On 05.02.2011 06:21, William Tu wrote:
Dear R users, I'm using graph library to create a mesh-like network topology and implement a load balance routing algorithm. The current implementation uses graph, RBGL, and Rgraphviz libraries. I have a few attributes on every edge to represent the network loading and capacity, and I frequently update these values. However, I found it works so slow and right now I'm consider rewriting it using C or Python. Then I found another library, which is "igraph". I made a performance comparison between "graph" and "igraph" as below. For both graph, I create two attributes for each edge and set/get the value of all edges and measure the total elapsed time. A. using graph package: 108 nodes, 832 edges: 17 sec 140 nodes, 4800 edges: 576 sec B. using igraph package: 100 nodes, 4950 edges: 4 sec 200 nodes, 19900 edges: 111 sec igraph is much much faster than graph! Is this reasonable? or I did something wrong?
Calculating graphs efficiently is not a trivial task and you can optimize for different szenarios. Unless you doubt about the accuracy of results, I would not be worried about a factor of 5 in different implementations.
Uwe Ligges
ps. I'm using 2 core 3GHz CPU with 2G ram. Thanks in advance, William ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
