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postProcessDensOpt

Density Optimization


Description

Implementation of the density optimization algorithm as a post processing algorithm.

Usage

postProcessDensOpt(dyncomm,Parameters)

Arguments

dyncomm

a DynCom post processing algorithm. See DynCommPostProcess

Parameters

A two column matrix defining the parameters for this algorithm. See the PARAMETERS section on this page

Details

Is an algorithm that provides a community structure, not explicitly based on modularity, but based on the increase of the average community density. Contrary to modularity-based algorithms, it tends to disband large communities into smaller ones. It is an algorithm currently developed for directed networks only.

Value

postProcessDensOpt object

Performance

Initialization

Uses a matrix with three columns and a maximum of verticelAll()^2 rows with the edges between vertices and their weight (vertex<->vertex<->weight) of the original graph. Temporarily stores a copy of the graph to calculate a new community mapping.

Results

Uses a matrix with two columns and verticesAll() rows with the new community mapping (vertex<->community). Uses a matrix with three columns and a maximum of communityCount()^2+communityCount() rows with the edges between communities and their weight (community<->community<->weight).

Methods

results(differential)

Get additional results of the algorithm or the currently selected post processing steps. See results

quality()

Get the quality measurement of the graph after the last iteration. See quality

communityCount()

Get the number of communities after the last iteration. See communityCount

communities()

Get all communities after the last iteration. See communities

communitiesEdgeCount()

Get the number of community to community edges in the graph. See communitiesEdgeCount

communityNeighbours(community)

Get the neighbours of the given community after the last iteration. See communityNeighbours

communityInnerEdgesWeight(community)

Get the sum of weights of the inner edges of the given community after the last iteration. See communityInnerEdgesWeight

communityTotalWeight(community)

Get the sum of weights of all edges of the given community after the last iteration. See communityTotalWeight

communityEdgeWeight(source,destination)

Get the weight of the edge that goes from source to destination after the last iteration. See communityEdgeWeight

communityVertexCount(community)

Get the amount of vertices in the given community after the last iteration. See communityVertexCount

community(vertex)

Get the community of the given vertex after the last iteration. See community

vertexCount()

Get the total number of vertices after the last iteration. See vertexCount

verticesAll()

Get all vertices in the graph after the last iteration. See verticesAll

neighbours(vertex)

Get the neighbours of the given vertex after the last iteration. See neighbours

edgeWeight(source,destination)

Get the weight of the edge that goes from source vertex to destination vertex after the last iteration. See edgeWeight

vertices(community)

Get all vertices belonging to the given community after the last iteration. See vertices

communityMapping()

Get the community mapping for all communities after the last iteration.See communityMapping

communityMapping()

Get the community mapping for all communities after the last iteration.See communityMapping

Author(s)

poltergeist0

Examples

## Not run: 
Parameters<-matrix(c("-e","0.1"),1,2,TRUE)
dc<-DynCommMain(ALGORITHM$LOUVAIN,CRITERION$MODULARITY,Parameters)
dc$addRemoveEdgesFile("initial_graph.txt")
dc$communityCount()
dc$communities()
dc$communityNodeCount(1)
dc$vertices(1)
dc$communityMapping(TRUE)
dc$time()
dc$addRemoveEdgesFile("s0000000000.txt")

## End(Not run)

DynComm

Dynamic Network Communities Detection and Generation

v2020.1.6
GPL-2
Authors
Rui P. Sarmento [aut, cre] (<https://orcid.org/0000-0003-1891-5295>), Luís Lemos [aut], Mário Cordeiro [ctb], Giulio Rossetti [ctb]
Initial release

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