mathlib-initiative/mathlib-tactics huggingface dataset:
Module: Mathlib.MeasureTheory.Measure.FiniteMeasure

Goal state before:
pp: case hf
Ω' : Type u_2
inst✝⁶ : MeasurableSpace Ω'
inst✝⁵ : TopologicalSpace Ω'
inst✝⁴ : BorelSpace Ω'
Ω : Type u_3
inst✝³ : MeasurableSpace Ω
inst✝² : TopologicalSpace Ω
inst✝¹ : BorelSpace Ω
inst✝ : NormalSpace Ω'
f : Ω → Ω'
hf : IsClosedEmbedding f
M : Set (FiniteMeasure Ω') := {μ | μ (range f)ᶜ = 0}
A : IsEmbedding Subtype.val
μ : ↑M
s : Set Ω'
hs : MeasurableSet s
⊢ ∀ (s : Set Ω), MeasurableSet s → MeasurableSet (f '' s)

pp: case hs
Ω' : Type u_2
inst✝⁶ : MeasurableSpace Ω'
inst✝⁵ : TopologicalSpace Ω'
inst✝⁴ : BorelSpace Ω'
Ω : Type u_3
inst✝³ : MeasurableSpace Ω
inst✝² : TopologicalSpace Ω
inst✝¹ : BorelSpace Ω
inst✝ : NormalSpace Ω'
f : Ω → Ω'
hf : IsClosedEmbedding f
M : Set (FiniteMeasure Ω') := {μ | μ (range f)ᶜ = 0}
A : IsEmbedding Subtype.val
μ : ↑M
s : Set Ω'
hs : MeasurableSet s
⊢ MeasurableSet (f ⁻¹' s)

Tactic:
· exact fun t ht ↦ hf.measurableEmbedding.measurableSet_image' ht

Goal state after:
case hs
Ω' : Type u_2
inst✝⁶ : MeasurableSpace Ω'
inst✝⁵ : TopologicalSpace Ω'
inst✝⁴ : BorelSpace Ω'
Ω : Type u_3
inst✝³ : MeasurableSpace Ω
inst✝² : TopologicalSpace Ω
inst✝¹ : BorelSpace Ω
inst✝ : NormalSpace Ω'
f : Ω → Ω'
hf : IsClosedEmbedding f
M : Set (FiniteMeasure Ω') := {μ | μ (range f)ᶜ = 0}
A : IsEmbedding Subtype.val
μ : ↑M
s : Set Ω'
hs : MeasurableSet s
⊢ MeasurableSet (f ⁻¹' s)
Module: Mathlib.Probability.Independence.Kernel.IndepFun

Goal state before:
pp: α : Type u_1
Ω : Type u_2
ι : Type u_3
mα : MeasurableSpace α
mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
β : ι → Type u_8
mβ : (i : ι) → MeasurableSpace (β i)
f g : (i : ι) → Ω → β i
hf :
  ∀ (S : Finset ι) {sets : (i : ι) → Set (β i)},
    (∀ i ∈ S, MeasurableSet (sets i)) → ∀ᵐ (a : α) ∂μ, (κ a) (⋂ i ∈ S, f i ⁻¹' sets i) = ∏ i ∈ S, (κ a) (f i ⁻¹' sets i)
h : ∀ (i : ι), ∀ᵐ (a : α) ∂μ, f i =ᵐ[κ a] g i
S : Finset ι
sets : (i : ι) → Set (β i)
hmeas : ∀ i ∈ S, MeasurableSet (sets i)
this : ∀ᵐ (a : α) ∂μ, ∀ i ∈ S, f i =ᵐ[κ a] g i
a : α
⊢ (∀ i ∈ S, f i =ᵐ[κ a] g i) →
    (κ a) (⋂ i ∈ S, f i ⁻¹' sets i) = ∏ i ∈ S, (κ a) (f i ⁻¹' sets i) →
      (κ a) (⋂ i ∈ S, g i ⁻¹' sets i) = ∏ i ∈ S, (κ a) (g i ⁻¹' sets i)

Tactic:
ha

Goal state after:
α : Type u_1
Ω : Type u_2
ι : Type u_3
mα : MeasurableSpace α
mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
β : ι → Type u_8
mβ : (i : ι) → MeasurableSpace (β i)
f g : (i : ι) → Ω → β i
hf :
  ∀ (S : Finset ι) {sets : (i : ι) → Set (β i)},
    (∀ i ∈ S, MeasurableSet (sets i)) → ∀ᵐ (a : α) ∂μ, (κ a) (⋂ i ∈ S, f i ⁻¹' sets i) = ∏ i ∈ S, (κ a) (f i ⁻¹' sets i)
h : ∀ (i : ι), ∀ᵐ (a : α) ∂μ, f i =ᵐ[κ a] g i
S : Finset ι
sets : (i : ι) → Set (β i)
hmeas : ∀ i ∈ S, MeasurableSet (sets i)
this : ∀ᵐ (a : α) ∂μ, ∀ i ∈ S, f i =ᵐ[κ a] g i
a : α
ha : ∀ i ∈ S, f i =ᵐ[κ a] g i
⊢ (κ a) (⋂ i ∈ S, f i ⁻¹' sets i) = ∏ i ∈ S, (κ a) (f i ⁻¹' sets i) →
    (κ a) (⋂ i ∈ S, g i ⁻¹' sets i) = ∏ i ∈ S, (κ a) (g i ⁻¹' sets i)
Module: Mathlib.Probability.Independence.Kernel.Indep

Goal state before:
pp: α : Type u_1
Ω : Type u_2
ι : Type u_3
_mα : MeasurableSpace α
s : ι → Set Ω
_mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
h : ∀ (S : Finset ι), ∀ᵐ (a : α) ∂μ, (κ a) (⋂ i ∈ S, s i) = ∏ i ∈ S, (κ a) (s i)
S : Finset ι
f : ι → Set Ω
hf : ∀ i ∈ S, f i ∈ (fun i ↦ {s i}) i
a : α
⊢ (κ a) (⋂ i ∈ S, s i) = ∏ i ∈ S, (κ a) (s i) → (κ a) (⋂ i ∈ S, f i) = ∏ i ∈ S, (κ a) (f i)

Tactic:
ha

Goal state after:
α : Type u_1
Ω : Type u_2
ι : Type u_3
_mα : MeasurableSpace α
s : ι → Set Ω
_mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
h : ∀ (S : Finset ι), ∀ᵐ (a : α) ∂μ, (κ a) (⋂ i ∈ S, s i) = ∏ i ∈ S, (κ a) (s i)
S : Finset ι
f : ι → Set Ω
hf : ∀ i ∈ S, f i ∈ (fun i ↦ {s i}) i
a : α
ha : (κ a) (⋂ i ∈ S, s i) = ∏ i ∈ S, (κ a) (s i)
⊢ (κ a) (⋂ i ∈ S, f i) = ∏ i ∈ S, (κ a) (f i)
Module: Mathlib.Probability.Independence.Kernel.Indep

Goal state before:
pp: case inr.basic
α : Type u_1
Ω : Type u_2
_mα : MeasurableSpace α
m₂ m : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
inst✝ : IsZeroOrMarkovKernel κ
p1 p2 : Set (Set Ω)
h2 : m₂ ≤ m
hp2 : IsPiSystem p2
hpm2 : m₂ = generateFrom p2
hyp : IndepSets p1 p2 κ μ
t1 t2 : Set Ω
ht1 : t1 ∈ p1
ht1m : MeasurableSet t1
h : IsMarkovKernel κ
u : Set Ω
hu : u ∈ p2
⊢ ∀ᵐ (a : α) ∂μ, (κ a) (t1 ∩ u) = (κ a) t1 * (κ a) u

Tactic:
| basic u hu =>

Goal state after:
Module: Mathlib.Probability.Independence.Kernel.Indep

Goal state before:
pp: α : Type u_1
Ω : Type u_2
_mα : MeasurableSpace α
m₂ m : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
inst✝ : IsZeroOrMarkovKernel κ
p1 p2 : Set (Set Ω)
h2 : m₂ ≤ m
hp2 : IsPiSystem p2
hpm2 : m₂ = generateFrom p2
hyp : IndepSets p1 p2 κ μ
t1 t2 : Set Ω
ht1 : t1 ∈ p1
ht1m : MeasurableSet t1
h : IsMarkovKernel κ
u : Set Ω
hu : MeasurableSet u
ihu : ∀ᵐ (a : α) ∂μ, (κ a) (t1 ∩ u) = (κ a) t1 * (κ a) u
a : α
⊢ (κ a) (t1 ∩ u) = (κ a) t1 * (κ a) u → (κ a) (t1 ∩ uᶜ) = (κ a) t1 * (κ a) uᶜ

Tactic:
ha

Goal state after:
α : Type u_1
Ω : Type u_2
_mα : MeasurableSpace α
m₂ m : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
inst✝ : IsZeroOrMarkovKernel κ
p1 p2 : Set (Set Ω)
h2 : m₂ ≤ m
hp2 : IsPiSystem p2
hpm2 : m₂ = generateFrom p2
hyp : IndepSets p1 p2 κ μ
t1 t2 : Set Ω
ht1 : t1 ∈ p1
ht1m : MeasurableSet t1
h : IsMarkovKernel κ
u : Set Ω
hu : MeasurableSet u
ihu : ∀ᵐ (a : α) ∂μ, (κ a) (t1 ∩ u) = (κ a) t1 * (κ a) u
a : α
ha : (κ a) (t1 ∩ u) = (κ a) t1 * (κ a) u
⊢ (κ a) (t1 ∩ uᶜ) = (κ a) t1 * (κ a) uᶜ
Module: Mathlib.Probability.Independence.Kernel.IndepFun

Goal state before:
pp: α : Type u_1
Ω : Type u_2
ι : Type u_3
mα : MeasurableSpace α
mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
β : ι → Type u_8
mβ : (i : ι) → MeasurableSpace (β i)
f g : (i : ι) → Ω → β i
h : ∀ (i : ι), ∀ᵐ (a : α) ∂μ, f i =ᵐ[κ a] g i
h' : iIndepFun g κ μ
i : ι
a : α
⊢ f i =ᵐ[κ a] g i → g i =ᵐ[κ a] f i

Tactic:
ha

Goal state after:
α : Type u_1
Ω : Type u_2
ι : Type u_3
mα : MeasurableSpace α
mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
β : ι → Type u_8
mβ : (i : ι) → MeasurableSpace (β i)
f g : (i : ι) → Ω → β i
h : ∀ (i : ι), ∀ᵐ (a : α) ∂μ, f i =ᵐ[κ a] g i
h' : iIndepFun g κ μ
i : ι
a : α
ha : f i =ᵐ[κ a] g i
⊢ g i =ᵐ[κ a] f i
Module: Mathlib.Probability.Independence.Kernel.IndepFun

Goal state before:
pp: α : Type u_1
Ω : Type u_2
ι : Type u_3
mα : MeasurableSpace α
mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
β : ι → Type u_8
γ : ι → Type u_9
mβ : (i : ι) → MeasurableSpace (β i)
mγ : (i : ι) → MeasurableSpace (γ i)
f : (i : ι) → Ω → β i
h :
  ∀ (S : Finset ι) {sets : (i : ι) → Set (β i)},
    (∀ i ∈ S, MeasurableSet (sets i)) → ∀ᵐ (a : α) ∂μ, (κ a) (⋂ i ∈ S, f i ⁻¹' sets i) = ∏ i ∈ S, (κ a) (f i ⁻¹' sets i)
g : (i : ι) → β i → γ i
hg : ∀ (i : ι), Measurable (g i)
t : Finset ι
s : (i : ι) → Set (γ i)
hs : ∀ i ∈ t, MeasurableSet (s i)
this : ∀ᵐ (a : α) ∂μ, (κ a) (⋂ i ∈ t, f i ⁻¹' g i ⁻¹' s i) = ∏ i ∈ t, (κ a) (f i ⁻¹' g i ⁻¹' s i)
a : α
⊢ (κ a) (⋂ i ∈ t, f i ⁻¹' g i ⁻¹' s i) = ∏ i ∈ t, (κ a) (f i ⁻¹' g i ⁻¹' s i) →
    (κ a) (⋂ i ∈ t, g i ∘ f i ⁻¹' s i) = ∏ i ∈ t, (κ a) (g i ∘ f i ⁻¹' s i)

Tactic:
ha

Goal state after:
α : Type u_1
Ω : Type u_2
ι : Type u_3
mα : MeasurableSpace α
mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
β : ι → Type u_8
γ : ι → Type u_9
mβ : (i : ι) → MeasurableSpace (β i)
mγ : (i : ι) → MeasurableSpace (γ i)
f : (i : ι) → Ω → β i
h :
  ∀ (S : Finset ι) {sets : (i : ι) → Set (β i)},
    (∀ i ∈ S, MeasurableSet (sets i)) → ∀ᵐ (a : α) ∂μ, (κ a) (⋂ i ∈ S, f i ⁻¹' sets i) = ∏ i ∈ S, (κ a) (f i ⁻¹' sets i)
g : (i : ι) → β i → γ i
hg : ∀ (i : ι), Measurable (g i)
t : Finset ι
s : (i : ι) → Set (γ i)
hs : ∀ i ∈ t, MeasurableSet (s i)
this : ∀ᵐ (a : α) ∂μ, (κ a) (⋂ i ∈ t, f i ⁻¹' g i ⁻¹' s i) = ∏ i ∈ t, (κ a) (f i ⁻¹' g i ⁻¹' s i)
a : α
ha : (κ a) (⋂ i ∈ t, f i ⁻¹' g i ⁻¹' s i) = ∏ i ∈ t, (κ a) (f i ⁻¹' g i ⁻¹' s i)
⊢ (κ a) (⋂ i ∈ t, g i ∘ f i ⁻¹' s i) = ∏ i ∈ t, (κ a) (g i ∘ f i ⁻¹' s i)
Module: Mathlib.Probability.Independence.Kernel.Indep

Goal state before:
pp: α : Type u_1
Ω : Type u_2
_mα : MeasurableSpace α
m₂ m : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
inst✝ : IsZeroOrMarkovKernel κ
p1 p2 : Set (Set Ω)
h2 : m₂ ≤ m
hp2 : IsPiSystem p2
hpm2 : m₂ = generateFrom p2
hyp : IndepSets p1 p2 κ μ
t1 t2 : Set Ω
ht1 : t1 ∈ p1
ht1m : MeasurableSet t1
h : IsMarkovKernel κ
f : ℕ → Set Ω
hfd : Pairwise (Function.onFun Disjoint f)
hfm : ∀ (i : ℕ), MeasurableSet (f i)
ihf : ∀ᵐ (a : α) ∂μ, ∀ (i : ℕ), (κ a) (t1 ∩ f i) = (κ a) t1 * (κ a) (f i)
a : α
⊢ (∀ (i : ℕ), (κ a) (t1 ∩ f i) = (κ a) t1 * (κ a) (f i)) → (κ a) (t1 ∩ ⋃ i, f i) = (κ a) t1 * (κ a) (⋃ i, f i)

Tactic:
ha

Goal state after:
α : Type u_1
Ω : Type u_2
_mα : MeasurableSpace α
m₂ m : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
inst✝ : IsZeroOrMarkovKernel κ
p1 p2 : Set (Set Ω)
h2 : m₂ ≤ m
hp2 : IsPiSystem p2
hpm2 : m₂ = generateFrom p2
hyp : IndepSets p1 p2 κ μ
t1 t2 : Set Ω
ht1 : t1 ∈ p1
ht1m : MeasurableSet t1
h : IsMarkovKernel κ
f : ℕ → Set Ω
hfd : Pairwise (Function.onFun Disjoint f)
hfm : ∀ (i : ℕ), MeasurableSet (f i)
ihf : ∀ᵐ (a : α) ∂μ, ∀ (i : ℕ), (κ a) (t1 ∩ f i) = (κ a) t1 * (κ a) (f i)
a : α
ha : ∀ (i : ℕ), (κ a) (t1 ∩ f i) = (κ a) t1 * (κ a) (f i)
⊢ (κ a) (t1 ∩ ⋃ i, f i) = (κ a) t1 * (κ a) (⋃ i, f i)
Module: Mathlib.Probability.Independence.Kernel.Indep

Goal state before:
pp: α : Type u_1
Ω : Type u_2
_mα : MeasurableSpace α
m1 m2 m : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
inst✝ : IsZeroOrMarkovKernel κ
p1 p2 : Set (Set Ω)
h1 : m1 ≤ m
h2 : m2 ≤ m
hp1 : IsPiSystem p1
hp2 : IsPiSystem p2
hpm1 : m1 = generateFrom p1
hpm2 : m2 = generateFrom p2
hyp : IndepSets p1 p2 κ μ
h : IsMarkovKernel κ
t1 t2 : Set Ω
ht2 : t2 ∈ {s | MeasurableSet s}
t : Set Ω
ht : MeasurableSet t
iht : ∀ᵐ (a : α) ∂μ, (κ a) (t ∩ t2) = (κ a) t * (κ a) t2
a : α
⊢ (κ a) (t ∩ t2) = (κ a) t * (κ a) t2 → (κ a) (tᶜ ∩ t2) = (κ a) tᶜ * (κ a) t2

Tactic:
ha

Goal state after:
α : Type u_1
Ω : Type u_2
_mα : MeasurableSpace α
m1 m2 m : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
inst✝ : IsZeroOrMarkovKernel κ
p1 p2 : Set (Set Ω)
h1 : m1 ≤ m
h2 : m2 ≤ m
hp1 : IsPiSystem p1
hp2 : IsPiSystem p2
hpm1 : m1 = generateFrom p1
hpm2 : m2 = generateFrom p2
hyp : IndepSets p1 p2 κ μ
h : IsMarkovKernel κ
t1 t2 : Set Ω
ht2 : t2 ∈ {s | MeasurableSet s}
t : Set Ω
ht : MeasurableSet t
iht : ∀ᵐ (a : α) ∂μ, (κ a) (t ∩ t2) = (κ a) t * (κ a) t2
a : α
ha : (κ a) (t ∩ t2) = (κ a) t * (κ a) t2
⊢ (κ a) (tᶜ ∩ t2) = (κ a) tᶜ * (κ a) t2
Module: Mathlib.Probability.Independence.Kernel.Indep

Goal state before:
pp: α : Type u_1
Ω : Type u_2
_mα : MeasurableSpace α
m1 m2 m : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
inst✝ : IsZeroOrMarkovKernel κ
p1 p2 : Set (Set Ω)
h1 : m1 ≤ m
h2 : m2 ≤ m
hp1 : IsPiSystem p1
hp2 : IsPiSystem p2
hpm1 : m1 = generateFrom p1
hpm2 : m2 = generateFrom p2
hyp : IndepSets p1 p2 κ μ
h✝ : IsMarkovKernel κ
t1 t2 : Set Ω
ht2 : t2 ∈ {s | MeasurableSet s}
f : ℕ → Set Ω
hf_disj : Pairwise (Function.onFun Disjoint f)
hf_meas : ∀ (i : ℕ), MeasurableSet (f i)
h : ∀ᵐ (a : α) ∂μ, ∀ (i : ℕ), (κ a) (f i ∩ t2) = (κ a) (f i) * (κ a) t2
a : α
⊢ (∀ (i : ℕ), (κ a) (f i ∩ t2) = (κ a) (f i) * (κ a) t2) → (κ a) ((⋃ i, f i) ∩ t2) = (κ a) (⋃ i, f i) * (κ a) t2

Tactic:
ha

Goal state after:
α : Type u_1
Ω : Type u_2
_mα : MeasurableSpace α
m1 m2 m : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
inst✝ : IsZeroOrMarkovKernel κ
p1 p2 : Set (Set Ω)
h1 : m1 ≤ m
h2 : m2 ≤ m
hp1 : IsPiSystem p1
hp2 : IsPiSystem p2
hpm1 : m1 = generateFrom p1
hpm2 : m2 = generateFrom p2
hyp : IndepSets p1 p2 κ μ
h✝ : IsMarkovKernel κ
t1 t2 : Set Ω
ht2 : t2 ∈ {s | MeasurableSet s}
f : ℕ → Set Ω
hf_disj : Pairwise (Function.onFun Disjoint f)
hf_meas : ∀ (i : ℕ), MeasurableSet (f i)
h : ∀ᵐ (a : α) ∂μ, ∀ (i : ℕ), (κ a) (f i ∩ t2) = (κ a) (f i) * (κ a) t2
a : α
ha : ∀ (i : ℕ), (κ a) (f i ∩ t2) = (κ a) (f i) * (κ a) t2
⊢ (κ a) ((⋃ i, f i) ∩ t2) = (κ a) (⋃ i, f i) * (κ a) t2
Module: Mathlib.Probability.Independence.Kernel.Indep

Goal state before:
pp: α : Type u_1
Ω : Type u_2
ι : Type u_3
_mα : MeasurableSpace α
_mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
s : ι → Set (Set Ω)
S T : Set ι
h_indep : iIndepSets s κ μ
hST : Disjoint S T
t1 t2 : Set Ω
p1 : Finset ι
hp1 : ↑p1 ⊆ S
f1 : ι → Set Ω
ht1_m : ∀ x ∈ p1, f1 x ∈ s x
ht1_eq : t1 = ⋂ x ∈ p1, f1 x
p2 : Finset ι
hp2 : ↑p2 ⊆ T
f2 : ι → Set Ω
ht2_m : ∀ x ∈ p2, f2 x ∈ s x
ht2_eq : t2 = ⋂ x ∈ p2, f2 x
g : ι → Set Ω := fun i ↦ (if i ∈ p1 then f1 i else univ) ∩ if i ∈ p2 then f2 i else univ
hgm : ∀ i ∈ p1 ∪ p2, g i ∈ s i
h_p1_inter_p2 :
  (⋂ x ∈ p1, f1 x) ∩ ⋂ x ∈ p2, f2 x = ⋂ i ∈ p1 ∪ p2, (if i ∈ p1 then f1 i else univ) ∩ if i ∈ p2 then f2 i else univ
a : α
⊢ (κ a) (⋂ i ∈ p1 ∪ p2, g i) = ∏ i ∈ p1 ∪ p2, (κ a) (g i) → (κ a) (t1 ∩ t2) = ∏ n ∈ p1 ∪ p2, (κ a) (g n)

Tactic:
ha

Goal state after:
α : Type u_1
Ω : Type u_2
ι : Type u_3
_mα : MeasurableSpace α
_mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
s : ι → Set (Set Ω)
S T : Set ι
h_indep : iIndepSets s κ μ
hST : Disjoint S T
t1 t2 : Set Ω
p1 : Finset ι
hp1 : ↑p1 ⊆ S
f1 : ι → Set Ω
ht1_m : ∀ x ∈ p1, f1 x ∈ s x
ht1_eq : t1 = ⋂ x ∈ p1, f1 x
p2 : Finset ι
hp2 : ↑p2 ⊆ T
f2 : ι → Set Ω
ht2_m : ∀ x ∈ p2, f2 x ∈ s x
ht2_eq : t2 = ⋂ x ∈ p2, f2 x
g : ι → Set Ω := fun i ↦ (if i ∈ p1 then f1 i else univ) ∩ if i ∈ p2 then f2 i else univ
hgm : ∀ i ∈ p1 ∪ p2, g i ∈ s i
h_p1_inter_p2 :
  (⋂ x ∈ p1, f1 x) ∩ ⋂ x ∈ p2, f2 x = ⋂ i ∈ p1 ∪ p2, (if i ∈ p1 then f1 i else univ) ∩ if i ∈ p2 then f2 i else univ
a : α
ha : (κ a) (⋂ i ∈ p1 ∪ p2, g i) = ∏ i ∈ p1 ∪ p2, (κ a) (g i)
⊢ (κ a) (t1 ∩ t2) = ∏ n ∈ p1 ∪ p2, (κ a) (g n)
Module: Mathlib.Probability.Independence.Basic

Goal state before:
pp: ι : Type u_6
Ω : Type u_7
α : Type u_8
β : Type u_9
mΩ : MeasurableSpace Ω
mα : MeasurableSpace α
mβ : MeasurableSpace β
μ : Measure Ω
X : ι → Ω → α
Y : ι → Ω → β
f : ι → Set Ω
t : ι → Set β
s : Finset ι
inst✝ : Finite ι
hY : ∀ (i : ι), Measurable (Y i)
hindep : iIndepFun (fun i ω ↦ (X i ω, Y i ω)) μ
hf : ∀ i ∈ s, MeasurableSet (f i)
hy : ∀ i ∉ s, μ (Y i ⁻¹' t i) ≠ 0
ht : ∀ (i : ι), MeasurableSet (t i)
this : IsProbabilityMeasure μ
val✝ : Fintype ι
g : ι → Set Ω := fun i' ↦ if i' ∈ s then Y i' ⁻¹' t i' ∩ f i' else Y i' ⁻¹' t i'
⊢ (↑Finset.univ).Pairwise fun i j ↦ μ (Y i ⁻¹' t i) ≠ 0 ∨ μ (Y j ⁻¹' t j) ≠ ∞

Tactic:
exact fun _ _ i _ _ ↦ .inr <| measure_ne_top _ _

Goal state after:
Module: Mathlib.Probability.Independence.Kernel.Indep

Goal state before:
pp: α : Type u_1
Ω : Type u_2
ι : Type u_3
_mα : MeasurableSpace α
_mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
π : ι → Set (Set Ω)
a : ι
S : Finset ι
hp_ind : iIndepSets π κ μ
haS : a ∉ S
t1 t2 : Set Ω
s : Finset ι
hs_mem : s ⊆ S
ft1 : ι → Set Ω
hft1_mem : ∀ x ∈ s, ft1 x ∈ π x
ht1_eq : t1 = ⋂ x ∈ s, ft1 x
ht2_mem_pia : t2 ∈ π a
f : ι → Set Ω := fun n ↦ if n = a then t2 else if n ∈ s then ft1 n else univ
h_f_mem : ∀ n ∈ insert a s, f n ∈ π n
h_f_mem_pi : ∀ n ∈ s, f n ∈ π n
h_t1 : t1 = ⋂ n ∈ s, f n
h_μ_t1 : ∀ᵐ (a' : α) ∂μ, (κ a') t1 = ∏ n ∈ s, (κ a') (f n)
h_t2 : t2 = f a
h_t1_inter_t2 : t1 ∩ t2 = ⋂ n ∈ insert a s, f n
a' : α
ha' : (κ a') (⋂ i ∈ insert a s, f i) = ∏ i ∈ insert a s, (κ a') (f i)
⊢ (κ a') (t1 ∩ t2) = ∏ n ∈ insert a s, (κ a') (f n)

Tactic:
h_t1_inter_t2,

Goal state after:
α : Type u_1
Ω : Type u_2
ι : Type u_3
_mα : MeasurableSpace α
_mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
π : ι → Set (Set Ω)
a : ι
S : Finset ι
hp_ind : iIndepSets π κ μ
haS : a ∉ S
t1 t2 : Set Ω
s : Finset ι
hs_mem : s ⊆ S
ft1 : ι → Set Ω
hft1_mem : ∀ x ∈ s, ft1 x ∈ π x
ht1_eq : t1 = ⋂ x ∈ s, ft1 x
ht2_mem_pia : t2 ∈ π a
f : ι → Set Ω := fun n ↦ if n = a then t2 else if n ∈ s then ft1 n else univ
h_f_mem : ∀ n ∈ insert a s, f n ∈ π n
h_f_mem_pi : ∀ n ∈ s, f n ∈ π n
h_t1 : t1 = ⋂ n ∈ s, f n
h_μ_t1 : ∀ᵐ (a' : α) ∂μ, (κ a') t1 = ∏ n ∈ s, (κ a') (f n)
h_t2 : t2 = f a
h_t1_inter_t2 : t1 ∩ t2 = ⋂ n ∈ insert a s, f n
a' : α
ha' : (κ a') (⋂ i ∈ insert a s, f i) = ∏ i ∈ insert a s, (κ a') (f i)
⊢ (κ a') (⋂ n ∈ insert a s, f n) = ∏ n ∈ insert a s, (κ a') (f n)
Module: Mathlib.Probability.Independence.Integration

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
E : Type u_5
F : Type u_6
G : Type u_7
inst✝⁹ : TopologicalSpace E
inst✝⁸ : ContinuousENorm E
inst✝⁷ : MeasurableSpace E
inst✝⁶ : OpensMeasurableSpace E
inst✝⁵ : TopologicalSpace F
inst✝⁴ : ContinuousENorm F
inst✝³ : MeasurableSpace F
inst✝² : OpensMeasurableSpace F
inst✝¹ : TopologicalSpace G
inst✝ : ContinuousENorm G
X : Ω → E
Y : Ω → F
hXY : X ⟂ᵢ[μ] Y
hX : Integrable X μ
hY : Integrable Y μ
B : E → F → G
cB : Continuous (Function.uncurry B)
C : ℝ≥0
hB : ∀ (x : E) (y : F), ‖B x y‖ₑ ≤ ↑C * ‖x‖ₑ * ‖y‖ₑ
⊢ ↑C * ∫⁻ (ω : Ω), ‖X ω‖ₑ * ‖Y ω‖ₑ ∂μ = ↑C * ((∫⁻ (ω : Ω), ‖X ω‖ₑ ∂μ) * ∫⁻ (ω : Ω), ‖Y ω‖ₑ ∂μ)

Tactic:
by
    rw [lintegral_mul_eq_lintegral_mul_lintegral_of_indepFun'' hX.1.enorm hY.1.enorm
        (hXY.comp measurable_enorm measurable_enorm)]

Goal state after:
Module: Mathlib.Probability.Moments.Covariance

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
X Y : Ω → ℝ
μ : Measure Ω
c : ℝ
⊢ cov[X, fun ω ↦ Y ω / c; μ] = cov[X, Y; μ] / c

Tactic:
by
  simp_rw [← inv_mul_eq_div, covariance_const_mul_right]

Goal state after:
Module: Mathlib.Probability.Moments.Covariance

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
X Y : Ω → ℝ
μ : Measure Ω
⊢ cov[-1 • X, Y; μ] = -cov[X, Y; μ]

Tactic:
covariance_smul_left

Goal state after:
Ω : Type u_1
mΩ : MeasurableSpace Ω
X Y : Ω → ℝ
μ : Measure Ω
⊢ -1 * cov[X, Y; μ] = -cov[X, Y; μ]
Module: Mathlib.Probability.Moments.Variance

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
X : Ω → ℝ
Ω' : Type u_3
mΩ' : MeasurableSpace Ω'
μ : Measure Ω'
Y : Ω' → Ω
hX : AEMeasurable X (Measure.map Y μ)
hY : AEMeasurable Y μ
⊢ Var[X; Measure.map Y μ] = Var[X ∘ Y; μ]

Tactic:
rw [variance_eq_integral hX, integral_map hY, variance_eq_integral (hX.comp_aemeasurable hY),
    integral_map hY]
  · congr
  · exact hX.aestronglyMeasurable
  · refine AEStronglyMeasurable.pow ?_ _
    exact AEMeasurable.aestronglyMeasurable (by fun_prop)

Goal state after:
Module: Mathlib.Probability.Moments.Covariance

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
ι : Type u_2
X : ι → Ω → ℝ
s : Finset ι
inst✝ : IsFiniteMeasure μ
ι' : Type u_3
Y : ι' → Ω → ℝ
t : Finset ι'
hX : ∀ i ∈ s, MemLp (X i) 2 μ
hY : ∀ i ∈ t, MemLp (Y i) 2 μ
⊢ cov[fun ω ↦ ∑ i ∈ s, X i ω, fun ω ↦ ∑ j ∈ t, Y j ω; μ] = ∑ i ∈ s, ∑ j ∈ t, cov[X i, Y j; μ]

Tactic:
convert! covariance_sum_sum' hX hY
  all_goals simp

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

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
E : Type u_5
F : Type u_6
inst✝¹⁰ : TopologicalSpace E
inst✝⁹ : ContinuousENorm E
inst✝⁸ : MeasurableSpace E
inst✝⁷ : OpensMeasurableSpace E
inst✝⁶ : TopologicalSpace F
inst✝⁵ : ContinuousENorm F
inst✝⁴ : MeasurableSpace F
inst✝³ : OpensMeasurableSpace F
inst✝² : SMul E F
inst✝¹ : ContinuousSMul E F
inst✝ : ENormSMulClass E F
X : Ω → E
Y : Ω → F
hXY : X ⟂ᵢ[μ] Y
hX : Integrable X μ
hY : Integrable Y μ
⊢ ∀ (x : E) (y : F), ‖x • y‖ₑ ≤ ↑1 * ‖x‖ₑ * ‖y‖ₑ

Tactic:
by simp [enorm_smul]

Goal state after:
Module: Mathlib.Probability.IdentDistrib

Goal state before:
pp: α : Type u_1
β : Type u_2
γ : Type u_3
inst✝⁴ : MeasurableSpace α
inst✝³ : MeasurableSpace β
inst✝² : MeasurableSpace γ
μ : Measure α
ν : Measure β
f : α → γ
g : β → γ
inst✝¹ : NormedAddCommGroup γ
inst✝ : BorelSpace γ
h : IdentDistrib f g μ ν
hf : MemLp f 1 μ
⊢ MemLp g 1 ν

Tactic:
exact h.memLp_snd hf

Goal state after:
Module: Mathlib.Probability.Independence.Kernel.IndepFun

Goal state before:
pp: α : Type u_1
Ω : Type u_2
ι : Type u_3
mα : MeasurableSpace α
mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
β : ι → Type u_8
m : (i : ι) → MeasurableSpace (β i)
f : (i : ι) → Ω → β i
S T : Finset ι
hST : Disjoint S T
hf_Indep : iIndepFun f κ μ
hf_meas : ∀ (i : ι), AEMeasurable (f i) (⇑κ ∘ₘ μ)
h : IndepFun (fun a i ↦ AEMeasurable.mk (f ↑i) ⋯ a) (fun a i ↦ AEMeasurable.mk (f ↑i) ⋯ a) κ μ
this : ∀ᵐ (a : α) ∂μ, ∀ (i : ↥S), f ↑i =ᵐ[κ a] AEMeasurable.mk (f ↑i) ⋯
a : α
⊢ (∀ (i : ↥S), f ↑i =ᵐ[κ a] AEMeasurable.mk (f ↑i) ⋯) →
    (fun a i ↦ AEMeasurable.mk (f ↑i) ⋯ a) =ᵐ[κ a] fun a i ↦ f (↑i) a

Tactic:
ha

Goal state after:
α : Type u_1
Ω : Type u_2
ι : Type u_3
mα : MeasurableSpace α
mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
β : ι → Type u_8
m : (i : ι) → MeasurableSpace (β i)
f : (i : ι) → Ω → β i
S T : Finset ι
hST : Disjoint S T
hf_Indep : iIndepFun f κ μ
hf_meas : ∀ (i : ι), AEMeasurable (f i) (⇑κ ∘ₘ μ)
h : IndepFun (fun a i ↦ AEMeasurable.mk (f ↑i) ⋯ a) (fun a i ↦ AEMeasurable.mk (f ↑i) ⋯ a) κ μ
this : ∀ᵐ (a : α) ∂μ, ∀ (i : ↥S), f ↑i =ᵐ[κ a] AEMeasurable.mk (f ↑i) ⋯
a : α
ha : ∀ (i : ↥S), f ↑i =ᵐ[κ a] AEMeasurable.mk (f ↑i) ⋯
⊢ (fun a i ↦ AEMeasurable.mk (f ↑i) ⋯ a) =ᵐ[κ a] fun a i ↦ f (↑i) a
Module: Mathlib.Probability.Independence.Kernel.IndepFun

Goal state before:
pp: α : Type u_1
Ω : Type u_2
ι : Type u_3
mα : MeasurableSpace α
mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
β : ι → Type u_8
m : (i : ι) → MeasurableSpace (β i)
f : (i : ι) → Ω → β i
S T : Finset ι
hST : Disjoint S T
hf_Indep : iIndepFun f κ μ
hf_meas : ∀ (i : ι), AEMeasurable (f i) (⇑κ ∘ₘ μ)
h : IndepFun (fun a i ↦ AEMeasurable.mk (f ↑i) ⋯ a) (fun a i ↦ AEMeasurable.mk (f ↑i) ⋯ a) κ μ
this : ∀ᵐ (a : α) ∂μ, ∀ (i : ↥T), f ↑i =ᵐ[κ a] AEMeasurable.mk (f ↑i) ⋯
a : α
⊢ (∀ (i : ↥T), f ↑i =ᵐ[κ a] AEMeasurable.mk (f ↑i) ⋯) →
    (fun a i ↦ AEMeasurable.mk (f ↑i) ⋯ a) =ᵐ[κ a] fun a i ↦ f (↑i) a

Tactic:
ha

Goal state after:
α : Type u_1
Ω : Type u_2
ι : Type u_3
mα : MeasurableSpace α
mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
β : ι → Type u_8
m : (i : ι) → MeasurableSpace (β i)
f : (i : ι) → Ω → β i
S T : Finset ι
hST : Disjoint S T
hf_Indep : iIndepFun f κ μ
hf_meas : ∀ (i : ι), AEMeasurable (f i) (⇑κ ∘ₘ μ)
h : IndepFun (fun a i ↦ AEMeasurable.mk (f ↑i) ⋯ a) (fun a i ↦ AEMeasurable.mk (f ↑i) ⋯ a) κ μ
this : ∀ᵐ (a : α) ∂μ, ∀ (i : ↥T), f ↑i =ᵐ[κ a] AEMeasurable.mk (f ↑i) ⋯
a : α
ha : ∀ (i : ↥T), f ↑i =ᵐ[κ a] AEMeasurable.mk (f ↑i) ⋯
⊢ (fun a i ↦ AEMeasurable.mk (f ↑i) ⋯ a) =ᵐ[κ a] fun a i ↦ f (↑i) a
Module: Mathlib.Probability.Independence.Kernel.IndepFun

Goal state before:
pp: case refine_1
α : Type u_1
Ω : Type u_2
ι : Type u_3
mα : MeasurableSpace α
mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
β : ι → Type u_8
m : (i : ι) → MeasurableSpace (β i)
f : (i : ι) → Ω → β i
hf_Indep : iIndepFun f κ μ
hf_meas : ∀ (i : ι), AEMeasurable (f i) (⇑κ ∘ₘ μ)
i j k : ι
hik : i ≠ k
hjk : j ≠ k
h : IndepFun (fun a ↦ (AEMeasurable.mk (f i) ⋯ a, AEMeasurable.mk (f j) ⋯ a)) (AEMeasurable.mk (f k) ⋯) κ μ
⊢ ∀ᵐ (a : α) ∂μ, (fun a ↦ (AEMeasurable.mk (f i) ⋯ a, AEMeasurable.mk (f j) ⋯ a)) =ᵐ[κ a] fun a ↦ (f i a, f j a)

Tactic:
filter_upwards [Measure.ae_ae_of_ae_comp (hf_meas i).ae_eq_mk,
      Measure.ae_ae_of_ae_comp (hf_meas j).ae_eq_mk] with a hi hj
    filter_upwards [hi, hj] with ω hωi hωj
    rw [← hωi, ← hωj]

Goal state after:
Module: Mathlib.Probability.Independence.Kernel.IndepFun

Goal state before:
pp: case refine_1
α : Type u_1
Ω : Type u_2
ι : Type u_3
mα : MeasurableSpace α
mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
β : ι → Type u_8
m : (i : ι) → MeasurableSpace (β i)
f : (i : ι) → Ω → β i
hf_indep : iIndepFun f κ μ
hf_meas : ∀ (i : ι), AEMeasurable (f i) (⇑κ ∘ₘ μ)
i j k l : ι
hik : i ≠ k
hil : i ≠ l
hjk : j ≠ k
hjl : j ≠ l
h :
  IndepFun (fun a ↦ (AEMeasurable.mk (f i) ⋯ a, AEMeasurable.mk (f j) ⋯ a))
    (fun a ↦ (AEMeasurable.mk (f k) ⋯ a, AEMeasurable.mk (f l) ⋯ a)) κ μ
⊢ ∀ᵐ (a : α) ∂μ, (fun a ↦ (AEMeasurable.mk (f i) ⋯ a, AEMeasurable.mk (f j) ⋯ a)) =ᵐ[κ a] fun a ↦ (f i a, f j a)

Tactic:
filter_upwards [Measure.ae_ae_of_ae_comp (hf_meas i).ae_eq_mk,
      Measure.ae_ae_of_ae_comp (hf_meas j).ae_eq_mk] with a hi hj
    filter_upwards [hi, hj] with ω hωi hωj
    rw [← hωi, ← hωj]

Goal state after: