MonteCarloSummary for integer u0.

[korsbo]

This may not be a big issue, but I thought I'd report it.

MonteCarloSummary does not work if you have used an initial condition of integers. This error popped up for me when I was playing with jump equations. An obvious workaroud is to use floats in the u0 vector, so this problem is not very crippling. It would, however, be more pleasing if the function handled Integer input too.

using DifferentialEquations

rn = @reaction_network test begin
    (p, d), 0 ↔ x
    end p d
p = [100., 1]
u0 = [0]
tspan = (0., 10)

discrete_prob = DiscreteProblem(u0,tspan,p)
# discrete_prob = DiscreteProblem(float.(u0),tspan,p) # works
jump_prob = JumpProblem(discrete_prob,Direct(),rn)
mc_prob = MonteCarloProblem(jump_prob)
sol = solve(mc_prob,FunctionMap(); num_monte=10)
summary = MonteCarloSummary(sol)

InexactError: Int64(0.2)

Stacktrace:
 [1] Type at ./float.jl:703 [inlined]
 [2] convert at ./number.jl:7 [inlined]
 [3] setindex! at ./array.jl:767 [inlined]
 [4] macro expansion at ./broadcast.jl:843 [inlined]
 [5] macro expansion at ./simdloop.jl:73 [inlined]
 [6] copyto! at ./broadcast.jl:842 [inlined]
 [7] copyto! at ./broadcast.jl:797 [inlined]
 [8] materialize!(::Array{Int64,1}, ::Base.Broadcast.Broadcasted{Base.Broadcast.DefaultArrayStyle{1},Nothing,typeof(+),Tuple{Array{Int64,1},Base.Broadcast.Broadcasted{Base.Broadcast.DefaultArrayStyle{1},Nothing,typeof(/),Tuple{Array{Int64,1},Int64}}}}) at ./broadcast.jl:756
 [9] #componentwise_meanvar#57(::Bool, ::Function, ::Base.Generator{MonteCarloSolution{Int64,3,Array{ODESolution{Int64,2,Array{Array{Int64,1},1},Nothing,Nothing,Array{Float64,1},Array{Array{Array{Float64,1},1},1},DiscreteProblem{Array{Int64,1},Tuple{Float64,Float64},true,Array{Float64,1},DiscreteFunction{true,getfield(DiffEqBase, Symbol("##270#271")),Nothing},Nothing},FunctionMap{false},OrdinaryDiffEq.InterpolationData{DiscreteFunction{true,getfield(DiffEqBase, Symbol("##270#271")),Nothing},Array{Array{Int64,1},1},Array{Float64,1},Array{Array{Array{Float64,1},1},1},OrdinaryDiffEq.FunctionMapCache{Array{Int64,1},Array{Int64,1}}}},1}},getfield(DiffEqMonteCarlo, Symbol("##14#15")){Float64}}) at /home/Niklas/.julia/packages/DiffEqMonteCarlo/c9ztK/src/analysis.jl:180
 [10] componentwise_meanvar at /home/Niklas/.julia/packages/DiffEqMonteCarlo/c9ztK/src/analysis.jl:170 [inlined]
 [11] timepoint_meanvar at /home/Niklas/.julia/packages/DiffEqMonteCarlo/c9ztK/src/analysis.jl:97 [inlined]
 [12] timeseries_point_meanvar(::MonteCarloSolution{Int64,3,Array{ODESolution{Int64,2,Array{Array{Int64,1},1},Nothing,Nothing,Array{Float64,1},Array{Array{Array{Float64,1},1},1},DiscreteProblem{Array{Int64,1},Tuple{Float64,Float64},true,Array{Float64,1},DiscreteFunction{true,getfield(DiffEqBase, Symbol("##270#271")),Nothing},Nothing},FunctionMap{false},OrdinaryDiffEq.InterpolationData{DiscreteFunction{true,getfield(DiffEqBase, Symbol("##270#271")),Nothing},Array{Array{Int64,1},1},Array{Float64,1},Array{Array{Array{Float64,1},1},1},OrdinaryDiffEq.FunctionMapCache{Array{Int64,1},Array{Int64,1}}}},1}}, ::Array{Float64,1}) at /home/Niklas/.julia/packages/DiffEqMonteCarlo/c9ztK/src/analysis.jl:131
 [13] #MonteCarloSummary#38(::Array{Float64,1}, ::Type, ::MonteCarloSolution{Int64,3,Array{ODESolution{Int64,2,Array{Array{Int64,1},1},Nothing,Nothing,Array{Float64,1},Array{Array{Array{Float64,1},1},1},DiscreteProblem{Array{Int64,1},Tuple{Float64,Float64},true,Array{Float64,1},DiscreteFunction{true,getfield(DiffEqBase, Symbol("##270#271")),Nothing},Nothing},FunctionMap{false},OrdinaryDiffEq.InterpolationData{DiscreteFunction{true,getfield(DiffEqBase, Symbol("##270#271")),Nothing},Array{Array{Int64,1},1},Array{Float64,1},Array{Array{Array{Float64,1},1},1},OrdinaryDiffEq.FunctionMapCache{Array{Int64,1},Array{Int64,1}}}},1}}, ::Array{Float64,1}) at /home/Niklas/.julia/packages/DiffEqMonteCarlo/c9ztK/src/analysis.jl:105
 [14] MonteCarloSummary(::MonteCarloSolution{Int64,3,Array{ODESolution{Int64,2,Array{Array{Int64,1},1},Nothing,Nothing,Array{Float64,1},Array{Array{Array{Float64,1},1},1},DiscreteProblem{Array{Int64,1},Tuple{Float64,Float64},true,Array{Float64,1},DiscreteFunction{true,getfield(DiffEqBase, Symbol("##270#271")),Nothing},Nothing},FunctionMap{false},OrdinaryDiffEq.InterpolationData{DiscreteFunction{true,getfield(DiffEqBase, Symbol("##270#271")),Nothing},Array{Array{Int64,1},1},Array{Float64,1},Array{Array{Array{Float64,1},1},1},OrdinaryDiffEq.FunctionMapCache{Array{Int64,1},Array{Int64,1}}}},1}}, ::Array{Float64,1}) at /home/Niklas/.julia/packages/DiffEqMonteCarlo/c9ztK/src/analysis.jl:104 (repeats 2 times)
 [15] top-level scope at In[7]:13

[ChrisRackauckas]

We need to add float to some of the pre-allocations, since things like mean should always just use the float for completeness.

[ChrisRackauckas-Claude]

Triage: This is fixed. EnsembleSummary (renamed from MonteCarloSummary, now in SciMLBase) works with integer u0 on DiffEqBase v6.211.0 / SciMLBase v2.151.0 / Julia 1.10.11. Recommend closing.