Release Notes

Mdapy 1.0.3 (March 28, 2026)

🛠️ Other Improvements

  • Added explained_variance_ratio for PCA.

  • For these analysis methods (CNA, PTM, and IDS), simulation boxes with a thickness below 15 Å are automatically treated as small boxes.

  • The optimized elastic constant workflow can be validated using pymatgen.

  • Improved the calculator setup behavior for the System.

  • Fixed a bug in the minimize class.

  • Updated parts of the documentation.

Mdapy 1.0.2 (March 4, 2026)

🛠️ Other Improvements

  • Reduced the size of the published source distribution (sdist).

  • Added support for writing bec, stress, and virial fields in the comment line when using write_xyz.

  • Improved LammpsPotential handling of general simulation boxes; it can now correctly compute stress, forces, and energy for such structures.

  • Added newest version of NEPCPU for fixing a bug in qNEP.

Mdapy 1.0.1 (March 2, 2026)

🏆 New Features

  • Added support for converting VASP OUTCAR files to XYZ format for GPUMD. This supports single-point calculations, structure minimization, and AIMD multi-frame trajectories.

  • Added functionality to identify chemical species based on vdW-radius connectivity between atoms.

🛠️ Other Improvements

  • Fixed a bug in the HEA model builder.

  • Optimized the cfg2xyz conversion tool.

  • Added a neighbor-search benchmark to the documentation.

  • Improved the energy minimization workflow.

  • Optimized stress computation in LammpsPotential and added corresponding tests.

  • Added support for saving BEC information in XYZTraj.

  • Added tests for qNEP.

  • Removed warnings in test_void by introducing an explicit implode cast method.

🚀 Build System

  • Binary wheels are now built separately for each Python version, instead of using the stable ABI (> Python 3.12). This change ensures compatibility with Python 3.13, where the stable ABI is not supported.

Mdapy 1.0.0 (January 3, 2026)

🚀 Summary

This is a milestone update for mdapy, featuring a near-complete rewrite of the core architecture. A primary driver for this transition was the limitations of our previous JIT dependency, Taichi; its development pace constrained our support for newer Python versions.

To ensure long-term sustainability, we have reconstructed mdapy by migrating computationally intensive kernels to C++ using the modern nanobind wrapper. As a result, mdapy now depends solely on NumPy and Polars, making it exceptionally lightweight and compatible with all modern Python environments.

Key changes include:

  • Engine Shift: With the removal of Taichi, mdapy now focuses on high-performance CPU computation.

  • GUI & Tools: Experimental Polyscope support has been removed to focus on core stability. However, a lightweight Jupyter-based GUI remains available as an optional dependency.

  • Modern Build System: We have transitioned from setup.py to pyproject.toml.

  • Reliability: Extensive test suites have been added to ensure the correctness of all algorithms.

This is a brand-new foundation for the project, and we strongly recommend all users to upgrade.

🏆 New features

  • qNEP Integration: Support for evaluating energy, force, virial, charge, and BEC properties.

  • Structural Analysis: Added Static Structure Factors and the Wigner-Seitz method for point defect detection.

  • Mechanical Properties: Support for calculating elastic constants.

  • I/O Enhancements: Added XYZ trajectory loading and introduced the MP file format (Parquet-based), providing high-speed I/O and efficient storage.

  • Minimization: Improved FIRE2 method for energy minimization with cell optimization.

  • GPUMD Ecosystem: A series of new features compatible with the GPUMD economy.

🛠️ Other improvements

  • Compatibility: Full support for Python >= 3.9.

  • Reliability: Significantly expanded test case coverage.

  • Efficiency: Optimized import overhead; import mdapy is now significantly faster.

⚠️ Limitations

  • Documentation: The documentation is currently being updated and is not yet complete. We are actively working on this and welcome any community contributions or feedback.