Graph Statistics in Python is a package for graph statistical algorithms.
A graph, or network, provides a mathematically intuitive representation of data with some sort of relationship between items. For example, a social network can be represented as a graph by considering all participants in the social network as nodes, with connections representing whether each pair of individuals in the network are friends with one another. Naively, one might apply traditional statistical techniques to a graph, which neglects the spatial arrangement of nodes within the network and is not utilizing all of the information present in the graph. In this package, we provide utilities and algorithms designed for the processing and analysis of graphs with specialized graph statistical algorithms.
The official documentation with usage is at https://graspy.neurodata.io/
GraSPy package requires only a standard computer with enough RAM to support the in-memory operations.
This package is supported for Linux and macOS. The package has been tested on the following systems:
- Linux: Ubuntu 16.04
- macOS: Mojave (10.14.1)
- Windows: 10
This package is written for Python3. Currently, it is supported for Python 3.5, 3.6, and 3.7.
GraSPy mainly depends on the Python scientific stack.
networkx numpy scikit-learn scipy seaborn
Install from pip
pip install graspy
Install from Github
git clone https://github.com/neurodata/graspy cd graspy python3 setup.py install
Please visit the tutorial section in the official website
This project is covered under the Apache 2.0 License.