mathlib-initiative/mathlib-tactics huggingface dataset:
Module: Mathlib.MeasureTheory.VectorMeasure.Decomposition.Hahn

Goal state before:
pp: case e'_4
α : Type u_1
inst✝ : MeasurableSpace α
s : SignedMeasure α
i : Set α
hi : s i < 0
hi₁ : MeasurableSet i
h : ¬s ≤[i] 0
hn : ∀ (n : ℕ), ¬s ≤[i \ ⋃ l, ⋃ (_ : l < n), s.restrictNonposSeq i l] 0
A : Set α := i \ ⋃ l, s.restrictNonposSeq i l
hA : A = i \ ⋃ l, s.restrictNonposSeq i l
bdd : ℕ → ℕ := fun n ↦ s.findExistsOneDivLT (i \ ⋃ k, ⋃ (_ : k ≤ n), s.restrictNonposSeq i k)
n : ℕ
⊢ (fun l ↦ ⋃ (_ : l ≤ n), s.restrictNonposSeq i l) = fun l ↦ ⋃ (_ : l < n + 1), s.restrictNonposSeq i l

Tactic:
· ext l
        simp only [exists_prop, Set.mem_iUnion, and_congr_left_iff]
        exact fun _ => Nat.lt_succ_iff.symm

Goal state after:
Module: Mathlib.MeasureTheory.VectorMeasure.Basic

Goal state before:
pp: case pos
α : Type u_1
m : MeasurableSpace α
M : Type u_4
inst✝¹ : AddCommMonoid M
inst✝ : TopologicalSpace M
v : VectorMeasure α M
μ : VectorMeasure α ℝ≥0∞
h : v ≪ᵥ μ
s : Set α
hs : μ.ennrealToMeasure s = 0
hmeas : MeasurableSet s
⊢ v s = 0

pp: case neg
α : Type u_1
m : MeasurableSpace α
M : Type u_4
inst✝¹ : AddCommMonoid M
inst✝ : TopologicalSpace M
v : VectorMeasure α M
μ : VectorMeasure α ℝ≥0∞
h : v ≪ᵥ μ
s : Set α
hs : μ.ennrealToMeasure s = 0
hmeas : ¬MeasurableSet s
⊢ v s = 0

Tactic:
· rw [ennrealToMeasure_apply hmeas] at hs
      exact h hs

Goal state after:
case neg
α : Type u_1
m : MeasurableSpace α
M : Type u_4
inst✝¹ : AddCommMonoid M
inst✝ : TopologicalSpace M
v : VectorMeasure α M
μ : VectorMeasure α ℝ≥0∞
h : v ≪ᵥ μ
s : Set α
hs : μ.ennrealToMeasure s = 0
hmeas : ¬MeasurableSet s
⊢ v s = 0
Module: Mathlib.MeasureTheory.VectorMeasure.WithDensity

Goal state before:
pp: α : Type u_1
m : MeasurableSpace α
μ : Measure α
E : Type u_2
inst✝¹ : NormedAddCommGroup E
inst✝ : NormedSpace ℝ E
f : α → E
⊢ μ.withDensityᵥ (-f) = -μ.withDensityᵥ f

Tactic:
by_cases hf : Integrable f μ
  · ext1 i hi
    rw [_root_.neg_apply, withDensityᵥ_apply hf hi, ← integral_neg,
      withDensityᵥ_apply hf.neg hi]
    simp only [Pi.neg_apply]
  · rw [withDensityᵥ, withDensityᵥ, dif_neg hf, dif_neg, neg_zero]
    rwa [integrable_neg_iff]

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

Goal state before:
pp: Ω : Type u_1
inst✝⁴ : TopologicalSpace Ω
inst✝³ : MeasurableSpace Ω
inst✝² : OpensMeasurableSpace Ω
ι : Type u_2
L : Filter ι
inst✝¹ : L.IsCountablyGenerated
μ : Measure Ω
inst✝ : IsFiniteMeasure μ
c : ℝ≥0
E : Set Ω
E_mble : MeasurableSet E
fs : ι → Ω →ᵇ ℝ≥0
fs_bdd : ∀ᶠ (i : ι) in L, ∀ᵐ (ω : Ω) ∂μ, (fs i) ω ≤ c
fs_lim : ∀ᵐ (ω : Ω) ∂μ, Tendsto (fun i ↦ (fs i) ω) L (𝓝 (E.indicator (fun x ↦ 1) ω))
⊢ Tendsto (fun n ↦ ∫⁻ (ω : Ω), ↑((fs n) ω) ∂μ) L (𝓝 (μ E))

Tactic:
convert! tendsto_lintegral_nn_filter_of_le_const μ fs_bdd fs_lim

Goal state after:
Ω : Type u_1
inst✝⁴ : TopologicalSpace Ω
inst✝³ : MeasurableSpace Ω
inst✝² : OpensMeasurableSpace Ω
ι : Type u_2
L : Filter ι
inst✝¹ : L.IsCountablyGenerated
μ : Measure Ω
inst✝ : IsFiniteMeasure μ
c : ℝ≥0
E : Set Ω
E_mble : MeasurableSet E
fs : ι → Ω →ᵇ ℝ≥0
fs_bdd : ∀ᶠ (i : ι) in L, ∀ᵐ (ω : Ω) ∂μ, (fs i) ω ≤ c
fs_lim : ∀ᵐ (ω : Ω) ∂μ, Tendsto (fun i ↦ (fs i) ω) L (𝓝 (E.indicator (fun x ↦ 1) ω))
⊢ μ E = ∫⁻ (ω : Ω), ↑(E.indicator (fun x ↦ 1) ω) ∂μ
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 : iIndepFun f κ μ
h : ∀ (i : ι), ∀ᵐ (a : α) ∂μ, f i =ᵐ[κ a] g i
⊢ iIndepFun g κ μ

Tactic:
rw [iIndepFun_iff_measure_inter_preimage_eq_mul] at hf ⊢
  intro S sets hmeas
  have : ∀ᵐ a ∂μ, ∀ i ∈ S, f i =ᵐ[κ a] g i :=
    (ae_ball_iff (Finset.countable_toSet S)).2 (fun i hi ↦ h i)
  filter_upwards [this, hf S hmeas] with a ha h'a
  have A i (hi : i ∈ S) : (κ a) (g i ⁻¹' sets i) = (κ a) (f i ⁻¹' sets i) := by
    apply measure_congr
    filter_upwards [ha i hi] with ω hω
    change (g i ω ∈ sets i) = (f i ω ∈ sets i)
    simp [hω]
  have B : (κ a) (⋂ i ∈ S, g i ⁻¹' sets i) = (κ a) (⋂ i ∈ S, f i ⁻¹' sets i) := by
    apply measure_congr
    filter_upwards [(ae_ball_iff (Finset.countable_toSet S)).2 ha] with ω hω
    change (ω ∈ ⋂ i ∈ S, g i ⁻¹' sets i) = (ω ∈ ⋂ i ∈ S, f i ⁻¹' sets i)
    simp +contextual [hω]
  convert! h'a using 2 with i hi
  exact A i hi

Goal state after:
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

pp: case h
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‖₊
⊢ ∀ (b : ℝ≥0∞), (∀ᶠ (n : ℕ) in atTop, b ≤ ∫⁻ (x : Ω), ENNReal.ofReal (f x) ∂μs n) → b ≤ ↑‖f‖₊

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

Goal state after:
case h
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‖₊
⊢ ∀ (b : ℝ≥0∞), (∀ᶠ (n : ℕ) in atTop, b ≤ ∫⁻ (x : Ω), ENNReal.ofReal (f x) ∂μs n) → b ≤ ↑‖f‖₊
Module: Mathlib.Probability.Independence.Kernel.IndepFun

Goal state before:
pp: case refine_1
α : Type u_1
Ω : Type u_2
β : Type u_4
β' : Type u_5
γ : Type u_6
γ' : Type u_7
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'
mγ : MeasurableSpace γ
mγ' : MeasurableSpace γ'
φ : β → γ
ψ : β' → γ'
hfg : IndepFun f g κ μ
hf : AEMeasurable f (⇑κ ∘ₘ μ)
hg : AEMeasurable g (⇑κ ∘ₘ μ)
hφ : AEMeasurable φ (Measure.map f (⇑κ ∘ₘ μ))
hψ : AEMeasurable ψ (Measure.map g (⇑κ ∘ₘ μ))
h : IndepFun (AEMeasurable.mk φ hφ ∘ f) (AEMeasurable.mk ψ hψ ∘ g) κ μ
hφ_ae : ∀ᵐ (x : Ω) ∂⇑κ ∘ₘ μ, φ (f x) = AEMeasurable.mk φ hφ (f x)
hψ_ae : ∀ᵐ (x : Ω) ∂⇑κ ∘ₘ μ, ψ (g x) = AEMeasurable.mk ψ hψ (g x)
⊢ ∀ᵐ (a : α) ∂μ, AEMeasurable.mk φ hφ ∘ f =ᵐ[κ a] φ ∘ f

Tactic:
filter_upwards [Measure.ae_ae_of_ae_comp (hφ_ae)] with a haφ

Goal state after:
α : Type u_1
Ω : Type u_2
β : Type u_4
β' : Type u_5
γ : Type u_6
γ' : Type u_7
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'
mγ : MeasurableSpace γ
mγ' : MeasurableSpace γ'
φ : β → γ
ψ : β' → γ'
hfg : IndepFun f g κ μ
hf : AEMeasurable f (⇑κ ∘ₘ μ)
hg : AEMeasurable g (⇑κ ∘ₘ μ)
hφ : AEMeasurable φ (Measure.map f (⇑κ ∘ₘ μ))
hψ : AEMeasurable ψ (Measure.map g (⇑κ ∘ₘ μ))
h : IndepFun (AEMeasurable.mk φ hφ ∘ f) (AEMeasurable.mk ψ hψ ∘ g) κ μ
hφ_ae : ∀ᵐ (x : Ω) ∂⇑κ ∘ₘ μ, φ (f x) = AEMeasurable.mk φ hφ (f x)
hψ_ae : ∀ᵐ (x : Ω) ∂⇑κ ∘ₘ μ, ψ (g x) = AEMeasurable.mk ψ hψ (g x)
a : α
haφ : ∀ᵐ (ω : Ω) ∂κ a, φ (f ω) = AEMeasurable.mk φ hφ (f ω)
⊢ AEMeasurable.mk φ hφ ∘ f =ᵐ[κ a] φ ∘ f
Module: Mathlib.MeasureTheory.Measure.Portmanteau

Goal state before:
pp: Ω : Type u_1
ι : Type u_2
mΩ : MeasurableSpace Ω
inst✝² : TopologicalSpace Ω
inst✝¹ : OpensMeasurableSpace Ω
μ : ProbabilityMeasure Ω
μs : ι → ProbabilityMeasure Ω
L : Filter ι
inst✝ : L.IsCountablyGenerated
h : ∀ (F : Set Ω), IsClosed[inst✝²] F → limsup (fun i ↦ (μs i) F) L ≤ μ F
⊢ Tendsto μs L (𝓝 μ)

Tactic:
by
  apply Filter.tendsto_of_seq_tendsto fun u hu ↦ ?_
  apply tendsto_of_forall_isClosed_limsup_le_nat fun F hF ↦ le_trans ?_ (h F hF)
  exact (limsup_comp (fun i ↦ μs i F) u _).trans_le
    (limsup_le_limsup_of_le hu (by isBoundedDefault) ⟨1, by simp⟩)

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

Goal state before:
pp: case pos
α : Type u_1
Ω : Type u_2
β : Type u_4
γ : Type u_6
mα : MeasurableSpace α
mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
mβ : MeasurableSpace β
mγ : MeasurableSpace γ
inst✝¹ : IsFiniteMeasure μ
inst✝ : IsFiniteKernel κ
f : Ω → β
g : Ω → γ
hf : Measurable f
hg : Measurable g
h :
  ∀ (s : Set β) (t : Set γ),
    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)
u : Set α
s : Set β
t : Set γ
hu : MeasurableSet u
hs : MeasurableSet s
ht : MeasurableSet t
h_set_eq : ∀ (ω : α), Prod.mk ω ⁻¹' u ×ˢ s ×ˢ t = if ω ∈ u then s ×ˢ t else ∅
ω : α
hω : (κ ω) (f ⁻¹' s ∩ g ⁻¹' t) = (κ ω) (f ⁻¹' s) * (κ ω) (g ⁻¹' t)
hωu : ω ∈ u
⊢ (Measure.map (fun ω ↦ (f ω, g ω)) (κ ω)) (s ×ˢ t) = ((κ.map f ×ₖ κ.map g) ω) (s ×ˢ t)

Tactic:
Measure.map_apply (by fun_prop) (hs.prod ht),

Goal state after:
case pos
α : Type u_1
Ω : Type u_2
β : Type u_4
γ : Type u_6
mα : MeasurableSpace α
mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
mβ : MeasurableSpace β
mγ : MeasurableSpace γ
inst✝¹ : IsFiniteMeasure μ
inst✝ : IsFiniteKernel κ
f : Ω → β
g : Ω → γ
hf : Measurable f
hg : Measurable g
h :
  ∀ (s : Set β) (t : Set γ),
    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)
u : Set α
s : Set β
t : Set γ
hu : MeasurableSet u
hs : MeasurableSet s
ht : MeasurableSet t
h_set_eq : ∀ (ω : α), Prod.mk ω ⁻¹' u ×ˢ s ×ˢ t = if ω ∈ u then s ×ˢ t else ∅
ω : α
hω : (κ ω) (f ⁻¹' s ∩ g ⁻¹' t) = (κ ω) (f ⁻¹' s) * (κ ω) (g ⁻¹' t)
hωu : ω ∈ u
⊢ (κ ω) ((fun ω ↦ (f ω, g ω)) ⁻¹' s ×ˢ t) = ((κ.map f ×ₖ κ.map g) ω) (s ×ˢ t)
Module: Mathlib.Probability.Density

Goal state before:
pp: Ω : Type u_1
E : Type u_2
inst✝ : MeasurableSpace E
x✝ : MeasurableSpace Ω
X : Ω → E
ℙ : Measure Ω
μ : Measure E
hX : AEMeasurable X ℙ
⊢ AEMeasurable X ℙ ∧ (map X ℙ).HaveLebesgueDecomposition μ ∧ map X ℙ ≪ μ ↔
    (map X ℙ).HaveLebesgueDecomposition μ ∧ map X ℙ ≪ μ

Tactic:
simp only [hX, true_and]

Goal state after:
Module: Mathlib.Probability.Density

Goal state before:
pp: Ω : Type u_1
G : Type u_2
mΩ : MeasurableSpace Ω
ℙ : Measure Ω
inst✝⁶ : Group G
mG : MeasurableSpace G
inst✝⁵ : MeasurableMul₂ G
inst✝⁴ : MeasurableInv G
μ : Measure G
inst✝³ : μ.IsMulLeftInvariant
X Y : Ω → G
inst✝² : SFinite μ
inst✝¹ : HasPDF X ℙ μ
inst✝ : HasPDF Y ℙ μ
σX : SigmaFinite (map X ℙ)
σY : SigmaFinite (map Y ℙ)
hXY : X ⟂ᵢ[ℙ] Y
this✝ : AEMeasurable X ℙ
this : AEMeasurable Y ℙ
⊢ (map (X * Y) ℙ).HaveLebesgueDecomposition μ ∧ map (X * Y) ℙ ≪ μ

Tactic:
hXY.map_mul_eq_map_mconv_map₀' (by fun_prop) (by fun_prop) σX σY

Goal state after:
Ω : Type u_1
G : Type u_2
mΩ : MeasurableSpace Ω
ℙ : Measure Ω
inst✝⁶ : Group G
mG : MeasurableSpace G
inst✝⁵ : MeasurableMul₂ G
inst✝⁴ : MeasurableInv G
μ : Measure G
inst✝³ : μ.IsMulLeftInvariant
X Y : Ω → G
inst✝² : SFinite μ
inst✝¹ : HasPDF X ℙ μ
inst✝ : HasPDF Y ℙ μ
σX : SigmaFinite (map X ℙ)
σY : SigmaFinite (map Y ℙ)
hXY : X ⟂ᵢ[ℙ] Y
this✝ : AEMeasurable X ℙ
this : AEMeasurable Y ℙ
⊢ (map X ℙ ∗ₘ map Y ℙ).HaveLebesgueDecomposition μ ∧ map X ℙ ∗ₘ map Y ℙ ≪ μ
Module: Mathlib.Probability.Independence.Integration

Goal state before:
pp: case add
Ω : Type u_1
Mf mΩ : MeasurableSpace Ω
μ : Measure Ω
hMf : Mf ≤ mΩ
c : ℝ≥0∞
T : Set Ω
h_meas_T : MeasurableSet T
h_ind : IndepSets {s | MeasurableSet s} {T} μ
h_mul_indicator : ∀ (g : Ω → ℝ≥0∞), Measurable g → Measurable fun a ↦ g a * T.indicator (fun x ↦ c) a
⊢ ∀ ⦃f g : Ω → ℝ≥0∞⦄,
    Disjoint (Function.support f) (Function.support g) →
      Measurable f →
        Measurable g →
          ∫⁻ (ω : Ω), f ω * T.indicator (fun x ↦ c) ω ∂μ =
              (∫⁻ (ω : Ω), f ω ∂μ) * ∫⁻ (ω : Ω), T.indicator (fun x ↦ c) ω ∂μ →
            ∫⁻ (ω : Ω), g ω * T.indicator (fun x ↦ c) ω ∂μ =
                (∫⁻ (ω : Ω), g ω ∂μ) * ∫⁻ (ω : Ω), T.indicator (fun x ↦ c) ω ∂μ →
              ∫⁻ (ω : Ω), (f + g) ω * T.indicator (fun x ↦ c) ω ∂μ =
                (∫⁻ (ω : Ω), (f + g) ω ∂μ) * ∫⁻ (ω : Ω), T.indicator (fun x ↦ c) ω ∂μ

pp: case iSup
Ω : Type u_1
Mf mΩ : MeasurableSpace Ω
μ : Measure Ω
hMf : Mf ≤ mΩ
c : ℝ≥0∞
T : Set Ω
h_meas_T : MeasurableSet T
h_ind : IndepSets {s | MeasurableSet s} {T} μ
h_mul_indicator : ∀ (g : Ω → ℝ≥0∞), Measurable g → Measurable fun a ↦ g a * T.indicator (fun x ↦ c) a
⊢ ∀ ⦃f : ℕ → Ω → ℝ≥0∞⦄,
    (∀ (n : ℕ), Measurable (f n)) →
      Monotone f →
        (∀ (n : ℕ),
            ∫⁻ (ω : Ω), f n ω * T.indicator (fun x ↦ c) ω ∂μ =
              (∫⁻ (ω : Ω), f n ω ∂μ) * ∫⁻ (ω : Ω), T.indicator (fun x ↦ c) ω ∂μ) →
          ∫⁻ (ω : Ω), (fun x ↦ ⨆ n, f n x) ω * T.indicator (fun x ↦ c) ω ∂μ =
            (∫⁻ (ω : Ω), (fun x ↦ ⨆ n, f n x) ω ∂μ) * ∫⁻ (ω : Ω), T.indicator (fun x ↦ c) ω ∂μ

Tactic:
· intro f' g _ h_meas_f' _ h_ind_f' h_ind_g
    have h_measM_f' : Measurable f' := h_meas_f'.mono hMf le_rfl
    simp_rw [Pi.add_apply, right_distrib]
    rw [lintegral_add_left (h_mul_indicator _ h_measM_f'), lintegral_add_left h_measM_f',
      right_distrib, h_ind_f', h_ind_g]

Goal state after:
case iSup
Ω : Type u_1
Mf mΩ : MeasurableSpace Ω
μ : Measure Ω
hMf : Mf ≤ mΩ
c : ℝ≥0∞
T : Set Ω
h_meas_T : MeasurableSet T
h_ind : IndepSets {s | MeasurableSet s} {T} μ
h_mul_indicator : ∀ (g : Ω → ℝ≥0∞), Measurable g → Measurable fun a ↦ g a * T.indicator (fun x ↦ c) a
⊢ ∀ ⦃f : ℕ → Ω → ℝ≥0∞⦄,
    (∀ (n : ℕ), Measurable (f n)) →
      Monotone f →
        (∀ (n : ℕ),
            ∫⁻ (ω : Ω), f n ω * T.indicator (fun x ↦ c) ω ∂μ =
              (∫⁻ (ω : Ω), f n ω ∂μ) * ∫⁻ (ω : Ω), T.indicator (fun x ↦ c) ω ∂μ) →
          ∫⁻ (ω : Ω), (fun x ↦ ⨆ n, f n x) ω * T.indicator (fun x ↦ c) ω ∂μ =
            (∫⁻ (ω : Ω), (fun x ↦ ⨆ n, f n x) ω ∂μ) * ∫⁻ (ω : Ω), T.indicator (fun x ↦ c) ω ∂μ
Module: Mathlib.Probability.Independence.Kernel.IndepFun

Goal state before:
pp: case mpr
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 : ι), i ∈ S ∨ i ∈ T → f i x ∈ sets_s' i ∩ sets_t' i
⊢ (∀ i ∈ S, f i x ∈ sets_s' i) ∧ ∀ i ∈ T, f i x ∈ sets_t' i

Tactic:
· exact ⟨fun i hi => (h i (Or.inl hi)).1, fun i hi => (h i (Or.inr hi)).2⟩

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_3
X : ι → Ω → ℝ
s : Finset ι
hs : ∀ i ∈ s, MemLp (X i) 2 μ
h : (↑s).Pairwise fun i j ↦ X i ⟂ᵢ[μ] X j
⊢ Var[∑ i ∈ s, X i; μ] = ∑ i ∈ s, Var[X i; μ]

Tactic:
by_cases h'' : ∀ i ∈ s, X i =ᵐ[μ] 0

Goal state after:
case pos
Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
ι : Type u_3
X : ι → Ω → ℝ
s : Finset ι
hs : ∀ i ∈ s, MemLp (X i) 2 μ
h : (↑s).Pairwise fun i j ↦ X i ⟂ᵢ[μ] X j
h'' : ∀ i ∈ s, X i =ᵐ[μ] 0
⊢ Var[∑ i ∈ s, X i; μ] = ∑ i ∈ s, Var[X i; μ]

case neg
Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
ι : Type u_3
X : ι → Ω → ℝ
s : Finset ι
hs : ∀ i ∈ s, MemLp (X i) 2 μ
h : (↑s).Pairwise fun i j ↦ X i ⟂ᵢ[μ] X j
h'' : ¬∀ i ∈ s, X i =ᵐ[μ] 0
⊢ Var[∑ i ∈ s, X i; μ] = ∑ i ∈ s, Var[X i; μ]
Module: Mathlib.Probability.Moments.Variance

Goal state before:
pp: case pos
Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
ι : Type u_3
X : ι → Ω → ℝ
s : Finset ι
hs : ∀ i ∈ s, MemLp (X i) 2 μ
h : (↑s).Pairwise fun i j ↦ X i ⟂ᵢ[μ] X j
h'' : ∀ i ∈ s, X i =ᵐ[μ] 0
⊢ ∑ i ∈ s, X i =ᵐ[μ] 0

Tactic:
have := fun (i : s) ↦ h'' i.1 i.2

Goal state after:
case pos
Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
ι : Type u_3
X : ι → Ω → ℝ
s : Finset ι
hs : ∀ i ∈ s, MemLp (X i) 2 μ
h : (↑s).Pairwise fun i j ↦ X i ⟂ᵢ[μ] X j
h'' : ∀ i ∈ s, X i =ᵐ[μ] 0
this : ∀ (i : ↥s), X ↑i =ᵐ[μ] 0
⊢ ∑ i ∈ s, X i =ᵐ[μ] 0
Module: Mathlib.Probability.HasLaw

Goal state before:
pp: Ω : Type u_1
𝓧 : Type u_2
mΩ : MeasurableSpace Ω
m𝓧 : MeasurableSpace 𝓧
μ : Measure 𝓧
P : Measure Ω
X : Ω → 𝓧
hX : HasLaw X μ P
f : 𝓧 → ℝ≥0∞
hf : AEMeasurable f μ
⊢ ∫⁻ (ω : Ω), f (X ω) ∂P = ∫⁻ (x : 𝓧), f x ∂μ

Tactic:
by
  rw [← hX.map_eq, lintegral_map' _ hX.aemeasurable]
  rwa [hX.map_eq]

Goal state after:
Module: Mathlib.Probability.IdentDistrib

Goal state before:
pp: case neg
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✝ : OpensMeasurableSpace γ
h : IdentDistrib f g μ ν
p : ℝ≥0∞
h0 : ¬p = 0
h_top : ¬p = ∞
⊢ eLpNorm f p μ = eLpNorm g p ν

Tactic:
simp only [eLpNorm_eq_eLpNorm' h0 h_top, eLpNorm', one_div]

Goal state after:
case neg
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✝ : OpensMeasurableSpace γ
h : IdentDistrib f g μ ν
p : ℝ≥0∞
h0 : ¬p = 0
h_top : ¬p = ∞
⊢ (∫⁻ (a : α), ‖f a‖ₑ ^ p.toReal ∂μ) ^ p.toReal⁻¹ = (∫⁻ (a : β), ‖g a‖ₑ ^ p.toReal ∂ν) ^ p.toReal⁻¹
Module: Mathlib.MeasureTheory.Function.ConvergenceInDistribution

Goal state before:
pp: ι : Type u_1
E : Type u_2
Ω' : Type u_3
Ω'' : Type u_4
m' : MeasurableSpace Ω'
μ' : Measure Ω'
inst✝⁵ : IsProbabilityMeasure μ'
m'' : MeasurableSpace Ω''
μ'' : Measure Ω''
inst✝⁴ : IsProbabilityMeasure μ''
mE : MeasurableSpace E
l : Filter ι
inst✝³ : SeminormedAddCommGroup E
inst✝² : SecondCountableTopology E
inst✝¹ : BorelSpace E
X : ι → Ω'' → E
inst✝ : l.IsCountablyGenerated
Y : ι → Ω'' → E
Z : Ω' → E
hXZ : TendstoInDistribution X l Z (fun x ↦ μ'') μ'
hXY : TendstoInMeasure μ'' (Y - X) l 0
hY : ∀ (i : ι), AEMeasurable (Y i) μ''
hZ : AEMeasurable Z μ'
hX : ∀ (i : ι), AEMeasurable (X i) μ''
hE : Nonempty E
x₀ : E := hE.some
F : E → ℝ
M : ℝ
hF_bounded : ∀ (x y : E), dist (F x) (F y) ≤ M
L : NNReal
hF_lip : LipschitzWith L F
hF_cont : Continuous[PseudoMetricSpace.toUniformSpace.toTopologicalSpace, _] F
hL : 0 < L
this : ∀ ε > 0, ∀ᶠ (n : ι) in l, |∫ (ω : E), F ω ∂Measure.map (Y n) μ'' - ∫ (ω : E), F ω ∂Measure.map Z μ'| < ↑L * ε
⊢ ∀ ε > 0, ∀ᶠ (x : ι) in l, |∫ (ω : E), F ω ∂Measure.map (Y x) μ'' - ∫ (ω : E), F ω ∂Measure.map Z μ'| < ε

Tactic:
by
    intro ε hε
    convert! this (ε / L) (by positivity)
    field_simp

Goal state after:
Module: Mathlib.MeasureTheory.Function.Intersectivity

Goal state before:
pp: α : Type u_2
inst✝¹ : MeasurableSpace α
μ : Measure α
inst✝ : IsFiniteMeasure μ
r : ℝ≥0∞
s : ℕ → Set α
hs : ∀ (n : ℕ), MeasurableSet (s n)
hr₀ : r ≠ 0
hr : ∀ (n : ℕ), r ≤ μ (s n)
M : (α → ℝ) → Set α := fun f ↦ {x | eLpNormEssSup f μ < ↑‖f x‖₊}
N : Set α := ⋃ u, M ((⋂ n ∈ u, s n).indicator 1)
hN₀ : μ N = 0
u : Finset ℕ
x : α
hx : x ∈ (⋂ n ∈ u, s n) \ N
hu : μ (⋂ n ∈ u, s n) = 0
⊢ (⋂ n ∈ u, s n).indicator 1 =ᵐ[μ] 0

Tactic:
indicator_ae_eq_zero,

Goal state after:
α : Type u_2
inst✝¹ : MeasurableSpace α
μ : Measure α
inst✝ : IsFiniteMeasure μ
r : ℝ≥0∞
s : ℕ → Set α
hs : ∀ (n : ℕ), MeasurableSet (s n)
hr₀ : r ≠ 0
hr : ∀ (n : ℕ), r ≤ μ (s n)
M : (α → ℝ) → Set α := fun f ↦ {x | eLpNormEssSup f μ < ↑‖f x‖₊}
N : Set α := ⋃ u, M ((⋂ n ∈ u, s n).indicator 1)
hN₀ : μ N = 0
u : Finset ℕ
x : α
hx : x ∈ (⋂ n ∈ u, s n) \ N
hu : μ (⋂ n ∈ u, s n) = 0
⊢ μ ((⋂ n ∈ u, s n) ∩ support 1) = 0
Module: Mathlib.Probability.Process.Filtration

Goal state before:
pp: case pos
Ω : Type u_1
ι : Type u_2
m : MeasurableSpace Ω
inst✝ : PartialOrder ι
𝓕 : Filtration ι m
this✝ : TopologicalSpace ι := Preorder.topology ι
this : OrderTopology ι
i : ι
hne : (𝓝[>] i).NeBot
⊢ ↑𝓕 i ≤ ↑𝓕₊ i

Tactic:
rw [rightCont_eq_of_neBot_nhdsGT]

Goal state after:
case pos
Ω : Type u_1
ι : Type u_2
m : MeasurableSpace Ω
inst✝ : PartialOrder ι
𝓕 : Filtration ι m
this✝ : TopologicalSpace ι := Preorder.topology ι
this : OrderTopology ι
i : ι
hne : (𝓝[>] i).NeBot
⊢ ↑𝓕 i ≤ ⨅ j, ⨅ (_ : j > i), ↑𝓕 j
Module: Mathlib.MeasureTheory.Function.UnifTight

Goal state before:
pp: case neg
α : Type u_1
β : Type u_2
m : MeasurableSpace α
μ : Measure α
inst✝ : NormedAddCommGroup β
p : ℝ≥0∞
hp_top : p ≠ ∞
n : ℕ
h : ∀ {f : Fin n → α → β}, (∀ (i : Fin n), MemLp (f i) p μ) → UnifTight f p μ
f : Fin (n + 1) → α → β
hfLp : ∀ (i : Fin (n + 1)), MemLp (f i) p μ
ε : ℝ≥0
hε : 0 < ε
hε_top : ¬↑ε = ∞
g : Fin n → α → β := fun k ↦ f k.castSucc
hgLp : ∀ (i : Fin n), MemLp (g i) p μ
S : Set α
hμS : μ S ≠ ∞
hFε : ∀ (i : Fin n), eLpNorm (Sᶜ.indicator (g i)) p μ ≤ ↑ε
s : Set α
left✝ : MeasurableSet s
hμs : μ s < ∞
hfε : eLpNorm (sᶜ.indicator (f (Fin.last n))) p μ < ↑ε
hi : n ≤ ↑(Fin.last n)
⊢ eLpNorm ((s ∪ S)ᶜ.indicator (f (Fin.last n))) p μ ≤ ↑ε

Tactic:
rw [compl_union, inter_comm, ← indicator_indicator]

Goal state after:
case neg
α : Type u_1
β : Type u_2
m : MeasurableSpace α
μ : Measure α
inst✝ : NormedAddCommGroup β
p : ℝ≥0∞
hp_top : p ≠ ∞
n : ℕ
h : ∀ {f : Fin n → α → β}, (∀ (i : Fin n), MemLp (f i) p μ) → UnifTight f p μ
f : Fin (n + 1) → α → β
hfLp : ∀ (i : Fin (n + 1)), MemLp (f i) p μ
ε : ℝ≥0
hε : 0 < ε
hε_top : ¬↑ε = ∞
g : Fin n → α → β := fun k ↦ f k.castSucc
hgLp : ∀ (i : Fin n), MemLp (g i) p μ
S : Set α
hμS : μ S ≠ ∞
hFε : ∀ (i : Fin n), eLpNorm (Sᶜ.indicator (g i)) p μ ≤ ↑ε
s : Set α
left✝ : MeasurableSet s
hμs : μ s < ∞
hfε : eLpNorm (sᶜ.indicator (f (Fin.last n))) p μ < ↑ε
hi : n ≤ ↑(Fin.last n)
⊢ eLpNorm (Sᶜ.indicator (sᶜ.indicator (f (Fin.last n)))) p μ ≤ ↑ε
Module: Mathlib.Topology.Algebra.Order.Support

Goal state before:
pp: X : Type u_1
M : Type u_2
inst✝² : TopologicalSpace X
inst✝¹ : One M
inst✝ : SemilatticeSup M
f g : X → M
hf : HasCompactMulSupport f
hg : HasCompactMulSupport g
⊢ HasCompactMulSupport (f ⊔ g)

Tactic:
apply IsCompact.of_isClosed_subset (IsCompact.union hf hg) (isClosed_mulTSupport _)

Goal state after:
X : Type u_1
M : Type u_2
inst✝² : TopologicalSpace X
inst✝¹ : One M
inst✝ : SemilatticeSup M
f g : X → M
hf : HasCompactMulSupport f
hg : HasCompactMulSupport g
⊢ mulTSupport (f ⊔ g) ⊆ mulTSupport f ∪ mulTSupport g