mathlib-initiative/mathlib-tactics huggingface dataset:
Module: Mathlib.MeasureTheory.Function.ConditionalExpectation.Real

Goal state before:
pp: α : Type u_1
m m0 : MeasurableSpace α
μ : Measure α
E : Type u_2
inst✝⁶ : NormedAddCommGroup E
inst✝⁵ : NormedSpace ℝ E
inst✝⁴ : CompleteSpace E
inst✝³ : PartialOrder E
inst✝² : ClosedIciTopology E
inst✝¹ : IsOrderedAddMonoid E
inst✝ : IsOrderedModule ℝ E
f : α → E
c : E
hc : 0 ≤ c
hfc : ∀ᵐ (x : α) ∂μ, f x ≤ c
⊢ ∀ᵐ (x : α) ∂μ, μ[f | m] x ≤ c

Tactic:
by_cases! hm : ¬ m ≤ m0
  · filter_upwards with a using by simpa [condExp_of_not_le hm]
  by_cases! hfint : ¬ Integrable f μ
  · filter_upwards with a using by simpa [condExp_of_not_integrable hfint]
  by_cases! hsig : ¬ SigmaFinite (μ.trim hm)
  · filter_upwards with a using by simpa [condExp_of_not_sigmaFinite hm hsig]
  refine (isCountablySpanning_spanningSets (μ.trim hm)).null_of_forall_restrict_null ?_ ?_ <;>
    rintro - ⟨n, rfl⟩
  · exact hm _ (measurableSet_spanningSets (μ.trim hm) n)
  · have h1 := condExp_restrict_ae_eq_restrict hm (measurableSet_spanningSets (μ.trim hm) n) hfint
    have h2 := condExp_mono (μ := μ.restrict (spanningSets (μ.trim hm) n)) (m := m)
      hfint.restrict (integrable_const c) (ae_restrict_of_ae hfc)
    filter_upwards [h1, h2] with a ha hb
    grw [← ha, hb, condExp_const hm]

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

Goal state before:
pp: Ω : Type u_1
inst✝¹ : MeasurableSpace Ω
inst✝ : TopologicalSpace Ω
μ : FiniteMeasure Ω
⊢ (↑μ univ).toNNReal = μ.mass

Tactic:
rfl

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

Goal state before:
pp: Ω : Type u_1
inst✝² : MeasurableSpace Ω
inst✝¹ : TopologicalSpace Ω
inst✝ : OpensMeasurableSpace Ω
γ : Type u_3
F : Filter γ
μs : γ → FiniteMeasure Ω
μ : FiniteMeasure Ω
⊢ (∀ (y : Ω →ᵇ ℝ≥0),
      Tendsto (fun i ↦ ((topDualPairing ℝ≥0 (Ω →ᵇ ℝ≥0)) (μs i).toWeakDualBCNN) y) F
        (𝓝 (((topDualPairing ℝ≥0 (Ω →ᵇ ℝ≥0)) μ.toWeakDualBCNN) y))) ↔
    ∀ (f : Ω →ᵇ ℝ≥0), Tendsto (fun i ↦ (μs i).toWeakDualBCNN f) F (𝓝 (μ.toWeakDualBCNN f))

Tactic:
rfl

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

Goal state before:
pp: Ω : Type u_1
inst✝² : MeasurableSpace Ω
inst✝¹ : TopologicalSpace Ω
inst✝ : OpensMeasurableSpace Ω
γ : Type u_3
F : Filter γ
μs : γ → FiniteMeasure Ω
μ : FiniteMeasure Ω
⊢ (∀ (f : Ω →ᵇ ℝ≥0), Tendsto (fun i ↦ (μs i).toWeakDualBCNN f) F (𝓝 (μ.toWeakDualBCNN f))) ↔
    ∀ (f : Ω →ᵇ ℝ≥0), Tendsto (fun i ↦ (μs i).testAgainstNN f) F (𝓝 (μ.testAgainstNN f))

Tactic:
rfl

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

Goal state before:
pp: case inr
Ω : Type u_1
ι : Type u_2
L : Filter ι
inst✝⁴ : MeasurableSpace Ω
inst✝³ : TopologicalSpace Ω
inst✝² : PseudoMetrizableSpace Ω
inst✝¹ : OpensMeasurableSpace Ω
μ : Measure Ω
inst✝ : IsFiniteMeasure μ
μs : ι → Measure Ω
h : ∀ {E : Set Ω}, MeasurableSet E → μ (frontier E) = 0 → Tendsto (fun i ↦ (μs i) E) L (𝓝 (μ E))
F : Set Ω
F_closed : IsClosed[inst✝³] F
this : PseudoMetricSpace Ω := pseudoMetrizableSpacePseudoMetric Ω
h✝ : L.NeBot
ex : ∃ rs, Tendsto rs atTop (𝓝 0) ∧ ∀ (n : ℕ), 0 < rs n ∧ μ (frontier (Metric.thickening (rs n) F)) = 0
rs : ℕ → ℝ := Classical.choose ex
⊢ limsup (fun i ↦ (μs i) F) L ≤ μ F

Tactic:
have rs_lim : Tendsto rs atTop (𝓝 0) := (Classical.choose_spec ex).1

Goal state after:
case inr
Ω : Type u_1
ι : Type u_2
L : Filter ι
inst✝⁴ : MeasurableSpace Ω
inst✝³ : TopologicalSpace Ω
inst✝² : PseudoMetrizableSpace Ω
inst✝¹ : OpensMeasurableSpace Ω
μ : Measure Ω
inst✝ : IsFiniteMeasure μ
μs : ι → Measure Ω
h : ∀ {E : Set Ω}, MeasurableSet E → μ (frontier E) = 0 → Tendsto (fun i ↦ (μs i) E) L (𝓝 (μ E))
F : Set Ω
F_closed : IsClosed[inst✝³] F
this : PseudoMetricSpace Ω := pseudoMetrizableSpacePseudoMetric Ω
h✝ : L.NeBot
ex : ∃ rs, Tendsto rs atTop (𝓝 0) ∧ ∀ (n : ℕ), 0 < rs n ∧ μ (frontier (Metric.thickening (rs n) F)) = 0
rs : ℕ → ℝ := Classical.choose ex
rs_lim : Tendsto rs atTop (𝓝 0)
⊢ limsup (fun i ↦ (μs i) F) L ≤ μ F
Module: Mathlib.Probability.Independence.Basic

Goal state before:
pp: Ω : Type u_1
ι : Type u_2
m : ι → MeasurableSpace Ω
_mΩ : MeasurableSpace Ω
μ : Measure Ω
⊢ (∀ (s : Finset ι) {f : ι → Set Ω}, (∀ i ∈ s, f i ∈ {s | MeasurableSet s}) → μ (⋂ i ∈ s, f i) = ∏ i ∈ s, μ (f i)) ↔
    ∀ (s : Finset ι) {f : ι → Set Ω}, (∀ i ∈ s, MeasurableSet (f i)) → μ (⋂ i ∈ s, f i) = ∏ i ∈ s, μ (f i)

Tactic:
rfl

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

Goal state before:
pp: Ω : Type u_1
m₁ m₂ _mΩ : MeasurableSpace Ω
μ : Measure Ω
⊢ (∀ (t1 t2 : Set Ω), t1 ∈ {s | MeasurableSet s} → t2 ∈ {s | MeasurableSet s} → μ (t1 ∩ t2) = μ t1 * μ t2) ↔
    ∀ (t1 t2 : Set Ω), MeasurableSet t1 → MeasurableSet t2 → μ (t1 ∩ t2) = μ t1 * μ t2

Tactic:
rfl

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
s : ι → Set (Set Ω)
_mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
h_indep : iIndepSets s κ μ
i j : ι
hij : i ≠ j
t₁ t₂ : Set Ω
ht₁ : t₁ ∈ s i
ht₂ : t₂ ∈ s j
hf_m : ∀ x ∈ {i, j}, (if x = i then t₁ else t₂) ∈ s x
h_inter : (⋂ t ∈ {i, j}, if t = i then t₁ else t₂) = (if i = i then t₁ else t₂) ∩ if j = i then t₁ else t₂
a : α
h_indep' : (κ a) (⋂ i_1 ∈ {i, j}, if i_1 = i then t₁ else t₂) = ∏ i_1 ∈ {i, j}, (κ a) (if i_1 = i then t₁ else t₂)
⊢ (κ a) (t₁ ∩ t₂) = (κ a) t₁ * (κ a) t₂

Tactic:
grind

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

Goal state before:
pp: Ω : Type u_1
ι : Type u_2
_mΩ : MeasurableSpace Ω
μ : Measure Ω
s : ι → Set Ω
⊢ iIndepSets (fun i ↦ {s i}) μ ↔ ∀ (t : Finset ι), μ (⋂ i ∈ t, s i) = ∏ i ∈ t, μ (s i)

Tactic:
simp_rw [iIndepSets, Kernel.iIndepSets_singleton_iff, ae_dirac_eq, Filter.eventually_pure,
    Kernel.const_apply]

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

Goal state before:
pp: case mpr
Ω : Type u_1
β : Type u_6
β' : Type u_7
_mΩ : MeasurableSpace Ω
μ : Measure Ω
f : Ω → β
g : Ω → β'
mβ : MeasurableSpace β
mβ' : MeasurableSpace β'
hf : AEMeasurable f μ
hg : AEMeasurable g μ
σf : SigmaFinite (Measure.map f μ)
σg : SigmaFinite (Measure.map g μ)
h₀ :
  ∀ {s : Set β} {t : Set β'},
    MeasurableSet s →
      MeasurableSet t →
        μ (f ⁻¹' s) * μ (g ⁻¹' t) = (Measure.map f μ) s * (Measure.map g μ) t ∧
          μ (f ⁻¹' s ∩ g ⁻¹' t) = (Measure.map (fun ω ↦ (f ω, g ω)) μ) (s ×ˢ t)
⊢ Measure.map (fun ω ↦ (f ω, g ω)) μ = (Measure.map f μ).prod (Measure.map g μ) →
    ∀ (s : Set β) (t : Set β'), MeasurableSet s → MeasurableSet t → μ (f ⁻¹' s ∩ g ⁻¹' t) = μ (f ⁻¹' s) * μ (g ⁻¹' t)

Tactic:
intro h s t hs ht

Goal state after:
case mpr
Ω : Type u_1
β : Type u_6
β' : Type u_7
_mΩ : MeasurableSpace Ω
μ : Measure Ω
f : Ω → β
g : Ω → β'
mβ : MeasurableSpace β
mβ' : MeasurableSpace β'
hf : AEMeasurable f μ
hg : AEMeasurable g μ
σf : SigmaFinite (Measure.map f μ)
σg : SigmaFinite (Measure.map g μ)
h₀ :
  ∀ {s : Set β} {t : Set β'},
    MeasurableSet s →
      MeasurableSet t →
        μ (f ⁻¹' s) * μ (g ⁻¹' t) = (Measure.map f μ) s * (Measure.map g μ) t ∧
          μ (f ⁻¹' s ∩ g ⁻¹' t) = (Measure.map (fun ω ↦ (f ω, g ω)) μ) (s ×ˢ t)
h : Measure.map (fun ω ↦ (f ω, g ω)) μ = (Measure.map f μ).prod (Measure.map g μ)
s : Set β
t : Set β'
hs : MeasurableSet s
ht : MeasurableSet t
⊢ μ (f ⁻¹' s ∩ g ⁻¹' t) = μ (f ⁻¹' s) * μ (g ⁻¹' t)
Module: Mathlib.MeasureTheory.Measure.Portmanteau

Goal state before:
pp: case hf
Ω : Type u_1
inst✝³ : MeasurableSpace Ω
inst✝² : TopologicalSpace Ω
inst✝¹ : OpensMeasurableSpace Ω
μ : Measure Ω
μs : ℕ → Measure Ω
inst✝ : ∀ (i : ℕ), IsProbabilityMeasure (μs i)
f : Ω →ᵇ ℝ
f_nn : 0 ≤ f
h_opens : ∀ (G : Set Ω), IsOpen[inst✝²] G → μ G ≤ liminf (fun i ↦ (μs i) G) atTop
same : ∫⁻ (x : Ω), ENNReal.ofReal (f x) ∂μ ≤ liminf (fun i ↦ ∫⁻ (x : Ω), ENNReal.ofReal (f x) ∂μs i) atTop
obs : ∀ (i : ℕ), ∫⁻ (x : Ω), ↑‖f x‖₊ ∂μs i ≤ ↑‖f‖₊
⊢ autoParam (IsBoundedUnder (fun x1 x2 ↦ x1 ≥ x2) atTop fun i ↦ ∫⁻ (x : Ω), ENNReal.ofReal (f x) ∂μs i)
    liminf_le_of_le._auto_1

Tactic:
refine ⟨0, .of_forall (by simp)⟩

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

Goal state before:
pp: case mp
α : Type u_1
Ω : Type u_2
β : Type u_4
β' : Type u_5
mα : MeasurableSpace α
mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
f : Ω → β
g : Ω → β'
mβ : MeasurableSpace β
mβ' : MeasurableSpace β'
inst✝ : IsZeroOrMarkovKernel κ
hf : Measurable f
hg : Measurable g
⊢ (∀ (s : Set β) (t : Set β'),
      MeasurableSet s →
        MeasurableSet t → ∀ᵐ (a : α) ∂μ, (κ a) (f ⁻¹' s ∩ g ⁻¹' t) = (κ a) (f ⁻¹' s) * (κ a) (g ⁻¹' t)) →
    ∀ (s : Set β) (t : Set β'), MeasurableSet s → MeasurableSet t → IndepSet (f ⁻¹' s) (g ⁻¹' t) κ μ

Tactic:
intro h s t hs ht

Goal state after:
case mp
α : Type u_1
Ω : Type u_2
β : Type u_4
β' : Type u_5
mα : MeasurableSpace α
mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
f : Ω → β
g : Ω → β'
mβ : MeasurableSpace β
mβ' : MeasurableSpace β'
inst✝ : IsZeroOrMarkovKernel κ
hf : Measurable f
hg : Measurable g
h :
  ∀ (s : Set β) (t : Set β'),
    MeasurableSet s → MeasurableSet t → ∀ᵐ (a : α) ∂μ, (κ a) (f ⁻¹' s ∩ g ⁻¹' t) = (κ a) (f ⁻¹' s) * (κ a) (g ⁻¹' t)
s : Set β
t : Set β'
hs : MeasurableSet s
ht : MeasurableSet t
⊢ IndepSet (f ⁻¹' s) (g ⁻¹' t) κ μ
Module: Mathlib.Probability.Independence.Kernel.IndepFun

Goal state before:
pp: case mpr
α : Type u_1
Ω : Type u_2
β : Type u_4
β' : Type u_5
mα : MeasurableSpace α
mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
f : Ω → β
g : Ω → β'
mβ : MeasurableSpace β
mβ' : MeasurableSpace β'
inst✝ : IsZeroOrMarkovKernel κ
hf : Measurable f
hg : Measurable g
⊢ (∀ (s : Set β) (t : Set β'), MeasurableSet s → MeasurableSet t → IndepSet (f ⁻¹' s) (g ⁻¹' t) κ μ) →
    ∀ (s : Set β) (t : Set β'),
      MeasurableSet s → MeasurableSet t → ∀ᵐ (a : α) ∂μ, (κ a) (f ⁻¹' s ∩ g ⁻¹' t) = (κ a) (f ⁻¹' s) * (κ a) (g ⁻¹' t)

Tactic:
intro h s t hs ht

Goal state after:
case mpr
α : Type u_1
Ω : Type u_2
β : Type u_4
β' : Type u_5
mα : MeasurableSpace α
mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
f : Ω → β
g : Ω → β'
mβ : MeasurableSpace β
mβ' : MeasurableSpace β'
inst✝ : IsZeroOrMarkovKernel κ
hf : Measurable f
hg : Measurable g
h : ∀ (s : Set β) (t : Set β'), MeasurableSet s → MeasurableSet t → IndepSet (f ⁻¹' s) (g ⁻¹' t) κ μ
s : Set β
t : Set β'
hs : MeasurableSet s
ht : MeasurableSet t
⊢ ∀ᵐ (a : α) ∂μ, (κ a) (f ⁻¹' s ∩ g ⁻¹' t) = (κ a) (f ⁻¹' s) * (κ a) (g ⁻¹' t)
Module: Mathlib.Probability.Independence.Basic

Goal state before:
pp: case refine_2
ι : Type u_11
inst✝² : Fintype ι
Ω : ι → Type u_12
mΩ : (i : ι) → MeasurableSpace (Ω i)
μ : (i : ι) → Measure (Ω i)
inst✝¹ : ∀ (i : ι), IsProbabilityMeasure (μ i)
𝓧 : ι → Type u_13
inst✝ : (i : ι) → MeasurableSpace (𝓧 i)
X : (i : ι) → Ω i → 𝓧 i
mX : ∀ (i : ι), AEMeasurable (X i) (μ i)
i : ι
⊢ Measure.map (X i ∘ Function.eval i) (Measure.pi μ) = Measure.map (fun ω ↦ X i (ω i)) (Measure.pi μ)

pp: case refine_2.hg
ι : Type u_11
inst✝² : Fintype ι
Ω : ι → Type u_12
mΩ : (i : ι) → MeasurableSpace (Ω i)
μ : (i : ι) → Measure (Ω i)
inst✝¹ : ∀ (i : ι), IsProbabilityMeasure (μ i)
𝓧 : ι → Type u_13
inst✝ : (i : ι) → MeasurableSpace (𝓧 i)
X : (i : ι) → Ω i → 𝓧 i
mX : ∀ (i : ι), AEMeasurable (X i) (μ i)
i : ι
⊢ AEMeasurable (X i) (Measure.map (Function.eval i) (Measure.pi μ))

pp: case refine_2.hf
ι : Type u_11
inst✝² : Fintype ι
Ω : ι → Type u_12
mΩ : (i : ι) → MeasurableSpace (Ω i)
μ : (i : ι) → Measure (Ω i)
inst✝¹ : ∀ (i : ι), IsProbabilityMeasure (μ i)
𝓧 : ι → Type u_13
inst✝ : (i : ι) → MeasurableSpace (𝓧 i)
X : (i : ι) → Ω i → 𝓧 i
mX : ∀ (i : ι), AEMeasurable (X i) (μ i)
i : ι
⊢ AEMeasurable (Function.eval i) (Measure.pi μ)

Tactic:
Function.comp_def

Goal state after:
case refine_2
ι : Type u_11
inst✝² : Fintype ι
Ω : ι → Type u_12
mΩ : (i : ι) → MeasurableSpace (Ω i)
μ : (i : ι) → Measure (Ω i)
inst✝¹ : ∀ (i : ι), IsProbabilityMeasure (μ i)
𝓧 : ι → Type u_13
inst✝ : (i : ι) → MeasurableSpace (𝓧 i)
X : (i : ι) → Ω i → 𝓧 i
mX : ∀ (i : ι), AEMeasurable (X i) (μ i)
i : ι
⊢ Measure.map (fun x ↦ X i (Function.eval i x)) (Measure.pi μ) = Measure.map (fun ω ↦ X i (ω i)) (Measure.pi μ)

case refine_2.hg
ι : Type u_11
inst✝² : Fintype ι
Ω : ι → Type u_12
mΩ : (i : ι) → MeasurableSpace (Ω i)
μ : (i : ι) → Measure (Ω i)
inst✝¹ : ∀ (i : ι), IsProbabilityMeasure (μ i)
𝓧 : ι → Type u_13
inst✝ : (i : ι) → MeasurableSpace (𝓧 i)
X : (i : ι) → Ω i → 𝓧 i
mX : ∀ (i : ι), AEMeasurable (X i) (μ i)
i : ι
⊢ AEMeasurable (X i) (Measure.map (Function.eval i) (Measure.pi μ))

case refine_2.hf
ι : Type u_11
inst✝² : Fintype ι
Ω : ι → Type u_12
mΩ : (i : ι) → MeasurableSpace (Ω i)
μ : (i : ι) → Measure (Ω i)
inst✝¹ : ∀ (i : ι), IsProbabilityMeasure (μ i)
𝓧 : ι → Type u_13
inst✝ : (i : ι) → MeasurableSpace (𝓧 i)
X : (i : ι) → Ω i → 𝓧 i
mX : ∀ (i : ι), AEMeasurable (X i) (μ i)
i : ι
⊢ AEMeasurable (Function.eval i) (Measure.pi μ)
Module: Mathlib.MeasureTheory.Measure.Portmanteau

Goal state before:
pp: case mpr.inr.refine_1
γ : Type u_1
Ω : Type u_2
mΩ : MeasurableSpace Ω
inst✝² : PseudoEMetricSpace Ω
inst✝¹ : OpensMeasurableSpace Ω
F : Filter γ
inst✝ : F.IsCountablyGenerated
μs : γ → ProbabilityMeasure Ω
μ : ProbabilityMeasure Ω
hne : F.NeBot
h :
  ∀ (f : Ω → ℝ),
    (∃ C, ∀ (x y : Ω), dist (f x) (f y) ≤ C) →
      (∃ L, LipschitzWith L f) → Tendsto (fun i ↦ ∫ (ω : Ω), f ω ∂↑(μs i)) F (𝓝 (∫ (ω : Ω), f ω ∂↑μ))
s : Set Ω
hs : IsClosed[PseudoEMetricSpace.toUniformSpace.toTopologicalSpace] s
ε : ℝ
ε_pos : 0 < ε
fs : ℕ → Ω → ℝ := fun n ω ↦ ↑((thickenedIndicator ⋯ s) ω)
key₁ : Tendsto (fun n ↦ ∫ (ω : Ω), fs n ω ∂↑μ) atTop (𝓝 ((↑μ).real s))
room₁ : (↑μ).real s < (↑μ).real s + ε / 2
M : ℕ
hM : ∀ (b : ℕ), M ≤ b → ∫ (ω : Ω), fs b ω ∂↑μ < (↑μ).real s + ε / 2
x y : Ω
h1 : ∀ (x : Ω), fs M x ≤ 1
h2 : ∀ (x : Ω), 0 ≤ fs M x
⊢ -1 ≤ fs M x - fs M y ∧ fs M x - fs M y ≤ 1

Tactic:
grind

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

Goal state before:
pp: case inr
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
n : ι
hn_mem_insert : n ∈ insert a s
hn_mem : n ∈ s
⊢ (if n = a then t2 else if n ∈ s then ft1 n else univ) ∈ π n

Tactic:
grind

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_forall : ∀ n ∈ s, f n = ft1 n
⊢ t1 = ⋂ n ∈ s, f n

Tactic:
grind

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

Goal state before:
pp: Ω : Type u_1
inst✝² : MeasurableSpace Ω
inst✝¹ : TopologicalSpace Ω
inst✝ : SecondCountableTopology Ω
S : Set (Set Ω)
ν : ProbabilityMeasure Ω
h : ∀ (u : Set Ω), IsOpen[inst✝¹] u → ∀ x ∈ u, ∃ s ∈ S, s ∈ 𝓝 x ∧ s ⊆ u
G : Set Ω
hG : IsOpen[inst✝¹] G
r : ℝ≥0
hr : r < ν G
s : ↑G → Set Ω
hsS : ∀ (x : ↑G), s x ∈ S
hs_nhds : ∀ (x : ↑G), s x ∈ 𝓝 ↑x
hsG : ∀ (x : ↑G), s x ⊆ G
T₀ : Set ↑G
T₀_count : T₀.Countable
hT₀ : ⋃ i ∈ T₀, interior (s i) = ⋃ i, interior (s i)
⊢ s '' T₀ ⊆ S

Tactic:
grind

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

Goal state before:
pp: Ω : Type u_1
inst✝² : MeasurableSpace Ω
inst✝¹ : TopologicalSpace Ω
inst✝ : SecondCountableTopology Ω
S : Set (Set Ω)
ν : ProbabilityMeasure Ω
h : ∀ (u : Set Ω), IsOpen[inst✝¹] u → ∀ x ∈ u, ∃ s ∈ S, s ∈ 𝓝 x ∧ s ⊆ u
G : Set Ω
hG : IsOpen[inst✝¹] G
r : ℝ≥0
hr : r < ν G
s : ↑G → Set Ω
hsS : ∀ (x : ↑G), s x ∈ S
hs_nhds : ∀ (x : ↑G), s x ∈ 𝓝 ↑x
hsG : ∀ (x : ↑G), s x ⊆ G
T₀ : Set ↑G
T₀_count : T₀.Countable
hT₀ : ⋃ i ∈ T₀, interior (s i) = ⋃ i, interior (s i)
⊢ ∀ (i : Set Ω) (i_1 : Ω) (i_2 : i_1 ∈ G), ⟨i_1, i_2⟩ ∈ T₀ → s ⟨i_1, i_2⟩ = i → i ⊆ G

Tactic:
grind

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

Goal state before:
pp: Ω : Type u_1
inst✝² : MeasurableSpace Ω
inst✝¹ : TopologicalSpace Ω
inst✝ : SecondCountableTopology Ω
S : Set (Set Ω)
ν : ProbabilityMeasure Ω
h : ∀ (u : Set Ω), IsOpen[inst✝¹] u → ∀ x ∈ u, ∃ s ∈ S, s ∈ 𝓝 x ∧ s ⊆ u
G : Set Ω
hG : IsOpen[inst✝¹] G
r : ℝ≥0
hr : r < ν G
T : Set (Set Ω)
TS : T ⊆ S
T_count : T.Countable
hT : ⋃ t ∈ T, t = G
this✝ : T.Nonempty
f : ℕ → Set Ω
hf : T = range f
G_eq : G = ⋃ n, f n
this : Tendsto (fun i ↦ ν (accumulate f i)) atTop (𝓝 (ν G))
n : ℕ
hn : r < ν (accumulate f n)
⊢ ∀ t ∈ Finset.image f (Finset.range (n + 1)), t ∈ S

Tactic:
grind

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), Measurable (f i)
hμ : μ ≠ 0
η : Kernel α Ω
η_eq : ⇑κ =ᵐ[μ] ⇑η
hη : IsMarkovKernel η
πSβ : Set (Set ((i : ↥S) → β ↑i)) := univ.pi '' univ.pi fun i ↦ {s | MeasurableSet s}
πS : Set (Set Ω) := {s | ∃ t ∈ πSβ, (fun a i ↦ f (↑i) a) ⁻¹' t = s}
hπS_pi : IsPiSystem πS
hπS_gen : MeasurableSpace.comap (fun a i ↦ f (↑i) a) MeasurableSpace.pi = generateFrom πS
πTβ : Set (Set ((i : ↥T) → β ↑i)) := univ.pi '' univ.pi fun i ↦ {s | MeasurableSet s}
πT : Set (Set Ω) := {s | ∃ t ∈ πTβ, (fun a i ↦ f (↑i) a) ⁻¹' t = s}
hπT_pi : IsPiSystem πT
hπT_gen : MeasurableSpace.comap (fun a i ↦ f (↑i) a) MeasurableSpace.pi = generateFrom πT
s : Set ((i : ↥S) → β ↑i)
sets_s : (i : ↥S) → Set (β ↑i)
hs2 : univ.pi sets_s = s
t : Set ((i : ↥T) → β ↑i)
sets_t : (i : ↥T) → Set (β ↑i)
ht2 : univ.pi sets_t = t
hs1 : ∀ (i : ↥S), MeasurableSet (sets_s i)
ht1 : ∀ (i : ↥T), MeasurableSet (sets_t i)
sets_s' : (i : ι) → Set (β i) := fun i ↦ if hi : i ∈ S then sets_s ⟨i, hi⟩ else univ
h_sets_s'_eq : ∀ {i : ι} (hi : i ∈ S), sets_s' i = sets_s ⟨i, hi⟩
h_sets_s'_univ : ∀ {i : ι}, i ∈ T → sets_s' i = univ
sets_t' : (i : ι) → Set (β i) := fun i ↦ if hi : i ∈ T then sets_t ⟨i, hi⟩ else univ
h_sets_t'_univ : ∀ {i : ι}, i ∈ S → sets_t' i = univ
h_meas_s' : ∀ i ∈ S, MeasurableSet (sets_s' i)
h_meas_t' : ∀ i ∈ T, MeasurableSet (sets_t' i)
x : Ω
⊢ (∀ (i : ↥S), f (↑i) x ∈ sets_s i) ↔ ∀ i ∈ S, x ∈ f i ⁻¹' sets_s' i

Tactic:
grind

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

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
X : Ω → ℝ
μ : Measure Ω
inst✝ : IsFiniteMeasure μ
hX : MemLp X 2 μ
h : (fun ω ↦ (X ω - ∫ (x : Ω), X x ∂μ) ^ 2) =ᵐ[μ] 0
ω : Ω
hω : X ω - ∫ (x : Ω), X x ∂μ = 0
⊢ X ω = ∫ (x : Ω), X x ∂μ

Tactic:
grind

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

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
c : ℝ
X : Ω → ℝ
μ : Measure Ω
⊢ c ^ 2 * eVar[X; μ].toReal = c ^ 2 * Var[X; μ]

Tactic:
rfl

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

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
ι : Type u_2
s : Finset ι
X : ι → Ω → ℝ
inst✝ : IsFiniteMeasure μ
hX : ∀ i ∈ s, MemLp (X i) 2 μ
⊢ ∑ i ∈ s, cov[X i, ∑ i ∈ s, X i; μ] = ∑ i ∈ s, ∑ j ∈ s, cov[X i, X j; μ]

Tactic:
refine Finset.sum_congr rfl fun i hi ↦ ?_
    rw [covariance_sum_right' (by simpa) (hX i hi)]

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
G : Type u_7
𝕜 : Type u_8
inst✝¹⁰ : NontriviallyNormedField 𝕜
inst✝⁹ : SeminormedAddCommGroup E
inst✝⁸ : NormedSpace 𝕜 E
inst✝⁷ : MeasurableSpace E
inst✝⁶ : OpensMeasurableSpace E
inst✝⁵ : SeminormedAddCommGroup F
inst✝⁴ : NormedSpace 𝕜 F
inst✝³ : MeasurableSpace F
inst✝² : OpensMeasurableSpace F
inst✝¹ : SeminormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
X : Ω → E
Y : Ω → F
hXY : X ⟂ᵢ[μ] Y
hX : Integrable X μ
hY : Integrable Y μ
B : E →L[𝕜] F →L[𝕜] G
⊢ Integrable (fun ω ↦ (B (X ω)) (Y ω)) μ

Tactic:
by
  refine hXY.integrable_op hX hY (B · ·) (by fun_prop) ‖B‖₊ (fun x y ↦ ?_)
  rw [← toReal_le_toReal (by finiteness) (by finiteness)]
  simp [B.le_opNorm₂]

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

Goal state before:
pp: case mp
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_meas : ∀ (i : ι), Measurable (f i)
hμ : μ ≠ 0
η : Kernel α Ω
η_eq : ⇑κ =ᵐ[μ] ⇑η
hη : IsMarkovKernel η
πSβ : Set (Set ((i : ↥S) → β ↑i)) := univ.pi '' univ.pi fun i ↦ {s | MeasurableSet s}
πS : Set (Set Ω) := {s | ∃ t ∈ πSβ, (fun a i ↦ f (↑i) a) ⁻¹' t = s}
hπS_pi : IsPiSystem πS
hπS_gen : MeasurableSpace.comap (fun a i ↦ f (↑i) a) MeasurableSpace.pi = generateFrom πS
πTβ : Set (Set ((i : ↥T) → β ↑i)) := univ.pi '' univ.pi fun i ↦ {s | MeasurableSet s}
πT : Set (Set Ω) := {s | ∃ t ∈ πTβ, (fun a i ↦ f (↑i) a) ⁻¹' t = s}
hπT_pi : IsPiSystem πT
hπT_gen : MeasurableSpace.comap (fun a i ↦ f (↑i) a) MeasurableSpace.pi = generateFrom πT
s : Set ((i : ↥S) → β ↑i)
sets_s : (i : ↥S) → Set (β ↑i)
hs2 : univ.pi sets_s = s
t : Set ((i : ↥T) → β ↑i)
sets_t : (i : ↥T) → Set (β ↑i)
ht2 : univ.pi sets_t = t
hs1 : ∀ (i : ↥S), MeasurableSet (sets_s i)
ht1 : ∀ (i : ↥T), MeasurableSet (sets_t i)
sets_s' : (i : ι) → Set (β i) := fun i ↦ if hi : i ∈ S then sets_s ⟨i, hi⟩ else univ
h_sets_s'_eq : ∀ {i : ι} (hi : i ∈ S), sets_s' i = sets_s ⟨i, hi⟩
h_sets_s'_univ : ∀ {i : ι}, i ∈ T → sets_s' i = univ
sets_t' : (i : ι) → Set (β i) := fun i ↦ if hi : i ∈ T then sets_t ⟨i, hi⟩ else univ
h_sets_t'_univ : ∀ {i : ι}, i ∈ S → sets_t' i = univ
h_meas_s' : ∀ i ∈ S, MeasurableSet (sets_s' i)
h_meas_t' : ∀ i ∈ T, MeasurableSet (sets_t' i)
h_eq_inter_S : (fun ω i ↦ f (↑i) ω) ⁻¹' univ.pi sets_s = ⋂ i ∈ S, f i ⁻¹' sets_s' i
h_eq_inter_T : (fun ω i ↦ f (↑i) ω) ⁻¹' univ.pi sets_t = ⋂ i ∈ T, f i ⁻¹' sets_t' i
hf_Indep :
  ∀ (S : Finset ι) {sets : (i : ι) → Set (β i)},
    (∀ i ∈ S, MeasurableSet (sets i)) → ∀ᵐ (a : α) ∂μ, (η a) (⋂ i ∈ S, f i ⁻¹' sets i) = ∏ i ∈ S, (η a) (f i ⁻¹' sets i)
x : Ω
h : (∀ i ∈ S, f i x ∈ sets_s' i) ∧ ∀ i ∈ T, f i x ∈ sets_t' i
⊢ ∀ (i : ι), i ∈ S ∨ i ∈ T → f i x ∈ sets_s' i ∩ sets_t' i

Tactic:
grind

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

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
X : Ω → ℝ
inst✝ : MeasurableSingletonClass Ω
x : Ω
⊢ Var[X; Measure.dirac x] = 0

Tactic:
rw [variance_eq_integral]
  · simp
  · exact aemeasurable_dirac

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

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
Ω' : Type u_3
mΩ' : MeasurableSpace Ω'
ν : Measure Ω'
X : Ω → Ω'
hX : MeasurePreserving X μ ν
f : Ω' → ℝ
hf : AEMeasurable f ν
⊢ Var[fun ω ↦ f (X ω); μ] = Var[f ∘ X; μ]

Tactic:
Function.comp_def

Goal state after:
Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
Ω' : Type u_3
mΩ' : MeasurableSpace Ω'
ν : Measure Ω'
X : Ω → Ω'
hX : MeasurePreserving X μ ν
f : Ω' → ℝ
hf : AEMeasurable f ν
⊢ Var[fun ω ↦ f (X ω); μ] = Var[fun x ↦ f (X x); μ]
Module: Mathlib.Probability.Moments.Variance

Goal state before:
pp: case e'_4
Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
inst✝ : IsFiniteMeasure μ
X : Ω → ℝ
hX : MemLp X 2 μ
c : ℝ
hc : 0 < c
⊢ eVar[X; μ] / ENNReal.ofReal c ^ 2 = eVar[X; μ] / ↑c.toNNReal ^ 2

Tactic:
rfl

Goal state after: