These scripts perform the computation and caching of the features, compute/caching covariances and cross-validated VAMP scoring.

First one needs to obtain the DESRES fast folders data set, which is copyrighted and needed to be licensed first (it is free of charge for academic use).

After the data set has been extracted, one should point the path definitions in paths.py.

Then one wants to invoke cache_features.py to compute and cache the features.

After this step we invoke the calc_cov_single_feat.py script, which computes the VAMP scores for not combined features. The calc_cov_combined_features.py script computes the latter for the combined features of flexible torsions and exp(-d) transformation or best scoring contact feature.

Finally in msm_on_vamp_space, we run a MSM analysis. we project onto the VAMP basis computed earlier and cluster via kmeans for different centers. This discretization is then evaluated by a VAMP score computed on MSM.