CodeEntropy: A Python Package for Multiscale Cell Correlation Entropy Estimation from Molecular Dynamics Simulations

CodeEntropy is an open-source Python package implementing the multiscale cell correlation (MCC) method for estimating entropy directly from molecular dynamics (MD) simulations. The software provides a modular, configuration-driven framework in which MCC calculations are expressed as a dependency-constrained workflow represented by a directed acyclic graph (DAG). This design maps the theoretical stages of MCC onto explicit computational transformations, enabling transparent and reproducible entropy estimation across molecular hierarchies. Designed as a reference implementation, CodeEntropy emphasises correctness, reproducibility, and transparency through structured outputs, automated testing, and continuous integration. Results are exported in machine-readable formats suitable for downstream analysis and integration with existing molecular simulation workflows. Distributed under the MIT License, CodeEntropy provides a sustainable platform for reproducible entropy estimation and for extending theoretical developments within the molecular simulation community.