AutomaticDifferentiation: C++ & Ada

Grab either 8feb2020_ada_AD for Ada examples, or cpp_AD_5mar20.tar for the C++ setup.

Ada Package and C++ Templates for Automatic Differentiation with examples:

Assignment operator is overloaded so that a normal looking function definition in a client app also provides access to evaluations of its analytic derivatives.

Automatic differentiation means the user does not need to define the analytic expression for all the various partial derivatives. It also means that those complex expressions are essentially calculated at compile time, and merely evaluated at runtime.

First order derivatives only, forward accumulation.

Examples are included that demonstrate a damped Newton's method for finding roots of systems of nonlinear equations.