Slicing operations on 1-D spectra

For the last part of GSoc, I implemented slicing operations on spectrum objects. Pythonically, this implies overriding the __getitem__ method. This method is passed the slice object and it returns a new spectrum1D object with the requested slicing parameters applied. For example:
>>> from specutils.io import read_fits
>>> spectra = read_fits.read_fits_spectrum1d("test.fits")  # linear spectra file
>>> indexed_spectra = spectra[::2]  # this creates a new spectra object which skips
                                                # every alternate object from the original spectra
>>> spectra.dispersion
[320.66, 321.43, 322.77, 324.23, 326.97, 329.44]
>>> indexed_spectra.dispersion
[320.66, 322.77, 326.97]

The spectra can be sliced using the same interface as slicing for python lists. Internally, an indexer model is used to slice the WCS. This is because the WCS is not a list, it is a mapping from input to output. Python slicing operations cannot be directly applied to WCS'es. This indexer model provides an adapter to interface with the slice operations. It also allows WCS'es to slice from negative indices.

For GSoC, this is it. However, I will continue to contribute to Astropy, and specifically to the specutils package. The next step will be to enable transformations between different WCS'es and models, making it easier for users to convert to and fro between different formats.