Reorder Optim tests and relax bounds requirement in SpeedMapping

Author: Vaibhavdixit02

lib/OptimizationOptimJL/test/runtests.jl

@@ -7,16 +7,6 @@ using Test
     x0 = zeros(2)
     _p = [1.0, 100.0]
     l1 = rosenbrock(x0, _p)
-    f = OptimizationFunction(rosenbrock, Optimization.AutoForwardDiff())
-    prob = OptimizationProblem(f, x0, _p)
-    Random.seed!(1234)
-    sol = solve(prob, SimulatedAnnealing())
-    @test 10 * sol.minimum < l1
-
-    Random.seed!(1234)
-    prob = OptimizationProblem(f, x0, _p, lb = [-1.0, -1.0], ub = [0.8, 0.8])
-    sol = solve(prob, SAMIN())
-    @test 10 * sol.minimum < l1
 
     prob = OptimizationProblem(rosenbrock, x0, _p)
     sol = solve(prob,
@@ -25,12 +15,17 @@ using Test
                                                                          b = 0.5)))
     @test 10 * sol.minimum < l1
 
-    cons = (res, x, p) -> res .= [x[1]^2 + x[2]^2]
-    optprob = OptimizationFunction(rosenbrock, Optimization.AutoForwardDiff(); cons = cons)
-    optprob = OptimizationFunction(rosenbrock, Optimization.AutoModelingToolkit();
-                                   cons = cons)
+    f = OptimizationFunction(rosenbrock, Optimization.AutoForwardDiff())
 
-    prob = OptimizationProblem(optprob, x0, _p)
+    Random.seed!(1234)
+    prob = OptimizationProblem(f, x0, _p, lb = [-1.0, -1.0], ub = [0.8, 0.8])
+    sol = solve(prob, SAMIN())
+    @test 10 * sol.minimum < l1
+
+    prob = OptimizationProblem(f, x0, _p)
+    Random.seed!(1234)
+    sol = solve(prob, SimulatedAnnealing())
+    @test 10 * sol.minimum < l1
 
     sol = solve(prob, Optim.BFGS())
     @test 10 * sol.minimum < l1
@@ -41,6 +36,10 @@ using Test
     sol = solve(prob, Optim.KrylovTrustRegion())
     @test 10 * sol.minimum < l1
 
+    cons = (res, x, p) -> res .= [x[1]^2 + x[2]^2]
+    optprob = OptimizationFunction(rosenbrock, Optimization.AutoModelingToolkit();
+                                   cons = cons)
+
     prob = OptimizationProblem(optprob, x0, _p, lcons = [-Inf], ucons = [Inf])
     sol = solve(prob, IPNewton())
     @test 10 * sol.minimum < l1

lib/OptimizationPolyalgorithms/Project.toml

@@ -7,11 +7,13 @@ version = "0.1.0"
 Optimization = "7f7a1694-90dd-40f0-9382-eb1efda571ba"
 OptimizationOptimJL = "36348300-93cb-4f02-beb5-3c3902f8871e"
 OptimizationOptimisers = "42dfb2eb-d2b4-4451-abcd-913932933ac1"
+Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
 
 [compat]
 Optimization = "3"
 OptimizationOptimJL = "0.1"
 OptimizationOptimisers = "0.1"
+Reexport = "1.2"
 julia = "1.6"
 
 [extras]

lib/OptimizationSpeedMapping/src/OptimizationSpeedMapping.jl

@@ -9,7 +9,6 @@ export SpeedMappingOpt
 struct SpeedMappingOpt end
 
 SciMLBase.allowsbounds(::SpeedMappingOpt) = true
-SciMLBase.requiresbounds(::SpeedMappingOpt) = true
 SciMLBase.allowscallback(::SpeedMappingOpt) = false
 
 function __map_optimizer_args(prob::OptimizationProblem, opt::SpeedMappingOpt;