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760f90e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 | import OAI.Computability.UniqueGames.Foundations.FiniteTrialsLemmas
namespace OAI
section
/-! An actual finite probability rectangle implementing all thresholds from a
fixed finite list. The seed distribution is shared; each local acceptance test
depends only on its own density. -/
namespace UniqueGamesTheorem.Foundations.CorrelatedSampling
noncomputable section
variable {α : Type*} [Fintype α]
private theorem sum_div_const {ι : Type*} [Fintype ι] (f : ι → ℝ) (c : ℝ) :
(∑ i, f i) / c = ∑ i, f i / c := by
simp only [div_eq_mul_inv, Finset.sum_mul]
abbrev RectangleSeed (thresholds : List ℝ) (α : Type*) :=
α × Fin (thresholdPartition thresholds).length
def rectangleWeight (thresholds : List ℝ) (seed : RectangleSeed thresholds α) : ℝ :=
((thresholdPartition thresholds)[seed.2].hi - (thresholdPartition thresholds)[seed.2].lo) /
(Fintype.card α : ℝ)
def rectangleAccept (thresholds : List ℝ) (density : α → ℝ)
(seed : RectangleSeed thresholds α) : Bool :=
decide ((thresholdPartition thresholds)[seed.2].lo < density seed.1)
theorem rectangleWeight_nonnegative (thresholds : List ℝ) (seed : RectangleSeed thresholds α) :
0 ≤ rectangleWeight thresholds seed :=
div_nonneg (sub_nonneg.mpr ((thresholdPartition thresholds)[seed.2].valid)) (by positivity)
theorem rectangleWeight_normalized [Nonempty α] (thresholds : List ℝ) :
∑ seed : RectangleSeed thresholds α, rectangleWeight thresholds seed = 1 := by
rw [Fintype.sum_prod_type]
have hrow (a : α) : (∑ i, rectangleWeight thresholds (a, i)) =
1 / (Fintype.card α : ℝ) := by
unfold rectangleWeight
rw [← sum_div_const, sum_interval_get (fun I => I.hi - I.lo), partition_total_mass]
simp_rw [hrow]
have hc : (Fintype.card α : ℝ) ≠ 0 := by exact_mod_cast Fintype.card_ne_zero
simp [hc]
def rectangleDistribution [Nonempty α] (thresholds : List ℝ) :
Games.FiniteDistribution (RectangleSeed thresholds α) where
weight := rectangleWeight thresholds
nonnegative := rectangleWeight_nonnegative thresholds
normalized := rectangleWeight_normalized thresholds
theorem rectangle_row_mass (thresholds : List ℝ) (density : α → ℝ) (a : α)
(hm : density a ∈ thresholds) (h0 : 0 ≤ density a) (h1 : density a ≤ 1) :
(∑ i, if rectangleAccept thresholds density (a, i) then
rectangleWeight thresholds (a, i) else 0) = density a / (Fintype.card α : ℝ) := by
calc
_ = (∑ i : Fin (thresholdPartition thresholds).length,
if (thresholdPartition thresholds)[i].lo < density a then
(thresholdPartition thresholds)[i].hi - (thresholdPartition thresholds)[i].lo else 0) /
(Fintype.card α : ℝ) := by
rw [sum_div_const]
apply Finset.sum_congr rfl
intro i _
simp [rectangleAccept, rectangleWeight, ite_div]
_ = density a / (Fintype.card α : ℝ) := by
rw [sum_interval_get (fun I => if I.lo < density a then I.hi - I.lo else 0),
partition_acceptance_mass thresholds (density a) hm h0 h1]
theorem rectangle_acceptance_mass (thresholds : List ℝ) (density : α → ℝ)
(hm : ∀ a, density a ∈ thresholds) (h0 : ∀ a, 0 ≤ density a)
(h1 : ∀ a, density a ≤ 1) :
eventMass (rectangleWeight thresholds) (rectangleAccept thresholds density) =
(∑ a, density a) / (Fintype.card α : ℝ) := by
unfold eventMass
rw [Fintype.sum_prod_type]
simp_rw [rectangle_row_mass thresholds density _ (hm _) (h0 _) (h1 _)]
rw [sum_div_const]
theorem rectangle_label_mass [DecidableEq α] (thresholds : List ℝ) (density : α → ℝ) (a : α)
(hm : ∀ x, density x ∈ thresholds) (h0 : ∀ x, 0 ≤ density x)
(h1 : ∀ x, density x ≤ 1) :
eventMass (rectangleWeight thresholds)
(fun seed => rectangleAccept thresholds density seed && decide (seed.1 = a)) =
density a / (Fintype.card α : ℝ) := by
unfold eventMass
rw [Fintype.sum_prod_type]
calc
_ = ∑ x : α, if x = a then density x / (Fintype.card α : ℝ) else 0 := by
apply Finset.sum_congr rfl
intro x _
by_cases hx : x = a
· simpa [hx] using rectangle_row_mass thresholds density x (hm x) (h0 x) (h1 x)
· simp [hx]
_ = density a / (Fintype.card α : ℝ) := by simp
omit [Fintype α] in theorem rectangle_and (thresholds : List ℝ) (p q : α → ℝ) :
(fun seed => rectangleAccept thresholds p seed && rectangleAccept thresholds q seed) =
rectangleAccept thresholds (fun a => min (p a) (q a)) := by
funext seed
simp [rectangleAccept]
omit [Fintype α] in theorem rectangle_or (thresholds : List ℝ) (p q : α → ℝ) :
(fun seed => rectangleAccept thresholds p seed || rectangleAccept thresholds q seed) =
rectangleAccept thresholds (fun a => max (p a) (q a)) := by
funext seed
simp [rectangleAccept]
theorem min_mem_thresholds (thresholds : List ℝ) {x y : ℝ} (hx : x ∈ thresholds)
(hy : y ∈ thresholds) : min x y ∈ thresholds := by
by_cases h : x ≤ y <;> simp [min_def, h, hx, hy]
theorem max_mem_thresholds (thresholds : List ℝ) {x y : ℝ} (hx : x ∈ thresholds)
(hy : y ∈ thresholds) : max x y ∈ thresholds := by
by_cases h : x ≤ y <;> simp [max_def, h, hx, hy]
theorem rectangle_union_mass (thresholds : List ℝ) (p q : α → ℝ)
(hpm : ∀ a, p a ∈ thresholds) (hqm : ∀ a, q a ∈ thresholds)
(hp0 : ∀ a, 0 ≤ p a) (_hq0 : ∀ a, 0 ≤ q a)
(hp1 : ∀ a, p a ≤ 1) (hq1 : ∀ a, q a ≤ 1) :
eventMass (rectangleWeight thresholds)
(fun seed => rectangleAccept thresholds p seed || rectangleAccept thresholds q seed) =
unionMass p q / (Fintype.card α : ℝ) := by
rw [rectangle_or]
exact rectangle_acceptance_mass thresholds _
(fun a => max_mem_thresholds thresholds (hpm a) (hqm a))
(fun a => (hp0 a).trans (le_max_left _ _)) (fun a => max_le (hp1 a) (hq1 a))
theorem rectangle_common_label_mass [DecidableEq α] (thresholds : List ℝ)
(p q : α → ℝ) (a : α)
(hpm : ∀ x, p x ∈ thresholds) (hqm : ∀ x, q x ∈ thresholds)
(hp0 : ∀ x, 0 ≤ p x) (hq0 : ∀ x, 0 ≤ q x)
(hp1 : ∀ x, p x ≤ 1) (_hq1 : ∀ x, q x ≤ 1) :
eventMass (rectangleWeight thresholds)
(fun seed => (rectangleAccept thresholds p seed && rectangleAccept thresholds q seed) &&
decide (seed.1 = a)) = min (p a) (q a) / (Fintype.card α : ℝ) := by
have hand := congrFun (rectangle_and thresholds p q)
simp_rw [hand]
exact rectangle_label_mass thresholds _ a
(fun x => min_mem_thresholds thresholds (hpm x) (hqm x))
(fun x => le_min (hp0 x) (hq0 x)) (fun x => (min_le_left _ _).trans (hp1 x))
end
end UniqueGamesTheorem.Foundations.CorrelatedSampling
end
end OAI
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