BallInf

Infinity-norm ball (BallInf)

LazySets.BallInf — Type.
BallInf{N<:Real} <: AbstractHyperrectangle{N}

Type that represents a ball in the infinity norm.

Fields

  • center – center of the ball as a real vector
  • radius – radius of the ball as a real scalar ($≥ 0$)

Notes

Mathematically, a ball in the infinity norm is defined as the set

\[\mathcal{B}_∞^n(c, r) = \{ x ∈ \mathbb{R}^n : ‖ x - c ‖_∞ ≤ r \},\]

where $c ∈ \mathbb{R}^n$ is its center and $r ∈ \mathbb{R}_+$ its radius. Here $‖ ⋅ ‖_∞$ denotes the infinity norm, defined as $‖ x ‖_∞ = \max\limits_{i=1,…,n} \vert x_i \vert$ for any $x ∈ \mathbb{R}^n$.

Examples

Create the two-dimensional unit ball and compute its support function along the positive $x=y$ direction:

julia> B = BallInf(zeros(2), 1.0)
BallInf{Float64}([0.0, 0.0], 1.0)
julia> dim(B)
2
julia> ρ([1., 1.], B)
2.0
source
LazySets.center — Method.
center(B::BallInf{N}) where {N<:Real}

Return the center of a ball in the infinity norm.

Input

  • B – ball in the infinity norm

Output

The center of the ball in the infinity norm.

source
LazySets.radius — Function.
radius(B::BallInf, [p]::Real=Inf)

Return the radius of a ball in the infinity norm.

Input

  • B – ball in the infinity norm
  • p – (optional, default: Inf) norm

Output

A real number representing the radius.

Notes

The radius is defined as the radius of the enclosing ball of the given $p$-norm of minimal volume with the same center.

source
LazySets.radius_hyperrectangle — Method.
radius_hyperrectangle(B::BallInf{N}) where {N<:Real}

Return the box radius of a ball in the infinity norm, which is the same in every dimension.

Input

  • B – ball in the infinity norm

Output

The box radius of the ball in the infinity norm.

source
LazySets.radius_hyperrectangle — Method.
radius_hyperrectangle(B::BallInf{N}, i::Int) where {N<:Real}

Return the box radius of a ball in the infinity norm in a given dimension.

Input

  • B – ball in the infinity norm
  • i – dimension of interest

Output

The box radius of the ball in the infinity norm in the given dimension.

source
LazySets.isflat — Method.
isflat(B::BallInf)

Determine whether a ball in the infinity norm is flat, i.e. whether its radius is zero.

Input

  • B – ball in the infinity norm

Output

true iff the ball is flat.

Notes

For robustness with respect to floating-point inputs, this function relies on the result of isapproxzero when applied to the radius of the ball. Hence, this function depends on the absolute zero tolerance ABSZTOL.

source
Base.rand — Method.
rand(::Type{BallInf}; [N]::Type{<:Real}=Float64, [dim]::Int=2,
     [rng]::AbstractRNG=GLOBAL_RNG, [seed]::Union{Int, Nothing}=nothing)

Create a random ball in the infinity norm.

Input

  • BallInf – type for dispatch
  • N – (optional, default: Float64) numeric type
  • dim – (optional, default: 2) dimension
  • rng – (optional, default: GLOBAL_RNG) random number generator
  • seed – (optional, default: nothing) seed for reseeding

Output

A random ball in the infinity norm.

Algorithm

All numbers are normally distributed with mean 0 and standard deviation 1. Additionally, the radius is nonnegative.

source
LazySets.σ — Method.
σ(d::AbstractVector{N}, B::BallInf{N}) where {N<:Real}

Return the support vector of a ball in the infinity norm in a given direction.

Input

  • d – direction
  • B – ball in the infinity norm

Output

The support vector in the given direction. If the direction has norm zero, the vertex with biggest values is returned.

source
LazySets.ρ — Method.
ρ(d::AbstractVector{N}, B::BallInf{N}) where {N<:Real}

Evaluate the support function of a ball in the infinity norm in a given direction.

Input

  • d – direction
  • B – ball in the infinity norm

Output

Evaluation of the support function in the given direction.

Algorithm

Let $B$ be a ball in the infinity norm with center $c$ and radius $r$ and let d be the direction of interest. For balls with dimensions less than 30 we use the implementation for AbstractHyperrectangle, taylored to a BallInf, which computes

\[ ∑_{i=1}^n d_i * (c_i + \textrm{sgn}(d_i) * r)\]

where $\textrm{sgn}(α) = 1$ if $α ≥ 0$ and $\textrm{sgn}(α) = 1$ if $α < 0$.

For balls of higher dimension, we instead exploit that for a support vector $v = σ(d, B) = c + \textrm{sgn}(d) * (r, …, r)ᵀ$ we have

\[ ρ(d, B) = ⟨d, v⟩ = ⟨d, c⟩ + ⟨d, \textrm{sgn}(d) * (r, …, r)ᵀ⟩ = ⟨d, c⟩ + r · ∑_{i=1}^n |d_i|\]

where $⟨·, ·⟩$ denotes the dot product.

source
LazySets.translate — Method.
translate(B::BallInf{N}, v::AbstractVector{N}) where {N<:Real}

Translate (i.e., shift) a ball in the infinity norm by a given vector.

Input

  • B – ball in the infinity norm
  • v – translation vector

Output

A translated ball in the infinity norm.

Algorithm

We add the vector to the center of the ball.

source

Inherited from LazySet:

Inherited from AbstractPolytope:

Inherited from AbstractCentrallySymmetricPolytope:

Inherited from AbstractZonotope:

Inherited from AbstractHyperrectangle: