SLAM - A pure python package for Surface anaLysis And Modeling

Title

SLAM - A pure python package for Surface anaLysis And Modeling

Leaders

• Guillaume AUZIAS : @AuziasGuillaume/guillaume.auzias
• Alexandre PRON: @AlexandrePron/alexp

Collaborators

No response

Brainhack Global 2022 Event

Brainhack Marseille

Project Description

Slam (https://brain-slam.github.io/slam/) is an open source python package dedicated to the representation of neuroanatomical surfaces stemming from MRI data in the form of triangular meshes and to their processing and analysis.

Main features include read/write gifti (and nifti) file format, geodesic distance computation, several implementations of graph Laplacian and Gradient, mesh surgery (boundary identification, large hole closing), several types of mapping between the mesh and a sphere, a disc… Have a look at the examples on the documentation website: https://brain-slam.github.io/slam/auto_examples/index.html

Link to project repository/sources

https://github.com/brain-slam/slam

Goals for Brainhack Global

• to improve the documentation of basic core functions and modules (e.g. the curvature.py module)
• to increase unit test coverage and quality of basic core functions and modules
• to speed-up specific pieces of code such as the computation of the curvatures
• to help potential users to get familiar with this python package depending on their use cases

Good first issues

1. issue one: https://github.com/brain-slam/slam/issues/89

Communication channels

https://mattermost.brainhack.org/brainhack/channels/slam

Skills

• will to share ideas and good time: 100%
• code documentation: 80%
• GitHub workflows: 10%
• scientific python (e.g. numpy): 20 %
• mesh processing: 10%

Various levels of expertise are welcome since some of our objectives can be addressed with no coding effort (documentation) and others require advanced knowledge of numpy (code speed-up)

Onboarding documentation

https://github.com/brain-slam/slam/blob/master/README.md

What will participants learn?

• clean python code documentation
• working according to github workflow for a scientific project
• code profiling and optimization (for code speed up)
• continuous integration and unit test (for code speed up)

Data to use

No response

Number of collaborators

3

Credit to collaborators

Project contributors are listed on the project README using all-contributors

Image

Type

coding_methods, documentation

Development status

2_releases_existing

Topic

other

Tools

other

Programming language

Python

Modalities

MRI

Git skills

1_commit_push

Anything else?

No response

Things to do after the project is submitted and ready to review.

• Add a comment below the main post of your issue saying: Hi @brainhackorg/project-monitors my project is ready!
• Twitter-sized summary of your project pitch.