Added WCS support

[mchalela]

The main changes are the removal of header keyword arguments: dispersion_key, first_wavelength, dispersion_type. These arguments were used solely for reconstructing the spectral axis. This PR implements the use of astropy WCS methods to reconstruct the spectral axis by recognizing the header format.

The extension is now detected automatically but if many extensions are present in a file the user can still specify the extension to use. Solves issue #36.

Those 3 arguments are removed from read_spectrum, spectrum and NirdustSpectrum.

[leliel12]

Yo cambiaria

nirdust/nirdust.py

Line 573 in 1cd4398

ext = _get_science_extension(hdulist, extension)

Por

def read_spectrum(file_name, extension=None, z=0, **kwargs):

    with fits.open(file_name) as hdulist:
        if extension is None:
            ext_candidates = infer_fits_science_extension(hdulist, extension)
            if len(ext_candidates) > 1:
                raise HeaderKeywordError(
                    "More than one extension with relevant keywords. "
                    "Please specify the extension."
                )
        
            extension = extension_candidates[0]
        
        flux = hdulist[ext].data
        header = hdulist[ext].header

    single_spectrum = spectrum(flux, header, z, **kwargs)

    return single_spectrum

Con eso hago public el _get_science_extension y puede usarse para por las dudas para otras cosas y ademas le sacamos responsabilidad de decidir que hacer con el None, cosa que es realmente informacion relevante para read_spectrum

Asi infer_fits_science_extension (tal ves no es el mejor nombre) quedaria:

def infer_fit_science_extension(hdulist, extension):
    """Auto detect fits science extension using the provided keywords."""

    if len(hdulist) == 1:
        return np.array([0])

    keys = {'CRVAL1'}   # keywords that are present in science extensions
    extl = []
    for ext, hdu in enumerate(hdulist):
        if keys.issubset(hdu.header.keys()):
            extl.append(ext)

    return np.array(extl)

[mchalela]

Puse todos los cambios, mas test y docu. Quedo mucho mejor 👍