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Add set inequality syntax for matrices #3766

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@odow odow commented Jun 3, 2024

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All modified and coverable lines are covered by tests ✅

Project coverage is 98.39%. Comparing base (b369f5b) to head (19c7f62).

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@@           Coverage Diff           @@
##           master    #3766   +/-   ##
=======================================
  Coverage   98.38%   98.39%           
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=======================================
+ Hits         5790     5809   +19     
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docs/src/manual/constraints.md Outdated Show resolved Hide resolved
@odow
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odow commented Jun 4, 2024

I can see us getting asked to support this for all matrices, not just symmetric ones. But perhaps that' a PR for another day.

@LebedevRI
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I can see us getting asked to support this for all matrices, not just symmetric ones. But perhaps that' a PR for another day.

FWIW, yes. The vec() escape hatch is meh, and may make issues w/ matrix shape mismatch (== comparing wrong things) less easy to discover.

@odow odow changed the title Add set inequality syntax for symmetric matrices Add set inequality syntax for matrices Jun 5, 2024
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blegat commented Jun 5, 2024

What we are doing for @constraint(model, x <= y, set) is a bit weird, it will give a value and dual that are inconsistent with the scalar @constraint(model, x <= y) (similar to what we noticed and fixed for Convex.jl). I'm wondering if, instead of interpreting it as y - x in set, we shouldn't rather see it as x - y in -set. We would still encode it as y - x in set but we could keep the -1 flip in the shape so that it's recovered when you query value or dual.

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blegat commented Jun 5, 2024

As this is breaking then maybe we should continue to do what we do but we should add a warning in the docs that @constraint(model, x >= y, set) is preferred since @constraint(model, x <= y, set) may have a behavior that's unexpected or confusing which makes the things less readable or error-prone if value or dual are used.

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What we are doing for @constraint(model, x <= y, set) is a bit weird, it will give a value and dual that are inconsistent with the scalar @constraint(model, x <= y) (similar to what we noticed and fixed for Convex.jl).

I'm wondering if, instead of interpreting it as y - x in set,

Peanut gallery comment: the docs and disscussion in the issue make it seem
like x <= y is treated exactly as x >= y, i.e. it would have still resulted in x-y in set?

we shouldn't rather see it as x - y in -set. We would still encode it as y - x in set but we could keep the -1 flip in the shape so that it's recovered when you query value or dual.

This kinda sounds like either solution would address my concerns from #3765, i think.

As this is breaking then maybe we should continue to do what we do but we should add a warning in the docs that @constraint(model, x >= y, set) is preferred since @constraint(model, x <= y, set) may have a behavior that's unexpected or confusing which makes the things less readable or error-prone if value or dual are used.

Peanut gallery comment: the concern here is external non JuMP/MOI sets/code, correct? Since i don't think this syntax currently works on native JuMP/MOI stuff, so it would only affect extensions?

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odow commented Jun 5, 2024

Let's just throw an error for these <= cases. I'll document the PSDCone case in a separate PR.

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blegat commented Jun 5, 2024

But it already does it for AbstractVector so wouldn't adding an error be breaking ?

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LebedevRI commented Jun 5, 2024

Peanut gallery comment:
it's going to be unfortunate that there's difference in behavior in these inequality constraints.
From outside, what would //i// think the best, no-unexpected-behavior, be, is:

@constraint(model, x >= y)

is always the same as

@constraint(model, x - y >= 0)
@constraint(model, x - y in Nonnegatives)

likewise

@constraint(model, x <= y)

is always the same as

@constraint(model, x - y <= 0)
@constraint(model, x - y in Nonpositives)

... for any [common] type of x and y, be it either a scalar, a vector, a symmetric matrix, or a non-symmetric matrix.

Currently

@constraint(model, x >= y)
@constraint(model, x <= y)

are not valid, and the code is always expected to explicitly spell out the cone type.
They already do that, so that change would greatly improve the QoL for the "normal" comparisons,
make bugs basically impossible in them (have i mentioned that manually spelling the set is a bit mouthful?),
while not particularly affecting the cone constraints - one can't automatically guess
which constraint was meant there, wherein that is trivial and obvious in "normal" case...

As i see it, it's an obvious trade-off, and the current solution is not obviously optimal.
(If this makes any sense, but is clearly contentious, perhaps defer until the monthly(?) developer call?)

I'll shut up now.

@odow odow force-pushed the od/symmetric-inequality branch from e982863 to 7a9a6be Compare June 5, 2024 20:56
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odow commented Jun 5, 2024

I've added an error for these new cases. No change to the existing vector support. I've added a warning to #3769, and we don't mention x <= y, Set() in the documentation.

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odow commented Jun 6, 2024

I actually think this is less problematic that it seems. You're opting into a new syntax.

In Boyd's book, they have:

$x \preceq_K y \iff y - x \in K$

And they write

We also write $x \succeq_K y$ for $y \preceq_K x$

It's not obvious that flipping $\preceq$ to $\succeq$ should change the sign of the primal or dual value. That's just not the way you interpret it.

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FWIW i believe this (& its non-symmetric friend) can proceed without waiting for the understanding in #3770 to be reached.

set_start_value.(y, [6 4; 4 7])
g = [x[1, 1] - y[1, 1], x[1, 2] - y[1, 2], x[2, 2] - y[2, 2]]
for set in (Nonnegatives(), Nonpositives(), Zeros())
c = @constraint(model, x >= y, set)
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Add a test for x - y in set

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Ah. @mlubin, I remember now.

We can't support x - y in Nonnegatives() because then we can't tell it apart from @constraint(model, x >= y) which was the whole point in the first place.

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We can't support x - y in Nonnegatives()

What do you mean ? You mean x >= y, Nonnegatives() ?

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No I mean @constraint(model, x - y in Nonnegatives()) because this hits the same codepath as @constraint(model, x >= y).

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Unless I intercept the GreaterThan(false) method, but then I think the last time I looked that makes ambiguities.

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Inequality constraints over symmetric matrices are cumbersome
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