Common Solver Options (Solve Keyword Arguments)

CommonSolve.solveMethod
CommonSolve.solve(args...; kwargs...)

Solves an equation or other mathematical problem using the algorithm specified in the arguments. Generally, the interface is:

CommonSolve.solve(prob::ProblemType,alg::SolverType; kwargs...)::SolutionType

where the keyword arguments are uniform across all choices of algorithms.

By default, solve defaults to using solve! on the iterator form, i.e.:

solve(args...; kwargs...) = solve!(init(args...; kwargs...))
solve(prob::OptimizationProblem, alg::AbstractOptimizationAlgorithm; kwargs...)

Keyword Arguments

The arguments to solve are common across all of the optimizers. These common arguments are:

  • maxiters (the maximum number of iterations)
  • maxtime (the maximum of time the optimization runs for)
  • abstol (absolute tolerance in changes of the objective value)
  • reltol (relative tolerance in changes of the objective value)
  • callback (a callback function)

If the chosen global optimzer employs a local optimization method a similiar set of common local optimizer arguments exists. The common local optimizer arguments are:

  • local_method (optimiser used for local optimization in global method)
  • local_maxiters (the maximum number of iterations)
  • local_maxtime (the maximum of time the optimization runs for)
  • local_abstol (absolute tolerance in changes of the objective value)
  • local_reltol (relative tolerance in changes of the objective value)
  • local_options (NamedTuple of keyword arguments for local optimizer)

Some optimizer algorithms have special keyword arguments documented in the solver portion of the documentation and their respective documentation. These arguments can be passed as kwargs... to solve. Similiarly, the special kewyword arguments for the local_method of a global optimizer are passed as a NamedTuple to local_options.

Over time we hope to cover more of these keyword arguments under the common interface.

If a common argument is not implemented for a optimizer a warning will be shown.

Callback Functions

The callback function callback is a function which is called after every optimizer step. Its signature is:

callback = (x,other_args) -> false

where other_args is are the extra return arguments of the optimization f. This allows for saving values from the optimization and using them for plotting and display without recalculating. The callback should return a Boolean value, and the default should be false, such that the optimization gets stopped if it returns true.

Callback Example

function loss(p) 
    # Some calculations
    lossval,x,y,z
end

function callback(p,lossval,x,y,z)
    # Do some analysis

    # When lossval < 0.01, stop the optimization
    lossval < 0.01
end