optimizer.md: rename to SemOptimizerMyopt

Author: Alexey Stukalov

docs/src/developer/optimizer.md

@@ -1,63 +1,74 @@
 # Custom optimizer types
 
-The optimizer part of a model connects it to the optimization backend. 
-Let's say we want to implement a new optimizer as `SemOptimizerName`. The first part of the implementation is very similar to loss functions, so we just show the implementation of `SemOptimizerOptim` here as a reference:
+The optimizer part of a model connects it to the optimization backend.
+Let's say we want to implement a new optimizer as `SemOptimizerMyopt`.
+The first part of the implementation is very similar to loss functions,
+so we just show the implementation of `SemOptimizerOptim` here as a reference:
 
 ```julia
 ############################################################################################
 ### Types and Constructor
 ############################################################################################
-mutable struct SemOptimizerName{A, B} <: SemOptimizer{:Name}
+struct SemOptimizerMyopt{A, B} <: SemOptimizer{:Myopt}
     algorithm::A
     options::B
 end
 
-SemOptimizer{:Name}(args...; kwargs...) = SemOptimizerName(args...; kwargs...)
+SemOptimizer(Val{:Myopt}, args...; kwargs...) = SemOptimizerMyopt(args...; kwargs...)
 
-SemOptimizerName(;
+SemOptimizer_impltype(::Val{:Myopt}) = SemOptimizerMyopt
+
+SemOptimizerMyopt(;
     algorithm = LBFGS(),
     options = Optim.Options(; f_reltol = 1e-10, x_abstol = 1.5e-8),
     kwargs...,
-) = SemOptimizerName(algorithm, options)
+) = SemOptimizerMyopt(algorithm, options)
+
+struct MyOptResult{O <: SemOptimizerMyopt} <: SEM.SemOptimizerResult{O}
+    optimizer::O
+    ...
+end
 
 ############################################################################################
 ### Recommended methods
 ############################################################################################
 
-update_observed(optimizer::SemOptimizerName, observed::SemObserved; kwargs...) = optimizer
+update_observed(optimizer::SemOptimizerMyopt, observed::SemObserved; kwargs...) = optimizer
 
 ############################################################################################
 ### additional methods
 ############################################################################################
 
-options(optimizer::SemOptimizerName) = optimizer.options
+options(optimizer::SemOptimizerMyopt) = optimizer.options
 ```
 
-Note that your optimizer is a subtype of `SemOptimizer{:Name}`, where you can choose a `:Name` that can later be used as a keyword argument to `fit(engine = :Name)`.
-Similarly, `SemOptimizer{:Name}(args...; kwargs...) = SemOptimizerName(args...; kwargs...)` should be defined as well as a constructor that uses only keyword arguments:
+Note that your optimizer is a subtype of `SemOptimizer{:Myopt}`,
+where you can choose a `:Myopt` that can later be used as a keyword argument to `fit(engine = :Myopt)`.
+Similarly, `SemOptimizer{:Myopt}(args...; kwargs...) = SemOptimizerMyopt(args...; kwargs...)`
+should be defined as well as a constructor that uses only keyword arguments:
 
 ```julia
-SemOptimizerName(;
+SemOptimizerMyopt(;
     algorithm = LBFGS(),
     options = Optim.Options(; f_reltol = 1e-10, x_abstol = 1.5e-8),
     kwargs...,
-) = SemOptimizerName(algorithm, options)
+) = SemOptimizerMyopt(algorithm, options)
 ```
 A method for `update_observed` and additional methods might be usefull, but are not necessary.
 
 Now comes the substantive part: We need to provide a method for `fit`:
 
 ```julia
 function fit(
-    optim::SemOptimizerName,
+    optim::SemOptimizerMyopt,
     model::AbstractSem,
     start_params::AbstractVector;
     kwargs...,
 )
-    optimization_result = ...
-
     ...
 
+    optimization_result = MyoptResult(optim, ...)
+
     return SemFit(minimum, minimizer, start_params, model, optimization_result)
 end
 ```
@@ -67,7 +78,7 @@ The method has to return a `SemFit` object that consists of the minimum of the o
 In addition, you might want to provide methods to access properties of your optimization result:
 
 ```julia
-algorithm_name(res::MyOptimizationResult) = ...
-n_iterations(res::MyOptimizationResult) = ...
-convergence(res::MyOptimizationResult) = ...
+algorithm_name(res::MyOptResult) = ...
+n_iterations(res::MyOptResult) = ...
+convergence(res::MyOptResult) = ...
 ```