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
⊢ Set.EqOn (iteratedDerivWithin (n + 1) (fun x ↦ (1 + x) ^ a) B)
    (fun x ↦ (descPochhammer ℤ (n + 1)).smeval a * (1 + x) ^ (a - ↑(n + 1))) B

Tactic:
| succ n ih =>

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

Goal state before:
pp: 𝕜 : Type u_1
inst✝⁴ : NontriviallyNormedField 𝕜
E : Type u_2
inst✝³ : NormedAddCommGroup E
inst✝² : NormedSpace 𝕜 E
F : Type u_3
inst✝¹ : NormedAddCommGroup F
inst✝ : NormedSpace 𝕜 F
f : E → F
p : FormalMultilinearSeries 𝕜 E F
s : Set E
x : E
r : ℝ≥0∞
h : HasFPowerSeriesWithinOnBall f p s x r
h' : AnalyticOn 𝕜 f s
hu : UniqueDiffOn 𝕜 s
hx : x ∈ s
n : ℕ
hn : p n = 0
this : iteratedFDerivWithin 𝕜 n f s x = (p.iteratedFDerivSeries n 0) fun x ↦ 0
⊢ iteratedFDerivWithin 𝕜 n f s x = 0

Tactic:
rw [this, p.iteratedFDerivSeries_eq_zero (p.congr_zero (Nat.zero_add n).symm hn), zero_apply]

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

Goal state before:
pp: 𝕜 : Type u_1
inst✝⁴ : NontriviallyNormedField 𝕜
E : Type u_2
inst✝³ : NormedAddCommGroup E
inst✝² : NormedSpace 𝕜 E
F : Type u_3
inst✝¹ : NormedAddCommGroup F
inst✝ : NormedSpace 𝕜 F
f : E → F
p : FormalMultilinearSeries 𝕜 E F
s : Set E
x : E
r : ℝ≥0∞
h : HasFPowerSeriesWithinOnBall f p s x r
h' : AnalyticOn 𝕜 f s
hs : UniqueDiffOn 𝕜 s
hx : x ∈ s
n : ℕ
v : Fin n → E
h's : s ⊆ Metric.eball x r
I : insert x s ∩ Metric.eball x r = s
fcont : ContDiffOn 𝕜 (↑n) f s
g : E → F := fun z ↦ (p n) fun x_1 ↦ z - x
gcont : ContDiff 𝕜 ω g
q : FormalMultilinearSeries 𝕜 E F := fun k ↦ if h : n = k then h ▸ p n else 0
⊢ HasFiniteFPowerSeriesOnBall g q x (n + 1) r

Tactic:
apply HasFiniteFPowerSeriesOnBall.mk' _ h.r_pos

Goal state after:
𝕜 : Type u_1
inst✝⁴ : NontriviallyNormedField 𝕜
E : Type u_2
inst✝³ : NormedAddCommGroup E
inst✝² : NormedSpace 𝕜 E
F : Type u_3
inst✝¹ : NormedAddCommGroup F
inst✝ : NormedSpace 𝕜 F
f : E → F
p : FormalMultilinearSeries 𝕜 E F
s : Set E
x : E
r : ℝ≥0∞
h : HasFPowerSeriesWithinOnBall f p s x r
h' : AnalyticOn 𝕜 f s
hs : UniqueDiffOn 𝕜 s
hx : x ∈ s
n : ℕ
v : Fin n → E
h's : s ⊆ Metric.eball x r
I : insert x s ∩ Metric.eball x r = s
fcont : ContDiffOn 𝕜 (↑n) f s
g : E → F := ⋯
gcont : ContDiff 𝕜 ω g
q : FormalMultilinearSeries 𝕜 E F := ⋯
⊢ ∀ y ∈ Metric.eball 0 r, (∑ i ∈ Finset.range (n + 1), (q i) fun x ↦ y) = g (x + y)

𝕜 : Type u_1
inst✝⁴ : NontriviallyNormedField 𝕜
E : Type u_2
inst✝³ : NormedAddCommGroup E
inst✝² : NormedSpace 𝕜 E
F : Type u_3
inst✝¹ : NormedAddCommGroup F
inst✝ : NormedSpace 𝕜 F
f : E → F
p : FormalMultilinearSeries 𝕜 E F
s : Set E
x : E
r : ℝ≥0∞
h : HasFPowerSeriesWithinOnBall f p s x r
h' : AnalyticOn 𝕜 f s
hs : UniqueDiffOn 𝕜 s
hx : x ∈ s
n : ℕ
v : Fin n → E
h's : s ⊆ Metric.eball x r
I : insert x s ∩ Metric.eball x r = s
fcont : ContDiffOn 𝕜 (↑n) f s
g : E → F := ⋯
gcont : ContDiff 𝕜 ω g
q : FormalMultilinearSeries 𝕜 E F := ⋯
⊢ ∀ (m : ℕ), n + 1 ≤ m → q m = 0
Module: Mathlib.Analysis.Analytic.Binomial

Goal state before:
pp: case e'_10
a b : ℂ
⊢ (FormalMultilinearSeries.ofScalars ℂ fun n ↦ a * ↑n + b) =
    (b - a) • FormalMultilinearSeries.ofScalars ℂ 1 + a • FormalMultilinearSeries.ofScalars ℂ fun n ↦ ↑n + 1

Tactic:
ext; simp; ring

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

Goal state before:
pp: 𝕜 : Type u_1
inst✝⁴ : NontriviallyNormedField 𝕜
E : Type u_2
inst✝³ : NormedAddCommGroup E
inst✝² : NormedSpace 𝕜 E
F : Type u_3
inst✝¹ : NormedAddCommGroup F
inst✝ : NormedSpace 𝕜 F
f : E → F
p : FormalMultilinearSeries 𝕜 E F
s : Set E
x : E
r : ℝ≥0∞
h : HasFPowerSeriesWithinOnBall f p s x r
h' : AnalyticOn 𝕜 f s
hs : UniqueDiffOn 𝕜 s
hx : x ∈ s
n : ℕ
v : Fin n → E
h's : s ⊆ Metric.eball x r
I : insert x s ∩ Metric.eball x r = s
fcont : ContDiffOn 𝕜 (↑n) f s
g : E → F := ⋯
gcont : ContDiff 𝕜 ω g
q : FormalMultilinearSeries 𝕜 E F := ⋯
⊢ ∀ (m : ℕ), n + 1 ≤ m → q m = 0

Tactic:
· intro m hm
      have : n ≠ m := by lia
      simp [q, this]

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

Goal state before:
pp: case e'_10
a b : ℝ
⊢ (FormalMultilinearSeries.ofScalars ℝ fun x ↦ a * ↑x + b) =
    (b - a) • FormalMultilinearSeries.ofScalars ℝ 1 + a • FormalMultilinearSeries.ofScalars ℝ fun n ↦ ↑n + 1

Tactic:
ext; simp; ring

Goal state after:
Module: Mathlib.Analysis.AperiodicOrder.Delone.Basic

Goal state before:
pp: case coveringRadius
X : Type u_1
Y : Type u_2
inst✝² : MetricSpace X
inst✝¹ : MetricSpace Y
Z : Type u_3
inst✝ : MetricSpace Z
D : DeloneSet X
f : X ≃ Y
g : Y ≃ Z
K₁f K₂f K₁g K₂g : ℝ≥0
hf₁_pos : 0 < K₁f
hf₂_pos : 0 < K₂f
hg₁_pos : 0 < K₁g
hg₂_pos : 0 < K₂g
hf_anti : AntilipschitzWith K₁f ⇑f
hf_lip : LipschitzWith K₂f ⇑f
hg_anti : AntilipschitzWith K₁g ⇑g
hg_lip : LipschitzWith K₂g ⇑g
⊢ ↑(mapBilipschitz g K₁g K₂g hg₁_pos hg₂_pos hg_anti hg_lip
          (mapBilipschitz f K₁f K₂f hf₁_pos hf₂_pos hf_anti hf_lip D)).coveringRadius =
    ↑(mapBilipschitz (f.trans g) (K₁f * K₁g) (K₂g * K₂f) ⋯ ⋯ ⋯ ⋯ D).coveringRadius

Tactic:
· simp only [mapBilipschitz_coveringRadius, NNReal.coe_mul, mul_assoc]

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

Goal state before:
pp: x : EReal
n : ℕ
⊢ (↑n * x).exp.log = ↑n * x.exp.log

Tactic:
log_exp

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

Goal state before:
pp: α : Type u_1
β : Type u_2
l : Filter α
k f : α → β
inst✝⁴ : TopologicalSpace β
inst✝³ : Field β
inst✝² : LinearOrder β
inst✝¹ : IsStrictOrderedRing β
inst✝ : OrderTopology β
hk : Tendsto k l atTop
⊢ SuperpolynomialDecay l k f ↔ ∀ (z : ℕ), IsBoundedUnder (fun x1 x2 ↦ x1 ≤ x2) l fun a ↦ |k a ^ z * f a|

Tactic:
refine
    ⟨fun h z => Tendsto.isBoundedUnder_le (Tendsto.abs (h z)), fun h =>
      (superpolynomialDecay_iff_abs_tendsto_zero l k f).2 fun z => ?_⟩

Goal state after:
α : Type u_1
β : Type u_2
l : Filter α
k f : α → β
inst✝⁴ : TopologicalSpace β
inst✝³ : Field β
inst✝² : LinearOrder β
inst✝¹ : IsStrictOrderedRing β
inst✝ : OrderTopology β
hk : Tendsto k l atTop
h : ∀ (z : ℕ), IsBoundedUnder (fun x1 x2 ↦ x1 ≤ x2) l fun a ↦ |k a ^ z * f a|
z : ℕ
⊢ Tendsto (fun a ↦ |k a ^ z * f a|) l (𝓝 0)
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 ({x | g x + ↑ε ≤ f x ∧ g x ≤ ↑N} ∩ spanningSets μ p) = 0

Tactic:
have A : (∫⁻ x in s, g x ∂μ) + ε * μ s ≤ (∫⁻ x in s, g x ∂μ) + 0 :=
      calc
        (∫⁻ x in s, g x ∂μ) + ε * μ s = (∫⁻ x in s, g x ∂μ) + ∫⁻ _ in s, ε ∂μ := by
          simp only [lintegral_const, Set.univ_inter, MeasurableSet.univ, Measure.restrict_apply]
        _ = ∫⁻ x in s, g x + ε ∂μ := (lintegral_add_right _ measurable_const).symm
        _ ≤ ∫⁻ x in s, f x ∂μ :=
          setLIntegral_mono_ae hf.restrict <| ae_of_all _ fun x hx => hx.1.1
        _ ≤ (∫⁻ x in s, g x ∂μ) + 0 := by
          rw [add_zero, ← Measure.restrict_toMeasurable s_lt_top.ne]
          refine h _ (measurableSet_toMeasurable ..) ?_
          rwa [measure_toMeasurable]

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 < ∞
A : ∫⁻ (x : α) in s, g x ∂μ + ↑ε * μ s ≤ ∫⁻ (x : α) in s, g x ∂μ + 0
⊢ μ ({x | g x + ↑ε ≤ f x ∧ g x ≤ ↑N} ∩ spanningSets μ p) = 0
Module: Mathlib.MeasureTheory.Integral.Average

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

Tactic:
have := Fact.mk h.lt_top
  rw [← measure_mul_laverage, restrict_apply_univ]

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

Goal state before:
pp: case neg
α : Type u_1
E : Type u_2
m0 : MeasurableSpace α
inst✝¹ : NormedAddCommGroup E
inst✝ : NormedSpace ℝ E
μ : Measure α
f : α → E
s t : Set α
hd : AEDisjoint μ s t
ht : NullMeasurableSet t μ
hsμ : μ s ≠ ∞
htμ : μ t ≠ ∞
hfs : IntegrableOn f s μ
hft : IntegrableOn f t μ
hse : ¬μ s = 0
⊢ ⨍ (x : α) in s ∪ t, f x ∂μ ∈ [⨍ (x : α) in s, f x ∂μ -[ℝ] ⨍ (x : α) in t, f x ∂μ]

Tactic:
· refine
      mem_segment_iff_div.mpr
        ⟨μ.real s, μ.real t, ENNReal.toReal_nonneg, ENNReal.toReal_nonneg, ?_,
          (average_union hd ht hsμ htμ hfs hft).symm⟩
    calc
      0 < μ.real s := ENNReal.toReal_pos hse hsμ
      _ ≤ _ := le_add_of_nonneg_right ENNReal.toReal_nonneg

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

Goal state before:
pp: case refine_1
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 < ∞
⊢ Set.univ ∈ Set.image2 (fun x1 x2 ↦ x1 ×ˢ x2) {s | MeasurableSet s} {t | MeasurableSet t}

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 < ∞
⊢ ∀ t ∈ Set.image2 (fun x1 x2 ↦ x1 ×ˢ x2) {s | MeasurableSet s} {t | MeasurableSet t},
    ∫⁻ (x : α × β) in t, f x ∂μ = ∫⁻ (x : α × β) in t, g x ∂μ

Tactic:
· exact ⟨Set.univ, .univ, Set.univ, .univ, Set.univ_prod_univ⟩

Goal state after:
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 < ∞
⊢ ∀ t ∈ Set.image2 (fun x1 x2 ↦ x1 ×ˢ x2) {s | MeasurableSet s} {t | MeasurableSet t},
    ∫⁻ (x : α × β) in t, f x ∂μ = ∫⁻ (x : α × β) in t, g x ∂μ
Module: Mathlib.MeasureTheory.Measure.Sub

Goal state before:
pp: α : Type u_1
m : MeasurableSpace α
μ ν : Measure α
s : Set α
h_meas_s : MeasurableSet s
h_nonempty : {d | μ ≤ d + ν}.Nonempty
⊢ (sInf {d | μ ≤ d + ν}).restrict s = sInf {d | μ.restrict s ≤ d + ν.restrict s}

Tactic:
restrict_sInf_eq_sInf_restrict h_nonempty h_meas_s

Goal state after:
α : Type u_1
m : MeasurableSpace α
μ ν : Measure α
s : Set α
h_meas_s : MeasurableSet s
h_nonempty : {d | μ ≤ d + ν}.Nonempty
⊢ sInf ((fun μ ↦ μ.restrict s) '' {d | μ ≤ d + ν}) = sInf {d | μ.restrict s ≤ d + ν.restrict s}
Module: Mathlib.MeasureTheory.Covering.Vitali

Goal state before:
pp: α : Type u_1
ι : Type u_2
inst✝⁴ : PseudoMetricSpace α
inst✝³ : MeasurableSpace α
inst✝² : OpensMeasurableSpace α
inst✝¹ : SecondCountableTopology α
μ : Measure α
inst✝ : IsLocallyFiniteMeasure μ
s : Set α
t : Set ι
C : ℝ≥0
r : ι → ℝ
c : ι → α
B : ι → Set α
hB : ∀ a ∈ t, B a ⊆ closedBall (c a) (r a)
μB : ∀ a ∈ t, μ (closedBall (c a) (3 * r a)) ≤ ↑C * μ (B a)
ht : ∀ a ∈ t, (interior (B a)).Nonempty
h't : ∀ a ∈ t, IsClosed[PseudoMetricSpace.toUniformSpace.toTopologicalSpace] (B a)
hf : ∀ x ∈ s, ∃ᶠ (ε : ℝ) in 𝓝[>] 0, ∃ a ∈ t, r a = ε ∧ c a = x
⊢ ∀ x ∈ s, ∀ ε > 0, ∃ a ∈ t, r a ≤ ε ∧ c a = x

Tactic:
intro x hx ε hε

Goal state after:
α : Type u_1
ι : Type u_2
inst✝⁴ : PseudoMetricSpace α
inst✝³ : MeasurableSpace α
inst✝² : OpensMeasurableSpace α
inst✝¹ : SecondCountableTopology α
μ : Measure α
inst✝ : IsLocallyFiniteMeasure μ
s : Set α
t : Set ι
C : ℝ≥0
r : ι → ℝ
c : ι → α
B : ι → Set α
hB : ∀ a ∈ t, B a ⊆ closedBall (c a) (r a)
μB : ∀ a ∈ t, μ (closedBall (c a) (3 * r a)) ≤ ↑C * μ (B a)
ht : ∀ a ∈ t, (interior (B a)).Nonempty
h't : ∀ a ∈ t, IsClosed[PseudoMetricSpace.toUniformSpace.toTopologicalSpace] (B a)
hf : ∀ x ∈ s, ∃ᶠ (ε : ℝ) in 𝓝[>] 0, ∃ a ∈ t, r a = ε ∧ c a = x
x : α
hx : x ∈ s
ε : ℝ
hε : ε > 0
⊢ ∃ a ∈ t, r a ≤ ε ∧ c a = x
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
⊢ (r • ν).singularPart μ + μ.withDensity ((r • ν).rnDeriv μ) = (r • ν).singularPart μ + r • μ.withDensity (ν.rnDeriv μ)

Tactic:
← (r • ν).haveLebesgueDecomposition_add μ,

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
⊢ r • ν = (r • ν).singularPart μ + r • μ.withDensity (ν.rnDeriv μ)
Module: Mathlib.Order.Monotone.Extension

Goal state before:
pp: case neg
α : Type u_1
β : Type u_2
inst✝¹ : LinearOrder α
inst✝ : ConditionallyCompleteLinearOrder β
f : α → β
s : Set α
h : MonotoneOn f s
hu : BddAbove (f '' s)
a : β
ha : a ∈ lowerBounds (f '' s)
hu' : ∀ (x : α), BddAbove (f '' (Iic x ∩ s))
g : α → β := fun x ↦ if Disjoint (Iic x) s then a else sSup (f '' (Iic x ∩ s))
hgs : EqOn f g s
x y : α
hxy : x ≤ y
hx : Disjoint (Iic x) s
hy : ¬Disjoint (Iic y) s
z : α
hz : z ∈ Iic y ∩ s
⊢ a ≤ sSup (f '' (Iic y ∩ s))

Tactic:
exact le_csSup_of_le (hu' _) (mem_image_of_mem _ hz) (ha <| mem_image_of_mem _ hz.2)

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

Goal state before:
pp: 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)
y : ℝ
hy : y - x < 0
this : 0 < (y - x) ^ 2
⊢ ↑hf.stieltjesFunction (y + -1 * (y - x) ^ 2) - f x ≤ f y - f x

Tactic:
exact (sub_le_sub_iff_right _).2 (hf.rightLim_le (by linarith))

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
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
h : ¬(μ₁, ξ).1 ⟂ₘ ν
ε : ℝ≥0
hε₁ : 0 < ε
E : Set α
hE₁ : MeasurableSet E
hE₂ : 0 < ν E
hE₃ : ∀ (A : Set α), MeasurableSet A → ↑ε * ν (A ∩ E) ≤ (μ - ν.withDensity ξ) (A ∩ E)
hε₂ : ∀ (A : Set α), MeasurableSet A → ∫⁻ (a : α) in A ∩ E, ↑ε + ξ a ∂ν ≤ μ (A ∩ E)
A : Set α
hA : MeasurableSet A
this :
  ∫⁻ (a : α) in A, (ξ + E.indicator fun x ↦ ↑ε) a ∂ν = ∫⁻ (a : α) in A ∩ E, ↑ε + ξ a ∂ν + ∫⁻ (a : α) in A \ E, ξ a ∂ν
⊢ ∫⁻ (x : α) in A, (ξ + E.indicator fun x ↦ ↑ε) x ∂ν ≤ μ A

Tactic:
rw [this, ← measure_inter_add_sdiff A hE₁]

Goal state after:
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
h : ¬(μ₁, ξ).1 ⟂ₘ ν
ε : ℝ≥0
hε₁ : 0 < ε
E : Set α
hE₁ : MeasurableSet E
hE₂ : 0 < ν E
hE₃ : ∀ (A : Set α), MeasurableSet A → ↑ε * ν (A ∩ E) ≤ (μ - ν.withDensity ξ) (A ∩ E)
hε₂ : ∀ (A : Set α), MeasurableSet A → ∫⁻ (a : α) in A ∩ E, ↑ε + ξ a ∂ν ≤ μ (A ∩ E)
A : Set α
hA : MeasurableSet A
this :
  ∫⁻ (a : α) in A, (ξ + E.indicator fun x ↦ ↑ε) a ∂ν = ∫⁻ (a : α) in A ∩ E, ↑ε + ξ a ∂ν + ∫⁻ (a : α) in A \ E, ξ a ∂ν
⊢ ∫⁻ (a : α) in A ∩ E, ↑ε + ξ a ∂ν + ∫⁻ (a : α) in A \ E, ξ a ∂ν ≤ μ (A ∩ E) + μ (A \ E)
Module: Mathlib.Topology.EMetricSpace.VariationOnFromTo

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 : LocallyBoundedVariationOn f s
a b : α
ha : a ∈ s
hb : b ∈ s
⊢ variationOnFromTo f s a b = 0 ↔ ∀ ⦃x : α⦄, x ∈ s ∩ uIcc a b → ∀ ⦃y : α⦄, y ∈ s ∩ uIcc a b → edist (f x) (f y) = 0

Tactic:
rcases le_total a b with (ab | ba)

Goal state after:
case inl
α : Type u_1
inst✝¹ : LinearOrder α
E : Type u_2
inst✝ : PseudoEMetricSpace E
f : α → E
s : Set α
hf : LocallyBoundedVariationOn f s
a b : α
ha : a ∈ s
hb : b ∈ s
ab : a ≤ b
⊢ variationOnFromTo f s a b = 0 ↔ ∀ ⦃x : α⦄, x ∈ s ∩ uIcc a b → ∀ ⦃y : α⦄, y ∈ s ∩ uIcc a b → edist (f x) (f y) = 0

case inr
α : Type u_1
inst✝¹ : LinearOrder α
E : Type u_2
inst✝ : PseudoEMetricSpace E
f : α → E
s : Set α
hf : LocallyBoundedVariationOn f s
a b : α
ha : a ∈ s
hb : b ∈ s
ba : b ≤ a
⊢ variationOnFromTo f s a b = 0 ↔ ∀ ⦃x : α⦄, x ∈ s ∩ uIcc a b → ∀ ⦃y : α⦄, y ∈ s ∩ uIcc a b → edist (f x) (f y) = 0
Module: Mathlib.Topology.EMetricSpace.BoundedVariation

Goal state before:
pp: case succ
α : Type u_1
inst✝¹ : LinearOrder α
E : Type u_2
inst✝ : PseudoEMetricSpace E
f : α → E
s : Set α
u : ℕ → α
u_mono : Monotone u
u_mem : ∀ (i : ℕ), u i ∈ s
n : ℕ
ih :
  ∃ p,
    ↑p.snd p.fst = u n ∧
      ∑ x ∈ Finset.range n, edist (f (u (x + 1))) (f (u x)) =
        ∑ i ∈ Finset.range p.fst, edist (f (↑p.snd (i + 1))) (f (↑p.snd i))
⊢ ∃ p,
    ↑p.snd p.fst = u (n + 1) ∧
      ∑ x ∈ Finset.range (n + 1), edist (f (u (x + 1))) (f (u x)) =
        ∑ i ∈ Finset.range p.fst, edist (f (↑p.snd (i + 1))) (f (↑p.snd i))

Tactic:
| succ n ih =>

Goal state after:
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
n : ℕ
u : ℕ → α
⊢ Monotone u →
    (∀ (i : ℕ), u i ∈ s) →
      ∑ x ∈ Finset.range n, edist (f (u (x + 1))) (f (u x)) ≤
        ⨆ p ∈ {p | p.1 ∈ s ∧ p.2 ∈ s ∧ p.1 ≤ p.2}, eVariationOn f (s ∩ Icc p.1 p.2)

Tactic:
hu

Goal state after:
α : Type u_1
inst✝¹ : LinearOrder α
E : Type u_2
inst✝ : PseudoEMetricSpace E
f : α → E
s : Set α
n : ℕ
u : ℕ → α
hu : Monotone u
⊢ (∀ (i : ℕ), u i ∈ s) →
    ∑ x ∈ Finset.range n, edist (f (u (x + 1))) (f (u x)) ≤
      ⨆ p ∈ {p | p.1 ∈ s ∧ p.2 ∈ s ∧ p.1 ≤ p.2}, eVariationOn f (s ∩ Icc p.1 p.2)
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
⊢ (r • ν).singularPart μ + μ.withDensity ((r • ν).rnDeriv μ) = (r • ν).singularPart μ + r • μ.withDensity (ν.rnDeriv μ)

Tactic:
← (r • ν).haveLebesgueDecomposition_add μ,

Goal state after:
α : Type u_1
m : MeasurableSpace α
ν μ : Measure α
inst✝¹ : SigmaFinite ν
inst✝ : SigmaFinite μ
r : ℝ≥0
⊢ r • ν = (r • ν).singularPart μ + r • μ.withDensity (ν.rnDeriv μ)
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
s : Set α
hs : MeasurableSet s
⊢ Tendsto (fun t ↦ ↑t * (μ.withDensity (v.limRatioMeas hρ)) s) (𝓝[>] 1) (𝓝 (1 * (μ.withDensity (v.limRatioMeas hρ)) s))

Tactic:
refine ENNReal.Tendsto.mul_const (ENNReal.tendsto_coe.2 nhdsWithin_le_nhds) ?_

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 ≪ μ
s : Set α
hs : MeasurableSet s
⊢ 1 ≠ 0 ∨ (μ.withDensity (v.limRatioMeas hρ)) s ≠ ∞
Module: Mathlib.Topology.EMetricSpace.BoundedVariation

Goal state before:
pp: case succ
α : Type u_1
inst✝¹ : LinearOrder α
E✝ : Type u_2
inst✝ : PseudoEMetricSpace E✝
f : α → E✝
s : Set α
E : ℕ → α
hE : Monotone E
n : ℕ
ih :
  (∀ (i : ℕ), 0 < i → i < n → E i ∈ s) →
    ∑ i ∈ Finset.range n, eVariationOn f (s ∩ Icc (E i) (E (i + 1))) = eVariationOn f (s ∩ Icc (E 0) (E n))
hn : ∀ (i : ℕ), 0 < i → i < n + 1 → E i ∈ s
⊢ ∑ i ∈ Finset.range (n + 1), eVariationOn f (s ∩ Icc (E i) (E (i + 1))) = eVariationOn f (s ∩ Icc (E 0) (E (n + 1)))

Tactic:
| succ n ih =>

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

Goal state before:
pp: case succ
α : Type u_1
inst✝¹ : LinearOrder α
E : Type u_2
inst✝ : PseudoEMetricSpace E
f : α → E
u : ℕ → α
hu : Monotone u
n : ℕ
ih : eVariationOn f (u '' Iic n) = ∑ i ∈ Finset.range n, edist (f (u i)) (f (u (i + 1)))
⊢ eVariationOn f (u '' Iic (n + 1)) = ∑ i ∈ Finset.range (n + 1), edist (f (u i)) (f (u (i + 1)))

Tactic:
| succ n ih =>

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

Goal state before:
pp: case inl
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
t : Set β
φ : β → α
hφ : MonotoneOn φ t
h✝ : IsEmpty β
⊢ eVariationOn f (φ '' t) ≤ eVariationOn (f ∘ φ) t

Tactic:
simp [Set.eq_empty_of_isEmpty]

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

Goal state before:
pp: case inl
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
t : Set β
φ : β → α
hφ : AntitoneOn φ t
h✝ : IsEmpty β
⊢ eVariationOn f (φ '' t) ≤ eVariationOn (f ∘ φ) t

Tactic:
simp [Set.eq_empty_of_isEmpty]

Goal state after: