Infinity-norm ball (BallInf)

LazySets.BallInfType
BallInf{N, VN<:AbstractVector{N}} <: 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,Array{Float64,1}}([0.0, 0.0], 1.0)

julia> dim(B)
2

julia> ρ([1., 1.], B)
2.0
source
LazySets.centerMethod
center(B::BallInf)

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.radiusFunction
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_hyperrectangleMethod
radius_hyperrectangle(B::BallInf)

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_hyperrectangleMethod
radius_hyperrectangle(B::BallInf, i::Int)

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.isflatMethod
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.randMethod
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.σMethod
σ(d::AbstractVector, B::BallInf)

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.ρMethod
ρ(d::AbstractVector, B::BallInf)

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.translateMethod
translate(B::BallInf, v::AbstractVector)

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: