Metadata-Version: 2.1
Name: mne-nirs
Version: 0.0.3
Summary: An MNE compatible package for processing near-infrared spectroscopy data.
Home-page: https://mne.tools/mne-nirs/
Maintainer: Robert Luke
Maintainer-email: robert.luke@mq.edu.au
License: BSD (3-clause)
Download-URL: https://github.com/mne-tools/mne-nirs
Project-URL: Documentation, https://mne.tools/mne-nirs/
Project-URL: Source, https://github.com/mne-tools/mne-nirs/
Project-URL: Tracker, https://github.com/mne-tools/mne-nirs/issues/
Description: MNE-NIRS: Near-Infrared Spectroscopy Analysis
        =============================================
        
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        **MNE-NIRS** is an `MNE <https://mne.tools>`_ compatible near-infrared spectroscopy processing package. 
        
        MNE has support for common fNIRS waveform analysis (see `tutorial <https://mne.tools/stable/auto_tutorials/preprocessing/plot_70_fnirs_processing.html>`_), this package adds additional GLM style analysis, helper functions, algorithms, and plotting.
        
        
        Documentation
        -------------
        
        Documentation for this project is hosted `here <https://mne-tools.github.io/mne-nirs>`_.
        
        
        Examples
        --------
        
        - MNE examples:
            - `Basic waveform analysis pipeline <https://mne.tools/dev/auto_tutorials/preprocessing/plot_70_fnirs_processing.html#sphx-glr-auto-tutorials-preprocessing-plot-70-fnirs-processing-py>`_.
            - `Artifact rejection discussion <https://mne.tools/dev/auto_examples/preprocessing/plot_fnirs_artifact_removal.html#ex-fnirs-artifacts>`_.
        - MNE-NIRS examples:
            - `Simulated haemodynamic response GLM analysis <https://mne.tools/mne-nirs/auto_examples/plot_11_hrf_simulation.html>`_.
            - `Measured haemodynamic response GLM analysis <https://mne.tools/mne-nirs/auto_examples/plot_10_hrf.html>`_.
            - `Group level GLM analysis <https://mne.tools/mne-nirs/auto_examples/plot_12_group_glm.html>`_.
            - `Signal enhancement <https://mne-tools.github.io/mne-nirs/auto_examples/plot_20_cui.html>`_.
            - `Frequency and filtering <https://mne.tools/mne-nirs/auto_examples/plot_30_frequency.html>`_.
        
        
        Contributing
        ------------
        
        Contributions are welcome (more than welcome!). Contributions can be feature requests, improved documentation, bug reports, code improvements, new code, etc. Anything will be appreciated. *Note*: this package adheres to the same contribution  `standards as MNE <https://mne.tools/stable/install/contributing.html>`_.
        
        
        Acknowledgements
        ----------------
        
        This package is built on top of many other great packages. If you use MNE-NIRS you should also acknowledge these packages.
        
        MNE: https://mne.tools/dev/overview/cite.html
        
        Nilearn: http://nilearn.github.io/authors.html#citing
        
        statsmodels: https://www.statsmodels.org/stable/index.html#citation
        
        Until there is a journal article specifically on MNE-NIRS, please cite `this article <https://www.biorxiv.org/content/10.1101/2020.12.22.423886v1>`_.
        
Keywords: neuroscience neuroimaging fNIRS NIRS brain
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved
Classifier: Programming Language :: Python
Classifier: Topic :: Software Development
Classifier: Topic :: Scientific/Engineering
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS
Classifier: Programming Language :: Python :: 3
Description-Content-Type: text/x-rst
Provides-Extra: tests
Provides-Extra: docs
