# EnsembleSummary deprecated?

I’m very new to Julia so I might be misinterpreting what’s happening here.

The `EnsembleSummary` function stopped working for me which doesn’t seem to make sense since it is part of SciMLBase so maybe dependencies are messed up somewhere but here’s a MWE from Turing documentation

``````using Turing, DifferentialEquations, Plots

u0 = [1.0,1.0]
tspan = (0.0,10.0)
function multiplicative_noise!(du,u,p,t)
x,y = u
du[1] = p[5]*x
du[2] = p[6]*y
end
p = [1.5,1.0,3.0,1.0,0.1,0.1]

function lotka_volterra!(du,u,p,t)
x,y = u
α,β,γ,δ = p
du[1] = dx = α*x - β*x*y
du[2] = dy = δ*x*y - γ*y
end

prob_sde = SDEProblem(lotka_volterra!,multiplicative_noise!,u0,tspan,p)

ensembleprob = EnsembleProblem(prob_sde)
data = solve(ensembleprob,SOSRI(),saveat=0.1,trajectories=1000)

@model function fitlv(data, prob)
σ ~ InverseGamma(2,3)
α ~ truncated(Normal(1.3,0.5),0.5,2.5)
β ~ truncated(Normal(1.2,0.25),0.5,2)
γ ~ truncated(Normal(3.2,0.25),2.2,4.0)
δ ~ truncated(Normal(1.2,0.25),0.5,2.0)
ϕ1 ~ truncated(Normal(0.12,0.3),0.05,0.25)
ϕ2 ~ truncated(Normal(0.12,0.3),0.05,0.25)
α = 1.5
p = [α,β,γ,δ,ϕ1,ϕ2]
prob = remake(prob, p=p)
predicted = solve(prob,SOSRI(),saveat=0.1)

if predicted.retcode != :Success
Turing.acclogp!(_varinfo, -Inf)
end
for j in 1:length(data)
for i = 1:length(predicted)
data[j][i] ~ MvNormal(predicted[i],σ)
end
end
end;

EnsembleSummary(data)
``````

and this is the error message

``````StackOverflowError:

Stacktrace:
[1] depwarn(::String, ::Symbol; force::Bool) at ./deprecated.jl:79
[2] depwarn(::String, ::Symbol) at ./deprecated.jl:80
[3] EnsembleSummary(::EnsembleSolution{Float64,3,Array{RODESolution{Float64,2,Array{Array{Float64,1},1},Nothing,Nothing,Array{Float64,1},NoiseProcess{Float64,2,Float64,Array{Float64,1},Array{Float64,1},Array{Array{Float64,1},1},typeof(DiffEqNoiseProcess.INPLACE_WHITE_NOISE_DIST),typeof(DiffEqNoiseProcess.INPLACE_WHITE_NOISE_BRIDGE),true,ResettableStacks.ResettableStack{Tuple{Float64,Array{Float64,1},Array{Float64,1}},true},ResettableStacks.ResettableStack{Tuple{Float64,Array{Float64,1},Array{Float64,1}},true},RSWM{Float64},Nothing,RandomNumbers.Xorshifts.Xoroshiro128Plus},SDEProblem{Array{Float64,1},Tuple{Float64,Float64},true,Array{Float64,1},Nothing,SDEFunction{true,typeof(lotka_volterra!),typeof(multiplicative_noise!),LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},typeof(multiplicative_noise!),Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{(),Tuple{}}},Nothing},SOSRI,StochasticDiffEq.LinearInterpolationData{Array{Array{Float64,1},1},Array{Float64,1}},DiffEqBase.DEStats},1}}) at ./deprecated.jl:71
[4] EnsembleSummary(::EnsembleSolution{Float64,3,Array{RODESolution{Float64,2,Array{Array{Float64,1},1},Nothing,Nothing,Array{Float64,1},NoiseProcess{Float64,2,Float64,Array{Float64,1},Array{Float64,1},Array{Array{Float64,1},1},typeof(DiffEqNoiseProcess.INPLACE_WHITE_NOISE_DIST),typeof(DiffEqNoiseProcess.INPLACE_WHITE_NOISE_BRIDGE),true,ResettableStacks.ResettableStack{Tuple{Float64,Array{Float64,1},Array{Float64,1}},true},ResettableStacks.ResettableStack{Tuple{Float64,Array{Float64,1},Array{Float64,1}},true},RSWM{Float64},Nothing,RandomNumbers.Xorshifts.Xoroshiro128Plus},SDEProblem{Array{Float64,1},Tuple{Float64,Float64},true,Array{Float64,1},Nothing,SDEFunction{true,typeof(lotka_volterra!),typeof(multiplicative_noise!),LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},typeof(multiplicative_noise!),Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{(),Tuple{}}},Nothing},SOSRI,StochasticDiffEq.LinearInterpolationData{Array{Array{Float64,1},1},Array{Float64,1}},DiffEqBase.DEStats},1}}) at ./deprecated.jl:72 (repeats 32472 times)
[5] top-level scope at In[5]:1