--- title: "Getting started with rgexf" author: "George G. Vega Yon" date: "August 11, 2021" output: rmarkdown::html_vignette vignette: > %\VignetteIndexEntry{rgexf} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} --- ```{r setup, echo=FALSE} knitr::opts_chunk$set(fig.width = 7) ``` # Introduction The `rgexf` package provides a way to interact with [GEXF files](http://gexf.net/format/). The GEXF standard was developed by the [Gephi](https://gephi.org/)--"Like Photoshop for graphs"--core team, and can be used to save static and dynamic networks. With the `rgexf` package, users can create `gexf` (R) objects from scratch, import GEXF files, coerce `gexf` objects into `igraph` objects, and visualize graphs using the [`gexf-js` JavaScript library](https://github.com/raphv/gexf-js). In this vignette, we will illustrate how can we (a) import a GEXF file into R and visualize it with `igraph,` and (b) create a `gexf` object from scratch. # Reading GEXF files The `rgexf` package comes with a network from Les Misérables, which is featured in Gephi. To read GEXF files, we can use the `read.gexf` function: ```{r read-gexf} # Loading rgexf library(rgexf) # Accessing the path of the file fn <- system.file( "gexf-graphs/lesmiserables.gexf", package = "rgexf" ) lesmi <- read.gexf(fn) # Taking a look at the first handful of nodes and edges head(lesmi) ``` Moreover, we can directly plot the graph using the `plot.gexf` method--through the `gexf-js` library--or coercing it into an `igraph` object and use igraph's plotting engine: ```{r igraph-plot} lesmi_ig <- gexf.to.igraph(lesmi) lesmi_ig op <- par(mai = rep(0, 4)) # For extra space plot(lesmi_ig) par(op) ``` We can also go back: ```{r go-back} head(igraph.to.gexf(lesmi_ig)) ``` Using the `plot.gexf` method--which uses the `gexf-js` JavaScript library--results in a Web visualization of the graph, like this: ```r plot(g) ``` ```{r gexf-js, echo = FALSE} knitr::include_graphics(path = system.file("gexf-graphs/lesmiserables.png", package="rgexf")) ``` An live version of the figure is available [here](https://gvegayon.github.io/rgexf/lesmiserables/). # Creating GEXF files This example was extracted directly from the demo "gexfrandom." Here we create three networks with the same set of vertices and layout, we color them and finalize plotting it with igraph. ```{r} # Random graph demo set.seed(11) ``` Creating the vertices: ```{r} # Vertex n <- 30 prb <- .3 vertex1 <- data.frame(id = 1:n, label = 1:n) vertex2 <- data.frame(id = (n + 1):(2 * n), label = (n + 1):(2 * n)) vertex3 <- data.frame( id = (2 * n + 1):(3 * n), label = (2 * n + 1):(3 * n) ) ``` Building edges: ```{r} # Edges edges1 <- combn(vertex1$label, 2) edges1 <- edges1[, which(runif(ncol(edges1)) > (1 - prb))] edges1 <- data.frame(source = edges1[1, ], target = edges1[2, ]) edges2 <- combn(vertex2$label, 2) edges2 <- edges2[, which(runif(ncol(edges2)) > (1 - prb))] edges2 <- data.frame(source = edges2[1, ], target = edges2[2, ]) edges3 <- combn(vertex3$label, 2) edges3 <- edges3[, which(runif(ncol(edges3)) > (1 - prb))] edges3 <- data.frame(source = edges3[1, ], target = edges3[2, ]) ``` We can and add visual attributes: ```{r} # Visual attributes size <- runif(n, max = 100) color <- terrain.colors(n) color <- color[order(runif(n))][1:n] color <- cbind(t(col2rgb(color)), 1) color2 <- heat.colors(n) color2 <- color2[order(runif(n))][1:n] color2 <- cbind(t(col2rgb(color2)), 1) color3 <- topo.colors(n) color3 <- color3[order(runif(n))][1:n] color3 <- cbind(t(col2rgb(color3)), 1) ``` Generating a layout: ```{r} # Nice layout pos <- matrix(0, nrow = n, ncol = 3) for (i in 2:n) { pos[i, 1] <- pos[i - 1, 1] + cos(2 * pi * (i * 1.7 - 1) / n) pos[i, 2] <- pos[i - 1, 2] + sin(2 * pi * (i - 1) / n) } pos <- pos / (max(pos) - min(pos)) pos2 <- pos pos2[, 1] <- pos2[, 1] + max(pos2[, 1]) - min(pos[, 1]) pos3 <- pos pos3[, 1] <- pos3[, 1] + max(pos2[, 1]) - min(pos[, 1]) ``` And finally, we can build the `gexf` object: ```{r} graph <- gexf( rbind(vertex1, vertex2, vertex3), rbind(edges1, edges2, edges3), nodesVizAtt = list( size = c(size, size, size), color = rbind(color, color2, color3), position = rbind(pos, pos2, pos3) ) ) # Taking a quick look head(graph) ``` As before, we can either directly call the plot function for `gexf` objects, or coerce it into an `igraph` object: ```{r igraph-plot-2} # plot(graph) op <- par(mai = rep(0, 4)) # For extra space plot(gexf.to.igraph(graph)) par(op) ```