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[docs] modify the TokenIgnores in vale for fewer false negatives (#2114)
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docs/.vale.ini

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@@ -6,5 +6,4 @@ Vocab = JuMP-Vocab
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[*.md]
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BasedOnStyles = Vale, Google
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# Skip \\token and \token LaTeX commands
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TokenIgnores = \\\\[a-z]+, \\[a-z]+, [a-zA-Z]+_[_a-zA-Z]+
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TokenIgnores = \$.+?\$, \]\(@(ref|id).+?\)

docs/src/background/duality.md

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@@ -214,7 +214,7 @@ However, the dual of [`PositiveSemidefiniteConeSquare`](@ref) is not so straight
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forward. This section explains the duality convention we use, and how it is
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derived.
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!!! info "tl;dr"
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!!! info
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If you have a [`PositiveSemidefiniteConeSquare`](@ref) constraint, the
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result matrix ``A`` from [`ConstraintDual`](@ref) is not positive
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semidefinite. However, ``A + A^\top`` is positive semidefinite.

docs/src/changelog.md

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- Added `Utilities.set_with_dimension`
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- Added two-argument `optimize!(::AbstractOptimizer, ::ModelLike)`
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- The experimental feature `copy_to_and_optimize!` has been removed
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- Det bridges now support getting `ConstraintFunction` and `ConstraintSet`
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- `Det` bridges now support getting `ConstraintFunction` and `ConstraintSet`
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- Various minor bug fixes identified by improved testing
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## v0.10.1 (September 8, 2021)
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## v0.9.18 (November 3, 2020)
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- Various improvements for working with complex numbers
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- Added `GeoMeantoRelEntrBridge` to bridge a geomean constraint to a relative entropy constraint
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- Added `GeoMeantoRelEntrBridge` to bridge a `GeometricMeanCone` constraint to a
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relative entropy constraint
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## v0.9.17 (September 21, 2020)
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* Added support for starting values for `Variable.VectorizeBridge` (#944).
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* Fixed `MOI.add_constraints` with non-bridged variable constraint on bridged
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variable (#951).
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* Fixed corner cases and docstring of geomean bridge (#961, #962, #966).
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* Fixed corner cases and docstring of `GeoMeanBridge` (#961, #962, #966).
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* Fixed choice between variable or constraint bridges for constrained
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variables (#973).
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* Improve performance of bridge shortest path (#945, #946, #956).
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* Added `InvalidIndex` tests in `basic_constraint_tests` (#921).
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* Added tests for the constant term in indicator constraint (#929).
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- Bridges improvements:
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* Added support for starting values for functionize bridges (#923).
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* Added support for starting values for `Functionize` bridges (#923).
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* Added variable indices context to variable bridges (#920).
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* Fixed a typo in printing o `debug_supports` (#927).
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- Performance improvement in `default_copy_to` and bridge optimizer (#696).
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- Add `Silent` and implement setting optimizer attributes in caching and mock
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optimizers (#695).
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- Add functionize bridges (SingleVariable and VectorOfVariables) (#659).
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- Add `Functionize` bridges (SingleVariable and VectorOfVariables) (#659).
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- Minor typo fixes (#694).
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## v0.8.3 (March 6, 2019)

docs/src/manual/constraints.md

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@@ -92,8 +92,8 @@ Below is a list of common constraint types and how they are represented
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as function-set pairs in MOI. In the notation below, ``x`` is a vector of
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decision variables, ``x_i`` is a scalar decision variable, ``\alpha, \beta`` are
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scalar constants, ``a, b`` are constant vectors, `A` is a constant matrix and
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``\mathbb{R}_+`` (resp. ``\mathbb{R}_-``) is the set of nonnegative (resp.
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nonpositive) real numbers.
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``\mathbb{R}_+`` (resp. ``\mathbb{R}_-``) is the set of non-negative (resp.
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non-positive) real numbers.
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### Linear constraints
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docs/src/tutorials/mathprogbase.md

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If you haven't used JuMP before, start with the tutorial
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[Getting started with JuMP](https://jump.dev/JuMP.jl/stable/tutorials/getting_started/getting_started_with_JuMP/)
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### linprog
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### `linprog`
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Here is one way of transitioning from `linprog`:
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end
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```
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### mixintprog
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### `mixintprog`
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Here is one way of transitioning from `mixintprog`:
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end
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```
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### quadprog
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### `quadprog`
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Here is one way of transitioning from `quadprog`:
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docs/styles/Vocab/JuMP-Vocab/accept.txt

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backports
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blogposts
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bugfixe(?s)
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const
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expr
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datastructure
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docstring(?s)
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doctest
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getters
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[Jj]ulia
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[Pp]recompil(ation|(e(?d)))
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src
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subexpression(?s)
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% JuMP-related vocab
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[Cc]anonicaliz(e|ation|ing)
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[Dd]et
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functionize
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geomean
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(lin|mixint|quad)prog
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(log|root)det
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(L|Q)Ps
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multiobjective
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nonconvex
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[Nn]on(posi|nega)tive(?s)
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parameterizing
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[Pp]resolve
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[Ss]emi(continuous|integer|definite)
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tl
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Presolve
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[Ss]emidefinite
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unboundedness
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[Un]nivariate
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