neurodata/graspy: GraSPy 0.3

Announcement: GraSPy 0.3

We're happy to announce the release of GraSPy 0.3! 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 5 months of work with over 11 pull requests by 7 contributors. Highlights include:

• Added seeded graph matching as a capability for graph matching, renamed graph matching class to GraphMatch
• Added functions for simulating a pair of correlated RDPG graphs.
• Deprecated Python 3.5
• Added different backend hypothesis tests for the LatentDistributionTest from Hyppo
• Added a correction to make LatentDistributionTest valid for differently sized graphs

• Updated default value of rescale in RDPG simulation
• Updated default value of scaled in MASE estimation
• Improved error throwing in AutoGMM
• Clarified the API for inference submodule

• FastApproximateQAP was renamed to GraphMatch
• fit method of LatentDistributionTest and LatentPositionTest now returns self instead of a p-value

• Python 3.5

• Jaewon Chung
• Benjamin Pedigo
• Ali Saad-Eldin
• Shan Qiu
• Bijan Varjavand
• Anton Alyakin (new contributor!)
• Casey Weiner (new contributor!)