gemini_south',\n",
       " 'gemn',\n",
       " 'gems',\n",
       " 'greenwich',\n",
       " 'haleakala',\n",
       " 'iao',\n",
       " 'irtf',\n",
       " 'jcmt',\n",
       " 'keck',\n",
       " 'kpno',\n",
       " 'lapalma',\n",
       " 'lasilla',\n",
       " 'lbt',\n",
       " 'lco',\n",
       " 'lick',\n",
       " 'lowell',\n",
       " 'mcdonald',\n",
       " 'mdm',\n",
       " 'medicina',\n",
       " 'mmt',\n",
       " 'mro',\n",
       " 'mso',\n",
       " 'mtbigelow',\n",
       " 'mwa',\n",
       " 'mwo',\n",
       " 'noto',\n",
       " 'ohp',\n",
       " 'paranal',\n",
       " 'salt',\n",
       " 'sirene',\n",
       " 'spm',\n",
       " 'spo',\n",
       " 'srt',\n",
       " 'sso',\n",
       " 'tona',\n",
       " 'tug',\n",
       " 'ukirt',\n",
       " 'vbo',\n",
       " 'vla']"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coordinates.EarthLocation.get_site_names()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are a few telescopes missing: ATCA, ASKAP, IRAM 30m dish, Plateau de Burre (NOEMA)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "col = '#{:02X}{:02X}{:02X}'.format(int(mpl.cm.hsv(0.9)[0] * 255), \n",
    "                                   int(mpl.cm.hsv(0.9)[1] * 255),\n",
    "                                   int(mpl.cm.hsv(0.9)[2] * 255))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "vla = astroplan.Observer.at_site('vla')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "time = Time('2020-09-13 12:00:00')\n",
    "time_range = Time([\"2020-09-01T00:00:00\", \"2020-10-01T00:00:00\"])\n",
    "observe_time = time + np.linspace(-240, 240, 4800)*u.hour\n",
    "sun_coord = coordinates.get_sun(time)\n",
    "moon_coord = coordinates.get_moon(time)\n",
    "n1052 = astroplan.FixedTarget.from_name('NGC1052')\n",
    "sun = astroplan.FixedTarget(name='Sun', coord=sun_coord)\n",
    "moon = astroplan.FixedTarget(name='Moon', coord=moon_coord)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f7dc2d38fd0>"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_style('darkgrid')\n",
    "fig = plt.figure(figsize=(10.0, 8.0))\n",
    "ax = fig.add_axes([0.17, 0.17, 0.77, 0.77])\n",
    "plot_altitude(sun, vla, time, ax=ax, style_kwargs={'color':'#faa14f', \n",
    "                                                   'linestyle':'--'})\n",
    "plot_altitude(moon, vla, time, ax=ax, style_kwargs={'color':'#C42129', \n",
    "                                                   'linestyle':'--'})\n",
    "plot_altitude(n1052, vla, time, ax=ax, style_kwargs={'color':'#045277'}, \n",
    "              brightness_shading=True, airmass_yaxis=True)\n",
    "ax.legend(loc=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[45.44427782 44.97086194 44.45779003 ... 38.20051525 37.36450291\n",
      " 36.50396285]\n",
      "[ 21.69067678  20.59889888  19.49843289 ... -75.87766982 -76.66465431\n",
      " -77.37855153]\n"
     ]
    }
   ],
   "source": [
    "print(vla.altaz(observe_time, n1052).alt.value)\n",
    "print(vla.moon_altaz(observe_time).alt.value)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sns.set_style('darkgrid')\n",
    "fig = plt.figure(figsize=(10.0, 8.0))\n",
    "ax = fig.add_axes([0.17, 0.17, 0.77, 0.77])\n",
    "plot_altitude(sun, vla, observe_time, ax=ax, style_kwargs={'color':'#faa14f', \n",
    "                                                   'linestyle':'--'})\n",
    "# plot_altitude(moon, vla, observe_time, ax=ax, style_kwargs={'color':'#C42129', \n",
    "#                                                    'linestyle':'--'})\n",
    "plot_altitude(n1052, vla, observe_time, ax=ax, style_kwargs={'color':'#045277'}, \n",
    "              brightness_shading=True, airmass_yaxis=True)\n",
    "ax.plot(observe_time, vla.moon_altaz(observe_time).alt)\n",
    "ax.legend(loc=2)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}