up

src/systems/diffeqs/abstractodesystem.jl

@@ -529,12 +529,12 @@ function SciMLBase.BVProblem{iip, specialize}(sys::AbstractODESystem, u0map = []
         kwargs1 = merge(kwargs1, (callback = cbs,))
     end
 
-    # Construct initial conditions
+    # Construct initial conditions.
     _u0 = u0 isa Function ? u0(tspan[1]) : u0
 
-    # Define the boundary conditions
+    # Define the boundary conditions.
     bc = if iip 
-        (residual, u, p, t) -> residual .= u[1] - _u0
+        (residual, u, p, t) -> (residual .= u[1] - _u0)
     else
         (u, p, t) -> (u[1] - _u0)
     end

test/bvproblem.jl

@@ -2,32 +2,31 @@ using BoundaryValueDiffEq, OrdinaryDiffEq
 using ModelingToolkit
 using ModelingToolkit: t_nounits as t, D_nounits as D
 
-@parameters σ = 10. ρ = 28 β = 8/3
-@variables x(t) = 1 y(t) = 0 z(t) = 0
+@parameters α = 7.5 β = 4. γ = 8. δ = 5. 
+@variables x(t) = 1. y(t) = 2. 
 
-eqs = [D(x) ~ σ*(y-x),
-       D(y) ~ x*(ρ-z)-y,
-       D(z) ~ x*y - β*z]
+eqs = [D(x) ~ α*x - β*x*y,
+       D(y) ~ -γ*y + δ*x*y]
 
-u0map = [:x => 1., :y => 0., :z => 0.]
-parammap = [:ρ => 28., :β => 8/3, :σ => 10.]
+u0map = [:x => 1., :y => 2.]
+parammap = [:α => 7.5, :β => 4, :γ => 8., :δ => 5.]
 tspan = (0., 10.)
 
-@mtkbuild lorenz = ODESystem(eqs, t)
+@mtkbuild lotkavolterra = ODESystem(eqs, t)
 
-bvp = SciMLBase.BVProblem{true, SciMLBase.AutoSpecialize}(lorenz, u0map, tspan, parammap)
-sol = solve(bvp, MIRK4(), dt = 0.1);
+bvp = SciMLBase.BVProblem{true, SciMLBase.AutoSpecialize}(lotkavolterra, u0map, tspan, parammap)
+sol = solve(bvp, MIRK4(), dt = 0.01);
 
-bvp2 = SciMLBase.BVProblem{false, SciMLBase.AutoSpecialize}(lorenz, u0map, tspan, parammap)
-sol2 = solve(bvp, MIRK4(), dt = 0.1);
+bvp2 = SciMLBase.BVProblem{false, SciMLBase.AutoSpecialize}(lotkavolterra, u0map, tspan, parammap)
+sol2 = solve(bvp, MIRK4(), dt = 0.01);
 
-op = ODEProblem(lorenz, u0map, tspan, parammap)
-osol = solve(op)
+op = ODEProblem(lotkavolterra, u0map, tspan, parammap)
+osol = solve(op, Vern9())
 
-@test sol.u[end] ≈ osol.u[end]
-@test sol2.u[end] ≈ osol.u[end]
-@test sol.u[1] == [1., 0., 0.]
-@test sol2.u[1] == [1., 0., 0.]
+@test isapprox(sol.u[end],osol.u[end]; atol = 0.001)
+@test isapprox(sol2.u[end],osol.u[end]; atol = 0.001)
+@test sol.u[1] == [1., 2.]
+@test sol2.u[1] == [1., 2.]
 
 ### Testing on pendulum
 
@@ -39,16 +38,17 @@ eqs = [D(D(θ)) ~ -(g / L) * sin(θ)]
 @mtkbuild pend = ODESystem(eqs, t)
 
 u0map = [θ => π/2, D(θ) => π/2]
-parammap = [:L => 2.]
+parammap = [:L => 2., :g => 9.81]
 tspan = (0., 10.)
 
 bvp = SciMLBase.BVProblem{true, SciMLBase.AutoSpecialize}(pend, u0map, tspan, parammap)
-sol = solve(bvp, MIRK4(), dt = 0.05);
+sol = solve(bvp, MIRK4(), dt = 0.01);
 
 bvp2 = SciMLBase.BVProblem{false, SciMLBase.AutoSpecialize}(pend, u0map, tspan, parammap)
-sol2 = solve(bvp2, MIRK4(), dt = 0.05);
+sol2 = solve(bvp2, MIRK4(), dt = 0.01);
 
-osol = solve(pend)
+op = ODEProblem(pend, u0map, tspan, parammap)
+osol = solve(op, Vern9())
 
 @test sol.u[end] ≈ osol.u[end]
 @test sol.u[1] == [π/2, π/2]