I teach a course on convex optimization and use Julia/JuMP (along with Matlab/CVX) to introduce students to implementation aspects – however, I am not a super-user of Julia/JuMP and may be missing something obvious, but I am a greatly puzzled and hope someone can help out.
Problem: I have a student implementing an SDP, who keeps getting the same error (on a Windows 10 laptop with Julia/JuMP v1.7/1.3) for code that runs fine on my computer (MacOS Julia/JuMP v1.8/1.3).
The error on the student’s end is attached in the figure: MethodError → QuadExpr / AffExpr about object type issues. The simple piece of code/script that works on my end, but fails on theirs is attached here.
If someone can help us understand why this issue happens on identical code for different computers that would be great, so I can avoid future issues with students. I have asked the student to update to Julia 1.8 (from 1.7) but am not sure that is the core issue and if so, I’d love to better understand what is happening.
Much appreciated and thank you for any responses!
using Graphs, LinearAlgebra, JuMP using SCS n=3; A1=rand([0,1],n,n); #random nxn adjaceny matrix. Values of 0 or 1. A2=A1+A1'; #makes Adjacency matrix symmetric, implying undirected graph. A=A2-Diagonal(diag(A2)); #makes diagonal of adjacency matrix zeros, removing self loops model=Model(SCS.Optimizer); # model=Model(SCS.Optimizer); gamma=@variable(model) w=@variable(model, [1:n]) #constraints for fast mixing markov chain @constraint(model, c1, A*Diagonal(w)*A' + (1/n).*ones(n,n) <= gamma.*I(n) + I(n), PSDCone()) @constraint(model, c2, I(n) - A*Diagonal(w)*A' - (1/n)*ones(n,n) <= gamma.*I(n), PSDCone()) @constraint(model, c3, A*Diagonal(w)*A' <= I(n), PSDCone()) @constraint(model, c4, w .>= 0) @constraint(model, c5, gamma >= 0) @objective(model,Min, gamma) optimize!(model) wVal = value.(w) gammaVal = value(gamma)