-- Mathlib/Analysis/SpecialFunctions/Gamma/BohrMollerup.lean
theorem tendsto_logGammaSeq (hf_conv : ConvexOn ℝ (Ioi 0) f)
    (hf_feq : ∀ {y : ℝ}, 0 < y → f (y + 1) = f y + log y) (hx : 0 < x) :
    Tendsto (logGammaSeq x) atTop (𝓝 <| f x - f 1)

Proof state:
f : ℝ → ℝ
hf_conv : ConvexOn ℝ (Ioi 0) f
hf_feq : ∀ {y : ℝ}, 0 < y → f (y + 1) = f y + log y
m : ℕ
x : ℝ
hx : 0 < x
hy : ↑m < x - 1
hy' : x - 1 ≤ ↑m + 1
hm : Tendsto (logGammaSeq (x - 1)) atTop (𝓝 (f (x - 1) - f 1))
n : ℕ
hn : 1 ≤ n
⊢ logGammaSeq (x - 1) n = logGammaSeq x (n - 1) + x * (log (↑(n - 1) + 1) - log ↑(n - 1)) - log (x - 1)

Tactic:
have := logGammaSeq_add_one (x - 1) (n - 1)

Result:
f : ℝ → ℝ
hf_conv : ConvexOn ℝ (Ioi 0) f
hf_feq : ∀ {y : ℝ}, 0 < y → f (y + 1) = f y + log y
m : ℕ
x : ℝ
hx : 0 < x
hy : ↑m < x - 1
hy' : x - 1 ≤ ↑m + 1
hm : Tendsto (logGammaSeq (x - 1)) atTop (𝓝 (f (x - 1) - f 1))
n : ℕ
hn : 1 ≤ n
this :
  logGammaSeq (x - 1 + 1) (n - 1) =
    logGammaSeq (x - 1) (n - 1 + 1) + log (x - 1) - (x - 1 + 1) * (log (↑(n - 1) + 1) - log ↑(n - 1))
⊢ logGammaSeq (x - 1) n = logGammaSeq x (n - 1) + x * (log (↑(n - 1) + 1) - log ↑(n - 1)) - log (x - 1)

Proof state:
case refine_1.inl
f : ℝ → ℝ
x : ℝ
hf_conv : ConvexOn ℝ (Ioi 0) f
hf_feq : ∀ {y : ℝ}, 0 < y → f (y + 1) = f y + log y
hx : 0 < x
this : ∀ (m : ℕ), ↑m < x → x ≤ ↑m + 1 → Tendsto (logGammaSeq x) atTop (𝓝 (f x - f 1))
h✝ : x < 1
⊢ ↑⌈x - 1⌉₊ < x

Tactic:
rwa [Nat.ceil_eq_zero.mpr (by linarith : x - 1 ≤ 0), Nat.cast_zero]

Result:
no goals

Proof state:
case refine_2
f : ℝ → ℝ
x : ℝ
hf_conv : ConvexOn ℝ (Ioi 0) f
hf_feq : ∀ {y : ℝ}, 0 < y → f (y + 1) = f y + log y
hx : 0 < x
this : ∀ (m : ℕ), ↑m < x → x ≤ ↑m + 1 → Tendsto (logGammaSeq x) atTop (𝓝 (f x - f 1))
⊢ x - 1 ≤ ↑⌈x - 1⌉₊

Tactic:
exact Nat.le_ceil _

Result:
no goals

Proof state:
case h
f : ℝ → ℝ
hf_conv : ConvexOn ℝ (Ioi 0) f
hf_feq : ∀ {y : ℝ}, 0 < y → f (y + 1) = f y + log y
m : ℕ
x : ℝ
hx : 0 < x
hy : ↑m < x - 1
hy' : x - 1 ≤ ↑m + 1
this :
  ∀ᶠ (n : ℕ) in atTop,
    logGammaSeq (x - 1) n = logGammaSeq x (n - 1) + x * (log (↑(n - 1) + 1) - log ↑(n - 1)) - log (x - 1)
hm :
  Tendsto
    ((fun x_1 => logGammaSeq x (x_1 - 1) + x * (log (↑(x_1 - 1) + 1) - log ↑(x_1 - 1)) - log (x - 1) + log (x - 1)) ∘
      fun a => a + 1)
    atTop (𝓝 (f (x - 1) - f 1 + log (x - 1)))
n : ℕ
⊢ ((fun x_1 =>
          (fun n => logGammaSeq x (n - 1) + x * (log (↑(n - 1) + 1) - log ↑(n - 1)) - log (x - 1)) x_1 +
            (fun b => log (x - 1)) x_1) ∘
        fun a => a + 1)
      n =
    logGammaSeq x n + x * (log (↑n + 1) - log ↑n)

Tactic:
dsimp only [Function.comp_apply]

Result:
case h
f : ℝ → ℝ
hf_conv : ConvexOn ℝ (Ioi 0) f
hf_feq : ∀ {y : ℝ}, 0 < y → f (y + 1) = f y + log y
m : ℕ
x : ℝ
hx : 0 < x
hy : ↑m < x - 1
hy' : x - 1 ≤ ↑m + 1
this :
  ∀ᶠ (n : ℕ) in atTop,
    logGammaSeq (x - 1) n = logGammaSeq x (n - 1) + x * (log (↑(n - 1) + 1) - log ↑(n - 1)) - log (x - 1)
hm :
  Tendsto
    ((fun x_1 => logGammaSeq x (x_1 - 1) + x * (log (↑(x_1 - 1) + 1) - log ↑(x_1 - 1)) - log (x - 1) + log (x - 1)) ∘
      fun a => a + 1)
    atTop (𝓝 (f (x - 1) - f 1 + log (x - 1)))
n : ℕ
⊢ logGammaSeq x (n + 1 - 1) + x * (log (↑(n + 1 - 1) + 1) - log ↑(n + 1 - 1)) - log (x - 1) + log (x - 1) =
    logGammaSeq x n + x * (log (↑n + 1) - log ↑n)

Proof state:
f : ℝ → ℝ
hf_conv : ConvexOn ℝ (Ioi 0) f
hf_feq : ∀ {y : ℝ}, 0 < y → f (y + 1) = f y + log y
m : ℕ
x : ℝ
hx : 0 < x
hy : ↑m < x - 1
hy' : x - 1 ≤ ↑m + 1
hm : Tendsto (logGammaSeq (x - 1)) atTop (𝓝 (f (x - 1) - f 1))
⊢ ∀ᶠ (n : ℕ) in atTop,
    logGammaSeq (x - 1) n = logGammaSeq x (n - 1) + x * (log (↑(n - 1) + 1) - log ↑(n - 1)) - log (x - 1)

Tactic:
refine Eventually.mp (eventually_ge_atTop 1) (Eventually.of_forall fun n hn => ?_)

Result:
f : ℝ → ℝ
hf_conv : ConvexOn ℝ (Ioi 0) f
hf_feq : ∀ {y : ℝ}, 0 < y → f (y + 1) = f y + log y
m : ℕ
x : ℝ
hx : 0 < x
hy : ↑m < x - 1
hy' : x - 1 ≤ ↑m + 1
hm : Tendsto (logGammaSeq (x - 1)) atTop (𝓝 (f (x - 1) - f 1))
n : ℕ
hn : 1 ≤ n
⊢ logGammaSeq (x - 1) n = logGammaSeq x (n - 1) + x * (log (↑(n - 1) + 1) - log ↑(n - 1)) - log (x - 1)

Proof state:
case succ
f : ℝ → ℝ
hf_conv : ConvexOn ℝ (Ioi 0) f
hf_feq : ∀ {y : ℝ}, 0 < y → f (y + 1) = f y + log y
m : ℕ
hm : ∀ {x : ℝ}, 0 < x → ↑m < x → x ≤ ↑m + 1 → Tendsto (logGammaSeq x) atTop (𝓝 (f x - f 1))
x : ℝ
hx : 0 < x
hy : ↑(m + 1) < x
hy' : x ≤ ↑(m + 1) + 1
⊢ Tendsto (logGammaSeq x) atTop (𝓝 (f x - f 1))

Tactic:
rw [Nat.cast_succ, ← sub_le_iff_le_add] at hy'

Result:
case succ
f : ℝ → ℝ
hf_conv : ConvexOn ℝ (Ioi 0) f
hf_feq : ∀ {y : ℝ}, 0 < y → f (y + 1) = f y + log y
m : ℕ
hm : ∀ {x : ℝ}, 0 < x → ↑m < x → x ≤ ↑m + 1 → Tendsto (logGammaSeq x) atTop (𝓝 (f x - f 1))
x : ℝ
hx : 0 < x
hy : ↑(m + 1) < x
hy' : x - 1 ≤ ↑m + 1
⊢ Tendsto (logGammaSeq x) atTop (𝓝 (f x - f 1))

Proof state:
case succ
f : ℝ → ℝ
hf_conv : ConvexOn ℝ (Ioi 0) f
hf_feq : ∀ {y : ℝ}, 0 < y → f (y + 1) = f y + log y
m : ℕ
hm : ∀ {x : ℝ}, 0 < x → ↑m < x → x ≤ ↑m + 1 → Tendsto (logGammaSeq x) atTop (𝓝 (f x - f 1))
x : ℝ
hx : 0 < x
hy : ↑(m + 1) < x
hy' : x - 1 ≤ ↑m + 1
⊢ Tendsto (logGammaSeq x) atTop (𝓝 (f x - f 1))

Tactic:
rw [Nat.cast_succ, ← lt_sub_iff_add_lt] at hy

Result:
case succ
f : ℝ → ℝ
hf_conv : ConvexOn ℝ (Ioi 0) f
hf_feq : ∀ {y : ℝ}, 0 < y → f (y + 1) = f y + log y
m : ℕ
hm : ∀ {x : ℝ}, 0 < x → ↑m < x → x ≤ ↑m + 1 → Tendsto (logGammaSeq x) atTop (𝓝 (f x - f 1))
x : ℝ
hx : 0 < x
hy : ↑m < x - 1
hy' : x - 1 ≤ ↑m + 1
⊢ Tendsto (logGammaSeq x) atTop (𝓝 (f x - f 1))

Proof state:
f : ℝ → ℝ
x : ℝ
hf_conv : ConvexOn ℝ (Ioi 0) f
hf_feq : ∀ {y : ℝ}, 0 < y → f (y + 1) = f y + log y
hx : 0 < x
m : ℕ
⊢ ↑m < x → x ≤ ↑m + 1 → Tendsto (logGammaSeq x) atTop (𝓝 (f x - f 1))

Tactic:
induction' m with m hm generalizing x

Result:
case zero
f : ℝ → ℝ
hf_conv : ConvexOn ℝ (Ioi 0) f
hf_feq : ∀ {y : ℝ}, 0 < y → f (y + 1) = f y + log y
x : ℝ
hx : 0 < x
⊢ ↑0 < x → x ≤ ↑0 + 1 → Tendsto (logGammaSeq x) atTop (𝓝 (f x - f 1))

case succ
f : ℝ → ℝ
hf_conv : ConvexOn ℝ (Ioi 0) f
hf_feq : ∀ {y : ℝ}, 0 < y → f (y + 1) = f y + log y
m : ℕ
hm : ∀ {x : ℝ}, 0 < x → ↑m < x → x ≤ ↑m + 1 → Tendsto (logGammaSeq x) atTop (𝓝 (f x - f 1))
x : ℝ
hx : 0 < x
⊢ ↑(m + 1) < x → x ≤ ↑(m + 1) + 1 → Tendsto (logGammaSeq x) atTop (𝓝 (f x - f 1))

Proof state:
case refine_2
f : ℝ → ℝ
x : ℝ
hf_conv : ConvexOn ℝ (Ioi 0) f
hf_feq : ∀ {y : ℝ}, 0 < y → f (y + 1) = f y + log y
hx : 0 < x
this : ∀ (m : ℕ), ↑m < x → x ≤ ↑m + 1 → Tendsto (logGammaSeq x) atTop (𝓝 (f x - f 1))
⊢ x ≤ ↑⌈x - 1⌉₊ + 1

Tactic:
rw [← sub_le_iff_le_add]

Result:
case refine_2
f : ℝ → ℝ
x : ℝ
hf_conv : ConvexOn ℝ (Ioi 0) f
hf_feq : ∀ {y : ℝ}, 0 < y → f (y + 1) = f y + log y
hx : 0 < x
this : ∀ (m : ℕ), ↑m < x → x ≤ ↑m + 1 → Tendsto (logGammaSeq x) atTop (𝓝 (f x - f 1))
⊢ x - 1 ≤ ↑⌈x - 1⌉₊

Proof state:
f : ℝ → ℝ
x : ℝ
hf_conv : ConvexOn ℝ (Ioi 0) f
hf_feq : ∀ {y : ℝ}, 0 < y → f (y + 1) = f y + log y
hx : 0 < x
this : ∀ (m : ℕ), ↑m < x → x ≤ ↑m + 1 → Tendsto (logGammaSeq x) atTop (𝓝 (f x - f 1))
h✝ : 1 ≤ x
⊢ 0 ≤ x - 1

Tactic:
linarith

Result:
no goals

Proof state:
f : ℝ → ℝ
hf_conv : ConvexOn ℝ (Ioi 0) f
hf_feq : ∀ {y : ℝ}, 0 < y → f (y + 1) = f y + log y
m : ℕ
x : ℝ
hx : 0 < x
hy : ↑m < x - 1
hy' : x - 1 ≤ ↑m + 1
hm : Tendsto (logGammaSeq (x - 1)) atTop (𝓝 (f (x - 1) - f 1))
n : ℕ
hn : 1 ≤ n
this : logGammaSeq x (n - 1) = logGammaSeq (x - 1) n + log (x - 1) - x * (log (↑(n - 1) + 1) - log ↑(n - 1))
⊢ logGammaSeq (x - 1) n =
    logGammaSeq (x - 1) n + log (x - 1) - x * (log (↑(n - 1) + 1) - log ↑(n - 1)) +
        x * (log (↑(n - 1) + 1) - log ↑(n - 1)) -
      log (x - 1)

Tactic:
ring

Result:
no goals

Proof state:
case h.e'_4
f : ℝ → ℝ
x : ℝ
hf_conv : ConvexOn ℝ (Ioi 0) f
hf_feq : ∀ {y : ℝ}, 0 < y → f (y + 1) = f y + log y
hx : 0 < x
this : ∀ (m : ℕ), ↑m < x → x ≤ ↑m + 1 → Tendsto (logGammaSeq x) atTop (𝓝 (f x - f 1))
h✝ : 1 ≤ x
⊢ x = x - 1 + 1

Tactic:
abel

Result:
no goals