Playing around coordinates.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Coordinates in observational astronomy\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "First, we’re going to investigate the area of the sky around the picturesque group of galaxies named “Hickson Compact Group 7,” download an image, and do something with its coordinates."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Importing all the libraries that we need\n",
    "\n",
    "from astropy import units as u\n",
    "from astropy.coordinates import SkyCoord\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set up matplotlib and use a nicer set of plot parameters\n",
    "from astropy.visualization import astropy_mpl_style\n",
    "import matplotlib.pyplot as plt\n",
    "plt.style.use(astropy_mpl_style)\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Describing on-sky locations with coordinates\n",
    "\n",
    "\n",
    "The SkyCoord class in the astropy.coordinates package is used to represent celestial coordinates. First, we’ll make a SkyCoord object based on our object’s name, “Hickson Compact Group 7” or “HCG 7” for short. Most astronomical object names can be found by SESAME, a service which queries Simbad, NED, and VizieR and returns the object’s type and its J2000 position. This service can be used via the SkyCoord.from_name() class method:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# initialize a SkyCood object named hcg7_center at the location of HCG 7\n",
    "hcg7_center = SkyCoord.from_name('HCG 7')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "#if you don't have an internet connection, run the following command\n",
    "# hcg7_center = SkyCoord(9.81625*u.deg, 0.88806*u.deg, frame='icrs')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "astropy.coordinates.sky_coordinate.SkyCoord"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(hcg7_center)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<SkyCoord (ICRS): (ra, dec) in deg\n",
      "    (9.81625, 0.88805556)>\n"
     ]
    }
   ],
   "source": [
    "print(hcg7_center)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['T',\n",
       " '__abstractmethods__',\n",
       " '__bool__',\n",
       " '__class__',\n",
       " '__delattr__',\n",
       " '__dict__',\n",
       " '__dir__',\n",
       " '__doc__',\n",
       " '__eq__',\n",
       " '__format__',\n",
       " '__ge__',\n",
       " '__getattr__',\n",
       " '__getattribute__',\n",
       " '__getitem__',\n",
       " '__gt__',\n",
       " '__hash__',\n",
       " '__init__',\n",
       " '__init_subclass__',\n",
       " '__iter__',\n",
       " '__le__',\n",
       " '__len__',\n",
       " '__lt__',\n",
       " '__module__',\n",
       " '__ne__',\n",
       " '__new__',\n",
       " '__reduce__',\n",
       " '__reduce_ex__',\n",
       " '__repr__',\n",
       " '__setattr__',\n",
       " '__sizeof__',\n",
       " '__str__',\n",
       " '__subclasshook__',\n",
       " '__weakref__',\n",
       " '_abc_impl',\n",
       " '_apply',\n",
       " '_extra_frameattr_names',\n",
       " '_sky_coord_frame',\n",
       " 'altaz',\n",
       " 'apply_space_motion',\n",
       " 'barycentrictrueecliptic',\n",
       " 'cache',\n",
       " 'cartesian',\n",
       " 'cirs',\n",
       " 'contained_by',\n",
       " 'copy',\n",
       " 'data',\n",
       " 'dec',\n",
       " 'default_differential',\n",
       " 'default_representation',\n",
       " 'diagonal',\n",
       " 'differential_type',\n",
       " 'directional_offset_by',\n",
       " 'distance',\n",
       " 'equinox',\n",
       " 'fk4',\n",
       " 'fk4noeterms',\n",
       " 'fk5',\n",
       " 'flatten',\n",
       " 'frame',\n",
       " 'frame_attributes',\n",
       " 'frame_specific_representation_info',\n",
       " 'from_name',\n",
       " 'from_pixel',\n",
       " 'galactic',\n",
       " 'galacticlsr',\n",
       " 'galactocentric',\n",
       " 'galcen_coord',\n",
       " 'galcen_distance',\n",
       " 'galcen_v_sun',\n",
       " 'gcrs',\n",
       " 'geocentrictrueecliptic',\n",
       " 'get_constellation',\n",
       " 'get_frame_attr_names',\n",
       " 'get_representation_cls',\n",
       " 'get_representation_component_names',\n",
       " 'get_representation_component_units',\n",
       " 'guess_from_table',\n",
       " 'has_data',\n",
       " 'hcrs',\n",
       " 'heliocentrictrueecliptic',\n",
       " 'icrs',\n",
       " 'info',\n",
       " 'is_equivalent_frame',\n",
       " 'is_frame_attr_default',\n",
       " 'is_transformable_to',\n",
       " 'isscalar',\n",
       " 'itrs',\n",
       " 'location',\n",
       " 'lsr',\n",
       " 'match_to_catalog_3d',\n",
       " 'match_to_catalog_sky',\n",
       " 'name',\n",
       " 'ndim',\n",
       " 'obsgeoloc',\n",
       " 'obsgeovel',\n",
       " 'obstime',\n",
       " 'obswl',\n",
       " 'pm_dec',\n",
       " 'pm_ra_cosdec',\n",
       " 'position_angle',\n",
       " 'precessedgeocentric',\n",
       " 'pressure',\n",
       " 'proper_motion',\n",
       " 'ra',\n",
       " 'radial_velocity',\n",
       " 'radial_velocity_correction',\n",
       " 'ravel',\n",
       " 'realize_frame',\n",
       " 'relative_humidity',\n",
       " 'replicate',\n",
       " 'replicate_without_data',\n",
       " 'represent_as',\n",
       " 'representation',\n",
       " 'representation_component_names',\n",
       " 'representation_component_units',\n",
       " 'representation_info',\n",
       " 'representation_type',\n",
       " 'reshape',\n",
       " 'roll',\n",
       " 'search_around_3d',\n",
       " 'search_around_sky',\n",
       " 'separation',\n",
       " 'separation_3d',\n",
       " 'set_representation_cls',\n",
       " 'shape',\n",
       " 'size',\n",
       " 'skyoffset_frame',\n",
       " 'spherical',\n",
       " 'spherical_offsets_to',\n",
       " 'sphericalcoslat',\n",
       " 'squeeze',\n",
       " 'supergalactic',\n",
       " 'swapaxes',\n",
       " 'take',\n",
       " 'temperature',\n",
       " 'to_pixel',\n",
       " 'to_string',\n",
       " 'transform_to',\n",
       " 'transpose',\n",
       " 'v_bary',\n",
       " 'velocity',\n",
       " 'z_sun']"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#This is a directory. Let's checkout it's methods and attributes\n",
    "\n",
    "dir(hcg7_center)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "9d48m58.5s 0d53m17s\n",
      "0.6544166666666668 0d53m17s\n"
     ]
    }
   ],
   "source": [
    "print(hcg7_center.ra, hcg7_center.dec)\n",
    "print(hcg7_center.ra.hour, hcg7_center.dec)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Downloading an Image\n",
    "\n",
    "Now that we have our object set at SkyCoord object, we can try to use it to access data from the Sloan Digitial Sky Survey (SDSS). Let’s start by trying to get a picture using the SDSS image cutout service to make sure HCG 7 is in the SDSS footprint and has good image quality."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('HCG7_SDSS_cutout.jpg', <http.client.HTTPMessage at 0x7f1be8fdf978>)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Python standard-library\n",
    "from urllib.parse import urlencode\n",
    "from urllib.request import urlretrieve\n",
    "\n",
    "# tell the SDSS service how big of a cutout we want\n",
    "im_size = 12*u.arcmin # get a 12 arcmin square\n",
    "im_pixels = 1024\n",
    "cutoutbaseurl = 'http://skyservice.pha.jhu.edu/DR12/ImgCutout/getjpeg.aspx'\n",
    "query_string = urlencode(dict(ra=hcg7_center.ra.deg,\n",
    "                              dec=hcg7_center.dec.deg,\n",
    "                              width=im_pixels, height=im_pixels,\n",
    "                              scale=im_size.to(u.arcsec).value/im_pixels))\n",
    "url = cutoutbaseurl + '?' + query_string\n",
    "\n",
    "# this downloads the image to your disk\n",
    "urlretrieve(url, 'HCG7_SDSS_cutout.jpg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image\n",
    "Image('HCG7_SDSS_cutout.jpg')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It's so pretty right! The center of it is the same RA and Dec value we entered above"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In Astropy, the most common object you’ll work with for coordinates is SkyCoord. A SkyCoord can most easily be created directly from angles as shown below.\n",
    "\n",
    "In this tutorial we’ll be converting between frames. Let’s start in the ICRS frame (which happens to be the default.)\n",
    "\n",
    "For much of this tutorial we’ll work with the Hickson Compact Group 7. We can create an object either by passing the degrees explicitly (using the astropy units library) or by passing in strings. The two coordinates below are equivalent:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<SkyCoord (ICRS): (ra, dec) in deg\n",
      "    (9.81625, 0.88806)>\n"
     ]
    }
   ],
   "source": [
    "hcg7_center = SkyCoord(9.81625*u.deg, 0.88806*u.deg, frame='icrs')  # using degrees directly\n",
    "print(hcg7_center)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<SkyCoord (ICRS): (ra, dec) in deg\n",
      "    (9.81625, 0.88806)>\n"
     ]
    }
   ],
   "source": [
    "hcg7_center = SkyCoord('0h39m15.9s', '0d53m17.016s', frame='icrs')  # passing in string format\n",
    "print(hcg7_center)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "9d48m58.5s\n",
      "0d53m17.016s\n"
     ]
    }
   ],
   "source": [
    "#The RA and dec of the object can be accessed using the object hcg7_center\n",
    "\n",
    "print(hcg7_center.ra)\n",
    "print(hcg7_center.dec)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Frame Transformations\n",
    "\n",
    "astropy.coordinates provides many tools to transform between different coordinate systems. For instance, we can use it to transform from ICRS coordinates (in RA and Dec) to Galactic coordinates.\n",
    "\n",
    "TThe key piece to understand is that all coordinates in Astropy are in particular “frames” and we can transform between a specific SkyCoord object in one frame to another. For example, we can transform our previously-defined center of HCG 7 from ICRS to Galactic coordinates:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "hcg7_center = SkyCoord(9.81625*u.deg, 0.88806*u.deg, frame='icrs')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are three different ways of transforming coordinates. Each has its pros and cons, but all should give you the same result. The first way to transform to other built-in frames is by specifying those attributes. For instance, let’s see the location of HCG 7 in Galactic coordinates."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<SkyCoord (Galactic): (l, b) in deg\n",
       "    (116.47556813, -61.83099472)>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hcg7_center.galactic"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Transforming coordinates using the transform_to() method and other coordinate object\n",
    "The above is actually a special “quick-access” form that internally does the same as what’s in the cell below: it uses the `transform_to()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<SkyCoord (Galactic): (l, b) in deg\n",
       "    (116.47556813, -61.83099472)>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from astropy.coordinates import Galactic  # new coordinate baseclass\n",
    "hcg7_center.transform_to(Galactic())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Transforming coordinates using the transform_to() method and a string\n",
    "Finally, we can transform using the transform_to() method and a string with the name of a built-in coordinate system."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<SkyCoord (Galactic): (l, b) in deg\n",
       "    (116.47556813, -61.83099472)>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hcg7_center.transform_to('galactic')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can transform to many coordinate frames and equinoxes.\n",
    "\n",
    "These coordinates are available by default:\n",
    "\n",
    "ICRS\n",
    "\n",
    "FK5\n",
    "\n",
    "FK4\n",
    "\n",
    "FK4NoETerms\n",
    "\n",
    "Galactic\n",
    "\n",
    "Galactocentric\n",
    "\n",
    "Supergalactic\n",
    "\n",
    "AltAz\n",
    "\n",
    "GCRS\n",
    "\n",
    "CIRS\n",
    "\n",
    "ITRS\n",
    "\n",
    "HCRS\n",
    "\n",
    "PrecessedGeocentric\n",
    "\n",
    "GeocentricTrueEcliptic\n",
    "\n",
    "BarycentricTrueEcliptic\n",
    "\n",
    "HeliocentricTrueEcliptic\n",
    "\n",
    "SkyOffsetFrame\n",
    "\n",
    "GalacticLSR\n",
    "\n",
    "LSR\n",
    "\n",
    "BaseEclipticFrame\n",
    "\n",
    "BaseRADecFrame\n",
    "\n",
    "Let’s focus on just a few of these. We can try FK5 coordinates next:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<SkyCoord (FK5: equinox=J2000.000): (ra, dec) in deg\n",
      "    (9.81625645, 0.88806155)>\n"
     ]
    }
   ],
   "source": [
    "hcg7_center_fk5 = hcg7_center.transform_to('fk5')\n",
    "print(hcg7_center_fk5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<SkyCoord (FK5: equinox=J1975.000): (ra, dec) in deg\n",
       "    (9.49565759, 0.75084648)>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from astropy.coordinates import FK5\n",
    "hcg7_center_fk5.transform_to(FK5(equinox='J1975'))  # precess to a different equinox\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "'SkyCoord' object has no attribute 'ra'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-20-1275c2f67eab>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mhcg7_center\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgalactic\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mra\u001b[0m  \u001b[0;31m# should fail because Galactic coordinates are l/b not RA/Dec\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/astropy/coordinates/sky_coordinate.py\u001b[0m in \u001b[0;36m__getattr__\u001b[0;34m(self, attr)\u001b[0m\n\u001b[1;32m    598\u001b[0m         \u001b[0;31m# Fail\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    599\u001b[0m         raise AttributeError(\"'{0}' object has no attribute '{1}'\"\n\u001b[0;32m--> 600\u001b[0;31m                              .format(self.__class__.__name__, attr))\n\u001b[0m\u001b[1;32m    601\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    602\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__setattr__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mattr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mval\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mAttributeError\u001b[0m: 'SkyCoord' object has no attribute 'ra'"
     ]
    }
   ],
   "source": [
    "hcg7_center.galactic.ra  # should fail because Galactic coordinates are l/b not RA/Dec"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "116d28m32.0453s -61d49m51.581s\n"
     ]
    }
   ],
   "source": [
    "print(hcg7_center.galactic.l, hcg7_center.galactic.b)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Transform frames to get to altitude-azimuth (“AltAz”)\n",
    "To actually do anything with observability we need to convert to a frame local to an on-earth observer. By far the most common choice is horizontal altitude-azimuth coordinates, or “AltAz”. We first need to specify both where and when we want to try to observe.\n",
    "\n",
    "We’ll need to import a few more specific module"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "from astropy.coordinates import EarthLocation\n",
    "from astropy.time import Time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "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": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "EarthLocation.get_site_names()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "VBO = EarthLocation.of_site('Vainu Bappu Observatory')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let’s check the altitude at 12:00 PM UTC"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "observing_time = Time('2010-12-21 12:00')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we use these to create an AltAz frame object. Note that this frame has some other information about the atmosphere, which can be used to correct for atmospheric refraction. Here we leave that alone, because the default is to ignore this effect (by setting the pressure to 0)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<AltAz Frame (obstime=2010-12-21 12:00:00.000, location=(1206621.15671278, 6108765.3777786, 1379891.35439858) m, pressure=0.0 hPa, temperature=0.0 deg_C, relative_humidity=0.0, obswl=1.0 micron)>\n"
     ]
    }
   ],
   "source": [
    "from astropy.coordinates import AltAz\n",
    "\n",
    "aa = AltAz(location=VBO, obstime=observing_time)\n",
    "print(aa)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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mJjqUqIq0BfVzwHrvLwDaQmUvo3WZREQSak9dM399ew/Hjs3ntEE8rVF3Ik1Q07z3nZPCdq6i20Lky3WIiEgMLH55G20dnhtOnz6opzXqTqQJaq0x5vwuZe8DVkc5HhERidCeumYef2s3M8fkc9bM0YkOJ+oibQHdCPzFGPNXYJgx5i7gEuDSmEUmIiK9WrwiaD196szppKVY6wkibEF571cAJwJrgHuBLcAC7/2rMYxNRER6sKeumcdX7+aYsfmcdXTqtZ6gH/eQvPe7gR8DGGNGhp6NEhGRBDjUejoj9e49deq1BWWM+Vj4vSdjzCnGmB1ApTFmvTHm2JhHKCIihwlvPb03RVtP0HcX35eB8Bkjfgv8naC77+/ArTGKS0REenD3i1tSvvUEfXfxTSE0Us8YM4VgVd1zvffVxpivA2WRXMRaOwW4DxhHMEz9bufc7V32McDtwEVAE3C9c+610LbrgG+Fdv2+c+73kVxXRCTVbK5s5K9ryjlhwoiUbj1B3y2oNiAr9P4M4B3vfXXo+yZgWITXaQNudM7NBhYCn7HWzu6yz4UEs1PMBD5FaJYKa+0o4GbgNIIHg2+21o6M8LoiIinl1y9sosPDZ846KqVbT9B3gnoe+IEx5kTg/wF/Dtt2HId3//XIOVfe2RpyztUD64BJXXa7FLjPOeedcyuAQmvtBOB84BnnXLVzrgZ4BrggkuuKiKSSt3bVUlpWyRnTizhlSup/Tu+ri+/zwP8StGiWA/8dtu1aBrAelLV2GnASwVRJ4SYBO8K+3xkq66m8V6Wlpf0N7ZCGhoYjOj6ZpXLdILXrp7oNXtGon/eeO9cHE/mclludND+vWP7uek1Q3vtdwDk9bPt6fy9mrc0HHgG+4Jyr6+/x/VFSUjLgY0tLS4/o+GSWynWD1K6f6jZ4RaN+L26uZPPKtzh/1jiuvuj46AQWBdGo25IlS7ot77GLzxgT0f2lSPez1mYSJKf7nXOPdrPLLoJBGZ0mh8p6KhcRGRLaOjr4n+c3kZ5m+PdFMxIdTtz01oLaS7CKbl92Ab1OoRsaoXcPsM45d1sPu/0J+Ky19iGCARG1zrlya+1TwH+FDYw4D/hGBHGJiKSEx98qZ1NlI1efMoXJhZGOTRv8ektQOcaY+yI4R2YE+5xJcM9qtbX2jVDZTUAxgHPuTuAJgiHmZQQjBD8e2lZtrf0e0Dmt0nedc9WIiAwBDQfbuHPZZgqGZXLDGdMSHU5c9ZagfhDhOX7U1w7OuWVAr+MhnXMe+EwP2+4lmANQRGRIuWf5VvYfaOUr5x7DiJxI2gOpo8cE5b3/TjwDERGRw+2oaeKhVTuYXpTH5fMmJjqcuIt0PSgREYmzXzy/ibYOzxfOPpqMtKH353ro1VhEZBB4eWs1pRv3cfr0UZwxvSjR4SSEEpSISJJpaevgx3/fQGa64cZzjkl0OAmjBCUikmTuX7md7TVNXHtqMVNH5SY6nISJKEEZY75kjJkXer/QGLPdGLPFGHN6bMMTERlaymsPcM/yrUwYkcPHF05LdDgJFWkL6osEy7wD/BC4Dfg+8PNYBCUiMlTd9uxGDrZ1cOM5M8nJTE90OAkV6ZLvBd77WmPMcGAu8D7vfbsx5qcxjE1EZEhZtqmS0rJKFs0oSvm1niIRaYLaYYw5AzgeWBpKTiOA9tiFJiIydDS2tPGjZ9aTnZHGjecek/JrPUUi0gT1FeBhoAX4cKjsYuCVWAQlIjLU/PqFzeytP8jnzjp6SM2315uIEpT3/gmg62PMS0IvERE5Am/tquX/XtvJrHHDuWr+5ESHkzQiHcU32xgzLvQ+3xjzHYLJXofWxFAiIlHW2t7B9596hzRj+Ob5xw3JGSN6EulP4kGgMPT+J8B7gYXAXbEISkRkqFi8Yhtbqhq5ZkExx44bnuhwkkqk96Cmee/Xm+Cu3eXAbOAA/xx6LiIi/bR+bz33rNhK8chhfPL0aYkOJ+lEmqCaQ0PMZwPbvfeVxpgMICd2oYmIpK6Wtg5ueWIt3nu+feHsIf/MU3ciTVAPAM8Cw4E7QmUnoxaUiMiA/OalLZRVNvKxBcXMnVSQ6HCSUqSj+L5ojDkPaPXePxcq7iCYYUJERPph9e5a7ntlGzNG5/FvZ85IdDhJK9IWFN77p7t8vzL64YiIpLYDLe3c8sQ6jDHccuEssjI0aq8nESWo0P2m/wDOAkYTtny79/69sQlNRCT1/Oy5jWyvaeJTZ0xn1vgRiQ4nqUWaun8G/BuwFDgFeAQYS3BfSkREIvDchn089tZuTpxYwMdPn5rocJJepF18lwOne++3G2O+472/3RjzFMFzULf0dbC19l6CqZEqnHNzutn+FeCjYTHNAsY456qttVuBeoJ5/9qcc/MjjFlEJGnsrW/mB0+tIy8rne9dPFsP5EYg0gSVC+wIvT9gjMn13r9jjDkpwuMXE4z+u6+7jc65W4FbAay1lwBfdM5Vh+1ytnOuMsJriYgklQ7vueWJtdQ2t/GDi49nYoHm2otEpCl8HXBq6P1K4BZjzLeAXZEc7JxbClT3uWPgKoKZK0REUsJz5bBy+34+cPx4zps1LtHhDBqRtqA+zz+X1vgS8GuCZ6I+Fc1grLW5wAXAZ8OKPfC0tdYDdznn7o7kXKWlpQOOo6Gh4YiOT2apXDdI7fqpboNTWZ3nqV0djMkxLMzeS2lpRaJDiqpY/u4ifQ7q1bD3G4H3xSQauAR4sUv33iLn3C5r7VjgGWvtO6EWWa9KSkoGHERpaekRHZ/MUrlukNr1U90Gn8qGg/zw96+Sblr4xZULOHpMfqJDirpo/O6WLOl+YYyI79IZY6YaYz5ojLk6/HVEUb3blXTp3nPO7Qp9rQAeAxZE+ZoiIlHX1tHBN/+yhuqmFi6falIyOcVapM9BfQP4T2AtwSSxnTzBNEhHzFpbQPCc1TVhZXlAmnOuPvT+POC70bieiEgs3bVsC6/t2M8lcyZw6rC9iQ5nUIr0HtSNwHzv/dqBXMRa+yBQAoy21u4Ebia0lpRz7s7QbpcBTzvnGsMOHQc8Zq3tjPUB59yTA4lBRCRenl1fweKXt3H06Dy++r5jWPGiEtRARJqgqoCtA72Ic+6qCPZZTDAcPbxsMzB3oNcVEYm3sn0N3PK3dYzIyeDWy07ULOVHINIE9QXgbmPMz4HDhqB477dHPSoRkUGo9kArX37sLQ62tXPrh+YxuVDPOx2JSBNUFsH9n66DIjygjwciMuS1d3i+9Zc17Kpt5nNnHc1p00YlOqRBL9JRfL8CbgJGENw76nxlxSguEZFB5eelG1mxtZrzZ43jmlOnJDqclBBpCyoD+J33vr3PPUVEhpiHX9/JQ6t2cvyEEXzr/OMwxvR9kPQp0hbUT4CvG/3URUQOs3xLFT/5x0bGj8jmJx86QYMioijSFtTngPHATcaYqvAN3vviqEclIjIIbKps4Bt/epvsjDRuu2wuo/OzEx1SSok0QV3T9y4iIkNHRf1BPv/wmxxobeenl53IzLGaKSLa+kxQxph04BPAp7z3B2MfkohIcqtvbuXzD7/B3vqDfOP9x7LoqNGJDikl9XkPKjQw4jygI/bhiIgkt5a2Dr7yx9WUVTbyidOncfm8SYkOKWX1Z8n37xhjMmMZjIhIMmvv8Nz8xFpWhebY+/czpyc6pJQW6T2o/0cwSOJLxph9BA/oAhokISJDg/eeHz7zDn9fX8GZM4q46bxjNZw8xjRIQkSkD957bi8t4/G3yjlpcgE/+uAcMtIjXq1IBijSBQufj3UgIiLJ6p7lW7l/5Q5mjRvObZfP1bNOcdJjgjLGfNN7/4PQ+x7XYPLefzsWgYmIJIP/fWU7d724helFefziI3PJz46040mOVG8/6clh7zWxlIgMOQ+s3M4vni9jSuEwfvkv8yjM1fSj8dRjgvLefzrs/ce728cYo05YEUlJD67awc+eK2Ny4TB+feVJjNEsEXE3oARjjDnBGHMrsDPK8YiIJNyDq3Zw27MbmVSQw6/tSYwbnpPokIakiBOUMWaMMebzxpjXgDeABcDnYxaZiEgCLH55K7c9u5GJBTnceeXJjB+h5JQovd7tCz2Y+0HgeuB8oAx4EJgKXOG9r+j5aBGRwcN7z10vbuGe5VspHpnLr+w8tZwSrK/hKHsJpjhaDNzsvX8NwBjzHzGOS0Qkbjqfc7p/5Q6OHp3HHf9yEkV5GhCRaH0lqLeARcBpwEZjzBbvfU1/L2KtvRe4GKhwzs3pZnsJ8DiwJVT0qHPuu6FtFwC3Eywt/1vn3I/6e30RkZ60dXTwg6fe4S9v7+G4ccP5nyvmUThMs7olg14TlPe+xBgzFfgY8GXgF8aYp4E8giXfI7UYuAO4r5d9XnDOXRxeYK1NB34JvJ9gQMar1to/OefW9uPaIiLdam5t55t/WcPSskrmFxdy64dO1HNOSSSS2cy3ee+/572fCZwLlBN0+71pjPlxJBdxzi0FqgcQ3wKgzDm32TnXAjwEXDqA84iIHKauuZXPPfwGS8sqOXvmGH7+YT2Em2z69dvw3i8DlhljPgdcRtCyipbTrbVvAruBLzvn1gCTgB1h++wk6G7sU2lp6YADaWhoOKLjk1kq1w1Su36qW/RUH/Tcs8FT0QynjYELCipZvuyFmF1Pv7uBGdDHBe99M8FovgejFMdrwFTnXIO19iLgj8DMIzlhSUnJgI8tLS09ouOTWSrXDVK7fqpbdKzdU8cPH3mL6uYW/n3RdD6xcFrMZyXX7653S5Ys6bY8KWaCcM7VOecaQu+fADKttaOBXRw+zdLkUJmISL89X7aPf3voNeqaW/nORbO54fTpWjIjiSVFh6u1djyw1znnrbULCBJnFbAfmGmtnU6QmK4Erk5cpCIyGHnvue+V7fxy6SbysjP42eUnML94ZKLDkj7EJUFZax8ESoDR1tqdwM2ERgE65+4EPgJ82lrbBhwArnTOeaDNWvtZ4CmCYeb3hu5NiYhE5GBbOz98ej1/XbOH4pHD+OnlJzJtVF6iw5IIxCVBOeeu6mP7HQTD0Lvb9gTwRCziEpHUtq/hIF/742pWl9dxavFIfvjBORToGadBIym6+EREou31nfv5+uNvU93UwhUnTeJLZ8/UKriDjBKUiKQU7z3/9/pOfvZcGenG8O0LZ3HJnAmJDksGQAlKRFJGY0sbP3jqHZ55p4LxI7L58aUnMGv8iESHJQOkBCUiKWFjRQNf/9PbbK9pYuG0UXz3A7MZqRVwBzUlKBEZ1Lz3/PGt3fz02Y20tnfw6UUzuH7hVNL0fNOgpwQlIoNW7YFW/uvpd3h2wz6K8rL4wcXHc4qeb0oZSlAiMii9tqOG//zrWirqD7JoRhH/ecEsRmkNp5SiBCUig8rBtnbuWraFP7y6ncz0NL5y7jFccdIkTVmUgpSgRGTQWL+3npufWMumykZmjsnnux+YzdFj8hMdlsSIEpSIJL3W9g4Wv7yNe5dvpcN7rj9tKv96xnSyMvTgbSpTghKRpLZuTx3fe/IdNu5rYErhMG6+aDZzJxUkOiyJAyUoEUlKza3t/OalLdz/6g48nmtOLebfzpxOTmZ6okOTOFGCEpGks3xLFT96Zj27a5uZXpTHty84jjkT1WoaapSgRCRpVDYc5OelZTy1bi9Z6Wl8etEMrl1QTKYmeR2SlKBEJOHaOzwPrNzO3S9uobGlnVOLR/L1846leGRuokOTBFKCEpGEenVbNT9b69l7oIwx+VncdP5xvP/YsXquSZSgRCQxdtQ08YvSMkrLKkkzcO2pxdxwxjTysvRnSQL6lyAicVXX3MrvVmzjoVU7aOvwLJpRxOm51fxLydGJDk2SjBKUiMRFS1sHS17fyb0rtlLX3Mb0oly+ePZMTp9eRGlpaaLDkySkBCUiMdXe4fnb2j3c/eIWyuuaKcrL4qbzjuWSEyaQkabRedKzuCQoa+29wMVAhXNuTjfbPwp8DTBAPfBp59yboW1bQ2XtQJtzbn48YhaRI+O957kN+7jzxc1sqWoiLyudT505nWvmFzMsSw/bSt/i1YJaDNwB3NfD9i3AWc65GmvthcDdwGlh2892zlXGNkQRiQbvPc+XVfKbl7awoaKB7Iw0rjm1mOsWFFOoFW6lH+KSoCupm1cAABR4SURBVJxzS62103rZ/lLYtyuAyTEPSkSiqsN7nt9YyW+XB4kpI83w4bmT+MTp0xg7PDvR4ckglIz3oG4A/hb2vQeettZ64C7n3N2RnORIbro2NDSk7E3bVK4bpHb9krVu7d7zRhU8V+7Z2wzpBhaOgXMmwMisctauKmdtH+dI1rpFSyrXL5Z1S6oEZa09myBBLQorXuSc22WtHQs8Y619xzm3tK9zlZSUDDiO0tLSIzo+maVy3SC165dsdWtubedPq8u5f+V2dtc2k52Rhj15ItecWsz4ETn9Oley1S3aUrl+0ajbkiVLui1PmgRlrT0R+C1woXOuqrPcObcr9LXCWvsYsADoM0GJSGxUN7aw5PWdLHljF7UHWsnLSue606Zy9SlTtOS6RFVSJChrbTHwKHCtc25DWHkekOacqw+9Pw/4boLCFBnSNlTU89CqnTy5bg+t7Z6x+dl87qyjuWzuRPKzk+JPiaSYeA0zfxAoAUZba3cCNwOZAM65O4FvA0XAr6y18M/h5OOAx0JlGcADzrkn4xGziEBbewelZZUseX0nr+3YD8Bx44Zz1SmTef9x4zTLuMRUvEbxXdXH9k8Cn+ymfDMwN1ZxiUj3KuoP8vhbu3nsrV3sa2ghzcDZM8dw9fwpzJ1UoIlcJS7ULhcRIJjxYcXWKh59czfLNlXS4WFUbiafWDiVy+ZO6vfAB5EjpQQlMsTtqGniz2+X89c1e6ioPwjA/OKRXHbiREpmjiErQ914khhKUCJDUH1zK//YsI8n1pTz+s5aAEblZnHtqcVceuJEpo7SQoGSeEpQIkNES1sHy7dU8eS6vSwtq6SlvYP0NMNZR4/mkhMmcOb0IjI06EGSiBKUSApra+9g5fYann6nguc27qPhYBsAx08YwUWzx/P+48YyUvPjSZJSghJJMa2hpPSP9RWUbtxHbXOQlKaNyuXq+VM477hx6sKTQUEJSiQFNLa0sWJLNc9t3MeLm6sOtZSKRw7j8nmTOPeYsRwzNl/Dw2VQUYISGaTKaw/wwqYqXthUyaodNbS2ewCOGp2HPXky5xwzhpljlJRk8FKCEhkk2jo8r2yr5qXNVby0pZotVY0ApBmYO6mA9xw1mrNmjqF4pLrvJDUoQYkkKe89myobeWVbDS9vrebVbZ7WVW8AUJCTwfmzxnHG9CLOmFFE4bDMBEcrEn1KUCJJwnvPtpomXtuxn1Xba1i5vYbqplYgaCVNzoX3nziNM6YXcfyEEaSnqetOUpsSVBdr99SxvcHT1t6hZ0Ikpto7PGX7GnhzVy2v79zP6zv3U9XYcmj71FG5nHPMWE4tHsn8qSN5bcWLlCyakcCIReJLCaqLe5dv5fkyz90blzJ7/AhOnFTACRNGcPyEEYzO17LVMnB1za28XV7H6l21rN5dy9vldTS2tB/aXjwyl/ccNZqTpxRyypSRWiZdhjwlqC4+Mm8SpqGSmvThrCmv4/Wd+w9tmzAih+MnjGDWuOHMGj+c48YNZ3iO+v7l3Zpa2thQ0cC6vfWsLa8LWuY1Bw5tT08zHDMmn3mTC5k3qYATJxXoA5BIF0pQXSycXkTztjRKSk6hpa2D9RX1vF1ex9uhT7x/X1/B39dXHNp/UkEOx44LktXMMfkcPSafccOzNbR3iPDeU9XYQtm+BjZUNLBhXwPr99azrboJH7bfuOHZnHPMGI4fP4ITJhUwa9xwcjLTExa3yGCgBNWLrIw0TphYwAkTC+CUKQDsP9DKO3vqgk/Ge+rZUFHPsxv28eyGfYeOG5GTwVGj85kxOo8ZRXkcNTqPaUV5jMrNVOIaxOqaW9lS2cjmquBVtq+RTZUN1IQGMnQanZfFmUcVMWvccI4bN4LZ44erdSQyAEpQ/VQ4LJOF04tYOL3oUFntgVY2VNRTVtlI2b4GNlY0sHbP4d2DECSuaaPymFaUS/HI4DVl5DAmFw7Tp+kk0dLWwc79B9ixv4kdNQfYVt0UejUeGlHXKSPNML0oj9OmjmLmmHyODbWiR+VpbjuRaFCCioKCYZmcOnUUp04ddaisvcOzu/YAmyob2VzZyNbqRrZWNbFxXwNv7a591znG5GcxuXAYEwuGMWFEDhMLg6/jh2czdniO1uSJkrb2DvY1HKS8rpk9dc3srm2mvK6ZnfsPsGv/ASrqDx7WNQeQnZFG8chcTp4y8lCreHpRHsUjh2mkp0gMKUHFSHqaYcrIXKaMzKVk5phD5d579jW0sL0m+GS+c/8BdtYEX9ftrT+0Nk84A4zKy2JsfjZjhwev0XnZjM7PYnR+NkW5WYzKy2LksMwh+wezvcNTe6CV3U2eFVuqqGpsobKxhX0NB4NX/UH21h+ksvEgHV0zEEESmlgwjDOPymdKYdCynVI4jOJRuYwfkUOaumZF4k4JKs6MMYeSzPzikYdt895T09RKeV0zu2oPsKe2mT31wSf8ivrgU/+6vfW9nr8gJ4PC3CwKh2VSOCyTETmZjMjJoGBYJsOzM9hR5cncXEl+Vga5WRnkZqWTl5VOTmY62RlpCbtH5r2ntd3T1NrOgZY2mlrbaTjYTsPBNhpb2qhvbqP+YCv1zW3UNrdS29RKbXMr+w+0UtPUSu2B1n+2fNa8+a7zD8/OYNzwbGaOzWdsfjYTCnKYMCKHCQXDmFiQQ1FelpKQSJKJW4Ky1t4LXAxUOOfmdLPdALcDFwFNwPXOuddC264DvhXa9fvOud/HJ+r4MsYwKi9oDR0/YUS3+xxsa2dfQwtVDQcPtRCqm1qobmyhqqmFmqZW9jcFo8rCn7EJ98Dmt7otTzOQk5FOdmYa2RlpZGekk5WeRma6ISs9jYz0NDLSDOlphow0gzGGNBO08IwxeB+kCA90eOjwno4OT1vnq72Dtg7PwbYOWts7aGnvoLm1g4Nt7TS3dtDuu2na9CI3M52CYZlMLMhhzoQRFOZm0li5h5Nmz6QoL4uiUKtzTH627vGJDELxbEEtBu4A7uth+4XAzNDrNODXwGnW2lHAzcB8gr99q6y1f3LO1cQ84iSUnZHO5MJgYEVfWts7qGtuo645aGE0HGzjlTdWM2XGzFDLpJ2mljaaWto50Bq8mlvbaW7roKWtg4NtHdS2tNLa0UFru6c1lGDau+sj60W6MWSkB0ktIz2N7FDSy85IoyAnk5zMIBnmZAatuWGZ6eRmpZOfnUFeVgb52enkZwctweE5GYzIyaQgJ7Pb+3KlpRWUhEZcisjgFrcE5Zxbaq2d1ssulwL3Oec8sMJaW2itnQCUAM8456oBrLXPABcAD8Y45EEvMz3tUEuiU9sOQ8lJk4/ovN572r3He/ChllKnzl6ydBPWwlLXmYgMQDLdg5oE7Aj7fmeorKdySRBjDBlKOiISY8mUoKKqtLR0wMc2NDQc0fHJLJXrBqldP9Vt8Erl+sWybsmUoHYB4TcPJofKdhF084WXl/Z1spKSkr526VFpaekRHZ/MUrlukNr1U90Gr1SuXzTqtmTJkm7LkylB/Qn4rLX2IYJBErXOuXJr7VPAf1lrO8dknwd8I1FBiohIfMRzmPmDBC2h0dbanQQj8zIBnHN3Ak8QDDEvIxhm/vHQtmpr7feAV0On+m7ngAkREUld8RzFd1Uf2z3wmR623QvcG4u4REQkOQ3NeXFERCTpKUGJiEhSUoISEZGkZHw/5z8bDJYsWZJ6lRIRSWFXXHHFu57+T8kEJSIig5+6+EREJCkpQYmISFJSghIRkaSkBCUiIklJCUpERJJSMk0WmxSstRcQLD2fDvzWOfejBIcUFdbae4GLgQrn3JxExxNN1topBCs1jyNYdflu59ztiY0qeqy1OcBSIJvg/+zDzrmbExtVdFlr04GVwC7n3MWJjidarLVbgXqgHWhzzs1PbETRZa0tBH4LzCH4v/cJ59zyaJ1fLagwof8kvyRYfn42cJW1dnZio4qaxQQrEaeiNuBG59xsYCHwmRT6vQEcBM5xzs0F5gEXWGsXJjimaPs8sC7RQcTI2c65eamWnEJuB550zh0HzCXKv0O1oA63AChzzm0GCC39cSmwNqFRRYFzbqm1dlqi44gF51w5UB56X2+tXUew6vKg/73BoYmUG0LfZoZeKfMAo7V2MvAB4AfAlxIcjkTIWlsAvBe4HsA51wK0RPMaSlCH6255+dMSFIsMQCgJnwS8nOBQoirUul8FHA380jmXSvX7OfBVYHiiA4kBDzxtrfXAXc65uxMdUBRNB/YBv7PWziX49/l551xjtC6gLj5JGdbafOAR4AvOubpExxNNzrl259w8ghWlF1hrU+I+orW2877oqkTHEiOLnHMnE9w2+Iy19r2JDiiKMoCTgV87504CGoGvR/MCSlCH62nZeUly1tpMguR0v3Pu0UTHEyvOuf3Ac6TO/cQzgQ+GBhM8BJxjrf1DYkOKHufcrtDXCuAxgtsIqWInsDOsNf8wQcKKGiWow70KzLTWTrfWZgFXEixFL0nMWmuAe4B1zrnbEh1PtFlrx4RGS2GtHQa8H3gnsVFFh3PuG865yc65aQT/3551zl2T4LCiwlqbZ60d3vkeOA94O7FRRY9zbg+ww1p7bKjoXKJ831f3oMI459qstZ8FniIYZn6vc25NgsOKCmvtg0AJMNpauxO42Tl3T2KjipozgWuB1dbaN0JlNznnnkhgTNE0Afh96D5UGvB/zrm/JDgm6ds44DFrLQR/ax9wzj2Z2JCi7v8B94c+0G8GPh7Nk2s2cxERSUrq4hMRkaSkBCUiIklJCUpERJKSEpSIiCQlJSgREUlKSlAyZBljxhljlhpj6o0xP010PNIzY8zfjDHXJToOiS8lKIkpY8xWY8z7upRdb4xZlqiYwnwKqARGeO9vjPfFjTG3GGNajTENYa8ZPew72hjzojGmyhiz3xiz3BhzZpd9vmiM2WOMqTPG3GuMyY5PTQ5df7Exps0YM6FLeUM3r1ZjzOYeznOLMeaw2SS89xd6738fy/gl+ShBScowxvT3wfOpwFrfw8OAAzjfQDjvfX7Yq9s/2gSzmX8CGAOMBP4b+HNnjMaY8wnmQTuXoF4zgO/EPPoQY0we8GGgFjhsJogu9csHjgGqge/FKz4ZnJSgJOGMMbOMMaWhlsEaY8wHw7aVGmM+Gfb9Ya0vY4w3xnzGGLMR2GgCPzPGVIRaEquNMe+aWNUYsxi4Dvhq6BP9+0Kf3B82xvzBGFMHXG+MyTbG/NwYszv0+nlny8QYU2KM2WmM+WroeuXGmA8ZYy4yxmwwxlQbY26Kxs/Ie9/svV/vve8ADMECeCOBUaFdrgPu8d6v8d7XEPzxv77Lz+lzxpjNxphKY8ytxpi0sJ/pi6Gf2/7QPmeEyneE6tZX99qHgf3Ad0OxdCuUUP8P+LP3/nfdbL8AuAmwod/Lm6HyQ/8O+htv6Hf4E2PMdmPMXmPMncaYYX3UR5KAEpQklDEmE/gz8DQwltDUKcaYY3s98HAfIlgWZTbBfGfvJfiUXgD8C1DV9QDv/fXA/cCPQ5/s/x7adCnBpJeFoe3fJFgEcR7BgmwLgG+FnWo8kEOwVMu3gd8QtCBOAd4D/KcxZnovsV8SSmRrjDGfDt9gjHnLGHN11zKgmWCOyN967ytCm44H3gzb9U1gnDGmKKzsMmA+wYSelxK0yDqdBrwFFAEPEEzceirB8h7XAHcYY/J7qcd1wIOh444zxpzSw34/BvKAz3a30Xv/JPBf/LNlObeH8/Qn3h8R/HuYF9re+buSZOe910uvmL2ArQTdU/vDXk3AstD29wB7gLSwYx4Ebgm9LwU+Gbbt+s5jQ9974Jyw788BNhAklbQ+YlsMfD/s+1uApV322QRcFPb9+cDW0PsS4ACQHvp+eCie08L2XwV8qIfrzwYmEsz7eAbBootXRfAzzQGuAq7rEucFYd93Lmo4LeznFL79P4B/hP1MN4ZtOyG0/7iwsipgXg/xFAMdndsJ5rK8vZv9PgzUADP6qN8twB+6lB36d9CfeAlam43AUWHbTge2JPr/hl59v9SCknj4kPe+sPNF8Mex00Rghw+6rjptI/iUG6lDi0x6758F7gB+CVQYY+42xowYyLnC4tvWJbaJYd9Xee/bQ+8PhL7uDdt+AOi25eG9X+u93+29b/fev0SwfPZH+grQB919DwJfN8Z0tjAagPB6dr6vDysLr1vXenSNGe99RPUgmKh3nfe+c6Le+4GrQ61jAIwxxxDMOH+d7/k+W39EGu8YIBdYFeoO3A88GSqXJKcEJYm2G5jSeT8kpJh/rsPVSPAHptP4bs5x2CAH7/0vvPenELRQjgG+0o94ug6Y2E0w6CA8tt39OF9/eIJP/JHKJBgMAbCGoAuy01xgr/c+vHszfK2zaNbjY8CM0AjCPcBtwGjgIgBjTC7BWl13eu8jWb4mmjNYVxIkq+PDPiQV+GCwhiQ5JShJtJcJuvy+aozJNMaUAJcQ3FMAeAO43BiTa4w5Griht5MZY041xpwW+vTeSHC/pqO3Y/rwIPAtY8wYY8xognsXUVlQzxhzqTFmZGhgxwLgc8DjPey70BizyBiTZYwZZoz5GsFyDp2Lxd0H3GCMmW2MKSS4T7a4y2m+ErreFODzgItCHU4HjiK4Nzcv9JpDcF/oY6Hd7iTocvtmhKfdC0zr8qFlQEIt898APzPGjA3FPMkEox4lySlBSUJ571sIEtKFBJ92fwV8zHvfuSDfz4AWgj9avyfoPurNCII/SDUE3VhVwK1HEOL3gZUEN+RXA6+FyqLhSqCMoBvuPuC/fdizPqGBEx8NfZtN0G1ZRdC6vAj4gPd+NxwaXPBjgtV2txPU/eYu13uc4J7YG8BfCbrcjtR1wOPe+9Xe+z2dL4LuyouNMcUEXYALgVrT5XmoHs65JPS1yhjzWhRi/BrBz3lFaHTm34H+DMKRBNF6UCJDgDHGAzO992WJjkUkUmpBiYhIUlKCEhGRpKQuPhERSUpqQYmISFJSghIRkaSkBCUiIklJCUpERJKSEpSIiCSl/w+3/V6dG0RmUwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "\n",
    "# this gives a Time object with an *array* of times\n",
    "delta_hours = np.linspace(0, 6, 100)*u.hour\n",
    "full_night_times = observing_time + delta_hours\n",
    "full_night_aa_frames = AltAz(location=VBO, obstime=full_night_times)\n",
    "full_night_aa_coos = hcg7_center.transform_to(full_night_aa_frames)\n",
    "\n",
    "plt.plot(delta_hours, full_night_aa_coos.secz)\n",
    "plt.xlabel('Hours from 5:30pm AZ time')\n",
    "plt.ylabel('Airmass [Sec(z)]')\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Great! Looks like the lowest airmass is in another hour and half or so (7 PM). But that might still be twilight… When should we start observing for proper dark skies? Fortunately, Astropy provides a get_sun function that can be used to check this. Let’s use it to check if we’re in 18-degree twilight or not."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from astropy.coordinates import get_sun\n",
    "\n",
    "full_night_sun_coos = get_sun(full_night_times).transform_to(full_night_aa_frames)\n",
    "plt.plot(delta_hours, full_night_sun_coos.alt.deg)\n",
    "plt.axhline(-18, color='k')\n",
    "plt.xlabel('Hours from 6pm AZ time')\n",
    "plt.ylabel('Sun altitude')\n",
    "plt.tight_layout()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}