bugfix for msmbuilder issue #247 regarding loading prepared trajectories. If the metric is RMSD or a hybrid metric, then just the trajectories are loaded. But I needed to add a check for LPRMSD, buuuut this doesn't work since it's a plugin. So, the change is to only load prepared trajectories if the metric is in an instance of a subclass of Vectorized. This should work because then we can use np.concatenate on the prepared trajectories. All other metrics are handled by loading trajectories and preparing later.
messed up in the bug fix. Needed to have metrics.Vectorized
added fix for Cluster.py to work with hierarchical. I broke it earlier...
Merge pull request #248 from schwancr/lprmsd_cluster_check

bugfix for msmbuilder issue #247 regarding loading prepared trajectories...
Add ergodic triming option to BuildMSM.py
Lets see if that works better
Update BuildMSM.py

change trim=False to trim=True in the def run(...) line,
Merge pull request #1 from schwancr/patch-1

Update BuildMSM.py
Merge pull request #250 from rmcgibbo/master

Add ergodic triming option to BuildMSM.py
added check for openmp support
bugfix in extensions
Merge pull request #253 from SimTk/djf0

added check for openmp support
Updated MLE notes re issue #255
Removed some latex temp files for mle_notes.
Merge pull request #260 from SimTk/fix_mle_notes

Updated MLE notes re issue #255
changed AssignHierarchical to output the correct assignments file. The script now needs a stride to be input by the user.
Merge branch 'assign_hier' of github.com:schwancr/msmbuilder into assign_hier