msmbuilder.clustering.KCenters¶

class msmbuilder.clustering.KCenters(metric, trajectories=None, prep_trajectories=None, k=None, distance_cutoff=None, seed=0)[source]¶

__init__(metric, trajectories=None, prep_trajectories=None, k=None, distance_cutoff=None, seed=0)[source]¶

Run kcenters clustering algorithm.

Terminates either when k clusters have been identified, or when every data is clustered better than distance_cutoff.

Parameters:

metric : msmbuilder.metrics.AbstractDistanceMetric A metric capable of handling ptraj trajectory : Trajectory or list of msmbuilder.Trajectory data to cluster k : {int, None} number of desired clusters, or None distance_cutoff : {float, None} Stop identifying new clusters once the distance of every data to its cluster center falls below this value. Supply either this or k seed : int, optional index of the frame to use as the first cluster center

See also

_kcenters

implementation

References

[R6]	Beauchamp, MSMBuilder2

Methods

__init__(metric[, trajectories, ...])	Run kcenters clustering algorithm.
get_assignments	Assign the trajectories you passed into the constructor based on
get_distances	Extract the distance from each frame to its assigned cluster kcenter
get_generator_indices	Get the generator indices corresponding to frames in self.ptraj.
get_generators_as_traj	Get a trajectory containing the generators