basic.lean

/-
Copyright (c) 2015, 2017 Jeremy Avigad. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Metric spaces.

Authors: Jeremy Avigad, Robert Y. Lewis, Johannes Hölzl, Mario Carneiro, Sébastien Gouëzel

Many definitions and theorems expected on metric spaces are already introduced on uniform spaces and
topological spaces. For example:
  open and closed sets, compactness, completeness, continuity and uniform continuity
-/
import data.real.nnreal topology.metric_space.emetric_space topology.algebra.ordered
open lattice set filter classical topological_space
noncomputable theory

open_locale uniformity
open_locale topological_space

universes u v w
variables {α : Type u} {β : Type v} {γ : Type w}

/-- Construct a uniform structure from a distance function and metric space axioms -/
def uniform_space_of_dist
  (dist : α → α → ℝ)
  (dist_self : ∀ x : α, dist x x = 0)
  (dist_comm : ∀ x y : α, dist x y = dist y x)
  (dist_triangle : ∀ x y z : α, dist x z ≤ dist x y + dist y z) : uniform_space α :=
uniform_space.of_core {
  uniformity := (⨅ ε>0, principal {p:α×α | dist p.1 p.2 < ε}),
  refl       := le_infi $ assume ε, le_infi $
    by simp [set.subset_def, id_rel, dist_self, (>)] {contextual := tt},
  comp       := le_infi $ assume ε, le_infi $ assume h, lift'_le
    (mem_infi_sets (ε / 2) $ mem_infi_sets (div_pos_of_pos_of_pos h two_pos) (subset.refl _)) $
    have ∀ (a b c : α), dist a c < ε / 2 → dist c b < ε / 2 → dist a b < ε,
      from assume a b c hac hcb,
      calc dist a b ≤ dist a c + dist c b : dist_triangle _ _ _
        ... < ε / 2 + ε / 2 : add_lt_add hac hcb
        ... = ε : by rw [div_add_div_same, add_self_div_two],
    by simpa [comp_rel],
  symm       := tendsto_infi.2 $ assume ε, tendsto_infi.2 $ assume h,
    tendsto_infi' ε $ tendsto_infi' h $ tendsto_principal_principal.2 $ by simp [dist_comm] }

/-- The distance function (given an ambient metric space on `α`), which returns
  a nonnegative real number `dist x y` given `x y : α`. -/
class has_dist (α : Type*) := (dist : α → α → ℝ)

export has_dist (dist)

section prio
set_option default_priority 100 -- see Note [default priority]
/-- Metric space

Each metric space induces a canonical `uniform_space` and hence a canonical `topological_space`.
This is enforced in the type class definition, by extending the `uniform_space` structure. When
instantiating a `metric_space` structure, the uniformity fields are not necessary, they will be
filled in by default. In the same way, each metric space induces an emetric space structure.
It is included in the structure, but filled in by default.

When one instantiates a metric space structure, for instance a product structure,
this makes it possible to use a uniform structure and an edistance that are exactly
the ones for the uniform spaces product and the emetric spaces products, thereby
ensuring that everything in defeq in diamonds.-/
class metric_space (α : Type u) extends has_dist α : Type u :=
(dist_self : ∀ x : α, dist x x = 0)
(eq_of_dist_eq_zero : ∀ {x y : α}, dist x y = 0 → x = y)
(dist_comm : ∀ x y : α, dist x y = dist y x)
(dist_triangle : ∀ x y z : α, dist x z ≤ dist x y + dist y z)
(edist : α → α → ennreal := λx y, ennreal.of_real (dist x y))
(edist_dist : ∀ x y : α, edist x y = ennreal.of_real (dist x y) . control_laws_tac)
(to_uniform_space : uniform_space α := uniform_space_of_dist dist dist_self dist_comm dist_triangle)
(uniformity_dist : 𝓤 α = ⨅ ε>0, principal {p:α×α | dist p.1 p.2 < ε} . control_laws_tac)
end prio

variables [metric_space α]

@[priority 100] -- see Note [lower instance priority]
instance metric_space.to_uniform_space' : uniform_space α :=
metric_space.to_uniform_space α

@[priority 200] -- see Note [lower instance priority]
instance metric_space.to_has_edist : has_edist α := ⟨metric_space.edist⟩

@[simp] theorem dist_self (x : α) : dist x x = 0 := metric_space.dist_self x

theorem eq_of_dist_eq_zero {x y : α} : dist x y = 0 → x = y :=
metric_space.eq_of_dist_eq_zero

theorem dist_comm (x y : α) : dist x y = dist y x := metric_space.dist_comm x y

theorem edist_dist (x y : α) : edist x y = ennreal.of_real (dist x y) :=
metric_space.edist_dist _ x y

@[simp] theorem dist_eq_zero {x y : α} : dist x y = 0 ↔ x = y :=
iff.intro eq_of_dist_eq_zero (assume : x = y, this ▸ dist_self _)

@[simp] theorem zero_eq_dist {x y : α} : 0 = dist x y ↔ x = y :=
by rw [eq_comm, dist_eq_zero]

theorem dist_triangle (x y z : α) : dist x z ≤ dist x y + dist y z :=
metric_space.dist_triangle x y z

theorem dist_triangle_left (x y z : α) : dist x y ≤ dist z x + dist z y :=
by rw dist_comm z; apply dist_triangle

theorem dist_triangle_right (x y z : α) : dist x y ≤ dist x z + dist y z :=
by rw dist_comm y; apply dist_triangle

lemma dist_triangle4 (x y z w : α) :
  dist x w ≤ dist x y + dist y z + dist z w :=
calc
  dist x w ≤ dist x z + dist z w : dist_triangle x z w
       ... ≤ (dist x y + dist y z) + dist z w : add_le_add_right (metric_space.dist_triangle x y z) _

lemma dist_triangle4_left (x₁ y₁ x₂ y₂ : α) :
  dist x₂ y₂ ≤ dist x₁ y₁ + (dist x₁ x₂ + dist y₁ y₂) :=
by rw [add_left_comm, dist_comm x₁, ← add_assoc]; apply dist_triangle4

lemma dist_triangle4_right (x₁ y₁ x₂ y₂ : α) :
  dist x₁ y₁ ≤ dist x₁ x₂ + dist y₁ y₂ + dist x₂ y₂ :=
by rw [add_right_comm, dist_comm y₁]; apply dist_triangle4

/-- The triangle (polygon) inequality for sequences of points; `finset.Ico` version. -/
lemma dist_le_Ico_sum_dist (f : ℕ → α) {m n} (h : m ≤ n) :
  dist (f m) (f n) ≤ (finset.Ico m n).sum (λ i, dist (f i) (f (i + 1))) :=
begin
  revert n,
  apply nat.le_induction,
  { simp only [finset.sum_empty, finset.Ico.self_eq_empty, dist_self] },
  { assume n hn hrec,
    calc dist (f m) (f (n+1)) ≤ dist (f m) (f n) + dist _ _ : dist_triangle _ _ _
      ... ≤ (finset.Ico m n).sum _ + _ : add_le_add hrec (le_refl _)
      ... = (finset.Ico m (n+1)).sum _ :
        by rw [finset.Ico.succ_top hn, finset.sum_insert, add_comm]; simp }
end

/-- The triangle (polygon) inequality for sequences of points; `finset.range` version. -/
lemma dist_le_range_sum_dist (f : ℕ → α) (n : ℕ) :
  dist (f 0) (f n) ≤ (finset.range n).sum (λ i, dist (f i) (f (i + 1))) :=
finset.Ico.zero_bot n ▸ dist_le_Ico_sum_dist f (nat.zero_le n)

/-- A version of `dist_le_Ico_sum_dist` with each intermediate distance replaced
with an upper estimate. -/
lemma dist_le_Ico_sum_of_dist_le {f : ℕ → α} {m n} (hmn : m ≤ n)
  {d : ℕ → ℝ} (hd : ∀ {k}, m ≤ k → k < n → dist (f k) (f (k + 1)) ≤ d k) :
  dist (f m) (f n) ≤ (finset.Ico m n).sum d :=
le_trans (dist_le_Ico_sum_dist f hmn) $
finset.sum_le_sum $ λ k hk, hd (finset.Ico.mem.1 hk).1 (finset.Ico.mem.1 hk).2

/-- A version of `dist_le_range_sum_dist` with each intermediate distance replaced
with an upper estimate. -/
lemma dist_le_range_sum_of_dist_le {f : ℕ → α} (n : ℕ)
  {d : ℕ → ℝ} (hd : ∀ {k}, k < n → dist (f k) (f (k + 1)) ≤ d k) :
  dist (f 0) (f n) ≤ (finset.range n).sum d :=
finset.Ico.zero_bot n ▸ dist_le_Ico_sum_of_dist_le (zero_le n) (λ _ _, hd)

theorem swap_dist : function.swap (@dist α _) = dist :=
by funext x y; exact dist_comm _ _

theorem abs_dist_sub_le (x y z : α) : abs (dist x z - dist y z) ≤ dist x y :=
abs_sub_le_iff.2
 ⟨sub_le_iff_le_add.2 (dist_triangle _ _ _),
  sub_le_iff_le_add.2 (dist_triangle_left _ _ _)⟩

theorem dist_nonneg {x y : α} : 0 ≤ dist x y :=
have 2 * dist x y ≥ 0,
  from calc 2 * dist x y = dist x y + dist y x : by rw [dist_comm x y, two_mul]
    ... ≥ 0 : by rw ← dist_self x; apply dist_triangle,
nonneg_of_mul_nonneg_left this two_pos

@[simp] theorem dist_le_zero {x y : α} : dist x y ≤ 0 ↔ x = y :=
by simpa [le_antisymm_iff, dist_nonneg] using @dist_eq_zero _ _ x y

@[simp] theorem dist_pos {x y : α} : 0 < dist x y ↔ x ≠ y :=
by simpa [-dist_le_zero] using not_congr (@dist_le_zero _ _ x y)

@[simp] theorem abs_dist {a b : α} : abs (dist a b) = dist a b :=
abs_of_nonneg dist_nonneg

theorem eq_of_forall_dist_le {x y : α} (h : ∀ε, ε > 0 → dist x y ≤ ε) : x = y :=
eq_of_dist_eq_zero (eq_of_le_of_forall_le_of_dense dist_nonneg h)

/-- Distance as a nonnegative real number. -/
def nndist (a b : α) : nnreal := ⟨dist a b, dist_nonneg⟩

/--Express `nndist` in terms of `edist`-/
lemma nndist_edist (x y : α) : nndist x y = (edist x y).to_nnreal :=
by simp [nndist, edist_dist, nnreal.of_real, max_eq_left dist_nonneg, ennreal.of_real]

/--Express `edist` in terms of `nndist`-/
lemma edist_nndist (x y : α) : edist x y = ↑(nndist x y) :=
by { rw [edist_dist, nndist, ennreal.of_real_eq_coe_nnreal] }

/--In a metric space, the extended distance is always finite-/
lemma edist_ne_top (x y : α) : edist x y ≠ ⊤ :=
by rw [edist_dist x y]; apply ennreal.coe_ne_top

/--In a metric space, the extended distance is always finite-/
lemma edist_lt_top {α : Type*} [metric_space α] (x y : α) : edist x y < ⊤ :=
ennreal.lt_top_iff_ne_top.2 (edist_ne_top x y)

/--`nndist x x` vanishes-/
@[simp] lemma nndist_self (a : α) : nndist a a = 0 := (nnreal.coe_eq_zero _).1 (dist_self a)

/--Express `dist` in terms of `nndist`-/
lemma dist_nndist (x y : α) : dist x y = ↑(nndist x y) := rfl

/--Express `nndist` in terms of `dist`-/
lemma nndist_dist (x y : α) : nndist x y = nnreal.of_real (dist x y) :=
by rw [dist_nndist, nnreal.of_real_coe]

/--Deduce the equality of points with the vanishing of the nonnegative distance-/
theorem eq_of_nndist_eq_zero {x y : α} : nndist x y = 0 → x = y :=
by simp only [nnreal.eq_iff.symm, (dist_nndist _ _).symm, imp_self, nnreal.coe_zero, dist_eq_zero]

theorem nndist_comm (x y : α) : nndist x y = nndist y x :=
by simpa [nnreal.eq_iff.symm] using dist_comm x y

/--Characterize the equality of points with the vanishing of the nonnegative distance-/
@[simp] theorem nndist_eq_zero {x y : α} : nndist x y = 0 ↔ x = y :=
by simp only [nnreal.eq_iff.symm, (dist_nndist _ _).symm, imp_self, nnreal.coe_zero, dist_eq_zero]

@[simp] theorem zero_eq_nndist {x y : α} : 0 = nndist x y ↔ x = y :=
by simp only [nnreal.eq_iff.symm, (dist_nndist _ _).symm, imp_self, nnreal.coe_zero, zero_eq_dist]

/--Triangle inequality for the nonnegative distance-/
theorem nndist_triangle (x y z : α) : nndist x z ≤ nndist x y + nndist y z :=
by simpa [nnreal.coe_le] using dist_triangle x y z

theorem nndist_triangle_left (x y z : α) : nndist x y ≤ nndist z x + nndist z y :=
by simpa [nnreal.coe_le] using dist_triangle_left x y z

theorem nndist_triangle_right (x y z : α) : nndist x y ≤ nndist x z + nndist y z :=
by simpa [nnreal.coe_le] using dist_triangle_right x y z

/--Express `dist` in terms of `edist`-/
lemma dist_edist (x y : α) : dist x y = (edist x y).to_real :=
by rw [edist_dist, ennreal.to_real_of_real (dist_nonneg)]

namespace metric

/- instantiate metric space as a topology -/
variables {x y z : α} {ε ε₁ ε₂ : ℝ} {s : set α}

/-- `ball x ε` is the set of all points `y` with `dist y x < ε` -/
def ball (x : α) (ε : ℝ) : set α := {y | dist y x < ε}

@[simp] theorem mem_ball : y ∈ ball x ε ↔ dist y x < ε := iff.rfl

theorem mem_ball' : y ∈ ball x ε ↔ dist x y < ε := by rw dist_comm; refl

/-- `closed_ball x ε` is the set of all points `y` with `dist y x ≤ ε` -/
def closed_ball (x : α) (ε : ℝ) := {y | dist y x ≤ ε}

@[simp] theorem mem_closed_ball : y ∈ closed_ball x ε ↔ dist y x ≤ ε := iff.rfl

theorem ball_subset_closed_ball : ball x ε ⊆ closed_ball x ε :=
assume y (hy : _ < _), le_of_lt hy

theorem pos_of_mem_ball (hy : y ∈ ball x ε) : ε > 0 :=
lt_of_le_of_lt dist_nonneg hy

theorem mem_ball_self (h : ε > 0) : x ∈ ball x ε :=
show dist x x < ε, by rw dist_self; assumption

theorem mem_closed_ball_self (h : ε ≥ 0) : x ∈ closed_ball x ε :=
show dist x x ≤ ε, by rw dist_self; assumption

theorem mem_ball_comm : x ∈ ball y ε ↔ y ∈ ball x ε :=
by simp [dist_comm]

theorem ball_subset_ball (h : ε₁ ≤ ε₂) : ball x ε₁ ⊆ ball x ε₂ :=
λ y (yx : _ < ε₁), lt_of_lt_of_le yx h

theorem closed_ball_subset_closed_ball {α : Type u} [metric_space α] {ε₁ ε₂ : ℝ} {x : α} (h : ε₁ ≤ ε₂) :
  closed_ball x ε₁ ⊆ closed_ball x ε₂ :=
λ y (yx : _ ≤ ε₁), le_trans yx h

theorem ball_disjoint (h : ε₁ + ε₂ ≤ dist x y) : ball x ε₁ ∩ ball y ε₂ = ∅ :=
eq_empty_iff_forall_not_mem.2 $ λ z ⟨h₁, h₂⟩,
not_lt_of_le (dist_triangle_left x y z)
  (lt_of_lt_of_le (add_lt_add h₁ h₂) h)

theorem ball_disjoint_same (h : ε ≤ dist x y / 2) : ball x ε ∩ ball y ε = ∅ :=
ball_disjoint $ by rwa [← two_mul, ← le_div_iff' two_pos]

theorem ball_subset (h : dist x y ≤ ε₂ - ε₁) : ball x ε₁ ⊆ ball y ε₂ :=
λ z zx, by rw ← add_sub_cancel'_right ε₁ ε₂; exact
lt_of_le_of_lt (dist_triangle z x y) (add_lt_add_of_lt_of_le zx h)

theorem ball_half_subset (y) (h : y ∈ ball x (ε / 2)) : ball y (ε / 2) ⊆ ball x ε :=
ball_subset $ by rw sub_self_div_two; exact le_of_lt h

theorem exists_ball_subset_ball (h : y ∈ ball x ε) : ∃ ε' > 0, ball y ε' ⊆ ball x ε :=
⟨_, sub_pos.2 h, ball_subset $ by rw sub_sub_self⟩

theorem ball_eq_empty_iff_nonpos : ε ≤ 0 ↔ ball x ε = ∅ :=
(eq_empty_iff_forall_not_mem.trans
⟨λ h, le_of_not_gt $ λ ε0, h _ $ mem_ball_self ε0,
 λ ε0 y h, not_lt_of_le ε0 $ pos_of_mem_ball h⟩).symm

theorem uniformity_basis_dist :
  (𝓤 α).has_basis (λ ε : ℝ, 0 < ε) (λ ε, {p:α×α | dist p.1 p.2 < ε}) :=
(metric_space.uniformity_dist α).symm ▸ has_basis_binfi_principal
  (λ r (hr : 0 < r) p (hp : 0 < p), ⟨min r p, lt_min hr hp,
    λ x (hx : dist _ _ < _), lt_of_lt_of_le hx (min_le_left r p),
    λ x (hx : dist _ _ < _), lt_of_lt_of_le hx (min_le_right r p)⟩) $
  nonempty_Ioi

/-- Given `f : β → ℝ`, if `f` sends `{i | p i}` to a set of positive numbers
accumulating to zero, then `f i`-neighborhoods of the diagonal form a basis of `𝓤 α`.

For specific bases see `uniformity_basis_dist`, `uniformity_basis_dist_inv_nat_succ`,
and `uniformity_basis_dist_inv_nat_pos`. -/
protected theorem mk_uniformity_basis {β : Type*} {p : β → Prop} {f : β → ℝ}
  (hf₀ : ∀ i, p i → 0 < f i) (hf : ∀ ⦃ε⦄, 0 < ε → ∃ i (hi : p i), f i ≤ ε) :
  (𝓤 α).has_basis p (λ i, {p:α×α | dist p.1 p.2 < f i}) :=
begin
  refine λ s, uniformity_basis_dist.mem_iff.trans _,
  split,
  { rintros ⟨ε, ε₀, hε⟩,
    obtain ⟨i, hi, H⟩ : ∃ i (hi : p i), f i ≤ ε, from hf ε₀,
    exact ⟨i, hi, λ x (hx : _ < _), hε $ lt_of_lt_of_le hx H⟩ },
  { exact λ ⟨i, hi, H⟩, ⟨f i, hf₀ i hi, H⟩ }
end

theorem uniformity_basis_dist_inv_nat_succ :
  (𝓤 α).has_basis (λ _, true) (λ n:ℕ, {p:α×α | dist p.1 p.2 < 1 / (↑n+1) }) :=
metric.mk_uniformity_basis (λ n _, div_pos zero_lt_one $ nat.cast_add_one_pos n)
  (λ ε ε0, (exists_nat_one_div_lt ε0).imp $ λ n hn, ⟨trivial, le_of_lt hn⟩)

theorem uniformity_basis_dist_inv_nat_pos :
  (𝓤 α).has_basis (λ n:ℕ, 0<n) (λ n:ℕ, {p:α×α | dist p.1 p.2 < 1 / ↑n }) :=
metric.mk_uniformity_basis (λ n hn, div_pos zero_lt_one $ nat.cast_pos.2 hn)
  (λ ε ε0, let ⟨n, hn⟩ := exists_nat_one_div_lt ε0 in ⟨n+1, nat.succ_pos n, le_of_lt hn⟩)

/-- Given `f : β → ℝ`, if `f` sends `{i | p i}` to a set of positive numbers
accumulating to zero, then closed neighborhoods of the diagonal of sizes `{f i | p i}`
form a basis of `𝓤 α`.

Currently we have only one specific basis `uniformity_basis_dist_le` based on this constructor.
More can be easily added if needed in the future. -/
protected theorem mk_uniformity_basis_le {β : Type*} {p : β → Prop} {f : β → ℝ}
  (hf₀ : ∀ x, p x → 0 < f x) (hf : ∀ ε, 0 < ε → ∃ x (hx : p x), f x ≤ ε) :
  (𝓤 α).has_basis p (λ x, {p:α×α | dist p.1 p.2 ≤ f x}) :=
begin
  refine λ s, uniformity_basis_dist.mem_iff.trans _,
  split,
  { rintros ⟨ε, ε₀, hε⟩,
    rcases dense ε₀ with ⟨ε', hε'⟩,
    rcases hf ε' hε'.1 with ⟨i, hi, H⟩,
    exact ⟨i, hi, λ x (hx : _ ≤ _), hε $ lt_of_le_of_lt (le_trans hx H) hε'.2⟩ },
  { exact λ ⟨i, hi, H⟩, ⟨f i, hf₀ i hi, λ x (hx : _ < _), H (le_of_lt hx)⟩ }
end

/-- Contant size closed neighborhoods of the diagonal form a basis
of the uniformity filter. -/
theorem uniformity_basis_dist_le :
  (𝓤 α).has_basis (λ ε : ℝ, 0 < ε) (λ ε, {p:α×α | dist p.1 p.2 ≤ ε}) :=
metric.mk_uniformity_basis_le (λ _, id) (λ ε ε₀, ⟨ε, ε₀, le_refl ε⟩)

theorem mem_uniformity_dist {s : set (α×α)} :
  s ∈ 𝓤 α ↔ (∃ε>0, ∀{a b:α}, dist a b < ε → (a, b) ∈ s) :=
uniformity_basis_dist.mem_uniformity_iff

/-- A constant size neighborhood of the diagonal is an entourage. -/
theorem dist_mem_uniformity {ε:ℝ} (ε0 : 0 < ε) :
  {p:α×α | dist p.1 p.2 < ε} ∈ 𝓤 α :=
mem_uniformity_dist.2 ⟨ε, ε0, λ a b, id⟩

theorem uniform_continuous_iff [metric_space β] {f : α → β} :
  uniform_continuous f ↔ ∀ ε > 0, ∃ δ > 0,
    ∀{a b:α}, dist a b < δ → dist (f a) (f b) < ε :=
uniformity_basis_dist.uniform_continuous_iff uniformity_basis_dist

theorem uniform_embedding_iff [metric_space β] {f : α → β} :
  uniform_embedding f ↔ function.injective f ∧ uniform_continuous f ∧
    ∀ δ > 0, ∃ ε > 0, ∀ {a b : α}, dist (f a) (f b) < ε → dist a b < δ :=
uniform_embedding_def'.trans $ and_congr iff.rfl $ and_congr iff.rfl
⟨λ H δ δ0, let ⟨t, tu, ht⟩ := H _ (dist_mem_uniformity δ0),
               ⟨ε, ε0, hε⟩ := mem_uniformity_dist.1 tu in
  ⟨ε, ε0, λ a b h, ht _ _ (hε h)⟩,
 λ H s su, let ⟨δ, δ0, hδ⟩ := mem_uniformity_dist.1 su, ⟨ε, ε0, hε⟩ := H _ δ0 in
  ⟨_, dist_mem_uniformity ε0, λ a b h, hδ (hε h)⟩⟩

/-- A map between metric spaces is a uniform embedding if and only if the distance between `f x`
and `f y` is controlled in terms of the distance between `x` and `y` and conversely. -/
theorem uniform_embedding_iff' [metric_space β] {f : α → β} :
  uniform_embedding f ↔
  (∀ ε > 0, ∃ δ > 0, ∀ {a b : α}, dist a b < δ → dist (f a) (f b) < ε) ∧
  (∀ δ > 0, ∃ ε > 0, ∀ {a b : α}, dist (f a) (f b) < ε → dist a b < δ) :=
begin
  split,
  { assume h,
    exact ⟨uniform_continuous_iff.1 (uniform_embedding_iff.1 h).2.1,
          (uniform_embedding_iff.1 h).2.2⟩ },
  { rintros ⟨h₁, h₂⟩,
    refine uniform_embedding_iff.2 ⟨_, uniform_continuous_iff.2 h₁, h₂⟩,
    assume x y hxy,
    have : dist x y ≤ 0,
    { refine le_of_forall_lt' (λδ δpos, _),
      rcases h₂ δ δpos with ⟨ε, εpos, hε⟩,
      have : dist (f x) (f y) < ε, by simpa [hxy],
      exact hε this },
    simpa using this }
end

theorem totally_bounded_iff {s : set α} :
  totally_bounded s ↔ ∀ ε > 0, ∃t : set α, finite t ∧ s ⊆ ⋃y∈t, ball y ε :=
⟨λ H ε ε0, H _ (dist_mem_uniformity ε0),
 λ H r ru, let ⟨ε, ε0, hε⟩ := mem_uniformity_dist.1 ru,
               ⟨t, ft, h⟩ := H ε ε0 in
  ⟨t, ft, subset.trans h $ Union_subset_Union $ λ y, Union_subset_Union $ λ yt z, hε⟩⟩

/-- A metric space space is totally bounded if one can reconstruct up to any ε>0 any element of the
space from finitely many data. -/
lemma totally_bounded_of_finite_discretization {α : Type u} [metric_space α] {s : set α}
  (H : ∀ε > (0 : ℝ), ∃ (β : Type u) [fintype β] (F : s → β),
    ∀x y, F x = F y → dist (x:α) y < ε) :
  totally_bounded s :=
begin
  cases s.eq_empty_or_nonempty with hs hs,
  { rw hs, exact totally_bounded_empty },
  rcases hs with ⟨x0, hx0⟩,
  haveI : inhabited s := ⟨⟨x0, hx0⟩⟩,
  refine totally_bounded_iff.2 (λ ε ε0, _),
  rcases H ε ε0 with ⟨β, fβ, F, hF⟩,
  let Finv := function.inv_fun F,
  refine ⟨range (subtype.val ∘ Finv), finite_range _, λ x xs, _⟩,
  let x' := Finv (F ⟨x, xs⟩),
  have : F x' = F ⟨x, xs⟩ := function.inv_fun_eq ⟨⟨x, xs⟩, rfl⟩,
  simp only [set.mem_Union, set.mem_range],
  exact ⟨_, ⟨F ⟨x, xs⟩, rfl⟩, hF _ _ this.symm⟩
end

protected lemma cauchy_iff {f : filter α} :
  cauchy f ↔ f ≠ ⊥ ∧ ∀ ε > 0, ∃ t ∈ f, ∀ x y ∈ t, dist x y < ε :=
uniformity_basis_dist.cauchy_iff

theorem nhds_basis_ball : (𝓝 x).has_basis (λ ε:ℝ, 0 < ε) (ball x) :=
nhds_basis_uniformity uniformity_basis_dist

theorem mem_nhds_iff : s ∈ 𝓝 x ↔ ∃ε>0, ball x ε ⊆ s :=
nhds_basis_ball.mem_iff

theorem nhds_basis_closed_ball : (𝓝 x).has_basis (λ ε:ℝ, 0 < ε) (closed_ball x) :=
nhds_basis_uniformity uniformity_basis_dist_le

theorem nhds_basis_ball_inv_nat_succ :
  (𝓝 x).has_basis (λ _, true) (λ n:ℕ, ball x (1 / (↑n+1))) :=
nhds_basis_uniformity uniformity_basis_dist_inv_nat_succ

theorem nhds_basis_ball_inv_nat_pos :
  (𝓝 x).has_basis (λ n, 0<n) (λ n:ℕ, ball x (1 / ↑n)) :=
nhds_basis_uniformity uniformity_basis_dist_inv_nat_pos

theorem is_open_iff : is_open s ↔ ∀x∈s, ∃ε>0, ball x ε ⊆ s :=
by simp only [is_open_iff_nhds, mem_nhds_iff, le_principal_iff]

theorem is_open_ball : is_open (ball x ε) :=
is_open_iff.2 $ λ y, exists_ball_subset_ball

theorem ball_mem_nhds (x : α) {ε : ℝ} (ε0 : 0 < ε) : ball x ε ∈ 𝓝 x :=
mem_nhds_sets is_open_ball (mem_ball_self ε0)

theorem nhds_within_basis_ball {s : set α} :
  (nhds_within x s).has_basis (λ ε:ℝ, 0 < ε) (λ ε, ball x ε ∩ s) :=
nhds_within_has_basis nhds_basis_ball s

@[nolint] -- see Note [nolint_ge]
theorem mem_nhds_within_iff {t : set α} : s ∈ nhds_within x t ↔ ∃ε>0, ball x ε ∩ t ⊆ s :=
nhds_within_basis_ball.mem_iff

@[nolint] -- see Note [nolint_ge]
theorem tendsto_nhds_within_nhds_within [metric_space β] {t : set β} {f : α → β} {a b} :
  tendsto f (nhds_within a s) (nhds_within b t) ↔
    ∀ ε > 0, ∃ δ > 0, ∀{x:α}, x ∈ s → dist x a < δ → f x ∈ t ∧ dist (f x) b < ε :=
(nhds_within_basis_ball.tendsto_iff nhds_within_basis_ball).trans $
  by simp only [inter_comm, mem_inter_iff, and_imp, mem_ball]

@[nolint] -- see Note [nolint_ge]
theorem tendsto_nhds_within_nhds [metric_space β] {f : α → β} {a b} :
  tendsto f (nhds_within a s) (𝓝 b) ↔
    ∀ ε > 0, ∃ δ > 0, ∀{x:α}, x ∈ s → dist x a < δ → dist (f x) b < ε :=
by { rw [← nhds_within_univ, tendsto_nhds_within_nhds_within],
  simp only [mem_univ, true_and] }

@[nolint] -- see Note [nolint_ge]
theorem tendsto_nhds_nhds [metric_space β] {f : α → β} {a b} :
  tendsto f (𝓝 a) (𝓝 b) ↔
    ∀ ε > 0, ∃ δ > 0, ∀{x:α}, dist x a < δ → dist (f x) b < ε :=
nhds_basis_ball.tendsto_iff nhds_basis_ball

@[nolint] -- see Note [nolint_ge]
theorem continuous_at_iff [metric_space β] {f : α → β} {a : α} :
  continuous_at f a ↔
    ∀ ε > 0, ∃ δ > 0, ∀{x:α}, dist x a < δ → dist (f x) (f a) < ε :=
by rw [continuous_at, tendsto_nhds_nhds]

theorem continuous_iff [metric_space β] {f : α → β} :
  continuous f ↔
    ∀b (ε > 0), ∃ δ > 0, ∀a, dist a b < δ → dist (f a) (f b) < ε :=
continuous_iff_continuous_at.trans $ forall_congr $ λ b, tendsto_nhds_nhds

theorem tendsto_nhds {f : filter β} {u : β → α} {a : α} :
  tendsto u f (𝓝 a) ↔ ∀ ε > 0, ∀ᶠ x in f, dist (u x) a < ε :=
nhds_basis_ball.tendsto_right_iff

theorem continuous_iff' [topological_space β] {f : β → α} :
  continuous f ↔ ∀a (ε > 0), ∀ᶠ x in 𝓝 a, dist (f x) (f a) < ε :=
continuous_iff_continuous_at.trans $ forall_congr $ λ b, tendsto_nhds

theorem tendsto_at_top [nonempty β] [semilattice_sup β] {u : β → α} {a : α} :
  tendsto u at_top (𝓝 a) ↔ ∀ε>0, ∃N, ∀n≥N, dist (u n) a < ε :=
(at_top_basis.tendsto_iff nhds_basis_ball).trans $
  by { simp only [exists_prop, true_and], refl }

end metric

open metric

@[priority 100] -- see Note [lower instance priority]
instance metric_space.to_separated : separated α :=
separated_def.2 $ λ x y h, eq_of_forall_dist_le $
  λ ε ε0, le_of_lt (h _ (dist_mem_uniformity ε0))

