SparkseeNet  5.2.0
Public Member Functions | List of all members
com.sparsity.sparksee.algorithms.CommunitiesSCD Class Reference

CommunitiesSCD class. More...

Inheritance diagram for com.sparsity.sparksee.algorithms.CommunitiesSCD:
Inheritance graph
Collaboration diagram for com.sparsity.sparksee.algorithms.CommunitiesSCD:
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Public Member Functions

void AddNodeType (int type)
 Allows connectivity through nodes of the given type. More...
 
void AddEdgeType (int type)
 Allows connectivity through edges of the given type. More...
 
void AddAllNodeTypes ()
 Allows connectivity through all node types of the graph.
 
void AddAllEdgeTypes ()
 Allows connectivity through all edge types of the graph. More...
 
 CommunitiesSCD (com.sparsity.sparksee.gdb.Session session)
 Creates a new instance of CommunitiesSCD. More...
 
void ExcludeNodes (com.sparsity.sparksee.gdb.Objects nodes)
 Set which nodes can't be used. More...
 
void Run ()
 Executes the algorithm.
 
void SetMaterializedAttribute (System.String 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. More...
 
com.sparsity.sparksee.algorithms.DisjointCommunities GetCommunities ()
 Returns the results generated by the execution of the algorithm. More...
 
void ExcludeEdges (com.sparsity.sparksee.gdb.Objects edges)
 Set which edges can't be used. More...
 
void SetLookAhead (int lookahead)
 Sets the size of the lookahead iterations to look. More...
 
boolean IsClosed ()
 Gets if CommunityDetection instance has been closed or not. More...
 
void Close ()
 Closes the CommunityDetection instance. More...
 

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

Constructor & Destructor Documentation

com.sparsity.sparksee.algorithms.CommunitiesSCD.CommunitiesSCD ( com.sparsity.sparksee.gdb.Session  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

Member Function Documentation

void com.sparsity.sparksee.algorithms.CommunitiesSCD.AddAllEdgeTypes ( )

Allows connectivity through all edge types of the graph.

The edges can be used in Any direction.

void com.sparsity.sparksee.algorithms.CommunitiesSCD.AddEdgeType ( int  type)

Allows connectivity through edges of the given type.

The edges can be used in Any direction.

Parameters
type[in] Edge type.
void com.sparsity.sparksee.algorithms.CommunitiesSCD.AddNodeType ( int  type)

Allows connectivity through nodes of the given type.

Parameters
typenull
void com.sparsity.sparksee.algorithms.CommunityDetection.Close ( )
inherited

Closes the CommunityDetection instance.

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

void com.sparsity.sparksee.algorithms.CommunitiesSCD.ExcludeEdges ( com.sparsity.sparksee.gdb.Objects  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.
void com.sparsity.sparksee.algorithms.CommunitiesSCD.ExcludeNodes ( com.sparsity.sparksee.gdb.Objects  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.
com.sparsity.sparksee.algorithms.DisjointCommunities com.sparsity.sparksee.algorithms.CommunitiesSCD.GetCommunities ( )

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.
boolean com.sparsity.sparksee.algorithms.CommunityDetection.IsClosed ( )
inherited

Gets if CommunityDetection instance has been closed or not.

See Also
Close()
Returns
TRUE if the CommunityDetection instance has been closed, FALSE otherwise.
void com.sparsity.sparksee.algorithms.CommunitiesSCD.SetLookAhead ( int  lookahead)

Sets the size of the lookahead iterations to look.

Parameters
lookahead[in] Number of iterations. It must be positive or zero.
void com.sparsity.sparksee.algorithms.CommunitiesSCD.SetMaterializedAttribute ( System.String  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.