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Merge pull request #3 from mnoergaard/main
Refactor of fMRIPrep to PETPrep
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README.rst

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*fMRIPrep*: A Robust Preprocessing Pipeline for fMRI Data
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*PETPrep*: A Robust Preprocessing Pipeline for PET Data
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=========================================================
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*fMRIPrep* is a *NiPreps (NeuroImaging PREProcessing toolS)* application
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*PETPrep* is a *NiPreps (NeuroImaging PREProcessing toolS)* application
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(`www.nipreps.org <https://www.nipreps.org>`__) for the preprocessing of
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task-based and resting-state functional MRI (fMRI).
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positron emission tomography (PET) imaging.
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.. image:: https://img.shields.io/badge/RRID-SCR__016216-blue.svg
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:target: https://doi.org/10.1038/s41592-018-0235-4
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:alt: RRID:SCR_016216
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.. image:: https://img.shields.io/pypi/v/fmriprep.svg
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:target: https://pypi.python.org/pypi/fmriprep/
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.. image:: https://img.shields.io/pypi/v/petprep.svg
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:target: https://pypi.python.org/pypi/petprep/
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:alt: Latest Version
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.. image:: https://circleci.com/gh/nipreps/fmriprep/tree/master.svg?style=shield
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:target: https://circleci.com/gh/nipreps/fmriprep/tree/master
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.. image:: https://circleci.com/gh/nipreps/petprep/tree/master.svg?style=shield
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:target: https://circleci.com/gh/nipreps/petprep/tree/master
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.. image:: https://readthedocs.org/projects/fmriprep/badge/?version=latest
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:target: https://fmriprep.org/en/latest/?badge=latest
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.. image:: https://readthedocs.org/projects/petprep/badge/?version=latest
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:target: https://petprep.org/en/latest/?badge=latest
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:alt: Documentation Status
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.. image:: https://img.shields.io/badge/doi-10.1038%2Fs41592--018--0235--4-blue.svg
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:target: https://doi.org/10.1038/s41592-018-0235-4
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:alt: Published in Nature Methods
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.. image:: https://img.shields.io/badge/docker-nipreps/fmriprep-brightgreen.svg?logo=docker&style=flat
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:target: https://hub.docker.com/r/nipreps/fmriprep/tags/
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.. image:: https://img.shields.io/badge/docker-nipreps/petprep-brightgreen.svg?logo=docker&style=flat
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:target: https://hub.docker.com/r/nipreps/petprep/tags/
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:alt: Docker image available!
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.. image:: https://codeocean.com/codeocean-assets/badge/open-in-code-ocean.svg
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About
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-----
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.. image:: https://github.com/oesteban/fmriprep/raw/f4c7a9804be26c912b24ef4dccba54bdd72fa1fd/docs/_static/fmriprep-21.0.0.svg
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.. image:: https://github.com/oesteban/petprep/raw/f4c7a9804be26c912b24ef4dccba54bdd72fa1fd/docs/_static/petprep-21.0.0.svg
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*fMRIPrep* is a functional magnetic resonance imaging (fMRI) data
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*PETPrep* is a positron emission tomography (PET) data
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preprocessing pipeline that is designed to provide an easily accessible,
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state-of-the-art interface that is robust to variations in scan acquisition
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protocols and that requires minimal user input, while providing easily
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interpretable and comprehensive error and output reporting.
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It performs basic processing steps (coregistration, normalization, unwarping,
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noise component extraction, segmentation, skull-stripping, etc.) providing
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outputs that can be easily submitted to a variety of group level analyses,
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including task-based or resting-state fMRI, graph theory measures, and surface
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including PET imaging studies, graph theory measures, and surface
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or volume-based statistics.
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.. note::
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*fMRIPrep* performs minimal preprocessing.
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*PETPrep* performs minimal preprocessing.
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Here we define 'minimal preprocessing' as motion correction, field
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unwarping, normalization, bias field correction, and brain extraction.
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See the `workflows section of our documentation
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<https://fmriprep.readthedocs.io/en/latest/workflows.html>`__ for more details.
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<https://petprep.readthedocs.io/en/latest/workflows.html>`__ for more details.
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The *fMRIPrep* pipeline uses a combination of tools from well-known software
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The *PETPrep* pipeline uses a combination of tools from well-known software
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packages, including FSL_, ANTs_, FreeSurfer_ and AFNI_.
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This pipeline was designed to provide the best software implementation for each
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state of preprocessing, and will be updated as newer and better neuroimaging
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software become available.
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This tool allows you to easily do the following:
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- Take fMRI data from raw to fully preprocessed form.
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- Take PET data from raw to fully preprocessed form.
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- Implement tools from different software packages.
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- Achieve optimal data processing quality by using the best tools available.
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- Generate preprocessing quality reports, with which the user can easily
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speed-up from manual processing or shell-scripted pipelines.
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More information and documentation can be found at
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https://fmriprep.readthedocs.io/
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https://petprep.readthedocs.io/
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Principles
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----------
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*fMRIPrep* is built around three principles:
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*PETPrep* is built around three principles:
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1. **Robustness** - The pipeline adapts the preprocessing steps depending on
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the input dataset and should provide results as good as possible
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automatic fashion.
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3. **"Glass box"** philosophy - Automation should not mean that one should not
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visually inspect the results or understand the methods.
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Thus, *fMRIPrep* provides visual reports for each subject, detailing the
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Thus, *PETPrep* provides visual reports for each subject, detailing the
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accuracy of the most important processing steps.
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This, combined with the documentation, can help researchers to understand
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the process and decide which subjects should be kept for the group level
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Citation
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--------
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**Citation boilerplate**.
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Please acknowledge this work using the citation boilerplate that *fMRIPrep* includes
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Please acknowledge this work using the citation boilerplate that *PETPrep* includes
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in the visual report generated for every subject processed.
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For a more detailed description of the citation boilerplate and its relevance,
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please check out the
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**Plagiarism disclaimer**.
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The boilerplate text is public domain, distributed under the
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`CC0 license <https://creativecommons.org/publicdomain/zero/1.0/>`__,
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and we recommend *fMRIPrep* users to reproduce it verbatim in their works.
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and we recommend *PETPrep* users to reproduce it verbatim in their works.
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Therefore, if reviewers and/or editors raise concerns because the text is flagged by automated
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plagiarism detection, please refer them to the *NiPreps* community and/or the note to this
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effect in the `boilerplate documentation page <https://www.nipreps.org/intro/transparency/#citation-boilerplates>`__.
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**Papers**.
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*fMRIPrep* contributors have published two relevant papers:
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*PETPrep* contributors have published two relevant papers:
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`Esteban et al. (2019) <https://doi.org/10.1038/s41592-018-0235-4>`__
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[`preprint <https://doi.org/10.1101/306951>`__], and
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`Esteban et al. (2020) <https://doi.org/10.1038/s41596-020-0327-3>`__
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[`preprint <https://doi.org/10.1101/694364>`__].
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**Other**.
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Other materials that have been generated over time include the
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`OHBM 2018 software demonstration <https://effigies.github.io/fmriprep-demo/>`__
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`OHBM 2018 software demonstration <https://effigies.github.io/petprep-demo/>`__
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and some conference posters:
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* Organization for Human Brain Mapping 2018
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License information
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-------------------
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*fMRIPrep* adheres to the
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*PETPrep* adheres to the
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`general licensing guidelines <https://www.nipreps.org/community/licensing/>`__
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of the *NiPreps framework*.
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License
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~~~~~~~
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Copyright (c) the *NiPreps* Developers.
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As of the 21.0.x pre-release and release series, *fMRIPrep* is
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As of the 21.0.x pre-release and release series, *PETPrep* is
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licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at

docs/Makefile

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# User-friendly check for sphinx-build
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ifeq ($(shell which $(SPHINXBUILD) >/dev/null 2>&1; echo $$?), 1)
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$(error The '$(SPHINXBUILD)' command was not found. Make sure you have Sphinx installed, then set the SPHINXBUILD environment variable to point to the full path of the '$(SPHINXBUILD)' executable. Alternatively you can add the directory with the executable to your PATH. If you don\'t have Sphinx installed, grab it from https://www.sphinx-doc.org/)
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$(error The '$(SPHINXBUILD)' command was not found. Make sure you have Sphinx installed, then set the SPHINXBUILD environment variable to point to the full path of the '$(SPHINXBUILD)' executable. Alternatively you can add the directory with the executable to your PATH. If you don''t have Sphinx installed, grab it from https://www.sphinx-doc.org/)
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endif
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# Internal variables.
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@echo
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@echo "Build finished; now you can run "qcollectiongenerator" with the" \
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".qhcp project file in $(BUILDDIR)/qthelp, like this:"
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@echo "# qcollectiongenerator $(BUILDDIR)/qthelp/fMRIprep.qhcp"
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@echo "# qcollectiongenerator $(BUILDDIR)/qthelp/PETPrep.qhcp"
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@echo "To view the help file:"
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@echo "# assistant -collectionFile $(BUILDDIR)/qthelp/fMRIprep.qhc"
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@echo "# assistant -collectionFile $(BUILDDIR)/qthelp/PETPrep.qhc"
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.PHONY: applehelp
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applehelp:
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@echo
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@echo "Build finished."
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@echo "To view the help file:"
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@echo "# mkdir -p $$HOME/.local/share/devhelp/fMRIprep"
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@echo "# ln -s $(BUILDDIR)/devhelp $$HOME/.local/share/devhelp/fMRIprep"
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@echo "# mkdir -p $$HOME/.local/share/devhelp/PETPrep"
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@echo "# ln -s $(BUILDDIR)/devhelp $$HOME/.local/share/devhelp/PETPrep"
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@echo "# devhelp"
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.PHONY: epub

docs/_static/sbatch.slurm

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#!/bin/bash
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#
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#SBATCH -J fmriprep
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#SBATCH -J petprep
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#SBATCH --time=48:00:00
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#SBATCH -n 1
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#SBATCH --cpus-per-task=16
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# ------------------------------------------
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BIDS_DIR="$STUDY/data"
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DERIVS_DIR="derivatives/fmriprep-1.5.0"
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DERIVS_DIR="derivatives/petprep-1.5.0"
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LOCAL_FREESURFER_DIR="$STUDY/data/derivatives/freesurfer-6.0.1"
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# Prepare some writeable bind-mount points.
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TEMPLATEFLOW_HOST_HOME=$HOME/.cache/templateflow
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FMRIPREP_HOST_CACHE=$HOME/.cache/fmriprep
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FMRIPREP_HOST_CACHE=$HOME/.cache/petprep
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mkdir -p ${TEMPLATEFLOW_HOST_HOME}
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mkdir -p ${FMRIPREP_HOST_CACHE}
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# Designate a templateflow bind-mount point
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export SINGULARITYENV_TEMPLATEFLOW_HOME="/templateflow"
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SINGULARITY_CMD="singularity run --cleanenv -B $BIDS_DIR:/data -B ${TEMPLATEFLOW_HOST_HOME}:${SINGULARITYENV_TEMPLATEFLOW_HOME} -B $L_SCRATCH:/work -B ${LOCAL_FREESURFER_DIR}:/fsdir $STUDY/images/nipreps_fmriprep_1.5.0.simg"
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SINGULARITY_CMD="singularity run --cleanenv -B $BIDS_DIR:/data -B ${TEMPLATEFLOW_HOST_HOME}:${SINGULARITYENV_TEMPLATEFLOW_HOME} -B $L_SCRATCH:/work -B ${LOCAL_FREESURFER_DIR}:/fsdir $STUDY/images/nipreps_petprep_1.5.0.simg"
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# Parse the participants.tsv file and extract one subject ID from the line corresponding to this SLURM task.
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subject=$( sed -n -E "$((${SLURM_ARRAY_TASK_ID} + 1))s/sub-(\S*)\>.*/\1/gp" ${BIDS_DIR}/participants.tsv )

docs/api.rst

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================
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The *NiPreps* community and contributing guidelines
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---------------------------------------------------
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*fMRIPrep* is a *NiPreps* application, and abides by the
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*PETPrep* is a *NiPreps* application, and abides by the
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`NiPreps Community guidelines <https://www.nipreps.org/community/>`__.
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Please, make sure you have read and understood all the documentation
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provided in the `NiPreps portal <https://www.nipreps.org>`__ before
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you get started.
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Setting up your development environment
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---------------------------------------
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We believe that *fMRIPrep* must be free to use, inspect, and critique.
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We believe that *PETPrep* must be free to use, inspect, and critique.
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Correspondingly, you should be free to modify our software to improve it
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or adapt it to new use cases and we especially welcome contributions to
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improve it or its documentation.
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Internal configuration system
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.. automodule:: fmriprep.config
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.. automodule:: petprep.config
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:members: from_dict, load, get, dumps, to_filename, init_spaces
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Workflows
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.. automodule:: fmriprep.workflows.base
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.. automodule:: fmriprep.workflows.pet
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.. automodule:: fmriprep.workflows.pet.fit
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.. automodule:: petprep.workflows.base
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.. automodule:: petprep.workflows.pet
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.. automodule:: petprep.workflows.pet.fit

docs/benchmarks.rst

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| B | 2 T1w, 6 PEPolar fieldmaps, 8 SE-BOLD (4274 volumes total) |
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+------------+----------------------------------------------------------------------------------------+
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fMRIPrep versions and modes
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PETPrep versions and modes
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~~~~~~~~~~~~~~~~~~~~~~~~~~~
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All commands took the form ``fmriprep sourcedata/raw . participant $OPTIONS``.
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All commands took the form ``petprep sourcedata/raw . participant $OPTIONS``.
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The specific options for each version or mode are presented in the following table.
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+------------+----------------------------------------------------------------------------------------+
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* Memory: 64GiB
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* Storage: PC801 NVMe SK hynix 2TB
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* OS: Ubuntu 22.04
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* Environment: Docker images published to https://hub.docker.com/r/nipreps/fmriprep/
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* Environment: Docker images published to https://hub.docker.com/r/nipreps/petprep/
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Benchmarks
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----------

docs/conf.py

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# fmriprep documentation build configuration file, created by
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# petprep documentation build configuration file, created by
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# sphinx-quickstart on Mon May 9 09:04:25 2016.
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#
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# This file is execfile()d with the current directory set to its
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master_doc = 'index'
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# General information about the project.
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project = 'fmriprep'
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author = 'The fMRIPrep developers'
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project = 'petprep'
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author = 'The PETPrep developers'
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copyright = f'2016-, {author}'
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# The version info for the project you're documenting, acts as replacement for
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# The name for this set of Sphinx documents.
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# "<project> v<release> documentation" by default.
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# html_title = u'fmriprep vversion'
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# html_title = u'petprep vversion'
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# A shorter title for the navigation bar. Default is the same as html_title.
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# html_short_title = None
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# html_search_scorer = 'scorer.js'
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# Output file base name for HTML help builder.
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htmlhelp_basename = 'fmriprepdoc'
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htmlhelp_basename = 'petprepdoc'
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# -- Options for LaTeX output ---------------------------------------------
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# (source start file, target name, title,
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# author, documentclass [howto, manual, or own class]).
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latex_documents = [
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(master_doc, 'fmriprep.tex', 'fMRIprep Documentation', author, 'manual'),
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(master_doc, 'petprep.tex', 'PETPrep Documentation', author, 'manual'),
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]
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# The name of an image file (relative to this directory) to place at the top of
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# One entry per manual page. List of tuples
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# (source start file, name, description, authors, manual section).
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man_pages = [(master_doc, 'fmriprep', 'fmriprep Documentation', [author], 1)]
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man_pages = [(master_doc, 'petprep', 'petprep Documentation', [author], 1)]
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# If true, show URL addresses after external links.
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# man_show_urls = False
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texinfo_documents = [
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(
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master_doc,
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'fmriprep',
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'fMRIprep Documentation',
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'petprep',
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'PETPrep Documentation',
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author,
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'fmriprep',
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'petprep',
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'One line description of project.',
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'Miscellaneous',
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),
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# The following is used by sphinx.ext.linkcode to provide links to github
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linkcode_resolve = make_linkcode_resolve(
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'fmriprep',
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'https://github.com/nipreps/fmriprep/blob/{revision}/{package}/{path}#L{lineno}',
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'petprep',
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'https://github.com/nipreps/petprep/blob/{revision}/{package}/{path}#L{lineno}',
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)
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# Example configuration for intersphinx: refer to the Python standard library.

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