# The Bayesian SDE in the Turing tutorial issues an error

**URL:** <https://discourse.julialang.org/t/the-bayesian-sde-in-the-turing-tutorial-issues-an-error/73447>\
**Category:** Probabilistic Programming\
**Tags:** diffeq, sde, turing\
**Created:** [December 21, 2021, 5:41pm UTC](https://discourse.julialang.org/t/the-bayesian-sde-in-the-turing-tutorial-issues-an-error/73447 "2021-12-21T17:41:56Z")\
**Posts on this page:** 20\
**Page:** 1

<div class="post-metadata">

**Author:** ![lilianping](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/lilianping/32/32108_2.png) [@lilianping](https://discourse.julialang.org/u/lilianping)\
**Post date:** [December 21, 2021, 5:41pm UTC](https://discourse.julialang.org/t/the-bayesian-sde-in-the-turing-tutorial-issues-an-error/73447/1 "2021-12-21T17:41:56Z")

</div>

When I tried to run the code in the Turing tutorial, the following error occurred when running to beyesianSDE, why is it?

 ![image](https://global.discourse-cdn.com/julialang/original/3X/c/4/c42030753c826ce834980ff5feee96614805d080.png)

---

<div class="post-metadata">

**Author:** ![ChrisRackauckas](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/chrisrackauckas/32/77_2.png) [@ChrisRackauckas](https://discourse.julialang.org/u/ChrisRackauckas)\
**Post date:** [December 21, 2021, 11:36pm UTC](https://discourse.julialang.org/t/the-bayesian-sde-in-the-turing-tutorial-issues-an-error/73447/2 "2021-12-21T23:36:46Z")

</div>

What code did you run?

---

<div class="post-metadata">

**Author:** ![lilianping](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/lilianping/32/32108_2.png) [@lilianping](https://discourse.julialang.org/u/lilianping)\
**Post date:** [December 22, 2021, 7:01am UTC](https://discourse.julialang.org/t/the-bayesian-sde-in-the-turing-tutorial-issues-an-error/73447/3 "2021-12-22T07:01:47Z")

</div>

Turing tutorial ： Bayesian Estimation of Differential Equations，The last part， Inference of a Stochastic Differential Equation，When I run to the following part，the problem I described above appears

 ![image](https://global.discourse-cdn.com/julialang/original/3X/0/3/03370db60d6b5b13518b77da709abeccfdc03a83.png)

---

<div class="post-metadata">

**Author:** ![ptoche](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/ptoche/32/23554_2.png) [@ptoche](https://discourse.julialang.org/u/ptoche)\
**Post date:** [December 22, 2021, 8:10am UTC](https://discourse.julialang.org/t/the-bayesian-sde-in-the-turing-tutorial-issues-an-error/73447/4 "2021-12-22T08:10:42Z")

</div>

What version of Julia are you on?

I’m assuming you mean this tutorial: [Bayesian Estimation of Differential Equations](https://turing.ml/dev/tutorials/10-bayesian-differential-equations/)

