igraph

问题 Suppose I have a dataset in R indicating the individuals within groups. Here is an example: grp <- c(1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5) ind <- c("A", "C", "D", "B", "C", "D", "E", "A", "D", "E", "B", "F", "E", "A", "F") data.frame(grp, ind) So, the data look like this: grp ind 1 1 A 2 1 C 3 1 D 4 2 B 5 2 C 6 2 D 7 2 E 8 3 A 9 3 D 10 3 E 11 4 B 12 4 F 13 4 E 14 5 A 15 5 F So, group 1 is composed of individuals (A, C, D), group 2 is composed of individuals (B, C, D, E), and so on. I

问题 I found an example showing how to calculate LCC by hand (see image). How can I replicate these steps in R? Focus is on finding the "Actual number of links among Neighbors" (middle step) I would preferably have to calculate it by hand *Does the igraph package provide this number? Example adjacency matrix: matrix(data = c(0,1,0,1,1,0,0,1,1,1,0,1,1,0,1,0), ncol = 4) 回答1: All of this can be done in igraph . It is nice that you gave an example, but since the graph is fully connected, all vertices

问题 I'm trying to compile an igraph C code in the Visual Studio 2013, already got all libraries included in the properties, just as some examples that come with the distribution of igraph C, but i still got the following problems in the output window: 1>igraph.lib(prpack.obj) : error LNK2001: unresolved external symbol "public: __thiscall prpack::prpack_base_graph::~prpack_base_graph(void)" (??1prpack_base_graph@prpack@@QAE@XZ) 1>igraph.lib(prpack.obj) : error LNK2001: unresolved external symbol

问题 I would like to use igraph to explore some network data. My data have this structure: a <- c(13, 32, NA, NA) b <- c(32, NA, NA, NA) c <- c(34, 13, 32, NA) d <- c(5, NA, NA, NA) net <- rbind(a, b, c, d) First column: focal subject id From 2 to 4 columns: receivers from focal subject In the plot, subject 5 should be isolated. library(reshape) library(igraph) net <- as.data.frame(net) mdata <- melt(net, id=c("V1")) g <- graph.data.frame(mdata[,c(1,3)]) Warning message: In graph.data.frame(mdata[

问题 I have a dataframe like this: 1 2 2 3 4 5 .... Now, I plot this graph in R using the library igraph using the following code: wt=read.table("NP7.txt") wt1=matrix(nrow=nrow(wt), ncol=2) wt1=data.frame(wt1) wt1[,1:2]=wt[,1:2] write.table(wt1,"test.txt") library(igraph) wt=read.table("test.txt") wg7 <- graph.edgelist(cbind(as.character(wt$X1), as.character(wt$X2)), directed=F) sum(clusters(wg7)$csize>2) plot(wg7) a <- largest.clique(wg7) Now, on running this code I get the plot of the graph and

问题 Using R,I try to calculate Betweenness centrality for about 1 million nodes and more than 20 million edges. To do so I have a pretty decent machine with 128GB ram and 4*2.40GHz CPU and a 64bit windows. Yet, using betweeness() of Igraph takes ages. I am wondering is there any quick solution? would it be faster, if I use Gephi?! 来源： https://stackoverflow.com/questions/21718078/betweenness-centrality-for-relatively-large-scale-data

问题 Drawing a graph with R and igraph, I'm using color to label vertex type. See code below. Is it possible to fill vertices with a pattern rather than a color so that the node types are distinguishable when viewed in color AND black and white? I need 4 unique colors/patterns. The only palette from colorbrewer that fits is this one: http://colorbrewer2.org/#type=sequential&scheme=OrRd&n=4 However, for my sparse graph, its still difficult to differentiate the colors. Also, I'm color blind, which

问题 It seems no such questions has ever been asked in SO. However, the help page of igraph on customizing node shapes is rather vague. Can someone provide a complete example of customizing node shape in igraph ? 回答1: You do not say what language you use, so I am going to respond in R. The shapes that are built-in can be listed with shapes() . Unfortunately, ellipse is not among them. The help page ?shapes gives a few examples of how to add additional node shapes - a triangle, a star and adding an

问题 I have been having trouble with this. I can only get one or the other but not both options in one graph. Below is the code and I received a lot of help from @lukeA to get me to this point. I have the following graph in which I can get the cluster colors into the visNetwork Igraph : library(igraph) library(visNetwork) B = matrix( c(1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 47, 3, 0, 3, 0, 1, 10, 13, 5, 0, 3, 19, 0, 1, 0, 1, 7, 3, 1, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 3, 1, 0, 32, 0, 0, 3, 2, 1, 0, 0, 0,

问题 I want to reshape a data frame by combining two variables. For example: Here is a new data: dat = data.frame( var1 = c("a", "a", "a", "Emily", "b", "Bob", "c"), var2 = c("Jhon", "Emily", "Julie", "Angela", "Bob", "Paul", "Paul"), stringsAsFactors = F ) Excepted output: # var1 var2 var3 var4 var5 # 1 a Jhon Emily Julie Angela # 2 b Bob Paul c <NA> 回答1: Using base R you can do: relation=function(dat){ .relation=function(x){ k = unique(sort(c(dat[dat[, 1] %in% x, 2], x, dat[dat[, 2] %in% x, 1]))