Remove acronyms (#445)

Author: odow

Project.toml

@@ -1,7 +1,7 @@
 name = "Pajarito"
 uuid = "2f354839-79df-5901-9f0a-cdb2aac6fe30"
-repo = "https://github.com/jump-dev/Pajarito.jl.git"
 authors = ["Chris Coey <coey.chris@gmail.com>"]
+repo = "https://github.com/jump-dev/Pajarito.jl.git"
 version = "0.8.1"
 
 [deps]

src/Cones/Cones.jl

@@ -9,9 +9,7 @@ module Cones
 
 import LinearAlgebra
 import JuMP
-const MOI = JuMP.MOI
-const VR = JuMP.VariableRef
-const AE = JuMP.AffExpr
+import MathOptInterface as MOI
 
 import Pajarito: Cache, Optimizer
 
@@ -35,15 +33,15 @@ const OACone = Union{
     MOI.PositiveSemidefiniteConeTriangle,
 }
 
-setup_auxiliary(::Cache, ::Optimizer) = VR[]
+setup_auxiliary(::Cache, ::Optimizer) = JuMP.VariableRef[]
 
 extend_start(::Cache, ::Vector{Float64}, ::Optimizer) = Float64[]
 
 num_ext_variables(::Cache) = 0
 
 function dot_expr(
     z::AbstractVecOrMat{Float64},
-    vars::AbstractVecOrMat{<:Union{VR,AE}},
+    vars::AbstractVecOrMat{<:Union{JuMP.VariableRef,JuMP.AffExpr}},
     opt::Optimizer,
 )
     return JuMP.@expression(opt.oa_model, LinearAlgebra.dot(z, vars))

src/Cones/exponentialcone.jl

@@ -13,11 +13,15 @@ equivalently (p < 0, q ≥ p * (log(r / -p) + 1))
 =#
 
 mutable struct ExponentialCone <: Cache
-    oa_s::Vector{AE}
+    oa_s::Vector{JuMP.AffExpr}
     ExponentialCone() = new()
 end
 
-function create_cache(oa_s::Vector{AE}, ::MOI.ExponentialCone, ::Optimizer)
+function create_cache(
+    oa_s::Vector{JuMP.AffExpr},
+    ::MOI.ExponentialCone,
+    ::Optimizer,
+)
     @assert length(oa_s) == 3
     cache = ExponentialCone()
     cache.oa_s = oa_s
@@ -51,13 +55,13 @@ function get_subp_cuts(
     if p > 0 || r < 0
         # z ∉ K
         @warn("exponential cone dual vector violates variable bounds")
-        return AE[]
+        return JuMP.AffExpr[]
     end
     q = z[2]
     (u, v, w) = cache.oa_s
 
     if p > -1e-12
-        return AE[]
+        return JuMP.AffExpr[]
     elseif r / -p > 1e-8
         # strengthened cut is (p, p * (log(r / -p) + 1), r)
         q = p * (log(r / -p) + 1)
@@ -67,7 +71,7 @@ function get_subp_cuts(
         r = -p * exp(q / p - 1)
         cut = JuMP.@expression(opt.oa_model, p * u + q * v + r * w)
     else
-        return AE[]
+        return JuMP.AffExpr[]
     end
     return [cut]
 end
@@ -95,7 +99,7 @@ function get_sep_cuts(
             q = -log(ℯ / 2 * r)
             cut = JuMP.@expression(opt.oa_model, -u + q * v + r * w)
         else
-            return AE[]
+            return JuMP.AffExpr[]
         end
     elseif ws / vs > 1e-8 && us - vs * log(ws / vs) > opt.tol_feas
         # vs and ws not near zero
@@ -108,7 +112,7 @@ function get_sep_cuts(
         q = (us - vs) / vs * -p
         cut = JuMP.@expression(opt.oa_model, p * u + q * v + w)
     else
-        return AE[]
+        return JuMP.AffExpr[]
     end
     return [cut]
 end

