Skip to main content

JUelich NeuroImaging FEature extractoR

Project description

Junifer logo

junifer - JUelich NeuroImaging FEature extractoR

PyPI PyPI - Python Version PyPI - Wheel GitHub Codecov

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

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.

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-0.0.1.dev174.tar.gz (619.3 kB view details)

Uploaded Source

Built Distribution

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

junifer-0.0.1.dev174-py3-none-any.whl (473.4 kB view details)

Uploaded Python 3

File details

Details for the file junifer-0.0.1.dev174.tar.gz.

File metadata

  • Download URL: junifer-0.0.1.dev174.tar.gz
  • Upload date:
  • Size: 619.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.1

File hashes

Hashes for junifer-0.0.1.dev174.tar.gz
Algorithm Hash digest
SHA256 3e17797701280c546211db2d2bc854ac8f3516a7590856460b4f1fb7d8719594
MD5 08e7ac2e0b688c45e4f8e76c941a8558
BLAKE2b-256 14f79284081084bd0dae6e7ab7d8d71be4c8052b11be268464a7d521196cd8e4

See more details on using hashes here.

File details

Details for the file junifer-0.0.1.dev174-py3-none-any.whl.

File metadata

  • Download URL: junifer-0.0.1.dev174-py3-none-any.whl
  • Upload date:
  • Size: 473.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.1

File hashes

Hashes for junifer-0.0.1.dev174-py3-none-any.whl
Algorithm Hash digest
SHA256 94aee029c5b6fdd14cac48c24f2e523d388d28ba328cbe7944ed2e0eecf86581
MD5 d4b3793f2de0c3984c4d0697e4c84578
BLAKE2b-256 211a549fd9313fa8698358faa61df1e2deaea0a39b9068541e899fb20494b3e4

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