tsl: a PyTorch library for spatiotemporal data processing

tsl (Torch Spatiotemporal) is a library built to accelerate research on neural spatiotemporal data processing methods, with a focus on Graph Neural Networks.

tsl is built on several libraries of the Python scientific computing ecosystem, with the final objective of providing a straightforward process that goes from data preprocessing to model prototyping. In particular, tsl offers a wide range of utilities to develop neural networks in PyTorch for processing spatiotemporal data signals.

Installation

tsl is compatible with Python>=3.7. We recommend installation from source to be up-to-date with the latest version:

git clone https://github.com/TorchSpatiotemporal/tsl.git
cd tsl
python setup.py install  # Or 'pip install .'

To solve all dependencies, we recommend using Anaconda and the provided environment configuration by running the command:

conda env create -f tsl_env.yml

Alternatively, you can install the library from pip:

pip install torch-spatiotemporal

Please refer to PyG installation guidelines for installation of PyG ecosystem without conda.

Tutorial

The best way to start using tsl is by following the tutorial notebook in examples/notebooks/a_gentle_introduction_to_tsl.ipynb.

Documentation

The documentation is hosted on readthedocs. For local access, you can build it from the docs directory.

Credits

Andrea Cini, Ivan Marisca