You can use savesensitivities.py to produce plots that show the sensitivity of observables to the parameters varied in the production. The left hand plot is a colormap with the sensitivity values of a bin b Sb(p) as colour values. The right hand side plot shows a mean of all the calculated sensitivities in that bin and the according rms as errobar.
Assume that you are in a directory that includes a folder 'mc' that holds the MC runs and a folder 'ref' that holds the reference data, you can do the following:
savesensitivities.py --datadir . --oudir splots --observables weights1
This will process all the observables found in weights1 (if they exist in the aida files). The plots will be stored in the folder 'splots'.
It is also possible to re-use previously stored interpolations by using --ipoldir ipols. In order to speed up things, the switch --use_weave 1 may also be used.
If the script is done you can create an html-gallery using the 'makegallery.py'-script from professor/tools.
This will produce the file gallery-sens.html that will have all the *.png files to be found in the folder 'splots' ordered in one column. The number of columns, N, can be set by an additional '-c N'.