Update documentation for FSFModel

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.. warning:: FSF class is currently under development

Only one model of FSF (Field Spread Function) is currently available.

Two models of FSF (Field Spread Function) are currently available:

FSF *MOFFAT1*

-------------

- `~mpdaf.MUSE.OldMoffatModel` (``model='MOFFAT1'``): the old model with a fixed

  beta.

- `~mpdaf.MUSE.MoffatModel2` (``model=2``): a circular MOFFAT with polynomials

  for beta and FWHM.

Example with *MOFFAT1*

----------------------

The MUSE FSF is supposed to be a Moffat function with a FWHM which varies

linearly with the wavelength:

    fwhm = a + b*lbda

    :math:`FWHM = a + b * lbda`

With:

 - a (float) constant in arcsec which defined the FWHM.

 - b (float) constant which defined the FWHM.

We create the `~mpdaf.MUSE.FSF` object like this:

We create the `~mpdaf.MUSE.FSFModel` object like this:

.. ipython::

  In [1]: from mpdaf.MUSE import FSF

  In [1]: from mpdaf.MUSE import FSFModel, OldMoffatModel

  In [2]: fsf = OldMoffatModel(a=0.885, b=-2.94E-05, beta=2.8, pixstep=0.2)

  In [2]: fsf = FSF(typ='MOFFAT1')

  In [3]: isinstance(fsf, FSFModel)

`~mpdaf.MUSE.FSF.get_FSF` returns for each wavelength an array and the FWHM in

pixel and in arcseconds.

Various methods allow to get the FSF array (2D or 3D, as mpdaf Image or Cube)

for given wavelengths, or the FWHM in pixel and in arcseconds.

.. ipython::

  In [3]: fsf_array, fwhm_pix, fwhm_arcsec = fsf.get_FSF(lbda=[5000, 9000], step=0.2, size=21, beta=2.8, a=0.885, b=-2.94E-05)

  In [1]: lbda = np.array([5000, 9000])

  In [4]: print(fwhm_pix)

  In [4]: fsf.get_fwhm(lbda)

  In [5]: print(fwhm_arcsec)

  In [5]: fsf.get_fwhm(lbda, unit='pix')

  In [20]: im5000 = fsf.get_2darray(lbda[0], shape=(25, 25))

  In [20]: fsfcube = fsf.get_3darray(lbda, shape=(25, 25))

  In [27]: plt.figure()

  @savefig FSF1.png width=3.5in

  In [26]: plt.imshow(fsf_array[1], vmin=0, vmax=60, interpolation='nearest')

  In [26]: plt.imshow(im5000)

  In [27]: plt.figure()

  @savefig FSF2.png width=3.5in

  In [28]: plt.imshow(fsf_array[0], vmin=0, vmax=60, interpolation='nearest')

  In [28]: plt.imshow(fsfcube[1])

The FSF model can be saved to a FITS header with

`mpdaf.MUSE.FSFModel.to_header`, and read with `mpdaf.MUSE.FSFModel.read`.

It is also possible to use `~mpdaf.MUSE.FSF.get_FSF_cube` that returns a cube of

FSFs with the same coordinates that the MUSE data cube given as input.

MUSE mosaic field map

=====================