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)) =
    (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:
show a - (n + 1) = a - n - 1 by ring,

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.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
s : Set E
x : E
h : AnalyticOn 𝕜 f s
hs : UniqueDiffOn 𝕜 s
hx : x ∈ s
n : ℕ
σ : Perm (Fin n)
⊢ ContinuousMultilinearMap.domDomCongr σ (iteratedFDerivWithin 𝕜 n f s x) = iteratedFDerivWithin 𝕜 n f s x

Tactic:
ext
  exact h.iteratedFDerivWithin_comp_perm hs hx _ _

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
s : Set E
x : E
h : ContDiffWithinAt 𝕜 ω f s x
hs : UniqueDiffOn 𝕜 s
hx : x ∈ s
n : ℕ
σ : Perm (Fin n)
⊢ ContinuousMultilinearMap.domDomCongr σ (iteratedFDerivWithin 𝕜 n f s x) = iteratedFDerivWithin 𝕜 n f s x

Tactic:
ext
  exact h.iteratedFDerivWithin_comp_perm hs hx _ _

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

Goal state before:
pp: case inl.inr.inl
y : ℝ
y_neg : y < 0
⊢ ⊥ = ↑y * ∞.log

Tactic:
log_top,

Goal state after:
case inl.inr.inl
y : ℝ
y_neg : y < 0
⊢ ⊥ = ↑y * ⊤
Module: Mathlib.Analysis.SpecialFunctions.Log.ENNRealLog

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

Tactic:
log_top,

Goal state after:
case inr.inr.inr.inl
y : ℝ
y_pos : 0 < y
⊢ ⊤ = ↑y * ⊤
Module: Mathlib.MeasureTheory.Covering.VitaliFamily

Goal state before:
pp: X : Type u_1
inst✝ : PseudoMetricSpace X
m0 : MeasurableSpace X
μ : Measure X
v : VitaliFamily μ
ι : Type u_2
l : Filter ι
f : ι → Set X
x : X
⊢ Tendsto f l (v.filterAt x) ↔ (∀ᶠ (i : ι) in l, f i ∈ v.setsAt x) ∧ ∀ ε > 0, ∀ᶠ (i : ι) in l, f i ⊆ closedBall x ε

Tactic:
simp only [filterAt, tendsto_inf, nhds_basis_closedBall.smallSets.tendsto_right_iff,
    tendsto_principal, and_comm, mem_powerset_iff]

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

Goal state before:
pp: case neg.inl
u : ℕ → EReal
v : ℕ → ℕ
h : Monotone u
hv₀ : (linearGrowthSup fun n ↦ ↑(v n)) ≠ 0
hv₁ : (linearGrowthSup fun n ↦ ↑(v n)) ≠ ⊤
u_0 : ¬u = ⊥
v_0 : 0 < linearGrowthSup fun n ↦ ↑(v n)
b : EReal
u_b : b > linearGrowthInf u
b_0 : 0 < b
v_a : ⊤ > linearGrowthSup fun n ↦ ↑(v n)
a_0 : 0 < ⊤
⊢ linearGrowthInf (u ∘ v) ≤ ⊤ * b

pp: case neg.inr
u : ℕ → EReal
v : ℕ → ℕ
h : Monotone u
hv₀ : (linearGrowthSup fun n ↦ ↑(v n)) ≠ 0
hv₁ : (linearGrowthSup fun n ↦ ↑(v n)) ≠ ⊤
u_0 : ¬u = ⊥
v_0 : 0 < linearGrowthSup fun n ↦ ↑(v n)
a : EReal
v_a : a > linearGrowthSup fun n ↦ ↑(v n)
b : EReal
u_b : b > linearGrowthInf u
a_0 : 0 < a
b_0 : 0 < b
a_top : a ≠ ⊤
⊢ linearGrowthInf (u ∘ v) ≤ a * b

Tactic:
· rw [top_mul_of_pos b_0]; exact le_top

Goal state after:
case neg.inr
u : ℕ → EReal
v : ℕ → ℕ
h : Monotone u
hv₀ : (linearGrowthSup fun n ↦ ↑(v n)) ≠ 0
hv₁ : (linearGrowthSup fun n ↦ ↑(v n)) ≠ ⊤
u_0 : ¬u = ⊥
v_0 : 0 < linearGrowthSup fun n ↦ ↑(v n)
a : EReal
v_a : a > linearGrowthSup fun n ↦ ↑(v n)
b : EReal
u_b : b > linearGrowthInf u
a_0 : 0 < a
b_0 : 0 < b
a_top : a ≠ ⊤
⊢ linearGrowthInf (u ∘ v) ≤ a * b
Module: Mathlib.Analysis.Asymptotics.ExpGrowth

Goal state before:
pp: u v : ℕ → ℝ≥0∞
b : ℝ≥0∞
hb : b ≠ 0
h : ∀ᶠ (n : ℕ) in atTop, b * u n ≤ v n
⊢ expGrowthSup u ≤ expGrowthSup v

Tactic:
by
  apply (expGrowthSup_eventually_monotone h).trans' (le_expGrowthSup_mul'.trans' _)
  rcases eq_top_or_lt_top b with rfl | b_top
  · exact expGrowthInf_top ▸ le_add_of_nonneg_left le_top
  · rw [expGrowthInf_const hb b_top.ne, zero_add]

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

Goal state before:
pp: case neg.inr.refine_2
u : ℕ → EReal
v : ℕ → ℕ
h : Monotone u
hv₀ : (linearGrowthSup fun n ↦ ↑(v n)) ≠ 0
hv₁ : (linearGrowthSup fun n ↦ ↑(v n)) ≠ ⊤
u_0 : ¬u = ⊥
v_0 : 0 < linearGrowthSup fun n ↦ ↑(v n)
a : EReal
v_a : a > linearGrowthSup fun n ↦ ↑(v n)
b : EReal
a_0 : 0 < a
b_0 : 0 < b
a_top : a ≠ ⊤
a' : EReal
a_a' : a' < a
a_0' : 0 < a'
a_a_inv' : a⁻¹ < a'⁻¹
v_a' : ∀ᶠ (n : ℕ) in atTop, ↑(v n) ≤ a' * ↑n
u_b : ∃ᶠ (x : ℕ) in atTop, (u x ≤ b * ↑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
un_bn : u n ≤ b * ↑n
right✝ : 0 < n
k : ℕ
an_k : a⁻¹ * ↑n ≤ ↑k
k_an' : a' * ↑k ≤ ↑n
vk_ak' : ↑(v k) ≤ a' * ↑k
⊢ u (v k) ≤ b * (a * ↑k)

Tactic:
rw [← EReal.div_eq_inv_mul, div_le_iff_le_mul a_0 a_top] at an_k

Goal state after:
case neg.inr.refine_2
u : ℕ → EReal
v : ℕ → ℕ
h : Monotone u
hv₀ : (linearGrowthSup fun n ↦ ↑(v n)) ≠ 0
hv₁ : (linearGrowthSup fun n ↦ ↑(v n)) ≠ ⊤
u_0 : ¬u = ⊥
v_0 : 0 < linearGrowthSup fun n ↦ ↑(v n)
a : EReal
v_a : a > linearGrowthSup fun n ↦ ↑(v n)
b : EReal
a_0 : 0 < a
b_0 : 0 < b
a_top : a ≠ ⊤
a' : EReal
a_a' : a' < a
a_0' : 0 < a'
a_a_inv' : a⁻¹ < a'⁻¹
v_a' : ∀ᶠ (n : ℕ) in atTop, ↑(v n) ≤ a' * ↑n
u_b : ∃ᶠ (x : ℕ) in atTop, (u x ≤ b * ↑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
un_bn : u n ≤ b * ↑n
right✝ : 0 < n
k : ℕ
an_k : ↑n ≤ a * ↑k
k_an' : a' * ↑k ≤ ↑n
vk_ak' : ↑(v k) ≤ a' * ↑k
⊢ u (v k) ≤ b * (a * ↑k)
Module: Mathlib.Analysis.Asymptotics.ExpGrowth

