pyclustering.cluster.kmeans.kmeans_observer Class Reference

Observer of K-Means algorithm that is used to collect information about clustering process on each iteration of the algorithm. More...

Public Member Functions
def	__init__ (self)
	Initializer of observer of K-Means algorithm.
def	__len__ (self)
	Returns amount of steps that were observer during clustering process in K-Means algorithm.
def	notify (self, clusters, centers)
	This method is called by K-Means algorithm to notify about changes. More...
def	set_evolution_centers (self, evolution_centers)
	Set evolution of changes of centers during clustering process. More...
def	get_centers (self, iteration)
	Get method to return centers at specific iteration of clustering process. More...
def	set_evolution_clusters (self, evolution_clusters)
	Set evolution of changes of centers during clustering process. More...
def	get_clusters (self, iteration)
	Get method to return allocated clusters at specific iteration of clustering process. More...

Detailed Description

Observer of K-Means algorithm that is used to collect information about clustering process on each iteration of the algorithm.

See also

kmeans

Definition at line 30 of file kmeans.py.

Member Function Documentation

get_centers()

def pyclustering.cluster.kmeans.kmeans_observer.get_centers	(		self,
			iteration
	)

Get method to return centers at specific iteration of clustering process.

Parameters

[in]

iteration

(uint): Clustering process iteration at which centers are required.

Returns

(array_like) Centers at specific iteration.

Definition at line 78 of file kmeans.py.

get_clusters()

def pyclustering.cluster.kmeans.kmeans_observer.get_clusters	(		self,
			iteration
	)

Get method to return allocated clusters at specific iteration of clustering process.

Parameters

[in]

iteration

(uint): Clustering process iteration at which clusters are required.

Returns

(array_like) Clusters at specific iteration.

Definition at line 100 of file kmeans.py.

Referenced by pyclustering.samples.answer_reader.get_cluster_lengths(), and pyclustering.cluster.optics.optics.process().

notify()

def pyclustering.cluster.kmeans.kmeans_observer.notify	(		self,
			clusters,
			centers
	)

This method is called by K-Means algorithm to notify about changes.

Parameters

[in]	clusters	(array_like): Allocated clusters by K-Means algorithm.
[in]	centers	(array_like): Allocated centers by K-Means algorithm.

Definition at line 56 of file kmeans.py.

set_evolution_centers()

def pyclustering.cluster.kmeans.kmeans_observer.set_evolution_centers	(		self,
			evolution_centers
	)

Set evolution of changes of centers during clustering process.

Parameters

[in]

evolution_centers

(array_like): Evolution of changes of centers during clustering process.

Definition at line 68 of file kmeans.py.

set_evolution_clusters()

def pyclustering.cluster.kmeans.kmeans_observer.set_evolution_clusters	(		self,
			evolution_clusters
	)

Set evolution of changes of centers during clustering process.

Parameters

[in]

evolution_clusters

(array_like): Evolution of changes of clusters during clustering process.

Definition at line 90 of file kmeans.py.

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The documentation for this class was generated from the following file:

• pyclustering/cluster/kmeans.py