Improve CAFOS pairs matching

[juanep97]

This improves astrometric calibration of CAFOS polarimetry images using the distance between pairs computed from already calibrated images.

The mean and std was computed by executing the following commands in the IOP4 IPython terminal:

In [1]: qs = ReducedFit.objects.filter(flags__has=ReducedFit.FLAGS.BUILT_REDUCED, instrument="CAFOS2.2").all()
In [2]: np.mean([redf.astrometry_info[-1]['seg_disp_sign'] for redf in qs[len(qs)-300:len(qs)-1]], axis=0)
In [3]: np.std([redf.astrometry_info[-1]['seg_disp_sign'] for redf in qs[len(qs)-300:len(qs)-1]], axis=0)

By using precomputed distances from already calibrated images, it increases the success rate for images with low number of stars where blind pair matching might fail.

[morcuended]

The mean and std was computed by executing the following commands in the IOP4 IPython terminal:

In [1]: qs = ReducedFit.objects.filter(flags__has=ReducedFit.FLAGS.BUILT_REDUCED, instrument="CAFOS2.2").all()
In [2]: np.mean([redf.astrometry_info[-1]['seg_disp_sign'] for redf in qs[len(qs)-300:len(qs)-1]], axis=0)
In [3]: np.std([redf.astrometry_info[-1]['seg_disp_sign'] for redf in qs[len(qs)-300:len(qs)-1]], axis=0)

Do you think it is worth to keep this piece of information in the docs?

[morcuended]

Looks good. I left some minor comments, but I think it can be merged.

[juanep97]

The mean and std was computed by executing the following commands in the IOP4 IPython terminal:

In [1]: qs = ReducedFit.objects.filter(flags__has=ReducedFit.FLAGS.BUILT_REDUCED, instrument="CAFOS2.2").all()
In [2]: np.mean([redf.astrometry_info[-1]['seg_disp_sign'] for redf in qs[len(qs)-300:len(qs)-1]], axis=0)
In [3]: np.std([redf.astrometry_info[-1]['seg_disp_sign'] for redf in qs[len(qs)-300:len(qs)-1]], axis=0)

Do you think it is worth to keep this piece of information in the docs?

It will be one of the jupyter notebooks that I'm -slowly- writing for the docs. I included a comment in the meantime.

[morcuended]

Looks good. Go ahead with the merging.