I am trying to visualize graphs in R with the igraph package. I wish to visualize graphs with the edge size being between 2000 to 70,000. The plots look like this:
This is not a nice plot as you cannot see anything. I have figured out how to take away the labels, but still you cannot see anything since the vertices are so big.
Can I remove the vertices and just look at the edges?
For example here is the same plot but I took the picture before it was finished. It seems that R only draws the edges before it is finished:
You can set the vertex size to 0.
library(igraph)
g <- barabasi.game(100)
plot( g, vertex.size=0, vertex.label=NA, edge.arrow.size=0 )
Related
I am automatically generating graphs whose nodes need to be in fixed positions. For example:
There is actually an arc from node V4 to node V16, but we annot see it because there are also arcs from V4 to V10 and from V10 to V16.
Note that both the nodes and the arcs are generated automatically, and that the positions may vary, so I would need an automated way to curve arcs that are hidden behind other arcs.
Also note that none of these solutions are valid: igraph: Resolving tight overlapping nodes ; Using igraph, how to force curvature when arrows point in opposite directions. The first one simply places de nodes in a certain way, but my nodes need to be fixed. The second one simply deals with pairs of nodes that have two arcs connecting them going in the opposite direction.
UPDATE: The construction of the graph is the result of the learning process of the graph that forms a Bayesian Network using bnlearn library, so I am not very sure how could I produce a reproducible example. The positions of the nodes are fixed because they represent positions. I actually need some magic, some kind of detection of overlapping arcs: If two arcs overlap, curve one of them slightly so that it can be seen. I know from the linked questions that curving an arc is an option, so I thought maybe this kind of magic could be achieved
One solution would be to use the qgraph package. In the example below it automatically curves the bidirectional edges:
library(igraph)
library(qgraph)
# the raster layout
layout <- cbind(1:3, rep(1:3, each = 3))
# fully connected network
adj <- matrix(1, 9, 9)
# plot directed and undirected network
layout(matrix(1:2, 1, 2))
qgraph(adj, layout = layout, directed = FALSE, title = "undirected")
qgraph(adj, layout = layout, directed = TRUE, title = "directed") # automatically curves the bidirectional arrows
To convert an igraph object to something qgraph can use, all you need is an edgelist or adjacency matrix:
g <- make_ring(9)
edgeList <- do.call(rbind, igraph::get.adjedgelist(g))
qgraph(edgeList)
If you also want to include the axes, you can do so using axis() since qgraph uses base graphics. However, you probably have to tinker with par() as well to make it look nice.
We have an non square adjacency matrix p (197x190)matrix without weights (only 1 if the 2 telephone numbers have called with each other and 0 otherwise). We tried to visualize this with a graph using this simple code and the igraph package:
p<-as.matrix(dcast(SNA_data, A_NUMBER~B_NUMBER, value.var="W", fill=0))[,]
graph<-graph.adjacency(p, mode="undirected", weighted=NULL)
plot(graph)
The result is a very small graph in plot that is totally unreadable graph anybody knows how to solve this?
Thanks in advance.
Try to use x11() to plot your graph in an external window :
library(igraph)
adjm1<-matrix(sample(0:1,1000,replace=TRUE,prob=c(0.9,01)),nc=10)
g1<-graph.adjacency(adjm1)
x11()
plot(g1)
Reference for the simulation : using graph.adjacency() in R
If your matrix is not a square, it might be worth trying an incidence matrix. By default the matrix is directed from rows to columns.
# create the network object
network <- graph_from_incidence_matrix(p)
network
class(network)
# plot it
plot(network)
I want to create a graph plot with each community of nodes been covered by some background color, similar to the graph by the following code
karate <- graph.famous("Zachary")
wc <- walktrap.community(karate)
modularity(wc)
membership(wc)
plot(wc, karate)
But different from this approach, I want to: (1) group the nodes by myself, instead of resulting from community detection algorithm. I achieved this by wc$membership <- some_vector; (2) plot such graph possibly with overlap between communities, then how can I assign one node to multiple communities?
Plot the graph itself instead of the community structure, and use an appropriately constructed mark.groups argument to plot() to tell igraph which groups should be enclosed by the same group. The following quote is from the manual page of plot.igraph:
mark.groups: A list of vertex id vectors. It is interpreted as a set of vertex groups. Each vertex group is highlighted, by plotting a colored smoothed polygon around and "under" it.
I want to analyse a social network using the R packages statnet and/or igraph in reference to force-directed graph drawing (kamada.kawai/fruchterman.reingold). I wounder, if it is possible to adjust the "force" between 2 specific nodes, e.g. to consider a larger or smaller cooperation between 2 stakeholders. However, i do not want to edit the general force between all nodes
(as proposed here:)
How do I lengthen edges in an igraph network plot (layout=fruchterman.reingold)?
The idea on this would be to get a more realistic image of a social network, also for further analysis.
Thanks a lot and nice weekend to everybody!
This layout algorithm supports edge weights, which are basically used as multipliers for the attraction forces along the edges. I.e. edges with high weight will tend to be shorter. Here is a simple example
library(igraph)
g <- graph.ring(10)
# Edge weights, will be recycled
E(g)$weight <- c(1,4)
coords <- layout.fruchterman.reingold(g, weights=E(g)$weight)
# Eliminate the margin
par(mar=c(0,0,0,0))
plot(g, layout=coords, vertex.color="#E495A5", vertex.size=20)
I am working with graphs in R. I am currently using igraph and I would like to be able to plot bidirectional edges "reciprocal edges" of a graph. So far I've seen it is possible to plot "bidirectional" graphs but not reciprocal edges, for example: E(1,3) and E(3,1) could potentially be represented as a bidirectional edge <-->, but instead I would like to plot two parallel edges one pointing to the opposite direction of the other || .
There exist in Rgraphviz an option when plotting "plot(rEG, recipEdges = "distinct")" that makes this, but I like more how plots look like on igraph. Thanks in advance.
In igraph, you can use the edge attribute curved to curve the edges you want.
For example, here is a graph based small adjacency matrix:
library("igraph")
adj <- matrix(c(
0,1,1,
1,0,1,
0,0,0),3,3,byrow=TRUE)
library("igraph")
G <- graph.adjacency(adj)
The edge between node 0 and 1 is bidirected (Actually, it isn't, it are two edges and they just look like a bidirected edge because they are straight).:
plot(G)
To change this, we can use the edgelist:
E <- t(apply(get.edgelist(G),1,sort))
E(G)$curved <- 0
E(G)[duplicated(E) | duplicated(E,fromLast =TRUE)]$curved <- 0.2
plot(G)
Another option is my package, where this is the default behavior:
library("qgraph")
qgraph(adj)
which can be suppressed with the bidirectional argument.
Try plot(graph, edge.curved=TRUE). It definitely works in igraph 0.6, and it may also work in igraph 0.5.4 (not sure when it was added).