nsplattner

Its based on the same problem, but my request is more basic: I would just like to have a convenient way for assigning the output sets to the input sets....

I would suggest to use feature trajectories and engine-independent analysis options. Since this will be done with MDtraj and PyEMMA, there is no reason to make it engine-dependent. For storing...

I think the case to consider here is not so much when computing features is fast. If you work with larger systems/datasets and you want to work with residue minimum...

I think this is a misunderstanding. What I was saying is not that intermediate feature trajectories always have to be used. I just wanted to point out that its good...

Yes, I think we agree on this, 2.) is optional. There are different ways of implementing this: a) featurization as a separate tasks which only computes feature trajectories and stores...

For basic model building functionality required for adaptive sampling it would be sufficient to slightly extend the options of ```remote_analysis()```. The minimal functionality includes the following options: - featurizer selection...

I'm not sure how the function ```remote_analysis()``` is supposed to work. The choice of features seems to be hardcoded (line 44, ``` feat.add_backbone_torsions() ```) Is this supposed to be an...

O.k., thanks for the details! It is obvious what to change, the problem is that a) its not clear that this is an example since its placed in the package...

I think this should be feasible. But I think for both, GROMACS and Acemd the important thing is not so much to have everything available, but just to document where...

I'm in favour of option 1. Some system-specific files are always needed, but its not a big overhead to copy them (they are usually small compared to the results files)....