Merge pull request #91 from tkoolen/tk/update-moi-0.6

Update to MOI 0.6.

README.md

@@ -22,8 +22,8 @@ Here's the basic problem setup:
 
 ```julia
 # create a MathOptInterface optimizer instance
-using OSQP.MathOptInterfaceOSQP
-optimizer = OSQPOptimizer()
+using OSQP
+optimizer = OSQP.Optimizer()
 
 # create a Parametron.Model, which holds problem information
 using Parametron
@@ -127,7 +127,7 @@ julia> value.(model, x)
 Note that the solver is warm-started. Also note that updating the parameters and solving a new QP instance is quite fast:
 
 ```julia
-julia> using MathOptInterface; MathOptInterface.set!(optimizer, OSQPSettings.Verbose(), false) # silence the optimizer
+julia> using MathOptInterface; using OSQP.MathOptInterfaceOSQP: OSQPSettings; MathOptInterface.set!(optimizer, OSQPSettings.Verbose(), false) # silence the optimizer
 
 julia> using BenchmarkTools
 
@@ -166,7 +166,7 @@ using Random
 n, m = 5, 15
 Xdata = randn(n, m)
 pdata = Vector{Float64}(undef, m);
-model = Model(OSQPOptimizer())
+model = Model(OSQP.Optimizer())
 X = Parameter(model, val=Xdata)
 p = Parameter(model, val=pdata)
 g = [Variable(model) for _ = 1:n]

REQUIRE

@@ -1,5 +1,5 @@
 julia 0.7
-MathOptInterface 0.5 0.6
+MathOptInterface 0.6 0.7
 MacroTools
 FunctionWrappers 0.1.0
 DocStringExtensions

docs/Manifest.toml

@@ -3,9 +3,9 @@ uuid = "2a0f44e3-6c83-55bd-87e4-b1978d98bd5f"
 
 [[Compat]]
 deps = ["Base64", "Dates", "DelimitedFiles", "Distributed", "InteractiveUtils", "LibGit2", "Libdl", "LinearAlgebra", "Markdown", "Mmap", "Pkg", "Printf", "REPL", "Random", "Serialization", "SharedArrays", "Sockets", "SparseArrays", "Statistics", "Test", "UUIDs", "Unicode"]
-git-tree-sha1 = "2d9e14d19bad3f9ad5cc5e4cffabc3cfa59de825"
+git-tree-sha1 = "ec61a16eed883ad0cfa002d7489b3ce6d039bb9a"
 uuid = "34da2185-b29b-5c13-b0c7-acf172513d20"
-version = "1.3.0"
+version = "1.4.0"
 
 [[Dates]]
 deps = ["Printf"]
@@ -66,9 +66,9 @@ uuid = "d6f4376e-aef5-505a-96c1-9c027394607a"
 
 [[MathOptInterface]]
 deps = ["Compat", "Unicode"]
-git-tree-sha1 = "6bb3530fb9ed16a2f9324d6de54ec5ab9e5822e0"
+git-tree-sha1 = "e645d549092a3a9405eef089836440dd68feaf6b"
 uuid = "b8f27783-ece8-5eb3-8dc8-9495eed66fee"
-version = "0.5.1"
+version = "0.6.3"
 
 [[Mmap]]
 uuid = "a63ad114-7e13-5084-954f-fe012c677804"

src/model.jl

@@ -13,8 +13,8 @@ mutable struct Model{T, O<:MOI.AbstractOptimizer}
         backend = ParametronMOIModel{T}()
         initialized = false
         objective = Objective(T, @expression zero(AffineFunction{T}))
-        MOI.set!(backend, MOI.ObjectiveSense(), MOI.OptimizationSense(Minimize))
-        MOI.set!(backend, MOI.ObjectiveFunction{typeof(objective.f)}(), objective.f)
+        MOI.set(backend, MOI.ObjectiveSense(), MOI.OptimizationSense(Minimize))
+        MOI.set(backend, MOI.ObjectiveFunction{typeof(objective.f)}(), objective.f)
         constraints = Constraints{T}()
         model_var_to_optimizer = Vector{MOI.VariableIndex}()
         new{T, O}(params, backend, optimizer, initialized, objective, constraints, model_var_to_optimizer)
@@ -48,7 +48,7 @@ Create a new decision variable (`Variable`) associated with the model.
 """
 function Variable(m::Model)
     m.initialized && error("Model has already been initialized.")
-    index = MOI.addvariable!(m.backend)
+    index = MOI.add_variable(m.backend)
     Variable(index)
 end
 
@@ -60,38 +60,38 @@ Set the objective function and optimization sense (`Minimize` or `Maximize`).
 function setobjective!(m::Model{T}, sense::Sense, expr) where T
     m.initialized && error("Model was already initialized. setobjective! can only be called before initialization.")
     m.objective = Objective(T, expr)
-    MOI.set!(m.backend, MOI.ObjectiveSense(), MOI.OptimizationSense(sense))
-    MOI.set!(m.backend, MOI.ObjectiveFunction{typeof(m.objective.f)}(), m.objective.f)
+    MOI.set(m.backend, MOI.ObjectiveSense(), MOI.OptimizationSense(sense))
+    MOI.set(m.backend, MOI.ObjectiveFunction{typeof(m.objective.f)}(), m.objective.f)
     nothing
 end
 
-function addconstraint!(m::Model, constraint::Constraint)
-    m.initialized && error("Model was already initialized. addconstraint! can only be called before initialization.")
-    constraint.modelindex = MOI.addconstraint!(m.backend, constraint.f, constraint.set)
+function add_constraint(m::Model, constraint::Constraint)
+    m.initialized && error("Model was already initialized. add_constraint can only be called before initialization.")
+    constraint.modelindex = MOI.add_constraint(m.backend, constraint.f, constraint.set)
     push!(m.constraints, constraint)
     nothing
 end
 
 _add_nonnegative_constraint!(m::Model{T}, expr, val::AffineFunction) where {T} =
-    addconstraint!(m, Constraint(T, expr, MOI.GreaterThan(zero(T))))
+    add_constraint(m, Constraint(T, expr, MOI.GreaterThan(zero(T))))
 _add_nonpositive_constraint!(m::Model{T}, expr, val::AffineFunction) where {T} =
-    addconstraint!(m, Constraint(T, expr, MOI.LessThan(zero(T))))
+    add_constraint(m, Constraint(T, expr, MOI.LessThan(zero(T))))
 _add_zero_constraint!(m::Model{T}, expr, val::AffineFunction) where {T} =
-    addconstraint!(m, Constraint(T, expr, MOI.EqualTo(zero(T))))
+    add_constraint(m, Constraint(T, expr, MOI.EqualTo(zero(T))))
 
 _add_nonnegative_constraint!(m::Model{T}, expr, val::AbstractVector{<:AffineFunction}) where {T} =
-    addconstraint!(m, Constraint(T, expr, MOI.Nonnegatives(length(val))))
+    add_constraint(m, Constraint(T, expr, MOI.Nonnegatives(length(val))))
 _add_nonpositive_constraint!(m::Model{T}, expr, val::AbstractVector{<:AffineFunction}) where {T} =
-    addconstraint!(m, Constraint(T, expr, MOI.Nonpositives(length(val))))
+    add_constraint(m, Constraint(T, expr, MOI.Nonpositives(length(val))))
 _add_zero_constraint!(m::Model{T}, expr, val::AbstractVector{<:AffineFunction}) where {T} =
-    addconstraint!(m, Constraint(T, expr, MOI.Zeros(length(val))))
+    add_constraint(m, Constraint(T, expr, MOI.Zeros(length(val))))
 
 add_nonnegative_constraint!(m::Model, expr) = _add_nonnegative_constraint!(m, expr, evalarg(expr))
 add_nonpositive_constraint!(m::Model, expr) = _add_nonpositive_constraint!(m, expr, evalarg(expr))
 add_zero_constraint!(m::Model, expr) = _add_zero_constraint!(m, expr, evalarg(expr))
 
-add_integer_constraint!(m::Model, x::Variable) = addconstraint!(m, Constraint(MOI.SingleVariable(MOI.VariableIndex(x)), MOI.Integer()))
-add_binary_constraint!(m::Model, x::Variable) = addconstraint!(m, Constraint(MOI.SingleVariable(MOI.VariableIndex(x)), MOI.ZeroOne()))
+add_integer_constraint!(m::Model, x::Variable) = add_constraint(m, Constraint(MOI.SingleVariable(MOI.VariableIndex(x)), MOI.Integer()))
+add_binary_constraint!(m::Model, x::Variable) = add_constraint(m, Constraint(MOI.SingleVariable(MOI.VariableIndex(x)), MOI.ZeroOne()))
 
 function mapindices!(m::Model, idxmap)
     mapindices!(m.constraints, idxmap)
@@ -111,7 +111,7 @@ Users should generally not need to call this function directly, as it is automat
 called the first time [`solve!`](@ref) is called on a `Model`.
 """
 @noinline function initialize!(m::Model)
-    indexmap = MOI.copy!(m.optimizer, m.backend)
+    indexmap = MOI.copy_to(m.optimizer, m.backend)
     mapindices!(m, indexmap)
     m.initialized = true
     nothing

src/moi_interop.jl

@@ -1,13 +1,13 @@
 # MOI backend AbstractModel
 MOIU.@model(ParametronMOIModel, # modelname
-    (ZeroOne, Integer), # scalarsets
-    (LessThan, GreaterThan, EqualTo), # typedscalarsets
-    (Zeros, Nonnegatives, Nonpositives), # vectorsets
+    (MOI.ZeroOne, MOI.Integer), # scalarsets
+    (MOI.LessThan, MOI.GreaterThan, MOI.EqualTo), # typedscalarsets
+    (MOI.Zeros, MOI.Nonnegatives, MOI.Nonpositives), # vectorsets
     (), # typedvectorsets
-    (SingleVariable,), # scalarfunctions
-    (ScalarAffineFunction,), # typedscalarfunctions
+    (MOI.SingleVariable,), # scalarfunctions
+    (MOI.ScalarAffineFunction,), # typedscalarfunctions
     (), # vectorfunctions
-    (VectorAffineFunction,) # typedvectorfunctions
+    (MOI.VectorAffineFunction,) # typedvectorfunctions
 )
 
 
@@ -127,7 +127,7 @@ end
 
 function update!(objective::Objective{E, F}, optimizer::MOI.AbstractOptimizer, varmap) where {E, F}
     update!(objective.f, objective.expr(), varmap)
-    MOI.set!(optimizer, MOI.ObjectiveFunction{F}(), objective.f)
+    MOI.set(optimizer, MOI.ObjectiveFunction{F}(), objective.f)
     nothing
 end
 
@@ -160,7 +160,7 @@ end
 
 function update!(constraint::Constraint, optimizer::MOI.AbstractOptimizer, varmap)
     update!(constraint.f, constraint.expr(), varmap)
-    MOI.set!(optimizer, MOI.ConstraintFunction(), constraint.optimizerindex, constraint.f)
+    MOI.set(optimizer, MOI.ConstraintFunction(), constraint.optimizerindex, constraint.f)
     nothing
 end
 update!(constraint::Constraint{Nothing}, optimizer::MOI.AbstractOptimizer, varmap) = nothing

test/model.jl

@@ -4,7 +4,8 @@ using Test
 using Random
 using LinearAlgebra
 using Parametron
-using OSQP.MathOptInterfaceOSQP
+using OSQP
+using OSQP.MathOptInterfaceOSQP: OSQPSettings
 using GLPK
 using StaticArrays: SVector
 
@@ -13,12 +14,12 @@ import MathOptInterface
 const MOI = MathOptInterface
 
 function defaultoptimizer()
-    optimizer = OSQPOptimizer()
-    MOI.set!(optimizer, OSQPSettings.Verbose(), false)
-    MOI.set!(optimizer, OSQPSettings.EpsAbs(), 1e-8)
-    MOI.set!(optimizer, OSQPSettings.EpsRel(), 1e-16)
-    MOI.set!(optimizer, OSQPSettings.MaxIter(), 10000)
-    MOI.set!(optimizer, OSQPSettings.AdaptiveRhoInterval(), 25) # required for deterministic behavior
+    optimizer = OSQP.Optimizer()
+    MOI.set(optimizer, OSQPSettings.Verbose(), false)
+    MOI.set(optimizer, OSQPSettings.EpsAbs(), 1e-8)
+    MOI.set(optimizer, OSQPSettings.EpsRel(), 1e-16)
+    MOI.set(optimizer, OSQPSettings.MaxIter(), 10000)
+    MOI.set(optimizer, OSQPSettings.AdaptiveRhoInterval(), 25) # required for deterministic behavior
     optimizer
 end
 
@@ -235,11 +236,11 @@ end
 glpk_works = false
 try
     optimizer = GLPK.Optimizer()
-    x = MOI.addvariable!(optimizer)
+    x = MOI.add_variable(optimizer)
     f = MOI.ScalarAffineFunction([MOI.ScalarAffineTerm(1.0, x)], 0.0)
     s = MOI.GreaterThan(0.0)
-    ci = MOI.addconstraint!(optimizer, f, s)
-    MOI.set!(optimizer, MOI.ConstraintFunction(), ci, f)
+    ci = MOI.add_constraint(optimizer, f, s)
+    MOI.set(optimizer, MOI.ConstraintFunction(), ci, f)
     global glpk_works = true
 catch e
     if !(e isa MOI.UnsupportedAttribute{MOI.ConstraintFunction})