Merge 3eda667 into 8b4d362

.gitignore

@@ -0,0 +1 @@
+Manifest.toml

.travis.yml

@@ -1,17 +1,15 @@
 language: julia
+coveralls: true
 os:
     - linux
 julia:
-    - 0.5
-    - nightly
+    - 1.0
+    - 1.1
+    - 1.2
+    - 1.3
 notifications:
     email: false
 sudo: false
 addons:
     apt_packages:
         - libgmp-dev
-script:
-    - if [[ -a .git/shallow ]]; then git fetch --unshallow; fi
-    - julia --check-bounds=yes -e 'Pkg.init(); Pkg.add("JuMP"); Pkg.clone(pwd()); Pkg.build("JuMPChance"); Pkg.test("JuMPChance"; coverage=true)'
-after_success:
-    - julia -e 'cd(Pkg.dir("JuMPChance")); Pkg.add("Coverage"); using Coverage; Coveralls.submit(Coveralls.process_folder())'

Project.toml

@@ -0,0 +1,23 @@
+name = "JuMPChance"
+uuid = "bbd82366-0c69-5eef-bed9-5a0dd17fc720"
+
+[deps]
+Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
+ECOS = "e2685f51-7e38-5353-a97d-a921fd2c8199"
+JuMP = "4076af6c-e467-56ae-b986-b466b2749572"
+MathProgBase = "fdba3010-5040-5b88-9595-932c9decdf73"
+
+[compat]
+Distributions = "0.21"
+ECOS = "0.10"
+JuMP = "0.18"
+MathProgBase = "0.7.7"
+julia = "1"
+
+[extras]
+GLPKMathProgInterface = "3c7084bd-78ad-589a-b5bb-dbd673274bea"
+Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
+Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
+
+[targets]
+test = ["GLPKMathProgInterface", "Random", "Test"]

appveyor.yml

@@ -1,9 +1,23 @@
 environment:
   matrix:
-  - JULIAVERSION: "julialang/bin/winnt/x86/0.5/julia-0.5-latest-win32.exe"
-  - JULIAVERSION: "julialang/bin/winnt/x64/0.5/julia-0.5-latest-win64.exe"
-  - JULIAVERSION: "julianightlies/bin/winnt/x86/julia-latest-win32.exe"
-  - JULIAVERSION: "julianightlies/bin/winnt/x64/julia-latest-win64.exe"
+  - julia_version: 1.0
+  - julia_version: 1.1
+  - julia_version: 1.2
+  - julia_version: 1.3
+
+platform:
+  - x86 # 32-bit
+  - x64 # 64-bit
+
+# This is left as an example for the next big version switch.
+#matrix:
+#  allow_failures:
+#  - julia_version: latest
+
+branches:
+  only:
+    - master
+    - /release-.*/
 
 notifications:
   - provider: Email
@@ -12,17 +26,12 @@ notifications:
     on_build_status_changed: false
 
 install:
-# Download most recent Julia Windows binary
-  - ps: (new-object net.webclient).DownloadFile(
-        $("http://s3.amazonaws.com/"+$env:JULIAVERSION),
-        "C:\projects\julia-binary.exe")
-# Run installer silently, output to C:\projects\julia
-  - C:\projects\julia-binary.exe /S /D=C:\projects\julia
+  - ps: iex ((new-object net.webclient).DownloadString("https://raw.githubusercontent.com/JuliaCI/Appveyor.jl/version-1/bin/install.ps1"))
 
 build_script:
-# Need to convert from shallow to complete for Pkg.clone to work
-  - IF EXIST .git\shallow (git fetch --unshallow)
-  - C:\projects\julia\bin\julia -e "versioninfo(); Pkg.clone(pwd(), \"JuMPChance\"); Pkg.build(\"JuMPChance\");"
+  - echo "%JL_BUILD_SCRIPT%"
+  - C:\julia\bin\julia -e "%JL_BUILD_SCRIPT%"
 
 test_script:
-  - C:\projects\julia\bin\julia -e "Pkg.test(\"JuMPChance\")"
+  - echo "%JL_TEST_SCRIPT%"
+  - C:\julia\bin\julia -e "%JL_TEST_SCRIPT%"

src/JuMPChance.jl

@@ -15,7 +15,7 @@ export ChanceModel,
     @indepnormal
 
 # stores extension data inside JuMP Model
-type CCData
+mutable struct CCData
     # pure chance constraints
     chanceconstr
     # robust chance constraints
@@ -45,7 +45,7 @@ end
 
 
 # pointer back to JuMP model and r.v. index
-type IndepNormal <: JuMP.AbstractJuMPScalar
+mutable struct IndepNormal <: JuMP.AbstractJuMPScalar
     m::Model
     idx::Int
 end
@@ -71,19 +71,13 @@ function getmean(v::IndepNormal)
     return ccdata.RVmeans[v.idx]
 end
 
-@Base.deprecate getMean getmean
-
 function getvariance(v::IndepNormal)
     ccdata = getCCData(v.m)
     return ccdata.RVvars[v.idx]
 end
 
-@Base.deprecate getVariance getvariance
-
 getstdev(v::IndepNormal) = sqrt(getvariance(v))
 
-@Base.deprecate getStdev getstdev
-
 const CCAffExpr = JuMP.GenericAffExpr{AffExpr,IndepNormal}
 
 CCAffExpr() = CCAffExpr(IndepNormal[],AffExpr[],AffExpr())
@@ -132,7 +126,7 @@ function Base.show(io::IO,a::RandomAffExpr)
     print(io, string(join(strs," + "), " + ", string(a.constant)))
 end
 
-type ChanceConstr <: JuMP.AbstractConstraint
+mutable struct ChanceConstr <: JuMP.AbstractConstraint
     ccexpr::CCAffExpr
     sense::Symbol # :(<=) or :(>=), right-hand side assumed to be zero
     with_probability::Float64 # with this probability *or greater*
@@ -194,7 +188,7 @@ function JuMP.show(io::IO,c::ChanceConstr)
     end
 end
 
-type TwoSideChanceConstr <: JuMP.AbstractConstraint
+mutable struct TwoSideChanceConstr <: JuMP.AbstractConstraint
     ccexpr::CCAffExpr
     lb::AffExpr
     ub::AffExpr

src/macros.jl

@@ -2,9 +2,8 @@ using Base.Meta
 
 macro indepnormal(m, x, mean, var)
     m = esc(m)
-    kwsymbol = VERSION < v"0.6.0-dev.1934" ? :kw : :(=) # changed by julia PR #19868
-    @assert isexpr(mean,kwsymbol) && mean.args[1] == :mean
-    @assert isexpr(var,kwsymbol) && var.args[1] == :var
+    @assert isexpr(mean, :(=)) && mean.args[1] == :mean
+    @assert isexpr(var, :(=)) && var.args[1] == :var
     mean = esc(mean.args[2])
     var = esc(var.args[2])
 
@@ -41,12 +40,6 @@ macro indepnormal(m, x, mean, var)
     end
 end
 
-macro defIndepNormal(m, x, mean, var)
-    Base.warn_once("@defIndepNormal is deprecated. Use @indepnormal instead")
-    return :(@indepnormal($(esc(m)),$(esc(x)),$(esc(mean)),$(esc(var))))
-end
-export @defIndepNormal
-
 # Extensions to make JuMP macros work with chance constraints
 
 function JuMP.constructconstraint!(faff::CCAffExpr, sense::Symbol)

src/solve.jl

@@ -130,7 +130,7 @@ function solvehook(m::Model; suppress_warnings=false, method=:Refomulate,lineari
                 end
                 continue
             end
-            
+
             # add auxiliary variables for variance of each term
             varterm = @variable(m, [1:nterms])
             defvar = @constraint(m, [i=1:nterms], varterm[i] == getstdev(ccexpr.vars[i])*ccexpr.coeffs[i])
@@ -198,7 +198,7 @@ function solvecc_cuts(m::Model, suppress_warnings::Bool, probability_tolerance::
     twosidechancevarterm = Dict()
     linearizechanceconstr = Int[]
     linearizetwosidechanceconstr = Int[]
-    
+
     # one sided chance constraints case
     for i in 1:nchanceconstr
         cc = ccdata.chanceconstr[i]
@@ -229,7 +229,7 @@ function solvecc_cuts(m::Model, suppress_warnings::Bool, probability_tolerance::
             defvar = @constraint(m, [k=1:nterms], chancevarterm[i][k] == getstdev(ccexpr.vars[k])*ccexpr.coeffs[k])
         end
     end
-    
+
     # Two sided chance constraints with :Cuts option
     lbvar = @variable(m, [1:ntwosidechanceconstr])
     ubvar = @variable(m, [1:ntwosidechanceconstr])
@@ -293,7 +293,7 @@ function solvecc_cuts(m::Model, suppress_warnings::Bool, probability_tolerance::
 
         nviol = 0
         nviol_obj = 0
-        
+
         # check violated chance constraints
         for i in linearizechanceconstr
             cc::ChanceConstr = ccdata.chanceconstr[i]
@@ -338,7 +338,7 @@ function solvecc_cuts(m::Model, suppress_warnings::Bool, probability_tolerance::
                 end
             end
         end
-        
+
         # check violated two sided chance constraint
         for i in linearizetwosidechanceconstr
             cc::TwoSideChanceConstr = ccdata.twosidechanceconstr[i]
@@ -401,7 +401,7 @@ function solvecc_cuts(m::Model, suppress_warnings::Bool, probability_tolerance::
         end
         return nviol, nviol_obj
     end
-    
+
     do_lazy = has_integers && lazy_constraints
     (debug && !do_lazy) && println("Solving deterministic model")
 
