igraph

问题 I'm trying to use "gspan" algorithm using R. I installed and loaded igraph . But when I call "gspan", I get this error: > results = subdue(graph1); Error in library(igraph0) : there is no package called ‘igraph0’ Could any one give me a solution, thanks in advance. 回答1: From the CRAN repo: Package ‘igraph0’ was removed from the CRAN repository. Formerly available versions can be obtained from the archive. This was a transitional package from Mar 2012 to Sept 2013. Packages depending on it

问题 I am starting to use the package called visNetwork and I feel like it has a ton of potential for User-Interface use in the future. There are few things that I am having trouble with though. I have created an igraph and have also applied a clustering algorithm to that specifically the fastgreedy algorithm. Example Code Provided: 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

问题 I'm trying to create a tree graph, and since the "father" has a lot of "children" I'd like it to be a very wide graph. Therefore, I tried to resize the window with the windows option and set margins to zero width in order to have a wide graph. These are my program lines: windows(heigth=7, width=14, record=TRUE, rescale="fit") par(mar=c(1,0,1,0), omi=c(0,0,0,0), oma=c(0,0,0,0)) plot(graph_name,layout=layout.reingold.tilford(tree)) I get a wide device window but the plot is in the middle and

问题 Trying to find communities in tweet data. The cosine similarity between different words forms the adjacency matrix. Then, I created graph out of that adjacency matrix. Visualization of the graph is the task here: # Document Term Matrix dtm = DocumentTermMatrix(tweets) ### adjust threshold here dtms = removeSparseTerms(dtm, 0.998) dim(dtms) # cosine similarity matrix t = as.matrix(dtms) # comparing two word feature vectors #cosine(t[,"yesterday"], t[,"yet"]) numWords = dim(t)[2] # cosine

问题 I am trying to implement a "Minimum Cost Network Flow" transportation problem solution in R . I understand that this could be implemented from scratch using something like lpSolve . However, I see that there is a convenient igraph implementation for "Maximum Flow". Such a pre-existing solution would be a lot more convenient, but I can't find an equivalent function for Minimum Cost. Is there an igraph function that calculates Minimum Cost Network Flow solutions, or is there a way to apply the

问题 I'm working with igraph for R. My graph is based on an edgelist which includes parallel edges (more than one edge with the same source and target). I would like to convert these parallel edges to an edge attribute weight. Is there an eay way to do this? If there is no easy way. how can I identify these parallel edges? duplicated(E(net)) does not return a single duplicate. I suppose its looking for duplicated edge ids. 回答1: You can also use E(graph)$weight <- 1 followed by simplify(graph, edge

问题 I would like to detect overlapping communities in small networks/graphs. By overlapping, I mean that a node can be included within more than one communities/clusters in the output of the detection algorithm. I have looked at various community detection algorithms curretly provided by igraph , but I think none of them handles overlapping communities. Ideally, I would like to be able to programmatically utilize some implementation of such algorithm(s) in Python. However, implementation in other

问题 I would like to display the parsing (POS tagging) from openNLP as a tree structure visualization. Below I provide the parse tree from openNLP but I can not plot as a visual tree common to Python's parsing. install.packages( "http://datacube.wu.ac.at/src/contrib/openNLPmodels.en_1.5-1.tar.gz", repos=NULL, type="source" ) library(NLP) library(openNLP) x <- 'Scroll bar does not work the best either.' s <- as.String(x) ## Annotators sent_token_annotator <- Maxent_Sent_Token_Annotator() word_token

问题 I have some c code that utilizes the igraph library. I would like to put an R wrapper around it and send it off to CRAN as an R package. igraph already has an R port on CRAN, so it would make sense for my R package 'foo' to depend on R's igraph. Since foo uses its own C code that depends on the C igraph, how can I link my C functions to the original igraph library? I've read that this is done in a file called Makevars, but linking to an external library is very hairy. If this isn't possible,

问题 How do I plot a network of type bipartite in R? Similar to this: I have similar data but with weights for both genes and diseases and SARS. This network is an example. I have different kind of attributes. I followed a link here. But due to my little knowledge in this topic, I could not get much out of it. Thanks in advance for any help. 回答1: From the ?bipartite_graph help: Bipartite graphs have a type vertex attribute in igraph, this is boolean and FALSE for the vertices of the first kind and