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        "description": "# fmralign\n[Functional alignment and template estimation library](https://parietal-inria.github.io/fmralign-docs) for functional Magnetic Resonance Imaging (fMRI) data\n\nThis library is meant to be a light-weight Python library that handles functional\nalignment tasks. It is compatible with and inspired from [Nilearn](http://nilearn.github.io).\n\nAlternative implementations of these ideas can be found in the\n[pymvpa](http://www.pymvpa.org) or [brainiak](http://brainiak.org) packages.\n\n## Getting Started\n\n### Prerequisites\n\nfmralign requires a Python installation and the following dependencies:\n* Python >= 3.6,\n* Numpy >= 1.16.2\n* SciPy >= 1.2.2\n* Scikit-learn >= 0.20\n* Matplotlib >= '1.5.0'\n* Nibabel >= 2.5.0\n* Nilearn >= 3.1.1\n\n### Installing\n\nOpen a terminal window, go the location where you want to install it. Then run:\n\n```\npip install fmralign\n```\n\nIf you plan to use optimal transport based method, you should also run:\n\n```\npip install POT\n```\n\nYou're up and running!\n\n### Documentation\n\nYou can found an introduction to functional alignment, a user guide and some examples\non how to use the package at https://parietal-inria.github.io/fmralign-docs. \n\n## License\n\nThis project is licensed under the Simplified BSD License.\n\n## Acknowledgments\n\nThis project has received funding from the European Union\u2019s Horizon\n2020 Research and Innovation Programme under Grant Agreement No. 785907\n(HBP SGA2).\nThis project was supported by [Digiteo](http://www.digiteo.fr).\n\n\n",
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        "license": "new BSD",
        "maintainer": "Bertrand Thirion, Thomas Bazeille",
        "maintainer_email": "bertrand.thirion@inria.fr",
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