@@ -415,7 +415,7 @@ function solvecc_cuts(m::Model, suppress_warnings::Bool, probability_tolerance::
         #toc()
         return status
     end
-    
+
     if status != :Optimal
         return status
     end
@@ -425,7 +425,7 @@ function solvecc_cuts(m::Model, suppress_warnings::Bool, probability_tolerance::
     while niter < iteration_limit
 
         nviol, nviol_obj = addcuts(nothing)
- 
+
         if nviol == 0 && nviol_obj == 0
             silent || println("Done after $niter iterations")
             #toc()
@@ -511,11 +511,11 @@ function solverobustcc_cuts(m::Model, suppress_warnings::Bool, probability_toler
     debug && println("Variance deviations: ", vars_deviation)
 
     # TODO: special handling for quadratic objectives
-    
+
     debug && println("Solving deterministic model")
 
     status = solve(m, suppress_warnings=suppress_warnings, ignore_solve_hook=true)
-    
+
     if status != :Optimal
         return status
     end
@@ -656,14 +656,14 @@ function solverobustcc_cuts(m::Model, suppress_warnings::Bool, probability_toler
 end
 
 # We can remove the code for IndexedVector once JuMP issue #340 is resolved.
-type IndexedVector{T}
+mutable struct IndexedVector{T}
     elts::Vector{T}
     nzidx::Vector{Int}
     nnz::Int
     empty::BitArray{1}
 end
 
-IndexedVector{T}(::Type{T},n::Integer) = IndexedVector(zeros(T,n),zeros(Int,n),0,trues(n))
+IndexedVector(::Type{T},n::Integer) where {T} = IndexedVector(zeros(T,n),zeros(Int,n),0,trues(n))
 
 function addelt!(v::IndexedVector{AffExpr},i::Integer,val::AffExpr)
     if v.empty[i]  # new index
@@ -676,7 +676,7 @@ function addelt!(v::IndexedVector{AffExpr},i::Integer,val::AffExpr)
     return nothing
 end
 
-function addelt!{T}(v::IndexedVector{T},i::Integer,val::T)
+function addelt!(v::IndexedVector{T},i::Integer,val::T) where {T}
     if v.empty[i]  # new index
         v.elts[i] = val
         v.nzidx[v.nnz += 1] = i
@@ -687,7 +687,7 @@ function addelt!{T}(v::IndexedVector{T},i::Integer,val::T)
     return nothing
 end
 
-function Base.empty!{T}(v::IndexedVector{T})
+function Base.empty!(v::IndexedVector{T}) where {T}
     elts = v.elts
     nzidx = v.nzidx
     empty = v.empty
@@ -713,7 +713,7 @@ end
 # Adapted from JuMP:
 # returns a GenericAffExpr with terms merged
 # assume that v is zero'd
-function merge_duplicates{CoefType <: JuMP.GenericAffExpr}(aff::JuMP.GenericAffExpr{CoefType,IndepNormal}, v::IndexedVector{CoefType}, counts::IndexedVector{Int}, m::Model)
+function merge_duplicates(aff::JuMP.GenericAffExpr{CoefType,IndepNormal}, v::IndexedVector{CoefType}, counts::IndexedVector{Int}, m::Model) where {CoefType <: JuMP.GenericAffExpr}
     ccdata = getCCData(m)
 
     resize!(v, ccdata.numRVs)
@@ -734,8 +734,8 @@ function merge_duplicates{CoefType <: JuMP.GenericAffExpr}(aff::JuMP.GenericAffE
     for ind in 1:length(aff.coeffs)
         addelt!(v, aff.vars[ind].idx, aff.coeffs[ind])
     end
-    vars = Array{IndepNormal}(v.nnz)
-    coeffs = Array{CoefType}(v.nnz)
+    vars = Array{IndepNormal}(undef, v.nnz)
+    coeffs = Array{CoefType}(undef, v.nnz)
     for i in 1:v.nnz
         idx = v.nzidx[i]
         vars[i] = IndepNormal(m,idx)
@@ -748,17 +748,17 @@ function merge_duplicates{CoefType <: JuMP.GenericAffExpr}(aff::JuMP.GenericAffE
 
 end
 
-function merge_duplicates{CoefType <: Number}(aff::JuMP.GenericAffExpr{CoefType,IndepNormal}, v::IndexedVector{CoefType}, m::Model)
+function merge_duplicates(aff::JuMP.GenericAffExpr{CoefType,IndepNormal}, v::IndexedVector{CoefType}, m::Model) where {CoefType <: Number}
     ccdata = getCCData(m)
 
     resize!(v, ccdata.numRVs)
     for ind in 1:length(aff.coeffs)
         var = aff.vars[ind]
-        is(var.m, m) || error("Variable does not belong to this model")
+        var.m === m || error("Variable does not belong to this model")
         addelt!(v, aff.vars[ind].idx, aff.coeffs[ind])
     end
-    vars = Array{IndepNormal}(v.nnz)
-    coeffs = Array{CoefType}(v.nnz)
+    vars = Array{IndepNormal}(undef, v.nnz)
+    coeffs = Array{CoefType}(undef, v.nnz)
     for i in 1:v.nnz
         idx = v.nzidx[i]
         vars[i] = IndepNormal(m,idx)