(original) (raw)

## ----g1, message=FALSE, warning=FALSE----------------------------------------- library(graph) set.seed(123) g1 = randomEGraph(LETTERS[1:15], edges = 100) g1 ## ----simplefuns, message=FALSE, warning=FALSE--------------------------------- nodes(g1) degree(g1) adj(g1, "A") acc(g1, c("E", "G")) ## ----subG, message=FALSE, warning=FALSE--------------------------------------- sg1 = subGraph(c("A", "E", "F", "L"), g1) boundary(sg1, g1) edges(sg1) edgeWeights(sg1) ## ----example1, message=FALSE, warning=FALSE----------------------------------- V <- LETTERS[1:4] edL1 <- vector("list", length = 4) names(edL1) <- V for (i in 1:4) edL1[[i]] <- list(edges = c(2, 1, 4, 3)[i], weights = sqrt(i)) gR <- graphNEL(nodes = V, edgeL = edL1) edL2 <- vector("list", length = 4) names(edL2) <- V for (i in 1:4) edL2[[i]] <- list(edges = c(2, 1, 2, 1)[i], weights = sqrt(i)) gR2 <- graphNEL(nodes = V, edgeL = edL2, edgemode = "directed") ## ----addNodes, message=FALSE, warning=FALSE----------------------------------- gX = addNode(c("E", "F"), gR) gX gX2 = addEdge(c("E", "F", "F"), c("A", "D", "E"), gX, c(1, 2, 3)) gX2 gR3 = combineNodes(c("A", "B"), gR, "W") gR3 clearNode("A", gX) ## ----combine, message=FALSE, warning=FALSE------------------------------------ ##find the underlying graph ugraph(gR2) ## ----unions, message=FALSE, warning=FALSE------------------------------------- set.seed(123) gR3 <- randomGraph(LETTERS[1:4], M <- 1:2, p = .5) x1 <- intersection(gR, gR3) x1 x2 <- union(gR, gR3) x2 x3 <- complement(gR) x3 ## ----randomEGraph, message=FALSE, warning=FALSE------------------------------- set.seed(333) V = letters[1:12] g1 = randomEGraph(V, .1) g1 g2 = randomEGraph(V, edges = 20) g2 ## ----randomGraph, message=FALSE, warning=FALSE-------------------------------- set.seed(23) V <- LETTERS[1:20] M <- 1:4 g1 <- randomGraph(V, M, .2) ## ----randomNodeGraph, eval = FALSE-------------------------------------------- # set.seed(123) # c1 <- c(1,1,2,4) # names(c1) <- letters[1:4] # g1 <- randomNodeGraph(c1) ## ----rGraph, message=FALSE, warning=FALSE------------------------------------- g1 g1cc <- connComp(g1) g1cc g1.sub <- subGraph(g1cc[[1]], g1) g1.sub ## ----dfs, message=FALSE, warning=FALSE---------------------------------------- DFS(gX2, "E") ## ----clusterGraph, message=FALSE, warning=FALSE------------------------------- cG1 <- new("clusterGraph", clusters = list(a = c(1, 2, 3), b = c(4, 5, 6))) cG1 acc(cG1, c("1", "2")) ## ----distanceGraph, message=FALSE, warning=FALSE------------------------------ set.seed(123) x <- rnorm(26) names(x) <- letters library(stats) d1 <- dist(x) g1 <- new("distGraph", Dist = d1) g1