eteq/coordinates.ipynb

## coordinates.ipynb
{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Using `astropy.coordinates` to Match Catalogs and Plan Observations"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this tutorial, we will explore how the `astropy.coordinates` package and related astropy functionality can be used to help in planning observations or other exercises focused on large coordinate catalogs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Python standard-library\n",
    "from urllib.parse import urlencode\n",
    "from urllib.request import urlretrieve\n",
    "\n",
    "# Third-party dependencies\n",
    "from astropy import units as u\n",
    "from astropy.coordinates import SkyCoord\n",
    "from astropy.table import Table\n",
    "import numpy as np\n",
    "from IPython.display import Image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Set up matplotlib and use a nicer set of plot parameters\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Describing on-sky locations with `coordinates`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's start by considering a field around the picturesque Hickson Compact Group 7.  To do anything with this, we need to get an object that represents the coordinates of the center of this group.\n",
    "\n",
    "In Astropy, the most common object you'll work with for coordinates is `SkyCoord`.  A `SkyCoord` can be created most easily directly from angles as shown below.  It's also wise to explicitly specify the frame your coordinates are in, although this is not strictly necessary because the default is ICRS. \n",
    "\n",
    "(If you're not sure what ICRS is, it's basically safe to think of it as an approximation to an equatorial system at the J2000 equinox)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<SkyCoord (ICRS): (ra, dec) in deg\n",
       "    ( 9.81625,  0.88806)>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hcg7_center = SkyCoord(9.81625*u.deg, 0.88806*u.deg, frame='icrs')\n",
    "hcg7_center"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "SkyCoord will also accept string-formatted coordinates either as separate strings for ra/dec or a single string.  You'll have to give units, though, if they aren't part of the string itself."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<SkyCoord (ICRS): (ra, dec) in deg\n",
       "    ( 9.81625,  0.88806)>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SkyCoord('0h39m15.9s', '0d53m17.016s', frame='icrs')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<SkyCoord (ICRS): (ra, dec) in deg\n",
       "    ( 9.81625,  0.88806)>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SkyCoord('0:39:15.9 0:53:17.016', unit=(u.hour, u.deg), frame='icrs')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If the object you're interested in is in [SESAME](http://cdsweb.u-strasbg.fr/cgi-bin/Sesame), you can also look it up directly from its name using the `SkyCoord.from_name()` class method<sup>1</sup>. Note that this requires an internet connection.  It's safe to skip if you don't have one, because we defined it above explicitly.\n",
    "\n",
    "*If you don't know what a class method is, think of it like an alternative constructor for a `SkyCoord` object -- calling `SkyCoord.from_name()` with a name gives you a new `SkyCoord` object. For more detailed background on what class methods are and when they're useful, see [this page](https://julien.danjou.info/blog/2013/guide-python-static-class-abstract-methods).*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<SkyCoord (ICRS): (ra, dec) in deg\n",
       "    ( 9.849602,  0.87817)>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hcg7_center = SkyCoord.from_name('HCG 7')\n",
    "hcg7_center"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This object we just created has various useful ways of accessing the information contained within it.  In particular, the ``ra`` and ``dec`` attributes are specialized [``Quantity``](http://docs.astropy.org/en/stable/units/index.html) objects (actually, a subclass called [``Angle``](http://docs.astropy.org/en/stable/api/astropy.coordinates.Angle.html), which in turn is subclassed by [``Latitude``](http://docs.astropy.org/en/stable/api/astropy.coordinates.Latitude.html) and [``Longitude``](http://docs.astropy.org/en/stable/api/astropy.coordinates.Longitude.html)).  These objects store angles and provide pretty representations of those angles, as well as some useful attributes to quickly convert to common angle units:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(astropy.coordinates.angles.Longitude, astropy.coordinates.angles.Latitude)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(hcg7_center.ra), type(hcg7_center.dec)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$0^\\circ52{}^\\prime41.412{}^{\\prime\\prime}$"
      ],
      "text/plain": [
       "<Latitude 0.87817 deg>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hcg7_center.dec"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$9^\\circ50{}^\\prime58.5672{}^{\\prime\\prime}$"
      ],
      "text/plain": [
       "<Longitude 9.849602 deg>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hcg7_center.ra"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.6566401333333335"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hcg7_center.ra.hour"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now that we have a `SkyCoord` object, we can try to use it to access data from the [Sloan Digitial Sky Survey](http://www.sdss.org/) (SDSS).  Let's start by trying to get a picture using the SDSS image cutout service to make sure HCG7 is in the SDSS footprint and has good image quality.\n",
