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++ or Python.
2.1.110 Oct 2014 22:09
Add debian patch for python paths. Documentation of Lyap solvers. Documentation of Lyap solvers. Adding robust OCP example.
2.0.219 Sep 2014 12:43
Fixed missing typemaps for numpy, added Ipython notebook.