-- Mathlib/MeasureTheory/Measure/LevyProkhorovMetric.lean
/-- The identity map `LevyProkhorov (ProbabilityMeasure Ω) → ProbabilityMeasure Ω` is continuous. -/
lemma LevyProkhorov.continuous_equiv_probabilityMeasure :
    Continuous (LevyProkhorov.equiv (α := ProbabilityMeasure Ω))

Proof state:
case neg.h
Ω : Type u_1
inst✝² : MeasurableSpace Ω
inst✝¹ : PseudoMetricSpace Ω
inst✝ : OpensMeasurableSpace Ω
μs : ℕ → LevyProkhorov (ProbabilityMeasure Ω)
ν : LevyProkhorov (ProbabilityMeasure Ω)
hμs : Tendsto μs atTop (𝓝 ν)
P : ProbabilityMeasure Ω := (equiv (ProbabilityMeasure Ω)) ν
Ps : ℕ → ProbabilityMeasure Ω := fun n => (equiv (ProbabilityMeasure Ω)) (μs n)
f✝ f : Ω →ᵇ ℝ
f_nn : 0 ≤ f
f_zero : ¬‖f‖ = 0
norm_f_pos : 0 < ‖f‖
δ : ℝ
δ_pos : 0 < δ
⊢ limsup (fun i => ∫ (x : Ω), f x ∂↑((⇑(equiv (ProbabilityMeasure Ω)) ∘ μs) i)) atTop ≤ ∫ (x : Ω), f x ∂↑P + δ

Tactic:
apply limsup_le_of_le ?_

Result:
case neg.h
Ω : Type u_1
inst✝² : MeasurableSpace Ω
inst✝¹ : PseudoMetricSpace Ω
inst✝ : OpensMeasurableSpace Ω
μs : ℕ → LevyProkhorov (ProbabilityMeasure Ω)
ν : LevyProkhorov (ProbabilityMeasure Ω)
hμs : Tendsto μs atTop (𝓝 ν)
P : ProbabilityMeasure Ω := (equiv (ProbabilityMeasure Ω)) ν
Ps : ℕ → ProbabilityMeasure Ω := fun n => (equiv (ProbabilityMeasure Ω)) (μs n)
f✝ f : Ω →ᵇ ℝ
f_nn : 0 ≤ f
f_zero : ¬‖f‖ = 0
norm_f_pos : 0 < ‖f‖
δ : ℝ
δ_pos : 0 < δ
⊢ ∀ᶠ (n : ℕ) in atTop, ∫ (x : Ω), f x ∂↑((⇑(equiv (ProbabilityMeasure Ω)) ∘ μs) n) ≤ ∫ (x : Ω), f x ∂↑P + δ

Ω : Type u_1
inst✝² : MeasurableSpace Ω
inst✝¹ : PseudoMetricSpace Ω
inst✝ : OpensMeasurableSpace Ω
μs : ℕ → LevyProkhorov (ProbabilityMeasure Ω)
ν : LevyProkhorov (ProbabilityMeasure Ω)
hμs : Tendsto μs atTop (𝓝 ν)
P : ProbabilityMeasure Ω := (equiv (ProbabilityMeasure Ω)) ν
Ps : ℕ → ProbabilityMeasure Ω := fun n => (equiv (ProbabilityMeasure Ω)) (μs n)
f✝ f : Ω →ᵇ ℝ
f_nn : 0 ≤ f
f_zero : ¬‖f‖ = 0
norm_f_pos : 0 < ‖f‖
δ : ℝ
δ_pos : 0 < δ
⊢ IsCoboundedUnder (fun x1 x2 => x1 ≤ x2) atTop fun i => ∫ (x : Ω), f x ∂↑((⇑(equiv (ProbabilityMeasure Ω)) ∘ μs) i)

Proof state:
Ω : Type u_1
inst✝² : MeasurableSpace Ω
inst✝¹ : PseudoMetricSpace Ω
inst✝ : OpensMeasurableSpace Ω
μs : ℕ → LevyProkhorov (ProbabilityMeasure Ω)
ν : LevyProkhorov (ProbabilityMeasure Ω)
hμs : Tendsto μs atTop (𝓝 ν)
P : ProbabilityMeasure Ω := (equiv (ProbabilityMeasure Ω)) ν
Ps : ℕ → ProbabilityMeasure Ω := fun n => (equiv (ProbabilityMeasure Ω)) (μs n)
f✝ f : Ω →ᵇ ℝ
f_nn : 0 ≤ f
f_zero : ¬‖f‖ = 0
norm_f_pos : 0 < ‖f‖
δ : ℝ
δ_pos : 0 < δ
⊢ IsCoboundedUnder (fun x1 x2 => x1 ≤ x2) atTop fun i => ∫ (x : Ω), f x ∂↑((⇑(equiv (ProbabilityMeasure Ω)) ∘ μs) i)

Tactic:
simp only [IsCoboundedUnder, IsCobounded, eventually_map, eventually_atTop,
           forall_exists_index]

Result:
Ω : Type u_1
inst✝² : MeasurableSpace Ω
inst✝¹ : PseudoMetricSpace Ω
inst✝ : OpensMeasurableSpace Ω
μs : ℕ → LevyProkhorov (ProbabilityMeasure Ω)
ν : LevyProkhorov (ProbabilityMeasure Ω)
hμs : Tendsto μs atTop (𝓝 ν)
P : ProbabilityMeasure Ω := (equiv (ProbabilityMeasure Ω)) ν
Ps : ℕ → ProbabilityMeasure Ω := fun n => (equiv (ProbabilityMeasure Ω)) (μs n)
f✝ f : Ω →ᵇ ℝ
f_nn : 0 ≤ f
f_zero : ¬‖f‖ = 0
norm_f_pos : 0 < ‖f‖
δ : ℝ
δ_pos : 0 < δ
⊢ ∃ b, ∀ (a : ℝ) (x : ℕ), (∀ b ≥ x, ∫ (x : Ω), f x ∂↑((⇑(equiv (ProbabilityMeasure Ω)) ∘ μs) b) ≤ a) → b ≤ a

Proof state:
case neg.h.intro.intro.intro
Ω : Type u_1
inst✝² : MeasurableSpace Ω
inst✝¹ : PseudoMetricSpace Ω
inst✝ : OpensMeasurableSpace Ω
μs : ℕ → LevyProkhorov (ProbabilityMeasure Ω)
ν : LevyProkhorov (ProbabilityMeasure Ω)
hμs : Tendsto μs atTop (𝓝 ν)
P : ProbabilityMeasure Ω := (equiv (ProbabilityMeasure Ω)) ν
Ps : ℕ → ProbabilityMeasure Ω := fun n => (equiv (ProbabilityMeasure Ω)) (μs n)
f✝ f : Ω →ᵇ ℝ
f_nn : 0 ≤ f
f_zero : ¬‖f‖ = 0
norm_f_pos : 0 < ‖f‖
δ : ℝ
δ_pos : 0 < δ
εs : ℕ → ℝ
left✝ : StrictAnti εs
εs_pos : ∀ (n : ℕ), 0 < εs n
εs_lim : Tendsto εs atTop (𝓝 0)
ε_of_room : Tendsto (fun x => dist (μs x) ν + εs x) atTop (𝓝 0)
ε_of_room' : Tendsto (fun n => dist (μs n) ν + εs n) atTop (𝓝[>] 0)
key :
  Tendsto
    ((fun ε => ∫ (t : ℝ) in Ioc 0 ‖f‖, (↑(P (thickening ε {a | t ≤ f a}))).toReal) ∘ fun n => dist (μs n) ν + εs n)
    atTop (𝓝 (∫ (t : ℝ) in Ioc 0 ‖f‖, (↑(P {a | t ≤ f a})).toReal))
aux : ∀ (z : ℝ), Iio (z + δ / 2) ∈ 𝓝 z
⊢ ∀ᶠ (n : ℕ) in atTop, ∫ (x : Ω), f x ∂↑((⇑(equiv (ProbabilityMeasure Ω)) ∘ μs) n) ≤ ∫ (x : Ω), f x ∂↑P + δ

Tactic:
filter_upwards [key (aux _), ε_of_room <| Iio_mem_nhds <| half_pos <|
                  mul_pos (inv_pos.mpr norm_f_pos) δ_pos]
  with n hn hn'

