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Add lean source and binary files (part 125)
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import OAI.Probability.LatticePassage.Model
import Mathlib.Probability.Independence.InfinitePi
namespace OAI
namespace CompanionFPP
open MeasureTheory ProbabilityTheory Set
noncomputable instance environmentProbability : IsProbabilityMeasure environmentLaw :=
inferInstanceAs (IsProbabilityMeasure (Measure.infinitePi (fun _ : Edge => expMeasure 1)))
theorem edge_marginal (e : Edge) :
Measure.map (fun ω : Environment => ω e) environmentLaw = expMeasure 1 :=
Measure.infinitePi_map_eval _ e
theorem independent_edge_weights : iIndepFun (fun e (ω : Environment) => ω e) environmentLaw :=
iIndepFun_infinitePi (X := fun _ (x : ℝ) => x) (fun _ => measurable_id)
theorem exponential_positive : ∀ᵐ x ∂expMeasure 1, 0 < x := by
have hc : (expMeasure 1 (Iic 0)).toReal = 0 := by
rw [← measureReal_def, ← cdf_eq_real]
simp [cdf_expMeasure_eq (r := 1) (by norm_num)]
have hz : expMeasure 1 (Iic 0) = 0 :=
(ENNReal.toReal_eq_toReal_iff' (measure_ne_top _ _) ENNReal.zero_ne_top).mp
(by simpa using hc)
simpa only [ae_iff, not_lt, Iic] using hz
theorem all_edge_weights_positive : ∀ᵐ ω ∂environmentLaw, ∀ e, 0 < ω e := by
rw [ae_all_iff]
intro e
exact (measurePreserving_eval_infinitePi (fun _ : Edge => expMeasure 1) e).quasiMeasurePreserving.ae exponential_positive
theorem all_path_costs_nonnegative :
∀ᵐ ω ∂environmentLaw, ∀ x y (p : lattice.Walk x y), 0 ≤ pathCost ω p := by
filter_upwards [all_edge_weights_positive] with ω hω
intro x y p
exact pathCost_nonneg ω (fun e => (hω e).le) p
end CompanionFPP
end OAI