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  • Dec 07 16:40
    ChrisRackauckas commented #785
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  • Dec 03 08:41

    ChrisRackauckas on master

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Christopher Rackauckas
@ChrisRackauckas
It will have to be updated for sure.
I know ForwardDiff no longer exports the derivative functions, so someone will have to go in and change those kinds of things.
Paweł Biernat
@pwl
I don't know how @PerezHz would feel about it, maybe you should write him first?
Christopher Rackauckas
@ChrisRackauckas
Okay, I'll email him.
Thanks for the heads up on this
Paweł Biernat
@pwl
if you won't be able to reach him you can try to write @lbenet, he will know what the status of the package is
I think he is his advisor, but I'm not so sure about it now:-)
Jorge Pérez
@PerezHz
Hi everyone! @ChrisRackauckas thanks for contacting us, glad to know you're interested in what we've been working on! :smile: Yes, we did take it down, we're re-organizing it (it's pretty much mixed with some celestial mechanics stuff) and planning to re-upload the generic parts of the code
Christopher Rackauckas
@ChrisRackauckas
Okay cool!
I am currently wrapping a bunch of packages into DifferentialEquations.jl, and would like to have that as one of the options to choose from.
Just let me know when you got something you want to show.
Paweł Biernat
@pwl
Are there any plans to release the interval arithmetic ODE solver? I saw something like that on @lbenet presentation.
Jorge Pérez
@PerezHz
Sure Chris, we'll let you know!
Yes @pwl there are plans, we're still working on it; the thing is, the leap towards interval arithmetics is non-trivial enough, @lbenet can give you more details about that
Christopher Rackauckas
@ChrisRackauckas
Are you going to be using ArbReals? I know dpsanders is in on that project.
Jorge Pérez
@PerezHz
AFAIK, we'll be using @dpsanders ValidatedNumerics.jl
Christopher Rackauckas
@ChrisRackauckas
I see
This application would be perfect for ArbReals though.
Though Interval{Float64} would be faster for small calculations, Interval{BigFloat} would do better than ArbReals if you need 500+ bits of accuracy.
But in the middle, 64-~500 bits, ArbReals is the way to go.
I kow Sanders and Benet have been on the emails with Jeffrey Sarnoff on ArbFloats/ArbReals, so I wonder if that's why.
Felix Henneke
@fhenneke
I might be mistaken, but should the name fehlberg in runge-kutta-fehlberg not be spelled with an E instead of a U?
Christopher Rackauckas
@ChrisRackauckas
Yes.
Where's do I have the error?
Felix Henneke
@fhenneke
everywhere? e.g. on the first page of the documentation and in the ode_tableaus.jl in the source code
Christopher Rackauckas
@ChrisRackauckas
oh...
:worried:
Thanks for letting me know!
Felix Henneke
@fhenneke
btw: keep up the good work! :)
Christopher Rackauckas
@ChrisRackauckas
Thanks!
Romain Veltz
@rveltz
HI,
I tried the simple code
'using DifferentialEquations

function vanDerPolExample(u₀=[0,sqrt(3)])
f1(u,t) = (1-u[2].^2)*u[1] - u[2]
f2(u,t) = u[1]
f(u,t) = [f1(u,t);f2(u,t)]
return(ODEProblem(f,u₀))
end
prob = vanDerPolExample()
Δt = 1//2^(4) #The initial timestepping size. It will automatically assigned if not given.
tspan = [0,20] # The timespan. This is the default if not given.
sol = solve(prob::ODEProblem,tspan,Δt=Δt,alg=:RK4)'

but it gives the error (line 12 is the solve):

