Tidy up quadratic constraint printing about jump.jl HOT 9 CLOSED

What did you mean by this? All I can think of is grouping like variables (e.g. 2 xz + 3zx => 5xz).

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Yeah that was it

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Also:

julia> addConstraint(m,x^2-x^2==0)
1.0 x² - 1.0 x² == 0

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Hah, yep.
I'm still in love with those ²s :D

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Gonna claim 0.3 as the quadratic constraints update - so I'll put this under 0.3

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Just quadratic? Want to shoot for full nonlinear (Ipopt, Mosek) support as well?

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So we'll definitely support quadratic for those, but I think general convex optimization depends on getting automatic differentiation done well first, so, later.

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Fair enough. More structured stuff like SDPs would be really cool, though!

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CVX-style convex doesn't need AD afaik, the conic structure is built up with the expression. Replicating CVX will be a bit past 0.3 though :). General nonlinear does need AD, which might come sooner rather than later. I had a good chat with the AD guys at Argonne.

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