# RNG in DiscreteProblem solver

**URL:** <https://discourse.julialang.org/t/rng-in-discreteproblem-solver/95929>\
**Category:** Modelling & Simulations\
**Created:** [March 11, 2023, 5:51pm UTC](https://discourse.julialang.org/t/rng-in-discreteproblem-solver/95929 "2023-03-11T17:51:51Z")\
**Posts on this page:** 1\
**Showing post:** 3

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**Author:** ![sdwfrost](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/sdwfrost/32/2831_2.png) [@sdwfrost](https://discourse.julialang.org/u/sdwfrost)\
**Post date:** [March 11, 2023, 7:30pm UTC](https://discourse.julialang.org/t/rng-in-discreteproblem-solver/95929/3 "2023-03-11T19:30:59Z")

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It’s basically this model (see code at end)

> [@Tips on (sort of) creating a new Problem type in SciML, derived from an existing type](https://discourse.julialang.org/t/tips-on-sort-of-creating-a-new-problem-type-in-sciml-derived-from-an-existing-type/95749/2):
>
> Is this code cleaner? Is composition the best way here, rather than use traits e.g. via SimpleTraits.jl? I mostly need the types for the time and the state, so the typing should be sufficient. What are the scenarios for using the isinplace type? # TODO: # Add MarkovSystem # Generalize to integer steps # Write integrator struct # Write init and step methods import SciMLBase: DiscreteProblem, ODESolution import OrdinaryDiffEq: solve, FunctionMap import Random: AbstractRNG import Plots: plot str…

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