ERROR: LoadError: BoundsError
in getindex at ./number.jl:21 [inlined]
in (::#f1#10)(::Rational{Int64}, ::Array{Float64,1}) at /Users/rveltz/Downloads/ode.jl:4
in (::#f#12{#f1#10,#f2#11})(::Rational{Int64}, ::Array{Float64,1}) at /Users/rveltz/Downloads/ode.jl:6
in (::DifferentialEquations.##500#507{DifferentialEquations.ODEProblem{Array{Float64,1},Float64}})(::Rational{Int64}, ::Array{Float64,1}, ::Array{Float64,1}) at /Users/rveltz/.julia/v0.5/DifferentialEquations/src/ode/ode_solve.jl:79
in ode_solve(::DifferentialEquations.ODEIntegrator{:RK4,Array{Float64,1},Float64,2,Rational{Int64}}) at /Users/rveltz/.julia/v0.5/DifferentialEquations/src/ode/ode_integrators.jl:376
in #solve#499(::Array{Any,1}, ::Function, ::DifferentialEquations.ODEProblem{Array{Float64,1},Float64}, ::Array{Int64,1}) at /Users/rveltz/.julia/v0.5/DifferentialEquations/src/ode/ode_solve.jl:134
in (::DifferentialEquations.#kw##solve)(::Array{Any,1}, ::DifferentialEquations.#solve, ::DifferentialEquations.ODEProblem{Array{Float64,1},Float64}, ::Array{Int64,1}) at ./<missing>:0
in include_from_node1(::String) at ./loading.jl:426
in include_from_node1(::String) at /Applications/Julia-0.5.app/Contents/Resources/julia/lib/julia/sys.dylib:?
while loading /Users/rveltz/Downloads/ode.jl, in expression starting on line 12

Do you have any idea?

Thank you,



Christopher Rackauckas
@ChrisRackauckas
Are you on master? Then the API changed to (t,u) and (t,u,du) to match ODE.jl, ODEInterface.jl, and Sundials.jl. IF you're not on master, than it's okay.
Christopher Rackauckas
@ChrisRackauckas
You may want to look at the updated docs if you're on master (/ the new version is coming out). That's pretty much the only user facing change.
Christopher Rackauckas
@ChrisRackauckas
But that's gotta be it: the error happened on 376 of ode_integrators which is just f(t,u,k₁), which is just k₁[:]=f(t,u), so the error is inside the function call, and it's likely erroring because if u and t are flip then there's no t[1].
Romain Veltz
@rveltz
That was it! The inplace modification is still available then?
Christopher Rackauckas
@ChrisRackauckas
Yes. It's (t,u,du). Julia usually has the in-place moded variable first, but all the Fortran codes that we have wrapped have them last. So it's slightly more efficient for the Fortran codes to just have everything be (t,u,du). ODE.jl for some reason already had that ordering, so that means all DE packages (that I know of) are standardized on it now.
So it's different from the Julia standard, but at least all DE packages are the same? I'm not sure about it still, but that's mostly because of the Fortran wrappers.
Romain Veltz
@rveltz
One last thing if I may. I have trouble using sundials. Do you have a working example? I looked for linearODEExample() in your code but could not put my finger on it. Can you give me a little push please?
Christopher Rackauckas
@ChrisRackauckas
In v0.3.0 the example problems changed to prob_ode_... (since anonymous functions in the sense they are used there actually compile for full performance. Not necessary for most things, but required for the threading tests)
So it's now prob = prob_ode_linear
The docs should all be updated for that.
That needs to be updated though.
One sec on that.
Christopher Rackauckas
@ChrisRackauckas
The testing for conditional dependencies will get turned back on tonight FYI. They had to be disabled for tests to pass on v0.4 due to Travis/AppVoyer issues (but they work on v0.5)
Romain Veltz
@rveltz

When using sundials, I always get:

ERROR: UndefVarError: cvode_fulloutput not defined
in #solve#499(::Array{Any,1}, ::Function, ::DifferentialEquations.ODEProblem{Float64,Float64}, ::Array{Int64,1}) at /Users/rveltz/.julia/v0.5/DifferentialEquations/src/ode/ode_solve.jl:255
in (::DifferentialEquations.#kw##solve)(::Array{Any,1}, ::DifferentialEquations.#solve, ::DifferentialEquations.ODEProblem{Float64,Float64}, ::Array{Int64,1}) at ./<missing>:0

Christopher Rackauckas
@ChrisRackauckas

Oh, did you check the conditional deps docs? There's a PR that needs to go through, so right now it's compatible with the branch for that PR (since it's right about to merge and change everything). Either use the branch handles from alyst/Sundials.jl, i.e.

Pkg.clone("https://github.com/alyst/Sundials.jl")
Pkg.checkout("Sundials","handles")

or just wait for the PR. It's here: JuliaDiffEq/Sundials.jl#67. It should've gone through, but Travis hasn't been working and we can't merge until it does...

It'll go through whenever Travis works again. Likely within a day or so? Lots of things are changing there, but it should settle down once that PR goes through.
Romain Veltz
@rveltz
thx, i got it to work!