Skip to main content
https://img.shields.io/pypi/v/fslpy.svg https://anaconda.org/conda-forge/fslpy/badges/version.svg https://zenodo.org/badge/DOI/10.5281/zenodo.1470750.svg https://git.fmrib.ox.ac.uk/fsl/fslpy/badges/master/coverage.svg

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.

Installation

Install fslpy and its core dependencies via pip:

pip install fslpy

fslpy is also available on conda-forge:

conda install -c conda-forge fslpy

Dependencies

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 the wx idle loop.

  • indexed_gzip: The fsl.data.image.Image class can use indexed_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 use trimesh to perform geometric queries on the mesh.

  • Pillow: The fsl.data.bitmap.Bitmap class uses Pillow 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.

Non-Python dependencies

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.

Documentation

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.

Tests

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.

Contributing

If you are interested in contributing to fslpy, check out the contributing guide.

Credits

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.

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

fslpy-3.15.3.tar.gz (4.7 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

fslpy-3.15.3-py3-none-any.whl (4.7 MB view details)

Uploaded Python 3

File details

Details for the file fslpy-3.15.3.tar.gz.

File metadata

  • Download URL: fslpy-3.15.3.tar.gz
  • Upload date:
  • Size: 4.7 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.13

File hashes

Hashes for fslpy-3.15.3.tar.gz
Algorithm Hash digest
SHA256 40b75597e787cd7188d3ae4e47ef6a90346a36167a7b0cdde8dfa73c07cca2a4
MD5 7e9f6cd03bd2ddc88d612c1ff6e6c9bf
BLAKE2b-256 665adc40e09c0ebe5650823bb3c49dcc679a8ef16e91a6b3959d2f8c85b06876

See more details on using hashes here.

File details

Details for the file fslpy-3.15.3-py3-none-any.whl.

File metadata

  • Download URL: fslpy-3.15.3-py3-none-any.whl
  • Upload date:
  • Size: 4.7 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.13

File hashes

Hashes for fslpy-3.15.3-py3-none-any.whl
Algorithm Hash digest
SHA256 d26845d002338ebeb4618cbceab5a10058e187c4a10777103cbd8c89a6be3ebd
MD5 23b6c5deed1b00b0a687dd5154f315a4
BLAKE2b-256 82cd90c0098370f8fdc995f7f69a882f3a088867ecd62c5d0fe7f1b6c56a1643

See more details on using hashes here.

Release history Release notifications | RSS feed

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