Map additional variables (nodes) to a graph object

The function insert additional nodes to a graph object. Among the node types, additional source or sink nodes can be added. Regarding the former, source nodes can represent: (i) data variables; (ii) a group variable; (iii) Latent Variables (LV). For the latter, an outcome variable, representing the prediction of interest, can be added. Moreover, mapGraph() can also create a new graph object starting from a compact symbolic formula.

mapGraph(graph, type = "outcome", LV = NULL, f = NULL, ...)

Arguments

graph: An igraph object.
type: A character value specifying the type of mapping. Five types can be specified. If type = "source" is specified, an additional source node (or more) is added to the graph. If type = "group", an additional group source node is added. If type = "outcome" (default), a prediction sink node is mapped to the graph. If type = "LV", a LV source node is included (where the number of LV depends on the LV argument). If type = "clusterLV", a series of clusters for the data are computed and a different LV source node is added separately for each cluster.
LV: The number of LV source nodes to add to the graph. This argument needs to be specified when type = "LV". When type = "clusterLV" the LV number is defined internally equal to the number of clusters. (default = NULL).
f: A formula object (default = NULL). A new graph object is created according to the specified formula object.
...: Currently ignored.

Value

mapGraph returns invisibly the graphical object with the mapped node variables.

Author

Mario Grassi mario.grassi@unipv.it

Examples


# Load Amyotrophic Lateral Sclerosis (ALS)
ig<- alsData$graph; gplot(ig)


# ... map source nodes to ALS graph 
ig1 <- mapGraph(ig, type = "source"); gplot(ig1, l="dot")


# ... map group source node to ALS graph 
ig2 <- mapGraph(ig, type = "group"); gplot(ig2, l="fdp")


# ... map outcome sink to ALS graph 
ig3 <- mapGraph(ig, type = "outcome"); gplot(ig3, l="dot")


# ... map LV source nodes to ALS graph 
ig4 <- mapGraph(ig, type = "LV", LV = 3); gplot(ig4, l="fdp")


# ... map LV source nodes to the clusters of ALS graph 
ig5 <- mapGraph(ig, type = "clusterLV"); gplot(ig5, l="dot")
#> modularity = 0.5588502 
#> 
#> Community sizes
#>  3  1  4  2 
#>  4  8  9 11 
#> 


# ... create a new graph with the formula variables
formula <- as.formula("z4747 ~ z1432 + z5603 + z5630")
ig6 <- mapGraph(f=formula); gplot(ig6)