modred Compute modal decompositions and reduced-order models easily, efficiently, and in parallel
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Python library Python decompositions

modred Description

modred is a Python library that computes modal decompositions and reduced-order models for any type of data. The Proper Orthogonal Decomposition (POD), balanced POD (BPOD), Dynamic Mode Decomposition (DMD), Eigensystem Realization Algorithm, and Observer Kalman Filter Identification methods are all provided with easy-to-use interfaces.The library is applicable to a broad range of fields and data types because users can write simple functions to interface their data with modred (essentially load and save functions).Furthermore, the computationally intensive algorithms (POD, BPOD, and DMD) are parallelized via MPI (mpi4py) for distributed memory. The vast majority of computation time occurs in user-supplied functions; modred itself is lightweight. Thus, if speed is limited, users can wrap compiled code in Python and use this with modred.The library is unit tested and has been used on a few different research projects already.The documentation is available at: http://packages.python.org/modred; a good place to start is the tutorial!Product's homepage

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