![]() ![]() Sampling, interpolation, and statistics in mystic are all designed ![]() Greatly reduces the barrier to solving hard optimization problems. By providing a robust interface designed toĮnable the user to easily configure and control solvers, mystic mystic providesĪ large selection of constraints, including probabistic and dimensionally Of space where the constraints are respected), or both. constraints, which constrain the solver to only search in regions Solution space that violate the constraints), or as “hard constraints” Optimization algorithms in mystic can accept parameter constraints,Īs “soft constraints” (i.e. The API also makes it easy to bind a favoriteģrd party solver into the mystic framework. To configure and launch an optimization job. Solvers all conform to a solver API, thus also have common method calls Where possible, mystic optimizers share a common interface, and thus canīe easily swapped without the user having to write any new code. Parallel computing, either within each iteration or as an ensemble of State, can be reconfigured dynamically, and can be restarted from a Users can customize optimizer stop conditions, where bothĬompound and user-provided conditions may be used. Optimizers can advance one iteration with Step, or run to completion Monitor and steer optimizations as the fit processes are running. mystic gives the user fine-grained power to both Provide workflow at the fitting layer, not just access to the algorithmsĪs function calls. All optimization algorithms included in mystic The mystic framework provides a collection of optimization algorithmsĪnd tools that allows the user to more robustly (and easily) solve hard ![]()
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