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

Goal state before:
pp: α : Type u_1
β : Type u_2
ι : Type u_3
m : MeasurableSpace α
μ : Measure α
inst✝ : NormedAddCommGroup β
p : ℝ≥0∞
hp : 1 ≤ p
hp' : p ≠ ∞
f : ι → α → β
hf : ∀ (i : ι), StronglyMeasurable (f i)
h : ∀ (ε : ℝ), 0 < ε → ∃ C, 0 < C ∧ ∀ (i : ι), eLpNorm ({x | C ≤ ‖f i x‖₊}.indicator (f i)) p μ ≤ ENNReal.ofReal ε
hpzero : p ≠ 0
hμ : ¬μ univ = 0
ε : ℝ
hε : 0 < ε
C : ℝ≥0
hCpos : 0 < C
hC : ∀ (i : ι), eLpNorm ({x | C ≤ ‖f i x‖₊}.indicator (f i)) p μ ≤ ENNReal.ofReal (ε / 2)
i : ι
s : Set α
hs : MeasurableSet s
hμs : μ s ≤ ENNReal.ofReal ((ε / (2 * ↑C)) ^ p.toReal)
hμs' : ¬μ s = 0
⊢ ENNReal.ofReal (ε / 2) + ENNReal.ofReal (ε / 2) ≤ ENNReal.ofReal ε

Tactic:
by
      rw [← ENNReal.ofReal_add (half_pos hε).le (half_pos hε).le, add_halves]

Goal state after:
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✝² : NormedAddCommGroup E
inst✝¹ : NormedSpace ℝ E
inst✝ : CompleteSpace E
f : α → E
p : ℝ≥0∞
hp : 1 ≤ p
hf : MemLp f p μ
⊢ lpNorm μ[f | m] p μ ≤ lpNorm f p μ

Tactic:
by_cases NeZero μ
  · have hp' : 0 < p := zero_lt_one.trans_le hp
    by_cases! hm : ¬ m ≤ m0
    · simp [condExp_of_not_le hm]
    by_cases! hsig : ¬ SigmaFinite (μ.trim hm)
    · simp [condExp_of_not_sigmaFinite hm hsig]
    · by_cases! hpt : p ≠ ⊤
      · rw [lpNorm_eq_integral_norm_rpow_toReal hp'.ne.symm hpt hf.1,
          lpNorm_eq_integral_norm_rpow_toReal hp'.ne.symm hpt integrable_condExp.1]
        gcongr ?_ ^ ?_
        have : 1 ≤ p.toReal := by
          rwa [← ENNReal.toReal_one, ENNReal.toReal_le_toReal ENNReal.one_ne_top hpt]
        exact integral_norm_condExp_rpow_le this <|
          (integrable_norm_rpow_iff hf.1 hp'.ne.symm hpt).2 hf
      · by_cases! h : MemLp μ[f | m] ⊤ μ
        · simp_all only [lpNorm_exponent_top_eq_essSup]
          exact hf.essSup_norm_condExp_le_essSup_norm
        · simp_all
  · simp_all [not_neZero]

Goal state after:
Module: Mathlib.MeasureTheory.Function.ConditionalExpectation.Real

Goal state before:
pp: case pos
α : Type u_1
m m0 : MeasurableSpace α
μ : Measure α
E : Type u_2
inst✝² : NormedAddCommGroup E
inst✝¹ : NormedSpace ℝ E
inst✝ : CompleteSpace E
f : α → E
p : ℝ≥0∞
hp : 1 ≤ p
hf : MemLp f p μ
hp' : 0 < p
hpt : p ≠ ∞
⊢ MemLp μ[f | m] p μ

Tactic:
rw [← integrable_norm_rpow_iff integrable_condExp.1 hp'.ne.symm hpt]

Goal state after:
case pos
α : Type u_1
m m0 : MeasurableSpace α
μ : Measure α
E : Type u_2
inst✝² : NormedAddCommGroup E
inst✝¹ : NormedSpace ℝ E
inst✝ : CompleteSpace E
f : α → E
p : ℝ≥0∞
hp : 1 ≤ p
hf : MemLp f p μ
hp' : 0 < p
hpt : p ≠ ∞
⊢ Integrable (fun x ↦ ‖μ[f | m] x‖ ^ p.toReal) μ
Module: Mathlib.MeasureTheory.Function.UniformIntegrable

Goal state before:

Tactic:
C • (δ : ℝ≥0∞) ^ (1 / p.toReal) ≤ C • μ { x | C ≤ ‖f (ℐ C) x‖₊ } ^ (1 / p.toReal) := by
          rw [ENNReal.smul_def, ENNReal.smul_def, smul_eq_mul, smul_eq_mul]
          simp_rw [ENNReal.ofReal_coe_nnreal] at hℐ
          refine mul_le_mul' le_rfl
            (ENNReal.rpow_le_rpow (hℐ C).le (one_div_nonneg.2 ENNReal.toReal_nonneg))
        _ ≤ eLpNorm ({ x | C ≤ ‖f (ℐ C) x‖₊ }.indicator (f (ℐ C))) p μ := by
          refine le_eLpNorm_of_bddBelow hp hp' _
            (measurableSet_le measurable_const (hf _).nnnorm.measurable)
            (Eventually.of_forall fun x hx => ?_)
          rwa [nnnorm_indicator_eq_indicator_nnnorm, Set.indicator_of_mem hx]
        _ ≤ eLpNorm (f (ℐ C)) p μ := eLpNorm_indicator_le _

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
p : ℝ≥0 × FiniteMeasure Ω
g : Ω →ᵇ ℝ
⊢ Tendsto (fun i ↦ ∫ (x : Ω), g x ∂↑(i.1 • i.2)) (𝓝 p) (𝓝 (∫ (x : Ω), g x ∂↑((fun p ↦ p.1 • p.2) p)))

Tactic:
have A : Tendsto (fun (i : ℝ≥0 × FiniteMeasure Ω) ↦ i.1) (𝓝 p) (𝓝 (p.1)) := by
    rw [nhds_prod_eq]
    exact tendsto_fst

Goal state after:
Ω : Type u_1
inst✝² : MeasurableSpace Ω
inst✝¹ : TopologicalSpace Ω
inst✝ : OpensMeasurableSpace Ω
p : ℝ≥0 × FiniteMeasure Ω
g : Ω →ᵇ ℝ
A : Tendsto (fun i ↦ i.1) (𝓝 p) (𝓝 p.1)
⊢ Tendsto (fun i ↦ ∫ (x : Ω), g x ∂↑(i.1 • i.2)) (𝓝 p) (𝓝 (∫ (x : Ω), g x ∂↑((fun p ↦ p.1 • p.2) p)))
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)
s' : Set (Set Ω)
_mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
u : Set ι
h : ∃ n ∈ u, IndepSets (s n) s' κ μ
t1 t2 : Set Ω
ht1 : t1 ∈ ⋂ n ∈ u, s n
ht2 : t2 ∈ s'
⊢ ∀ᵐ (a : α) ∂μ, (κ a) (t1 ∩ t2) = (κ a) t1 * (κ a) t2

Tactic:
rcases h with ⟨n, hn, h⟩

Goal state after:
α : Type u_1
Ω : Type u_2
ι : Type u_3
_mα : MeasurableSpace α
s : ι → Set (Set Ω)
s' : Set (Set Ω)
_mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
u : Set ι
t1 t2 : Set Ω
ht1 : t1 ∈ ⋂ n ∈ u, s n
ht2 : t2 ∈ s'
n : ι
hn : n ∈ u
h : IndepSets (s n) s' κ μ
⊢ ∀ᵐ (a : α) ∂μ, (κ a) (t1 ∩ t2) = (κ a) t1 * (κ a) t2
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
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)

Tactic:
Set.preimage_comp

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, f i ⁻¹' g i ⁻¹' s i) = ∏ x ∈ t, (κ a) (f x ⁻¹' g x ⁻¹' s x)
Module: Mathlib.Probability.Independence.Basic

Goal state before:
pp: Ω : Type u_7
mΩ : MeasurableSpace Ω
μ : Measure Ω
M : Type u_10
inst✝² : Monoid M
inst✝¹ : MeasurableSpace M
inst✝ : MeasurableMul₂ M
f g : Ω → M
hf : AEMeasurable f μ
hg : AEMeasurable g μ
σf : SigmaFinite (Measure.map f μ)
σg : SigmaFinite (Measure.map g μ)
hfg : f ⟂ᵢ[μ] g
| f * g

Tactic:
change (fun x ↦ x.1 * x.2) ∘ (fun ω ↦ (f ω, g ω))

Goal state after:
Ω : Type u_7
mΩ : MeasurableSpace Ω
μ : Measure Ω
M : Type u_10
inst✝² : Monoid M
inst✝¹ : MeasurableSpace M
inst✝ : MeasurableMul₂ M
f g : Ω → M
hf : AEMeasurable f μ
hg : AEMeasurable g μ
σf : SigmaFinite (Measure.map f μ)
σg : SigmaFinite (Measure.map g μ)
hfg : f ⟂ᵢ[μ] g
| (fun x ↦ x.1 * x.2) ∘ fun ω ↦ (f ω, g ω)
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
s : ι → Set Ω
hsm : ∀ (n : ι), MeasurableSet (s n)
hs : iIndepSet s κ μ
S T : Set ι
hST : Disjoint S T
hμ : μ ≠ 0
η : Kernel α Ω
η_eq : ⇑κ =ᵐ[μ] ⇑η
hη : IsMarkovKernel η
⊢ Indep (generateFrom (piiUnionInter (fun k ↦ {s k}) S)) (generateFrom (piiUnionInter (fun k ↦ {s k}) T)) η μ

Tactic:
refine
    IndepSets.indep'
      (fun t ht => generateFrom_piiUnionInter_le _ ?_ _ _ (measurableSet_generateFrom ht))
      (fun t ht => generateFrom_piiUnionInter_le _ ?_ _ _ (measurableSet_generateFrom ht)) ?_ ?_ ?_

Goal state after:
case inr.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
s : ι → Set Ω
hsm : ∀ (n : ι), MeasurableSet (s n)
hs : iIndepSet s κ μ
S T : Set ι
hST : Disjoint S T
hμ : μ ≠ 0
η : Kernel α Ω
η_eq : ⇑κ =ᵐ[μ] ⇑η
hη : IsMarkovKernel η
t : Set Ω
ht : t ∈ piiUnionInter (fun k ↦ {s k}) S
⊢ ∀ (n : ι), generateFrom {s n} ≤ _mΩ

case inr.refine_2
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 Ω
hsm : ∀ (n : ι), MeasurableSet (s n)
hs : iIndepSet s κ μ
S T : Set ι
hST : Disjoint S T
hμ : μ ≠ 0
η : Kernel α Ω
η_eq : ⇑κ =ᵐ[μ] ⇑η
hη : IsMarkovKernel η
t : Set Ω
ht : t ∈ piiUnionInter (fun k ↦ {s k}) T
⊢ ∀ (n : ι), generateFrom {s n} ≤ _mΩ

case inr.refine_3
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 Ω
hsm : ∀ (n : ι), MeasurableSet (s n)
hs : iIndepSet s κ μ
S T : Set ι
hST : Disjoint S T
hμ : μ ≠ 0
η : Kernel α Ω
η_eq : ⇑κ =ᵐ[μ] ⇑η
hη : IsMarkovKernel η
⊢ IsPiSystem (piiUnionInter (fun k ↦ {s k}) S)

case inr.refine_4
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 Ω
hsm : ∀ (n : ι), MeasurableSet (s n)
hs : iIndepSet s κ μ
S T : Set ι
hST : Disjoint S T
hμ : μ ≠ 0
η : Kernel α Ω
η_eq : ⇑κ =ᵐ[μ] ⇑η
hη : IsMarkovKernel η
⊢ IsPiSystem (piiUnionInter (fun k ↦ {s k}) T)

case inr.refine_5
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 Ω
hsm : ∀ (n : ι), MeasurableSet (s n)
hs : iIndepSet s κ μ
S T : Set ι
hST : Disjoint S T
hμ : μ ≠ 0
η : Kernel α Ω
η_eq : ⇑κ =ᵐ[μ] ⇑η
hη : IsMarkovKernel η
⊢ IndepSets (piiUnionInter (fun k ↦ {s k}) S) (piiUnionInter (fun k ↦ {s k}) T) η μ
Module: Mathlib.Probability.Independence.Kernel.Indep

Goal state before:
pp: α : Type u_1
ι : Type u_3
_mα : MeasurableSpace α
Ω : Type u_4
m : ι → MeasurableSpace Ω
m' m0 : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
inst✝ : IsZeroOrMarkovKernel κ
h_indep : ∀ (i : ι), Indep (m i) m' κ μ
h_le : ∀ (i : ι), m i ≤ m0
h_le' : m' ≤ m0
hm : Directed (fun x1 x2 ↦ x1 ≤ x2) m
p : ι → Set (Set Ω) := fun n ↦ {t | MeasurableSet t}
hp : ∀ (n : ι), IsPiSystem (p n)
h_gen_n : ∀ (n : ι), m n = generateFrom (p n)
hp_supr_pi : IsPiSystem (⋃ n, p n)
p' : Set (Set Ω) := {t | MeasurableSet t}
hp'_pi : IsPiSystem p'
h_gen' : m' = generateFrom p'
i : ι
| Indep (m i) m' κ μ

Tactic:
h_gen_n i,

Goal state after:
α : Type u_1
ι : Type u_3
_mα : MeasurableSpace α
Ω : Type u_4
m : ι → MeasurableSpace Ω
m' m0 : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
inst✝ : IsZeroOrMarkovKernel κ
h_indep : ∀ (i : ι), Indep (m i) m' κ μ
h_le : ∀ (i : ι), m i ≤ m0
h_le' : m' ≤ m0
hm : Directed (fun x1 x2 ↦ x1 ≤ x2) m
p : ι → Set (Set Ω) := fun n ↦ {t | MeasurableSet t}
hp : ∀ (n : ι), IsPiSystem (p n)
h_gen_n : ∀ (n : ι), m n = generateFrom (p n)
hp_supr_pi : IsPiSystem (⋃ n, p n)
p' : Set (Set Ω) := {t | MeasurableSet t}
hp'_pi : IsPiSystem p'
h_gen' : m' = generateFrom p'
i : ι
| Indep (generateFrom (p i)) m' κ μ
Module: Mathlib.Probability.Independence.Integration

Goal state before:
pp: case iSup
Ω : Type u_1
f : Ω → ℝ≥0∞
Mf Mg mΩ : MeasurableSpace Ω
μ : Measure Ω
hMf : Mf ≤ mΩ
hMg : Mg ≤ mΩ
h_ind : Indep Mf Mg μ
h_meas_f : Measurable f
h_measM_f : Measurable f
⊢ ∀ ⦃f_1 : ℕ → Ω → ℝ≥0∞⦄,
    (∀ (n : ℕ), Measurable (f_1 n)) →
      Monotone f_1 →
        (∀ (n : ℕ), ∫⁻ (ω : Ω), f ω * f_1 n ω ∂μ = (∫⁻ (ω : Ω), f ω ∂μ) * ∫⁻ (ω : Ω), f_1 n ω ∂μ) →
          ∫⁻ (ω : Ω), f ω * (fun x ↦ ⨆ n, f_1 n x) ω ∂μ = (∫⁻ (ω : Ω), f ω ∂μ) * ∫⁻ (ω : Ω), (fun x ↦ ⨆ n, f_1 n x) ω ∂μ

Tactic:
intro f' h_meas_f' h_mono_f' h_ind_f'
    have h_measM_f' : ∀ n, Measurable (f' n) := fun n => (h_meas_f' n).mono hMg le_rfl
    simp_rw [mul_iSup]
    rw [lintegral_iSup, lintegral_iSup h_measM_f' h_mono_f', mul_iSup]
    · simp_rw [← h_ind_f']
    · exact fun n => h_measM_f.mul (h_measM_f' n)
    · exact fun n m (h_le : n ≤ m) a => mul_le_mul_right (h_mono_f' h_le a) _

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

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

Tactic:
by
  convert! covariance_sum_left' hX hY
  simp

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

Goal state before:
pp: case hfm
Ω : Type u_1
mΩ : MeasurableSpace Ω
X Y : Ω → ℝ
Ω' : Type u_2
mΩ' : MeasurableSpace Ω'
μ : Measure Ω'
Z : Ω' → Ω
hX : AEStronglyMeasurable X (Measure.map Z μ)
hY : AEStronglyMeasurable Y (Measure.map Z μ)
hZ : AEMeasurable Z μ
⊢ AEStronglyMeasurable (fun ω ↦ (X ω - ∫ (x : Ω), X x ∂Measure.map Z μ) * (Y ω - ∫ (x : Ω), Y x ∂Measure.map Z μ))
    (Measure.map Z μ)

