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

Goal state before:
pp: case inl
ι : Type u_1
X : ι → Type u_2
mX : (i : ι) → MeasurableSpace (X i)
μ : (i : ι) → Measure (X i)
hμ : ∀ (i : ι), IsProbabilityMeasure (μ i)
A : ℕ → Set ((i : ι) → X i)
A_mem : ∀ (n : ℕ), A n ∈ measurableCylinders X
A_anti : Antitone A
A_inter : ⋂ n, A n = ∅
this : ∀ (i : ι), Nonempty (X i)
s : ℕ → Finset ι
S : (n : ℕ) → Set ((i : ↥(s n)) → X ↑i)
mS : ∀ (n : ℕ), MeasurableSet (S n)
A_eq : ∀ (n : ℕ), A n = cylinder (s n) (S n)
u : Set ι := ⋃ n, ↑(s n)
t : ℕ → Finset ↑u := fun n ↦ (s n).preimage Subtype.val ⋯
f : ((i : ↑u) → X ↑i) → (i : ι) → X i := fun x i ↦ if hi : i ∈ u then x ⟨i, hi⟩ else Classical.ofNonempty
aux : (n : ℕ) → ↥(t n) ≃ ↥(s n) :=
  fun n ↦ { toFun := fun i ↦ ⟨↑↑i, ⋯⟩, invFun := fun i ↦ ⟨⟨↑i, ⋯⟩, ⋯⟩, left_inv := ⋯, right_inv := ⋯ }
g : (n : ℕ) → ((a : ↥(t n)) → X ↑((aux n) a)) ≃ ((b : ↥(s n)) → X ↑b) :=
  fun n ↦ Equiv.piCongrLeft (fun i ↦ X ↑i) (aux n)
r_comp_f : ∀ (n : ℕ), (s n).restrict ∘ f = ⇑(g n) ∘ fun x i ↦ x ↑i
B : ℕ → Set ((i : ↑u) → X ↑i) := fun n ↦ f ⁻¹' A n
T : (n : ℕ) → Set ((a : ↥(t n)) → X ↑((aux n) a)) := fun n ↦ ⇑(g n) ⁻¹' S n
B_eq : ∀ (n : ℕ), B n = cylinder (t n) (T n)
mT : ∀ (n : ℕ), MeasurableSet (T n)
B_mem : ∀ (n : ℕ), B n ∈ measurableCylinders fun i ↦ X ↑i
mB : ∀ (n : ℕ), MeasurableSet (B n)
B_anti : Antitone B
B_inter : ⋂ n, B n = ∅
u_fin : Finite ↑u
x✝ : Fintype ↑u := Fintype.ofFinite ↑u
⊢ Tendsto (fun n ↦ (piContent fun i ↦ μ ↑i) (B n)) atTop (𝓝 0)

Tactic:
simp_rw [fun n ↦ piContent_eq_measure_pi (fun i : u ↦ μ i) (mB n)]

Goal state after:
case inl
ι : Type u_1
X : ι → Type u_2
mX : (i : ι) → MeasurableSpace (X i)
μ : (i : ι) → Measure (X i)
hμ : ∀ (i : ι), IsProbabilityMeasure (μ i)
A : ℕ → Set ((i : ι) → X i)
A_mem : ∀ (n : ℕ), A n ∈ measurableCylinders X
A_anti : Antitone A
A_inter : ⋂ n, A n = ∅
this : ∀ (i : ι), Nonempty (X i)
s : ℕ → Finset ι
S : (n : ℕ) → Set ((i : ↥(s n)) → X ↑i)
mS : ∀ (n : ℕ), MeasurableSet (S n)
A_eq : ∀ (n : ℕ), A n = cylinder (s n) (S n)
u : Set ι := ⋃ n, ↑(s n)
t : ℕ → Finset ↑u := fun n ↦ (s n).preimage Subtype.val ⋯
f : ((i : ↑u) → X ↑i) → (i : ι) → X i := fun x i ↦ if hi : i ∈ u then x ⟨i, hi⟩ else Classical.ofNonempty
aux : (n : ℕ) → ↥(t n) ≃ ↥(s n) :=
  fun n ↦ { toFun := fun i ↦ ⟨↑↑i, ⋯⟩, invFun := fun i ↦ ⟨⟨↑i, ⋯⟩, ⋯⟩, left_inv := ⋯, right_inv := ⋯ }
g : (n : ℕ) → ((a : ↥(t n)) → X ↑((aux n) a)) ≃ ((b : ↥(s n)) → X ↑b) :=
  fun n ↦ Equiv.piCongrLeft (fun i ↦ X ↑i) (aux n)
r_comp_f : ∀ (n : ℕ), (s n).restrict ∘ f = ⇑(g n) ∘ fun x i ↦ x ↑i
B : ℕ → Set ((i : ↑u) → X ↑i) := fun n ↦ f ⁻¹' A n
T : (n : ℕ) → Set ((a : ↥(t n)) → X ↑((aux n) a)) := fun n ↦ ⇑(g n) ⁻¹' S n
B_eq : ∀ (n : ℕ), B n = cylinder (t n) (T n)
mT : ∀ (n : ℕ), MeasurableSet (T n)
B_mem : ∀ (n : ℕ), B n ∈ measurableCylinders fun i ↦ X ↑i
mB : ∀ (n : ℕ), MeasurableSet (B n)
B_anti : Antitone B
B_inter : ⋂ n, B n = ∅
u_fin : Finite ↑u
x✝ : Fintype ↑u := Fintype.ofFinite ↑u
⊢ Tendsto (fun n ↦ (Measure.pi fun i ↦ μ ↑i) (B n)) atTop (𝓝 0)
Module: Mathlib.Probability.Kernel.RadonNikodym

Goal state before:
pp: α : Type u_1
γ : Type u_2
mα : MeasurableSpace α
mγ : MeasurableSpace γ
hαγ : MeasurableSpace.CountableOrCountablyGenerated α γ
κ η : Kernel α γ
inst✝¹ : IsFiniteKernel κ
inst✝ : IsFiniteKernel η
a : α
s : Set γ
hs : MeasurableSet s
⊢ ((η.withDensity (κ.rnDeriv η)) a) (s ∩ κ.mutuallySingularSetSlice η a ∪ s \ κ.mutuallySingularSetSlice η a) +
      ((κ.singularPart η) a) (s ∩ κ.mutuallySingularSetSlice η a ∪ s \ κ.mutuallySingularSetSlice η a) =
    (κ a) (s ∩ κ.mutuallySingularSetSlice η a ∪ s \ κ.mutuallySingularSetSlice η a)

Tactic:
have hm := measurableSet_mutuallySingularSetSlice κ η a

Goal state after:
α : Type u_1
γ : Type u_2
mα : MeasurableSpace α
mγ : MeasurableSpace γ
hαγ : MeasurableSpace.CountableOrCountablyGenerated α γ
κ η : Kernel α γ
inst✝¹ : IsFiniteKernel κ
inst✝ : IsFiniteKernel η
a : α
s : Set γ
hs : MeasurableSet s
hm : MeasurableSet (κ.mutuallySingularSetSlice η a)
⊢ ((η.withDensity (κ.rnDeriv η)) a) (s ∩ κ.mutuallySingularSetSlice η a ∪ s \ κ.mutuallySingularSetSlice η a) +
      ((κ.singularPart η) a) (s ∩ κ.mutuallySingularSetSlice η a ∪ s \ κ.mutuallySingularSetSlice η a) =
    (κ a) (s ∩ κ.mutuallySingularSetSlice η a ∪ s \ κ.mutuallySingularSetSlice η a)
Module: Mathlib.Probability.Kernel.RadonNikodym

Goal state before:
pp: α : Type u_1
γ : Type u_2
mα : MeasurableSpace α
mγ : MeasurableSpace γ
κ η : Kernel α γ
hαγ : MeasurableSpace.CountableOrCountablyGenerated α γ
hκ : IsFiniteKernel κ
inst✝ : IsFiniteKernel η
a : α
⊢ ((κ.singularPart η) a) univ ≤ κ.bound

Tactic:
have h : withDensity η (rnDeriv κ η) a univ + singularPart κ η a univ = κ a univ := by
    conv_rhs => rw [← rnDeriv_add_singularPart κ η]
    simp

Goal state after:
α : Type u_1
γ : Type u_2
mα : MeasurableSpace α
mγ : MeasurableSpace γ
κ η : Kernel α γ
hαγ : MeasurableSpace.CountableOrCountablyGenerated α γ
hκ : IsFiniteKernel κ
inst✝ : IsFiniteKernel η
a : α
h : ((η.withDensity (κ.rnDeriv η)) a) univ + ((κ.singularPart η) a) univ = (κ a) univ
⊢ ((κ.singularPart η) a) univ ≤ κ.bound
Module: Mathlib.Probability.Kernel.Deterministic

Goal state before:
pp: case mpr
α : Type u_1
β : Type u_2
mα : MeasurableSpace α
mβ : MeasurableSpace β
κ : Kernel α β
inst✝ : IsFiniteKernel κ
⊢ (∀ (a : α), IsZeroOneMeasure (κ a)) → IsDeterministic κ

Tactic:
· intro _
    refine ⟨?_⟩
    ext : 1
    rw [parallelComp_comp_copy, prod_apply]
    refine Measure.prod_eq fun s t hs ht ↦ ?_
    rw [copy_comp_apply_prod _ _ hs ht]
    exact measure_inter_eq_prod hs ht

Goal state after:
Module: Mathlib.Probability.Kernel.Deterministic

Goal state before:
pp: case inl
α : Type u_1
β : Type u_2
mα : MeasurableSpace α
mβ : MeasurableSpace β
γ : Type u_3
inst✝³ : MeasurableSpace γ
κ : Kernel α β
η : Kernel β γ
inst✝² : IsMarkovKernel κ
inst✝¹ : IsMarkovKernel η
inst✝ : IsDeterministic (η ∘ₖ κ)
a : α
s : Set γ
t : Set β
hs : MeasurableSet s
ht : MeasurableSet t
this : ∀ (b : β), (η b) s * t.indicator 1 b = t.indicator (fun b ↦ (η b) s) b
h₀ : ((η ∘ₖ κ) a) s = 0
⊢ ∫⁻ (a : β) in t, (η a) s ∂κ a = 0

