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SciML / DiffEqCallbacks.jl

A library of useful callbacks for hybrid scientific machine learning (SciML) with augmented differential equation solvers
https://docs.sciml.ai/DiffEqCallbacks/stable/
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DualNumbers package #188

Closed ArnoStrouwen closed 6 months ago

ArnoStrouwen commented 6 months ago

Running the tests locally, I get the very weird error,

julia> sol1 = solve(prob2D, BS3(), callback = cb2D, abstol = fill(1e-6, 4, 2))
ERROR: MethodError: Cannot `convert` an object of type Matrix{Float64} to an object of type Float64

Closest candidates are:
  convert(::Type{T}, ::DualNumbers.Dual) where T<:Union{Real, Complex}
   @ DualNumbers C:\Users\arno\.julia\packages\DualNumbers\5knFX\src\dual.jl:24
  convert(::Type{T}, ::T) where T
   @ Base Base.jl:84
  convert(::Type{T}, ::T) where T<:Number
   @ Base number.jl:6
  ...

I can't reproduce this on CI: https://github.com/SciML/DiffEqCallbacks.jl/pull/187 How are we using this DualNumbers package at all...

ArnoStrouwen commented 6 months ago

I've since resorted to nuking my .julia folder, which resolved the issue. Since, CI nor other people could easily reproduce, and I have upped the lower bounds here https://github.com/SciML/DiffEqCallbacks.jl/pull/189, this issue will likely not pop up again and I'm thus closing the issue.