mathlib-initiative/mathlib-tactics huggingface dataset:
Module: Mathlib.GroupTheory.PushoutI

Goal state before:
pp: ι : Type u_1
G : ι → Type u_2
H : Type u_3
K : Type u_4
inst✝⁴ : Monoid K
inst✝³ : (i : ι) → Group (G i)
inst✝² : Group H
φ : (i : ι) → H →* G i
d : Transversal φ
inst✝¹ : DecidableEq ι
inst✝ : (i : ι) → DecidableEq (G i)
i✝ : ι
p : Pair d i✝
n : ↑↑(φ i✝).range × ↑(d.set i✝) := ⋯.equiv p.head
w : Word G :=
  (Word.equivPair i✝).symm
    (let __src := p.toPair;
    { head := ↑n.2, tail := __src.tail, fstIdx_ne := ⋯ })
i : ι
g : G i
hg : ⟨i, g⟩ ∈ (Word.rcons { head := ↑n.2, tail := p.tail, fstIdx_ne := ⋯ }).toList
⊢ g ∈ d.set i

Tactic:
Word.mem_rcons_iff

Goal state after:
ι : Type u_1
G : ι → Type u_2
H : Type u_3
K : Type u_4
inst✝⁴ : Monoid K
inst✝³ : (i : ι) → Group (G i)
inst✝² : Group H
φ : (i : ι) → H →* G i
d : Transversal φ
inst✝¹ : DecidableEq ι
inst✝ : (i : ι) → DecidableEq (G i)
i✝ : ι
p : Pair d i✝
n : ↑↑(φ i✝).range × ↑(d.set i✝) := ⋯.equiv p.head
w : Word G :=
  (Word.equivPair i✝).symm
    (let __src := p.toPair;
    { head := ↑n.2, tail := __src.tail, fstIdx_ne := ⋯ })
i : ι
g : G i
hg :
  ⟨i, g⟩ ∈ { head := ↑n.2, tail := p.tail, fstIdx_ne := ⋯ }.tail.toList ∨
    g ≠ 1 ∧ ∃ (h : i✝ = i), g = h ▸ { head := ↑n.2, tail := p.tail, fstIdx_ne := ⋯ }.head
⊢ g ∈ d.set i
Module: Mathlib.GroupTheory.SpecificGroups.Alternating.KleinFour

Goal state before:
pp: α : Type u_1
inst✝¹ : DecidableEq α
inst✝ : Fintype α
hα4 : Nat.card α = 4
x✝ : (kleinFour α).Normal
this✝ : Nat.card (↥(alternatingGroup α) ⧸ kleinFour α) = 3
comm_le : commutator ↥(alternatingGroup α) ≤ kleinFour α
comm_ne_bot : commutator ↥(alternatingGroup α) ≠ ⊥
k : ↥(alternatingGroup α)
hk : k ∈ commutator ↥(alternatingGroup α)
hk' : k ≠ 1
g : ↥(alternatingGroup α)
hg : (↑g).cycleType = {2, 2}
c : Perm α
hc : (MulAut.conjNormal c) k = g
fc : MulAut ↥(alternatingGroup α) := MulAut.conjNormal c
this : ⊤ = Subgroup.map (MulEquiv.toMonoidHom fc) ⊤
⊢ (MulAut.conjNormal c) k ∈ ⁅⊤, ⊤⁆

Tactic:
rw [this, ← Subgroup.map_commutator]

Goal state after:
α : Type u_1
inst✝¹ : DecidableEq α
inst✝ : Fintype α
hα4 : Nat.card α = 4
x✝ : (kleinFour α).Normal
this✝ : Nat.card (↥(alternatingGroup α) ⧸ kleinFour α) = 3
comm_le : commutator ↥(alternatingGroup α) ≤ kleinFour α
comm_ne_bot : commutator ↥(alternatingGroup α) ≠ ⊥
k : ↥(alternatingGroup α)
hk : k ∈ commutator ↥(alternatingGroup α)
hk' : k ≠ 1
g : ↥(alternatingGroup α)
hg : (↑g).cycleType = {2, 2}
c : Perm α
hc : (MulAut.conjNormal c) k = g
fc : MulAut ↥(alternatingGroup α) := MulAut.conjNormal c
this : ⊤ = Subgroup.map (MulEquiv.toMonoidHom fc) ⊤
⊢ (MulAut.conjNormal c) k ∈ Subgroup.map (MulEquiv.toMonoidHom fc) ⁅⊤, ⊤⁆
Module: Mathlib.Probability.Kernel.Composition.Comp

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
ι : Type u_4
inst✝ : Countable ι
κ : ι → Kernel α β
η : Kernel β γ
⊢ η ∘ₖ Kernel.sum κ = Kernel.sum fun i ↦ η ∘ₖ κ i

Tactic:
by
  ext _ _ hs
  simp_rw [sum_apply, comp_apply' _ _ _ hs, Measure.sum_apply _ hs, sum_apply,
    lintegral_sum_measure, comp_apply' _ _ _ hs]

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

Goal state before:
pp: α : Type u_1
β : Type u_2
mα : MeasurableSpace α
mβ : MeasurableSpace β
μ : Measure α
ι : Type u_3
inst✝ : Countable ι
κ : ι → Kernel α β
h : ∀ (i : ι), IsSFiniteKernel (κ i)
⊢ μ ⊗ₘ Kernel.sum κ = sum fun i ↦ μ ⊗ₘ κ i

Tactic:
rw [compProd, ← Kernel.sum_prodMkLeft, Kernel.compProd_sum_right]
  rfl

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
s : Set (β × γ)
hs : MeasurableSet s
κ : Kernel α β
inst✝¹ : IsSFiniteKernel κ
η : Kernel (α × β) γ
inst✝ : IsSFiniteKernel η
a : α
⊢ ((Measure.dirac (a, a)).bind
        ⇑(swap γ β ∘ₖ (η ∥ₖ Kernel.id) ∘ₖ deterministic ⇑MeasurableEquiv.prodAssoc.symm ⋯ ∘ₖ (Kernel.id ∥ₖ copy β) ∘ₖ
            (Kernel.id ∥ₖ κ)))
      s =
    ∫⁻ (b : β), (η (a, b)) (Prod.mk b ⁻¹' s) ∂κ a

Tactic:
Measure.dirac_bind (by fun_prop),

Goal state after:
α : Type u_1
β : Type u_2
γ : Type u_3
mα : MeasurableSpace α
mβ : MeasurableSpace β
mγ : MeasurableSpace γ
s : Set (β × γ)
hs : MeasurableSet s
κ : Kernel α β
inst✝¹ : IsSFiniteKernel κ
η : Kernel (α × β) γ
inst✝ : IsSFiniteKernel η
a : α
⊢ ((swap γ β ∘ₖ (η ∥ₖ Kernel.id) ∘ₖ deterministic ⇑MeasurableEquiv.prodAssoc.symm ⋯ ∘ₖ (Kernel.id ∥ₖ copy β) ∘ₖ
          (Kernel.id ∥ₖ κ))
        (a, a))
      s =
    ∫⁻ (b : β), (η (a, b)) (Prod.mk b ⁻¹' s) ∂κ a
Module: Mathlib.Probability.Kernel.Composition.MapComap

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
f : β → γ
g : β → δ
hf : Measurable f
hg : ¬Measurable g
⊢ ¬Measurable fun x ↦ (f x, g x)

Tactic:
contrapose hg

Goal state after:
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
f : β → γ
g : β → δ
hf : Measurable f
hg : Measurable fun x ↦ (f x, g x)
⊢ Measurable g
Module: Mathlib.Probability.Kernel.Composition.CompProd

Goal state before:
pp: case e_f
α : Type u_1
β : Type u_2
γ : Type u_3
mα : MeasurableSpace α
mβ : MeasurableSpace β
mγ : MeasurableSpace γ
s : Set (β × γ)
hs : MeasurableSet s
κ : Kernel α β
inst✝¹ : IsSFiniteKernel κ
η : Kernel (α × β) γ
inst✝ : IsSFiniteKernel η
a : α
b : β
⊢ ((Measure.dirac (((a, a).1, b).1, ((a, a).1, b).2, ((a, a).1, b).2)).bind
        ⇑(swap γ β ∘ₖ (η ∥ₖ Kernel.id) ∘ₖ deterministic ⇑MeasurableEquiv.prodAssoc.symm ⋯))
      s =
    (η (a, b)) (Prod.mk b ⁻¹' s)

Tactic:
Measure.dirac_bind (by fun_prop),

Goal state after:
case e_f
α : Type u_1
β : Type u_2
γ : Type u_3
mα : MeasurableSpace α
mβ : MeasurableSpace β
mγ : MeasurableSpace γ
s : Set (β × γ)
hs : MeasurableSet s
κ : Kernel α β
inst✝¹ : IsSFiniteKernel κ
η : Kernel (α × β) γ
inst✝ : IsSFiniteKernel η
a : α
b : β
⊢ ((swap γ β ∘ₖ (η ∥ₖ Kernel.id) ∘ₖ deterministic ⇑MeasurableEquiv.prodAssoc.symm ⋯)
        (((a, a).1, b).1, ((a, a).1, b).2, ((a, a).1, b).2))
      s =
    (η (a, b)) (Prod.mk b ⁻¹' s)
Module: Mathlib.Probability.Kernel.Composition.CompProd

Goal state before:
pp: case e_f
α : Type u_1
β : Type u_2
γ : Type u_3
mα : MeasurableSpace α
mβ : MeasurableSpace β
mγ : MeasurableSpace γ
s : Set (β × γ)
hs : MeasurableSet s
κ : Kernel α β
inst✝¹ : IsSFiniteKernel κ
η : Kernel (α × β) γ
inst✝ : IsSFiniteKernel η
a : α
b : β
⊢ ((Measure.dirac (MeasurableEquiv.prodAssoc.symm (((a, a).1, b).1, ((a, a).1, b).2, ((a, a).1, b).2))).bind
        ⇑(swap γ β ∘ₖ (η ∥ₖ Kernel.id)))
      s =
    (η (a, b)) (Prod.mk b ⁻¹' s)

Tactic:
Measure.dirac_bind (by fun_prop),

Goal state after:
case e_f
α : Type u_1
β : Type u_2
γ : Type u_3
mα : MeasurableSpace α
mβ : MeasurableSpace β
mγ : MeasurableSpace γ
s : Set (β × γ)
hs : MeasurableSet s
κ : Kernel α β
inst✝¹ : IsSFiniteKernel κ
η : Kernel (α × β) γ
inst✝ : IsSFiniteKernel η
a : α
b : β
⊢ ((swap γ β ∘ₖ (η ∥ₖ Kernel.id)) (MeasurableEquiv.prodAssoc.symm (((a, a).1, b).1, ((a, a).1, b).2, ((a, a).1, b).2)))
      s =
    (η (a, b)) (Prod.mk b ⁻¹' s)
Module: Mathlib.Probability.Kernel.Composition.MeasureCompProd

Goal state before:
pp: case pos
α : Type u_1
β : Type u_2
mα : MeasurableSpace α
mβ : MeasurableSpace β
μ ν : Measure α
κ η : Kernel α β
inst✝¹ : SFinite μ
inst✝ : IsSFiniteKernel κ
h_zero : ∀ (a : α), NeZero (κ a)
h : μ ⊗ₘ κ ≪ ν ⊗ₘ η
s : Set α
hs : MeasurableSet s
hs0 : ν s = 0
hν : SFinite ν
hη : IsSFiniteKernel η
⊢ (ν ⊗ₘ η) (s ×ˢ univ) = 0

Tactic:
Measure.compProd_apply_prod hs MeasurableSet.univ

Goal state after:
case pos
α : Type u_1
β : Type u_2
mα : MeasurableSpace α
mβ : MeasurableSpace β
μ ν : Measure α
κ η : Kernel α β
inst✝¹ : SFinite μ
inst✝ : IsSFiniteKernel κ
h_zero : ∀ (a : α), NeZero (κ a)
h : μ ⊗ₘ κ ≪ ν ⊗ₘ η
s : Set α
hs : MeasurableSet s
hs0 : ν s = 0
hν : SFinite ν
hη : IsSFiniteKernel η
⊢ ∫⁻ (a : α) in s, (η a) univ ∂ν = 0
Module: Mathlib.Probability.Kernel.Composition.Prod

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✝
γ : Type u_4
δ : Type u_5
mγ : MeasurableSpace γ
mδ : MeasurableSpace δ
κ : Kernel α β
inst✝¹ : IsMarkovKernel κ
η : Kernel α γ
inst✝ : IsMarkovKernel η
⊢ IsMarkovKernel (κ ×ₖ η)

Tactic:
rw [Kernel.prod]

Goal state after:
α : Type u_1
β : Type u_2
γ✝ : Type u_3
mα : MeasurableSpace α
mβ : MeasurableSpace β
mγ✝ : MeasurableSpace γ✝
γ : Type u_4
δ : Type u_5
mγ : MeasurableSpace γ
mδ : MeasurableSpace δ
κ : Kernel α β
inst✝¹ : IsMarkovKernel κ
η : Kernel α γ
inst✝ : IsMarkovKernel η
⊢ IsMarkovKernel (κ ∥ₖ η ∘ₖ copy α)
Module: Mathlib.Probability.Kernel.Composition.Prod

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✝
γ : Type u_4
δ : Type u_5
mγ : MeasurableSpace γ
mδ : MeasurableSpace δ
κ : Kernel α β
inst✝¹ : IsFiniteKernel κ
η : Kernel α γ
inst✝ : IsFiniteKernel η
⊢ IsFiniteKernel (κ ×ₖ η)

Tactic:
rw [Kernel.prod]

Goal state after:
α : Type u_1
β : Type u_2
γ✝ : Type u_3
mα : MeasurableSpace α
mβ : MeasurableSpace β
mγ✝ : MeasurableSpace γ✝
γ : Type u_4
δ : Type u_5
mγ : MeasurableSpace γ
mδ : MeasurableSpace δ
κ : Kernel α β
inst✝¹ : IsFiniteKernel κ
η : Kernel α γ
inst✝ : IsFiniteKernel η
⊢ IsFiniteKernel (κ ∥ₖ η ∘ₖ copy α)
Module: Mathlib.Probability.Kernel.Composition.Prod

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✝
γ : Type u_4
δ : Type u_5
mγ : MeasurableSpace γ
mδ : MeasurableSpace δ
κ : Kernel α β
η : Kernel α γ
⊢ IsSFiniteKernel (κ ×ₖ η)

Tactic:
rw [Kernel.prod]

Goal state after:
α : Type u_1
β : Type u_2
γ✝ : Type u_3
mα : MeasurableSpace α
mβ : MeasurableSpace β
mγ✝ : MeasurableSpace γ✝
γ : Type u_4
δ : Type u_5
mγ : MeasurableSpace γ
mδ : MeasurableSpace δ
κ : Kernel α β
η : Kernel α γ
⊢ IsSFiniteKernel (κ ∥ₖ η ∘ₖ copy α)
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
mγ : MeasurableSpace γ
κ : Kernel α β
inst✝¹ : IsSFiniteKernel κ
η : Kernel α γ
inst✝ : IsMarkovKernel η
a : α
⊢ (Measure.dirac (a, a)).bind ⇑(κ ∥ₖ η).fst = κ a

Tactic:
Measure.dirac_bind (by fun_prop),

Goal state after:
α : Type u_1
β : Type u_2
mα : MeasurableSpace α
mβ : MeasurableSpace β
γ : Type u_4
mγ : MeasurableSpace γ
κ : Kernel α β
inst✝¹ : IsSFiniteKernel κ
η : Kernel α γ
inst✝ : IsMarkovKernel η
a : α
⊢ (κ ∥ₖ η).fst (a, a) = κ a
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
mγ : MeasurableSpace γ
κ : Kernel α β
η : Kernel α γ
inst✝¹ : IsSFiniteKernel κ
inst✝ : IsSFiniteKernel η
x : α
f : γ × β → ℝ≥0∞
hf : Measurable f
⊢ ∫⁻ (b : γ × β), f b ∂((κ ×ₖ η).map Prod.swap) x = ∫⁻ (b : γ × β), f b ∂(η ×ₖ κ) x

Tactic:
rw [lintegral_map _ measurable_swap _ hf, lintegral_prod, lintegral_prod _ _ _ hf]

Goal state after:
α : Type u_1
β : Type u_2
mα : MeasurableSpace α
mβ : MeasurableSpace β
γ : Type u_4
mγ : MeasurableSpace γ
κ : Kernel α β
η : Kernel α γ
inst✝¹ : IsSFiniteKernel κ
inst✝ : IsSFiniteKernel η
x : α
f : γ × β → ℝ≥0∞
hf : Measurable f
⊢ ∫⁻ (b : β), ∫⁻ (c : γ), f (b, c).swap ∂η x ∂κ x = ∫⁻ (b : γ), ∫⁻ (c : β), f (b, c) ∂κ x ∂η x

case hg
α : Type u_1
β : Type u_2
mα : MeasurableSpace α
mβ : MeasurableSpace β
γ : Type u_4
mγ : MeasurableSpace γ
κ : Kernel α β
η : Kernel α γ
inst✝¹ : IsSFiniteKernel κ
inst✝ : IsSFiniteKernel η
x : α
f : γ × β → ℝ≥0∞
hf : Measurable f
⊢ Measurable fun a ↦ f a.swap
Module: Mathlib.Probability.Kernel.Composition.MeasureComp

Goal state before:
pp: α : Type u_1
mα : MeasurableSpace α
μ : Measure α
s : Set PUnit.{1}
hs : MeasurableSet s
⊢ (⇑(Kernel.discard α) ∘ₘ μ) s = (μ Set.univ • dirac ()) s

Tactic:
simp [Measure.bind_apply hs (Kernel.aemeasurable _), mul_comm]

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
⊢ (κ ×ₖ (ξ ×ₖ η)).map ⇑MeasurableEquiv.prodAssoc.symm = κ ×ₖ ξ ×ₖ η

Tactic:
rw [← prodAssoc_prod, ← Kernel.map_comp_right _ (by fun_prop) (by fun_prop)]

Goal state after:
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
⊢ (κ ×ₖ ξ ×ₖ η).map (⇑MeasurableEquiv.prodAssoc.symm ∘ ⇑MeasurableEquiv.prodAssoc) = κ ×ₖ ξ ×ₖ η
Module: Mathlib.Probability.Kernel.Composition.RadonNikodym

Goal state before:
pp: case refine_3
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 : Set (α × β)
ht : 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 →
    ∫⁻ (x : α × β) in tᶜ, (μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ κ) x ∂ν ⊗ₘ κ = ∫⁻ (x : α × β) in tᶜ, μ.rnDeriv ν x.1 ∂ν ⊗ₘ κ

Tactic:
ht_eq

Goal state after:
case refine_3
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 : Set (α × β)
ht : MeasurableSet t
ht_eq : ∫⁻ (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
⊢ ∫⁻ (x : α × β) in tᶜ, (μ ⊗ₘ κ).rnDeriv (ν ⊗ₘ κ) x ∂ν ⊗ₘ κ = ∫⁻ (x : α × β) in tᶜ, μ.rnDeriv ν x.1 ∂ν ⊗ₘ κ
Module: Mathlib.Probability.Kernel.MeasurableIntegral

Goal state before:
pp: case pos.refine_2
α : Type u_1
β : Type u_2
mα : MeasurableSpace α
mβ : MeasurableSpace β
κ : Kernel α β
E : Type u_4
inst✝² : NormedAddCommGroup E
inst✝¹ : IsSFiniteKernel κ
inst✝ : NormedSpace ℝ E
f : α → β → E
hf : StronglyMeasurable (uncurry f)
hE : CompleteSpace E
this✝² : MeasurableSpace E := borel E
this✝¹ : BorelSpace E
this✝ : TopologicalSpace.SeparableSpace ↑(range (uncurry f) ∪ {0})
s : ℕ → SimpleFunc (α × β) E := SimpleFunc.approxOn (uncurry f) ⋯ (range (uncurry f) ∪ {0}) 0 ⋯
s' : ℕ → α → SimpleFunc β E := fun n x ↦ (s n).comp (Prod.mk x) ⋯
f' : ℕ → α → E := fun n ↦ {x | Integrable (f x) (κ x)}.indicator fun x ↦ SimpleFunc.integral (κ x) (s' n x)
hf' : ∀ (n : ℕ), StronglyMeasurable (f' n)
x : α
hfx : Integrable (f x) (κ x)
this : ∀ (n : ℕ), Integrable (⇑(s' n x)) (κ x)
⊢ ∀ᵐ (a : β) ∂κ x, Tendsto (fun n ↦ (s' n x) a) atTop (𝓝 (f x a))

Tactic:
refine Eventually.of_forall fun y => SimpleFunc.tendsto_approxOn hf.measurable (by simp) ?_
        apply subset_closure
        simp [-uncurry_apply_pair]

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

Goal state before:
pp: case refine_2.e_f.hf
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
f f' : SimpleFunc (β × γ) ℝ≥0∞
a✝ : Disjoint (Function.support ⇑f) (Function.support ⇑f')
hf_eq : ∫⁻ (a : β × γ), f a ∂(κ ⊗ₖ η) a = ∫⁻ (a_1 : β), ∫⁻ (c : γ), f (a_1, c) ∂η (a, a_1) ∂κ a
hf'_eq : ∫⁻ (a : β × γ), f' a ∂(κ ⊗ₖ η) a = ∫⁻ (a_1 : β), ∫⁻ (c : γ), f' (a_1, c) ∂η (a, a_1) ∂κ a
b : β
⊢ Measurable fun c ↦ f (b, c)

Tactic:
exact (SimpleFunc.measurable _).comp measurable_prodMk_left

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.tilted f = ∫ (x : α) in s, (rexp (f x) / ∫ (x : α), rexp (f x) ∂μ) • g x ∂μ

Tactic:
rw [tilted_eq_withDensity_nnreal, setIntegral_withDensity_eq_setIntegral_smul₀']
    · congr
    · suffices AEMeasurable (fun x ↦ exp (f x) / ∫ x, exp (f x) ∂μ) μ by
        rw [← aemeasurable_coe_nnreal_real_iff]
        refine AEMeasurable.restrict ?_
        simpa only [NNReal.coe_mk]
      exact (measurable_exp.comp_aemeasurable hf).div_const _

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

Goal state before:
pp: α : Type u_1
mα : MeasurableSpace α
μ ν : Measure α
f : α → ℝ
inst✝¹ : IsProbabilityMeasure μ
inst✝ : SigmaFinite ν
hμν : μ ≪ ν
hf : Integrable f μ
h_int : Integrable (llr μ ν) μ
hfμ : Integrable (fun x ↦ rexp (f x)) μ
hfν : AEMeasurable f ν
⊢ ∫ (a : α), f a - log (∫ (x : α), rexp (f x) ∂μ) ∂μ + ∫ (a : α), llr μ ν a ∂μ =
    ∫ (x : α), f x ∂μ - log (∫ (x : α), rexp (f x) ∂μ) + ∫ (x : α), llr μ ν x ∂μ

Tactic:
integral_sub hf (integrable_const _)

Goal state after:
α : Type u_1
mα : MeasurableSpace α
μ ν : Measure α
f : α → ℝ
inst✝¹ : IsProbabilityMeasure μ
inst✝ : SigmaFinite ν
hμν : μ ≪ ν
hf : Integrable f μ
h_int : Integrable (llr μ ν) μ
hfμ : Integrable (fun x ↦ rexp (f x)) μ
hfν : AEMeasurable f ν
⊢ ∫ (a : α), f a ∂μ - ∫ (a : α), log (∫ (x : α), rexp (f x) ∂μ) ∂μ + ∫ (a : α), llr μ ν a ∂μ =
    ∫ (x : α), f x ∂μ - log (∫ (x : α), rexp (f x) ∂μ) + ∫ (x : α), llr μ ν x ∂μ
Module: Mathlib.MeasureTheory.Measure.LogLikelihoodRatio

Goal state before:
pp: α : Type u_1
mα : MeasurableSpace α
μ ν : Measure α
f : α → ℝ
inst✝¹ : SigmaFinite μ
inst✝ : SigmaFinite ν
hμν : μ ≪ ν
hf : Integrable (fun x ↦ rexp (f x)) ν
h0 : NeZero ν
x : α
hx : (μ.rnDeriv (ν.tilted f) x).toReal = (rexp (-f x) * ∫ (x : α), rexp (f x) ∂ν) * (μ.rnDeriv ν x).toReal
hx_pos : 0 < μ.rnDeriv ν x
hx_lt_top : μ.rnDeriv ν x < ∞
⊢ ∫ (x : α), rexp (f x) ∂ν ≠ 0

pp: case hx
α : Type u_1
mα : MeasurableSpace α
μ ν : Measure α
f : α → ℝ
inst✝¹ : SigmaFinite μ
inst✝ : SigmaFinite ν
hμν : μ ≪ ν
hf : Integrable (fun x ↦ rexp (f x)) ν
h0 : NeZero ν
x : α
hx : (μ.rnDeriv (ν.tilted f) x).toReal = (rexp (-f x) * ∫ (x : α), rexp (f x) ∂ν) * (μ.rnDeriv ν x).toReal
hx_pos : 0 < μ.rnDeriv ν x
hx_lt_top : μ.rnDeriv ν x < ∞
⊢ rexp (-f x) * ∫ (x : α), rexp (f x) ∂ν ≠ 0

pp: case hy
α : Type u_1
mα : MeasurableSpace α
μ ν : Measure α
f : α → ℝ
inst✝¹ : SigmaFinite μ
inst✝ : SigmaFinite ν
hμν : μ ≪ ν
hf : Integrable (fun x ↦ rexp (f x)) ν
h0 : NeZero ν
x : α
hx : (μ.rnDeriv (ν.tilted f) x).toReal = (rexp (-f x) * ∫ (x : α), rexp (f x) ∂ν) * (μ.rnDeriv ν x).toReal
hx_pos : 0 < μ.rnDeriv ν x
hx_lt_top : μ.rnDeriv ν x < ∞
⊢ (μ.rnDeriv ν x).toReal ≠ 0

Tactic:
· exact (integral_exp_pos hf).ne'

Goal state after:
case hx
α : Type u_1
mα : MeasurableSpace α
μ ν : Measure α
f : α → ℝ
inst✝¹ : SigmaFinite μ
inst✝ : SigmaFinite ν
hμν : μ ≪ ν
hf : Integrable (fun x ↦ rexp (f x)) ν
h0 : NeZero ν
x : α
hx : (μ.rnDeriv (ν.tilted f) x).toReal = (rexp (-f x) * ∫ (x : α), rexp (f x) ∂ν) * (μ.rnDeriv ν x).toReal
hx_pos : 0 < μ.rnDeriv ν x
hx_lt_top : μ.rnDeriv ν x < ∞
⊢ rexp (-f x) * ∫ (x : α), rexp (f x) ∂ν ≠ 0

case hy
α : Type u_1
mα : MeasurableSpace α
μ ν : Measure α
f : α → ℝ
inst✝¹ : SigmaFinite μ
inst✝ : SigmaFinite ν
hμν : μ ≪ ν
hf : Integrable (fun x ↦ rexp (f x)) ν
h0 : NeZero ν
x : α
hx : (μ.rnDeriv (ν.tilted f) x).toReal = (rexp (-f x) * ∫ (x : α), rexp (f x) ∂ν) * (μ.rnDeriv ν x).toReal
hx_pos : 0 < μ.rnDeriv ν x
hx_lt_top : μ.rnDeriv ν x < ∞
⊢ (μ.rnDeriv ν x).toReal ≠ 0
Module: Mathlib.MeasureTheory.Function.ConditionalExpectation.Unique

Goal state before:
pp: case refine_2
α : Type u_1
E' : Type u_2
𝕜 : Type u_4
p : ℝ≥0∞
m m0 : MeasurableSpace α
μ : Measure α
inst✝⁴ : RCLike 𝕜
inst✝³ : NormedAddCommGroup E'
inst✝² : InnerProductSpace 𝕜 E'
inst✝¹ : CompleteSpace E'
inst✝ : NormedSpace ℝ E'
hm : m ≤ m0
f : ↥(lpMeas E' 𝕜 m p μ)
hp_ne_zero : p ≠ 0
hp_ne_top : p ≠ ∞
hf_int_finite : ∀ (s : Set α), MeasurableSet s → μ s < ∞ → IntegrableOn (↑↑↑f) s μ
hf_zero : ∀ (s : Set α), MeasurableSet s → μ s < ∞ → ∫ (x : α) in s, ↑↑↑f x ∂μ = 0
g : α → E'
hg_sm : FinStronglyMeasurable g (μ.trim hm)
hfg : ↑↑↑f =ᵐ[μ] g
⊢ ∀ (s : Set α), MeasurableSet s → μ s < ∞ → ∫ (x : α) in s, g x ∂μ = 0

Tactic:
intro s hs hμs
    have hfg_restrict : f =ᵐ[μ.restrict s] g := ae_restrict_of_ae hfg
    rw [integral_congr_ae hfg_restrict.symm]
    exact hf_zero s hs hμs

Goal state after:
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
hμ : ¬μ = 0
hν : ¬ν = 0
⊢ μ.real univ * log (μ.real univ / ν.real univ) + ν.real univ - μ.real univ =
    ν.real univ * klFun (μ.real univ / ν.real univ)

Tactic:
have : ν.real univ * (μ.real univ / ν.real univ) = μ.real univ := by
    rw [mul_div_cancel₀]; simp [ENNReal.toReal_eq_zero_iff, hν, measureReal_def]

Goal state after:
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
hμ : ¬μ = 0
hν : ¬ν = 0
this : ν.real univ * (μ.real univ / ν.real univ) = μ.real univ
⊢ μ.real univ * log (μ.real univ / ν.real univ) + ν.real univ - μ.real univ =
    ν.real univ * klFun (μ.real univ / ν.real univ)