MathNet VS autodiff

Standard deviation isn’t the square root. I generally just use https://numerics.mathdotnet.com . If you need to visualize the data somehow you might want to look at R

I've done this with the Mono version of Godot and C# libraries, specifically https://www.alglib.net/ and https://numerics.mathdotnet.com/

Maybe something like this: https://numerics.mathdotnet.com?

Math.net Numerics has a lot of that, for this use case it has the extensions AlmostEqual.

I completely agree. Specifying the metric rather than the Christoffel symbols would make it much easier for the users. Something like https://github.com/autodiff/autodiff might just work as the metric tensor is made up of primitives.

Old username :D So far I have been using Eigen for linear algebra and NLOPT for optimization algorithms. I have found "autodiff" that hopefully looks easy to use: https://github.com/autodiff/autodiff

Forward-mode differentiation is easy to implement in C++ with templates, operator overloading, and dual numbers (https://en.wikipedia.org/wiki/Automatic_differentiation#Auto...). Some libraries such as autodiff (https://github.com/autodiff/autodiff) and CppAD (https://github.com/coin-or/CppAD) use this method.

I was thinking of adding [autodiff](https://github.com/autodiff/autodiff) in the future, mainly because it works seamlessly with *Eigen*. One big advantage would be that I could use it for AD for NonlinearSystems as well.