Name: Yibei Chen (@yibeichan)
Email: yibeichan@gmail.com
Satra Ghosh (@satra)
Dorota Jarecka (@djarecka)
Hao-Ting Wang (@htwangtw)
Chris Markiewicz (@effigies)
The goal of this project was to convert existing neuroimaging analytical workflows that are written in other languages to the new dataflow engine Pydra. The main deliverables of the project are comprehensive Pydra workflows that use interfaces from neuroimaging packages such as FSL, SPM, ANTs, AFNI, FreeSurfer.
During the past ten weeks, I have contributed in four GitHub Repos: pydra-tutorial, pydra-fsl, pydra-fitlins, and pydra
- converting pydra tutorial into jupyterbook - done (link)
- converting first-level GLM (Nilearn) to Pydra - done (link)
- see this PR
- converting two-level GLM (Nilearn) to Pydra - hasn't been merged yet (PR)
- this notebook hasn't passed the tests in GHA but works fine locally for @yibeichan (Python 3.7 & 3.8) and @effigies (Python 3.10), though @djarecka (Python 3.8) still has problems with the notebook locally.
- it is also related to Pydra that error messages are not very clear enough to identify where (which node) the error is (e.g., this PR made by @effigies)
- converting fitlins to Pydra - hasn't been merged yet (PR)
- we encountered some typing issues that are related to python version and needed a decision
- currently the converting is conducted in a half-dynamic and half-static way. This repo is related to GLM in Nilearn and so we decided to make it fully dynamic after converting the two-level GLM (Nilearn) to Pydra.
- converting FSL to Pydra - hasn't been merged yet (PR)
- in this task, I have improved the
converter.py
, converted all interfaces that are needed for three-level GLM, and documented the wiki - we encountered some Large File Storage (LFS) issues that needed changes in GHA (see this PR)
- we also encountered some issues that are related to the Pydra pacakge, see this PR by @yibeichan and PRs from @djarecka (e.g., here and here)
- in this task, I have improved the
My goal/task was to convert as many workflows as possible; however, unexpected errors/bugs have occurred from time to time and have slowed down the progress. Meanwhile, the journey itself has been very rewarding and I deeply appreciate every of my mentors for their patience and help. Thanks for bringing me into an open, equal, and meaningful community.
I will keep working on this project after GSoC.
@yibeichan - Thank you for all your PRs! Below some comments and updates: