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CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained C-code generation and interfaces state-of-the-art codes such as SUNDIALS, IPOPT etc. It can be used from C++, Python, Matlab/Octave, Julia or Javascript

A Symbolic Package for Octave using SymPy

An Octave kernel for IPython

Sample code in MATLAB/Octave for "Kalman Filter for Beginners"

GNU Octave Mirror (https://www.octave.org/hg/octave). Report bugs and submit pull requests (patches) at https://bugs.octave.org