FITS Light Python Viewer

Posted on

The Python-based application FitsViewerLight is a FITS file viewer that can display both raw images and spectra.

FIT/FITS type files 1 are widely used in astronomy and allow the sharing of all types of data. There are many file viewers of this type, including the very famous SAOImageDS9 developed by the High Energy Astrophysics Division’s du Harvard-Smithsonian Center for Astrophysics 2.

There is also KStars, which I have already presented here. (Spectre de Phecda) which integrates an image viewer, but does not allow to display processed spectra directly. Concretely, there is an embarrassment of choice! Here is a NASA list of software that can read these files 3 :

But sometimes we prefer to have a little home-made script that suits us. Thus, the little software mentioned below is simply a personal need with a will to have something very light with only a few functionalities, and, above all, allowing to display a raw image as well as a processed spectrum, on any platform..


This small software, with the original name of FitsViewerLight for the moment, allows you to quickly visualise a spectrum file initially processed with software such as Demetra 4 ou ISIS 5, via the menu or by simple Drag ‘n Drop. On the right side of the window, the file header is also available and it is possible to modify some values if needed as you can see on the picture below.

Capture d'écran du FitsViewerLight après l'ouverture d'un spectre
Screenshot of the FitsViewerLight after opening a spectrum

In the same way, it is also possible to open a raw image and several indications are available in the status bar, such as the maximum pixel value. Indeed, when acquiring a spectrum, in particular, it is important to check that the image is not saturated.

Moreover, just for fun, I integrated the “Cyberpunk” style, whose creation and use are indicated at this address :

Capture d'écran du FitsViewerLight après l'ouverture d'un spectre
Screenshot of the FitsViewerLight with “Cyberpunk” style activated.

The whole software is in Python and the display of the graphic is done with the Matplotlib module 6. You will find the sources as always on my Git repository at the following address :

Sources and further information


Faites comme moi, partagez !