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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 Jun 9, 2022
  • C++
Funkerfish
Funkerfish commented Jun 8, 2022

Hello again!

Now I try to calculate the Lyapunov spectrum in a two-parameter plane. But a warning comes when I choose some of the parameter regions:

Warning: Instability detected. Aborting

From what I googled, the warning comes because it returns a NAN in the trajectory. I am thinking if I can use the 'isnan' function to skip those parameter sets that cause the NAN and continue my

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.


Want to back this issue? **[Post a bounty on it!](https://www.bountysource.com/issues/64400386-add-tests-for-different-number-types-float32-complex?utm_campaign=plugin&utm_content=tracker%2F89129719&utm_medium=issues&utm_source=githu

good first issue testing Hacktoberfest
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

good first issue low priority speculation
Datseris
Datseris commented Feb 17, 2022

I'm reading again the Nonlinear Time Series Analysis textbook by Kantz & Schreiber. In section 6.5 they describe a rather straightforward method for estimating a good value of the Theiler window. It is a method by Provenzale et al

Provenzale, A., Smith, L. A., Vio, R. &Murante, G. (1992). Distinguishing between low-dimensional dynamics and randomness in measured time series. Physica D, 58, 31

enhancement good first issue wanted feature

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