I have data that looks similar to these two adjacency matrices:
data1999 <- data.frame(node1=c("A", "A", "B", "D", "B", "C", "D"),
node2=c("A", "A", "D", "B", "B", "C", "D"),
link=c(1, 1, 1, 1, 1, 1, 1),
stringsAsFactors = FALSE)
adj.m1999 <- reshape2::acast(data1999, node1 ~ node2)
> adj.m1999
A B C D
A 2 0 0 0
B 0 1 0 1
C 0 0 1 0
D 0 1 0 1
data2000 <- data.frame(node1=c("A", "A", "B", "C", "D", "C", "D"),
node2=c("A", "A", "B", "C", "D", "D", "C"),
link=c(1, 1, 1, 1, 1, 1, 1),
stringsAsFactors = FALSE)
adj.m2000 <- reshape2::acast(data2000, node1 ~ node2)
> adj.m2000
A B C D
A 2 0 0 0
B 0 1 0 0
C 0 0 1 1
D 0 0 1 1
Note that in 1999, node D and B have a link.
Note that in 2000, node D and C have a link.
Based on this information, I want to construct a new adjacency matrix (with all the nodes of my 2000 data) in which B-D and D-B have a value of 1 while the rest has a zero:
> result
A B C D
A 0 0 0 0
B 0 0 1 0
C 0 1 0 0
D 0 0 0 0
In my real-life data, data 1999 can have additional nodes that don't return in 2000 and vice versa.
Any ideas?
In graph theory, the product of two adjacency matices m1 and m2 gives in position (i,j) the number of ways to go from i to j, going first through m1 then through m2. This is related to what you want but not exactly the same as, if we do
adj.m1999 %*% adj.m2000
, we get:So for example, you can go from C to D in one way, and that would be C -> C, followed by C -> D. In your example, you don't take into account links (or edges) that are on the diagonal, and also your graph is not directed, so, if I understand correctly what you want, you could do: