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Add lean source and binary files (part 125)
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import OAI.Probability.MatroidProphet.SafeSamples
namespace OAI
namespace MatroidProphet
open Finset
variable {α : Type*} [Fintype α] [DecidableEq α]
attribute [local instance] Classical.propDecidable
noncomputable def safeEndpointParityCount (M : Matroid α) (hE : M.E = Set.univ)
(κ : ℕ) (D : ℕ → Set α) (G : ℕ → Finset α) (h : ℕ) (d : α) (C T : Finset α) (parity : Bool) : ℝ :=
∑ i ∈ range (pathHorizon h-1), if safeBirthEvent M hE κ D G h d (-(i:ℤ)) C T ∧
(-(i:ℤ)) % 2 = (if parity then 1 else 0) then 1 else 0
noncomputable def safeSampleCount (M : Matroid α) (hE : M.E = Set.univ)
(κ : ℕ) (D : ℕ → Set α) (G : ℕ → Finset α) (h : ℕ) (I C T : Finset α) (parity : Bool) : ℝ :=
∑ d ∈ I, safeEndpointParityCount M hE κ D G h d C T parity
omit [DecidableEq α] in
lemma safeSampleCount_parity_split (M : Matroid α) (hE : M.E = Set.univ)
(κ : ℕ) (D : ℕ → Set α) (G : ℕ → Finset α) (h : ℕ) (I C T : Finset α) :
safeSampleCount M hE κ D G h I C T false + safeSampleCount M hE κ D G h I C T true =
safeCountBeforeParity M hE κ D G h I C T := by
unfold safeSampleCount safeCountBeforeParity
rw [← sum_add_distrib]
apply sum_congr rfl
intro d hd
unfold safeEndpointParityCount safeEndpointCount
rw [← sum_add_distrib]
apply sum_congr rfl
intro i hi
have hm0 := Int.emod_nonneg (-(i:ℤ)) (by norm_num : (2:ℤ) ≠ 0)
have hm1 := Int.emod_lt_of_pos (-(i:ℤ)) (by norm_num : (0:ℤ) < 2)
have hm : (-(i:ℤ)) % 2 = 0 ∨ (-(i:ℤ)) % 2 = 1 := by omega
by_cases hs : safeBirthEvent M hE κ D G h d (-(i:ℤ)) C T
· rcases hm with hm | hm <;> simp [hs, hm]
· simp [hs]
noncomputable def fairParityExpectation (f : Bool → ℝ) : ℝ := (f false + f true) / 2
omit [DecidableEq α] in
lemma safeSampleCount_fair_parity (M : Matroid α) (hE : M.E = Set.univ)
(κ : ℕ) (D : ℕ → Set α) (G : ℕ → Finset α) (h : ℕ) (I C T : Finset α) :
fairParityExpectation (safeSampleCount M hE κ D G h I C T) =
safeCountBeforeParity M hE κ D G h I C T / 2 := by
unfold fairParityExpectation
rw [safeSampleCount_parity_split]
theorem safeSampleCount_lower (M : Matroid α) (hE : M.E = Set.univ)
(κ : ℕ) (hκ : 0 < κ) (D : ℕ → Set α) (G : ℕ → Finset α)
(hG : Pairwise (fun i j => Disjoint (G i) (G j))) (q : α → ℝ)
(hq0 : ∀ e, 0 ≤ q e) (hq1 : ∀ e, q e ≤ 1)
(h : ℕ) (I : Finset α) (hI : M.Indep (I : Set α)) :
(((2:ℝ)^12)⁻¹) / 4 * I.card - (D h).ncard / (κ:ℝ) ≤
bitsExpectation q univ (fun C => bitsExpectation q univ (fun T =>
fairParityExpectation (safeSampleCount M hE κ D G h I C T))) := by
have hpre := safeCountBeforeParity_lower M hE κ hκ D G hG q hq0 hq1 h I hI
have heq : bitsExpectation q univ (fun C => bitsExpectation q univ (fun T =>
fairParityExpectation (safeSampleCount M hE κ D G h I C T))) =
(bitsExpectation q univ (fun C => bitsExpectation q univ (safeCountBeforeParity M hE κ D G h I C))) / 2 := by
simp only [safeSampleCount_fair_parity, div_eq_mul_inv]
rw [show bitsExpectation q univ (fun C => bitsExpectation q univ (fun T =>
safeCountBeforeParity M hE κ D G h I C T * (2:ℝ)⁻¹)) =
bitsExpectation q univ (fun C => bitsExpectation q univ (safeCountBeforeParity M hE κ D G h I C) * (2:ℝ)⁻¹) from by