Tactic:
exact (hX.sub aestronglyMeasurable_const).mul (hY.sub aestronglyMeasurable_const)

Goal state after:
Module: Mathlib.Probability.IdentDistrib

Goal state before:
pp: α : Type u_1
β : Type u_2
γ : Type u_3
inst✝² : MeasurableSpace α
inst✝¹ : MeasurableSpace β
inst✝ : MeasurableSpace γ
μ : Measure α
ν : Measure β
f : α → γ
g : β → γ
κ : Measure γ
h₀ : IdentDistrib f g μ ν
h₁ : HasLaw f κ μ
⊢ Measure.map g ν = κ

Tactic:
by simp [h₀.map_eq, ← h₁.map_eq]

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)
⊢ IndepFun (fun a i ↦ f (↑i) a) (fun a i ↦ f (↑i) a) κ μ

Tactic:
have h : IndepFun (fun a (i : S) ↦ (hf_meas i).mk (f i) a)
      (fun a (i : T) ↦ (hf_meas i).mk (f i) a) κ μ := by
    refine iIndepFun.indepFun_finset S T hST ?_ fun i ↦ (hf_meas i).measurable_mk
    exact iIndepFun.congr' hf_Indep fun i ↦ Measure.ae_ae_of_ae_comp (hf_meas i).ae_eq_mk

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
⊢ IndepFun (fun a i ↦ f (↑i) a) (fun a i ↦ f (↑i) a) κ μ
Module: Mathlib.MeasureTheory.Function.FactorsThrough

Goal state before:
pp: X : Type u_1
Y : Type u_2
Z : Type u_3
mY : MeasurableSpace Y
f : X → Y
g : X → Z
inst✝¹ : MeasurableSpace Z
inst✝ : MeasurableSingletonClass Z
hg : Measurable g
x₁ x₂ : X
h : f x₁ = f x₂
s : Set Y
hs : f ⁻¹' s = g ⁻¹' {g x₂}
⊢ x₁ ∈ f ⁻¹' s

Tactic:
mem_preimage,

Goal state after:
X : Type u_1
Y : Type u_2
Z : Type u_3
mY : MeasurableSpace Y
f : X → Y
g : X → Z
inst✝¹ : MeasurableSpace Z
inst✝ : MeasurableSingletonClass Z
hg : Measurable g
x₁ x₂ : X
h : f x₁ = f x₂
s : Set Y
hs : f ⁻¹' s = g ⁻¹' {g x₂}
⊢ f x₁ ∈ s
Module: Mathlib.MeasureTheory.Function.FactorsThrough

Goal state before:
pp: X : Type u_1
Y : Type u_2
Z : Type u_3
mY : MeasurableSpace Y
f : X → Y
g : X → Z
inst✝¹ : MeasurableSpace Z
inst✝ : MeasurableSingletonClass Z
hg : Measurable g
x₁ x₂ : X
h : f x₁ = f x₂
s : Set Y
hs : f ⁻¹' s = g ⁻¹' {g x₂}
⊢ x₂ ∈ g ⁻¹' {g x₂}

Tactic:
mem_preimage,

Goal state after:
X : Type u_1
Y : Type u_2
Z : Type u_3
mY : MeasurableSpace Y
f : X → Y
g : X → Z
inst✝¹ : MeasurableSpace Z
inst✝ : MeasurableSingletonClass Z
hg : Measurable g
x₁ x₂ : X
h : f x₁ = f x₂
s : Set Y
hs : f ⁻¹' s = g ⁻¹' {g x₂}
⊢ g x₂ ∈ {g x₂}
Module: Mathlib.MeasureTheory.Function.ConvergenceInDistribution

Goal state before:
pp: case h₁
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
ε : ℝ
hε : ε > 0
n : ι
h_int_Y : Integrable (fun x ↦ F (Y n x)) μ''
h_int_X : Integrable (fun x ↦ F (X n x)) μ''
h_int_sub : Integrable (fun a ↦ ‖F (Y n a) - F (X n a)‖) μ''
⊢ |∫ (x : Ω''), F (Y n x) ∂μ'' - ∫ (x : Ω''), F (X n x) ∂μ''| ≤
    ↑L * (ε / 2) + M * μ''.real {ω | ε / 2 ≤ ‖Y n ω - X n ω‖}

Tactic:
← integral_sub h_int_Y h_int_X,

Goal state after:
case h₁
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
ε : ℝ
hε : ε > 0
n : ι
h_int_Y : Integrable (fun x ↦ F (Y n x)) μ''
h_int_X : Integrable (fun x ↦ F (X n x)) μ''
h_int_sub : Integrable (fun a ↦ ‖F (Y n a) - F (X n a)‖) μ''
⊢ |∫ (a : Ω''), F (Y n a) - F (X n a) ∂μ''| ≤ ↑L * (ε / 2) + M * μ''.real {ω | ε / 2 ≤ ‖Y n ω - X n ω‖}
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
ε : ℝ
hε : ε > 0
n : ι
h_int_Y : Integrable (fun x ↦ F (Y n x)) μ''
h_int_X : Integrable (fun x ↦ F (X n x)) μ''
h_int_sub : Integrable (fun a ↦ ‖F (Y n a) - F (X n a)‖) μ''
⊢ ∫ (a : Ω''), ‖F (Y n a) - F (X n a)‖ ∂μ'' =
    ∫ (a : Ω'') in {x | ‖Y n x - X n x‖ < ε / 2}, ‖F (Y n a) - F (X n a)‖ ∂μ'' +
      ∫ (a : Ω'') in {x | ε / 2 ≤ ‖Y n x - X n x‖}, ‖F (Y n a) - F (X n a)‖ ∂μ''

Tactic:
by
      symm
      simp_rw [← not_lt]
      refine integral_add_compl₀ ?_ h_int_sub
      exact nullMeasurableSet_lt (by fun_prop) (by fun_prop)

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

Goal state before:
pp: case intro
α : Type u_1
Ω : Type u_2
ι : Type u_3
β : Type u_4
mα : MeasurableSpace α
mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
mβ : MeasurableSpace β
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)) κ μ
hf : ∀ i ∈ s, MeasurableSet (f i)
hy : ∀ᵐ (a : α) ∂μ, ∀ i ∉ s, (κ a) (Y i ⁻¹' t i) ≠ 0
ht : ∀ (i : ι), MeasurableSet (t i)
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'
hYt : ∀ (i : ι), MeasurableSet (Y i ⁻¹' t i)
⊢ ∀ᵐ (a : α) ∂μ, (κ a)[⋂ i ∈ s, f i | ⋂ i, Y i ⁻¹' t i] = ∏ i ∈ s, (κ a)[f i | Y i ⁻¹' t i]

Tactic:
have hg i : MeasurableSet[(mα.prod mβ).comap fun ω ↦ (X i ω, Y i ω)] (g i) := by
    by_cases hi : i ∈ s <;> simp only [hi, ↓reduceIte, g]
    · obtain ⟨A, hA, hA'⟩ := hf i hi
      exact (hYt _).inter ⟨A ×ˢ .univ, hA.prod .univ, by ext; simp [← hA']⟩
    · exact hYt _

Goal state after:
case intro
α : Type u_1
Ω : Type u_2
ι : Type u_3
β : Type u_4
mα : MeasurableSpace α
mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
mβ : MeasurableSpace β
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)) κ μ
hf : ∀ i ∈ s, MeasurableSet (f i)
hy : ∀ᵐ (a : α) ∂μ, ∀ i ∉ s, (κ a) (Y i ⁻¹' t i) ≠ 0
ht : ∀ (i : ι), MeasurableSet (t i)
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'
hYt : ∀ (i : ι), MeasurableSet (Y i ⁻¹' t i)
hg : ∀ (i : ι), MeasurableSet (g i)
⊢ ∀ᵐ (a : α) ∂μ, (κ a)[⋂ i ∈ s, f i | ⋂ i, Y i ⁻¹' t i] = ∏ i ∈ s, (κ a)[f i | Y i ⁻¹' t i]
Module: Mathlib.Probability.Process.Filtration

Goal state before:
pp: Ω : Type u_1
ι : Type u_2
m : MeasurableSpace Ω
β : ι → Type u_3
inst✝³ : (i : ι) → TopologicalSpace (β i)
inst✝² : ∀ (i : ι), MetrizableSpace (β i)
mβ : (i : ι) → MeasurableSpace (β i)
inst✝¹ : ∀ (i : ι), BorelSpace (β i)
inst✝ : Preorder ι
u : (i : ι) → Ω → β i
hum : ∀ (i : ι), StronglyMeasurable (u i)
i : ι
⊢ ↑(natural u hum) i = MeasurableSpace.comap (fun ω j ↦ u (↑j) ω) inferInstance

Tactic:
simp_rw [natural, MeasurableSpace.comap_process_pi, iSup_subtype']
  rfl

Goal state after:
Module: Mathlib.MeasureTheory.Function.LpSeminorm.Count

Goal state before:
pp: case refine_1
α : Type u_1
ε : Type u_2
inst✝³ : MeasurableSpace α
inst✝² : TopologicalSpace ε
inst✝¹ : ContinuousENorm ε
f : α → ε
p : ℝ≥0∞
inst✝ : Finite α
h : ∀ (i : α), ‖f i‖ₑ < ∞
this : Fintype α
⊢ ∀ (x : α), ‖f x‖ₑ ≤ ‖Finset.univ.sup fun x ↦ ‖f x‖ₑ‖ₑ

Tactic:
exact fun x ↦ Finset.le_sup (f := (‖f ·‖ₑ)) (Finset.mem_univ x)

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

Goal state before:
pp: case neg
α : Type u_1
β : Type u_2
ι : Type u_3
m : MeasurableSpace α
μ : Measure α
inst✝ : NormedAddCommGroup β
f : ι → α → β
p : ℝ≥0∞
hf : UnifTight f p μ
ε : ℝ≥0∞
hε : ε ≠ 0
hε_top : ¬ε = ∞
s : Set α
hμs : μ s ≠ ∞
hfs : ∀ (i : ι), eLpNorm (sᶜ.indicator (f i)) p μ ≤ ↑ε.toNNReal
⊢ ∀ᶠ (s : Set α) in μ.cofinite.smallSets, ∀ (i : ι), eLpNorm (s.indicator (f i)) p μ ≤ ε

Tactic:
refine (eventually_smallSets' ?_).2 ⟨sᶜ, ?_, fun i ↦ (coe_toNNReal hε_top) ▸ hfs i⟩

Goal state after:
case neg.refine_1
α : Type u_1
β : Type u_2
ι : Type u_3
m : MeasurableSpace α
μ : Measure α
inst✝ : NormedAddCommGroup β
f : ι → α → β
p : ℝ≥0∞
hf : UnifTight f p μ
ε : ℝ≥0∞
hε : ε ≠ 0
hε_top : ¬ε = ∞
s : Set α
hμs : μ s ≠ ∞
hfs : ∀ (i : ι), eLpNorm (sᶜ.indicator (f i)) p μ ≤ ↑ε.toNNReal
⊢ ∀ ⦃s t : Set α⦄,
    s ⊆ t → (∀ (i : ι), eLpNorm (t.indicator (f i)) p μ ≤ ε) → ∀ (i : ι), eLpNorm (s.indicator (f i)) p μ ≤ ε

case neg.refine_2
α : Type u_1
β : Type u_2
ι : Type u_3
m : MeasurableSpace α
μ : Measure α
inst✝ : NormedAddCommGroup β
f : ι → α → β
p : ℝ≥0∞
hf : UnifTight f p μ
ε : ℝ≥0∞
hε : ε ≠ 0
hε_top : ¬ε = ∞
s : Set α
hμs : μ s ≠ ∞
hfs : ∀ (i : ι), eLpNorm (sᶜ.indicator (f i)) p μ ≤ ↑ε.toNNReal
⊢ sᶜ ∈ μ.cofinite
Module: Mathlib.Topology.ContinuousMap.CompactlySupported

Goal state before:
pp: α : Type u_2
inst✝ : TopologicalSpace α
f g : α →C_c ℝ
x : α
⊢ (f + g).nnrealPart x ≤ (f.nnrealPart + g.nnrealPart) x

Tactic:
simpa using Real.toNNReal_add_le

Goal state after: