Reputation: 13510
So I have to adjacency matrices which are numpy 2D arrays and I want to count the number of similar elements between the two. This might sound silly and I know it can be done using a simple for loop but I am wondering if there is a oneliner to do so? Or maybe a faster way of doing it since I am dealing with large matrices. The following code is what I have now:
adj1 = graph1.get_adjacency()
adj2 = graph2.get_adjacency()
count = 0
for i in range(len(adj1)):
for j in range(len(adj1)):
if adj[i][j] == adj[i][j]:
count += 1
Upvotes: 2
Views: 429
Reputation: 76
If you wanted to be able to use the results of comparing adj1 and adj2, I suggest separating this into two lines:
test = np.equal(adj1,adj2)
count = sum(test[test == True])
But this will give you the same result as the accepted answer.
Upvotes: 1
Reputation: 97331
try this:
np.sum(adj1 == adj2)
if the dtype of adj1 and adj2 is float:
np.sum(np.isclose(adj1, adj2))
Upvotes: 3