apply bitsExpectation_congr; intro C hC; exact bitsExpectation_mul_right q univ _ _]
exact bitsExpectation_mul_right q univ _ _
rw [heq]
have hnonneg : 0 ≤ (D h).ncard / (κ:ℝ) := div_nonneg (Nat.cast_nonneg _) (Nat.cast_nonneg _)
linarith
omit [Fintype α] [DecidableEq α] in
lemma sum_unique_indicators {ι : Type*} (J : Finset ι) (p : ι → Prop) [DecidablePred p]
(huniq : ∀ i ∈ J, ∀ j ∈ J, p i → p j → i = j) :
(∑ i ∈ J, if p i then (1:ℝ) else 0) = if ∃ i ∈ J, p i then 1 else 0 := by
classical
by_cases hex : ∃ i ∈ J, p i
· obtain ⟨i, hi, hp⟩ := hex
rw [ite_eq_left ⟨i, hi, hp⟩]
calc
_ = if p i then (1:ℝ) else 0 := by
apply sum_eq_single i
· intro j hj hji
exact ite_eq_right (fun hjp => hji (huniq j hj i hi hjp hp))
· intro hnot
exact (hnot hi).elim
_ = 1 := ite_eq_left hp
· rw [ite_eq_right hex]
apply sum_eq_zero
intro i hi
exact ite_eq_right (fun hp => hex ⟨i, hi, hp⟩)
noncomputable def IsSafeSample (M : Matroid α) (hE : M.E = Set.univ)
(κ : ℕ) (D : ℕ → Set α) (G : ℕ → Finset α) (h : ℕ) (d : α) (C T : Finset α) (parity : Bool) : Prop :=
let b := nominalBirth M hE κ D (fun i => (C : Set α) ∩ (G i : Set α)) h d
activation h + 2 ≤ b ∧ b ≤ 0 ∧ b % 2 = (if parity then 1 else 0) ∧
d ∉ densityExpansion M hE κ (D h)
(guardedPath M hE κ D (fun i => (C : Set α) ∩ (G i : Set α)) h (b-2) ∪
lowerCompetition M hE κ D (fun i => (C : Set α) ∩ (G i : Set α))
(fun i => (T : Set α) ∩ (G i : Set α)) b h)
omit [DecidableEq α] in
lemma isSafeSample_iff_endpoint (M : Matroid α) (hE : M.E = Set.univ)
(κ : ℕ) (D : ℕ → Set α) (G : ℕ → Finset α) (h : ℕ) (d : α) (C T : Finset α) (parity : Bool) :
IsSafeSample M hE κ D G h d C T parity ↔ ∃ i ∈ range (pathHorizon h-1),
safeBirthEvent M hE κ D G h d (-(i:ℤ)) C T ∧ (-(i:ℤ)) % 2 = (if parity then 1 else 0) := by
let b := nominalBirth M hE κ D (fun i => (C : Set α) ∩ (G i : Set α)) h d
have ht := activation_add_horizon h
have hH := pathHorizon_pos h
constructor
· rintro ⟨hlo, hhi, hp, hs⟩
have hi0 : 0 ≤ -b := by omega
have hieq : -(((-b).toNat:ℕ):ℤ) = b := by rw [Int.toNat_of_nonneg hi0]; omega
refine ⟨(-b).toNat, mem_range.mpr ?_, ?_, ?_⟩
· have hiNat := Int.toNat_of_nonneg hi0
change activation h + 2 ≤ b at hlo
omega
· rw [hieq]
exact ⟨rfl, hs⟩
· simpa only [hieq] using hp
· rintro ⟨i, hi, hs, hp⟩
have hbirth := hs.1
have hbound := mem_range.mp hi
change _ ∧ _ ∧ _ ∧ _
rw [hbirth]
exact ⟨by omega, by omega, hp, hs.2⟩
noncomputable def safeSampleSet (M : Matroid α) (hE : M.E = Set.univ)
(κ : ℕ) (D : ℕ → Set α) (G : ℕ → Finset α) (h : ℕ) (I C T : Finset α) (parity : Bool) : Finset α :=
I.filter (fun d => IsSafeSample M hE κ D G h d C T parity)
omit [DecidableEq α] in
lemma safeSampleCount_eq_card (M : Matroid α) (hE : M.E = Set.univ)
(κ : ℕ) (D : ℕ → Set α) (G : ℕ → Finset α) (h : ℕ) (I C T : Finset α) (parity : Bool) :
safeSampleCount M hE κ D G h I C T parity = (safeSampleSet M hE κ D G h I C T parity).card := by
unfold safeSampleCount safeSampleSet
have hpoint (d : α) : safeEndpointParityCount M hE κ D G h d C T parity =
if IsSafeSample M hE κ D G h d C T parity then 1 else 0 := by
unfold safeEndpointParityCount
rw [sum_unique_indicators]
· simp only [← isSafeSample_iff_endpoint]
· intro i hi j hj hsi hsj
have hbi := hsi.1.1
have hbj := hsj.1.1
omega
simp_rw [hpoint]
simp
end MatroidProphet
end OAI