DynComm
Provides a single interface for all algorithms in the different languages.
DynComm(Algorithm,Criterion,Parameters)
Includes methods to get results of processing and to interact with the vertices, edges and communities. Provided methods to return information on the graph are divided into two layers. A lower level layer that interacts with vertices and how they connect. And a higher level layer that interacts with communities and how they connect. Besides the main algorithm, also accepts post processing algorithms that are used mainly to filter the results. Post processing algorithms can use additional computational resources so check the Performance section of the help page of each algorithm you intend to use.
DynComm object
A two column matrix defining additional parameters to be passed to the selected ALGORITHM and CRITERION. The first column names the parameter and the second defines its value.
Owsinski-Zadrozny quality function parameter. Values [0.0:1.0]. Default: 0.5
Shi-Malik quality function kappa_min value. Value > 0 . Default 1
Treat graph as weighted. In other words, do not ignore weights for edges that define them when inserting edges in the graph. A weight of exactly zero removes the edge instead of inserting so its weight is never ignored. Without this parameter defined or for edges that do not have a weight defined, edges are assigned the default value of 1 (one). As an example, reading from a file may define weights (a third column) for some edges (defined in rows, one per row) and not for others. With this parameter defined, the edges that have weights that are not exactly zero, have their weight replaced by the default value. Values TRUE,FALSE. Default FALSE
Stops when, on a cycle of the algorithm, the quality is increased by less than the value given in this parameter. Value > 0 . Default 0.01
Community-Vertex.
Boolean parameter that indicates if sending community mapping to a file
prints the community first, if true, or the vertex first, if false. See
communityMapping for details.
Default TRUE
Set a list of post processing steps. See postProcess
Select between getting the results of the algorithm or one of the post
processing steps. See select
Get additional results of the algorithm or the currently selected post
processing steps. See results
Add and remove edges read from a matrix or file. See addRemoveEdges
Alias for addRemoveEdges(). See addRemoveEdges
Alias for addRemoveEdges(). See addRemoveEdges
Get the quality measurement of the graph after the last iteration.
See quality
Get the number of communities after the last iteration.
See communityCount
Get all communities after the last iteration. See communities
Get the number of community to community edges in the graph. See communitiesEdgeCount
Get the neighbours of the given community after the last iteration.
See communityNeighbours
Get the sum of weights of the inner edges of the given community after
the last iteration. See communityInnerEdgesWeight
Get the sum of weights of all edges of the given community after the
last iteration. See communityTotalWeight
Get the weight of the edge that goes from source community to destination
community after the last iteration. See communityEdgeWeight
Get the amount of vertices in the given community after the last
iteration. See communityVertexCount
Alias for communityVertexCount(). See communityVertexCount
Get the community of the given vertex after the last iteration.
See community
Get the total number of vertices after the last iteration. See vertexCount
Alias for vertexCount(). See vertexCount
Get all vertices in the graph after the last iteration. See verticesAll
Alias for verticesAll(). See verticesAll
Get the neighbours of the given vertex after the last iteration. See neighbours
Get the weight of the edge that goes from source vertex to destination
vertex after the last iteration. See edgeWeight
Alias for edgeWeight(). See edgeWeight
Get all vertices belonging to the given community after the last iteration.
See vertices
Alias for vertices(community). See vertices
Get the number of vertex to vertex edges in the graph. See edgeCount
Get the community mapping for all communities after the last iteration.
See communityMapping
Get the cumulative time spent on processing after the last iteration.
See time
Get the source code versions of the different sources.
See version
poltergeist0
Parameters<-matrix(c("e","0.1","w", "FALSE"),ncol=2, byrow=TRUE)
dc<-DynComm(ALGORITHM$LOUVAIN,CRITERION$MODULARITY,Parameters)
dc$addRemoveEdges(
matrix(
c(10,20,10,30,20,30,30,60,40,60,40,50,50,70,60,70)
,ncol=2,byrow=TRUE)
)
## or
## dc$addRemoveEdges("initial_graph.txt")
dc$communityCount()
## You can use the non inline version of the functions
DynComm.communities(dc)
## Several alias have been defined.
## In this case, communityNodeCount is alias of communityVertexCount
dc$communityNodeCount(10)
dc$communityNeighbours(10)
dc$communityInnerEdgesWeight(10)
dc$communityTotalWeight(10)
dc$communityEdgeWeight(10,40)
dc$community(10) ##this parameter is a vertex not a community. Do not confuse them
dc$vertices(10)
dc$communityMapping(TRUE)
dc$quality()
dc$time()
## lets add post processing :)
dc$postProcess(
list(
list(POSTPROCESSING$DENSOPT)
)
)
## the results of the last step of post processing are selected automatically
## densopt post processing algorithm may change the community mapping so...
## check it
dc$communityMapping(TRUE)
## densopt post processing algorithm may change quality so check it
dc$quality()
## time is now the total time of the main algorithm plus the time of every...
## post processing algorithm up to the one selected
dc$time()
## get back to main algorithm results to check they haven't changed
dc$select(POSTPROCESSING$NONE)
dc$communityMapping(TRUE)
dc$quality()
dc$time()
## add and remove edges. Notice that there is one more column to give...
## weights of zero on the edges to remove. In this case, all other weights...
## are ignored because the graph is set to ignore weights (parameter w is...
## false).
dc$addRemoveEdges(
matrix(
c(30,60,0,40,60,0.23,10,80,2342,80,90,3.1415)
,ncol=3,byrow=TRUE)
)
## since the post processing was not reset, it will be automatically...
## calculated and results switched to the last step. In this case, to the...
## densopt algorithm
dc$communityMapping(TRUE)
dc$quality()
dc$time()
## get back to main algorithm results to check them
dc$select(POSTPROCESSING$NONE)
dc$communityMapping(TRUE)
dc$quality()
dc$time()
## lets reset/remove post processing
dc$postProcess()Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.