openAI-math-dataset / lean /OAI /Analysis /IrrationalRotation /Model /FiniteKernelMixture.lean
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import Mathlib.Probability.Kernel.Composition.MeasureCompProd
import Mathlib.MeasureTheory.Measure.WithDensity
namespace OAI
open MeasureTheory ProbabilityTheory
open scoped ENNReal
namespace Invariant233.FiniteKernelMixture
variable {I X Y : Type*} [Fintype I] [MeasurableSpace X] [MeasurableSpace Y]
noncomputable def weightedKernel (κ : I → Kernel X Y) (w : I → X → ℝ≥0∞)
(hw : ∀ i, Measurable (w i)) : Kernel X Y where
toFun x := ∑ i, w i x • κ i x
measurable' := by
apply Measure.measurable_of_measurable_coe
intro s hs
simp only [Measure.finsetSum_apply, Measure.smul_apply, smul_eq_mul]
exact Finset.measurable_sum _ (fun i _ => (hw i).mul (Kernel.measurable_coe (κ i) hs))
noncomputable def normalizedKernel (κ : I → Kernel X Y) (w : I → X → ℝ≥0∞)
(hw : ∀ i, Measurable (w i)) : Kernel X Y :=
weightedKernel κ (fun i x => w i x / ∑ j, w j x)
(fun i => (hw i).div (Finset.measurable_sum _ (fun j _ => hw j)))
noncomputable def diagonalReplacementKernel (q : ℝ≥0∞) (p : I → ℝ≥0∞)
(u : I → X → ℝ≥0∞) (hu : ∀ i, Measurable (u i))
(ν : I → Measure X) : Kernel X X :=
normalizedKernel
(fun o : Option I => match o with
| none => Kernel.id
| some i => Kernel.const X (ν i))
(fun o x => match o with
| none => q
| some i => p i * u i x)
(fun o => by cases o with
| none => exact measurable_const
| some i => exact measurable_const.mul (hu i))
end Invariant233.FiniteKernelMixture
end OAI