-- Lean 4 proof step from Mathlib.Probability.Kernel.Disintegration.CDFToKernel (goal)
Goal:
α : Type u_1
β : Type u_2
mα : MeasurableSpace α
mβ : MeasurableSpace β
κ : Kernel.{u_1, u_2} α (β × ℝ)
ν : Kernel α β
f : α × β → StieltjesFunction ℝ
inst : IsFiniteKernel κ
hf : IsCondKernelCDF f κ ν
a : α
s t : Set (β × ℝ)
ht : MeasurableSet t
ht_eq :
  ∫⁻ (b : β),
      (((IsCondKernelCDF.toKernel f hf : (a : α × β) → Measure ℝ) (a, b) : Measure ℝ) : (a : Set ℝ) → ℝ≥0∞)
        (Prod.mk b ⁻¹' t) ∂(ν : (a : α) → Measure β) a =
    (((κ : (a : α) → Measure (β × ℝ)) a : Measure (β × ℝ)) : (a : Set (β × ℝ)) → ℝ≥0∞) t
calc :
  ∫⁻ (b : β),
      (((IsCondKernelCDF.toKernel f hf : (a : α × β) → Measure ℝ) (a, b) : Measure ℝ) : (a : Set ℝ) → ℝ≥0∞)
        (Prod.mk b ⁻¹' t)ᶜ ∂(ν : (a : α) → Measure β) a =
    ∫⁻ (b : β),
      HSub.hSub (α := ℝ≥0∞) (β := ℝ≥0∞)
        ((((IsCondKernelCDF.toKernel f hf : (a : α × β) → Measure ℝ) (a, b) : Measure ℝ) : (a : Set ℝ) → ℝ≥0∞) univ :
          ℝ≥0∞)
        ((((IsCondKernelCDF.toKernel f hf : (a : α × β) → Measure ℝ) (a, b) : Measure ℝ) : (a : Set ℝ) → ℝ≥0∞)
            (Prod.mk b ⁻¹' t) :
          ℝ≥0∞) ∂(ν : (a : α) → Measure β) a
⊢ ∫⁻ (b : β),
      (((IsCondKernelCDF.toKernel f hf : (a : α × β) → Measure ℝ) (a, b) : Measure ℝ) : (a : Set ℝ) → ℝ≥0∞)
        (Prod.mk b ⁻¹' tᶜ) ∂(ν : (a : α) → Measure β) a =
    (((κ : (a : α) → Measure (β × ℝ)) a : Measure (β × ℝ)) : (a : Set (β × ℝ)) → ℝ≥0∞) tᶜ
have calc₁ : ∫⁻ (b : β),
    HSub.hSub (α := ℝ≥0∞) (β := ℝ≥0∞)
      ((((IsCondKernelCDF.toKernel f hf : (a : α × β) → Measure ℝ) (a, b) : Measure ℝ) : (a : Set ℝ) → ℝ≥0∞) univ :
        ℝ≥0∞)
      ((((IsCondKernelCDF.toKernel f hf : (a : α × β) → Measure ℝ) (a, b) : Measure ℝ) : (a : Set ℝ) → ℝ≥0∞)
          (Prod.mk b ⁻¹' t) :
        ℝ≥0∞) ∂(ν : (a : α) → Measure β) a =
  ∫⁻ (x : β),
      (((IsCondKernelCDF.toKernel f hf : (a : α × β) → Measure ℝ) (a, x) : Measure ℝ) : (a : Set ℝ) → ℝ≥0∞)
        univ ∂(ν : (a : α) → Measure β) a -
    ∫⁻ (x : β),
      (((IsCondKernelCDF.toKernel f hf : (a : α × β) → Measure ℝ) (a, x) : Measure ℝ) : (a : Set ℝ) → ℝ≥0∞)
        (Prod.mk x ⁻¹' t) ∂(ν : (a : α) → Measure β) a
Tactic: calc ∫⁻ b, hf.toKernel f (a, b) (Prod.mk b ⁻¹' tᶜ) ∂(ν a)
      = ∫⁻ b, hf.toKernel f (a, b) (Prod.mk b ⁻¹' t)ᶜ ∂(ν a) := rfl
    _ = ∫⁻ b, hf.toKernel f (a, b) univ
          - hf.toKernel f (a, b) (Prod.mk b ⁻¹' t) ∂(ν a) := by
        congr with x : 1
        exact measure_compl (measurable_prodMk_left ht)
          (measure_ne_top (hf.toKernel f (a, x)) _)
    _ = ∫⁻ x, hf.toKernel f (a, x) univ ∂(ν a) -
          ∫⁻ x, hf.toKernel f (a, x) (Prod.mk x ⁻¹' t) ∂(ν a) := by
        have h_le : (fun x ↦ hf.toKernel f (a, x) (Prod.mk x ⁻¹' t))
              ≤ᵐ[ν a] fun x ↦ hf.toKernel f (a, x) univ :=
          Eventually.of_forall fun _ ↦ measure_mono (subset_univ _)
        rw [lintegral_sub _ _ h_le]
        · exact Kernel.measurable_kernel_prodMk_left' ht a
        refine ((lintegral_mono_ae h_le).trans_lt ?_).ne
        rw [lintegral_toKernel_univ hf]
        exact measure_lt_top _ univ
    _ = κ a univ - κ a t := by rw [ht_eq, lintegral_toKernel_univ hf]
    _ = κ a tᶜ := (measure_compl ht (measure_ne_top _ _)).symm