mathlib-initiative/mathlib-tactics huggingface dataset:
Module: Mathlib.Probability.Kernel.Composition.Prod

Goal state before:
pp: α : Type u_1
β : Type u_2
mα : MeasurableSpace α
mβ : MeasurableSpace β
γ : Type u_4
δ : Type u_5
mγ : MeasurableSpace γ
mδ : MeasurableSpace δ
κ : Kernel α β
inst✝² : IsSFiniteKernel κ
η : Kernel α γ
inst✝¹ : IsSFiniteKernel η
ξ : Kernel α δ
inst✝ : IsSFiniteKernel ξ
a : α
⊢ Measurable ⇑MeasurableEquiv.prodAssoc

Tactic:
fun_prop

Goal state after:
Module: Mathlib.Probability.Kernel.Composition.Prod

Goal state before:
pp: α : Type u_1
β : Type u_2
mα : MeasurableSpace α
mβ : MeasurableSpace β
γ : Type u_4
δ : Type u_5
mγ : MeasurableSpace γ
mδ : MeasurableSpace δ
κ : Kernel α β
inst✝² : IsSFiniteKernel κ
η : Kernel α γ
inst✝¹ : IsSFiniteKernel η
ξ : Kernel α δ
inst✝ : IsSFiniteKernel ξ
⊢ Measurable ⇑MeasurableEquiv.prodAssoc

Tactic:
fun_prop

Goal state after:
Module: Mathlib.Probability.Kernel.Composition.Prod

Goal state before:
pp: α : Type u_1
β : Type u_2
mα : MeasurableSpace α
mβ : MeasurableSpace β
γ : Type u_4
δ : Type u_5
mγ : MeasurableSpace γ
mδ : MeasurableSpace δ
κ : Kernel α β
inst✝² : IsSFiniteKernel κ
η : Kernel α γ
inst✝¹ : IsSFiniteKernel η
ξ : Kernel α δ
inst✝ : IsSFiniteKernel ξ
⊢ Measurable ⇑MeasurableEquiv.prodAssoc.symm

Tactic:
fun_prop

Goal state after:
Module: Mathlib.Probability.Kernel.Composition.CompProd

Goal state before:
pp: case pos
α : Type u_1
β : Type u_2
γ : Type u_3
mα : MeasurableSpace α
mβ : MeasurableSpace β
mγ : MeasurableSpace γ
κ : Kernel α β
inst✝¹ : IsSFiniteKernel κ
η : Kernel (α × β) γ
inst✝ : IsSFiniteKernel η
s : Set β
t : Set γ
hs : MeasurableSet s
ht : MeasurableSet t
a : α
u : Set (β × γ)
hu : MeasurableSet u
b : β
h : b ∈ s
⊢ (η (a, b)) {c | (b, c) ∈ u ∧ b ∈ s ∧ c ∈ t} = (η (a, b)) ({c | (b, c) ∈ u} ∩ t)

Tactic:
simp only [h, true_and, Set.inter_def, Set.mem_ofPred]

Goal state after:
Module: Mathlib.Probability.Kernel.Composition.CompProd

Goal state before:
pp: α : Type u_1
β : Type u_2
γ : Type u_3
mα : MeasurableSpace α
mβ : MeasurableSpace β
mγ : MeasurableSpace γ
κ : Kernel α β
inst✝¹ : IsSFiniteKernel κ
η : Kernel (α × β) γ
inst✝ : IsSFiniteKernel η
a : α
f : β → γ → ℝ≥0∞
hf : Measurable (Function.uncurry f)
F : ℕ → SimpleFunc (β × γ) ℝ≥0∞ := SimpleFunc.eapprox (Function.uncurry f)
h : ∀ (a : β) (b : γ), ⨆ n, (F n) (a, b) = f a b
h_mono : Monotone F
this✝ : ∀ (b : β), ∫⁻ (c : γ), ⨆ n, (F n) (b, c) ∂η (a, b) = ⨆ n, ∫⁻ (c : γ), (F n) (b, c) ∂η (a, b)
f' : SimpleFunc (β × γ) ℝ≥0∞
this : (fun b ↦ ∫⁻ (c : γ), f' (b, c) ∂η (a, b)) = (fun ab ↦ ∫⁻ (c : γ), f' (ab.2, c) ∂η ab) ∘ fun b ↦ (a, b)
⊢ Measurable ((fun ab ↦ ∫⁻ (c : γ), f' (ab.2, c) ∂η ab) ∘ fun b ↦ (a, b))

Tactic:
fun_prop

Goal state after:
Module: Mathlib.Probability.Kernel.Composition.RadonNikodym

Goal state before:
pp: α : Type u_1
β : Type u_2
mα : MeasurableSpace α
mβ : MeasurableSpace β
μ ν : Measure α
hμν : μ ≪ ν
κ : Kernel α β
inst✝² : IsFiniteMeasure μ
inst✝¹ : IsFiniteMeasure ν
inst✝ : IsFiniteKernel κ
⊢ Measurable ((μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ κ))

Tactic:
fun_prop

Goal state after:
Module: Mathlib.Probability.Kernel.Composition.RadonNikodym

Goal state before:
pp: α : Type u_1
β : Type u_2
mα : MeasurableSpace α
mβ : MeasurableSpace β
μ ν : Measure α
hμν : μ ≪ ν
κ : Kernel α β
inst✝² : IsFiniteMeasure μ
inst✝¹ : IsFiniteMeasure ν
inst✝ : IsFiniteKernel κ
⊢ Measurable fun p ↦ μ.rnDeriv ν p.1

Tactic:
fun_prop

Goal state after:
Module: Mathlib.Probability.Kernel.Composition.RadonNikodym

Goal state before:
pp: α : Type u_1
β : Type u_2
mα : MeasurableSpace α
mβ : MeasurableSpace β
μ ν : Measure α
hμν : μ ≪ ν
κ : Kernel α β
inst✝² : IsFiniteMeasure μ
inst✝¹ : IsFiniteMeasure ν
inst✝ : IsFiniteKernel κ
s : Set (α × β)
hs : MeasurableSet s
x✝ : (ν ⊗ₘ κ) s < ∞
t₁ : Set α
t₂ : Set β
ht₁ : MeasurableSet t₁
ht₂ : MeasurableSet t₂
⊢ Measurable fun x ↦ μ.rnDeriv ν x.1

Tactic:
fun_prop

Goal state after:
Module: Mathlib.Probability.Kernel.Composition.RadonNikodym

Goal state before:
pp: case refine_2
α : Type u_1
β : Type u_2
mα : MeasurableSpace α
mβ : MeasurableSpace β
μ ν : Measure α
hμν : μ ≪ ν
κ : Kernel α β
inst✝² : IsFiniteMeasure μ
inst✝¹ : IsFiniteMeasure ν
inst✝ : IsFiniteKernel κ
s : Set (α × β)
hs : MeasurableSet s
x✝ : (ν ⊗ₘ κ) s < ∞
h_key :
  ∀ (t₁ : Set α) (t₂ : Set β),
    MeasurableSet t₁ →
      MeasurableSet t₂ →
        ∫⁻ (x : α × β) in t₁ ×ˢ t₂, (μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ κ) x ∂ν ⊗ₘ κ =
          ∫⁻ (x : α × β) in t₁ ×ˢ t₂, μ.rnDeriv ν x.1 ∂ν ⊗ₘ κ
⊢ ∀ t ∈ image2 (fun x1 x2 ↦ x1 ×ˢ x2) {s | MeasurableSet s} {t | MeasurableSet t},
    ∫⁻ (x : α × β) in t, (μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ κ) x ∂ν ⊗ₘ κ = ∫⁻ (x : α × β) in t, μ.rnDeriv ν x.1 ∂ν ⊗ₘ κ

Tactic:
rintro _ ⟨t₁, ht₁, t₂, ht₂, rfl⟩

Goal state after:
case refine_2
α : Type u_1
β : Type u_2
mα : MeasurableSpace α
mβ : MeasurableSpace β
μ ν : Measure α
hμν : μ ≪ ν
κ : Kernel α β
inst✝² : IsFiniteMeasure μ
inst✝¹ : IsFiniteMeasure ν
inst✝ : IsFiniteKernel κ
s : Set (α × β)
hs : MeasurableSet s
x✝ : (ν ⊗ₘ κ) s < ∞
h_key :
  ∀ (t₁ : Set α) (t₂ : Set β),
    MeasurableSet t₁ →
      MeasurableSet t₂ →
        ∫⁻ (x : α × β) in t₁ ×ˢ t₂, (μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ κ) x ∂ν ⊗ₘ κ =
          ∫⁻ (x : α × β) in t₁ ×ˢ t₂, μ.rnDeriv ν x.1 ∂ν ⊗ₘ κ
t₁ : Set α
ht₁ : t₁ ∈ {s | MeasurableSet s}
t₂ : Set β
ht₂ : t₂ ∈ {t | MeasurableSet t}
⊢ ∫⁻ (x : α × β) in (fun x1 x2 ↦ x1 ×ˢ x2) t₁ t₂, (μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ κ) x ∂ν ⊗ₘ κ =
    ∫⁻ (x : α × β) in (fun x1 x2 ↦ x1 ×ˢ x2) t₁ t₂, μ.rnDeriv ν x.1 ∂ν ⊗ₘ κ
Module: Mathlib.Probability.Kernel.Composition.CompProd

Goal state before:
pp: case refine_1
α : Type u_1
β : Type u_2
γ : Type u_3
mα : MeasurableSpace α
mβ : MeasurableSpace β
mγ : MeasurableSpace γ
κ : Kernel α β
inst✝¹ : IsSFiniteKernel κ
η : Kernel (α × β) γ
inst✝ : IsSFiniteKernel η
a : α
f : β → γ → ℝ≥0∞
hf : Measurable (Function.uncurry f)
F : ℕ → SimpleFunc (β × γ) ℝ≥0∞ := SimpleFunc.eapprox (Function.uncurry f)
h : ∀ (a : β) (b : γ), ⨆ n, (F n) (a, b) = f a b
h_mono : Monotone F
this : ∀ (b : β), ∫⁻ (c : γ), ⨆ n, (F n) (b, c) ∂η (a, b) = ⨆ n, ∫⁻ (c : γ), (F n) (b, c) ∂η (a, b)
h_some_meas_integral : ∀ (f' : SimpleFunc (β × γ) ℝ≥0∞), Measurable fun b ↦ ∫⁻ (c : γ), f' (b, c) ∂η (a, b)
n : ℕ
c : ℝ≥0∞
s : Set (β × γ)
hs : MeasurableSet s
⊢ ∫⁻ (a : β × γ), (SimpleFunc.piecewise s hs (SimpleFunc.const (β × γ) c) (SimpleFunc.const (β × γ) 0)) a ∂(κ ⊗ₖ η) a =
    ∫⁻ (a_1 : β),
      ∫⁻ (c_1 : γ),
        (SimpleFunc.piecewise s hs (SimpleFunc.const (β × γ) c) (SimpleFunc.const (β × γ) 0))
          (a_1, c_1) ∂η (a, a_1) ∂κ a

Tactic:
simp +unfoldPartialApp only [SimpleFunc.const_zero,
      SimpleFunc.coe_piecewise, SimpleFunc.coe_const, SimpleFunc.coe_zero,
      Set.piecewise_eq_indicator, Function.const, lintegral_indicator_const hs]

Goal state after:
case refine_1
α : Type u_1
β : Type u_2
γ : Type u_3
mα : MeasurableSpace α
mβ : MeasurableSpace β
mγ : MeasurableSpace γ
κ : Kernel α β
inst✝¹ : IsSFiniteKernel κ
η : Kernel (α × β) γ
inst✝ : IsSFiniteKernel η
a : α
f : β → γ → ℝ≥0∞
hf : Measurable (Function.uncurry f)
F : ℕ → SimpleFunc (β × γ) ℝ≥0∞ := SimpleFunc.eapprox (Function.uncurry f)
h : ∀ (a : β) (b : γ), ⨆ n, (F n) (a, b) = f a b
h_mono : Monotone F
this : ∀ (b : β), ∫⁻ (c : γ), ⨆ n, (F n) (b, c) ∂η (a, b) = ⨆ n, ∫⁻ (c : γ), (F n) (b, c) ∂η (a, b)
h_some_meas_integral : ∀ (f' : SimpleFunc (β × γ) ℝ≥0∞), Measurable fun b ↦ ∫⁻ (c : γ), f' (b, c) ∂η (a, b)
n : ℕ
c : ℝ≥0∞
s : Set (β × γ)
hs : MeasurableSet s
⊢ c * ((κ ⊗ₖ η) a) s = ∫⁻ (a_1 : β), ∫⁻ (c_1 : γ), s.indicator (fun x ↦ c) (a_1, c_1) ∂η (a, a_1) ∂κ a
Module: Mathlib.Probability.Kernel.Composition.RadonNikodym

Goal state before:
pp: α : Type u_1
β : Type u_2
mα : MeasurableSpace α
mβ : MeasurableSpace β
μ ν : Measure α
κ : Kernel α β
inst✝² : IsFiniteMeasure μ
inst✝¹ : IsFiniteMeasure ν
inst✝ : IsFiniteKernel κ
⊢ Measurable ((ν.withDensity (μ.rnDeriv ν)).rnDeriv ν)

Tactic:
fun_prop

Goal state after:
Module: Mathlib.Probability.Kernel.Composition.RadonNikodym

Goal state before:
pp: α : Type u_1
β : Type u_2
mα : MeasurableSpace α
mβ : MeasurableSpace β
μ ν : Measure α
κ : Kernel α β
inst✝² : IsFiniteMeasure μ
inst✝¹ : IsFiniteMeasure ν
inst✝ : IsFiniteKernel κ
⊢ Measurable (μ.rnDeriv ν)

Tactic:
fun_prop

Goal state after:
Module: Mathlib.MeasureTheory.Measure.Decomposition.IntegralRNDeriv

Goal state before:
pp: 𝓧 : Type u_1
m𝓧 : MeasurableSpace 𝓧
μ : Measure 𝓧
𝓨 : Type u_2
m𝓨 : MeasurableSpace 𝓨
κ η : Kernel 𝓧 𝓨
inst✝² : IsFiniteMeasure μ
inst✝¹ : IsSFiniteKernel κ
inst✝ : IsFiniteKernel η
hκη : μ ⊗ₘ κ ≪ μ ⊗ₘ η
⊢ Measurable fun a ↦ ∫⁻ (b : 𝓨), (μ ⊗ₘ κ).rnDeriv (μ ⊗ₘ η) (a, b) ∂η a

Tactic:
fun_prop

Goal state after:
Module: Mathlib.Probability.Kernel.Composition.CompProd

Goal state before:
pp: α : Type u_1
β : Type u_2
γ : Type u_3
mα : MeasurableSpace α
mβ : MeasurableSpace β
mγ : MeasurableSpace γ
δ : Type u_4
mδ : MeasurableSpace δ
κ : Kernel α β
η : Kernel (α × β) γ
ξ : Kernel (α × β × γ) δ
hκ : IsSFiniteKernel κ
hη : IsSFiniteKernel η
hξ : IsSFiniteKernel ξ
a : α
s : Set ((β × γ) × δ)
hs : MeasurableSet s
⊢ Measurable ⇑MeasurableEquiv.prodAssoc.symm

Tactic:
fun_prop

Goal state after:
Module: Mathlib.MeasureTheory.Measure.Decomposition.IntegralRNDeriv

Goal state before:
pp: 𝓧 : Type u_1
m𝓧 : MeasurableSpace 𝓧
μ : Measure 𝓧
𝓨 : Type u_2
m𝓨 : MeasurableSpace 𝓨
κ η : Kernel 𝓧 𝓨
inst✝² : IsFiniteMeasure μ
inst✝¹ : IsSFiniteKernel κ
inst✝ : IsFiniteKernel η
hκη : μ ⊗ₘ κ ≪ μ ⊗ₘ η
s : Set 𝓧
hs : MeasurableSet s
hsμ : μ s < ∞
⊢ Measurable ((μ ⊗ₘ κ).rnDeriv (μ ⊗ₘ η))

Tactic:
fun_prop

Goal state after:
Module: Mathlib.Probability.Kernel.Composition.CompProd

Goal state before:
pp: α : Type u_1
β : Type u_2
γ : Type u_3
mα : MeasurableSpace α
mβ : MeasurableSpace β
mγ : MeasurableSpace γ
δ : Type u_4
mδ : MeasurableSpace δ
κ : Kernel α β
η : Kernel (α × β) γ
ξ : Kernel (α × β × γ) δ
hκ : IsSFiniteKernel κ
hη : IsSFiniteKernel η
hξ : IsSFiniteKernel ξ
a : α
s : Set ((β × γ) × δ)
hs : MeasurableSet s
b : β
⊢ Measurable fun x ↦ MeasurableEquiv.prodAssoc.symm (b, x)

Tactic:
fun_prop

Goal state after:
Module: Mathlib.MeasureTheory.Measure.Decomposition.IntegralRNDeriv

Goal state before:
pp: 𝓧 : Type u_1
m𝓧 : MeasurableSpace 𝓧
μ ν : Measure 𝓧
𝓨 : Type u_2
m𝓨 : MeasurableSpace 𝓨
κ η : Kernel 𝓧 𝓨
f : ℝ → ℝ
inst✝³ : IsFiniteMeasure μ
inst✝² : IsFiniteMeasure ν
inst✝¹ : IsMarkovKernel κ
inst✝ : IsMarkovKernel η
hf : StronglyMeasurable f
hf_cvx : ConvexOn ℝ (Ici 0) f
hf_cont_at : ContinuousWithinAt f (Ici 0) 0
h_int : Integrable (fun p ↦ f ((μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) p).toReal) (ν ⊗ₘ η)
hκη : μ ⊗ₘ κ ≪ μ ⊗ₘ η
hf_cont : ContinuousOn f (Ici 0)
h_lt_top : ∀ᵐ (a : 𝓧) ∂ν, ∀ᵐ (b : 𝓨) ∂η a, (μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) (a, b) < ∞
h_integrable :
  (∀ᵐ (x : 𝓧) ∂ν, Integrable (fun y ↦ ((μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) (x, y)).toReal) (η x)) ∧
    Integrable (fun x ↦ ∫ (y : 𝓨), ‖((μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) (x, y)).toReal‖ ∂η x) ν
⊢ StronglyMeasurable fun p ↦ f ((μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) p).toReal

Tactic:
fun_prop

Goal state after:
Module: Mathlib.MeasureTheory.Measure.Decomposition.IntegralRNDeriv

Goal state before:
pp: 𝓧 : Type u_1
m𝓧 : MeasurableSpace 𝓧
μ ν : Measure 𝓧
𝓨 : Type u_2
m𝓨 : MeasurableSpace 𝓨
κ η : Kernel 𝓧 𝓨
f : ℝ → ℝ
inst✝³ : IsFiniteMeasure μ
inst✝² : IsFiniteMeasure ν
inst✝¹ : IsMarkovKernel κ
inst✝ : IsMarkovKernel η
hf : StronglyMeasurable f
hf_cvx : ConvexOn ℝ (Ici 0) f
hf_cont_at : ContinuousWithinAt f (Ici 0) 0
h_int : Integrable (fun p ↦ f ((μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) p).toReal) (ν ⊗ₘ η)
hκη : μ ⊗ₘ κ ≪ μ ⊗ₘ η
hf_cont : ContinuousOn f (Ici 0)
h_lt_top : ∀ᵐ (a : 𝓧) ∂ν, ∀ᵐ (b : 𝓨) ∂η a, (μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) (a, b) < ∞
h_integrable : Integrable (fun x ↦ ((μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) x).toReal) (ν ⊗ₘ η)
⊢ StronglyMeasurable fun x ↦ ((μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) x).toReal

Tactic:
fun_prop

Goal state after:
Module: Mathlib.MeasureTheory.Measure.Tilted

Goal state before:
pp: case pos
α : Type u_1
mα : MeasurableSpace α
μ : Measure α
E : Type u_2
inst✝² : NormedAddCommGroup E
inst✝¹ : NormedSpace ℝ E
inst✝ : SFinite μ
f : α → ℝ
g : α → E
s : Set α
hf : AEMeasurable f μ
⊢ (∫ (x : α) in s, g x ∂μ.withDensity fun x ↦ ↑(NNReal.mk (rexp (f x) / ∫ (x : α), rexp (f x) ∂μ) ⋯)) =
    ∫ (x : α) in s, (rexp (f x) / ∫ (x : α), rexp (f x) ∂μ) • g x ∂μ

Tactic:
setIntegral_withDensity_eq_setIntegral_smul₀'

Goal state after:
case pos
α : Type u_1
mα : MeasurableSpace α
μ : Measure α
E : Type u_2
inst✝² : NormedAddCommGroup E
inst✝¹ : NormedSpace ℝ E
inst✝ : SFinite μ
f : α → ℝ
g : α → E
s : Set α
hf : AEMeasurable f μ
⊢ ∫ (x : α) in s, NNReal.mk (rexp (f x) / ∫ (x : α), rexp (f x) ∂μ) ⋯ • g x ∂μ =
    ∫ (x : α) in s, (rexp (f x) / ∫ (x : α), rexp (f x) ∂μ) • g x ∂μ

case pos.hf
α : Type u_1
mα : MeasurableSpace α
μ : Measure α
E : Type u_2
inst✝² : NormedAddCommGroup E
inst✝¹ : NormedSpace ℝ E
inst✝ : SFinite μ
f : α → ℝ
g : α → E
s : Set α
hf : AEMeasurable f μ
⊢ AEMeasurable (fun x ↦ NNReal.mk (rexp (f x) / ∫ (x : α), rexp (f x) ∂μ) ⋯) (μ.restrict s)
Module: Mathlib.Probability.Kernel.Composition.IntegralCompProd

Goal state before:
pp: α : Type u_1
β : Type u_2
γ : Type u_3
E : Type u_4
mα : MeasurableSpace α
mβ : MeasurableSpace β
mγ : MeasurableSpace γ
inst✝³ : NormedAddCommGroup E
a : α
κ : Kernel α β
η : Kernel β γ
inst✝² : NormedSpace ℝ E
E' : Type u_5
inst✝¹ : NormedAddCommGroup E'
inst✝ : NormedSpace ℝ E'
f g : γ → E
F : E → E'
hf : Integrable f ((η ∘ₖ κ) a)
hg : Integrable g ((η ∘ₖ κ) a)
⊢ ∫ (x : β), F (∫ (y : γ), f y + g y ∂η x) ∂κ a = ∫ (x : β), F (∫ (y : γ), f y ∂η x + ∫ (y : γ), g y ∂η x) ∂κ a

Tactic:
refine integral_congr_ae ?_
  filter_upwards [hf.ae_of_comp, hg.ae_of_comp] with _ h2f h2g
  simp [integral_add h2f h2g]

Goal state after:
Module: Mathlib.MeasureTheory.Measure.Decomposition.IntegralRNDeriv

Goal state before:
pp: 𝓧 : Type u_1
m𝓧 : MeasurableSpace 𝓧
μ ν : Measure 𝓧
𝓨 : Type u_2
m𝓨 : MeasurableSpace 𝓨
κ η : Kernel 𝓧 𝓨
f : ℝ → ℝ
inst✝³ : IsFiniteMeasure μ
inst✝² : IsFiniteMeasure ν
inst✝¹ : IsMarkovKernel κ
inst✝ : IsMarkovKernel η
hf : StronglyMeasurable f
hf_cvx : ConvexOn ℝ (Ici 0) f
hf_cont_at : ContinuousWithinAt f (Ici 0) 0
h_int :
  (∀ᵐ (x : 𝓧) ∂ν, Integrable (fun y ↦ f ((μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) (x, y)).toReal) (η x)) ∧
    Integrable (fun x ↦ ∫ (y : 𝓨), ‖f ((μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) (x, y)).toReal‖ ∂η x) ν
hκη : μ ⊗ₘ κ ≪ μ ⊗ₘ η
hf_cont : ContinuousOn f (Ici 0)
h_lt_top : ∀ᵐ (a : 𝓧) ∂ν, ∀ᵐ (b : 𝓨) ∂η a, (μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) (a, b) < ∞
h_integrable :
  (∀ᵐ (x : 𝓧) ∂ν, Integrable (fun y ↦ ((μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) (x, y)).toReal) (η x)) ∧
    Integrable (fun x ↦ ∫ (y : 𝓨), ‖((μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) (x, y)).toReal‖ ∂η x) ν
h_ae1 : ∀ᵐ (a : 𝓧) ∂ν, μ.rnDeriv ν a * ∫⁻ (b : 𝓨), (μ ⊗ₘ κ).rnDeriv (μ ⊗ₘ η) (a, b) ∂η a = μ.rnDeriv ν a
h_compProd : ∀ᵐ (x : 𝓧 × 𝓨) ∂ν ⊗ₘ η, μ.rnDeriv ν x.1 * (μ ⊗ₘ κ).rnDeriv (μ ⊗ₘ η) x = (μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) x
⊢ Measurable fun x ↦ μ.rnDeriv ν x.1 * (μ ⊗ₘ κ).rnDeriv (μ ⊗ₘ η) x = (μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) x

Tactic:
fun_prop

Goal state after:
Module: Mathlib.MeasureTheory.Measure.Decomposition.IntegralRNDeriv

Goal state before:
pp: 𝓧 : Type u_1
m𝓧 : MeasurableSpace 𝓧
μ ν : Measure 𝓧
𝓨 : Type u_2
m𝓨 : MeasurableSpace 𝓨
κ η : Kernel 𝓧 𝓨
f : ℝ → ℝ
inst✝³ : IsFiniteMeasure μ
inst✝² : IsFiniteMeasure ν
inst✝¹ : IsMarkovKernel κ
inst✝ : IsMarkovKernel η
hf : StronglyMeasurable f
hf_cvx : ConvexOn ℝ (Ici 0) f
hf_cont_at : ContinuousWithinAt f (Ici 0) 0
h_int✝ :
  (∀ᵐ (x : 𝓧) ∂ν, Integrable (fun y ↦ f ((μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) (x, y)).toReal) (η x)) ∧
    Integrable (fun x ↦ ∫ (y : 𝓨), ‖f ((μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) (x, y)).toReal‖ ∂η x) ν
hκη : μ ⊗ₘ κ ≪ μ ⊗ₘ η
hf_cont : ContinuousOn f (Ici 0)
h_lt_top✝ : ∀ᵐ (a : 𝓧) ∂ν, ∀ᵐ (b : 𝓨) ∂η a, (μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) (a, b) < ∞
h_integrable :
  (∀ᵐ (x : 𝓧) ∂ν, Integrable (fun y ↦ ((μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) (x, y)).toReal) (η x)) ∧
    Integrable (fun x ↦ ∫ (y : 𝓨), ‖((μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) (x, y)).toReal‖ ∂η x) ν
h_ae1 : ∀ᵐ (a : 𝓧) ∂ν, μ.rnDeriv ν a * ∫⁻ (b : 𝓨), (μ ⊗ₘ κ).rnDeriv (μ ⊗ₘ η) (a, b) ∂η a = μ.rnDeriv ν a
h_ae2 :
  ∀ᵐ (a : 𝓧) ∂ν, ∀ᵐ (b : 𝓨) ∂η a, μ.rnDeriv ν a * (μ ⊗ₘ κ).rnDeriv (μ ⊗ₘ η) (a, b) = (μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) (a, b)
a : 𝓧
h_eq_one : μ.rnDeriv ν a * ∫⁻ (b : 𝓨), (μ ⊗ₘ κ).rnDeriv (μ ⊗ₘ η) (a, b) ∂η a = μ.rnDeriv ν a
h_mul_eq : ∀ᵐ (b : 𝓨) ∂η a, μ.rnDeriv ν a * (μ ⊗ₘ κ).rnDeriv (μ ⊗ₘ η) (a, b) = (μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) (a, b)
h_lt_top : ∀ᵐ (b : 𝓨) ∂η a, (μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) (a, b) < ∞
h_int' : Integrable (fun y ↦ ((μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) (a, y)).toReal) (η a)
h_int : Integrable (fun y ↦ f ((μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) (a, y)).toReal) (η a)
⊢ Measurable fun b ↦ (μ ⊗ₘ κ).rnDeriv (μ ⊗ₘ η) (a, b)

Tactic:
fun_prop

Goal state after:
Module: Mathlib.MeasureTheory.Measure.Tilted

Goal state before:
pp: α : Type u_1
mα : MeasurableSpace α
μ : Measure α
E : Type u_2
inst✝¹ : NormedAddCommGroup E
inst✝ : NormedSpace ℝ E
f : α → ℝ
hf : Integrable (fun x ↦ rexp (f x)) μ
g : α → E
hμ : ¬μ = 0
hf_meas : AEMeasurable f μ
⊢ AEMeasurable (fun x ↦ ENNReal.ofReal (rexp (f x) / ∫ (x : α), rexp (f x) ∂μ)) μ

Tactic:
fun_prop

Goal state after:
Module: Mathlib.MeasureTheory.Measure.Decomposition.IntegralRNDeriv

Goal state before:
pp: 𝓧 : Type u_1
m𝓧 : MeasurableSpace 𝓧
μ ν : Measure 𝓧
𝓨 : Type u_2
m𝓨 : MeasurableSpace 𝓨
κ η : Kernel 𝓧 𝓨
f : ℝ → ℝ
inst✝³ : IsFiniteMeasure μ
inst✝² : IsFiniteMeasure ν
inst✝¹ : IsMarkovKernel κ
inst✝ : IsMarkovKernel η
hf : StronglyMeasurable f
hf_cvx : ConvexOn ℝ (Ici 0) f
hf_cont_at : ContinuousWithinAt f (Ici 0) 0
h_int✝ :
  (∀ᵐ (x : 𝓧) ∂ν, Integrable (fun y ↦ f ((μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) (x, y)).toReal) (η x)) ∧
    Integrable (fun x ↦ ∫ (y : 𝓨), ‖f ((μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) (x, y)).toReal‖ ∂η x) ν
hκη : μ ⊗ₘ κ ≪ μ ⊗ₘ η
hf_cont : ContinuousOn f (Ici 0)
h_lt_top✝ : ∀ᵐ (a : 𝓧) ∂ν, ∀ᵐ (b : 𝓨) ∂η a, (μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) (a, b) < ∞
h_integrable :
  (∀ᵐ (x : 𝓧) ∂ν, Integrable (fun y ↦ ((μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) (x, y)).toReal) (η x)) ∧
    Integrable (fun x ↦ ∫ (y : 𝓨), ‖((μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) (x, y)).toReal‖ ∂η x) ν
h_ae1 : ∀ᵐ (a : 𝓧) ∂ν, μ.rnDeriv ν a * ∫⁻ (b : 𝓨), (μ ⊗ₘ κ).rnDeriv (μ ⊗ₘ η) (a, b) ∂η a = μ.rnDeriv ν a
h_ae2 :
  ∀ᵐ (a : 𝓧) ∂ν, ∀ᵐ (b : 𝓨) ∂η a, μ.rnDeriv ν a * (μ ⊗ₘ κ).rnDeriv (μ ⊗ₘ η) (a, b) = (μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) (a, b)
a : 𝓧
h_eq_one : μ.rnDeriv ν a * ∫⁻ (b : 𝓨), (μ ⊗ₘ κ).rnDeriv (μ ⊗ₘ η) (a, b) ∂η a = μ.rnDeriv ν a
h_mul_eq : ∀ᵐ (b : 𝓨) ∂η a, μ.rnDeriv ν a * (μ ⊗ₘ κ).rnDeriv (μ ⊗ₘ η) (a, b) = (μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) (a, b)
h_lt_top : ∀ᵐ (b : 𝓨) ∂η a, (μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) (a, b) < ∞
h_int' : Integrable (fun y ↦ ((μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) (a, y)).toReal) (η a)
h_int : Integrable (fun y ↦ f ((μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) (a, y)).toReal) (η a)
⊢ AEMeasurable (fun x ↦ (μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) (a, x)) (η a)

Tactic:
fun_prop

Goal state after:
Module: Mathlib.InformationTheory.KullbackLeibler.KLFun

Goal state before:
pp: ⊢ Continuous fun x ↦ x * log x + 1 - x

Tactic:
fun_prop

Goal state after:
Module: Mathlib.InformationTheory.KullbackLeibler.KLFun

Goal state before:
pp: α : Type u_1
mα : MeasurableSpace α
μ ν : Measure α
inst✝¹ : IsFiniteMeasure μ
inst✝ : IsFiniteMeasure ν
hμν : μ ≪ ν
⊢ Integrable (fun x ↦ 1 - (μ.rnDeriv ν x).toReal) ν

Tactic:
fun_prop

Goal state after:
Module: Mathlib.MeasureTheory.Measure.Decomposition.IntegralRNDeriv

Goal state before:
pp: 𝓧 : Type u_1
m𝓧 : MeasurableSpace 𝓧
μ ν : Measure 𝓧
𝓨 : Type u_2
m𝓨 : MeasurableSpace 𝓨
κ η : Kernel 𝓧 𝓨
f : ℝ → ℝ
inst✝³ : IsFiniteMeasure μ
inst✝² : IsFiniteMeasure ν
inst✝¹ : IsMarkovKernel κ
inst✝ : IsMarkovKernel η
hf : StronglyMeasurable f
hf_cvx : ConvexOn ℝ (Ici 0) f
hf_cont_at : ContinuousWithinAt f (Ici 0) 0
hf_int : Integrable (fun p ↦ f ((μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) p).toReal) (ν ⊗ₘ η)
hκη : μ ⊗ₘ κ ≪ μ ⊗ₘ η
hf_cont : ContinuousOn f (Ici 0)
c c' : ℝ
h : ∀ (x : ℝ), 0 ≤ x → c * x + c' ≤ f x
⊢ Integrable (fun x ↦ c * (μ.rnDeriv ν x).toReal + c') ν

Tactic:
fun_prop

Goal state after:
Module: Mathlib.MeasureTheory.Measure.Decomposition.IntegralRNDeriv

Goal state before:
pp: 𝓧 : Type u_1
m𝓧 : MeasurableSpace 𝓧
μ ν : Measure 𝓧
𝓨 : Type u_2
m𝓨 : MeasurableSpace 𝓨
κ η : Kernel 𝓧 𝓨
f : ℝ → ℝ
inst✝³ : IsFiniteMeasure μ
inst✝² : IsFiniteMeasure ν
inst✝¹ : IsMarkovKernel κ
inst✝ : IsMarkovKernel η
hf : StronglyMeasurable f
hf_cvx : ConvexOn ℝ (Ici 0) f
hf_cont_at : ContinuousWithinAt f (Ici 0) 0
hf_int : Integrable (fun p ↦ f ((μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ η) p).toReal) (ν ⊗ₘ η)
hκη : μ ⊗ₘ κ ≪ μ ⊗ₘ η
hf_cont : ContinuousOn f (Ici 0)
c c' : ℝ
h : ∀ (x : ℝ), 0 ≤ x → c * x + c' ≤ f x
⊢ StronglyMeasurable fun a ↦ f (μ.rnDeriv ν a).toReal

Tactic:
fun_prop

Goal state after:
Module: Mathlib.InformationTheory.KullbackLeibler.KLFun

Goal state before:
pp: case hg
α : Type u_1
mα : MeasurableSpace α
μ ν : Measure α
inst✝¹ : IsFiniteMeasure μ
inst✝ : IsFiniteMeasure ν
hμν : μ ≪ ν
h_int : Integrable (llr μ ν) μ
⊢ Integrable (fun a ↦ 1) ν

Tactic:
fun_prop

Goal state after:
Module: Mathlib.InformationTheory.KullbackLeibler.KLFun

Goal state before:
pp: case hg
α : Type u_1
mα : MeasurableSpace α
μ ν : Measure α
inst✝¹ : IsFiniteMeasure μ
inst✝ : IsFiniteMeasure ν
hμν : μ ≪ ν
h_int : Integrable (llr μ ν) μ
⊢ Integrable (fun x ↦ (μ.rnDeriv ν x).toReal) ν

Tactic:
fun_prop

Goal state after:
Module: Mathlib.MeasureTheory.Function.LpSeminorm.Trim

Goal state before:
pp: α : Type u_1
ε : Type u_3
m m0 : MeasurableSpace α
q : ℝ
μ : Measure α
inst✝¹ : TopologicalSpace ε
inst✝ : ContinuousENorm ε
hm : m ≤ m0
f : α → ε
hf : StronglyMeasurable f
⊢ Measurable fun a ↦ ‖f a‖ₑ ^ q

Tactic:
fun_prop

Goal state after:
Module: Mathlib.InformationTheory.KullbackLeibler.Basic

Goal state before:
pp: α : Type u_1
mα : MeasurableSpace α
μ ν : Measure α
inst✝¹ : IsFiniteMeasure μ
inst✝ : IsFiniteMeasure ν
hμν : μ ≪ ν
⊢ Measurable fun x ↦ klFun (μ.rnDeriv ν x).toReal

Tactic:
fun_prop

Goal state after:
Module: Mathlib.MeasureTheory.Function.LpSpace.CompleteOfCompleteLp

Goal state before:
pp: case inr
α : Type u_1
E : Type u_2
inst✝¹ : NormedAddCommGroup E
mα : MeasurableSpace α
p : ℝ≥0∞
μ : Measure α
inst✝ : Nontrivial ↥(Lp E p μ)
f : ↥(Lp E p μ)
hf : f ≠ 0
hfne : ¬↑↑f =ᵐ[μ] 0
h'p : p < ∞
⊢ Nontrivial ↥(Lp ℝ p μ)

Tactic:
rcases eq_or_ne p 0 with rfl | hp

Goal state after:
case inr.inl
α : Type u_1
E : Type u_2
inst✝¹ : NormedAddCommGroup E
mα : MeasurableSpace α
μ : Measure α
inst✝ : Nontrivial ↥(Lp E 0 μ)
f : ↥(Lp E 0 μ)
hf : f ≠ 0
hfne : ¬↑↑f =ᵐ[μ] 0
h'p : 0 < ∞
⊢ Nontrivial ↥(Lp ℝ 0 μ)

case inr.inr
α : Type u_1
E : Type u_2
inst✝¹ : NormedAddCommGroup E
mα : MeasurableSpace α
p : ℝ≥0∞
μ : Measure α
inst✝ : Nontrivial ↥(Lp E p μ)
f : ↥(Lp E p μ)
hf : f ≠ 0
hfne : ¬↑↑f =ᵐ[μ] 0
h'p : p < ∞
hp : p ≠ 0
⊢ Nontrivial ↥(Lp ℝ p μ)
Module: Mathlib.InformationTheory.KullbackLeibler.Basic

Goal state before:
pp: case neg
α : Type u_1
mα : MeasurableSpace α
μ ν : Measure α
inst✝¹ : IsFiniteMeasure μ
inst✝ : IsFiniteMeasure ν
hμν : μ ≪ ν
h_int : Integrable (llr μ ν) μ
c : ℝ≥0
hc : ¬c = 0
h_llr : llr (c • μ) ν =ᵐ[μ] fun x ↦ llr μ ν x + log ↑c
⊢ Integrable (fun x ↦ llr μ ν x + log ↑c) μ

Tactic:
fun_prop

Goal state after:
Module: Mathlib.MeasureTheory.Function.LpSpace.CompleteOfCompleteLp

Goal state before:
pp: α : Type u_1
E : Type u_2
inst✝³ : NormedAddCommGroup E
mα : MeasurableSpace α
p : ℝ≥0∞
μ : Measure α
inst✝² : NormedSpace ℝ E
hp : Fact (1 ≤ p)
inst✝¹ : CompleteSpace ↥(Lp E p μ)
inst✝ : Nontrivial ↥(Lp E p μ)
f : ↥(Lp ℝ p μ)
hf : f ≠ 0
m : E →L[ℝ] ↥(Lp E p μ) := (compLpL₂ p μ (lsmul ℝ ℝ).flip).flip f
u : ℕ → E
hu : CauchySeq u
g : ↥(Lp E p μ)
hg : Tendsto (⇑m ∘ u) atTop (𝓝 g)
f' : ℕ → α → E := fun n ↦ ↑↑((⇑m ∘ u) n)
ns : ℕ → ℕ
hns : StrictMono ns
nslim : ∀ᵐ (x : α) ∂μ, Tendsto (fun i ↦ f' (ns i) x) atTop (𝓝 (↑↑g x))
this : (ae (μ.restrict (Function.support ↑↑f))).NeBot
A : ∀ᵐ (x : α) ∂μ.restrict (Function.support ↑↑f), Tendsto (fun i ↦ f' (ns i) x) atTop (𝓝 (↑↑g x))
⊢ Measurable ↑↑f

Tactic:
fun_prop

Goal state after:
Module: Mathlib.InformationTheory.KullbackLeibler.Basic

Goal state before:
pp: case neg.h_int
α : Type u_1
mα : MeasurableSpace α
μ ν : Measure α
inst✝¹ : IsFiniteMeasure μ
inst✝ : IsFiniteMeasure ν
hμν : μ ≪ ν
h_int : Integrable (llr μ ν) μ
c : ℝ≥0
hc : ¬c = 0
h_llr_left : llr (c⁻¹ • μ) ν =ᵐ[μ] fun x ↦ llr μ ν x + log ↑c⁻¹
h_llr_right : llr μ (c • ν) =ᵐ[μ] fun x ↦ llr μ ν x - log ↑c
⊢ Integrable (fun x ↦ llr μ ν x + log ↑c⁻¹) μ

Tactic:
fun_prop

Goal state after: