Skip to content

Latest commit

 

History

History
31 lines (22 loc) · 1.85 KB

README.md

File metadata and controls

31 lines (22 loc) · 1.85 KB
Raw

SBMGraphGenerator

Graph generator with tunable parameters based on the degree-corrected stochastic blockmodel.

Notes:

  • The generator is non-deterministic; it generates a different graph each time it is run.
  • The graph parameters are controlled indirectly; they will not match the inputs exactly.
  • For more extreme graph parameter combinations, the generator may not be able to fit a matching stochastic blockmodel and the generation may fail. Re-running the generator a few times may fix the issue, but for the most part the best solution is to use less extreme parameters.

Requirements:

  • The requirements for running this generator are listed in requirements.txt.
  • All requirements should be installable via pip, but from our experience, the graph-tool package can be tricky to install. The following instructions worked for our system:
conda config --add channels conda-forge
conda config --add channels pkgw-forge
conda install -c pkgw-forge gtk3 
conda install -c vgauthier graph-tool

For more information, refer to the graph-tool installation instructions

Usage:

To generate a graph locally, use python generate.py <args>. Note that generating graphs with more than a few million vertices/edges can take several hours.

!WARNING: EXPERIMENTAL! To generate a graph on a remote system, use python generate.py --remote <remote_url> <args>. The generator uses the Paramiko and getpass packages for authentication. You will need to provide your username and password on the command-line. Systems that do not support a username + password authentication method are not supported.

© Virginia Polytechnic Institute and State University, 2022.

License

Please refer to the included LICENSE file.