SciML / OrdinaryDiffEq.jl

High performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)
https://diffeq.sciml.ai/latest/
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Default tolerances are too large for Tsit5 #2163

Open AshtonSBradley opened 3 months ago

AshtonSBradley commented 3 months ago

Describe the example

Predator-prey solution is wrong using defaults. Also occurs if we instead use defaults in DifferentialEquations.

Doesn't seem to occur if we switch to e.g. Vern6 defaults.

Minimal Reproducible Example 👇

    using OrdinaryDiffEq
    using Plots

    # system parameters
    λ = .7   # 🐇 linear growth - bunnies reproduce
    γ = 0.4  # 🐇 nonlinear loss - wolf eats rabbit
    κ = 0.3  # 🐺 nonlinear growth - wolf eats rabbit
    β = 1.2  # 🐺 linear loss - wolves get old
    p = [λ γ β κ]

    function pprey(u,p,t)
        λ,γ,β,κ = p                         
        r,w = u
        dr = λ*r - γ*r*w        
        dw = - β*w + κ*r*w
        return [dr;dw]
    end 

r̄, w̄ = β/κ, λ/γ     
ti = 0.0            
tf = 50.0           
Nt = 200
t = LinRange(ti,tf,Nt)
alg = Tsit5()  
# alg = Vern6()     # Much better default

u0 = [β/κ + .2 ; λ/γ] # lots of carrots this month!  
prob = ODEProblem(pprey,u0,(ti,tf),p)

sol = solve(prob,alg=Tsit5(),saveat=t);  # default reltol=1e-3 (??!!)
# sol = solve(prob,alg=Tsit5(),saveat=t,reltol=1e-4); 
sol2 = solve(prob,alg=Vern6(),saveat=t);

r = sol[1,:]; w = sol[2,:];
r2= sol2[1,:]; w2 = sol2[2,:];

plot(r,w,size=(450,300),label="numerical solution")
plot!(r2,w2,label="correct numerical")
scatter!([r̄],[w̄],label="steady state",legend=:outerright) 
xlabel!("rabbits")
ylabel!("wolves")
Screenshot 2024-03-26 at 3 39 12 PM

Not Working Environment (please complete the following information):

julia> Pkg.status()
Status `~/Dropbox/Teaching/2024/phsi365/integrator_test/Project.toml`
⌃ [1dea7af3] OrdinaryDiffEq v6.49.4
  [91a5bcdd] Plots v1.40.2
  [47edcb42] ADTypes v0.2.7
⌅ [79e6a3ab] Adapt v3.7.2
⌅ [ec485272] ArnoldiMethod v0.2.0
⌃ [4fba245c] ArrayInterface v7.7.1
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  [2a0fbf3d] CPUSummary v0.2.4
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  [944b1d66] CodecZlib v0.7.4
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  [3da002f7] ColorTypes v0.11.4
  [c3611d14] ColorVectorSpace v0.10.0
  [5ae59095] Colors v0.12.10
  [38540f10] CommonSolve v0.2.4
  [bbf7d656] CommonSubexpressions v0.3.0
  [34da2185] Compat v4.14.0
  [f0e56b4a] ConcurrentUtilities v2.4.1
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  [e2d170a0] DataValueInterfaces v1.0.0
  [8bb1440f] DelimitedFiles v1.9.1
⌃ [2b5f629d] DiffEqBase v6.130.0
  [163ba53b] DiffResults v1.1.0
  [b552c78f] DiffRules v1.15.1
  [b4f34e82] Distances v0.10.11
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⌃ [46192b85] GPUArraysCore v0.1.5
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  [86223c79] Graphs v1.9.0
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⌅ [ef3ab10e] KLU v0.4.1
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⌅ [0b1a1467] KrylovKit v0.6.1
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⌅ [7ed4a6bd] LinearSolve v1.42.0
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⌅ [8913a72c] NonlinearSolve v1.6.0
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⌃ [1dea7af3] OrdinaryDiffEq v6.49.4
  [65ce6f38] PackageExtensionCompat v1.0.2
  [d96e819e] Parameters v0.12.3
  [69de0a69] Parsers v2.8.1
  [b98c9c47] Pipe v1.3.0
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  [91a5bcdd] Plots v1.40.2
  [f517fe37] Polyester v0.7.10
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  [d236fae5] PreallocationTools v0.4.20
  [aea7be01] PrecompileTools v1.2.1
  [21216c6a] Preferences v1.4.3
  [3cdcf5f2] RecipesBase v1.3.4
  [01d81517] RecipesPipeline v0.6.12
⌅ [731186ca] RecursiveArrayTools v2.38.10
  [f2c3362d] RecursiveFactorization v0.2.21
  [189a3867] Reexport v1.2.2
  [05181044] RelocatableFolders v1.0.1
  [ae029012] Requires v1.3.0
  [7e49a35a] RuntimeGeneratedFunctions v0.5.12
  [94e857df] SIMDTypes v0.1.0
  [476501e8] SLEEFPirates v0.6.42
⌅ [0bca4576] SciMLBase v1.98.1
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⌅ [c0aeaf25] SciMLOperators v0.2.12
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Julia Version 1.10.2
Commit bd47eca2c8a (2024-03-01 10:14 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: macOS (x86_64-apple-darwin22.4.0)
  CPU: 16 × Intel(R) Core(TM) i9-9900K CPU @ 3.60GHz
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-15.0.7 (ORCJIT, skylake)
Threads: 8 default, 0 interactive, 4 GC (on 16 virtual cores)
Environment:
  JULIA_NUM_THREADS = 8
  JULIA_PKG_DEVDIR = /Users/abradley/Dropbox/Julia/Dev
  JULIA_EDITOR = code

Additional context

Here it is clear that this isn't the solution, which should be periodic, and is found by a small reduction in tolerance to e.g. reltol=1e-4. Alternately, switching to alg=Vern6() with default tolerances produces a credible solution.