I was curious to try it out, but installing `Turing` leads to several seemingly important downgrades. In case this is useful, here is the output of `Pkg.add("Turing")` immediately after `Pkg.add("DifferentialEquations")` on a new environment and `Julia v1.7`.

```julia
   Resolving package versions...
ERROR: LoadError: Unsatisfiable requirements detected for package AdvancedPS [576499cb]:
 AdvancedPS [576499cb] log:
 ├─possible versions are: 0.1.0-0.3.0 or uninstalled
 ├─restricted by compatibility requirements with Libtask [6f1fad26] to versions: 0.1.0-0.2.4 or uninstalled
 │ └─Libtask [6f1fad26] log:
 │ ├─possible versions are: 0.1.1-0.6.1 or uninstalled
 │ ├─restricted by compatibility requirements with Turing [fce5fe82] to versions: 0.1.1-0.5.3
 │ │ └─Turing [fce5fe82] log:
 │ │ ├─possible versions are: 0.5.0-0.19.2 or uninstalled
 │ │ ├─restricted to versions * by an explicit requirement, leaving only versions 0.5.0-0.19.2
 │ │ ├─restricted by compatibility requirements with MCMCChain [1671dc4f] to versions: 0.6.11-0.19.2 or uninstalled, leaving only versions: 0.6.11-0.19.2
 │ │ │ └─MCMCChain [1671dc4f] log:
 │ │ │ ├─possible versions are: 0.1.0-0.2.3 or uninstalled
 │ │ │ └─restricted by julia compatibility requirements to versions: uninstalled
 │ │ ├─restricted by compatibility requirements with Requires [ae029012] to versions: 0.8.0-0.19.2 or uninstalled, leaving only versions: 0.8.0-0.19.2
 │ │ │ └─Requires [ae029012] log:
 │ │ │ ├─possible versions are: 0.5.0-1.2.0 or uninstalled
 │ │ │ ├─restricted by compatibility requirements with Plots [91a5bcdd] to versions: 0.5.0-1.2.0
 │ │ │ │ └─Plots [91a5bcdd] log:
 │ │ │ │ ├─possible versions are: 0.12.1-1.25.3 or uninstalled
 │ │ │ │ ├─restricted to versions * by an explicit requirement, leaving only versions 0.12.1-1.25.3
 │ │ │ │ ├─restricted by compatibility requirements with StatsPlots [f3b207a7] to versions: 0.14.0-1.25.3
 │ │ │ │ │ └─StatsPlots [f3b207a7] log:
 │ │ │ │ │ ├─possible versions are: 0.10.0-0.14.30 or uninstalled
 │ │ │ │ │ ├─restricted to versions * by an explicit requirement, leaving only versions 0.10.0-0.14.30
 │ │ │ │ │ └─restricted by compatibility requirements with Reexport [189a3867] to versions: 0.14.18-0.14.30 or uninstalled, leaving only versions: 0.14.18-0.14.30
 │ │ │ │ │ └─Reexport [189a3867] log:
 │ │ │ │ │ ├─possible versions are: 0.2.0-1.2.2 or uninstalled
 │ │ │ │ │ ├─restricted by compatibility requirements with Plots [91a5bcdd] to versions: 0.2.0-1.2.2
 │ │ │ │ │ │ └─Plots [91a5bcdd] log: see above
 │ │ │ │ │ └─restricted by compatibility requirements with LinearSolve [7ed4a6bd] to versions: 1.0.0-1.2.2
 │ │ │ │ │ └─LinearSolve [7ed4a6bd] log:
 │ │ │ │ │ ├─possible versions are: 0.1.0-1.1.2 or uninstalled
 │ │ │ │ │ └─restricted by compatibility requirements with DifferentialEquations [0c46a032] to versions: 1.0.0-1.1.2
 │ │ │ │ │ └─DifferentialEquations [0c46a032] log:
 │ │ │ │ │ ├─possible versions are: 5.0.0-6.21.0 or uninstalled
 │ │ │ │ │ └─restricted to versions 6.21.0 by an explicit requirement, leaving only versions 6.21.0
 │ │ │ │ ├─restricted by compatibility requirements with StaticArrays [90137ffa] to versions: 0.21.0-1.25.3 or uninstalled, leaving only versions: 0.21.0-1.25.3
 │ │ │ │ │ └─StaticArrays [90137ffa] log:
 │ │ │ │ │ ├─possible versions are: 0.8.0-1.2.13 or uninstalled
 │ │ │ │ │ ├─restricted by compatibility requirements with ModelingToolkit [961ee093] to versions: 0.10.0-1.2.13
 │ │ │ │ │ │ └─ModelingToolkit [961ee093] log:
 │ │ │ │ │ │ ├─possible versions are: 0.0.1-7.1.3 or uninstalled
 │ │ │ │ │ │ ├─restricted by compatibility requirements with ParameterizedFunctions [65888b18] to versions: 1.3.0-7.1.3
 │ │ │ │ │ │ │ └─ParameterizedFunctions [65888b18] log:
 │ │ │ │ │ │ │ ├─possible versions are: 3.2.0-5.12.2 or uninstalled
 │ │ │ │ │ │ │ ├─restricted by compatibility requirements with DifferentialEquations [0c46a032] to versions: 5.0.0-5.12.2
 │ │ │ │ │ │ │ │ └─DifferentialEquations [0c46a032] log: see above
 │ │ │ │ │ │ │ ├─restricted by compatibility requirements with Reexport [189a3867] to versions: [3.2.0-5.3.0, 5.8.0-5.12.2] or uninstalled, leaving only versions: [5.0.0-5.3.0, 5.8.0-5.12.2]
 │ │ │ │ │ │ │ │ └─Reexport [189a3867] log: see above
 │ │ │ │ │ │ │ └─restricted by compatibility requirements with ModelingToolkit [961ee093] to versions: [3.2.0-4.2.1, 5.8.0-5.12.2] or uninstalled, leaving only versions: 5.8.0-5.12.2
 │ │ │ │ │ │ │ └─ModelingToolkit [961ee093] log: see above
 │ │ │ │ │ │ ├─restricted by compatibility requirements with DiffEqJump [c894b116] to versions: [0.0.1-3.1.1, 5.26.0-7.1.3] or uninstalled, leaving only versions: [1.3.0-3.1.1, 5.26.0-7.1.3]
 │ │ │ │ │ │ │ └─DiffEqJump [c894b116] log:
 │ │ │ │ │ │ │ ├─possible versions are: 5.0.0-8.0.0 or uninstalled
 │ │ │ │ │ │ │ └─restricted by compatibility requirements with DifferentialEquations [0c46a032] to versions: 7.0.0-8.0.0
 │ │ │ │ │ │ │ └─DifferentialEquations [0c46a032] log: see above
 │ │ │ │ │ │ ├─restricted by compatibility requirements with UnPack [3a884ed6] to versions: [0.0.1-2.0.0, 3.2.0-7.1.3] or uninstalled, leaving only versions: [1.3.0-2.0.0, 5.26.0-7.1.3]
 │ │ │ │ │ │ │ └─UnPack [3a884ed6] log:
 │ │ │ │ │ │ │ ├─possible versions are: 0.1.0-1.0.2 or uninstalled
 │ │ │ │ │ │ │ └─restricted by compatibility requirements with DiffEqJump [c894b116] to versions: 1.0.2
 │ │ │ │ │ │ │ └─DiffEqJump [c894b116] log: see above
 │ │ │ │ │ │ └─restricted by compatibility requirements with StaticArrays [90137ffa] to versions: 4.0.7-7.1.3 or uninstalled, leaving only versions: 5.26.0-7.1.3
 │ │ │ │ │ │ └─StaticArrays [90137ffa] log: see above
 │ │ │ │ │ ├─restricted by compatibility requirements with StochasticDiffEq [789caeaf] to versions: 0.11.0-1.2.13
 │ │ │ │ │ │ └─StochasticDiffEq [789caeaf] log:
 │ │ │ │ │ │ ├─possible versions are: 5.0.0-6.43.0 or uninstalled
 │ │ │ │ │ │ ├─restricted by compatibility requirements with DifferentialEquations [0c46a032] to versions: 6.37.0-6.43.0
 │ │ │ │ │ │ │ └─DifferentialEquations [0c46a032] log: see above
 │ │ │ │ │ │ └─restricted by compatibility requirements with OrdinaryDiffEq [1dea7af3] to versions: [5.0.0-6.20.0, 6.43.0] or uninstalled, leaving only versions: 6.43.0
 │ │ │ │ │ │ └─OrdinaryDiffEq [1dea7af3] log:
 │ │ │ │ │ │ ├─possible versions are: 4.0.0-6.0.3 or uninstalled
 │ │ │ │ │ │ └─restricted by compatibility requirements with DifferentialEquations [0c46a032] to versions: 6.0.0-6.0.3
 │ │ │ │ │ │ └─DifferentialEquations [0c46a032] log: see above
 │ │ │ │ │ └─restricted by compatibility requirements with DEDataArrays [754358af] to versions: 1.0.0-1.2.13
 │ │ │ │ │ └─DEDataArrays [754358af] log:
 │ │ │ │ │ ├─possible versions are: 0.1.0-0.2.0 or uninstalled
 │ │ │ │ │ └─restricted by compatibility requirements with DiffEqBase [2b5f629d] to versions: 0.2.0
 │ │ │ │ │ └─DiffEqBase [2b5f629d] log:
 │ │ │ │ │ ├─possible versions are: 3.13.2-6.78.0 or uninstalled
 │ │ │ │ │ ├─restricted by compatibility requirements with DifferentialEquations [0c46a032] to versions: 6.72.0-6.78.0
 │ │ │ │ │ │ └─DifferentialEquations [0c46a032] log: see above
 │ │ │ │ │ ├─restricted by compatibility requirements with OrdinaryDiffEq [1dea7af3] to versions: 6.75.0-6.78.0
 │ │ │ │ │ │ └─OrdinaryDiffEq [1dea7af3] log: see above
 │ │ │ │ │ └─restricted by compatibility requirements with PreallocationTools [d236fae5] to versions: [3.13.2-6.70.0, 6.76.0-6.78.0] or uninstalled, leaving only versions: 6.76.0-6.78.0
 │ │ │ │ │ └─PreallocationTools [d236fae5] log:
 │ │ │ │ │ ├─possible versions are: 0.1.0-0.2.1 or uninstalled
 │ │ │ │ │ └─restricted by compatibility requirements with OrdinaryDiffEq [1dea7af3] to versions: 0.2.0-0.2.1
 │ │ │ │ │ └─OrdinaryDiffEq [1dea7af3] log: see above
 │ │ │ │ ├─restricted by compatibility requirements with Requires [ae029012] to versions: 0.28.4-1.25.3 or uninstalled, leaving only versions: 0.28.4-1.25.3
 │ │ │ │ │ └─Requires [ae029012] log: see above
 │ │ │ │ └─restricted by compatibility requirements with Reexport [189a3867] to versions: 1.10.1-1.25.3 or uninstalled, leaving only versions: 1.10.1-1.25.3
 │ │ │ │ └─Reexport [189a3867] log: see above
 │ │ │ └─restricted by compatibility requirements with LinearSolve [7ed4a6bd] to versions: 1.0.0-1.2.0
 │ │ │ └─LinearSolve [7ed4a6bd] log: see above
 │ │ └─restricted by compatibility requirements with Reexport [189a3867] to versions: 0.15.11-0.19.2 or uninstalled, leaving only versions: 0.15.11-0.19.2
 │ │ └─Reexport [189a3867] log: see above
 │ ├─restricted by compatibility requirements with Libtask_jll [3ae2931a] to versions: [0.1.1-0.4.2, 0.6.0-0.6.1] or uninstalled, leaving only versions: 0.1.1-0.4.2
 │ │ └─Libtask_jll [3ae2931a] log:
 │ │ ├─possible versions are: 0.3.0-0.5.1 or uninstalled
 │ │ └─restricted by julia compatibility requirements to versions: [0.3.0-0.3.2, 0.5.0-0.5.1] or uninstalled
 │ ├─restricted by compatibility requirements with Turing [fce5fe82] to versions: 0.3.1-0.5.3, leaving only versions: 0.3.1-0.4.2
 │ │ └─Turing [fce5fe82] log: see above
 │ └─restricted by compatibility requirements with Turing [fce5fe82] to versions: 0.4.0-0.5.3, leaving only versions: 0.4.0-0.4.2
 │ └─Turing [fce5fe82] log: see above
 ├─restricted by compatibility requirements with Libtask [6f1fad26] to versions: uninstalled
 │ └─Libtask [6f1fad26] log: see above
 └─restricted by compatibility requirements with Turing [fce5fe82] to versions: 0.1.0-0.2.4 — no versions left
   └─Turing [fce5fe82] log: see above
Stacktrace:
  [1] propagate_constraints!(graph::Pkg.Resolve.Graph, sources::Set{Int64}; log_events::Bool)
    @ Pkg.Resolve /Applications/Julia-1.7.app/Contents/Resources/julia/share/julia/stdlib/v1.7/Pkg/src/Resolve/graphtype.jl:1063
  [2] propagate_constraints! (repeats 2 times)
    @ /Applications/Julia-1.7.app/Contents/Resources/julia/share/julia/stdlib/v1.7/Pkg/src/Resolve/graphtype.jl:1000 [inlined]
  [3] simplify_graph!(graph::Pkg.Resolve.Graph, sources::Set{Int64}; clean_graph::Bool)
    @ Pkg.Resolve /Applications/Julia-1.7.app/Contents/Resources/julia/share/julia/stdlib/v1.7/Pkg/src/Resolve/graphtype.jl:1519
  [4] simplify_graph! (repeats 2 times)
    @ /Applications/Julia-1.7.app/Contents/Resources/julia/share/julia/stdlib/v1.7/Pkg/src/Resolve/graphtype.jl:1519 [inlined]
  [5] resolve_versions!(env::Pkg.Types.EnvCache, registries::Vector{Pkg.Registry.RegistryInstance}, pkgs::Vector{Pkg.Types.PackageSpec}, julia_version::VersionNumber)
    @ Pkg.Operations /Applications/Julia-1.7.app/Contents/Resources/julia/share/julia/stdlib/v1.7/Pkg/src/Operations.jl:335
  [6] targeted_resolve(env::Pkg.Types.EnvCache, registries::Vector{Pkg.Registry.RegistryInstance}, pkgs::Vector{Pkg.Types.PackageSpec}, preserve::Pkg.Types.PreserveLevel, julia_version::VersionNumber)
    @ Pkg.Operations /Applications/Julia-1.7.app/Contents/Resources/julia/share/julia/stdlib/v1.7/Pkg/src/Operations.jl:1154
  [7] tiered_resolve(env::Pkg.Types.EnvCache, registries::Vector{Pkg.Registry.RegistryInstance}, pkgs::Vector{Pkg.Types.PackageSpec}, julia_version::VersionNumber)
    @ Pkg.Operations /Applications/Julia-1.7.app/Contents/Resources/julia/share/julia/stdlib/v1.7/Pkg/src/Operations.jl:1139
  [8] _resolve(io::Base.TTY, env::Pkg.Types.EnvCache, registries::Vector{Pkg.Registry.RegistryInstance}, pkgs::Vector{Pkg.Types.PackageSpec}, preserve::Pkg.Types.PreserveLevel, julia_version::VersionNumber)
    @ Pkg.Operations /Applications/Julia-1.7.app/Contents/Resources/julia/share/julia/stdlib/v1.7/Pkg/src/Operations.jl:1160
  [9] add(ctx::Pkg.Types.Context, pkgs::Vector{Pkg.Types.PackageSpec}, new_git::Set{Base.UUID}; preserve::Pkg.Types.PreserveLevel, platform::Base.BinaryPlatforms.Platform)
   Installed DelayDiffEq ──────────────── v5.31.0
   Installed Setfield ─────────────────── v0.7.1
   Installed ChainRulesCore ───────────── v0.9.45
   Installed ArrayInterface ───────────── v2.14.17
   Installed Reexport ─────────────────── v0.2.0
   Installed RangeArrays ──────────────── v0.3.2
   Installed TerminalLoggers ──────────── v0.1.5
   Installed LogExpFunctions ──────────── v0.3.0
   Installed ExponentialUtilities ─────── v1.8.2
   Installed ScientificTypesBase ──────── v2.3.0
   Installed AdvancedHMC ──────────────── v0.2.27
   Installed MLJModelInterface ────────── v1.3.3
   Installed VectorizationBase ────────── v0.16.2
   Installed Hwloc ────────────────────── v1.3.0
   Installed PrettyTables ─────────────── v1.3.1
   Installed LightGraphs ──────────────── v1.3.5
   Installed FillArrays ───────────────── v0.11.9
   Installed Interpolations ───────────── v0.13.2
   Installed RecursiveFactorization ───── v0.1.13
   Installed FastBroadcast ────────────── v0.1.8
   Installed LogDensityProblems ───────── v0.10.6
   Installed Distributions ────────────── v0.24.18
   Installed SymbolicUtils ────────────── v0.13.2
   Installed LoopVectorization ────────── v0.10.0
    Updating `~/Julia/workspace/odes/Project.toml`
  [0c46a032] ↓ DifferentialEquations v6.21.0 ⇒ v6.18.0
  [31c24e10] ↓ Distributions v0.25.37 ⇒ v0.24.18
  [fce5fe82] + Turing v0.15.1
    Updating `~/Julia/workspace/odes/Manifest.toml`
  [621f4979] + AbstractFFTs v1.0.1
  [80f14c24] + AbstractMCMC v2.5.0
  [7a57a42e] + AbstractPPL v0.1.4
  [0bf59076] + AdvancedHMC v0.2.27
  [5b7e9947] + AdvancedMH v0.5.9
  [b5ca4192] + AdvancedVI v0.1.3
  [ec485272] ↓ ArnoldiMethod v0.2.0 ⇒ v0.1.0
  [4fba245c] ↓ ArrayInterface v3.2.1 ⇒ v2.14.17
  [4c555306] ↓ ArrayLayouts v0.7.8 ⇒ v0.7.5
  [15f4f7f2] - AutoHashEquals v0.2.0
