| Name | pydra-fsl JSON |
| Version |
0.1.1
JSON |
| download |
| home_page | None |
| Summary | Pydra tasks package for fsl |
| upload_time | 2024-05-18 12:20:17 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.8 |
| license | Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. Definitions. "License" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document. "Licensor" shall mean the copyright owner or entity authorized by the copyright owner that is granting the License. "Legal Entity" shall mean the union of the acting entity and all other entities that control, are controlled by, or are under common control with that entity. For the purposes of this definition, "control" means (i) the power, direct or indirect, to cause the direction or management of such entity, whether by contract or otherwise, or (ii) ownership of fifty percent (50%) or more of the outstanding shares, or (iii) beneficial ownership of such entity. "You" (or "Your") shall mean an individual or Legal Entity exercising permissions granted by this License. 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| keywords |
fsl
neuroimaging
pydra
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
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No Travis.
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# pydra-fsl
[![PyPI - Version][pypi-version]][pypi-project]
[![PyPI - Python Version][pypi-pyversions]][pypi-project]
[![PyPI - Downloads][pypi-downloads]][pypi-project]
[![Status-docs][status-docs-badge]][status-docs-link]
[![Status-CICD][status-cicd-badge]][status-cicd-link]
----
Pydra tasks for FSL.
[Pydra][pydra] is a dataflow engine which provides
a set of lightweight abstractions for DAG
construction, manipulation, and distributed execution.
[FSL][fsl] is a comprehensive library of analysis tools
for FMRI, MRI and DTI brain imaging data.
**Table of contents**
- [Available tasks](#available-tasks)
- [Installation](#installation)
- [Development](#development)
- [License](#license)
## Tested interfaces
| Module | Tasks |
|--------|--------------------------------------------------------------------------------------------------------------------|
| bet | BET, RobustFOV |
| eddy | Eddy, ApplyTopup, Topup |
| fast | FAST |
| flirt | FLIRT, ApplyXFM, ConcatXFM, ConvertXFM, InvertXFM, FixScaleSkew, Img2ImgCoord, Img2StdCoord, Std2ImgCoord |
| fnirt | FNIRT, FNIRTFileUtils, ApplyWarp, ConvertWarp, InvWarp |
| fugue | FUGUE, PrepareFieldmap, Prelude, SigLoss |
| maths | (**experimental**) Maths, Mul |
| susan | SUSAN |
| utils | ChFileType, FFT, Info, Interleave, Merge, Orient, Reorient2Std, ROI, SelectVols, Slice, SmoothFill, Split, SwapDim |
## Installation
```console
pip install pydra-fsl
```
A separate installation of FSL is required to use this package.
Please review the FSL [installation instructions][fsl-install]
and [licensing details][fsl-license].
## Automatic Conversion
Automatically generated tasks can be found in the `pydra.tasks.fsl.auto` sub-package.
These interfaces should be treated with caution as they likely do not pass testing.
Generated tasks that have been edited and pass testing will be imported into one or more of the
`pydra.tasks.fsl.v*` sub-packages (e.g. `pydra.tasks.fsl.v7_4`) corresponding
to the version of the fsl toolkit they are designed for.
### Continuous integration
This template uses [GitHub Actions](https://docs.github.com/en/actions/) to run tests and
deploy packages to PYPI. New packages are built and uploaded when releases are created on
GitHub, or new releases of Nipype or the Nipype2Pydra conversion tool are released.
Releases triggered by updates to Nipype or Nipype2Pydra are signified by the `postN`
suffix where `N = <nipype-version><nipype2pydra-version>` with the '.'s stripped, e.g.
`v0.2.3post185010` corresponds to the v0.2.3 tag of this repository with auto-generated
packages from Nipype 1.8.5 using Nipype2Pydra 0.1.0.
## Development
### Methodology
The development of this package is expected to have two phases
1. Where the corresponding Nipype interfaces are considered to be the ground truth, and
the Pydra tasks are generated from them
2. When the Pydra tasks are considered be mature and they are edited by hand
Different tasks will probably mature at different times so there will probably be an
intermediate phase between 1 and 2.
### Developer installation
Before the pydra task interfaces can be generated and installed, the file-format classes
[fileformats](https://arcanaframework.github.io/fileformats/) packages
corresponding to FSL specific file formats will need to be installed
```console
pip install -e ./related-packages/fileformats[dev]
pip install -e ./related-packages/fileformats-extras[dev]
```
Next install the requirements for running the auto-conversion script and generate the
Pydra task interfaces from their Nipype counterparts
```console
pip install -r nipype-auto-conv/requirements.txt
```
The run the conversion script to convert Nipype interfaces to Pydra
```console
nipype-auto-conv/generate
```
Install repo in developer mode from the source directory and install pre-commit to
ensure consistent code-style and quality.
```console
pip install -e .[test,dev]
pre-commit install
```
### Auto-conversion phase
The auto-converted Pydra tasks are generated from their corresponding Nipype interface
in combination with "conversion hints" contained in YAML specs
located in `nipype-auto-conv/specs/`. The self-documented conversion specs are
to be edited by hand in order to assist the auto-converter produce valid pydra tasks.
After editing one or more conversion specs the `pydra.tasks.fsl.auto` package should
be regenerated by running
```console
nipype-auto-conv/generate
```
The tests should be run on the auto-generated tasks to see if they are valid
```console
pytest pydra/tasks/fsl/auto/tests/test_<the-name-of-the-task-you-edited>.py
```
If the test passes you should then edit the `pydra/tasks/fsl/v*/__init__.py` file
to import the auto-generated task interface to signify that it has been validated and is
ready for use, where v* corresponds to the version of FSL that you have tested
it against e.g.
```console
from pydra.tasks.fsl.auto import <the-task-you-have-validated>
```
and copy the test file `pydra/tasks/fsl/auto/tests/test_<validated-task>.py`
into `pydra/tasks/fsl/v*/tests`.
### File-formats and sample test data
The automatically generated tests will attempt to provided the task instance to be tested
with sensible default values based on the type of the field and any constraints it has
on it. However, these will often need to be manually overridden after consulting the
underlying tool's documentation.
For file-based data, automatically generated file-system objects will be created for
selected format types, e.g. Nifti, Dicom. Therefore, it is important to specify the
format of the file using the "mime-like" string corresponding to a
[fileformats](https://github.com/ArcanaFramework/fileformats) class
in the `inputs > types` and `outputs > types` dicts of the YAML spec.
If the required file-type is not found implemented within fileformats, please see the `fileformats`
docs [https://arcanaframework.github.io/fileformats/developer.html] for instructions on how to define
new fileformat types, and see
[fileformats-medimage-extras](https://github.com/ArcanaFramework/fileformats-medimage-extras/blob/6c2dabe91e95687eebc2639bb6f034cf9595ecfc/fileformats/extras/medimage/nifti.py#L30-L48)
for an example on how to implement methods to generate sample data for them. Implementations of
new fileformats that are specific to FSL, and functions to
generate sample data for them, should be defined in `related-packages/fileformats`
and `related-packages/fileformats-extras`, respectively.
## License
This project is distributed under the terms of the [Apache License, Version 2.0][license].
[pypi-project]: https://pypi.org/project/pydra-fsl
[pypi-version]: https://img.shields.io/pypi/v/pydra-fsl.svg
[pypi-pyversions]: https://img.shields.io/pypi/pyversions/pydra-fsl.svg
[pypi-downloads]: https://static.pepy.tech/badge/pydra-fsl
[status-docs]: https://github.com/aramis-lab/pydra-fsl/actions/workflows/docs.yaml/badge.svg
[status-test]: https://github.com/aramis-lab/pydra-fsl/actions/workflows/test.yaml/badge.svg
[pydra]: https://pydra.readthedocs.io/
[fsl]: https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FSL
[fsl-install]: https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FslInstallation
[fsl-license]: https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/Licence
[license]: https://spdx.org/licenses/Apache-2.0.html
[status-docs-badge]: https://img.shields.io/badge/docs-latest-brightgreen.svg?style=flat
[status-cicd-badge]: https://github.com/nipype/pydra-fsl/actions/workflows/ci-cd.yaml/badge.svg
[status-docs-link]: https://nipype.github.io/pydra-fsl/
[status-cicd-link]: https://github.com/nipype/pydra-fsl/actions/workflows/ci-cd.yaml
Raw data
{
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"name": "pydra-fsl",
"maintainer": null,
"docs_url": null,
"requires_python": ">=3.8",
"maintainer_email": "Nipype developers <neuroimaging@python.org>, Ghislain Vaillant <ghislain.vaillant@icm-institute.org>",
"keywords": "fsl, neuroimaging, pydra",
"author": null,
"author_email": "Nipype developers <neuroimaging@python.org>, Ghislain Vaillant <ghislain.vaillant@icm-institute.org>",
"download_url": "https://files.pythonhosted.org/packages/1f/27/36c0791b04a8b23bcc3a4ce925f9cff7e7a450791220ebe008ef47fa403e/pydra_fsl-0.1.1.tar.gz",
"platform": null,
