Further analysis of Alex's data from the dev workshop

Alex has run a load of simulations of Ar presented in https://github.com/MDMCproject/documents/tree/master/DeveloperMeetings/2023-23-August/slides/argon-refinement/results

These should be analysed using the `Control.plot_results()` method (which extracts the uncertainty from the Gaussian process), as a function of the number of refinement steps

The syntax to do this is something like:
```
from MDMC.control.plot_results import PlotResults

Plot_results('resultsstart095-3375.csv')
```

This will give the corner plot and mean and uncertainties of the optimized Gaussian process generated from that file. If you remove lines from the file (or if you are clever, only read in certain lines), then you will be able to see how the uncertainty in the parameters changes with the number of refinement steps.

I would *expect* that beyond ~50 points we stop seeing much gain in the uncertainty, but this is very much to be proven.

Note, it doesn't matter which optimizer was used to generate the file, all should be fine and work from this same code.