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nonlinear

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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 or Matlab/Octave.

  • Updated Oct 24, 2021
  • C++
JonasIsensee
JonasIsensee commented Oct 7, 2018

TSP claims to be type agnostic.
There should be tests for this.
In particular Float32 and Complex numbers will be of Interest.


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Datseris
Datseris commented Sep 12, 2021

I was really young programming-wise when I wrote parallel_integrator of in-place continuous systems. I wrote it as having a matrix state, where each column is each state of the dynamical system. I'm not sure why I went with this route instead of the route of having it a vector of states. I'm certain that I have benchmarked both cases extensively and chose the one with most performance.

But th

Datseris
Datseris commented Aug 1, 2021

We have established the validity of our unified embedding methods because we even wrote a paper utilizing them in detail and comparing them with each other. There isn't any doubt that they work. However, the way we have written our tests is brittle, because (due to chaos) running the test on different machines may make them fail. For example while working on PR #93 I've seen things like:

M

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