Merge pull request #89 from JuliaOpt/bl/nonnegative

Simplify thanks to NonposToNoneg bridge
jump-dev · Feb 8, 2019 · 32b7b5e · 32b7b5e
2 parents 41e14c7 + 235d273
commit 32b7b5e
Show file tree

Hide file tree

Showing 3 changed files with 35 additions and 28 deletions.
diff --git a/REQUIRE b/REQUIRE
@@ -1,5 +1,5 @@
 julia 0.6
 MathProgBase 0.5 0.8
-MathOptInterface 0.8.1 0.9
+MathOptInterface 0.8.2 0.9
 Compat 0.68
 BinaryProvider 0.3
diff --git a/src/MOI_wrapper.jl b/src/MOI_wrapper.jl
@@ -6,8 +6,8 @@ const VI = MOI.VariableIndex
 const MOIU = MOI.Utilities
 
 const SF = Union{MOI.VectorOfVariables, MOI.VectorAffineFunction{Float64}}
-const SS = Union{MOI.Zeros, MOI.Nonnegatives, MOI.Nonpositives,
-                 MOI.SecondOrderCone, MOI.ExponentialCone}
+const SS = Union{MOI.Zeros, MOI.Nonnegatives, MOI.SecondOrderCone,
+                 MOI.ExponentialCone}
 
 struct Solution
     ret_val::Int
@@ -97,17 +97,15 @@ end
 
 using Compat.SparseArrays
 
-const LPCones = Union{MOI.Nonnegatives, MOI.Nonpositives}
-
 # Computes cone dimensions
 constroffset(cone::ConeData, ci::CI{<:MOI.AbstractFunction, MOI.Zeros}) = ci.value
 function _allocate_constraint(cone::ConeData, f, s::MOI.Zeros)
     ci = cone.f
     cone.f += MOI.dimension(s)
     ci
 end
-constroffset(cone::ConeData, ci::CI{<:MOI.AbstractFunction, <:LPCones}) = ci.value
-function _allocate_constraint(cone::ConeData, f, s::LPCones)
+constroffset(cone::ConeData, ci::CI{<:MOI.AbstractFunction, MOI.Nonnegatives}) = ci.value
+function _allocate_constraint(cone::ConeData, f, s::MOI.Nonnegatives)
     ci = cone.l
     cone.l += MOI.dimension(s)
     ci
@@ -131,8 +129,6 @@ function MOIU.allocate_constraint(instance::Optimizer, f::F, s::S) where {F <: M
 end
 
 # Build constraint matrix
-scalecoef(rows, coef, minus, s) = minus ? -coef : coef
-scalecoef(rows, coef, minus, s::Union{MOI.Nonpositives, Type{MOI.Nonpositives}}) = minus ? coef : -coef
 output_index(t::MOI.VectorAffineTerm) = t.output_index
 variable_index_value(t::MOI.ScalarAffineTerm) = t.variable_index.value
 variable_index_value(t::MOI.VectorAffineTerm) = variable_index_value(t.scalar_term)
@@ -142,7 +138,7 @@ constrrows(s::MOI.AbstractVectorSet) = 1:MOI.dimension(s)
 constrrows(instance::Optimizer, ci::CI{<:MOI.AbstractVectorFunction, MOI.Zeros}) = 1:instance.cone.eqnrows[constroffset(instance, ci)]
 constrrows(instance::Optimizer, ci::CI{<:MOI.AbstractVectorFunction, <:MOI.AbstractVectorSet}) = 1:instance.cone.ineqnrows[constroffset(instance, ci)]
 matrix(data::ModelData, s::MOI.Zeros) = data.b, data.IA, data.JA, data.VA
-matrix(data::ModelData, s::Union{LPCones, MOI.SecondOrderCone, MOI.ExponentialCone}) = data.h, data.IG, data.JG, data.VG
+matrix(data::ModelData, s::Union{MOI.Nonnegatives, MOI.SecondOrderCone, MOI.ExponentialCone}) = data.h, data.IG, data.JG, data.VG
 matrix(instance::Optimizer, s) = matrix(instance.data, s)
 MOIU.load_constraint(instance::Optimizer, ci, f::MOI.VectorOfVariables, s) = MOIU.load_constraint(instance, ci, MOI.VectorAffineFunction{Float64}(f), s)
 # ECOS orders differently than MOI the second and third dimension of the exponential cone
@@ -171,10 +167,10 @@ function MOIU.load_constraint(instance::Optimizer, ci, f::MOI.VectorAffineFuncti
     # The ECOS format is b - Ax ∈ cone
     # so minus=false for b and minus=true for A
     b, Is, Js, Vs = matrix(instance, s)
-    b[i] .= scalecoef(rows, orderval(f.constants, s), false, s)
+    b[i] .= orderval(f.constants, s)
     append!(Is, offset .+ orderidx(I, s))
     append!(Js, J)
-    append!(Vs, scalecoef(I, V, true, s))
+    append!(Vs, -V)
 end
 
 function MOIU.allocate_variables(instance::Optimizer, nvars::Integer)
@@ -318,7 +314,7 @@ end
 function MOI.get(instance::Optimizer, ::MOI.ConstraintPrimal, ci::CI{<:MOI.AbstractFunction, S}) where S <: MOI.AbstractSet
     offset = constroffset(instance, ci)
     rows = constrrows(instance, ci)
-    return scalecoef(rows, reorderval(instance.sol.slack[offset .+ rows], S), false, S)
+    return reorderval(instance.sol.slack[offset .+ rows], S)
 end
 
 function MOI.get(instance::Optimizer, ::MOI.DualStatus)
@@ -346,7 +342,7 @@ _dual(instance, ci::CI) = instance.sol.dual_ineq
 function MOI.get(instance::Optimizer, ::MOI.ConstraintDual, ci::CI{<:MOI.AbstractFunction, S}) where S <: MOI.AbstractSet
     offset = constroffset(instance, ci)
     rows = constrrows(instance, ci)
-    scalecoef(rows, reorderval(_dual(instance, ci)[offset .+ rows], S), false, S)
+    return reorderval(_dual(instance, ci)[offset .+ rows], S)
 end
 
 MOI.get(instance::Optimizer, ::MOI.ResultCount) = 1
diff --git a/test/MOI_wrapper.jl b/test/MOI_wrapper.jl
@@ -1,9 +1,24 @@
+using Compat
+using Compat.Test
+
 using MathOptInterface
 const MOI = MathOptInterface
 const MOIT = MOI.Test
+const MOIU = MOI.Utilities
 const MOIB = MOI.Bridges
 
-const MOIU = MOI.Utilities
+import ECOS
+const optimizer = ECOS.Optimizer(verbose=false)
+
+@testset "SolverName" begin
+    @test MOI.get(optimizer, MOI.SolverName()) == "ECOS"
+end
+
+@testset "supports_allocate_load" begin
+    @test MOIU.supports_allocate_load(optimizer, false)
+    @test !MOIU.supports_allocate_load(optimizer, true)
+end
+
 MOIU.@model(ECOSModelData,
             (), (), # No scalar functions
             (MOI.Zeros, MOI.Nonnegatives, MOI.Nonpositives, MOI.SecondOrderCone,
@@ -12,13 +27,18 @@ MOIU.@model(ECOSModelData,
             (), (), # No scalar sets
             (MOI.VectorOfVariables,),
             (MOI.VectorAffineFunction,))
-const optimizer = MOIU.CachingOptimizer(ECOSModelData{Float64}(), ECOS.Optimizer(verbose=false))
+# UniversalFallback is needed for starting values, even if they are ignored by ECOS
+const cache = MOIU.UniversalFallback(ECOSModelData{Float64}())
+const cached = MOIU.CachingOptimizer(cache, optimizer)
+
+# Essential bridges that are needed for all tests
+const bridged = MOIB.Vectorize{Float64}(MOIB.NonposToNonneg{Float64}(cached))
 
 # SOC2 requires 1e-4
 const config = MOIT.TestConfig(atol=1e-4, rtol=1e-4)
 
 @testset "Unit" begin
-    MOIT.unittest(MOIB.SplitInterval{Float64}(MOIB.Vectorize{Float64}(optimizer)),
+    MOIT.unittest(MOIB.SplitInterval{Float64}(bridged),
                   config,
                   [# Quadratic functions are not supported
                    "solve_qcp_edge_cases", "solve_qp_edge_cases",
@@ -27,21 +47,12 @@ const config = MOIT.TestConfig(atol=1e-4, rtol=1e-4)
 end
 
 @testset "Continuous linear problems" begin
-    MOIT.contlineartest(MOIB.SplitInterval{Float64}(MOIB.Vectorize{Float64}(optimizer)),
+    MOIT.contlineartest(MOIB.SplitInterval{Float64}(bridged),
                         config)
 end
 
 @testset "Continuous conic problems" begin
     exclude = ["sdp", "rootdet", "logdet"]
-    MOIT.contconictest(MOIB.GeoMean{Float64}(MOIB.RSOC{Float64}(MOIB.Vectorize{Float64}(optimizer))),
+    MOIT.contconictest(MOIB.GeoMean{Float64}(MOIB.RSOC{Float64}(bridged)),
                        config, exclude)
 end
-
-@testset "SolverName" begin
-    @test MOI.get(optimizer, MOI.SolverName()) == "ECOS"
-end
-
-@testset "supports_allocate_load" begin
-    @test MOIU.supports_allocate_load(optimizer.optimizer, false)
-    @test !MOIU.supports_allocate_load(optimizer.optimizer, true)
-end