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Add lean source and binary files (part 128)
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import Mathlib
import OAI.Probability.SKRatio.Quantization.BinFunctional
namespace OAI
noncomputable section
open scoped BigOperators Matrix
open MeasureTheory ProbabilityTheory Filter Real
namespace SKRatio.Bins
open Planted Scalar SKRatioClock.Regression MatrixNet Calculus
variable {α : Type*} [Fintype α] [DecidableEq α] {n : ℕ}
attribute [local instance] Classical.propDecidable
lemma norm_of_sum_sq_one {p : Fin n → ℝ} (hp : ∑ i, p i^2=1) :
‖WithLp.toLp 2 p‖=1 := by
have he := EuclideanSpace.real_norm_sq_eq (WithLp.toLp 2 p)
simp only [hp] at he
nlinarith only [he,norm_nonneg (WithLp.toLp 2 p)]
lemma quadratic_vector_difference (M : Matrix (Fin n) (Fin n) ℝ)
{p q : Fin n → ℝ} (hp : ∑ i, p i^2=1) (hq : ∑ i, q i^2=1) :
|quadratic M p-quadratic M q| ≤
2*euclideanOpNorm M*‖WithLp.toLp 2 (fun i => p i-q i)‖ := by
let A := Matrix.toEuclideanCLM (𝕜 := ℝ) M
let P : EuclideanSpace ℝ (Fin n) := WithLp.toLp 2 p
let Q : EuclideanSpace ℝ (Fin n) := WithLp.toLp 2 q
have hP : ‖P‖=1 := norm_of_sum_sq_one hp
have hQ : ‖Q‖=1 := norm_of_sum_sq_one hq
have he : inner ℝ P (A P)-inner ℝ Q (A Q) =
inner ℝ (P-Q) (A P)+inner ℝ Q (A (P-Q)) := by
simp only [map_sub,inner_sub_left,inner_sub_right]
ring
rw [quadratic_inner,quadratic_inner]
change |inner ℝ P (A P)-inner ℝ Q (A Q)|≤_
rw [he]
have h1 := (abs_real_inner_le_norm (P-Q) (A P)).trans
(mul_le_mul_of_nonneg_left (A.le_opNorm P) (norm_nonneg _))
have h2 := (abs_real_inner_le_norm Q (A (P-Q))).trans
(mul_le_mul_of_nonneg_left (A.le_opNorm (P-Q)) (norm_nonneg _))
rw [hP] at h1
rw [hQ] at h2
have ht := abs_add_le (inner ℝ (P-Q) (A P)) (inner ℝ Q (A (P-Q)))
change |inner ℝ (P-Q) (A P)+inner ℝ Q (A (P-Q))|≤2*‖A‖*‖P-Q‖
nlinarith only [ht,h1,h2]
lemma variance_bilinear_difference (M : Matrix (Fin n) (Fin n) ℝ)
(v : Fin n → ℝ) (hv : ∀ i, |v i|≤1)
{p q : Fin n → ℝ} (hp : ∑ i, p i^2=1) (hq : ∑ i, q i^2=1) :
|p ⬝ᵥ (M*ᵥ(fun i => v i*p i))-q ⬝ᵥ (M*ᵥ(fun i => v i*q i))|≤
2*euclideanOpNorm M*‖WithLp.toLp 2 (fun i => p i-q i)‖ := by
have he (p : Fin n → ℝ) : p ⬝ᵥ (M*ᵥ(fun i => v i*p i))=
quadratic (M*Matrix.diagonal v) p := by
simp only [quadratic,Matrix.mul_diagonal,dotProduct,Matrix.mulVec,Finset.mul_sum]
apply Finset.sum_congr rfl
intro i _
apply Finset.sum_congr rfl
intro j _
ring
rw [he,he]
apply (quadratic_vector_difference _ hp hq).trans
have hd := matrix_diagonal_opNorm_le v 1 (by norm_num) hv
have hn : euclideanOpNorm (M*Matrix.diagonal v)≤euclideanOpNorm M := by
unfold euclideanOpNorm
rw [map_mul]
exact (norm_mul_le _ _).trans ((mul_le_mul_of_nonneg_left hd (norm_nonneg _)).trans_eq (mul_one _))
gcongr
abbrev WeightBox (α : Type*) := α → Set.Icc (0:ℝ) 1
lemma binT_le_one [Nonempty (Fin n)] (σ : Fin n → α) (a : α) : binT σ a≤1 := by
have hs : binT σ a^2≤1 := by
