Custom optimizer types

The optimizer part of a model connects it to the optimization engine. Let's say we want to implement a new optimizer as SemOptimizerMyopt.

############################################################################################
### Types and Constructor
############################################################################################
struct SemOptimizerMyopt{A, B} <: SemOptimizer{:Myopt}
    algorithm::A
    options::B
end

SEM.sem_optimizer_subtype(::Val{:Myopt}) = SemOptimizerMyopt

SemOptimizerMyopt(;
    algorithm = ...,
    options = ...,
    kwargs...,
) = SemOptimizerMyopt(algorithm, options)

struct MyoptResult{O <: SemOptimizerMyopt} <: SEM.SemOptimizerResult{O}
    optimizer::O
    ...
end

############################################################################################
### Recommended methods
############################################################################################

update_observed(optimizer::SemOptimizerMyopt, observed::SemObserved; kwargs...) = optimizer

############################################################################################
### additional methods
############################################################################################

options(optimizer::SemOptimizerMyopt) = optimizer.options

Note that SemOptimizerMyopt is defined as a subtype of SemOptimizer{:Myopt}, andSEM.semoptimizersubtype(::Val{:Myopt})returnsSemOptimizerMyopt. This instructs *SEM.jl* to useSemOptimizerMyoptwhen:Myoptis specified as the engine for model fitting:fit(..., engine = :Myopt)`.

A method for update_observed and additional methods might be usefull, but are not necessary.

Now comes the essential part: we need to provide the fit method with SemOptimizerMyopt as the first positional argument.

function fit(
    optim::SemOptimizerMyopt,
    model::AbstractSem,
    start_params::AbstractVector;
    kwargs...,
)
    # ... prepare the Myopt optimization problem

    myopt_res = ... # fit the problem with the Myopt engine
    minimum = ... # extract the minimum from myopt_res
    minimizer = ... # extract the solution (parameter estimates)
    optim_result = MyoptResult(optim, myopt_res, ...) # store the original Myopt result and params

    return SemFit(minimum, minimizer, start_params, model, optim_result)
end

This method is responsible for converting the SEM into the format required by your optimization engine, running the optimization, extracting the solution and returning the SemFit object, which should package:

• the minimum of the objective at the solution
• the minimizer (the vector of the SEM parameter estimates)
• the starting values
• the SEM model
• MyoptResult object with any relevant engine-specific details you want to preserve

In addition, you might want to provide methods to access engine-specific properties stored in MyoptResult:

algorithm_name(res::MyoptResult) = ...
n_iterations(res::MyoptResult) = ...
convergence(res::MyoptResult) = ...