schrodinger.analysis.cluster module

Provides a class for clustering a set of values - for example, 3D coordinates.

@copyright: Schrodinger, LLC. All rights reserved.

class schrodinger.analysis.cluster.ClusterValues(values, n_clusters=8, **kmeans_args)[source]

Bases: object

__init__(values, n_clusters=8, **kmeans_args)[source]

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.

getClusterMemberships()[source]

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).

Used by the unit test to verify that the clustering works correctly.

getClusteredValues()[source]

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

getClusterCenters()[source]

Return a numpy array of cluster centroids.