  [13072b0f] + AxisAlgorithms v1.0.1
  [39de3d68] + AxisArrays v0.4.4
  [6e4b80f9] + BenchmarkTools v0.7.0
  [e2ed5e7c] - Bijections v0.1.3
  [76274a88] + Bijectors v0.8.16
  [b99e7846] + BinaryProvider v0.5.10
  [62783981] - BitTwiddlingConvenienceFunctions v0.1.1
  [2a0fbf3d] - CPUSummary v0.1.6
  [082447d4] + ChainRules v0.7.70
  [d360d2e6] ↓ ChainRulesCore v1.11.2 ⇒ v0.9.45
  [9e997f8a] - ChangesOfVariables v0.1.2
  [fb6a15b2] - CloseOpenIntervals v0.1.4
  [88cd18e8] + ConsoleProgressMonitor v0.1.2
  [754358af] - DEDataArrays v0.2.0
  [bcd4f6db] ↓ DelayDiffEq v5.32.3 ⇒ v5.31.0
  [b429d917] - DensityInterface v0.4.0
  [2b5f629d] ↓ DiffEqBase v6.78.0 ⇒ v6.69.1
  [459566f4] ↓ DiffEqCallbacks v2.19.0 ⇒ v2.17.0
  [c894b116] ↓ DiffEqJump v8.0.0 ⇒ v7.3.1
  [b552c78f] ↓ DiffRules v1.9.0 ⇒ v1.5.0
  [0c46a032] ↓ DifferentialEquations v6.21.0 ⇒ v6.18.0
  [31c24e10] ↓ Distributions v0.25.37 ⇒ v0.24.18
  [ced4e74d] + DistributionsAD v0.6.29
  [366bfd00] + DynamicPPL v0.10.20
  [7c1d4256] ↓ DynamicPolynomials v0.4.1 ⇒ v0.3.3
  [da5c29d0] ↓ EllipsisNotation v1.1.3 ⇒ v1.0.0
  [cad2338a] + EllipticalSliceSampling v0.3.1
  [d4d017d3] ↓ ExponentialUtilities v1.10.2 ⇒ v1.8.2
  [7a1cc6ca] + FFTW v1.4.5
  [7034ab61] ↓ FastBroadcast v0.1.11 ⇒ v0.1.8
  [1a297f60] ↓ FillArrays v0.12.7 ⇒ v0.11.9
  [d9f16b24] + Functors v0.1.0
  [3e5b6fbb] - HostCPUFeatures v0.1.5
  [0e44f5e4] ↓ Hwloc v2.0.0 ⇒ v1.3.0
  [505f98c9] + InplaceOps v0.3.0
  [a98d9a8b] + Interpolations v0.13.2
  [3587e190] - InverseFunctions v0.1.2
  [41ab1584] + InvertedIndices v1.1.0
  [c8e1da08] + IterTools v1.4.0
  [98e50ef6] ↓ JuliaFormatter v0.19.2 ⇒ v0.15.11
  [ef3ab10e] - KLU v0.2.3
  [5ab0869b] + KernelDensity v0.6.3
  [ba0b0d4f] - Krylov v0.7.9
  [0b1a1467] - KrylovKit v0.5.3
  [2ee39098] ↓ LabelledArrays v1.6.7 ⇒ v1.6.6
  [10f19ff3] - LayoutPointers v0.1.4
  [1d6d02ad] + LeftChildRightSiblingTrees v0.1.3
  [6f1fad26] + Libtask v0.4.2
  [093fc24a] + LightGraphs v1.3.5
  [7ed4a6bd] - LinearSolve v1.1.2
  [6fdf6af0] + LogDensityProblems v0.10.6
  [2ab3a3ac] ↓ LogExpFunctions v0.3.6 ⇒ v0.3.0
  [e6f89c97] + LoggingExtras v0.4.7
  [bdcacae8] ↓ LoopVectorization v0.12.99 ⇒ v0.10.0
  [c7f686f2] + MCMCChains v4.14.1
  [e80e1ace] + MLJModelInterface v1.3.3
  [d125e4d3] - ManualMemory v0.1.6
  [dbb5928d] + MappedArrays v0.4.1
  [e9d8d322] - Metatheory v1.3.2
  [961ee093] ↓ ModelingToolkit v7.1.3 ⇒ v6.4.7
  [102ac46a] ↓ MultivariatePolynomials v0.4.2 ⇒ v0.3.2
  [d8a4904e] - MutableArithmetics v0.3.1
  [872c559c] + NNlib v0.7.31
  [86f7a689] + NamedArrays v0.9.6
  [c020b1a1] + NaturalSort v1.0.0
  [1dea7af3] ↓ OrdinaryDiffEq v6.0.3 ⇒ v5.55.1
  [65888b18] ↓ ParameterizedFunctions v5.12.2 ⇒ v5.12.1
  [f517fe37] - Polyester v0.5.4
  [1d0040c9] - PolyesterWeave v0.1.2
  [d236fae5] - PreallocationTools v0.2.1
  [08abe8d2] + PrettyTables v1.3.1
  [33c8b6b6] + ProgressLogging v0.1.4
  [92933f4c] + ProgressMeter v1.7.1
  [b3c3ace0] + RangeArrays v0.3.2
  [c84ed2f1] + Ratios v0.4.2
  [731186ca] ↓ RecursiveArrayTools v2.20.0 ⇒ v2.11.4
  [f2c3362d] ↓ RecursiveFactorization v0.2.5 ⇒ v0.1.13
  [189a3867] ↓ Reexport v1.2.2 ⇒ v0.2.0
  [42d2dcc6] - Referenceables v0.1.2
  [3cdde19b] - SIMDDualNumbers v0.1.0
  [94e857df] - SIMDTypes v0.1.0
  [476501e8] ↓ SLEEFPirates v0.6.28 ⇒ v0.6.8
  [0bca4576] ↓ SciMLBase v1.23.1 ⇒ v1.13.6
  [30f210dd] + ScientificTypesBase v2.3.0
  [276daf66] ↓ SpecialFunctions v1.8.1 ⇒ v0.10.3
  [aedffcd0] - Static v0.4.1
  [64bff920] + StatisticalTraits v2.1.0
  [4c63d2b9] ↓ StatsFuns v0.9.14 ⇒ v0.9.7
  [789caeaf] ↓ StochasticDiffEq v6.43.0 ⇒ v6.40.0
  [7792a7ef] - StrideArraysCore v0.2.9
  [d1185830] ↓ SymbolicUtils v0.18.2 ⇒ v0.13.2
  [0c5d862f] ↓ Symbolics v4.2.0 ⇒ v3.2.3
  [8ea1fca8] - TermInterface v0.2.3
  [5d786b92] + TerminalLoggers v0.1.5
  [8290d209] ↓ ThreadingUtilities v0.4.6 ⇒ v0.2.3
  [ac1d9e8a] - ThreadsX v0.1.8
  [9f7883ad] + Tracker v0.2.16
  [84d833dd] + TransformVariables v0.4.1
  [d5829a12] - TriangularSolve v0.1.8
  [fce5fe82] + Turing v0.15.1
  [3d5dd08c] ↓ VectorizationBase v0.21.23 ⇒ v0.16.2
  [efce3f68] + WoodburyMatrices v0.5.5
  [f5851436] + FFTW_jll v3.3.10+0
  [1d5cc7b8] + IntelOpenMP_jll v2018.0.3+2
  [856f044c] + MKL_jll v2021.1.1+2
  [4af54fe1] + LazyArtifacts
  [05823500] - OpenLibm_jll
    Building Libtask → `~/.julia/scratchspaces/44cfe95a-1eb2-52ea-b672-e2afdf69b78f/83e082fccb4e37d93df6440cdbd41dcbe5e46cb6/build.log`
Precompiling project...
  100 dependencies successfully precompiled in 149 seconds (94 already precompiled)

