Version 0.2.0

Major API update to support multiple down-stream tasks. The classes now only construct the manifold models. Member functions are added to compute umap layouts or detect hdbscan clusters from the manifold. Especially the approximate nn-descent-based k-MST can speed up computing hdbscan clusters on high-dimensional data.

Full Changelog: https://github.com/vda-lab/multi_mst/commits/v0.2.0

Version 0.1.4

• Support numpy >= 2.0
• No longer force numba compile on import

Full Changelog: https://github.com/vda-lab/multi_mst/commits/v0.1.4

Version 0.1.3

• Added a nearest-neighbour descent based variant for the k-MST algorithm. This version creates approximate k-MSTs and is much faster on datasets that do not behave nicely with KD-Trees. The compute time and accuracy are evaluated in new benchmark notebooks.
• Keyword arguments for UMAP are no longer taken from **kwargs. Instead use the named umap_kwargs=dict(...) keyword argument.

Full Changelog: https://github.com/vda-lab/multi_mst/commits/v0.1.3

Version 0.1.2

• Update Github Actions to also publish pure python wheel.

Full Changelog: https://github.com/vda-lab/multi_mst/commits/v0.1.2

Version 0.1.1

• Updated Github Actions to create Releases automatically when version tags are pushed.

Full Changelog: https://github.com/vda-lab/multi_mst/commits/v0.1.1

Version 0.1.0

Initial Release.

Full Changelog: https://github.com/vda-lab/multi_mst/commits/v0.1.0