similar to: igraph: Turn multiple edges into weights

Hello, I am trying to implement a formula aij= transition from state S_i to S_j/no of transition at state S_i Code I have written is working with three state {1,2,3 }, but if the number of states become={1,2,3,4,......n} then the code will not work, so can some help me with this. For and some rows of my data frame look like

Hi, I think you overthought this one a little bit, I don't know if this is the kind of code you are expecting but I came up with something like that: generate_transition_matrix <- function(data, n_states) { #To be sure I imagine you should check n_states is right at this point transitions <- matrix(0, n_states, n_states) #we could improve a little bit here because at

Hi, So I've been figuring out how to use igraph in R and like it for it's speed and simplicity. Now I have a graph built from an edgelist where vectors have a $name attribute. I have another dataframe with attributes tied to a vector ID, which is the same as the $name attribute of vectors represented in the graph. How can I iterate over the graph by V(g)$name and do

Hello: I have been looking into projects that will automatically restrict hacking attempts on my servers running CentOS 5. I think the two top contenders are: DenyHosts - http://denyhosts.sourceforge.net Fail2ban - http://www.fail2ban.org >From what I see, DenyHosts only blocks based on failed SSH attempts whereas Fail2ban blocks failed attempts for other access as well. The main benefit

Dear colleagues, I have extracted the dates of several news stories from a newspaper data base to chart coverage trends of an issue over time. They are in a data frame that looks just like one generated by the reproducible code below. I can already generate a histogram of the dates with various intervals (months, quarters, weeks years) using hist.Date. However, there are two other

Hi R-users, I have a data set like this (first ten rows): id patient_id date code class eala ID1564262 1562 6.4.2006 12:00 5555 1 NA ID1564262 1562 6.4.2006 12:00 5555 1 NA ID1564264 1365 14.2.2006 14:35 5555 1 50 ID1564265 1342 7.4.2006 14:30 2222 2 50 ID1564266 1648 7.4.200614:30 2222 2 50 ID1564267 1263 10.2.2006 15:45 2222 2 10 ID1564267 1263 10.2.200615:45 3333 3 10 ID1564269 5646

Dear colleagues, I'm trying to have a look at the Assortative and Disassortative ( http://en.wikipedia.org/wiki/Assortative_mixing) of the network I have. But it seems that the igraph hasn't mentioned that yet. I have to get the in/out degree of the vertices of each edge and calculate the Pearson's Correlation coefficient which seems to be quite a huge task for me. :( So I wonder if

I'm stuck on a seemingly simple problem. I'm trying to subset the data by several numbers and it cuts out half of the rows. Here is the sample code: test <- as.matrix(c(1,1,1,1,3,3,7,7,7,7)) Count <- tapply(test[,1], test[,1], length) # count for each value spp <- unique(test[,1]) Count1 <- as.data.frame(cbind(Count,spp)) Max <- max(Count) Count1$sppMax <-

Hi, I have two data sets look like below: ========================== state count1 percent1 CA 19 0.34 TX 22 0.35 FL 11 0.24 OR 34 0.42 GA 52 0.62 MN 12 0.17 NC 19 0.34 state count2 percent2 FL 22 0.35 MN 22 0.35 CA 11 0.24 TX 52 0.62 ========================== How to combine these two data set and make it look like below?

Hello All, I have been trying to do bonpow for a while now.Bonpow works for few graphs and for few others it goes out of memory. I did see reply to one of the posting Alph Centrality Crashed in Igraph memory error. The solution in the posting was to use sparse matrix. This is the link of the message. http://lists.gnu.org/archive/html/igraph-help/2008-04/msg00071.html I was able to obtain

#I have a dataset with two factor. I want to combine those factors into a single factor and count the number of data values for each new factor. The following gives a comparable dataframe: a <- rep(c("a", "b"), c(6,6)) b <- rep(c("c", "d"), c(6,6)) df <- data.frame(f1=a, f2=b, d=rnorm(12)) df # I use the 'interaction' function to combine

I have inconsistent directory listing on share mounted on linux from windows 2k. Some time not all files appear in the directory listing. If reading directory listing multiple times (60-200 times) files listed originally would have one or two files missing in one of consecutive lists. The same problem appear as well if you are making backup of Windows files from multiple directories, there are

I have a graph with edge and vertex weights, stored in two data frames: --8<---------------cut here---------------start------------->8--- vertices <- data.frame(vertex=c("a","b","c","d"),weight=c(1,2,1,3)) edges <-

Hi, Does anyone know of a package in R that has a function to convert network data (e.g. an adjacency matrix or ) from 2-mode to 1-mode? I am conducting social network analysis. I know that Pajek has this function under Net --> Transform --> 2-mode to 1-mode --> Rows. I have searched the documentation under packages 'sna', 'network', 'igraph', and

Hi to all, I have this dataframe (I show the first six rows) >head(table) A R Fold.Change P.Value Count1 Count2 1 ENSRNOE00000000002_at 0 1.13 0.60 1 1 2 ENSRNOE00000000009_at 0 -1.04 0.73 3 3 3 ENSRNOE00000000020_at 0 -1.08

I am having trouble plotting one of my graphs (think graph theory graph with edges and vertices, not scatterplots or histograms). For some pairs of vertices, I want multiple edges to be visible in my graph. As an example of this, in my script below, I want two edges to be visible from vertex 1 and vertex 9 (among some others) yet when I plot it, only one edge is visible.

I am using the code below to output some network measures: central_social <- data.frame(V(s641_social)$name, indegree_social, outdegree_social, incloseness_social, outcloseness_social, betweenness_social, eigen_social) and I get the following error: Error in Re(z) : non-numeric argument to function I know this has to do with V but I cannot figure out what is wrong. s641-social is a graph

Hi, I'm working on some social networks and I managed to create the graphs with labels and edges weight, but I would also like to change the size of the vertices according to the age of the persons in the network and the shape according to the gender. Now for the age, I have people with ages between 20 and 78, and I would like to have 4 categories (sizes): 20-35, 36-50, 50-65, >65. I have

R-users, I have been using R for about 1 year, and I have run across a couple of graphics problem that I am not quite sure how to address. I have read up on the email threads regarding the differences between density and relative frequencies (count/sum(count) on the R list, and I am hoping that someone could provide me with some advice/comments concerning my approach. I will admit

I am getting some unexpected results from some functions of igraph and it is possible that I am misinterpreting the vertex numbers. Eg., the max betweenness measure seems to be from a vertex that is not connected to a single other vertex. Below if my code snippet: require(igraph) my.graph <- graph.adjacency(adjmatrix = my.adj.matrix, mode=c("undirected")) most.between.vert <-