```

And problems with `MCMCChain` too.

```julia
julia> Pkg.add("MCMCChain")
   Resolving package versions...
ERROR: Unsatisfiable requirements detected for package MCMCChain [1671dc4f]:
 MCMCChain [1671dc4f] log:
 ├─possible versions are: 0.1.0-0.2.3 or uninstalled
 ├─restricted to versions * by an explicit requirement, leaving only versions 0.1.0-0.2.3
 └─restricted by julia compatibility requirements to versions: uninstalled — no versions left
Stacktrace:
  [1] propagate_constraints!(graph::Pkg.Resolve.Graph, sources::Set{Int64}; log_events::Bool)
    @ Pkg.Resolve /Applications/Julia-1.7.app/Contents/Resources/julia/share/julia/stdlib/v1.7/Pkg/src/Resolve/graphtype.jl:1063
  [2] propagate_constraints! (repeats 2 times)
    @ /Applications/Julia-1.7.app/Contents/Resources/julia/share/julia/stdlib/v1.7/Pkg/src/Resolve/graphtype.jl:1000 [inlined]
  [3] simplify_graph!(graph::Pkg.Resolve.Graph, sources::Set{Int64}; clean_graph::Bool)
    @ Pkg.Resolve /Applications/Julia-1.7.app/Contents/Resources/julia/share/julia/stdlib/v1.7/Pkg/src/Resolve/graphtype.jl:1519
  [4] simplify_graph! (repeats 2 times)
    @ /Applications/Julia-1.7.app/Contents/Resources/julia/share/julia/stdlib/v1.7/Pkg/src/Resolve/graphtype.jl:1519 [inlined]
  [5] resolve_versions!(env::Pkg.Types.EnvCache, registries::Vector{Pkg.Registry.RegistryInstance}, pkgs::Vector{Pkg.Types.PackageSpec}, julia_version::VersionNumber)
    @ Pkg.Operations /Applications/Julia-1.7.app/Contents/Resources/julia/share/julia/stdlib/v1.7/Pkg/src/Operations.jl:335
  [6] targeted_resolve(env::Pkg.Types.EnvCache, registries::Vector{Pkg.Registry.RegistryInstance}, pkgs::Vector{Pkg.Types.PackageSpec}, preserve::Pkg.Types.PreserveLevel, julia_version::VersionNumber)
    @ Pkg.Operations /Applications/Julia-1.7.app/Contents/Resources/julia/share/julia/stdlib/v1.7/Pkg/src/Operations.jl:1154
  [7] tiered_resolve(env::Pkg.Types.EnvCache, registries::Vector{Pkg.Registry.RegistryInstance}, pkgs::Vector{Pkg.Types.PackageSpec}, julia_version::VersionNumber)
    @ Pkg.Operations /Applications/Julia-1.7.app/Contents/Resources/julia/share/julia/stdlib/v1.7/Pkg/src/Operations.jl:1139
  [8] _resolve(io::Base.TTY, env::Pkg.Types.EnvCache, registries::Vector{Pkg.Registry.RegistryInstance}, pkgs::Vector{Pkg.Types.PackageSpec}, preserve::Pkg.Types.PreserveLevel, julia_version::VersionNumber)
    @ Pkg.Operations /Applications/Julia-1.7.app/Contents/Resources/julia/share/julia/stdlib/v1.7/Pkg/src/Operations.jl:1160
  [9] add(ctx::Pkg.Types.Context, pkgs::Vector{Pkg.Types.PackageSpec}, new_git::Set{Base.UUID}; preserve::Pkg.Types.PreserveLevel, platform::Base.BinaryPlatforms.Platform)
    @ Pkg.Operations /Applications/Julia-1.7.app/Contents/Resources/julia/share/julia/stdlib/v1.7/Pkg/src/Operations.jl:1176
 [10] add(ctx::Pkg.Types.Context, pkgs::Vector{Pkg.Types.PackageSpec}; preserve::Pkg.Types.PreserveLevel, platform::Base.BinaryPlatforms.Platform, kwargs::Base.Pairs{Symbol, Base.TTY, Tuple{Symbol}, NamedTuple{(:io,), Tuple{Base.TTY}}})
    @ Pkg.API /Applications/Julia-1.7.app/Contents/Resources/julia/share/julia/stdlib/v1.7/Pkg/src/API.jl:268
 [11] add(pkgs::Vector{Pkg.Types.PackageSpec}; io::Base.TTY, kwargs::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
    @ Pkg.API /Applications/Julia-1.7.app/Contents/Resources/julia/share/julia/stdlib/v1.7/Pkg/src/API.jl:149
 [12] add(pkgs::Vector{Pkg.Types.PackageSpec})
    @ Pkg.API /Applications/Julia-1.7.app/Contents/Resources/julia/share/julia/stdlib/v1.7/Pkg/src/API.jl:144
 [13] #add#27
    @ /Applications/Julia-1.7.app/Contents/Resources/julia/share/julia/stdlib/v1.7/Pkg/src/API.jl:142 [inlined]
 [14] add
    @ /Applications/Julia-1.7.app/Contents/Resources/julia/share/julia/stdlib/v1.7/Pkg/src/API.jl:142 [inlined]
 [15] #add#26
    @ /Applications/Julia-1.7.app/Contents/Resources/julia/share/julia/stdlib/v1.7/Pkg/src/API.jl:141 [inlined]
 [16] add(pkg::String)
    @ Pkg.API /Applications/Julia-1.7.app/Contents/Resources/julia/share/julia/stdlib/v1.7/Pkg/src/API.jl:141
 [17] top-level scope
    @ REPL[7]:1

```

---

<div class="post-metadata">

**Author:** ![lilianping](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/lilianping/32/32108_2.png) [@lilianping](https://discourse.julialang.org/u/lilianping)\
**Post date:** [December 22, 2021, 8:25am UTC](https://discourse.julialang.org/t/the-bayesian-sde-in-the-turing-tutorial-issues-an-error/73447/5 "2021-12-22T08:25:53Z")

</div>

The version I use is as follows：

 ![image](https://global.discourse-cdn.com/julialang/original/3X/7/9/792c41db76db30dac981736223bb08b8408503ce.png)  
Is it a problem with the 1.6 version?

---

<div class="post-metadata">

**Author:** ![ptoche](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/ptoche/32/23554_2.png) [@ptoche](https://discourse.julialang.org/u/ptoche)\
**Post date:** [December 22, 2021, 8:31am UTC](https://discourse.julialang.org/t/the-bayesian-sde-in-the-turing-tutorial-issues-an-error/73447/6 "2021-12-22T08:31:53Z")

</div>

I don’t know. but if you want Chris to be able to help you, you should gather as much information as possible, e.g. OS and versions of the packages you are running. **So far I’m able to run the tutorial, except the parts involving `MCMCChains`, which I cannot even install.** For convenience, I have copied the code (next time, instead of screenshots, copy-paste the code to make it easier for others). **Which part of the following code doesn’t run for you?**

```julia
dir = expanduser("~/Julia/workspace/odes")
push!(LOAD_PATH, dir)
import Pkg
Pkg.activate(dir)
Base.active_project()

# using Pkg; Pkg.add(["DifferentialEquations", "Turing", "Plots", "StatsPlots"])
# Pkg.add(["Zygote", "DiffEqSensitivity"])

"""
# https://github.com/TuringLang/TuringTutorials.

To locally run this tutorial, do the following commands:

using TuringTutorials
TuringTutorials.weave_file("10-bayesian-differential-equations", "10_bayesian-differential-equations.jmd")
"""

using Distributions
using DifferentialEquations
using Turing
# using MCMCChains
using Plots, StatsPlots

# Set a seed for reproducibility.
using Random
Random.seed!(14);

function lotka_volterra(du,u,p,t)
  x, y = u
  α, β, γ, δ = p
  du[1] = (α - β*y)x # dx =
  du[2] = (δ*x - γ)y # dy =
end
p = [1.5, 1.0, 3.0, 1.0]
u0 = [1.0,1.0]
prob1 = ODEProblem(lotka_volterra,u0,(0.0,10.0),p)
sol = solve(prob1,Tsit5())
plot(sol)

sol1 = solve(prob1,Tsit5(),saveat=0.1)
odedata = Array(sol1) + 0.8 * randn(size(Array(sol1)))
plot(sol1, alpha = 0.3, legend = false); scatter!(sol1.t, odedata')

# Direct Handling of Bayesian Estimation with Turing
# Turing and DifferentialEquations are completely composable and we can write of the differential equation inside a Turing @model 

Turing.setadbackend(:forwarddiff)

@model function fitlv(data, prob1)
    σ ~ InverseGamma(2, 3) # ~ is the tilde character
    α ~ truncated(Normal(1.5,0.5),0.5,2.5)
    β ~ truncated(Normal(1.2,0.5),0,2)
    γ ~ truncated(Normal(3.0,0.5),1,4)
    δ ~ truncated(Normal(1.0,0.5),0,2)

    p = [α,β,γ,δ]
    prob = remake(prob1, p=p)
    predicted = solve(prob,Tsit5(),saveat=0.1)

    for i = 1:length(predicted)
        data[:,i] ~ MvNormal(predicted[i], σ)
    end
end

model = fitlv(odedata, prob1)

# This next command runs 3 independent chains without using multithreading.
chain = mapreduce(c -> sample(model, NUTS(.65),1000), chainscat, 1:3)

plot(chain)

# Data retrodiction
# Retrodiction: generate simulated data using samples from the posterior distribution, and compare to the original data.

pl = scatter(sol1.t, odedata');

chain_array = Array(chain)
for k in 1:300
    resol = solve(remake(prob1,p=chain_array[rand(1:1500), 1:4]),Tsit5(),saveat=0.1)
    plot!(resol, alpha=0.1, color = "#BBBBBB", legend = false)
end
# display(pl)
plot!(sol1, w=1, legend = false)

# Lokta Volterra with missing predator data

@model function fitlv2(data, prob1) # data should be a Vector
    σ ~ InverseGamma(2, 3) # ~ is the tilde character
    α ~ truncated(Normal(1.5,0.5),0.5,2.5)
    β ~ truncated(Normal(1.2,0.5),0,2)
    γ ~ truncated(Normal(3.0,0.5),1,4)
    δ ~ truncated(Normal(1.0,0.5),0,2)

    p = [α,β,γ,δ]
    prob = remake(prob1, p=p)
    predicted = solve(prob,Tsit5(),saveat=0.1)

    for i = 1:length(predicted)
        data[i] ~ Normal(predicted[i][2], σ) # predicted[i][2] is the data for y - a scalar, so we use Normal instead of MvNormal
    end
end

model2 = fitlv2(odedata[2,:], prob1)

# multithreading to sample 3 independent chains
Threads.nthreads()

# This next command runs 3 independent chains with multithreading.
chain2 = sample(model2, NUTS(.45), MCMCThreads(), 5000, 3, progress=false)

pl = scatter(sol1.t, odedata');
chain_array2 = Array(chain2)
for k in 1:300
    resol = solve(remake(prob1,p=chain_array2[rand(1:12000), 1:4]),Tsit5(),saveat=0.1)
    # Note that due to a bug in AxisArray, the variables from the chain will be returned always in
    # the order it is stored in the array, not by the specified order in the call - :α, :β, :γ, :δ
    plot!(resol, alpha=0.1, color = "#BBBBBB", legend = false)
end
#display(pl)
plot!(sol1, w=1, legend = false)

# Inference of Delay Differential Equations

function delay_lotka_volterra(du, u, h, p, t)
   x, y = u
   α, β, γ, δ = p
   du[1] = α * h(p, t-1; idxs=1) - β * x * y
   du[2] = -γ * y + δ * x * y
   return
end

p = (1.5,1.0,3.0,1.0)
u0 = [1.0; 1.0]
tspan = (0.0,10.0)
h(p, t; idxs::Int) = 1.0
prob1 = DDEProblem(delay_lotka_volterra,u0,h,tspan,p)
sol = solve(prob1,saveat=0.1)
ddedata = Array(sol)
ddedata = ddedata + 0.5 * randn(size(ddedata))

scatter(sol.t, ddedata'); plot!(sol)

# Now we define and run the Turing model.

Turing.setadbackend(:forwarddiff)
@model function fitlv(data, prob1)

    σ ~ InverseGamma(2, 3)
    α ~ Truncated(Normal(1.5,0.5),0.5,2.5)
    β ~ Truncated(Normal(1.2,0.5),0,2)
    γ ~ Truncated(Normal(3.0,0.5),1,4)
    δ ~ Truncated(Normal(1.0,0.5),0,2)

    p = [α,β,γ,δ]

    #prob = DDEProblem(delay_lotka_volterra,u0,_h,tspan,p)
    prob = remake(prob1, p=p)
    predicted = solve(prob,saveat=0.1)
    for i = 1:length(predicted)
        data[:,i] ~ MvNormal(predicted[i], σ)
    end
end;
model = fitlv(ddedata, prob1)

# Draw samples using multithreading
chain = sample(model, NUTS(.65), MCMCThreads(), 300, 3, progress=true)
plot(chain)

pl = scatter(sol.t, ddedata')
chain_array = Array(chain)
for k in 1:100
    resol = solve(remake(prob1,p=chain_array[rand(1:450),1:4]),Tsit5(),saveat=0.1)
    # Note that due to a bug in AxisArray, the variables from the chain will be returned always in
    # the order it is stored in the array, not by the specified order in the call - :α, :β, :γ, :δ

    plot!(resol, alpha=0.1, color = "#BBBBBB", legend = false)
end
#display(pl)
plot!(sol)

using Zygote, DiffEqSensitivity
Turing.setadbackend(:zygote)
prob1 = ODEProblem(lotka_volterra,u0,(0.0,10.0),p)

@model function fitlv(data, prob)
    σ ~ InverseGamma(2, 3)
    α ~ truncated(Normal(1.5,0.5),0.5,2.5)
    β ~ truncated(Normal(1.2,0.5),0,2)
    γ ~ truncated(Normal(3.0,0.5),1,4)
    δ ~ truncated(Normal(1.0,0.5),0,2)
    p = [α,β,γ,δ]
    prob = remake(prob, p=p)

    predicted = solve(prob,saveat=0.1)
    for i = 1:length(predicted)
        data[:,i] ~ MvNormal(predicted[i], σ)
    end
end;
model = fitlv(odedata, prob1)
chain = sample(model, NUTS(.65),1000)

@model function fitlv(data, prob)
    σ ~ InverseGamma(2, 3)
    α ~ truncated(Normal(1.5,0.5),0.5,2.5)
    β ~ truncated(Normal(1.2,0.5),0,2)
    γ ~ truncated(Normal(3.0,0.5),1,4)
    δ ~ truncated(Normal(1.0,0.5),0,2)
    p = [α,β,γ,δ]
    prob = remake(prob, p=p)
    predicted = solve(prob,saveat=0.1,sensealg=InterpolatingAdjoint(autojacvec=ReverseDiffVJP(true)))
    for i = 1:length(predicted)
        data[:,i] ~ MvNormal(predicted[i], σ)
    end
end;
model = fitlv(odedata, prob1)
@time chain = sample(model, NUTS(.65),1000)

# Inference of a Stochastic Differential Equation

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)
@time data = solve(ensembleprob,SOSRI(),saveat=0.1,trajectories=1000)
plot(EnsembleSummary(data))

Turing.setadbackend(:forwarddiff)
@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)
    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;

model = fitlv(data, prob_sde)
chain = sample(model, NUTS(0.25), 5000, init_theta = [1.5,1.3,1.2,2.7,1.2,0.12,0.12])
plot(chain)

```

---

<div class="post-metadata">

**Author:** ![nilshg](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/nilshg/32/2283_2.png) [@nilshg](https://discourse.julialang.org/u/nilshg)\
**Post date:** [December 22, 2021, 8:56am UTC](https://discourse.julialang.org/t/the-bayesian-sde-in-the-turing-tutorial-issues-an-error/73447/7 "2021-12-22T08:56:38Z")

</div>

Turing is not compatible with Julia 1.7, you need to use 1.6.5

---

<div class="post-metadata">

**Author:** ![ChrisRackauckas](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/chrisrackauckas/32/77_2.png) [@ChrisRackauckas](https://discourse.julialang.org/u/ChrisRackauckas)\
**Post date:** [December 22, 2021, 9:57am UTC](https://discourse.julialang.org/t/the-bayesian-sde-in-the-turing-tutorial-issues-an-error/73447/8 "2021-12-22T09:57:57Z")

</div>

That error looks like it’s from having data the wrong size. There’s a spot in the tutorial where data might get redefined that wasn’t ran on your side or something. I can’t quite run it right now very easily because of this whole v1.7 issue.

---

<div class="post-metadata">

**Author:** ![lilianping](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/lilianping/32/32108_2.png) [@lilianping](https://discourse.julialang.org/u/lilianping)\
**Post date:** [December 22, 2021, 10:13am UTC](https://discourse.julialang.org/t/the-bayesian-sde-in-the-turing-tutorial-issues-an-error/73447/9 "2021-12-22T10:13:12Z")

</div>

thanks for your advise.  
The error appears in the last part of the code you showed. I also ran the code you posted, and it still got the same error.

```julia
model = fitlv(data, prob_sde)
chain = sample(model, NUTS(0.25), 5000, init_theta = [1.5,1.3,1.2,2.7,1.2,0.12,0.12])
plot(chain) #Error when running here
@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)
    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; #But actually there is a problem here

```

This is the code I am running,

```julia
using Turing, Distributions, DifferentialEquations

# Import MCMCChain, Plots, and StatsPlots for visualizations and diagnostics.
using MCMCChains, Plots, StatsPlots

# Set a seed for reproducibility.
using Random
Random.seed!(14);

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)
@time data = solve(ensembleprob,SOSRI(),saveat=0.1,trajectories=1000)
plot(EnsembleSummary(data))

Turing.setadbackend(:forwarddiff)
@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)
    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;

model = fitlv(data, prob_sde)
chain = sample(model, NUTS(0.25), 5000, init_theta = [1.5,1.3,1.2,2.7,1.2,0.12,0.12])
plot(chain)

```

---

<div class="post-metadata">

**Author:** ![lilianping](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/lilianping/32/32108_2.png) [@lilianping](https://discourse.julialang.org/u/lilianping)\
**Post date:** [December 22, 2021, 10:14am UTC](https://discourse.julialang.org/t/the-bayesian-sde-in-the-turing-tutorial-issues-an-error/73447/10 "2021-12-22T10:14:33Z")

</div>

The version I am using is 1.6.1. Will this be compatible with Turing?

---

<div class="post-metadata">

**Author:** ![lilianping](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/lilianping/32/32108_2.png) [@lilianping](https://discourse.julialang.org/u/lilianping)\
**Post date:** [December 22, 2021, 10:15am UTC](https://discourse.julialang.org/t/the-bayesian-sde-in-the-turing-tutorial-issues-an-error/73447/11 "2021-12-22T10:15:26Z")

</div>

The version I am using is 1.6.1. Will this be compatible with Turing? I’m not sure

---

<div class="post-metadata">

**Author:** ![ptoche](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/ptoche/32/23554_2.png) [@ptoche](https://discourse.julialang.org/u/ptoche)\
**Post date:** [December 22, 2021, 10:55am UTC](https://discourse.julialang.org/t/the-bayesian-sde-in-the-turing-tutorial-issues-an-error/73447/12 "2021-12-22T10:55:45Z")

</div>

Can you not update to 1.6.5?

---

<div class="post-metadata">

**Author:** ![nilshg](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/nilshg/32/2283_2.png) [@nilshg](https://discourse.julialang.org/u/nilshg)\
**Post date:** [December 22, 2021, 11:01am UTC](https://discourse.julialang.org/t/the-bayesian-sde-in-the-turing-tutorial-issues-an-error/73447/13 "2021-12-22T11:01:33Z")

</div>

1.6.1 should be fine, although 1.6.5 is preferred (as a patch release it should be a drop-in replacement and not affect the error you’re seeing here).

Just make sure you’re on the latest releases of the packages you’re using

---

<div class="post-metadata">

**Author:** ![lilianping](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/lilianping/32/32108_2.png) [@lilianping](https://discourse.julialang.org/u/lilianping)\
**Post date:** [December 22, 2021, 11:25am UTC](https://discourse.julialang.org/t/the-bayesian-sde-in-the-turing-tutorial-issues-an-error/73447/14 "2021-12-22T11:25:45Z")

</div>

I mean ,this is not a version issue, I just tried 1.6.5 and still have this error

---

<div class="post-metadata">

**Author:** ![lilianping](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/lilianping/32/32108_2.png) [@lilianping](https://discourse.julialang.org/u/lilianping)\
**Post date:** [December 22, 2021, 11:26am UTC](https://discourse.julialang.org/t/the-bayesian-sde-in-the-turing-tutorial-issues-an-error/73447/15 "2021-12-22T11:26:20Z")

</div>

ok，thank you so much

---

<div class="post-metadata">

**Author:** ![ptoche](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/ptoche/32/23554_2.png) [@ptoche](https://discourse.julialang.org/u/ptoche)\
**Post date:** [December 22, 2021, 1:12pm UTC](https://discourse.julialang.org/t/the-bayesian-sde-in-the-turing-tutorial-issues-an-error/73447/16 "2021-12-22T13:12:42Z")

</div>

> [@lilianping](#):
>
> ` init_theta = [1.5,1.3,1.2,2.7,1.2,0.12,0.12])`

The section below **Inference of a Stochastic Differential Equation** runs fine for me on `v1.7`. I get the 14-plot panel. But it does take several minutes to run.

---

<div class="post-metadata">

**Author:** ![lilianping](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/lilianping/32/32108_2.png) [@lilianping](https://discourse.julialang.org/u/lilianping)\
**Post date:** [December 23, 2021, 1:07am UTC](https://discourse.julialang.org/t/the-bayesian-sde-in-the-turing-tutorial-issues-an-error/73447/17 "2021-12-23T01:07:16Z")

</div>

I tried version 1.6.3 and still have this problem. I will try to upgrade 1.7, thank you for your help

---

<div class="post-metadata">

**Author:** ![ptoche](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/ptoche/32/23554_2.png) [@ptoche](https://discourse.julialang.org/u/ptoche)\
**Post date:** [December 23, 2021, 7:18am UTC](https://discourse.julialang.org/t/the-bayesian-sde-in-the-turing-tutorial-issues-an-error/73447/18 "2021-12-23T07:18:31Z")

</div>

`v1.7` won’t be the right version for `Turing` yet, you’ll need to wait a few bug fixes and an update to the package. The piece of code you copy-pasted cannot be run as is (is it the section below **Inference of a Stochastic Differential Equation**?) perhaps you’ve inadvertently changed something to the original code? The error you report is surprising if you’re running the part of the code I refer to.

---

<div class="post-metadata">

**Author:** ![lilianping](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/lilianping/32/32108_2.png) [@lilianping](https://discourse.julialang.org/u/lilianping)\
**Post date:** [December 23, 2021, 12:04pm UTC](https://discourse.julialang.org/t/the-bayesian-sde-in-the-turing-tutorial-issues-an-error/73447/19 "2021-12-23T12:04:03Z")

</div>

I did not make changes to the code. Actually, the code I changed had the same problem first, so I copied the code of the tutorials, but it also had the same problem. Not only me, I asked my classmates to run the same code. The same problem occurred.

---

<div class="post-metadata">

**Author:** ![ChrisRackauckas](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/chrisrackauckas/32/77_2.png) [@ChrisRackauckas](https://discourse.julialang.org/u/ChrisRackauckas)\
**Post date:** [December 23, 2021, 12:54pm UTC](https://discourse.julialang.org/t/the-bayesian-sde-in-the-turing-tutorial-issues-an-error/73447/20 "2021-12-23T12:54:05Z")

</div>

Are you on older package versions?

[Next page](https://discourse.julialang.org/t/the-bayesian-sde-in-the-turing-tutorial-issues-an-error/73447.md?page=2)