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## [igraph] representation large networks with edge and nodes features

 From: Leonardo Mazzoni Subject: [igraph] representation large networks with edge and nodes features Date: Fri, 01 Jun 2018 11:40:56 +0200 User-agent: webmail UniFI

```Hi everybody,
I need to represent a large matrix with the following features.
```
It is a symmetric 562x562 matrix composed by decimal values that goes from 0 to 1 and I would like to represent its maximum spanning tree (with the function mst, weighting for the negative values) with the following features:
```
```
1) assign quantitative attributes to nodes, shaping their size (setting a scale) and creating the correspondent legend 2) assign qualitative attributes to nodes, defining their colour (setting correspondent category) and creating the correspondent legend
```
Then, the representation of my networks should be like these:
```
a) represent first a graph with the chacateristics of point 1 and 2 with the edge values (that go from 0 to 1) with only the values bigger than a certain threshold of relationship (e.g. bigger than 0.3); b) represent a second graph with the chacateristics of point 1 and 2 with all the edge values, assigning diverse colours to diverse level of intensity of the relationship (from 0.1 to 0.2, from 0.2 to 0.3,etc..).
```
```
I tried to do something, but I stopped, looking at the incomprehensible graph that I produced..
```I forward my first attempt to do it with i-graph:

```
g <- graph_from_adjacency_matrix(foo, mode = "upper", weighted = T, diag = F)
```max_spann_tree <- mst(g, weights = -E(g)\$weight)
```
plot.igraph(max_spann_tree,vertex.label=V(net)\$name, vertex.attibutes=V(net), edge.color="grey",vertex.color="red",edge.attributes=E(g)\$weight,layout=layout.spring)
```
Any suggestions to do it in igraph?
```
In the attachment there is a picture of the Product Space by Hidalgo et al. (2007), that is more or less the picture I would like to get.
```https://www.google.com/search?q=the+product+space+hidalgo&client=firefox-b-ab&source=lnms&tbm=isch&sa=X&ved=0ahUKEwjOiNu5lbLbAhWIcRQKHV5VCSIQ_AUICigB&biw=1366&bih=654#imgrc=FeSyfj9wjHcVnM: