l3lab/ntp-mathlib huggingface dataset:
/-- Any function in `ℒp` can be approximated by bounded continuous functions when `p < ∞`,
version in terms of `snorm`. -/
theorem Memℒp.exists_boundedContinuous_snorm_sub_le [μ.WeaklyRegular] (hp : p ≠ ∞) {f : α → E}
    (hf : Memℒp f p μ) {ε : ℝ≥0∞} (hε : ε ≠ 0) :
    ∃ g : α →ᵇ E, snorm (f - (g : α → E)) p μ ≤ ε ∧ Memℒp g p μ := by
  suffices H :
    ∃ g : α → E, snorm (f - g) p μ ≤ ε ∧ Continuous g ∧ Memℒp g p μ ∧ IsBounded (range g)
  · rcases H with ⟨g, hg, g_cont, g_mem, g_bd⟩
    exact ⟨⟨⟨g, g_cont⟩, Metric.isBounded_range_iff.1 g_bd⟩, hg, g_mem⟩
  -- It suffices to check that the set of functions we consider approximates characteristic
  -- functions, is stable under addition and made of ae strongly measurable functions.
  -- First check the latter easy facts.
  apply hf.induction_dense hp _ _ _ _ hε
  rotate_left
  -- stability under addition
  · rintro f g ⟨f_cont, f_mem, f_bd⟩ ⟨g_cont, g_mem, g_bd⟩
    refine' ⟨f_cont.add g_cont, f_mem.add g_mem, _⟩
    let f' : α →ᵇ E := ⟨⟨f, f_cont⟩, Metric.isBounded_range_iff.1 f_bd⟩
    let g' : α →ᵇ E := ⟨⟨g, g_cont⟩, Metric.isBounded_range_iff.1 g_bd⟩
    exact (f' + g').isBounded_range
  -- ae strong measurability
  · 

Proof state:
α : Type u_1
inst✝⁶ : MeasurableSpace α
inst✝⁵ : TopologicalSpace α
inst✝⁴ : T4Space α
inst✝³ : BorelSpace α
E : Type u_2
inst✝² : NormedAddCommGroup E
μ : Measure α
p : ℝ≥0∞
inst✝¹ : NormedSpace ℝ E
inst✝ : Measure.WeaklyRegular μ
hp : p ≠ ⊤
f : α → E
hf : Memℒp f p
ε : ℝ≥0∞
hε : ε ≠ 0
⊢ ∀ (f : α → E), Continuous f ∧ Memℒp f p ∧ IsBounded (range f) → AEStronglyMeasurable f μ

Next tactic:
exact fun f ⟨_, h, _⟩ => h.aestronglyMeasurable
/-- Any function in `ℒp` can be approximated by bounded continuous functions when `p < ∞`,
version in terms of `snorm`. -/
theorem Memℒp.exists_boundedContinuous_snorm_sub_le [μ.WeaklyRegular] (hp : p ≠ ∞) {f : α → E}
    (hf : Memℒp f p μ) {ε : ℝ≥0∞} (hε : ε ≠ 0) :
    ∃ g : α →ᵇ E, snorm (f - (g : α → E)) p μ ≤ ε ∧ Memℒp g p μ := by
  suffices H :
    ∃ g : α → E, snorm (f - g) p μ ≤ ε ∧ Continuous g ∧ Memℒp g p μ ∧ IsBounded (range g)
  · rcases H with ⟨g, hg, g_cont, g_mem, g_bd⟩
    exact ⟨⟨⟨g, g_cont⟩, Metric.isBounded_range_iff.1 g_bd⟩, hg, g_mem⟩
  -- It suffices to check that the set of functions we consider approximates characteristic
  -- functions, is stable under addition and made of ae strongly measurable functions.
  -- First check the latter easy facts.
  apply hf.induction_dense hp _ _ _ _ hε
  rotate_left
  -- stability under addition
  · rintro f g ⟨f_cont, f_mem, f_bd⟩ ⟨g_cont, g_mem, g_bd⟩
    refine' ⟨f_cont.add g_cont, f_mem.add g_mem, _⟩
    let f' : α →ᵇ E := ⟨⟨f, f_cont⟩, Metric.isBounded_range_iff.1 f_bd⟩
    let g' : α →ᵇ E := ⟨⟨g, g_cont⟩, Metric.isBounded_range_iff.1 g_bd⟩
    exact (f' + g').isBounded_range
  -- ae strong measurability
  · exact fun f ⟨_, h, _⟩ => h.aestronglyMeasurable
  -- We are left with approximating characteristic functions.
  -- This follows from `exists_continuous_snorm_sub_le_of_closed`.
  

