add tests

src/Sets/HalfSpace/HalfSpaceModule.jl

@@ -272,6 +272,9 @@ function load_symengine_halfspace()
         julia> all(_is_halfspace.([:(x1 <= 0), :(x1 < 0), :(x1 > 0), :(x1 >= 0)]))
         true
 
+        julia> _is_halfspace(:(x1 = 0))
+        false
+
         julia> _is_halfspace(:(2*x1 <= 4))
         true
 

src/Sets/HalfSpace/rand.jl

@@ -29,8 +29,8 @@ function rand(::Type{HalfSpace};
     rng = reseed!(rng, seed)
     a = randn(rng, N, dim)
     while iszero(a)
-        a = randn(rng, N, dim)
-    end
+        a = randn(rng, N, dim)  # COV_EXCL_LINE
+    end  # COV_EXCL_LINE
     b = randn(rng, N)
     return HalfSpace(a, b)
 end

test/Sets/HalfSpace.jl

@@ -109,20 +109,31 @@ for N in [Float64, Rational{Int}, Float32]
     @test !is_intersection_empty(hs1, hs4) && !empty_intersection && v ∈ hs1 && v ∈ hs4
 
     # check for tighter constraint
-    c1 = HalfSpace([1.0, 0.0], 1.0)
-    c2 = HalfSpace([2.0, 0.0], 2.0)
-    c3 = HalfSpace([2.0, 0.0], 1.0)
+    c1 = HalfSpace(N[1, 0], N(1))
+    c2 = HalfSpace(N[2, 0], N(2))
+    c3 = HalfSpace(N[2, 0], N(1))
     @test LazySets.is_tighter_same_dir_2D(c1, c2) &&
-          LazySets.is_tighter_same_dir_2D(c3, c2)
+          LazySets.is_tighter_same_dir_2D(c3, c2) &&
+          LazySets.is_tighter_same_dir_2D(c1, c1)
     @test !LazySets.is_tighter_same_dir_2D(c1, c2; strict=true) &&
-          LazySets.is_tighter_same_dir_2D(c3, c2; strict=true)
+          LazySets.is_tighter_same_dir_2D(c3, c2; strict=true) &&
+          !LazySets.is_tighter_same_dir_2D(c1, c1; strict=true)
+    c4 = HalfSpace(N[0, 1], N(2))
+    c5 = HalfSpace(N[0, 1], N(1))
+    @test !LazySets.is_tighter_same_dir_2D(c4, c5) &&
+          LazySets.is_tighter_same_dir_2D(c5, c4)
+    @test !LazySets.is_tighter_same_dir_2D(c4, c5; strict=true) &&
+          LazySets.is_tighter_same_dir_2D(c5, c4; strict=true)
 
     # test concrete linear map of a half-space
     H = HalfSpace(N[1, -1], N(0)) # x <= y
     M = N[1 0; 0 0] # non-invertible matrix
     @test_throws ArgumentError linear_map(M, H, algorithm="vrep")
     M = N[2 2; 0 1] # invertible matrix
     @test linear_map(M, H) == HalfSpace(N[0.5, -2.0], N(0.0))
+    M = zeros(N, 2, 2) # result is a singleton
+    X = linear_map(M, H)
+    @test X isa HPolyhedron && isequivalent(X, ZeroSet{N}(2))
 
     if test_suite_polyhedra
         if N == Float64 || N == Float32
@@ -140,6 +151,9 @@ for N in [Float64, Rational{Int}, Float32]
     hs_vec = convert(HalfSpace{N,Vector{N}}, hs_sev)
     @test hs_vec.a == N[0, 1, 0] && hs_vec.b == N(1)
 
+    # complement
+    @test complement(HalfSpace(N[1, -2], N(3))) == HalfSpace(N[-1, 2], N(-3))
+
     # complement check
     for (h1, h2, eq) in [(HalfSpace(N[-1], N(0)), HalfSpace(N[1 // 2], N(0)), true),
                          (HalfSpace(N[1, 3], N(1)), HalfSpace(N[-2, -6], N(-2)), true),
@@ -221,15 +235,24 @@ for N in [Float64]
         @test HalfSpace(2x + 3y ≥ 5) == HalfSpace([-2.0, -3.0], -5.0)
         @test HalfSpace(2x + 3y ≥ 5, vars) == HalfSpace([-2.0, -3.0], -5.0)
 
+        @test_throws ArgumentError HalfSpace(2x == 5y, vars)
+
         # doesn't work because get_vars returns variables [y, x]
         # => both tests below require vars to pass
         @test HalfSpace(2x ≥ 5y - 1, vars) == HalfSpace([-2.0, 5.0], 1.0)
         @test HalfSpace(2x >= 5y - 1, vars) == HalfSpace([-2.0, 5.0], 1.0)
 
+        # test passing a combination of operations
+        vars = @variables x[1:2] t
+        @test HalfSpace(x[1] <= t, vars) == HalfSpace([1.0, 0.0, -1.0], 0.0)
+
         # test with sparse variables
         @variables x[1:5]
         @test HalfSpace(2x[1] + 5x[4] <= 10.0, x) == HalfSpace([2.0, 0.0, 0.0, 5.0, 0.0], 10.0)
         @test HalfSpace(2x[1] + 5x[4] >= -10.0 + x[3], x) ==
               HalfSpace([-2.0, 0.0, 1.0, -5.0, 0.0], 10.0)
     end
 end
+
+# isoperationtype
+@test !isoperationtype(HalfSpace)