====================
BrainSpace
====================
.. image:: https://github.com/MICA-MNI/brainspace/workflows/Python%20package/badge.svg
:target: https://github.com/MICA-MNI/brainspace/actions
.. image:: https://codecov.io/gh/mica-mni/brainspace/branch/master/graph/badge.svg
:target: https://codecov.io/gh/mica-mni/brainspace
.. image:: https://img.shields.io/appveyor/build/OualidBenkarim/brainspace/master?logo=appveyor
:alt: AppVeyor branch
.. image:: https://img.shields.io/pypi/v/brainspace
:target: https://pypi.python.org/pypi/brainspace
.. image:: https://img.shields.io/pypi/l/brainspace?label=License
:target: https://opensource.org/licenses/BSD-3-Clause
.. image:: https://img.shields.io/pypi/pyversions/brainspace
:alt: PyPI - Python Version
BrainSpace is a lightweight cross-platform toolbox primarily intended
for macroscale gradient mapping and analysis of
neuroimaging and connectome level data. The current version
of BrainSpace is available in Python and MATLAB, programming
languages widely used by the neuroimaging and network neuroscience
communities. The toolbox also contains several maps that allow for
exploratory analysis of gradient correspondence with other
brain-derived features, together with tools to generate spatial null models.
For installation instructions, examples and documentation of BrainSpace see
our `documentation <https://brainspace.readthedocs.io>`_.
Happy gradient analysis!
License
-----------
The BrainSpace source code is available under the BSD (3-Clause) license.
Support
-----------
If you have problems installing the software or questions about usage
and documentation, or something else related to BrainSpace,
you can post to the Issues section of our `repository <https://github.com/MICA-MNI/BrainSpace/issues>`_.
Paper
-----------
If you consider using BrainSpace, please cite our manuscript:
Vos de Wael R, Benkarim O, Paquola C, Lariviere S, Royer J, Tavakol S, Xu T, Hong S, Langs G, Valk S, Misic B, Milham M, Margulies D, Smallwood J, Bernhardt B (2020). BrainSpace: a toolbox for the analysis of macroscale gradients in neuroimaging and connectomics datasets. Commun Biol 3, 103.
Core development team
-----------------------
* Reinder Vos de Wael, MICA Lab - Montreal Neurological Institute
* Oualid Benkarim, MICA Lab - Montreal Neurological Institute
* Boris Bernhardt, MICA Lab - Montreal Neurological Institute
Raw data
{
"_id": null,
"home_page": "https://github.com/MICA-MNI/BrainSpace",
"name": "brainspace",
"maintainer": "",
"docs_url": null,
"requires_python": ">=3.5",
"maintainer_email": "",
"keywords": "brain cortex gradient manifold",
"author": "BrainSpace developers",
"author_email": "oualid.benkarim@mcgill.ca",
"download_url": "https://files.pythonhosted.org/packages/e5/25/922f8d94f6c62a722e8c99f1bdd09c076bb6b06a4661440ac1a3cfc5f641/brainspace-0.1.10.tar.gz",
"platform": null,
"description": "====================\nBrainSpace\n====================\n\n\n.. image:: https://github.com/MICA-MNI/brainspace/workflows/Python%20package/badge.svg\n :target: https://github.com/MICA-MNI/brainspace/actions\n\n.. image:: https://codecov.io/gh/mica-mni/brainspace/branch/master/graph/badge.svg\n :target: https://codecov.io/gh/mica-mni/brainspace\n\n.. image:: https://img.shields.io/appveyor/build/OualidBenkarim/brainspace/master?logo=appveyor\n :alt: AppVeyor branch\n\n.. image:: https://img.shields.io/pypi/v/brainspace\n :target: https://pypi.python.org/pypi/brainspace\n\n.. image:: https://img.shields.io/pypi/l/brainspace?label=License\n :target: https://opensource.org/licenses/BSD-3-Clause\n\n.. image:: https://img.shields.io/pypi/pyversions/brainspace\n :alt: PyPI - Python Version\n\nBrainSpace is a lightweight cross-platform toolbox primarily intended \nfor macroscale gradient mapping and analysis of \nneuroimaging and connectome level data. The current version \nof BrainSpace is available in Python and MATLAB, programming \nlanguages widely used by the neuroimaging and network neuroscience \ncommunities. The toolbox also contains several maps that allow for \nexploratory analysis of gradient correspondence with other \nbrain-derived features, together with tools to generate spatial null models.\n\nFor installation instructions, examples and documentation of BrainSpace see\nour `documentation <https://brainspace.readthedocs.io>`_.\n\nHappy gradient analysis! \n\nLicense\n-----------\n\nThe BrainSpace source code is available under the BSD (3-Clause) license.\n\nSupport\n-----------\n\nIf you have problems installing the software or questions about usage \nand documentation, or something else related to BrainSpace, \nyou can post to the Issues section of our `repository <https://github.com/MICA-MNI/BrainSpace/issues>`_.\n\nPaper\n-----------\n\nIf you consider using BrainSpace, please cite our manuscript: \nVos de Wael R, Benkarim O, Paquola C, Lariviere S, Royer J, Tavakol S, Xu T, Hong S, Langs G, Valk S, Misic B, Milham M, Margulies D, Smallwood J, Bernhardt B (2020). BrainSpace: a toolbox for the analysis of macroscale gradients in neuroimaging and connectomics datasets. Commun Biol 3, 103.\n\nCore development team\n-----------------------\n\n* Reinder Vos de Wael, MICA Lab - Montreal Neurological Institute\n* Oualid Benkarim, MICA Lab - Montreal Neurological Institute\n* Boris Bernhardt, MICA Lab - Montreal Neurological Institute\n\n",
"bugtrack_url": null,
"license": "",
"summary": "Cortical gradients and beyond",
"version": "0.1.10",
"split_keywords": [
"brain",
"cortex",
"gradient",
"manifold"
],
"urls": [
{
"comment_text": "",
"digests": {
"md5": "bb65cdcdc1659da8e06382fb6e094706",
"sha256": "6ab0f732bb04134792685200317777243b6f8d6ddc7a8f06558ab6444da93fe6"
},
"downloads": -1,
"filename": "brainspace-0.1.10-py3-none-any.whl",
"has_sig": false,
"md5_digest": "bb65cdcdc1659da8e06382fb6e094706",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.5",
"size": 60668255,
"upload_time": "2022-12-20T03:12:17",
"upload_time_iso_8601": "2022-12-20T03:12:17.375788Z",
"url": "https://files.pythonhosted.org/packages/bc/f0/05fd42fb078486d7e5d8008564cf7a27833a8681e416eedeb436ad02831d/brainspace-0.1.10-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"md5": "24d2cf856ef1d445fcbe800094a41829",
"sha256": "cea5a454dc4e31b9bdce8d208e155897d98fffcb19cb623c685380977f0c9a57"
},
"downloads": -1,
"filename": "brainspace-0.1.10.tar.gz",
"has_sig": false,
"md5_digest": "24d2cf856ef1d445fcbe800094a41829",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.5",
"size": 60411974,
"upload_time": "2022-12-20T03:12:22",
"upload_time_iso_8601": "2022-12-20T03:12:22.691022Z",
"url": "https://files.pythonhosted.org/packages/e5/25/922f8d94f6c62a722e8c99f1bdd09c076bb6b06a4661440ac1a3cfc5f641/brainspace-0.1.10.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2022-12-20 03:12:22",
"github": true,
"gitlab": false,
"bitbucket": false,
"github_user": "MICA-MNI",
"github_project": "BrainSpace",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"requirements": [
{
"name": "numpy",
"specs": [
[
">=",
"1.11.0"
]
]
},
{
"name": "scipy",
"specs": [
[
">=",
"0.17.0"
]
]
},
{
"name": "scikit-learn",
"specs": [
[
">=",
"0.22.0"
]
]
},
{
"name": "matplotlib",
"specs": [
[
">=",
"2.0.0"
]
]
},
{
"name": "vtk",
"specs": [
[
">=",
"8.1.0"
]
]
},
{
"name": "nibabel",
"specs": []
},
{
"name": "nilearn",
"specs": []
}
],
"lcname": "brainspace"
}