Goal state before:
pp: case a
u v : ℕ → ℝ≥0∞
⊢ expGrowthSup (u ⊔ v) ≤ expGrowthSup (u + v)

Tactic:
· refine expGrowthSup_monotone fun n ↦ ?_
    exact sup_le (self_le_add_right (u n) (v n)) (self_le_add_left (v n) (u n))

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

Goal state before:
pp: case 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 : 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
I : m / τ < m
a' : ι
ha' : a' ∈ A
xA : δ a' ∈ δ '' A
hx : m / τ < δ a'
⊢ ∃ a' ∈ A, m / τ ≤ δ a'

Tactic:
exact ⟨a', ha', hx.le⟩

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

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

Tactic:
by
  rcases eq_or_ne μ 0 with hμ | hμ
  · rw [hμ, lintegral_zero_measure, laverage_zero_measure, mul_zero]
  · rw [laverage_eq, ENNReal.mul_div_cancel (measure_univ_ne_zero.2 hμ) (measure_ne_top _ _)]

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

Goal state before:
pp: case neg
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 = ⊥
⊢ linearGrowthSup (u ∘ v) = a * linearGrowthSup u

Tactic:
by_cases! u_1 : ∀ᶠ n : ℕ in atTop, u n ≤ 0

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
⊢ linearGrowthSup (u ∘ v) = a * linearGrowthSup u

case neg
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
⊢ linearGrowthSup (u ∘ v) = a * linearGrowthSup u
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:
refine h _ (measurableSet_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 < ∞
⊢ μ (toMeasurable μ s) < ∞
Module: Mathlib.MeasureTheory.Integral.Average

Goal state before:
pp: 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
⊢ ⨍ (x : α), f x ∂μ = (μ.real univ)⁻¹ • ∫ (x : α), f x ∂μ

Tactic:
rw [average_eq', integral_smul_measure, ENNReal.toReal_inv, measureReal_def]

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

Goal state before:
pp: α : Type u_1
E : Type u_2
m0 : MeasurableSpace α
inst✝¹ : NormedAddCommGroup E
inst✝ : NormedSpace ℝ E
μ : Measure α
f g : α → E
h : f =ᵐ[μ] g
⊢ ⨍ (x : α), f x ∂μ = ⨍ (x : α), g x ∂μ

Tactic:
by
  simp only [average_eq, integral_congr_ae h]

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

Goal state before:
pp: 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
⊢ ⨍ (x : α) in s ∪ t, f x ∂μ ∈ [⨍ (x : α) in s, f x ∂μ -[ℝ] ⨍ (x : α) in t, f x ∂μ]

Tactic:
by_cases hse : μ s = 0
  · rw [← ae_eq_empty] at hse
    rw [restrict_congr_set (hse.union EventuallyEq.rfl), empty_union]
    exact right_mem_segment _ _ _
  · 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.Measure.Decomposition.Hahn

Goal state before:
pp: case refine_1
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
d_split : ∀ (s t : Set α), MeasurableSet t → d s = d (s \ t) + d (s ∩ t)
d_Union : ∀ (s : ℕ → Set α), Monotone s → Tendsto (fun n ↦ d (s n)) atTop (𝓝 (d (⋃ n, s n)))
d_Inter :
  ∀ (s : ℕ → Set α),
    (∀ (n : ℕ), MeasurableSet (s n)) →
      (∀ (n m : ℕ), n ≤ m → s m ⊆ s n) → Tendsto (fun n ↦ d (s n)) atTop (𝓝 (d (⋂ n, s n)))
bdd_c : BddAbove c
c_nonempty : c.Nonempty
d_le_γ : ∀ (s : Set α), MeasurableSet s → d s ≤ γ
this✝ : ∀ (n : ℕ), ∃ s, MeasurableSet s ∧ γ - (1 / 2) ^ n < d s
e : ℕ → Set α
he : ∀ (x : ℕ), MeasurableSet (e x) ∧ γ - (1 / 2) ^ x < d (e x)
he₁ : ∀ (n : ℕ), MeasurableSet (e n)
he₂ : ∀ (n : ℕ), γ - (1 / 2) ^ n < d (e n)
f : ℕ → ℕ → Set α := fun n m ↦ (Finset.Ico n (m + 1)).inf e
hf : ∀ (n m : ℕ), MeasurableSet (f n m)
f_subset_f : ∀ {a b c d : ℕ}, a ≤ b → c ≤ d → f a d ⊆ f b c
f_succ : ∀ (n m : ℕ), n ≤ m → f n (m + 1) = f n m ∩ e (m + 1)
n m : ℕ
h : m ≤ n
this : γ - (1 / 2) ^ m < d (e m)
⊢ γ - 2 * (1 / 2) ^ m + (1 / 2) ^ m ≤ d ({m}.inf e)

Tactic:
Finset.inf_singleton

Goal state after:
case refine_1
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
d_split : ∀ (s t : Set α), MeasurableSet t → d s = d (s \ t) + d (s ∩ t)
d_Union : ∀ (s : ℕ → Set α), Monotone s → Tendsto (fun n ↦ d (s n)) atTop (𝓝 (d (⋃ n, s n)))
d_Inter :
  ∀ (s : ℕ → Set α),
    (∀ (n : ℕ), MeasurableSet (s n)) →
      (∀ (n m : ℕ), n ≤ m → s m ⊆ s n) → Tendsto (fun n ↦ d (s n)) atTop (𝓝 (d (⋂ n, s n)))
bdd_c : BddAbove c
c_nonempty : c.Nonempty
d_le_γ : ∀ (s : Set α), MeasurableSet s → d s ≤ γ
this✝ : ∀ (n : ℕ), ∃ s, MeasurableSet s ∧ γ - (1 / 2) ^ n < d s
e : ℕ → Set α
he : ∀ (x : ℕ), MeasurableSet (e x) ∧ γ - (1 / 2) ^ x < d (e x)
he₁ : ∀ (n : ℕ), MeasurableSet (e n)
he₂ : ∀ (n : ℕ), γ - (1 / 2) ^ n < d (e n)
f : ℕ → ℕ → Set α := fun n m ↦ (Finset.Ico n (m + 1)).inf e
hf : ∀ (n m : ℕ), MeasurableSet (f n m)
f_subset_f : ∀ {a b c d : ℕ}, a ≤ b → c ≤ d → f a d ⊆ f b c
f_succ : ∀ (n m : ℕ), n ≤ m → f n (m + 1) = f n m ∩ e (m + 1)
n m : ℕ
h : m ≤ n
this : γ - (1 / 2) ^ m < d (e m)
⊢ γ - 2 * (1 / 2) ^ m + (1 / 2) ^ m ≤ d (e m)
Module: Mathlib.MeasureTheory.Measure.Sub

Goal state before:
pp: case a.refine_2
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
ν' : Measure α
h_ν'_in : μ.restrict s ≤ ν' + ν.restrict s
⊢ (fun μ ↦ μ.restrict s) (ν' + ⊤.restrict sᶜ) = ν'.restrict s

Tactic:
ext1 t h_meas_t

Goal state after:
case a.refine_2
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
ν' : Measure α
h_ν'_in : μ.restrict s ≤ ν' + ν.restrict s
t : Set α
h_meas_t : MeasurableSet t
⊢ ((fun μ ↦ μ.restrict s) (ν' + ⊤.restrict sᶜ)) t = (ν'.restrict s) t
Module: Mathlib.MeasureTheory.Measure.Sub

Goal state before:
pp: α : Type u_1
m : MeasurableSpace α
μ ν : Measure α
s : Set α
h_le : μ.restrict s ≤ ν.restrict s
h_meas_s : MeasurableSet s
⊢ (μ - ν) s = 0

Tactic:
rw [← restrict_apply_self, restrict_sub_eq_restrict_sub_restrict, sub_eq_zero_of_le]

Goal state after:
α : Type u_1
m : MeasurableSpace α
μ ν : Measure α
s : Set α
h_le : μ.restrict s ≤ ν.restrict s
h_meas_s : MeasurableSet s
⊢ 0 s = 0

α : Type u_1
m : MeasurableSpace α
μ ν : Measure α
s : Set α
h_le : μ.restrict s ≤ ν.restrict s
h_meas_s : MeasurableSet s
⊢ μ.restrict s ≤ ν.restrict s

α : Type u_1
m : MeasurableSpace α
μ ν : Measure α
s : Set α
h_le : μ.restrict s ≤ ν.restrict s
h_meas_s : MeasurableSet s
⊢ MeasurableSet s
Module: Mathlib.MeasureTheory.Integral.Average

Goal state before:
pp: α : Type u_1
E : Type u_2
m0 : MeasurableSpace α
inst✝² : NormedAddCommGroup E
inst✝¹ : NormedSpace ℝ E
μ : Measure α
inst✝ : CompleteSpace E
ι : Type u_4
a : ι → Set α
l : Filter ι
f : α → E
c : E
g : ι → α → ℝ
K : ℝ
hf : Tendsto (fun i ↦ ⨍ (y : α) in a i, ‖f y - c‖ ∂μ) l (𝓝 0)
f_int : ∀ᶠ (i : ι) in l, IntegrableOn f (a i) μ
hg : Tendsto (fun i ↦ ∫ (y : α), g i y ∂μ) l (𝓝 1)
g_supp : ∀ᶠ (i : ι) in l, support (g i) ⊆ a i
g_bound : ∀ᶠ (i : ι) in l, ∀ (x : α), |g i x| ≤ K / μ.real (a i)
g_int : ∀ᶠ (i : ι) in l, Integrable (g i) μ
I : ∀ᶠ (i : ι) in l, ∫ (y : α), g i y • (f y - c) ∂μ + (∫ (y : α), g i y ∂μ) • c = ∫ (y : α), g i y • f y ∂μ
this : Tendsto (fun x ↦ K * ⨍ (y : α) in a x, ‖f y - c‖ ∂μ) l (𝓝 (K * 0))
⊢ Tendsto (fun i ↦ ∫ (y : α), g i y • (f y - c) ∂μ) l (𝓝 0)

Tactic:
simp only [mul_zero] at this

Goal state after:
α : Type u_1
E : Type u_2
m0 : MeasurableSpace α
inst✝² : NormedAddCommGroup E
inst✝¹ : NormedSpace ℝ E
μ : Measure α
inst✝ : CompleteSpace E
ι : Type u_4
a : ι → Set α
l : Filter ι
f : α → E
c : E
g : ι → α → ℝ
K : ℝ
hf : Tendsto (fun i ↦ ⨍ (y : α) in a i, ‖f y - c‖ ∂μ) l (𝓝 0)
f_int : ∀ᶠ (i : ι) in l, IntegrableOn f (a i) μ
hg : Tendsto (fun i ↦ ∫ (y : α), g i y ∂μ) l (𝓝 1)
g_supp : ∀ᶠ (i : ι) in l, support (g i) ⊆ a i
g_bound : ∀ᶠ (i : ι) in l, ∀ (x : α), |g i x| ≤ K / μ.real (a i)
g_int : ∀ᶠ (i : ι) in l, Integrable (g i) μ
I : ∀ᶠ (i : ι) in l, ∫ (y : α), g i y • (f y - c) ∂μ + (∫ (y : α), g i y ∂μ) • c = ∫ (y : α), g i y • f y ∂μ
this : Tendsto (fun x ↦ K * ⨍ (y : α) in a x, ‖f y - c‖ ∂μ) l (𝓝 0)
⊢ Tendsto (fun i ↦ ∫ (y : α), g i y • (f y - c) ∂μ) l (𝓝 0)
Module: Mathlib.MeasureTheory.Measure.Decomposition.Lebesgue

Goal state before:
pp: α : Type u_1
m : MeasurableSpace α
μ : Measure α
inst✝ : SigmaFinite μ
h : μ.withDensity (μ.rnDeriv μ) = μ.withDensity 1
h_one : μ = μ.withDensity 1
⊢ μ.rnDeriv μ =ᵐ[μ] fun x ↦ 1

Tactic:
rwa [withDensity_eq_iff_of_sigmaFinite (measurable_rnDeriv _ _).aemeasurable] at h

Goal state after:
α : Type u_1
m : MeasurableSpace α
μ : Measure α
inst✝ : SigmaFinite μ
h : μ.withDensity (μ.rnDeriv μ) = μ.withDensity 1
h_one : μ = μ.withDensity 1
⊢ AEMeasurable 1 μ
Module: Mathlib.MeasureTheory.Integral.Average

Goal state before:
pp: α : Type u_1
E : Type u_2
m0 : MeasurableSpace α
inst✝² : NormedAddCommGroup E
inst✝¹ : NormedSpace ℝ E
μ : Measure α
inst✝ : CompleteSpace E
ι : Type u_4
a : ι → Set α
l : Filter ι
f : α → E
c : E
g : ι → α → ℝ
K : ℝ
hf : Tendsto (fun i ↦ ⨍ (y : α) in a i, ‖f y - c‖ ∂μ) l (𝓝 0)
f_int : ∀ᶠ (i : ι) in l, IntegrableOn f (a i) μ
hg : Tendsto (fun i ↦ ∫ (y : α), g i y ∂μ) l (𝓝 1)
g_supp : ∀ᶠ (i : ι) in l, support (g i) ⊆ a i
g_bound : ∀ᶠ (i : ι) in l, ∀ (x : α), |g i x| ≤ K / μ.real (a i)
g_int : ∀ᶠ (i : ι) in l, Integrable (g i) μ
I : ∀ᶠ (i : ι) in l, ∫ (y : α), g i y • (f y - c) ∂μ + (∫ (y : α), g i y ∂μ) • c = ∫ (y : α), g i y • f y ∂μ
this✝ : Tendsto (fun x ↦ K * ⨍ (y : α) in a x, ‖f y - c‖ ∂μ) l (𝓝 0)
i : ι
hi : support (g i) ⊆ a i
h''i : IntegrableOn f (a i) μ
hi_int : 0 < ∫ (y : α), g i y ∂μ
h : μ (a i) = ∞
h'i : ∀ (x : α), g i x = 0
this : ∫ (y : α), g i y ∂μ = ∫ (y : α), 0 ∂μ
⊢ False

Tactic:
simp [this] at hi_int

Goal state after:
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
s : Set α
m n : ℕ
u : ℕ → α
hu : MonotoneOn u (Icc m n)
us : ∀ i ∈ Icc m n, u i ∈ s
hnm : n ≤ m
⊢ ∑ i ∈ Finset.Ico m n, edist (f (u (i + 1))) (f (u i)) ≤ eVariationOn f s

Tactic:
simp [Finset.Ico_eq_empty_of_le hnm]

Goal state after:
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 c : α
ha : a ∈ s
hb : b ∈ s
hc : c ∈ s
⊢ variationOnFromTo f s a b - variationOnFromTo f s c b = variationOnFromTo f s a c

Tactic:
by
  rw [← variationOnFromTo.add hf ha hc hb, add_sub_cancel_right]

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

Goal state before:
pp: α : Type u_1
inst✝ : LinearOrder α
f : α → ℝ
s : Set α
hf : LocallyBoundedVariationOn f s
a b c : α
as : a ∈ s
bs : b ∈ s
cs : c ∈ s
bc : b ≤ c
⊢ variationOnFromTo f s b c = variationOnFromTo f s a c - variationOnFromTo f s a b

Tactic:
rw [← variationOnFromTo.add hf as bs cs, add_sub_cancel_left]

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

Goal state before:
pp: α : Type u_1
m : MeasurableSpace α
ν : Measure α
inst✝¹ : SigmaFinite ν
μ : Measure α
inst✝ : SFinite μ
hμ : IsFiniteMeasure μ
s : ℕ → Set α := disjointed (spanningSets ν)
⊢ μ.HaveLebesgueDecomposition ν

Tactic:
have hsm : ∀ n, MeasurableSet (s n) := .disjointed <| measurableSet_spanningSets _

Goal state after:
α : Type u_1
m : MeasurableSpace α
ν : Measure α
inst✝¹ : SigmaFinite ν
μ : Measure α
inst✝ : SFinite μ
hμ : IsFiniteMeasure μ
s : ℕ → Set α := disjointed (spanningSets ν)
hsm : ∀ (n : ℕ), MeasurableSet (s n)
⊢ μ.HaveLebesgueDecomposition ν
Module: Mathlib.Topology.ContinuousMap.StarOrdered

Goal state before:
pp: α : Type u_1
inst✝⁸ : TopologicalSpace α
R : Type u_2
inst✝⁷ : PartialOrder R
inst✝⁶ : NonUnitalSemiring R
inst✝⁵ : StarRing R
inst✝⁴ : StarOrderedRing R
inst✝³ : TopologicalSpace R
inst✝² : ContinuousStar R
inst✝¹ : IsTopologicalSemiring R
inst✝ : ContinuousSqrt R
⊢ ∀ (x y : C(α, R)), x ≤ y ↔ ∃ s, y = x + star s * s

Tactic:
intro f

Goal state after:
α : Type u_1
inst✝⁸ : TopologicalSpace α
R : Type u_2
inst✝⁷ : PartialOrder R
inst✝⁶ : NonUnitalSemiring R
inst✝⁵ : StarRing R
inst✝⁴ : StarOrderedRing R
inst✝³ : TopologicalSpace R
inst✝² : ContinuousStar R
inst✝¹ : IsTopologicalSemiring R
inst✝ : ContinuousSqrt R
f : C(α, R)
⊢ ∀ (y : C(α, R)), f ≤ y ↔ ∃ s, y = f + star s * s
Module: Mathlib.Topology.EMetricSpace.BoundedVariation

Goal state before:
pp: 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
hf : BoundedVariationOn f s
x : α
A : Tendsto (fun y ↦ eVariationOn f (s ∩ Ico y x)) (𝓝[s ∩ Iio x] x) (𝓝 0)
B : Tendsto (fun y ↦ eVariationOn f (s ∩ Ico y x)) (𝓝[s ∩ Ici x] x) (𝓝 0)
⊢ Tendsto (fun y ↦ eVariationOn f (s ∩ Ico y x)) (𝓝[s ∩ Iio x ∪ s ∩ Ici x] x) (𝓝 0)

Tactic:
nhdsWithin_union,

Goal state after:
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
hf : BoundedVariationOn f s
x : α
A : Tendsto (fun y ↦ eVariationOn f (s ∩ Ico y x)) (𝓝[s ∩ Iio x] x) (𝓝 0)
B : Tendsto (fun y ↦ eVariationOn f (s ∩ Ico y x)) (𝓝[s ∩ Ici x] x) (𝓝 0)
⊢ Tendsto (fun y ↦ eVariationOn f (s ∩ Ico y x)) (𝓝[s ∩ Iio x] x ⊔ 𝓝[s ∩ Ici x] x) (𝓝 0)