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Add lean source and binary files (part 125)
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import OAI.Probability.MatroidProphet.SafeParity
import OAI.Probability.MatroidProphet.Residual.Statistics
namespace OAI
namespace MatroidProphet
open Finset Pivots
variable {α : Type*} [Fintype α] [DecidableEq α]
attribute [local instance] Classical.propDecidable
omit [DecidableEq α] in
lemma nominalBirth_eq_iff_departure (M : Matroid α) (hE : M.E = Set.univ)
(κ : ℕ) (D C : ℕ → Set α) (h : ℕ) (d : α) (hd : d ∉ M.closure ∅) (b : ℤ) :
nominalBirth M hE κ D C h d = b ↔
d ∈ nominalPath M hE κ D C h b ∧ d ∉ nominalPath M hE κ D C h (b-1) := by
rw [mem_nominal_iff_birth_le M hE κ D C h d hd b,
mem_nominal_iff_birth_le M hE κ D C h d hd (b-1)]
omega
omit [DecidableEq α] in
lemma isSafeSample_iff_window (M : Matroid α) (hE : M.E = Set.univ)
(κ : ℕ) (D : ℕ → Set α) (G : ℕ → Finset α) (h : ℕ) (U : Set α) (I C T : Finset α)
(hIU : (I : Set α) ⊆ U) (d : α) (hdI : d ∈ I) (hd : d ∉ M.closure ∅) (parity : Bool) :
IsSafeSample M hE κ D G h d C T parity ↔
∃ b : ParityWindow (activation h) (boolParity parity),
d ∈ safeLayerSet M hE κ D (fun i => (C : Set α) ∩ (G i : Set α))
(fun i => (T : Set α) ∩ (G i : Set α)) h U (I : Set α) (boolParity parity) b := by
constructor
· intro hs
obtain ⟨hlo, hhi, hp, hex⟩ := hs
let birth := nominalBirth M hE κ D (fun i => (C : Set α) ∩ (G i : Set α)) h d
have hbwin : birth ∈ Set.Icc (activation h-2) 1 := by
change activation h+2 ≤ birth at hlo
change birth ≤ 0 at hhi
constructor <;> omega
have hbpar : birth % 2 = ((boolParity parity).val : ℤ) := by
rw [boolParity_val]
exact hp
refine ⟨⟨⟨birth, hbwin⟩, hbpar⟩, ?_⟩
have hdep := (nominalBirth_eq_iff_departure M hE κ D _ h d hd birth).mp rfl
exact ⟨⟨hdI, hIU hdI, hlo, hhi, hdep.1, hdep.2⟩, hex⟩
· rintro ⟨b, hb⟩
rcases hb with ⟨⟨_, _, hlo, hhi, hmem, hnot⟩, hex⟩
have hbirth := (nominalBirth_eq_iff_departure M hE κ D _ h d hd b.val.val).mpr ⟨hmem, hnot⟩
unfold IsSafeSample
rw [hbirth]
have hp := b.property.trans (boolParity_val parity)
exact ⟨hlo, hhi, hp, hex⟩
theorem safeSampleCount_eq_layerStatistic
{α : Type u_1} [Fintype α] [DecidableEq α] (M : Matroid α) (hE : M.E = Set.univ)
(κ : ℕ) (D : ℕ → Set α) (G : ℕ → Finset α) (h : ℕ) (U : Set α) (I C T : Finset α)
(hIU : (I : Set α) ⊆ U) (hIL : ∀ d ∈ I, d ∉ M.closure ∅) (parity : Bool) :
safeSampleCount M hE κ D G h I C T parity =
(safeLayerStatistic M hE κ D (fun i => (C : Set α) ∩ (G i : Set α))
(fun i => (T : Set α) ∩ (G i : Set α)) h U (I : Set α) (boolParity parity) : ℝ) := by
let W := ParityWindow (activation h) (boolParity parity)
let L : W → Set α := safeLayerSet M hE κ D (fun i => (C : Set α) ∩ (G i : Set α))
(fun i => (T : Set α) ∩ (G i : Set α)) h U (I : Set α) (boolParity parity)
