The fslpy
project is a FSL
programming library written in Python. It is used by FSLeyes.
fslpy
is tested against Python versions 3.8, 3.9, 3.10, and 3.11.
Install fslpy
and its core dependencies via pip:
pip install fslpy
fslpy
is also available on conda-forge:
conda install -c conda-forge fslpy
All of the core dependencies of fslpy
are listed in the
pyproject.toml file.
Some optional dependencies (labelled extra
in pyproject.toml
) provide
addditional functionality:
wxPython
: The fsl.utils.idle module has functionality to schedule functions on thewx
idle loop.indexed_gzip
: The fsl.data.image.Image class can useindexed_gzip
to keep large compressed images on disk instead of decompressing and loading them into memory..trimesh
/rtree
: The fsl.data.mesh.TriangleMesh class has some methods which usetrimesh
to perform geometric queries on the mesh.Pillow
: The fsl.data.bitmap.Bitmap class usesPillow
to load image files.
If you are using Linux, you need to install wxPython first, as binaries are not available on PyPI. Install wxPython like so, changing the URL for your specific platform:
pip install -f https://extras.wxpython.org/wxPython4/extras/linux/gtk2/ubuntu-16.04/ wxpython
Once wxPython has been installed, you can type the following to install the remaining optional dependencies:
pip install "fslpy[extra]"
Dependencies for testing and documentation are also listed in pyproject.toml
,
and are respectively labelled as test
and doc
.
The fsl.data.dicom module requires the presence of Chris Rorden's dcm2niix program.
The rtree
library assumes that libspatialindex
is installed on
your system.
The fsl.transform.x5 module uses h5py, which requires libhdf5
.
API documentation for fslpy
is hosted at
https://open.win.ox.ac.uk/pages/fsl/fslpy/.
fslpy
is documented using sphinx. You
can build the API documentation by running:
pip install ".[doc]" sphinx-build doc html
The HTML documentation will be generated and saved in the html/
directory.
Run the test suite via:
pip install ".[test]" pytest
Some tests will only pass if the test environment meets certain criteria -
refer to the tool.pytest.init_options
section of
[pyproject.toml
](pyproject.toml) for a list of [pytest
marks](https://docs.pytest.org/en/7.1.x/example/markers.html) which can be
selectively enabled or disabled.
If you are interested in contributing to fslpy
, check out the
contributing guide.
The fsl.data.dicom module is little more than a thin wrapper around Chris Rorden's dcm2niix program.
The example.mgz file, used for testing,
originates from the nibabel
test data set.