sparksee.CommunitiesSCD Class Reference

CommunitiesSCD class. More...

Inheritance diagram for sparksee.CommunitiesSCD:

Inheritance graph
Collaboration diagram for sparksee.CommunitiesSCD:

Collaboration graph

List of all members.

Public Member Functions

def add_node_type
 Allows connectivity through nodes of the given type.
def add_edge_type
 Allows connectivity through edges of the given type.
def add_all_node_types
 Allows connectivity through all node types of the graph.
def add_all_edge_types
 Allows connectivity through all edge types of the graph.
def __init__
 Creates a new instance of CommunitiesSCD.
def exclude_nodes
 Set which nodes can't be used.
def run
 Executes the algorithm.
def set_materialized_attribute
 Creates a new common attribute type for all node types in the graph in order to store, persistently, the results related to the disjoint communities found while executing this algorithm.
def get_communities
 Returns the results generated by the execution of the algorithm.
def exclude_edges
 Set which edges can't be used.
def set_look_ahead
 Sets the size of the lookahead iterations to look.
def is_closed
 Gets if CommunityDetection has been closed or not.
def close
 Closes the CommunityDetection instance.


Detailed Description

CommunitiesSCD class.

Implementation of the community detection algorithm "Scalable Community Detection" based on the paper "High quality, scalable and parallel community detection for large real graphs" by Arnau Prat-Perez, David Dominguez-Sal, Josep-Lluis Larriba-Pey - WWW 2014.

The purpose of this algorithm is to find disjoint communities in an undirected graph or in a directed graph which will be considered as an undirected one.

It is possible to set some restrictions after constructing a new instance of this class and before running it in order to limit the results.

After the execution, we can retrieve the results stored in an instance of the DisjointCommunities class using the getCommunities method.

Check out the 'Algorithms' section in the SPARKSEE User Manual for more details on this.

Author:
Sparsity Technologies http://www.sparsity-technologies.com

Member Function Documentation

def sparksee.CommunitiesSCD.add_node_type (   self,
  type 
)

Allows connectivity through nodes of the given type.

Parameters:
type null

Reimplemented from sparksee.DisjointCommunityDetection.

def sparksee.CommunitiesSCD.add_edge_type (   self,
  type 
)

Allows connectivity through edges of the given type.

The edges can be used in Any direction.

Parameters:
type [in] Edge type.

Reimplemented from sparksee.DisjointCommunityDetection.

def sparksee.CommunitiesSCD.add_all_edge_types (   self  ) 

Allows connectivity through all edge types of the graph.

The edges can be used in Any direction.

Reimplemented from sparksee.DisjointCommunityDetection.

def sparksee.CommunitiesSCD.__init__ (   self,
  session 
)

Creates a new instance of CommunitiesSCD.

After creating this instance is required to indicate the set of edge types and the set of node types which will be navigated through while traversing the graph in order to find the communities.

Parameters:
session [in] Session to get the graph from and calculate the communities

def sparksee.CommunitiesSCD.exclude_nodes (   self,
  nodes 
)

Set which nodes can't be used.

This will replace any previously specified set of excluded nodes. Should only be used to exclude the usage of specific nodes from allowed node types because it's less efficient than not allowing a node type.

Parameters:
nodes [in] A set of node identifiers that must be kept intact until the destruction of the class.

Reimplemented from sparksee.DisjointCommunityDetection.

def sparksee.CommunitiesSCD.set_materialized_attribute (   self,
  attributeName 
)

Creates a new common attribute type for all node types in the graph in order to store, persistently, the results related to the disjoint communities found while executing this algorithm.

Whenever the user wants to retrieve the results, even when the graph has been closed and opened again, it is only necessary to create a new instance of the class DisjointCommunities indicating the graph and the name of the common attribute type which stores the results. This instance will have all the information related to the disjoint communities found in the moment of the execution of the algorithm that stored this data.

It is possible to run the algorithm without specifying this parameter in order to avoid materializing the results of the execution.

Parameters:
attributeName [in] The name of the common attribute type for all node types in the graph which will store persistently the results generated by the execution of the algorithm.

Reimplemented from sparksee.DisjointCommunityDetection.

def sparksee.CommunitiesSCD.get_communities (   self  ) 

Returns the results generated by the execution of the algorithm.

These results contain information related to the disjoint communities found as the number of different components, the set of nodes contained in each component or many other data.

Returns:
Returns an instance of the class DisjointCommunities which contain information related to the disjoint communities found.

Reimplemented from sparksee.DisjointCommunityDetection.

def sparksee.CommunitiesSCD.exclude_edges (   self,
  edges 
)

Set which edges can't be used.

This will replace any previously specified set of excluded edges. Should only be used to exclude the usage of specific edges from allowed edge types because it's less efficient than not allowing an edge type.

Parameters:
edges [in] A set of edge identifiers that must be kept intact until the destruction of the class.

Reimplemented from sparksee.DisjointCommunityDetection.

def sparksee.CommunitiesSCD.set_look_ahead (   self,
  lookahead 
)

Sets the size of the lookahead iterations to look.

Parameters:
lookahead [in] Number of iterations. It must be positive or zero.

def sparksee.CommunityDetection.is_closed (   self  )  [inherited]

Gets if CommunityDetection has been closed or not.

See also:
close()
Returns:
TRUE if the CommunityDetection instance has been closed, FALSE otherwise.

def sparksee.CommunityDetection.close (   self  )  [inherited]

Closes the CommunityDetection instance.

It must be called to ensure the integrity of all data.


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