Merge pull request #2151 from JuliaReach/schillic/doctests

Make doctests independent of Julia version

src/Approximations/template_directions.jl

@@ -500,8 +500,12 @@ Cartesian components of each direction are obtained with
 The integer passed as an argument is used to discretize ``φ``:
 
 ```jldoctest; filter = r"2246[0-9]*e-16"
-julia> pd = PolarDirections(2)
-PolarDirections{Float64,Array{Float64,1}}(2, Array{Float64,1}[[1.0, 0.0], [-1.0, 1.2246467991473532e-16]])
+julia> pd = PolarDirections(2);
+
+julia> pd.stack
+2-element Array{Array{Float64,1},1}:
+ [1.0, 0.0]
+ [-1.0, 1.2246467991473532e-16]
 
 julia> length(pd)
 2
@@ -685,8 +689,14 @@ passed (in which case the optional argument `n` needs to be specified).
 Creating a template with box directions in dimension two:
 
 ```jldoctest
-julia> dirs = CustomDirections([[1.0, 0.0], [-1.0, 0.0], [0.0, 1.0], [0.0, -1.0]])
-CustomDirections{Float64,Array{Float64,1}}(Array{Float64,1}[[1.0, 0.0], [-1.0, 0.0], [0.0, 1.0], [0.0, -1.0]], 2, true, true)
+julia> dirs = CustomDirections([[1.0, 0.0], [-1.0, 0.0], [0.0, 1.0], [0.0, -1.0]]);
+
+julia> dirs.directions
+4-element Array{Array{Float64,1},1}:
+ [1.0, 0.0]
+ [-1.0, 0.0]
+ [0.0, 1.0]
+ [0.0, -1.0]
 
 julia> LazySets.Approximations.isbounding(dirs)
 true

src/LazyOperations/CartesianProductArray.jl

@@ -472,8 +472,17 @@ julia> using LazySets: block_to_dimension_indices
 
 julia> cpa = CartesianProductArray([BallInf(zeros(n), 1.0) for n in [1, 3, 2, 3]]);
 
-julia> block_to_dimension_indices(cpa, [2, 4, 8])
-(Tuple{Int64,Int64}[(-1, -1), (2, 4), (-1, -1), (7, 9)], 2)
+julia> m, k = block_to_dimension_indices(cpa, [2, 4, 8]);
+
+julia> m
+4-element Array{Tuple{Int64,Int64},1}:
+ (-1, -1)
+ (2, 4)
+ (-1, -1)
+ (7, 9)
+
+julia> k
+2
 ```
 This vector represents the mapping "second block from dimension 2 to dimension 4,
 fourth block from dimension 7 to dimension 9."

src/Sets/VPolygon.jl

@@ -34,8 +34,13 @@ A polygon in vertex representation can be constructed by passing the list of
 vertices. For example, we can build the right triangle
 
 ```jldoctest polygon_vrep
-julia> P = VPolygon([[0, 0], [1, 0], [0, 1]])
-VPolygon{Int64,Array{Int64,1}}(Array{Int64,1}[[0, 0], [1, 0], [0, 1]])
+julia> P = VPolygon([[0, 0], [1, 0], [0, 1]]);
+
+julia> P.vertices
+3-element Array{Array{Int64,1},1}:
+ [0, 0]
+ [1, 0]
+ [0, 1]
 ```
 
 Alternatively, a `VPolygon` can be constructed passing a matrix of vertices,
@@ -47,8 +52,13 @@ julia> M = [0 1 0; 0 0 1.]
  0.0  1.0  0.0
  0.0  0.0  1.0
 
-julia> VPolygon(M)
-VPolygon{Float64,Array{Float64,1}}(Array{Float64,1}[[0.0, 0.0], [1.0, 0.0], [0.0, 1.0]])
+julia> P = VPolygon(M);
+
+julia> P.vertices
+3-element Array{Array{Float64,1},1}:
+ [0.0, 0.0]
+ [1.0, 0.0]
+ [0.0, 1.0]
 ```
 """
 struct VPolygon{N<:Real, VN<:AbstractVector{N}} <: AbstractPolygon{N}

src/Sets/VPolytope.jl

@@ -25,23 +25,34 @@ Type that represents a convex polytope in V-representation.
 A polytope in vertex representation can be constructed by passing the list of
 vertices. For example, we can build the tetrahedron:
 
-```jldoctest polytope_vrep
-julia> P = VPolytope([0 0 0; 1 0 0; 0 1 0; 0 0 1])
-VPolytope{Int64,Array{Int64,1}}(Array{Int64,1}[[0, 1, 0, 0], [0, 0, 1, 0], [0, 0, 0, 1]])
+```jldoctest
+julia> P = VPolytope([0 0 0; 1 0 0; 0 1 0; 0 0 1]);
+
+julia> P.vertices
+3-element Array{Array{Int64,1},1}:
+ [0, 1, 0, 0]
+ [0, 0, 1, 0]
+ [0, 0, 0, 1]
 ```
 
 Alternatively, a `VPolytope` can be constructed passing a matrix of vertices,
 where each *column* represents a vertex:
 
-```jldoctest polytope_vrep
+```jldoctest
 julia> M = [0 0 0; 1 0 0; 0 1 0; 0 0 1]'
 3×4 LinearAlgebra.Adjoint{Int64,Array{Int64,2}}:
  0  1  0  0
  0  0  1  0
  0  0  0  1
 
-julia> VPolytope(M)
-VPolytope{Int64,Array{Int64,1}}(Array{Int64,1}[[0, 0, 0], [1, 0, 0], [0, 1, 0], [0, 0, 1]])
+julia> P = VPolytope(M);
+
+julia> P.vertices
+4-element Array{Array{Int64,1},1}:
+ [0, 0, 0]
+ [1, 0, 0]
+ [0, 1, 0]
+ [0, 0, 1]
 ```
 """
 struct VPolytope{N<:Real, VN<:AbstractVector{N}} <: AbstractPolytope{N}
@@ -91,14 +102,19 @@ If it is empty, the result is ``-1``.
 ### Examples
 
 ```jldoctest
-julia> v = VPolytope()
-VPolytope{Float64,Array{Float64,1}}(Array{Float64,1}[])
+julia> v = VPolytope();
+
+julia> v.vertices
+0-element Array{Array{Float64,1},1}
 
 julia> dim(v)
 -1
 
-julia> v = VPolytope([ones(3)])
-VPolytope{Float64,Array{Float64,1}}(Array{Float64,1}[[1.0, 1.0, 1.0]])
+julia> v = VPolytope([ones(3)]);
+
+julia> v.vertices
+1-element Array{Array{Float64,1},1}:
+ [1.0, 1.0, 1.0]
 
 julia> dim(v) == 3
 true