Release Notes: GraSPy 0.2

We're happy to announce the release of GraSPy 0.2! GraSPy is a Python package for understanding the properties of random graphs that arise from modern datasets, such as social networks and brain networks.

For more information, please visit our website and our tutorials.


This release is the result of over 8 months of work with over 25 pull requests by 10 contributors. Highlights include:

  • Added AutoGMMCluster in cluster submodule. AutoGMMCluster is Python equivalent to mclust in R.
  • Added subgraph submodule, which detects vertices that maximally correlates to given features.
  • Added match submodule. Used for matching vertices from a pair of graphs with unknown vertex correspondence.
  • Added functions for simulating a pair of correlated ER and SBM graphs.


  • Diagonal augmentation is default behavior in AdjacencySpectralEmbed.
  • Added functionality in to_laplace to allow for directed graphs.
  • Updated docstrings.
  • Updated documentation website.
  • Various bug fixes.

API Changes

  • Added **kwargs argument for heatmap.



Contributors to this release