Subsampling for MCLMC tuning

[reubenharry]

Current behavior

The third stage of tuning computes effective sample size using correlation length averaged across dimensions. For high dimensional problems, it might be better to subsample only n dimensions, for efficiency reasons.

Desired behavior

Have a default maximum number of dimensions n, and run a chain in the third stage of tuning that only returns a random choice of n dimensions.