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<a href="https://zenodo.org/badge/latestdoi/601919618"><img src="https://zenodo.org/badge/601919618.svg" height="20"/></a>
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<a href="https://www.gnu.org/licenses/gpl-3.0"><img src="https://img.shields.io/badge/License-GPLv3-blue.svg" height="20"/></a>
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<a href="https://github.com/DynamicsAndNeuralSystems/pyspi/actions/workflows/run_unit_tests.yaml"><img src="https://github.com/DynamicsAndNeuralSystems/pyspi/actions/workflows/run_unit_tests.yaml/badge.svg" height="20"/></a>
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<a href="https://twitter.com/compTimeSeries"><img src="https://img.shields.io/twitter/url/https/twitter.com/compTimeSeries.svg?style=social&label=Follow%20%40compTimeSeries" height="20"/></a>
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<a href="https://twitter.com/compTimeSeries"><img src="https://img.shields.io/twitter/url/https/twitter.com/compTimeSeries.svg?style=social&label=Follow%20%40compTimeSeries" height="20"/></a><br>
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<a href="https://www.python.org"><img src="https://img.shields.io/badge/Python-3.8%20|%203.9-3776AB.svg?style=flat&logo=python&logoColor=white" alt="Python 3.8 | 3.9"></a>
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</p>
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_pyspi_ is a comprehensive python library for computing statistics of pairwise interactions (SPIs) from multivariate time-series (MTS) data.

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