Starting from the plot/plot.py script, add a post-fit plotting script. This will need to do two things:
- access the post-fit results and apply the post-fit values for the parameters onto the templates
- sample from the central values and covariance matrix to get the post-fit uncertainty
- one can do something similar to what is done for pre-fit (already in the code)
An additional thing that will be important is to allow the user to define a version for the plots, such that the plots end up in a folder with the version name. This will make our lives much easier when we're mass-producing plots.