mathlib-initiative/mathlib-tactics huggingface dataset:
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_2
F : Filter γ
μs : γ → FiniteMeasure Ω
μ : FiniteMeasure Ω
h : ∀ (f : Ω →ᵇ ℝ≥0), Tendsto (fun i ↦ ∫⁻ (x : Ω), ↑(f x) ∂↑(μs i)) F (𝓝 (∫⁻ (x : Ω), ↑(f x) ∂↑μ))
f : Ω →ᵇ ℝ
f_pos : Ω →ᵇ ℝ≥0 := f.nnrealPart
_def_f_pos : f_pos = f.nnrealPart
f_neg : Ω →ᵇ ℝ≥0 := (-f).nnrealPart
_def_f_neg : f_neg = (-f).nnrealPart
tends_pos : Tendsto (ENNReal.toReal ∘ fun i ↦ ∫⁻ (x : Ω), ↑(f_pos x) ∂↑(μs i)) F (𝓝 (∫⁻ (x : Ω), ↑(f_pos x) ∂↑μ).toReal)
tends_neg : Tendsto (ENNReal.toReal ∘ fun i ↦ ∫⁻ (x : Ω), ↑(f_neg x) ∂↑(μs i)) F (𝓝 (∫⁻ (x : Ω), ↑(f_neg x) ∂↑μ).toReal)
aux :
  ∀ (g : Ω →ᵇ ℝ≥0),
    (ENNReal.toReal ∘ fun i ↦ ∫⁻ (x : Ω), ↑(g x) ∂↑(μs i)) = fun i ↦ (∫⁻ (x : Ω), ↑(g x) ∂↑(μs i)).toReal
⊢ Tendsto (fun i ↦ ∫ (x : Ω), ↑(f_pos x) ∂↑(μs i) - ∫ (x : Ω), ↑(f_neg x) ∂↑(μs i)) F
    (𝓝 (∫ (x : Ω), ↑(f_pos x) ∂↑μ - ∫ (x : Ω), ↑(f_neg x) ∂↑μ))

Tactic:
simp_rw [aux, BoundedContinuousFunction.toReal_lintegral_coe_eq_integral] at tends_pos tends_neg

Goal state after:
Ω : Type u_1
inst✝² : MeasurableSpace Ω
inst✝¹ : TopologicalSpace Ω
inst✝ : OpensMeasurableSpace Ω
γ : Type u_2
F : Filter γ
μs : γ → FiniteMeasure Ω
μ : FiniteMeasure Ω
h : ∀ (f : Ω →ᵇ ℝ≥0), Tendsto (fun i ↦ ∫⁻ (x : Ω), ↑(f x) ∂↑(μs i)) F (𝓝 (∫⁻ (x : Ω), ↑(f x) ∂↑μ))
f : Ω →ᵇ ℝ
f_pos : Ω →ᵇ ℝ≥0 := f.nnrealPart
_def_f_pos : f_pos = f.nnrealPart
f_neg : Ω →ᵇ ℝ≥0 := (-f).nnrealPart
_def_f_neg : f_neg = (-f).nnrealPart
aux :
  ∀ (g : Ω →ᵇ ℝ≥0),
    (ENNReal.toReal ∘ fun i ↦ ∫⁻ (x : Ω), ↑(g x) ∂↑(μs i)) = fun i ↦ (∫⁻ (x : Ω), ↑(g x) ∂↑(μs i)).toReal
tends_pos : Tendsto (fun i ↦ ∫ (x : Ω), ↑(f_pos x) ∂↑(μs i)) F (𝓝 (∫ (x : Ω), ↑(f_pos x) ∂↑μ))
tends_neg : Tendsto (fun i ↦ ∫ (x : Ω), ↑(f_neg x) ∂↑(μs i)) F (𝓝 (∫ (x : Ω), ↑(f_neg x) ∂↑μ))
⊢ Tendsto (fun i ↦ ∫ (x : Ω), ↑(f_pos x) ∂↑(μs i) - ∫ (x : Ω), ↑(f_neg x) ∂↑(μs i)) F
    (𝓝 (∫ (x : Ω), ↑(f_pos x) ∂↑μ - ∫ (x : Ω), ↑(f_neg x) ∂↑μ))
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 η : Kernel α Ω
μ : Measure α
π : ι → Set (Set Ω)
h : ⇑κ =ᵐ[μ] ⇑η
a✝² : Finset ι
a✝¹ : ι → Set Ω
a✝ : ∀ i ∈ a✝², a✝¹ i ∈ π i
⊢ (∀ᵐ (a : α) ∂μ, (κ a) (⋂ i ∈ a✝², a✝¹ i) = ∏ i ∈ a✝², (κ a) (a✝¹ i)) ↔
    ∀ᵐ (a : α) ∂μ, (η a) (⋂ i ∈ a✝², a✝¹ i) = ∏ i ∈ a✝², (η a) (a✝¹ i)

Tactic:
refine ⟨fun h' ↦ ?_, fun h' ↦ ?_⟩ <;>
  · filter_upwards [h, h'] with a ha h'a
    simpa [ha] using h'a

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

Goal state before:
pp: α : Type u_1
Ω : Type u_2
_mα : MeasurableSpace α
_mΩ : MeasurableSpace Ω
κ η : Kernel α Ω
μ : Measure α
s1 s2 : Set (Set Ω)
h : ⇑κ =ᵐ[μ] ⇑η
a✝³ a✝² : Set Ω
a✝¹ : a✝³ ∈ s1
a✝ : a✝² ∈ s2
⊢ (∀ᵐ (a : α) ∂μ, (κ a) (a✝³ ∩ a✝²) = (κ a) a✝³ * (κ a) a✝²) ↔ ∀ᵐ (a : α) ∂μ, (η a) (a✝³ ∩ a✝²) = (η a) a✝³ * (η a) a✝²

Tactic:
refine ⟨fun h' ↦ ?_, fun h' ↦ ?_⟩ <;>
  · filter_upwards [h, h'] with a ha h'a
    simpa [ha] using h'a

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

Goal state before:
pp: case inr.inl
α : Type u_1
Ω : Type u_2
_mα : MeasurableSpace α
m' _mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
inst✝ : IsZeroOrMarkovKernel κ
s t : Set Ω
a✝ : s ∈ {s | MeasurableSet s}
h : IsMarkovKernel κ
a : α
ht : t = ∅
⊢ (κ a) (s ∩ ∅) = (κ a) s * (κ a) ∅

Tactic:
Set.inter_empty,

Goal state after:
case inr.inl
α : Type u_1
Ω : Type u_2
_mα : MeasurableSpace α
m' _mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
inst✝ : IsZeroOrMarkovKernel κ
s t : Set Ω
a✝ : s ∈ {s | MeasurableSet s}
h : IsMarkovKernel κ
a : α
ht : t = ∅
⊢ (κ a) ∅ = (κ a) s * (κ a) ∅
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
rs_pos : ∀ (n : ℕ), 0 < rs n
rs_null : ∀ (n : ℕ), μ (frontier (Metric.thickening (rs n) F)) = 0
Fthicks_open : ∀ (n : ℕ), IsOpen[inst✝³] (Metric.thickening (rs n) F)
key : ∀ (n : ℕ), Tendsto (fun i ↦ (μs i) (Metric.thickening (rs n) F)) L (𝓝 (μ (Metric.thickening (rs n) F)))
ε : ℝ≥0
ε_pos : 0 < ε
μF_finite : μ F < ∞
keyB : Tendsto (fun r ↦ μ (Metric.cthickening r F)) (𝓝 0) (𝓝 (μ F))
nhds : Iio (μ F + ↑ε) ∈ 𝓝 (μ F)
m : ℕ
hm : ∀ (b : ℕ), m ≤ b → μ (Metric.cthickening (rs b) F) < μ F + ↑ε
aux : (fun i ↦ (μs i) F) ≤ᶠ[L] fun i ↦ (μs i) (Metric.thickening (rs m) F)
⊢ μ (Metric.thickening (rs m) F) ≤ μ F + ↑ε

Tactic:
apply (measure_mono (Metric.thickening_subset_cthickening (rs m) F)).trans (hm m rfl.le).le

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

Goal state before:
pp: case e'_3.a
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
h'a : (κ a) (⋂ i ∈ S, f i ⁻¹' sets i) = ∏ i ∈ S, (κ a) (f i ⁻¹' sets i)
A : ∀ i ∈ S, (κ a) (g i ⁻¹' sets i) = (κ a) (f i ⁻¹' sets i)
B : (κ a) (⋂ i ∈ S, g i ⁻¹' sets i) = (κ a) (⋂ i ∈ S, f i ⁻¹' sets i)
i : ι
hi : i ∈ S
⊢ (κ a) (g i ⁻¹' sets i) = (κ a) (f i ⁻¹' sets i)

Tactic:
exact A i hi

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
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)
⊢ ∀ (S : Finset ι) {sets : (i : ι) → Set (γ i)},
    (∀ i ∈ S, MeasurableSet (sets i)) →
      ∀ᵐ (a : α) ∂μ, (κ a) (⋂ i ∈ S, g i ∘ f i ⁻¹' sets i) = ∏ i ∈ S, (κ a) (g i ∘ f i ⁻¹' sets i)

Tactic:
refine fun t s hs ↦ ?_

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)
⊢ ∀ᵐ (a : α) ∂μ, (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.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)
⊢ ∀ᵐ (a : α) ∂μ, (κ a) (⋂ i ∈ t, g i ∘ f i ⁻¹' s i) = ∏ i ∈ t, (κ a) (g i ∘ f i ⁻¹' s i)

Tactic:
filter_upwards [this] with a 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.Basic

Goal state before:
pp: 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)
⊢ iIndepFun (fun i ω ↦ X i (ω i)) (Measure.pi μ)

Tactic:
by
  refine iIndepFun_iff_map_fun_eq_pi_map ?_ |>.2 ?_
  · exact fun i ↦ (mX i).comp_quasiMeasurePreserving (Measure.quasiMeasurePreserving_eval _ i)
  rw [Measure.pi_map_pi mX]
  congr
  ext i : 1
  rw [← (measurePreserving_eval μ i).map_eq, AEMeasurable.map_map_of_aemeasurable,
    Function.comp_def]
  · rw [(measurePreserving_eval μ i).map_eq]
    exact mX i
  · exact (measurable_pi_apply i).aemeasurable

Goal state after:
Module: Mathlib.Probability.Density

Goal state before:
pp: Ω : Type u_1
E : Type u_2
inst✝¹ : MeasurableSpace E
m : MeasurableSpace Ω
ℙ : Measure Ω
μ : Measure E
X : Ω → E
inst✝ : HasPDF X ℙ μ
⊢ ∫⁻ (x : E), pdf X ℙ μ x ∂μ = ℙ Set.univ

Tactic:
by
  rw [← setLIntegral_univ, ← map_eq_setLIntegral_pdf X ℙ μ MeasurableSet.univ,
    map_apply_of_aemeasurable (HasPDF.aemeasurable X ℙ μ) MeasurableSet.univ, Set.preimage_univ]

Goal state after:
Module: Mathlib.Probability.Density

Goal state before:
pp: Ω : Type u_1
m : MeasurableSpace Ω
ℙ : Measure Ω
X : Ω → ℝ
inst✝¹ : IsFiniteMeasure ℙ
inst✝ : HasPDF X ℙ volume
⊢ ∫ (x : ℝ), x * (pdf X ℙ volume x).toReal = ∫ (x : ℝ), (pdf X ℙ volume x).toReal * x

Tactic:
congr with x; exact mul_comm _ _

Goal state after:
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∞
a✝¹ : Disjoint (Function.support f') (Function.support g)
h_meas_f' : Measurable f'
a✝ : Measurable g
h_ind_f' :
  ∫⁻ (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
h_ind_g :
  ∫⁻ (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
h_measM_f' : Measurable f'
⊢ ∫⁻ (ω : Ω), f' ω * T.indicator (fun x ↦ c) ω + g ω * T.indicator (fun x ↦ c) ω ∂μ =
    (∫⁻ (ω : Ω), f' ω + g ω ∂μ) * ∫⁻ (ω : Ω), T.indicator (fun x ↦ c) ω ∂μ

Tactic:
lintegral_add_left (h_mul_indicator _ h_measM_f'),

Goal state after:
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∞
a✝¹ : Disjoint (Function.support f') (Function.support g)
h_meas_f' : Measurable f'
a✝ : Measurable g
h_ind_f' :
  ∫⁻ (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
h_ind_g :
  ∫⁻ (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
h_measM_f' : Measurable f'
⊢ ∫⁻ (a : Ω), f' a * T.indicator (fun x ↦ c) a ∂μ + ∫⁻ (a : Ω), g a * T.indicator (fun x ↦ c) a ∂μ =
    (∫⁻ (ω : Ω), f' ω + g ω ∂μ) * ∫⁻ (ω : Ω), T.indicator (fun x ↦ c) ω ∂μ
Module: Mathlib.Probability.Independence.Kernel.Indep

Goal state before:
pp: case refine_2.empty
α : Type u_1
Ω : Type u_2
_mα : MeasurableSpace α
m₁ m₂ x✝ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
h_indep : Indep m₁ m₂ κ μ
s t : Set Ω
hs : MeasurableSet s
ht : MeasurableSet t
s' t' : Set Ω
hs' : s' ∈ {s_1 | MeasurableSet s_1}
⊢ ∅ ∈ {s | MeasurableSet s}

Tactic:
exact @MeasurableSet.empty _ m₂

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

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
⊢ Var[0; μ] = 0

Tactic:
simp only [variance, evariance_zero, ENNReal.toReal_zero]

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

Goal state before:
pp: case e_f.hX
ι : Type u_2
inst✝¹ : Fintype ι
Ω : ι → Type u_3
mΩ : (i : ι) → MeasurableSpace (Ω i)
μ : (i : ι) → Measure (Ω i)
inst✝ : ∀ (i : ι), IsProbabilityMeasure (μ i)
X : (i : ι) → Ω i → ℝ
h : ∀ (i : ι), MemLp (X i) 2 (μ i)
i : ι
⊢ AEMeasurable (X i) (μ i)

Tactic:
exact (h i).aestronglyMeasurable.aemeasurable

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
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) ⋯
⊢ ∀ᵐ (a : α) ∂μ, (fun a i ↦ AEMeasurable.mk (f ↑i) ⋯ a) =ᵐ[κ a] fun a i ↦ f (↑i) a

Tactic:
filter_upwards [this] with a 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: case 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
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) ⋯
⊢ ∀ᵐ (a : α) ∂μ, (fun a i ↦ AEMeasurable.mk (f ↑i) ⋯ a) =ᵐ[κ a] fun a i ↦ f (↑i) a

Tactic:
filter_upwards [this] with a 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 : Type u_8
m : MeasurableSpace β
inst✝¹ : CommMonoid β
inst✝ : MeasurableMul₂ β
f : ι → Ω → β
hf_Indep : iIndepFun f κ μ
hf_meas : ∀ (i : ι), AEMeasurable (f i) (⇑κ ∘ₘ μ)
s : Finset ι
i : ι
hi : i ∉ s
h : IndepFun (∏ j ∈ s, AEMeasurable.mk (f j) ⋯) (AEMeasurable.mk (f i) ⋯) κ μ
this : ∀ᵐ (a : α) ∂μ, ∀ (i : ↥s), f ↑i =ᵐ[κ a] AEMeasurable.mk (f ↑i) ⋯
⊢ ∀ᵐ (a : α) ∂μ, ∏ j ∈ s, AEMeasurable.mk (f j) ⋯ =ᵐ[κ a] ∏ j ∈ s, f j

Tactic:
filter_upwards [this] with a 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 : Type u_8
m : MeasurableSpace β
inst✝¹ : CommMonoid β
inst✝ : MeasurableMul₂ β
f : ι → Ω → β
hf_Indep : iIndepFun f κ μ
hf_meas : ∀ (i : ι), AEMeasurable (f i) (⇑κ ∘ₘ μ)
s : Finset ι
i : ι
hi : i ∉ s
h : IndepFun (∏ j ∈ s, AEMeasurable.mk (f j) ⋯) (AEMeasurable.mk (f i) ⋯) 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) ⋯
⊢ ∏ j ∈ s, AEMeasurable.mk (f j) ⋯ =ᵐ[κ a] ∏ j ∈ s, f j
Module: Mathlib.MeasureTheory.Function.ConvergenceInDistribution

Goal state before:
pp: case h₂
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''
⊢ dist (F (Y n a)) (F (X n a)) ≤ M

Tactic:
convert!
          hF_bounded _
            _

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

Goal state before:
pp: case h
α : Type u_1
β : Type u_2
m : MeasurableSpace α
inst✝ : NormedAddCommGroup β
μ : Measure α
p : ℝ≥0∞
hp : 1 ≤ p
hp' : p ≠ ∞
f : ℕ → α → β
g : α → β
hf : ∀ (n : ℕ), StronglyMeasurable (f n)
hg : StronglyMeasurable g
hg' : MemLp g p μ
hui : UnifIntegrable f p μ
hut : UnifTight f p μ
hfg : ∀ᵐ (x : α) ∂μ, Tendsto (fun n ↦ f n x) atTop (𝓝 (g x))
ε : ℝ≥0∞
hε : ε > 0
hfinε : ε ≠ ∞
hμ : μ ≠ 0
hε' : 0 < ε / 3
Eg : Set α
hmEg : MeasurableSet Eg
hμEg : μ Eg < ∞
hgε : eLpNorm (Egᶜ.indicator g) p μ < ε / 3
Ef : Set α
hmEf : MeasurableSet Ef
hμEf : μ Ef < ∞
hfε : ∀ (i : ℕ), eLpNorm (Efᶜ.indicator (f i)) p μ ≤ ε / 3
E : Set α := Ef ∪ Eg
hmE : MeasurableSet E
hfmE : μ E < ∞
hgE' : MemLp g p (μ.restrict E)
huiE : UnifIntegrable f p (μ.restrict E)
hfgE : ∀ᵐ (x : α) ∂μ.restrict E, Tendsto (fun n ↦ f n x) atTop (𝓝 (g x))
ffmE : Fact (μ E < ∞)
hInner : ∀ ε > 0, ∃ N, ∀ n ≥ N, eLpNorm (f n - g) p (μ.restrict E) ≤ ε
N : ℕ
hfngε : ∀ n ≥ N, eLpNorm (f n - g) p (μ.restrict E) ≤ ε / 3
n : ℕ
hn : n ≥ N
hmfngE : AEStronglyMeasurable (E.indicator (f n - g)) μ
hfngEε : eLpNorm (E.indicator (f n - g)) p μ ≤ ε / 3
hmgEc : AEStronglyMeasurable (Eᶜ.indicator g) μ
hgEcε : eLpNorm (Eᶜ.indicator g) p μ ≤ ε / 3
⊢ eLpNorm (f n - g) p μ ≤ ε

Tactic:
have hmfnEc : AEStronglyMeasurable _ μ := ((hf n).indicator hmE.compl).aestronglyMeasurable

Goal state after:
case h
α : Type u_1
β : Type u_2
m : MeasurableSpace α
inst✝ : NormedAddCommGroup β
μ : Measure α
p : ℝ≥0∞
hp : 1 ≤ p
hp' : p ≠ ∞
f : ℕ → α → β
g : α → β
hf : ∀ (n : ℕ), StronglyMeasurable (f n)
hg : StronglyMeasurable g
hg' : MemLp g p μ
hui : UnifIntegrable f p μ
hut : UnifTight f p μ
hfg : ∀ᵐ (x : α) ∂μ, Tendsto (fun n ↦ f n x) atTop (𝓝 (g x))
ε : ℝ≥0∞
hε : ε > 0
hfinε : ε ≠ ∞
hμ : μ ≠ 0
hε' : 0 < ε / 3
Eg : Set α
hmEg : MeasurableSet Eg
hμEg : μ Eg < ∞
hgε : eLpNorm (Egᶜ.indicator g) p μ < ε / 3
Ef : Set α
hmEf : MeasurableSet Ef
hμEf : μ Ef < ∞
hfε : ∀ (i : ℕ), eLpNorm (Efᶜ.indicator (f i)) p μ ≤ ε / 3
E : Set α := Ef ∪ Eg
hmE : MeasurableSet E
hfmE : μ E < ∞
hgE' : MemLp g p (μ.restrict E)
huiE : UnifIntegrable f p (μ.restrict E)
hfgE : ∀ᵐ (x : α) ∂μ.restrict E, Tendsto (fun n ↦ f n x) atTop (𝓝 (g x))
ffmE : Fact (μ E < ∞)
hInner : ∀ ε > 0, ∃ N, ∀ n ≥ N, eLpNorm (f n - g) p (μ.restrict E) ≤ ε
N : ℕ
hfngε : ∀ n ≥ N, eLpNorm (f n - g) p (μ.restrict E) ≤ ε / 3
n : ℕ
hn : n ≥ N
hmfngE : AEStronglyMeasurable (E.indicator (f n - g)) μ
hfngEε : eLpNorm (E.indicator (f n - g)) p μ ≤ ε / 3
hmgEc : AEStronglyMeasurable (Eᶜ.indicator g) μ
hgEcε : eLpNorm (Eᶜ.indicator g) p μ ≤ ε / 3
hmfnEc : AEStronglyMeasurable (Eᶜ.indicator (f n)) μ
⊢ eLpNorm (f n - g) p μ ≤ ε
Module: Mathlib.MeasureTheory.Integral.CurveIntegral.Basic

Goal state before:
pp: case inr.inr
𝕜 : Type u_1
E : Type u_2
F : Type u_3
inst✝⁴ : RCLike 𝕜
inst✝³ : NormedAddCommGroup E
inst✝² : NormedSpace 𝕜 E
inst✝¹ : NormedAddCommGroup F
inst✝ : NormedSpace 𝕜 F
a b c : E
t : ℝ
ω : E → E →L[𝕜] F
γab : Path a b
γbc : Path b c
ht : t < 1 / 2
instE : NormedSpace ℝ E := NormedSpace.restrictScalars ℝ 𝕜 E
H₁ : ⇑(γab.trans γbc).extend =ᶠ[𝓝 t] fun s ↦ γab.extend (2 * s)
ht₀ : 0 < t
⊢ 𝓝[Icc 0 2] (2 * t) = 𝓝[I] (2 * t)

Tactic:
rw [nhdsWithin_eq_nhds.2, nhdsWithin_eq_nhds.2]

Goal state after:
case inr.inr
𝕜 : Type u_1
E : Type u_2
F : Type u_3
inst✝⁴ : RCLike 𝕜
inst✝³ : NormedAddCommGroup E
inst✝² : NormedSpace 𝕜 E
inst✝¹ : NormedAddCommGroup F
inst✝ : NormedSpace 𝕜 F
a b c : E
t : ℝ
ω : E → E →L[𝕜] F
γab : Path a b
γbc : Path b c
ht : t < 1 / 2
instE : NormedSpace ℝ E := NormedSpace.restrictScalars ℝ 𝕜 E
H₁ : ⇑(γab.trans γbc).extend =ᶠ[𝓝 t] fun s ↦ γab.extend (2 * s)
ht₀ : 0 < t
⊢ I ∈ 𝓝 (2 * t)

case inr.inr
𝕜 : Type u_1
E : Type u_2
F : Type u_3
inst✝⁴ : RCLike 𝕜
inst✝³ : NormedAddCommGroup E
inst✝² : NormedSpace 𝕜 E
inst✝¹ : NormedAddCommGroup F
inst✝ : NormedSpace 𝕜 F
a b c : E
t : ℝ
ω : E → E →L[𝕜] F
γab : Path a b
γbc : Path b c
ht : t < 1 / 2
instE : NormedSpace ℝ E := NormedSpace.restrictScalars ℝ 𝕜 E
H₁ : ⇑(γab.trans γbc).extend =ᶠ[𝓝 t] fun s ↦ γab.extend (2 * s)
ht₀ : 0 < t
⊢ Icc 0 2 ∈ 𝓝 (2 * t)
Module: Mathlib.MeasureTheory.Integral.MeanValue

Goal state before:
pp: α : Type u_1
inst✝¹ : TopologicalSpace α
inst✝ : MeasurableSpace α
s : Set α
f g : α → ℝ
μ : Measure α
hs_conn : IsConnected s
hs_meas : MeasurableSet s
hf : ContinuousOn f s
hg : IntegrableOn g s μ
hfg : IntegrableOn (fun x ↦ f x * g x) s μ
hg0 : ∀ᵐ (x : α) ∂μ.restrict s, 0 ≤ g x
ρ : α → ENNReal := fun x ↦ ENNReal.ofReal (g x)
ν : Measure α := μ.withDensity ρ
hρ_ae : AEMeasurable ρ (μ.restrict s)
hρ_top : ∀ᵐ (x : α) ∂μ.restrict s, ρ x < ⊤
h_toReal_ae : (fun x ↦ (ρ x).toReal) =ᵐ[μ.restrict s] g
heq : ∫ (x : α) in s, f x * g x ∂μ = ∫ (x : α) in s, f x ∂ν
hg1 : ∫ (x : α) in s, g x ∂μ = ∫ (x : α) in s, 1 ∂ν
hν0 : ∫ (x : α) in s, 1 ∂ν = 0
c : α
hc : c ∈ s
⊢ 0 = f c * ∫ (x : α) in s, g x ∂μ

Tactic:
simp [hν0, hg1]

Goal state after:
Module: Mathlib.MeasureTheory.Integral.IntervalIntegral.TrapezoidalRule

Goal state before:
pp: f : ℝ → ℝ
N : ℕ
N_nonzero : 0 < N
a b : ℝ
⊢ trapezoidal_error f N a b = -trapezoidal_error f N b a

Tactic:
unfold trapezoidal_error
  rw [trapezoidal_integral_symm f N_nonzero a b, integral_symm, neg_sub_neg, neg_sub]

Goal state after: