fsl-pipe 1.1.1

Declarative pipelines based on Filetrees

Declarative pipelines based on Filetrees. A pipeline is defined by:

• A file-tree, which defines the directory structure of the inputs and outputs of the pipeline. A tutorial on these file-trees is available here.
• A set of recipes describing how all the pipeline outputs are produced. A tutorial on writing these recipes is available here. Fsl-pipe will stitch these recipes together to produce any user-selected output files. Resulting jobs will either run locally, run distributed using dask, or be submitted to a cluster using fsl-sub.

An example diffusion MRI pipeline using fsl-pipe with detailed comments is available here.

Installation

pip install fsl-pipe

Any bug reports and feature requests are very welcome (see issue tracker).

Setting up local test environment

First clone the repository:

git clone https://git.fmrib.ox.ac.uk/fsl/fsl-pipe.git

Then, we install the package in an interactive manner:

cd fsl-pipe
pip install -e .

Running tests

Tests are run using the pytest framework. After installation (pip install pytest) they can be run from the project root as:

pytest src/tests

Compiling documentation

The documentation is build using sphinx. After installation (pip install sphinx) run:

cd doc
sphinx-build source build
open build/index.html

Contributing

Merge requests with any bug fixes or documentation updates are always welcome.

For new features, please raise an issue to allow for discussion before you spend the time implementing them.

Releasing new versions

• Ensure CHANGELOG.md is up to date.
• Run bump2version (install using pip install bump2version)
• Push to gitlab (including tags in the push)
• After the continuous integration (CI) succeeds, manually run the job to upload fsl-pipe to pypi (see here)
• Upload code on conda-forge using their automated release detection.