# ModelingToolkit/ ODESystem in Turing

**URL:** <https://discourse.julialang.org/t/modelingtoolkit-odesystem-in-turing/115700>\
**Category:** Probabilistic Programming\
**Tags:** turing, modelingtoolkit\
**Created:** [June 15, 2024, 9:24pm UTC](https://discourse.julialang.org/t/modelingtoolkit-odesystem-in-turing/115700 "2024-06-15T21:24:10Z")\
**Posts on this page:** 1\
**Showing post:** 8

<div class="post-metadata">

**Author:** ![cryptic.ax](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/cryptic.ax/32/220540_2.png) [@cryptic.ax](https://discourse.julialang.org/u/cryptic.ax)\
**Post date:** [June 16, 2024, 5:32pm UTC](https://discourse.julialang.org/t/modelingtoolkit-odesystem-in-turing/115700/8 "2024-06-16T17:32:29Z")

</div>

> [@Indentify parameters in an ODEProblem](https://discourse.julialang.org/t/indentify-parameters-in-an-odeproblem/114784/17):
>
> Indeed, I was following that page already. But I got a totally lost with all the different options available to modify ODE problems. Apologies, I modified the code while you were typing a reply, i hope you caught that? I implemented it like this: # ordered symbols syms = [sys.lC\_i, sys.lC\_e, sys.lC\_h, sys.lR\_ie, sys.lR\_ea, sys.lR\_ih, sys.lA\_w, sys.lA\_e] @model function LGDS(x::AbstractArray, prob, params::Dict, t\_int) # cache for remake(prob, p=newp) lbc = GeneralLazyBufferCache…

This is that discourse post. The method at the end is what you should use. Feel free to ask if anything is not clear.

EDIT: They’re using Turing.jl too, so it should map 1-1 with your use case.

---

_[View the full topic](https://discourse.julialang.org/t/modelingtoolkit-odesystem-in-turing/115700)._