    "\n",
    "This requires an internet connection, but if it fails, don't worry: the file is included in the repository so you can just let it use the local file``'HCG7_SDSS_cutout.jpg'``, defined at the top of the cell.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('HCG7_SDSS_cutout.jpg', <http.client.HTTPMessage at 0x1122978d0>)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "impix = 1024\n",
    "imsize = 12*u.arcmin\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=impix, height=impix, \n",
    "                              scale=imsize.to(u.arcsec).value/impix))\n",
    "url = cutoutbaseurl + '?' + query_string\n",
    "\n",
    "# this downloads the image to your disk\n",
    "urlretrieve(url, 'HCG7_SDSS_cutout.jpg')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now lets take a look at the image."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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iinK61HJWKaKzsEX5ie1DDaMc00ZzxxRkc8nNaCuKPukde+aM4PrR83UjoKTk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ZKkDtTSeeD0qTzWaLyyflBzyaAG/Nk4H1FPRMqx9BniowSmO1AY9BxxigCWKF5nCKuWY4HNLd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\nbhzVaaQyys5AyxycVOt/IpqPKnfUacdORS8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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image('HCG7_SDSS_cutout.jpg')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Very pretty!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exercises"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create a `SkyCoord` of some other astronomical object you find interesting. Using only a single method/function call, get a string with the RA/Dec in the form 'HH:MM:SS.S DD:MM:SS.S'.  Check your answer against an academic paper or some web site like [SIMBAD](http://simbad.u-strasbg.fr/simbad/) that will show you sexigesimal coordinates for the object.\n",
    "\n",
    "(Hint: `SkyCoord.to_string()` might be worth reading up on)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now get an image of that object from the Digitized Sky Survey and download it and/or show it in the notebook. Bonus points if you figure out the (one-line) trick to get it to display in the notebook *without* ever downloading the file yourself.\n",
    "\n",
    "(Hint: STScI has an easy-to-access [copy of the DSS](https://archive.stsci.edu/dss/).  The pattern to follow for the web URL is ``http://archive.stsci.edu/cgi-bin/dss_search?f=GIF&ra=RA&dec=DEC``)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Using `coordinates` and `table` to match and compare catalogs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "At the end of the last section, we determined that HCG7 is in the SDSS imaging survey, so that means we can use the cells below to download catalogs of objects directly from the SDSS. Later on, we will match this catalog to another catalog covering the same field, allowing us to make plots using the combination of the two catalogs."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will access the SDSS SQL database using the [astroquery](https://astroquery.readthedocs.org) affiliated package.  This will require an internet connection and a working install of astroquery. If you don't have these you can just skip down two cells, because the data files are provided with the repository. Depending on your version of astroquery it might also issue a warning, which you should be able to safely ignore."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/erik/miniconda3/lib/python3.5/site-packages/astroquery/sdss/__init__.py:29: UserWarning: Experimental: SDSS has not yet been refactored to have its API match the rest of astroquery (but it's nearly there).\n",
      "  warnings.warn(\"Experimental: SDSS has not yet been refactored to have its API \"\n"
     ]
    }
   ],
   "source": [
    "from astroquery.sdss import SDSS\n",
    "sdss = SDSS.query_region(coordinates=hcg7_center, radius=20*u.arcmin, \n",
    "                         spectro=True, \n",
    "                         photoobj_fields=['ra','dec','u','g','r','i','z'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`astroquery` queries gives us back an [`astropy.table.Table` object](http://docs.astropy.org/en/stable/table/index.html).  We could just work with this directly without saving anything to disk if we wanted to.  But here we will use the capability to  write to disk.  That way, if you quit the session and come back later, you don't have to run the query a second time.\n",
    "\n",
    "(Note that this won't work fail if you skipped the last step.  Don't worry, you can just skip to the next cell with ``Table.read`` and use the copy of this table included in the tutorial.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "sdss.write('HCG7_SDSS_photo.dat', format='ascii')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you don't have internet, you can read the table into python by running the cell below.  But if you did the astroquery step above, you could skip this, as the table is already in memory as the `sdss` variable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "sdss = Table.read('HCG7_SDSS_photo.dat', format='ascii')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ok, so we have a catalog of objects we got from the SDSS.  Now lets say you have your own catalog of objects in the same field that you want to match to this SDSS catalog.  In this case, we will use a catalog extracted from the [2MASS](http://www.ipac.caltech.edu/2mass/).  We first load up this catalog into python."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "twomass = Table.read('HCG7_2MASS.tbl', format='ascii')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now to do matching we need `SkyCoord` objects.  We'll have to build these from the tables we loaded, but it turns out that's pretty straightforward: we grab the RA and dec columns from the table and provide them to the `SkyCoord` constructor.  Lets first have a look at the tables to see just what everything is that's in them."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "&lt;Table length=682&gt;\n",
       "<table id=\"table4649811304\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>ra</th><th>dec</th><th>u</th><th>g</th><th>r</th><th>i</th><th>z</th></tr></thead>\n",
       "<thead><tr><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th></tr></thead>\n",
       "<tr><td>9.85142233276</td><td>0.660021031159</td><td>22.8327</td><td>20.50534</td><td>19.02676</td><td>17.70129</td><td>16.97601</td></tr>\n",
       "<tr><td>9.91318165979</td><td>1.10494984959</td><td>20.45888</td><td>19.25467</td><td>18.52454</td><td>18.19474</td><td>17.88742</td></tr>\n",
       "<tr><td>9.78676663674</td><td>0.884631488113</td><td>19.60848</td><td>18.68292</td><td>17.76442</td><td>17.38597</td><td>17.11522</td></tr>\n",
       "<tr><td>9.86140974949</td><td>0.745947843825</td><td>23.01928</td><td>21.50809</td><td>20.29095</td><td>19.78649</td><td>19.47331</td></tr>\n",
       "<tr><td>10.0195110549</td><td>0.747784712598</td><td>22.44757</td><td>20.61082</td><td>18.8336</td><td>18.19663</td><td>17.71837</td></tr>\n",
       "<tr><td>9.56078248604</td><td>0.619560657218</td><td>19.78478</td><td>17.88036</td><td>16.91253</td><td>16.49844</td><td>16.16783</td></tr>\n",
       "<tr><td>9.69389626833</td><td>1.11425662554</td><td>26.13163</td><td>20.6128</td><td>20.56435</td><td>20.34916</td><td>19.66869</td></tr>\n",
       "<tr><td>10.0775826926</td><td>0.790111126439</td><td>21.14568</td><td>18.76275</td><td>17.45607</td><td>16.95887</td><td>16.72254</td></tr>\n",
       "<tr><td>10.1303393483</td><td>1.15237735566</td><td>22.96277</td><td>21.15212</td><td>19.39642</td><td>18.78123</td><td>18.43637</td></tr>\n",
       "<tr><td>9.63379865776</td><td>1.04451580716</td><td>20.88008</td><td>19.80103</td><td>18.69122</td><td>18.20208</td><td>17.96495</td></tr>\n",
       "<tr><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td></tr>\n",
       "<tr><td>9.72918957822</td><td>0.656378251653</td><td>20.75797</td><td>19.03338</td><td>18.19287</td><td>17.87208</td><td>17.72765</td></tr>\n",
       "<tr><td>9.95221365072</td><td>0.845145619645</td><td>22.81809</td><td>20.70747</td><td>19.24776</td><td>18.60262</td><td>18.24147</td></tr>\n",
       "<tr><td>9.93099932805</td><td>0.638142996055</td><td>23.25417</td><td>22.10502</td><td>20.48582</td><td>19.46803</td><td>18.93533</td></tr>\n",
       "<tr><td>9.90274476846</td><td>0.794652307436</td><td>25.6569</td><td>21.92934</td><td>20.24096</td><td>19.32332</td><td>18.97122</td></tr>\n",
       "<tr><td>9.95289117463</td><td>0.941581105711</td><td>20.8403</td><td>19.91397</td><td>19.63015</td><td>19.47071</td><td>19.44774</td></tr>\n",
       "<tr><td>10.0614782147</td><td>0.710481131796</td><td>19.97823</td><td>17.32766</td><td>16.07767</td><td>15.58068</td><td>15.30027</td></tr>\n",
       "<tr><td>9.86737236493</td><td>1.1203947898</td><td>20.42693</td><td>19.39079</td><td>19.06576</td><td>18.92027</td><td>18.93778</td></tr>\n",
       "<tr><td>10.086274222</td><td>0.880830948406</td><td>18.45603</td><td>16.49136</td><td>15.44498</td><td>14.9986</td><td>14.61169</td></tr>\n",
       "<tr><td>9.53729913946</td><td>0.855434437201</td><td>22.17931</td><td>20.77754</td><td>19.05077</td><td>18.44905</td><td>18.08414</td></tr>\n",
       "<tr><td>9.74546663598</td><td>0.804785379786</td><td>23.40089</td><td>22.80742</td><td>21.17173</td><td>20.07909</td><td>19.74573</td></tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<Table length=682>\n",
       "      ra           dec          u        g        r        i        z    \n",
       "   float64       float64     float64  float64  float64  float64  float64 \n",
       "------------- -------------- -------- -------- -------- -------- --------\n",
       "9.85142233276 0.660021031159  22.8327 20.50534 19.02676 17.70129 16.97601\n",
       "9.91318165979  1.10494984959 20.45888 19.25467 18.52454 18.19474 17.88742\n",
       "9.78676663674 0.884631488113 19.60848 18.68292 17.76442 17.38597 17.11522\n",
       "9.86140974949 0.745947843825 23.01928 21.50809 20.29095 19.78649 19.47331\n",
       "10.0195110549 0.747784712598 22.44757 20.61082  18.8336 18.19663 17.71837\n",
       "9.56078248604 0.619560657218 19.78478 17.88036 16.91253 16.49844 16.16783\n",
       "9.69389626833  1.11425662554 26.13163  20.6128 20.56435 20.34916 19.66869\n",
       "10.0775826926 0.790111126439 21.14568 18.76275 17.45607 16.95887 16.72254\n",
       "10.1303393483  1.15237735566 22.96277 21.15212 19.39642 18.78123 18.43637\n",
       "9.63379865776  1.04451580716 20.88008 19.80103 18.69122 18.20208 17.96495\n",
       "          ...            ...      ...      ...      ...      ...      ...\n",
       "9.72918957822 0.656378251653 20.75797 19.03338 18.19287 17.87208 17.72765\n",
       "9.95221365072 0.845145619645 22.81809 20.70747 19.24776 18.60262 18.24147\n",
       "9.93099932805 0.638142996055 23.25417 22.10502 20.48582 19.46803 18.93533\n",
       "9.90274476846 0.794652307436  25.6569 21.92934 20.24096 19.32332 18.97122\n",
       "9.95289117463 0.941581105711  20.8403 19.91397 19.63015 19.47071 19.44774\n",
       "10.0614782147 0.710481131796 19.97823 17.32766 16.07767 15.58068 15.30027\n",
       "9.86737236493   1.1203947898 20.42693 19.39079 19.06576 18.92027 18.93778\n",
       " 10.086274222 0.880830948406 18.45603 16.49136 15.44498  14.9986 14.61169\n",
       "9.53729913946 0.855434437201 22.17931 20.77754 19.05077 18.44905 18.08414\n",
       "9.74546663598 0.804785379786 23.40089 22.80742 21.17173 20.07909 19.74573"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sdss # just to see an example of the format"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "&lt;Table masked=True length=23&gt;\n",
       "<table id=\"table4650030360\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>designation</th><th>ra</th><th>dec</th><th>r_k20fe</th><th>j_m_k20fe</th><th>j_msig_k20fe</th><th>j_flg_k20fe</th><th>h_m_k20fe</th><th>h_msig_k20fe</th><th>h_flg_k20fe</th><th>k_m_k20fe</th><th>k_msig_k20fe</th><th>k_flg_k20fe</th><th>k_ba</th><th>k_phi</th><th>sup_ba</th><th>sup_phi</th><th>r_ext</th><th>j_m_ext</th><th>j_msig_ext</th><th>h_m_ext</th><th>h_msig_ext</th><th>k_m_ext</th><th>k_msig_ext</th><th>cc_flg</th><th>dist</th><th>angle</th></tr></thead>\n",
       "<thead><tr><th></th><th>deg</th><th>deg</th><th>arcsec</th><th>mag</th><th>mag</th><th></th><th>mag</th><th>mag</th><th></th><th>mag</th><th>mag</th><th></th><th></th><th>deg</th><th></th><th>deg</th><th>arcsec</th><th>mag</th><th>mag</th><th>mag</th><th>mag</th><th>mag</th><th>mag</th><th></th><th>arcsec</th><th>deg</th></tr></thead>\n",
       "<thead><tr><th>str16</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>int64</th><th>float64</th><th>float64</th><th>int64</th><th>float64</th><th>float64</th><th>int64</th><th>float64</th><th>int64</th><th>float64</th><th>int64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>str1</th><th>float64</th><th>float64</th></tr></thead>\n",
       "<tr><td>00402069+0052508</td><td>10.086218</td><td>0.880798</td><td>9.4</td><td>13.835</td><td>0.068</td><td>0</td><td>13.01</td><td>0.086</td><td>0</td><td>12.588</td><td>0.089</td><td>0</td><td>0.8</td><td>70</td><td>0.82</td><td>35</td><td>18.62</td><td>13.632</td><td>0.088</td><td>12.744</td><td>0.104</td><td>12.398</td><td>0.105</td><td>0</td><td>972.120611</td><td>91.538952</td></tr>\n",
       "<tr><td>00395984+0103545</td><td>9.99935</td><td>1.06514</td><td>12.9</td><td>12.925</td><td>0.035</td><td>0</td><td>12.183</td><td>0.042</td><td>0</td><td>11.89</td><td>0.067</td><td>0</td><td>0.8</td><td>35</td><td>0.7</td><td>40</td><td>35.9</td><td>12.469</td><td>0.048</td><td>11.91</td><td>0.066</td><td>11.522</td><td>0.087</td><td>0</td><td>916.927636</td><td>45.951861</td></tr>\n",
       "<tr><td>00401849+0049448</td><td>10.077062</td><td>0.82913</td><td>6.0</td><td>14.918</td><td>0.086</td><td>0</td><td>14.113</td><td>0.107</td><td>0</td><td>13.714</td><td>0.103</td><td>0</td><td>0.6</td><td>-15</td><td>1.0</td><td>90</td><td>11.35</td><td>14.631</td><td>0.121</td><td>13.953</td><td>0.169</td><td>13.525</td><td>0.161</td><td>0</td><td>962.489231</td><td>102.73149</td></tr>\n",
       "<tr><td>00395277+0057124</td><td>9.969907</td><td>0.953472</td><td>5.3</td><td>14.702</td><td>0.049</td><td>0</td><td>14.248</td><td>0.069</td><td>0</td><td>13.899</td><td>0.095</td><td>0</td><td>0.6</td><td>-60</td><td>0.44</td><td>-50</td><td>10.59</td><td>14.62</td><td>0.144</td><td>14.15</td><td>0.296</td><td>13.73</td><td>0.2</td><td>0</td><td>601.136444</td><td>66.93659</td></tr>\n",
       "<tr><td>00401864+0047245</td><td>10.077704</td><td>0.790143</td><td>7.6</td><td>15.585</td><td>0.134</td><td>1</td><td>15.003</td><td>0.18</td><td>1</td><td>14.049</td><td>0.142</td><td>1</td><td>0.5</td><td>30</td><td>0.46</td><td>30</td><td>14.48</td><td>14.977</td><td>0.138</td><td>14.855</td><td>0.303</td><td>13.653</td><td>0.18</td><td>0</td><td>1004.982128</td><td>110.53147</td></tr>\n",
       "<tr><td>00393485+0051355</td><td>9.895219</td><td>0.859882</td><td>39.3</td><td>11.415</td><td>0.031</td><td>3</td><td>10.755</td><td>0.044</td><td>3</td><td>10.514</td><td>0.068</td><td>3</td><td>0.6</td><td>-30</td><td>0.7</td><td>-60</td><td>92.29</td><td>11.415</td><td>0.018</td><td>10.155</td><td>0.054</td><td>9.976</td><td>0.085</td><td>0</td><td>301.813395</td><td>109.639102</td></tr>\n",
       "<tr><td>00392964+0103495</td><td>9.873526</td><td>1.063769</td><td>10.9</td><td>14.463</td><td>0.065</td><td>0</td><td>13.618</td><td>0.067</td><td>0</td><td>13.258</td><td>0.091</td><td>0</td><td>0.4</td><td>55</td><td>0.28</td><td>60</td><td>20.35</td><td>14.2</td><td>0.086</td><td>13.363</td><td>0.091</td><td>13.101</td><td>0.133</td><td>0</td><td>665.301415</td><td>18.051526</td></tr>\n",
       "<tr><td>00403343+0049079</td><td>10.139293</td><td>0.818865</td><td>5.0</td><td>15.484</td><td>0.15</td><td>0</td><td>--</td><td>--</td><td>--</td><td>13.97</td><td>0.137</td><td>0</td><td>1.0</td><td>90</td><td>1.0</td><td>90</td><td>10.05</td><td>15.035</td><td>0.183</td><td>14.725</td><td>0.0</td><td>13.654</td><td>0.189</td><td>0</td><td>1189.207905</td><td>102.088788</td></tr>\n",
       "<tr><td>00393319+0035505</td><td>9.888305</td><td>0.597381</td><td>11.5</td><td>13.156</td><td>0.033</td><td>0</td><td>12.509</td><td>0.043</td><td>0</td><td>12.073</td><td>0.059</td><td>0</td><td>0.6</td><td>-55</td><td>0.52</td><td>-40</td><td>21.64</td><td>13.026</td><td>0.04</td><td>12.247</td><td>0.046</td><td>11.978</td><td>0.065</td><td>0</td><td>1078.11027</td><td>166.0785</td></tr>\n",
       "<tr><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td></tr>\n",
       "<tr><td>00391798+0041588</td><td>9.824936</td><td>0.699687</td><td>6.1</td><td>15.685</td><td>0.168</td><td>0</td><td>14.89</td><td>0.191</td><td>0</td><td>14.003</td><td>0.155</td><td>0</td><td>1.0</td><td>90</td><td>1.0</td><td>90</td><td>11.4</td><td>15.677</td><td>0.312</td><td>14.415</td><td>0.226</td><td>13.568</td><td>0.19</td><td>0</td><td>678.863209</td><td>177.360117</td></tr>\n",
       "<tr><td>00384796+0034572</td><td>9.699858</td><td>0.582578</td><td>5.1</td><td>14.925</td><td>0.077</td><td>0</td><td>14.224</td><td>0.114</td><td>0</td><td>13.536</td><td>0.079</td><td>0</td><td>1.0</td><td>90</td><td>1.0</td><td>90</td><td>10.2</td><td>14.839</td><td>0.133</td><td>14.111</td><td>0.192</td><td>13.461</td><td>0.137</td><td>0</td><td>1176.842625</td><td>200.856597</td></tr>\n",
       "<tr><td>00390392+0050579</td><td>9.766345</td><td>0.849419</td><td>5.0</td><td>14.895</td><td>0.07</td><td>0</td><td>14.238</td><td>0.087</td><td>0</td><td>13.834</td><td>0.11</td><td>0</td><td>1.0</td><td>90</td><td>1.0</td><td>90</td><td>10.05</td><td>14.706</td><td>0.107</td><td>14.033</td><td>0.132</td><td>13.75</td><td>0.187</td><td>0</td><td>227.201453</td><td>232.24689</td></tr>\n",
       "<tr><td>00391339+0051508</td><td>9.805797</td><td>0.864135</td><td>52.8</td><td>10.362</td><td>0.014</td><td>0</td><td>9.631</td><td>0.017</td><td>0</td><td>9.334</td><td>0.024</td><td>0</td><td>0.3</td><td>-15</td><td>0.4</td><td>-15</td><td>75.02</td><td>10.279</td><td>0.015</td><td>9.527</td><td>0.016</td><td>9.247</td><td>0.023</td><td>0</td><td>93.990015</td><td>203.598476</td></tr>\n",
       "<tr><td>00391786+0054458</td><td>9.824418</td><td>0.912743</td><td>27.9</td><td>11.082</td><td>0.016</td><td>0</td><td>10.384</td><td>0.022</td><td>0</td><td>10.147</td><td>0.032</td><td>0</td><td>0.5</td><td>5</td><td>0.7</td><td>5</td><td>42.75</td><td>10.914</td><td>0.018</td><td>10.251</td><td>0.021</td><td>10.031</td><td>0.03</td><td>0</td><td>93.596555</td><td>18.308033</td></tr>\n",
       "<tr><td>00385879+0057269</td><td>9.744971</td><td>0.957478</td><td>5.0</td><td>15.535</td><td>0.122</td><td>0</td><td>14.796</td><td>0.145</td><td>0</td><td>14.278</td><td>0.165</td><td>0</td><td>1.0</td><td>90</td><td>1.0</td><td>90</td><td>10.05</td><td>15.535</td><td>0.122</td><td>14.623</td><td>0.227</td><td>14.147</td><td>0.269</td><td>0</td><td>358.163568</td><td>314.246475</td></tr>\n",
       "<tr><td>00391879+0053308</td><td>9.828303</td><td>0.891909</td><td>15.4</td><td>13.044</td><td>0.047</td><td>0</td><td>12.412</td><td>0.063</td><td>0</td><td>12.077</td><td>0.094</td><td>0</td><td>0.8</td><td>60</td><td>0.74</td><td>65</td><td>23.62</td><td>12.755</td><td>0.048</td><td>12.283</td><td>0.072</td><td>11.713</td><td>0.096</td><td>0</td><td>45.544562</td><td>72.287562</td></tr>\n",
       "<tr><td>00391213+0102408</td><td>9.80055</td><td>1.044691</td><td>5.0</td><td>15.568</td><td>0.126</td><td>0</td><td>15.047</td><td>0.181</td><td>0</td><td>14.356</td><td>0.176</td><td>0</td><td>1.0</td><td>90</td><td>1.0</td><td>90</td><td>10.05</td><td>15.295</td><td>0.181</td><td>15.047</td><td>0.181</td><td>14.067</td><td>0.25</td><td>0</td><td>566.696375</td><td>354.276982</td></tr>\n",
       "<tr><td>00383990+0104442</td><td>9.666268</td><td>1.078968</td><td>5.3</td><td>15.255</td><td>0.108</td><td>0</td><td>14.232</td><td>0.121</td><td>0</td><td>13.873</td><td>0.113</td><td>0</td><td>1.0</td><td>90</td><td>1.0</td><td>90</td><td>10.44</td><td>15.151</td><td>0.18</td><td>13.812</td><td>0.149</td><td>13.552</td><td>0.155</td><td>0</td><td>873.946372</td><td>321.851314</td></tr>\n",
       "<tr><td>00384916+0050212</td><td>9.704872</td><td>0.839244</td><td>5.1</td><td>15.075</td><td>0.088</td><td>0</td><td>14.651</td><td>0.17</td><td>0</td><td>13.804</td><td>0.101</td><td>0</td><td>1.0</td><td>90</td><td>1.0</td><td>90</td><td>10.2</td><td>15.053</td><td>0.159</td><td>14.651</td><td>0.17</td><td>13.682</td><td>0.171</td><td>0</td><td>437.740484</td><td>246.331036</td></tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<Table masked=True length=23>\n",
       "  designation        ra      dec    r_k20fe ... cc_flg     dist      angle   \n",
       "                    deg      deg     arcsec ...           arcsec      deg    \n",
       "     str16        float64  float64  float64 ...  str1    float64    float64  \n",
       "---------------- --------- -------- ------- ... ------ ----------- ----------\n",
       "00402069+0052508 10.086218 0.880798     9.4 ...      0  972.120611  91.538952\n",
       "00395984+0103545   9.99935  1.06514    12.9 ...      0  916.927636  45.951861\n",
       "00401849+0049448 10.077062  0.82913     6.0 ...      0  962.489231  102.73149\n",
       "00395277+0057124  9.969907 0.953472     5.3 ...      0  601.136444   66.93659\n",
       "00401864+0047245 10.077704 0.790143     7.6 ...      0 1004.982128  110.53147\n",
       "00393485+0051355  9.895219 0.859882    39.3 ...      0  301.813395 109.639102\n",
       "00392964+0103495  9.873526 1.063769    10.9 ...      0  665.301415  18.051526\n",
       "00403343+0049079 10.139293 0.818865     5.0 ...      0 1189.207905 102.088788\n",
       "00393319+0035505  9.888305 0.597381    11.5 ...      0  1078.11027   166.0785\n",
       "             ...       ...      ...     ... ...    ...         ...        ...\n",
       "00391798+0041588  9.824936 0.699687     6.1 ...      0  678.863209 177.360117\n",
       "00384796+0034572  9.699858 0.582578     5.1 ...      0 1176.842625 200.856597\n",
       "00390392+0050579  9.766345 0.849419     5.0 ...      0  227.201453  232.24689\n",
       "00391339+0051508  9.805797 0.864135    52.8 ...      0   93.990015 203.598476\n",
       "00391786+0054458  9.824418 0.912743    27.9 ...      0   93.596555  18.308033\n",
       "00385879+0057269  9.744971 0.957478     5.0 ...      0  358.163568 314.246475\n",
       "00391879+0053308  9.828303 0.891909    15.4 ...      0   45.544562  72.287562\n",
       "00391213+0102408   9.80055 1.044691     5.0 ...      0  566.696375 354.276982\n",
       "00383990+0104442  9.666268 1.078968     5.3 ...      0  873.946372 321.851314\n",
       "00384916+0050212  9.704872 0.839244     5.1 ...      0  437.740484 246.331036"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "twomass # just to see an example of the format"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "OK, looks like they both have ``ra`` and ``dec`` columns, so we should be able to use that to make `SkyCoord`s.\n",
    "\n",
    "You might first think you need to create a separate `SkyCoord` for *every* row in the table, given that up until now all `SkyCoord`s we made were for just a single point.  You could do this, but it will make your code much slower.  Instead, `SkyCoord` supports *arrays* of coordinate values - you just pass in array-like inputs (array `Quantity`s, lists of strings, `Table` columns, etc.), and `SkyCoord` will happily do all of its operations element-wise."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "coo_sdss = SkyCoord(sdss['ra']*u.deg, sdss['dec']*u.deg)\n",
    "coo_twomass = SkyCoord(twomass['ra'], twomass['dec'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note a subtle difference here: you had to give units for SDSS but *not* for 2MASS.  This is because the 2MASS table has units associated with the columns, while the SDSS table does not (so you have to put them in manually).\n",
    "\n",
    "Now we simply use the ``SkyCoord.match_to_catalog_sky`` method to match the two catalogs. Note that order matters: we're matching 2MASS to SDSS because there are many *more* entires in the SDSS, so it seems likely that most 2MASS objects are in SDSS (but not vice versa)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "idx_sdss, d2d_sdss, d3d_sdss = coo_twomass.match_to_catalog_sky(coo_sdss)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "``idx`` are the indecies into ``coo_sdss`` that get the closest matches, while ``d2d`` and ``d3d`` are the on-sky and real-space distances between the matches. In our case ``d3d`` can be ignored because we didn't give a line-of-sight distance, so its value is not particularly useful.   But ``d2d`` provides a good diagnosis of whether we actually have real matches:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Gzww6M8lhSS4cjs11SY5fxvH6pSSfGtpfneSJ0/mbk5ZhNYb88OVrWi/gt4F3zps/hNE3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\nkgElSWrJgJIktWRASZJaMqAkSS39P/72EP62gPabAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x115f205c0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(d2d_sdss.arcsec, histtype='step', range=(0,2))\n",
    "plt.xlabel('separation [arcsec]')\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ok, they're all within an arcsecond that's promising.  But are we sure it's not just that *anything* has matches within an arcescond?  Lets check by comparing to a set of *random* points.\n",
    "\n",
    "We first create a set of uniformly random points (with size matching `coo_twomass`) that cover the same range of RA/Decs that are in `coo_sdss`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<Angle [  9.8493984 ,  9.65669048, 10.12478312,  9.85938713,  9.83017942,\n",
       "           9.78054797, 10.14040149, 10.16292212,  9.67810445, 10.13893976,\n",
       "           9.8322437 , 10.16051017,  9.53123199, 10.15969804, 10.07968765,\n",
       "          10.0965924 ,  9.98826816,  9.75845484, 10.09495031,  9.86533625,\n",
       "           9.81065051,  9.74167212, 10.17485253] deg>,\n",
       " <Angle [ 1.20195718, 0.69264857, 1.0923804 , 0.80993355, 0.87852961,\n",
       "          0.62830677, 0.65853346, 0.82618337, 0.68079827, 0.63197826,\n",
       "          0.79075179, 1.16755721, 0.54859745, 1.20517246, 1.10735837,\n",
       "          1.05405108, 1.07893763, 1.08187781, 0.90754804, 1.17804732,\n",
       "          0.80903263, 1.14221721, 0.79837397] deg>)"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ras_sim = np.random.rand(len(coo_twomass))*coo_sdss.ra.ptp() + coo_sdss.ra.min()\n",
    "decs_sim = np.random.rand(len(coo_twomass))*coo_sdss.dec.ptp() + coo_sdss.dec.min()\n",
    "ras_sim, decs_sim"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we create a `SkyCoord` from these points and match it to `coo_sdss` just like we did above for 2MASS.\n",
    "\n",
    "Note that we do not need to explicitly specify units for `ras_sim` and `decs_sim`, because they already are unitful `Angle` objects because they were created from `coo_sdss.ra`/`coo_sdss.dec`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "coo_simulated = SkyCoord(ras_sim, decs_sim)  \n",
