Remove debugginb stuff.

SciML · Jul 28, 2020 · 13540b8 · 13540b8
1 parent bdd30a2
commit 13540b8
Showing 1 changed file with 17 additions and 21 deletions.
diff --git a/test/solve_SDEs.jl b/test/solve_SDEs.jl
@@ -89,15 +89,11 @@ end
 push!(identical_networks, reaction_networks_constraint[9] => (real_f_3,real_g_3,zeros(7,6)))
 
 for (i,networks) in enumerate(identical_networks)
-    println(i)
     for factor in [1e-1, 1e0, 1e1], repeat in 1:3
-        println(repeat, "   ", factor)
         u0 = 100. .+ factor*rand(length(networks[1].states))
         p = 0.01 .+ factor*rand(length(networks[1].ps))
         (i==2) && (u0[1] += 1000.)
         (i==3) ? (p[2:2:6] .*= 1000.; u0 .+= 1000) : (p[1] += 500.)
-        println(u0)
-        println(p)
         prob1 = SDEProblem(networks[1],u0,(0.,100.),p)
         sol1 = solve(prob1,ImplicitEM(),saveat=0.01,maxiters=1e7)
         prob2 = SDEProblem(networks[2][1],networks[2][2],u0,(0.,100.),p,noise_rate_prototype=networks[2][3])
@@ -115,23 +111,23 @@ end
 ### Compares level of noise with noise scalling. ###
 
 # Tests with a single noise scaling parameter.
-#noise_scaling_network = @reaction_network begin
-#    (k1,k2), X1 ↔ X2
-#end k1 k2
-#for repeat = 1:5
-#    p = 1. .+ rand(2)
-#    u0 = 10000*(1. .+ rand(2))
-#    sol001 = solve(SDEProblem(noise_scaling_network,u0,(0.,1000.),vcat(p,0.01),noise_scaling=(@variables η1)[1]),ImplicitEM())
-#    sol01 = solve(SDEProblem(noise_scaling_network,u0,(0.,1000.),vcat(p,0.1),noise_scaling=(@variables η1)[1]),ImplicitEM())
-#    sol1 = solve(SDEProblem(noise_scaling_network,u0,(0.,1000.),vcat(p,1.),noise_scaling=(@variables η2)[1]),ImplicitEM())
-#    sol10 = solve(SDEProblem(noise_scaling_network,u0,(0.,1000.),vcat(p,10.),noise_scaling=(@variables η3)[1]),ImplicitEM())
-#    @test 2*std(first.(sol001.u)[100:end]) < std(first.(sol01.u)[100:end])
-#    @test 2*std(last.(sol001.u)[100:end]) < std(last.(sol01.u)[100:end])
-#    @test 2*std(first.(sol01.u)[100:end]) < std(first.(sol1.u)[100:end])
-#    @test 2*std(last.(sol01.u)[100:end]) < std(last.(sol1.u)[100:end])
-#    @test 2*std(first.(sol1.u)[100:end]) < std(first.(sol10.u)[100:end])
-#    @test 2*std(last.(sol1.u)[100:end]) < std(last.(sol10.u)[100:end])
-#end
+noise_scaling_network = @reaction_network begin
+    (k1,k2), X1 ↔ X2
+end k1 k2
+for repeat = 1:5
+    p = 1. .+ rand(2)
+    u0 = 10000*(1. .+ rand(2))
+    sol001 = solve(SDEProblem(noise_scaling_network,u0,(0.,1000.),vcat(p,0.01),noise_scaling=(@variables η1)[1]),ImplicitEM())
+    sol01 = solve(SDEProblem(noise_scaling_network,u0,(0.,1000.),vcat(p,0.1),noise_scaling=(@variables η1)[1]),ImplicitEM())
+    sol1 = solve(SDEProblem(noise_scaling_network,u0,(0.,1000.),vcat(p,1.),noise_scaling=(@variables η2)[1]),ImplicitEM())
+    sol10 = solve(SDEProblem(noise_scaling_network,u0,(0.,1000.),vcat(p,10.),noise_scaling=(@variables η3)[1]),ImplicitEM())
+    @test 2*std(first.(sol001.u)[100:end]) < std(first.(sol01.u)[100:end])
+    @test 2*std(last.(sol001.u)[100:end]) < std(last.(sol01.u)[100:end])
+    @test 2*std(first.(sol01.u)[100:end]) < std(first.(sol1.u)[100:end])
+    @test 2*std(last.(sol01.u)[100:end]) < std(last.(sol1.u)[100:end])
+    @test 2*std(first.(sol1.u)[100:end]) < std(first.(sol10.u)[100:end])
+    @test 2*std(last.(sol1.u)[100:end]) < std(last.(sol10.u)[100:end])
+end
 
 
 ### Tries to create a large number of problem, ensuring there are no errors (cannot solve as solution likely to go into negatives). ###