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    "# Week 14 - Astropy\n",
    "\n",
    "## Today's Agenda\n",
    "\n",
    "- Useful functions of [Astropy](http://www.astropy.org/)\n",
    "- Units\n",
    "- Time\n",
    "- Coordinates\n",
    "- FITS files\n",
    "- Analytic functions\n",
    "- AstroPy Tables and different formats"
   ]
  },
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    "[Astropy](http://www.astropy.org/) is a package that is meant to provide a lot of basic functionality for astronomy work in Python\n",
    "\n",
    "This can be roughly broken up into two areas. One is astronomical calculations:  \n",
    "* unit and physical quantity conversions\n",
    "* physical constants specific to astronomy\n",
    "* celestial coordinate and time transformations\n",
    "\n",
    "The other is file type and structures:\n",
    "* FITS files, implementing the former standalone PyFITS interface\n",
    "* Virtual Observatory (VO) tables\n",
    "* common ASCII table formats, e.g. for online catalogues or data supplements of scientific publications\n",
    "* Hierarchical Data Format (HDF5) files\n",
    "\n",
    "`AstroPy` normallly comes with the Anaconda installation. But in case you happen to not have it installed it on your computer, you can simply do a \n",
    "```sh\n",
    "    pip install --no-deps astropy\n",
    "```\n",
    "\n",
    "You can always update it via \n",
    "```sh\n",
    "    conda update astropy\n",
    "```\n",
    "This is just a __glimpse__ of all the features that `AstroPy` has:\n",
    "\n",
    "<img src=\"./images/astropy_sections.png\" alt=\"Astropy Features\" width=\"600\">\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "For purposes of today, we'll focus just on what astropy can do for units, time, coordinates, image manipulation, and more."
   ]
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    "# Importing Modules\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "sns.set_context(\"notebook\")"
   ]
  },
  {
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   "source": [
    "import astropy\n",
    "from astropy import units as u\n",
    "from astropy.coordinates import SkyCoord\n",
    "from astropy import constants as const"
   ]
  },
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   "source": [
    "## Units\n",
    "\n",
    "Astropy.units introduces units and allows for unit conversions. It doesn't, however, correctly handle spherical coordinates, but the astropy.coordinates package will address this later.\n",
    "\n",
    "These units can be used to create objects that are made up of both a value and a unit, and basic math can be easily carried out with these. We can add the .unit and .value properties to get the units and numerical values, respectively."
   ]
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7.0 m / s\n",
      "m / s\n"
     ]
    }
   ],
   "source": [
    "d=42*u.meter\n",
    "t=6*u.second\n",
    "v=d/t\n",
    "print v\n",
    "print v.unit"
   ]
  },
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   "source": [
    "Astropy includes a large number of units, and this can include imperial units as well if desired by importing and enabling imperial units. The .find_equivalent_units() function will also return all the other units that are already defined in astropy. Below we do a quick list of the units that are defined for time and length units"
   ]
  },
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     "text": [
      "  Primary name | Unit definition | Aliases \n",
      "[\n",
      "  a            | 3.15576e+07 s   | annum    ,\n",
      "  d            | 86400 s         | day      ,\n",
      "  fortnight    | 1.2096e+06 s    |          ,\n",
      "  h            | 3600 s          | hour, hr ,\n",
      "  min          | 60 s            | minute   ,\n",
      "  s            | irreducible     | second   ,\n",
      "  sday         | 86164.1 s       |          ,\n",
      "  wk           | 604800 s        | week     ,\n",
      "  yr           | 3.15576e+07 s   | year     ,\n",
      "]\n",
      "  Primary name | Unit definition | Aliases                         \n",
      "[\n",
      "  AU           | 1.49598e+11 m   | au, astronomical_unit            ,\n",
      "  Angstrom     | 1e-10 m         | AA, angstrom                     ,\n",
      "  cm           | 0.01 m          | centimeter                       ,\n",
      "  earthRad     | 6.37814e+06 m   | R_earth, Rearth                  ,\n",
      "  ft           | 0.3048 m        | foot                             ,\n",
      "  fur          | 201.168 m       | furlong                          ,\n",
      "  inch         | 0.0254 m        |                                  ,\n",
      "  jupiterRad   | 7.1492e+07 m    | R_jup, Rjup, R_jupiter, Rjupiter ,\n",
      "  lyr          | 9.46073e+15 m   | lightyear                        ,\n",
      "  m            | irreducible     | meter                            ,\n",
      "  mi           | 1609.34 m       | mile                             ,\n",
      "  micron       | 1e-06 m         |                                  ,\n",
      "  mil          | 2.54e-05 m      | thou                             ,\n",
      "  nmi          | 1852 m          | nauticalmile, NM                 ,\n",
      "  pc           | 3.08568e+16 m   | parsec                           ,\n",
      "  solRad       | 6.95508e+08 m   | R_sun, Rsun                      ,\n",
      "  yd           | 0.9144 m        | yard                             ,\n",
      "]\n"
     ]
    }
   ],
   "source": [
    "from astropy.units import imperial\n",
    "imperial.enable()\n",
    "print( u.s.find_equivalent_units() )\n",
    "print( u.m.find_equivalent_units() )"
   ]
  },
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   "source": [
    "The package also provides constants, with the units included. The full list of units can be found [here](http://docs.astropy.org/en/stable/constants/). We can take a quick look at c and G below, and see that these are objects which have value, uncertainty, and units."
   ]
  },
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     "text": [
      "  Name   = Speed of light in vacuum\n",
      "  Value  = 299792458.0\n",
      "  Uncertainty  = 0.0\n",
      "  Unit  = m / s\n",
      "  Reference = CODATA 2010\n",
      "  Name   = Gravitational constant\n",
      "  Value  = 6.67384e-11\n",
      "  Uncertainty  = 8e-15\n",
      "  Unit  = m3 / (kg s2)\n",
      "  Reference = CODATA 2010\n"
     ]
    }
   ],
   "source": [
    "print const.c\n",
    "print const.G"
   ]
  },
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   "source": [
    "Astropy has an aditional function that will allow for unit conversions. So we can, for example, create an object that is the distance to Mars, and then convert that to kilometers or miles. A brief note is that if you try to convert a pure unit (like the 4th line below) into another unit, you'll get a unitless value representing the conversion between the two.\n",
    "\n",
    "This can also be used to convert constants into other units, so we can convert the speed of light to the somewhat useful pc/yr or the entirely unuseful furlong/fortnight"
   ]
  },
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     "text": [
      "224396806.05 km\n",
      "139433710.91 mi\n",
      "149597870.7\n",
      "0.306601393788 pc / yr\n",
      "1.80261749979e+12 fur / fortnight\n"
     ]
    }
   ],
   "source": [
    "Mars=1.5*u.AU\n",
    "print Mars.to('kilometer')\n",
    "print Mars.to('mile')\n",
    "print u.AU.to('kilometer')\n",
    "print const.c.to('pc/yr')\n",
    "print const.c.to('fur/fortnight')"
   ]
  },
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   "source": [
    "To use this more practically, we can calculate the time it will take for light to reach the earth just by dividing 1 AU by the speed of light, as done below. Since AU is a unit, and c is in m/s, we end up with an answer that is (AU\\*m/s). By using .decompose() we can simplify that expression, which in this case will end up with an answer that is just in seconds. Finally, we can then convert that answer to minutes to get the answer of about 8 1/3 minutes that is commonly used. None of this required our doing the conversions where we might've slipped up."
   ]
  },
  {
   "cell_type": "code",
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3.33564095198e-09 AU s / m\n",
      "499.004783836 s\n",
      "8.31674639727 min\n"
     ]
    }
   ],
   "source": [
    "time=1*u.AU/const.c\n",
    "print(time)\n",
    "\n",
    "time_s=time.decompose()\n",
    "print(time_s)\n",
    "\n",
    "time_min=time_s.to(u.minute)\n",
    "print(time_min)"
   ]
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   "source": [
    "## Time\n",
    "\n",
    "Astropy handles time in a similar way to units, with creating Time objects. These objects have two main properties.  \n",
    "The format is simply how the time is displayed. This is the difference between, for example, Julian Date, Modified Julian Date, and ISO time (YYYY-MM-DD HH:MM:SS). The second is the scale, and is the difference between terrestrial time vs time at the barycenter of the solar system.\n",
    "\n",
    "We can start off by changing a time from one format to many others. We can also subtract times and we will get a timedelta unit."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "57867.346424\n",
      "2017-04-24 08:18:51.034\n",
      "2017.31101006\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<TimeDelta object: scale='tai' format='jd' value=1000.0>"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from astropy.time import Time\n",
    "t=Time(57867.346424, format='mjd', scale='utc')\n",
    "t1=Time(58867.346424, format='mjd', scale='utc')\n",
    "print t.mjd\n",
    "print t.iso\n",
    "print t.jyear\n",
    "t1-t"
   ]
  },
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   "source": [
    "## Coordinates\n",
    "\n",
    "Coordinates again work by using an object time defined for this purpose. We can establish a point in the ICRS frame (this is approximately the equatorial coordinate) by defining the ra and dec. Note that here we are using u.degree in specifying the coordinates.\n",
    "\n",
    "We can then print out the RA and dec, as well as change the units displayed. In the last line, we can also convert from ICRS equatorial coordinates to galactic coordinates."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<SkyCoord (ICRS): (ra, dec) in deg\n",
      "    ( 10.68458,  41.26917)>\n",
      "10d41m04.488s\n",
      "41d16m09.012s\n",
      "0.712305333333\n",
      "hms_tuple(h=0.0, m=42.0, s=44.299200000000525)\n",
      "<SkyCoord (Galactic): (l, b) in deg\n",
      "    ( 121.17424181, -21.57288557)>\n"
     ]
    }
   ],
   "source": [
    "c = SkyCoord(ra=10.68458*u.degree, dec=41.26917*u.degree, frame='icrs')\n",
    "print c\n",
    "print c.ra\n",
    "print c.dec\n",
    "print c.ra.hour\n",
    "print c.ra.hms\n",
    "print c.galactic"
   ]
  },
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   "source": [
    "## Slightly practical application of this\n",
    "\n",
    "Using some of these astropy functions, we can do some fancier applications. Starting off, we import a listing of stars with RA and dec from the attached table, and store them in the coordinate formats that are used by astropy. We then use matplotlib to plot this, and are able to easily convert them into radians thanks to astropy. This plot is accurate, but it lacks reference for where these points are."
   ]
  },
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    {
     "name": "stdout",
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     "text": [
      "['rowid' 'pl_hostname' 'pl_letter' 'pl_discmethod' 'pl_pnum' 'ra_str' 'ra'\n",
      " 'dec_str' 'dec' 'st_rah']\n"
     ]
    },
    {
     "data": {
      "image/png": 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atx0P13XRaAwWSes2hme3T+Dat58AhkFiAhggkbt8XkSjYcEwkivFmqWGJN0YH811TIzr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\nhIQwQRAEQRAEMZD8P9sHWE4+nheeAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x120b68150>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "hosts={}\n",
    "data=np.loadtxt('./data/planets.tab', dtype='str', delimiter='\\t')\n",
    "print data[0]\n",
    "hosts['ra_hours']=data[1:,9].astype(float)\n",
    "hosts['ra']=data[1:,6].astype(float)\n",
    "hosts['dec']=data[1:,8].astype(float)\n",
    "#print hosts['ra_hours']\n",
    "#print hosts['dec']\n",
    "\n",
    "import astropy.units as u\n",
    "import astropy.coordinates as coord\n",
    "from astropy.coordinates import SkyCoord\n",
    "ra = coord.Angle(hosts['ra']*u.degree)\n",
    "ra = ra.wrap_at(180*u.degree)\n",
    "dec = coord.Angle(hosts['dec']*u.degree)\n",
    "\n",
    "fig = plt.figure(figsize=(12,8))\n",
    "ax = fig.add_subplot(111, projection=\"mollweide\")\n",
    "plt.title('Map of Exoplanets')\n",
    "ax.scatter(ra.radian, dec.radian)\n",
    "ax.set_xticklabels(['14h','16h','18h','20h','22h','0h','2h','4h','6h','8h','10h'])\n",
    "ax.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "To fix this, we will add some references to this by adding a few more sets of data points. The first is relatively simple, we put in a line at the celestial equator. This just has to be a set of points that are all at declination of 0, and from -180 to +180 degrees in RA. These are a and b in the below.\n",
    "\n",
    "We also want to add the planes of the ecliptic and the galaxy on this. For both, we use coordinate objects and provide numpy arrays where one coordinate is at zero, and the other goes from 0 to 360. With astropy we can then easily convert from each coordinate system to ICRS. There's some for loops to modify the plotting, but the important thing is that this will give us a plot that has not just the locations of all the planets that we've plotted, but will also include the celestial equator, galactic plane, and ecliptic plane on it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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9YBs7BrbzXvhd3unfTCpdXMxM803n0LFzmTv2cBaMX8jC8YvocFSc2VQ3Tqct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\nwmA+KFjN5Ro4eHjdjqz32+t2EPA6DY+VDTpph4vr71rJtWc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DHgmH42Vxoh7fZDALbfKj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Fx5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\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x123049510>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "a=coord.Angle((np.arange(361)-180)*u.degree)\n",
    "b=coord.Angle(np.zeros(len(a))*u.degree)\n",
    "numpoints=360\n",
    "galaxy=SkyCoord(l=coord.Angle((np.arange(numpoints))*u.degree), b=coord.Angle(np.zeros(numpoints)*u.degree), frame='galactic')\n",
    "ecliptic=SkyCoord(lon=coord.Angle((np.arange(numpoints))*u.degree), lat=coord.Angle(np.zeros(numpoints)*u.degree), frame='geocentrictrueecliptic')\n",
    "ecl_eq=ecliptic.icrs\n",
    "gal_eq=galaxy.icrs\n",
    "#print gal_eq\n",
    "fixed_ra=[]\n",
    "for item in gal_eq.ra.radian:\n",
    "   if item < np.pi:\n",
    "      fixed_ra.append(item)\n",
    "   else:\n",
    "      fixed_ra.append(item-2*np.pi)\n",
    "i=np.argmin(fixed_ra)\n",
    "fixed_dec=[x for x in gal_eq.dec.radian]\n",
    "\n",
    "fixed_ra_eq=[]\n",
    "for item in ecl_eq.ra.radian:\n",
    "   if item < np.pi:\n",
    "      fixed_ra_eq.append(item)\n",
    "   else:\n",
    "      fixed_ra_eq.append(item-2*np.pi)\n",
    "j=np.argmin(fixed_ra_eq)\n",
    "fixed_dec_eq=[x for x in ecl_eq.dec.radian]\n",
    "\n",
    "fig = plt.figure(figsize=(12,8))\n",
    "ax = fig.add_subplot(111, projection=\"mollweide\")\n",
    "plt.title('Map of Exoplanets')\n",
    "ax.scatter(ra.radian, dec.radian)\n",
    "ax.plot(a.radian, b.radian, color='r', lw=2)\n",
    "#ax.scatter(gal_eq.ra.radian, gal_eq.dec.radian, color='g')\n",
    "ax.plot(fixed_ra[i:]+fixed_ra[:i], fixed_dec[i:]+fixed_dec[:i], color='g', lw=2)\n",
    "ax.plot(fixed_ra_eq[j:]+fixed_ra_eq[:j], fixed_dec_eq[j:]+fixed_dec_eq[:j], color='m', lw=2)\n",
    "ax.set_xticklabels(['14h','16h','18h','20h','22h','0h','2h','4h','6h','8h','10h'])\n",
    "ax.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "source": [
    "# Reading in FITS files\n",
    "\n",
    "One of the useful things with `Astropy` is that you can use it for reading in FITS files, and extracting info such as bands, exposure times, intrument information, etc.\n",
    "\n",
    "In this example, we will read in a FITS image file, and extract its information"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--2017-04-24 09:54:34--  http://star.herts.ac.uk/~gb/python/656nmos.fits\n",
      "Resolving star.herts.ac.uk... 147.197.221.254\n",
      "Connecting to star.herts.ac.uk|147.197.221.254|:80... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 10298880 (9.8M) [image/fits]\n",
      "Saving to: `./data/hst_image.fits'\n",
      "\n",
      "100%[======================================>] 10,298,880  4.86M/s   in 2.0s    \n",
      "\n",
      "2017-04-24 09:54:36 (4.86 MB/s) - `./data/hst_image.fits' saved [10298880/10298880]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# We will use  `wget` to download the necessary file to the `data` folder.\n",
    "!wget 'http://star.herts.ac.uk/~gb/python/656nmos.fits' -O ./data/hst_image.fits"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "Now we can extract some of the information stored in the FITS file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "from astropy.io import fits\n",
    "filename = './data/hst_image.fits'\n",
    "hdulist = fits.open(filename)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "The returned object, hdulist, (an instance of the [HDUList](http://docs.astropy.org/en/stable/io/fits/api/hdulists.html#hdulist) class) behaves like a Python list, and each element maps to a Header-Data Unit (HDU) in the FITS file. You can view more information about the FITS file with:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Filename: ./data/hst_image.fits\n",
      "No.    Name         Type      Cards   Dimensions   Format\n",
      "  0  PRIMARY     PrimaryHDU     290   (1600, 1600)   float32   \n",
      "  1  656nmos_cvt.tab  TableHDU       353   1R x 49C   [D25.17, D25.17, E15.7, E15.7, E15.7, E15.7, E15.7, E15.7, E15.7, E15.7, A1, E15.7, I12, I12, D25.17, D25.17, A8, A8, I12, E15.7, E15.7, E15.7, E15.7, E15.7, E15.7, I12, I12, I12, I12, I12, I12, I12, I12, A48, E15.7, E15.7, E15.7, E15.7, E15.7, E15.7, E15.7, E15.7, E15.7, E15.7, E15.7, E15.7, E15.7, E15.7, E15.7]   \n"
     ]
    }
   ],
   "source": [
    "hdulist.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "As we can see, this file contains two HDUs. The first contains the image, the second a data table. To access the primary HDU, which contains the main data, you can then do:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "hdu = hdulist[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "To read the header of the FITS file, you can read __`hdulist`__. The following shows the different keys for the header"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '',\n",
       "       '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '',\n",
       "       '', '', '', '', '', '', '', 'ALLG-MAX', 'ALLG-MIN', 'ASTR_I',\n",
       "       'ATODCORR', 'ATODFILE', 'ATODGAIN', 'ATODSAT', 'BACKGRND',\n",
       "       'BADPIXEL', 'BIASCORR', 'BIASDFIL', 'BIASEVEN', 'BIASFILE',\n",
       "       'BIASODD', 'BITPIX', 'BLEVCORR', 'BLEVDFIL', 'BLEVFILE', 'BSCALE',\n",
       "       'BZERO', 'CALIBDEF', 'CD1_1', 'CD1_2', 'CD2_1', 'CD2_2', 'CDBSFILE',\n",
       "       'COMPTAB', 'CRPIX1', 'CRPIX2', 'CRVAL1', 'CRVAL2', 'CTYPE1',\n",
       "       'CTYPE2', 'DADSCLAS', 'DADSDATE', 'DADSFILE', 'DARKCORR',\n",
       "       'DARKDFIL', 'DARKFILE', 'DARKTIME', 'DATALOST', 'DATAMAX',\n",
       "       'DATAMEAN', 'DATAMIN', 'DATE', 'DATE-OBS', 'DEC_SUN', 'DEC_TARG',\n",
       "       'DETECTOR', 'DEZERO', 'DOHISTOS', 'DOPHOTOM', 'DOSATMAP',\n",
       "       'EPLONGPM', 'EQNX_SUN', 'EQRADTRG', 'EQUINOX', 'ERRCNT', 'EXPEND',\n",
       "       'EXPFLAG', 'EXPSTART', 'EXPTIME', 'EXTEND', 'FGSLOCK', 'FILENAME',\n",
       "       'FILETYPE', 'FILLCNT', 'FILTER1', 'FILTER2', 'FILTNAM1', 'FILTNAM2',\n",
       "       'FILTROT', 'FITSDATE', 'FLATCORR', 'FLATDFIL', 'FLATFILE',\n",
       "       'FLATNTRG', 'FPKTTIME', 'FR_GAL1', 'FR_GAL2', 'FR_GAL3', 'FR_GAL4',\n",
       "       'FR_GALS', 'FR_LOWF', 'FR_LOWF1', 'FR_LOWF2', 'FR_LOWF3',\n",
       "       'FR_LOWF4', 'FR_STAR1', 'FR_STAR2', 'FR_STAR3', 'FR_STAR4',\n",
       "       'FR_STARS', 'FTOTAL', 'FTOTAL1', 'FTOTAL2', 'FTOTAL3', 'FTOTAL4',\n",
       "       'GOODMAX', 'GOODMIN', 'GPIXELS', 'GRAPHTAB', 'HISTORY', 'HISTORY',\n",
       "       'HISTORY', 'HISTORY', 'HISTORY', 'HISTORY', 'HISTORY', 'HISTORY',\n",
       "       'HISTORY', 'HISTORY', 'HISTORY', 'HISTORY', 'HISTORY', 'HISTORY',\n",
       "       'HISTORY', 'HISTORY', 'HISTORY', 'HISTORY', 'HISTORY', 'HISTORY',\n",
       "       'HISTORY', 'HISTORY', 'HISTORY', 'HISTORY', 'HISTORY', 'HISTORY',\n",
       "       'HISTORY', 'HISTORY', 'HISTORY', 'HISTORY', 'HISTORY', 'HISTORY',\n",
       "       'HISTORY', 'HISTORY', 'HISTORY', 'HISTORY', 'HISTORY', 'HISTORY',\n",
       "       'HISTORY', 'HISTORY', 'HISTORY', 'HISTORY', 'HISTORY', 'HISTORY',\n",
       "       'HISTORY', 'HISTORY', 'HISTORY', 'HISTORY', 'HISTWIDE', 'IMAGETYP',\n",
       "       'IMAG_I', 'INSTRUME', 'IRAF_I', 'KSPOTS', 'LINENUM', 'LONGPMER',\n",
       "       'LPKTTIME', 'LRFWAVE', 'MASKCORR', 'MASKFILE', 'MEANC10',\n",
       "       'MEANC100', 'MEANC200', 'MEANC25', 'MEANC300', 'MEANC50', 'MEDIAN',\n",
       "       'MEDSHADO', 'MIR_REVR', 'MODE', 'MOONANGL', 'MTFLAG', 'NAXIS',\n",
       "       'NAXIS1', 'NAXIS2', 'NCOMBINE', 'NPDECTRG', 'NPRATRG', 'NSHUTA17',\n",
       "       'OCRVL1', 'OCRVL2', 'ODATTYPE', 'OPSIZE', 'ORIENTAT', 'ORIGIN',\n",
       "       'OUTDTYPE', 'OVERLAP', 'PA_V3', 'PEP_EXPO', 'PHOTBW', 'PHOTFLAM',\n",
       "       'PHOTMODE', 'PHOTPLAM', 'PHOTTAB', 'PHOTZPT', 'PKTFMT', 'PODPSFF',\n",
       "       'PROPOSID', 'PSTPTIME', 'PSTRTIME', 'PYS_HEXP', 'PYS_ITER',\n",
       "       'PYS_VERS', 'RA_SUN', 'RA_TARG', 'READTIME', 'ROOTNAME', 'ROTRTTRG',\n",
       "       'RSDPFILL', 'SATURATE', 'SDASMGNU', 'SEQLINE', 'SEQNAME', 'SERIALS',\n",
       "       'SEXC_I', 'SHADCORR', 'SHADFILE', 'SHUTTER', 'SIMPLE', 'SKEWNESS',\n",
       "       'SKYSUB1', 'SKYSUB2', 'SKYSUB3', 'SKYSUB4', 'SOFTERRS', 'STAC_I',\n",
       "       'STATICD', 'STDCFFF', 'STDCFFP', 'SUNANGLE', 'SUN_ALT', 'SURFALTD',\n",
       "       'SURFLATD', 'SURFLONG', 'TARGNAME', 'TIME-OBS', 'UBAY3TMP',\n",
       "       'UCH1CJTM', 'UCH2CJTM', 'UCH3CJTM', 'UCH4CJTM', 'UEXPODUR',\n",
       "       'UEXPOTIM', 'USCALE', 'UZERO', 'XSHIFT', 'YSHIFT'], \n",
       "      dtype='|S8')"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sort(hdulist[0].header.keys())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "As we can see, this file contains two HDUs. The first contains the image, the second a data table.\n",
    "\n",
    "Let's look at the image of the FITS file.\n",
    "The hdu object then has two important attributes: data, which behaves like a Numpy array, can be used to access the data, and header, which behaves like a dictionary, can be used to access the header information. First, we can take a look at the data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1600, 1600)"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hdu.data.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "This tells us that it is a 1600-by-1600 pixel image. We can now take a peak at the header. To access the primary HDU, which contains the main data, you can then do:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SIMPLE  =                    T / FITS STANDARD                                  \n",
       "BITPIX  =                  -32 / FITS BITS/PIXEL                                \n",
       "NAXIS   =                    2 / NUMBER OF AXES                                 \n",
       "NAXIS1  =                 1600 /                                                \n",
       "NAXIS2  =                 1600 /                                                \n",
       "EXTEND  =                    T / There maybe standard extensions                \n",
       "BSCALE  =                1.0E0 / REAL = TAPE*BSCALE + BZERO                     \n",
       "BZERO   =                0.0E0 /                                                \n",
       "OPSIZE  =                 2112 / PSIZE of original image                        \n",
       "ORIGIN  = 'STScI-STSDAS'       / Fitsio version 21-Feb-1996                     \n",
       "FITSDATE= '2005-07-01'         / Date FITS file was created                     \n",
       "FILENAME= '656nmos_cvt.hhh'    / Original filename                              \n",
       "ALLG-MAX=           0.000000E0 / Data max in all groups                         \n",
       "ALLG-MIN=           0.000000E0 / Data min in all groups                         \n",
       "ODATTYPE= 'FLOATING'           / Original datatype: Single precision real       \n",
       "SDASMGNU=                    1 / Number of groups in original image             \n",
       "CRVAL1  =      274.71149247724                                                  \n",
       "CRVAL2  =     -13.816384007184                                                  \n",
       "CRPIX1  =                386.5                                                  \n",
       "CRPIX2  =                 396.                                                  \n",
       "CD1_1   =          1.878013E-5                                                  \n",
       "CD1_2   =         -2.031193E-5                                                  \n",
       "CD2_1   =         -2.029358E-5                                                  \n",
       "CD2_2   =         -1.879711E-5                                                  \n",
       "DATAMIN =           0.000000E0 / DATA MIN                                       \n",
       "DATAMAX =           0.000000E0 / DATA MAX                                       \n",
       "MIR_REVR=                    T                                                  \n",
       "ORIENTAT=            -131.9115                                                  \n",
       "FILLCNT =                    0                                                  \n",
       "ERRCNT  =                    0                                                  \n",
       "FPKTTIME=     49808.7324543649                                                  \n",
       "LPKTTIME=      49808.732622189                                                  \n",
       "CTYPE1  = 'RA---TAN'                                                            \n",
       "CTYPE2  = 'DEC--TAN'                                                            \n",
       "DETECTOR=                    4                                                  \n",
       "DEZERO  =             311.3041                                                  \n",
       "BIASEVEN=             311.3347                                                  \n",
       "BIASODD =             311.2736                                                  \n",
       "GOODMIN =             20.02589                                                  \n",
       "GOODMAX =             5584.467                                                  \n",
       "DATAMEAN=              89.2569                                                  \n",
       "GPIXELS =               559905                                                  \n",
       "SOFTERRS=                    0                                                  \n",
       "CALIBDEF=                80081                                                  \n",
       "STATICD =                    0                                                  \n",
       "ATODSAT =                   15                                                  \n",
       "DATALOST=                    0                                                  \n",
       "BADPIXEL=                    0                                                  \n",
       "OVERLAP =                    0                                                  \n",
       "PHOTMODE= 'WFPC2,4,A2D7,F656N,,CAL                         '                    \n",
       "PHOTFLAM=         1.528990E-16                                                  \n",
       "PHOTZPT =                -21.1                                                  \n",
       "PHOTPLAM=             6563.585                                                  \n",
       "PHOTBW  =             55.16187                                                  \n",
       "MEDIAN  =             93.54508                                                  \n",
       "MEDSHADO=             66.10242                                                  \n",
       "HISTWIDE=             62.41553                                                  \n",
       "SKEWNESS=           -0.1202522                                                  \n",
       "MEANC10 =             126.9503                                                  \n",
       "MEANC25 =             128.0693                                                  \n",
       "MEANC50 =             134.1882                                                  \n",
       "MEANC100=               132.23                                                  \n",
       "MEANC200=             114.3746                                                  \n",
       "MEANC300=             100.2731                                                  \n",
       "BACKGRND=             42.37756                                                  \n",
       "DADSFILE= 'U2LX0501T.D0F'      /                                                \n",
       "DADSCLAS= 'CAL     '           /                                                \n",
       "DADSDATE= '02-APR-1995 16:09:04' /                                              \n",
       "                                                                                \n",
       "                 / GROUP PARAMETERS: OSS                                        \n",
       "                                                                                \n",
       "                 / GROUP PARAMETERS: PODPS                                      \n",
       "                                                                                \n",
       "                 / GROUP PARAMETERS: DATA QUALITY FILE SUMMARY                  \n",
       "                                                                                \n",
       "                 / GROUP PARAMETERS: PHOTOMETRY                                 \n",
       "                                                                                \n",
       "                 / GROUP PARAMETERS: IMAGE STATISTICS                           \n",
       "                                                                                \n",
       "                 / WFPC-II DATA DESCRIPTOR KEYWORDS                             \n",
       "INSTRUME= 'WFPC2             ' / instrument in use                              \n",
       "ROOTNAME= 'U2LX0501T         ' / rootname of the observation set                \n",
       "FILETYPE= 'SCI               ' / shp, ext, edq, sdq, sci                        \n",
       "                                                                                \n",
       "                 / SCIENCE INSTRUMENT CONFIGURATION                             \n",
       "MODE    = 'FULL              ' / instr. mode: FULL (full res.), AREA (area int.)\n",
       "SERIALS = 'ON                ' / serial clocks: ON, OFF                         \n",
       "                                                                                \n",
       "                 / IMAGE TYPE CHARACTERISTICS                                   \n",
       "IMAGETYP= 'EXT               ' / DARK/BIAS/IFLAT/UFLAT/VFLAT/KSPOT/EXT/ECAL     \n",
       "CDBSFILE= 'NO                ' / GENERIC/BIAS/DARK/FLAT/MASK/NO                 \n",
       "PKTFMT  =                  104 / packet format code                             \n",
       "DATE    = '02/04/95          ' / date file written (dd/mm/yy)                   \n",
       "                                                                                \n",
       "                 / FILTER CONFIGURATION                                         \n",
       "FILTNAM1= 'F656N             ' / first filter name                              \n",
       "FILTNAM2= '                  ' / second filter name                             \n",
       "FILTER1 =                   31 / first filter number (0-48)                     \n",
       "FILTER2 =                    0 / second filter number (0-48)                    \n",
       "FILTROT =                  0.0 / partial filter rotation angle (degrees)        \n",
       "LRFWAVE =                  0.0 / linear ramp filter wavelength                  \n",
       "                                                                                \n",
       "                 / INSTRUMENT STATUS USED IN DATA PROCESSING                    \n",
       "UCH1CJTM=      -88.34862518311 / TEC cold junction #1 temperature (Celsius)     \n",
       "UCH2CJTM=      -88.80734252930 / TEC cold junction #2 temperature (Celsius)     \n",
       "UCH3CJTM=      -88.39449310303 / TEC cold junction #3 temperature (Celsius)     \n",
       "UCH4CJTM=      -88.90411376953 / TEC cold junction #4 temperature (Celsius)     \n",
       "UBAY3TMP=       13.61565399170 / bay 3 A1 temperature (deg C)                   \n",
       "KSPOTS  = 'OFF               ' / Status of Kelsall spot lamps: ON, OFF          \n",
       "SHUTTER = 'B                 ' / Shutter in place at the beginning of the exposu\n",
       "ATODGAIN=       7.000000000000 / Analog to Digital Gain (Electrons/DN)          \n",
       "                                                                                \n",
       "                 / RSDP CONTROL KEYWORDS                                        \n",
       "MASKCORR= 'COMPLETE'           / Do mask correction: PERFORM, OMIT, COMPLETE    \n",
       "ATODCORR= 'COMPLETE'           / Do A-to-D correction: PERFORM, OMIT, COMPLETE  \n",
       "BLEVCORR= 'COMPLETE'           / Do bias level correction: PERFORM, OMIT, COMPLE\n",
       "BIASCORR= 'COMPLETE'           / Do bias correction: PERFORM, OMIT, COMPLETE    \n",
       "DARKCORR= 'COMPLETE'           / Do dark correction: PERFORM, OMIT, COMPLETE    \n",
       "FLATCORR= 'COMPLETE'           / Do flat field correction: PERFORM, OMIT, COMPLE\n",
       "SHADCORR= 'COMPLETE'           / Do shaded shutter correction: PERFORM, OMIT, CO\n",
       "DOSATMAP= 'OMIT              ' / Output saturated pixel map: PERFORM, OMIT, COMP\n",
       "DOPHOTOM= 'COMPLETE'           / Fill photometry keywords: PERFORM, OMIT, COMPLE\n",
       "DOHISTOS= 'OMIT    '           / Make histograms: PERFORM, OMIT, COMPLETE       \n",
       "OUTDTYPE= 'REAL    '           / Output image datatype: REAL, LONG, SHORT       \n",
       "                                                                                \n",
       "                 / CALIBRATION REFERENCE FILES                                  \n",
       "MASKFILE= 'uref$f8213081u.r0h' / name of the input DQF of known bad pixels      \n",
       "ATODFILE= 'uref$dbu1405iu.r1h' / name of the A-to-D conversion file             \n",
       "BLEVFILE= 'ucal$u2lx0501t.x0h' / Engineering file with extended register data   \n",
       "BLEVDFIL= 'ucal$u2lx0501t.q1h' / Engineering file DQF                           \n",
       "BIASFILE= 'uref$fcb1503du.r2h' / name of the bias frame reference file          \n",
       "BIASDFIL= 'uref$fcb1503du.b2h' / name of the bias frame reference DQF           \n",
       "DARKFILE= 'uref$f461210tu.r3h' / name of the dark reference file                \n",
       "DARKDFIL= 'uref$f461210tu.b3h' / name of the dark reference DQF                 \n",
       "FLATFILE= 'uref$g6h0945cu.r4h' / name of the flat field reference file          \n",
       "FLATDFIL= 'uref$g6h0945cu.b4h' / name of the flat field reference DQF           \n",
       "SHADFILE= 'uref$e371355iu.r5h' / name of the reference file for shutter shading \n",
       "PHOTTAB = '                  ' / name of the photometry calibration table       \n",
       "GRAPHTAB= 'mtab$m1p1255om.tmg' / the HST graph table                            \n",
       "COMPTAB = 'mtab$m4i1217km.tmc' / the HST components table                       \n",
       "                                                                                \n",
       "                 / DEFAULT KEYWORDS SET BY STSCI                                \n",
       "SATURATE=                 4095 / Data value at which saturation occurs          \n",
       "USCALE  =                  1.0 / Scale factor for output image                  \n",
       "UZERO   =                  0.0 / Zero point for output image                    \n",
       "                                                                                \n",
       "                 / READOUT DURATION INFORMATION                                 \n",
       "READTIME=                  464 / Length of time for CCD readout in clock ticks  \n",
       "                                                                                \n",
       "                 / PLANETARY SCIENCE KEYWORDS                                   \n",
       "PA_V3   =        0.9299789E+02 / position angle of v3 axis of HST               \n",
       "RA_SUN  =  0.1065970464620E+02 / right ascension of the sun (deg)               \n",
       "DEC_SUN =  0.4585364087424E+01 / declination of the sun (deg)                   \n",
       "EQNX_SUN=               2000.0 / equinox of the sun                             \n",
       "MTFLAG  =                    F / moving target flag                             \n",
       "EQRADTRG=                  0.0 / equatorial radius of target                    \n",
       "FLATNTRG=                  0.0 / flattening of target                           \n",
       "NPDECTRG=                  0.0 / north pole declination of target               \n",
       "NPRATRG =                  0.0 / north pole right ascension of target           \n",
       "ROTRTTRG=                  0.0 / rotation rate of target                        \n",
       "LONGPMER=                  0.0 / longitude of prime meridian                    \n",
       "EPLONGPM=                  0.0 / epoch of longitude of prime meridian           \n",
       "SURFLATD=                  0.0 / surface feature latitude                       \n",
       "SURFLONG=                  0.0 / surface feature longitude                      \n",
       "SURFALTD=                  0.0 / surface feature altitude                       \n",
       "                                                                                \n",
       "                 / PODPS FILL VALUES                                            \n",
       "PODPSFF =                    0 / 0=(no podps fill), 1=(podps fill present)      \n",
       "STDCFFF =                    0 / 0=(no st dcf fill), 1=(st dcf fill present)    \n",
       "STDCFFP = '0000              ' / st dcf fill pattern (hex)                      \n",
       "RSDPFILL=                 -100 / bad data fill value for calibrated images      \n",
       "                                                                                \n",
       "                 / EXPOSURE TIME AND RELATED INFORMATION                        \n",
       "UEXPODUR=                 1100 / Commanded duration of exposure (seconds)       \n",
       "NSHUTA17=                    1 / Number of AP17 shutter B closes                \n",
       "DARKTIME=       1100.000000000 / Dark time (seconds)                            \n",
       "UEXPOTIM=                23408 / Major frame pulse time preceding exposure start\n",
       "PSTRTIME= '1995.091:17:32:39 ' / Predicted obs. start time  (yyyy:ddd:hh:mm:ss) \n",
       "PSTPTIME= '1995.091:17:52:39 ' / Predicted obs. stop  time  (yyyy:ddd:hh:mm:ss) \n",
       "                                                                                \n",
       "                 / EXPOSURE INFORMATION                                         \n",
       "SUNANGLE=       96.85704040527 / angle between sun and V1 axis (deg)            \n",
       "MOONANGL=       115.2464447021 / angle between moon and V1 axis (deg)           \n",
       "SUN_ALT =       36.93915557861 / altitude of the sun above Earth's limb (deg)   \n",
       "FGSLOCK = 'FINE              ' / commanded FGS lock (FINE,COARSE,GYROS,UNKNOWN) \n",
       "                                                                                \n",
       "DATE-OBS= ' 1/04/95          ' / UT date of start of observation (dd/mm/yy)     \n",
       "TIME-OBS= '17:15:17          ' / UT time of start of observation (hh:mm:ss)     \n",
       "EXPSTART=       49808.71894742 / exposure start time (Modified Julian Date)     \n",
       "EXPEND  =       49808.73167890 / exposure end time (Modified Julian Date)       \n",
       "EXPTIME =                1100. / exposure duration (seconds)--calculated        \n",
       "EXPFLAG = 'NORMAL            ' / Exposure interruption indicator                \n",
       "                                                                                \n",
       "                 / TARGET & PROPOSAL ID                                         \n",
       "TARGNAME= 'M16-A             ' / proposer's target name                         \n",
       "RA_TARG =  0.2747039166667E+03 / right ascension of the target (deg) (J2000)    \n",
       "DEC_TARG= -0.1383091666667E+02 / declination of the target (deg) (J2000)        \n",
       "                                                                                \n",
       "PROPOSID=                05773 / PEP proposal identifier                        \n",
       "PEP_EXPO= '4.2000017#001     ' / PEP exposure identifier including sequence     \n",
       "LINENUM = '4.010             ' / PEP proposal line number                       \n",
       "SEQLINE = '4.200             ' / PEP line number of defined sequence            \n",
       "SEQNAME = 'M16SEQ            ' / PEP define/use sequence name                   \n",
       "                                                                                \n",
       "HISTORY   MASKFILE=uref$f8213081u.r0h  MASKCORR=COMPLETED                       \n",
       "HISTORY   PEDIGREE=INFLIGHT 01/01/1994 - 15/05/1995                             \n",
       "HISTORY   DESCRIP=STATIC MASK - INCLUDES CHARGE TRANSFER TRAPS                  \n",
       "HISTORY   BIASFILE=uref$fcb1503du.r2h  BIASCORR=COMPLETED                       \n",
       "HISTORY   PEDIGREE=INFLIGHT 13/01/1995 - 11/04/1995                             \n",
       "HISTORY   DESCRIP=not signif. different from f1j16* but generated from new data \n",
       "HISTORY   DARKFILE=uref$f461210tu.r3h  DARKCORR=COMPLETED                       \n",
       "HISTORY   PEDIGREE=INFLIGHT 27/03/1995 - 04/04/1995                             \n",
       "HISTORY   DESCRIP=dark,full mode,serials on,gain=7,-88C                         \n",
       "HISTORY   FLATFILE=uref$g6h0945cu.r4h  FLATCORR=COMPLETED                       \n",
       "HISTORY   PEDIGREE=INFLIGHT 01/05/1994 - 01/10/1994                             \n",
       "HISTORY   DESCRIP=Improved Cyc4 flat, fixed errors at CCD edges - now < 0.5% RMS\n",
       "HISTORY   SHADFILE=uref$e371355iu.r5h  SHADCORR=COMPLETED                       \n",
       "HISTORY   PEDIGREE=GROUND                                                       \n",
       "HISTORY   DESCRIP=                                                              \n",
       "HISTORY   PC1: bias jump level ~0.155 DN.                                       \n",
       "HISTORY   The following throughput tables were used:                            \n",
       "HISTORY   crotacomp$hst_ota_007_syn.fits, crwfpc2comp$wfpc2_optics_006_syn.fits,\n",
       "HISTORY   crwfpc2comp$wfpc2_f656n_005_syn.fits,                                 \n",
       "HISTORY   crwfpc2comp$wfpc2_dqepc1_005_syn.fits,                                \n",
       "HISTORY   crwfpc2comp$wfpc2_a2d7pc1_004_syn.fits,                               \n",
       "HISTORY   crwfpc2comp$wfpc2_flatpc1_003_syn.fits                                \n",
       "HISTORY   WF2: bias jump level ~0.180 DN.                                       \n",
       "HISTORY   The following throughput tables were used:                            \n",
       "HISTORY   crotacomp$hst_ota_007_syn.fits, crwfpc2comp$wfpc2_optics_006_syn.fits,\n",
       "HISTORY   crwfpc2comp$wfpc2_f656n_005_syn.fits,                                 \n",
       "HISTORY   crwfpc2comp$wfpc2_dqewfc2_005_syn.fits,                               \n",
       "HISTORY   crwfpc2comp$wfpc2_a2d7wf2_004_syn.fits,                               \n",
       "HISTORY   crwfpc2comp$wfpc2_flatwf2_003_syn.fits                                \n",
       "HISTORY   WF3: bias jump level ~0.274 DN.                                       \n",
       "HISTORY   The following throughput tables were used:                            \n",
       "HISTORY   crotacomp$hst_ota_007_syn.fits, crwfpc2comp$wfpc2_optics_006_syn.fits,\n",
       "HISTORY   crwfpc2comp$wfpc2_f656n_005_syn.fits,                                 \n",
       "HISTORY   crwfpc2comp$wfpc2_dqewfc3_005_syn.fits,                               \n",
       "HISTORY   crwfpc2comp$wfpc2_a2d7wf3_004_syn.fits,                               \n",
       "HISTORY   crwfpc2comp$wfpc2_flatwf3_003_syn.fits                                \n",
       "HISTORY   WF4: bias jump level ~0.202 DN.                                       \n",
       "HISTORY   The following throughput tables were used:                            \n",
       "HISTORY   crotacomp$hst_ota_007_syn.fits, crwfpc2comp$wfpc2_optics_006_syn.fits,\n",
       "HISTORY   crwfpc2comp$wfpc2_f656n_005_syn.fits,                                 \n",
       "HISTORY   crwfpc2comp$wfpc2_dqewfc4_005_syn.fits,                               \n",
       "HISTORY   crwfpc2comp$wfpc2_a2d7wf4_004_syn.fits,                               \n",
       "HISTORY   crwfpc2comp$wfpc2_flatwf4_003_syn.fits                                \n",
       "HISTORY   Ran task WARMPIX, version 1.1 (Sep 28, 1999) at Mon 00:16:49          \n",
       "HISTORY   29-Jul-2002, rej_thresh=0.10000, fix_thresh=0.00300,                  \n",
       "HISTORY   var_thresh=0.00300,                                                   \n",
       "HISTORY   fix_dqval=1024, rej_val=INDEF                                         \n",
       "SKYSUB1 =                 13.7 / Sky value for chip 1                           \n",
       "PYS_VERS=                  1.7 / PyStack.py: Version                            \n",
       "IRAF_I  = 'IRAF V2.11 May 1997 release:2.11.3b'                                 \n",
       "STAC_I  = '$RCSfile: imstack_imshift_imcomb.cl,v $ $Revision: 1.1 $'            \n",
       "PYS_ITER=                    5 / PyStack.py: Number of iterations               \n",
       "PYS_HEXP=                    2 / PyStack.py: Value of exponent                  \n",
       "SKYSUB2 =                86.37 / Sky value for chip 2                           \n",
       "SKYSUB3 =                88.54 / Sky value for chip 3                           \n",
       "SKYSUB4 =                44.66 / Sky value for chip 4                           \n",
       "NCOMBINE=                    2 / Number of exposures for this association       \n",
       "ASTR_I  = '$RCSfile: image_type.cl,v $ $Revision: 1.1 $'                        \n",
       "XSHIFT  =         -2.136230E-4 / Y shift in degrees from USNO stars             \n",
       "YSHIFT  =         -2.765656E-5 / X shift in degrees from USNO stars             \n",
       "OCRVL1  =             274.7039 / Old CRVAL1 value before USNO correction        \n",
       "OCRVL2  =            -13.83092 / Old CRVAL2 value before USNO correction        \n",
       "FR_LOWF1=            0.9928686 / Fraction of flux in low frequency for chip 1   \n",
       "FR_STAR1=          5.451115E-4 / Fraction of flux in stars for chip 1           \n",
       "FR_GAL1 =          0.006586314 / Fraction of flux in stars for chip 1           \n",
       "FTOTAL1 =             3886.887 / Total flux in chip 1                           \n",
       "FR_LOWF2=            0.9486716 / Fraction of flux in low frequency for chip 2   \n",
       "FR_STAR2=          0.004499074 / Fraction of flux in stars for chip 2           \n",
       "FR_GAL2 =           0.04682927 / Fraction of flux in stars for chip 2           \n",
       "FTOTAL2 =             12345.12 / Total flux in chip 2                           \n",
       "FR_LOWF3=            0.9776544 / Fraction of flux in low frequency for chip 3   \n",
       "FR_STAR3=          6.581650E-4 / Fraction of flux in stars for chip 3           \n",
       "FR_GAL3 =           0.02168746 / Fraction of flux in stars for chip 3           \n",
       "FTOTAL3 =             16654.92 / Total flux in chip 3                           \n",
       "FR_LOWF4=            0.9892846 / Fraction of flux in low frequency for chip 4   \n",
       "FR_STAR4=          0.001161799 / Fraction of flux in stars for chip 4           \n",
       "FR_GAL4 =           0.00955356 / Fraction of flux in stars for chip 4           \n",
       "FTOTAL4 =             24094.24 / Total flux in chip 4                           \n",
       "FR_LOWF =            0.9773308 / Fraction of flux in low frequency for all chips\n",
       "FR_STARS=          0.001695556 / Fraction of flux in stars for all chips        \n",
       "FR_GALS =           0.02097363 / Fraction of flux in stars for all chips        \n",
       "FTOTAL  =             56981.16 / Total flux in all chips                        \n",
       "IMAG_I  = '$RCSfile$ $Revision$'                                                \n",
       "EQUINOX =                2000.                                                  \n",
       "SEXC_I  = '$RCSfile$ $Revision$'                                                \n",
       "HISTORY   Ran task WMOSAIC, version 2.1 (Jun 1995), at Fri 16:17:34 01-Jul-2005 "
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hdu.header"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "We can access individual header keywords using standard item notation:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'WFPC2'"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hdu.header['INSTRUME']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1100.0"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hdu.header['EXPTIME']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "We can plot the image using matplotlib:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/victor2/anaconda/lib/python2.7/site-packages/ipykernel/__main__.py:2: RuntimeWarning: divide by zero encountered in log10\n",
      "  from ipykernel import kernelapp as app\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x118a9ae10>"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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e+83mquyE62E5BWViCzFyv1gHuVSF1UKTwUykISxe4yY/Jio5lcZccJzLRvhv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\nOpDYn9OWxgM+t0lATo3lu2crEIDgcnh4GNPptDwq5i//5b8cu7u78R/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pSAcfLMoL2wnD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VwwL6yufdaVfZ3sk8HkaROcJ0kmH1bYBi3e3m3GwiZEM23cZ/bhaRS6wYIBhhkExKyfndfN5mUA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8w3F5eRnvvfdeARytVis+85nP1NgQwMXl5WVcXV3Fzc1NKTwG6MxmsxK5397elrqr+Xxe7uMN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ZndcBupu/Tj6OioPa1rADSdTgeJblXVP//zP9fFxUW714HUB9s6MaE+dBi9M1tOsb3js9mz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\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m3R7y4HACZvvi3rxCxgmm135xLcxTskhOWBxL8bFVd77k+vq6jo6O6i//8i/ry1/+crOx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\nlfYBBk787+SHe+K3zLyv1+u2BclkMmm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NwRX9XK1W7Z14i8WiLV4nQTFryrgMSp082H+k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\nwffRs4YAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x118d58dd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,10))\n",
    "plt.imshow(np.log10(hdu.data), origin='lower', cmap='gray', vmin=1.5, vmax=3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "You can also add new fields to the FITS file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "hdu.header['MODIFIED'] = '2014-12-01'  # adds a new keyword"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "and we can also change the data, for example subtracting a background value:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "hdu.data = hdu.data - 0.5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "This only changes the FITS file in memory. You can write to a file with:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "hdu.writeto('./data/hubble-image-background-subtracted.fits', overwrite=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "README.md                               astropy_data_latex.tex\r\n",
      "astropy_data.tb                         hst_image.fits\r\n",
      "astropy_data_2.tb                       hubble-image-background-subtracted.fits\r\n",
      "astropy_data_csv.csv                    planets.tab\r\n",
      "astropy_data_ecsv.ecsv                  sources.dat\r\n"
     ]
    }
   ],
   "source": [
    "!ls ./data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# Analytic Functions\n",
    "\n",
    "`Astropy` comes with some built-in analytic functions, e.g. the _`blackbody radiation`_ function.\n",
    "\n",
    "## Blackbody Radiation\n",
    "Blackbody flux is calculated with Planck law ([Rybicki & Lightman 1979](http://docs.astropy.org/en/stable/analytic_functions/index.html#ref-rybicki1979))\n",
    "\n",
    "$$B_{\\lambda}(T) = \\frac{2 h c^{2} / \\lambda^{5}}{exp(h c / \\lambda k T) - 1}$$\n",
    "$$B_{\\nu}(T) = \\frac{2 h \\nu^{3} / c^{2}}{exp(h \\nu / k T) - 1}$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "from astropy.analytic_functions import blackbody_lambda, blackbody_nu"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "def Planck_func(temp, lam_arr, opt='lam'):\n",
    "    \"\"\"\n",
    "    Computes the Blackbody radiation curve of a blackbody of a given temperature `temp`.\n",
    "    \n",
    "    Parameters\n",
    "    ----------\n",
    "    temp: float or array-like\n",
    "        temperature(s) of the blackbody\n",
    "    \n",
    "    lam_arr: float or array_like\n",
    "        aray of wavelenths to evaluate the Planck function.\n",
    "    \n",
    "    opt: str, optional (default = 'lam')\n",
    "        Option for returning either the flux of `lambda` (wavelength) or `nu` (frequency).\n",
    "        Options:\n",
    "            - `lam`: Return flux for `lambda' or wavelength\n",
    "            - `nu` : Returns flux for `nu` (frequency)\n",
    "    \"\"\"\n",
    "    wavelengths = lam_arr * u.AA\n",
    "    temperature = temp * u.K\n",
    "    with np.errstate(all='ignore'):\n",
    "        flux_lam = blackbody_lambda(wavelengths, temperature)\n",
    "        flux_nu  = blackbody_nu(wavelengths, temperature)\n",
    "    \n",
    "    if opt=='lam':\n",
    "        return flux_lam\n",
    "    if opt=='nu':\n",
    "        return flux_nu"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "Let's plot the Planck function for two bodies with temperatures $T_1 = 8000\\ K$ and $T_2 = 6000\\ K$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "lam_arr = np.arange(1e2, 2e4)\n",
    "nu_arr  = (const.c/(lam_arr * u.AA)).to(1./u.s).value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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LLBUlSiVMBjUqUc1jZNbSPMzO+DA360vI9YlIGYWFkcYN167WyaWXFoslqees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B8azycv3cFdG7LYuT4Tz010nzjafJqvvPZdduVv4882PTav14r4/Zx4z/swp6ex7mtfnnV+rU0D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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1218f2b50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(15,8))\n",
    "ax1  = fig.add_subplot(121, axisbg='white')\n",
    "ax2  = fig.add_subplot(122, axisbg='white')\n",
    "ax1.set_xlabel(r'$\\lambda$ (Ansgstrom)', fontsize=25)\n",
    "ax1.set_ylabel(r'$B_{\\lambda}(T)$', fontsize=25)\n",
    "ax2.set_xlabel(r'$\\nu$ (\\textrm{s}^{-1})', fontsize=25)\n",
    "ax2.set_ylabel(r'$B_{\\nu}(T)$', fontsize=25)\n",
    "ax2.set_xscale('log')\n",
    "\n",
    "temp_arr = [6e3, 8e3, 1e4, 1.2e4]\n",
    "for temp in temp_arr:\n",
    "    ax1.plot(lam_arr, Planck_func(temp, lam_arr=lam_arr, opt='lam'), label='T = {0} K'.format(int(temp)))\n",
    "    ax2.plot(nu_arr , Planck_func(temp, lam_arr=lam_arr, opt='nu' ), label='T = {0} K'.format(int(temp)))\n",
    "    ax1.legend(loc=1, prop={'size':20})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# AstroPy Tables\n",
    "\n",
    "## Read files\n",
    "You can use `Astropy` to __read__ tables from data files. We'll use it to read the `sources.dat` file, which contains columns and rows of data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "obsid redshift  X      Y     object\r\n",
      "3102  0.32      4167  4085   Q1250+568-A\r\n",
      "877   0.22      4378  3892   \"Source 82\"\r\n",
      "\r\n"
     ]
    }
   ],
   "source": [
    "!head ./data/sources.dat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "obsid redshift  X    Y      object  \n",
      "----- -------- ---- ---- -----------\n",
      " 3102     0.32 4167 4085 Q1250+568-A\n",
      "  877     0.22 4378 3892   Source 82\n"
     ]
    }
   ],
   "source": [
    "from astropy.io import ascii\n",
    "sources_tb = ascii.read('./data/sources.dat')\n",
    "\n",
    "print( sources_tb )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Write to files\n",
    "\n",
    "You can also write directoy to a file using the data in the `AstroPy` table.\n",
    "Let's create a new `AstroPy` Table:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      x             y      \n",
      "------------- -------------\n",
      "15.2414976634 87.3902978029\n",
      "14.2858102529 63.4778235534\n",
      "12.6837892045 95.1038332346\n",
      "15.7433361157 84.0554583013\n",
      "10.6276318955 96.0939150693\n",
      "13.6078233437 90.8772263701\n",
      "16.7426639018 53.5680565112\n",
      "18.5854346321 63.4464077849\n",
      "16.8978153196 53.8207361937\n",
      "11.3037331537 62.9365050838\n",
      "          ...           ...\n",
      " 18.942591823 76.8984462197\n",
      "14.3360864888 93.3963823352\n",
      "19.5899858716 54.7713213972\n",
      "14.8603557394 65.0842136962\n",
      "10.2954772658 86.2165081125\n",
      "11.9427749909  98.733046694\n",
      "10.8330331892 55.5301147739\n",
      "16.8250678957 69.3254817244\n",
      " 16.792578986 59.2414887155\n",
      "12.4648161361 70.4455159566\n",
      "10.8867007288  99.185886158\n",
      "Length = 1000 rows\n"
     ]
    }
   ],
   "source": [
    "from astropy.table import Table, Column, MaskedColumn\n",
    "x = np.random.uniform(low=10, high=20, size=(1000,))\n",
    "y = np.random.uniform(low=100, high=50, size=(x.size,))\n",
    "z = np.random.uniform(low=30, high=50, size=(x.size,))\n",
    "data = Table([x, y], names=['x', 'y'])\n",
    "print(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "ascii.write(data, './data/astropy_data.tb', overwrite=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "Let's see what's in the `astropy_data.tb` file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x y\r\n",
      "15.241497663441134 87.3902978028505\r\n",
      "14.285810252905431 63.47782355343405\r\n",
      "12.68378920454439 95.10383323455497\r\n",
      "15.743336115743206 84.05545830126047\r\n",
      "10.627631895531712 96.09391506928101\r\n",
      "13.607823343675943 90.87722637008545\r\n",
      "16.742663901777668 53.568056511155795\r\n",
      "18.585434632105862 63.44640778487338\r\n",
      "16.897815319630578 53.820736193723626\r\n"
     ]
    }
   ],
   "source": [
    "!head ./data/astropy_data.tb"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "You can also specify the _delimiter_ of the file. For example, we can separate it with a _comma_."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "ascii.write(data, './data/astropy_data_2.tb', delimiter=',', overwrite=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x,y\r\n",
      "15.241497663441134,87.3902978028505\r\n",
      "14.285810252905431,63.47782355343405\r\n",
      "12.68378920454439,95.10383323455497\r\n",
      "15.743336115743206,84.05545830126047\r\n",
      "10.627631895531712,96.09391506928101\r\n",
      "13.607823343675943,90.87722637008545\r\n",
      "16.742663901777668,53.568056511155795\r\n",
      "18.585434632105862,63.44640778487338\r\n",
      "16.897815319630578,53.820736193723626\r\n"
     ]
    }
   ],
   "source": [
    "!head ./data/astropy_data_2.tb"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## AstroPy Tables to other Formats\n",
    "\n",
    "The `AstroPy` tables can also be converted to multiple formats"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### to Pandas DataFrames\n",
    "\n",
    "A nice feature of `AstroPy` Tables is that you can export your data into different formats. \n",
    "For example, you can export it as a ```Pandas``` Dataframe. \n",
    "\n",
    "See here for more info on how to use pandas with Astropy: [http://docs.astropy.org/en/stable/table/pandas.html](http://docs.astropy.org/en/stable/table/pandas.html)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>15.241498</td>\n",
       "      <td>87.390298</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>14.285810</td>\n",
       "      <td>63.477824</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>12.683789</td>\n",
       "      <td>95.103833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>15.743336</td>\n",
       "      <td>84.055458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10.627632</td>\n",
       "      <td>96.093915</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           x          y\n",
       "0  15.241498  87.390298\n",
       "1  14.285810  63.477824\n",
       "2  12.683789  95.103833\n",
       "3  15.743336  84.055458\n",
       "4  10.627632  96.093915"
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = data.to_pandas()\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "And to compare, let's see the `AstroPy` Tables format"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "&lt;Table length=1000&gt;\n",
       "<table id=\"table4712314512\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>x</th><th>y</th></tr></thead>\n",
       "<thead><tr><th>float64</th><th>float64</th></tr></thead>\n",
       "<tr><td>15.2414976634</td><td>87.3902978029</td></tr>\n",
       "<tr><td>14.2858102529</td><td>63.4778235534</td></tr>\n",
       "<tr><td>12.6837892045</td><td>95.1038332346</td></tr>\n",
       "<tr><td>15.7433361157</td><td>84.0554583013</td></tr>\n",
       "<tr><td>10.6276318955</td><td>96.0939150693</td></tr>\n",
       "<tr><td>13.6078233437</td><td>90.8772263701</td></tr>\n",
       "<tr><td>16.7426639018</td><td>53.5680565112</td></tr>\n",
       "<tr><td>18.5854346321</td><td>63.4464077849</td></tr>\n",
       "<tr><td>16.8978153196</td><td>53.8207361937</td></tr>\n",
       "<tr><td>11.3037331537</td><td>62.9365050838</td></tr>\n",
       "<tr><td>...</td><td>...</td></tr>\n",
       "<tr><td>14.3360864888</td><td>93.3963823352</td></tr>\n",
       "<tr><td>19.5899858716</td><td>54.7713213972</td></tr>\n",
       "<tr><td>14.8603557394</td><td>65.0842136962</td></tr>\n",
       "<tr><td>10.2954772658</td><td>86.2165081125</td></tr>\n",
       "<tr><td>11.9427749909</td><td>98.733046694</td></tr>\n",
       "<tr><td>10.8330331892</td><td>55.5301147739</td></tr>\n",
       "<tr><td>16.8250678957</td><td>69.3254817244</td></tr>\n",
       "<tr><td>16.792578986</td><td>59.2414887155</td></tr>\n",
       "<tr><td>12.4648161361</td><td>70.4455159566</td></tr>\n",
       "<tr><td>10.8867007288</td><td>99.185886158</td></tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<Table length=1000>\n",
       "      x             y      \n",
       "   float64       float64   \n",
       "------------- -------------\n",
       "15.2414976634 87.3902978029\n",
       "14.2858102529 63.4778235534\n",
       "12.6837892045 95.1038332346\n",
       "15.7433361157 84.0554583013\n",
       "10.6276318955 96.0939150693\n",
       "13.6078233437 90.8772263701\n",
       "16.7426639018 53.5680565112\n",
       "18.5854346321 63.4464077849\n",
       "16.8978153196 53.8207361937\n",
       "11.3037331537 62.9365050838\n",
       "          ...           ...\n",
       "14.3360864888 93.3963823352\n",
       "19.5899858716 54.7713213972\n",
       "14.8603557394 65.0842136962\n",
       "10.2954772658 86.2165081125\n",
       "11.9427749909  98.733046694\n",
       "10.8330331892 55.5301147739\n",
       "16.8250678957 69.3254817244\n",
       " 16.792578986 59.2414887155\n",
       "12.4648161361 70.4455159566\n",
       "10.8867007288  99.185886158"
      ]
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### to LaTeX tables\n",
    "\n",
    "A nice thing about `AstroPy` is that you can convert your data into LaTeX tables. This is easily done with writing it to a file. You can then copy it and use it on your next publication"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\\begin{table}\n",
      "\\begin{tabular}{cc}\n",
      "x & y \\\\\n",
      "15.2414976634 & 87.3902978029 \\\\\n",
      "14.2858102529 & 63.4778235534 \\\\\n",
      "12.6837892045 & 95.1038332346 \\\\\n",
      "15.7433361157 & 84.0554583013 \\\\\n",
      "10.6276318955 & 96.0939150693 \\\\\n",
      "13.6078233437 & 90.8772263701 \\\\\n",
      "16.7426639018 & 53.5680565112 \\\\\n",
      "18.5854346321 & 63.4464077849 \\\\\n",
      "16.8978153196 & 53.8207361937 \\\\\n",
      "11.3037331537 & 62.9365050838 \\\\\n",
      "\\end{tabular}\n",
      "\\end{table}\n"
     ]
    }
   ],
   "source": [
    "import sys\n",
    "ascii.write(data[0:10], sys.stdout, format='latex')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "To save it as a file, you can do this:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "ascii.write(data, './data/astropy_data_latex.tex', format='latex')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\\begin{table}\r\n",
      "\\begin{tabular}{cc}\r\n",
      "x & y \\\\\r\n",
      "15.2414976634 & 87.3902978029 \\\\\r\n",
      "14.2858102529 & 63.4778235534 \\\\\r\n",
      "12.6837892045 & 95.1038332346 \\\\\r\n",
      "15.7433361157 & 84.0554583013 \\\\\r\n",
      "10.6276318955 & 96.0939150693 \\\\\r\n",
      "13.6078233437 & 90.8772263701 \\\\\r\n",
      "16.7426639018 & 53.5680565112 \\\\\r\n"
     ]
    }
   ],
   "source": [
    "# I'm only showing the first 10 lines\n",
    "!head ./data/astropy_data_latex.tex"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### to CSV files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "ascii.write(data, './data/astropy_data_csv.csv', format='csv', fast_writer=False) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x,y\r\n",
      "15.2414976634,87.3902978029\r\n",
      "14.2858102529,63.4778235534\r\n",
      "12.6837892045,95.1038332346\r\n",
      "15.7433361157,84.0554583013\r\n",
      "10.6276318955,96.0939150693\r\n",
      "13.6078233437,90.8772263701\r\n",
      "16.7426639018,53.5680565112\r\n",
      "18.5854346321,63.4464077849\r\n",
      "16.8978153196,53.8207361937\r\n"
     ]
    }
   ],
   "source": [
    "!head ./data/astropy_data_csv.csv"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### Other formats\n",
    "\n",
    "`AstroPy` tables come with a great support for many different types of files.\n",
    "This is a list of the supported files that you can import/export AstroPy tables.\n",
    "\n",
    "![astropy_formats](./images/astropy_table_formats.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### Data tables and Column types\n",
    "\n",
    "You can also use `AstroPy` tables to preserve the metadata of a column. For example, you can keep the units of each column, so that you use the data later on, and still be able to use unit conversions, etc. for this."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "t = Table(masked=True)\n",
    "t['x'] = MaskedColumn([1.0, 2.0], unit='m', dtype='float32')\n",
    "t['x'][1] = np.ma.masked\n",
    "t['y'] = MaskedColumn([False, True], dtype='bool')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "&lt;Table masked=True length=2&gt;\n",
       "<table id=\"table4879619792\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>x</th><th>y</th></tr></thead>\n",
       "<thead><tr><th>m</th><th></th></tr></thead>\n",
       "<thead><tr><th>float32</th><th>bool</th></tr></thead>\n",
       "<tr><td>1.0</td><td>False</td></tr>\n",
       "<tr><td>--</td><td>True</td></tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<Table masked=True length=2>\n",
       "   x      y  \n",
       "   m         \n",
       "float32  bool\n",
       "------- -----\n",
       "    1.0 False\n",
       "     --  True"
      ]
     },
     "execution_count": 129,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "Now we can save it into a `ecsv` file. This type of file will preserve the type of units, and more, for each of the columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# %ECSV 0.9\n",
      "# ---\n",
      "# datatype:\n",
      "# - {name: x, unit: m, datatype: float32}\n",
      "# - {name: y, datatype: bool}\n",
      "x y\n",
      "1.0 False\n",
      "\"\" True\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from astropy.extern.six.moves import StringIO\n",
    "fh = StringIO()\n",
    "t.write(fh, format='ascii.ecsv')  \n",
    "table_string = fh.getvalue()      \n",
    "print(table_string) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "&lt;Table masked=True length=2&gt;\n",
       "<table id=\"table4879596240\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>x</th><th>y</th></tr></thead>\n",
       "<thead><tr><th>m</th><th></th></tr></thead>\n",
       "<thead><tr><th>float32</th><th>bool</th></tr></thead>\n",
       "<tr><td>1.0</td><td>False</td></tr>\n",
       "<tr><td>--</td><td>True</td></tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<Table masked=True length=2>\n",
       "   x      y  \n",
       "   m         \n",
       "float32  bool\n",
       "------- -----\n",
       "    1.0 False\n",
       "     --  True"
      ]
     },
     "execution_count": 131,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Table.read(table_string, format='ascii')  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "Or you can dump it into a file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "t.write('./data/astropy_data_ecsv.ecsv', format='ascii.ecsv', overwrite=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "And you can now read it in"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "&lt;Table masked=True length=2&gt;\n",
       "<table id=\"table4858493456\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>x</th><th>y</th></tr></thead>\n",
       "<thead><tr><th>m</th><th></th></tr></thead>\n",
       "<thead><tr><th>float32</th><th>bool</th></tr></thead>\n",
       "<tr><td>1.0</td><td>False</td></tr>\n",
       "<tr><td>--</td><td>True</td></tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<Table masked=True length=2>\n",
       "   x      y  \n",
       "   m         \n",
       "float32  bool\n",
       "------- -----\n",
       "    1.0 False\n",
       "     --  True"
      ]
     },
     "execution_count": 133,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_ecsv = ascii.read('./data/astropy_data_ecsv.ecsv', format='ecsv')\n",
    "data_ecsv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "&lt;MaskedColumn name=&apos;x&apos; dtype=&apos;float32&apos; unit=&apos;m&apos; length=2&gt;\n",
       "<table>\n",
       "<tr><td>1.0</td></tr>\n",
       "<tr><td>--</td></tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<MaskedColumn name='x' dtype='float32' unit='m' length=2>\n",
       "1.0\n",
       " --"
      ]
     },
     "execution_count": 134,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_ecsv['x']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# Resources\n",
    "\n",
    "For further reading and exercises, you can check out:\n",
    "- Astropy Documents: [http://docs.astropy.org/en/stable/index.html](http://docs.astropy.org/en/stable/index.html)\n",
    "- Programming and Statistics - Python Notes (Notes from a class at the University of Hertfordshire) [https://star.herts.ac.uk/~gb/python/](https://star.herts.ac.uk/~gb/python/)\n",
    "- HST FITS files for fun: [https://www.spacetelescope.org/projects/fits_liberator/m17data/](https://www.spacetelescope.org/projects/fits_liberator/m17data/)\n",
    "- AstroPy on _Aperture Photometry_: [http://photutils.readthedocs.io/en/stable/photutils/aperture.html](http://photutils.readthedocs.io/en/stable/photutils/aperture.html)\n",
    "- AstroPy Tutorials [http://www.astropy.org/astropy-tutorials/](http://www.astropy.org/astropy-tutorials/)\n",
    "- Photutils - AstroPy package for doing Photometry [http://photutils.readthedocs.io/en/stable/index.html](http://photutils.readthedocs.io/en/stable/index.html)"
   ]
  }
 ],
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