/-Instantiate a metric space as an emetric space. Before we can state the instance,
we need to show that the uniform structure coming from the edistance and the
distance coincide. -/

/-- Expressing the uniformity in terms of `edist` -/
protected lemma metric.uniformity_basis_edist :
  (𝓤 α).has_basis (λ ε:ennreal, 0 < ε) (λ ε, {p | edist p.1 p.2 < ε}) :=
begin
  intro t,
  refine mem_uniformity_dist.trans ⟨_, _⟩; rintro ⟨ε, ε0, Hε⟩,
  { use [ennreal.of_real ε, ennreal.of_real_pos.2 ε0],
    rintros ⟨a, b⟩,
    simp only [edist_dist, ennreal.of_real_lt_of_real_iff ε0],
    exact Hε },
  { rcases ennreal.lt_iff_exists_real_btwn.1 ε0 with ⟨ε', _, ε0', hε⟩,
    rw [ennreal.of_real_pos] at ε0',
    refine ⟨ε', ε0', λ a b h, Hε (lt_trans _ hε)⟩,
    rwa [edist_dist, ennreal.of_real_lt_of_real_iff ε0'] }
end

@[nolint] -- see Note [nolint_ge]
theorem metric.uniformity_edist : 𝓤 α = (⨅ ε>0, principal {p:α×α | edist p.1 p.2 < ε}) :=
metric.uniformity_basis_edist.eq_binfi

/-- A metric space induces an emetric space -/
@[priority 100] -- see Note [lower instance priority]
instance metric_space.to_emetric_space : emetric_space α :=
{ edist               := edist,
  edist_self          := by simp [edist_dist],
  eq_of_edist_eq_zero := assume x y h, by simpa [edist_dist] using h,
  edist_comm          := by simp only [edist_dist, dist_comm]; simp,
  edist_triangle      := assume x y z, begin
    simp only [edist_dist, (ennreal.of_real_add _ _).symm, dist_nonneg],
    rw ennreal.of_real_le_of_real_iff _,
    { exact dist_triangle _ _ _ },
    { simpa using add_le_add (dist_nonneg : 0 ≤ dist x y) dist_nonneg }
  end,
  uniformity_edist    := metric.uniformity_edist,
  ..‹metric_space α› }

/-- Balls defined using the distance or the edistance coincide -/
lemma metric.emetric_ball {x : α} {ε : ℝ} : emetric.ball x (ennreal.of_real ε) = ball x ε :=
begin
  ext y,
  simp only [emetric.mem_ball, mem_ball, edist_dist],
  exact ennreal.of_real_lt_of_real_iff_of_nonneg dist_nonneg
end

/-- Closed balls defined using the distance or the edistance coincide -/
lemma metric.emetric_closed_ball {x : α} {ε : ℝ} (h : 0 ≤ ε) :
  emetric.closed_ball x (ennreal.of_real ε) = closed_ball x ε :=
by ext y; simp [edist_dist]; rw ennreal.of_real_le_of_real_iff h

def metric_space.replace_uniformity {α} [U : uniform_space α] (m : metric_space α)
  (H : @uniformity _ U = @uniformity _ (metric_space.to_uniform_space α)) :
  metric_space α :=
{ dist               := @dist _ m.to_has_dist,
  dist_self          := dist_self,
  eq_of_dist_eq_zero := @eq_of_dist_eq_zero _ _,
  dist_comm          := dist_comm,
  dist_triangle      := dist_triangle,
  edist              := edist,
  edist_dist         := edist_dist,
  to_uniform_space   := U,
  uniformity_dist    := H.trans (metric_space.uniformity_dist α) }

/-- One gets a metric space from an emetric space if the edistance
is everywhere finite, by pushing the edistance to reals. We set it up so that the edist and the
uniformity are defeq in the metric space and the emetric space. In this definition, the distance
is given separately, to be able to prescribe some expression which is not defeq to the push-forward
of the edistance to reals. -/
def emetric_space.to_metric_space_of_dist {α : Type u} [e : emetric_space α]
  (dist : α → α → ℝ)
  (edist_ne_top : ∀x y: α, edist x y ≠ ⊤)
  (h : ∀x y, dist x y = ennreal.to_real (edist x y)) :
  metric_space α :=
let m : metric_space α :=
{ dist := dist,
  eq_of_dist_eq_zero := λx y hxy, by simpa [h, ennreal.to_real_eq_zero_iff, edist_ne_top x y] using hxy,
  dist_self          := λx, by simp [h],
  dist_comm          := λx y, by simp [h, emetric_space.edist_comm],
  dist_triangle      := λx y z, begin
    simp only [h],
    rw [← ennreal.to_real_add (edist_ne_top _ _) (edist_ne_top _ _),
        ennreal.to_real_le_to_real (edist_ne_top _ _)],
    { exact edist_triangle _ _ _ },
    { simp [ennreal.add_eq_top, edist_ne_top] }
  end,
  edist := λx y, edist x y,
  edist_dist := λx y, by simp [h, ennreal.of_real_to_real, edist_ne_top] } in
m.replace_uniformity $ by { rw [uniformity_edist, metric.uniformity_edist], refl }

/-- One gets a metric space from an emetric space if the edistance
is everywhere finite, by pushing the edistance to reals. We set it up so that the edist and the
uniformity are defeq in the metric space and the emetric space. -/
def emetric_space.to_metric_space {α : Type u} [e : emetric_space α] (h : ∀x y: α, edist x y ≠ ⊤) :
  metric_space α :=
emetric_space.to_metric_space_of_dist (λx y, ennreal.to_real (edist x y)) h (λx y, rfl)

/-- A very useful criterion to show that a space is complete is to show that all sequences
which satisfy a bound of the form `dist (u n) (u m) < B N` for all `n m ≥ N` are
converging. This is often applied for `B N = 2^{-N}`, i.e., with a very fast convergence to
`0`, which makes it possible to use arguments of converging series, while this is impossible
to do in general for arbitrary Cauchy sequences. -/
theorem metric.complete_of_convergent_controlled_sequences (B : ℕ → real) (hB : ∀n, 0 < B n)
  (H : ∀u : ℕ → α, (∀N n m : ℕ, N ≤ n → N ≤ m → dist (u n) (u m) < B N) → ∃x, tendsto u at_top (𝓝 x)) :
  complete_space α :=
begin
  -- this follows from the same criterion in emetric spaces. We just need to translate
  -- the convergence assumption from `dist` to `edist`
  apply emetric.complete_of_convergent_controlled_sequences (λn, ennreal.of_real (B n)),
  { simp [hB] },
  { assume u Hu,
    apply H,
    assume N n m hn hm,
    rw [← ennreal.of_real_lt_of_real_iff (hB N), ← edist_dist],
    exact Hu N n m hn hm }
end

theorem metric.complete_of_cauchy_seq_tendsto :
  (∀ u : ℕ → α, cauchy_seq u → ∃a, tendsto u at_top (𝓝 a)) → complete_space α :=
emetric.complete_of_cauchy_seq_tendsto

section real

/-- Instantiate the reals as a metric space. -/
instance real.metric_space : metric_space ℝ :=
{ dist               := λx y, abs (x - y),
  dist_self          := by simp [abs_zero],
  eq_of_dist_eq_zero := by simp [add_neg_eq_zero],
  dist_comm          := assume x y, abs_sub _ _,
  dist_triangle      := assume x y z, abs_sub_le _ _ _ }

theorem real.dist_eq (x y : ℝ) : dist x y = abs (x - y) := rfl

theorem real.dist_0_eq_abs (x : ℝ) : dist x 0 = abs x :=
by simp [real.dist_eq]

instance : order_topology ℝ :=
order_topology_of_nhds_abs $ λ x, begin
  simp only [show ∀ r, {b : ℝ | abs (x - b) < r} = ball x r,
    by simp [-sub_eq_add_neg, abs_sub, ball, real.dist_eq]],
  apply le_antisymm,
  { simp [le_infi_iff],
    exact λ ε ε0, mem_nhds_sets (is_open_ball) (mem_ball_self ε0) },
  { intros s h,
    rcases mem_nhds_iff.1 h with ⟨ε, ε0, ss⟩,
    exact mem_infi_sets _ (mem_infi_sets ε0 (mem_principal_sets.2 ss)) },
end

lemma closed_ball_Icc {x r : ℝ} : closed_ball x r = Icc (x-r) (x+r) :=
by ext y; rw [mem_closed_ball, dist_comm, real.dist_eq,
  abs_sub_le_iff, mem_Icc, ← sub_le_iff_le_add', sub_le]

/-- Special case of the sandwich theorem; see `tendsto_of_tendsto_of_tendsto_of_le_of_le`
for the general case. -/
lemma squeeze_zero {α} {f g : α → ℝ} {t₀ : filter α} (hf : ∀t, 0 ≤ f t) (hft : ∀t, f t ≤ g t)
  (g0 : tendsto g t₀ (𝓝 0)) : tendsto f t₀ (𝓝 0) :=
begin
  apply tendsto_of_tendsto_of_tendsto_of_le_of_le (tendsto_const_nhds) g0;
  simp [*]; exact filter.univ_mem_sets
end

theorem metric.uniformity_eq_comap_nhds_zero :
  𝓤 α = comap (λp:α×α, dist p.1 p.2) (𝓝 (0 : ℝ)) :=
by { ext s,
  simp [mem_uniformity_dist, (nhds_basis_ball.comap _).mem_iff, subset_def, real.dist_0_eq_abs] }

lemma cauchy_seq_iff_tendsto_dist_at_top_0 [nonempty β] [semilattice_sup β] {u : β → α} :
  cauchy_seq u ↔ tendsto (λ (n : β × β), dist (u n.1) (u n.2)) at_top (𝓝 0) :=
by rw [cauchy_seq_iff_tendsto, metric.uniformity_eq_comap_nhds_zero, tendsto_comap_iff,
  prod.map_def]

end real

section cauchy_seq
variables [nonempty β] [semilattice_sup β]

/-- In a metric space, Cauchy sequences are characterized by the fact that, eventually,
the distance between its elements is arbitrarily small -/
theorem metric.cauchy_seq_iff {u : β → α} :
  cauchy_seq u ↔ ∀ε>0, ∃N, ∀m n≥N, dist (u m) (u n) < ε :=
uniformity_basis_dist.cauchy_seq_iff

/-- A variation around the metric characterization of Cauchy sequences -/
theorem metric.cauchy_seq_iff' {u : β → α} :
  cauchy_seq u ↔ ∀ε>0, ∃N, ∀n≥N, dist (u n) (u N) < ε :=
uniformity_basis_dist.cauchy_seq_iff'

/-- If the distance between `s n` and `s m`, `n, m ≥ N` is bounded above by `b N`
and `b` converges to zero, then `s` is a Cauchy sequence.  -/
lemma cauchy_seq_of_le_tendsto_0 {s : β → α} (b : β → ℝ)
  (h : ∀ n m N : β, N ≤ n → N ≤ m → dist (s n) (s m) ≤ b N) (h₀ : tendsto b at_top (nhds 0)) :
  cauchy_seq s :=
metric.cauchy_seq_iff.2 $ λ ε ε0,
  (metric.tendsto_at_top.1 h₀ ε ε0).imp $ λ N hN m n hm hn,
  calc dist (s m) (s n) ≤ b N : h m n N hm hn
                    ... ≤ abs (b N) : le_abs_self _
                    ... = dist (b N) 0 : by rw real.dist_0_eq_abs; refl
                    ... < ε : (hN _ (le_refl N))

/-- A Cauchy sequence on the natural numbers is bounded. -/
theorem cauchy_seq_bdd {u : ℕ → α} (hu : cauchy_seq u) :
  ∃ R > 0, ∀ m n, dist (u m) (u n) < R :=
begin
  rcases metric.cauchy_seq_iff'.1 hu 1 zero_lt_one with ⟨N, hN⟩,
  suffices : ∃ R > 0, ∀ n, dist (u n) (u N) < R,
  { rcases this with ⟨R, R0, H⟩,
    exact ⟨_, add_pos R0 R0, λ m n,
      lt_of_le_of_lt (dist_triangle_right _ _ _) (add_lt_add (H m) (H n))⟩ },
  let R := finset.sup (finset.range N) (λ n, nndist (u n) (u N)),
  refine ⟨↑R + 1, add_pos_of_nonneg_of_pos R.2 zero_lt_one, λ n, _⟩,
  cases le_or_lt N n,
  { exact lt_of_lt_of_le (hN _ h) (le_add_of_nonneg_left R.2) },
  { have : _ ≤ R := finset.le_sup (finset.mem_range.2 h),
    exact lt_of_le_of_lt this (lt_add_of_pos_right _ zero_lt_one) }
end

/-- Yet another metric characterization of Cauchy sequences on integers. This one is often the
most efficient. -/
lemma cauchy_seq_iff_le_tendsto_0 {s : ℕ → α} : cauchy_seq s ↔ ∃ b : ℕ → ℝ,
  (∀ n, 0 ≤ b n) ∧
  (∀ n m N : ℕ, N ≤ n → N ≤ m → dist (s n) (s m) ≤ b N) ∧
  tendsto b at_top (𝓝 0) :=
⟨λ hs, begin
  /- `s` is a Cauchy sequence. The sequence `b` will be constructed by taking
  the supremum of the distances between `s n` and `s m` for `n m ≥ N`.
  First, we prove that all these distances are bounded, as otherwise the Sup
  would not make sense. -/
  let S := λ N, (λ(p : ℕ × ℕ), dist (s p.1) (s p.2)) '' {p | p.1 ≥ N ∧ p.2 ≥ N},
  have hS : ∀ N, ∃ x, ∀ y ∈ S N, y ≤ x,
  { rcases cauchy_seq_bdd hs with ⟨R, R0, hR⟩,
    refine λ N, ⟨R, _⟩, rintro _ ⟨⟨m, n⟩, _, rfl⟩,
    exact le_of_lt (hR m n) },
  have bdd : bdd_above (range (λ(p : ℕ × ℕ), dist (s p.1) (s p.2))),
  { rcases cauchy_seq_bdd hs with ⟨R, R0, hR⟩,
    use R, rintro _ ⟨⟨m, n⟩, rfl⟩, exact le_of_lt (hR m n) },
  -- Prove that it bounds the distances of points in the Cauchy sequence
  have ub : ∀ m n N, N ≤ m → N ≤ n → dist (s m) (s n) ≤ real.Sup (S N) :=
    λ m n N hm hn, real.le_Sup _ (hS N) ⟨⟨_, _⟩, ⟨hm, hn⟩, rfl⟩,
  have S0m : ∀ n, (0:ℝ) ∈ S n := λ n, ⟨⟨n, n⟩, ⟨le_refl _, le_refl _⟩, dist_self _⟩,
  have S0 := λ n, real.le_Sup _ (hS n) (S0m n),
  -- Prove that it tends to `0`, by using the Cauchy property of `s`
  refine ⟨λ N, real.Sup (S N), S0, ub, metric.tendsto_at_top.2 (λ ε ε0, _)⟩,
  refine (metric.cauchy_seq_iff.1 hs (ε/2) (half_pos ε0)).imp (λ N hN n hn, _),
  rw [real.dist_0_eq_abs, abs_of_nonneg (S0 n)],
  refine lt_of_le_of_lt (real.Sup_le_ub _ ⟨_, S0m _⟩ _) (half_lt_self ε0),
  rintro _ ⟨⟨m', n'⟩, ⟨hm', hn'⟩, rfl⟩,
  exact le_of_lt (hN _ _ (le_trans hn hm') (le_trans hn hn'))
  end,
λ ⟨b, _, b_bound, b_lim⟩, cauchy_seq_of_le_tendsto_0 b b_bound b_lim⟩

end cauchy_seq

def metric_space.induced {α β} (f : α → β) (hf : function.injective f)
  (m : metric_space β) : metric_space α :=
{ dist               := λ x y, dist (f x) (f y),
  dist_self          := λ x, dist_self _,
  eq_of_dist_eq_zero := λ x y h, hf (dist_eq_zero.1 h),
  dist_comm          := λ x y, dist_comm _ _,
  dist_triangle      := λ x y z, dist_triangle _ _ _,
  edist              := λ x y, edist (f x) (f y),
  edist_dist         := λ x y, edist_dist _ _,
  to_uniform_space   := uniform_space.comap f m.to_uniform_space,
  uniformity_dist    := begin
    apply @uniformity_dist_of_mem_uniformity _ _ _ _ _ (λ x y, dist (f x) (f y)),
    refine λ s, mem_comap_sets.trans _,
    split; intro H,
    { rcases H with ⟨r, ru, rs⟩,
      rcases mem_uniformity_dist.1 ru with ⟨ε, ε0, hε⟩,
      refine ⟨ε, ε0, λ a b h, rs (hε _)⟩, exact h },
    { rcases H with ⟨ε, ε0, hε⟩,
      exact ⟨_, dist_mem_uniformity ε0, λ ⟨a, b⟩, hε⟩ }
  end }

instance subtype.metric_space {α : Type*} {p : α → Prop} [t : metric_space α] :
  metric_space (subtype p) :=
metric_space.induced subtype.val (λ x y, subtype.eq) t

theorem subtype.dist_eq {p : α → Prop} (x y : subtype p) : dist x y = dist x.1 y.1 := rfl

section nnreal

instance : metric_space nnreal := by unfold nnreal; apply_instance

lemma nnreal.dist_eq (a b : nnreal) : dist a b = abs ((a:ℝ) - b) := rfl

lemma nnreal.nndist_eq (a b : nnreal) :
  nndist a b = max (a - b) (b - a) :=
begin
  wlog h : a ≤ b,
  { apply nnreal.coe_eq.1,
    rw [nnreal.sub_eq_zero h, max_eq_right (zero_le $ b - a), ← dist_nndist, nnreal.dist_eq,
      nnreal.coe_sub h, abs, neg_sub],
    apply max_eq_right,
    linarith [nnreal.coe_le.2 h] },
  rwa [nndist_comm, max_comm]
end
end nnreal

section prod

instance prod.metric_space_max [metric_space β] : metric_space (α × β) :=
{ dist := λ x y, max (dist x.1 y.1) (dist x.2 y.2),
  dist_self := λ x, by simp,
  eq_of_dist_eq_zero := λ x y h, begin
    cases max_le_iff.1 (le_of_eq h) with h₁ h₂,
    exact prod.ext_iff.2 ⟨dist_le_zero.1 h₁, dist_le_zero.1 h₂⟩
  end,
  dist_comm := λ x y, by simp [dist_comm],
  dist_triangle := λ x y z, max_le
    (le_trans (dist_triangle _ _ _) (add_le_add (le_max_left _ _) (le_max_left _ _)))
    (le_trans (dist_triangle _ _ _) (add_le_add (le_max_right _ _) (le_max_right _ _))),
  edist := λ x y, max (edist x.1 y.1) (edist x.2 y.2),
  edist_dist := assume x y, begin
    have : monotone ennreal.of_real := assume x y h, ennreal.of_real_le_of_real h,
    rw [edist_dist, edist_dist, this.map_max.symm]
  end,
  uniformity_dist := begin
    refine uniformity_prod.trans _,
    simp only [uniformity_basis_dist.eq_binfi, comap_infi],
    rw ← infi_inf_eq, congr, funext,
    rw ← infi_inf_eq, congr, funext,
    simp [inf_principal, ext_iff, max_lt_iff]
  end,
  to_uniform_space := prod.uniform_space }

lemma prod.dist_eq [metric_space β] {x y : α × β} :
  dist x y = max (dist x.1 y.1) (dist x.2 y.2) := rfl

end prod

theorem uniform_continuous_dist' : uniform_continuous (λp:α×α, dist p.1 p.2) :=
metric.uniform_continuous_iff.2 (λ ε ε0, ⟨ε/2, half_pos ε0,
begin
  suffices,
  { intros p q h, cases p with p₁ p₂, cases q with q₁ q₂,
    cases max_lt_iff.1 h with h₁ h₂, clear h,
    dsimp at h₁ h₂ ⊢,
    rw real.dist_eq,
    refine abs_sub_lt_iff.2 ⟨_, _⟩,
    { revert p₁ p₂ q₁ q₂ h₁ h₂, exact this },
    { apply this; rwa dist_comm } },
  intros p₁ p₂ q₁ q₂ h₁ h₂,
  have := add_lt_add
    (abs_sub_lt_iff.1 (lt_of_le_of_lt (abs_dist_sub_le p₁ q₁ p₂) h₁)).1
    (abs_sub_lt_iff.1 (lt_of_le_of_lt (abs_dist_sub_le p₂ q₂ q₁) h₂)).1,
  rwa [add_halves, dist_comm p₂, sub_add_sub_cancel, dist_comm q₂] at this
end⟩)

theorem uniform_continuous_dist [uniform_space β] {f g : β → α}
  (hf : uniform_continuous f) (hg : uniform_continuous g) :
  uniform_continuous (λb, dist (f b) (g b)) :=
uniform_continuous_dist'.comp (hf.prod_mk hg)

theorem continuous_dist' : continuous (λp:α×α, dist p.1 p.2) :=
uniform_continuous_dist'.continuous

theorem continuous_dist [topological_space β] {f g : β → α}
  (hf : continuous f) (hg : continuous g) : continuous (λb, dist (f b) (g b)) :=
continuous_dist'.comp (hf.prod_mk hg)

theorem tendsto_dist {f g : β → α} {x : filter β} {a b : α}
  (hf : tendsto f x (𝓝 a)) (hg : tendsto g x (𝓝 b)) :
  tendsto (λx, dist (f x) (g x)) x (𝓝 (dist a b)) :=
have tendsto (λp:α×α, dist p.1 p.2) (𝓝 (a, b)) (𝓝 (dist a b)),
  from continuous_iff_continuous_at.mp continuous_dist' (a, b),
tendsto.comp (by rw [nhds_prod_eq] at this; exact this) (hf.prod_mk hg)

lemma nhds_comap_dist (a : α) : (𝓝 (0 : ℝ)).comap (λa', dist a' a) = 𝓝 a :=
by simp only [@nhds_eq_comap_uniformity α, metric.uniformity_eq_comap_nhds_zero,
  comap_comap_comp, (∘), dist_comm]

lemma tendsto_iff_dist_tendsto_zero {f : β → α} {x : filter β} {a : α} :
  (tendsto f x (𝓝 a)) ↔ (tendsto (λb, dist (f b) a) x (𝓝 0)) :=
by rw [← nhds_comap_dist a, tendsto_comap_iff]

lemma uniform_continuous_nndist' : uniform_continuous (λp:α×α, nndist p.1 p.2) :=
uniform_continuous_subtype_mk uniform_continuous_dist' _

lemma continuous_nndist' : continuous (λp:α×α, nndist p.1 p.2) :=
uniform_continuous_nndist'.continuous

lemma continuous_nndist [topological_space β] {f g : β → α}
  (hf : continuous f) (hg : continuous g) : continuous (λb, nndist (f b) (g b)) :=
continuous_nndist'.comp (hf.prod_mk hg)

lemma tendsto_nndist' (a b :α) :
  tendsto (λp:α×α, nndist p.1 p.2) (filter.prod (𝓝 a) (𝓝 b)) (𝓝 (nndist a b)) :=
by rw [← nhds_prod_eq]; exact continuous_iff_continuous_at.1 continuous_nndist' _

namespace metric
variables {x y z : α} {ε ε₁ ε₂ : ℝ} {s : set α}

theorem is_closed_ball : is_closed (closed_ball x ε) :=
is_closed_le (continuous_dist continuous_id continuous_const) continuous_const

/-- ε-characterization of the closure in metric spaces-/
@[nolint] -- see Note [nolint_ge]
theorem mem_closure_iff {α : Type u} [metric_space α] {s : set α} {a : α} :
  a ∈ closure s ↔ ∀ε>0, ∃b ∈ s, dist a b < ε :=
(mem_closure_iff_nhds_basis nhds_basis_ball).trans $
  by simp only [mem_ball, dist_comm]

lemma mem_closure_range_iff {α : Type u} [metric_space α] {e : β → α} {a : α} :
  a ∈ closure (range e) ↔ ∀ε>0, ∃ k : β, dist a (e k) < ε :=
by simp only [mem_closure_iff, exists_range_iff]

lemma mem_closure_range_iff_nat {α : Type u} [metric_space α] {e : β → α} {a : α} :
  a ∈ closure (range e) ↔ ∀n : ℕ, ∃ k : β, dist a (e k) < 1 / ((n : ℝ) + 1) :=
(mem_closure_iff_nhds_basis nhds_basis_ball_inv_nat_succ).trans $
  by simp only [mem_ball, dist_comm, exists_range_iff, forall_const]

theorem mem_of_closed' {α : Type u} [metric_space α] {s : set α} (hs : is_closed s)
  {a : α} : a ∈ s ↔ ∀ε>0, ∃b ∈ s, dist a b < ε :=
by simpa only [closure_eq_of_is_closed hs] using @mem_closure_iff _ _ s a

end metric

section pi
open finset lattice
variables {π : β → Type*} [fintype β] [∀b, metric_space (π b)]

/-- A finite product of metric spaces is a metric space, with the sup distance. -/
instance metric_space_pi : metric_space (Πb, π b) :=
begin
  /- we construct the instance from the emetric space instance to avoid checking again that the
  uniformity is the same as the product uniformity, but we register nevertheless a nice formula
  for the distance -/
  refine emetric_space.to_metric_space_of_dist
    (λf g, ((sup univ (λb, nndist (f b) (g b)) : nnreal) : ℝ)) _ _,
  show ∀ (x y : Π (b : β), π b), edist x y ≠ ⊤,
  { assume x y,
    rw ← lt_top_iff_ne_top,
    have : (⊥ : ennreal) < ⊤ := ennreal.coe_lt_top,
    simp [edist, this],
    assume b,
    rw lt_top_iff_ne_top,
    exact edist_ne_top (x b) (y b) },
  show ∀ (x y : Π (b : β), π b), ↑(sup univ (λ (b : β), nndist (x b) (y b))) =
    ennreal.to_real (sup univ (λ (b : β), edist (x b) (y b))),
  { assume x y,
    have : sup univ (λ (b : β), edist (x b) (y b)) = ↑(sup univ (λ (b : β), nndist (x b) (y b))),
    { simp [edist_nndist],
      refine eq.symm (comp_sup_eq_sup_comp _ _ _),
      exact (assume x y h, ennreal.coe_le_coe.2 h), refl },
    rw this,
    refl }
end

lemma dist_pi_def (f g : Πb, π b) :
  dist f g = (sup univ (λb, nndist (f b) (g b)) : nnreal) := rfl

lemma dist_pi_lt_iff {f g : Πb, π b} {r : ℝ} (hr : 0 < r) :
  dist f g < r ↔ ∀b, dist (f b) (g b) < r :=
begin
  lift r to nnreal using le_of_lt hr,
  rw_mod_cast [dist_pi_def, finset.sup_lt_iff],
  { simp [nndist], refl },
  { exact hr }
end

lemma dist_pi_le_iff {f g : Πb, π b} {r : ℝ} (hr : 0 ≤ r) :
  dist f g ≤ r ↔ ∀b, dist (f b) (g b) ≤ r :=
begin
  lift r to nnreal using hr,
  rw_mod_cast [dist_pi_def, finset.sup_le_iff],
  simp [nndist],
  refl
end

/-- An open ball in a product space is a product of open balls. The assumption `0 < r`
is necessary for the case of the empty product. -/
lemma ball_pi (x : Πb, π b) {r : ℝ} (hr : 0 < r) :
  ball x r = { y | ∀b, y b ∈ ball (x b) r } :=
by { ext p, simp [dist_pi_lt_iff hr] }

/-- A closed ball in a product space is a product of closed balls. The assumption `0 ≤ r`
is necessary for the case of the empty product. -/
lemma closed_ball_pi (x : Πb, π b) {r : ℝ} (hr : 0 ≤ r) :
  closed_ball x r = { y | ∀b, y b ∈ closed_ball (x b) r } :=
by { ext p, simp [dist_pi_le_iff hr] }

end pi

section compact

/-- Any compact set in a metric space can be covered by finitely many balls of a given positive
radius -/
lemma finite_cover_balls_of_compact {α : Type u} [metric_space α] {s : set α}
  (hs : compact s) {e : ℝ} (he : 0 < e) :
  ∃t ⊆ s, finite t ∧ s ⊆ ⋃x∈t, ball x e :=
begin
  apply hs.elim_finite_subcover_image,
  { simp [is_open_ball] },
  { intros x xs,
    simp,
    exact ⟨x, ⟨xs, by simpa⟩⟩ }
end

alias finite_cover_balls_of_compact ← compact.finite_cover_balls

end compact

section proper_space
open metric

/-- A metric space is proper if all closed balls are compact. -/
class proper_space (α : Type u) [metric_space α] : Prop :=
(compact_ball : ∀x:α, ∀r, compact (closed_ball x r))

/-- If all closed balls of large enough radius are compact, then the space is proper. Especially
useful when the lower bound for the radius is 0. -/
lemma proper_space_of_compact_closed_ball_of_le
  (R : ℝ) (h : ∀x:α, ∀r, R ≤ r → compact (closed_ball x r)) :
  proper_space α :=
⟨begin
  assume x r,
  by_cases hr : R ≤ r,
  { exact h x r hr },
  { have : closed_ball x r = closed_ball x R ∩ closed_ball x r,
    { symmetry,
      apply inter_eq_self_of_subset_right,
      exact closed_ball_subset_closed_ball (le_of_lt (not_le.1 hr)) },
    rw this,
    exact (h x R (le_refl _)).inter_right is_closed_ball }
end⟩

/- A compact metric space is proper -/
@[priority 100] -- see Note [lower instance priority]
instance proper_of_compact [compact_space α] : proper_space α :=
⟨assume x r, compact_of_is_closed_subset compact_univ is_closed_ball (subset_univ _)⟩

/-- A proper space is locally compact -/
@[priority 100] -- see Note [lower instance priority]
instance locally_compact_of_proper [proper_space α] :
  locally_compact_space α :=
begin
  apply locally_compact_of_compact_nhds,
  intros x,
  existsi closed_ball x 1,
  split,
  { apply mem_nhds_iff.2,
    existsi (1 : ℝ),
    simp,
    exact ⟨zero_lt_one, ball_subset_closed_ball⟩ },
  { apply proper_space.compact_ball }
end

/-- A proper space is complete -/
@[priority 100] -- see Note [lower instance priority]
instance complete_of_proper [proper_space α] : complete_space α :=
⟨begin
  intros f hf,
  /- We want to show that the Cauchy filter `f` is converging. It suffices to find a closed
  ball (therefore compact by properness) where it is nontrivial. -/
  have A : ∃ t ∈ f, ∀ x y ∈ t, dist x y < 1 := (metric.cauchy_iff.1 hf).2 1 zero_lt_one,
  rcases A with ⟨t, ⟨t_fset, ht⟩⟩,
  rcases nonempty_of_mem_sets hf.1 t_fset with ⟨x, xt⟩,
  have : t ⊆ closed_ball x 1 := by intros y yt; simp [dist_comm]; apply le_of_lt (ht x y xt yt),
  have : closed_ball x 1 ∈ f := f.sets_of_superset t_fset this,
  rcases (compact_iff_totally_bounded_complete.1 (proper_space.compact_ball x 1)).2 f hf (le_principal_iff.2 this)
    with ⟨y, _, hy⟩,
  exact ⟨y, hy⟩
end⟩

/-- A proper metric space is separable, and therefore second countable. Indeed, any ball is
compact, and therefore admits a countable dense subset. Taking a countable union over the balls
centered at a fixed point and with integer radius, one obtains a countable set which is
dense in the whole space. -/
@[priority 100] -- see Note [lower instance priority]
instance second_countable_of_proper [proper_space α] :
  second_countable_topology α :=
begin
  /- We show that the space admits a countable dense subset. The case where the space is empty
  is special, and trivial. -/
  have A : (univ : set α) = ∅ → ∃(s : set α), countable s ∧ closure s = (univ : set α) :=
    assume H, ⟨∅, ⟨by simp, by simp; exact H.symm⟩⟩,
  have B : (univ : set α).nonempty → ∃(s : set α), countable s ∧ closure s = (univ : set α) :=
  begin
    /- When the space is not empty, we take a point `x` in the space, and then a countable set
    `T r` which is dense in the closed ball `closed_ball x r` for each `r`. Then the set
    `t = ⋃ T n` (where the union is over all integers `n`) is countable, as a countable union
    of countable sets, and dense in the space by construction. -/
    rintros ⟨x, x_univ⟩,
    choose T a using show ∀ (r:ℝ), ∃ t ⊆ closed_ball x r, (countable (t : set α) ∧ closed_ball x r = closure t),
      from assume r, emetric.countable_closure_of_compact (proper_space.compact_ball _ _),
    let t := (⋃n:ℕ, T (n : ℝ)),
    have T₁ : countable t := by finish [countable_Union],
    have T₂ : closure t ⊆ univ := by simp,
    have T₃ : univ ⊆ closure t :=
    begin
      intros y y_univ,
      rcases exists_nat_gt (dist y x) with ⟨n, n_large⟩,
      have h : y ∈ closed_ball x (n : ℝ) := by simp; apply le_of_lt n_large,
      have h' : closed_ball x (n : ℝ) = closure (T (n : ℝ)) := by finish,
      have : y ∈ closure (T (n : ℝ)) := by rwa h' at h,
      show y ∈ closure t, from mem_of_mem_of_subset this (by apply closure_mono; apply subset_Union (λ(n:ℕ), T (n:ℝ))),
    end,
    exact ⟨t, ⟨T₁, subset.antisymm T₂ T₃⟩⟩
  end,
  haveI : separable_space α := ⟨(eq_empty_or_nonempty univ).elim A B⟩,
  apply emetric.second_countable_of_separable,
end

/-- A finite product of proper spaces is proper. -/
instance pi_proper_space {π : β → Type*} [fintype β] [∀b, metric_space (π b)]
  [h : ∀b, proper_space (π b)] : proper_space (Πb, π b) :=
begin
  refine proper_space_of_compact_closed_ball_of_le 0 (λx r hr, _),
  rw closed_ball_pi _ hr,
  apply compact_pi_infinite (λb, _),
  apply (h b).compact_ball
end

end proper_space

namespace metric
section second_countable
open topological_space

/-- A metric space is second countable if, for every ε > 0, there is a countable set which is ε-dense. -/
lemma second_countable_of_almost_dense_set
  (H : ∀ε > (0 : ℝ), ∃ s : set α, countable s ∧ (∀x, ∃y ∈ s, dist x y ≤ ε)) :
  second_countable_topology α :=
begin
  choose T T_dense using H,
  have I1 : ∀n:ℕ, (n:ℝ) + 1 > 0 :=
    λn, lt_of_lt_of_le zero_lt_one (le_add_of_nonneg_left (nat.cast_nonneg _)),
  have I : ∀n:ℕ, (n+1 : ℝ)⁻¹ > 0 := λn, inv_pos'.2 (I1 n),
  let t := ⋃n:ℕ, T (n+1)⁻¹ (I n),
  have count_t : countable t := by finish [countable_Union],
  have clos_t : closure t = univ,
  { refine subset.antisymm (subset_univ _) (λx xuniv, mem_closure_iff.2 (λε εpos, _)),
    rcases exists_nat_gt ε⁻¹ with ⟨n, hn⟩,
    have : ε⁻¹ < n + 1 := lt_of_lt_of_le hn (le_add_of_nonneg_right zero_le_one),
    have nε : ((n:ℝ)+1)⁻¹ < ε := (inv_lt (I1 n) εpos).2 this,
    rcases (T_dense (n+1)⁻¹ (I n)).2 x with ⟨y, yT, Dxy⟩,
    have : y ∈ t := mem_of_mem_of_subset yT (by apply subset_Union (λ (n:ℕ), T (n+1)⁻¹ (I n))),
    exact ⟨y, this, lt_of_le_of_lt Dxy nε⟩ },
  haveI : separable_space α := ⟨⟨t, ⟨count_t, clos_t⟩⟩⟩,
  exact emetric.second_countable_of_separable α
end

/-- A metric space space is second countable if one can reconstruct up to any ε>0 any element of the
space from countably many data. -/
lemma second_countable_of_countable_discretization {α : Type u} [metric_space α]
  (H : ∀ε > (0 : ℝ), ∃ (β : Type u) [encodable β] (F : α → β), ∀x y, F x = F y → dist x y ≤ ε) :
  second_countable_topology α :=
begin
  cases (univ : set α).eq_empty_or_nonempty with hs hs,
  { haveI : compact_space α := ⟨by rw hs; exact compact_empty⟩, by apply_instance },
  rcases hs with ⟨x0, hx0⟩,
  letI : inhabited α := ⟨x0⟩,
  refine second_countable_of_almost_dense_set (λε ε0, _),
  rcases H ε ε0 with ⟨β, fβ, F, hF⟩,
  let Finv := function.inv_fun F,
  refine ⟨range Finv, ⟨countable_range _, λx, _⟩⟩,
  let x' := Finv (F x),
  have : F x' = F x := function.inv_fun_eq ⟨x, rfl⟩,
  exact ⟨x', mem_range_self _, hF _ _ this.symm⟩
end

end second_countable
end metric

lemma lebesgue_number_lemma_of_metric
  {s : set α} {ι} {c : ι → set α} (hs : compact s)
  (hc₁ : ∀ i, is_open (c i)) (hc₂ : s ⊆ ⋃ i, c i) :
  ∃ δ > 0, ∀ x ∈ s, ∃ i, ball x δ ⊆ c i :=
let ⟨n, en, hn⟩ := lebesgue_number_lemma hs hc₁ hc₂,
    ⟨δ, δ0, hδ⟩ := mem_uniformity_dist.1 en in
⟨δ, δ0, assume x hx, let ⟨i, hi⟩ := hn x hx in
 ⟨i, assume y hy, hi (hδ (mem_ball'.mp hy))⟩⟩

lemma lebesgue_number_lemma_of_metric_sUnion
  {s : set α} {c : set (set α)} (hs : compact s)
  (hc₁ : ∀ t ∈ c, is_open t) (hc₂ : s ⊆ ⋃₀ c) :
  ∃ δ > 0, ∀ x ∈ s, ∃ t ∈ c, ball x δ ⊆ t :=
by rw sUnion_eq_Union at hc₂;
   simpa using lebesgue_number_lemma_of_metric hs (by simpa) hc₂

namespace metric

/-- Boundedness of a subset of a metric space. We formulate the definition to work
even in the empty space. -/
def bounded (s : set α) : Prop :=
∃C, ∀x y ∈ s, dist x y ≤ C

section bounded
variables {x : α} {s t : set α} {r : ℝ}

@[simp] lemma bounded_empty : bounded (∅ : set α) :=
⟨0, by simp⟩

lemma bounded_iff_mem_bounded : bounded s ↔ ∀ x ∈ s, bounded s :=
⟨λ h _ _, h, λ H,
  s.eq_empty_or_nonempty.elim
  (λ hs, hs.symm ▸ bounded_empty)
  (λ ⟨x, hx⟩, H x hx)⟩

/-- Subsets of a bounded set are also bounded -/
lemma bounded.subset (incl : s ⊆ t) : bounded t → bounded s :=
Exists.imp $ λ C hC x y hx hy, hC x y (incl hx) (incl hy)

/-- Closed balls are bounded -/
lemma bounded_closed_ball : bounded (closed_ball x r) :=
⟨r + r, λ y z hy hz, begin
  simp only [mem_closed_ball] at *,
  calc dist y z ≤ dist y x + dist z x : dist_triangle_right _ _ _
            ... ≤ r + r : add_le_add hy hz
end⟩

/-- Open balls are bounded -/
lemma bounded_ball : bounded (ball x r) :=
bounded_closed_ball.subset ball_subset_closed_ball

/-- Given a point, a bounded subset is included in some ball around this point -/
lemma bounded_iff_subset_ball (c : α) : bounded s ↔ ∃r, s ⊆ closed_ball c r :=
begin
  split; rintro ⟨C, hC⟩,
  { cases s.eq_empty_or_nonempty with h h,
    { subst s, exact ⟨0, by simp⟩ },
    { rcases h with ⟨x, hx⟩,
      exact ⟨C + dist x c, λ y hy, calc
        dist y c ≤ dist y x + dist x c : dist_triangle _ _ _
            ... ≤ C + dist x c : add_le_add_right (hC y x hy hx) _⟩ } },
  { exact bounded_closed_ball.subset hC }
end

/-- The union of two bounded sets is bounded iff each of the sets is bounded -/
@[simp] lemma bounded_union :
  bounded (s ∪ t) ↔ bounded s ∧ bounded t :=
⟨λh, ⟨h.subset (by simp), h.subset (by simp)⟩,
begin
  rintro ⟨hs, ht⟩,
  refine bounded_iff_mem_bounded.2 (λ x _, _),
  rw bounded_iff_subset_ball x at hs ht ⊢,
  rcases hs with ⟨Cs, hCs⟩, rcases ht with ⟨Ct, hCt⟩,
  exact ⟨max Cs Ct, union_subset
    (subset.trans hCs $ closed_ball_subset_closed_ball $ le_max_left _ _)
    (subset.trans hCt $ closed_ball_subset_closed_ball $ le_max_right _ _)⟩,
end⟩

/-- A finite union of bounded sets is bounded -/
lemma bounded_bUnion {I : set β} {s : β → set α} (H : finite I) :
  bounded (⋃i∈I, s i) ↔ ∀i ∈ I, bounded (s i) :=
finite.induction_on H (by simp) $ λ x I _ _ IH,
by simp [or_imp_distrib, forall_and_distrib, IH]

/-- A compact set is bounded -/
lemma bounded_of_compact {s : set α} (h : compact s) : bounded s :=
-- We cover the compact set by finitely many balls of radius 1,
-- and then argue that a finite union of bounded sets is bounded
let ⟨t, ht, fint, subs⟩ := finite_cover_balls_of_compact h zero_lt_one in
bounded.subset subs $ (bounded_bUnion fint).2 $ λ i hi, bounded_ball

alias bounded_of_compact ← compact.bounded

/-- A finite set is bounded -/
lemma bounded_of_finite {s : set α} (h : finite s) : bounded s :=
h.compact.bounded

/-- A singleton is bounded -/
lemma bounded_singleton {x : α} : bounded ({x} : set α) :=
bounded_of_finite $ finite_singleton _

/-- Characterization of the boundedness of the range of a function -/
lemma bounded_range_iff {f : β → α} : bounded (range f) ↔ ∃C, ∀x y, dist (f x) (f y) ≤ C :=
exists_congr $ λ C, ⟨
  λ H x y, H _ _ ⟨x, rfl⟩ ⟨y, rfl⟩,
  by rintro H _ _ ⟨x, rfl⟩ ⟨y, rfl⟩; exact H x y⟩

/-- In a compact space, all sets are bounded -/
lemma bounded_of_compact_space [compact_space α] : bounded s :=
compact_univ.bounded.subset (subset_univ _)

/-- The Heine–Borel theorem:
In a proper space, a set is compact if and only if it is closed and bounded -/
lemma compact_iff_closed_bounded [proper_space α] :
  compact s ↔ is_closed s ∧ bounded s :=
⟨λ h, ⟨closed_of_compact _ h, h.bounded⟩, begin
  rintro ⟨hc, hb⟩,
  cases s.eq_empty_or_nonempty with h h, {simp [h, compact_empty]},
  rcases h with ⟨x, hx⟩,
  rcases (bounded_iff_subset_ball x).1 hb with ⟨r, hr⟩,
  exact compact_of_is_closed_subset (proper_space.compact_ball x r) hc hr
end⟩

/-- The image of a proper space under an expanding onto map is proper. -/
lemma proper_image_of_proper [proper_space α] [metric_space β] (f : α → β)
  (f_cont : continuous f) (hf : range f = univ) (C : ℝ)
  (hC : ∀x y, dist x y ≤ C * dist (f x) (f y)) : proper_space β :=
begin
  apply proper_space_of_compact_closed_ball_of_le 0 (λx₀ r hr, _),
  let K := f ⁻¹' (closed_ball x₀ r),
  have A : is_closed K :=
    continuous_iff_is_closed.1 f_cont (closed_ball x₀ r) (is_closed_ball),
  have B : bounded K := ⟨max C 0 * (r + r), λx y hx hy, calc
    dist x y ≤ C * dist (f x) (f y) : hC x y
    ... ≤ max C 0 * dist (f x) (f y) : mul_le_mul_of_nonneg_right (le_max_left _ _) (dist_nonneg)
    ... ≤ max C 0 * (dist (f x) x₀ + dist (f y) x₀) :
      mul_le_mul_of_nonneg_left (dist_triangle_right (f x) (f y) x₀) (le_max_right _ _)
    ... ≤ max C 0 * (r + r) : begin
      simp only [mem_closed_ball, mem_preimage] at hx hy,
      exact mul_le_mul_of_nonneg_left (add_le_add hx hy) (le_max_right _ _)
    end⟩,
  have : compact K := compact_iff_closed_bounded.2 ⟨A, B⟩,
  have C : compact (f '' K) := this.image f_cont,
  have : f '' K = closed_ball x₀ r,
    by { rw image_preimage_eq_of_subset, rw hf, exact subset_univ _ },
  rwa this at C
end

end bounded

section diam
variables {s : set α} {x y z : α}

/-- The diameter of a set in a metric space. To get controllable behavior even when the diameter
should be infinite, we express it in terms of the emetric.diameter -/
def diam (s : set α) : ℝ := ennreal.to_real (emetric.diam s)

/-- The diameter of a set is always nonnegative -/
lemma diam_nonneg : 0 ≤ diam s := ennreal.to_real_nonneg

lemma diam_subsingleton (hs : s.subsingleton) : diam s = 0 :=
by simp only [diam, emetric.diam_subsingleton hs, ennreal.zero_to_real]

/-- The empty set has zero diameter -/
@[simp] lemma diam_empty : diam (∅ : set α) = 0 :=
diam_subsingleton subsingleton_empty

/-- A singleton has zero diameter -/
@[simp] lemma diam_singleton : diam ({x} : set α) = 0 :=
diam_subsingleton subsingleton_singleton

@[simp] lemma diam_pair : diam ({x, y} : set α) = dist x y :=
by simp only [diam, emetric.diam_pair, dist_edist]

@[simp] lemma diam_triple :
  metric.diam ({x, y, z} : set α) = max (dist x y) (max (dist y z) (dist x z)) :=
begin
  simp only [metric.diam, emetric.diam_triple, dist_edist],
  rw [ennreal.to_real_max, ennreal.to_real_max];
    apply_rules [ne_of_lt, edist_lt_top, max_lt]
end

/-- If the distance between any two points in a set is bounded by some constant `C`,
then `ennreal.of_real C`  bounds the emetric diameter of this set. -/
lemma ediam_le_of_forall_dist_le {C : ℝ} (h : ∀ (x ∈ s) (y ∈ s), dist x y ≤ C) :
  emetric.diam s ≤ ennreal.of_real C :=
emetric.diam_le_of_forall_edist_le $
λ x hx y hy, (edist_dist x y).symm ▸ ennreal.of_real_le_of_real (h x hx y hy)

/-- If the distance between any two points in a set is bounded by some non-negative constant,
this constant bounds the diameter. -/
lemma diam_le_of_forall_dist_le {C : ℝ} (h₀ : 0 ≤ C) (h : ∀ (x ∈ s) (y ∈ s), dist x y ≤ C) :
  diam s ≤ C :=
ennreal.to_real_le_of_le_of_real h₀ (ediam_le_of_forall_dist_le h)

/-- If the distance between any two points in a nonempty set is bounded by some constant,
this constant bounds the diameter. -/
lemma diam_le_of_forall_dist_le_of_nonempty (hs : s.nonempty) {C : ℝ}
  (h : ∀ (x ∈ s) (y ∈ s), dist x y ≤ C) : diam s ≤ C :=
have h₀ : 0 ≤ C, from let ⟨x, hx⟩ := hs in le_trans dist_nonneg (h x hx x hx),
diam_le_of_forall_dist_le h₀ h

/-- The distance between two points in a set is controlled by the diameter of the set. -/
lemma dist_le_diam_of_mem' (h : emetric.diam s ≠ ⊤) (hx : x ∈ s) (hy : y ∈ s) :
  dist x y ≤ diam s :=
begin
  rw [diam, dist_edist],
  rw ennreal.to_real_le_to_real (edist_ne_top _ _) h,
  exact emetric.edist_le_diam_of_mem hx hy
end

/-- Characterize the boundedness of a set in terms of the finiteness of its emetric.diameter. -/
lemma bounded_iff_ediam_ne_top : bounded s ↔ emetric.diam s ≠ ⊤ :=
iff.intro
  (λ ⟨C, hC⟩, ne_top_of_le_ne_top ennreal.of_real_ne_top
    (ediam_le_of_forall_dist_le $ λ x hx y hy, hC x y hx hy))
  (λ h, ⟨diam s, λ x y hx hy, dist_le_diam_of_mem' h hx hy⟩)

lemma bounded.ediam_ne_top (h : bounded s) : emetric.diam s ≠ ⊤ :=
bounded_iff_ediam_ne_top.1 h

/-- The distance between two points in a set is controlled by the diameter of the set. -/
lemma dist_le_diam_of_mem (h : bounded s) (hx : x ∈ s) (hy : y ∈ s) : dist x y ≤ diam s :=
dist_le_diam_of_mem' h.ediam_ne_top hx hy

/-- An unbounded set has zero diameter. If you would prefer to get the value ∞, use `emetric.diam`.
This lemma makes it possible to avoid side conditions in some situations -/
lemma diam_eq_zero_of_unbounded (h : ¬(bounded s)) : diam s = 0 :=
begin
  simp only [bounded_iff_ediam_ne_top, not_not, ne.def] at h,
  simp [diam, h]
end

/-- If `s ⊆ t`, then the diameter of `s` is bounded by that of `t`, provided `t` is bounded. -/
lemma diam_mono {s t : set α} (h : s ⊆ t) (ht : bounded t) : diam s ≤ diam t :=
begin
  unfold diam,
  rw ennreal.to_real_le_to_real (bounded.subset h ht).ediam_ne_top ht.ediam_ne_top,
  exact emetric.diam_mono h
end

/-- The diameter of a union is controlled by the sum of the diameters, and the distance between
any two points in each of the sets. This lemma is true without any side condition, since it is
obviously true if `s ∪ t` is unbounded. -/
lemma diam_union {t : set α} (xs : x ∈ s) (yt : y ∈ t) : diam (s ∪ t) ≤ diam s + dist x y + diam t :=
begin
  classical, by_cases H : bounded (s ∪ t),
  { have hs : bounded s, from H.subset (subset_union_left _ _),
    have ht : bounded t, from H.subset (subset_union_right _ _),
    rw [bounded_iff_ediam_ne_top] at H hs ht,
    rw [dist_edist, diam, diam, diam, ← ennreal.to_real_add, ← ennreal.to_real_add,
      ennreal.to_real_le_to_real];
      repeat { apply ennreal.add_ne_top.2; split }; try { assumption };
      try { apply edist_ne_top },
    exact emetric.diam_union xs yt },
  { rw [diam_eq_zero_of_unbounded H],
    apply_rules [add_nonneg, diam_nonneg, dist_nonneg] }
end

/-- If two sets intersect, the diameter of the union is bounded by the sum of the diameters. -/
lemma diam_union' {t : set α} (h : (s ∩ t).nonempty) : diam (s ∪ t) ≤ diam s + diam t :=
begin
  rcases h with ⟨x, ⟨xs, xt⟩⟩,
  simpa using diam_union xs xt
end

/-- The diameter of a closed ball of radius `r` is at most `2 r`. -/
lemma diam_closed_ball {r : ℝ} (h : r ≥ 0) : diam (closed_ball x r) ≤ 2 * r :=
diam_le_of_forall_dist_le (mul_nonneg (le_of_lt two_pos) h) $ λa ha b hb, calc
  dist a b ≤ dist a x + dist b x : dist_triangle_right _ _ _
  ... ≤ r + r : add_le_add ha hb
  ... = 2 * r : by simp [mul_two, mul_comm]

/-- The diameter of a ball of radius `r` is at most `2 r`. -/
lemma diam_ball {r : ℝ} (h : r ≥ 0) : diam (ball x r) ≤ 2 * r :=
le_trans (diam_mono ball_subset_closed_ball bounded_closed_ball) (diam_closed_ball h)

end diam

end metric