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MethodError: no method matching RodasTableau... #2524

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dtxl opened this issue Nov 12, 2024 · 5 comments · Fixed by #2525
Closed

MethodError: no method matching RodasTableau... #2524

dtxl opened this issue Nov 12, 2024 · 5 comments · Fixed by #2525
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@dtxl
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dtxl commented Nov 12, 2024

Describe the bug 🐞

Since a few days "Solution= DifferentialEquations.solve(odeProblem, OrdinaryDiffEq.AutoVern8(OrdinaryDiffEq.Rodas5(), nonstifftol = 11 / 10), saveat = 1, abstol=DEAbsTol, reltol=DERelTol, maxiters=DEMaxIter)" sometimes but not always stops and shows the error

ERROR: MethodError: no method matching OrdinaryDiffEqRosenbrock.RodasTableau(::Matrix{…}, ::Matrix{…}, ::Float64, ::Vector{…}, ::Vector{…}, ::Matrix{…})
The type OrdinaryDiffEqRosenbrock.RodasTableau exists, but no method is defined for this combination of argument types when trying to construct it.

Closest candidates are:
OrdinaryDiffEqRosenbrock.RodasTableau(::Matrix{T}, ::Matrix{T}, ::T, ::Vector{T2}, ::Vector{T}, ::Matrix{T}) where {T, T2}

Minimal Reproducible Example 👇
The error sometimes occurs with

Solution= DifferentialEquations.solve(odeProblem, OrdinaryDiffEq.AutoVern8(OrdinaryDiffEq.Rodas5(), nonstifftol = 11 / 10), saveat = 1, abstol=DEAbsTol, reltol=DERelTol, maxiters=DEMaxIter) 

Error & Stacktrace ⚠️

1-element ExceptionStack:
LoadError: MethodError: no method matching OrdinaryDiffEqRosenbrock.RodasTableau(::Matrix{BigFloat}, ::Matrix{BigFloat}, ::Float64, ::Vector{Float64}, ::Vector{BigFloat}, ::Matrix{BigFloat})
The type `OrdinaryDiffEqRosenbrock.RodasTableau` exists, but no method is defined for this combination of argument types when trying to construct it.

Closest candidates are:
  OrdinaryDiffEqRosenbrock.RodasTableau(::Matrix{T}, ::Matrix{T}, ::T, ::Vector{T2}, ::Vector{T}, ::Matrix{T}) where {T, T2}
   @ OrdinaryDiffEqRosenbrock ~/.julia/packages/OrdinaryDiffEqRosenbrock/mmVby/src/rosenbrock_tableaus.jl:226

Stacktrace:
  [1] Rodas5Tableau(T::Type, T2::Type)
    @ OrdinaryDiffEqRosenbrock ~/.julia/packages/OrdinaryDiffEqRosenbrock/mmVby/src/rosenbrock_tableaus.jl:383
  [2] alg_cache(alg::Rodas5{1, true, Nothing, typeof(OrdinaryDiffEqCore.DEFAULT_PRECS), Val{:forward}, true, nothing, typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!)}, u::Vector{BigFloat}, rate_prototype::Vector{BigFloat}, ::Type{BigFloat}, ::Type{BigFloat}, ::Type{Float64}, uprev::Vector{BigFloat}, uprev2::Vector{BigFloat}, f::ODEFunction{true, SciMLBase.AutoSpecialize, FunctionWrappersWrappers.FunctionWrappersWrapper{Tuple{FunctionWrappers.FunctionWrapper{Nothing, Tuple{Vector{BigFloat}, Vector{BigFloat}, Vector{BigFloat}, Float64}}, FunctionWrappers.FunctionWrapper{Nothing, Tuple{Vector{ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}, Vector{ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}, Vector{BigFloat}, Float64}}, FunctionWrappers.FunctionWrapper{Nothing, Tuple{Vector{ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}, Vector{BigFloat}, Vector{BigFloat}, ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}}, FunctionWrappers.FunctionWrapper{Nothing, Tuple{Vector{ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}, Vector{ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}, Vector{BigFloat}, ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}}}, false}, UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing, Nothing}, t::Float64, dt::Float64, reltol::Float64, p::Vector{BigFloat}, calck::Bool, ::Val{true})
    @ OrdinaryDiffEqRosenbrock ~/.julia/packages/OrdinaryDiffEqRosenbrock/mmVby/src/rosenbrock_caches.jl:748
  [3] macro expansion
    @ ~/.julia/packages/OrdinaryDiffEqCore/2K6jv/src/caches/basic_caches.jl:0 [inlined]
  [4] __alg_cache(algs::Tuple{Vern8{typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!), Static.False}, Rodas5{1, true, Nothing, typeof(OrdinaryDiffEqCore.DEFAULT_PRECS), Val{:forward}, true, nothing, typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!)}}, u::Vector{BigFloat}, rate_prototype::Vector{BigFloat}, ::Type{BigFloat}, ::Type{BigFloat}, ::Type{Float64}, uprev::Vector{BigFloat}, uprev2::Vector{BigFloat}, f::ODEFunction{true, SciMLBase.AutoSpecialize, FunctionWrappersWrappers.FunctionWrappersWrapper{Tuple{FunctionWrappers.FunctionWrapper{Nothing, Tuple{Vector{BigFloat}, Vector{BigFloat}, Vector{BigFloat}, Float64}}, FunctionWrappers.FunctionWrapper{Nothing, Tuple{Vector{ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}, Vector{ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}, Vector{BigFloat}, Float64}}, FunctionWrappers.FunctionWrapper{Nothing, Tuple{Vector{ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}, Vector{BigFloat}, Vector{BigFloat}, ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}}, FunctionWrappers.FunctionWrapper{Nothing, Tuple{Vector{ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}, Vector{ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}, Vector{BigFloat}, ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}}}, false}, UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing, Nothing}, t::Float64, dt::Float64, reltol::Float64, p::Vector{BigFloat}, calck::Bool, ::Val{true})
    @ OrdinaryDiffEqCore ~/.julia/packages/OrdinaryDiffEqCore/2K6jv/src/caches/basic_caches.jl:109
  [5] alg_cache(alg::CompositeAlgorithm{1, Tuple{Vern8{typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!), Static.False}, Rodas5{1, true, Nothing, typeof(OrdinaryDiffEqCore.DEFAULT_PRECS), Val{:forward}, true, nothing, typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!)}}, OrdinaryDiffEqCore.AutoSwitchCache{Vern8{typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!), Static.False}, Rodas5{0, true, Nothing, typeof(OrdinaryDiffEqCore.DEFAULT_PRECS), Val{:forward}, true, nothing, typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!)}, Float64, Int64}}, u::Vector{BigFloat}, rate_prototype::Vector{BigFloat}, ::Type{BigFloat}, ::Type{BigFloat}, ::Type{Float64}, uprev::Vector{BigFloat}, uprev2::Vector{BigFloat}, f::ODEFunction{true, SciMLBase.AutoSpecialize, FunctionWrappersWrappers.FunctionWrappersWrapper{Tuple{FunctionWrappers.FunctionWrapper{Nothing, Tuple{Vector{BigFloat}, Vector{BigFloat}, Vector{BigFloat}, Float64}}, FunctionWrappers.FunctionWrapper{Nothing, Tuple{Vector{ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}, Vector{ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}, Vector{BigFloat}, Float64}}, FunctionWrappers.FunctionWrapper{Nothing, Tuple{Vector{ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}, Vector{BigFloat}, Vector{BigFloat}, ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}}, FunctionWrappers.FunctionWrapper{Nothing, Tuple{Vector{ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}, Vector{ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}, Vector{BigFloat}, ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}}}, false}, UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing, Nothing}, t::Float64, dt::Float64, reltol::Float64, p::Vector{BigFloat}, calck::Bool, ::Val{true})
    @ OrdinaryDiffEqCore ~/.julia/packages/OrdinaryDiffEqCore/2K6jv/src/caches/basic_caches.jl:63
  [6] __init(prob::ODEProblem{Vector{BigFloat}, Tuple{Float64, Float64}, true, Vector{BigFloat}, ODEFunction{true, SciMLBase.AutoSpecialize, FunctionWrappersWrappers.FunctionWrappersWrapper{Tuple{FunctionWrappers.FunctionWrapper{Nothing, Tuple{Vector{BigFloat}, Vector{BigFloat}, Vector{BigFloat}, Float64}}, FunctionWrappers.FunctionWrapper{Nothing, Tuple{Vector{ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}, Vector{ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}, Vector{BigFloat}, Float64}}, FunctionWrappers.FunctionWrapper{Nothing, Tuple{Vector{ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}, Vector{BigFloat}, Vector{BigFloat}, ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}}, FunctionWrappers.FunctionWrapper{Nothing, Tuple{Vector{ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}, Vector{ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}, Vector{BigFloat}, ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}}}, false}, UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, alg::CompositeAlgorithm{1, Tuple{Vern8{typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!), Static.False}, Rodas5{1, true, Nothing, typeof(OrdinaryDiffEqCore.DEFAULT_PRECS), Val{:forward}, true, nothing, typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!)}}, AutoSwitch{Vern8{typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!), Static.False}, Rodas5{0, true, Nothing, typeof(OrdinaryDiffEqCore.DEFAULT_PRECS), Val{:forward}, true, nothing, typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!)}, Float64, Int64}}, timeseries_init::Tuple{}, ts_init::Tuple{}, ks_init::Tuple{}, recompile::Type{Val{true}}; saveat::Int64, tstops::Tuple{}, d_discontinuities::Tuple{}, save_idxs::Nothing, save_everystep::Bool, save_on::Bool, save_start::Bool, save_end::Nothing, callback::Nothing, dense::Bool, calck::Bool, dt::Float64, dtmin::Float64, dtmax::Float64, force_dtmin::Bool, adaptive::Bool, gamma::Rational{Int64}, abstol::Float64, reltol::Float64, qmin::Rational{Int64}, qmax::Int64, qsteady_min::Int64, qsteady_max::Int64, beta1::Nothing, beta2::Nothing, qoldinit::Rational{Int64}, controller::Nothing, fullnormalize::Bool, failfactor::Int64, maxiters::Int64, internalnorm::typeof(DiffEqBase.ODE_DEFAULT_NORM), internalopnorm::typeof(opnorm), isoutofdomain::typeof(DiffEqBase.ODE_DEFAULT_ISOUTOFDOMAIN), unstable_check::typeof(DiffEqBase.ODE_DEFAULT_UNSTABLE_CHECK), verbose::Bool, timeseries_errors::Bool, dense_errors::Bool, advance_to_tstop::Bool, stop_at_next_tstop::Bool, initialize_save::Bool, progress::Bool, progress_steps::Int64, progress_name::String, progress_message::typeof(DiffEqBase.ODE_DEFAULT_PROG_MESSAGE), progress_id::Symbol, userdata::Nothing, allow_extrapolation::Bool, initialize_integrator::Bool, alias_u0::Bool, alias_du0::Bool, initializealg::OrdinaryDiffEqCore.DefaultInit, kwargs::@Kwargs{})
    @ OrdinaryDiffEqCore ~/.julia/packages/OrdinaryDiffEqCore/2K6jv/src/solve.jl:376
  [7] __solve(::ODEProblem{Vector{BigFloat}, Tuple{Float64, Float64}, true, Vector{BigFloat}, ODEFunction{true, SciMLBase.AutoSpecialize, FunctionWrappersWrappers.FunctionWrappersWrapper{Tuple{FunctionWrappers.FunctionWrapper{Nothing, Tuple{Vector{BigFloat}, Vector{BigFloat}, Vector{BigFloat}, Float64}}, FunctionWrappers.FunctionWrapper{Nothing, Tuple{Vector{ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}, Vector{ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}, Vector{BigFloat}, Float64}}, FunctionWrappers.FunctionWrapper{Nothing, Tuple{Vector{ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}, Vector{BigFloat}, Vector{BigFloat}, ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}}, FunctionWrappers.FunctionWrapper{Nothing, Tuple{Vector{ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}, Vector{ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}, Vector{BigFloat}, ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}}}, false}, UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, ::CompositeAlgorithm{1, Tuple{Vern8{typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!), Static.False}, Rodas5{1, true, Nothing, typeof(OrdinaryDiffEqCore.DEFAULT_PRECS), Val{:forward}, true, nothing, typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!)}}, AutoSwitch{Vern8{typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!), Static.False}, Rodas5{0, true, Nothing, typeof(OrdinaryDiffEqCore.DEFAULT_PRECS), Val{:forward}, true, nothing, typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!)}, Float64, Int64}}; kwargs::@Kwargs{saveat::Int64, abstol::Float64, reltol::Float64, maxiters::Int64})
    @ OrdinaryDiffEqCore ~/.julia/packages/OrdinaryDiffEqCore/2K6jv/src/solve.jl:6
  [8] solve_call(_prob::ODEProblem{Vector{BigFloat}, Tuple{Float64, Float64}, true, Vector{BigFloat}, ODEFunction{true, SciMLBase.AutoSpecialize, FunctionWrappersWrappers.FunctionWrappersWrapper{Tuple{FunctionWrappers.FunctionWrapper{Nothing, Tuple{Vector{BigFloat}, Vector{BigFloat}, Vector{BigFloat}, Float64}}, FunctionWrappers.FunctionWrapper{Nothing, Tuple{Vector{ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}, Vector{ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}, Vector{BigFloat}, Float64}}, FunctionWrappers.FunctionWrapper{Nothing, Tuple{Vector{ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}, Vector{BigFloat}, Vector{BigFloat}, ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}}, FunctionWrappers.FunctionWrapper{Nothing, Tuple{Vector{ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}, Vector{ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}, Vector{BigFloat}, ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, BigFloat}, BigFloat, 1}}}}, false}, UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, args::CompositeAlgorithm{1, Tuple{Vern8{typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!), Static.False}, Rodas5{1, true, Nothing, typeof(OrdinaryDiffEqCore.DEFAULT_PRECS), Val{:forward}, true, nothing, typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!)}}, AutoSwitch{Vern8{typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!), Static.False}, Rodas5{0, true, Nothing, typeof(OrdinaryDiffEqCore.DEFAULT_PRECS), Val{:forward}, true, nothing, typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!)}, Float64, Int64}}; merge_callbacks::Bool, kwargshandle::Nothing, kwargs::@Kwargs{saveat::Int64, abstol::Float64, reltol::Float64, maxiters::Int64})
    @ DiffEqBase ~/.julia/packages/DiffEqBase/frOsk/src/solve.jl:612
  [9] solve_up(prob::ODEProblem{Vector{BigFloat}, Tuple{Float64, Float64}, true, Vector{BigFloat}, ODEFunction{true, SciMLBase.AutoSpecialize, var"#658#729"{Int64, Vector{BigFloat}, Vector{BigFloat}}, UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, sensealg::Nothing, u0::Vector{BigFloat}, p::Vector{BigFloat}, args::CompositeAlgorithm{0, Tuple{Vern8{typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!), Static.False}, Rodas5{0, true, Nothing, typeof(OrdinaryDiffEqCore.DEFAULT_PRECS), Val{:forward}, true, nothing, typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!)}}, AutoSwitch{Vern8{typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!), Static.False}, Rodas5{0, true, Nothing, typeof(OrdinaryDiffEqCore.DEFAULT_PRECS), Val{:forward}, true, nothing, typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!)}, Float64, Int64}}; kwargs::@Kwargs{saveat::Int64, abstol::Float64, reltol::Float64, maxiters::Int64})
    @ DiffEqBase ~/.julia/packages/DiffEqBase/frOsk/src/solve.jl:1092
 [10] solve(prob::ODEProblem{Vector{BigFloat}, Tuple{Float64, Float64}, true, Vector{BigFloat}, ODEFunction{true, SciMLBase.AutoSpecialize, var"#658#729"{Int64, Vector{BigFloat}, Vector{BigFloat}}, UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, args::CompositeAlgorithm{0, Tuple{Vern8{typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!), Static.False}, Rodas5{0, true, Nothing, typeof(OrdinaryDiffEqCore.DEFAULT_PRECS), Val{:forward}, true, nothing, typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!)}}, AutoSwitch{Vern8{typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!), Static.False}, Rodas5{0, true, Nothing, typeof(OrdinaryDiffEqCore.DEFAULT_PRECS), Val{:forward}, true, nothing, typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!)}, Float64, Int64}}; sensealg::Nothing, u0::Nothing, p::Nothing, wrap::Val{true}, kwargs::@Kwargs{saveat::Int64, abstol::Float64, reltol::Float64, maxiters::Int64})
    @ DiffEqBase ~/.julia/packages/DiffEqBase/frOsk/src/solve.jl:1015
 [11] RunCommunityDynamics(_theDimension::Int64, _R::Vector{BigFloat}, _K::Vector{BigFloat}, _D::Matrix{BigFloat}, _u0::Vector{BigFloat}, _tspan::Tuple{Float64, Float64}, _DEAbsTol::Float64, _DERelTol::Float64, _DEMaxIter::Int64, _Linearize::Bool)

Environment (please complete the following information):

  • Output of using Pkg; Pkg.status()
  [093aae92] BSplineKit v0.17.6
  [336ed68f] CSV v0.10.15
⌅ [3da002f7] ColorTypes v0.11.5
⌅ [5ae59095] Colors v0.12.11
  [861a8166] Combinatorics v1.0.2
  [a8cc5b0e] Crayons v4.1.1
  [a93c6f00] DataFrames v1.7.0
  [8bb1440f] DelimitedFiles v1.9.1
  [0c46a032] DifferentialEquations v7.15.0
  [f6369f11] ForwardDiff v0.10.38
  [38e38edf] GLM v1.9.0
  [50e95529] GeoStatsSolvers v0.7.16
  [a98d9a8b] Interpolations v0.15.1
  [98e50ef6] JuliaFormatter v1.0.62
  [b964fa9f] LaTeXStrings v1.4.0
  [d3d80556] LineSearches v7.3.0
  [4345ca2d] Loess v0.6.4
  [429524aa] Optim v1.10.0
  [7f7a1694] Optimization v4.0.5
  [36348300] OptimizationOptimJL v0.4.1
  [1dea7af3] OrdinaryDiffEq v6.90.1
  [a03496cd] PlotlyBase v0.8.19
  [f0f68f2c] PlotlyJS v0.18.15
  [f2990250] PlotlyKaleido v2.2.5
  [91a5bcdd] Plots v1.40.8
  [10745b16] Statistics v1.11.1
  [2913bbd2] StatsBase v0.34.3
  [f3b207a7] StatsPlots v0.15.7
  [bd369af6] Tables v1.12.0
  [ade2ca70] Dates v1.11.0
  [8ba89e20] Distributed v1.11.0
  [37e2e46d] LinearAlgebra v1.11.0
  [44cfe95a] Pkg v1.11.0
  [9a3f8284] Random v1.11.0
  [1a1011a3] SharedArrays v1.11.0
  • Output of using Pkg; Pkg.status(; mode = PKGMODE_MANIFEST)
  [47edcb42] ADTypes v1.9.0
  [621f4979] AbstractFFTs v1.5.0
  [1520ce14] AbstractTrees v0.4.5
  [7d9f7c33] Accessors v0.1.38
  [79e6a3ab] Adapt v4.1.1
  [66dad0bd] AliasTables v1.1.3
  [dce04be8] ArgCheck v2.3.0
  [ec485272] ArnoldiMethod v0.4.0
  [7d9fca2a] Arpack v0.5.4
  [4fba245c] ArrayInterface v7.17.0
  [4c555306] ArrayLayouts v1.10.4
  [bf4720bc] AssetRegistry v0.1.0
  [13072b0f] AxisAlgorithms v1.1.0
  [39de3d68] AxisArrays v0.4.7
  [093aae92] BSplineKit v0.17.6
  [aae01518] BandedMatrices v1.7.5
  [198e06fe] BangBang v0.4.3
  [9718e550] Baselet v0.1.1
  [0e736298] Bessels v0.2.8
  [e2ed5e7c] Bijections v0.1.9
  [d1d4a3ce] BitFlags v0.1.9
  [62783981] BitTwiddlingConvenienceFunctions v0.1.6
  [ad839575] Blink v0.12.9
  [764a87c0] BoundaryValueDiffEq v5.12.0
  [56b672f2] BoundaryValueDiffEqCore v1.0.2
  [85d9eb09] BoundaryValueDiffEqFIRK v1.0.2
  [1a22d4ce] BoundaryValueDiffEqMIRK v1.0.1
  [ed55bfe0] BoundaryValueDiffEqShooting v1.0.2
  [fa961155] CEnum v0.5.0
  [2a0fbf3d] CPUSummary v0.2.6
  [00ebfdb7] CSTParser v3.4.3
  [336ed68f] CSV v0.10.15
  [324d7699] CategoricalArrays v0.10.8
  [d360d2e6] ChainRulesCore v1.25.0
  [7a955b69] CircularArrays v1.4.0
  [fb6a15b2] CloseOpenIntervals v0.1.13
  [aaaa29a8] Clustering v0.15.7
  [5900dafe] CoDa v1.4.0
  [944b1d66] CodecZlib v0.7.6
  [35d6a980] ColorSchemes v3.27.1
⌅ [3da002f7] ColorTypes v0.11.5
⌃ [c3611d14] ColorVectorSpace v0.10.0
⌅ [5ae59095] Colors v0.12.11
⌅ [9cc86067] ColumnSelectors v0.1.1
  [861a8166] Combinatorics v1.0.2
  [a80b9123] CommonMark v0.8.15
  [38540f10] CommonSolve v0.2.4
  [bbf7d656] CommonSubexpressions v0.3.1
  [f70d9fcc] CommonWorldInvalidations v1.0.0
  [34da2185] Compat v4.16.0
  [b152e2b5] CompositeTypes v0.1.4
  [a33af91c] CompositionsBase v0.1.2
  [2569d6c7] ConcreteStructs v0.2.3
  [f0e56b4a] ConcurrentUtilities v2.4.2
  [88cd18e8] ConsoleProgressMonitor v0.1.2
  [187b0558] ConstructionBase v1.5.8
  [d38c429a] Contour v0.6.3
  [adafc99b] CpuId v0.3.1
  [a8cc5b0e] Crayons v4.1.1
  [9a962f9c] DataAPI v1.16.0
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  [76f85450] LibGit2 v1.11.0
  [8f399da3] Libdl v1.11.0
  [37e2e46d] LinearAlgebra v1.11.0
  [56ddb016] Logging v1.11.0
  [d6f4376e] Markdown v1.11.0
  [a63ad114] Mmap v1.11.0
  [ca575930] NetworkOptions v1.2.0
  [44cfe95a] Pkg v1.11.0
  [de0858da] Printf v1.11.0
  [3fa0cd96] REPL v1.11.0
  [9a3f8284] Random v1.11.0
  [ea8e919c] SHA v0.7.0
  [9e88b42a] Serialization v1.11.0
  [1a1011a3] SharedArrays v1.11.0
  [6462fe0b] Sockets v1.11.0
  [2f01184e] SparseArrays v1.11.0
  [f489334b] StyledStrings v1.11.0
  [4607b0f0] SuiteSparse
  [fa267f1f] TOML v1.0.3
  [a4e569a6] Tar v1.10.0
  [8dfed614] Test v1.11.0
  [cf7118a7] UUIDs v1.11.0
  [4ec0a83e] Unicode v1.11.0
  [e66e0078] CompilerSupportLibraries_jll v1.1.1+0
  [deac9b47] LibCURL_jll v8.6.0+0
  [e37daf67] LibGit2_jll v1.7.2+0
  [29816b5a] LibSSH2_jll v1.11.0+1
  [c8ffd9c3] MbedTLS_jll v2.28.6+0
  [14a3606d] MozillaCACerts_jll v2023.12.12
  [4536629a] OpenBLAS_jll v0.3.27+1
  [05823500] OpenLibm_jll v0.8.1+2
  [efcefdf7] PCRE2_jll v10.42.0+1
  [bea87d4a] SuiteSparse_jll v7.7.0+0
  [83775a58] Zlib_jll v1.2.13+1
  [8e850b90] libblastrampoline_jll v5.11.0+0
  [8e850ede] nghttp2_jll v1.59.0+0
  [3f19e933] p7zip_jll v17.4.0+2
  • Output of versioninfo()
Julia Version 1.11.1
Commit 8f5b7ca12ad (2024-10-16 10:53 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: macOS (x86_64-apple-darwin22.4.0)
  CPU: 12 × Intel(R) Core(TM) i9-8950HK CPU @ 2.90GHz
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, skylake)
Threads: 1 default, 0 interactive, 1 GC (on 12 virtual cores)

Additional context

@dtxl dtxl added the bug label Nov 12, 2024
@ChrisRackauckas
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Your MWE isn't runnable. odeProblem isn't defined. Please share how to get this error.

@dtxl
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dtxl commented Nov 12, 2024

The following sample produces the error.

using DifferentialEquations
function ODE(du, u, params, t, R, K)
end
params = [1. 0.91758707304098; 1.48439909482661 1.]
u0 = [0.1, 0.1]
tspan = (1.0, 31.0)
R = [0.443280390004304303, 1.172917082211452]
K = [13.470600276901400604, 12.52980757005]
ODE_ = (du, u, params, t) -> ODE(du, u, t, R, K)
odeProblem = DifferentialEquations.ODEProblem(ODE_, u0, tspan, params)
SwitchAlg = OrdinaryDiffEq.AutoVern8(OrdinaryDiffEq.Rodas5(), nonstifftol = 11 / 10)
Solution = DifferentialEquations.solve(odeProblem, SwitchAlg, saveat = 1, abstol = 1.e-12, reltol = 1.e-6, maxiters = 100)

@ChrisRackauckas
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using OrdinaryDiffEq
function ODE(du, u, t, R, K)
end
params = [1. 0.91758707304098; 1.48439909482661 1.]
u0 = [0.1, 0.1]
tspan = (1.0, 31.0)
R = [0.443280390004304303, 1.172917082211452]
K = [13.470600276901400604, 12.52980757005]
ODE_ = (du, u, params, t) -> ODE(du, u, t, R, K)
odeProblem = ODEProblem(ODE_, u0, tspan, params)
SwitchAlg = OrdinaryDiffEq.AutoVern8(OrdinaryDiffEq.Rodas5(), nonstifftol = 11 / 10)
Solution = solve(odeProblem, SwitchAlg, saveat = 1, abstol = 1.e-12, reltol = 1.e-6, maxiters = 100)
julia> Solution = solve(odeProblem, SwitchAlg, saveat = 1, abstol = 1.e-12, reltol = 1.e-6, maxiters = 100)
retcode: Success
Interpolation: 1st order linear
t: 31-element Vector{Float64}:
  1.0
  2.0
  3.0
  4.0
  
 28.0
 29.0
 30.0
 31.0
u: 31-element Vector{Vector{Float64}}:
 [0.1, 0.1]
 [0.1, 0.1]
 [0.1, 0.1]
 [0.1, 0.1]
 
 [0.1, 0.1]
 [0.1, 0.1]
 [0.1, 0.1]
 [0.1, 0.1]

Works fine when I copy pasted it (with a small correction to ODE).

Your error message seemed to require BigFloat time or state? Your MWE here only has Float64s though, so I don't see how this MWE is supposed to cover or reproduce that error anyways?

@dtxl
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dtxl commented Nov 12, 2024

Sorry for the mistake, you are right, I am using BigFloat. So with
params = BigFloat[1. 0.91758707304098; 1.48439909482661 1.]
u0 = BigFloat[0.1, 0.1]
tspan = (1.0, 31.0)
R = BigFloat[0.443280390004304303, 1.172917082211452]
K = BigFloat[13.470600276901400604, 12.52980757005]
the error occurs.

@ChrisRackauckas
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One line typo that needs a better test when mixing different precisions. Fixed in #2525, should be released in about a day.

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