UMAP Layout Optimizer: Attractive & Repulsive Forces

UMAP reduces high-dimensional data to a handful of dimensions by optimizing a low-dimensional layout so that its k-nearest-neighbor graph structure is preserved — using an attractive force along graph edges and an inverse-square repulsive force between every pair of points, exactly the two-force tug-of-war visualized here in real time. Four synthetic clusters start as random noise in 3D and are pulled and pushed into shape epoch by epoch; tune n_neighbors, min_dist, repulsion strength and optimizer speed while live readouts track layout stress and how much of the original neighbor structure survives the embedding.