Proof state:
α : Type u_1
inst✝⁶ : MeasurableSpace α
inst✝⁵ : TopologicalSpace α
inst✝⁴ : T4Space α
inst✝³ : BorelSpace α
E : Type u_2
inst✝² : NormedAddCommGroup E
μ : Measure α
p : ℝ≥0∞
inst✝¹ : NormedSpace ℝ E
inst✝ : Measure.WeaklyRegular μ
hp : p ≠ ⊤
f : α → E
hf : Memℒp f p
ε : ℝ≥0∞
hε : ε ≠ 0
⊢ ∀ (c : E) ⦃s : Set α⦄,
    MeasurableSet s →
      ↑↑μ s < ⊤ →
        ∀ {ε : ℝ≥0∞},
          ε ≠ 0 → ∃ g, snorm (g - Set.indicator s fun x => c) p μ ≤ ε ∧ Continuous g ∧ Memℒp g p ∧ IsBounded (range g)

Next tactic:
intro c t ht htμ ε hε
/-- Any function in `ℒp` can be approximated by bounded continuous functions when `p < ∞`,
version in terms of `snorm`. -/
theorem Memℒp.exists_boundedContinuous_snorm_sub_le [μ.WeaklyRegular] (hp : p ≠ ∞) {f : α → E}
    (hf : Memℒp f p μ) {ε : ℝ≥0∞} (hε : ε ≠ 0) :
    ∃ g : α →ᵇ E, snorm (f - (g : α → E)) p μ ≤ ε ∧ Memℒp g p μ := by
  suffices H :
    ∃ g : α → E, snorm (f - g) p μ ≤ ε ∧ Continuous g ∧ Memℒp g p μ ∧ IsBounded (range g)
  · rcases H with ⟨g, hg, g_cont, g_mem, g_bd⟩
    exact ⟨⟨⟨g, g_cont⟩, Metric.isBounded_range_iff.1 g_bd⟩, hg, g_mem⟩
  -- It suffices to check that the set of functions we consider approximates characteristic
  -- functions, is stable under addition and made of ae strongly measurable functions.
  -- First check the latter easy facts.
  apply hf.induction_dense hp _ _ _ _ hε
  rotate_left
  -- stability under addition
  · rintro f g ⟨f_cont, f_mem, f_bd⟩ ⟨g_cont, g_mem, g_bd⟩
    refine' ⟨f_cont.add g_cont, f_mem.add g_mem, _⟩
    let f' : α →ᵇ E := ⟨⟨f, f_cont⟩, Metric.isBounded_range_iff.1 f_bd⟩
    let g' : α →ᵇ E := ⟨⟨g, g_cont⟩, Metric.isBounded_range_iff.1 g_bd⟩
    exact (f' + g').isBounded_range
  -- ae strong measurability
  · exact fun f ⟨_, h, _⟩ => h.aestronglyMeasurable
  -- We are left with approximating characteristic functions.
  -- This follows from `exists_continuous_snorm_sub_le_of_closed`.
  intro c t ht htμ ε hε
  

Proof state:
α : Type u_1
inst✝⁶ : MeasurableSpace α
inst✝⁵ : TopologicalSpace α
inst✝⁴ : T4Space α
inst✝³ : BorelSpace α
E : Type u_2
inst✝² : NormedAddCommGroup E
μ : Measure α
p : ℝ≥0∞
inst✝¹ : NormedSpace ℝ E
inst✝ : Measure.WeaklyRegular μ
hp : p ≠ ⊤
f : α → E
hf : Memℒp f p
ε✝ : ℝ≥0∞
hε✝ : ε✝ ≠ 0
c : E
t : Set α
ht : MeasurableSet t
htμ : ↑↑μ t < ⊤
ε : ℝ≥0∞
hε : ε ≠ 0
⊢ ∃ g, snorm (g - Set.indicator t fun x => c) p μ ≤ ε ∧ Continuous g ∧ Memℒp g p ∧ IsBounded (range g)

Next tactic:
rcases exists_Lp_half E μ p hε with ⟨δ, δpos, hδ⟩
/-- Any function in `ℒp` can be approximated by bounded continuous functions when `p < ∞`,
version in terms of `snorm`. -/
theorem Memℒp.exists_boundedContinuous_snorm_sub_le [μ.WeaklyRegular] (hp : p ≠ ∞) {f : α → E}
    (hf : Memℒp f p μ) {ε : ℝ≥0∞} (hε : ε ≠ 0) :
    ∃ g : α →ᵇ E, snorm (f - (g : α → E)) p μ ≤ ε ∧ Memℒp g p μ := by
  suffices H :
    ∃ g : α → E, snorm (f - g) p μ ≤ ε ∧ Continuous g ∧ Memℒp g p μ ∧ IsBounded (range g)
  · rcases H with ⟨g, hg, g_cont, g_mem, g_bd⟩
    exact ⟨⟨⟨g, g_cont⟩, Metric.isBounded_range_iff.1 g_bd⟩, hg, g_mem⟩
  -- It suffices to check that the set of functions we consider approximates characteristic
  -- functions, is stable under addition and made of ae strongly measurable functions.
  -- First check the latter easy facts.
  apply hf.induction_dense hp _ _ _ _ hε
  rotate_left
  -- stability under addition
  · rintro f g ⟨f_cont, f_mem, f_bd⟩ ⟨g_cont, g_mem, g_bd⟩
    refine' ⟨f_cont.add g_cont, f_mem.add g_mem, _⟩
    let f' : α →ᵇ E := ⟨⟨f, f_cont⟩, Metric.isBounded_range_iff.1 f_bd⟩
    let g' : α →ᵇ E := ⟨⟨g, g_cont⟩, Metric.isBounded_range_iff.1 g_bd⟩
    exact (f' + g').isBounded_range
  -- ae strong measurability
  · exact fun f ⟨_, h, _⟩ => h.aestronglyMeasurable
  -- We are left with approximating characteristic functions.
  -- This follows from `exists_continuous_snorm_sub_le_of_closed`.
  intro c t ht htμ ε hε
  rcases exists_Lp_half E μ p hε with ⟨δ, δpos, hδ⟩
  

Proof state:
case intro.intro
α : Type u_1
inst✝⁶ : MeasurableSpace α
inst✝⁵ : TopologicalSpace α
inst✝⁴ : T4Space α
inst✝³ : BorelSpace α
E : Type u_2
inst✝² : NormedAddCommGroup E
μ : Measure α
p : ℝ≥0∞
inst✝¹ : NormedSpace ℝ E
inst✝ : Measure.WeaklyRegular μ
hp : p ≠ ⊤
f : α → E
hf : Memℒp f p
ε✝ : ℝ≥0∞
hε✝ : ε✝ ≠ 0
c : E
t : Set α
ht : MeasurableSet t
htμ : ↑↑μ t < ⊤
ε : ℝ≥0∞
hε : ε ≠ 0
δ : ℝ≥0∞
δpos : 0 < δ
hδ :
  ∀ (f g : α → E),
    AEStronglyMeasurable f μ → AEStronglyMeasurable g μ → snorm f p μ ≤ δ → snorm g p μ ≤ δ → snorm (f + g) p μ < ε
⊢ ∃ g, snorm (g - Set.indicator t fun x => c) p μ ≤ ε ∧ Continuous g ∧ Memℒp g p ∧ IsBounded (range g)

Next tactic:
obtain ⟨η, ηpos, hη⟩ :
    ∃ η : ℝ≥0, 0 < η ∧ ∀ s : Set α, μ s ≤ η → snorm (s.indicator fun _x => c) p μ ≤ δ
/-- Any function in `ℒp` can be approximated by bounded continuous functions when `p < ∞`,
version in terms of `snorm`. -/
theorem Memℒp.exists_boundedContinuous_snorm_sub_le [μ.WeaklyRegular] (hp : p ≠ ∞) {f : α → E}
    (hf : Memℒp f p μ) {ε : ℝ≥0∞} (hε : ε ≠ 0) :
    ∃ g : α →ᵇ E, snorm (f - (g : α → E)) p μ ≤ ε ∧ Memℒp g p μ := by
  suffices H :
    ∃ g : α → E, snorm (f - g) p μ ≤ ε ∧ Continuous g ∧ Memℒp g p μ ∧ IsBounded (range g)
  · rcases H with ⟨g, hg, g_cont, g_mem, g_bd⟩
    exact ⟨⟨⟨g, g_cont⟩, Metric.isBounded_range_iff.1 g_bd⟩, hg, g_mem⟩
  -- It suffices to check that the set of functions we consider approximates characteristic
  -- functions, is stable under addition and made of ae strongly measurable functions.
  -- First check the latter easy facts.
  apply hf.induction_dense hp _ _ _ _ hε
  rotate_left
  -- stability under addition
  · rintro f g ⟨f_cont, f_mem, f_bd⟩ ⟨g_cont, g_mem, g_bd⟩
    refine' ⟨f_cont.add g_cont, f_mem.add g_mem, _⟩
    let f' : α →ᵇ E := ⟨⟨f, f_cont⟩, Metric.isBounded_range_iff.1 f_bd⟩
    let g' : α →ᵇ E := ⟨⟨g, g_cont⟩, Metric.isBounded_range_iff.1 g_bd⟩
    exact (f' + g').isBounded_range
  -- ae strong measurability
  · exact fun f ⟨_, h, _⟩ => h.aestronglyMeasurable
  -- We are left with approximating characteristic functions.
  -- This follows from `exists_continuous_snorm_sub_le_of_closed`.
  intro c t ht htμ ε hε
  rcases exists_Lp_half E μ p hε with ⟨δ, δpos, hδ⟩
  obtain ⟨η, ηpos, hη⟩ :
    ∃ η : ℝ≥0, 0 < η ∧ ∀ s : Set α, μ s ≤ η → snorm (s.indicator fun _x => c) p μ ≤ δ
  

Proof state:
α : Type u_1
inst✝⁶ : MeasurableSpace α
inst✝⁵ : TopologicalSpace α
inst✝⁴ : T4Space α
inst✝³ : BorelSpace α
E : Type u_2
inst✝² : NormedAddCommGroup E
μ : Measure α
p : ℝ≥0∞
inst✝¹ : NormedSpace ℝ E
inst✝ : Measure.WeaklyRegular μ
hp : p ≠ ⊤
f : α → E
hf : Memℒp f p
ε✝ : ℝ≥0∞
hε✝ : ε✝ ≠ 0
c : E
t : Set α
ht : MeasurableSet t
htμ : ↑↑μ t < ⊤
ε : ℝ≥0∞
hε : ε ≠ 0
δ : ℝ≥0∞
δpos : 0 < δ
hδ :
  ∀ (f g : α → E),
    AEStronglyMeasurable f μ → AEStronglyMeasurable g μ → snorm f p μ ≤ δ → snorm g p μ ≤ δ → snorm (f + g) p μ < ε
⊢ ∃ η, 0 < η ∧ ∀ (s : Set α), ↑↑μ s ≤ ↑η → snorm (Set.indicator s fun _x => c) p μ ≤ δ
case intro.intro.intro.intro
α : Type u_1
inst✝⁶ : MeasurableSpace α
inst✝⁵ : TopologicalSpace α
inst✝⁴ : T4Space α
inst✝³ : BorelSpace α
E : Type u_2
inst✝² : NormedAddCommGroup E
μ : Measure α
p : ℝ≥0∞
inst✝¹ : NormedSpace ℝ E
inst✝ : Measure.WeaklyRegular μ
hp : p ≠ ⊤
f : α → E
hf : Memℒp f p
ε✝ : ℝ≥0∞
hε✝ : ε✝ ≠ 0
c : E
t : Set α
ht : MeasurableSet t
htμ : ↑↑μ t < ⊤
ε : ℝ≥0∞
hε : ε ≠ 0
δ : ℝ≥0∞
δpos : 0 < δ
hδ :
  ∀ (f g : α → E),
    AEStronglyMeasurable f μ → AEStronglyMeasurable g μ → snorm f p μ ≤ δ → snorm g p μ ≤ δ → snorm (f + g) p μ < ε
η : ℝ≥0
ηpos : 0 < η
hη : ∀ (s : Set α), ↑↑μ s ≤ ↑η → snorm (Set.indicator s fun _x => c) p μ ≤ δ
⊢ ∃ g, snorm (g - Set.indicator t fun x => c) p μ ≤ ε ∧ Continuous g ∧ Memℒp g p ∧ IsBounded (range g)

Next tactic:
exact exists_snorm_indicator_le hp c δpos.ne'
/-- Any function in `ℒp` can be approximated by bounded continuous functions when `p < ∞`,
version in terms of `snorm`. -/
theorem Memℒp.exists_boundedContinuous_snorm_sub_le [μ.WeaklyRegular] (hp : p ≠ ∞) {f : α → E}
    (hf : Memℒp f p μ) {ε : ℝ≥0∞} (hε : ε ≠ 0) :
    ∃ g : α →ᵇ E, snorm (f - (g : α → E)) p μ ≤ ε ∧ Memℒp g p μ := by
  suffices H :
    ∃ g : α → E, snorm (f - g) p μ ≤ ε ∧ Continuous g ∧ Memℒp g p μ ∧ IsBounded (range g)
  · rcases H with ⟨g, hg, g_cont, g_mem, g_bd⟩
    exact ⟨⟨⟨g, g_cont⟩, Metric.isBounded_range_iff.1 g_bd⟩, hg, g_mem⟩
  -- It suffices to check that the set of functions we consider approximates characteristic
  -- functions, is stable under addition and made of ae strongly measurable functions.
  -- First check the latter easy facts.
  apply hf.induction_dense hp _ _ _ _ hε
  rotate_left
  -- stability under addition
  · rintro f g ⟨f_cont, f_mem, f_bd⟩ ⟨g_cont, g_mem, g_bd⟩
    refine' ⟨f_cont.add g_cont, f_mem.add g_mem, _⟩
    let f' : α →ᵇ E := ⟨⟨f, f_cont⟩, Metric.isBounded_range_iff.1 f_bd⟩
    let g' : α →ᵇ E := ⟨⟨g, g_cont⟩, Metric.isBounded_range_iff.1 g_bd⟩
    exact (f' + g').isBounded_range
  -- ae strong measurability
  · exact fun f ⟨_, h, _⟩ => h.aestronglyMeasurable
  -- We are left with approximating characteristic functions.
  -- This follows from `exists_continuous_snorm_sub_le_of_closed`.
  intro c t ht htμ ε hε
  rcases exists_Lp_half E μ p hε with ⟨δ, δpos, hδ⟩
  obtain ⟨η, ηpos, hη⟩ :
    ∃ η : ℝ≥0, 0 < η ∧ ∀ s : Set α, μ s ≤ η → snorm (s.indicator fun _x => c) p μ ≤ δ
  exact exists_snorm_indicator_le hp c δpos.ne'
  

Proof state:
case intro.intro.intro.intro
α : Type u_1
inst✝⁶ : MeasurableSpace α
inst✝⁵ : TopologicalSpace α
inst✝⁴ : T4Space α
inst✝³ : BorelSpace α
E : Type u_2
inst✝² : NormedAddCommGroup E
μ : Measure α
p : ℝ≥0∞
inst✝¹ : NormedSpace ℝ E
inst✝ : Measure.WeaklyRegular μ
hp : p ≠ ⊤
f : α → E
hf : Memℒp f p
ε✝ : ℝ≥0∞
hε✝ : ε✝ ≠ 0
c : E
t : Set α
ht : MeasurableSet t
htμ : ↑↑μ t < ⊤
ε : ℝ≥0∞
hε : ε ≠ 0
δ : ℝ≥0∞
δpos : 0 < δ
hδ :
  ∀ (f g : α → E),
    AEStronglyMeasurable f μ → AEStronglyMeasurable g μ → snorm f p μ ≤ δ → snorm g p μ ≤ δ → snorm (f + g) p μ < ε
η : ℝ≥0
ηpos : 0 < η
hη : ∀ (s : Set α), ↑↑μ s ≤ ↑η → snorm (Set.indicator s fun _x => c) p μ ≤ δ
⊢ ∃ g, snorm (g - Set.indicator t fun x => c) p μ ≤ ε ∧ Continuous g ∧ Memℒp g p ∧ IsBounded (range g)

Next tactic:
have hη_pos' : (0 : ℝ≥0∞) < η := ENNReal.coe_pos.2 ηpos
/-- Any function in `ℒp` can be approximated by bounded continuous functions when `p < ∞`,
version in terms of `snorm`. -/
theorem Memℒp.exists_boundedContinuous_snorm_sub_le [μ.WeaklyRegular] (hp : p ≠ ∞) {f : α → E}
    (hf : Memℒp f p μ) {ε : ℝ≥0∞} (hε : ε ≠ 0) :
    ∃ g : α →ᵇ E, snorm (f - (g : α → E)) p μ ≤ ε ∧ Memℒp g p μ := by
  suffices H :
    ∃ g : α → E, snorm (f - g) p μ ≤ ε ∧ Continuous g ∧ Memℒp g p μ ∧ IsBounded (range g)
  · rcases H with ⟨g, hg, g_cont, g_mem, g_bd⟩
    exact ⟨⟨⟨g, g_cont⟩, Metric.isBounded_range_iff.1 g_bd⟩, hg, g_mem⟩
  -- It suffices to check that the set of functions we consider approximates characteristic
  -- functions, is stable under addition and made of ae strongly measurable functions.
  -- First check the latter easy facts.
  apply hf.induction_dense hp _ _ _ _ hε
  rotate_left
  -- stability under addition
  · rintro f g ⟨f_cont, f_mem, f_bd⟩ ⟨g_cont, g_mem, g_bd⟩
    refine' ⟨f_cont.add g_cont, f_mem.add g_mem, _⟩
    let f' : α →ᵇ E := ⟨⟨f, f_cont⟩, Metric.isBounded_range_iff.1 f_bd⟩
    let g' : α →ᵇ E := ⟨⟨g, g_cont⟩, Metric.isBounded_range_iff.1 g_bd⟩
    exact (f' + g').isBounded_range
  -- ae strong measurability
  · exact fun f ⟨_, h, _⟩ => h.aestronglyMeasurable
  -- We are left with approximating characteristic functions.
  -- This follows from `exists_continuous_snorm_sub_le_of_closed`.
  intro c t ht htμ ε hε
  rcases exists_Lp_half E μ p hε with ⟨δ, δpos, hδ⟩
  obtain ⟨η, ηpos, hη⟩ :
    ∃ η : ℝ≥0, 0 < η ∧ ∀ s : Set α, μ s ≤ η → snorm (s.indicator fun _x => c) p μ ≤ δ
  exact exists_snorm_indicator_le hp c δpos.ne'
  have hη_pos' : (0 : ℝ≥0∞) < η := ENNReal.coe_pos.2 ηpos
  

Proof state:
case intro.intro.intro.intro
α : Type u_1
inst✝⁶ : MeasurableSpace α
inst✝⁵ : TopologicalSpace α
inst✝⁴ : T4Space α
inst✝³ : BorelSpace α
E : Type u_2
inst✝² : NormedAddCommGroup E
μ : Measure α
p : ℝ≥0∞
inst✝¹ : NormedSpace ℝ E
inst✝ : Measure.WeaklyRegular μ
hp : p ≠ ⊤
f : α → E
hf : Memℒp f p
ε✝ : ℝ≥0∞
hε✝ : ε✝ ≠ 0
c : E
t : Set α
ht : MeasurableSet t
htμ : ↑↑μ t < ⊤
ε : ℝ≥0∞
hε : ε ≠ 0
δ : ℝ≥0∞
δpos : 0 < δ
hδ :
  ∀ (f g : α → E),
    AEStronglyMeasurable f μ → AEStronglyMeasurable g μ → snorm f p μ ≤ δ → snorm g p μ ≤ δ → snorm (f + g) p μ < ε
η : ℝ≥0
ηpos : 0 < η
hη : ∀ (s : Set α), ↑↑μ s ≤ ↑η → snorm (Set.indicator s fun _x => c) p μ ≤ δ
hη_pos' : 0 < ↑η
⊢ ∃ g, snorm (g - Set.indicator t fun x => c) p μ ≤ ε ∧ Continuous g ∧ Memℒp g p ∧ IsBounded (range g)

Next tactic:
obtain ⟨s, st, s_closed, μs⟩ : ∃ s, s ⊆ t ∧ IsClosed s ∧ μ (t \ s) < η
/-- Any function in `ℒp` can be approximated by bounded continuous functions when `p < ∞`,
version in terms of `snorm`. -/
theorem Memℒp.exists_boundedContinuous_snorm_sub_le [μ.WeaklyRegular] (hp : p ≠ ∞) {f : α → E}
    (hf : Memℒp f p μ) {ε : ℝ≥0∞} (hε : ε ≠ 0) :
    ∃ g : α →ᵇ E, snorm (f - (g : α → E)) p μ ≤ ε ∧ Memℒp g p μ := by
  suffices H :
    ∃ g : α → E, snorm (f - g) p μ ≤ ε ∧ Continuous g ∧ Memℒp g p μ ∧ IsBounded (range g)
  · rcases H with ⟨g, hg, g_cont, g_mem, g_bd⟩
    exact ⟨⟨⟨g, g_cont⟩, Metric.isBounded_range_iff.1 g_bd⟩, hg, g_mem⟩
  -- It suffices to check that the set of functions we consider approximates characteristic
  -- functions, is stable under addition and made of ae strongly measurable functions.
  -- First check the latter easy facts.
  apply hf.induction_dense hp _ _ _ _ hε
  rotate_left
  -- stability under addition
  · rintro f g ⟨f_cont, f_mem, f_bd⟩ ⟨g_cont, g_mem, g_bd⟩
    refine' ⟨f_cont.add g_cont, f_mem.add g_mem, _⟩
    let f' : α →ᵇ E := ⟨⟨f, f_cont⟩, Metric.isBounded_range_iff.1 f_bd⟩
    let g' : α →ᵇ E := ⟨⟨g, g_cont⟩, Metric.isBounded_range_iff.1 g_bd⟩
    exact (f' + g').isBounded_range
  -- ae strong measurability
  · exact fun f ⟨_, h, _⟩ => h.aestronglyMeasurable
  -- We are left with approximating characteristic functions.
  -- This follows from `exists_continuous_snorm_sub_le_of_closed`.
  intro c t ht htμ ε hε
  rcases exists_Lp_half E μ p hε with ⟨δ, δpos, hδ⟩
  obtain ⟨η, ηpos, hη⟩ :
    ∃ η : ℝ≥0, 0 < η ∧ ∀ s : Set α, μ s ≤ η → snorm (s.indicator fun _x => c) p μ ≤ δ
  exact exists_snorm_indicator_le hp c δpos.ne'
  have hη_pos' : (0 : ℝ≥0∞) < η := ENNReal.coe_pos.2 ηpos
  obtain ⟨s, st, s_closed, μs⟩ : ∃ s, s ⊆ t ∧ IsClosed s ∧ μ (t \ s) < η
  exact ht.exists_isClosed_diff_lt htμ.ne hη_pos'.ne'
  

Proof state:
case intro.intro.intro.intro.intro.intro.intro
α : Type u_1
inst✝⁶ : MeasurableSpace α
inst✝⁵ : TopologicalSpace α
inst✝⁴ : T4Space α
inst✝³ : BorelSpace α
E : Type u_2
inst✝² : NormedAddCommGroup E
μ : Measure α
p : ℝ≥0∞
inst✝¹ : NormedSpace ℝ E
inst✝ : Measure.WeaklyRegular μ
hp : p ≠ ⊤
f : α → E
hf : Memℒp f p
ε✝ : ℝ≥0∞
hε✝ : ε✝ ≠ 0
c : E
t : Set α
ht : MeasurableSet t
htμ : ↑↑μ t < ⊤
ε : ℝ≥0∞
hε : ε ≠ 0
δ : ℝ≥0∞
δpos : 0 < δ
hδ :
  ∀ (f g : α → E),
    AEStronglyMeasurable f μ → AEStronglyMeasurable g μ → snorm f p μ ≤ δ → snorm g p μ ≤ δ → snorm (f + g) p μ < ε
η : ℝ≥0
ηpos : 0 < η
hη : ∀ (s : Set α), ↑↑μ s ≤ ↑η → snorm (Set.indicator s fun _x => c) p μ ≤ δ
hη_pos' : 0 < ↑η
s : Set α
st : s ⊆ t
s_closed : IsClosed s
μs : ↑↑μ (t \ s) < ↑η
⊢ ∃ g, snorm (g - Set.indicator t fun x => c) p μ ≤ ε ∧ Continuous g ∧ Memℒp g p ∧ IsBounded (range g)

Next tactic:
have hsμ : μ s < ∞ := (measure_mono st).trans_lt htμ
/-- Any function in `ℒp` can be approximated by bounded continuous functions when `p < ∞`,
version in terms of `snorm`. -/
theorem Memℒp.exists_boundedContinuous_snorm_sub_le [μ.WeaklyRegular] (hp : p ≠ ∞) {f : α → E}
    (hf : Memℒp f p μ) {ε : ℝ≥0∞} (hε : ε ≠ 0) :
    ∃ g : α →ᵇ E, snorm (f - (g : α → E)) p μ ≤ ε ∧ Memℒp g p μ := by
  suffices H :
    ∃ g : α → E, snorm (f - g) p μ ≤ ε ∧ Continuous g ∧ Memℒp g p μ ∧ IsBounded (range g)
  · rcases H with ⟨g, hg, g_cont, g_mem, g_bd⟩
    exact ⟨⟨⟨g, g_cont⟩, Metric.isBounded_range_iff.1 g_bd⟩, hg, g_mem⟩
  -- It suffices to check that the set of functions we consider approximates characteristic
  -- functions, is stable under addition and made of ae strongly measurable functions.
  -- First check the latter easy facts.
  apply hf.induction_dense hp _ _ _ _ hε
  rotate_left
  -- stability under addition
  · rintro f g ⟨f_cont, f_mem, f_bd⟩ ⟨g_cont, g_mem, g_bd⟩
    refine' ⟨f_cont.add g_cont, f_mem.add g_mem, _⟩
    let f' : α →ᵇ E := ⟨⟨f, f_cont⟩, Metric.isBounded_range_iff.1 f_bd⟩
    let g' : α →ᵇ E := ⟨⟨g, g_cont⟩, Metric.isBounded_range_iff.1 g_bd⟩
    exact (f' + g').isBounded_range
  -- ae strong measurability
  · exact fun f ⟨_, h, _⟩ => h.aestronglyMeasurable
  -- We are left with approximating characteristic functions.
  -- This follows from `exists_continuous_snorm_sub_le_of_closed`.
  intro c t ht htμ ε hε
  rcases exists_Lp_half E μ p hε with ⟨δ, δpos, hδ⟩
  obtain ⟨η, ηpos, hη⟩ :
    ∃ η : ℝ≥0, 0 < η ∧ ∀ s : Set α, μ s ≤ η → snorm (s.indicator fun _x => c) p μ ≤ δ
  exact exists_snorm_indicator_le hp c δpos.ne'
  have hη_pos' : (0 : ℝ≥0∞) < η := ENNReal.coe_pos.2 ηpos
  obtain ⟨s, st, s_closed, μs⟩ : ∃ s, s ⊆ t ∧ IsClosed s ∧ μ (t \ s) < η
  exact ht.exists_isClosed_diff_lt htμ.ne hη_pos'.ne'
  have hsμ : μ s < ∞ := (measure_mono st).trans_lt htμ
  

Proof state:
case intro.intro.intro.intro.intro.intro.intro
α : Type u_1
inst✝⁶ : MeasurableSpace α
inst✝⁵ : TopologicalSpace α
inst✝⁴ : T4Space α
inst✝³ : BorelSpace α
E : Type u_2
inst✝² : NormedAddCommGroup E
μ : Measure α
p : ℝ≥0∞
inst✝¹ : NormedSpace ℝ E
inst✝ : Measure.WeaklyRegular μ
hp : p ≠ ⊤
f : α → E
hf : Memℒp f p
ε✝ : ℝ≥0∞
hε✝ : ε✝ ≠ 0
c : E
t : Set α
ht : MeasurableSet t
htμ : ↑↑μ t < ⊤
ε : ℝ≥0∞
hε : ε ≠ 0
δ : ℝ≥0∞
δpos : 0 < δ
hδ :
  ∀ (f g : α → E),
    AEStronglyMeasurable f μ → AEStronglyMeasurable g μ → snorm f p μ ≤ δ → snorm g p μ ≤ δ → snorm (f + g) p μ < ε
η : ℝ≥0
ηpos : 0 < η
hη : ∀ (s : Set α), ↑↑μ s ≤ ↑η → snorm (Set.indicator s fun _x => c) p μ ≤ δ
hη_pos' : 0 < ↑η
s : Set α
st : s ⊆ t
s_closed : IsClosed s
μs : ↑↑μ (t \ s) < ↑η
hsμ : ↑↑μ s < ⊤
⊢ ∃ g, snorm (g - Set.indicator t fun x => c) p μ ≤ ε ∧ Continuous g ∧ Memℒp g p ∧ IsBounded (range g)

Next tactic:
have I1 : snorm ((s.indicator fun _y => c) - t.indicator fun _y => c) p μ ≤ δ := by
    rw [← snorm_neg, neg_sub, ← indicator_diff st]
    exact hη _ μs.le
/-- Any function in `ℒp` can be approximated by bounded continuous functions when `p < ∞`,
version in terms of `snorm`. -/
theorem Memℒp.exists_boundedContinuous_snorm_sub_le [μ.WeaklyRegular] (hp : p ≠ ∞) {f : α → E}
    (hf : Memℒp f p μ) {ε : ℝ≥0∞} (hε : ε ≠ 0) :
    ∃ g : α →ᵇ E, snorm (f - (g : α → E)) p μ ≤ ε ∧ Memℒp g p μ := by
  suffices H :
    ∃ g : α → E, snorm (f - g) p μ ≤ ε ∧ Continuous g ∧ Memℒp g p μ ∧ IsBounded (range g)
  · rcases H with ⟨g, hg, g_cont, g_mem, g_bd⟩
    exact ⟨⟨⟨g, g_cont⟩, Metric.isBounded_range_iff.1 g_bd⟩, hg, g_mem⟩
  -- It suffices to check that the set of functions we consider approximates characteristic
  -- functions, is stable under addition and made of ae strongly measurable functions.
  -- First check the latter easy facts.
  apply hf.induction_dense hp _ _ _ _ hε
  rotate_left
  -- stability under addition
  · rintro f g ⟨f_cont, f_mem, f_bd⟩ ⟨g_cont, g_mem, g_bd⟩
    refine' ⟨f_cont.add g_cont, f_mem.add g_mem, _⟩
    let f' : α →ᵇ E := ⟨⟨f, f_cont⟩, Metric.isBounded_range_iff.1 f_bd⟩
    let g' : α →ᵇ E := ⟨⟨g, g_cont⟩, Metric.isBounded_range_iff.1 g_bd⟩
    exact (f' + g').isBounded_range
  -- ae strong measurability
  · exact fun f ⟨_, h, _⟩ => h.aestronglyMeasurable
  -- We are left with approximating characteristic functions.
  -- This follows from `exists_continuous_snorm_sub_le_of_closed`.
  intro c t ht htμ ε hε
  rcases exists_Lp_half E μ p hε with ⟨δ, δpos, hδ⟩
  obtain ⟨η, ηpos, hη⟩ :
    ∃ η : ℝ≥0, 0 < η ∧ ∀ s : Set α, μ s ≤ η → snorm (s.indicator fun _x => c) p μ ≤ δ
  exact exists_snorm_indicator_le hp c δpos.ne'
  have hη_pos' : (0 : ℝ≥0∞) < η := ENNReal.coe_pos.2 ηpos
  obtain ⟨s, st, s_closed, μs⟩ : ∃ s, s ⊆ t ∧ IsClosed s ∧ μ (t \ s) < η
  exact ht.exists_isClosed_diff_lt htμ.ne hη_pos'.ne'
  have hsμ : μ s < ∞ := (measure_mono st).trans_lt htμ
  have I1 : snorm ((s.indicator fun _y => c) - t.indicator fun _y => c) p μ ≤ δ := by
    

Proof state:
α : Type u_1
inst✝⁶ : MeasurableSpace α
inst✝⁵ : TopologicalSpace α
inst✝⁴ : T4Space α
inst✝³ : BorelSpace α
E : Type u_2
inst✝² : NormedAddCommGroup E
μ : Measure α
p : ℝ≥0∞
inst✝¹ : NormedSpace ℝ E
inst✝ : Measure.WeaklyRegular μ
hp : p ≠ ⊤
f : α → E
hf : Memℒp f p
ε✝ : ℝ≥0∞
hε✝ : ε✝ ≠ 0
c : E
t : Set α
ht : MeasurableSet t
htμ : ↑↑μ t < ⊤
ε : ℝ≥0∞
hε : ε ≠ 0
δ : ℝ≥0∞
δpos : 0 < δ
hδ :
  ∀ (f g : α → E),
    AEStronglyMeasurable f μ → AEStronglyMeasurable g μ → snorm f p μ ≤ δ → snorm g p μ ≤ δ → snorm (f + g) p μ < ε
η : ℝ≥0
ηpos : 0 < η
hη : ∀ (s : Set α), ↑↑μ s ≤ ↑η → snorm (Set.indicator s fun _x => c) p μ ≤ δ
hη_pos' : 0 < ↑η
s : Set α
st : s ⊆ t
s_closed : IsClosed s
μs : ↑↑μ (t \ s) < ↑η
hsμ : ↑↑μ s < ⊤
⊢ snorm ((Set.indicator s fun _y => c) - Set.indicator t fun _y => c) p μ ≤ δ

Next tactic:
rw [← snorm_neg, neg_sub, ← indicator_diff st]