Hi, Tamas!
First of all, thank you for your answer, it is very useful.
After your message I tried to recreate your result so I made two Erdos-Renyi graph (both with 1.2 million vertices and 5.1 million edges) but the first one was directed and the second one was undirected. I made a label_prop clustering on these graphs which method can handle directed graphs as well. In the first case the Rgui freezed out, but in the second case the community detection was done in less than 5 minutes. So, it looks like the comm. det. algorithms can't handle the big directed graphs.
After this I wanted to try this experiment in a Python enviroment and then another problem poped up. In Phyton, after installing the igraph package I tried to import igraph and I got an error message which advised me to use jgraph but in the jgraph package there are no any graph methods or functions.
Do you have any idea what is wrong with the Python igraph package or what I should do to recreate the experiment in Python?
I tried to install igraph from the source provided by Christoph Gohlke but the same happened.
- Phyton version: 3.5.1 Anaconda 2.4.1 (64-bit), MSC v1900 64-bit (AMD-64)
- 16 Gbyte RAM
- win10 64-bit
- Igraph 0.1.11
Thx and best regards,
Adam