`CorrelatedWienerProcess` bridge function has not the correct arguments (Correlated Lorenz)

oameye commented 4 weeks ago

Describe the bug 🐞

When adding a CorrelatedWienerProcess to the lorenz ODE, the intergrator errors as it can not find the correct method for the bridge function made in the construction of the CorrelatedWienerProcess. The integrator gives 10 arguments, but the bridge function has 9.

Minimal Reproducible Example 👇

using StochasticDiffEq
using DiffEqNoiseProcess

Γ = [1.0 0.3 0.0; 0.3 1 0.5; 0.0 0.5 1.0]
W = CorrelatedWienerProcess(Γ,0.0,zeros(3),zeros(3))

tspan = (0.0, 1.0)
prob = NoiseProblem(W, (0.0, 1.0))
sol = solve(prob; dt = 0.01) # works

function lorenz_rule(u, p, t)
    σ = p[1]
    ρ = p[2]
    β = p[3]
    du1 = σ * (u[2] - u[1])
    du2 = u[1] * (ρ - u[3]) - u[2]
    du3 = u[1] * u[2] - β * u[3]
    return [du1, du2, du3]
end

u0 = [0, 10.0, 0]
g(u, p, t) = ones(3)
p0 = [10, 28, 8 / 3]

prob = SDEProblem(lorenz_rule, g, u0, tspan, p0; noise=W)
solve(prob, LambaEM())

Error & Stacktrace ⚠️

ERROR: MethodError: no method matching (::DiffEqNoiseProcess.var"#99#101")(::Vector{…}, ::NoiseProcess{…}, ::Int64, ::Vector{…}, ::Float64, ::Float64, ::Vector{…}, ::Vector{…}, ::Float64, ::RandomNumbers.Xorshifts.Xoroshiro128Plus)

Closest candidates are:
  (::DiffEqNoiseProcess.var"#99#101")(::Any, ::Any, ::Any, ::Any, ::Any, ::Any, ::Any, ::Any, ::Any)
   @ DiffEqNoiseProcess C:\Users\orjan\.julia\packages\DiffEqNoiseProcess\ezGyU\src\correlated_noisefunc.jl:11

Stacktrace:
  [1] reject_step!
    @ C:\Users\orjan\.julia\packages\DiffEqNoiseProcess\ezGyU\src\noise_interfaces\noise_process_interface.jl:292 [inlined]
  [2] reject_step! (repeats 2 times)
    @ C:\Users\orjan\.julia\packages\StochasticDiffEq\M3bKo\src\integrators\integrator_utils.jl:7 [inlined]
  [3] loopheader!
    @ C:\Users\orjan\.julia\packages\StochasticDiffEq\M3bKo\src\integrators\integrator_utils.jl:42 [inlined]
  [4] solve!(integrator::StochasticDiffEq.SDEIntegrator{…})
    @ StochasticDiffEq C:\Users\orjan\.julia\packages\StochasticDiffEq\M3bKo\src\solve.jl:614
  [5] __solve(prob::SDEProblem{…}, alg::LambaEM{…}, timeseries::Vector{…}, ts::Vector{…}, ks::Nothing, recompile::Type{…}; kwargs::@Kwargs{})
    @ StochasticDiffEq C:\Users\orjan\.julia\packages\StochasticDiffEq\M3bKo\src\solve.jl:7
  [6] __solve (repeats 5 times)
    @ C:\Users\orjan\.julia\packages\StochasticDiffEq\M3bKo\src\solve.jl:1 [inlined]
  [7] #solve_call#44
    @ C:\Users\orjan\.julia\packages\DiffEqBase\2SsGl\src\solve.jl:612 [inlined]
  [8] solve_call
    @ C:\Users\orjan\.julia\packages\DiffEqBase\2SsGl\src\solve.jl:569 [inlined]
  [9] #solve_up#53
    @ C:\Users\orjan\.julia\packages\DiffEqBase\2SsGl\src\solve.jl:1080 [inlined]
 [10] solve_up
    @ C:\Users\orjan\.julia\packages\DiffEqBase\2SsGl\src\solve.jl:1066 [inlined]
 [11] #solve#51
    @ C:\Users\orjan\.julia\packages\DiffEqBase\2SsGl\src\solve.jl:1003 [inlined]
 [12] solve(prob::SDEProblem{…}, args::LambaEM{…})
    @ DiffEqBase C:\Users\orjan\.julia\packages\DiffEqBase\2SsGl\src\solve.jl:993
 [13] top-level scope
    @ Untitled-1:28
Some type information was truncated. Use `show(err)` to see complete types.

Environment (please complete the following information):

Output of using Pkg; Pkg.status()

  [77a26b50] DiffEqNoiseProcess v5.23.0
  [789caeaf] StochasticDiffEq v6.67.0

Output of using Pkg; Pkg.status(; mode = PKGMODE_MANIFEST)

  [47edcb42] ADTypes v1.7.1
  [7d9f7c33] Accessors v0.1.37
  [79e6a3ab] Adapt v4.0.4
  [66dad0bd] AliasTables v1.1.3
  [ec485272] ArnoldiMethod v0.4.0
  [4fba245c] ArrayInterface v7.15.0
  [4c555306] ArrayLayouts v1.10.2
  [62783981] BitTwiddlingConvenienceFunctions v0.1.6
  [2a0fbf3d] CPUSummary v0.2.6
  [d360d2e6] ChainRulesCore v1.24.0
  [fb6a15b2] CloseOpenIntervals v0.1.13
  [38540f10] CommonSolve v0.2.4
  [bbf7d656] CommonSubexpressions v0.3.0
  [f70d9fcc] CommonWorldInvalidations v1.0.0
  [34da2185] Compat v4.16.0
  [a33af91c] CompositionsBase v0.1.2
  [2569d6c7] ConcreteStructs v0.2.3
  [187b0558] ConstructionBase v1.5.6
  [adafc99b] CpuId v0.3.1
  [9a962f9c] DataAPI v1.16.0
  [864edb3b] DataStructures v0.18.20
  [e2d170a0] DataValueInterfaces v1.0.0
  [2b5f629d] DiffEqBase v6.153.0
  [77a26b50] DiffEqNoiseProcess v5.23.0
  [163ba53b] DiffResults v1.1.0
  [b552c78f] DiffRules v1.15.1
  [a0c0ee7d] DifferentiationInterface v0.5.13
  [b4f34e82] Distances v0.10.11
  [31c24e10] Distributions v0.25.110
  [ffbed154] DocStringExtensions v0.9.3
  [4e289a0a] EnumX v1.0.4
  [f151be2c] EnzymeCore v0.7.8
  [d4d017d3] ExponentialUtilities v1.26.1
  [e2ba6199] ExprTools v0.1.10
⌅ [6b7a57c9] Expronicon v0.8.5
  [7034ab61] FastBroadcast v0.3.5
  [9aa1b823] FastClosures v0.3.2
  [29a986be] FastLapackInterface v2.0.4
  [1a297f60] FillArrays v1.11.0
  [6a86dc24] FiniteDiff v2.24.0
  [f6369f11] ForwardDiff v0.10.36
  [069b7b12] FunctionWrappers v1.1.3
  [77dc65aa] FunctionWrappersWrappers v0.1.3
  [46192b85] GPUArraysCore v0.1.6
  [c145ed77] GenericSchur v0.5.4
  [86223c79] Graphs v1.11.2
  [3e5b6fbb] HostCPUFeatures v0.1.17
  [34004b35] HypergeometricFunctions v0.3.24
  [615f187c] IfElse v0.1.1
  [d25df0c9] Inflate v0.1.5
  [3587e190] InverseFunctions v0.1.16
  [92d709cd] IrrationalConstants v0.2.2
  [82899510] IteratorInterfaceExtensions v1.0.0
  [692b3bcd] JLLWrappers v1.5.0
  [ccbc3e58] JumpProcesses v9.13.3
  [ef3ab10e] KLU v0.6.0
  [ba0b0d4f] Krylov v0.9.6
  [10f19ff3] LayoutPointers v0.1.17
  [5078a376] LazyArrays v2.2.0
  [2d8b4e74] LevyArea v1.0.0
  [d3d80556] LineSearches v7.3.0
  [7ed4a6bd] LinearSolve v2.32.0
  [2ab3a3ac] LogExpFunctions v0.3.28
  [bdcacae8] LoopVectorization v0.12.171
  [d8e11817] MLStyle v0.4.17
  [1914dd2f] MacroTools v0.5.13
  [d125e4d3] ManualMemory v0.1.8
  [bb5d69b7] MaybeInplace v0.1.3
  [e1d29d7a] Missings v1.2.0
  [46d2c3a1] MuladdMacro v0.2.4
  [d41bc354] NLSolversBase v7.8.3
  [2774e3e8] NLsolve v4.5.1
  [77ba4419] NaNMath v1.0.2
  [8913a72c] NonlinearSolve v3.14.0
  [6fe1bfb0] OffsetArrays v1.14.1
  [429524aa] Optim v1.9.4
  [bac558e1] OrderedCollections v1.6.3
  [1dea7af3] OrdinaryDiffEq v6.87.0
  [90014a1f] PDMats v0.11.31
  [65ce6f38] PackageExtensionCompat v1.0.2
  [d96e819e] Parameters v0.12.3
  [e409e4f3] PoissonRandom v0.4.4
  [f517fe37] Polyester v0.7.16
  [1d0040c9] PolyesterWeave v0.2.2
  [85a6dd25] PositiveFactorizations v0.2.4
  [d236fae5] PreallocationTools v0.4.23
  [aea7be01] PrecompileTools v1.2.1
  [21216c6a] Preferences v1.4.3
  [43287f4e] PtrArrays v1.2.0
  [1fd47b50] QuadGK v2.10.1
  [74087812] Random123 v1.7.0
  [e6cf234a] RandomNumbers v1.6.0
  [3cdcf5f2] RecipesBase v1.3.4
  [731186ca] RecursiveArrayTools v3.27.0
  [f2c3362d] RecursiveFactorization v0.2.23
  [189a3867] Reexport v1.2.2
  [ae029012] Requires v1.3.0
  [ae5879a3] ResettableStacks v1.1.1
  [79098fc4] Rmath v0.7.1
  [7e49a35a] RuntimeGeneratedFunctions v0.5.13
  [94e857df] SIMDTypes v0.1.0
  [476501e8] SLEEFPirates v0.6.43
  [0bca4576] SciMLBase v2.49.0
  [c0aeaf25] SciMLOperators v0.3.9
  [53ae85a6] SciMLStructures v1.4.2
  [efcf1570] Setfield v1.1.1
  [727e6d20] SimpleNonlinearSolve v1.12.0
  [699a6c99] SimpleTraits v0.9.4
  [ce78b400] SimpleUnPack v1.1.0
  [a2af1166] SortingAlgorithms v1.2.1
  [47a9eef4] SparseDiffTools v2.20.0
  [0a514795] SparseMatrixColorings v0.4.0
  [e56a9233] Sparspak v0.3.9
  [276daf66] SpecialFunctions v2.4.0
  [aedffcd0] Static v1.1.1
  [0d7ed370] StaticArrayInterface v1.8.0
  [90137ffa] StaticArrays v1.9.7
  [1e83bf80] StaticArraysCore v1.4.3
  [82ae8749] StatsAPI v1.7.0
  [2913bbd2] StatsBase v0.34.3
  [4c63d2b9] StatsFuns v1.3.1
  [789caeaf] StochasticDiffEq v6.67.0
  [7792a7ef] StrideArraysCore v0.5.7
  [2efcf032] SymbolicIndexingInterface v0.3.28
  [3783bdb8] TableTraits v1.0.1
  [bd369af6] Tables v1.12.0
  [8290d209] ThreadingUtilities v0.5.2
  [a759f4b9] TimerOutputs v0.5.24
  [d5829a12] TriangularSolve v0.2.1
  [410a4b4d] Tricks v0.1.9
  [781d530d] TruncatedStacktraces v1.4.0
  [3a884ed6] UnPack v1.0.2
  [3d5dd08c] VectorizationBase v0.21.70
  [19fa3120] VertexSafeGraphs v0.2.0
  [1d5cc7b8] IntelOpenMP_jll v2024.2.0+0
  [856f044c] MKL_jll v2024.2.0+0
  [efe28fd5] OpenSpecFun_jll v0.5.5+0
⌅ [f50d1b31] Rmath_jll v0.4.3+0
  [1317d2d5] oneTBB_jll v2021.12.0+0
  [0dad84c5] ArgTools v1.1.1
  [56f22d72] Artifacts
  [2a0f44e3] Base64
  [ade2ca70] Dates
  [8ba89e20] Distributed
  [f43a241f] Downloads v1.6.0
  [7b1f6079] FileWatching
  [9fa8497b] Future
  [b77e0a4c] InteractiveUtils
  [4af54fe1] LazyArtifacts
  [b27032c2] LibCURL v0.6.4
  [76f85450] LibGit2
  [8f399da3] Libdl
  [37e2e46d] LinearAlgebra
  [56ddb016] Logging
  [d6f4376e] Markdown
  [a63ad114] Mmap
  [ca575930] NetworkOptions v1.2.0
  [44cfe95a] Pkg v1.10.0
  [de0858da] Printf
  [3fa0cd96] REPL
  [9a3f8284] Random
  [ea8e919c] SHA v0.7.0
  [9e88b42a] Serialization
  [1a1011a3] SharedArrays
  [6462fe0b] Sockets
  [2f01184e] SparseArrays v1.10.0
  [10745b16] Statistics v1.10.0
  [4607b0f0] SuiteSparse
  [fa267f1f] TOML v1.0.3
  [a4e569a6] Tar v1.10.0
  [8dfed614] Test
  [cf7118a7] UUIDs
  [4ec0a83e] Unicode
  [e66e0078] CompilerSupportLibraries_jll v1.1.1+0
  [deac9b47] LibCURL_jll v8.4.0+0
  [e37daf67] LibGit2_jll v1.6.4+0
  [29816b5a] LibSSH2_jll v1.11.0+1
  [c8ffd9c3] MbedTLS_jll v2.28.2+1
  [14a3606d] MozillaCACerts_jll v2023.1.10
  [4536629a] OpenBLAS_jll v0.3.23+4
  [05823500] OpenLibm_jll v0.8.1+2
  [bea87d4a] SuiteSparse_jll v7.2.1+1
  [83775a58] Zlib_jll v1.2.13+1
  [8e850b90] libblastrampoline_jll v5.8.0+1
  [8e850ede] nghttp2_jll v1.52.0+1
  [3f19e933] p7zip_jll v17.4.0+2

Output of versioninfo()

Julia Version 1.10.4
Commit 48d4fd4843 (2024-06-04 10:41 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Windows (x86_64-w64-mingw32)
  CPU: 12 × AMD Ryzen 5 5600X 6-Core Processor
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-15.0.7 (ORCJIT, znver3)
Threads: 10 default, 0 interactive, 5 GC (on 12 virtual cores)
Environment:
  JULIA_PKG_PRESERVE_TIERED_INSTALLED = true
  JULIA_EDITOR = code
  JULIA_NUM_THREADS = 10

ChrisRackauckas commented 3 weeks ago

CorrelatedWienerProcess does not have the bridge function defined, so it won't be compatible here. That's already tracked in https://github.com/SciML/DiffEqNoiseProcess.jl/issues/85

oameye commented 2 weeks ago

Should we maybe add a warning or error when adaptive solver is used with correlated noise? Similar to https://github.com/SciML/StochasticDiffEq.jl/issues/578.

ChrisRackauckas commented 2 weeks ago

Yes, it would be good to add traits to https://github.com/SciML/SciMLBase.jl/blob/master/src/alg_traits.jl for allows_non_wiener_noise which is false for any high order (that uses levy areas) or adaptive method, and then check for it.

oameye commented 2 weeks ago

Okay will make a PR this week

rmsrosa commented 2 weeks ago

Besides adding traits for allows_non_wiener_noise, I think the line https://github.com/SciML/DiffEqNoiseProcess.jl/blob/master/src/correlated_noisefunc.jl#L11 should be fixed to have the correct number of arguments:

Current L11

    bridge = function (W, W0, Wh, q, h, u, p, t, rng)

should be

    bridge = function (dW, W, W0, Wh, q, h, u, p, t, rng)

ChrisRackauckas commented 1 week ago

Yes good point. Both would cause an error of course, but you'd get the nicer error message.

SciML / StochasticDiffEq.jl

`CorrelatedWienerProcess` bridge function has not the correct arguments (Correlated Lorenz) #581