schrodinger.analysis.cluster.ClusterValues

Class ClusterValues

object --+ | ClusterValues

Instance Methods

__init__(self, values, n_clusters=8, **kmeans_args)
Cluster the specified list of values (e.g.

getClusterMemberships(self)
Returns a list corresponding to which cluster each value was assigned.

getClusteredValues(self)
Return a list of clustered values.

getClusterCenters(self)
Return a numpy array of cluster centroids.

Inherited from object: __delattr__, __format__, __getattribute__, __hash__, __new__, __reduce__, __reduce_ex__, __repr__, __setattr__, __sizeof__, __str__, __subclasshook__

init(self, values, n_clusters=8, **kmeans_args)
(Constructor)

Cluster the specified list of values (e.g. coordinates) into the given number of clusters. NOTE: This clustering algorithm is an inherintly random process, so results from different runs may not be consistent.

Parameters:

values (List or numpy array of values to cluster. Each item can be a float or a list of floats (e.g. 3D coordinates).) - Values to cluster (will be cast into a numpy array)
n_clusters (int) - Number of clusters to generate.
Other arguments are passed directly to KMeans.

Overrides: object.__init__

getClusterMemberships(self)

Returns a list corresponding to which cluster each value was assigned. The length of the list is equal to the number of the input values. Each value ranges from 0 to (number of output clusters-1).

getClusteredValues(self)

Return a list of clustered values. Outer list represents clusters, each item (cluster) will consist of one or more input values.

Class ClusterValues

__init__(self, values, n_clusters=8, **kmeans_args) (Constructor)

getClusterMemberships(self)

getClusteredValues(self)

init(self, values, n_clusters=8, **kmeans_args)
(Constructor)