remake type promotion fails with empty initial conditions

[hersle]

The last @test_nowarn in

using Test
using ModelingToolkit
using ModelingToolkit: t_nounits as t, D_nounits as D
using DifferentialEquations
using ForwardDiff

@testset "remake type promotion with empty initial conditions" begin
    @parameters P
    @variables x(t)

    # numerical ODE: x′(t) = P with x(0) = 0
    sys_num = structural_simplify(ODESystem([D(x) ~ P], t, [x], [P]; name = :sys))
    prob_num_uninit = ODEProblem(sys_num, [x => 0.0], (0.0, 1.0), [P => NaN]) # uninitialized problem
    x_at_1_num(P) = solve(remake(prob_num_uninit; p = [sys_num.P => P]))(1.0, idxs=x)

    # analytical solution: x(t) = P*t
    sys_anal = structural_simplify(ODESystem([x ~ P*t], t, [x], [P]; name = :sys))
    prob_anal_uninit = ODEProblem(sys_anal, [], (0.0, 1.0), [P => NaN])
    x_at_1_anal(P) = solve(remake(prob_anal_uninit; p = [sys_anal.P => P]))(1.0, idxs=x)

    @test_nowarn x_at_1_num(1.0)
    @test_nowarn x_at_1_anal(1.0)
    @test_nowarn ForwardDiff.derivative(x_at_1_num, 1.0)
    @test_nowarn ForwardDiff.derivative(x_at_1_anal, 1.0)
end

fails with the error

  MethodError: no method matching Float64(::Nothing)

  Closest candidates are:
    Float64(::IrrationalConstants.Loghalf)
     @ IrrationalConstants C:\Users\herma\.julia\packages\IrrationalConstants\vp5v4\src\macro.jl:112
    Float64(::Int8)
     @ Base float.jl:159
    Float64(::UInt8)
     @ Base float.jl:165
    ...

  Stacktrace:
    [1] convert(::Type{ForwardDiff.Dual{ForwardDiff.Tag{var"#x_at_1_anal#10"{ODEProblem{Nothing, Tuple{Float64, Float64}, true, ModelingToolkit.MTKParameters{Tuple{Vector{Float64}}, Tuple{}, Tuple{}, Tuple{}, Tuple{}, Nothing, Nothing}, ODEFunction{true, SciMLBase.AutoSpecialize, ModelingToolkit.var"#f#709"{RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋arg1, :ˍ₋arg2, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x68b6838e, 0xdcde5d93, 0xe95aa607, 0x31d03dbd, 0xdc6d45c2), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :ˍ₋arg1, :ˍ₋arg2, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0xfeaddeee, 0x8de91b1a, 0x6c8ccac3, 0x1362a2f5, 0x5821e073), Nothing}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ModelingToolkit.var"#878#generated_observed#718"{Bool, ODESystem, Dict{Any, Any}, Vector{Any}}, Nothing, ODESystem, Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, ODESystem, Num}, Float64}, Float64, 1}}, x::Nothing)
      @ ForwardDiff C:\Users\herma\.julia\packages\ForwardDiff\PcZ48\src\dual.jl:435
    [2] ForwardDiff.Dual{ForwardDiff.Tag{var"#x_at_1_anal#10"{ODEProblem{Nothing, Tuple{Float64, Float64}, true, ModelingToolkit.MTKParameters{Tuple{Vector{Float64}}, Tuple{}, Tuple{}, Tuple{}, Tuple{}, Nothing, Nothing}, ODEFunction{true, SciMLBase.AutoSpecialize, ModelingToolkit.var"#f#709"{RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋arg1, :ˍ₋arg2, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x68b6838e, 0xdcde5d93, 0xe95aa607, 0x31d03dbd, 0xdc6d45c2), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :ˍ₋arg1, :ˍ₋arg2, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0xfeaddeee, 0x8de91b1a, 0x6c8ccac3, 0x1362a2f5, 0x5821e073), Nothing}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ModelingToolkit.var"#878#generated_observed#718"{Bool, ODESystem, Dict{Any, Any}, Vector{Any}}, Nothing, ODESystem, Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, ODESystem, Num}, Float64}, Float64, 1}(x::Nothing)
      @ ForwardDiff C:\Users\herma\.julia\packages\ForwardDiff\PcZ48\src\dual.jl:77
    [3] _broadcast_getindex_evalf(f::Type{ForwardDiff.Dual{ForwardDiff.Tag{var"#x_at_1_anal#10"{ODEProblem{Nothing, Tuple{Float64, Float64}, true, ModelingToolkit.MTKParameters{Tuple{Vector{Float64}}, Tuple{}, Tuple{}, Tuple{}, Tuple{}, Nothing, Nothing}, ODEFunction{true, SciMLBase.AutoSpecialize, ModelingToolkit.var"#f#709"{RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋arg1, :ˍ₋arg2, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x68b6838e, 0xdcde5d93, 0xe95aa607, 0x31d03dbd, 0xdc6d45c2), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :ˍ₋arg1, :ˍ₋arg2, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0xfeaddeee, 0x8de91b1a, 0x6c8ccac3, 0x1362a2f5, 0x5821e073), Nothing}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ModelingToolkit.var"#878#generated_observed#718"{Bool, ODESystem, Dict{Any, Any}, Vector{Any}}, Nothing, ODESystem, Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, ODESystem, Num}, Float64}, Float64, 1}}, args::Nothing)
      @ Base.Broadcast .\broadcast.jl:709
    [4] _broadcast_getindex
      @ .\broadcast.jl:682 [inlined]
    [5] getindex
      @ .\broadcast.jl:636 [inlined]
    [6] copy
      @ .\broadcast.jl:918 [inlined]
    [7] materialize
      @ .\broadcast.jl:903 [inlined]
    [8] promote_u0
      @ C:\Users\herma\.julia\packages\DiffEqBase\NaUtB\src\forwarddiff.jl:269 [inlined]
    [9] get_concrete_problem(prob::ODEProblem{Nothing, Tuple{Float64, Float64}, true, ModelingToolkit.MTKParameters{Tuple{Vector{ForwardDiff.Dual{ForwardDiff.Tag{var"#x_at_1_anal#10"{ODEProblem{Nothing, Tuple{Float64, Float64}, true, ModelingToolkit.MTKParameters{Tuple{Vector{Float64}}, Tuple{}, Tuple{}, Tuple{}, Tuple{}, Nothing, Nothing}, ODEFunction{true, SciMLBase.AutoSpecialize, ModelingToolkit.var"#f#709"{RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋arg1, :ˍ₋arg2, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x68b6838e, 0xdcde5d93, 0xe95aa607, 0x31d03dbd, 0xdc6d45c2), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :ˍ₋arg1, :ˍ₋arg2, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0xfeaddeee, 0x8de91b1a, 0x6c8ccac3, 0x1362a2f5, 0x5821e073), Nothing}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ModelingToolkit.var"#878#generated_observed#718"{Bool, ODESystem, Dict{Any, Any}, Vector{Any}}, Nothing, ODESystem, Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, ODESystem, Num}, Float64}, Float64, 1}}}, Tuple{}, Tuple{}, Tuple{}, Tuple{}, Nothing, Nothing}, ODEFunction{true, SciMLBase.AutoSpecialize, ModelingToolkit.var"#f#709"{RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋arg1, :ˍ₋arg2, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x68b6838e, 0xdcde5d93, 0xe95aa607, 0x31d03dbd, 0xdc6d45c2), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :ˍ₋arg1, :ˍ₋arg2, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0xfeaddeee, 0x8de91b1a, 0x6c8ccac3, 0x1362a2f5, 0x5821e073), Nothing}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ModelingToolkit.var"#878#generated_observed#718"{Bool, ODESystem, Dict{Any, Any}, Vector{Any}}, Nothing, ODESystem, Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, isadapt::Bool; kwargs::@Kwargs{u0::Nothing, p::ModelingToolkit.MTKParameters{Tuple{Vector{ForwardDiff.Dual{ForwardDiff.Tag{var"#x_at_1_anal#10"{ODEProblem{Nothing, Tuple{Float64, Float64}, true, ModelingToolkit.MTKParameters{Tuple{Vector{Float64}}, Tuple{}, Tuple{}, Tuple{}, Tuple{}, Nothing, Nothing}, ODEFunction{true, SciMLBase.AutoSpecialize, ModelingToolkit.var"#f#709"{RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋arg1, :ˍ₋arg2, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x68b6838e, 0xdcde5d93, 0xe95aa607, 0x31d03dbd, 0xdc6d45c2), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :ˍ₋arg1, :ˍ₋arg2, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0xfeaddeee, 0x8de91b1a, 0x6c8ccac3, 0x1362a2f5, 0x5821e073), Nothing}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ModelingToolkit.var"#878#generated_observed#718"{Bool, ODESystem, Dict{Any, Any}, Vector{Any}}, Nothing, ODESystem, Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, ODESystem, Num}, Float64}, Float64, 1}}}, Tuple{}, Tuple{}, Tuple{}, Tuple{}, Nothing, Nothing}})
      @ DiffEqBase C:\Users\herma\.julia\packages\DiffEqBase\NaUtB\src\solve.jl:1171
   [10] solve_up(::ODEProblem{Nothing, Tuple{Float64, Float64}, true, ModelingToolkit.MTKParameters{Tuple{Vector{ForwardDiff.Dual{ForwardDiff.Tag{var"#x_at_1_anal#10"{ODEProblem{Nothing, Tuple{Float64, Float64}, true, ModelingToolkit.MTKParameters{Tuple{Vector{Float64}}, Tuple{}, Tuple{}, Tuple{}, Tuple{}, Nothing, Nothing}, ODEFunction{true, SciMLBase.AutoSpecialize, ModelingToolkit.var"#f#709"{RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋arg1, :ˍ₋arg2, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x68b6838e, 0xdcde5d93, 0xe95aa607, 0x31d03dbd, 0xdc6d45c2), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :ˍ₋arg1, :ˍ₋arg2, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0xfeaddeee, 0x8de91b1a, 0x6c8ccac3, 0x1362a2f5, 0x5821e073), Nothing}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ModelingToolkit.var"#878#generated_observed#718"{Bool, ODESystem, Dict{Any, Any}, Vector{Any}}, Nothing, ODESystem, Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, ODESystem, Num}, Float64}, Float64, 1}}}, Tuple{}, Tuple{}, Tuple{}, Tuple{}, Nothing, Nothing}, ODEFunction{true, SciMLBase.AutoSpecialize, ModelingToolkit.var"#f#709"{RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋arg1, :ˍ₋arg2, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x68b6838e, 0xdcde5d93, 0xe95aa607, 0x31d03dbd, 0xdc6d45c2), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :ˍ₋arg1, :ˍ₋arg2, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0xfeaddeee, 