Rgraphviz test

## Settings for RMarkdown http://yihui.name/knitr/options#chunk_options
opts_chunk$set(comment = "", warning = FALSE, message = FALSE, tidy = FALSE, 
    echo = T, fig.width = 5, fig.height = 5)
options(width = 125, scipen = 5, digits = 5)

setwd("~/statistics/Rmedstats/")

Reference

• Manual: http://mae.ucdavis.edu/dsouza/Lectures/Rgraphviz.pdf

Different layout methods

library("Rgraphviz")
set.seed(123)
V <- letters[1:10]
M <- 1:4
g1 <- randomGraph(V, M, 0.2)

## dot
plot(g1)

## neato
plot(g1, "neato")

## twopi
plot(g1, "twopi")

Reciprocated edges

rEG <- new("graphNEL", nodes = c("A", "B"), edgemode = "directed")
plot(rEG)

rEG <- addEdge("A", "B", rEG, 1)
plot(rEG)

rEG <- addEdge("B", "A", rEG, 1)
plot(rEG)

plot(rEG, recipEdges = "distinct")

Cluster graphs

cG <- new("clusterGraph",
          clusters = list(
              a = c(1:10), b = c(11:13),
              c = c(14:20), d = c(21, 22))
          )
plot(cG)

Causal diagram like

causal1 <- new(Class = "graphNEL", nodes = c("L", "A", "Y"), edgemode = "directed")
causal1 <- addEdge(from = "A", to = "Y", graph = causal1, weight = 2)
causal1 <- addEdge(from = "L", to = "A", graph = causal1, weight = 2)
causal1 <- addEdge(from = "L", to = "Y", graph = causal1, weight = 2)
plot(causal1)

causal1 <- new(Class = “track”, nodes = c(“L”, “A”, “Y”), edgemode = “directed”)
causal1 <- addEdge(from = “A”, to = “Y”, graph = causal1, weight = 2)
causal1 <- addEdge(from = “L”, to = “A”, graph = causal1, weight = 2)
causal1 <- addEdge(from = “L”, to = “Y”, graph = causal1, weight = 2)
plot(causal1)