msmbuilder: MSMBuilder 3.4
Robert T. McGibbon, Matthew P. Harrigan, Bharath Ramsundar, Kyle A. Beauchamp, msultan, Christian R. Schwantes, Carlos X. Hernández, peastman, Brooke E. Husic, pfrstg, Stephen Liu, Steven M. Kearnes, Joshua L. Adelman, gkiss · Zenodo (CERN European Organization for Nuclear Research) · 2016
We're pleased to announce MSMBuilder 3.4. It contains a plethora of new features, bug fixes, and improvements. API Changes Range-based slicing on dataset objects is no longer allowed. Keys in the dataset object don't have to be continuous. The empty slice, e.g. ds[:] loads all trajectories in a list (#610). Ward clustering has been renamed AgglomerativeClustering in scikit-learn. Please use the new msmbuilder wrapper class AgglomerativeClustering. An alias for Ward has been made available (#685). PCCA.trimmed_microstates_to_macrostates has been removed. This dictionary was actually keyed by untrimmed microstate labels. PCCA.transform would throw an exception when operating on a system with trimming because it was using this misleading dictionary. Please use pcca.microstate_mapping_ for this functionality (#709). UnionDataset has been removed after deprecation in 3.3. Please use FeatureUnion instead (#671). SubsetFeaturizer and ilk have been removed from the msmbuilder.featurizer namespace. Please import them from msmbuilder.featurizer.subset (#738). FirstSlicer has been removed. Use Slicer(first=x) for the same functionality (#738). msmbuilder.featurizer.load has been removed. Featurizer.save has been removed. Please use utils.load, utils.dump (#738). New Features Dataset objects can call, fit_transform_with() to simplify the common pattern of applying an estimator to a dataset object to produce a new dataset object (#610). kinetic_mapping is a new option to tICA. It's similar to weighted_transform, but based on a better theoretical framework. weighted_transform is deprecated (#766). VonMisesFeaturizer uses soft bins around the unit-circle to give an alternate representation of dihedral angles (#744). MarkovStateModel has a partial_transform() method (#707). KapaAngleFeaturizer is available via the command line (#681). MarkovStateModel has a new attribute, percent_retained_, for ergodic trimming (#689). AlphaAngleFeaturizer computes the dihedral angles between alpha carbons (#691). FunctionFeaturizer computes features based on an arbitrary Python function or callable (#717). Automatic State Partitioning (APM) uses kinetic information to cluster conformations (#748). Improvements Consistent counts setup and ergodic cutoff across various flavors of Markov models (#718, #729, #701, #705). Tests no longer depend on sklearn.hmm, which has been removed (#690). Improvements to RSMDFeaturizer (#695, #764). SparseTICA is completely re-written with large performance improvements when dealing with large numbers of features (#704). Links for downloading example data are un-broken after figshare changed URLs (#751).