import OAI.Combinatorics.BooleanFunctions.Projection import OAI.Combinatorics.BooleanFunctions.FiniteCLT namespace OAI open scoped BigOperators Topology NNReal ENNReal open MeasureTheory ProbabilityTheory Filter Real noncomputable section namespace SquareRootDegree namespace Observations attribute [local instance] Classical.propDecidable variable {γ β κ : Type*} [Fintype γ] [Fintype β] [Fintype κ] [DecidableEq γ] [DecidableEq κ] def cubeSum (x : Cube γ) : ℝ := ∑ i, sign (x i) def score (F : Cube γ → β) : Cube γ → ℝ := conditionalAverage F cubeSum def variance (F : Cube γ → β) : ℝ := average (fun x => (score F x)^2) omit [Fintype β] [Fintype κ] in theorem cubeSum_zero : average (cubeSum (γ := γ)) = 0 := by unfold cubeSum rw [average_sum] have hz : average sign = 0 := by norm_num [average,sign,Fintype.sum_bool] have hi (i : γ) : average (fun x : Cube γ => sign (x i)) = 0 := by calc _ = average sign := by convert average_pi_eval i sign using 1 congr 1 exact Subsingleton.elim _ _ _ = 0 := hz simp only [hi,Finset.sum_const_zero] omit [Fintype κ] in theorem score_zero (F : Cube γ → β) : average (score F) = 0 := by rw [score,average_conditionalAverage] exact cubeSum_zero omit [Fintype β] [DecidableEq γ] [DecidableEq κ] in theorem cubeSum_block (x : Cube (κ × γ)) : cubeSum x = ∑ j, cubeSum (fun i => x (j,i)) := by exact Fintype.sum_prod_type _ def grouped (F : Cube γ → β) (x : Cube (κ × γ)) : κ → β := fun j => F (fun i => x (j,i)) omit [DecidableEq γ] [DecidableEq κ] in theorem grouped_degree (F : Cube γ → β) (D : ℕ) (hF : ∀ b, fourierDegree (cell F b) ≤ D) (b : κ → β) : fourierDegree (cell (grouped F) b) ≤ Fintype.card κ*D := by have h := fourierDegree_comp_tuple_le (fun j x => F (fun i => x (j,i))) (fun _ : κ => D) (fun j a => fourierDegree_block_cell_le F D hF j a) (cell id b) have he : (fun x : Cube (κ × γ) => cell id b (fun j => F (fun i => x (j,i)))) = cell (grouped F) b := by funext x unfold cell grouped rfl rw [he] at h simpa only [Finset.sum_const,Finset.card_univ,smul_eq_mul] using h theorem grouped_score (F : Cube γ → β) : score (grouped (κ := κ) F) = fun x => ∑ j, score F (fun i => x (j,i)) := by let e := blockCurry κ γ Bool let G : (κ → Cube γ) → (κ → β) := fun x j => F (x j) let R : (κ → Cube γ) → ℝ := fun x => ∑ j, cubeSum (x j) have he : cubeSum (γ := κ × γ) = R ∘ e := by funext x; exact cubeSum_block x have hp := Projection.conditional_tuple_sum (ι := κ) F cubeSum have hc := Projection.conditional_equiv e G R have hscore : conditionalAverage (G ∘ e) (cubeSum (γ := κ × γ)) = (fun x => ∑ j, conditionalAverage F cubeSum (x j)) ∘ e := by rw [he,hc] exact congrArg (fun p => p ∘ e) hp convert hscore using 1 · unfold score congr 1 · unfold score funext x apply Finset.sum_congr rfl intro j _ congr 1 omit [Fintype β] [Fintype κ] [DecidableEq κ] in theorem variance_nonneg (F : Cube γ → β) : 0 ≤ variance F := average_nonneg (fun _ => sq_nonneg _) def standardValue (F : Cube γ → β) (b : β) : ℝ := (Real.sqrt (variance F))⁻¹*conditionalValue F cubeSum b def standard (F : Cube γ → β) (x : Cube γ) : ℝ := standardValue F (F x) omit [Fintype κ] [DecidableEq κ] in theorem standard_zero (F : Cube γ → β) : average (standard F) = 0 := by change average (fun x => (Real.sqrt (variance F))⁻¹*score F x) = 0 rw [average_const_mul,score_zero,mul_zero] omit [Fintype β] [Fintype κ] [DecidableEq κ] in theorem standard_sq (F : Cube γ → β) (hv : 0 < variance F) : average (fun x => (standard F x)^2) = 1 := by change average (fun x => ((Real.sqrt (variance F))⁻¹*score F x)^2) = 1 simp only [mul_pow,average_const_mul,inv_pow] rw [Real.sq_sqrt hv.le] exact inv_mul_cancel₀ hv.ne' end Observations end SquareRootDegree end end OAI