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msmbuilder: MSMBuilder v3.3.0

Authors: Robert T. McGibbon; Bharath Ramsundar; Matthew Harrigan; Kyle Beauchamp; Christian Schwantes; peastman; pfrstg; +5 Authors

msmbuilder: MSMBuilder v3.3.0

Abstract

We're pleased to announce the release of MSMBuilder v3.3.0. The focus of this release is a completely re-written module for constructing HMMs as well as bug fixes and incremental improvements. API Changes FeatureUnion is an estimator that deprecates the functionality of UnionDataset. Passing a list of paths to dataset() will no longer automatically yield a UnionDataset. This behavior is still available by specifying fmt="dir-npy-union", but is deprecated (#611). The command line flag for featurizers --out (deprecated in 3.2) now saves the featurizer as a pickle file (#546). Please use --transformed for the old behavior. This is consistent with other command-line commands. The default number of timescales in MarkovStateModel is now one less than the number of states (was 10). This addresses some bugs with implied_timescales and PCCA(+) (#603). New Features GaussianHMM and VonMisesHMM is rewritten to feature higher code reuse and code quality (#583, #582, #584, #572, #570). KDTree can find n nearest points to e.g. a cluster center (#599). Slicer featurizer can slice feature arrays as part of a pipeline (#567). Improvements PCCAPlus is compatible with scipy 0.16 (#620). Documentation improvements (#618, #608, #604, #602) Test improvements, especially for Windows (#593, #590, #588, #579, #578, #577, #576) Bug fix: MarkovStateModel.sample() produced trajectories of incorrect length. This function is still deprecated (#556). Bug fix: The muller example dataset did not respect users' specifications for initial coordinates (#631). MarkovStateModel.draw_samples failed if discrete trajectories did not contain every possible state (#638). Function can now accept a single trajectory, as well as a list of them. SuperposeFeaturizer now respects the topology argument when loading the reference trajectory (#555).

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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