Gammalib and ctools do not include classes and scripts to make plots.
This is intentional because creating and maintaining plotting tools that work on most user’s machines and cover most user’s needs is a big project in itself, and deciding to support a plotting package that is popular now as part of the CTA science tools could become very problematic in the future.
But we realise that most ctools users need to create plots for their high-level science results, so on this page we provide a few pointers to external packages and tools.
The most common way to create publication-quality astronomy plots at the moment is to use the matplotlib Python plotting package. As illustrated by the matplotlib gallery, virtually any plot can be constructed, but matplotlib doesn’t have built-in easy-to-use classes or functions to create the common plots for gamma-ray astronomy, which are sky maps and spectra, so in the sections below we give some specific pointers for those.
For creating publication quality sky map plots via a Python script a good choice is to use APLPy, WCSAxes or kapteyn, which are all based on matplotlib.
You can also use interactive astronomy image viewers like DS9, Aladin or Ginga which allow you to save the image to a PNG or PDF file after customising it interactively, but also contain command line options to create the plot, i.e. you can write a bash or Python script to make the plot reproducible (DS9 and Ginga also feature direct communication with Python, but that is a bit harder to use and usually used for interactive image analysis, not plotting scripts).
To plot spectra or spectral energy distributions (including flux model curves, flux model error bands, flux points and residuals) and light curves, you can use matplotlib directly, or use the classes and scripts in Gammapy.
Another option is to use virtual observatory interactive spectrum tools like IRIS, CASSIS or VOSpec which allow you to save the plot to a PNG or PDF file after creating it interactively.
