The Mystic framework provides a collection of optimization algorithms and tools that allows the user to more robustly (and readily) solve optimization problems.

All optimization algorithms included in mystic provide workflow at the fitting layer, not just access to the algorithms as function calls. Mystic gives the user fine-grained power to both monitor and steer optimizations as the fit processes are running.

Where possible, mystic optimizers share a common interface, and thus can be easily swapped without the user having to write any new code. Mystic solvers all conform to a solver API, thus also have common method calls to configure and launch an optimization job.

The API also makes it easy to bind a favorite 3rd party solver into the mystic framework.

By providing a robust interface created to allow the user to easily control and configure solvers, Mystic will reduce the barrier to implementing a target fitting problem as stable code.

Thus the user can focus on building their physical models, and not spend time hacking together an interface to optimization code.

Here are some key features of "Mystic":

· a common interface
· the ability to impose solver-independent bounds constraints
· the ability to apply solver-independent monitors
· the ability to configure solver-independent termination conditions
· a control handler yielding: [pause, continue, exit, and user_callback]
· ease in selecting initial conditions: [initial_guess, random]
· ease in selecting mutation strategies (for differential evolution)
· easily generate a fit model (several example models are included)
· configure and auto-generate a cost function from a model