mathlib-initiative/mathlib-tactics huggingface dataset:
Module: Mathlib.Analysis.SpecialFunctions.Pow.Deriv

Goal state before:
pp: case inr.hf
p : ℝ
h : 1 ≤ p
⊢ ContinuousAt (fun x ↦ x ^ p) 0

pp: case inr.hg
p : ℝ
h : 1 ≤ p
⊢ ContinuousAt (fun x ↦ p * x ^ (p - 1)) 0

Tactic:
exacts [continuousAt_id.rpow_const (Or.inr (zero_le_one.trans h)),
    continuousAt_const.mul (continuousAt_id.rpow_const (Or.inr (sub_nonneg.2 h)))]

Goal state after:
Module: Mathlib.Analysis.SpecialFunctions.Pow.Deriv

Goal state before:
pp: case pos
x p : ℝ
h : p ≠ 0
h' : x ≠ 0 ∨ 1 ≤ p
⊢ deriv (fun x ↦ x ^ p) x = p * x ^ (p - 1)

pp: case neg
x p : ℝ
h : p ≠ 0
h' : x = 0 ∧ p < 1
⊢ deriv (fun x ↦ x ^ p) x = p * x ^ (p - 1)

Tactic:
· apply (Real.hasDerivAt_rpow_const h').deriv

Goal state after:
case neg
x p : ℝ
h : p ≠ 0
h' : x = 0 ∧ p < 1
⊢ deriv (fun x ↦ x ^ p) x = p * x ^ (p - 1)
Module: Mathlib.Topology.MetricSpace.Cover

Goal state before:
pp: X : Type u_1
inst✝ : PseudoEMetricSpace X
ε : ℝ≥0
s : Set X
hε : ε ≠ 0
hs : ∀ ε > 0, ∃ t ⊆ s, t.Finite ∧ s ⊆ ⋃ y ∈ t, eball y ε
N : Set X
hNA : N ⊆ s
hN_finite : N.Finite
hN : s ⊆ ⋃ y ∈ N, eball y ↑ε
⊢ s ⊆ ⋃ y ∈ N, closedEBall y ↑ε

Tactic:
· refine hN.trans fun x hx ↦ ?_
    simp only [Set.mem_iUnion, Metric.mem_eball, exists_prop, Metric.mem_closedEBall] at hx ⊢
    obtain ⟨y, hyN, hy⟩ := hx
    exact ⟨y, hyN, hy.le⟩

Goal state after:
Module: Mathlib.Topology.MetricSpace.Cover

Goal state before:
pp: X : Type u_1
inst✝ : PseudoEMetricSpace X
ε : ℝ≥0
s : Set X
hε : ε ≠ 0
hs : TotallyBounded s
⊢ ∃ N ⊆ s, N.Finite ∧ IsCover ε s N

Tactic:
by
  rw [EMetric.totallyBounded_iff'] at hs
  obtain ⟨N, hNA, hN_finite, hN⟩ := hs ε (by positivity)
  simp only [isCover_iff_subset_iUnion_closedEBall]
  refine ⟨N, by simpa, by simpa, ?_⟩
  · refine hN.trans fun x hx ↦ ?_
    simp only [Set.mem_iUnion, Metric.mem_eball, exists_prop, Metric.mem_closedEBall] at hx ⊢
    obtain ⟨y, hyN, hy⟩ := hx
    exact ⟨y, hyN, hy.le⟩

Goal state after:
Module: Mathlib.Analysis.SpecialFunctions.Log.ERealExp

Goal state before:
pp: x : EReal
⊢ (-x).exp = x.exp⁻¹

Tactic:
by
  induction x
  · simp
  · rw [exp_coe, ← EReal.coe_neg, exp_coe, ← ENNReal.ofReal_inv_of_pos (Real.exp_pos _),
      Real.exp_neg]
  · simp

Goal state after:
Module: Mathlib.Analysis.SpecialFunctions.Log.ENNRealLogExp

Goal state before:
pp: case e'_5
b : ℝ≥0∞
hb : 1 < b
⊢ ⊥ = ⊥ * b.log

Tactic:
rw [EReal.bot_mul_of_pos (zero_lt_log_iff.2 hb)]

Goal state after:
Module: Mathlib.Analysis.SpecialFunctions.Log.ENNRealLog

Goal state before:
pp: case inr.inr.inr.inl
y : ℝ
y_pos : 0 < y
⊢ (∞ ^ y).log = ↑y * ∞.log

pp: case inr.inr.inr.inr
x : ℝ≥0∞
y : ℝ
y_pos : 0 < y
x_real : 0 < x.toReal
⊢ (x ^ y).log = ↑y * x.log

Tactic:
· rw [ENNReal.top_rpow_of_pos y_pos, log_top, EReal.mul_top_of_pos]; norm_cast

Goal state after:
case inr.inr.inr.inr
x : ℝ≥0∞
y : ℝ
y_pos : 0 < y
x_real : 0 < x.toReal
⊢ (x ^ y).log = ↑y * x.log
Module: Mathlib.Analysis.Asymptotics.LinearGrowth

Goal state before:
pp: u : ℕ → EReal
n : ℕ
⊢ (-u) n / ↑n = (-fun n ↦ u n / ↑n) n

Tactic:
Pi.neg_apply,

Goal state after:
u : ℕ → EReal
n : ℕ
⊢ -u n / ↑n = (-fun n ↦ u n / ↑n) n
Module: Mathlib.Analysis.Asymptotics.LinearGrowth

Goal state before:
pp: u : ℕ → EReal
n : ℕ
⊢ -u n / ↑n = (-fun n ↦ u n / ↑n) n

Tactic:
Pi.neg_apply,

Goal state after:
u : ℕ → EReal
n : ℕ
⊢ -u n / ↑n = -(u n / ↑n)
Module: Mathlib.Analysis.Asymptotics.ExpGrowth

Goal state before:
pp: u : ℕ → ℝ≥0∞
n : ℕ
⊢ (u⁻¹ n).log / ↑n = (-fun n ↦ (u n).log / ↑n) n

Tactic:
Pi.neg_apply,

Goal state after:
u : ℕ → ℝ≥0∞
n : ℕ
⊢ (u⁻¹ n).log / ↑n = -((u n).log / ↑n)
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 (Set ι)
UT : U ⊆ T
hU : IsChain (fun x1 x2 ↦ x1 ⊆ x2) U
a : ι
hat : a ∈ t
b : ι
u : Set ι
uU : u ∈ U
hbu : b ∈ u
hab : (B a ∩ B b).Nonempty
c : ι
cu : c ∈ u
ac : (B a ∩ B c).Nonempty
hc : δ a ≤ τ * δ c
⊢ ∃ c, (∃ t ∈ U, c ∈ t) ∧ (B a ∩ B c).Nonempty ∧ δ a ≤ τ * δ c

Tactic:
exact ⟨c, ⟨u, uU, cu⟩, ac, hc⟩

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

Goal state before:
pp: α : Type u_1
m : MeasurableSpace α
μ : Measure α
β : Type u_2
inst✝⁶ : CompleteLinearOrder β
inst✝⁵ : DenselyOrdered β
inst✝⁴ : TopologicalSpace β
inst✝³ : OrderTopology β
inst✝² : SecondCountableTopology β
inst✝¹ : MeasurableSpace β
inst✝ : BorelSpace β
s : Set β
s_count : s.Countable
s_dense : Dense s
f : α → β
h :
  ∀ p ∈ s,
    ∀ q ∈ s, p < q → ∃ u v, MeasurableSet u ∧ MeasurableSet v ∧ {x | f x < p} ⊆ u ∧ {x | q < f x} ⊆ v ∧ μ (u ∩ v) = 0
this✝ : Encodable ↑s
u v : β → β → Set α
huv :
  ∀ (p q : β),
    MeasurableSet (u p q) ∧
      MeasurableSet (v p q) ∧
        {x | f x < p} ⊆ u p q ∧ {x | q < f x} ⊆ v p q ∧ (p ∈ s → q ∈ s → p < q → μ (u p q ∩ v p q) = 0)
u' : β → Set α := fun p ↦ ⋂ q ∈ s ∩ Ioi p, u p q
u'_meas : ∀ (i : β), MeasurableSet (u' i)
f' : α → β := fun x ↦ ⨅ i, (u' ↑i).piecewise (fun x ↦ ↑i) (fun x ↦ ⊤) x
f'_meas : Measurable f'
t : Set α := ⋃ p, ⋃ q, u' ↑p ∩ v ↑p ↑q
μt : μ t ≤ 0
this : μ t = 0
y : α
⊢ y ∈ {x | (fun x ↦ x ∉ t) x}ᶜ ↔ y ∈ t

Tactic:
simp only [mem_ofPred_eq, mem_compl_iff, not_notMem]

Goal state after:
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 ∈ Set.Ioo 0 (linearGrowthInf fun n ↦ ↑(v n)) →
    ∀ b' ∈ Set.Ioo 0 (linearGrowthSup u), a * b' ≤ linearGrowthSup (u ∘ v)

Tactic:
⟨a_0, a_v⟩

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' ∈ Set.Ioo 0 (linearGrowthSup u), a * b' ≤ linearGrowthSup (u ∘ v)
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)
⊢ expGrowthSup (∑ x ∈ insert a t, u x) = ⨆ x ∈ insert a t, expGrowthSup (u x)

Tactic:
rw [Finset.sum_insert a_t, expGrowthSup_add, ← Finset.iSup_coe,
    Finset.coe_insert a t, iSup_insert, Finset.iSup_coe, ha]

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 ≠ ∞
⊢ ∃ s,
    MeasurableSet s ∧
      (∀ (t : Set α), MeasurableSet t → t ⊆ s → ν t ≤ μ t) ∧ ∀ (t : Set α), MeasurableSet t → t ⊆ sᶜ → μ t ≤ ν t

Tactic:
have to_nnreal_μ : ∀ s, ((μ s).toNNReal : ℝ≥0∞) = μ s := fun s => ENNReal.coe_toNNReal <| hμ _

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
⊢ ∃ s,
    MeasurableSet s ∧
      (∀ (t : Set α), MeasurableSet t → t ⊆ s → ν t ≤ μ t) ∧ ∀ (t : Set α), MeasurableSet t → t ⊆ sᶜ → μ t ≤ ν t
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 = ∫⁻ (x : α), f x ∂(μ s)⁻¹ • μ.restrict s

Tactic:
by
  simp only [laverage_eq', restrict_apply_univ]

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:
apply le_antisymm _ (linearGrowthSup_comp_nonneg h u_0 v_top)

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 : 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: α : Type u_1
E : Type u_2
m0 : MeasurableSpace α
inst✝³ : NormedAddCommGroup E
inst✝² : NormedSpace ℝ E
inst✝¹ : CompleteSpace E
μ : Measure α
inst✝ : IsFiniteMeasure μ
h : NeZero μ
c : E
⊢ ⨍ (_x : α), c ∂μ = c

Tactic:
by
  rw [average, integral_const, measureReal_def, measure_univ, ENNReal.toReal_one, one_smul]

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
inst✝ : IsFiniteMeasure μ
hμ : μ ≠ 0
hf : Integrable f μ
⊢ 0 < μ {x | ⨍ (a : α), f a ∂μ ≤ f x}

Tactic:
simpa using measure_setAverage_le_pos (Measure.measure_univ_ne_zero.2 hμ) (measure_ne_top _ _)
    hf.integrableOn

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

Goal state before:
pp: case left
α : Type u_1
m : MeasurableSpace α
μ ν : Measure α
inst✝ : ν.HaveLebesgueDecomposition μ
hμν : μ ≪ ν.singularPart μ + μ.withDensity (ν.rnDeriv μ)
s : Set α
x✝ : MeasurableSet s
hνs : (μ.withDensity (ν.rnDeriv μ)) s = 0
t : Set α
left✝ : MeasurableSet t
ht1 : (ν.singularPart μ) t = 0
ht2 : μ tᶜ = 0
⊢ μ (s ∩ t) = 0

pp: case right
α : Type u_1
m : MeasurableSpace α
μ ν : Measure α
inst✝ : ν.HaveLebesgueDecomposition μ
hμν : μ ≪ ν.singularPart μ + μ.withDensity (ν.rnDeriv μ)
s : Set α
x✝ : MeasurableSet s
hνs : (μ.withDensity (ν.rnDeriv μ)) s = 0
t : Set α
left✝ : MeasurableSet t
ht1 : (ν.singularPart μ) t = 0
ht2 : μ tᶜ = 0
⊢ μ (s ∩ tᶜ) = 0

Tactic:
· refine hμν ?_
    simp only [coe_add, Pi.add_apply, add_eq_zero]
    constructor
    · exact measure_mono_null Set.inter_subset_right ht1
    · exact measure_mono_null Set.inter_subset_left hνs

Goal state after:
case right
α : Type u_1
m : MeasurableSpace α
μ ν : Measure α
inst✝ : ν.HaveLebesgueDecomposition μ
hμν : μ ≪ ν.singularPart μ + μ.withDensity (ν.rnDeriv μ)
s : Set α
x✝ : MeasurableSet s
hνs : (μ.withDensity (ν.rnDeriv μ)) s = 0
t : Set α
left✝ : MeasurableSet t
ht1 : (ν.singularPart μ) t = 0
ht2 : μ tᶜ = 0
⊢ μ (s ∩ tᶜ) = 0
Module: Mathlib.MeasureTheory.Measure.Decomposition.Lebesgue

Goal state before:
pp: case pos
α : Type u_1
m : MeasurableSpace α
μ ν : Measure α
s : Set α
hs : μ s ≠ ∞
hl : μ.HaveLebesgueDecomposition ν
⊢ ∫⁻ (x : α) in toMeasurable μ s, μ.rnDeriv ν x ∂ν < ∞

Tactic:
← withDensity_apply _ (measurableSet_toMeasurable _ _)

Goal state after:
case pos
α : Type u_1
m : MeasurableSpace α
μ ν : Measure α
s : Set α
hs : μ s ≠ ∞
hl : μ.HaveLebesgueDecomposition ν
⊢ (ν.withDensity (μ.rnDeriv ν)) (toMeasurable μ s) < ∞
Module: Mathlib.MeasureTheory.Measure.Decomposition.Lebesgue

Goal state before:
pp: α : Type u_1
m : MeasurableSpace α
ν μ : Measure α
inst✝¹ : IsFiniteMeasure ν
inst✝ : ν.HaveLebesgueDecomposition μ
r : ℝ≥0∞
hr : r ≠ 0
hr_ne_top : r ≠ ∞
⊢ r.toNNReal ≠ 0

Tactic:
rw [ne_eq, ENNReal.toNNReal_eq_zero_iff]

Goal state after:
α : Type u_1
m : MeasurableSpace α
ν μ : Measure α
inst✝¹ : IsFiniteMeasure ν
inst✝ : ν.HaveLebesgueDecomposition μ
r : ℝ≥0∞
hr : r ≠ 0
hr_ne_top : r ≠ ∞
⊢ ¬(r = 0 ∨ r = ∞)
Module: Mathlib.MeasureTheory.Measure.Decomposition.Lebesgue

Goal state before:
pp: α : Type u_1
m : MeasurableSpace α
ν μ : Measure α
inst✝¹ : IsFiniteMeasure ν
inst✝ : ν.HaveLebesgueDecomposition μ
r : ℝ≥0∞
hr : r ≠ 0
hr_ne_top : r ≠ ∞
h : ν.rnDeriv (r.toNNReal • μ) =ᵐ[μ] r.toNNReal⁻¹ • ν.rnDeriv μ
x : α
⊢ r.toNNReal ≠ 0

Tactic:
rw [ne_eq, ENNReal.toNNReal_eq_zero_iff]

Goal state after:
α : Type u_1
m : MeasurableSpace α
ν μ : Measure α
inst✝¹ : IsFiniteMeasure ν
inst✝ : ν.HaveLebesgueDecomposition μ
r : ℝ≥0∞
hr : r ≠ 0
hr_ne_top : r ≠ ∞
h : ν.rnDeriv (r.toNNReal • μ) =ᵐ[μ] r.toNNReal⁻¹ • ν.rnDeriv μ
x : α
⊢ ¬(r = 0 ∨ r = ∞)
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 ⟂ₘ μ
A : ∀ ε > 0, ∀ᵐ (x : α) ∂μ, ∀ᶠ (a : Set α) in v.filterAt x, ρ a < ↑ε * μ a
u : ℕ → ℝ≥0
left✝ : StrictAnti u
u_pos : ∀ (n : ℕ), 0 < u n
u_lim : Tendsto u atTop (𝓝 0)
B : ∀ᵐ (x : α) ∂μ, ∀ (n : ℕ), ∀ᶠ (a : Set α) in v.filterAt x, ρ a < ↑(u n) * μ a
x : α
hx : ∀ (n : ℕ), ∀ᶠ (a : Set α) in v.filterAt x, ρ a < ↑(u n) * μ a
h'x : ∀ᶠ (a : Set α) in v.filterAt x, 0 < μ a
z : ℝ≥0∞
hz : z > 0
w : ℝ≥0
w_pos : 0 < ↑w
w_lt : ↑w < z
n : ℕ
hn : u n < w
a : Set α
ha : ρ a < ↑(u n) * μ a
μa_pos : 0 < μ a
μa_lt_top : μ a < ∞
⊢ ↑w * μ a ≤ z * μ a

Tactic:
w_lt

Goal state after:
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 ⟂ₘ μ
A : ∀ ε > 0, ∀ᵐ (x : α) ∂μ, ∀ᶠ (a : Set α) in v.filterAt x, ρ a < ↑ε * μ a
u : ℕ → ℝ≥0
left✝ : StrictAnti u
u_pos : ∀ (n : ℕ), 0 < u n
u_lim : Tendsto u atTop (𝓝 0)
B : ∀ᵐ (x : α) ∂μ, ∀ (n : ℕ), ∀ᶠ (a : Set α) in v.filterAt x, ρ a < ↑(u n) * μ a
x : α
hx : ∀ (n : ℕ), ∀ᶠ (a : Set α) in v.filterAt x, ρ a < ↑(u n) * μ a
h'x : ∀ᶠ (a : Set α) in v.filterAt x, 0 < μ a
z : ℝ≥0∞
hz : z > 0
w : ℝ≥0
w_pos : 0 < ↑w
w_lt : ↑w < z
n : ℕ
hn : u n < w
a : Set α
ha : ρ a < ↑(u n) * μ a
μa_pos : 0 < μ a
μa_lt_top : μ a < ∞
⊢ z * μ a ≤ z * μ a
Module: Mathlib.MeasureTheory.Measure.Decomposition.Lebesgue

Goal state before:
pp: case 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
n : ℕ
⊢ AEMeasurable (⨆ k, ⨆ (_ : k ≤ n), f k) ν

Tactic:
refine Measurable.aemeasurable ?_

Goal state after:
case 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
n : ℕ
⊢ Measurable (⨆ k, ⨆ (_ : k ≤ n), f k)
Module: Mathlib.MeasureTheory.Covering.Differentiation

Goal state before:
pp: case refine_5
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
p q : ℝ≥0
hpq : p < q
s : Set α := {x | ∃ c, Tendsto (fun a ↦ ρ a / μ a) (v.filterAt x) (𝓝 c)}
o : ℕ → Set α := spanningSets (ρ + μ)
u : ℕ → Set α := fun n ↦ s ∩ {x | v.limRatio ρ x < ↑p} ∩ o n
w : ℕ → Set α := fun n ↦ s ∩ {x | ↑q < v.limRatio ρ x} ∩ o n
m n : ℕ
I : (ρ + μ) (u m) ≠ ∞
J : (ρ + μ) (w n) ≠ ∞
⊢ μ (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) = 0

Tactic:
have A :
    ρ (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) ≤
      p * μ (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) :=
    calc
      ρ (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) =
          ρ (u m ∩ toMeasurable (ρ + μ) (w n)) :=
        measure_toMeasurable_add_inter_left (measurableSet_toMeasurable _ _) I
      _ ≤ (p • μ) (u m ∩ toMeasurable (ρ + μ) (w n)) := by
        refine v.measure_le_of_frequently_le (p • μ) hρ _ fun x hx => ?_
        have L : Tendsto (fun a : Set α => ρ a / μ a) (v.filterAt x) (𝓝 (v.limRatio ρ x)) :=
          tendsto_nhds_limUnder hx.1.1.1
        have I : ∀ᶠ b : Set α in v.filterAt x, ρ b / μ b < p := (tendsto_order.1 L).2 _ hx.1.1.2
        apply I.frequently.mono fun a ha => ?_
        rw [coe_nnreal_smul_apply]
        refine (ENNReal.div_le_iff_le_mul ?_ (Or.inr (bot_le.trans_lt ha).ne')).1 ha.le
        simp only [ENNReal.coe_ne_top, Ne, or_true, not_false_iff]
      _ = p * μ (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) := by
        simp only [coe_nnreal_smul_apply,
          measure_toMeasurable_add_inter_right (measurableSet_toMeasurable _ _) I]

Goal state after:
case refine_5
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
p q : ℝ≥0
hpq : p < q
s : Set α := {x | ∃ c, Tendsto (fun a ↦ ρ a / μ a) (v.filterAt x) (𝓝 c)}
o : ℕ → Set α := spanningSets (ρ + μ)
u : ℕ → Set α := fun n ↦ s ∩ {x | v.limRatio ρ x < ↑p} ∩ o n
w : ℕ → Set α := fun n ↦ s ∩ {x | ↑q < v.limRatio ρ x} ∩ o n
m n : ℕ
I : (ρ + μ) (u m) ≠ ∞
J : (ρ + μ) (w n) ≠ ∞
A :
  ρ (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) ≤
    ↑p * μ (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n))
⊢ μ (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) = 0
Module: Mathlib.Analysis.Calculus.Monotone

Goal state before:
pp: case hfh
f : ℝ → ℝ
hf : Monotone f
x : ℝ
hx :
  Tendsto (fun b ↦ (↑hf.stieltjesFunction b - f x) / (b - x)) (𝓝[<] x)
      (𝓝 (hf.stieltjesFunction.measure.rnDeriv volume x).toReal) ∧
    Tendsto (fun b ↦ (↑hf.stieltjesFunction b - f x) / (b - x)) (𝓝[>] x)
      (𝓝 (hf.stieltjesFunction.measure.rnDeriv volume x).toReal)
h'x : ¬¬ContinuousAt f x
A : ↑hf.stieltjesFunction x = f x
L1 : Tendsto (fun y ↦ (f y - f x) / (y - x)) (𝓝[>] x) (𝓝 (hf.stieltjesFunction.measure.rnDeriv volume x).toReal)
this :
  Tendsto (fun y ↦ (↑hf.stieltjesFunction (y + -1 * (y - x) ^ 2) - f x) / (y - x)) (𝓝[<] x)
    (𝓝 (hf.stieltjesFunction.measure.rnDeriv volume x).toReal)
⊢ ∀ᶠ (b : ℝ) in 𝓝[<] x, (f b - f x) / (b - x) ≤ (↑hf.stieltjesFunction (b + -1 * (b - x) ^ 2) - f x) / (b - x)

Tactic:
· filter_upwards [self_mem_nhdsWithin]
      rintro y hy
      rw [mem_Iio, ← sub_neg] at hy
      have : 0 < (y - x) ^ 2 := sq_pos_of_neg hy
      apply div_le_div_of_nonpos_of_le hy.le
      exact (sub_le_sub_iff_right _).2 (hf.rightLim_le (by linarith))

Goal state after:
Module: Mathlib.Analysis.Calculus.Monotone

Goal state before:
pp: f : ℝ → ℝ
hf : Monotone f
⊢ ∀ᵐ (x : ℝ), DifferentiableAt ℝ f x

Tactic:
filter_upwards [hf.ae_hasDerivAt] with x hx using hx.differentiableAt

Goal state after:
Module: Mathlib.Topology.EMetricSpace.VariationOnFromTo

Goal state before:
pp: case pos
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
a b : α
hab : a ≤ b
⊢ |variationOnFromTo f s a b| ≤ (eVariationOn f s).toReal

Tactic:
simp only [variationOnFromTo, hab, ↓reduceIte, ENNReal.abs_toReal]
    exact ENNReal.toReal_mono hf (eVariationOn.mono _ inter_subset_left)

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

Goal state before:
pp: α : Type u_1
m : MeasurableSpace α
ν μ : Measure α
inst✝¹ : SigmaFinite ν
inst✝ : SigmaFinite μ
r : ℝ≥0∞
hr : r ≠ 0
hr_ne_top : r ≠ ∞
⊢ r.toNNReal ≠ 0

Tactic:
rw [ne_eq, ENNReal.toNNReal_eq_zero_iff]

Goal state after:
α : Type u_1
m : MeasurableSpace α
ν μ : Measure α
inst✝¹ : SigmaFinite ν
inst✝ : SigmaFinite μ
r : ℝ≥0∞
hr : r ≠ 0
hr_ne_top : r ≠ ∞
⊢ ¬(r = 0 ∨ r = ∞)
Module: Mathlib.Topology.EMetricSpace.VariationOnFromTo

Goal state before:
pp: α : Type u_1
inst✝³ : LinearOrder α
s : Set α
E : Type u_3
inst✝² : PseudoMetricSpace E
inst✝¹ : TopologicalSpace α
inst✝ : OrderTopology α
f : α → E
l : E
a b : α
ha : a ∈ s
hb : b ∈ s
hf : LocallyBoundedVariationOn f s
h'f : Tendsto f (𝓝[s ∩ Ioi b] b) (𝓝 l)
⊢ Tendsto (variationOnFromTo f s a) (𝓝[s ∩ Ioi b] b) (𝓝 (variationOnFromTo f s a b + dist (f b) l))

Tactic:
suffices H : Tendsto (fun x ↦ variationOnFromTo f s a b + variationOnFromTo f s b x)
      (𝓝[s ∩ Ioi b] b) (𝓝 (variationOnFromTo f s a b + dist (f b) l)) by
    apply Tendsto.congr' _ H
    filter_upwards [self_mem_nhdsWithin] with x hx
    rw [variationOnFromTo.add hf ha hb hx.1]
  apply Tendsto.const_add
  suffices H : Tendsto (fun x ↦ (eVariationOn f (s ∩ Icc b x)).toReal) (𝓝[s ∩ Ioi b] b)
      (𝓝 (dist (f b) l)) by
    apply Tendsto.congr' _ H
    filter_upwards [self_mem_nhdsWithin] with x hx using by simp [variationOnFromTo, hx.2.le]
  rw [dist_edist]
  exact (ENNReal.tendsto_toReal (by simp)).comp (hf.tendsto_eVariationOn_Icc_right h'f hb)

Goal state after:
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 : TopologicalSpace α
inst✝ : OrderTopology α
f : α → E
s : Set α
a : α
h : (𝓝[s ∩ Iio a] a).NeBot
h' : ContinuousWithinAt f (s ∩ Iic a) a
ha : a ∈ s
⊢ eVariationOn f (s ∩ Iio a) = eVariationOn f (s ∩ Iic a)

Tactic:
have : Tendsto f (𝓝[s ∩ Iio a] a) (𝓝 (f a)) := h'.mono (by grind)

Goal state after:
case pos
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
h : (𝓝[s ∩ Iio a] a).NeBot
h' : ContinuousWithinAt f (s ∩ Iic a) a
ha : a ∈ s
this : Tendsto f (𝓝[s ∩ Iio a] a) (𝓝 (f a))
⊢ eVariationOn f (s ∩ Iio a) = eVariationOn f (s ∩ Iic a)
Module: Mathlib.Analysis.CStarAlgebra.ContinuousFunctionalCalculus.Unital

Goal state before:
pp: case pos
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✝ g : R → R
a✝ : A
ha : p a✝
hf : ContinuousOn f✝ (spectrum R a✝)
hg : ContinuousOn g (spectrum R a✝)
f : R → R
a : A
h : ContinuousOn f (spectrum R a)
⊢ star (cfc f a) * cfc f a = cfc f a * star (cfc f a)

pp: case neg
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✝ g : R → R
a✝ : A
ha : p a✝
hf : ContinuousOn f✝ (spectrum R a✝)
hg : ContinuousOn g (spectrum R a✝)
f : R → R
a : A
h : ¬ContinuousOn f (spectrum R a)
⊢ star (cfc f a) * cfc f a = cfc f a * star (cfc f a)

Tactic:
· rw [← cfc_star, ← cfc_mul .., ← cfc_mul ..]
      congr! 2
      exact mul_comm _ _

Goal state after:
case neg
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✝ g : R → R
a✝ : A
ha : p a✝
hf : ContinuousOn f✝ (spectrum R a✝)
hg : ContinuousOn g (spectrum R a✝)
f : R → R
a : A
h : ¬ContinuousOn f (spectrum R a)
⊢ star (cfc f a) * cfc f a = cfc f a * star (cfc f a)