Result:
case h
Ω : Type u_1
inst✝² : MeasurableSpace Ω
inst✝¹ : PseudoMetricSpace Ω
inst✝ : OpensMeasurableSpace Ω
μs : ℕ → LevyProkhorov (ProbabilityMeasure Ω)
ν : LevyProkhorov (ProbabilityMeasure Ω)
hμs : Tendsto μs atTop (𝓝 ν)
P : ProbabilityMeasure Ω := (equiv (ProbabilityMeasure Ω)) ν
Ps : ℕ → ProbabilityMeasure Ω := fun n => (equiv (ProbabilityMeasure Ω)) (μs n)
f✝ f : Ω →ᵇ ℝ
f_nn : 0 ≤ f
f_zero : ¬‖f‖ = 0
norm_f_pos : 0 < ‖f‖
δ : ℝ
δ_pos : 0 < δ
εs : ℕ → ℝ
left✝ : StrictAnti εs
εs_pos : ∀ (n : ℕ), 0 < εs n
εs_lim : Tendsto εs atTop (𝓝 0)
ε_of_room : Tendsto (fun x => dist (μs x) ν + εs x) atTop (𝓝 0)
ε_of_room' : Tendsto (fun n => dist (μs n) ν + εs n) atTop (𝓝[>] 0)
key :
  Tendsto
    ((fun ε => ∫ (t : ℝ) in Ioc 0 ‖f‖, (↑(P (thickening ε {a | t ≤ f a}))).toReal) ∘ fun n => dist (μs n) ν + εs n)
    atTop (𝓝 (∫ (t : ℝ) in Ioc 0 ‖f‖, (↑(P {a | t ≤ f a})).toReal))
aux : ∀ (z : ℝ), Iio (z + δ / 2) ∈ 𝓝 z
n : ℕ
hn :
  n ∈
    ((fun ε => ∫ (t : ℝ) in Ioc 0 ‖f‖, (↑(P (thickening ε {a | t ≤ f a}))).toReal) ∘ fun n => dist (μs n) ν + εs n) ⁻¹'
      Iio ((∫ (t : ℝ) in Ioc 0 ‖f‖, (↑(P {a | t ≤ f a})).toReal) + δ / 2)
hn' : n ∈ (fun x => dist (μs x) ν + εs x) ⁻¹' Iio (‖f‖⁻¹ * δ / 2)
⊢ ∫ (x : Ω), f x ∂↑((⇑(equiv (ProbabilityMeasure Ω)) ∘ μs) n) ≤ ∫ (x : Ω), f x ∂↑P + δ

Proof state:
case neg
Ω : Type u_1
inst✝² : MeasurableSpace Ω
inst✝¹ : PseudoMetricSpace Ω
inst✝ : OpensMeasurableSpace Ω
μs : ℕ → LevyProkhorov (ProbabilityMeasure Ω)
ν : LevyProkhorov (ProbabilityMeasure Ω)
hμs : Tendsto μs atTop (𝓝 ν)
P : ProbabilityMeasure Ω := (equiv (ProbabilityMeasure Ω)) ν
Ps : ℕ → ProbabilityMeasure Ω := fun n => (equiv (ProbabilityMeasure Ω)) (μs n)
f✝ f : Ω →ᵇ ℝ
f_nn : 0 ≤ f
f_zero : ¬‖f‖ = 0
norm_f_pos : 0 < ‖f‖
⊢ limsup (fun i => ∫ (x : Ω), f x ∂↑((⇑(equiv (ProbabilityMeasure Ω)) ∘ μs) i)) atTop ≤ ∫ (x : Ω), f x ∂↑P

Tactic:
apply _root_.le_of_forall_pos_le_add

Result:
case neg.h
Ω : Type u_1
inst✝² : MeasurableSpace Ω
inst✝¹ : PseudoMetricSpace Ω
inst✝ : OpensMeasurableSpace Ω
μs : ℕ → LevyProkhorov (ProbabilityMeasure Ω)
ν : LevyProkhorov (ProbabilityMeasure Ω)
hμs : Tendsto μs atTop (𝓝 ν)
P : ProbabilityMeasure Ω := (equiv (ProbabilityMeasure Ω)) ν
Ps : ℕ → ProbabilityMeasure Ω := fun n => (equiv (ProbabilityMeasure Ω)) (μs n)
f✝ f : Ω →ᵇ ℝ
f_nn : 0 ≤ f
f_zero : ¬‖f‖ = 0
norm_f_pos : 0 < ‖f‖
⊢ ∀ (ε : ℝ),
    0 < ε → limsup (fun i => ∫ (x : Ω), f x ∂↑((⇑(equiv (ProbabilityMeasure Ω)) ∘ μs) i)) atTop ≤ ∫ (x : Ω), f x ∂↑P + ε