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  • Sep 17 02:39
    QiyaoWei commented #799
  • Sep 16 19:57
    ChrisRackauckas commented #799
  • Sep 16 15:48
    Tokazama commented #25
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    Tokazama commented #25
  • Sep 16 02:27
    ChrisRackauckas closed #681
  • Sep 16 02:27
    ChrisRackauckas commented #681
  • Sep 16 01:45
    samuela commented #681
  • Sep 15 16:39
    JianghuiDu opened #800
  • Sep 15 08:15
    timholy commented #25
  • Sep 14 21:57
    Tokazama commented #25
  • Sep 14 21:43
    timholy commented #25
  • Sep 14 20:58
    Tokazama commented #25
  • Sep 14 20:24
    timholy commented #25
  • Sep 08 15:56
    QiyaoWei opened #799
  • Sep 07 14:35
    Akshaye-Pal closed #795
  • Sep 07 14:35
    Akshaye-Pal commented #795
  • Sep 04 16:15
    ChrisRackauckas reopened #798
  • Sep 04 07:20
    rveltz commented #798
  • Sep 03 16:12
    ChrisRackauckas closed #798
  • Sep 03 16:12
    ChrisRackauckas commented #798
Christopher Rackauckas
@ChrisRackauckas
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!
Christopher Rackauckas
@ChrisRackauckas
:+1: . One all of this goes through that should just happen by default. Sorry for the friction.
Chris Binz
@crbinz
This message was deleted

Hi there. I'm trying to get this package to replace ODE.jl in my code, since I really like the design of it. My first attempt results in the following error:

ERROR: LoadError: LoadError: ArgumentError: argument is not a generic function
 in methods at reflection.jl:180
 in numparameters at /Users/cbinz/.julia/v0.4/DifferentialEquations/src/general/problems.jl:460
 in call at /Users/cbinz/.julia/v0.4/DifferentialEquations/src/general/problems.jl:395
...

Here's the line that throws the error:

        p = ODEProblem( (t,y)->vopeom(t, y, sat, propOpt), x)
Chris Binz
@crbinz
am I doing something obviously wrong here?
Christopher Rackauckas
@ChrisRackauckas
@crbinz Are you on master? v0.4 is only supported on the last release because of this issue.
On v0.4, you'd want to use "generic functions" anyways because they are a lot faster. Anonymous functions (in v0.4) have a lot of overhead (they are kept as code, and don't compile). So a quick fix would be:
f(t,y) = vopeom(t, y, sat, propOpt)
p = ODEProblem(f, x)
(In v0.5 you don't have to worry about this). But if you're on Julia v0.4 with DifferentialEquations v0.3.0 this issue shouldn't be there (according to Travis and AppVoyer?).
Chris Binz
@crbinz
Thanks, that helped. I think I was a version behind, probably
Christopher Rackauckas
@ChrisRackauckas
No problem.
Christopher Rackauckas
@ChrisRackauckas
@/all Hello all. This chatroom will be deprecated. Please use the shared JuliaDiffEq chat for further discussions. Thanks! https://gitter.im/JuliaDiffEq/Lobby
liuwa666
@liuwa666
Hello, Thanks for your wonderful projects, I like DifferentialEquations.jl very much, I'm a newer to julia and DifferentialEquations.jl, but i want to use julia, DifferentialEquations, and FluxML to continue my scientific projects moving on. I have a question to ask:
Can DifferentialEquations.jl support Cudanative???
liuwa666
@liuwa666
My projects refers to Power system security analysis and prediction, as power system is generally modeled to a huge and complicated DAE. So parallel computing is necessary
Christopher Rackauckas
@ChrisRackauckas
Hey, this is the wrong channel. This is our older channel. Our current channel is https://gitter.im/JuliaDiffEq/Lobby

Can DifferentialEquations.jl support Cudanative???

Yes it did in v0.6, but we do need to fix it.

Basically, the broadcast changes are going to be a bit complicated to unravel with some of the setups
Christopher Rackauckas
@ChrisRackauckas
@fuyingfuying
liuwa666
@liuwa666
@ChrisRackauckas thanks very much
craftsmanhe
@craftsmanhe
Hi Christopher, is there a wall time setting on these ODE solvers? like only run 5mins if not finish then return an flag or error? I saw there is a maxiter sets the maximum iteration times maybe similar.
Christopher Rackauckas
@ChrisRackauckas
@craftsmanhe this is the old old channel! Surprised I am still following it
There's no wall time setting, maybe it can be added quite easily. Open an issue
craftsmanhe
@craftsmanhe
Thanks. I got it.
Tirtash
@tirtash
I receive error while running the example of SDE in my jupyter notebook, I did the instruction and import all of the required libraries!! the error is this
MethodError: no method matching setindex!(::Float64, ::Int64, ::Int64)
@ChrisRackauckas
Tirtash
@tirtash
my julia version is Julia 1.5.2
Christopher Rackauckas
@ChrisRackauckas
@tirtash we migrated away from this channel in 2016. You'll want to use the standard JuliaDiffEq channels
Your issue is that you're looking at the v3 documentation
looks at the v6.16+ documentation
this will have the right syntax
Pushkar Anirudha Pandit
@ppandit95
Greeting to DifferentialEquations.jl community,
I have just started to work with julia as well as this library in my attempt to learn scientific machine learning
while solving worksop exercises on SciMLTutorials.jl github page I am facing certain warnings while computing the ensenbleproblem
---> Warning: Interrupted. Larger maxiters is needed
So any direction in this regard will be quite helpful
Christopher Rackauckas
@ChrisRackauckas
@ppandit95 this isn't the correct channel. It moved in 2016
You'll want to post which tutorial you're running and what you ran in the main channel
Pushkar Anirudha Pandit
@ppandit95
ohh currently I am trying to work with exercises in https://tutorials.sciml.ai/html/exercises/01-workshop_exercises.html
In part 5 while using ensembleproblem I encountered this issue.
Christopher Rackauckas
@ChrisRackauckas
Did you increase maxiters?
Pushkar Anirudha Pandit
@ppandit95
I havnt given any maxiters as argument while using the command
natschil
@natschil
But I'm still getting different results
Christopher Rackauckas
@ChrisRackauckas
Ask in the real channel