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 currently 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.dev73.tar.gz (558.8 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.dev73-py3-none-any.whl (533.4 kB view details)

Uploaded Python 3

File details

Details for the file junifer-0.0.3.dev73.tar.gz.

File metadata

  • Download URL: junifer-0.0.3.dev73.tar.gz
  • Upload date:
  • Size: 558.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.4

File hashes

Hashes for junifer-0.0.3.dev73.tar.gz
Algorithm Hash digest
SHA256 53b62e0055f10d050f52bc4714703de034c62c4bd9972690a73781038ea2bb8e
MD5 c450732411e2b2d2bb4308805343bc5b
BLAKE2b-256 0c062cb07e8e1e1a1c8cb6338d6f3856cd0b08dd3294b3ea6ce21a3ef3599ebd

See more details on using hashes here.

File details

Details for the file junifer-0.0.3.dev73-py3-none-any.whl.

File metadata

  • Download URL: junifer-0.0.3.dev73-py3-none-any.whl
  • Upload date:
  • Size: 533.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.4

File hashes

Hashes for junifer-0.0.3.dev73-py3-none-any.whl
Algorithm Hash digest
SHA256 b7beac553d3d2edb3f6cf85ede2bcaff69f980af35a80ec87d16939df93bcdc1
MD5 954092fb51047aa95c87e5fbd6aa2fe2
BLAKE2b-256 80870a77b057f22f5293303e25bc8baa18c2d139bc824b8b71b741fae7000ca5

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