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@ChrisRackauckas ChrisRackauckas commented Jun 17, 2021

Sometimes simple is better. Instead of using a derivative estimate, now we just check at t + dt * repeat_nudge to avoid repeated zeros, with a default to 1//100 which seems to be a nice balance between numerical stability and keeping most of the interval still an eventful zone.

Fixes SciML/DifferentialEquations.jl#758
Fixes SciML/DifferentialEquations.jl#647
Fixes SciML/DifferentialEquations.jl#724
Fixes SciML/DifferentialEquations.jl#601
Fixes SciML/DifferentialEquations.jl#642
Fixes #599

Sometimes simple is better. Instead of using a derivative estimate, now we just check at t + dt * repeat_nudge to avoid repeated zeros, with a default to 1//100 which seems to be a nice balance between numerical stability and keeping most of the interval still an eventful zone. Fixes SciML/DifferentialEquations.jl#758
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It's impressive that this works so well.

Co-authored-by: David Widmann <devmotion@users.noreply.github.com>
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BTW the GPU tiemouts are caused by CUDA 3.3 but fixed on master: https://julialang.slack.com/archives/C689Y34LE/p1623939645188500 AFAIK a new release will be available soon (possibly today).

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Awesome, those were confusing me but I at least figured out it was unrelated to this (because those don't test callbacks)

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