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import Mathlib
import OAI.Combinatorics.MatchingCount.Complexity.OnlineHistoryCost
namespace OAI
namespace MatchingFPRAS.OnlineTrial
open TreeTyped PhysicalStream Polynomial OnlineGraph OnlineSample
noncomputable def initialWeightPolynomial : Polynomial ℕ := 2*X+3+statePolynomial
lemma initial_weight {G : GraphInput} [Nontrivial (Fin G.n)] (f : Edges→Edges) (p : Trial.Parameters G) :
weight (initial f p) ≤ initialWeightPolynomial.eval (sizeNorm p (graph f (ExecutableAdaptive.graphRep G))) := by
have hs:=history_size f p p.K (initial f p).2 (history_initial f p)
have hw:=weight_le_stateSize (initial f p).2
have hk:=(sizeNorm_fields p (graph f (ExecutableAdaptive.graphRep G))).2.1
rw [weight_prod]
have hl : weight (initial f p).1=2*p.K+1 := by simp only [initial,weight_replicate,show weight false=1 from rfl];omega
rw [hl]
simp only [initialWeightPolynomial,Polynomial.eval_add,Polynomial.eval_mul,Polynomial.eval_X,Polynomial.eval_ofNat]
omega
end MatchingFPRAS.OnlineTrial
namespace MatchingFPRAS.OnlineGuard
open TreeTyped PhysicalStream Polynomial OnlineGraph OnlineTrial
lemma trial_bound : ∃ q : Polynomial ℕ,∀ (G : GraphInput) [Nontrivial (Fin G.n)]
(f : Edges→Edges) (_hf : ∀ es e,e∈f es↔e∈es) (p : Trial.Parameters G),
trialRealizer.cost (OnlineTrial.initial f p)+(trial (OnlineTrial.initial f p)).worst weight≤
q.eval (sizeNorm p (graph f (ExecutableAdaptive.graphRep G))) := by
obtain ⟨q,hq⟩:=sweep_bound
obtain ⟨r,hr⟩:=work_checked
refine ⟨q+2*(r.comp statePolynomial),?_⟩
intro G inst f hf p
let n:=sizeNorm p (graph f (ExecutableAdaptive.graphRep G))
have hs:=hq G f hf p
have hb : (sweep (OnlineTrial.initial f p)).All (fun s=>checkedRealizer.cost s+(checked s).worst weight≤r.eval (statePolynomial.eval n)) :=
(sweep_history f hf p).mono (fun s hs=>(hr s).trans (polynomial_eval_monotone r (history_size f p 0 s hs)))
have h1:=Experiment.worst_le _ _ _ (hb.mono (fun s hs=>Nat.le_trans (Nat.le_add_right _ _) hs))
have h2:=Experiment.worst_le _ _ _ (hb.mono (fun s hs=>Nat.le_trans (Nat.le_add_left _ _) hs))
change sweepRealizer.cost _+(sweep _).worst checkedRealizer.cost+((sweep _).bind checked).worst weight≤_
rw [Experiment.worst_bind]
simp only [Polynomial.eval_add,Polynomial.eval_mul,Polynomial.eval_ofNat,Polynomial.eval_comp]
dsimp only [n] at *
omega
end MatchingFPRAS.OnlineGuard
namespace MatchingFPRAS.OnlineAmplification
open TreeTyped PhysicalStream Polynomial OnlineGraph OnlineTrial OnlineSample
lemma run_bound : ∃ q : Polynomial ℕ,∀ (G : GraphInput) [Nontrivial (Fin G.n)]
(f : Edges→Edges) (_hf : ∀ es e,e∈f es↔e∈es) (p : Trial.Parameters G) (r : ℕ),
runRealizer.cost (r,OnlineTrial.initial f p)+(run (r,OnlineTrial.initial f p)).worst weight≤
q.eval (r+sizeNorm p (graph f (ExecutableAdaptive.graphRep G))) := by
obtain ⟨q,hq⟩:=OnlineGuard.trial_bound
obtain ⟨s,hs⟩:=OnlineTree.traverse_bound OnlineGuard.trialRealizer
obtain ⟨u,hu⟩:=work_repeatInput (A:=TrialInput)
obtain ⟨v,hv⟩:=OnlineMedian.polynomial_median
let I := initialWeightPolynomial
let R : Polynomial ℕ := 5*X+2+I
let B : Polynomial ℕ := X*(I+1)+1+q
let T := u.comp R+s.comp B
refine ⟨T+2*(v.comp T),?_⟩
intro G inst f hf p r
let n:=sizeNorm p (graph f (ExecutableAdaptive.graphRep G))
let z:=r+n
let x : TrialInput:=OnlineTrial.initial f p
have hn:n≤z := by dsimp [z];omega
have hr:r≤z := by dsimp [z];omega
have hx : weight x≤I.eval z := (initial_weight f p).trans (polynomial_eval_monotone I hn)
have hinput : r+weight (r,x) ≤R.eval z := by
have hw:=weight_nat_numeric r
simp only [weight_prod,R,Polynomial.eval_add,Polynomial.eval_mul,Polynomial.eval_X,Polynomial.eval_ofNat]
omega
have hrep := (hu (r,x)).trans (polynomial_eval_monotone u hinput)
have hwrep : weight (List.replicate r x)≤B.eval z := by
rw [weight_replicate]
simp only [B,Polynomial.eval_add,Polynomial.eval_mul,Polynomial.eval_X,Polynomial.eval_one]
nlinarith
have ht : ∀ a∈List.replicate r x,OnlineGuard.trialRealizer.cost a+(OnlineGuard.trial a).worst weight≤B.eval z := by
intro a ha
have he: a=x := (List.mem_replicate.mp ha).2
rw [he]
exact ((hq G f hf p).trans (polynomial_eval_monotone q hn)).trans (by
simp only [B,Polynomial.eval_add,Polynomial.eval_mul,Polynomial.eval_X,Polynomial.eval_one];omega)
have htrav:=hs (List.replicate r x) (B.eval z) hwrep ht
have htrial : trialsRealizer.cost (r,x)+(trials (r,x)).worst weight≤T.eval z := by
change repeatInputRealizer.cost (r,x)+(OnlineTree.traverse OnlineGuard.trialRealizer).cost (List.replicate r x)+
(OnlineTree.traverseM OnlineGuard.trial (List.replicate r x)).worst weight≤_
simp only [T,Polynomial.eval_add,Polynomial.eval_comp]
change repeatInputRealizer.cost (r,x)+weight (List.replicate r x)≤u.eval (R.eval z) at hrep
omega
have htail : (trials (r,x)).worst (fun as=>OnlineMedian.medianRealizer.cost as+weight (OnlineMedian.median as))≤v.eval (T.eval z) := by
apply Experiment.worst_le _ _ _
exact (Experiment.all_worst (trials (r,x)) weight).mono (fun as hw=>(hv as).trans
(polynomial_eval_monotone v (hw.trans (by omega))))
have hcost : (trials (r,x)).worst OnlineMedian.medianRealizer.cost≤v.eval (T.eval z) :=
(Experiment.worst_mono _ _ _ ((Experiment.all_true _).mono (fun _ _=>Nat.le_add_right _ _))).trans htail
have hout : (trials (r,x)).worst (weight ∘ OnlineMedian.median)≤v.eval (T.eval z) :=
(Experiment.worst_mono _ _ _ ((Experiment.all_true _).mono (fun _ _=>Nat.le_add_left _ _))).trans htail
have hboth : (trials (r,x)).worst OnlineMedian.medianRealizer.cost+
(trials (r,x)).worst (weight ∘ OnlineMedian.median)≤2*v.eval (T.eval z) := by omega
clear hcost hout htail
change trialsRealizer.cost (r,x)+(trials (r,x)).worst OnlineMedian.medianRealizer.cost+
(run (r,x)).worst weight≤_
rw [run,Experiment.worst_map]
simp only [Polynomial.eval_add,Polynomial.eval_mul,Polynomial.eval_ofNat,Polynomial.eval_comp]
change _ ≤ T.eval z+2*v.eval (T.eval z)
omega
end MatchingFPRAS.OnlineAmplification
end OAI