mathlib-initiative/mathlib-tactics huggingface dataset:
Module: Mathlib.Analysis.Analytic.Binomial

Goal state before:
pp: case succ
a : ℂ
B : Set ℂ := Metric.ball 0 1
n : ℕ
ih :
  Set.EqOn (iteratedDerivWithin n (fun x ↦ (1 + x) ^ a) B) (fun x ↦ (descPochhammer ℤ n).smeval a * (1 + x) ^ (a - ↑n))
    B
this✝ :
  iteratedDerivWithin (n + 1) (fun x ↦ (1 + x) ^ a) B = derivWithin (iteratedDerivWithin n (fun x ↦ (1 + x) ^ a) B) B
this :
  Set.EqOn (derivWithin (iteratedDerivWithin n (fun x ↦ (1 + x) ^ a) B) B)
    (derivWithin (fun x ↦ (descPochhammer ℤ n).smeval a * (1 + x) ^ (a - ↑n)) B) B
z : ℂ
hz : z ∈ B
⊢ (descPochhammer ℤ n).smeval a * ((a - ↑n) * (1 + z) ^ (a - ↑n - 1) * 1) =
    (descPochhammer ℤ (n + 1)).smeval a * (1 + z) ^ (a - (↑n + 1))

pp: case succ
a : ℂ
B : Set ℂ := Metric.ball 0 1
n : ℕ
ih :
  Set.EqOn (iteratedDerivWithin n (fun x ↦ (1 + x) ^ a) B) (fun x ↦ (descPochhammer ℤ n).smeval a * (1 + x) ^ (a - ↑n))
    B
this✝ :
  iteratedDerivWithin (n + 1) (fun x ↦ (1 + x) ^ a) B = derivWithin (iteratedDerivWithin n (fun x ↦ (1 + x) ^ a) B) B
this :
  Set.EqOn (derivWithin (iteratedDerivWithin n (fun x ↦ (1 + x) ^ a) B) B)
    (derivWithin (fun x ↦ (descPochhammer ℤ n).smeval a * (1 + x) ^ (a - ↑n)) B) B
z : ℂ
hz : z ∈ B
⊢ 1 + z ∈ slitPlane

Tactic:
mul_one,

Goal state after:
case succ
a : ℂ
B : Set ℂ := Metric.ball 0 1
n : ℕ
ih :
  Set.EqOn (iteratedDerivWithin n (fun x ↦ (1 + x) ^ a) B) (fun x ↦ (descPochhammer ℤ n).smeval a * (1 + x) ^ (a - ↑n))
    B
this✝ :
  iteratedDerivWithin (n + 1) (fun x ↦ (1 + x) ^ a) B = derivWithin (iteratedDerivWithin n (fun x ↦ (1 + x) ^ a) B) B
this :
  Set.EqOn (derivWithin (iteratedDerivWithin n (fun x ↦ (1 + x) ^ a) B) B)
    (derivWithin (fun x ↦ (descPochhammer ℤ n).smeval a * (1 + x) ^ (a - ↑n)) B) B
z : ℂ
hz : z ∈ B
⊢ (descPochhammer ℤ n).smeval a * ((a - ↑n) * (1 + z) ^ (a - ↑n - 1)) =
    (descPochhammer ℤ (n + 1)).smeval a * (1 + z) ^ (a - (↑n + 1))

case succ
a : ℂ
B : Set ℂ := Metric.ball 0 1
n : ℕ
ih :
  Set.EqOn (iteratedDerivWithin n (fun x ↦ (1 + x) ^ a) B) (fun x ↦ (descPochhammer ℤ n).smeval a * (1 + x) ^ (a - ↑n))
    B
this✝ :
  iteratedDerivWithin (n + 1) (fun x ↦ (1 + x) ^ a) B = derivWithin (iteratedDerivWithin n (fun x ↦ (1 + x) ^ a) B) B
this :
  Set.EqOn (derivWithin (iteratedDerivWithin n (fun x ↦ (1 + x) ^ a) B) B)
    (derivWithin (fun x ↦ (descPochhammer ℤ n).smeval a * (1 + x) ^ (a - ↑n)) B) B
z : ℂ
hz : z ∈ B
⊢ 1 + z ∈ slitPlane
Module: Mathlib.Analysis.Analytic.Binomial

Goal state before:
pp: case e'_9
a b x✝ : ℂ
⊢ (b - a) / (1 - x✝) + a / (1 - x✝) ^ 2 = (((b - a) • fun x ↦ 1 / (1 - x)) + a • fun x ↦ 1 / (1 - x) ^ 2) x✝

Tactic:
simp [div_eq_mul_inv]

Goal state after:
Module: Mathlib.Analysis.Analytic.Binomial

Goal state before:
pp: case e'_9
a b x✝ : ℝ
⊢ (b - a) / (1 - x✝) + a / (1 - x✝) ^ 2 = (((b - a) • fun x ↦ 1 / (1 - x)) + a • fun x ↦ 1 / (1 - x) ^ 2) x✝

Tactic:
simp [div_eq_mul_inv]

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

Goal state before:
pp: ⊢ expGrowthInf 0 ≤ ⊥

Tactic:
← expGrowthSup_zero

Goal state after:
⊢ expGrowthInf 0 ≤ expGrowthSup 0
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 : a ≠ 0
ha' : a ≠ ⊤
hv₁ : 0 < liminf (fun n ↦ ↑(v n) / ↑n) atTop
v_top : Tendsto v atTop atTop
u_0 : ¬u = ⊥
h' : ∃ᶠ (n : ℕ) in atTop, u n ≤ 0
n m : ℕ
n_m : n ≤ m
um_1 : u m ≤ 0
⊢ u n ≤ 0

Tactic:
exact (h n_m).trans um_1

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 = ⊥
h' : ∀ (n : ℕ), u n ≤ 0
⊢ linearGrowthInf (u ∘ v) = a * linearGrowthInf u

Tactic:
have u_0' : linearGrowthInf u = 0 := by
      apply le_antisymm _ (h.linearGrowthInf_nonneg u_0)
      exact (linearGrowthInf_monotone h').trans_eq (linearGrowthInf_const zero_ne_bot zero_ne_top)

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) = a * linearGrowthInf u
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) + ν (s \ t)).toNNReal =
    ↑(μ (s \ t)).toNNReal - ↑(ν (s \ t)).toNNReal + (↑(μ (s ∩ t)).toNNReal - ↑(ν (s ∩ t)).toNNReal)

Tactic:
ENNReal.toNNReal_add (hν _) (hν _),

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: case neg
α : Type u_1
m0 : MeasurableSpace α
μ ν : Measure α
f : α → ℝ≥0∞
hμ : ¬IsFiniteMeasure μ
⊢ ⨍⁻ (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

pp: case pos
α : Type u_1
m0 : MeasurableSpace α
μ ν : Measure α
f : α → ℝ≥0∞
hμ : IsFiniteMeasure μ
⊢ ⨍⁻ (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:
· rw [not_isFiniteMeasure_iff] at hμ
    simp [laverage_eq, hμ]

Goal state after:
case pos
α : Type u_1
m0 : MeasurableSpace α
μ ν : Measure α
f : α → ℝ≥0∞
hμ : IsFiniteMeasure μ
⊢ ⨍⁻ (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.MeasureTheory.Function.AEEqOfLIntegral

Goal state before:
pp: case refine_2
α : Type u_1
m0 : MeasurableSpace α
β : Type u_2
mβ : MeasurableSpace β
μ : Measure (α × β)
f g : α × β → ℝ≥0∞
hf : AEMeasurable f μ
hg : AEMeasurable g μ
hf_int : ∫⁻ (x : α × β), f x ∂μ ≠ ∞
h :
  ∀ ⦃s : Set α⦄,
    MeasurableSet s →
      ∀ ⦃t : Set β⦄, MeasurableSet t → ∫⁻ (x : α × β) in s ×ˢ t, f x ∂μ = ∫⁻ (x : α × β) in s ×ˢ t, g x ∂μ
hg_int : ∫⁻ (x : α × β), g x ∂μ ≠ ∞
s✝ : Set (α × β)
hs✝ : MeasurableSet s✝
x✝ : μ s✝ < ∞
s : Set α
hs : s ∈ {s | MeasurableSet s}
t : Set β
ht : t ∈ {t | MeasurableSet t}
⊢ ∫⁻ (x : α × β) in (fun x1 x2 ↦ x1 ×ˢ x2) s t, f x ∂μ = ∫⁻ (x : α × β) in (fun x1 x2 ↦ x1 ×ˢ x2) s t, g x ∂μ

Tactic:
exact h hs ht

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

Goal state before:
pp: α : Type u_1
m0 : MeasurableSpace α
μ : Measure α
s : Set α
inst✝ : TopologicalSpace α
f : α → ℝ
hs : IsConnected s
hf : ContinuousOn f s
hint : IntegrableOn f s μ
hμfin : μ s ≠ ∞
hμ0 : μ s ≠ 0
⊢ ∃ c ∈ s, f c = ⨍ (x : α) in s, f x ∂μ

Tactic:
let ave := ⨍ x in s, f x ∂μ
  let S₁ : Set α := {x | x ∈ s ∧ f x ≤ ave}
  let S₂ : Set α := {x | x ∈ s ∧ ave ≤ f x}
  have hS₁ : 0 < μ S₁ := measure_le_setAverage_pos hμ0 hμfin hint
  have hS₂ : 0 < μ S₂ := measure_setAverage_le_pos hμ0 hμfin hint
  rcases nonempty_of_measure_ne_zero hS₁.ne' with ⟨c₁, hc₁⟩
  rcases nonempty_of_measure_ne_zero hS₂.ne' with ⟨c₂, hc₂⟩
  apply hs.isPreconnected.intermediate_value hc₁.1 hc₂.1 hf
  grind

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

Goal state before:
pp: α : Type u_1
m : MeasurableSpace α
μ ν : Measure α
inst✝¹ : IsFiniteMeasure μ
inst✝ : IsFiniteMeasure ν
h : ¬μ ⟂ₘ ν
f : ℕ → Set α
hf₁ : ∀ (n : ℕ), MeasurableSet (f n)
hf₂ : ∀ (n : ℕ) (t : Set α), MeasurableSet t → ((1 / (↑n + 1)) • ν) (t ∩ f n) ≤ μ (t ∩ f n)
hf₃ : ∀ (n : ℕ) (t : Set α), MeasurableSet t → μ (t ∩ (f n)ᶜ) ≤ ((1 / (↑n + 1)) • ν) (t ∩ (f n)ᶜ)
A : Set α := ⋂ n, (f n)ᶜ
hAmeas : MeasurableSet A
hA₂ : ∀ (n : ℕ) (t : Set α), MeasurableSet t → μ (t ∩ A) ≤ ((1 / (↑n + 1)) • ν) (t ∩ A)
μA νA : ℝ≥0
hA₃ : ∀ (n : ℕ), ↑μA ≤ ↑(1 / (↑n + 1)) * ↑νA
hb : 0 < νA
c : ℝ≥0
hc : 0 < c
n : ℕ
hn : 1 / (↑n + 1) < ↑c * (↑νA)⁻¹
hb₁ : 0 < (↑νA)⁻¹
⊢ ↑(1 / (↑n + 1) * 1) < ↑c * ↑νA⁻¹

pp: α : Type u_1
m : MeasurableSpace α
μ ν : Measure α
inst✝¹ : IsFiniteMeasure μ
inst✝ : IsFiniteMeasure ν
h : ¬μ ⟂ₘ ν
f : ℕ → Set α
hf₁ : ∀ (n : ℕ), MeasurableSet (f n)
hf₂ : ∀ (n : ℕ) (t : Set α), MeasurableSet t → ((1 / (↑n + 1)) • ν) (t ∩ f n) ≤ μ (t ∩ f n)
hf₃ : ∀ (n : ℕ) (t : Set α), MeasurableSet t → μ (t ∩ (f n)ᶜ) ≤ ((1 / (↑n + 1)) • ν) (t ∩ (f n)ᶜ)
A : Set α := ⋂ n, (f n)ᶜ
hAmeas : MeasurableSet A
hA₂ : ∀ (n : ℕ) (t : Set α), MeasurableSet t → μ (t ∩ A) ≤ ((1 / (↑n + 1)) • ν) (t ∩ A)
μA νA : ℝ≥0
hA₃ : ∀ (n : ℕ), ↑μA ≤ ↑(1 / (↑n + 1)) * ↑νA
hb : 0 < νA
c : ℝ≥0
hc : 0 < c
n : ℕ
hn : 1 / (↑n + 1) < ↑c * (↑νA)⁻¹
hb₁ : 0 < (↑νA)⁻¹
⊢ νA ≠ 0

Tactic:
mul_one,

Goal state after:
α : Type u_1
m : MeasurableSpace α
μ ν : Measure α
inst✝¹ : IsFiniteMeasure μ
inst✝ : IsFiniteMeasure ν
h : ¬μ ⟂ₘ ν
f : ℕ → Set α
hf₁ : ∀ (n : ℕ), MeasurableSet (f n)
hf₂ : ∀ (n : ℕ) (t : Set α), MeasurableSet t → ((1 / (↑n + 1)) • ν) (t ∩ f n) ≤ μ (t ∩ f n)
hf₃ : ∀ (n : ℕ) (t : Set α), MeasurableSet t → μ (t ∩ (f n)ᶜ) ≤ ((1 / (↑n + 1)) • ν) (t ∩ (f n)ᶜ)
A : Set α := ⋂ n, (f n)ᶜ
hAmeas : MeasurableSet A
hA₂ : ∀ (n : ℕ) (t : Set α), MeasurableSet t → μ (t ∩ A) ≤ ((1 / (↑n + 1)) • ν) (t ∩ A)
μA νA : ℝ≥0
hA₃ : ∀ (n : ℕ), ↑μA ≤ ↑(1 / (↑n + 1)) * ↑νA
hb : 0 < νA
c : ℝ≥0
hc : 0 < c
n : ℕ
hn : 1 / (↑n + 1) < ↑c * (↑νA)⁻¹
hb₁ : 0 < (↑νA)⁻¹
⊢ ↑(1 / (↑n + 1)) < ↑c * ↑νA⁻¹

α : Type u_1
m : MeasurableSpace α
μ ν : Measure α
inst✝¹ : IsFiniteMeasure μ
inst✝ : IsFiniteMeasure ν
h : ¬μ ⟂ₘ ν
f : ℕ → Set α
hf₁ : ∀ (n : ℕ), MeasurableSet (f n)
hf₂ : ∀ (n : ℕ) (t : Set α), MeasurableSet t → ((1 / (↑n + 1)) • ν) (t ∩ f n) ≤ μ (t ∩ f n)
hf₃ : ∀ (n : ℕ) (t : Set α), MeasurableSet t → μ (t ∩ (f n)ᶜ) ≤ ((1 / (↑n + 1)) • ν) (t ∩ (f n)ᶜ)
A : Set α := ⋂ n, (f n)ᶜ
hAmeas : MeasurableSet A
hA₂ : ∀ (n : ℕ) (t : Set α), MeasurableSet t → μ (t ∩ A) ≤ ((1 / (↑n + 1)) • ν) (t ∩ A)
μA νA : ℝ≥0
hA₃ : ∀ (n : ℕ), ↑μA ≤ ↑(1 / (↑n + 1)) * ↑νA
hb : 0 < νA
c : ℝ≥0
hc : 0 < c
n : ℕ
hn : 1 / (↑n + 1) < ↑c * (↑νA)⁻¹
hb₁ : 0 < (↑νA)⁻¹
⊢ νA ≠ 0
Module: Mathlib.MeasureTheory.Measure.Decomposition.Lebesgue

Goal state before:
pp: case refine_4.refine_1
α : Type u_1
m : MeasurableSpace α
μ ν : Measure α
inst✝¹ : IsFiniteMeasure μ
inst✝ : IsFiniteMeasure ν
g : ℕ → ℝ≥0∞
h✝ : Monotone g
hg₂ : Filter.Tendsto g Filter.atTop (nhds (sSup (measurableLEEval ν μ)))
f : ℕ → α → ℝ≥0∞
hf₁ : ∀ (n : ℕ), f n ∈ measurableLE ν μ
hf₂ : ∀ (n : ℕ), (fun f ↦ ∫⁻ (x : α), f x ∂ν) (f n) = g n
ξ : α → ℝ≥0∞ := ⨆ n, ⨆ k, ⨆ (_ : k ≤ n), f k
hξ : ξ = ⨆ n, ⨆ k, ⨆ (_ : k ≤ n), f k
this :
  Filter.Tendsto (fun n ↦ ∫⁻ (x : α), (⨆ k, ⨆ (_ : k ≤ n), f k) x ∂ν) Filter.atTop
    (nhds (∫⁻ (x : α), (⨆ n, ⨆ k, ⨆ (_ : k ≤ n), f k) x ∂ν))
n : ℕ
⊢ g n ≤ ∫⁻ (x : α), (⨆ k, ⨆ (_ : k ≤ n), f k) x ∂ν

Tactic:
rw [← hf₂ n]

Goal state after:
case refine_4.refine_1
α : Type u_1
m : MeasurableSpace α
μ ν : Measure α
inst✝¹ : IsFiniteMeasure μ
inst✝ : IsFiniteMeasure ν
g : ℕ → ℝ≥0∞
h✝ : Monotone g
hg₂ : Filter.Tendsto g Filter.atTop (nhds (sSup (measurableLEEval ν μ)))
f : ℕ → α → ℝ≥0∞
hf₁ : ∀ (n : ℕ), f n ∈ measurableLE ν μ
hf₂ : ∀ (n : ℕ), (fun f ↦ ∫⁻ (x : α), f x ∂ν) (f n) = g n
ξ : α → ℝ≥0∞ := ⨆ n, ⨆ k, ⨆ (_ : k ≤ n), f k
hξ : ξ = ⨆ n, ⨆ k, ⨆ (_ : k ≤ n), f k
this :
  Filter.Tendsto (fun n ↦ ∫⁻ (x : α), (⨆ k, ⨆ (_ : k ≤ n), f k) x ∂ν) Filter.atTop
    (nhds (∫⁻ (x : α), (⨆ n, ⨆ k, ⨆ (_ : k ≤ n), f k) x ∂ν))
n : ℕ
⊢ (fun f ↦ ∫⁻ (x : α), f x ∂ν) (f n) ≤ ∫⁻ (x : α), (⨆ k, ⨆ (_ : k ≤ n), f k) x ∂ν
Module: Mathlib.MeasureTheory.Measure.Decomposition.Lebesgue

Goal state before:
pp: case refine_4.refine_2
α : Type u_1
m : MeasurableSpace α
μ ν : Measure α
inst✝¹ : IsFiniteMeasure μ
inst✝ : IsFiniteMeasure ν
g : ℕ → ℝ≥0∞
h✝ : Monotone g
hg₂ : Filter.Tendsto g Filter.atTop (nhds (sSup (measurableLEEval ν μ)))
f : ℕ → α → ℝ≥0∞
hf₁ : ∀ (n : ℕ), f n ∈ measurableLE ν μ
hf₂ : ∀ (n : ℕ), (fun f ↦ ∫⁻ (x : α), f x ∂ν) (f n) = g n
ξ : α → ℝ≥0∞ := ⨆ n, ⨆ k, ⨆ (_ : k ≤ n), f k
hξ : ξ = ⨆ n, ⨆ k, ⨆ (_ : k ≤ n), f k
this :
  Filter.Tendsto (fun n ↦ ∫⁻ (x : α), (⨆ k, ⨆ (_ : k ≤ n), f k) x ∂ν) Filter.atTop
    (nhds (∫⁻ (x : α), (⨆ n, ⨆ k, ⨆ (_ : k ≤ n), f k) x ∂ν))
n : ℕ
⊢ ∫⁻ (x : α), (⨆ k, ⨆ (_ : k ≤ n), f k) x ∂ν ≤ sSup (measurableLEEval ν μ)

Tactic:
· exact le_sSup ⟨⨆ (k : ℕ) (_ : k ≤ n), f k, iSup_mem_measurableLE' _ hf₁ _, rfl⟩

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

Goal state before:
pp: case refine_2
α : Type u_1
m : MeasurableSpace α
μ ν : Measure α
inst✝¹ : IsFiniteMeasure μ
inst✝ : IsFiniteMeasure ν
g : ℕ → ℝ≥0∞
h✝ : Monotone g
hg₂ : Filter.Tendsto g Filter.atTop (nhds (sSup (measurableLEEval ν μ)))
f : ℕ → α → ℝ≥0∞
hf₁ : ∀ (n : ℕ), f n ∈ measurableLE ν μ
hf₂ : ∀ (n : ℕ), (fun f ↦ ∫⁻ (x : α), f x ∂ν) (f n) = g n
ξ : α → ℝ≥0∞ := ⨆ n, ⨆ k, ⨆ (_ : k ≤ n), f k
hξ : ξ = ⨆ n, ⨆ k, ⨆ (_ : k ≤ n), f k
hξ₁ : sSup (measurableLEEval ν μ) = ∫⁻ (a : α), ξ a ∂ν
hξm : Measurable ξ
hξle : ∀ (A : Set α), MeasurableSet A → ∫⁻ (a : α) in A, ξ a ∂ν ≤ μ A
hle : ν.withDensity ξ ≤ μ
this : IsFiniteMeasure (ν.withDensity ξ)
μ₁ : Measure α := μ - ν.withDensity ξ
hμ₁ : μ₁ = μ - ν.withDensity ξ
⊢ μ = (μ₁, ξ).1 + ν.withDensity (μ₁, ξ).2

Tactic:
rw [hμ₁]
      ext1 A hA
      rw [Measure.coe_add, Pi.add_apply, Measure.sub_apply hA hle, add_comm,
        add_tsub_cancel_of_le (hle A)]

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

Goal state before:
pp: α : Type u_1
inst✝⁴ : PseudoMetricSpace α
m0 : MeasurableSpace α
μ : Measure α
v : VitaliFamily μ
inst✝³ : SecondCountableTopology α
inst✝² : BorelSpace α
inst✝¹ : IsLocallyFiniteMeasure μ
ρ : Measure α
inst✝ : IsLocallyFiniteMeasure ρ
hρ : ρ ≪ μ
x : α
x✝ : x ∈ v.limRatioMeas hρ ⁻¹' {0}
o : Set α
xo : x ∈ o
o_open : IsOpen[PseudoMetricSpace.toUniformSpace.toTopologicalSpace] o
μo : μ o < ∞
s : Set α := {x | v.limRatioMeas hρ x = 0} ∩ o
μs : μ s ≠ ∞
A : ∀ (q : ℝ≥0), 0 < q → ρ s ≤ ↑q * μ s
⊢ Tendsto (fun a ↦ a) (𝓝[>] 0) (𝓝 0)

Tactic:
exact nhdsWithin_le_nhds

Goal state after:
Module: Mathlib.Analysis.BoundedVariation

Goal state before:
pp: V : Type u_1
inst✝² : NormedAddCommGroup V
inst✝¹ : NormedSpace ℝ V
inst✝ : FiniteDimensional ℝ V
f : ℝ → V
s : Set ℝ
h : LocallyBoundedVariationOn f s
A : V ≃L[ℝ] ↑(Module.Basis.ofVectorSpaceIndex ℝ V) → ℝ :=
  (Module.Basis.ofVectorSpace ℝ V).equivFun.toContinuousLinearEquiv
⊢ ∀ᵐ (x : ℝ), x ∈ s → DifferentiableWithinAt ℝ (⇑A ∘ f) s x

Tactic:
apply ae_differentiableWithinAt_of_mem_pi

Goal state after:
V : Type u_1
inst✝² : NormedAddCommGroup V
inst✝¹ : NormedSpace ℝ V
inst✝ : FiniteDimensional ℝ V
f : ℝ → V
s : Set ℝ
h : LocallyBoundedVariationOn f s
A : V ≃L[ℝ] ↑(Module.Basis.ofVectorSpaceIndex ℝ V) → ℝ := ⋯
⊢ LocallyBoundedVariationOn (⇑A ∘ f) s
Module: Mathlib.Topology.EMetricSpace.BoundedVariation

Goal state before:
pp: α : Type u_1
inst✝² : LinearOrder α
E : Type u_2
inst✝¹ : PseudoEMetricSpace E
β : Type u_3
inst✝ : LinearOrder β
f : α → E
s : Set α
t : Set β
φ : β → α
hφ : AntitoneOn φ t
φst : MapsTo φ t s
n : ℕ
u : ℕ → β
hu : Monotone u
ut : ∀ (i : ℕ), u i ∈ t
⊢ ∑ i ∈ Finset.range (n, ⟨u, ⋯⟩).1, edist ((f ∘ φ) (↑(n, ⟨u, ⋯⟩).2 (i + 1))) ((f ∘ φ) (↑(n, ⟨u, ⋯⟩).2 i)) ≤
    eVariationOn f s

Tactic:
rw [← Finset.sum_range_reflect]

Goal state after:
α : Type u_1
inst✝² : LinearOrder α
E : Type u_2
inst✝¹ : PseudoEMetricSpace E
β : Type u_3
inst✝ : LinearOrder β
f : α → E
s : Set α
t : Set β
φ : β → α
hφ : AntitoneOn φ t
φst : MapsTo φ t s
n : ℕ
u : ℕ → β
hu : Monotone u
ut : ∀ (i : ℕ), u i ∈ t
⊢ ∑ j ∈ Finset.range (n, ⟨u, ⋯⟩).1,
      edist ((f ∘ φ) (↑(n, ⟨u, ⋯⟩).2 ((n, ⟨u, ⋯⟩).1 - 1 - j + 1))) ((f ∘ φ) (↑(n, ⟨u, ⋯⟩).2 ((n, ⟨u, ⋯⟩).1 - 1 - j))) ≤
    eVariationOn f s
Module: Mathlib.Topology.EMetricSpace.BoundedVariation

Goal state before:
pp: case h₂
α : Type u_1
inst✝³ : LinearOrder α
E : Type u_2
inst✝² : PseudoEMetricSpace E
inst✝¹ : TopologicalSpace α
inst✝ : OrderTopology α
f : α → E
s : Set α
a : α
l : E
h : (𝓝[s ∩ Iio a] a).NeBot
ha : a ∈ s
h'f : Tendsto f (𝓝[s ∩ Iio a] a) (𝓝 l)
u : ℕ → α
n : ℕ
u_mono : StrictMonoOn u (Iic (n + 1))
u_mem : ∀ i ∈ Iic (n + 1), u i ∈ s ∩ Iic a
this✝¹ : u (n + 1) ≤ a
hn : u (n + 1) = a
this✝ :
  Tendsto (fun y ↦ eVariationOn f (s ∩ Iio a) + edist (f a) (f y)) (𝓝[s ∩ Iio a] a)
    (𝓝 (eVariationOn f (s ∩ Iio a) + edist (f a) l))
this : s ∩ Ioo (u n) a ∈ 𝓝[s ∩ Iio a] a
y : α
hy : y ∈ s ∩ Ioo (u n) a
v : ℕ → α := ⋯
⊢ edist (f (u (n + 1))) (f (u n)) ≤ edist (f (v (n + 1))) (f (v n)) + edist (f (v (n + (1 + 1)))) (f (v (n + 1)))

Tactic:
add_comm (edist _ _),

Goal state after:
case h₂
α : Type u_1
inst✝³ : LinearOrder α
E : Type u_2
inst✝² : PseudoEMetricSpace E
inst✝¹ : TopologicalSpace α
inst✝ : OrderTopology α
f : α → E
s : Set α
a : α
l : E
h : (𝓝[s ∩ Iio a] a).NeBot
ha : a ∈ s
h'f : Tendsto f (𝓝[s ∩ Iio a] a) (𝓝 l)
u : ℕ → α
n : ℕ
u_mono : StrictMonoOn u (Iic (n + 1))
u_mem : ∀ i ∈ Iic (n + 1), u i ∈ s ∩ Iic a
this✝¹ : u (n + 1) ≤ a
hn : u (n + 1) = a
this✝ :
  Tendsto (fun y ↦ eVariationOn f (s ∩ Iio a) + edist (f a) (f y)) (𝓝[s ∩ Iio a] a)
    (𝓝 (eVariationOn f (s ∩ Iio a) + edist (f a) l))
this : s ∩ Ioo (u n) a ∈ 𝓝[s ∩ Iio a] a
y : α
hy : y ∈ s ∩ Ioo (u n) a
v : ℕ → α := fun i ↦ if i ≤ n then u i else if i = n + 1 then y else a
⊢ edist (f (u (n + 1))) (f (u n)) ≤ edist (f (v (n + (1 + 1)))) (f (v (n + 1))) + edist (f (v (n + 1))) (f (v n))
Module: Mathlib.Topology.EMetricSpace.BoundedVariation

Goal state before:
pp: case inl
α : Type u_1
inst✝¹ : LinearOrder α
E : Type u_2
inst✝ : PseudoEMetricSpace E
f : α → E
L : Filter α
hf : BoundedVariationOn f ∅
hL : ∀ y ∈ ∅, ∅ ∩ Ici y ∈ L
⊢ Tendsto (fun y ↦ eVariationOn f (∅ ∩ Ici y)) L (𝓝 0)

pp: case inr
α : Type u_1
inst✝¹ : LinearOrder α
E : Type u_2
inst✝ : PseudoEMetricSpace E
f : α → E
s : Set α
hf : BoundedVariationOn f s
L : Filter α
hL : ∀ y ∈ s, s ∩ Ici y ∈ L
x₀ : α
hx₀ : x₀ ∈ s
⊢ Tendsto (fun y ↦ eVariationOn f (s ∩ Ici y)) L (𝓝 0)

Tactic:
· simpa using tendsto_const_nhds

Goal state after:
case inr
α : Type u_1
inst✝¹ : LinearOrder α
E : Type u_2
inst✝ : PseudoEMetricSpace E
f : α → E
s : Set α
hf : BoundedVariationOn f s
L : Filter α
hL : ∀ y ∈ s, s ∩ Ici y ∈ L
x₀ : α
hx₀ : x₀ ∈ s
⊢ Tendsto (fun y ↦ eVariationOn f (s ∩ Ici y)) L (𝓝 0)
Module: Mathlib.Topology.EMetricSpace.BoundedVariation

Goal state before:
pp: α : Type u_1
inst✝¹ : LinearOrder α
E : Type u_2
inst✝ : PseudoEMetricSpace E
f : α → E
s : Set α
hf : BoundedVariationOn f s
L : Filter α
hL : ∀ y ∈ s, s ∩ Ici y ∈ L
x₀ : α
hx₀ : x₀ ∈ s
ε : ℝ≥0∞
εpos : ε > 0
δ : ℝ≥0∞
δpos : 0 < δ
hδ : δ < ε
H : ∃ᶠ (x : α) in L, ε ≤ eVariationOn f (s ∩ Ici x)
y : α
hy : y ∈ s
y' : α
hy' : ε ≤ eVariationOn f (s ∩ Ici y')
y'_mem : y' ∈ s ∩ Ici y
a : α
ha : a ∈ s ∩ Ici y'
b : α
hb : b ∈ s ∩ Ici y'
hab : a < b
h : δ < eVariationOn f (s ∩ Ici y' ∩ Icc a b)
this : Ici y' ∩ Icc a b = Icc a b
⊢ δ ≤ eVariationOn f (s ∩ Icc y b)

Tactic:
rw [inter_assoc, this] at h

Goal state after:
α : Type u_1
inst✝¹ : LinearOrder α
E : Type u_2
inst✝ : PseudoEMetricSpace E
f : α → E
s : Set α
hf : BoundedVariationOn f s
L : Filter α
hL : ∀ y ∈ s, s ∩ Ici y ∈ L
x₀ : α
hx₀ : x₀ ∈ s
ε : ℝ≥0∞
εpos : ε > 0
δ : ℝ≥0∞
δpos : 0 < δ
hδ : δ < ε
H : ∃ᶠ (x : α) in L, ε ≤ eVariationOn f (s ∩ Ici x)
y : α
hy : y ∈ s
y' : α
hy' : ε ≤ eVariationOn f (s ∩ Ici y')
y'_mem : y' ∈ s ∩ Ici y
a : α
ha : a ∈ s ∩ Ici y'
b : α
hb : b ∈ s ∩ Ici y'
hab : a < b
h : δ < eVariationOn f (s ∩ Icc a b)
this : Ici y' ∩ Icc a b = Icc a b
⊢ δ ≤ eVariationOn f (s ∩ Icc y b)
Module: Mathlib.Topology.EMetricSpace.BoundedVariation

Goal state before:
pp: case pos
α : Type u_1
inst✝³ : LinearOrder α
E : Type u_2
inst✝² : PseudoEMetricSpace E
inst✝¹ : CompleteSpace E
inst✝ : DenselyOrdered α
f : α → E
a : α
hf : BoundedVariationOn f univ
this✝ : TopologicalSpace α := Preorder.topology α
this : OrderTopology α
ha : IsBot a
A : Iic a = {a}
⊢ eVariationOn f (Iic a) = eVariationOn f (Iio a) + edist (f a) (Function.leftLim f a)

Tactic:
have B : Iio a = ∅ := by simp [ha.isMin]

Goal state after:
case pos
α : Type u_1
inst✝³ : LinearOrder α
E : Type u_2
inst✝² : PseudoEMetricSpace E
inst✝¹ : CompleteSpace E
inst✝ : DenselyOrdered α
f : α → E
a : α
hf : BoundedVariationOn f univ
this✝ : TopologicalSpace α := Preorder.topology α
this : OrderTopology α
ha : IsBot a
A : Iic a = {a}
B : Iio a = ∅
⊢ eVariationOn f (Iic a) = eVariationOn f (Iio a) + edist (f a) (Function.leftLim f a)
Module: Mathlib.Analysis.CStarAlgebra.ContinuousFunctionalCalculus.Unital

Goal state before:
pp: case monomial
R : Type u_1
A : Type u_2
p : A → Prop
inst✝⁸ : CommSemiring R
inst✝⁷ : StarRing R
inst✝⁶ : MetricSpace R
inst✝⁵ : IsTopologicalSemiring R
inst✝⁴ : ContinuousStar R
inst✝³ : TopologicalSpace A
inst✝² : Ring A
inst✝¹ : StarRing A
inst✝ : Algebra R A
instCFC : ContinuousFunctionalCalculus R A p
f : R → R
a : A
ha : p a
hf : ContinuousOn f (spectrum R a)
n : ℕ
r : R
a✝ : cfc (fun x ↦ Polynomial.eval (f x) (Polynomial.C r * X ^ n)) a = (aeval (cfc f a)) (Polynomial.C r * X ^ n)
⊢ r • cfc f a ^ (n + 1) = (algebraMap R A) r • cfc f a ^ (n + 1)

Tactic:
algebraMap_smul

Goal state after:
case monomial
R : Type u_1
A : Type u_2
p : A → Prop
inst✝⁸ : CommSemiring R
inst✝⁷ : StarRing R
inst✝⁶ : MetricSpace R
inst✝⁵ : IsTopologicalSemiring R
inst✝⁴ : ContinuousStar R
inst✝³ : TopologicalSpace A
inst✝² : Ring A
inst✝¹ : StarRing A
inst✝ : Algebra R A
instCFC : ContinuousFunctionalCalculus R A p
f : R → R
a : A
ha : p a
hf : ContinuousOn f (spectrum R a)
n : ℕ
r : R
a✝ : cfc (fun x ↦ Polynomial.eval (f x) (Polynomial.C r * X ^ n)) a = (aeval (cfc f a)) (Polynomial.C r * X ^ n)
⊢ r • cfc f a ^ (n + 1) = r • cfc f a ^ (n + 1)