infoTheoreticLabeledV2: V2 information functional for vertex-labeled graphs

In QuACN: QuACN: Quantitative Analysis of Complex Networks

Description

This method assigns a probability value to each vertex of the network using the V2 information functional for vertex-labeled graphs. It is based on the same principles as infoTheoreticGCM.

Usage

infoTheoreticLabeledV2(g, ci=NULL, lambda=1000)

Arguments

g	a graph as a graphNEL object. Each vertex must have an "atom" data attribute specifying its atomic number or chemical symbol.
ci	a list (or named vector) mapping each chemical symbol to a coefficient value. If not specified, 1 will be used for all elements.
lambda	specifies the scaling constant for the distance measures. The default value is 1000.

Details

For details see the vignette.

Value

The returned list consists of the following items:

entropy	contains the calculated entropy measure.
distance	contains the calculated distance measure.
pis	contains the calculated probability distribution.
fvi	contains the calculated values of the functional for each vertex.

Author(s)

Michael Schutte

References

M. Dehmer, N. Barbarini, K. Varmuza, and A. Graber. Novel topological descriptors for analyzing biological networks. BMC Structural Biology, 10:18, 2010.

Examples

set.seed(987)
g <- randomEGraph(as.character(1:10), 0.3)

nodeDataDefaults(g, "atom") <- "C"
nodeData(g, "2", "atom") <- "O"

infoTheoreticLabeledV2(g, ci=list(`C` = 0.5, `O` = 0.8))

QuACN documentation built on May 2, 2019, 5:46 p.m.