Download lean/OAI/Probability/PosteriorReplicas/Geometry/DensityBinsGeometry.lean from roseking/openAI-math-dataset: direct link, hf CLI and curl.
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| import OAI.Probability.PosteriorReplicas.Geometry.LabelEllipsoids | |
| namespace OAI | |
| open MeasureTheory ProbabilityTheory Set Matrix InnerProductSpace Filter Metric | |
| open scoped ENNReal NNReal RealInnerProductSpace Topology | |
| noncomputable section | |
| namespace PosteriorReplicas | |
| lemma affine_infDist_orthogonal {d : ℕ} (p x : Vec d) (U : Submodule ℝ (Vec d)) : | |
| Metric.infDist x (AffineSubspace.mk' p U : Set (Vec d)) = ‖Uᗮ.starProjection (x-p)‖ := by | |
| rw [PosteriorRegression.infDist_affine_mk', Submodule.starProjection_orthogonal_val, | |
| Submodule.starProjection_minimal, Metric.infDist_eq_iInf] | |
| simp only [dist_eq_norm] | |
| rfl | |
| def tupleDistance {d m : ℕ} (u : Tuple d m) (x : Vec d) : ℝ := | |
| ‖(differenceSpan u)ᗮ.starProjection (x-u 0)‖ | |
| lemma tupleDistance_eq_infDist {d m : ℕ} (u : Tuple d m) (x : Vec d) : | |
| tupleDistance u x = Metric.infDist x (AffineSubspace.mk' (u 0) (differenceSpan u) : Set (Vec d)) := | |
| (affine_infDist_orthogonal _ _ _).symm | |
| @[fun_prop] lemma measurable_tupleDistance_fixed {d m : ℕ} (u : Tuple d m) : | |
| Measurable (tupleDistance u) := by unfold tupleDistance; fun_prop | |
| lemma differenceSpan_finrank_le {d m : ℕ} (u : Tuple d m) : | |
| Module.finrank ℝ (differenceSpan u) ≤ m := by | |
| change Module.finrank ℝ (Submodule.span ℝ (range (differences u))) ≤ m | |
| simpa only [Set.finrank, Fintype.card_fin] using | |
| finrank_range_le_card (R := ℝ) (differences u) | |
| lemma tupleDistance_tube {d k m : ℕ} (hd : k+m+2 ≤ d) (u : Tuple d m) | |
| {f : Vec d → ℝ≥0∞} {L : ℝ≥0∞} (hfL : ∀ x, f x ≤ L) | |
| {r : ℝ} (hr : 0 < r) (hr1 : r ≤ 1) : | |
| (sphereLaw d).withDensity f {x | tupleDistance u x ≤ r} ≤ | |
| (L*ENNReal.ofReal ((72:ℝ)^d))*ENNReal.ofReal (r^(k+1)) := by | |
| let : NeZero d := ⟨by omega⟩ | |
| simp_rw [tupleDistance_eq_infDist] | |
| apply spherical_tilt_affine_tube hfL _ _ hr hr1 | |
| rw [AffineSubspace.direction_mk'] | |
| have h := differenceSpan_finrank_le u | |
| omega | |
| lemma tupleDistance_pos_ae {d m : ℕ} (hd : 3 ≤ d) (hm : m < d) (u : Tuple d m) | |
| (f : Vec d → ℝ≥0∞) : | |
| ∀ᵐ x ∂(sphereLaw d).withDensity f, 0 < tupleDistance u x := by | |
| let S := AffineSubspace.mk' (u 0) (differenceSpan u) | |
| have hz : sphereLaw d S = 0 := by | |
| apply base_affine_null hd .spherical S | |
| rw [AffineSubspace.direction_mk'] | |
| exact (differenceSpan_finrank_le u).trans_lt hm | |
| have hn : ∀ᵐ x ∂sphereLaw d, x ∉ S := by | |
