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Preparation for release 2.0.0
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.readthedocs.yaml

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build:
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os: ubuntu-20.04
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tools:
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python: "3.9"
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python: "3.10"
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# Build documentation in the docs/ directory with Sphinx
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sphinx:

AUTHORS.rst

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.. _core_devs:
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Core developers
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...............
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Developers
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..........
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The SUITPy core developers are:
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Contributors to SUITPy include:
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*Joern Diedrichsen
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*Jörn Diedrichsen
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*Maedbh King
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*Da Zhi
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Other contributors:
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*Ladan Shahshahani
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*Yao Li
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*Carlos Hernandez-Castillo
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*Suzanne Witt
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*Ladan Shahshahani
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*Bassel Arafat
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*Caroline Nettekoven
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*Yaping Wang
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.. _citing:
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CITATION.cff

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given-names: "Da"
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orcid: "https://orcid.org/0000-0001-6023-6523"
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title: "SUIT: A Python-based toolbox for cerebellar imaging analysis"
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version: 1.3.0
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date-released: 2023-10-08
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version: 2.0.0
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date-released: 2025-10-26
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url: "https://github.com/DiedrichsenLab/SUITPy"

README.rst

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The required dependencies to use the software are:
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* python >= 3.6
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* python >= 3.10,
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* setuptools
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* numpy >= 1.16
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* nibabel >= 2.5
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* pandas >= 0.24
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* matplotlib >= 1.5.1
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* scipy >=1.0
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* numpy >= 1.22.0
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* nibabel >= 3.2.1
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* pandas >= 2.0.0
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* matplotlib >= 3.5.0
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* plotly >= 5.10.0
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* scipy >= 1.9.0
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* neuroimagingtools >= 1.1.1
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* antspyx >= 0.6.1
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* torch >= 2.0.0
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Install
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-------

SUITPy/__init__.py

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"""
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import gzip
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__version__ = '1.3.2'
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__version__ = '2.0.0'
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from .atlas import (fetch_atlas)
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docs/source/index.rst

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.. SUITPy documentation master file, created by
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sphinx-quickstart on Tue Aug 11 12:46:22 2020.
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You can adapt this file completely to your liking, but it should at least
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contain the root `toctree` directive.
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.. SUITPy documentation master file
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SUITPy Documentation
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====================
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SUITPy is a Python toolbox dedicated to the analysis of imaging data of the human cerebellum. It provides a subset of the SUIT toolbox for Matlab (https://github.com/jdiedrichsen/suit).
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Currently, only mapping of volume data to the flatmap and display of the flatmap are implemented.
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SUITPy is a Python toolbox for the analysis of imaging data from the human cerebellum. With the new version 2 release it will have most of the functionality of the SUIT toolbox for Matlab (https://github.com/jdiedrichsen/suit).
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The newest developments will be implemented in the Python version.
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.. toctree::
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:maxdepth: 1
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Acknowledgements
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----------------
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SUITPy is developed by the Diedrichsenlab and collaborators, Carlos Hernandez-Castillo, Yao Li
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SUITPy is developed by the Diedrichsenlab and collaborators, including
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Carlos Hernandez-Castillo, Yao Li, Yaping Wang, Bassel Arafat, Caroline Nettekoven, Ladan Shahshahani, Da Zhi, Maedbh King, Jorn Diedrichsen, and many others.
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Funding for this work was provided by:
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.. image::
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images/CIHR.png
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images/RCP.png
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:width: 200 px
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.. image::
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images/RCP.png
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images/CIHR.png
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:width: 200 px
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Indices and tables
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------------------
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docs/source/install.rst

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* nibabel >= 3.2.1
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* pandas >= 2.0.0
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* matplotlib >= 3.5.0
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* plotly >= 5.10.0
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* scipy >= 1.9.0
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* neuroimagingtools >= 1.1.1
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* antspyx >= 0.6.1
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* torch >= 2.5.0
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(It is highly recommended to use the latest version of PyTorch as new generations of GPU (50 series, etc.) use the sm_120 CUDA architecture which is not compatible with older versions.)
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* torch >= 2.0.0
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Install over pip
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docs/source/isolate.rst

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--T1: T1w- image
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--T2: Additional (or standalone T2w image)
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--result_folder dir:
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--brain_mask Mask_image: Binary mask image from skull stripping step to improve affine normalization
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--template template: Templa] [--params PARAMS] [--save_cropped_files] [--save_transform]
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--result_folder: Folder to save the results (default: current folder)
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--brain_mask: Binary mask image from skull stripping step to improve affine normalization (optional)
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--template: Template for affine normalization
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--save_cropped_files: Save the images cropped and resampled to the UNet window
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--save_transform: Save the affine transformation matrix
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Architecture

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