have hcount (b : W) : (L b).ncard = (I.filter (fun d => d ∈ L b)).card := by
have hs : L b = ((I.filter (fun d => d ∈ L b) : Finset α) : Set α) := by
ext d
constructor
· intro hd
exact mem_filter.mpr ⟨hd.1.1, hd⟩
· intro hd
exact (mem_filter.mp hd).2
exact (congrArg Set.ncard hs).trans (Set.ncard_coe_finset _)
have hlabel (d : α) (hd : d ∈ I) :
(∑ b : W, if d ∈ L b then (1:ℝ) else 0) = if IsSafeSample M hE κ D G h d C T parity then 1 else 0 := by
rw [sum_unique_indicators]
· have he : (∃ b ∈ (univ : Finset W), d ∈ L b) ↔ IsSafeSample M hE κ D G h d C T parity := by
simp only [mem_univ, true_and]
exact (isSafeSample_iff_window M hE κ D G h U I C T hIU d hd (hIL d hd) parity).symm
simp only [he]
· intro b hb c hc hdb hdc
by_contra hbc
have hdisj := nominalLayerSet_disjoint M hE κ D (fun i => (C : Set α) ∩ (G i : Set α))
h U (boolParity parity) hbc
exact Set.disjoint_left.mp hdisj hdb.1.2 hdc.1.2
calc
safeSampleCount M hE κ D G h I C T parity =
∑ d ∈ I, if IsSafeSample M hE κ D G h d C T parity then (1:ℝ) else 0 := by
rw [safeSampleCount_eq_card]
simp [safeSampleSet]
_ = ∑ d ∈ I, ∑ b : W, if d ∈ L b then (1:ℝ) else 0 :=
sum_congr rfl (fun d hd => (hlabel d hd).symm)
_ = ∑ b : W, ∑ d ∈ I, if d ∈ L b then (1:ℝ) else 0 := sum_comm
_ = ∑ b : W, ((L b).ncard : ℝ) := by
apply sum_congr rfl
intro b hb
rw [hcount]
simp
_ = _ := by simp only [safeLayerStatistic, Nat.cast_sum]; rfl
theorem safeLayerStatistic_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) (U I : Set α) (hIU : I ⊆ U) (hI : M.Indep I) :
(((2:ℝ)^12)⁻¹) / 4 * I.ncard - (D h).ncard / (κ:ℝ) ≤
bitsExpectation q univ (fun C => bitsExpectation q univ (fun T =>
fairParityExpectation (fun parity => (safeLayerStatistic M hE κ D
(fun i => (C : Set α) ∩ (G i : Set α)) (fun i => (T : Set α) ∩ (G i : Set α))
h U I (boolParity parity) : ℝ)))) := by
let J := I.toFinset
have hJI : (J : Set α) = I := by simp [J]
have hJcard : J.card = I.ncard := by rw [← Set.ncard_coe_finset, hJI]
have hJ : M.Indep (J : Set α) := hJI.symm ▸ hI
have hJU : (J : Set α) ⊆ U := hJI.symm ▸ hIU
have hl := safeSampleCount_lower M hE κ hκ D G hG q hq0 hq1 h J hJ
rw [hJcard] at hl
have heq : bitsExpectation q univ (fun C => bitsExpectation q univ (fun T =>
fairParityExpectation (safeSampleCount M hE κ D G h J C T))) =
bitsExpectation q univ (fun C => bitsExpectation q univ (fun T =>
fairParityExpectation (fun parity => (safeLayerStatistic M hE κ D
(fun i => (C : Set α) ∩ (G i : Set α)) (fun i => (T : Set α) ∩ (G i : Set α))
h U I (boolParity parity) : ℝ)))) := by
apply bitsExpectation_congr
intro C hC
apply bitsExpectation_congr
intro T hT
congr 1
funext parity
rw [safeSampleCount_eq_layerStatistic M hE κ D G h U J C T hJU
(fun d hd => indep_not_loop M J hJ hd) parity, hJI]
exact hl.trans_eq heq
end MatroidProphet
end OAI