graph-visualization

What is the difference between D3.js and Cytoscape.js? Why would someone choose Cytoscape over D3.js? D3 is for charts and mostly static graphs. Cytoscape.js lets you manipulate highly-customisable and interactive graphs, and has an API as easy to use as jQuery. D3 is for arbitrary SVG . This means that although it can be used to make lots of different things, you have to build the renderer, interaction, and model yourself. Sometimes that's what you need. (Note SVG tends not to be able to performantly render highly complex scenes with lots of SVG elements, so evaluate your app's requirements

the below snapshot visual is created using the "visNetwork" package. My requirement here is that I have to hard code the edges and also after using visHierarchicalLayout(), I am not able to see them in order, Please help me with a dynamic approach such that no matter how many numbers, I get consecutive numbers in order without hard code. Thanks and please help. library(visNetwork) nodes <- data.frame(id = 1:7, label = 1:7) edges <- data.frame(from = c(1,2,3,4,5,6), to = c(2,3,4,5,6,7)) visNetwork(nodes, edges, width = "100%") %>% visEdges(arrows = "to") %>% visHierarchicalLayout() Using level

Like here , my Prefuse graph is too dense to see anything. So I tried the approach suggested by @bcr in the accepted answer. However, it does not work for me. This is what I tried: I retrieved the default settings. Then I changed the 2nd parameter of NBodyForce from ForceSimulator (called Distance ) and the second parameter of SpringForce (called DefaultSpringLength ) and fed them—along with the other default values—into my new ForceSimulator . But nothing in the output changed. What am I getting wrong? This is my code: private static void visualiseGraph(Graph graph) { Visualization vis = new

I want to truncate text that is over a predefined limit in d3. I'm not sure how to do it. Here's what I have now: node.append("text") .attr("dx", 20) .attr("dy", ".20em") .text(function(d) { if(d.rating > 25) return d.name; })); Text is only displayed if the rating > 25. How can truncate the text of those names? Manoj To truncate text use substring Try this code: DEMO .text(function (d) { if(d.name.length > 5) return d.name.substring(0,5)+'...'; else return d.name; }); 来源： https://stackoverflow.com/questions/21770344/truncate-text-in-d3

I tried to use networkx in python to turn an adjacent matrix into a graph. My "weighted" graph has about 8000 nodes and 14000 edges. Is there a great layout form or other packages, tools to make my graph become more beautiful? I hope the outcome is that the edge weight higher the nodes become closer. So that I could analyze the cluster nodes. I had tried all the layout provided in networkx document. I also tried to use gephi and it still a little bit not satisfied with my ideal. This is how it look in networkx. It can show out all the cluster but it looks a little bit terrible for someone who

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 measure between all column vectors of a matrix. adjMat = cosine(t) r = 3 for(i in 1:numWords) { highElement

I've been looking around for solutions to my question, but nothing does exactly what I want. What I want to do is save a whole JUNG graph (with custom vertex and edge rendering) to an image (PNG or JPEG). When I save the VisualizationViewer to a BufferedImage, it only takes the visible part. I want to save the whole graph, so that's not an option. Does anyone have an idea on how to render my whole graph to an image? Thanks in advance! I finally found the solution to my problem, using a VisualizationImageServer . Here is an example of how to create an image from a whole JUNG graph, for others