Compute modal decompositions and reduced-order models easily, efficiently, and in parallel.
Project description
Welcome to the modred project!
This is an easy-to-use and parallelized library for finding modal decompositions and reduced-order models.
Parallel implementations of the proper orthogonal decomposition (POD), balanced POD (BPOD), and dynamic mode decomposition (DMD) are provided, as well as serial implementations of the Observer Kalman filter Identification method (OKID) and the Eigensystem Realization Algorithm (ERA). Modred is applicable to a wide range of problems and nearly any data format.
The library itself is lightweight; the majority of the computation time is spent calling functions you provide. The library is essentially a wrapper that calls the functions in an efficient way.
Python’s speed limitations can be bypassed by calling compiled code via tools like Cython, SWIG, and f2py.
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