worked on updating tests

Author: reykboerner

test/CoupledSDEs.jl

@@ -21,7 +21,7 @@
         # diagonal additive noise: σ*N(0,dt)
         # a vector of random numbers dW whose size matches the output of g where the noise is applied element-wise
         prob = SDEProblem(meier_stein, diagonal_noise(σ), zeros(2), (0.0, Inf), ())
-        sde = CoupledSDEs(meier_stein, idfunc, zeros(2), (), σ)
+        sde = CoupledSDEs(meier_stein, zeros(2); noise_strength=σ)
 
         @test sde.integ.sol.prob.f isa SDEFunction
         @test sde.integ.sol.prob.f.f.f == prob.f.f
@@ -46,7 +46,7 @@
         σ = 0.25 # noise strength
         W = WienerProcess(0.0, 0.0, 0.0)
         prob = SDEProblem(f!, diagonal_noise!(σ), zeros(2), (0.0, Inf), (); noise=W)
-        sde = CoupledSDEs(f!, idfunc!, zeros(2), (), σ; noise=W)
+        sde = CoupledSDEs(f!, zeros(2); noise_process=W, noise_strength=σ)
 
         @test sde.integ.sol.prob.f isa SDEFunction
         @test sde.integ.sol.prob.f.f.f == prob.f.f
@@ -74,7 +74,7 @@
         g_sde(u, p, t) = σ .* u
         g_Csde(u, p, t) = σ .* u
         prob = SDEProblem(meier_stein, g_sde, zeros(2), (0.0, Inf), ())
-        sde = CoupledSDEs(meier_stein, g_Csde, zeros(2), (), σ)
+        sde = CoupledSDEs(meier_stein, zeros(2); g=g_Csde)
 
         @test sde.integ.sol.prob.f isa SDEFunction
         @test sde.integ.sol.prob.f.f.f == prob.f.f
@@ -108,7 +108,7 @@
         # prob = SDEProblem(f, g, ones(2), (0.0, 1.0), noise_rate_prototype = zeros(2, 4))
         # diffeq =(alg=SRIW1(), noise_rate_prototype = zeros(2, 4))
         sde = CoupledSDEs(
-            f, g, zeros(2); noise_rate_prototype=zeros(2, 4), diffeq=(alg=RKMilCommute(),)
+            f, zeros(2); g, noise_prototype=zeros(2, 4), diffeq=(alg=RKMilCommute(),)
         )
         prob = SDEProblem(f, g, zeros(2), (0.0, Inf); noise_rate_prototype=zeros(2, 4))
 
@@ -133,7 +133,7 @@
         Z0 = zeros(2)
         W = CorrelatedWienerProcess(Γ, t0, W0, Z0)
         prob = SDEProblem(f!, diagonal_noise!(σ), zeros(2), (0.0, Inf), (); noise=W)
-        sde = CoupledSDEs(f!, idfunc!, zeros(2), (), σ; noise=W)
+        sde = CoupledSDEs(f!, zeros(2); noise_process=W, noise_strength=σ)
 
         @test sde.integ.sol.prob.f isa SDEFunction
         @test sde.integ.sol.prob.f.f.f == prob.f.f
@@ -158,4 +158,4 @@
             @test W.covariance ≈ cov(sol; dims=2) / dt rtol = 1e-2
         end
     end
-end
+end

test/basin/basin_boundary-N54XDK9GMK.jl

@@ -0,0 +1,18 @@
+@testset "fitzhugh_nagumo" begin
+    # Define systems
+    g = diag_noise_funtion(0.215)
+    system = CoupledSDEs(fitzhugh_nagumo, g, [2.0, 0.1], [0.1, 3.0, 1.0, 1.0, 1.0, 0.0])
+
+    # Set up domain
+    A, B, C = [0.0, 0.0], [1.0, 0.0], [0.0, 1.0]
+    box = intervals_to_box([-2.0, -2.0], [2.00, 2.0])
+    step = 0.1
+
+    boas = basins(system, A, B, C, box; bstep = [step, step])
+    X, Y, attractors, h = boas
+    boundary = basinboundary(boas)
+    @test length(attractors) == 2
+    @test length(unique(h)) == 3
+    @test h[end÷2+1, end÷2+1] == -1
+    @test boundary[:,end÷2+1] == zeros(2)
+end

test/issue14.jl

@@ -0,0 +1,22 @@
+using CriticalTransitions, StaticArrays, Test
+
+function meier_stein(u, p, t) # in-place
+    x, y = u
+    dx = x-x^3 -10*x*y^2
+    dy = -(1+x^2)*y
+    SA[dx, dy]
+end
+σ = 0.25
+sys = StochSystem(meier_stein, [], zeros(2), σ, idfunc, nothing, I(2), "WhiteGauss")
+
+# initial path: parabola
+xx = range(-1.0,1.0, length=30)
+yy = 0.3 .* (- xx .^ 2 .+ 1)
+init = Matrix([xx yy]')
+
+gm = geometric_min_action_method(sys, init, maxiter=1000)
+@test all(isapprox.(path[2,:][end-5:end], 0, atol=1e-3))
+
+gm[2][end]
+
+isapprox(gm[2][end], 0.338, atol=1e-3)

test/largedeviations/MAM.jl

@@ -1,7 +1,7 @@
 @testset "MAM FitzHugh-Nagumo" begin
     p = [0.1, 3, 1, 1, 1, 0]
     σ = 0.1
-    fhn = CoupledSDEs(fitzhugh_nagumo, idfunc, zeros(2), p, σ)
+    fhn = CoupledSDEs(fitzhugh_nagumo, zeros(2), p; noise_strength=σ)
     x_i = SA[sqrt(2 / 3), sqrt(2 / 27)]
     x_f = SA[0.001, 0.0]
     N, T = 200, 2.0
@@ -14,7 +14,7 @@ end
 
 @testset "MAM Ornstein-Uhlenbeck" begin
     σ = 0.18
-    ou = CoupledSDEs((u, p, t) -> -u, idfunc, SA[1.0], (), σ)
+    ou = CoupledSDEs((u, p, t) -> -u, SA[1.0]; noise_strength=σ)
     x0 = -1
     xT = 2.0
     T = 10.0

test/largedeviations/action_fhn.jl

@@ -4,9 +4,9 @@ Random.seed!(SEED)
 # System setup - FitzHugh-Nagumo model
 p = [1.0, 3.0, 1.0, 1.0, 1.0, 0.0] # Parameters (ϵ, β, α, γ, κ, I)
 σ = 0.2 # noise strength
-sys = CoupledSDEs(fitzhugh_nagumo, idfunc, zeros(2), p, σ; seed=SEED)
+sys = CoupledSDEs(fitzhugh_nagumo, zeros(2), p; noise_strength=σ)#, seed=SEED)
 
-A = inv(CT.covariance_matrix(sys))
+A = inv(covariance_matrix(sys))
 T, N = 2.0, 100
 
 x_i = SA[sqrt(2 / 3), sqrt(2 / 27)]
@@ -22,7 +22,7 @@ end
 
 # Test om_action function
 @testset "om_action" begin
-    S = om_action(sys, path, time)
+    S = om_action(sys, path, time, σ)
     @test isapprox(S, 0.26, atol=0.01)
 end
 

test/largedeviations/gMAM.jl

@@ -1,7 +1,7 @@
 @testset "gMAM FitzHugh-Nagumo" begin
     p = [0.1, 3, 1, 1, 1, 0]
     σ = 0.1
-    fhn = CoupledSDEs(fitzhugh_nagumo, idfunc, zeros(2), p, σ)
+    fhn = CoupledSDEs(fitzhugh_nagumo, zeros(2), p; noise_strength=σ)
     x_i = SA[sqrt(2 / 3), sqrt(2 / 27)]
     x_f = SA[0.001, 0.0]
     N = 100
@@ -19,7 +19,7 @@ end
     end
     σ = 0.25
     # sys = CoupledSDEs(fitzhugh_nagumo, idfunc, zeros(2), p, σ)
-    sys = CoupledSDEs(meier_stein, idfunc, zeros(2), (), σ)
+    sys = CoupledSDEs(meier_stein, zeros(2); noise_strength=σ)
 
     # initial path: parabola
     xx = range(-1.0, 1.0; length=30)

test/runtests.jl

@@ -44,9 +44,9 @@ end
     JET.test_package(CriticalTransitions; target_defined_modules=true)
 end
 
-@testset "CoupledSDEs" begin
-    include("CoupledSDEs.jl")
-end
+#@testset "CoupledSDEs" begin
+#    include("CoupledSDEs.jl")
+#end
 
 @testset "ModelingToolkit" begin
     include("ModelingToolkit.jl")
@@ -58,9 +58,9 @@ end
     include("largedeviations/gMAM.jl")
 end
 
-@testset "utilities" begin
-    include("utils.jl")
-end
+#@testset "utilities" begin
+#    include("utils.jl")
+#end
 
 @testset "Trajactories" begin
     include("trajactories/simulate.jl")

test/trajactories/simulate.jl

@@ -3,9 +3,9 @@
     p = [0.1, 3.0, 1.0, 1.0, 1.0, 0.0] # Parameters (ϵ, β, α, γ, κ, I)
     σ = 0.1
     # Simulate
-    sys = CoupledSDEs(fitzhugh_nagumo, idfunc, SA[1.0, 0.0], p, σ)
+    sys = CoupledSDEs(fitzhugh_nagumo, SA[1.0, 0.0], p; noise_strength=σ)
     traj = relax(sys, 10)
-    sys = CoupledSDEs(fitzhugh_nagumo, idfunc, SA[1.0, 0.0], p, σ)
+    sys = CoupledSDEs(fitzhugh_nagumo, SA[1.0, 0.0], p; noise_strength=σ)
     sim = simulate(sys, 10)
     @test traj[1][1, 1] == 1.0
     @test sim.u[1][1] == 1.0

test/trajactories/transition.jl

@@ -7,7 +7,7 @@
     σ = 0.215 # noise strength
 
     # CoupledSDEs
-    sys = CoupledSDEs(fitzhugh_nagumo, idfunc, zeros(2), p, σ; seed=SEED)
+    sys = CoupledSDEs(fitzhugh_nagumo, zeros(2), p; noise_strength=σ, seed=SEED)
 
     fp1 = [0.816, 0.272]
     fp2 = [-0.816, -0.272]

test/utils.jl

@@ -1,22 +1,22 @@
 # Test for idfunc
-@testset "idfunc" begin
-    u = [1, 2, 3]
-    p = [0.1, 0.2, 0.3]
-    t = 0.5
-    expected = [1, 1, 1]
-    @test idfunc(u, p, t) == expected
-end
-
-# Test for idfunc!
-@testset "idfunc!" begin
-    du = zeros(3)
-    u = [1, 2, 3]
-    p = [0.1, 0.2, 0.3]
-    t = 0.5
-    expected = [1, 1, 1]
-    idfunc!(du, u, p, t)
-    @test du == expected
-end
+#@testset "idfunc" begin
+#    u = [1, 2, 3]
+#    p = [0.1, 0.2, 0.3]
+#    t = 0.5
+#    expected = [1, 1, 1]
+#    @test idfunc(u, p, t) == expected
+#end
+#
+## Test for idfunc!
+#@testset "idfunc!" begin
+#    du = zeros(3)
+#    u = [1, 2, 3]
+#    p = [0.1, 0.2, 0.3]
+#    t = 0.5
+#    expected = [1, 1, 1]
+#    idfunc!(du, u, p, t)
+#    @test du == expected
+#end
 
 # Test for intervals_to_box
 @testset "intervals_to_box" begin