Empty set (EmptySet)
LazySets.EmptySetModule.EmptySet
— TypeEmptySet{N} <: ConvexSet{N}
Type that represents the empty set, i.e., the set with no elements.
LazySets.EmptySetModule.∅
— Type∅
Alias for EmptySet{Float64}
.
Conversion
convert(::Type{EmptySet}, ::LazySet)
Operations
LazySets.chebyshev_center_radius
— Methodchebyshev_center_radius(∅::EmptySet; [kwargs]...)
Compute a Chebyshev center and the corresponding radius of an empty set.
Input
∅
– empty setkwargs
– further keyword arguments (ignored)
Output
An error.
LazySets.API.complement
— Methodcomplement(X::LazySet)
Compute the complement of a set.
Input
X
– set
Output
A set representing the complement of X
.
LazySets.API.complement
— MethodBase.rand
— Methodrand(T::Type{<:LazySet}; [N]::Type{<:Real}=Float64, [dim]::Int=2,
[rng]::AbstractRNG=GLOBAL_RNG, [seed]::Union{Int, Nothing}=nothing
)
Create a random set of the given set type.
Input
T
– set typeN
– (optional, default:Float64
) numeric typedim
– (optional, default: 2) dimensionrng
– (optional, default:GLOBAL_RNG
) random number generatorseed
– (optional, default:nothing
) seed for reseeding
Output
A random set of the given set type.
Base.rand
— MethodExtended help
rand(::Type{EmptySet}; [N]::Type{<:Real}=Float64, [dim]::Int=2,
[rng]::AbstractRNG=GLOBAL_RNG, [seed]::Union{Int, Nothing}=nothing)
Output
The (unique) empty set of the given numeric type and dimension.
LazySets.plot_recipe
— Methodplot_recipe(∅::EmptySet{N}, [ε]=zero(N)) where {N}
Convert an empty set to a sequence of points for plotting. In the special case of an empty set, the sequence is empty.
Input
∅
– empty setε
– (optional, default:0
) ignored, used for dispatch
Output
An empty array.
Undocumented implementations:
an_element
area
convex_hull
copy(::EmptySet)
diameter
dim
high
high
isbounded
isboundedtype
isconvextype
isempty
isoperationtype
isuniversal
low
low
norm
radius
rectify
reflect
surface
vertices_list
vertices
volume
exponential_map
∈
is_interior_point
linear_map
permute
project
sample
scale
scale!
ρ
σ
translate
translate!
cartesian_product
convex_hull
difference
distance
intersection
≈
isdisjoint
⊆
linear_combination
minkowski_difference
minkowski_sum
Inherited from LazySet
: