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...arwin8.6.0 attached base packages: [1] "tcltk" "methods" "stats" "graphics" "grDevices" "utils" "datasets" "base" other attached packages: igraph "0.1.2" > g <- graph.ring(10) > tkplot(g) Loading required package: tcltk Loading Tcl/Tk interface ... done [1] 1 ******************************************************************** An X window appears, and the graph can be interactively manipulated, as intended. But in JGR: **********************************************************...

Dear r-help, I create a graph of my baysian network. I use the package igraph. The names of vertex are within the circle, I would leave them outside the circle? > E(g)$color <- "black" > tkplot(g, ,vertex.label=names,layout=layout.kamada.kawai, edge.color=E(g)$color) Best Regards [[alternative HTML version deleted]]

...## suppose I have 100 gene (nodes) ## --------------------------------------------------------------------------- graph <- set.vertex.attribute(graph, "color", value=c(rep(c('green','red'),50))) graph <- set.vertex.attribute(graph, "name", value=genelist) tkplot(graph) ---------------------------------------------------------------------------- The 'color' attribute does work, the nodes are red and green, but the 'name' attribute doesn't work, I still have the numeric id on each node (0-99). Can anyone tell me how to solve this problem...

I have a number of (directed) graphs based on social groups, where the members have expresed likes and dislikes in respect to the other members. tkgraph makes it simple to draw the graphs in a very pleasing way, but I would like to differentiate between positive and negative relations in the graph by having the edges for the negative relations dashed and the positive ones continuous. Is

Hi, I have network data in the form of a couple of edgelists containing weights in the format "x,y,weight" whereby x represents row header and y represents column header. All edgelists are based on links among 634 nodes and I need to convert them into a 634*634 weighted matrix. I searched for online help using possible keywords I know, but I could not find a clue how to do this in

Hello, I am working with graph and adjacency matrix, the package 'graph' seems to be appropriate for this. An example in the package > mat <- rbind(c(0, 0, 1, 1), + c(0, 0, 1, 1), + c(1, 1, 0, 1), + c(1, 1, 1, 0)) > rownames(mat) <- colnames(mat) <- letters[1:4] > graph1 <- new("graphAM", adjMat=mat) > graph1 A

Hey, all. I'm looking for packages that are good at two things 1) Drawing directed graphs (i.e nodes and edges), both with single and double headed arrows, as well as allowing for differences in line width and solid versus dashed. Note: I've tried Rgraphviz here, but have run into some problems (which seem fixable and I may go with it in the end), and it doesn't satisfy need

Dear R users, I am trying to draw a network using igraph package. I intend to place the hub nodes (the ones with the relatively more connection with other nodes) in the center of the graph. Also, the graph need to be in the fashion that the higher the correlation between two nodes is , the closer the two nodes will be. Is there any layout that can help or any other way to do this? Thanks in

Hi folks, On R > install.packages("TeachingDemos", dependencies=TRUE) ...... installing to /usr/local/lib/R/site-library/mapproj/libs ** R ** inst ** preparing package for lazy loading ** help *** installing help indices ** building package indices ... ** testing if installed package can be loaded * DONE (mapproj) The downloaded packages are in

Hello all, I'm having a spot of trouble. I have made a very nice distance matrix from some comparison calculations. However, the matrix is 3096 x 3096, so it's relatively large. Currently I'm using the svn package as it seems to work for my data. The graph package errors and says the "adjacency matrix must be symmetric for undirected graphs". I though 3096 x 3096 was

...thm is now supported by the shortest path finder. It allows negative edge weight, but not negative cycles. See ?shortest.paths. - The graph.knn function was added to calculate the average nearest neighbor degree. It supports edge weights as well. - Curved edges are now supported by plot() and tkplot(), see ?igraph.plotting for the details. - Many bugs and memory leaks were fixed, see the News section on the igraph homepage for details. NEW FEATURES IN THE 0.5.1 VERSION - DrL layout generator was added, see ?layout.drl. - Uniform sampling of graphs with a given degree sequence, see ?deg...

...thm is now supported by the shortest path finder. It allows negative edge weight, but not negative cycles. See ?shortest.paths. - The graph.knn function was added to calculate the average nearest neighbor degree. It supports edge weights as well. - Curved edges are now supported by plot() and tkplot(), see ?igraph.plotting for the details. - Many bugs and memory leaks were fixed, see the News section on the igraph homepage for details. NEW FEATURES IN THE 0.5.1 VERSION - DrL layout generator was added, see ?layout.drl. - Uniform sampling of graphs with a given degree sequence, see ?deg...