mathlib-initiative/mathlib-tactics huggingface dataset:
Module: Mathlib.Probability.Kernel.Disintegration.Basic

Goal state before:
pp: case pos.right
α : Type u_1
β : Type u_2
Ω : Type u_3
mα : MeasurableSpace α
mβ : MeasurableSpace β
mΩ : MeasurableSpace Ω
κ : Kernel α (β × Ω)
κCond : Kernel (α × β) Ω
inst✝¹ : IsFiniteKernel κ.fst
inst✝ : κ.IsCondKernel κCond
a : α
h : κ.fst ⊗ₖ κCond = κ
h_sfin : IsSFiniteKernel κCond
h_eq : ∀ (s : Set β), MeasurableSet s → ∫⁻ (b : β), s.indicator (fun b ↦ (κCond (a, b)) univ) b ∂κ.fst a = (κ.fst a) s
h_meas : Measurable fun b ↦ (κCond (a, b)) univ
r : ℝ≥0∞
hr : r < 1
s : Set β := {b | (κCond (a, b)) univ ≤ r}
hs : MeasurableSet s
h_2_le : (s.indicator fun b ↦ (κCond (a, b)) univ) ≤ s.indicator fun x ↦ r
this : (κ.fst a) s ≤ ∫⁻ (b : β), s.indicator (fun x ↦ r) b ∂κ.fst a
⊢ (κ.fst a) {x | (κCond (a, x)) univ ≤ r} = 0

Tactic:
lintegral_indicator_const hs

Goal state after:
case pos.right
α : Type u_1
β : Type u_2
Ω : Type u_3
mα : MeasurableSpace α
mβ : MeasurableSpace β
mΩ : MeasurableSpace Ω
κ : Kernel α (β × Ω)
κCond : Kernel (α × β) Ω
inst✝¹ : IsFiniteKernel κ.fst
inst✝ : κ.IsCondKernel κCond
a : α
h : κ.fst ⊗ₖ κCond = κ
h_sfin : IsSFiniteKernel κCond
h_eq : ∀ (s : Set β), MeasurableSet s → ∫⁻ (b : β), s.indicator (fun b ↦ (κCond (a, b)) univ) b ∂κ.fst a = (κ.fst a) s
h_meas : Measurable fun b ↦ (κCond (a, b)) univ
r : ℝ≥0∞
hr : r < 1
s : Set β := {b | (κCond (a, b)) univ ≤ r}
hs : MeasurableSet s
h_2_le : (s.indicator fun b ↦ (κCond (a, b)) univ) ≤ s.indicator fun x ↦ r
this : (κ.fst a) s ≤ r * (κ.fst a) s
⊢ (κ.fst a) {x | (κCond (a, x)) univ ≤ r} = 0
Module: Mathlib.Probability.Kernel.Disintegration.Integral

Goal state before:
pp: α : Type u_1
β : Type u_2
Ω : Type u_3
mα : MeasurableSpace α
mβ : MeasurableSpace β
inst✝⁶ : MeasurableSpace Ω
inst✝⁵ : StandardBorelSpace Ω
inst✝⁴ : Nonempty Ω
inst✝³ : CountableOrCountablyGenerated α β
κ : Kernel α (β × Ω)
inst✝² : IsFiniteKernel κ
E : Type u_4
f : β × Ω → E
inst✝¹ : NormedAddCommGroup E
inst✝ : NormedSpace ℝ E
a : α
hf : AEStronglyMeasurable f (κ a)
⊢ AEStronglyMeasurable (fun x ↦ ∫ (y : Ω), f (x, y) ∂κ.condKernel (a, x)) (κ.fst a)

Tactic:
by
  rw [← κ.disintegrate κ.condKernel] at hf
  exact AEStronglyMeasurable.integral_kernel_compProd hf

Goal state after:
Module: Mathlib.Probability.Kernel.Disintegration.Density

Goal state before:
pp: case refine_2.refine_2.refine_1
α : Type u_1
β : Type u_2
γ : Type u_3
mα : MeasurableSpace α
mβ : MeasurableSpace β
mγ : MeasurableSpace γ
inst✝¹ : CountablyGenerated γ
κ : Kernel α (γ × β)
ν : Kernel α γ
hκν : κ.fst ≤ ν
inst✝ : IsFiniteKernel ν
a : α
s : Set β
hs : MeasurableSet s
ε : ℝ
x✝ : 0 < ε
n : ℕ
x : γ
⊢ ‖κ.densityProcess ν n a x s‖₊ ≤ 1

Tactic:
Real.nnnorm_of_nonneg (densityProcess_nonneg _ _ _ _ _ _)

Goal state after:
case refine_2.refine_2.refine_1
α : Type u_1
β : Type u_2
γ : Type u_3
mα : MeasurableSpace α
mβ : MeasurableSpace β
mγ : MeasurableSpace γ
inst✝¹ : CountablyGenerated γ
κ : Kernel α (γ × β)
ν : Kernel α γ
hκν : κ.fst ≤ ν
inst✝ : IsFiniteKernel ν
a : α
s : Set β
hs : MeasurableSet s
ε : ℝ
x✝ : 0 < ε
n : ℕ
x : γ
⊢ NNReal.mk (κ.densityProcess ν n a x s) ⋯ ≤ 1
Module: Mathlib.Probability.Kernel.Disintegration.Unique

Goal state before:
pp: α : Type u_1
Ω : Type u_3
mα : MeasurableSpace α
inst✝⁴ : MeasurableSpace Ω
inst✝³ : StandardBorelSpace Ω
inst✝² : Nonempty Ω
ρ : Measure (α × Ω)
inst✝¹ : IsFiniteMeasure ρ
κ : Kernel α Ω
inst✝ : IsFiniteKernel κ
hκ : ρ = ρ.fst ⊗ₘ κ
f : Ω → ℝ := embeddingReal Ω
hf : MeasurableEmbedding (embeddingReal Ω)
ρ' : Measure (α × ℝ) := Measure.map (Prod.map id f) ρ
hρ'def : ρ' = Measure.map (Prod.map id f) ρ
hρ' : ρ'.fst = ρ.fst
s : Set (α × ℝ)
hs : MeasurableSet s
⊢ (Measure.map (Prod.map id f) (ρ.fst ⊗ₘ κ)) s = (ρ'.fst ⊗ₘ κ.map f) s

Tactic:
Measure.map_apply (measurable_id.prodMap hf.measurable) hs,

Goal state after:
α : Type u_1
Ω : Type u_3
mα : MeasurableSpace α
inst✝⁴ : MeasurableSpace Ω
inst✝³ : StandardBorelSpace Ω
inst✝² : Nonempty Ω
ρ : Measure (α × Ω)
inst✝¹ : IsFiniteMeasure ρ
κ : Kernel α Ω
inst✝ : IsFiniteKernel κ
hκ : ρ = ρ.fst ⊗ₘ κ
f : Ω → ℝ := embeddingReal Ω
hf : MeasurableEmbedding (embeddingReal Ω)
ρ' : Measure (α × ℝ) := Measure.map (Prod.map id f) ρ
hρ'def : ρ' = Measure.map (Prod.map id f) ρ
hρ' : ρ'.fst = ρ.fst
s : Set (α × ℝ)
hs : MeasurableSet s
⊢ (ρ.fst ⊗ₘ κ) (Prod.map id (embeddingReal Ω) ⁻¹' s) = (ρ'.fst ⊗ₘ κ.map f) s
Module: Mathlib.Probability.Kernel.Disintegration.Density

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
inst✝¹ : CountablyGenerated γ
κ : Kernel α (γ × β)
ν : Kernel α γ
hκν : κ.fst ≤ ν
inst✝ : IsFiniteKernel ν
a : α
s : Set β
hs : MeasurableSet s
A✝ : Set γ
this✝ : IsFiniteKernel κ
hgen : mγ = generateFrom {s | ∃ n, MeasurableSet s}
hpi : IsPiSystem {s | ∃ n, MeasurableSet s}
A : Set γ
hA : MeasurableSet A
hA_eq : ∫ (x : γ) in A, κ.density ν a x s ∂ν a = (κ a).real (A ×ˢ s)
h : (κ a).real (A ×ˢ s) + ∫ (x : γ) in Aᶜ, κ.density ν a x s ∂ν a = (κ a).real (univ ×ˢ s)
this : Aᶜ ×ˢ s = univ ×ˢ s \ A ×ˢ s
⊢ A ×ˢ s ⊆ univ ×ˢ s

Tactic:
by intro x; simp

Goal state after:
Module: Mathlib.Probability.Kernel.Disintegration.Unique

Goal state before:
pp: α : Type u_1
Ω : Type u_3
mα : MeasurableSpace α
inst✝⁴ : MeasurableSpace Ω
inst✝³ : StandardBorelSpace Ω
inst✝² : Nonempty Ω
ρ : Measure (α × Ω)
inst✝¹ : IsFiniteMeasure ρ
κ : Kernel α Ω
inst✝ : IsFiniteKernel κ
hκ : ρ = ρ.fst ⊗ₘ κ
f : Ω → ℝ := embeddingReal Ω
hf : MeasurableEmbedding (embeddingReal Ω)
ρ' : Measure (α × ℝ) := Measure.map (Prod.map id f) ρ
hρ'def : ρ' = Measure.map (Prod.map id f) ρ
hρ' : ρ'.fst = ρ.fst
hρ'' : ∀ᵐ (x : α) ∂ρ.fst, (κ.map f) x = ρ'.condKernel x
s : Set (α × ℝ)
hs : MeasurableSet s
⊢ (Measure.map (Prod.map id f) (ρ.fst ⊗ₘ ρ.condKernel)) s =
    ∫⁻ (a : α), ((ρ.condKernel.map f) a) (Prod.mk a ⁻¹' s) ∂ρ.fst

Tactic:
Measure.map_apply (measurable_id.prodMap hf.measurable) hs,

Goal state after:
α : Type u_1
Ω : Type u_3
mα : MeasurableSpace α
inst✝⁴ : MeasurableSpace Ω
inst✝³ : StandardBorelSpace Ω
inst✝² : Nonempty Ω
ρ : Measure (α × Ω)
inst✝¹ : IsFiniteMeasure ρ
κ : Kernel α Ω
inst✝ : IsFiniteKernel κ
hκ : ρ = ρ.fst ⊗ₘ κ
f : Ω → ℝ := embeddingReal Ω
hf : MeasurableEmbedding (embeddingReal Ω)
ρ' : Measure (α × ℝ) := Measure.map (Prod.map id f) ρ
hρ'def : ρ' = Measure.map (Prod.map id f) ρ
hρ' : ρ'.fst = ρ.fst
hρ'' : ∀ᵐ (x : α) ∂ρ.fst, (κ.map f) x = ρ'.condKernel x
s : Set (α × ℝ)
hs : MeasurableSet s
⊢ (ρ.fst ⊗ₘ ρ.condKernel) (Prod.map id (embeddingReal Ω) ⁻¹' s) =
    ∫⁻ (a : α), ((ρ.condKernel.map f) a) (Prod.mk a ⁻¹' s) ∂ρ.fst
Module: Mathlib.Probability.Kernel.Disintegration.Unique

Goal state before:
pp: α : Type u_1
β : Type u_2
Ω : Type u_3
mα : MeasurableSpace α
mβ : MeasurableSpace β
inst✝⁴ : MeasurableSpace Ω
inst✝³ : StandardBorelSpace Ω
inst✝² : Nonempty Ω
ρ : Kernel α (β × Ω)
inst✝¹ : IsFiniteKernel ρ
κ : Kernel (α × β) Ω
inst✝ : IsFiniteKernel κ
hκ : ρ.fst ⊗ₖ κ = ρ
a : α
s : Set (β × Ω)
hs : MeasurableSet s
⊢ (ρ a) s = ((ρ a).fst ⊗ₘ κ.comap (fun b ↦ (a, b)) ⋯) s

Tactic:
conv_lhs => rw [← hκ]

Goal state after:
α : Type u_1
β : Type u_2
Ω : Type u_3
mα : MeasurableSpace α
mβ : MeasurableSpace β
inst✝⁴ : MeasurableSpace Ω
inst✝³ : StandardBorelSpace Ω
inst✝² : Nonempty Ω
ρ : Kernel α (β × Ω)
inst✝¹ : IsFiniteKernel ρ
κ : Kernel (α × β) Ω
inst✝ : IsFiniteKernel κ
hκ : ρ.fst ⊗ₖ κ = ρ
a : α
s : Set (β × Ω)
hs : MeasurableSet s
⊢ ((ρ.fst ⊗ₖ κ) a) s = ((ρ a).fst ⊗ₘ κ.comap (fun b ↦ (a, b)) ⋯) s
Module: Mathlib.Probability.Kernel.IonescuTulcea.Maps

Goal state before:
pp: case refine_2
ι : Type u_1
inst✝³ : LinearOrder ι
inst✝² : LocallyFiniteOrder ι
inst✝¹ : DecidableLE ι
X : ι → Type u_2
inst✝ : LocallyFiniteOrderBot ι
a b : ι
hab : a ≤ b
s : (i : ↥(Iic b)) → Set (X ↑i)
x : ((i : ↥(Iic a)) → X ↑i) × ((i : ↥(Ioc a b)) → X ↑i)
h : ∀ (a_1 : ι) (b_1 : a_1 ≤ b), (if h : a_1 ≤ a then x.1 ⟨a_1, ⋯⟩ else x.2 ⟨a_1, ⋯⟩) ∈ s ⟨a_1, ⋯⟩
i : ι
x✝ : a < i ∧ i ≤ b
hi1 : a < i
hi2 : i ≤ b
⊢ x.2 ⟨i, ⋯⟩ ∈ s ⟨i, ⋯⟩

Tactic:
convert! h i hi2
    rw [dif_neg (not_le.2 hi1)]

Goal state after:
Module: Mathlib.Probability.Kernel.CondDistrib

Goal state before:
pp: α : Type u_1
β : Type u_2
Ω : Type u_3
inst✝³ : MeasurableSpace Ω
inst✝² : StandardBorelSpace Ω
inst✝¹ : Nonempty Ω
mα : MeasurableSpace α
μ : Measure α
inst✝ : IsFiniteMeasure μ
X : α → β
Y : α → Ω
mβ : MeasurableSpace β
s : Set Ω
t : Set β
hX : Measurable X
hY : AEMeasurable Y μ
hs : MeasurableSet s
ht : MeasurableSet t
⊢ ∫⁻ (a : α) in X ⁻¹' t, ((condDistrib Y X μ) (X a)) s ∂μ = μ (X ⁻¹' t ∩ Y ⁻¹' s)

Tactic:
← lintegral_map (Kernel.measurable_coe _ hs) hX,

Goal state after:
α : Type u_1
β : Type u_2
Ω : Type u_3
inst✝³ : MeasurableSpace Ω
inst✝² : StandardBorelSpace Ω
inst✝¹ : Nonempty Ω
mα : MeasurableSpace α
μ : Measure α
inst✝ : IsFiniteMeasure μ
X : α → β
Y : α → Ω
mβ : MeasurableSpace β
s : Set Ω
t : Set β
hX : Measurable X
hY : AEMeasurable Y μ
hs : MeasurableSet s
ht : MeasurableSet t
⊢ ∫⁻ (a : β), ((condDistrib Y X μ) a) s ∂Measure.map X (μ.restrict (X ⁻¹' t)) = μ (X ⁻¹' t ∩ Y ⁻¹' s)
Module: Mathlib.Probability.Kernel.CondDistrib

Goal state before:
pp: case refine_2
α : Type u_1
β : Type u_2
Ω : Type u_3
F : Type u_4
inst✝⁶ : MeasurableSpace Ω
inst✝⁵ : StandardBorelSpace Ω
inst✝⁴ : Nonempty Ω
inst✝³ : NormedAddCommGroup F
mα : MeasurableSpace α
μ : Measure α
inst✝² : IsFiniteMeasure μ
X : α → β
Y : α → Ω
mβ : MeasurableSpace β
f : β × Ω → F
inst✝¹ : NormedSpace ℝ F
inst✝ : CompleteSpace F
hX : Measurable X
hY : AEMeasurable Y μ
hf_int : Integrable f (Measure.map (fun a ↦ (X a, Y a)) μ)
hf_int' : Integrable (fun a ↦ f (X a, Y a)) μ
t : Set β
ht : MeasurableSet t
a✝ : μ (X ⁻¹' t) < ∞
⊢ ∫ (x : α) in X ⁻¹' t ∩ Y ⁻¹' univ, f (X x, Y x) ∂μ = ∫ (a : α) in X ⁻¹' t, f (X a, Y a) ∂μ

Tactic:
preimage_univ,

Goal state after:
case refine_2
α : Type u_1
β : Type u_2
Ω : Type u_3
F : Type u_4
inst✝⁶ : MeasurableSpace Ω
inst✝⁵ : StandardBorelSpace Ω
inst✝⁴ : Nonempty Ω
inst✝³ : NormedAddCommGroup F
mα : MeasurableSpace α
μ : Measure α
inst✝² : IsFiniteMeasure μ
X : α → β
Y : α → Ω
mβ : MeasurableSpace β
f : β × Ω → F
inst✝¹ : NormedSpace ℝ F
inst✝ : CompleteSpace F
hX : Measurable X
hY : AEMeasurable Y μ
hf_int : Integrable f (Measure.map (fun a ↦ (X a, Y a)) μ)
hf_int' : Integrable (fun a ↦ f (X a, Y a)) μ
t : Set β
ht : MeasurableSet t
a✝ : μ (X ⁻¹' t) < ∞
⊢ ∫ (x : α) in X ⁻¹' t ∩ univ, f (X x, Y x) ∂μ = ∫ (a : α) in X ⁻¹' t, f (X a, Y a) ∂μ
Module: Mathlib.Probability.Kernel.CondDistrib

Goal state before:
pp: case pos
β : Type u_2
mβ : MeasurableSpace β
Ω : Type u_5
F : Type u_6
mΩ : MeasurableSpace Ω
X : Ω → β
μ : Measure Ω
inst✝ : TopologicalSpace F
f : Ω → F
hf : AEStronglyMeasurable f μ
s : Set Ω
hs : MeasurableSet s
hμs : μ s = 0
hX : AEMeasurable X μ
⊢ μ (X ⁻¹' univ ∩ (fun ω ↦ ω) ⁻¹' s) = 0

Tactic:
preimage_univ,

Goal state after:
case pos
β : Type u_2
mβ : MeasurableSpace β
Ω : Type u_5
F : Type u_6
mΩ : MeasurableSpace Ω
X : Ω → β
μ : Measure Ω
inst✝ : TopologicalSpace F
f : Ω → F
hf : AEStronglyMeasurable f μ
s : Set Ω
hs : MeasurableSet s
hμs : μ s = 0
hX : AEMeasurable X μ
⊢ μ (univ ∩ (fun ω ↦ ω) ⁻¹' s) = 0
Module: Mathlib.Probability.Kernel.RadonNikodym

Goal state before:
pp: α : Type u_1
γ : Type u_2
mα : MeasurableSpace α
mγ : MeasurableSpace γ
hαγ : MeasurableSpace.CountableOrCountablyGenerated α γ
κ η : Kernel α γ
inst✝¹ : IsFiniteKernel κ
inst✝ : IsFiniteKernel η
a : α
x : γ
hx : x ∈ {x | 1 ≤ κ.rnDerivAux (κ + η) a x}
⊢ ENNReal.ofReal (1 - κ.rnDerivAux (κ + η) a x) = 0 x

Tactic:
simp only [mem_ofPred_eq] at hx

Goal state after:
α : Type u_1
γ : Type u_2
mα : MeasurableSpace α
mγ : MeasurableSpace γ
hαγ : MeasurableSpace.CountableOrCountablyGenerated α γ
κ η : Kernel α γ
inst✝¹ : IsFiniteKernel κ
inst✝ : IsFiniteKernel η
a : α
x : γ
hx : 1 ≤ κ.rnDerivAux (κ + η) a x
⊢ ENNReal.ofReal (1 - κ.rnDerivAux (κ + η) a x) = 0 x
Module: Mathlib.Probability.ProductMeasure

Goal state before:
pp: ι : Type u_1
X : ι → Type u_2
mX : (i : ι) → MeasurableSpace (X i)
μ : (i : ι) → Measure (X i)
hμ : ∀ (i : ι), IsProbabilityMeasure (μ i)
ν : Measure ((i : ι) → X i)
hν : ∀ (s : Finset ι) (t : (i : ι) → Set (X i)), (∀ (i : ι), MeasurableSet (t i)) → ν ((↑s).pi t) = ∏ i ∈ s, (μ i) (t i)
s : Finset ι
t : (i : ↥s) → Set (X ↑i)
ht : ∀ (i : ↥s), MeasurableSet (t i)
⊢ ∏ x ∈ s.attach, (μ ↑x) (if h : ↑x ∈ s then t ⟨↑x, h⟩ else Set.univ) = ∏ i ∈ s.attach, (μ ↑i) (t i)

Tactic:
congr with i
    rw [dif_pos i.2]

Goal state after:
Module: Mathlib.Probability.Kernel.IonescuTulcea.Traj

Goal state before:
pp: X : ℕ → Type u_1
inst✝¹ : (n : ℕ) → MeasurableSpace (X n)
κ : (n : ℕ) → Kernel ((i : ↥(Iic n)) → X ↑i) (X (n + 1))
inst✝ : ∀ (n : ℕ), IsMarkovKernel (κ n)
a : ℕ
x₀ : (i : ↥(Iic a)) → X ↑i
⊢ IsProjectiveLimit (trajFun κ a x₀) (inducedFamily fun n ↦ (partialTraj κ a n) x₀)

Tactic:
refine isProjectiveLimit_nat_iff (isProjectiveMeasureFamily_partialTraj κ x₀) _ |>.2 fun n ↦ ?_
  ext s ms
  rw [Measure.map_apply (measurable_frestrictLe n) ms, trajFun, AddContent.measure_eq, trajContent,
    projectiveFamilyContent_congr _ (frestrictLe n ⁻¹' s) rfl ms]
  · exact generateFrom_measurableCylinders.symm
  · exact cylinder_mem_measurableCylinders _ _ ms

Goal state after:
Module: Mathlib.Probability.Kernel.Deterministic

Goal state before:
pp: α : Type u_1
β : Type u_2
mα : MeasurableSpace α
mβ : MeasurableSpace β
γ : Type u_3
inst✝³ : MeasurableSpace γ
κ : Kernel α β
η : Kernel β γ
inst✝² : IsMarkovKernel κ
inst✝¹ : IsMarkovKernel η
inst✝ : IsDeterministic (η ∘ₖ κ)
a : α
s : Set γ
t : Set β
hs : MeasurableSet s
ht : MeasurableSet t
this : ∀ (b : β), (η b) s * t.indicator 1 b = t.indicator (fun b ↦ (η b) s) b
⊢ ∫⁻ (b : β), t.indicator (fun b ↦ (η b) s) b ∂κ a = ((η ∘ₖ κ) a) s * (κ a) t

Tactic:
lintegral_indicator ht

Goal state after:
α : Type u_1
β : Type u_2
mα : MeasurableSpace α
mβ : MeasurableSpace β
γ : Type u_3
inst✝³ : MeasurableSpace γ
κ : Kernel α β
η : Kernel β γ
inst✝² : IsMarkovKernel κ
inst✝¹ : IsMarkovKernel η
inst✝ : IsDeterministic (η ∘ₖ κ)
a : α
s : Set γ
t : Set β
hs : MeasurableSet s
ht : MeasurableSet t
this : ∀ (b : β), (η b) s * t.indicator 1 b = t.indicator (fun b ↦ (η b) s) b
⊢ ∫⁻ (a : β) in t, (η a) s ∂κ a = ((η ∘ₖ κ) a) s * (κ a) t
Module: Mathlib.Probability.ProductMeasure

Goal state before:
pp: case hb
ι✝ : Type u_1
X✝ : ι✝ → Type u_2
mX✝ : (i : ι✝) → MeasurableSpace (X✝ i)
μ✝ : (i : ι✝) → Measure (X✝ i)
ι : Type u_1
X : ι → Type u_2
mX : (i : ι) → MeasurableSpace (X i)
μ : (i : ι) → Measure (X i)
hμ : ∀ (i : ι), IsProbabilityMeasure (μ i)
s : Set ι
hs : Countable ↑s
t : (i : ι) → Set (X i)
mt : ∀ i ∈ s, MeasurableSet (t i)
s_ne : Nonempty ↑s
⊢ Tendsto (fun s' ↦ ∏ i ∈ s', (μ ↑i) (t ↑i)) atTop (𝓝 (∏' (i : ↑s), (μ ↑i) (t ↑i)))

Tactic:
· rw [ENNReal.tprod_eq_iInf_prod (by simp [prob_le_one])]
    exact tendsto_atTop_iInf (prod_anti_set_of_le_one' (by simp [prob_le_one]))

Goal state after:
Module: Mathlib.Probability.Kernel.Posterior

Goal state before:
pp: Ω : Type u_1
𝓧 : Type u_2
mΩ : MeasurableSpace Ω
m𝓧 : MeasurableSpace 𝓧
κ : Kernel Ω 𝓧
μ : Measure Ω
inst✝⁵ : IsFiniteMeasure μ
inst✝⁴ : IsFiniteKernel κ
inst✝³ : StandardBorelSpace Ω
inst✝² : Nonempty Ω
inst✝¹ : MeasurableSpace.CountableOrCountablyGenerated Ω 𝓧
ν : Measure 𝓧
inst✝ : SFinite ν
h_ac : ∀ᵐ (ω : Ω) ∂μ, κ ω ≪ ν
⊢ ∀ᵐ (ω : Ω) ∂μ, κ ω ≪ ⇑κ ∘ₘ μ

Tactic:
← absolutelyContinuous_posterior_iff

Goal state after:
Ω : Type u_1
𝓧 : Type u_2
mΩ : MeasurableSpace Ω
m𝓧 : MeasurableSpace 𝓧
κ : Kernel Ω 𝓧
μ : Measure Ω
inst✝⁵ : IsFiniteMeasure μ
inst✝⁴ : IsFiniteKernel κ
inst✝³ : StandardBorelSpace Ω
inst✝² : Nonempty Ω
inst✝¹ : MeasurableSpace.CountableOrCountablyGenerated Ω 𝓧
ν : Measure 𝓧
inst✝ : SFinite ν
h_ac : ∀ᵐ (ω : Ω) ∂μ, κ ω ≪ ν
⊢ ∀ᵐ (b : 𝓧) ∂⇑κ ∘ₘ μ, (κ†μ) b ≪ μ
Module: Mathlib.Probability.ProbabilityMassFunction.Basic

Goal state before:
pp: α : Type u_1
p : PMF α
s : Finset α
⊢ p.toOuterMeasure ↑s = ∑ x ∈ s, p x

Tactic:
by
  refine (toOuterMeasure_apply p s).trans ((tsum_eq_sum (s := s) ?_).trans ?_)
  · exact fun x hx => Set.indicator_of_notMem (Finset.mem_coe.not.2 hx) _
  · exact Finset.sum_congr rfl fun x hx => Set.indicator_of_mem (Finset.mem_coe.2 hx) _

Goal state after:
Module: Mathlib.Probability.ProbabilityMassFunction.Monad

Goal state before:
pp: case neg
α : Type u_1
a : α
s : Set α
ha : a ∉ s
⊢ ∑' (x : α), s.indicator (⇑(pure a)) x = 0

Tactic:
refine (tsum_congr fun b => ?_).trans tsum_zero

Goal state after:
case neg
α : Type u_1
a : α
s : Set α
ha : a ∉ s
b : α
⊢ s.indicator (⇑(pure a)) b = 0
Module: Mathlib.Probability.ProbabilityMassFunction.Constructions

Goal state before:
pp: case false.mp
p : ℝ≥0
h : p ≤ 1
⊢ 1 - ↑p = 0 → p = 1

pp: case false.mpr
p : ℝ≥0
h : p ≤ 1
⊢ p = 1 → 1 - ↑p = 0

Tactic:
· intro h'
      simp only [tsub_eq_zero_iff_le, one_le_coe_iff] at h'
      exact eq_of_le_of_ge h h'

Goal state after:
case false.mpr
p : ℝ≥0
h : p ≤ 1
⊢ p = 1 → 1 - ↑p = 0
Module: Mathlib.Probability.Distributions.TwoValued

Goal state before:
pp: Ω : Type u_1
m : MeasurableSpace Ω
X : Ω → ℝ
μ : Measure Ω
inst✝ : IsZeroOrProbabilityMeasure μ
hXmeas : AEMeasurable X μ
hX : ∀ᵐ (ω : Ω) ∂μ, X ω = 0 ∨ X ω = 1
⊢ Var[X; μ] = μ.real {ω | X ω = 0} * μ.real {ω | X ω = 1}

Tactic:
obtain rfl | hμ := eq_zero_or_isProbabilityMeasure μ
  · simp
  simpa [Pi.mul_def, integral_of_ae_eq_zero_or_one, integral_one_sub_of_ae_eq_zero_or_one, mul_comm,
    *] using condVar_of_ae_eq_zero_or_one bot_le hXmeas hX

Goal state after:
Module: Mathlib.Probability.Kernel.Condexp

Goal state before:
pp: case inr
Ω : Type u_1
F : Type u_2
m mΩ : MeasurableSpace Ω
inst✝⁴ : StandardBorelSpace Ω
μ : Measure Ω
inst✝³ : IsFiniteMeasure μ
inst✝² : NormedAddCommGroup F
f : Ω → F
inst✝¹ : NormedSpace ℝ F
inst✝ : CompleteSpace F
hf_int : Integrable f μ
h : Nonempty Ω
⊢ μ[f | m ⊓ mΩ] =ᵐ[μ] fun ω ↦ ∫ (y : Ω), f y ∂(condExpKernel μ m) ω

Tactic:
have hX : @Measurable Ω Ω mΩ (m ⊓ mΩ) id := measurable_id.mono le_rfl (inf_le_right : m ⊓ mΩ ≤ mΩ)

Goal state after:
case inr
Ω : Type u_1
F : Type u_2
m mΩ : MeasurableSpace Ω
inst✝⁴ : StandardBorelSpace Ω
μ : Measure Ω
inst✝³ : IsFiniteMeasure μ
inst✝² : NormedAddCommGroup F
f : Ω → F
inst✝¹ : NormedSpace ℝ F
inst✝ : CompleteSpace F
hf_int : Integrable f μ
h : Nonempty Ω
hX : Measurable id
⊢ μ[f | m ⊓ mΩ] =ᵐ[μ] fun ω ↦ ∫ (y : Ω), f y ∂(condExpKernel μ m) ω
Module: Mathlib.Probability.Independence.ZeroOne

Goal state before:
pp: α : Type u_1
Ω : Type u_2
ι : Type u_3
_mα : MeasurableSpace α
s : ι → MeasurableSpace Ω
m0 : MeasurableSpace Ω
κ : Kernel α Ω
μα : Measure α
β : Type u_4
p : Set ι → Prop
f : Filter ι
ns : β → Set ι
h_le : ∀ (n : ι), s n ≤ m0
h_indep : iIndep s κ μα
hf : ∀ (t : Set ι), p t → tᶜ ∈ f
hns : Directed (fun x1 x2 ↦ x1 ⊆ x2) ns
hnsp : ∀ (a : β), p (ns a)
⊢ Indep (⨆ a, ⨆ n ∈ ns a, s n) (limsup s f) κ μα

Tactic:
rcases eq_or_ne μα 0 with rfl | hμ
  · simp
  obtain ⟨η, η_eq, hη⟩ : ∃ (η : Kernel α Ω), κ =ᵐ[μα] η ∧ IsMarkovKernel η :=
    exists_ae_eq_isMarkovKernel h_indep.ae_isProbabilityMeasure hμ
  replace h_indep := h_indep.congr η_eq
  apply Indep.congr (Filter.EventuallyEq.symm η_eq)
  apply indep_iSup_of_directed_le
  · exact fun a => indep_biSup_limsup h_le h_indep hf (hnsp a)
  · exact fun a => iSup₂_le fun n _ => h_le n
  · exact limsup_le_iSup.trans (iSup_le h_le)
  · intro a b
    obtain ⟨c, hc⟩ := hns a b
    refine ⟨c, ?_, ?_⟩ <;> refine iSup_mono fun n => iSup_mono' fun hn => ⟨?_, le_rfl⟩
    · exact hc.1 hn
    · exact hc.2 hn

Goal state after:
Module: Mathlib.Probability.Independence.Conditional

Goal state before:
pp: Ω : Type u_1
m' mΩ : MeasurableSpace Ω
inst✝¹ : StandardBorelSpace Ω
hm' : m' ≤ mΩ
s1 s2 : Set (Set Ω)
hs1 : ∀ s ∈ s1, MeasurableSet s
hs2 : ∀ s ∈ s2, MeasurableSet s
μ : Measure Ω
inst✝ : IsFiniteMeasure μ
hs1_eq : ∀ s ∈ s1, (fun ω ↦ (((condExpKernel μ m') ω) s).toReal) =ᵐ[μ] μ[s.indicator fun ω ↦ 1 | m']
hs2_eq : ∀ s ∈ s2, (fun ω ↦ (((condExpKernel μ m') ω) s).toReal) =ᵐ[μ] μ[s.indicator fun ω ↦ 1 | m']
hs12_eq :
  ∀ s ∈ s1, ∀ t ∈ s2, (fun ω ↦ (((condExpKernel μ m') ω) (s ∩ t)).toReal) =ᵐ[μ] μ[(s ∩ t).indicator fun ω ↦ 1 | m']
s t : Set Ω
h : ∀ᵐ (a : Ω) ∂μ.trim hm', ((condExpKernel μ m') a) (s ∩ t) = ((condExpKernel μ m') a) s * ((condExpKernel μ m') a) t
hs : s ∈ s1
ht : t ∈ s2
h' : (fun x ↦ ((condExpKernel μ m') x) (s ∩ t)) =ᵐ[μ] fun x ↦ ((condExpKernel μ m') x) s * ((condExpKernel μ m') x) t
ω : Ω
⊢ (((condExpKernel μ m') ω) s).toReal = μ[s.indicator fun ω ↦ 1 | m'] ω →
    (((condExpKernel μ m') ω) t).toReal = μ[t.indicator fun ω ↦ 1 | m'] ω →
      (((condExpKernel μ m') ω) (s ∩ t)).toReal = μ[(s ∩ t).indicator fun ω ↦ 1 | m'] ω →
        ((condExpKernel μ m') ω) (s ∩ t) = ((condExpKernel μ m') ω) s * ((condExpKernel μ m') ω) t →
          μ[(s ∩ t).indicator fun ω ↦ 1 | m'] ω = (μ[s.indicator fun ω ↦ 1 | m'] * μ[t.indicator fun ω ↦ 1 | m']) ω

Tactic:
hs_eq

Goal state after:
Ω : Type u_1
m' mΩ : MeasurableSpace Ω
inst✝¹ : StandardBorelSpace Ω
hm' : m' ≤ mΩ
s1 s2 : Set (Set Ω)
hs1 : ∀ s ∈ s1, MeasurableSet s
hs2 : ∀ s ∈ s2, MeasurableSet s
μ : Measure Ω
inst✝ : IsFiniteMeasure μ
hs1_eq : ∀ s ∈ s1, (fun ω ↦ (((condExpKernel μ m') ω) s).toReal) =ᵐ[μ] μ[s.indicator fun ω ↦ 1 | m']
hs2_eq : ∀ s ∈ s2, (fun ω ↦ (((condExpKernel μ m') ω) s).toReal) =ᵐ[μ] μ[s.indicator fun ω ↦ 1 | m']
hs12_eq :
  ∀ s ∈ s1, ∀ t ∈ s2, (fun ω ↦ (((condExpKernel μ m') ω) (s ∩ t)).toReal) =ᵐ[μ] μ[(s ∩ t).indicator fun ω ↦ 1 | m']
s t : Set Ω
h : ∀ᵐ (a : Ω) ∂μ.trim hm', ((condExpKernel μ m') a) (s ∩ t) = ((condExpKernel μ m') a) s * ((condExpKernel μ m') a) t
hs : s ∈ s1
ht : t ∈ s2
h' : (fun x ↦ ((condExpKernel μ m') x) (s ∩ t)) =ᵐ[μ] fun x ↦ ((condExpKernel μ m') x) s * ((condExpKernel μ m') x) t
ω : Ω
hs_eq : (((condExpKernel μ m') ω) s).toReal = μ[s.indicator fun ω ↦ 1 | m'] ω
⊢ (((condExpKernel μ m') ω) t).toReal = μ[t.indicator fun ω ↦ 1 | m'] ω →
    (((condExpKernel μ m') ω) (s ∩ t)).toReal = μ[(s ∩ t).indicator fun ω ↦ 1 | m'] ω →
      ((condExpKernel μ m') ω) (s ∩ t) = ((condExpKernel μ m') ω) s * ((condExpKernel μ m') ω) t →
        μ[(s ∩ t).indicator fun ω ↦ 1 | m'] ω = (μ[s.indicator fun ω ↦ 1 | m'] * μ[t.indicator fun ω ↦ 1 | m']) ω
Module: Mathlib.Probability.Independence.Conditional

Goal state before:
pp: Ω : Type u_1
m' mΩ : MeasurableSpace Ω
inst✝¹ : StandardBorelSpace Ω
hm' : m' ≤ mΩ
s1 s2 : Set (Set Ω)
hs1 : ∀ s ∈ s1, MeasurableSet s
hs2 : ∀ s ∈ s2, MeasurableSet s
μ : Measure Ω
inst✝ : IsFiniteMeasure μ
hs1_eq : ∀ s ∈ s1, (fun ω ↦ (((condExpKernel μ m') ω) s).toReal) =ᵐ[μ] μ[s.indicator fun ω ↦ 1 | m']
hs2_eq : ∀ s ∈ s2, (fun ω ↦ (((condExpKernel μ m') ω) s).toReal) =ᵐ[μ] μ[s.indicator fun ω ↦ 1 | m']
hs12_eq :
  ∀ s ∈ s1, ∀ t ∈ s2, (fun ω ↦ (((condExpKernel μ m') ω) (s ∩ t)).toReal) =ᵐ[μ] μ[(s ∩ t).indicator fun ω ↦ 1 | m']
s t : Set Ω
h : μ[(s ∩ t).indicator fun ω ↦ 1 | m'] =ᵐ[μ] μ[s.indicator fun ω ↦ 1 | m'] * μ[t.indicator fun ω ↦ 1 | m']
hs : s ∈ s1
ht : t ∈ s2
ω : Ω
⊢ (((condExpKernel μ m') ω) s).toReal = μ[s.indicator fun ω ↦ 1 | m'] ω →
    (((condExpKernel μ m') ω) t).toReal = μ[t.indicator fun ω ↦ 1 | m'] ω →
      (((condExpKernel μ m') ω) (s ∩ t)).toReal = μ[(s ∩ t).indicator fun ω ↦ 1 | m'] ω →
        μ[(s ∩ t).indicator fun ω ↦ 1 | m'] ω = (μ[s.indicator fun ω ↦ 1 | m'] * μ[t.indicator fun ω ↦ 1 | m']) ω →
          ((condExpKernel μ m') ω) (s ∩ t) = ((condExpKernel μ m') ω) s * ((condExpKernel μ m') ω) t

Tactic:
hs_eq

Goal state after:
Ω : Type u_1
m' mΩ : MeasurableSpace Ω
inst✝¹ : StandardBorelSpace Ω
hm' : m' ≤ mΩ
s1 s2 : Set (Set Ω)
hs1 : ∀ s ∈ s1, MeasurableSet s
hs2 : ∀ s ∈ s2, MeasurableSet s
μ : Measure Ω
inst✝ : IsFiniteMeasure μ
hs1_eq : ∀ s ∈ s1, (fun ω ↦ (((condExpKernel μ m') ω) s).toReal) =ᵐ[μ] μ[s.indicator fun ω ↦ 1 | m']
hs2_eq : ∀ s ∈ s2, (fun ω ↦ (((condExpKernel μ m') ω) s).toReal) =ᵐ[μ] μ[s.indicator fun ω ↦ 1 | m']
hs12_eq :
  ∀ s ∈ s1, ∀ t ∈ s2, (fun ω ↦ (((condExpKernel μ m') ω) (s ∩ t)).toReal) =ᵐ[μ] μ[(s ∩ t).indicator fun ω ↦ 1 | m']
s t : Set Ω
h : μ[(s ∩ t).indicator fun ω ↦ 1 | m'] =ᵐ[μ] μ[s.indicator fun ω ↦ 1 | m'] * μ[t.indicator fun ω ↦ 1 | m']
hs : s ∈ s1
ht : t ∈ s2
ω : Ω
hs_eq : (((condExpKernel μ m') ω) s).toReal = μ[s.indicator fun ω ↦ 1 | m'] ω
⊢ (((condExpKernel μ m') ω) t).toReal = μ[t.indicator fun ω ↦ 1 | m'] ω →
    (((condExpKernel μ m') ω) (s ∩ t)).toReal = μ[(s ∩ t).indicator fun ω ↦ 1 | m'] ω →
      μ[(s ∩ t).indicator fun ω ↦ 1 | m'] ω = (μ[s.indicator fun ω ↦ 1 | m'] * μ[t.indicator fun ω ↦ 1 | m']) ω →
        ((condExpKernel μ m') ω) (s ∩ t) = ((condExpKernel μ m') ω) s * ((condExpKernel μ m') ω) t