CSI-DevFest.ipynb

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    "# Devfest Space Workshop\n",
    "\n",
    "### Brought to you by Columbia Space Initiative\n",
    "### Feb. 2, 2019\n",
    "\n",
    "Learn how astronomers analyze space images with Python and Astropy!"
   ]
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   "source": [
    "import numpy as np\n",
    "\n",
    "# Set up matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "from astropy.io import fits\n",
    "import astropy.units as u\n",
    "from astropy.io import fits\n",
    "from astropy.time import Time\n",
    "from astropy.coordinates import SkyCoord, EarthLocation, AltAz"
   ]
  },
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   "source": [
    "## Locating our Astronomical Object"
   ]
  },
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   "source": [
    "Get the coordinates of your object."
   ]
  },
  {
   "cell_type": "code",
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   "source": [
    "Upload your FITS image to the online directory containing this Jupyter notebook."
   ]
  },
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   "cell_type": "code",
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   "source": [
    "## Opening FITS files and loading the image data"
   ]
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   "source": [
    "Let's get the header of this FITS file to find out what it contains."
   ]
  },
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   "source": [
    "Let's now open this file."
   ]
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   "source": [
    "Generally, the image information is located in the <code>PRIMARY</code> block. The blocks are numbered and can be accessed by indexing <code>hdu_list</code>."
   ]
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   "source": [
    "Our data is now stored as a 2-D numpy array."
   ]
  },
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   "source": [
    "Great! Now, we can close the FITS file."
   ]
  },
  {
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   "source": [
    "## Viewing the image data and getting basic statistics"
   ]
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   "source": [
    "Display the image."
   ]
  },
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    "Let's get some basic statistics about our image:"
   ]
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   "source": [
    "### Plotting a histogram"
   ]
  },
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   "source": [
    "To make a histogram with `matplotlib.pyplot.hist()`, we'll need to cast the data from a 2-D array to something one dimensional."
   ]
  },
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   "cell_type": "markdown",
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   "source": [
    "In this case, let's use the `ndarray.flatten()` to return a 1-D numpy array."
   ]
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   "source": [
    "### Displaying the image with a logarithmic scale"
   ]
  },
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   "source": [
    "What if we want to use a logarithmic color scale? To do so, we'll need to load the `LogNorm` object from `matplotlib`."
   ]
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    "We can use the values from our histogram to choose the scale of our logarithmic plot."
   ]
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 "metadata": {
  "astropy-tutorials": {
   "author": "Lia R. Corrales <lia@astro.columbia.edu>",
   "date": "January 2014",
   "description": "Demonstrates use of astropy.utils.data to download data; astropy.io.fits to open the file; matplotlib to view the image with different color scales and stretches and to make histrograms. Also includes method for simple image stacking.",
   "link_name": "Viewing and manipulating FITS images",
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