PyDMD

Implements multiple DMD variants including Optimized DMD and Physics-informed DMD, allowing users to handle noisy data and large datasets as highlighted in the key features section.

Built on NumPy and SciPy with Matplotlib for visualization, ensuring compatibility with the standard Python data science stack for efficient computations, as stated in the description.

Provides functions like plot_summary for mode reconstruction and energy spectrum analysis, enabling clear insights into system dynamics, demonstrated in the quickstart guide with flow past a cylinder data.

Allows fine-tuning through parameters such as eigenvalue constraints and bagging configurations, supporting both novice and advanced users per the philosophy and quickstart examples.