Add progress info for OptimizationBBO

lib/OptimizationBBO/Project.toml

@@ -8,9 +8,9 @@ BlackBoxOptim = "a134a8b2-14d6-55f6-9291-3336d3ab0209"
 Optimization = "7f7a1694-90dd-40f0-9382-eb1efda571ba"
 
 [compat]
-julia = "1"
 BlackBoxOptim = "0.6"
 Optimization = "3"
+julia = "1"
 
 [extras]
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"

lib/OptimizationBBO/src/OptimizationBBO.jl

@@ -9,14 +9,33 @@ for j in string.(BlackBoxOptim.SingleObjectiveMethodNames)
     eval(Meta.parse("export BBO_" * j))
 end
 
-decompose_trace(opt::BlackBoxOptim.OptRunController) = BlackBoxOptim.best_candidate(opt)
+function decompose_trace(opt::BlackBoxOptim.OptRunController, progress)
+    if progress
+        maxiters = opt.max_steps
+        max_time = opt.max_time
+        msg = "loss: " * sprint(show, best_fitness(opt), context = :compact => true)
+        if iszero(max_time)
+            # we stop at either convergence or max_steps
+            n_steps = BlackBoxOptim.num_steps(opt)
+            Base.@logmsg(Base.LogLevel(-1), msg, progress=n_steps / maxiters,
+                         _id=:OptimizationBBO)
+        else
+            # we stop at either convergence or max_time
+            elapsed = BlackBoxOptim.elapsed_time(opt)
+            Base.@logmsg(Base.LogLevel(-1), msg, progress=elapsed / max_time,
+                         _id=:OptimizationBBO)
+        end
+    end
+    return BlackBoxOptim.best_candidate(opt)
+end
 
 function __map_optimizer_args(prob::SciMLBase.OptimizationProblem, opt::BBO;
                               callback = nothing,
                               maxiters::Union{Number, Nothing} = nothing,
                               maxtime::Union{Number, Nothing} = nothing,
                               abstol::Union{Number, Nothing} = nothing,
                               reltol::Union{Number, Nothing} = nothing,
+                              verbose::Bool = false,
                               kwargs...)
     if !isnothing(reltol)
         @warn "common reltol is currently not used by $(opt)"
@@ -44,6 +63,12 @@ function __map_optimizer_args(prob::SciMLBase.OptimizationProblem, opt::BBO;
         mapped_args = (; mapped_args..., MinDeltaFitnessTolerance = abstol)
     end
 
+    if verbose
+        mapped_args = (; mapped_args..., TraceMode = :verbose)
+    else
+        mapped_args = (; mapped_args..., TraceMode = :silent)
+    end
+
     return mapped_args
 end
 
@@ -54,6 +79,7 @@ function SciMLBase.__solve(prob::SciMLBase.OptimizationProblem, opt::BBO,
                            maxtime::Union{Number, Nothing} = nothing,
                            abstol::Union{Number, Nothing} = nothing,
                            reltol::Union{Number, Nothing} = nothing,
+                           verbose::Bool = false,
                            progress = false, kwargs...)
     local x, cur, state
 
@@ -64,7 +90,7 @@ function SciMLBase.__solve(prob::SciMLBase.OptimizationProblem, opt::BBO,
     cur, state = iterate(data)
 
     function _cb(trace)
-        cb_call = callback(decompose_trace(trace), x...)
+        cb_call = callback(decompose_trace(trace, progress), x...)
         if !(typeof(cb_call) <: Bool)
             error("The callback should return a boolean `halt` for whether to stop the optimization process.")
         end
@@ -85,12 +111,19 @@ function SciMLBase.__solve(prob::SciMLBase.OptimizationProblem, opt::BBO,
 
     opt_args = __map_optimizer_args(prob, opt, callback = _cb, maxiters = maxiters,
                                     maxtime = maxtime, abstol = abstol, reltol = reltol;
-                                    kwargs...)
+                                    verbose = verbose, kwargs...)
 
     opt_setup = BlackBoxOptim.bbsetup(_loss; opt_args...)
 
     t0 = time()
+
     opt_res = BlackBoxOptim.bboptimize(opt_setup)
+
+    if progress
+        # Set progressbar to 1 to finish it
+        Base.@logmsg(Base.LogLevel(-1), "", progress=1, _id=:OptimizationBBO)
+    end
+
     t1 = time()
 
     opt_ret = Symbol(opt_res.stop_reason)

lib/OptimizationBBO/test/runtests.jl

@@ -12,4 +12,18 @@ using Test
                                             ub = [0.8, 0.8])
     sol = solve(prob, BBO_adaptive_de_rand_1_bin_radiuslimited())
     @test 10 * sol.minimum < l1
+
+    @test_logs begin
+        (Base.LogLevel(-1), "loss: 0.0")
+        min_level = Base.LogLevel(-1)
+        solve(prob, BBO_adaptive_de_rand_1_bin_radiuslimited(), progress = true)
+    end
+
+    @test_logs begin
+        (Base.LogLevel(-1), "loss: 0.0")
+        min_level = Base.LogLevel(-1)
+        solve(prob, BBO_adaptive_de_rand_1_bin_radiuslimited(),
+              progress = true,
+              maxtime = 5)
+    end
 end