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nonlinear-programming

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JuMP.jl
odow
odow commented Oct 3, 2020

Hi there!

This issue is a catch-all for documentation improvement suggestions. I'll keep it updated with things to work on, rather than having lots of separate issues.

  • If you have suggestions for things to add to the documentation, leave a comment below.
  • If you're looking to contribute to JuMP, picking something off this list is a great place to start!

General editing

The ea

Type: Documentation Status: Help Wanted good first issue
traversaro
traversaro commented Jan 23, 2022

If I run the copy&paste examples, such as https://mtk.sciml.ai/stable/tutorials/acausal_components/ :

using ModelingToolkit, Plots, DifferentialEquations

@variables t
@connector function Pin(;name)
    sts = @variables v(t)=1.0 i(t)=1.0 [connect = Flow]
    ODESystem(Equation[], t, sts, []; name=name)
end

function Ground(;name)
    @named g = Pin()
    eqs = [g.v ~ 0]
    
good first issue

CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained C-code generation and interfaces state-of-the-art codes such as SUNDIALS, IPOPT etc. It can be used from C++, Python or Matlab/Octave.

  • Updated Jun 9, 2022
  • C++

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