igraph creating a weighted adjacency matrix

Question

I'm trying to use the igraph package to draw a (sparse) weighted graph. I currently have an adjacency matrix, but cannot get the graph.adjacency function to recognise the edge weights.

Consider the following random symmetric matrix:

m <- read.table(row.names=1, header=TRUE, text=
"           A          B          C          D           E         F
A 0.00000000  0.0000000  0.0000000  0.0000000  0.05119703 1.3431599
B 0.00000000  0.0000000 -0.6088082  0.4016954  0.00000000 0.6132168
C 0.00000000 -0.6088082  0.0000000  0.0000000 -0.63295415 0.0000000
D 0.00000000  0.4016954  0.0000000  0.0000000 -0.29831267 0.0000000
E 0.05119703  0.0000000 -0.6329541 -0.2983127  0.00000000 0.1562458
F 1.34315990  0.6132168  0.0000000  0.0000000  0.15624584 0.0000000")
m <- as.matrix(m)

To plot, first I must get this adjacency matrix into the proper igraph format. This should be relatively simple with graph.adjacency. According to my reading of the documentation for graph.adjacency, I should do the following:

library(igraph)
ig <- graph.adjacency(m, mode="undirected", weighted=TRUE)

However, it doesn't recognise the edge weights:

str(ig)
# IGRAPH UNW- 6 8 -- 
# + attr: name (v/c), weight (e/n)
# + edges (vertex names):
# [1] A--E A--F B--C B--D B--F C--E D--E E--F
plot(ig)

How do I get igraph to recognise the edge weights?

Answer 1

The weights are there, weight (e/n) means that there is an edge attribute called weight, and it is numeric. See ?print.igraph. But they are not plotted by default, you need to add them as edge.label.

plot(ig, edge.label=round(E(ig)$weight, 3))

For plotting, make sure you read ?igraph.plotting.

Answer 2

@TWL's solution can be easily generalized to represent edges' width as a function of the weights, including negative weights. The trick is to translate all weights by summing the value of the smallest weight (plus optionally an offset that represents the width of the minimum weight). For example:

# reproducible example:
set.seed(12345)
a <- matrix(runif(5*5, min=-10, max=10), ncol=5)
diag(a) <- 0 # remove loops.
>a
           [,1]       [,2]      [,3]       [,4]       [,5]
[1,]  0.0000000 -6.6725643 -9.309291 -0.7501069 -0.9254385
[2,]  7.5154639  0.0000000 -6.952530 -2.2371204 -3.4649518
[3,]  5.2196466  0.1844867  0.000000 -1.9502972  9.3083065
[4,]  7.7224913  4.5541051 -9.977268  0.0000000  4.1496375
[5,] -0.8703808  9.7947388 -2.175933  9.0331751  0.0000000

# create igraph object.
g <- graph.adjacency(a, mode="undirected", weighted=TRUE)
plot(g)

# assign edge's width as a function of weights.
E(g)$width <- E(g)$weight + min(E(g)$weight) + 1 # offset=1
plot(g)