"description": "# pydra-fsl\n\n[![PyPI - Version][pypi-version]][pypi-project]\n[![PyPI - Python Version][pypi-pyversions]][pypi-project]\n[![PyPI - Downloads][pypi-downloads]][pypi-project]\n[![Status-docs][status-docs-badge]][status-docs-link]\n[![Status-CICD][status-cicd-badge]][status-cicd-link]\n\n----\n\nPydra tasks for FSL.\n\n[Pydra][pydra] is a dataflow engine which provides\na set of lightweight abstractions for DAG\nconstruction, manipulation, and distributed execution.\n\n[FSL][fsl] is a comprehensive library of analysis tools\nfor FMRI, MRI and DTI brain imaging data.\n\n**Table of contents**\n\n- [Available tasks](#available-tasks)\n- [Installation](#installation)\n- [Development](#development)\n- [License](#license)\n\n## Tested interfaces\n\n| Module | Tasks |\n|--------|--------------------------------------------------------------------------------------------------------------------|\n| bet | BET, RobustFOV |\n| eddy | Eddy, ApplyTopup, Topup |\n| fast | FAST |\n| flirt | FLIRT, ApplyXFM, ConcatXFM, ConvertXFM, InvertXFM, FixScaleSkew, Img2ImgCoord, Img2StdCoord, Std2ImgCoord |\n| fnirt | FNIRT, FNIRTFileUtils, ApplyWarp, ConvertWarp, InvWarp |\n| fugue | FUGUE, PrepareFieldmap, Prelude, SigLoss |\n| maths | (**experimental**) Maths, Mul |\n| susan | SUSAN |\n| utils | ChFileType, FFT, Info, Interleave, Merge, Orient, Reorient2Std, ROI, SelectVols, Slice, SmoothFill, Split, SwapDim |\n\n## Installation\n\n```console\npip install pydra-fsl\n```\n\nA separate installation of FSL is required to use this package.\nPlease review the FSL [installation instructions][fsl-install]\nand [licensing details][fsl-license].\n\n\n## Automatic Conversion\n\nAutomatically generated tasks can be found in the `pydra.tasks.fsl.auto` sub-package.\nThese interfaces should be treated with caution as they likely do not pass testing.\nGenerated tasks that have been edited and pass testing will be imported into one or more of the\n`pydra.tasks.fsl.v*` sub-packages (e.g. `pydra.tasks.fsl.v7_4`) corresponding\nto the version of the fsl toolkit they are designed for.\n\n\n### Continuous integration\n\nThis template uses [GitHub Actions](https://docs.github.com/en/actions/) to run tests and\ndeploy packages to PYPI. New packages are built and uploaded when releases are created on\nGitHub, or new releases of Nipype or the Nipype2Pydra conversion tool are released.\nReleases triggered by updates to Nipype or Nipype2Pydra are signified by the `postN`\nsuffix where `N = <nipype-version><nipype2pydra-version>` with the '.'s stripped, e.g.\n`v0.2.3post185010` corresponds to the v0.2.3 tag of this repository with auto-generated\npackages from Nipype 1.8.5 using Nipype2Pydra 0.1.0.\n\n## Development\n\n### Methodology\n\nThe development of this package is expected to have two phases\n\n1. Where the corresponding Nipype interfaces are considered to be the ground truth, and\n the Pydra tasks are generated from them\n2. When the Pydra tasks are considered be mature and they are edited by hand\n\nDifferent tasks will probably mature at different times so there will probably be an\nintermediate phase between 1 and 2.\n\n### Developer installation\n\nBefore the pydra task interfaces can be generated and installed, the file-format classes\n[fileformats](https://arcanaframework.github.io/fileformats/) packages\ncorresponding to FSL specific file formats will need to be installed\n\n```console\npip install -e ./related-packages/fileformats[dev]\npip install -e ./related-packages/fileformats-extras[dev]\n```\n\nNext install the requirements for running the auto-conversion script and generate the\nPydra task interfaces from their Nipype counterparts\n\n```console\npip install -r nipype-auto-conv/requirements.txt\n```\n\nThe run the conversion script to convert Nipype interfaces to Pydra\n\n```console\nnipype-auto-conv/generate\n```\n\nInstall repo in developer mode from the source directory and install pre-commit to\nensure consistent code-style and quality.\n\n```console\npip install -e .[test,dev]\npre-commit install\n```\n\n### Auto-conversion phase\n\nThe auto-converted Pydra tasks are generated from their corresponding Nipype interface\nin combination with \"conversion hints\" contained in YAML specs\nlocated in `nipype-auto-conv/specs/`. The self-documented conversion specs are\nto be edited by hand in order to assist the auto-converter produce valid pydra tasks.\nAfter editing one or more conversion specs the `pydra.tasks.fsl.auto` package should\nbe regenerated by running\n\n```console\nnipype-auto-conv/generate\n```\n\nThe tests should be run on the auto-generated tasks to see if they are valid\n\n```console\npytest pydra/tasks/fsl/auto/tests/test_<the-name-of-the-task-you-edited>.py\n```\n\nIf the test passes you should then edit the `pydra/tasks/fsl/v*/__init__.py` file\nto import the auto-generated task interface to signify that it has been validated and is\nready for use, where v* corresponds to the version of FSL that you have tested\nit against e.g.