0x8de91b1a, 0x6c8ccac3, 0x1362a2f5, 0x5821e073), Nothing}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ModelingToolkit.var"#878#generated_observed#718"{Bool, ODESystem, Dict{Any, Any}, Vector{Any}}, Nothing, ODESystem, Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, ::Nothing, ::Nothing, ::ModelingToolkit.MTKParameters{Tuple{Vector{ForwardDiff.Dual{ForwardDiff.Tag{var"#x_at_1_anal#10"{ODEProblem{Nothing, Tuple{Float64, Float64}, true, ModelingToolkit.MTKParameters{Tuple{Vector{Float64}}, Tuple{}, Tuple{}, Tuple{}, Tuple{}, Nothing, Nothing}, ODEFunction{true, SciMLBase.AutoSpecialize, ModelingToolkit.var"#f#709"{RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋arg1, :ˍ₋arg2, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x68b6838e, 0xdcde5d93, 0xe95aa607, 0x31d03dbd, 0xdc6d45c2), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :ˍ₋arg1, :ˍ₋arg2, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0xfeaddeee, 0x8de91b1a, 0x6c8ccac3, 0x1362a2f5, 0x5821e073), Nothing}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ModelingToolkit.var"#878#generated_observed#718"{Bool, ODESystem, Dict{Any, Any}, Vector{Any}}, Nothing, ODESystem, Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, ODESystem, Num}, Float64}, Float64, 1}}}, Tuple{}, Tuple{}, Tuple{}, Tuple{}, Nothing, Nothing}; kwargs::@Kwargs{})
      @ DiffEqBase C:\Users\herma\.julia\packages\DiffEqBase\NaUtB\src\solve.jl:1070
   [11] solve_up(::ODEProblem{Nothing, Tuple{Float64, Float64}, true, ModelingToolkit.MTKParameters{Tuple{Vector{ForwardDiff.Dual{ForwardDiff.Tag{var"#x_at_1_anal#10"{ODEProblem{Nothing, Tuple{Float64, Float64}, true, ModelingToolkit.MTKParameters{Tuple{Vector{Float64}}, Tuple{}, Tuple{}, Tuple{}, Tuple{}, Nothing, Nothing}, ODEFunction{true, SciMLBase.AutoSpecialize, ModelingToolkit.var"#f#709"{RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋arg1, :ˍ₋arg2, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x68b6838e, 0xdcde5d93, 0xe95aa607, 0x31d03dbd, 0xdc6d45c2), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :ˍ₋arg1, :ˍ₋arg2, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0xfeaddeee, 0x8de91b1a, 0x6c8ccac3, 0x1362a2f5, 0x5821e073), Nothing}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ModelingToolkit.var"#878#generated_observed#718"{Bool, ODESystem, Dict{Any, Any}, Vector{Any}}, Nothing, ODESystem, Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, ODESystem, Num}, Float64}, Float64, 1}}}, Tuple{}, Tuple{}, Tuple{}, Tuple{}, Nothing, Nothing}, ODEFunction{true, SciMLBase.AutoSpecialize, ModelingToolkit.var"#f#709"{RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋arg1, :ˍ₋arg2, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x68b6838e, 0xdcde5d93, 0xe95aa607, 0x31d03dbd, 0xdc6d45c2), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :ˍ₋arg1, :ˍ₋arg2, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0xfeaddeee, 0x8de91b1a, 0x6c8ccac3, 0x1362a2f5, 0x5821e073), Nothing}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ModelingToolkit.var"#878#generated_observed#718"{Bool, ODESystem, Dict{Any, Any}, Vector{Any}}, Nothing, ODESystem, Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, ::Nothing, ::Nothing, ::ModelingToolkit.MTKParameters{Tuple{Vector{ForwardDiff.Dual{ForwardDiff.Tag{var"#x_at_1_anal#10"{ODEProblem{Nothing, Tuple{Float64, Float64}, true, ModelingToolkit.MTKParameters{Tuple{Vector{Float64}}, Tuple{}, Tuple{}, Tuple{}, Tuple{}, Nothing, Nothing}, ODEFunction{true, SciMLBase.AutoSpecialize, ModelingToolkit.var"#f#709"{RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋arg1, :ˍ₋arg2, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x68b6838e, 0xdcde5d93, 0xe95aa607, 0x31d03dbd, 0xdc6d45c2), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :ˍ₋arg1, :ˍ₋arg2, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0xfeaddeee, 0x8de91b1a, 0x6c8ccac3, 0x1362a2f5, 0x5821e073), Nothing}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ModelingToolkit.var"#878#generated_observed#718"{Bool, ODESystem, Dict{Any, Any}, Vector{Any}}, Nothing, ODESystem, Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, ODESystem, Num}, Float64}, Float64, 1}}}, Tuple{}, Tuple{}, Tuple{}, Tuple{}, Nothing, Nothing})    
      @ DiffEqBase C:\Users\herma\.julia\packages\DiffEqBase\NaUtB\src\solve.jl:1066
   [12] solve(::ODEProblem{Nothing, Tuple{Float64, Float64}, true, ModelingToolkit.MTKParameters{Tuple{Vector{ForwardDiff.Dual{ForwardDiff.Tag{var"#x_at_1_anal#10"{ODEProblem{Nothing, Tuple{Float64, Float64}, true, ModelingToolkit.MTKParameters{Tuple{Vector{Float64}}, Tuple{}, Tuple{}, Tuple{}, Tuple{}, Nothing, Nothing}, ODEFunction{true, SciMLBase.AutoSpecialize, ModelingToolkit.var"#f#709"{RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋arg1, :ˍ₋arg2, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x68b6838e, 0xdcde5d93, 0xe95aa607, 0x31d03dbd, 0xdc6d45c2), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :ˍ₋arg1, :ˍ₋arg2, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0xfeaddeee, 0x8de91b1a, 0x6c8ccac3, 0x1362a2f5, 0x5821e073), Nothing}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ModelingToolkit.var"#878#generated_observed#718"{Bool, ODESystem, Dict{Any, Any}, Vector{Any}}, Nothing, ODESystem, Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, ODESystem, Num}, Float64}, Float64, 1}}}, Tuple{}, Tuple{}, Tuple{}, Tuple{}, Nothing, Nothing}, ODEFunction{true, SciMLBase.AutoSpecialize, ModelingToolkit.var"#f#709"{RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋arg1, :ˍ₋arg2, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x68b6838e, 0xdcde5d93, 0xe95aa607, 0x31d03dbd, 0xdc6d45c2), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :ˍ₋arg1, :ˍ₋arg2, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0xfeaddeee, 0x8de91b1a, 0x6c8ccac3, 0x1362a2f5, 0x5821e073), Nothing}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ModelingToolkit.var"#878#generated_observed#718"{Bool, ODESystem, Dict{Any, Any}, Vector{Any}}, Nothing, ODESystem, Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}; sensealg::Nothing, u0::Nothing, p::Nothing, wrap::Val{true}, kwargs::@Kwargs{})
      @ DiffEqBase C:\Users\herma\.julia\packages\DiffEqBase\NaUtB\src\solve.jl:1003
   [13] solve(::ODEProblem{Nothing, Tuple{Float64, Float64}, true, ModelingToolkit.MTKParameters{Tuple{Vector{ForwardDiff.Dual{ForwardDiff.Tag{var"#x_at_1_anal#10"{ODEProblem{Nothing, Tuple{Float64, Float64}, true, ModelingToolkit.MTKParameters{Tuple{Vector{Float64}}, Tuple{}, Tuple{}, Tuple{}, Tuple{}, Nothing, Nothing}, ODEFunction{true, SciMLBase.AutoSpecialize, ModelingToolkit.var"#f#709"{RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋arg1, :ˍ₋arg2, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x68b6838e, 0xdcde5d93, 0xe95aa607, 0x31d03dbd, 0xdc6d45c2), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :ˍ₋arg1, :ˍ₋arg2, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0xfeaddeee, 0x8de91b1a, 0x6c8ccac3, 0x1362a2f5, 0x5821e073), Nothing}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ModelingToolkit.var"#878#generated_observed#718"{Bool, ODESystem, Dict{Any, Any}, Vector{Any}}, Nothing, ODESystem, Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, ODESystem, Num}, Float64}, Float64, 1}}}, Tuple{}, Tuple{}, Tuple{}, Tuple{}, Nothing, Nothing}, ODEFunction{true, SciMLBase.AutoSpecialize, ModelingToolkit.var"#f#709"{RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋arg1, :ˍ₋arg2, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x68b6838e, 0xdcde5d93, 0xe95aa607, 0x31d03dbd, 0xdc6d45c2), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :ˍ₋arg1, :ˍ₋arg2, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0xfeaddeee, 0x8de91b1a, 0x6c8ccac3, 0x1362a2f5, 0x5821e073), Nothing}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ModelingToolkit.var"#878#generated_observed#718"{Bool, ODESystem, Dict{Any, Any}, Vector{Any}}, Nothing, ODESystem, Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem})
      @ DiffEqBase C:\Users\herma\.julia\packages\DiffEqBase\NaUtB\src\solve.jl:993
   [14] (::var"#x_at_1_anal#10"{ODEProblem{Nothing, Tuple{Float64, Float64}, true, ModelingToolkit.MTKParameters{Tuple{Vector{Float64}}, Tuple{}, Tuple{}, Tuple{}, Tuple{}, Nothing, Nothing}, ODEFunction{true, SciMLBase.AutoSpecialize, ModelingToolkit.var"#f#709"{RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋arg1, :ˍ₋arg2, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x68b6838e, 0xdcde5d93, 0xe95aa607, 0x31d03dbd, 0xdc6d45c2), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :ˍ₋arg1, :ˍ₋arg2, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0xfeaddeee, 0x8de91b1a, 0x6c8ccac3, 0x1362a2f5, 0x5821e073), Nothing}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ModelingToolkit.var"#878#generated_observed#718"{Bool, ODESystem, Dict{Any, Any}, Vector{Any}}, Nothing, ODESystem, Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, ODESystem, Num})(P::ForwardDiff.Dual{ForwardDiff.Tag{var"#x_at_1_anal#10"{ODEProblem{Nothing, Tuple{Float64, Float64}, true, ModelingToolkit.MTKParameters{Tuple{Vector{Float64}}, Tuple{}, Tuple{}, Tuple{}, Tuple{}, Nothing, Nothing}, ODEFunction{true, SciMLBase.AutoSpecialize, ModelingToolkit.var"#f#709"{RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋arg1, :ˍ₋arg2, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x68b6838e, 0xdcde5d93, 0xe95aa607, 0x31d03dbd, 0xdc6d45c2), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :ˍ₋arg1, :ˍ₋arg2, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0xfeaddeee, 0x8de91b1a, 0x6c8ccac3, 0x1362a2f5, 0x5821e073), Nothing}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ModelingToolkit.var"#878#generated_observed#718"{Bool, ODESystem, Dict{Any, Any}, Vector{Any}}, Nothing, ODESystem, Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, ODESystem, Num}, Float64}, Float64, 1})
      @ Main C:\Users\herma\Dropbox\School\UIO\Research\boltzmann\bug.jl:19
   [15] derivative
      @ C:\Users\herma\.julia\packages\ForwardDiff\PcZ48\src\derivative.jl:14 [inlined]
   [16] (::var"#8#18"{var"#x_at_1_anal#10"{ODEProblem{Nothing, Tuple{Float64, Float64}, true, ModelingToolkit.MTKParameters{Tuple{Vector{Float64}}, Tuple{}, Tuple{}, Tuple{}, Tuple{}, Nothing, Nothing}, ODEFunction{true, SciMLBase.AutoSpecialize, ModelingToolkit.var"#f#709"{RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋arg1, :ˍ₋arg2, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0x68b6838e, 0xdcde5d93, 0xe95aa607, 0x31d03dbd, 0xdc6d45c2), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :ˍ₋arg1, :ˍ₋arg2, :t), ModelingToolkit.var"#_RGF_ModTag", ModelingToolkit.var"#_RGF_ModTag", (0xfeaddeee, 0x8de91b1a, 0x6c8ccac3, 0x1362a2f5, 0x5821e073), Nothing}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ModelingToolkit.var"#878#generated_observed#718"{Bool, ODESystem, Dict{Any, Any}, Vector{Any}}, Nothing, ODESystem, Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, ODESystem, Num}})()     
      @ Main C:\Users\herma\.julia\juliaup\julia-1.10.2+0.x64.w64.mingw32\share\julia\stdlib\v1.10\Test\src\Test.jl:898     
    ...

Is there a missing type promotion when u0 = nothing (empty initial conditions)?

[ChrisRackauckas]

Is this with the latest MTK? Show ]st

[hersle]

Sorry, I should have clarified. It fails on both master and the most recent stable. Here is ]st on master:

  [0c46a032] DifferentialEquations v7.13.0
  [f6369f11] ForwardDiff v0.10.36
  [961ee093] ModelingToolkit v9.12.0 `https://github.com/SciML/ModelingToolkit.jl.git#master`
  [1dea7af3] OrdinaryDiffEq v6.74.1
  [90137ffa] StaticArrays v1.9.3
  [2efcf032] SymbolicIndexingInterface v0.3.16

[ChrisRackauckas]

Looks like a bug in the anytypedual handling @AayushSabharwal