mathlib-initiative/mathlib-tactics huggingface dataset:
Module: Mathlib.MeasureTheory.Covering.Vitali

Goal state before:
pp: α : Type u_1
ι : Type u_2
B : ι → Set α
t : Set ι
δ : ι → ℝ
τ : ℝ
hτ : 1 < τ
δnonneg : ∀ a ∈ t, 0 ≤ δ a
R : ℝ
δle : ∀ a ∈ t, δ a ≤ R
hne : ∀ a ∈ t, (B a).Nonempty
T : Set (Set ι) :=
  {u |
    u ⊆ t ∧
      u.PairwiseDisjoint B ∧ ∀ a ∈ t, ∀ b ∈ u, (B a ∩ B b).Nonempty → ∃ c ∈ u, (B a ∩ B c).Nonempty ∧ δ a ≤ τ * δ c}
u : Set ι
hu : Maximal (fun x ↦ x ∈ T) u
a : ι
hat : a ∈ t
hcon : ∀ b ∈ u, (B a ∩ B b).Nonempty → τ * δ b < δ a
a_disj : ∀ c ∈ u, Disjoint (B a) (B c)
A : Set ι := {a' | a' ∈ t ∧ ∀ c ∈ u, Disjoint (B a') (B c)}
Anonempty : A.Nonempty
m : ℝ := sSup (δ '' A)
bddA : BddAbove (δ '' A)
this : 0 ≤ m
mpos : 0 < m
⊢ m < m * τ

Tactic:
]

Goal state after:
α : Type u_1
ι : Type u_2
B : ι → Set α
t : Set ι
δ : ι → ℝ
τ : ℝ
hτ : 1 < τ
δnonneg : ∀ a ∈ t, 0 ≤ δ a
R : ℝ
δle : ∀ a ∈ t, δ a ≤ R
hne : ∀ a ∈ t, (B a).Nonempty
T : Set (Set ι) :=
  {u |
    u ⊆ t ∧
      u.PairwiseDisjoint B ∧ ∀ a ∈ t, ∀ b ∈ u, (B a ∩ B b).Nonempty → ∃ c ∈ u, (B a ∩ B c).Nonempty ∧ δ a ≤ τ * δ c}
u : Set ι
hu : Maximal (fun x ↦ x ∈ T) u
a : ι
hat : a ∈ t
hcon : ∀ b ∈ u, (B a ∩ B b).Nonempty → τ * δ b < δ a
a_disj : ∀ c ∈ u, Disjoint (B a) (B c)
A : Set ι := {a' | a' ∈ t ∧ ∀ c ∈ u, Disjoint (B a') (B c)}
Anonempty : A.Nonempty
m : ℝ := sSup (δ '' A)
bddA : BddAbove (δ '' A)
this : 0 ≤ m
mpos : 0 < m
⊢ m < m * τ
Module: Mathlib.Analysis.Asymptotics.ExpGrowth

Goal state before:
pp: case insert
α : Type u_1
u : α → ℕ → ℝ≥0∞
a : α
t : Finset α
a_t : a ∉ t
ha : expGrowthSup (∑ x ∈ t, u x) = ⨆ x ∈ t, expGrowthSup (u x)
⊢ max (expGrowthSup (u a)) (⨆ x ∈ t, expGrowthSup (u x)) = max (expGrowthSup (u a)) (⨆ x ∈ t, expGrowthSup (u x))

Tactic:
]

Goal state after:
Module: Mathlib.Analysis.Asymptotics.ExpGrowth

Goal state before:
pp: u : ℕ → ℝ≥0∞
v : ℕ → ℕ
hu : 1 ≤ᶠ[atTop] u
hv : Tendsto v atTop atTop
n : ℕ
h : 1 ≤ u n
⊢ 0 n ≤ (u n).log

Tactic:
]

Goal state after:
u : ℕ → ℝ≥0∞
v : ℕ → ℕ
hu : 1 ≤ᶠ[atTop] u
hv : Tendsto v atTop atTop
n : ℕ
h : 1 ≤ u n
⊢ 0 n ≤ (u n).log
Module: Mathlib.Analysis.Asymptotics.ExpGrowth

Goal state before:
pp: u : ℕ → ℝ≥0∞
v : ℕ → ℕ
hu : 1 ≤ᶠ[atTop] u
hv : Tendsto v atTop atTop
n : ℕ
h : 1 ≤ u n
⊢ 1 ≤ u n

Tactic:
]

Goal state after:
u : ℕ → ℝ≥0∞
v : ℕ → ℕ
hu : 1 ≤ᶠ[atTop] u
hv : Tendsto v atTop atTop
n : ℕ
h : 1 ≤ u n
⊢ 1 ≤ u n
Module: Mathlib.Analysis.Asymptotics.LinearGrowth

Goal state before:
pp: case neg
u : ℕ → EReal
v : ℕ → ℕ
h : Monotone u
hv : (linearGrowthInf fun n ↦ ↑(v n)) ≠ 0
v_0 : 0 < linearGrowthInf fun n ↦ ↑(v n)
u_0 : ¬u = ⊥
a : EReal
a_0 : 0 < a
a_v : a < linearGrowthInf fun n ↦ ↑(v n)
b : EReal
b_0 : 0 < b
b_u : b < linearGrowthSup u
a' : EReal
a_a' : a < a'
a_top' : a' ≠ ⊤
a_0' : 0 < a'
a_a_inv' : a'⁻¹ < a⁻¹
a_v' : ∀ᶠ (n : ℕ) in atTop, a' * ↑n ≤ ↑(v n)
⊢ ∃ᶠ (x : ℕ) in atTop, a' * ↑x ≤ ↑(v x) → a * b * ↑x ≤ (u ∘ v) x

Tactic:
]

Goal state after:
case neg
u : ℕ → EReal
v : ℕ → ℕ
h : Monotone u
hv : (linearGrowthInf fun n ↦ ↑(v n)) ≠ 0
v_0 : 0 < linearGrowthInf fun n ↦ ↑(v n)
u_0 : ¬u = ⊥
a : EReal
a_0 : 0 < a
a_v : a < linearGrowthInf fun n ↦ ↑(v n)
b : EReal
b_0 : 0 < b
b_u : b < linearGrowthSup u
a' : EReal
a_a' : a < a'
a_top' : a' ≠ ⊤
a_0' : 0 < a'
a_a_inv' : a'⁻¹ < a⁻¹
a_v' : ∀ᶠ (n : ℕ) in atTop, a' * ↑n ≤ ↑(v n)
⊢ ∃ᶠ (x : ℕ) in atTop, a' * ↑x ≤ ↑(v x) → a * b * ↑x ≤ (u ∘ v) x
Module: Mathlib.Analysis.Asymptotics.ExpGrowth

Goal state before:
pp: u : ℕ → ℝ≥0∞
v : ℕ → ℕ
hu : ∃ᶠ (n : ℕ) in atTop, 1 ≤ u n
hv₀ : (linearGrowthSup fun n ↦ ↑(v n)) ≠ 0
hv₁ : (linearGrowthSup fun n ↦ ↑(v n)) ≠ ⊤
hv₂ : Tendsto v atTop atTop
n : ℕ
h : 1 ≤ u n
⊢ 1 ≤ u n

Tactic:
]

Goal state after:
u : ℕ → ℝ≥0∞
v : ℕ → ℕ
hu : ∃ᶠ (n : ℕ) in atTop, 1 ≤ u n
hv₀ : (linearGrowthSup fun n ↦ ↑(v n)) ≠ 0
hv₁ : (linearGrowthSup fun n ↦ ↑(v n)) ≠ ⊤
hv₂ : Tendsto v atTop atTop
n : ℕ
h : 1 ≤ u n
⊢ 1 ≤ u n
Module: Mathlib.MeasureTheory.Covering.Vitali

Goal state before:
pp: case refine_1
α : Type u_1
ι : Type u_2
B : ι → Set α
t : Set ι
δ : ι → ℝ
τ : ℝ
hτ : 1 < τ
δnonneg : ∀ a ∈ t, 0 ≤ δ a
R : ℝ
δle : ∀ a ∈ t, δ a ≤ R
hne : ∀ a ∈ t, (B a).Nonempty
T : Set (Set ι) :=
  {u |
    u ⊆ t ∧
      u.PairwiseDisjoint B ∧ ∀ a ∈ t, ∀ b ∈ u, (B a ∩ B b).Nonempty → ∃ c ∈ u, (B a ∩ B c).Nonempty ∧ δ a ≤ τ * δ c}
u : Set ι
hu : Maximal (fun x ↦ x ∈ T) u
A : Set ι := {a' | a' ∈ t ∧ ∀ c ∈ u, Disjoint (B a') (B c)}
Anonempty : A.Nonempty
m : ℝ := sSup (δ '' A)
bddA : BddAbove (δ '' A)
a' : ι
a'A : a' ∈ A
ha' : m / τ ≤ δ a'
a'_ne_u : a' ∉ u
⊢ a' ∈ t ∧ u ⊆ t

Tactic:
]

Goal state after:
case refine_1
α : Type u_1
ι : Type u_2
B : ι → Set α
t : Set ι
δ : ι → ℝ
τ : ℝ
hτ : 1 < τ
δnonneg : ∀ a ∈ t, 0 ≤ δ a
R : ℝ
δle : ∀ a ∈ t, δ a ≤ R
hne : ∀ a ∈ t, (B a).Nonempty
T : Set (Set ι) :=
  {u |
    u ⊆ t ∧
      u.PairwiseDisjoint B ∧ ∀ a ∈ t, ∀ b ∈ u, (B a ∩ B b).Nonempty → ∃ c ∈ u, (B a ∩ B c).Nonempty ∧ δ a ≤ τ * δ c}
u : Set ι
hu : Maximal (fun x ↦ x ∈ T) u
A : Set ι := {a' | a' ∈ t ∧ ∀ c ∈ u, Disjoint (B a') (B c)}
Anonempty : A.Nonempty
m : ℝ := sSup (δ '' A)
bddA : BddAbove (δ '' A)
a' : ι
a'A : a' ∈ A
ha' : m / τ ≤ δ a'
a'_ne_u : a' ∉ u
⊢ a' ∈ t ∧ u ⊆ t
Module: Mathlib.Analysis.Asymptotics.LinearGrowth

Goal state before:
pp: case neg.refine_1
u : ℕ → EReal
v : ℕ → ℕ
h : Monotone u
hv : (linearGrowthInf fun n ↦ ↑(v n)) ≠ 0
v_0 : 0 < linearGrowthInf fun n ↦ ↑(v n)
u_0 : ¬u = ⊥
a : EReal
a_0 : 0 < a
a_v : a < linearGrowthInf fun n ↦ ↑(v n)
b : EReal
b_0 : 0 < b
a' : EReal
a_a' : a < a'
a_top' : a' ≠ ⊤
a_0' : 0 < a'
a_a_inv' : a'⁻¹ < a⁻¹
a_v' : ∀ᶠ (n : ℕ) in atTop, a' * ↑n ≤ ↑(v n)
b_u : ∃ᶠ (x : ℕ) in atTop, (b * ↑x ≤ u x ∧ 0 < x) ∧ ∃ m, a'⁻¹ * ↑x ≤ ↑m ∧ ↑m ≤ a⁻¹ * ↑x
M M' : ℕ
aM_M' : ↑M ≤ a'⁻¹ * ↑M'
n : ℕ
n_M' : M' ≤ n
bn_un : b * ↑n ≤ u n
right✝ : 0 < n
k : ℕ
an_k' : a'⁻¹ * ↑n ≤ ↑k
k_an : ↑k ≤ a⁻¹ * ↑n
⊢ M ≤ k

Tactic:
]

Goal state after:
case neg.refine_1
u : ℕ → EReal
v : ℕ → ℕ
h : Monotone u
hv : (linearGrowthInf fun n ↦ ↑(v n)) ≠ 0
v_0 : 0 < linearGrowthInf fun n ↦ ↑(v n)
u_0 : ¬u = ⊥
a : EReal
a_0 : 0 < a
a_v : a < linearGrowthInf fun n ↦ ↑(v n)
b : EReal
b_0 : 0 < b
a' : EReal
a_a' : a < a'
a_top' : a' ≠ ⊤
a_0' : 0 < a'
a_a_inv' : a'⁻¹ < a⁻¹
a_v' : ∀ᶠ (n : ℕ) in atTop, a' * ↑n ≤ ↑(v n)
b_u : ∃ᶠ (x : ℕ) in atTop, (b * ↑x ≤ u x ∧ 0 < x) ∧ ∃ m, a'⁻¹ * ↑x ≤ ↑m ∧ ↑m ≤ a⁻¹ * ↑x
M M' : ℕ
aM_M' : ↑M ≤ a'⁻¹ * ↑M'
n : ℕ
n_M' : M' ≤ n
bn_un : b * ↑n ≤ u n
right✝ : 0 < n
k : ℕ
an_k' : a'⁻¹ * ↑n ≤ ↑k
k_an : ↑k ≤ a⁻¹ * ↑n
⊢ M ≤ k
Module: Mathlib.Analysis.Asymptotics.LinearGrowth

Goal state before:
pp: case neg.refine_2
u : ℕ → EReal
v : ℕ → ℕ
h : Monotone u
hv : (linearGrowthInf fun n ↦ ↑(v n)) ≠ 0
v_0 : 0 < linearGrowthInf fun n ↦ ↑(v n)
u_0 : ¬u = ⊥
a : EReal
a_0 : 0 < a
a_v : a < linearGrowthInf fun n ↦ ↑(v n)
b : EReal
b_0 : 0 < b
a' : EReal
a_a' : a < a'
a_top' : a' ≠ ⊤
a_0' : 0 < a'
a_a_inv' : a'⁻¹ < a⁻¹
a_v' : ∀ᶠ (n : ℕ) in atTop, a' * ↑n ≤ ↑(v n)
b_u : ∃ᶠ (x : ℕ) in atTop, (b * ↑x ≤ u x ∧ 0 < x) ∧ ∃ m, a'⁻¹ * ↑x ≤ ↑m ∧ ↑m ≤ a⁻¹ * ↑x
M M' : ℕ
aM_M' : a' * ↑M ≤ ↑M'
n : ℕ
n_M' : M' ≤ n
bn_un : b * ↑n ≤ u n
right✝ : 0 < n
k : ℕ
an_k' : a'⁻¹ * ↑n ≤ ↑k
k_an : ↑k ≤ a⁻¹ * ↑n
ak_vk' : a' * ↑k ≤ ↑(v k)
⊢ b * (a * ↑k) ≤ u (v k)

Tactic:
]

Goal state after:
case neg.refine_2
u : ℕ → EReal
v : ℕ → ℕ
h : Monotone u
hv : (linearGrowthInf fun n ↦ ↑(v n)) ≠ 0
v_0 : 0 < linearGrowthInf fun n ↦ ↑(v n)
u_0 : ¬u = ⊥
a : EReal
a_0 : 0 < a
a_v : a < linearGrowthInf fun n ↦ ↑(v n)
b : EReal
b_0 : 0 < b
a' : EReal
a_a' : a < a'
a_top' : a' ≠ ⊤
a_0' : 0 < a'
a_a_inv' : a'⁻¹ < a⁻¹
a_v' : ∀ᶠ (n : ℕ) in atTop, a' * ↑n ≤ ↑(v n)
b_u : ∃ᶠ (x : ℕ) in atTop, (b * ↑x ≤ u x ∧ 0 < x) ∧ ∃ m, a'⁻¹ * ↑x ≤ ↑m ∧ ↑m ≤ a⁻¹ * ↑x
M M' : ℕ
aM_M' : a' * ↑M ≤ ↑M'
n : ℕ
n_M' : M' ≤ n
bn_un : b * ↑n ≤ u n
right✝ : 0 < n
k : ℕ
an_k' : a'⁻¹ * ↑n ≤ ↑k
k_an : ↑k ≤ a⁻¹ * ↑n
ak_vk' : a' * ↑k ≤ ↑(v k)
⊢ b * (a * ↑k) ≤ u (v k)
Module: Mathlib.Analysis.Asymptotics.LinearGrowth

Goal state before:
pp: case neg.refine_2
u : ℕ → EReal
v : ℕ → ℕ
h : Monotone u
hv : (linearGrowthInf fun n ↦ ↑(v n)) ≠ 0
v_0 : 0 < linearGrowthInf fun n ↦ ↑(v n)
u_0 : ¬u = ⊥
a : EReal
a_0 : 0 < a
a_v : a < linearGrowthInf fun n ↦ ↑(v n)
b : EReal
b_0 : 0 < b
a' : EReal
a_a' : a < a'
a_top' : a' ≠ ⊤
a_0' : 0 < a'
a_a_inv' : a'⁻¹ < a⁻¹
a_v' : ∀ᶠ (n : ℕ) in atTop, a' * ↑n ≤ ↑(v n)
b_u : ∃ᶠ (x : ℕ) in atTop, (b * ↑x ≤ u x ∧ 0 < x) ∧ ∃ m, a'⁻¹ * ↑x ≤ ↑m ∧ ↑m ≤ a⁻¹ * ↑x
M M' : ℕ
aM_M' : a' * ↑M ≤ ↑M'
n : ℕ
n_M' : M' ≤ n
bn_un : b * ↑n ≤ u n
right✝ : 0 < n
k : ℕ
an_k' : ↑n ≤ a' * ↑k
k_an : ↑k ≤ a⁻¹ * ↑n
ak_vk' : a' * ↑k ≤ ↑(v k)
⊢ b * (a * ↑k) ≤ u (v k)

Tactic:
]

Goal state after:
case neg.refine_2
u : ℕ → EReal
v : ℕ → ℕ
h : Monotone u
hv : (linearGrowthInf fun n ↦ ↑(v n)) ≠ 0
v_0 : 0 < linearGrowthInf fun n ↦ ↑(v n)
u_0 : ¬u = ⊥
a : EReal
a_0 : 0 < a
a_v : a < linearGrowthInf fun n ↦ ↑(v n)
b : EReal
b_0 : 0 < b
a' : EReal
a_a' : a < a'
a_top' : a' ≠ ⊤
a_0' : 0 < a'
a_a_inv' : a'⁻¹ < a⁻¹
a_v' : ∀ᶠ (n : ℕ) in atTop, a' * ↑n ≤ ↑(v n)
b_u : ∃ᶠ (x : ℕ) in atTop, (b * ↑x ≤ u x ∧ 0 < x) ∧ ∃ m, a'⁻¹ * ↑x ≤ ↑m ∧ ↑m ≤ a⁻¹ * ↑x
M M' : ℕ
aM_M' : a' * ↑M ≤ ↑M'
n : ℕ
n_M' : M' ≤ n
bn_un : b * ↑n ≤ u n
right✝ : 0 < n
k : ℕ
an_k' : ↑n ≤ a' * ↑k
k_an : ↑k ≤ a⁻¹ * ↑n
ak_vk' : a' * ↑k ≤ ↑(v k)
⊢ b * (a * ↑k) ≤ u (v k)
Module: Mathlib.Analysis.Asymptotics.LinearGrowth

Goal state before:
pp: case neg.refine_2
u : ℕ → EReal
v : ℕ → ℕ
h : Monotone u
hv : (linearGrowthInf fun n ↦ ↑(v n)) ≠ 0
v_0 : 0 < linearGrowthInf fun n ↦ ↑(v n)
u_0 : ¬u = ⊥
a : EReal
a_0 : 0 < a
a_v : a < linearGrowthInf fun n ↦ ↑(v n)
b : EReal
b_0 : 0 < b
a' : EReal
a_a' : a < a'
a_top' : a' ≠ ⊤
a_0' : 0 < a'
a_a_inv' : a'⁻¹ < a⁻¹
a_v' : ∀ᶠ (n : ℕ) in atTop, a' * ↑n ≤ ↑(v n)
b_u : ∃ᶠ (x : ℕ) in atTop, (b * ↑x ≤ u x ∧ 0 < x) ∧ ∃ m, a'⁻¹ * ↑x ≤ ↑m ∧ ↑m ≤ a⁻¹ * ↑x
M M' : ℕ
aM_M' : a' * ↑M ≤ ↑M'
n : ℕ
n_M' : M' ≤ n
bn_un : b * ↑n ≤ u n
right✝ : 0 < n
k : ℕ
an_k' : ↑n ≤ a' * ↑k
k_an : a * ↑k ≤ ↑n
ak_vk' : a' * ↑k ≤ ↑(v k)
⊢ b * (a * ↑k) ≤ u (v k)

Tactic:
]

Goal state after:
case neg.refine_2
u : ℕ → EReal
v : ℕ → ℕ
h : Monotone u
hv : (linearGrowthInf fun n ↦ ↑(v n)) ≠ 0
v_0 : 0 < linearGrowthInf fun n ↦ ↑(v n)
u_0 : ¬u = ⊥
a : EReal
a_0 : 0 < a
a_v : a < linearGrowthInf fun n ↦ ↑(v n)
b : EReal
b_0 : 0 < b
a' : EReal
a_a' : a < a'
a_top' : a' ≠ ⊤
a_0' : 0 < a'
a_a_inv' : a'⁻¹ < a⁻¹
a_v' : ∀ᶠ (n : ℕ) in atTop, a' * ↑n ≤ ↑(v n)
b_u : ∃ᶠ (x : ℕ) in atTop, (b * ↑x ≤ u x ∧ 0 < x) ∧ ∃ m, a'⁻¹ * ↑x ≤ ↑m ∧ ↑m ≤ a⁻¹ * ↑x
M M' : ℕ
aM_M' : a' * ↑M ≤ ↑M'
n : ℕ
n_M' : M' ≤ n
bn_un : b * ↑n ≤ u n
right✝ : 0 < n
k : ℕ
an_k' : ↑n ≤ a' * ↑k
k_an : a * ↑k ≤ ↑n
ak_vk' : a' * ↑k ≤ ↑(v k)
⊢ b * (a * ↑k) ≤ u (v k)
Module: Mathlib.Analysis.Asymptotics.LinearGrowth

Goal state before:
pp: u : ℕ → EReal
v : ℕ → ℕ
a : EReal
h : Monotone u
hv : Tendsto (fun n ↦ ↑(v n) / ↑n) atTop (𝓝 a)
ha : liminf (fun n ↦ ↑(v n) / ↑n) atTop ≠ 0
ha' : a ≠ ⊤
⊢ 0 < liminf (fun n ↦ ↑(v n) / ↑n) atTop

Tactic:
]

Goal state after:
u : ℕ → EReal
v : ℕ → ℕ
a : EReal
h : Monotone u
hv : Tendsto (fun n ↦ ↑(v n) / ↑n) atTop (𝓝 a)
ha : liminf (fun n ↦ ↑(v n) / ↑n) atTop ≠ 0
ha' : a ≠ ⊤
⊢ 0 < liminf (fun n ↦ ↑(v n) / ↑n) atTop
Module: Mathlib.Analysis.Asymptotics.LinearGrowth

Goal state before:
pp: case pos
u : ℕ → EReal
v : ℕ → ℕ
a : EReal
h : Monotone u
hv : Tendsto (fun n ↦ ↑(v n) / ↑n) atTop (𝓝 a)
ha : a ≠ 0
ha' : a ≠ ⊤
hv₁ : 0 < liminf (fun n ↦ ↑(v n) / ↑n) atTop
v_top : Tendsto v atTop atTop
u_0 : u = ⊥
⊢ ⊥ = ⊥

Tactic:
]

Goal state after:
Module: Mathlib.MeasureTheory.Covering.Vitali

Goal state before:
pp: case neg.inr
α : Type u_1
ι : Type u_2
B : ι → Set α
t : Set ι
δ : ι → ℝ
τ : ℝ
hτ : 1 < τ
δnonneg : ∀ a ∈ t, 0 ≤ δ a
R : ℝ
δle : ∀ a ∈ t, δ a ≤ R
hne : ∀ a ∈ t, (B a).Nonempty
T : Set (Set ι) :=
  {u |
    u ⊆ t ∧
      u.PairwiseDisjoint B ∧ ∀ a ∈ t, ∀ b ∈ u, (B a ∩ B b).Nonempty → ∃ c ∈ u, (B a ∩ B c).Nonempty ∧ δ a ≤ τ * δ c}
u : Set ι
hu : Maximal (fun x ↦ x ∈ T) u
A : Set ι := {a' | a' ∈ t ∧ ∀ c ∈ u, Disjoint (B a') (B c)}
Anonempty : A.Nonempty
m : ℝ := sSup (δ '' A)
bddA : BddAbove (δ '' A)
a' : ι
a'A : a' ∈ A
ha' : m / τ ≤ δ a'
a'_ne_u : a' ∉ u
c : ι
ct : c ∈ t
b : ι
ba'u : b ∈ insert a' u
hcb : ¬Disjoint (B c) (B b)
H : ∀ d ∈ u, Disjoint (B c) (B d)
H' : b ∈ u
⊢ ∃ c_1 ∈ insert a' u, (B c ∩ B c_1).Nonempty ∧ δ c ≤ τ * δ c_1

Tactic:
]

Goal state after:
case neg.inr
α : Type u_1
ι : Type u_2
B : ι → Set α
t : Set ι
δ : ι → ℝ
τ : ℝ
hτ : 1 < τ
δnonneg : ∀ a ∈ t, 0 ≤ δ a
R : ℝ
δle : ∀ a ∈ t, δ a ≤ R
hne : ∀ a ∈ t, (B a).Nonempty
T : Set (Set ι) :=
  {u |
    u ⊆ t ∧
      u.PairwiseDisjoint B ∧ ∀ a ∈ t, ∀ b ∈ u, (B a ∩ B b).Nonempty → ∃ c ∈ u, (B a ∩ B c).Nonempty ∧ δ a ≤ τ * δ c}
u : Set ι
hu : Maximal (fun x ↦ x ∈ T) u
A : Set ι := {a' | a' ∈ t ∧ ∀ c ∈ u, Disjoint (B a') (B c)}
Anonempty : A.Nonempty
m : ℝ := sSup (δ '' A)
bddA : BddAbove (δ '' A)
a' : ι
a'A : a' ∈ A
ha' : m / τ ≤ δ a'
a'_ne_u : a' ∉ u
c : ι
ct : c ∈ t
b : ι
ba'u : b ∈ insert a' u
hcb : ¬Disjoint (B c) (B b)
H : ∀ d ∈ u, Disjoint (B c) (B d)
H' : b ∈ u
⊢ ∃ c_1 ∈ insert a' u, (B c ∩ B c_1).Nonempty ∧ δ c ≤ τ * δ c_1
Module: Mathlib.Analysis.Asymptotics.LinearGrowth

Goal state before:
pp: case pos
u : ℕ → EReal
v : ℕ → ℕ
a : EReal
h : Monotone u
hv : Tendsto (fun n ↦ ↑(v n) / ↑n) atTop (𝓝 a)
ha : a ≠ 0
ha' : a ≠ ⊤
hv₁ : 0 < liminf (fun n ↦ ↑(v n) / ↑n) atTop
v_top : Tendsto v atTop atTop
u_0 : ¬u = ⊥
h' : ∀ (n : ℕ), u n ≤ 0
u_0' : linearGrowthInf u = 0
⊢ linearGrowthInf (u ∘ v) = 0

Tactic:
]

Goal state after:
case pos
u : ℕ → EReal
v : ℕ → ℕ
a : EReal
h : Monotone u
hv : Tendsto (fun n ↦ ↑(v n) / ↑n) atTop (𝓝 a)
ha : a ≠ 0
ha' : a ≠ ⊤
hv₁ : 0 < liminf (fun n ↦ ↑(v n) / ↑n) atTop
v_top : Tendsto v atTop atTop
u_0 : ¬u = ⊥
h' : ∀ (n : ℕ), u n ≤ 0
u_0' : linearGrowthInf u = 0
⊢ linearGrowthInf (u ∘ v) = 0
Module: Mathlib.MeasureTheory.Integral.Average

Goal state before:
pp: α : Type u_1
m0 : MeasurableSpace α
μ : Measure α
⊢ 0 = 0

Tactic:
]

Goal state after:
Module: Mathlib.MeasureTheory.Integral.Average

Goal state before:
pp: α : Type u_1
m0 : MeasurableSpace α
μ : Measure α
f : α → ℝ≥0∞
⊢ (μ univ)⁻¹ * ∫⁻ (a : α), f a ∂μ = (μ univ)⁻¹ * ∫⁻ (x : α), f x ∂μ

Tactic:
]

Goal state after:
Module: Mathlib.MeasureTheory.Measure.Decomposition.Hahn

Goal state before:
pp: α : Type u_1
mα : MeasurableSpace α
μ ν : Measure α
inst✝¹ : IsFiniteMeasure μ
inst✝ : IsFiniteMeasure ν
d : Set α → ℝ := fun s ↦ ↑(μ s).toNNReal - ↑(ν s).toNNReal
c : Set ℝ := d '' {s | MeasurableSet s}
γ : ℝ := sSup c
hμ : ∀ (s : Set α), μ s ≠ ∞
hν : ∀ (s : Set α), ν s ≠ ∞
to_nnreal_μ : ∀ (s : Set α), ↑(μ s).toNNReal = μ s
to_nnreal_ν : ∀ (s : Set α), ↑(ν s).toNNReal = ν s
s t : Set α
ht : MeasurableSet t
⊢ ↑(μ (s ∩ t)).toNNReal + ↑(μ (s \ t)).toNNReal - (↑(ν (s ∩ t)).toNNReal + ↑(ν (s \ t)).toNNReal) =
    ↑(μ (s \ t)).toNNReal - ↑(ν (s \ t)).toNNReal + (↑(μ (s ∩ t)).toNNReal - ↑(ν (s ∩ t)).toNNReal)

Tactic:
]

Goal state after:
α : Type u_1
mα : MeasurableSpace α
μ ν : Measure α
inst✝¹ : IsFiniteMeasure μ
inst✝ : IsFiniteMeasure ν
d : Set α → ℝ := fun s ↦ ↑(μ s).toNNReal - ↑(ν s).toNNReal
c : Set ℝ := d '' {s | MeasurableSet s}
γ : ℝ := sSup c
hμ : ∀ (s : Set α), μ s ≠ ∞
hν : ∀ (s : Set α), ν s ≠ ∞
to_nnreal_μ : ∀ (s : Set α), ↑(μ s).toNNReal = μ s
to_nnreal_ν : ∀ (s : Set α), ↑(ν s).toNNReal = ν s
s t : Set α
ht : MeasurableSet t
⊢ ↑(μ (s ∩ t)).toNNReal + ↑(μ (s \ t)).toNNReal - (↑(ν (s ∩ t)).toNNReal + ↑(ν (s \ t)).toNNReal) =
    ↑(μ (s \ t)).toNNReal - ↑(ν (s \ t)).toNNReal + (↑(μ (s ∩ t)).toNNReal - ↑(ν (s ∩ t)).toNNReal)
Module: Mathlib.MeasureTheory.Integral.Average

Goal state before:
pp: α : Type u_1
m0 : MeasurableSpace α
μ : Measure α
inst✝ : IsProbabilityMeasure μ
f : α → ℝ≥0∞
⊢ ∫⁻ (x : α), f x ∂μ = ∫⁻ (x : α), f x ∂μ

Tactic:
]

Goal state after:
Module: Mathlib.Analysis.Asymptotics.LinearGrowth

Goal state before:
pp: case neg.a
u : ℕ → EReal
v : ℕ → ℕ
a : EReal
h : Monotone u
hv : Tendsto (fun n ↦ ↑(v n) / ↑n) atTop (𝓝 a)
ha : limsup (fun n ↦ ↑(v n) / ↑n) atTop ≠ 0
ha' : limsup (fun n ↦ ↑(v n) / ↑n) atTop ≠ ⊤
hv₁ : 0 < liminf (fun n ↦ ↑(v n) / ↑n) atTop
v_top : Tendsto v atTop atTop
u_0 : ¬u = ⊥
h' : ∀ᶠ (x : ℕ) in atTop, 0 ≤ u x
⊢ linearGrowthInf (u ∘ v) ≤ limsup (fun n ↦ ↑(v n) / ↑n) atTop * linearGrowthInf u

Tactic:
]

Goal state after:
case neg.a
u : ℕ → EReal
v : ℕ → ℕ
a : EReal
h : Monotone u
hv : Tendsto (fun n ↦ ↑(v n) / ↑n) atTop (𝓝 a)
ha : limsup (fun n ↦ ↑(v n) / ↑n) atTop ≠ 0
ha' : limsup (fun n ↦ ↑(v n) / ↑n) atTop ≠ ⊤
hv₁ : 0 < liminf (fun n ↦ ↑(v n) / ↑n) atTop
v_top : Tendsto v atTop atTop
u_0 : ¬u = ⊥
h' : ∀ᶠ (x : ℕ) in atTop, 0 ≤ u x
⊢ linearGrowthInf (u ∘ v) ≤ limsup (fun n ↦ ↑(v n) / ↑n) atTop * linearGrowthInf u
Module: Mathlib.MeasureTheory.Integral.Average

Goal state before:
pp: case inl
α : Type u_1
m0 : MeasurableSpace α
μ : Measure α
inst✝ : IsFiniteMeasure μ
f : α → ℝ≥0∞
hμ : μ = 0
⊢ 0 = 0

Tactic:
]

Goal state after:
Module: Mathlib.Analysis.Asymptotics.LinearGrowth

Goal state before:
pp: case a
u : ℕ → EReal
v : ℕ → ℕ
a : EReal
h : Monotone u
hv : Tendsto (fun n ↦ ↑(v n) / ↑n) atTop (𝓝 a)
ha : a ≠ 0
ha' : a ≠ ⊤
hv₁ : 0 < liminf (fun n ↦ ↑(v n) / ↑n) atTop
v_top : Tendsto v atTop atTop
u_0 : ¬u = ⊥
h' : ∀ᶠ (x : ℕ) in atTop, 0 ≤ u x
⊢ liminf (fun n ↦ ↑(v n) / ↑n) atTop * linearGrowthInf u ≤ linearGrowthInf (u ∘ v)

Tactic:
]

Goal state after:
case a
u : ℕ → EReal
v : ℕ → ℕ
a : EReal
h : Monotone u
hv : Tendsto (fun n ↦ ↑(v n) / ↑n) atTop (𝓝 a)
ha : a ≠ 0
ha' : a ≠ ⊤
hv₁ : 0 < liminf (fun n ↦ ↑(v n) / ↑n) atTop
v_top : Tendsto v atTop atTop
u_0 : ¬u = ⊥
h' : ∀ᶠ (x : ℕ) in atTop, 0 ≤ u x
⊢ liminf (fun n ↦ ↑(v n) / ↑n) atTop * linearGrowthInf u ≤ linearGrowthInf (u ∘ v)
Module: Mathlib.MeasureTheory.Integral.Average

Goal state before:
pp: case inr
α : Type u_1
m0 : MeasurableSpace α
μ : Measure α
inst✝ : IsFiniteMeasure μ
f : α → ℝ≥0∞
hμ : μ ≠ 0
⊢ ∫⁻ (x : α), f x ∂μ = ∫⁻ (x : α), f x ∂μ

Tactic:
]

Goal state after:
Module: Mathlib.MeasureTheory.Integral.Average

Goal state before:
pp: α : Type u_1
m0 : MeasurableSpace α
μ : Measure α
f : α → ℝ≥0∞
s : Set α
⊢ (∫⁻ (x : α) in s, f x ∂μ) / μ s = (∫⁻ (x : α) in s, f x ∂μ) / μ s

Tactic:
]

Goal state after:
Module: Mathlib.Analysis.Asymptotics.LinearGrowth

Goal state before:
pp: case pos
u : ℕ → EReal
v : ℕ → ℕ
a : EReal
h : Monotone u
hv : Tendsto (fun n ↦ ↑(v n) / ↑n) atTop (𝓝 a)
ha : a ≠ 0
ha' : a ≠ ⊤
hv₁ : 0 < liminf (fun n ↦ ↑(v n) / ↑n) atTop
v_top : Tendsto v atTop atTop
u_0 : ¬u = ⊥
u_1 : ∀ᶠ (n : ℕ) in atTop, u n ≤ 0
u_0' : linearGrowthSup u = 0
⊢ linearGrowthSup (u ∘ v) = 0

Tactic:
]

Goal state after:
case pos
u : ℕ → EReal
v : ℕ → ℕ
a : EReal
h : Monotone u
hv : Tendsto (fun n ↦ ↑(v n) / ↑n) atTop (𝓝 a)
ha : a ≠ 0
ha' : a ≠ ⊤
hv₁ : 0 < liminf (fun n ↦ ↑(v n) / ↑n) atTop
v_top : Tendsto v atTop atTop
u_0 : ¬u = ⊥
u_1 : ∀ᶠ (n : ℕ) in atTop, u n ≤ 0
u_0' : linearGrowthSup u = 0
⊢ linearGrowthSup (u ∘ v) = 0
Module: Mathlib.MeasureTheory.Integral.Average

Goal state before:
pp: case inr
α : Type u_1
m0 : MeasurableSpace α
μ : Measure α
f : α → ℝ≥0∞
hf : ∫⁻ (x : α), f x ∂μ ≠ ∞
hμ : μ ≠ 0
⊢ (∫⁻ (x : α), f x ∂μ) / μ univ < ∞

Tactic:
]

Goal state after:
case inr
α : Type u_1
m0 : MeasurableSpace α
μ : Measure α
f : α → ℝ≥0∞
hf : ∫⁻ (x : α), f x ∂μ ≠ ∞
hμ : μ ≠ 0
⊢ (∫⁻ (x : α), f x ∂μ) / μ univ < ∞
Module: Mathlib.Analysis.Asymptotics.LinearGrowth

Goal state before:
pp: case neg.a
u : ℕ → EReal
v : ℕ → ℕ
a : EReal
h : Monotone u
hv : Tendsto (fun n ↦ ↑(v n) / ↑n) atTop (𝓝 a)
ha : limsup (fun n ↦ ↑(v n) / ↑n) atTop ≠ 0
ha' : limsup (fun n ↦ ↑(v n) / ↑n) atTop ≠ ⊤
hv₁ : 0 < liminf (fun n ↦ ↑(v n) / ↑n) atTop
v_top : Tendsto v atTop atTop
u_0 : ¬u = ⊥
u_1 : ∃ᶠ (x : ℕ) in atTop, 0 ≤ u x
⊢ linearGrowthSup (u ∘ v) ≤ limsup (fun n ↦ ↑(v n) / ↑n) atTop * linearGrowthSup u

Tactic:
]

Goal state after:
case neg.a
u : ℕ → EReal
v : ℕ → ℕ
a : EReal
h : Monotone u
hv : Tendsto (fun n ↦ ↑(v n) / ↑n) atTop (𝓝 a)
ha : limsup (fun n ↦ ↑(v n) / ↑n) atTop ≠ 0
ha' : limsup (fun n ↦ ↑(v n) / ↑n) atTop ≠ ⊤
hv₁ : 0 < liminf (fun n ↦ ↑(v n) / ↑n) atTop
v_top : Tendsto v atTop atTop
u_0 : ¬u = ⊥
u_1 : ∃ᶠ (x : ℕ) in atTop, 0 ≤ u x
⊢ linearGrowthSup (u ∘ v) ≤ limsup (fun n ↦ ↑(v n) / ↑n) atTop * linearGrowthSup u
Module: Mathlib.Analysis.Asymptotics.LinearGrowth

Goal state before:
pp: case a
u : ℕ → EReal
v : ℕ → ℕ
a : EReal
h : Monotone u
hv : Tendsto (fun n ↦ ↑(v n) / ↑n) atTop (𝓝 a)
ha : a ≠ 0
ha' : a ≠ ⊤
hv₁ : 0 < liminf (fun n ↦ ↑(v n) / ↑n) atTop
v_top : Tendsto v atTop atTop
u_0 : ¬u = ⊥
u_1 : ∃ᶠ (x : ℕ) in atTop, 0 ≤ u x
⊢ liminf (fun n ↦ ↑(v n) / ↑n) atTop * linearGrowthSup u ≤ linearGrowthSup (u ∘ v)

Tactic:
]

Goal state after:
case a
u : ℕ → EReal
v : ℕ → ℕ
a : EReal
h : Monotone u
hv : Tendsto (fun n ↦ ↑(v n) / ↑n) atTop (𝓝 a)
ha : a ≠ 0
ha' : a ≠ ⊤
hv₁ : 0 < liminf (fun n ↦ ↑(v n) / ↑n) atTop
v_top : Tendsto v atTop atTop
u_0 : ¬u = ⊥
u_1 : ∃ᶠ (x : ℕ) in atTop, 0 ≤ u x
⊢ liminf (fun n ↦ ↑(v n) / ↑n) atTop * linearGrowthSup u ≤ linearGrowthSup (u ∘ v)
Module: Mathlib.MeasureTheory.Integral.Average

Goal state before:
pp: case neg
α : Type u_1
m0 : MeasurableSpace α
μ ν : Measure α
f : α → ℝ≥0∞
hμ : μ univ = ∞
⊢ ⨍⁻ (x : α), f x ∂(μ + ν) =
    μ univ / (μ univ + ν univ) * ⨍⁻ (x : α), f x ∂μ + ν univ / (μ univ + ν univ) * ⨍⁻ (x : α), f x ∂ν

Tactic:
]

Goal state after:
case neg
α : Type u_1
m0 : MeasurableSpace α
μ ν : Measure α
f : α → ℝ≥0∞
hμ : μ univ = ∞
⊢ ⨍⁻ (x : α), f x ∂(μ + ν) =
    μ univ / (μ univ + ν univ) * ⨍⁻ (x : α), f x ∂μ + ν univ / (μ univ + ν univ) * ⨍⁻ (x : α), f x ∂ν
Module: Mathlib.Analysis.Asymptotics.LinearGrowth

Goal state before:
pp: u : ℕ → EReal
m : ℕ
h : Monotone u
hm : m ≠ 0
x : ℕ
hx : 0 < x
⊢ ↑x * (↑m / ↑x) = ↑m

Tactic:
]

Goal state after:
u : ℕ → EReal
m : ℕ
h : Monotone u
hm : m ≠ 0
x : ℕ
hx : 0 < x
⊢ ↑x * (↑m / ↑x) = ↑m
Module: Mathlib.MeasureTheory.Function.StronglyMeasurable.ENNReal

Goal state before:
pp: α : Type u_1
m : MeasurableSpace α
μ : Measure α
f : α → ℝ≥0∞
hf : ∫⁻ (x : α), f x ∂μ ≠ ∞
hf_meas : AEMeasurable f μ
⊢ ∫⁻ (a : α), f a ∂μ ≠ ∞

Tactic:
]

Goal state after:
α : Type u_1
m : MeasurableSpace α
μ : Measure α
f : α → ℝ≥0∞
hf : ∫⁻ (x : α), f x ∂μ ≠ ∞
hf_meas : AEMeasurable f μ
⊢ ∫⁻ (a : α), f a ∂μ ≠ ∞
Module: Mathlib.MeasureTheory.Function.AEEqOfLIntegral

Goal state before:
pp: α : Type u_1
m0 : MeasurableSpace α
μ : Measure α
inst✝ : SigmaFinite μ
f g : α → ℝ≥0∞
hf : AEMeasurable f μ
h : ∀ (s : Set α), MeasurableSet s → μ s < ∞ → ∫⁻ (x : α) in s, f x ∂μ ≤ ∫⁻ (x : α) in s, g x ∂μ
ε N : ℝ≥0
p : ℕ
εpos : 0 < ε
s : Set α := {x | g x + ↑ε ≤ f x ∧ g x ≤ ↑N} ∩ spanningSets μ p
s_lt_top : μ s < ∞
⊢ ∫⁻ (x : α) in toMeasurable μ s, f x ∂μ ≤ ∫⁻ (x : α) in toMeasurable μ s, g x ∂μ

Tactic:
]

Goal state after:
α : Type u_1
m0 : MeasurableSpace α
μ : Measure α
inst✝ : SigmaFinite μ
f g : α → ℝ≥0∞
hf : AEMeasurable f μ
h : ∀ (s : Set α), MeasurableSet s → μ s < ∞ → ∫⁻ (x : α) in s, f x ∂μ ≤ ∫⁻ (x : α) in s, g x ∂μ
ε N : ℝ≥0
p : ℕ
εpos : 0 < ε
s : Set α := {x | g x + ↑ε ≤ f x ∧ g x ≤ ↑N} ∩ spanningSets μ p
s_lt_top : μ s < ∞
⊢ ∫⁻ (x : α) in toMeasurable μ s, f x ∂μ ≤ ∫⁻ (x : α) in toMeasurable μ s, g x ∂μ
Module: Mathlib.MeasureTheory.Function.AEEqOfLIntegral

Goal state before:
pp: α : Type u_1
m0 : MeasurableSpace α
μ : Measure α
inst✝ : SigmaFinite μ
f g : α → ℝ≥0∞
hf : AEMeasurable f μ
h : ∀ (s : Set α), MeasurableSet s → μ s < ∞ → ∫⁻ (x : α) in s, f x ∂μ ≤ ∫⁻ (x : α) in s, g x ∂μ
ε N : ℝ≥0
p : ℕ
εpos : 0 < ε
s : Set α := {x | g x + ↑ε ≤ f x ∧ g x ≤ ↑N} ∩ spanningSets μ p
s_lt_top : μ s < ∞
⊢ μ s < ∞

Tactic:
]

Goal state after:
α : Type u_1
m0 : MeasurableSpace α
μ : Measure α
inst✝ : SigmaFinite μ
f g : α → ℝ≥0∞
hf : AEMeasurable f μ
h : ∀ (s : Set α), MeasurableSet s → μ s < ∞ → ∫⁻ (x : α) in s, f x ∂μ ≤ ∫⁻ (x : α) in s, g x ∂μ
ε N : ℝ≥0
p : ℕ
εpos : 0 < ε
s : Set α := {x | g x + ↑ε ≤ f x ∧ g x ≤ ↑N} ∩ spanningSets μ p
s_lt_top : μ s < ∞
⊢ μ s < ∞
Module: Mathlib.MeasureTheory.Integral.Average

Goal state before:
pp: case neg
α : Type u_1
m0 : MeasurableSpace α
μ ν : Measure α
f : α → ℝ≥0∞
hμ : IsFiniteMeasure μ
hν : ν univ = ∞
⊢ ⨍⁻ (x : α), f x ∂(μ + ν) =
    μ univ / (μ univ + ν univ) * ⨍⁻ (x : α), f x ∂μ + ν univ / (μ univ + ν univ) * ⨍⁻ (x : α), f x ∂ν

Tactic:
]

Goal state after:
case neg
α : Type u_1
m0 : MeasurableSpace α
μ ν : Measure α
f : α → ℝ≥0∞
hμ : IsFiniteMeasure μ
hν : ν univ = ∞
⊢ ⨍⁻ (x : α), f x ∂(μ + ν) =
    μ univ / (μ univ + ν univ) * ⨍⁻ (x : α), f x ∂μ + ν univ / (μ univ + ν univ) * ⨍⁻ (x : α), f x ∂ν