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MNT: Depend on newer sphinx (#3067)
* Depend on Sphinx >= 5 * Add apt requirement for graphviz, to restore workflow graphs * Build with Python 3.11, because why not? * Remove unused references producing warnings
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.readthedocs.yml

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build:
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os: ubuntu-22.04
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tools:
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python: "3.10"
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python: "3.11"
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apt_packages:
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- graphviz
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jobs:
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post_checkout:
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- git fetch --unshallow
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- path: .
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extra_requirements:
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- doc
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- path: wrapper/

docs/outputs.rst

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A multi-modal parcellation of human cerebral cortex. Nature. 2016.
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doi:`10.1038/nature18933 <https://doi.org/10.1038/nature18933>`_
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.. [Hallquist2013] Hallquist MN, Hwang K, Luna B. The Nuisance of Nuisance Regression.
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NeuroImage. 2013. doi:`10.1016/j.neuroimage.2013.05.116
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<https://doi.org/10.1016/j.neuroimage.2013.05.116>`_
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.. [Jenkinson2002] Jenkinson M, Bannister P, Brady M, Smith S. Improved optimization for the
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robust and accurate linear registration and motion correction of brain images. Neuroimage.
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2002. doi:`10.1016/s1053-8119(02)91132-8 <https://doi.org/10.1016/s1053-8119(02)91132-8>`__.
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.. [Lindquist2019] Lindquist, MA, Geuter, S, and Wager, TD, Caffo, BS,
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Modular preprocessing pipelines can reintroduce artifacts into fMRI data.
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Human Brain Mapping. 2019. doi: `10.1002/hbm.24528
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<https://doi.org/10.1002/hbm.24528>`_
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.. [Muschelli2014] Muschelli J, Nebel MB, Caffo BS, Barber AD, Pekar JJ, Mostofsky SH,
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Reduction of motion-related artifacts in resting state fMRI using aCompCor. NeuroImage. 2014.
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doi:`10.1016/j.neuroimage.2014.03.028 <http://doi.org/10.1016/j.neuroimage.2014.03.028>`_

pyproject.toml

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[project.optional-dependencies]
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doc = [
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"pydot >= 1.2.3",
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"sphinx >= 1.8",
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"sphinx >= 5",
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"sphinx-argparse",
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"sphinx_rtd_theme>=0.5.2",
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]

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