JuliaDynamics / Attractors.jl

Find attractors of dynamical systems, their basins, and continue them across parameters. Study global stability (a.k.a. non-local, or resilience). Also tipping points functionality.
MIT License
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Creating ics on grid for higher dimensions #99

Open KalelR opened 9 months ago

KalelR commented 9 months ago

This is the code I used to deal with the problem we discussed in Issue #76. There, using basins_of_attraction in high (maybe >5?) dimensional-systems wouldn't run, because the algorithm would get stuck generating initial conditions. I explain the idea for my solution in Issue #76. It's probably not the most optimal way of solving the problem, but it works and is fast enough for my use-cases. Let me know if you think it's worth keeping it like this!

codecov-commenter commented 9 months ago

Codecov Report

Merging #99 (5eedc82) into main (8171746) will decrease coverage by 1.39%. The diff coverage is 38.46%.

@@            Coverage Diff             @@
##             main      #99      +/-   ##
==========================================
- Coverage   84.27%   82.89%   -1.39%     
==========================================
  Files          20       20              
  Lines        1151     1175      +24     
==========================================
+ Hits          970      974       +4     
- Misses        181      201      +20     
Files Coverage Δ
src/mapping/attractor_mapping.jl 63.63% <38.46%> (-17.32%) :arrow_down:

... and 1 file with indirect coverage changes

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Datseris commented 9 months ago

I don't understand this PR. Can you please explain it? What are dimensions that are not "varying" ? What does this mean?

If someone calls basins_of_attraction(mapper, grid) then naturally all dimensions of the grid are varying, right? Or? This PR adds a function generate_ics_on_grid but doesn't reference this function anywhere, so I am not sure where or how this function would be used. Can you give a concrete example application?

Datseris commented 7 months ago

bump @KalelR