openAI-math-dataset / lean /OAI /Probability /SKGap /Entropy /WeightedRateAssembly.lean
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import Mathlib
import OAI.Probability.SKGap.Localization.ScalarEmpirical
namespace OAI
section
noncomputable section
namespace SKGap
open MeasureTheory ProbabilityTheory Real Set
open scoped ENNReal
lemma weighted_four_region_bound {α : Type*} [MeasurableSpace α] (μ : Measure α)
(f g : α → ℝ≥0∞) (hg : Measurable g) (B F D : Set α)
(hB : MeasurableSet B) (hF : MeasurableSet F) (hD : MeasurableSet D)
(hfg : ∀ x, f x ≤ g x) (k : ℝ≥0∞)
(hgood : ∀ x ∈ B ∩ Fᶜ ∩ Dᶜ, f x ≤ g x*k) :
(∫⁻ x, f x ∂μ) ≤ (∫⁻ x in Bᶜ,g x ∂μ)+(∫⁻ x in B ∩ F,g x ∂μ)+
(∫⁻ x in D,g x ∂μ)+(∫⁻ x,g x ∂μ)*k := by
have bound (E : Set α) : (∫⁻ x in E,f x ∂μ) ≤ (∫⁻ x in E,g x ∂μ) := lintegral_mono hfg
have sub (E E' : Set α) (h : E ⊆ E') : (∫⁻ x in E,g x ∂μ) ≤ (∫⁻ x in E',g x ∂μ) :=
lintegral_mono_set h
have hgood' : (∫⁻ x in B ∩ Fᶜ ∩ Dᶜ,f x ∂μ) ≤ (∫⁻ x,g x ∂μ)*k := by
calc
_ ≤ ∫⁻ x in B ∩ Fᶜ ∩ Dᶜ,g x*k ∂μ :=
lintegral_mono_ae (ae_restrict_of_forall_mem ((hB.inter hF.compl).inter hD.compl) hgood)
_ = (∫⁻ x in B ∩ Fᶜ ∩ Dᶜ,g x ∂μ)*k := lintegral_mul_const _ hg
_ ≤ (∫⁻ x,g x ∂μ)*k := mul_le_mul' (lintegral_mono' Measure.restrict_le_self le_rfl) le_rfl
have h3 := (lintegral_split_le μ f (B ∩ Fᶜ) D).trans
(add_le_add ((bound _).trans (sub _ _ (fun _ h=>h.2))) hgood')
have h2 := (lintegral_split_le μ f B F).trans (add_le_add (bound _) h3)
have h1 := (lintegral_split_le μ f univ B).trans (add_le_add
(by simpa only [univ_inter] using h2) (by simpa only [univ_inter] using bound Bᶜ))
simpa only [Measure.restrict_univ,add_comm,add_left_comm,add_assoc] using h1
end SKGap
end
end
end OAI