mathlib-initiative/mathlib-tactics huggingface dataset:
Module: Mathlib.Probability.Independence.Integration

Goal state before:
pp: Ω : Type u_1
f : Ω → ℝ≥0∞
Mf mΩ : MeasurableSpace Ω
μ : Measure Ω
hMf : Mf ≤ mΩ
c : ℝ≥0∞
T : Set Ω
h_meas_T : MeasurableSet T
h_ind : IndepSets {s | MeasurableSet s} {T} μ
h_meas_f : Measurable f
⊢ ∫⁻ (ω : Ω), f ω * T.indicator (fun x ↦ c) ω ∂μ = (∫⁻ (ω : Ω), f ω ∂μ) * ∫⁻ (ω : Ω), T.indicator (fun x ↦ c) ω ∂μ

Tactic:
by
  revert f
  have h_mul_indicator : ∀ g, Measurable g → Measurable fun a => g a * T.indicator (fun _ => c) a :=
    fun g h_mg => h_mg.mul (measurable_const.indicator h_meas_T)
  apply @Measurable.ennreal_induction _ Mf
  · intro c' s' h_meas_s'
    simp_rw [← inter_indicator_mul]
    rw [lintegral_indicator (MeasurableSet.inter (hMf _ h_meas_s') h_meas_T),
      lintegral_indicator (hMf _ h_meas_s'), lintegral_indicator h_meas_T]
    simp only [lintegral_const, univ_inter,
      MeasurableSet.univ, Measure.restrict_apply]
    rw [IndepSets_iff] at h_ind
    rw [mul_mul_mul_comm, h_ind s' T h_meas_s' (Set.mem_singleton _)]
  · intro f' g _ h_meas_f' _ h_ind_f' h_ind_g
    have h_measM_f' : Measurable f' := h_meas_f'.mono hMf le_rfl
    simp_rw [Pi.add_apply, right_distrib]
    rw [lintegral_add_left (h_mul_indicator _ h_measM_f'), lintegral_add_left h_measM_f',
      right_distrib, h_ind_f', h_ind_g]
  · intro f h_meas_f h_mono_f h_ind_f
    have h_measM_f : ∀ n, Measurable (f n) := fun n => (h_meas_f n).mono hMf le_rfl
    simp_rw [iSup_mul]
    rw [lintegral_iSup h_measM_f h_mono_f, lintegral_iSup, iSup_mul]
    · simp_rw [← h_ind_f]
    · exact fun n => h_mul_indicator _ (h_measM_f n)
    · exact fun m n h_le a => mul_le_mul_left (h_mono_f h_le a) _

Goal state after:
Module: Mathlib.Probability.Moments.Variance

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
X : Ω → ℝ
⊢ eVar[X; 0] = 0

Tactic:
simp [evariance]

Goal state after:
Module: Mathlib.Probability.Moments.Variance

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
⊢ eVar[0; μ] = 0

Tactic:
simp [evariance]

Goal state after:
Module: Mathlib.Probability.Independence.Integration

Goal state before:
pp: case iSup
Ω : Type u_1
f : Ω → ℝ≥0∞
Mf Mg mΩ : MeasurableSpace Ω
μ : Measure Ω
hMf : Mf ≤ mΩ
hMg : Mg ≤ mΩ
h_ind : Indep Mf Mg μ
h_meas_f : Measurable f
h_measM_f : Measurable f
f' : ℕ → Ω → ℝ≥0∞
h_meas_f' : ∀ (n : ℕ), Measurable (f' n)
h_mono_f' : Monotone f'
h_ind_f' : ∀ (n : ℕ), ∫⁻ (ω : Ω), f ω * f' n ω ∂μ = (∫⁻ (ω : Ω), f ω ∂μ) * ∫⁻ (ω : Ω), f' n ω ∂μ
h_measM_f' : ∀ (n : ℕ), Measurable (f' n)
⊢ ∫⁻ (ω : Ω), ⨆ i, f ω * f' i ω ∂μ = (∫⁻ (ω : Ω), f ω ∂μ) * ∫⁻ (ω : Ω), ⨆ n, f' n ω ∂μ

Tactic:
rw [lintegral_iSup, lintegral_iSup h_measM_f' h_mono_f', mul_iSup]

Goal state after:
case iSup
Ω : Type u_1
f : Ω → ℝ≥0∞
Mf Mg mΩ : MeasurableSpace Ω
μ : Measure Ω
hMf : Mf ≤ mΩ
hMg : Mg ≤ mΩ
h_ind : Indep Mf Mg μ
h_meas_f : Measurable f
h_measM_f : Measurable f
f' : ℕ → Ω → ℝ≥0∞
h_meas_f' : ∀ (n : ℕ), Measurable (f' n)
h_mono_f' : Monotone f'
h_ind_f' : ∀ (n : ℕ), ∫⁻ (ω : Ω), f ω * f' n ω ∂μ = (∫⁻ (ω : Ω), f ω ∂μ) * ∫⁻ (ω : Ω), f' n ω ∂μ
h_measM_f' : ∀ (n : ℕ), Measurable (f' n)
⊢ ⨆ n, ∫⁻ (a : Ω), f a * f' n a ∂μ = ⨆ i, (∫⁻ (ω : Ω), f ω ∂μ) * ∫⁻ (a : Ω), f' i a ∂μ

case iSup.hf
Ω : Type u_1
f : Ω → ℝ≥0∞
Mf Mg mΩ : MeasurableSpace Ω
μ : Measure Ω
hMf : Mf ≤ mΩ
hMg : Mg ≤ mΩ
h_ind : Indep Mf Mg μ
h_meas_f : Measurable f
h_measM_f : Measurable f
f' : ℕ → Ω → ℝ≥0∞
h_meas_f' : ∀ (n : ℕ), Measurable (f' n)
h_mono_f' : Monotone f'
h_ind_f' : ∀ (n : ℕ), ∫⁻ (ω : Ω), f ω * f' n ω ∂μ = (∫⁻ (ω : Ω), f ω ∂μ) * ∫⁻ (ω : Ω), f' n ω ∂μ
h_measM_f' : ∀ (n : ℕ), Measurable (f' n)
⊢ ∀ (n : ℕ), Measurable fun ω ↦ f ω * f' n ω

case iSup.h_mono
Ω : Type u_1
f : Ω → ℝ≥0∞
Mf Mg mΩ : MeasurableSpace Ω
μ : Measure Ω
hMf : Mf ≤ mΩ
hMg : Mg ≤ mΩ
h_ind : Indep Mf Mg μ
h_meas_f : Measurable f
h_measM_f : Measurable f
f' : ℕ → Ω → ℝ≥0∞
h_meas_f' : ∀ (n : ℕ), Measurable (f' n)
h_mono_f' : Monotone f'
h_ind_f' : ∀ (n : ℕ), ∫⁻ (ω : Ω), f ω * f' n ω ∂μ = (∫⁻ (ω : Ω), f ω ∂μ) * ∫⁻ (ω : Ω), f' n ω ∂μ
h_measM_f' : ∀ (n : ℕ), Measurable (f' n)
⊢ Monotone fun i ω ↦ f ω * f' i ω
Module: Mathlib.Probability.Moments.Covariance

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
X Y : Ω → ℝ
μ : Measure Ω
inst✝ : IsProbabilityMeasure μ
hY : Integrable Y μ
c : ℝ
⊢ cov[X, fun ω ↦ c - Y ω; μ] = -cov[X, Y; μ]

Tactic:
simp [sub_eq_add_neg, hY.fun_neg]

Goal state after:
Module: Mathlib.Probability.Moments.Covariance

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
ι : Type u_2
X : ι → Ω → ℝ
s : Finset ι
inst✝ : IsFiniteMeasure μ
ι' : Type u_3
Y : ι' → Ω → ℝ
t : Finset ι'
hX : ∀ i ∈ s, MemLp (X i) 2 μ
hY : ∀ i ∈ t, MemLp (Y i) 2 μ
⊢ cov[∑ i ∈ s, X i, ∑ j ∈ t, Y j; μ] = ∑ i ∈ s, ∑ j ∈ t, cov[X i, Y j; μ]

Tactic:
covariance_sum_left' hX

Goal state after:
Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
ι : Type u_2
X : ι → Ω → ℝ
s : Finset ι
inst✝ : IsFiniteMeasure μ
ι' : Type u_3
Y : ι' → Ω → ℝ
t : Finset ι'
hX : ∀ i ∈ s, MemLp (X i) 2 μ
hY : ∀ i ∈ t, MemLp (Y i) 2 μ
⊢ ∑ i ∈ s, cov[X i, ∑ j ∈ t, Y j; μ] = ∑ i ∈ s, ∑ j ∈ t, cov[X i, Y j; μ]

Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
ι : Type u_2
X : ι → Ω → ℝ
s : Finset ι
inst✝ : IsFiniteMeasure μ
ι' : Type u_3
Y : ι' → Ω → ℝ
t : Finset ι'
hX : ∀ i ∈ s, MemLp (X i) 2 μ
hY : ∀ i ∈ t, MemLp (Y i) 2 μ
⊢ MemLp (∑ j ∈ t, Y j) 2 μ
Module: Mathlib.Probability.Moments.Variance

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
inst✝ : IsFiniteMeasure μ
X : Ω → ℝ
hX : MemLp X 2 μ
c : ℝ
hc : 0 < c
⊢ μ {ω | c ≤ |X ω - ∫ (x : Ω), X x ∂μ|} ≤ ENNReal.ofReal (Var[X; μ] / c ^ 2)

Tactic:
rw [ENNReal.ofReal_div_of_pos (sq_pos_of_ne_zero hc.ne.symm), hX.ofReal_variance_eq]
  convert! @meas_ge_le_evariance_div_sq _ _ _ _ hX.1 c.toNNReal (by simp [hc]) using 1
  · simp
  · rw [ENNReal.ofReal_pow hc.le]
    rfl

Goal state after:
Module: Mathlib.Probability.HasLaw

Goal state before:
pp: Ω : Type u_1
𝓧 : Type u_2
mΩ : MeasurableSpace Ω
m𝓧 : MeasurableSpace 𝓧
X Y : Ω → 𝓧
μ : Measure 𝓧
P : Measure Ω
hX : HasLaw X μ P
hY : Y =ᵐ[P] X
⊢ map Y P = μ

Tactic:
map_congr hY,

Goal state after:
Ω : Type u_1
𝓧 : Type u_2
mΩ : MeasurableSpace Ω
m𝓧 : MeasurableSpace 𝓧
X Y : Ω → 𝓧
μ : Measure 𝓧
P : Measure Ω
hX : HasLaw X μ P
hY : Y =ᵐ[P] X
⊢ map X P = μ
Module: Mathlib.Probability.Independence.Integration

Goal state before:
pp: case pos
Ω : Type u_1
𝕜 : Type u_2
inst✝¹⁴ : RCLike 𝕜
mΩ : MeasurableSpace Ω
μ : Measure Ω
𝓧 : Type u_3
𝓨 : Type u_4
E : Type u_5
F : Type u_6
G : Type u_7
inst✝¹³ : MeasurableSpace 𝓧
inst✝¹² : MeasurableSpace 𝓨
inst✝¹¹ : NormedAddCommGroup E
inst✝¹⁰ : NormedSpace ℝ E
inst✝⁹ : NormedSpace 𝕜 E
inst✝⁸ : CompleteSpace E
inst✝⁷ : NormedAddCommGroup F
inst✝⁶ : NormedSpace ℝ F
inst✝⁵ : NormedSpace 𝕜 F
inst✝⁴ : CompleteSpace F
inst✝³ : NormedAddCommGroup G
inst✝² : NormedSpace ℝ G
inst✝¹ : NormedSpace 𝕜 G
inst✝ : CompleteSpace G
X : Ω → 𝓧
Y : Ω → 𝓨
f : 𝓧 → E
g : 𝓨 → F
hXY : X ⟂ᵢ[μ] Y
hX : AEMeasurable X μ
hY : AEMeasurable Y μ
hf : AEStronglyMeasurable f (Measure.map X μ)
hg : AEStronglyMeasurable g (Measure.map Y μ)
B : E →L[𝕜] F →L[𝕜] G
c : ℝ≥0
hc : c ≠ 0
hB : ∀ (x : E) (y : F), ↑c * ‖x‖ * ‖y‖ ≤ ‖(B x) y‖
this✝³ : MeasurableSpace E := borel E
this✝² : BorelSpace E
this✝¹ : MeasurableSpace F := borel F
this✝ : BorelSpace F
hfXgY : (f ∘ X) ⟂ᵢ[μ] g ∘ Y
hfX : AEStronglyMeasurable (f ∘ X) μ
hgY : AEStronglyMeasurable (g ∘ Y) μ
h'X : ¬∀ᵐ (ω : Ω) ∂μ, f (X ω) = 0
h'Y : ∀ᵐ (ω : Ω) ∂μ, g (Y ω) = 0
h' : ∀ᵐ (ω : Ω) ∂μ, (B (f (X ω))) (g (Y ω)) = 0
⊢ ∫ (ω : Ω), (B (f (X ω))) (g (Y ω)) ∂μ = (B (∫ (ω : Ω), f (X ω) ∂μ)) (∫ (ω : Ω), g (Y ω) ∂μ)

Tactic:
simp [integral_congr_ae h'Y, integral_congr_ae h']

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

Goal state before:
pp: ι : Type u_1
E : Type u_2
Ω' : Type u_3
m' : MeasurableSpace Ω'
μ' : Measure Ω'
inst✝⁴ : IsProbabilityMeasure μ'
mE : MeasurableSpace E
Z : Ω' → E
l : Filter ι
inst✝³ : PseudoEMetricSpace E
inst✝² : BorelSpace E
inst✝¹ : l.IsCountablyGenerated
inst✝ : l.NeBot
X : ι → Ω' → E
h : TendstoInMeasure μ' X l Z
hX : ∀ (i : ι), AEMeasurable (X i) μ'
⊢ TendstoInDistribution X l Z (fun x ↦ μ') μ'

Tactic:
have hZ := h.aemeasurable hX

Goal state after:
ι : Type u_1
E : Type u_2
Ω' : Type u_3
m' : MeasurableSpace Ω'
μ' : Measure Ω'
inst✝⁴ : IsProbabilityMeasure μ'
mE : MeasurableSpace E
Z : Ω' → E
l : Filter ι
inst✝³ : PseudoEMetricSpace E
inst✝² : BorelSpace E
inst✝¹ : l.IsCountablyGenerated
inst✝ : l.NeBot
X : ι → Ω' → E
h : TendstoInMeasure μ' X l Z
hX : ∀ (i : ι), AEMeasurable (X i) μ'
hZ : AEMeasurable Z μ'
⊢ TendstoInDistribution X l Z (fun x ↦ μ') μ'
Module: Mathlib.MeasureTheory.Function.ConvergenceInDistribution

Goal state before:
pp: ι : Type u_1
E : Type u_2
Ω' : Type u_3
Ω'' : Type u_4
m' : MeasurableSpace Ω'
μ' : Measure Ω'
inst✝⁵ : IsProbabilityMeasure μ'
m'' : MeasurableSpace Ω''
μ'' : Measure Ω''
inst✝⁴ : IsProbabilityMeasure μ''
mE : MeasurableSpace E
l : Filter ι
inst✝³ : SeminormedAddCommGroup E
inst✝² : SecondCountableTopology E
inst✝¹ : BorelSpace E
X : ι → Ω'' → E
inst✝ : l.IsCountablyGenerated
Y : ι → Ω'' → E
Z : Ω' → E
hXZ : TendstoInDistribution X l Z (fun x ↦ μ'') μ'
hXY : TendstoInMeasure μ'' (Y - X) l 0
hY : ∀ (i : ι), AEMeasurable (Y i) μ''
hZ : AEMeasurable Z μ'
hX : ∀ (i : ι), AEMeasurable (X i) μ''
hE : Nonempty E
x₀ : E := hE.some
F : E → ℝ
M : ℝ
L : NNReal
hF_lip : LipschitzWith L F
hF_cont : Continuous[PseudoMetricSpace.toUniformSpace.toTopologicalSpace, _] F
hL : 0 < L
ε : ℝ
hε : ε > 0
n : ι
a : Ω''
hF_bounded : dist (F (Y n a)) (F x₀) ≤ M
⊢ ‖F (Y n a)‖ - ‖F x₀‖ ≤ M

Tactic:
exact (abs_sub_abs_le_abs_sub (F (Y n a)) (F x₀)).trans hF_bounded

Goal state after:
Module: Mathlib.Probability.Process.Filtration

Goal state before:
pp: Ω : Type u_1
ι : Type u_2
m : MeasurableSpace Ω
inst✝² : PartialOrder ι
inst✝¹ : TopologicalSpace ι
inst✝ : OrderTopology ι
𝓕 : Filtration ι m
i : ι
⊢ ↑𝓕₊ i = if (𝓝[>] i).NeBot then ⨅ j, ⨅ (_ : j > i), ↑𝓕 j else ↑𝓕 i

Tactic:
simp +instances only [rightCont, OrderTopology.topology_eq_generate_intervals]

Goal state after:
Module: Mathlib.Probability.Independence.Kernel.IndepFun

Goal state before:
pp: α : Type u_1
Ω : Type u_2
ι : Type u_3
β : Type u_4
mα : MeasurableSpace α
mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
mβ : MeasurableSpace β
X : ι → Ω → α
Y : ι → Ω → β
f : ι → Set Ω
t : ι → Set β
s : Finset ι
inst✝ : Finite ι
hY : ∀ (i : ι), Measurable (Y i)
hindep : iIndepFun (fun i ω ↦ (X i ω, Y i ω)) κ μ
hf : ∀ i ∈ s, MeasurableSet (f i)
hy✝ : ∀ᵐ (a : α) ∂μ, ∀ i ∉ s, (κ a) (Y i ⁻¹' t i) ≠ 0
ht : ∀ (i : ι), MeasurableSet (t i)
val✝ : Fintype ι
g : ι → Set Ω := fun i' ↦ if i' ∈ s then Y i' ⁻¹' t i' ∩ f i' else Y i' ⁻¹' t i'
hYt✝ : ∀ (i : ι), MeasurableSet (Y i ⁻¹' t i)
hg✝ : ∀ (i : ι), MeasurableSet (g i)
a : α
hy : ∀ i ∉ s, (κ a) (Y i ⁻¹' t i) ≠ 0
a✝ : IsProbabilityMeasure (κ a)
hYt : (κ a) (⋂ i, Y i ⁻¹' t i) = ∏ i, (κ a) (Y i ⁻¹' t i)
hg : (κ a) (⋂ i, g i) = ∏ i, (κ a) (g i)
⊢ ((κ a) (⋂ i, Y i ⁻¹' t i))⁻¹ * (κ a) ((⋂ i, Y i ⁻¹' t i) ∩ ⋂ i ∈ s, f i) =
    ((κ a) (⋂ i, Y i ⁻¹' t i))⁻¹ * (κ a) (⋂ i, g i)

Tactic:
by
      congr 2
      calc
        _ = (⋂ i, Y i ⁻¹' t i) ∩ ⋂ i, if i ∈ s then f i else .univ := by
          congr 1
          simp only [Set.iInter_ite, Set.iInter_univ, Set.inter_univ]
        _ = ⋂ i, Y i ⁻¹' t i ∩ (if i ∈ s then f i else .univ) := by rw [Set.iInter_inter_distrib]
        _ = _ := Set.iInter_congr fun i ↦ by by_cases hi : i ∈ s <;> simp [hi, g]

Goal state after:
Module: Mathlib.MeasureTheory.Group.ModularCharacter

Goal state before:
pp: G : Type u_1
inst✝⁶ : TopologicalSpace G
inst✝⁵ : Group G
inst✝⁴ : IsTopologicalGroup G
inst✝³ : LocallyCompactSpace G
inst✝² : MeasurableSpace G
inst✝¹ : BorelSpace G
μ : Measure G
inst✝ : μ.IsHaarMeasure
g : G
ν : Measure G := haar
f : G → ℝ
f_cont : Continuous f
f_comp : HasCompactSupport ⇑{ toFun := f, continuous_toFun := f_cont }
f_nonneg : 0 ≤ { toFun := f, continuous_toFun := f_cont }
f_one : { toFun := f, continuous_toFun := f_cont } 1 ≠ 0
int_f_ne_zero : ∀ (μ₀ : Measure G) [μ₀.IsHaarMeasure], ∫ (x : G), f x ∂μ₀ ≠ 0
⊢ modularCharacterFun g = (map (fun x ↦ x * g) μ).haarScalarFactor μ

Tactic:
apply NNReal.coe_injective

Goal state after:
G : Type u_1
inst✝⁶ : TopologicalSpace G
inst✝⁵ : Group G
inst✝⁴ : IsTopologicalGroup G
inst✝³ : LocallyCompactSpace G
inst✝² : MeasurableSpace G
inst✝¹ : BorelSpace G
μ : Measure G
inst✝ : μ.IsHaarMeasure
g : G
ν : Measure G := ⋯
f : G → ℝ
f_cont : Continuous f
f_comp : HasCompactSupport ⇑{ toFun := f, continuous_toFun := f_cont }
f_nonneg : 0 ≤ { toFun := f, continuous_toFun := f_cont }
f_one : { toFun := f, continuous_toFun := f_cont } 1 ≠ 0
int_f_ne_zero : ∀ (μ₀ : Measure G) [μ₀.IsHaarMeasure], ∫ (x : G), f x ∂μ₀ ≠ 0
⊢ ↑(modularCharacterFun g) = ↑((map (fun x ↦ x * g) μ).haarScalarFactor μ)
Module: Mathlib.MeasureTheory.Integral.CircleTransform

Goal state before:
pp: E : Type u_1
inst✝¹ : NormedAddCommGroup E
inst✝ : NormedSpace ℂ E
R : ℝ
z w : ℂ
f : ℂ → E
⊢ ∫ (θ : ℝ) in 0..2 * π, (2 * ↑π * I)⁻¹ • (circleMap 0 R θ * I) • (circleMap z R θ - w)⁻¹ • f (circleMap z R θ) =
    (2 * ↑π * I)⁻¹ • ∫ (θ : ℝ) in 0..2 * π, (circleMap 0 R θ * I) • (circleMap z R θ - w)⁻¹ • f (circleMap z R θ)

Tactic:
circleMap

Goal state after:
E : Type u_1
inst✝¹ : NormedAddCommGroup E
inst✝ : NormedSpace ℂ E
R : ℝ
z w : ℂ
f : ℂ → E
⊢ ∫ (θ : ℝ) in 0..2 * π,
      (2 * ↑π * I)⁻¹ • ((0 + ↑R * cexp (↑θ * I)) * I) • (z + ↑R * cexp (↑θ * I) - w)⁻¹ • f (z + ↑R * cexp (↑θ * I)) =
    (2 * ↑π * I)⁻¹ •
      ∫ (θ : ℝ) in 0..2 * π,
        ((0 + ↑R * cexp (↑θ * I)) * I) • (z + ↑R * cexp (↑θ * I) - w)⁻¹ • f (z + ↑R * cexp (↑θ * I))
Module: Mathlib.MeasureTheory.Integral.Gamma

Goal state before:
pp: p : ℝ
hp : 1 ≤ p
⊢ ∫ (x : ℂ), rexp (-‖x‖ ^ p) = π * Real.Gamma (2 / p + 1)

Tactic:
by
  convert! (integral_rpow_mul_exp_neg_rpow hp (by linarith : (-2 : ℝ) < 0)) using 1
  · simp_rw [rpow_zero, one_mul]
  · rw [zero_add, Real.Gamma_add_one (div_ne_zero two_ne_zero (by linarith))]
    ring

Goal state after:
Module: Mathlib.MeasureTheory.Integral.CurveIntegral.Basic

Goal state before:
pp: 𝕜 : Type u_1
E : Type u_2
F : Type u_3
inst✝⁴ : RCLike 𝕜
inst✝³ : NormedAddCommGroup E
inst✝² : NormedSpace 𝕜 E
inst✝¹ : NormedAddCommGroup F
inst✝ : NormedSpace 𝕜 F
a b c : E
ω : E → E →L[𝕜] F
γab : Path a b
γbc : Path b c
h₁ : CurveIntegrable ω γab
h₂ : CurveIntegrable ω γbc
instF : NormedSpace ℝ F := NormedSpace.restrictScalars ℝ 𝕜 F
⊢ (∫ (x : ℝ) in 0..1 / 2, 2 • curveIntegralFun ω γab (2 * x)) +
      ∫ (x : ℝ) in 1 / 2..1, 2 • curveIntegralFun ω γbc (2 * x - 1) =
    ∫ᶜ (x : E) in γab, ω x + ∫ᶜ (x : E) in γbc, ω x

Tactic:
simp only [← ofNat_smul_eq_nsmul (R := ℝ)]

Goal state after:
𝕜 : Type u_1
E : Type u_2
F : Type u_3
inst✝⁴ : RCLike 𝕜
inst✝³ : NormedAddCommGroup E
inst✝² : NormedSpace 𝕜 E
inst✝¹ : NormedAddCommGroup F
inst✝ : NormedSpace 𝕜 F
a b c : E
ω : E → E →L[𝕜] F
γab : Path a b
γbc : Path b c
h₁ : CurveIntegrable ω γab
h₂ : CurveIntegrable ω γbc
instF : NormedSpace ℝ F := NormedSpace.restrictScalars ℝ 𝕜 F
⊢ (∫ (x : ℝ) in 0..1 / 2, 2 • curveIntegralFun ω γab (2 * x)) +
      ∫ (x : ℝ) in 1 / 2..1, 2 • curveIntegralFun ω γbc (2 * x - 1) =
    ∫ᶜ (x : E) in γab, ω x + ∫ᶜ (x : E) in γbc, ω x
Module: Mathlib.MeasureTheory.Integral.MeanValue

Goal state before:
pp: α : Type u_1
inst✝¹ : TopologicalSpace α
inst✝ : MeasurableSpace α
s : Set α
f g : α → ℝ
μ : Measure α
hs_conn : IsConnected s
hs_meas : MeasurableSet s
hf : ContinuousOn f s
hg : IntegrableOn g s μ
hfg : IntegrableOn (fun x ↦ f x * g x) s μ
hg0 : ∀ᵐ (x : α) ∂μ.restrict s, 0 ≤ g x
ρ : α → ENNReal := fun x ↦ ENNReal.ofReal (g x)
ν : Measure α := μ.withDensity ρ
hρ_ae : AEMeasurable ρ (μ.restrict s)
hρ_top : ∀ᵐ (x : α) ∂μ.restrict s, ρ x < ⊤
h_toReal_ae : (fun x ↦ (ρ x).toReal) =ᵐ[μ.restrict s] g
heq : ∫ (x : α) in s, f x * g x ∂μ = ∫ (x : α) in s, f x ∂ν
hg1 : g =ᵐ[μ.restrict s] 0
hν0 : ∫ (x : α) in s, 1 ∂ν = 0
c : α
hc : c ∈ s
heq_ae : (fun x ↦ f x * g x) =ᵐ[μ.restrict s] 0
⊢ ∫ (x : α) in s, f x * g x ∂μ = 0

Tactic:
simpa using! integral_congr_ae heq_ae

Goal state after:
Module: Mathlib.MeasureTheory.Integral.CurveIntegral.Basic

Goal state before:
pp: case h₁.refine_2
𝕜 : Type u_1
E : Type u_2
F : Type u_3
inst✝⁶ : RCLike 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace ℝ E
inst✝³ : NormedSpace 𝕜 E
inst✝² : NormedAddCommGroup F
inst✝¹ : NormedSpace 𝕜 F
inst✝ : CompleteSpace F
a : E
s : Set E
ω : E → E →L[𝕜] F
hs : Convex ℝ s
hω : ∀ᶠ (x : E) in 𝓝[s] a, ContinuousWithinAt ω s x
ha : a ∈ s
ε : ℝ
hε : 0 < ε
δ : ℝ
hδ₀ : δ > 0
hδ : ball a δ ∩ s ⊆ {z | ContinuousWithinAt ω s z ∧ dist (ω z) (ω a) ≤ ε}
b : E
hb : b ∈ ball a δ
hbs : b ∈ s
hsub : [a -[ℝ] b] ⊆ ball a δ ∩ s
t : ℝ
ht : t ∈ Icc 0 1
⊢ [a -[ℝ] b] ⊆ s

Tactic:
exact hs.segment_subset ha hbs

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

Goal state before:
pp: X : Type u_1
inst✝⁶ : TopologicalSpace X
inst✝⁵ : MeasurableSpace X
inst✝⁴ : BorelSpace X
inst✝³ : T2Space X
U : Set X
hU : IsOpen U
μ : Measure X
inst✝² : IsFiniteMeasure μ
inst✝¹ : μ.InnerRegularCompactLTTop
inst✝ : NormalSpace X
r : ENNReal
hr : r < μ U
K : Set X
KU : K ⊆ U
K_comp : IsCompact K
hK : r < μ K
f : X → ℝ
f_cont : Continuous f
fU : EqOn (⇑{ toFun := f, continuous_toFun := f_cont }) 0 Uᶜ
fK : EqOn (⇑{ toFun := f, continuous_toFun := f_cont }) 1 K
f_range : ∀ (x : X), { toFun := f, continuous_toFun := f_cont } x ∈ Icc 0 1
⊢ μ K ≤ ENNReal.ofReal (∫ (x : X), f x ∂μ)

Tactic:
apply Integrable.measure_le_integral

Goal state after:
case f_int
X : Type u_1
inst✝⁶ : TopologicalSpace X
inst✝⁵ : MeasurableSpace X
inst✝⁴ : BorelSpace X
inst✝³ : T2Space X
U : Set X
hU : IsOpen U
μ : Measure X
inst✝² : IsFiniteMeasure μ
inst✝¹ : μ.InnerRegularCompactLTTop
inst✝ : NormalSpace X
r : ENNReal
hr : r < μ U
K : Set X
KU : K ⊆ U
K_comp : IsCompact K
hK : r < μ K
f : X → ℝ
f_cont : Continuous f
fU : EqOn (⇑{ toFun := f, continuous_toFun := f_cont }) 0 Uᶜ
fK : EqOn (⇑{ toFun := f, continuous_toFun := f_cont }) 1 K
f_range : ∀ (x : X), { toFun := f, continuous_toFun := f_cont } x ∈ Icc 0 1
⊢ Integrable f μ

case f_nonneg
X : Type u_1
inst✝⁶ : TopologicalSpace X
inst✝⁵ : MeasurableSpace X
inst✝⁴ : BorelSpace X
inst✝³ : T2Space X
U : Set X
hU : IsOpen U
μ : Measure X
inst✝² : IsFiniteMeasure μ
inst✝¹ : μ.InnerRegularCompactLTTop
inst✝ : NormalSpace X
r : ENNReal
hr : r < μ U
K : Set X
KU : K ⊆ U
K_comp : IsCompact K
hK : r < μ K
f : X → ℝ
f_cont : Continuous f
fU : EqOn (⇑{ toFun := f, continuous_toFun := f_cont }) 0 Uᶜ
fK : EqOn (⇑{ toFun := f, continuous_toFun := f_cont }) 1 K
f_range : ∀ (x : X), { toFun := f, continuous_toFun := f_cont } x ∈ Icc 0 1
⊢ 0 ≤ᵐ[μ] f

case hs
X : Type u_1
inst✝⁶ : TopologicalSpace X
inst✝⁵ : MeasurableSpace X
inst✝⁴ : BorelSpace X
inst✝³ : T2Space X
U : Set X
hU : IsOpen U
μ : Measure X
inst✝² : IsFiniteMeasure μ
inst✝¹ : μ.InnerRegularCompactLTTop
inst✝ : NormalSpace X
r : ENNReal
hr : r < μ U
K : Set X
KU : K ⊆ U
K_comp : IsCompact K
hK : r < μ K
f : X → ℝ
f_cont : Continuous f
fU : EqOn (⇑{ toFun := f, continuous_toFun := f_cont }) 0 Uᶜ
fK : EqOn (⇑{ toFun := f, continuous_toFun := f_cont }) 1 K
f_range : ∀ (x : X), { toFun := f, continuous_toFun := f_cont } x ∈ Icc 0 1
⊢ ∀ x ∈ K, 1 ≤ f x
Module: Mathlib.MeasureTheory.Integral.RieszMarkovKakutani.Real

Goal state before:
pp: case h
X : Type u_1
inst✝⁴ : TopologicalSpace X
inst✝³ : T2Space X
inst✝² : MeasurableSpace X
inst✝¹ : BorelSpace X
Λ : (X →C_c ℝ) →ₚ[ℝ] ℝ
inst✝ : LocallyCompactSpace X
f : X →C_c ℝ
hf : ∀ (x : X), 0 ≤ f x
K : Set X
hK : IsCompact K
hfK : ∀ x ∈ K, f x = 1
p : NNReal
hp : Λ f = ↑p
⊢ (∀ x ∈ { carrier := K, isCompact' := hK }, 1 ≤ f x) ∧ (toNNRealLinear Λ) f.nnrealPart = p

Tactic:
refine ⟨(fun x hx ↦ Eq.ge (hfK x hx)), ?_⟩

Goal state after:
case h
X : Type u_1
inst✝⁴ : TopologicalSpace X
inst✝³ : T2Space X
inst✝² : MeasurableSpace X
inst✝¹ : BorelSpace X
Λ : (X →C_c ℝ) →ₚ[ℝ] ℝ
inst✝ : LocallyCompactSpace X
f : X →C_c ℝ
hf : ∀ (x : X), 0 ≤ f x
K : Set X
hK : IsCompact K
hfK : ∀ x ∈ K, f x = 1
p : NNReal
hp : Λ f = ↑p
⊢ (toNNRealLinear Λ) f.nnrealPart = p
Module: Mathlib.MeasureTheory.Integral.TorusIntegral

Goal state before:
pp: n : ℕ
E : Type u_1
inst✝¹ : NormedAddCommGroup E
inst✝ : NormedSpace ℂ E
f : (Fin (n + 1) → ℂ) → E
c : Fin (n + 1) → ℂ
R : Fin (n + 1) → ℝ
hf : TorusIntegrable f c R
⊢ (∯ (x : Fin (n + 1) → ℂ) in T(c, R), f x) =
    ∮ (x : ℂ) in C(c 0, R 0), ∯ (y : Fin n → ℂ) in T(c ∘ Fin.succ, R ∘ Fin.succ), f (Fin.cons x y)

Tactic:
by
  simpa using torusIntegral_succAbove hf 0

Goal state after:
Module: Mathlib.MeasureTheory.MeasurableSpace.Card

Goal state before:
pp: α : Type u
s : Set (Set α)
t : Set α
ht : t ∈ {t | GenerateMeasurable s t}
⊢ t ∈ generateMeasurableRec s (ω_ 1)

Tactic:
induction ht with

Goal state after:
Module: Mathlib.MeasureTheory.Measure.CharacteristicFunction.TaylorExpansion

Goal state before:
pp: E : Type u_1
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : InnerProductSpace ℝ E
inst✝³ : MeasurableSpace E
inst✝² : BorelSpace E
inst✝¹ : SecondCountableTopology E
μ : Measure E
inst✝ : IsFiniteMeasure μ
n : ℕ
t : E
hint : MemLp id (↑n) μ
x : Fin n → E
h : innerₗ E = ContinuousLinearMap.toLinearMap₁₂ (innerSL ℝ)
hint' : ∀ (k : ℕ), ↑k ≤ ↑n → Integrable (fun x ↦ ‖x‖ ^ k * ‖1 x‖) μ
⊢ ∫ (a : E), cexp (I * ↑⟪a, t⟫) * ∏ i, ↑⟪a, x i⟫ ∂μ = ∫ (y : E), (∏ i, ↑⟪y, x i⟫) * cexp (I * ↑⟪y, t⟫) ∂μ

Tactic:
congr with

Goal state after:
case e_f
E : Type u_1
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : InnerProductSpace ℝ E
inst✝³ : MeasurableSpace E
inst✝² : BorelSpace E
inst✝¹ : SecondCountableTopology E
μ : Measure E
inst✝ : IsFiniteMeasure μ
n : ℕ
t : E
hint : MemLp id (↑n) μ
x : Fin n → E
h : innerₗ E = ContinuousLinearMap.toLinearMap₁₂ (innerSL ℝ)
hint' : ∀ (k : ℕ), ↑k ≤ ↑n → Integrable (fun x ↦ ‖x‖ ^ k * ‖1 x‖) μ
x✝ : E
⊢ cexp (I * ↑⟪x✝, t⟫) * ∏ i, ↑⟪x✝, x i⟫ = (∏ i, ↑⟪x✝, x i⟫) * cexp (I * ↑⟪x✝, t⟫)
Module: Mathlib.MeasureTheory.Measure.LevyProkhorovMetric

Goal state before:
pp: case refine_2
Ω : Type u_1
inst✝⁴ : MeasurableSpace Ω
inst✝³ : PseudoEMetricSpace Ω
inst✝² : OpensMeasurableSpace Ω
μ ν : Measure Ω
inst✝¹ : IsProbabilityMeasure μ
inst✝ : IsProbabilityMeasure ν
δ : ℝ
δ_nn : 0 ≤ δ
h : ∀ (ε : ℝ) (B : Set Ω), δ < ε → MeasurableSet B → μ B ≤ ν (thickening ε B) + ENNReal.ofReal ε
ε : ℝ≥0∞
B : Set Ω
ε_gt : ENNReal.ofReal δ < ε
ε_lt_top : ε < ∞
B_mble : MeasurableSet B
⊢ ENNReal.ofReal δ < ENNReal.ofReal ε.toReal

Tactic:
· simpa [ofReal_toReal_eq_iff.mpr ε_lt_top.ne] using ε_gt

Goal state after:
Module: Mathlib.MeasureTheory.Measure.LevyProkhorovMetric

Goal state before:
pp: case hF_meas
Ω : Type u_1
inst✝² : MeasurableSpace Ω
inst✝¹ : PseudoMetricSpace Ω
inst✝ : OpensMeasurableSpace Ω
f : Ω →ᵇ ℝ
A : Set ℝ
A_finmeas : volume A ≠ ∞
μ : ProbabilityMeasure Ω
⊢ ∀ᶠ (n : ℝ) in 𝓝[>] 0, AEStronglyMeasurable (fun t ↦ ↑(μ (thickening n {a | t ≤ f a}))) (volume.restrict A)

Tactic:
apply Eventually.of_forall fun n ↦ Measurable.aestronglyMeasurable ?_

Goal state after:
Ω : Type u_1
inst✝² : MeasurableSpace Ω
inst✝¹ : PseudoMetricSpace Ω
inst✝ : OpensMeasurableSpace Ω
f : Ω →ᵇ ℝ
A : Set ℝ
A_finmeas : volume A ≠ ∞
μ : ProbabilityMeasure Ω
n : ℝ
⊢ Measurable fun t ↦ ↑(μ (thickening n {a | t ≤ f a}))
Module: Mathlib.MeasureTheory.Measure.FiniteMeasureProd

Goal state before:
pp: case refine_2
α : Type u_1
inst✝⁹ : MeasurableSpace α
β : Type u_2
inst✝⁸ : MeasurableSpace β
inst✝⁷ : TopologicalSpace α
inst✝⁶ : TopologicalSpace β
inst✝⁵ : SecondCountableTopology α
inst✝⁴ : SecondCountableTopology β
inst✝³ : PseudoMetrizableSpace α
inst✝² : PseudoMetrizableSpace β
inst✝¹ : OpensMeasurableSpace α
inst✝ : OpensMeasurableSpace β
μ : ProbabilityMeasure α × ProbabilityMeasure β
S : Set (Set (α × β)) :=
  {t | ∃ a b, MeasurableSet a ∧ μ.1 (frontier a) = 0 ∧ MeasurableSet b ∧ μ.2 (frontier b) = 0 ∧ t = a ×ˢ b}
a : Set α
b : Set β
ameas : MeasurableSet a
ha : μ.1 (frontier a) = 0
bmeas : MeasurableSet b
hb : μ.2 (frontier b) = 0
a' : Set α
b' : Set β
a'meas : MeasurableSet a'
ha' : μ.1 (frontier a') = 0
b'meas : MeasurableSet b'
hb' : μ.2 (frontier b') = 0
⊢ μ.2 (frontier (b ∩ b')) = 0

Tactic:
rw [null_iff_toMeasure_null] at hb hb' ⊢
      exact null_frontier_inter hb hb'

Goal state after: