import Mathlib
import OAI.Computability.VertexCover.Games.Stochastic
import OAI.Computability.VertexCover.Games.Mixture

namespace OAI

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namespace UniqueGames.Foundations.Games.FiniteDistribution
open scoped BigOperators
noncomputable section
variable {A B C : Type*} [Fintype A] [Fintype B] [Fintype C]

theorem weight_eq_probability_singleton [DecidableEq A] (μ : FiniteDistribution A) (a : A) :
    μ.weight a = μ.probability (fun x => decide (x = a)) := by
  classical
  simp [probability]

theorem pushforward_comp (μ : FiniteDistribution A) (f : A → B) (g : B → C) :
    (μ.pushforward f).pushforward g = μ.pushforward (fun a => g (f a)) := by
  classical
  apply eq_of_weight_eq
  intro «c»
  rw [weight_eq_probability_singleton, weight_eq_probability_singleton]
  simp only [probability_pushforward]

theorem transport_eq_pushforward (μ : FiniteDistribution A) (e : A ≃ B) :
    μ.transport e = μ.pushforward e := by
  classical
  apply eq_of_weight_eq
  intro b
  rw [weight_eq_probability_singleton, weight_eq_probability_singleton,
    probability_transport, probability_pushforward]

theorem expectation_pushforward (μ : FiniteDistribution A) (f : A → B) (h : B → ℝ) :
    (μ.pushforward f).expectation h = μ.expectation (fun a => h (f a)) := by
  classical
  simp only [expectation, pushforward, Finset.sum_mul]
  rw [Finset.sum_comm]
  apply Finset.sum_congr rfl
  intro a _
  simp [ite_mul]

theorem pushforward_mixture (μ : FiniteDistribution A) (ν : A → FiniteDistribution B)
    (f : B → C) :
    (μ.mixture ν).pushforward f = μ.mixture (fun a => (ν a).pushforward f) := by
  classical
  apply eq_of_weight_eq
  intro «c»
  rw [weight_eq_probability_singleton, weight_eq_probability_singleton]
  simp only [probability_pushforward, probability_mixture]

end
end UniqueGames.Foundations.Games.FiniteDistribution
end


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end OAI