GraSPy

Graph Statistics in Python is a package for graph statistical algorithms.

• Overview
• Documentation
• System Requirements
• Installation Guide
• Tutorials
• License
• Issues

Overview

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.

Documenation

The official documentation with usage is at https://graspy.neurodata.io/

System Requirements

Hardware requirements

GraSPy package requires only a standard computer with enough RAM to support the in-memory operations.

Software requirements

OS Requirements

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

Python Requirements

This package is written for Python3. Currently, it is supported for Python 3.5, 3.6, and 3.7.

Python Dependencies

GraSPy mainly depends on the Python scientific stack.

networkx
numpy
scikit-learn
scipy
seaborn

Installation Guide

Install from pip

pip install graspy

Install from Github

git clone https://github.com/neurodata/graspy
cd graspy
python3 setup.py install

Tutorials

Please visit the tutorial section in the official website

License

This project is covered under the Apache 2.0 License.