How to set inverse edge weights in igraph()

I've adapted the following code, taken from here to display a weighted and undirected network graph:

 # Create data
 set.seed(1)
 data <- matrix(sample(0:3, 25, replace=TRUE), nrow=5)
 data[lower.tri(data)] <- NA
 rownames(data) <- LETTERS[1:5]
 colnames(data) <- LETTERS[1:5]

 # Transform it in a graph format
 network <- graph_from_adjacency_matrix(data, weighted = TRUE)

 # Remove edges with NA weights
 network <- delete_edges(network, E(network)[is.na(E(network)$weight)])

 # Make the graph
 ggraph(network) +
   geom_edge_link(aes(edge_width=E(network)$weight), edge_colour="black", edge_alpha=0.3) +
   geom_node_point(color="#69b3a2", size=5) +
   geom_node_text(aes(label=name), repel = TRUE, size=8, color="#69b3a2") +
   theme_void() +
   theme(
     legend.position="none",
     plot.margin=unit(rep(1,4), "cm")
   )

However, in my case, lower values indicate stronger connections, and so I'm trying to work out how to create a graph where smaller values have thicker edges, i.e. to inverse the values of network$weight. In the example graph here, D>C would have the thickest edge, and A>C the thinnest.

Solution

If all your weights are positive, you could flip the values with a helper function like

flip <- function(x) max(x)-x+1
flip(c(10, 9, 1))
# [1]  1  2 10

and then use that when mapping the edge weights

geom_edge_link(aes(edge_width=flip(weight)), edge_colour="black", edge_alpha=0.3)