src/Cones/positivesemidefiniteconetriangle.jl

@@ -9,14 +9,14 @@ w ⪰ 0
 =#
 
 mutable struct PositiveSemidefiniteConeTriangle <: Cache
-    oa_s::Vector{AE}
+    oa_s::Vector{JuMP.AffExpr}
     d::Int
-    W::Matrix{<:Union{VR,AE}}
+    W::Matrix{<:Union{JuMP.VariableRef,JuMP.AffExpr}}
     PositiveSemidefiniteConeTriangle() = new()
 end
 
 function create_cache(
-    oa_s::Vector{AE},
+    oa_s::Vector{JuMP.AffExpr},
     moi_cone::MOI.PositiveSemidefiniteConeTriangle,
     ::Optimizer,
 )
@@ -57,7 +57,7 @@ function get_subp_cuts(
     # strengthened cuts from eigendecomposition are λᵢ * rᵢ * rᵢ'
     R = vec_to_symm(cache.d, z)
     F = LinearAlgebra.eigen!(LinearAlgebra.Symmetric(R, :U), 1e-9, Inf)
-    isempty(F.values) && return AE[]
+    isempty(F.values) && return JuMP.AffExpr[]
     R_eig = F.vectors * LinearAlgebra.Diagonal(sqrt.(F.values))
     return _get_cuts(R_eig, cache, opt)
 end
@@ -74,7 +74,7 @@ function get_sep_cuts(
         -Inf,
         -opt.tol_feas,
     )
-    isempty(F.values) && return AE[]
+    isempty(F.values) && return JuMP.AffExpr[]
     return _get_cuts(F.vectors, cache, opt)
 end
 
@@ -85,7 +85,7 @@ function _get_cuts(
 )
     # cuts from eigendecomposition are rᵢ * rᵢ'
     W = cache.W
-    cuts = AE[]
+    cuts = JuMP.AffExpr[]
     for i in 1:size(R_eig, 2)
         @views r_i = R_eig[:, i]
         R_i = r_i * r_i'

src/Cones/powercone.jl

@@ -14,11 +14,15 @@ equivalently (q > 0, p ≥ t / (1-t) * q * |(1-t) * r / q|^(1/t))
 
 mutable struct PowerCone <: Cache
     t::Real
-    oa_s::Vector{AE}
+    oa_s::Vector{JuMP.AffExpr}
     PowerCone() = new()
 end
 
-function create_cache(oa_s::Vector{AE}, moi_cone::MOI.PowerCone, ::Optimizer)
+function create_cache(
+    oa_s::Vector{JuMP.AffExpr},
+    moi_cone::MOI.PowerCone,
+    ::Optimizer,
+)
     @assert length(oa_s) == 3
     cache = PowerCone()
     cache.t = moi_cone.exponent
@@ -48,7 +52,7 @@ function get_subp_cuts(z::Vector{Float64}, cache::PowerCone, opt::Optimizer)
     if min(p, q) < 0
         # z ∉ K
         @warn("dual vector is not in the dual cone")
-        return AE[]
+        return JuMP.AffExpr[]
     end
 
     # strengthened cut is (p, q, sign(r) * (p/t)^t * (q/(1-t))^(1-t))
@@ -67,7 +71,7 @@ function get_sep_cuts(s::Vector{Float64}, cache::PowerCone, opt::Optimizer)
     # check s ∉ K
     t = cache.t
     if us >= 0 && vs >= 0 && (us^t * vs^(1 - t) - abs(ws)) > -opt.tol_feas
-        return AE[]
+        return JuMP.AffExpr[]
     end
 