    "idx_sim, d2d_sim, d3d_sim = coo_simulated.match_to_catalog_sky(coo_sdss)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now lets plot up the histogram of separations from our simulated catalog so we can compare to the above results from the *real* catalog."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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+FcBpAOcANKrqfyKCx8RPR2Ng65+5diso8iMi/QC8A+BxVf3M/zb1fj4gIj4j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\n0v8H5Io1njTppywAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x116866be0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(d2d_sim.arcsec, bins='auto', histtype='step', label='Simulated', linestyle='dashed')\n",
    "plt.hist(d2d_sdss.arcsec, bins='auto', histtype='step', label='2MASS')\n",
    "plt.xlabel('separation [arcsec]')\n",
    "plt.legend(loc=0)\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Alright, great - looks like randomly placed sources should be more like an arc*minute* away, so we can probably trust that our earlier matches which were within an arc*second* are valid.  So with that in mind, we can start computing things like colors that combine the SDSS and 2MASS photometry."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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hig9AKahgxVJIUABKQwUrFsMUHwAgSSQoAECSSFAAgCRxDQpA5dAiqRlIUAAqhRZJzcEU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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x116871a58>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rmag = sdss['r'][idx_sdss]\n",
    "grcolor = sdss['g'][idx_sdss] - rmag\n",
    "rKcolor = rmag - twomass['k_m_ext']\n",
    "\n",
    "plt.subplot(1, 2, 1)\n",
    "plt.scatter(rKcolor, rmag)\n",
    "plt.xlabel('r-K')\n",
    "plt.ylabel('r')\n",
    "plt.xlim(2.5, 4)\n",
    "plt.ylim(18, 12) #mags go backwards!\n",
    "\n",
    "plt.subplot(1, 2, 2)\n",
    "plt.scatter(rKcolor, rmag)\n",
    "plt.xlabel('r-K')\n",
    "plt.ylabel('g-r')\n",
    "plt.xlim(2.5, 4)\n",
    "\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For more on what matching options are available, check out the [separation and matching section of the astropy documentation](http://astropy.readthedocs.org/en/latest/coordinates/matchsep.html).  Or for more on what you can do with `SkyCoord`, see [its API documentation](http://astropy.readthedocs.org/en/latest/api/astropy.coordinates.SkyCoord.html)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exercises"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Check that the ``d2d_sdss`` variable matches the on-sky separations you get from comaparing the matched ``coo_sdss`` entries to ``coo_twomass``.  \n",
    "\n",
    "Hint: You'll likely find the ``SkyCoord.separation()`` method useful here."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Compute the *physical* separation between two (or more) objects in the catalogs.  You'll need line-of-sight distances, so a reasonable guess might be the distance to HCG 7, which is about 55 Mpc. \n",
    "\n",
    "Hint: you'll want to create new `SkyCoord` objects, but with ``distance`` attributes.  There's also a `SkyCoord` method that should do the rest of the work, but you'll have to poke around to figure out what it is."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Transforming between coordinate systems and planning observations"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now lets say something excites you about one of the objects in this catalog, and you want to know if and when you might go about observing it.  `astropy.coordinates` provides tools to enable this, as well."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Introducting frame transformations"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To understand the code in this section, it may help to read over the [overview of the astropy coordinates scheme](http://astropy.readthedocs.org/en/latest/coordinates/index.html#overview-of-astropy-coordinates-concepts).  The key bit to understand is that all coordinates in astropy are in particular \"frames\", and we can transform between a specific `SkyCoord` object from one frame to another.  For example, we can transform our previously-defined center of HCG7 from ICRS to Galactic coordinates:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<SkyCoord (Galactic): (l, b) in deg\n",
       "    ( 116.54378751, -61.84415576)>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hcg7_center.galactic"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The above is actually a special \"quick-access\" form which internally does the same as what's in the cell below: uses the `transform_to()` method to convert from one frame to another."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<SkyCoord (Galactic): (l, b) in deg\n",
       "    ( 116.54378751, -61.84415576)>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from astropy.coordinates import Galactic\n",
    "hcg7_center.transform_to(Galactic())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that changing frames also changes some of the attributes of the object, but usually in a way that makes sense:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "tags": [
     "raises-exception"
    ]
   },
   "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-31-d7bc134707f6>\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[0m\n\u001b[0m",
      "\u001b[0;32m/Users/erik/miniconda3/lib/python3.5/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    518\u001b[0m         \u001b[0;31m# Fail\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    519\u001b[0m         raise AttributeError(\"'{0}' object has no attribute '{1}'\"\n\u001b[0;32m--> 520\u001b[0;31m                              .format(self.__class__.__name__, attr))\n\u001b[0m\u001b[1;32m    521\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    522\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[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": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$-61^\\circ50{}^\\prime38.9607{}^{\\prime\\prime}$"
      ],
      "text/plain": [
       "<Latitude -61.84415575923695 deg>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hcg7_center.galactic.b"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Using frame transformations to get to AltAz"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "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 coordinates, or \"AltAz\" coordinates.  We first need to specify both where and when we want to try to observe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from astropy.coordinates import EarthLocation\n",
    "from astropy.time import Time\n",
    "\n",
    "observing_location = EarthLocation(lat='31d57.5m', lon='-111d35.8m', height=2096*u.m)  # Kitt Peak, Arizona\n",
    "# If you're using astropy v1.1 or later, you can replace the above with this:\n",
    "#observing_location = EarthLocation.of_site('Kitt Peak')\n",
    "\n",
    "observing_time = Time('2010-12-21 1:00')  # 1am UTC=6pm AZ mountain time"
   ]
  },
  {
   "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": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AltAz Frame (obstime=2010-12-21 01:00:00.000, location=(-1994310.09211632, -5037908.606337594, 3357621.752122168) m, pressure=0.0 hPa, temperature=0.0 deg_C, relative_humidity=0, obswl=1.0 micron)>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from astropy.coordinates import AltAz\n",
    "\n",
    "aa = AltAz(location=observing_location, obstime=observing_time)\n",
    "aa"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we can just transform our ICRS `SkyCoord` to `AltAz` to get the location in the sky over Kitt Peak at the requested time."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<SkyCoord (AltAz: obstime=2010-12-21 01:00:00.000, location=(-1994310.09211632, -5037908.606337594, 3357621.752122168) m, pressure=0.0 hPa, temperature=0.0 deg_C, relative_humidity=0, obswl=1.0 micron): (az, alt) in deg\n",
       "    ( 149.14900938,  55.03905882)>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hcg7_center.transform_to(aa)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Alright, it's up at 6pm, but that's pretty early to be observing.  We could just try various times one at a time to see if the airmass is at a darker time, but we can do better: lets try to create an airmass plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ZlQK3AtkA7n4PcBlwrZlFgBrgCnd3IGJm1wMvApnA/cG9KRE5yD7aUc1vZy7n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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x116cdcd30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 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=observing_location, 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 6pm AZ time')\n",
    "plt.ylabel('Airmass [Sec(z)]')\n",
    "plt.ylim(0.9,3)\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Great!  Looks like it's at the lowest airmass in another hour or so (7pm).  But might 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.  Lets use it to check if we're in 18-degree twilight or not."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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MH56lKjAWuDKf4nQPUDZoYb2Yz59vjpm9EeS5x8yuCDIvPdQCDUbN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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1199f8358>"
      ]
     },
     "metadata": {},
     "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()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Looks like it's just below 18 degrees at 7, so you should be good to go!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exercises"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Try to actually compute to some arbitrary precision (rather than eye-balling on a plot) when 18 degree twilight or sunrise/sunset hits on that night."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Try converting the HCG7 coordinates to an equatorial frame at some other equinox a while in the past (like J2000).  Do you see the precession of the equinoxes?\n",
    "\n",
    "Hint: To see a diagram of the supported frames look [here](http://docs.astropy.org/en/stable/coordinates/#module-astropy.coordinates).  One of those will do what you need if you give it the right frame attributes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Wrap-up"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For lots more documentation on the many other features of `astropy.coordinates`, check out [its section of the documentation](http://astropy.readthedocs.org/en/latest/coordinates/index.html).\n",
    "\n",
    "You might also be interested in [the astroplan affiliated package](http://astroplan.readthedocs.org/), which uses the `astropy.coordinates` to do more advanced versions of the tasks in the last section of this tutorial."
   ]
  }
 ],
 "metadata": {
  "astropy-tutorials": {
   "author": "Erik Tollerud <erik.tollerud@gmail.com>",
   "date": "July 2015",
   "description": "Demonstrates use of astropy.coordinates for common tasks. Includes matching catalogs against each other, basic observing planning tasks, and basic usage of coordinates.",
   "link_name": "Using astropy.coordinates to Match Catalogs and Plan Observations",
   "name": "",
   "published": true
  },
  "kernelspec": {
   "display_name": "Python [default]",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}