william-h-oliver/astrolink
A general-purpose algorithm for finding astrophysically-relevant clusters from point-cloud data.
This tool helps astrophysicists find meaningful groups of stars, galaxies, or other celestial objects within large datasets, even when those groups have irregular shapes or are part of larger structures. You provide your astronomical observation data as a collection of points, and it identifies and visualizes statistically distinct overdensities, helping you understand the hierarchical relationships between them. This is for researchers analyzing complex astronomical point-cloud data.
Use this if you need to identify and understand the inherent hierarchical clustering structure within your astrophysical point-cloud data without extensive manual parameter tuning.
Not ideal if your data is not point-based or if you are looking for simple, clearly separated clusters that can be found with basic geometric methods.
Stars
13
Forks
—
Language
Python
License
MIT
Category
Last pushed
Nov 13, 2025
Commits (30d)
0
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