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Pyvib

This repository contains the pyvib packages. A python library for nonlinear state space modeling using white-, gray- and blackbox models. See the documentation for further info.

Resources

• API documentation - technical details on all functions
• Getting-started guide - tutorial page (run with jupyter to get interactive features)
• Examples page - stand-alone executables of different applications

Dependencies

Required

This library requires numpy, scipy and python3.7. E.g. on Linux:

pip install numpy, scipy

Useful Links

Although this pakage does not have anything to do with control, state space models are ofthen used for this. See these packages for more(taken from harold)

• There is already an almost-matured control toolbox which is led by Richard Murray et al. and it can perform already most of the essential tasks. Hence, if you want to have something that resembles the basics of matlab control toolbox, you should give it a try. However, it is somewhat limited to SISO tools and also relies on SLICOT library which can lead to installation hassle and/or licensing problems for nontrivial tasks. https://github.com/python-control/python-control
• You can also use the tools available in SciPy “signal“ module for basics of LTI system manipulations. SciPy is a powerful all-purpose scientific package. This makes it extremely useful however admittedly every discipline has a limited presence hence the limited functionality. If you are looking for a quick LTI system manipulation and don’t want to install yet another package, then it might be the tool for you. https://docs.scipy.org/doc/scipy/reference/signal.html
• Instead, if you are interested in robust control you probably would appreciate the `Skogestad-Python`_ project. They are replicating the code parts of the now-classic book completely in Python. Awesome! https://github.com/alchemyst/Skogestad-Python
• harold MIMO systems and without dependency for SLICOT https://github.com/ilayn/harold/