Analyser of cluster ordering diagram. More...

Public Member Functions
def	cluster_ordering (self)
	(list) Returns values of dataset cluster ordering.

def	__init__ (self, ordering_diagram)
	Analyser of ordering diagram that is based on reachability-distances. More...

def	__len__ (self)
	Returns length of clustering-ordering diagram.

def	calculate_connvectivity_radius (self, amount_clusters, maximum_iterations=100)
	Calculates connectivity radius of allocation specified amount of clusters using ordering diagram and marks borders of clusters using indexes of values of ordering diagram. More...

def	extract_cluster_amount (self, radius)
	Obtains amount of clustering that can be allocated by using specified radius for ordering diagram and borders between them. More...

Detailed Description

Analyser of cluster ordering diagram.

Using cluster-ordering it is able to connectivity radius for allocation of specified amount of clusters and calculate amount of clusters using specified connectivity radius. Cluster-ordering is formed by OPTICS algorithm during cluster analysis.

See also: optics

Definition at line 105 of file optics.py.

Constructor & Destructor Documentation

◆ init()

def pyclustering.cluster.optics.ordering_analyser.__init__	(	self,
		ordering_diagram
	)

Analyser of ordering diagram that is based on reachability-distances.

See also: calculate_connvectivity_radius

Definition at line 125 of file optics.py.

Member Function Documentation

◆ calculate_connvectivity_radius()

def pyclustering.cluster.optics.ordering_analyser.calculate_connvectivity_radius	(	self,
		amount_clusters,
		maximum_iterations = `100`
	)

Calculates connectivity radius of allocation specified amount of clusters using ordering diagram and marks borders of clusters using indexes of values of ordering diagram.

Parameter 'maximum_iterations' is used to protect from hanging when it is impossible to allocate specified number of clusters.

Parameters

[in]	amount_clusters	(uint): amount of clusters that should be allocated by calculated connectivity radius.
[in]	maximum_iterations	(uint): maximum number of iteration for searching connectivity radius to allocated specified amount of clusters (by default it is restricted by 100 iterations).

Returns: (double, list) Value of connectivity radius and borders of clusters like (radius, borders), radius may be 'None' as well as borders may be '[]' if connectivity radius hasn't been found for the specified amount of iterations.

Definition at line 143 of file optics.py.

◆ extract_cluster_amount()

def pyclustering.cluster.optics.ordering_analyser.extract_cluster_amount	(	self,
		radius
	)

Obtains amount of clustering that can be allocated by using specified radius for ordering diagram and borders between them.

When growth of reachability-distances is detected than it is considered as a start point of cluster, than pick is detected and after that recession is observed until new growth (that means end of the current cluster and start of a new one) or end of diagram.

Parameters

[in] radius (double): connectivity radius that is used for cluster allocation.

Returns: (unit, list) Amount of clusters that can be allocated by the connectivity radius on ordering diagram and borders between them using indexes from ordering diagram (amount_clusters, border_clusters).

Definition at line 185 of file optics.py.

Referenced by pyclustering.cluster.optics.ordering_analyser.calculate_connvectivity_radius().

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

pyclustering/cluster/optics.py