pyALDIC: Open-source Python tool for advanced digital image correlation
Measure full-field displacement with adaptive meshing and a GUI—now in Python.
pyALDIC is a new open-source Python package that brings augmented Lagrangian digital image correlation (AL-DIC) to researchers and engineers for precise full-field displacement and strain measurements. Developed by Zixiang Tong and Jin Yang, the software combines an intuitive graphical user interface (GUI) with a scriptable Python API, making it accessible for both interactive use and automated batch processing. The implementation supports adaptive quadtree meshing and mask-aware subset splitting—critical for accurately tracking deformation near cracks, holes, and other discontinuities.
Performance is enhanced by Numba-based just-in-time compilation, allowing efficient analysis of large image datasets. pyALDIC offers selectable Local DIC and AL-DIC solver modes, giving users flexibility depending on their accuracy and speed requirements. Verification cases include synthetic displacement fields, rigid-body motion, Mode-I cracking, adaptive refinement, and experimental uniaxial tension. The software is distributed through PyPI, GitHub, and Zenodo under a BSD-3-Clause license, ensuring reproducibility. This tool lowers the barrier for using advanced DIC techniques in materials science, mechanical engineering, and computer vision, particularly for those who prefer Python over MATLAB.
- Combines GUI with scriptable Python API for interactive and automated use
- Adaptive quadtree meshing and mask-aware subset splitting near cracks/holes
- Numba acceleration enables efficient analysis; distributed under BSD-3-Clause
Why It Matters
Brings advanced DIC to Python ecosystem, enabling faster, reproducible deformation analysis in materials science and engineering.