Hyperopt analysis

Created by: Cmurilochem

I am starting the implementation of @juanrojochacon's hyperopt algorithm wherein data of 1/\varphi^{2} is used to decide on the best \chi^{2} hyperpoint.

I realized that all data needed are contained within tries.json as implemented here in hyperopt_loss branch.

So, I was wondering that the best approach would be to implement this post-hyperopt analysis in an external script like those in validphys. I see here some options:

• it could be a post-hyperopt.py similar to postfit.py
• an option in vp_hyperoptplot.py and implemented in hyperoptplot.py
• inside hyper_algorithm.py (my first option?)

Which one would you suggest ? Any other ideas are also very welcome.

Edited: The major advantage I see in having such external script is that we would be to recover any possible statistics we want with just one hyperopt experiment.