Update for JuMP v0.16

README.md

@@ -13,10 +13,6 @@ It is embedded in the [Julia programming language], and is an extension to the [
     - The source code is well-commented, if you'd like to understand more.
   - [Checkout the examples](example/).
 
-#### JuMPeR v0.4
-
-JuMPeR was recently updated to version v0.4. This changed the syntax to match the changes in JuMP v0.13. Unlike JuMP v0.13, there are no deprecation warnings. However, it should generally be a simple find-and-replace, e.g. `@defUnc` to `@uncertain`. See the documentation for examples.
-
 [Julia programming language]: http://julialang.org/
 [JuMP]: https://github.com/JuliaOpt/JuMP.jl
 [JuMPeR]: https://github.com/IainNZ/JuMPeR.jl

REQUIRE

@@ -1,2 +1,3 @@
 julia 0.5
-JuMP 0.14 0.15
+JuMP 0.16.2 0.17
+MathProgBase 0.6.4 0.7

src/solve.jl

@@ -43,7 +43,7 @@ function _solve_robust(rm::Model, suppress_warnings::Bool,
     # 2. Setup for uncertainty sets
     #-------------------------------------------------------------------
     # Prepare to pass through preferences to a sets
-    prefs = Dict{Symbol,Any}([name => value for (name,value) in kwargs])
+    prefs = Dict{Symbol,Any}(name => value for (name,value) in kwargs)
     # Build mapping from uncertainty sets to constraints
     uncsets_to_con_idxs = Dict{AbstractUncertaintySet,Vector{Int}}()
     for idx in 1:length(rmext.constraint_uncsets)

src/uncsets_basic_cut.jl

@@ -103,7 +103,7 @@ function get_worst_case_value(us::BasicUncertaintySet, rm::Model, idx::Int)
     con = rmext.unc_constraints[idx]
     # Update the cutting plane problem's objective, and solve
     cut_sense, unc_obj_coeffs, lhs_const = JuMPeR.build_cut_objective_sparse(rm, con)
-    @objective(us.cut_model, cut_sense, sum{u[2]*us.cut_vars[u[1]], u=unc_obj_coeffs})
+    @objective(us.cut_model, cut_sense, sum(u[2]*us.cut_vars[u[1]] for u=unc_obj_coeffs))
     cut_solve_status = solve(us.cut_model, suppress_warnings=true)
     cut_solve_status != :Optimal &&
         error("BasicUncertaintySet: cutting plane problem is infeasible or unbounded!")

test/REQUIRE

@@ -1,3 +1,4 @@
 BaseTestNext
 GLPKMathProgInterface
+GLPK 0.4 0.4.2
 ECOS

test/adp_inventory.jl

@@ -16,7 +16,7 @@
 using JuMP, JuMPeR
 using BaseTestNext
 
-const TOL = 1e-4
+const TOL = 5e-3
 
 if !(:lp_solvers in names(Main))
     print_with_color(:magenta, "Loading solvers...\n")
@@ -51,19 +51,19 @@ print_with_color(:yellow, "Adaptive Inventory Model...\n")
             @constraint(rm, p[i,t] <= P)
         end
         for i in 1:I
-            @constraint(rm, sum{p[i,t], t=1:T} <= Q)
+            @constraint(rm, sum(p[i,t] for t=1:T) <= Q)
         end
         # Constraint: cannot exceed inventory limits
         for t in 1:T
             @constraint(rm,
-                v1 + sum{p[i,s], i=1:I, s=1:t} - sum{d[s],s=1:t} >= Vmin)
+                v1 + sum(p[i,s] for i=1:I, s=1:t) - sum(d[s] for s=1:t) >= Vmin)
             @constraint(rm,
-                v1 + sum{p[i,s], i=1:I, s=1:t} - sum{d[s],s=1:t} <= Vmax)
+                v1 + sum(p[i,s] for i=1:I, s=1:t) - sum(d[s] for s=1:t) <= Vmax)
         end
     end
 
     @testset "Affine, manual" begin
-        rm = RobustModel()
+        rm = RobustModel(solver=solver)
         # Uncertain parameter: demand at each time stage
         @uncertain(rm, d_nom[t]*(1-θ) <= d[t=1:T] <= d_nom[t]*(1+θ))
         # Decision: how much to produce at each factory at each time
@@ -76,21 +76,21 @@ print_with_color(:yellow, "Adaptive Inventory Model...\n")
         end
         # Objective: total cost of production
         @variable(rm, F); @objective(rm, Min, F)
-        @constraint(rm, sum{c[i,t] * p[i,t], i=1:I, t=1:T} <= F)
+        @constraint(rm, sum(c[i,t] * p[i,t] for i=1:I, t=1:T) <= F)
         add_constraints(rm, p, d)
         solve(rm)
         @test isapprox(getvalue(F), 44272.82749, atol=TOL)
     end
 
     @testset "Affine, auto" begin
-        rm = RobustModel()
+        rm = RobustModel(solver=solver)
         # Uncertain parameter: demand at each time stage
         @uncertain(rm, d_nom[t]*(1-θ) <= d[t=1:T] <= d_nom[t]*(1+θ))
         # Decision: how much to produce at each factory at each time
         @adaptive(rm, p[i=1:I,t=1:T], policy=Affine, depends_on=d[1:t-1])
         # Objective: total cost of production
         @variable(rm, F); @objective(rm, Min, F)
-        @constraint(rm, sum{c[i,t] * p[i,t], i=1:I, t=1:T} <= F)
+        @constraint(rm, sum(c[i,t] * p[i,t] for i=1:I, t=1:T) <= F)
         add_constraints(rm, p, d)
         solve(rm)
         @test isapprox(getvalue(F), 44272.82749, atol=TOL)

test/adp_newsvendor.jl

@@ -56,7 +56,7 @@ print_with_color(:yellow, "Adaptive Newsvendor Model...\n")
     end
 
     @testset "Static, manual" begin
-        m = RobustModel()
+        m = RobustModel(solver=solver)
         D = add_set(m)
         @variable(m, x >= 0)
         @variable(m, S[1:N] >= 0)
@@ -70,7 +70,7 @@ print_with_color(:yellow, "Adaptive Newsvendor Model...\n")
     end  # "Static, manual"
 
     @testset "Static, auto" begin
-        m = RobustModel()
+        m = RobustModel(solver=solver)
         D = add_set(m)
         @variable(m, x >= 0)
         @adaptive(m, S[1:N] >= 0, policy=Static, depends_on=D)
@@ -84,7 +84,7 @@ print_with_color(:yellow, "Adaptive Newsvendor Model...\n")
     end  # "Static, auto"
 
     @testset "Affine, manual" begin
-        m = RobustModel()
+        m = RobustModel(solver=solver)
         D = add_set(m)
         @variable(m, x >= 0)
         @variable(m, S_aff[1:N,0:N])
@@ -105,7 +105,7 @@ print_with_color(:yellow, "Adaptive Newsvendor Model...\n")
     end
 
     @testset "Affine, auto" begin
-        m = RobustModel()
+        m = RobustModel(solver=solver)
         D = add_set(m)
         @variable(m, x >= 0)
         @adaptive(m, S[1:N] >= 0, policy=Affine, depends_on=D)

test/macro.jl

@@ -50,9 +50,9 @@ end
     @constraint(rm, 0 <= u - 5)
     @test lastus(rm) == "-u $le -5"
 
-    @constraint(rm, u == sum{i*v[i], i=1:3})
+    @constraint(rm, u == sum(i*v[i] for i=1:3))
     @test lastus(rm) == "u - v[1] - 2 v[2] - 3 v[3] $eq 0"
-    @constraint(rm, sum{i*v[i], i=1:3} + u >= 10)
+    @constraint(rm, sum(i*v[i] for i=1:3) + u >= 10)
     @test lastus(rm) == "v[1] + 2 v[2] + 3 v[3] + u $ge 10"
 end
 
@@ -82,10 +82,10 @@ end
     @constraint(rm, (u+w)*x + 2 + w*x <= u*z + 3)
     @test lastuc(rm) == "u x + w x + w x + -u z $le 1"
 
-    @constraint(rm, sum{v[i]*y[i], i=1:5; i!=3} <= 9)
+    @constraint(rm, sum(v[i]*y[i] for i=1:5 if i!=3) <= 9)
     @test lastuc(rm) == "v[1] y[1] + v[2] y[2] + v[4] y[4] + v[5] y[5] $le 9"
 
-    @constraint(rm, sum{i*(u+v[i])*(y[i]+x), i=1:2:5} <= 0)
+    @constraint(rm, sum(i*(u+v[i])*(y[i]+x) for i=1:2:5) <= 0)
     @test lastuc(rm) == "(u + v[1]) y[1] + (u + v[1]) x + (3 u + 3 v[3]) y[3] + (3 u + 3 v[3]) x + (5 u + 5 v[5]) y[5] + (5 u + 5 v[5]) x $le 0"
 
     foo = u*x

test/operators.jl

@@ -522,60 +522,60 @@ rm = RobustModel()
 us = JuMPeR.get_robust(rm).default_uncset
 nc = us.norm_constraints
 @uncertain(rm, u[1:3])
-@constraint(us, norm1{u[i],i=1:3} <= 1)
+@constraint(us, norm((u[i] for i=1:3),1) <= 1)
 @test string(nc[end]) == "‖u[1],u[2],u[3]‖₁ $leq 1"
-@constraint(us, norm2{u[i],i=1:3} <= 2)
+@constraint(us, norm(u[i] for i=1:3) <= 2)
 @test string(nc[end]) == "‖u[1],u[2],u[3]‖₂ $leq 2"
-@constraint(us, norm∞{u[i],i=1:3} <= 9)
+@constraint(us, norm((u[i] for i=1:3),Inf) <= 9)
 @test string(nc[end]) == "‖u[1],u[2],u[3]‖∞ $leq 9"
 
-@constraint(us, 2*norm1{u[i],i=1:3} <= 1)
+@constraint(us, 2*norm((u[i] for i=1:3),1) <= 1)
 @test string(nc[end]) == "2‖u[1],u[2],u[3]‖₁ $leq 1"
-@constraint(us, -1*norm1{u[i],i=1:3} >= -1)
+@constraint(us, -1*norm((u[i] for i=1:3),1) >= -1)
 @test string(nc[end]) == "‖u[1],u[2],u[3]‖₁ $leq 1"
 
-@constraint(us, 1 + norm1{u[i],i=1:3} <= 1)
+@constraint(us, 1 + norm((u[i] for i=1:3),1) <= 1)
 @test string(nc[end]) == "‖u[1],u[2],u[3]‖₁ $leq 0"
 
 @variable(rm, x)
 
-@test_throws ErrorException @constraint(us, norm1{u[i],i=1:3} + u[1] <= 1)
-@test_throws ErrorException @constraint(us, norm1{u[i],i=1:3} - u[1] <= 1)
-@test_throws ErrorException @constraint(us, norm1{u[i],i=1:3} * u[1] <= 1)
-@test_throws ErrorException @constraint(us, norm1{u[i],i=1:3} / u[1] <= 1)
+@test_throws ErrorException @constraint(us, norm((u[i] for i=1:3),1) + u[1] <= 1)
+@test_throws ErrorException @constraint(us, norm((u[i] for i=1:3),1) - u[1] <= 1)
+@test_throws ErrorException @constraint(us, norm((u[i] for i=1:3),1) * u[1] <= 1)
+@test_throws ErrorException @constraint(us, norm((u[i] for i=1:3),1) / u[1] <= 1)
 
-@test_throws ErrorException @constraint(us, norm1{u[i],i=1:3} + (2*u[1]) <= 1)
-@test_throws ErrorException @constraint(us, norm1{u[i],i=1:3} - (2*u[1]) <= 1)
-@test_throws ErrorException @constraint(us, norm1{u[i],i=1:3} * (2*u[1]) <= 1)
-@test_throws MethodError    @constraint(us, norm1{u[i],i=1:3} / (2*u[1]) <= 1)
+@test_throws ErrorException @constraint(us, norm((u[i] for i=1:3),1) + (2*u[1]) <= 1)
+@test_throws ErrorException @constraint(us, norm((u[i] for i=1:3),1) - (2*u[1]) <= 1)
+@test_throws ErrorException @constraint(us, norm((u[i] for i=1:3),1) * (2*u[1]) <= 1)
+@test_throws MethodError    @constraint(us, norm((u[i] for i=1:3),1) / (2*u[1]) <= 1)
 # MethodError: `/` has no method matching /(::Int64, ::JuMP.GenericAffExpr{Float64,JuMPeR.Uncertain})
 
-@test_throws ErrorException @constraint(us, norm1{u[i],i=1:3} + (2*u[1]*x+u[2]) <= 1)
-@test_throws ErrorException @constraint(us, norm1{u[i],i=1:3} - (2*u[1]*x+u[2]) <= 1)
-@test_throws ErrorException @constraint(us, norm1{u[i],i=1:3} * (2*u[1]*x+u[2]) <= 1)
-@test_throws MethodError    @constraint(us, norm1{u[i],i=1:3} / (2*u[1]*x+u[2]) <= 1)
+@test_throws ErrorException @constraint(us, norm((u[i] for i=1:3),1) + (2*u[1]*x+u[2]) <= 1)
+@test_throws ErrorException @constraint(us, norm((u[i] for i=1:3),1) - (2*u[1]*x+u[2]) <= 1)
+@test_throws ErrorException @constraint(us, norm((u[i] for i=1:3),1) * (2*u[1]*x+u[2]) <= 1)
+@test_throws MethodError    @constraint(us, norm((u[i] for i=1:3),1) / (2*u[1]*x+u[2]) <= 1)
 
-@test_throws ErrorException @constraint(us, x + norm1{u[i],i=1:3} <= 1)
-@test_throws ErrorException @constraint(us, x - norm1{u[i],i=1:3} <= 1)
-@test_throws ErrorException @constraint(us, (2x) + norm1{u[i],i=1:3} <= 1)
-@test_throws ErrorException @constraint(us, (2x) - norm1{u[i],i=1:3} <= 1)
+@test_throws ErrorException @constraint(us, x + norm((u[i] for i=1:3),1) <= 1)
+@test_throws ErrorException @constraint(us, x - norm((u[i] for i=1:3),1) <= 1)
+@test_throws ErrorException @constraint(us, (2x) + norm((u[i] for i=1:3),1) <= 1)
+@test_throws ErrorException @constraint(us, (2x) - norm((u[i] for i=1:3),1) <= 1)
 
-@test_throws ErrorException @constraint(us, (u[1]) + norm1{u[i],i=1:3} <= 1)
-@test_throws ErrorException @constraint(us, (u[1]) - norm1{u[i],i=1:3} <= 1)
-@test_throws ErrorException @constraint(us, (u[1]) * norm1{u[i],i=1:3} <= 1)
-# @constraint(us, (u[1]) / norm1{u[i],i=1:3} <= 1)
+@test_throws ErrorException @constraint(us, (u[1]) + norm((u[i] for i=1:3),1) <= 1)
+@test_throws ErrorException @constraint(us, (u[1]) - norm((u[i] for i=1:3),1) <= 1)
+@test_throws ErrorException @constraint(us, (u[1]) * norm((u[i] for i=1:3),1) <= 1)
+# @constraint(us, (u[1]) / norm((u[i] for i=1:3),1) <= 1)
 # UndefVarError: i not defined
 
-@test_throws ErrorException @constraint(us, (2*u[1]) + norm1{u[i],i=1:3} <= 1)
-@test_throws ErrorException @constraint(us, (2*u[1]) - norm1{u[i],i=1:3} <= 1)
-@test_throws ErrorException @constraint(us, (2*u[1]) * norm1{u[i],i=1:3} <= 1)
-# @constraint(us, (2*u[1]) / norm1{u[i],i=1:3} <= 1)
+@test_throws ErrorException @constraint(us, (2*u[1]) + norm((u[i] for i=1:3),1) <= 1)
+@test_throws ErrorException @constraint(us, (2*u[1]) - norm((u[i] for i=1:3),1) <= 1)
+@test_throws ErrorException @constraint(us, (2*u[1]) * norm((u[i] for i=1:3),1) <= 1)
+# @constraint(us, (2*u[1]) / norm((u[i] for i=1:3),1) <= 1)
 # UndefVarError: i not defined
 
-@test_throws ErrorException @constraint(us, (2*u[1]*x+u[2]) + norm1{u[i],i=1:3} <= 1)
-@test_throws ErrorException @constraint(us, (2*u[1]*x+u[2]) - norm1{u[i],i=1:3} <= 1)
-@test_throws ErrorException @constraint(us, (2*u[1]*x+u[2]) * norm1{u[i],i=1:3} <= 1)
-# @constraint(us, (2*u[1]*x+u[2]) / norm1{u[i],i=1:3} <= 1)
+@test_throws ErrorException @constraint(us, (2*u[1]*x+u[2]) + norm((u[i] for i=1:3),1) <= 1)
+@test_throws ErrorException @constraint(us, (2*u[1]*x+u[2]) - norm((u[i] for i=1:3),1) <= 1)
+@test_throws ErrorException @constraint(us, (2*u[1]*x+u[2]) * norm((u[i] for i=1:3),1) <= 1)
+# @constraint(us, (2*u[1]*x+u[2]) / norm((u[i] for i=1:3),1) <= 1)
 # UndefVarError: i not defined
 
 end  # "Unc. set norms"

test/print.jl

@@ -13,17 +13,11 @@
 
 using JuMP, JuMPeR
 using BaseTestNext
-import JuMP: REPLMode, IJuliaMode
-import JuMP: repl, ijulia
+import JuMP: repl
 
 # Helper function to test IO methods work correctly
-function io_test(mode, obj, exp_str; repl=:both)
-    if mode == REPLMode
-        repl != :show  && @test sprint(print, obj) == exp_str
-        repl != :print && @test sprint(show,  obj) == exp_str
-    else
-        @test sprint(writemime, "text/latex", obj) == "\$\$ $exp_str \$\$"
-    end
+function io_test(obj, exp_str; repl=:both)
+    @test sprint(print, obj) == exp_str
 end
 
 @testset "Printing" begin
@@ -65,27 +59,27 @@ print_with_color(:yellow, "Printing...\n")
     # @constraint(mod_1, norm([a,b]) <= 1)
     # ‖a,b‖₂ $le 1
 
-    io_test(REPLMode, mod_1, """
+    io_test(mod_1, """
 Max 2 vars[1]
 Subject to
- vars[10] $le 10
- vars[i] free $fa i $inset {1,2,$dots,9,10}
+ vars[10] ≤ 10
+ vars[i] ∀ i ∈ {1,2,…,9,10}
 Uncertain constraints:
-a vars[5] $le 5
+a vars[5] ≤ 5
 Uncertain parameters:
-bnd_free[i] free $fa i $inset {2,3,4,5}
-bnd_lowb[i] $ge 2 $fa i $inset {2,3,4,5}
-bnd_high[i] $le 5 $fa i $inset {2,3,4,5}
-2 $le bnd_both[i] $le 5 $fa i $inset {2,3,4,5}
-mat2d[i,j] free $fa i $inset {1,2,3}, j $inset {1,2,3}
-mat3d[i,j,k] free $fa i $inset {1,2,3}, j $inset {1,2,3}, k $inset {1,2,3}
-a $ge 1
-b $le 1
--1 $le c $le 1
-a1 $ge 1, integer
-b1 $le 1, integer
--1 $le c1 $le 1, integer
-x $inset {0,1}
+bnd_free[i] free ∀ i ∈ {2,3,4,5}
+bnd_lowb[i] ≥ 2 ∀ i ∈ {2,3,4,5}
+bnd_high[i] ≤ 5 ∀ i ∈ {2,3,4,5}
+2 ≤ bnd_both[i] ≤ 5 ∀ i ∈ {2,3,4,5}
+mat2d[i,j] free ∀ i ∈ {1,2,3}, j ∈ {1,2,3}
+mat3d[i,j,k] free ∀ i ∈ {1,2,3}, j ∈ {1,2,3}, k ∈ {1,2,3}
+a ≥ 1
+b ≤ 1
+-1 ≤ c ≤ 1
+a1 ≥ 1, integer
+b1 ≤ 1, integer
+-1 ≤ c1 ≤ 1, integer
+x ∈ {0,1}
 y free
 z free, integer
 """, repl=:print)
@@ -107,15 +101,15 @@ end  # "RobustModel"
     @uncertain(m, i <= bnd_difflo_with_up[i=2:5] <= 5)
     @uncertain(m, 2 <= bnd_diffup_with_lo[i=2:5] <= i)
 
-    io_test(REPLMode, bnd_free, "bnd_free[i] free $fa i $inset {2,3,4,5}")
-    io_test(REPLMode, bnd_lowb, "bnd_lowb[i] $ge 2 $fa i $inset {2,3,4,5}")
-    io_test(REPLMode, bnd_high, "bnd_high[i] $le 5 $fa i $inset {2,3,4,5}")
-    io_test(REPLMode, bnd_both, "2 $le bnd_both[i] $le 5 $fa i $inset {2,3,4,5}")
-    io_test(REPLMode, bnd_difflo, "bnd_difflo[i] $ge $dots $fa i $inset {2,3,4,5}")
-    io_test(REPLMode, bnd_diffup, "bnd_diffup[i] $le $dots $fa i $inset {2,3,4,5}")
-    io_test(REPLMode, bnd_diffbo, "$dots $le bnd_diffbo[i] $le $dots $fa i $inset {2,3,4,5}")
-    io_test(REPLMode, bnd_difflo_with_up, "$dots $le bnd_difflo_with_up[i] $le 5 $fa i $inset {2,3,4,5}")
-    io_test(REPLMode, bnd_diffup_with_lo, "2 $le bnd_diffup_with_lo[i] $le $dots $fa i $inset {2,3,4,5}")
+    io_test(bnd_free, "bnd_free[i] free $fa i $inset {2,3,4,5}")
+    io_test(bnd_lowb, "bnd_lowb[i] $ge 2 $fa i $inset {2,3,4,5}")
+    io_test(bnd_high, "bnd_high[i] $le 5 $fa i $inset {2,3,4,5}")
+    io_test(bnd_both, "2 $le bnd_both[i] $le 5 $fa i $inset {2,3,4,5}")
+    io_test(bnd_difflo, "bnd_difflo[i] $ge $dots $fa i $inset {2,3,4,5}")
+    io_test(bnd_diffup, "bnd_diffup[i] $le $dots $fa i $inset {2,3,4,5}")
+    io_test(bnd_diffbo, "$dots $le bnd_diffbo[i] $le $dots $fa i $inset {2,3,4,5}")
+    io_test(bnd_difflo_with_up, "$dots $le bnd_difflo_with_up[i] $le 5 $fa i $inset {2,3,4,5}")
+    io_test(bnd_diffup_with_lo, "2 $le bnd_diffup_with_lo[i] $le $dots $fa i $inset {2,3,4,5}")
 end  # "JuMPContainer{Uncertain}"
 
 end  # "Printing"