Tactic:
setLIntegral_eq_zero_iff ht <| η.measurable_coe hs

Goal state after:
case inl
α : Type u_1
β : Type u_2
mα : MeasurableSpace α
mβ : MeasurableSpace β
γ : Type u_3
inst✝³ : MeasurableSpace γ
κ : Kernel α β
η : Kernel β γ
inst✝² : IsMarkovKernel κ
inst✝¹ : IsMarkovKernel η
inst✝ : IsDeterministic (η ∘ₖ κ)
a : α
s : Set γ
t : Set β
hs : MeasurableSet s
ht : MeasurableSet t
this : ∀ (b : β), (η b) s * t.indicator 1 b = t.indicator (fun b ↦ (η b) s) b
h₀ : ((η ∘ₖ κ) a) s = 0
⊢ ∀ᵐ (x : β) ∂κ a, x ∈ t → (η x) s = 0
Module: Mathlib.Probability.ProductMeasure

Goal state before:
pp: ι : Type u_3
κ : ι → Type u_4
X : (i : ι) → κ i → Type u_5
mX : (i : ι) → (j : κ i) → MeasurableSpace (X i j)
μ : (i : ι) → (j : κ i) → Measure (X i j)
hμ : ∀ (i : ι) (j : κ i), IsProbabilityMeasure (μ i j)
⊢ map (⇑(piCurry X).symm) (infinitePi fun i ↦ infinitePi fun j ↦ μ i j) = infinitePi fun p ↦ μ p.fst p.snd

Tactic:
apply eq_infinitePi
  intro s t ht
  classical
  rw [map_apply (by fun_prop) (.pi (countable_toSet _) fun _ _ ↦ ht _),
    ← Finset.sigma_image_fst_preimage_mk s, coe_piCurry_symm, Finset.coe_sigma,
    Set.uncurry_preimage_sigma_pi, infinitePi_pi, Finset.prod_sigma]
  · exact Finset.prod_congr rfl (fun _ _ ↦ infinitePi_pi _ fun _ _ ↦ ht _)
  · simp only [mem_image, Sigma.exists, exists_and_right, exists_eq_right, forall_exists_index]
    exact fun i j hij ↦ MeasurableSet.pi (countable_toSet _) fun k hk ↦ by simp_all

Goal state after:
Module: Mathlib.Probability.Kernel.Posterior

Goal state before:
pp: 𝓧 : Type u_2
m𝓧 : MeasurableSpace 𝓧
Ω : Type u_5
inst✝⁵ : Countable Ω
inst✝⁴ : MeasurableSpace Ω
inst✝³ : Nonempty Ω
inst✝² : StandardBorelSpace Ω
κ : Kernel Ω 𝓧
inst✝¹ : IsFiniteKernel κ
μ : Measure Ω
inst✝ : IsFiniteMeasure μ
h_rnDeriv : ∀ᵐ (a : 𝓧) ∂⇑κ ∘ₘ μ, ∀ (i : Ω), κ.rnDeriv (Kernel.const Ω (⇑κ ∘ₘ μ)) i a = (∂κ i/∂⇑κ ∘ₘ μ) a
x : 𝓧
hx : (κ†μ) x = μ.withDensity fun ω ↦ κ.rnDeriv (Kernel.const Ω (⇑κ ∘ₘ μ)) ω x
hx_all : ∀ (i : Ω), κ.rnDeriv (Kernel.const Ω (⇑κ ∘ₘ μ)) i x = (∂κ i/∂⇑κ ∘ₘ μ) x
⊢ (κ†μ) x = μ.withDensity fun ω ↦ (∂κ ω/∂⇑κ ∘ₘ μ) x

Tactic:
simp_rw [hx, hx_all]

Goal state after:
Module: Mathlib.Probability.ProbabilityMassFunction.Monad

Goal state before:
pp: α : Type u_1
p : PMF α
x y : α
hy : y ≠ x
⊢ p y * (pure y) x = 0

Tactic:
by rw [pure_apply_of_ne _ _ hy.symm, mul_zero]

Goal state after:
Module: Mathlib.Probability.Distributions.Uniform

Goal state before:
pp: E : Type u_1
inst✝ : MeasurableSpace E
μ : Measure E
Ω : Type u_2
x✝ : MeasurableSpace Ω
ℙ : Measure Ω
X : Ω → E
s : Set E
hns : μ s ≠ 0
hnt : μ s ≠ ∞
hu : IsUniform X s ℙ μ
t : Set E := toMeasurable μ s
⊢ μ[|s] = (μ.restrict (toMeasurable μ s)).withDensity ((μ t)⁻¹ • 1)

Tactic:
withDensity_smul _ measurable_one,

Goal state after:
E : Type u_1
inst✝ : MeasurableSpace E
μ : Measure E
Ω : Type u_2
x✝ : MeasurableSpace Ω
ℙ : Measure Ω
X : Ω → E
s : Set E
hns : μ s ≠ 0
hnt : μ s ≠ ∞
hu : IsUniform X s ℙ μ
t : Set E := toMeasurable μ s
⊢ μ[|s] = (μ t)⁻¹ • (μ.restrict (toMeasurable μ s)).withDensity 1
Module: Mathlib.Probability.Distributions.Uniform

Goal state before:
pp: case neg
E : Type u_1
inst✝ : MeasurableSpace E
μ : Measure E
Ω : Type u_2
x✝ : MeasurableSpace Ω
ℙ : Measure Ω
X : Ω → E
s : Set E
hms : MeasurableSet s
hu : IsUniform X s ℙ μ
hnt : ¬μ s = ∞
hns : ¬μ s = 0
this✝ : HasPDF X ℙ μ
this : IsProbabilityMeasure ℙ
⊢ μ[|s] = (μ.restrict s).withDensity ((μ s)⁻¹ • 1)

Tactic:
withDensity_smul _ measurable_one,

Goal state after:
case neg
E : Type u_1
inst✝ : MeasurableSpace E
μ : Measure E
Ω : Type u_2
x✝ : MeasurableSpace Ω
ℙ : Measure Ω
X : Ω → E
s : Set E
hms : MeasurableSet s
hu : IsUniform X s ℙ μ
hnt : ¬μ s = ∞
hns : ¬μ s = 0
this✝ : HasPDF X ℙ μ
this : IsProbabilityMeasure ℙ
⊢ μ[|s] = (μ s)⁻¹ • (μ.restrict s).withDensity 1
Module: Mathlib.Probability.Distributions.Uniform

Goal state before:
pp: case pos
Ω : Type u_2
x✝ : MeasurableSpace Ω
ℙ : Measure Ω
X : Ω → ℝ
s : Set ℝ
hcs : IsCompact s
huX : IsUniform X s ℙ volume
hnt : volume s = 0 ∨ volume s = ∞
I : Integrable (fun x ↦ x * ENNReal.toReal 0) volume
⊢ Integrable (fun x ↦ x * (pdf X ℙ volume x).toReal) volume

Tactic:
apply I.congr

Goal state after:
case pos
Ω : Type u_2
x✝ : MeasurableSpace Ω
ℙ : Measure Ω
X : Ω → ℝ
s : Set ℝ
hcs : IsCompact s
huX : IsUniform X s ℙ volume
hnt : volume s = 0 ∨ volume s = ∞
I : Integrable (fun x ↦ x * ENNReal.toReal 0) volume
⊢ (fun x ↦ x * ENNReal.toReal 0) =ᵐ[volume] fun x ↦ x * (pdf X ℙ volume x).toReal
Module: Mathlib.Probability.Distributions.Uniform

Goal state before:
pp: α : Type u_1
s : Multiset α
hs : s ≠ 0
t : Set α
⊢ ∑' (x : α), t.indicator (⇑(ofMultiset s hs)) x =
    ∑' (i : α), ↑(Multiset.count i (Multiset.filter (fun x ↦ x ∈ t) s)) * (↑s.card)⁻¹

Tactic:
refine tsum_congr fun x => ?_

Goal state after:
α : Type u_1
s : Multiset α
hs : s ≠ 0
t : Set α
x : α
⊢ t.indicator (⇑(ofMultiset s hs)) x = ↑(Multiset.count x (Multiset.filter (fun x ↦ x ∈ t) s)) * (↑s.card)⁻¹
Module: Mathlib.Probability.Independence.Conditional

Goal state before:
pp: case refine_1
Ω : Type u_1
ι : Type u_2
m' mΩ : MeasurableSpace Ω
inst✝¹ : StandardBorelSpace Ω
hm' : m' ≤ mΩ
π : ι → Set (Set Ω)
hπ : ∀ (i : ι), ∀ s ∈ π i, MeasurableSet s
μ : Measure Ω
inst✝ : IsFiniteMeasure μ
h_eq' :
  ∀ (s : Finset ι) (f : ι → Set Ω),
    (∀ i ∈ s, f i ∈ π i) →
      ∀ i ∈ s, (fun ω ↦ (((condExpKernel μ m') ω) (f i)).toReal) =ᵐ[μ] μ[(f i).indicator fun ω ↦ 1 | m']
h_eq :
  ∀ (s : Finset ι) (f : ι → Set Ω),
    (∀ i ∈ s, f i ∈ π i) →
      ∀ᵐ (ω : Ω) ∂μ, ∀ i ∈ s, (((condExpKernel μ m') ω) (f i)).toReal = μ[(f i).indicator fun ω ↦ 1 | m'] ω
h_inter_eq :
  ∀ (s : Finset ι) (f : ι → Set Ω),
    (∀ i ∈ s, f i ∈ π i) →
      (fun ω ↦ (((condExpKernel μ m') ω) (⋂ i ∈ s, f i)).toReal) =ᵐ[μ] μ[(⋂ i ∈ s, f i).indicator fun ω ↦ 1 | m']
s : Finset ι
f : ι → Set Ω
h : ∀ᵐ (a : Ω) ∂μ.trim hm', ((condExpKernel μ m') a) (⋂ i ∈ s, f i) = ∏ i ∈ s, ((condExpKernel μ m') a) (f i)
hf : ∀ i ∈ s, f i ∈ π i
⊢ μ[(⋂ i ∈ s, f i).indicator fun ω ↦ 1 | m'] =ᵐ[μ] ∏ i ∈ s, μ[(f i).indicator fun ω ↦ 1 | m']

Tactic:
have h' := ae_eq_of_ae_eq_trim h
    filter_upwards [h_eq s f hf, h_inter_eq s f hf, h'] with ω h_eq h_inter_eq h'
    rw [← h_inter_eq, h', ENNReal.toReal_prod, Finset.prod_apply]
    exact Finset.prod_congr rfl h_eq

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

Goal state before:
pp: Ω : Type u_1
m' mΩ : MeasurableSpace Ω
inst✝¹ : StandardBorelSpace Ω
hm' : m' ≤ mΩ
s1 s2 : Set (Set Ω)
hs1 : ∀ s ∈ s1, MeasurableSet s
hs2 : ∀ s ∈ s2, MeasurableSet s
μ : Measure Ω
inst✝ : IsFiniteMeasure μ
⊢ (∀ (t1 t2 : Set Ω),
      t1 ∈ s1 →
        t2 ∈ s2 →
          ∀ᵐ (a : Ω) ∂μ.trim hm',
            ((condExpKernel μ m') a) (t1 ∩ t2) = ((condExpKernel μ m') a) t1 * ((condExpKernel μ m') a) t2) ↔
    ∀ (t1 t2 : Set Ω),
      t1 ∈ s1 →
        t2 ∈ s2 →
          μ[(t1 ∩ t2).indicator fun ω ↦ 1 | m'] =ᵐ[μ] μ[t1.indicator fun ω ↦ 1 | m'] * μ[t2.indicator fun ω ↦ 1 | m']

Tactic:
have hs1_eq : ∀ s ∈ s1, (fun ω ↦ ENNReal.toReal (condExpKernel μ m' ω s)) =ᵐ[μ] μ⟦s | m'⟧ :=
    fun s hs ↦ condExpKernel_ae_eq_condExp hm' (hs1 s hs)

Goal state after:
Ω : Type u_1
m' mΩ : MeasurableSpace Ω
inst✝¹ : StandardBorelSpace Ω
hm' : m' ≤ mΩ
s1 s2 : Set (Set Ω)
hs1 : ∀ s ∈ s1, MeasurableSet s
hs2 : ∀ s ∈ s2, MeasurableSet s
μ : Measure Ω
inst✝ : IsFiniteMeasure μ
hs1_eq : ∀ s ∈ s1, (fun ω ↦ (((condExpKernel μ m') ω) s).toReal) =ᵐ[μ] μ[s.indicator fun ω ↦ 1 | m']
⊢ (∀ (t1 t2 : Set Ω),
      t1 ∈ s1 →
        t2 ∈ s2 →
          ∀ᵐ (a : Ω) ∂μ.trim hm',
            ((condExpKernel μ m') a) (t1 ∩ t2) = ((condExpKernel μ m') a) t1 * ((condExpKernel μ m') a) t2) ↔
    ∀ (t1 t2 : Set Ω),
      t1 ∈ s1 →
        t2 ∈ s2 →
          μ[(t1 ∩ t2).indicator fun ω ↦ 1 | m'] =ᵐ[μ] μ[t1.indicator fun ω ↦ 1 | m'] * μ[t2.indicator fun ω ↦ 1 | m']
Module: Mathlib.Probability.Kernel.Category.SFinKer

Goal state before:
pp: X Y : SFinKer
⊢ X ⊗ Y ≅ Y ⊗ X

Tactic:
refine ⟨⟨Kernel.swap _ _, by rw [Kernel.swap]; infer_instance⟩,
      ⟨Kernel.swap _ _, by rw [Kernel.swap]; infer_instance⟩, ?_, ?_⟩

Goal state after:
case refine_1
X Y : SFinKer
⊢ { hom := Kernel.swap X.carrier Y.carrier, property := ⋯ } ≫
      { hom := Kernel.swap Y.carrier X.carrier, property := ⋯ } =
    𝟙 (X ⊗ Y)

case refine_2
X Y : SFinKer
⊢ { hom := Kernel.swap Y.carrier X.carrier, property := ⋯ } ≫
      { hom := Kernel.swap X.carrier Y.carrier, property := ⋯ } =
    𝟙 (Y ⊗ X)
Module: Mathlib.Probability.Independence.BoundedContinuousFunction

Goal state before:
pp: Ω : Type u_1
S : Type u_2
mΩ : MeasurableSpace Ω
P : Measure Ω
E : S → Type u_4
inst✝⁵ : (s : S) → TopologicalSpace (E s)
inst✝⁴ : (s : S) → MeasurableSpace (E s)
inst✝³ : ∀ (s : S), BorelSpace (E s)
inst✝² : ∀ (s : S), HasOuterApproxClosed (E s)
X : (s : S) → Ω → E s
inst✝¹ : Fintype S
inst✝ : IsProbabilityMeasure P
A : Set Ω
mA : NullMeasurableSet A P
mX : ∀ (s : S), AEMeasurable (X s) P
h : ∀ (f : (s : S) → E s →ᵇ ℝ), ∫ (ω : Ω) in A, ∏ s, (f s) (X s ω) ∂P = P.real A * ∫ (ω : Ω), ∏ s, (f s) (X s ω) ∂P
f : ℝ →ᵇ ℝ
g : (t : S) → E t →ᵇ ℝ
h1 :
  ∀ (ω : Ω),
    f (A.indicator 1 ω) * ∏ s, (g s) (X s ω) =
      A.indicator (fun ω ↦ f 1 * ∏ s, (g s) (X s ω)) ω + f 0 * ∏ s, (g s) (X s ω) -
        A.indicator (fun ω ↦ f 0 * ∏ s, (g s) (X s ω)) ω
h2 : ∀ (ω : Ω), f (A.indicator 1 ω) = A.indicator (fun x ↦ f 1) ω + Aᶜ.indicator (fun x ↦ f 0) ω
⊢ ∫ (x : Ω), (⇑f ∘ A.indicator 1 * ∏ t, ⇑(g t) ∘ X t) x ∂P =
    (∫ (x : Ω), (⇑f ∘ A.indicator 1) x ∂P) * ∫ (x : Ω), (∏ t, ⇑(g t) ∘ X t) x ∂P

Tactic:
have hg {c : ℝ} : Integrable (fun ω ↦ c * ∏ s, g s (X s ω)) P := by
    refine Integrable.of_bound ?_ (‖c‖ * ∏ s, ‖g s‖) (ae_of_all _ fun ω ↦ ?_)
    · exact (Finset.aestronglyMeasurable_fun_prod _ fun s _ ↦
        (g s).continuous.aestronglyMeasurable.comp_aemeasurable (mX s)).const_mul _
    · rw [norm_mul, norm_prod]
      gcongr with s
      exact (g s).norm_coe_le_norm _

Goal state after:
Ω : Type u_1
S : Type u_2
mΩ : MeasurableSpace Ω
P : Measure Ω
E : S → Type u_4
inst✝⁵ : (s : S) → TopologicalSpace (E s)
inst✝⁴ : (s : S) → MeasurableSpace (E s)
inst✝³ : ∀ (s : S), BorelSpace (E s)
inst✝² : ∀ (s : S), HasOuterApproxClosed (E s)
X : (s : S) → Ω → E s
inst✝¹ : Fintype S
inst✝ : IsProbabilityMeasure P
A : Set Ω
mA : NullMeasurableSet A P
mX : ∀ (s : S), AEMeasurable (X s) P
h : ∀ (f : (s : S) → E s →ᵇ ℝ), ∫ (ω : Ω) in A, ∏ s, (f s) (X s ω) ∂P = P.real A * ∫ (ω : Ω), ∏ s, (f s) (X s ω) ∂P
f : ℝ →ᵇ ℝ
g : (t : S) → E t →ᵇ ℝ
h1 :
  ∀ (ω : Ω),
    f (A.indicator 1 ω) * ∏ s, (g s) (X s ω) =
      A.indicator (fun ω ↦ f 1 * ∏ s, (g s) (X s ω)) ω + f 0 * ∏ s, (g s) (X s ω) -
        A.indicator (fun ω ↦ f 0 * ∏ s, (g s) (X s ω)) ω
h2 : ∀ (ω : Ω), f (A.indicator 1 ω) = A.indicator (fun x ↦ f 1) ω + Aᶜ.indicator (fun x ↦ f 0) ω
hg : ∀ {c : ℝ}, Integrable (fun ω ↦ c * ∏ s, (g s) (X s ω)) P
⊢ ∫ (x : Ω), (⇑f ∘ A.indicator 1 * ∏ t, ⇑(g t) ∘ X t) x ∂P =
    (∫ (x : Ω), (⇑f ∘ A.indicator 1) x ∂P) * ∫ (x : Ω), (∏ t, ⇑(g t) ∘ X t) x ∂P
Module: Mathlib.Probability.StrongLaw

Goal state before:
pp: Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : Ω → ℝ
hint : Integrable X ℙ
hnonneg : 0 ≤ X
K : ℕ
⊢ ∑ j ∈ range K, (↑j ^ 2)⁻¹ * ∫ (a : Ω), (truncation X ↑j ^ 2) a ≤ 2 * ∫ (a : Ω), X a

Tactic:
set Y := fun n : ℕ => truncation X n

Goal state after:
Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : Ω → ℝ
hint : Integrable X ℙ
hnonneg : 0 ≤ X
K : ℕ
Y : ℕ → Ω → ℝ := fun n ↦ truncation X ↑n
⊢ ∑ j ∈ range K, (↑j ^ 2)⁻¹ * ∫ (a : Ω), (truncation X ↑j ^ 2) a ≤ 2 * ∫ (a : Ω), X a
Module: Mathlib.Probability.StrongLaw

Goal state before:
pp: case e'_7
Ω : Type u_1
inst✝¹ : MeasureSpace Ω
inst✝ : IsProbabilityMeasure ℙ
X : ℕ → Ω → ℝ
hint : Integrable (X 0) ℙ
hindep : Pairwise ((fun f g ↦ f ⟂ᵢ g) on X)
hident : ∀ (i : ℕ), IdentDistrib (X i) (X 0) ℙ ℙ
hnonneg : ∀ (i : ℕ) (ω : Ω), 0 ≤ X i ω
c : ℝ
c_one : 1 < c
H : ∀ (n : ℕ), 0 < ↑⌊c ^ n⌋₊
ω : Ω
hω : (fun n ↦ ∑ i ∈ range ⌊c ^ n⌋₊, truncation (X i) (↑i) ω - ↑⌊c ^ n⌋₊ * ∫ (a : Ω), X 0 a) =o[atTop] fun n ↦ ↑⌊c ^ n⌋₊
h'ω : (fun n ↦ ∑ i ∈ range n, truncation (X i) (↑i) ω - ∑ i ∈ range n, X i ω) =o[atTop] fun n ↦ ↑n
A : Tendsto (fun n ↦ ⌊c ^ n⌋₊) atTop atTop
n : ℕ
⊢ ∑ i ∈ range ⌊c ^ n⌋₊, X i ω - ↑⌊c ^ n⌋₊ * ∫ (a : Ω), X 0 a =
    (∑ i ∈ range ⌊c ^ n⌋₊, truncation (X i) (↑i) ω - ↑⌊c ^ n⌋₊ * ∫ (a : Ω), X 0 a) -
      ((fun n ↦ ∑ i ∈ range n, truncation (X i) (↑i) ω - ∑ i ∈ range n, X i ω) ∘ fun n ↦ ⌊c ^ n⌋₊) n

Tactic:
simp only [Function.comp_apply, sub_sub_sub_cancel_left]

Goal state after:
Module: Mathlib.Probability.StrongLaw

Goal state before:
pp: Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
E : Type u_2
inst✝⁴ : NormedAddCommGroup E
inst✝³ : NormedSpace ℝ E
inst✝² : CompleteSpace E
inst✝¹ : MeasurableSpace E
inst✝ : BorelSpace E
X : ℕ → Ω → E
hint : Integrable (X 0) μ
hindep : Pairwise ((fun x1 x2 ↦ x1 ⟂ᵢ[μ] x2) on X)
hident : ∀ (i : ℕ), IdentDistrib (X i) (X 0) μ μ
h : ¬∀ᵐ (ω : Ω) ∂μ, X 0 ω = 0
this : IsProbabilityMeasure μ
A : ∀ (i : ℕ), Integrable (X i) μ
Y : ℕ → Ω → E := fun i ↦ AEStronglyMeasurable.mk (X i) ⋯
B : ∀ᵐ (ω : Ω) ∂μ, ∀ (n : ℕ), X n ω = Y n ω
Yint : Integrable (Y 0) μ
C : ∀ᵐ (ω : Ω) ∂μ, Tendsto (fun n ↦ (↑n)⁻¹ • ∑ i ∈ Finset.range n, Y i ω) atTop (𝓝 (∫ (x : Ω), Y 0 x ∂μ))
ω : Ω
h₁ : ∀ (n : ℕ), X n ω = Y n ω
⊢ Tendsto (fun n ↦ (↑n)⁻¹ • ∑ i ∈ Finset.range n, Y i ω) atTop (𝓝 (∫ (x : Ω), Y 0 x ∂μ)) →
    Tendsto (fun n ↦ (↑n)⁻¹ • ∑ i ∈ Finset.range n, X i ω) atTop (𝓝 (∫ (x : Ω), X 0 x ∂μ))

Tactic:
h₂

Goal state after:
Ω : Type u_1
mΩ : MeasurableSpace Ω
μ : Measure Ω
E : Type u_2
inst✝⁴ : NormedAddCommGroup E
inst✝³ : NormedSpace ℝ E
inst✝² : CompleteSpace E
inst✝¹ : MeasurableSpace E
inst✝ : BorelSpace E
X : ℕ → Ω → E
hint : Integrable (X 0) μ
hindep : Pairwise ((fun x1 x2 ↦ x1 ⟂ᵢ[μ] x2) on X)
hident : ∀ (i : ℕ), IdentDistrib (X i) (X 0) μ μ
h : ¬∀ᵐ (ω : Ω) ∂μ, X 0 ω = 0
this : IsProbabilityMeasure μ
A : ∀ (i : ℕ), Integrable (X i) μ
Y : ℕ → Ω → E := fun i ↦ AEStronglyMeasurable.mk (X i) ⋯
B : ∀ᵐ (ω : Ω) ∂μ, ∀ (n : ℕ), X n ω = Y n ω
Yint : Integrable (Y 0) μ
C : ∀ᵐ (ω : Ω) ∂μ, Tendsto (fun n ↦ (↑n)⁻¹ • ∑ i ∈ Finset.range n, Y i ω) atTop (𝓝 (∫ (x : Ω), Y 0 x ∂μ))
ω : Ω
h₁ : ∀ (n : ℕ), X n ω = Y n ω
h₂ : Tendsto (fun n ↦ (↑n)⁻¹ • ∑ i ∈ Finset.range n, Y i ω) atTop (𝓝 (∫ (x : Ω), Y 0 x ∂μ))
⊢ Tendsto (fun n ↦ (↑n)⁻¹ • ∑ i ∈ Finset.range n, X i ω) atTop (𝓝 (∫ (x : Ω), X 0 x ∂μ))
Module: Mathlib.RepresentationTheory.Semisimple

Goal state before:
pp: k : Type u_1
G : Type u_2
inst✝³ : Monoid G
inst✝² : Field k
M : Type u_4
inst✝¹ : AddCommGroup M
inst✝ : Module k[G] M
⊢ IsSemisimpleModule k[G] M ↔ (ofModule M).IsSemisimpleRepresentation

Tactic:
rw [isSemisimpleModule_iff]
  exact OrderIso.complementedLattice_iff Subrepresentation.submoduleSubrepresentationOrderIso

Goal state after:
Module: Mathlib.RepresentationTheory.Homological.GroupCohomology.Hilbert90

Goal state before:
pp: K L : Type
inst✝¹⁶ : Field K
inst✝¹⁵ : Field L
inst✝¹⁴ : Algebra K L
inst✝¹³ : FiniteDimensional K L
inst✝¹² : IsGalois K L
inst✝¹¹ : IsCyclic Gal(L/K)
g : Gal(L/K)
A : Type u_1
B : Type u_2
inst✝¹⁰ : CommRing A
inst✝⁹ : CommRing B
inst✝⁸ : Algebra A B
inst✝⁷ : Algebra A L
inst✝⁶ : Algebra A K
inst✝⁵ : Algebra B L
inst✝⁴ : IsScalarTower A B L
inst✝³ : IsScalarTower A K L
inst✝² : IsFractionRing A K
inst✝¹ : IsDomain A
inst✝ : IsIntegralClosure B A L
hg : ∀ (x : Gal(L/K)), x ∈ Subgroup.zpowers g
η : B
hη : (Algebra.norm K) ((algebraMap B L) η) = 1
this✝ : Module.IsTorsionFree A L
this : IsLocalization (Algebra.algebraMapSubmonoid B A⁰) L
η' : Lˣ := Units.mk0 ((algebraMap B L) η) ⋯
ε : Lˣ
hε : ↑ε / g ↑ε = (algebraMap B L) η
a : B
b : ↥(Algebra.algebraMapSubmonoid B A⁰)
h : IsLocalization.mk' L a b = ↑ε
t : A
ht : t ∈ ↑A⁰
ht' : (algebraMap A B) t = ↑b
⊢ t • IsLocalization.mk' L a b = (algebraMap B L) a

Tactic:
rw [Algebra.smul_def, IsScalarTower.algebraMap_apply A B L, ht', IsLocalization.mk'_spec']

Goal state after:
Module: Mathlib.RepresentationTheory.Homological.GroupCohomology.LowDegree

Goal state before:
pp: k G : Type u
inst✝¹ : CommRing k
inst✝ : Group G
A : Rep k G
f : ↥(cocycles₁ A)
g : G
⊢ (A.ρ g) (f g⁻¹) + f g = 0

Tactic:
← cocycles₁_map_one f,

Goal state after:
k G : Type u
inst✝¹ : CommRing k
inst✝ : Group G
A : Rep k G
f : ↥(cocycles₁ A)
g : G
⊢ (A.ρ g) (f g⁻¹) + f g = f 1
Module: Mathlib.RepresentationTheory.Homological.GroupCohomology.LowDegree

Goal state before:
pp: k G : Type u
inst✝¹ : CommRing k
inst✝ : Group G
A : Rep k G
x y : ↥(cocycles₂ A)
⊢ (ConcreteCategory.hom (H2π A)) x = (ConcreteCategory.hom (H2π A)) y ↔ ⇑x - ⇑y ∈ coboundaries₂ A

Tactic:
rw [← sub_eq_zero, ← map_sub, H2π_eq_zero_iff]

Goal state after:
k G : Type u
inst✝¹ : CommRing k
inst✝ : Group G
A : Rep k G
x y : ↥(cocycles₂ A)
⊢ ⇑(x - y) ∈ coboundaries₂ A ↔ ⇑x - ⇑y ∈ coboundaries₂ A
Module: Mathlib.RingTheory.MvPolynomial.Ideal

Goal state before:
pp: σ : Type u_1
R : Type u_2
inst✝ : CommSemiring R
x : MvPolynomial σ R
s : Set (σ →₀ ℕ)
⊢ x ∈ Ideal.span ((fun s ↦ (monomial s) 1) '' s) ↔
    ∀ xi ∈ x.support, ∃ si ∈ s, (monomial si) 1 ∣ (monomial xi) (coeff xi x)

Tactic:
by
  refine mem_ideal_span_monomial_image.trans (forall₂_congr fun xi hxi => ?_)
  simp_rw [monomial_dvd_monomial, one_dvd, and_true, mem_support_iff.mp hxi, false_or]

Goal state after:
Module: Mathlib.RingTheory.UniqueFactorizationDomain.Kaplansky

Goal state before:
pp: R : Type u_1
inst✝¹ : CommSemiring R
inst✝ : IsDomain R
a : R
ha : a ≠ 0
H : ∀ (I : Ideal R), I ≠ ⊥ → I.IsPrime → ∃ x ∈ I, Prime x
hzero : 0 ∉ closure {r | Prime r}
h : span {a} ∈ kaplanskySet (closure {r | Prime r}).toSubsemigroup
⊢ False

Tactic:
rcases exists_mem_kaplanskySet_eq_of_le hzero with ⟨T, hT, hT₂⟩

Goal state after:
R : Type u_1
inst✝¹ : CommSemiring R
inst✝ : IsDomain R
a : R
ha : a ≠ 0
H : ∀ (I : Ideal R), I ≠ ⊥ → I.IsPrime → ∃ x ∈ I, Prime x
hzero : 0 ∉ closure {r | Prime r}
h : span {a} ∈ kaplanskySet (closure {r | Prime r}).toSubsemigroup
T : Ideal R
hT : T ∈ kaplanskySet (closure {r | Prime r}).toSubsemigroup
hT₂ : ∀ I ∈ kaplanskySet (closure {r | Prime r}).toSubsemigroup, T ≤ I → I = T
⊢ False