Major release

New features:

• msm: variational scores for model selection of MSMs. The scores are based on the variational
  approach for Markov processes [1, 2] and can be employed for both reversible and non-reversible
  MSMs. Both the Rayleigh quotient as well as the kinetic variance [3] and their non-reversible
  generalizations are available. The scores are implemented in the score method of the MSM
  estimators MaximumLikelihoodMSM and OOMReweightedMSM. Rudimentary support for Cross-validation
  similar as suggested in [4] is implemented in the score_cv method, however this is currently
  inefficient and will be improved in future versions. #1093

• config: Added a lot of documentation and added mute option to silence PyEMMA (almost completely).

• References:
  [1] Noe, F. and F. Nueske: A variational approach to modeling slow processes
  in stochastic dynamical systems. SIAM Multiscale Model. Simul. 11, 635-655 (2013).
  [2] Wu, H and F. Noe: Variational approach for learning Markov processes
  from time series data (in preparation).
  [4] Noe, F. and C. Clementi: Kinetic distance and kinetic maps from molecular
  dynamics simulation. J. Chem. Theory Comput. 11, 5002-5011 (2015).
  [3] McGibbon, R and V. S. Pande: Variational cross-validation of slow
  dynamical modes in molecular kinetics, J. Chem. Phys. 142, 124105 (2015).

• coordinates:

  • kmeans: allow the random seed used for initializing the centers to be passed. The prior behaviour
    was to init the generator by time, if fixed_seed=False. Now bool and int can be passed. #1091

• datasets:

  • added a multi-ensemble data generator for the 1D asymmetric double well. #1097

Fixes:

• coordinates:

  • StreamingEstimators: If an exception occurred during flipping the in_memory property,
    the state is not updated. #1096
  • Removed deprecated method parametrize. Use estimate or fit for now. #1088
  • Readers: nice error messages for file handling errors (which file caused the error). #1085
  • TICA: raise ZeroRankError, if the input data contained only constant features. #1055
  • KMeans: Added progress bar for collecting the data in pre-clustering phase. #1084

• msm:

  • ImpliedTimescales estimation can be interrupted (strg+c, stop button in Jupyter notebooks). #1079

• general:

  • config: better documentation of the configuration parameters. #1095