Metadata-Version: 2.1
Name: fsleyes
Version: 1.0.13
Summary: FSLeyes, the FSL image viewer
Home-page: https://git.fmrib.ox.ac.uk/fsl/fsleyes/fsleyes
Author: Paul McCarthy
Author-email: pauldmccarthy@gmail.com
License: Apache License Version 2.0
Description: FSLeyes
        =======
        
        .. image:: https://img.shields.io/pypi/v/fsleyes.svg
           :target: https://pypi.python.org/pypi/fsleyes/
        
        .. image:: https://anaconda.org/conda-forge/fsleyes/badges/version.svg
           :target: https://anaconda.org/conda-forge/fsleyes
        
        .. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.1470761.svg
           :target: https://doi.org/10.5281/zenodo.1470761
        
        .. image:: https://git.fmrib.ox.ac.uk/fsl/fsleyes/fsleyes/badges/master/coverage.svg
           :target: https://git.fmrib.ox.ac.uk/fsl/fsleyes/fsleyes/commits/master/
        
        
        `FSLeyes <https://git.fmrib.ox.ac.uk/fsl/fsleyes/fsleyes>`_ is the `FSL
        <http://fsl.fmrib.ox.ac.uk/fsl/fslwiki>`_ image viewer.
        
        
        Installation
        ------------
        
        
        FSLeyes is a GUI application written in Python, and built on `wxPython
        <https://www.wxpython.org>`_. FSLeyes requires OpenGL for visualisation.
        
        
        In the majority of cases, you should be able to follow the installation
        instructions outlined at the FSLeyes home page:
        
        https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FSLeyes.
        
        
        Dependencies
        ------------
        
        
        All of the core dependencies of FSLeyes are listed in `requirements.txt
        <requirements.txt>`_.
        
        
        Some extra dependencies, which provide additional functionality, are listed in
        `requirements-extra.txt <requirements-extra.txt>`_ and
        `requirements-notebook.txt <requirements-notebook.txt>`_.
        
        
        Dependencies for running tests and building the documentation are listed
        in `requirements-dev.txt <requirements-dev.txt>`_.
        
        
        Being an OpenGL application, FSLeyes can only be used on computers with
        graphics hardware (or a software GL renderer) that supports one of the
        following versions:
        
        
        - OpenGL 1.4, with the following extensions:
        
          - ``ARB_vertex_program``
          - ``ARB_fragment_program``
          - ``EXT_framebuffer_object``
          - ``GL_ARB_texture_non_power_of_two``
        
        - OpenGL 2.1, with the following extensions:
        
          - ``EXT_framebuffer_object``
          - ``ARB_instanced_arrays``
          - ``ARB_draw_instanced``
        
        
        Documentation
        -------------
        
        The FSLeyes user and API documentation are hosted at:
        
         - https://open.win.ox.ac.uk/pages/fsl/fsleyes/fsleyes/userdoc/
         - https://open.win.ox.ac.uk/pages/fsl/fsleyes/fsleyes/apidoc/
        
        
        The FSLeyes user and API documentation is written in ReStructuredText, and can
        be built using `sphinx <http://www.sphinx-doc.org/>`_::
        
            pip install -r requirements-dev.txt
            python setup.py userdoc
            python setup.py apidoc
        
        The documentation will be generated and saved in ``userdoc/html/`` and
        ``apidoc/html/``.
        
        
        Credits
        -------
        
        
        Some of the FSLeyes icons are derived from the Freeline icon set, by Enes Dal,
        available at https://www.iconfinder.com/Enesdal, and released under the
        Creative Commons (Attribution 3.0 Unported) license.
        
        The volumetric spline interpolation routine uses code from:
        
        Daniel Ruijters and Philippe Thévenaz,
        GPU Prefilter for Accurate Cubic B-Spline Interpolation,
        The Computer Journal, vol. 55, no. 1, pp. 15-20, January 2012.
        http://dannyruijters.nl/docs/cudaPrefilter3.pdf
        
        The GLSL parser is based on code by Nicolas P . Rougier, available at
        https://github.com/rougier/glsl-parser, and released under the BSD license.
        
        DICOM to NIFTI conversion is performed with Chris Rorden's dcm2niix
        (https://github.com/rordenlab/dcm2niix).
        
        The *brain_colours* colour maps were produced and provided by Cyril Pernet
        (https://doi.org/10.1111/ejn.14430).
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Scientific/Engineering :: Visualization
Requires-Python: >=3.7
Description-Content-Type: text/x-rst
Provides-Extra: extras
