Download lean/OAI/Geometry/RCD/Metric/ApproximationRestriction.lean from roseking/openAI-math-dataset: direct link, hf CLI and curl.
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hf download hf://datasets/roseking/openAI-math-dataset/lean/OAI/Geometry/RCD/Metric/ApproximationRestriction.lean
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curl -L -o ApproximationRestriction.lean https://huggingface.co/datasets/roseking/openAI-math-dataset/resolve/main/lean/OAI/Geometry/RCD/Metric/ApproximationRestriction.lean
1.37 kB
| import OAI.Geometry.RCD.Coordinates.SplittingApproximation | |
| namespace OAI | |
| /-! # Restricting a pointed approximation to a smaller ball -/ | |
| open Metric | |
| namespace RegularPointCoordinates | |
| /-- Restriction costs a factor three in the approximation error because | |
| the preimage supplied by density must be shown to lie in the smaller ball. -/ | |
| theorem IsPointedApproximation.restrict_radius {X Y : Type*} | |
| [MetricSpace X] [MetricSpace Y] {p : X} {q : Y} {r R S ε : ℝ} | |
| (hr : 0 < r) (hS : 0 ≤ S) (hSR : S ≤ R) (hε : 0 ≤ ε) | |
| {f : X → Y} (hf : IsPointedApproximation p q r R ε f) : | |
| IsPointedApproximation p q r S (3 * ε) f := by | |
| have hlarge {x : X} (hx : dist x p ≤ S * r) : dist x p ≤ R * r := | |
| hx.trans (mul_le_mul_of_nonneg_right hSR hr.le) | |
| have hpp : dist p p ≤ R * r := by | |
| simp only [dist_self] | |
| exact mul_nonneg (hS.trans hSR) hr.le | |
| refine ⟨hf.1.trans (by linarith), fun x y hx hy => | |
| (hf.2.1 x y (hlarge hx) (hlarge hy)).trans (by linarith), ?_⟩ | |
| intro y hy | |
| obtain ⟨x, hx, hxy⟩ := hf.2.2 y (by linarith) | |
| refine ⟨x, ?_, hxy.trans (by linarith)⟩ | |
| have hd := (abs_le.mp (hf.2.1 x p hx hpp)).1 | |
| have ht := dist_triangle (f x) y (f p) | |
| have ht' := dist_triangle y q (f p) | |
| have hbase := hf.1 | |
| rw [dist_comm (f p)] at hbase | |
| apply (div_le_iff₀ hr).mp | |
| linarith | |
| end RegularPointCoordinates | |
| end OAI | |