Graph Statistics in Python (graspologic)

Simple, flexible and powerful graph analysis library grounded in statistical theories.

Graspologic offers scikit-learn compliant APIs and it provides clear feedback upon user error.

Graspologic is open-source and commercially usable software, and released under MIT License.

Graspologic was formerly known as GraSPy, and is now co-developed with Microsoft Research.

  1. J. Arroyo, A. Athreya, J. Cape, G. Chen, C. E. Priebe, and J. T. Vogelstein. Inference for Multiple Heterogenous Networks with a Common Invariant Subspace. Journal of Machine Learning Research, (142)22:1-49, 2021.
  2. H. Helm, J. V. Vogelstein, and C. E. Priebe. Vertex Classification on Weighted Networks. arXiv, 2019.
  3. J. Chung, B. D. Pedigo, E. W. Bridgeford, B. K. Varjavand, and J. T. Vogelstein. GraSPy: Graph Statistics in Python. Journal of Machine Learning Research, (158)20:1–7, 2019.
  4. C. E. Priebe, Y. Park, J. T. Vogelstein, J. M. Conroy, V. Lyzinski, M. Tang, A. Athreya, J. Cape, and E. Bridgeford. On a two-truths phenomenon in spectral graph clustering. Proceedings of the National Academy of Sciences of the United States of America, (13)116:5995–6000, 2019.
  5. A. Athreya, D. E. Fishkind, M. Tang, C. E. Priebe, Y. Park, J. T. Vogelstein, K. Levin, V. Lyzinski, Y. Qin, and D. L. Sussman. Statistical Inference on Random Dot Product Graphs: a Survey. Journal of Machine Learning Research, 2018.
  6. C. E. Priebe, D. L. Sussman, M. Tang, and J. T. Vogelstein. Statistical Inference on Errorfully Observed Graphs. Journal of Computational and Graphical Statistics, (4)24:930–953, 2015.
  7. L. Chen, J. T. Vogelstein, V. Lyzinski, and C. E. Priebe. A Joint Graph Inference Case Study: the C.elegans Chemical and Electrical Connectomes. Worm, 2015.
  8. C. E. Priebe, J. Vogelstein, and D. Bock. Optimizing the quantity/quality trade-off in connectome inference. Communications in Statistics - Theory and Methods, (19)42:3455–3462, 2013.
  9. D. E. Fishkind, D. L. Sussman, M. Tang, J. T. Vogelstein, and C. E. Priebe. Consistent adjacency-spectral partitioning for the stochastic block model when the model parameters are unknown. SIAM Journal on Matrix Analysis and Applications, (1)34:23–39, 2012.
  10. J. T. Vogelstein, R. J. Vogelstein, and C. E. Priebe. Are mental properties supervenient on brain properties? Scientific Reports, 2011.