Progressive Uniform Manifold Approximation and Projection (PUMAP) is a progressive algorithm for UMAP, which guarantees generating its intermediate output while it is in progress. Based on a progressive K-nearest neighbor lookup table, sequential steps in UMAP were converted to support progressiveness. Its loss and embedding output is comparable to UMAP within a reasonable time-bound.

The source code was built and tested under Ubuntu 18.04 environment. The instructions below assume that you are using Ubuntu 18.04.

1. Download the source code:

git clone https://github.com/hyungkwonko/progressive-umap.git

2. Build PANENE

mkdir build
cmake ..
make

3. Install Library

cd python
python setup.py install
pip install -r requirements.txt

4. Download Dataset

cd data/fashion
sh download.sh

5. Run Benchmark

python test.py

Even though the final loss was smaller in orifinal UMAP, Progressive UMAP showed a comparable output with a shorter time. Moreover, the time required for initialization was much shorter, we could see the first embedding in a few seconds.

If we increase ops, it means we append more points in a single batch. We tested how the projection results could be affected, setting ops 300, 500, 700 and 1000. As shown below, although the result of higher ops value took a little more time, the projection quality was almost the same.

If you want to use this repository for your own work, please cite our paper.

@inproceedings {s.20201061,
booktitle = {EuroVis 2020 - Short Papers},
editor = {Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta},
title = {{Progressive Uniform Manifold Approximation and Projection}},
author = {Ko, Hyung-Kwon and Jo, Jaemin and Seo, Jinwook},
year = {2020},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-106-9},
DOI = {10.2312/evs.20201061}
}