More EP tests.

dourouc05 · May 14, 2021 · 1896e1e · 1896e1e
1 parent 29b5aab
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diff --git a/src/ElementaryPath/ep.jl b/src/ElementaryPath/ep.jl
@@ -57,7 +57,7 @@ end
 # Solution.
 
 struct ElementaryPathSolution{T, O <: CombinatorialObjective} <:
-       CombinatorialInstance
+       CombinatorialSolution
     instance::ElementaryPathInstance{T, O}
     variables::Vector{Edge{T}}
     solutions::Dict{T, Vector{Edge{T}}}

diff --git a/test/ep.jl b/test/ep.jl
@@ -1,18 +1,4 @@
 @testset "ElementaryPath" begin
-    @testset "Copying" begin
-        g = path_digraph(3)
-        add_edge!(g, 2, 1)
-        rewards = Dict(Edge(1, 2) => 1.0, Edge(2, 3) => 3.0, Edge(2, 1) => 25.0)
-
-        i = ElementaryPathInstance(g, rewards, 1, 3)
-        i2 = copy(i)
-        @test i.graph == i2.graph
-        @test i.rewards == i2.rewards
-        @test i.src == i2.src
-        @test i.dst == i2.dst
-        @test i.objective == i2.objective
-    end
-
     @testset "Transforming a solution" begin
         g = path_digraph(3)
         add_edge!(g, 1, 3)
@@ -57,32 +43,31 @@
 
     @testset "Elementary paths" begin
         @testset "Interface" begin
+            g = path_digraph(3)
+            rewards = Dict(Edge(1, 2) => 1.0, Edge(2, 3) => 1.0)
+
+            @testset "Global interface" begin
+                i = ElementaryPathInstance(g, rewards, 1, 2)
+                @test objective(i) == Maximise()
+            end
+
             @testset "Source not in graph" begin
-                g = path_digraph(3)
-                rewards = Dict(Edge(1, 2) => 1.0, Edge(2, 3) => 1.0)
                 @test_throws ErrorException ElementaryPathInstance(g, rewards, 50, 2)
             end
 
             @testset "Destination not in graph" begin
-                g = path_digraph(3)
-                rewards = Dict(Edge(1, 2) => 1.0, Edge(2, 3) => 1.0)
                 @test_throws ErrorException ElementaryPathInstance(g, rewards, 1, 50)
             end
 
             @testset "Source is destination" begin
-                g = path_digraph(3)
-                rewards = Dict(Edge(1, 2) => 1.0, Edge(2, 3) => 1.0)
                 @test_throws ErrorException ElementaryPathInstance(g, rewards, 1, 1)
             end
 
             @testset "Source is destination" begin
-                g = path_digraph(3)
-                rewards = Dict(Edge(1, 2) => 1.0, Edge(2, 3) => 1.0)
                 @test_throws ErrorException ElementaryPathInstance(g, rewards, 1, 1)
             end
 
             @testset "An edge has a reward but is not in the graph" begin
-                g = path_digraph(3)
                 rewards = Dict(Edge(1, 2) => 1.0, Edge(2, 3) => 1.0, Edge(1, 3) => 1.0)
                 @test_throws ErrorException ElementaryPathInstance(g, rewards, 1, 2)
             end
@@ -102,6 +87,56 @@
                     "The graph contains a positive-cost cycle around edge 2 -> 1.",
                 ) solve(i, BellmanFordAlgorithm())
             end
+
+            @testset "Copy" begin
+                g = path_digraph(3)
+                add_edge!(g, 2, 1)
+                rewards = Dict(Edge(1, 2) => 1.0, Edge(2, 3) => 3.0, Edge(2, 1) => 25.0)
+
+                i = ElementaryPathInstance(g, rewards, 1, 3)
+                i2 = copy(i)
+                @test i.graph == i2.graph
+                @test i.rewards == i2.rewards
+                @test i.src == i2.src
+                @test i.dst == i2.dst
+                @test i.objective == i2.objective
+            end
+
+            @testset "Approximation" begin
+                i = ElementaryPathInstance(g, rewards, 1, 3)
+
+                @test approximation_ratio(i, DynamicProgramming()) == 1.0
+                @test approximation_term(i, DynamicProgramming()) == 0.0
+
+                @test approximation_ratio(i, DefaultLinearFormulation(Cbc.Optimizer)) == 1.0
+                @test approximation_term(i, DefaultLinearFormulation(Cbc.Optimizer)) == 0.0
+            end
+
+            @testset "Make solution" begin
+                i = ElementaryPathInstance(g, rewards, 1, 3)
+                d = Dict(Edge(1, 3) => 0.4, Edge(1, 2) => 0.8, Edge(2, 3) => 0.7)
+                s = make_solution(i, d)
+
+                @test s.instance == i
+                @test length(s.variables) == 2
+                @test Edge(1, 3) ∉ s.variables
+                @test Edge(1, 2) ∈ s.variables
+                @test Edge(2, 3) ∈ s.variables
+            end
+
+            @testset "Solution helpers" begin
+                i = ElementaryPathInstance(g, rewards, 1, 3)
+
+                # Infeasible solution.
+                s = ElementaryPathSolution(i, Edge{Int}[])
+                @test value(s) == -Inf
+
+                # Valid solution.
+                d = Dict(Edge(1, 3) => 0.4, Edge(1, 2) => 0.8, Edge(2, 3) => 0.7)
+                s = make_solution(i, d)
+
+                @test value(s) == 4
+            end
         end
 
         @testset "Basic" begin
@@ -163,23 +198,79 @@
 
     @testset "Budgeted elementary paths" begin
         @testset "Interface" begin
+            graph = path_digraph(3)
+            rewards = Dict(Edge(1, 2) => 1.0, Edge(2, 3) => 1.0)
+            weights = Dict(Edge(1, 2) => 1, Edge(2, 3) => 1)
+
+            @testset "Global interface" begin
+                i = MinimumBudget(ElementaryPathInstance(graph, rewards, 1, 2), weights)
+                @test objective(i) == Maximise()
+            end
+
             @testset "More edges have rewards than weights" begin
                 g = path_digraph(4)
-                rewards = Dict(Edge(1, 2) => 1.0, Edge(2, 3) => 1.0, Edge(4, 1) => 1.0)
-                weights = Dict(Edge(1, 2) => 1, Edge(2, 3) => 1)
-                @test_throws ErrorException MinimumBudget(ElementaryPathInstance(g, rewards, 1, 2), weights)
+                r = Dict(Edge(1, 2) => 1.0, Edge(2, 3) => 1.0, Edge(4, 1) => 1.0)
+                w = Dict(Edge(1, 2) => 1, Edge(2, 3) => 1)
+                @test_throws ErrorException MinimumBudget(ElementaryPathInstance(g, r, 1, 2), w)
             end
 
             @testset "Negative weight or budget" begin
-                g = path_digraph(3)
-                rewards = Dict(Edge(1, 2) => 1.0, Edge(2, 3) => 1.0)
-                weights = Dict(Edge(1, 2) => 1, Edge(2, 3) => 1)
-                @test_throws ErrorException MinimumBudget(ElementaryPathInstance(g, rewards, 1, 2), weights, -1)
+                w = Dict(Edge(1, 2) => 1, Edge(2, 3) => 1)
+                @test_throws ErrorException MinimumBudget(ElementaryPathInstance(graph, rewards, 1, 2), w, -1)
+
+                w[Edge(4, 2)] = 1
+                @test_throws ErrorException MinimumBudget(ElementaryPathInstance(graph, rewards, 1, 2), w)
+                w[Edge(4, 2)] = -1
+                @test_throws ErrorException MinimumBudget(ElementaryPathInstance(graph, rewards, 1, 2), w)
+            end
+
+            @testset "Copy" begin
+                i = MinimumBudget(ElementaryPathInstance(graph, rewards, 1, 2), weights)
+                i2 = copy(i)
+                @test i.weights == i2.weights
+                @test i.min_budget == i2.min_budget
+                @test i.compute_all_values == i2.compute_all_values
+                @test i.instance.graph == i2.instance.graph
+                @test i.instance.rewards == i2.instance.rewards
+                @test i.instance.src == i2.instance.src
+                @test i.instance.dst == i2.instance.dst
+                @test i.instance.objective == i2.instance.objective
+            end
+
+            @testset "Approximation" begin
+                i = MinimumBudget(ElementaryPathInstance(graph, rewards, 1, 2), weights)
+
+                @test approximation_ratio(i, DynamicProgramming()) == 1.0
+                @test approximation_term(i, DynamicProgramming()) == 0.0
+
+                @test approximation_ratio(i, DefaultLinearFormulation(Cbc.Optimizer)) == 1.0
+                @test approximation_term(i, DefaultLinearFormulation(Cbc.Optimizer)) == 0.0
+            end
+
+            @testset "Make solution" begin
+                i = MinimumBudget(ElementaryPathInstance(graph, rewards, 1, 2), weights)
+                d = Dict(Edge(1, 3) => 0.4, Edge(1, 2) => 0.8, Edge(2, 3) => 0.7)
+                s = make_solution(i, d)
+
+                @test s.instance == i
+                @test length(s.variables) == 2
+                @test Edge(1, 3) ∉ s.variables
+                @test Edge(1, 2) ∈ s.variables
+                @test Edge(2, 3) ∈ s.variables
+            end
+
+            @testset "Solution helpers" begin
+                i = MinimumBudget(ElementaryPathInstance(graph, rewards, 1, 2), weights)
+
+                # Infeasible solution.
+                s = BudgetedElementaryPathSolution(i, Edge{Int}[])
+                @test value(s) == -Inf
+
+                # Valid solution.
+                d = Dict(Edge(1, 3) => 0.4, Edge(1, 2) => 0.8, Edge(2, 3) => 0.7)
+                s = make_solution(i, d)
 
-                weights[Edge(4, 2)] = 1
-                @test_throws ErrorException MinimumBudget(ElementaryPathInstance(g, rewards, 1, 2), weights)
-                weights[Edge(4, 2)] = -1
-                @test_throws ErrorException MinimumBudget(ElementaryPathInstance(g, rewards, 1, 2), weights)
+                @test value(s) == 2
             end
         end