simplify tests

JuliaReach · Jul 5, 2019 · 1340ef9 · 1340ef9
1 parent 3d9c26c
commit 1340ef9
Showing 1 changed file with 19 additions and 26 deletions.
diff --git a/test/unit_overapproximate.jl b/test/unit_overapproximate.jl
@@ -160,19 +160,30 @@ for N in [Float64, Float32]
     @test lcl[7].b ≈ N(1)
     @test lcl[8].a ≈ N[sqrt(2)/2, -sqrt(2)/2]
     @test lcl[8].b ≈ N(1)
+end
 
-    # decomposed intersection between cartesian product array and abstract polyhedron
+for N in [Float64]
+    # decomposed linear map approximation
     i1 = Interval(N[0, 1])
     i2 = Interval(N[2, 3])
+    M = N[1 2; 0 1]
+    cpa = CartesianProductArray([i1, i2])
+    lm = M * cpa
+    d_oa = overapproximate(lm, CartesianProductArray{N, Interval{N}})
+    oa = overapproximate(lm, OctDirections)
+    @test oa ⊆ d_oa
+
+    # decomposed intersection between Cartesian product array and polyhedron
     h1 = Hyperrectangle(low=N[3, 4], high=N[5, 7])
     h2 = Hyperrectangle(low=N[5, 5], high=N[6, 8])
     cpa1 = CartesianProductArray([i1, i2, h1])
     o_cpa1 = overapproximate(cpa1)
     cpa2 = CartesianProductArray([i1, i2, h2])
     o_cpa2 = overapproximate(cpa2)
-    G = HPolyhedron([HalfSpace(N[1, 0, 0, 0], N(1))])
-    G_3 = HPolyhedron([HalfSpace(N[0, 0, 1, 0], N(1))])
-    G_3_neg = HPolyhedron([HalfSpace(N[0, 0, -1, 0], N(0))])
+    G = HalfSpace(N[1, 0, 0, 0], N(1))
+    G_3 = HalfSpace(N[0, 0, 1, 0], N(1))
+    G_3_neg = HalfSpace(N[0, 0, -1, 0], N(0))
+    G_comb = HalfSpace(N[1, 1, 0, 0], N(2.5))
 
     d_int_g = Intersection(cpa1, G)
     d_int_g_3 = Intersection(cpa1, G_3)
@@ -183,31 +194,13 @@ for N in [Float64, Float32]
     o_d_int_g_3 = overapproximate(d_int_g_3, CartesianProductArray, Hyperrectangle)
     o_d_int_g_3_neg = overapproximate(d_int_g_3_neg, CartesianProductArray, Hyperrectangle)
 
-    @test overapproximate(o_d_int_g) == overapproximate(d_int_g)
-    @test overapproximate(o_d_int_g_3) == overapproximate(d_int_g_3) == EmptySet{N}()
-    @test overapproximate(o_d_int_g_3_neg) == overapproximate(d_int_g_3_neg)
+    @test overapproximate(o_d_int_g) ≈ overapproximate(d_int_g)
+    @test isempty(d_int_g_3) && o_d_int_g_3 == EmptySet{N}()
+    @test overapproximate(o_d_int_g_3_neg) ≈ overapproximate(d_int_g_3_neg)
     @test overapproximate(d_int_cpa, Hyperrectangle) == l_int_cpa
     @test all([X isa CartesianProductArray for X in [d_int_cpa, o_d_int_g, o_d_int_g_3_neg]])
-end
 
-for N in [Float64]
-    # decomposed linear map approximation
-    i1 = Interval(N[0, 1])
-    i2 = Interval(N[2, 3])
-    M = N[1 2; 0 1]
-    cpa = CartesianProductArray([i1, i2])
-    lm = M * cpa
-    d_oa = overapproximate(lm, CartesianProductArray{N, Interval{N}})
-    oa = overapproximate(lm, OctDirections)
-    @test oa ⊆ d_oa
-
-    # decomposed intersection between cartesian product array and abstract polyhedron
-    i1 = Interval(N[0, 1])
-    i2 = Interval(N[2, 3])
-    h1 = Hyperrectangle(low=N[3, 4], high=N[5, 7])
-    cpa = CartesianProductArray([i1, i2, h1])
-    G_comb = HPolyhedron([HalfSpace(N[1, 1, 0, 0], N(2.5))])
-    int_g_comb = Intersection(cpa, G_comb)
+    int_g_comb = Intersection(cpa1, G_comb)
     o_d_int_g_comb = overapproximate(int_g_comb, CartesianProductArray, Hyperrectangle)
     o_bd_int_g_comb = overapproximate(int_g_comb, BoxDirections)
     @test overapproximate(o_d_int_g_comb) ≈ overapproximate(o_bd_int_g_comb)