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)

Bases: object

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

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()

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()

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

getClusterCenters()

Return a numpy array of cluster centroids.

__class__

alias of builtins.type

__delattr__

Implement delattr(self, name).

__dict__ = mappingproxy({'__module__': 'schrodinger.analysis.cluster', '__init__': <function ClusterValues.__init__>, 'getClusterMemberships': <function ClusterValues.getClusterMemberships>, 'getClusteredValues': <function ClusterValues.getClusteredValues>, 'getClusterCenters': <function ClusterValues.getClusterCenters>, '__dict__': <attribute '__dict__' of 'ClusterValues' objects>, '__weakref__': <attribute '__weakref__' of 'ClusterValues' objects>, '__doc__': None})

__dir__() → list

default dir() implementation

__eq__

Return self==value.

__format__()

default object formatter

__ge__

Return self>=value.

__getattribute__

Return getattr(self, name).

__gt__

Return self>value.

__hash__

Return hash(self).

__init_subclass__()

This method is called when a class is subclassed.

The default implementation does nothing. It may be overridden to extend subclasses.

__le__

Return self<=value.

__lt__

Return self<value.

__module__ = 'schrodinger.analysis.cluster'

__ne__

Return self!=value.

__new__()

Create and return a new object. See help(type) for accurate signature.

__reduce__()

helper for pickle

__reduce_ex__()

helper for pickle

__repr__

Return repr(self).

__setattr__

Implement setattr(self, name, value).

__sizeof__() → int

size of object in memory, in bytes

__str__

Return str(self).

__subclasshook__()

Abstract classes can override this to customize issubclass().

This is invoked early on by abc.ABCMeta.__subclasscheck__(). It should return True, False or NotImplemented. If it returns NotImplemented, the normal algorithm is used. Otherwise, it overrides the normal algorithm (and the outcome is cached).

__weakref__

list of weak references to the object (if defined)