     # gradient cut is (t * (us/vs)^(t-1), (1-t) * (us/vs)^t, -sign(ws))

src/Cones/secondordercone.jl

@@ -13,14 +13,14 @@ linear and 3-dim rotated second order cone constraints
 =#
 
 mutable struct SecondOrderCone{E<:NatExt} <: Cache
-    oa_s::Vector{AE}
+    oa_s::Vector{JuMP.AffExpr}
     d::Int
-    ϕ::Vector{VR}
+    ϕ::Vector{JuMP.VariableRef}
     SecondOrderCone{E}() where {E<:NatExt} = new{E}()
 end
 
 function create_cache(
-    oa_s::Vector{AE},
+    oa_s::Vector{JuMP.AffExpr},
     moi_cone::MOI.SecondOrderCone,
     opt::Optimizer,
 )
@@ -52,7 +52,7 @@ function get_sep_cuts(
     ws_norm = LinearAlgebra.norm(ws)
     # check s ∉ K
     if us - ws_norm > -opt.tol_feas
-        return AE[]
+        return JuMP.AffExpr[]
     end
 
     # cut is (1, -ws / ‖ws‖)
@@ -84,7 +84,7 @@ function _get_cuts(
     opt::Optimizer,
 )
     # strengthened cut is (‖r‖, r)
-    clean_array!(r) && return AE[]
+    clean_array!(r) && return JuMP.AffExpr[]
     p = LinearAlgebra.norm(r)
     u = cache.oa_s[1]
     @views w = cache.oa_s[2:end]
@@ -142,12 +142,12 @@ function _get_cuts(
     cache::SecondOrderCone{Ext},
     opt::Optimizer,
 )
-    clean_array!(r) && return AE[]
+    clean_array!(r) && return JuMP.AffExpr[]
     p = LinearAlgebra.norm(r)
     u = cache.oa_s[1]
     @views w = cache.oa_s[2:end]
     ϕ = cache.ϕ
-    cuts = AE[]
+    cuts = JuMP.AffExpr[]
     for i in 1:(cache.d)
         r_i = r[i]
         iszero(r_i) && continue

src/JuMP_tools.jl

@@ -5,7 +5,7 @@
 
 # tools for JuMP functions
 
-function add_cuts(cuts::Vector{AE}, opt::Optimizer, viol_only::Bool)
+function add_cuts(cuts::Vector{JuMP.AffExpr}, opt::Optimizer, viol_only::Bool)
     if viol_only
         # filter out unviolated cuts
         cuts = filter(cut -> get_value(cut, opt.lazy_cb) < -opt.tol_feas, cuts)
@@ -16,22 +16,28 @@ function add_cuts(cuts::Vector{AE}, opt::Optimizer, viol_only::Bool)
     return !isempty(cuts)
 end
 
-function _add_cuts(cuts::Vector{AE}, model::JuMP.Model, ::Nothing)
+function _add_cuts(cuts::Vector{JuMP.AffExpr}, model::JuMP.Model, ::Nothing)
     JuMP.@constraint(model, cuts .>= 0)
     return
 end
 
-function _add_cuts(cuts::Vector{AE}, model::JuMP.Model, cb)
+function _add_cuts(cuts::Vector{JuMP.AffExpr}, model::JuMP.Model, cb)
     cons = JuMP.@build_constraint(cuts .>= 0)
     MOI.submit.(model, MOI.LazyConstraint(cb), cons)
     return
 end
 
-get_value(expr::Union{VR,AE}, ::Nothing) = JuMP.value(expr)
+function get_value(expr::Union{JuMP.VariableRef,JuMP.AffExpr}, ::Nothing)
+    return JuMP.value(expr)
+end
 
-get_value(expr::Union{VR,AE}, cb) = JuMP.callback_value(cb, expr)
+function get_value(expr::Union{JuMP.VariableRef,JuMP.AffExpr}, cb)
+    return JuMP.callback_value(cb, expr)
+end
 
-get_value(exprs::Vector{<:Union{VR,AE}}, cb) = [get_value(e, cb) for e in exprs]
+function get_value(exprs::Vector{<:Union{JuMP.VariableRef,JuMP.AffExpr}}, cb)
+    return [get_value(e, cb) for e in exprs]
+end
 
 function check_set_time_limit(opt::Optimizer, model::JuMP.Model)
     time_left = opt.time_limit - time() + opt.solve_time