Skip to content

Conversation

@oscardssmith
Copy link
Member

Needed for SciML/OrdinaryDiffEq.jl#1763. The previous tolerance was overly strict.

@devmotion
Copy link
Member

So SciML/OrdinaryDiffEq.jl#1763 introduces regressions?

@oscardssmith
Copy link
Member Author

It is slightly less accurate when the timespan is greater than 1, but the policy of picking an initial dt that is fixed makes a lot less sense than picking one proportional to the timespan.

@devmotion
Copy link
Member

Because of the nested structure (nesting ODE solvers inside ODE solvers) tiny regressions in OrdinaryDiffEq are amplified in DelayDiffEq. So I'm also worried about small regressions. Could one introduce a branch such that larger time spans are still handled in the same way?

@oscardssmith
Copy link
Member Author

This was actually nu-necessary. I only need this change for DAEs.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Labels

None yet

Projects

None yet

Development

Successfully merging this pull request may close these issues.

2 participants