| Name | mne-connectivity JSON |
| Version |
0.7.0
JSON |
| download |
| home_page | None |
| Summary | mne-connectivity: A module for connectivity data analysis with MNE. |
| upload_time | 2024-06-12 15:29:00 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.9 |
| license | BSD 3-Clause License Copyright (c) 2021, MNE tools for MEG and EEG data analysis All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. |
| keywords |
connectivity
eeg
ieeg
meg
neuroscience
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
|
.. -*- mode: rst -*-
|GH|_ |Circle|_ |Azure|_ |Codecov|_ |PyPI|_ |PyPI_Release|_ |conda-forge|_
.. |GH| image:: https://github.com/mne-tools/mne-connectivity/actions/workflows/unit_tests.yml/badge.svg
.. _GH: https://github.com/mne-tools/mne-connectivity/actions/workflows/unit_tests.yml
.. |Circle| image:: https://circleci.com/gh/mne-tools/mne-connectivity.svg?style=shield
.. _Circle: https://circleci.com/gh/mne-tools/mne-connectivity
.. |Azure| image:: https://dev.azure.com/mne-tools/mne-connectivity/_apis/build/status/mne-tools.mne-connectivity?branchName=main
.. _Azure: https://dev.azure.com/mne-tools/mne-connectivity/_build/latest?definitionId=1&branchName=main
.. |Codecov| image:: https://codecov.io/gh/mne-tools/mne-connectivity/branch/main/graph/badge.svg
.. _Codecov: https://codecov.io/gh/mne-tools/mne-connectivity
.. |conda-forge| image:: https://img.shields.io/conda/dn/conda-forge/mne-connectivity.svg?label=Conda%20downloads
.. _conda-forge: https://anaconda.org/conda-forge/mne-connectivity
.. |PyPI| image:: https://img.shields.io/pypi/dm/mne-connectivity.svg?label=PyPI%20downloads
.. _PyPI: https://pypi.org/project/mne-connectivity/
.. |PyPI_Release| image:: https://img.shields.io/pypi/v/mne-connectivity.svg
.. _PyPI_Release: https://pypi.org/project/mne-connectivity/
.. _MNE-Connectivity: https://mne.tools/mne-connectivity/dev/
.. _MNE-Python: https://mne.tools/stable
.. _MNE-Connectivity documentation: https://mne.tools/mne-connectivity/stable/index.html
.. _installation guide: https://mne.tools/mne-connectivity/dev/install/index.html
.. _pip: https://pip.pypa.io/en/stable/
.. _Frites: https://github.com/brainets/frites
.. _contributing guide: https://github.com/mne-tools/mne-connectivity/blob/main/CONTRIBUTING.md
MNE-Connectivity
================
`MNE-Connectivity`_ is an open-source Python package for connectivity and
related measures of MEG, EEG, or iEEG data built on top of the
`MNE-Python`_ API. It includes modules for data input/output, visualization,
common connectivity analysis, and post-hoc statistics and processing.
.. target for :end-before: title-end-content
This project was initially ported over from mne-python starting v0.23, by Adam
Li as part of Google Summer of Code 2021. Subsequently v0.1 and v0.2 releases
were done as part of GSoC period. Future development will occur in subsequent
versions.
Documentation
^^^^^^^^^^^^^
Stable `MNE-Connectivity documentation`_ is available online.
Installing MNE-Connectivity
^^^^^^^^^^^^^^^^^^^^^^^^^^^
To install the latest stable version of MNE-Connectivity, you can use pip_ in a terminal:
.. code-block:: bash
pip install -U mne-connectivity
For more complete instructions and more advanced installation methods (e.g. for
the latest development version), see the `installation guide`_.
Get the latest code
^^^^^^^^^^^^^^^^^^^
To install the latest version of the code using pip_ open a terminal and type:
.. code-block:: bash
pip install -U https://github.com/mne-tools/mne-connectivity/archive/main.zip
To get the latest code using `git <https://git-scm.com/>`__, open a terminal and type:
.. code-block:: bash
git clone https://github.com/mne-tools/mne-connectivity.git
Alternatively, you can also download a
`zip file of the latest development version <https://github.com/mne-tools/mne-connectivity/archive/main.zip>`__.
Contributing to MNE-Connectivity
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Please see the documentation on the MNE-Connectivity homepage:
https://github.com/mne-tools/mne-connectivity/blob/main/CONTRIBUTING.md
Forum
^^^^^^
https://mne.discourse.group
A Note About Connectivity
^^^^^^^^^^^^^^^^^^^^^^^^^
In the neuroscience community as of 2021, the term "functional connectivity" can
have many different meanings and comprises many different measures. Some of
these measures are directed (i.e. try to map a statistical causal relationship between
brain regions), others are non-directed. Please note that the interpretation of your
functional connectivity measure depends on the data and underlying
assumptions.
For a taxonomy of functional connectivity measures and information on the
interpretation of those measures, we refer to
`Bastos and Schoffelen`_.
In mne-connectivity, we do not claim that any of our measures imply causal
connectivity.
.. _Bastos and Schoffelen: https://pubmed.ncbi.nlm.nih.gov/26778976/
Raw data
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