regain 0.0.2

REGAIN (Regularised Graph Inference)

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# regain Regularised graph inference across multiple time stamps, considering the influence of latent variables. It inherits functionalities from the [scikit-learn](https://github.com/scikit-learn/scikit-learn) package.

## Getting started ### Dependencies regain requires: - Python (>= 2.7 or >= 3.5) - NumPy (>= 1.8.2) - scikit-learn (>= 0.17)

To use the parameter selection via gaussian process optimisation, [GPyOpt](https://github.com/SheffieldML/GPyOpt) is required. You can install dependencies by running: `bash pip install -r requirements.txt `

### Installation The simplest way to install regain is using pip `bash pip install regain ` or conda

`bash conda install -c fdtomasi regain `

If you’d like to install from source, or want to contribute to the project (e.g. by sending pull requests via github), read on. Clone the repository in GitHub and add it to your $PYTHONPATH. `bash git clone https://github.com/fdtomasi/regain.git cd regain python setup.py develop `

## Quickstart TODO

## Citation `latex @{coming soon} `