Skip to main content

JUelich NeuroImaging FEature extractoR

Project description

Junifer logo

junifer - JUelich NeuroImaging FEature extractoR

PyPI PyPI - Python Version PyPI - Wheel Anaconda-Server Badge GitHub Codecov Code style: black

About

junifer is a data handling and feature extraction library targeted towards neuroimaging data specifically functional MRI data.

It is curently being developed and maintained at the Applied Machine Learning group at Forschungszentrum Juelich, Germany. Although the library is designed for people working at Institute of Neuroscience and Medicine - Brain and Behaviour (INM-7), it is designed to be as modular as possible thus enabling others to extend it easily.

The documentation is available at https://juaml.github.io/junifer.

Repository Organization

  • docs: Documentation, built using sphinx.
  • examples: Examples, using sphinx-gallery. File names of examples that create visual output must start with plot_, otherwise, with run_.
  • junifer: Main library directory.
    • api: User API module.
    • configs: Module for pre-defined configs for most used computing clusters.
    • data: Module that handles data required for the library to work (e.g. parcels, coordinates).
    • datagrabber: DataGrabber module.
    • datareader: DataReader module.
    • markers: Markers module.
    • pipeline: Pipeline module.
    • preprocess: Preprocessing module.
    • storage: Storage module.
    • testing: Testing components module.
    • utils: Utilities module (e.g. logging)

Installation

Use pip to install from PyPI like so:

pip install junifer

You can also install via conda, like so:

conda install -c conda-forge junifer

Citation

If you use junifer in a scientific publication, we would appreciate if you cite our work. Currently, we do not have a publication, so feel free to use the project URL.

Funding

We thank the Helmholtz Imaging Platform and SMHB for supporting development of Junifer. (The funding sources had no role in the design, implementation and evaluation of the pipeline.)

Contribution

Contributions are welcome and greatly appreciated. Please read the guidelines to get started.

License

junifer is released under the AGPL v3 license:

junifer, FZJuelich AML neuroimaging feature extraction library. Copyright (C) 2022, authors of junifer.

This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, either version 3 of the License, or any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License for more details.

You should have received a copy of the GNU Affero General Public License along with this program. If not, see http://www.gnu.org/licenses/.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

junifer-0.0.3.dev53.tar.gz (557.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

junifer-0.0.3.dev53-py3-none-any.whl (532.4 kB view details)

Uploaded Python 3

File details

Details for the file junifer-0.0.3.dev53.tar.gz.

File metadata

  • Download URL: junifer-0.0.3.dev53.tar.gz
  • Upload date:
  • Size: 557.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.3

File hashes

Hashes for junifer-0.0.3.dev53.tar.gz
Algorithm Hash digest
SHA256 19f24dc04388ac12c7a6ffd1097cb07b9667870df4ff2532ae7a343626739435
MD5 8f959e05a85193f7981e1d054b826aab
BLAKE2b-256 a0dbfbbd4559cd19c5ded54d64b1f0dd81942b3dcd78473f81c6c9c947f3c152

See more details on using hashes here.

File details

Details for the file junifer-0.0.3.dev53-py3-none-any.whl.

File metadata

  • Download URL: junifer-0.0.3.dev53-py3-none-any.whl
  • Upload date:
  • Size: 532.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.3

File hashes

Hashes for junifer-0.0.3.dev53-py3-none-any.whl
Algorithm Hash digest
SHA256 887548075631cd0d52d43b499cfdc47fa6d9b30e9eb0cdb1d5938c4f007de980
MD5 106b256b16513dd61754ff5ab957f8a1
BLAKE2b-256 167c1ac5baf093ed13f9c6434ce4c177a6d7547854b21975030f142ae864cfec

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page