Subject: Inquiry About GSOC 2025 – Improving Raw Data Browsing in MNE-Python
Dear MNE Team,
I hope you’re doing well. I am writing to express my keen interest in contributing to “Improve Raw Data Browsing (PyQtGraph/Matplotlib)” as part of Google Summer of Code 2025. As an aspiring AI/ML developer, I find MNE-Python’s role in neuroscience and EEG data analysis fascinating, and I would love to contribute while learning from the community.
I am currently a first-year undergraduate student specializing in AI and Machine Learning. While I am still in the early stages of my journey, I have a strong foundation in Python, data structures, and basic machine learning concepts. I am actively learning PyQtGraph, Matplotlib, and signal processing, and I am eager to apply and expand my skills through open-source contributions.
To better prepare for this project, I would appreciate your guidance on the following:
As a beginner, what essential skills should I focus on to effectively contribute to this project?
Are there any recommended learning resources for PyQtGraph, Matplotlib, EEG data visualization, or MNE-Python’s data browsing features?
Would you recommend any beginner-friendly issues or specific parts of MNE-Python’s codebase that I can explore to get hands-on experience before GSoC begins?
I am highly motivated to learn and contribute, whether through GSoC or independently. Any advice or suggestions would be greatly appreciated.
most of our GSoC projects require neuroscience domain knowledge. In our experience, it’s difficult even for accomplished programmers to “dive right in” to the MNE-Python codebase without that. The data browser improvements probably require the least amount of background, but even there it’s important to know the terminology, understand what scientists are looking for when they use the data browsers, etc.
All of those libraries have many tutorials, user guides, and/or contributor guides on their websites.
We haven’t been very diligent about labelling our issues as easy or good-first-issue or similar, so you may just need to read through a bunch of them until you find one that makes sense / that you think you know how to solve.
Thank you so much for the clarification. I will look into those libraries and have a solid base before applying! Looking forward to work on this project
hey I want to get started with DOC: add crossrefs in the info docstring #7774. I have cloned the repo but I cant seem to find the exact info docstring. could you let me know the file name? I found one docs.py in mne/utils/
we use a docstring lookup system that fills in some docstrings at import time. mne/utils/docs.py is where it’s found; it’s a huge dictionary called docdict. Match the %(placeholder)s found in the source .py file with a key of the same name in docdict; that’s what will need editing.