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Mathlib.Analysis.InnerProductSpace.EuclideanDist

Euclidean distance on a finite dimensional space #

When we define a smooth bump function on a normed space, it is useful to have a smooth distance on the space. Since the default distance is not guaranteed to be smooth, we define toEuclidean to be an equivalence between a finite dimensional topological vector space and the standard Euclidean space of the same dimension. Then we define Euclidean.dist x y = dist (toEuclidean x) (toEuclidean y) and provide some definitions (Euclidean.ball, Euclidean.closedBall) and simple lemmas about this distance. This way we hide the usage of toEuclidean behind an API.

If E is a finite dimensional space over , then toEuclidean is a continuous -linear equivalence between E and the Euclidean space of the same dimension.

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      If x and y are two points in a finite dimensional space over , then Euclidean.dist x y is the distance between these points in the metric defined by some inner product space structure on E.

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          Closed ball w.r.t. the euclidean distance.

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              Open ball w.r.t. the euclidean distance.

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                  theorem Euclidean.exists_pos_lt_subset_ball {E : Type u_1} [AddCommGroup E] [TopologicalSpace E] [IsTopologicalAddGroup E] [T2Space E] [Module E] [ContinuousSMul E] [FiniteDimensional E] {R : } {s : Set E} {x : E} (hR : 0 < R) (hs : IsClosed s) (h : s ball x R) :
                  rSet.Ioo 0 R, s ball x r
                  theorem ContDiff.euclidean_dist {F : Type u_2} [NormedAddCommGroup F] [NormedSpace F] {G : Type u_3} [NormedAddCommGroup G] [NormedSpace G] [FiniteDimensional G] {f g : FG} {n : ℕ∞} (hf : ContDiff (↑n) f) (hg : ContDiff (↑n) g) (h : ∀ (x : F), f x g x) :
                  ContDiff n fun (x : F) => Euclidean.dist (f x) (g x)