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Add lean source and binary files (part 59)
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import OAI.Computability.BinPacking.Inventory.IntegralSpeciesCounts
import OAI.Computability.BinPacking.Inventory.PhysicalPoolLift
import OAI.Computability.BinPacking.Packing.ConstructLocalState
import OAI.Computability.BinPacking.Packing.ExtractedCover
import OAI.Computability.BinPacking.Packing.LocalTemplateBases
namespace OAI
noncomputable section
namespace BinPackingGap.InventoryData
open scoped BigOperators
variable (D : InventoryData)
theorem card_template : Fintype.card D.Template = 2 * D.B := by
simp only [Template, Fintype.card_sigma, Fintype.card_prod, Fintype.card_bool,
D.card_localBin]
rw [← Finset.mul_sum]
rfl
def statePoolTemplates (hn : D.graph.n = 2 * D.k)
(S : ∀ v s, D.LocalState v s) :
PoolTemplates D.packingInstance D.Template (GlobalSpecies D.graph) FlagSpecies where
base := D.templateBase S
globalPool := D.physicalGlobalPool
flagPool := D.physicalFlagPool
globalSpecies := D.templateGlobalSpecies
flagSpecies := D.templateFlagSpecies
global_nonempty := by
intro t
apply (D.physicalGlobalPool_nonempty_iff _).mpr
have hc := D.doubled_stateGlobalSpecies_count hn (D.templateGlobalSpecies t)
have hp : 0 < (Finset.univ.filter (fun q : D.Template =>
D.templateGlobalSpecies q = D.templateGlobalSpecies t)).card := by
exact Finset.card_pos.mpr ⟨t, by simp⟩
change (Finset.univ.filter (fun q : D.Template =>
D.templateGlobalSpecies q = D.templateGlobalSpecies t)).card = _ at hc
omega
flag_nonempty := by
intro t
apply (D.physicalFlagPool_nonempty_iff _).mpr
have hc := D.doubled_stateFlagSpecies_count (D.templateFlagSpecies t)
have hp : 0 < (Finset.univ.filter (fun q : D.Template =>
D.templateFlagSpecies q = D.templateFlagSpecies t)).card := by
exact Finset.card_pos.mpr ⟨t, by simp⟩
change (Finset.univ.filter (fun q : D.Template =>
D.templateFlagSpecies q = D.templateFlagSpecies t)).card = _ at hc
omega
base_global := fun t =>
(D.labeledItems_disjoint_physicalGlobalPool (D.templateGlobalSpecies t)).mono_left
(D.templateBase_subset_labeledItems S t)
base_flag := fun t =>
(D.labeledItems_disjoint_physicalFlagPool (D.templateFlagSpecies t)).mono_left
(D.templateBase_subset_labeledItems S t)
global_flag := fun t => D.physicalGlobalPool_disjoint_physicalFlagPool
(D.templateGlobalSpecies t) (D.templateFlagSpecies t)
capacity := by
intro t u f
obtain ⟨j, hj⟩ := (D.mem_physicalGlobalPool (D.templateGlobalSpecies t) u.val).mp
u.property
obtain ⟨l, hl⟩ := (D.mem_physicalFlagPool (D.templateFlagSpecies t) f.val).mp
f.property
rw [← hj, ← hl]
exact D.templateBase_capacity S t ⟨D.templateGlobalSpecies t, j⟩
⟨D.templateFlagSpecies t, l⟩ rfl rfl
theorem statePoolTemplates_feasible (hn : D.graph.n = 2 * D.k)
(S : ∀ v s, D.LocalState v s) :
IndividualFeasible D.packingInstance (D.statePoolTemplates hn S).weights := by
apply (D.statePoolTemplates hn S).weights_feasible D.labeledItems
· exact D.templateBase_appearance_count S
· intro s
change (Finset.univ.filter (fun t : D.Template =>
D.templateGlobalSpecies t = s)).card = 2 * (D.physicalGlobalPool s).card
rw [D.card_physicalGlobalPool]
exact D.doubled_stateGlobalSpecies_count hn s
· intro f
change (Finset.univ.filter (fun t : D.Template =>
D.templateFlagSpecies t = f)).card = 2 * (D.physicalFlagPool f).card
rw [D.card_physicalFlagPool]
exact D.doubled_stateFlagSpecies_count f
· exact D.physicalInventory_indicator_partition
theorem statePoolTemplates_objective (hn : D.graph.n = 2 * D.k)
(S : ∀ v s, D.LocalState v s) :
FractionalCover.objective (D.statePoolTemplates hn S).weights = (D.B : ℝ) := by
rw [(D.statePoolTemplates hn S).objective_weights, D.card_template]
push_cast
ring
theorem ofCompetingTrees_physical_witness (G : GraphInput) {d : ℕ}
(T : CompetingTrees d) (hd : 0 < d) (R k : ℕ) (hn : G.n = 2 * k) :
∃ w : IndividualConfiguration (ofCompetingTrees G T R k).packingInstance → ℝ,
IndividualFeasible (ofCompetingTrees G T R k).packingInstance w ∧
FractionalCover.objective w = ((ofCompetingTrees G T R k).B : ℝ) := by
let D := ofCompetingTrees G T R k
let S : ∀ v s, D.LocalState v s := constructedLocalState G T hd R k
exact ⟨(D.statePoolTemplates hn S).weights,
D.statePoolTemplates_feasible hn S, D.statePoolTemplates_objective hn S⟩
theorem ofCompetingTrees_bothLP_eq (G : GraphInput) {d : ℕ}
(T : CompetingTrees d) (hd : 0 < d) (R k : ℕ) (hn : G.n = 2 * k) :
individualLP (ofCompetingTrees G T R k).packingInstance =
((ofCompetingTrees G T R k).B : ℝ) ∧
typeLP (ofCompetingTrees G T R k).packingInstance =
((ofCompetingTrees G T R k).B : ℝ) := by
obtain ⟨w, hw, hobj⟩ := ofCompetingTrees_physical_witness G T hd R k hn
exact bothLP_eq_of_physical_witness _ _
((ofCompetingTrees G T R k).packingInstance_n (by change k ≤ G.n; omega))
(fun i => ((ofCompetingTrees G T R k).packingInstance_size_mem_interval i).1)
w hw hobj
end BinPackingGap.InventoryData
end
namespace BinPackingGap
theorem reduction_bothLP_eq (c : ℕ) (rho : ℝ) (G : GraphInput) (k : ℕ)
(hn : G.n = 2 * k) :
individualLP (reductionInstance c rho G k) =
(reductionBinBound c rho G k : ℝ) ∧
typeLP (reductionInstance c rho G k) =
(reductionBinBound c rho G k : ℝ) :=
InventoryData.ofCompetingTrees_bothLP_eq G (reductionTrees c rho)
(depthDemand_pos c rho) _ k hn
end BinPackingGap
end OAI