Parallelization
- Monte Carlo Simulations can be run in parallel
- Optimization with multiple seeds can be run in parallel
Filter Function Derivatives
- New Filter function cost function can be used with analytical gradients for the optimization
Transfer Function
- New Base class MatrixTF to distinguish between transfer functions implemented as matrix multiplication and other transfer functions
- implementation of gaussian convolution as transfer function
Solver Algorithms
- the times are now set automatically to the transfer functions. The Solver must now be instantiated with the untransferred times
- drift Hamiltonians can be set to constant my setting only a single element otherwise you need one element for each transferred time step.
Optimizer
- scalar optimization algorithms available
- gradient free nelder mead algorithm available
- cost function weights must now be given in
Cost Functions
- refactoring of the angle axis representation