get edge between two node set
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Hamid Salari
el 10 de Ag. de 2017
Comentada: Hamid Salari
el 10 de Ag. de 2017
hi . i have a undirected graph with n nodes and two sets of node . A = [1 2 3 4] , B = [5 6 7 8] . there is no common member in this two set . how should i get number of edges between this two set ? something like :
findedge(G,[1 2 3 4],[5 6 7 8]) ;
p.s: the find edge gives me some unreal answer : it says [3;382;1839] that cant be true ! 4*4 nodes at last can have 16 edges between . and i tested and those numbers is not the edges index of existed edges between two set .
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Alex Karle
el 10 de Ag. de 2017
Hi Hamid,
I wrote some code that should solve this problem for you. The details of the code are commented:
% Let us take this graph as our example
s = [1 1 1 1 2 1 2 2 3 3 4 5 5 6 7];
t = [2 4 8 3 4 6 3 7 4 6 5 6 8 7 8];
G = graph(s,t);
plot(G)
% Let us say A = [1,2,3,4], B = [5,6,7,8]
A = [1,2,3,4];
B = [5,6,7,8];
% One way to do this is the following:
% Assuming this is an unweighted graph, then the adjacency matrix will have a '1'
% in row 'i' col 'j' if there is an edge 'i' <-> 'j', else there will be a '0'
adj_matrix = adjacency(G)
% Note that this is a sparse matrix, so it may not look like a normal matrix, but we can still use
% matrix indexing on it!
% adj_matrix(A,B) is equal to adj_matrix([1,2,3,4],[5,6,7,8]), creates a new matrix where the only
% elements are those that start in A and end in B. Thus, to find the number of edges between A and B
% we simply need to find the sum of all the '1's in this subsection of the adj_matrix, which can be
% done with a sum(sum(adj_matrix(A,B))
count = sum(sum(adj_matrix(A,B)))
If you want more information about the functions used, I would recommend looking at the MATLAB documentation:
The reason why "findedge(G,[1 2 3 4],[5 6 7 8])" does not return the desired result is because findedge looks for pairs of edges, like the following:
findedge(G,[1,2],[3,4],[5,6])
This will look for edges between 1 and 2, 3 and 4, and 5 and 6 as three seperate queries about the edges of the graph. For more documentation on the usage of findedge, look here: findedge.
Hope this helps!
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