This document outlines how our new implementation of DenMune is a faithful, high-performance translation of the conceptual algorithm presented in the original paper. A direct, line-by-line implementation of the paper's pseudocode would be algorithmically naïve and unacceptably slow for practical use.
Our implementation replaces inefficient loops with vectorized operations and modern data structures while preserving the core logic.
The initial steps of the algorithm involve building a k-nearest neighbor graph and deriving properties from it. Our implementation replaces the paper's implied loops with optimized scikit-learn and scipy equivalents.