\n\n```console\nfrom pydra.tasks.fsl.auto import <the-task-you-have-validated>\n```\n\nand copy the test file `pydra/tasks/fsl/auto/tests/test_<validated-task>.py`\ninto `pydra/tasks/fsl/v*/tests`.\n\n\n### File-formats and sample test data\n\nThe automatically generated tests will attempt to provided the task instance to be tested\nwith sensible default values based on the type of the field and any constraints it has\non it. However, these will often need to be manually overridden after consulting the\nunderlying tool's documentation.\n\nFor file-based data, automatically generated file-system objects will be created for\nselected format types, e.g. Nifti, Dicom. Therefore, it is important to specify the\nformat of the file using the \"mime-like\" string corresponding to a\n[fileformats](https://github.com/ArcanaFramework/fileformats) class\nin the `inputs > types` and `outputs > types` dicts of the YAML spec.\n\nIf the required file-type is not found implemented within fileformats, please see the `fileformats`\ndocs [https://arcanaframework.github.io/fileformats/developer.html] for instructions on how to define\nnew fileformat types, and see\n[fileformats-medimage-extras](https://github.com/ArcanaFramework/fileformats-medimage-extras/blob/6c2dabe91e95687eebc2639bb6f034cf9595ecfc/fileformats/extras/medimage/nifti.py#L30-L48)\nfor an example on how to implement methods to generate sample data for them. Implementations of\nnew fileformats that are specific to FSL, and functions to\ngenerate sample data for them, should be defined in `related-packages/fileformats`\nand `related-packages/fileformats-extras`, respectively.\n\n\n## License\n\nThis project is distributed under the terms of the [Apache License, Version 2.0][license].\n\n[pypi-project]: https://pypi.org/project/pydra-fsl\n\n[pypi-version]: https://img.shields.io/pypi/v/pydra-fsl.svg\n\n[pypi-pyversions]: https://img.shields.io/pypi/pyversions/pydra-fsl.svg\n\n[pypi-downloads]: https://static.pepy.tech/badge/pydra-fsl\n\n[status-docs]: https://github.com/aramis-lab/pydra-fsl/actions/workflows/docs.yaml/badge.svg\n\n[status-test]: https://github.com/aramis-lab/pydra-fsl/actions/workflows/test.yaml/badge.svg\n\n[pydra]: https://pydra.readthedocs.io/\n\n[fsl]: https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FSL\n\n[fsl-install]: https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FslInstallation\n\n[fsl-license]: https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/Licence\n\n[license]: https://spdx.org/licenses/Apache-2.0.html\n\n[status-docs-badge]: https://img.shields.io/badge/docs-latest-brightgreen.svg?style=flat\n\n[status-cicd-badge]: https://github.com/nipype/pydra-fsl/actions/workflows/ci-cd.yaml/badge.svg\n\n[status-docs-link]: https://nipype.github.io/pydra-fsl/\n\n[status-cicd-link]: https://github.com/nipype/pydra-fsl/actions/workflows/ci-cd.yaml\n",
"bugtrack_url": null,
"license": "Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. Definitions. \"License\" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document. \"Licensor\" shall mean the copyright owner or entity authorized by the copyright owner that is granting the License. \"Legal Entity\" shall mean the union of the acting entity and all other entities that control, are controlled by, or are under common control with that entity. For the purposes of this definition, \"control\" means (i) the power, direct or indirect, to cause the direction or management of such entity, whether by contract or otherwise, or (ii) ownership of fifty percent (50%) or more of the outstanding shares, or (iii) beneficial ownership of such entity. \"You\" (or \"Your\") shall mean an individual or Legal Entity exercising permissions granted by this License. \"Source\" form shall mean the preferred form for making modifications, including but not limited to software source code, documentation source, and configuration files. \"Object\" form shall mean any form resulting from mechanical transformation or translation of a Source form, including but not limited to compiled object code, generated documentation, and conversions to other media types. \"Work\" shall mean the work of authorship, whether in Source or Object form, made available under the License, as indicated by a copyright notice that is included in or attached to the work (an example is provided in the Appendix below). \"Derivative Works\" shall mean any work, whether in Source or Object form, that is based on (or derived from) the Work and for which the editorial revisions, annotations, elaborations, or other modifications represent, as a whole, an original work of authorship. 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