[docs] add Transitioning from MATLAB tutorial #3698

odow · 2024-03-03T03:34:47Z

Cherry-picked from #3697

~~Preview: https://jump.dev/JuMP.jl/previews/PR3698/tutorials/getting_started/transitioning_from_matlab/~~

https://jump.dev/JuMP.jl/previews/PR3698/tutorials/transitioning/transitioning_from_matlab/

codecov · 2024-03-03T03:46:59Z

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##           master    #3698   +/-   ##
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docs/src/tutorials/getting_started/transitioning_from_matlab.jl

araujoms · 2024-03-03T10:30:02Z

I don't have write access anymore since this PR is now in your branch.

araujoms

I've added the commands querying the solution status to the JuMP, YALMIP, and CVX codes. Also, note that in MATLAB the main function needs to be the first one, so I changed back the order.

docs/src/tutorials/getting_started/transitioning_from_matlab.jl

odow · 2024-03-03T20:55:55Z

I don't have write access anymore since this PR is now in your branch.

Yeah. I changed it here so that we can get a preview: https://jump.dev/JuMP.jl/previews/PR3698/tutorials/getting_started/transitioning_from_matlab/

docs/src/tutorials/getting_started/transitioning_from_matlab.jl

araujoms · 2024-03-03T22:49:04Z

Maybe it is worth it adding a paragraph explaining Symmetric and Hermitian?

blegat · 2024-03-04T12:25:31Z

It's also worth mentioning the difference between YALMIP and JuMP according to dualization. YALMIP is always in image form / geometric conic form while in JuMP it depends on the solver. See section 2.1 of the MOI paper for instance. You can refer to https://jump.dev/JuMP.jl/stable/tutorials/conic/dualization/

docs/src/tutorials/getting_started/transitioning_from_matlab.jl

Co-authored-by: Mateus Araújo <[email protected]>

odow · 2024-03-05T00:24:57Z

Maybe it is worth it adding a paragraph explaining Symmetric and Hermitian?

I'd like to keep this tutorial pretty tightly scoped to focus on JuMP/YALMIP/CVX.

It is not the place for this tutorial to be a cheatsheet of every difference between Julia and MATLAB. Symmetric and Hermitian should be reasonably self-evident. If it isn't users can always look up the Julia documentation.

odow · 2024-03-05T00:25:59Z

It's also worth mentioning the difference between YALMIP and JuMP according to dualization.

Is this necessary for users transitioning from MATLAB? It seems in the weeds. I'd prefer we left it out and got feedback first.

docs/src/tutorials/getting_started/transitioning_from_matlab.jl

araujoms · 2024-03-05T07:03:14Z

It is not the place for this tutorial to be a cheatsheet of every difference between Julia and MATLAB. Symmetric and Hermitian should be reasonably self-evident. If it isn't users can always look up the Julia documentation.

The difference is that with YALMIP and CVX one needs to do a = 0.5*(a+a') over and over again, to make sure your matrices are exactly Hermitian, whereas with JuMP this doesn't matter, you just have to wrap them in Hermitian.

blegat · 2024-03-05T08:24:27Z

Is this necessary for users transitioning from MATLAB? It seems in the weeds. I'd prefer we left it out and got feedback first.

This is the n°1 comment people have when coming from YALMIP (see for instance https://discourse.julialang.org/t/yalmip-vs-jump/30776/10 and https://discourse.julialang.org/t/jump-sumofsquares-generate-sdps-with-18x-more-constraints-than-yalmip/65377/15). It can just be a small note refering to the relevant part of the doc. (sorry I closed, missed click)

araujoms · 2024-03-05T09:01:56Z

I also think it would be worth it such a remark, it has a large impact on performance.

docs/src/tutorials/getting_started/transitioning_from_matlab.jl

Co-authored-by: Mateus Araújo <[email protected]>

araujoms · 2024-03-06T07:08:20Z

docs/src/tutorials/transitioning/transitioning_from_matlab.jl

+    optimize!(model)
+    if is_solved_and_feasible(model)
+        WT = dual(PPT)
+        return value(λ), real(LinearAlgebra.dot(WT, rhoT))


Why did add real here? It's redundant, dot already returns a real number from Julia 1.11 onwards.

Because the docs currently build with Julia 1.10 and we support Julia 1.6. Also, v1.11 isn't released yet.

What's the problem? It doesn't cause any error with older versions of Julia, the output is just slightly less neat.

dot currently returns a Complex{Float64} instead of a Float64. Your MATLAB examples return a Float64.

julia> import LinearAlgebra julia> A = LinearAlgebra.Hermitian(rand(ComplexF64, (3, 3))) 3×3 LinearAlgebra.Hermitian{ComplexF64, Matrix{ComplexF64}}: 0.468242+0.0im 0.296799+0.49972im 0.621408+0.148878im 0.296799-0.49972im 0.413853+0.0im 0.677598+0.875476im 0.621408-0.148878im 0.677598-0.875476im 0.59341+0.0im julia> LinearAlgebra.dot(A, A) 4.6860981128420285 + 0.0im julia> real(LinearAlgebra.dot(A, A)) 4.6860981128420285

I know. This is not an error, and will change anyway in Julia 1.11.

I know

I know because I saw your PR 😄

My point is that I personally would argue that changing from ComplexF64 to Float64 is a breaking change, and the fact it will change in Julia v1.11 is not compelling because we still have many JuMP users on a range of old versions. I want something that works across all versions, not just some upcoming one. We cannot assume that new users from MATLAB will use a recent version of Julia. See, for example, a discourse user on Julia v1.5.

I really don't understand the problem. It works. It's just slightly uglier. And moreover it's just example code in a tutorial. Nothing depends on whether its return value is Float64 or ComplexF64.

It doesn't work. One return a ComplexF64, and the other returns a Float64.

Why is this a problem?

araujoms · 2024-03-06T10:15:07Z

docs/src/tutorials/transitioning/transitioning_from_matlab.jl

+
+# The same applies for Hermitian matrices, using `LinearAlgebra.Hermitian` and
+# `LinearAlgebra.ishermitian`.
+


What I wanted to point out here is that with MATLAB you have to be paranoid about making your matrices exactly Hermitian, in order to not get subtle errors, whereas with JuMP you just need to wrap them and you're good to go.

But now I've tested it, and it turns out that it's not true. If you try to constrain a non-Hermitian matrix to be in HermitianPSDCone() you get an error message, as I expected, but if you try to constrain a non-Symmetric matrix to be in PSDCone() JuMP will let you (and fail afterwards, of course). Is that intentional?

For non-symmetric matrices, JuMP adds equality constraints for the off-diagonal elements. It lets you write

model = Model() @variable(model, X[1:2, 1:2]) @constraint(model, X in PSDCone())

We don't have the same for Hermitian because there is no HermitianPostiveSemidefininteConeSquare (I'm sure we've discussed, but I can't find the link. Edit: found it: #3369 (comment)).

Why? Is there any case where you would need that? As far as I can see this can either generate less efficient code or give you an error.

Regardless of the need, it exists in JuMP 1.0 so we are not changing it.

Someone could also write [x y; 1 z] in PSDCone() and we would add a constraint that y == 1. It may have been sensible to support only the triangular form of PSD, but we didn't do that, so it's no longer up for discussion.

We added Hessian support after 1.0, which is why it supports only the triangular form.

I was just curious, I wasn't suggesting to change this, it would clearly be a breaking change.

Although now that you brought it up, I will definitely suggest removing it when the time comes for JuMP 2.0.

I will definitely suggest removing it when the time comes for JuMP 2.0

My goal is not to release JuMP 2.0 if at all possible. If we did, it would be for a minimal set of breaking changes, not just to remove some things we don't like. The only candidate was the nonlinear changes, but we seem to have managed to sneak them in with minimal disruption. The JuMP developers have no plans for JuMP 2.0.

odow · 2024-03-06T22:26:23Z

Merging because this is good enough for now. If needed, we can make tweaks in smaller PRs, instead of hashing everything out here. (There are already 56 comments!)

odow mentioned this pull request Mar 3, 2024

add matlab tutorial #3697

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[docs] add Transitioning from MATLAB tutorial #3698

[docs] add Transitioning from MATLAB tutorial #3698

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		# The same applies for Hermitian matrices, using `LinearAlgebra.Hermitian` and
		# `LinearAlgebra.ishermitian`.

[docs] add Transitioning from MATLAB tutorial #3698

[docs] add Transitioning from MATLAB tutorial #3698

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