| Name | junifer JSON |
| Version |
0.0.4
JSON |
| download |
| home_page | None |
| Summary | JUelich NeuroImaging FEature extractoR |
| upload_time | 2024-04-05 15:43:28 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.8 |
| license | AGPL-3.0-only |
| keywords |
neuroimaging
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# junifer - JUelich NeuroImaging FEature extractoR
[](https://anaconda.org/conda-forge/junifer)
[](https://github.com/psf/black)
[](https://github.com/charliermarsh/ruff)
[](https://github.com/pre-commit/pre-commit)
[](https://doi.org/10.5281/zenodo.8176570)
[](https://fairsoftwarechecklist.net/v0.2?f=31&a=32113&i=32322&r=133)
## 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](https://www.fz-juelich.de/en/inm/inm-7/research-groups/applied-machine-learning-aml) group at [Forschungszentrum Juelich](https://www.fz-juelich.de/en), Germany. Although the library is designed for people working at [Institute of Neuroscience and Medicine - Brain and Behaviour (INM-7)](https://www.fz-juelich.de/en/inm/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](https://juaml.github.io/junifer/main/index.html).
## 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.
* `external`: Module for external libraries and tools.
* `markers`: Markers module.
* `onthefly`: Transformation components (on-the-fly) 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
```
### Optional dependencies
`junifer` supports a few optional dependencies to enable certain features. You can
install them by specifying a comma separated list within square brackets, like so:
```
pip install "junifer[bct,dev]"
```
* `bct` installs [bctpy](https://github.com/aestrivex/bctpy) to enable use of `onthefly` module.
* `neurokit2` installs [neurokit2](https://github.com/neuropsychology/NeuroKit) to enable use of [complexity markers](https://juaml.github.io/junifer/main/api/markers.html#module-junifer.markers.complexity).
* `all` includes all of the above.
* `dev` installs packages needed for development.
* `docs` installs packages needed for building documentation.
## 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's [Zenodo URL](https://doi.org/10.5281/zenodo.8176569).
## Funding
We thank the [Helmholtz Imaging Platform](https://helmholtz-imaging.de/) and
[SMHB](https://www.fz-juelich.de/en/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](https://juaml.github.io/junifer/main/contributing.html) to get started.
## License
junifer is released under the AGPL v3 license:
junifer, FZJuelich AML neuroimaging feature extraction library.
Copyright (C) 2023, 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/>.
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"description": "![Junifer logo](docs/images/junifer_logo.png \"junifer logo\")\n\n# junifer - JUelich NeuroImaging FEature extractoR\n\n\n\n\n[](https://anaconda.org/conda-forge/junifer)\n\n\n[](https://github.com/psf/black)\n[](https://github.com/charliermarsh/ruff)\n[](https://github.com/pre-commit/pre-commit)\n[](https://doi.org/10.5281/zenodo.8176570)\n[](https://fairsoftwarechecklist.net/v0.2?f=31&a=32113&i=32322&r=133)\n\n## About\n\n`junifer` is a data handling and feature extraction library targeted towards neuroimaging data specifically functional MRI data.\n\nIt is currently being developed and maintained at the [Applied Machine Learning](https://www.fz-juelich.de/en/inm/inm-7/research-groups/applied-machine-learning-aml) group at [Forschungszentrum Juelich](https://www.fz-juelich.de/en), Germany. Although the library is designed for people working at [Institute of Neuroscience and Medicine - Brain and Behaviour (INM-7)](https://www.fz-juelich.de/en/inm/inm-7), it is designed to be as modular as possible thus enabling others to extend it easily.\n\nThe documentation is available at [https://juaml.github.io/junifer](https://juaml.github.io/junifer/main/index.html).\n\n## Repository Organization\n\n* `docs`: Documentation, built using sphinx.\n* `examples`: Examples, using sphinx-gallery. File names of examples that create visual output must start with `plot_`, otherwise, with `run_`.\n* `junifer`: Main library directory.\n * `api`: User API module.\n * `configs`: Module for pre-defined configs for most used computing clusters.\n * `data`: Module that handles data required for the library to work (e.g. parcels, coordinates).\n * `datagrabber`: DataGrabber module.\n * `datareader`: DataReader module.\n * `external`: Module for external libraries and tools.\n * `markers`: Markers module.\n * `onthefly`: Transformation components (on-the-fly) module.\n * `pipeline`: Pipeline module.\n * `preprocess`: Preprocessing module.\n * `storage`: Storage module.\n * `testing`: Testing components module.\n * `utils`: Utilities module (e.g. logging).\n\n## Installation\n\nUse `pip` to install from PyPI like so:\n\n```\npip install junifer\n```\n\nYou can also install via `conda`, like so:\n\n```\nconda install -c conda-forge junifer\n```\n\n### Optional dependencies\n\n`junifer` supports a few optional dependencies to enable certain features. You can\ninstall them by specifying a comma separated list within square brackets, like so:\n\n```\npip install \"junifer[bct,dev]\"\n```\n\n* `bct` installs [bctpy](https://github.com/aestrivex/bctpy) to enable use of `onthefly` module.\n* `neurokit2` installs [neurokit2](https://github.com/neuropsychology/NeuroKit) to enable use of [complexity markers](https://juaml.github.io/junifer/main/api/markers.html#module-junifer.markers.complexity).\n* `all` includes all of the above.\n* `dev` installs packages needed for development.\n* `docs` installs packages needed for building documentation.\n\n## Citation\n\nIf 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's [Zenodo URL](https://doi.org/10.5281/zenodo.8176569).\n\n## Funding\n\nWe thank the [Helmholtz Imaging Platform](https://helmholtz-imaging.de/) and\n[SMHB](https://www.fz-juelich.de/en/smhb) for supporting development of `junifer`.\n(The funding sources had no role in the design, implementation and evaluation of the pipeline.)\n\n## Contribution\n\nContributions are welcome and greatly appreciated. Please read the [guidelines](https://juaml.github.io/junifer/main/contributing.html) to get started.\n\n## License\n\njunifer is released under the AGPL v3 license:\n\njunifer, FZJuelich AML neuroimaging feature extraction library.\nCopyright (C) 2023, authors of junifer.\n\nThis program is free software: you can redistribute it and/or modify\nit under the terms of the GNU Affero General Public License as published by\nthe Free Software Foundation, either version 3 of the License, or any later version.\n\nThis program is distributed in the hope that it will be useful,\nbut WITHOUT ANY WARRANTY; without even the implied warranty of\nMERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\nGNU Affero General Public License for more details.\n\nYou should have received a copy of the GNU Affero General Public License\nalong with this program. If not, see <http://www.gnu.org/licenses/>.\n",
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