SciML / OrdinaryDiffEq.jl

High performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)
https://diffeq.sciml.ai/latest/
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Split ODE problem do not work with factorization linear solvers #1726

Open ranocha opened 2 years ago

ranocha commented 2 years ago

I got the message

julia> sol = solve(ode, KenCarp4(), saveat=range(first(tspan), stop=last(tspan), length=200), abstol=1.0e-7, reltol=1.0e-7)
┌ Warning: Split ODE problem do not work with factorization linear solvers. Bug detailed in https://github.com/SciML/OrdinaryDiffEq.jl/pull/1643. Defaulting to linsolve=KrylovJL()
└ @ OrdinaryDiffEq ~/.julia/packages/OrdinaryDiffEq/DGMT0/src/alg_utils.jl:186

Xref https://github.com/SciML/OrdinaryDiffEq.jl/pull/1643

oscardssmith commented 2 years ago

Is this now fixed?