rw [←binT_unit σ]
exact Finset.single_le_sum (fun i _ => sq_nonneg (binT σ i)) (Finset.mem_univ a)
nlinarith only [hs]
def binBox [Nonempty (Fin n)] (σ : Fin n → α) : WeightBox α :=
fun a => ⟨binT σ a,binT_nonneg σ a,binT_le_one σ a⟩
omit [DecidableEq α] in
lemma finiteA_parameter_tolerance (β : ℝ) (h : α → ℝ) {a : ℝ} (ha : 0<a) :
∃ δ : ℝ, 0<δ ∧ ∀ (t : WeightBox α) (z z' : Parameters α),
‖z.val-z'.val‖<δ →
|finiteA β (fun d => t d) h z-finiteA β (fun d => t d) h z'|<a := by
have hc : Continuous (fun q : WeightBox α × Parameters α =>
finiteA β (fun d => q.1 d) h q.2) := by
unfold finiteA moment
have hb (d : α) := (continuous_paramB d).comp (continuous_snd (X := WeightBox α))
have hr (d : α) := (continuous_paramR d).comp (continuous_snd (X := WeightBox α))
have ht (d : α) : Continuous (fun q : WeightBox α × Parameters α => (q.1 d:ℝ)) :=
continuous_subtype_val.comp ((continuous_apply d).comp continuous_fst)
fun_prop
obtain ⟨δ,hδ,hcont⟩ := Metric.uniformContinuous_iff.mp
(CompactSpace.uniformContinuous_of_continuous hc) a ha
refine ⟨δ,hδ,fun t z z' hh => ?_⟩
apply hcont (a := (t,z)) (b := (t,z'))
simp only [Prod.dist_eq,dist_self,Subtype.dist_eq,dist_eq_norm,max_lt_iff]
exact ⟨hδ,hh⟩
theorem binForm_finite_net (β : ℝ) (h : α → ℝ) {K a : ℝ} (hK : 0≤K) (ha : 0<a) :
∃ F : Finset (Parameters α), ∀ {n : ℕ} (_ : 0<n) (σ : Fin n → α),
(∀ d, 2≤count σ d) → ∀ M : Matrix (Fin n) (Fin n) ℝ,
euclideanOpNorm M≤K → ∀ (z : Parameters α) (u : Directions σ),
∃ z' ∈ F,
(vectorOf z u) ⬝ᵥ (M*ᵥ(fun i => v (h (σ i))*vectorOf z u i))+
finiteA β (binT σ) h z ≤
(vectorOf z' u) ⬝ᵥ (M*ᵥ(fun i => v (h (σ i))*vectorOf z' u i))+
finiteA β (binT σ) h z'+a := by
obtain ⟨δ,hδ,hA⟩ := finiteA_parameter_tolerance β h (show 0<a/2 by positivity)
let η := min δ (a/(4*K+1))
have hη : 0<η := lt_min hδ (by positivity)
obtain ⟨F,hF⟩ := parameters_finite_net (α := α) hη
refine ⟨F,?_⟩
intro n hn σ hc M hM z u
have : Nonempty (Fin n) := Fin.pos_iff_nonempty.mp hn
have hc' : ∀ d, 0<count σ d := fun d => lt_of_lt_of_le (by norm_num) (hc d)
obtain ⟨z',hz',hnear⟩ := hF z
refine ⟨z',hz',?_⟩
have hA' := (le_abs_self _).trans (hA (binBox σ) z z' (hnear.trans_le (min_le_left _ _))).le
have hdiff := variance_bilinear_difference M (fun i => v (h (σ i)))
(fun i => by rw [abs_of_nonneg (v_pos _).le]; exact v_le_one _)
(vectorOf_unit hc' z u) (vectorOf_unit hc' z' u)
rw [vectorOf_difference hc'] at hdiff
have hkd := mul_le_mul_of_nonneg_right hM (norm_nonneg (z.val-z'.val))
have hηd := (lt_div_iff₀ (by positivity : 0<4*K+1)).mp (hnear.trans_le (min_le_right _ _))
have habs := le_abs_self ((vectorOf z u) ⬝ᵥ (M*ᵥ (fun i => v (h (σ i))*vectorOf z u i))-
(vectorOf z' u) ⬝ᵥ (M*ᵥ (fun i => v (h (σ i))*vectorOf z' u i)))
change finiteA β (binT σ) h z-finiteA β (binT σ) h z'≤a/2 at hA'
nlinarith only [habs,hdiff,hkd,hηd,hA',norm_nonneg (z.val-z'.val)]
end SKRatio.Bins
end
end OAI