sygnet 0.0.1

Synthetic data using Generative Adversarial Networks

SyGNet

Synthetic data using Generative Adversarial Networks

Principal Investigator: Dr Thomas Robinson ([e-mail])

Research team: Artem Nesterov, Maksim Zubok

sygnet is a Python package for generating synthetic data within social science contexts. The sygnet algorithm uses cutting-edge advances in deep learning methods to learn the underlying relationships between variables in a dataset. Users can then generate brand-new, synthetic observations that mimic the real data.

Installation

To install via pip, you can run the following command at the command line: pip install sygnet

sygnet requires:

numpy>=1.20
torch>=1.11.0
scikit-learn>=1.0
pandas>=1.4
datetime
tqdm

Version 0.0.1 (Alpha release)

Our first release! This version has been lightly tested and the core functionality has been implemented. You should expect both functionality and architecture to change considerably. Comments and bug reports are very welcome!