lsqfit

madsjulia · Nov 7, 2023 · 3b53612 · 3b53612
1 parent 250cd28
commit 3b53612
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Showing 2 changed files with 4 additions and 5 deletions.
diff --git a/src/MadsCalibrate.jl b/src/MadsCalibrate.jl
@@ -63,7 +63,7 @@ function calibraterandom(madsdata::AbstractDict, numberofsamples::Integer=1; tol
 		end
 		parameters, results = Mads.calibrate(madsdata; tolX=tolX, tolG=tolG, tolOF=tolOF, tolOFcount=tolOFcount, minOF=minOF, maxEval=maxEval, maxIter=maxIter, maxJacobians=maxJacobians, lambda=lambda, lambda_mu=lambda_mu, np_lambda=np_lambda, show_trace=show_trace, usenaive=usenaive, save_results=save_results)
 		phi = results.minimum
-		converged = results.x_converged | results.g_converged | results.f_converged # f_converged => of_conferged
+		converged = results.x_converged | results.g_converged # f_converged => of_conferged
 		!quiet && @info("Random initial guess #$(i): OF = $(phi) (converged=$(converged))")
 		if phi < bestphi || i == 1
 			bestparameters = parameters
@@ -135,7 +135,7 @@ function calibraterandom_parallel(madsdata::AbstractDict, numberofsamples::Integ
 		end
 		parameters, results = Mads.calibrate(madsdata; tolX=tolX, tolG=tolG, tolOF=tolOF, tolOFcount=tolOFcount, minOF=minOF, maxEval=maxEval, maxIter=maxIter, maxJacobians=maxJacobians, lambda=lambda, lambda_mu=lambda_mu, np_lambda=np_lambda, show_trace=show_trace, usenaive=usenaive, save_results=save_results, localsa=localsa, parallel_optimization=false)
 		phi = results.minimum
-		converged = results.x_converged | results.g_converged | results.f_converged # f_converged => of_conferged
+		converged = results.x_converged | results.g_converged # f_converged => of_conferged
 		if !quiet
 			if i == 1 && first_init
 				@info("First run using initial values #$(i): OF = $(phi) (converged=$(converged))")

diff --git a/src/MadsLevenbergMarquardt.jl b/src/MadsLevenbergMarquardt.jl
@@ -324,7 +324,6 @@ function naive_levenberg_marquardt(f::Function, g::Function, x0::AbstractVector{
 			break
 		end
 	end
-	LsqFit.LMResults(LsqFit.LevenbergMarquardt, x0, best_x, best_residual, g_calls, !converged, x_converged, g_converged, float(tolG), tr, f_calls, g_calls)
 	return LsqFit.LMResults(LsqFit.LevenbergMarquardt(), x0, currentx, currentsse, maxIter, true, true, true, 0.0, LsqFit.LMTrace{LsqFit.LevenbergMarquardt}(), nEval, maxIter)
 end
 
@@ -386,7 +385,7 @@ function levenberg_marquardt(f::Function, g::Function, x0, o::Function=x->(x'*x)
 	tr = LsqFit.LMTrace{LsqFit.LevenbergMarquardt}()
 	if show_trace
 		d = Dict("lambda" => lambda)
-		os = LsqFit.LMTrace{LsqFit.LevenbergMarquardt}(g_calls, best_residual, NaN, d)
+		os = LsqFit.LMState{LsqFit.LevenbergMarquardt}(g_calls, best_residual, NaN, d)
 		push!(tr, os)
 		println(os)
 	end
@@ -618,5 +617,5 @@ function levenberg_marquardt(f::Function, g::Function, x0, o::Function=x->(x'*x)
 		println("OF: $(best_residual) (final)")
 	end
 	callbackfinal(best_x, best_residual, NaN)
-	LsqFit.LMResults(LsqFit.LevenbergMarquardt, x0, best_x, best_residual, g_calls, !converged, x_converged, g_converged, float(tolG), tr, f_calls, g_calls)
+	LsqFit.LMResults(LsqFit.LevenbergMarquardt(), x0, best_x, best_residual, g_calls, !converged, x_converged, g_converged, float(tolG), tr, f_calls, g_calls)
 end