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Temporal network measures, temporal network generation, derivation of time-varying/dynamic connectivities, plotting functions.\n\nSome extra focus is placed on neuroimaging data (e.g. compatible with BIDS - _NB: currently not compliant with latest release candidate of BIDS Derivatives_).\n\n## Installation\n\nWith pip installed:\n\n`pip install teneto`\n\nto upgrade teneto:\n\n`pip install teneto -U`\n\nRequires: Python 3.6+\n\nInstalling teneto via pip installs all python package requirements as well.\n\n## Documentation\n\nMore detailed documentation can be found at  [teneto.readthedocs.io](https://teneto.readthedocs.io) and includes tutorials.\n\n## Outlook\n\nThis package is under active development. And a lot of changes will still be made.\n\n## Contributers\n\nFor a list of contributors to teneto, see:  [teneto.readthedocs.io](https://teneto.readthedocs.io/en/latest/contribute.html)\n\n## Cite\n\nIf using this, please cite us. At present we do not have a dedicated article about teneto, but you can cite the software using the [Zenodo DOI](https://doi.org/10.5281/zenodo.2535993) and/or the article where teneto is introduced, along with a considerable discussion about many of the measures in teneto:\n\nThompson et al (2017) \"From static to temporal network theory applications to functional brain connectivity.\" _Network Neuroscience_, 2: 1. p.69-99  [Link](https://www.mitpressjournals.org/doi/abs/10.1162/NETN_a_00011)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fwiheto%2Fteneto","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fwiheto%2Fteneto","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fwiheto%2Fteneto/lists"}