Release Notes

Some notes on new features in various releases

What’s new in 0.5

  • ParametricUMAP learns embeddings with neural networks.

  • AlignedUMAP can align multiple embeddings using relations between datasets.

  • DensMAP can preserve local density information in embeddings.

  • UMAP now depends on PyNNDescent, but has faster more parallel performance as a result.

  • UMAP now supports an update method to add new data and retrain.

  • Various performance improvements and bug fixes.

  • Additional plotting support, including text searching in interactive plots.

  • Support for “maximal distances” in neighbor graphs.

What’s new in 0.4

  • Inverse transform method. Generate points in the original space corresponding to points in embedded space. (Thanks to Joseph Courtney)

  • Different embedding spaces. Support for embedding to a variety of different spaces other than Euclidean. (Thanks to Joseph Courtney)

  • New metrics, including Hellinger distance for sparse count data.

  • New discrete/label metrics, including hierarchical categories, counts, ordinal data, and string edit distance.

  • Support for parallelism in neighbor search and layout optimization. (Thanks to Tom White)

  • Support for alternative methods to handling duplicated data samples. (Thanks to John Healy)

  • New plotting methods for fast and easy plots.

  • Initial support for dataframe embedding – still experimental, but worth trying.

  • Support for transform methods with sparse data.

  • Multithreading support when no random seed is set.

What’s new in 0.3

  • Supervised and semi-supervised dimension reduction. Support for using labels or partial labels for dimension reduction.

  • Transform method. Support for adding new unseen points to an existing embedding.

  • Performance improvements.

What’s new in 0.2

  • A new layout algorithm that handles large datasets (more) correctly.

  • Performance improvements.