| rw [ae_iff] | |
| simp only [not_not] | |
| convert hz using 2 | |
| ext x | |
| rfl | |
| filter_upwards [(withDensity_absolutelyContinuous (sphereLaw d) f).ae_le hn] with x hx | |
| rw [tupleDistance_eq_infDist] | |
| exact (S.closed_of_finiteDimensional.notMem_iff_infDist_pos | |
| ⟨u 0, AffineSubspace.self_mem_mk' _ _⟩).mp hx | |
| lemma labels_sub {d k : ℕ} (A : Rows d k) (x y : Vec d) : | |
| labels A (x-y) = labels A x - labels A y := by | |
| ext i | |
| simp [labels, inner_sub_right] | |
| lemma constrained_label_lift_le {d k : ℕ} {A : Rows d k} (hA : LinearIndependent ℝ A) | |
| (U : Submodule ℝ (Vec d)) (hU : ∀ i, A i ∈ Uᗮ) (p x : Vec d) : | |
| ‖liftLabel A (labels A x - labels A p)‖ ≤ ‖Uᗮ.starProjection (x-p)‖ := by | |
| have he : labels A (Uᗮ.starProjection (x-p)) = labels A (x-p) := by | |
| ext i | |
| change ⟪A i,Uᗮ.starProjection (x-p)⟫ = ⟪A i,x-p⟫ | |
| rw [← Uᗮ.inner_starProjection_left_eq_right, | |
| Uᗮ.starProjection_eq_self_iff.mpr (hU i)] | |
| rw [← labels_sub, ← he, liftLabel_eq_pairingLift] | |
| change ‖pairingLift A (fun i => ⟪A i,Uᗮ.starProjection (x-p)⟫)‖ ≤ _ | |
| rw [← starProjection_eq_pairingLift hA] | |
| exact Submodule.norm_starProjection_apply_le _ _ | |
| lemma constrained_tube_le_ellipsoid {d k m : ℕ} (ν : Measure (Vec d)) | |
| (u : Tuple d m) {A : Rows d k} (hA : LinearIndependent ℝ A) | |
| (hU : ∀ i, A i ∈ (differenceSpan u)ᗮ) (r : ℝ) : | |
| ν {x | tupleDistance u x ≤ r} ≤ | |
| ν {x | ‖liftLabel A (labels A x - labels A (u 0))‖ ≤ r} := by | |
| apply measure_mono | |
| intro x hx | |
| exact (constrained_label_lift_le hA _ hU _ _).trans hx | |
| lemma density_inverse_moment_bins {d k m : ℕ} (hd : k+m+2 ≤ d) | |
| (u : Tuple d m) {f : Vec d → ℝ≥0∞} {L : ℝ≥0∞} (hfL : ∀ x, f x ≤ L) | |
| [IsProbabilityMeasure ((sphereLaw d).withDensity f)] (J : ℕ) | |
| (hcut : (L*ENNReal.ofReal ((72:ℝ)^d))*ENNReal.ofReal ((1/2:ℝ)^J)* | |
| (1+(2:ℝ≥0∞)^(k+1)) ≤ 1) | |
| {A : Rows d k} (hA : LinearIndependent ℝ A) (hU : ∀ i, A i ∈ (differenceSpan u)ᗮ) : | |
| (∫⁻ x, ENNReal.ofReal ((tupleDistance u x)⁻¹^k) ∂(sphereLaw d).withDensity f) ≤ | |
| 2 + ∑ j ∈ Finset.range J, ENNReal.ofReal ((2:ℝ)^(k*(j+1))) * | |
| (sphereLaw d).withDensity f {x | ‖liftLabel A (labels A x-labels A (u 0))‖ ≤ (1/2:ℝ)^j} := by | |
| apply (inverse_moment_finite_bins _ (measurable_tupleDistance_fixed u) | |
| (fun x => norm_nonneg _) k J _ (fun r hr hr1 => tupleDistance_tube hd u hfL hr hr1) hcut).trans | |
| apply add_le_add le_rfl | |
| apply Finset.sum_le_sum | |
| intro j hj | |
| exact mul_le_mul' le_rfl (constrained_tube_le_ellipsoid _ u hA hU _) | |
| end PosteriorReplicas | |
| end | |
| end OAI | |