SciML / SciML/DataDrivenDiffEq.jl
DataDrivenProblem takes a very long time
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- Julia
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Description
Hello, I'm trying to run the example of eDMD used on a Nonlinear Time Continuous System, found here https://docs.sciml.ai/DataDrivenDiffEq/stable/libs/datadrivendmd/examples/example_04/#nonlinear_continuos , but the copy-pasteable code now takes about 15 minutes to run. I've tried to run the example on two different computers (one Windows 10, the other Manjaro stable) on VSCode.
The code seems to get stuck on the line
prob = DataDrivenProblem(solution)
Since a week ago or so the example worked, I thought that the problem may have been caused by https://github.com/SciML/NonlinearSolve.jl/issues/223 , but this issue seems to be solved and the example still takes a very long time to compute.
P.S. Thank you for the very nice package :)
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with the nonlinear continuous-system eDMD example linked in the issue and reproduce the delay around DataDrivenProblem(solution) on a current environment. Check recent changes and the referenced NonlinearSolve.jl issue while comparing the example's expected runtime; done means the copy-pasteable example no longer takes about 15 minutes.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- julia
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 25/100