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/-
Copyright (c) 2020 Scott Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johan Commelin, Scott Morrison
-/
import analysis.convex.combination
import linear_algebra.affine_space.independent
import tactic.field_simp

/-!
# Carathéodory's convexity theorem

Convex hull can be regarded as a refinement of affine span. Both are closure operators but whereas
convex hull takes values in the lattice of convex subsets, affine span takes values in the much
coarser sublattice of affine subspaces.

The cost of this refinement is that one no longer has bases. However Carathéodory's convexity
theorem offers some compensation. Given a set `s` together with a point `x` in its convex hull,
Carathéodory says that one may find an affine-independent family of elements `s` whose convex hull
contains `x`. Thus the difference from the case of affine span is that the affine-independent family
depends on `x`.

In particular, in finite dimensions Carathéodory's theorem implies that the convex hull of a set `s`
in `𝕜ᵈ` is the union of the convex hulls of the `(d + 1)`-tuples in `s`.

## Main results

* `convex_hull_eq_union`: Carathéodory's convexity theorem

## Implementation details

This theorem was formalized as part of the Sphere Eversion project.

## Tags
convex hull, caratheodory

-/

open set finset
open_locale big_operators

universes u
variables {𝕜 : Type*} {E : Type u} [linear_ordered_field 𝕜] [add_comm_group E] [module 𝕜 E]

namespace caratheodory

/-- If `x` is in the convex hull of some finset `t` whose elements are not affine-independent,
then it is in the convex hull of a strict subset of `t`. -/
lemma mem_convex_hull_erase [decidable_eq E] {t : finset E}
  (h : ¬ affine_independent 𝕜 (coe : t → E)) {x : E} (m : x ∈ convex_hull 𝕜 (↑t : set E)) :
  ∃ (y : (↑t : set E)), x ∈ convex_hull 𝕜 (↑(t.erase y) : set E) :=
begin
  simp only [finset.convex_hull_eq, mem_set_of_eq] at m ⊢,
  obtain ⟨f, fpos, fsum, rfl⟩ := m,
  obtain ⟨g, gcombo, gsum, gpos⟩ := exists_nontrivial_relation_sum_zero_of_not_affine_ind h,
  replace gpos := exists_pos_of_sum_zero_of_exists_nonzero g gsum gpos,
  clear h,
  let s := @finset.filter _ (λ z, 0 < g z) (λ _, linear_order.decidable_lt _ _) t,
  obtain ⟨i₀, mem, w⟩ : ∃ i₀ ∈ s, ∀ i ∈ s, f i₀ / g i₀ ≤ f i / g i,
  { apply s.exists_min_image (λ z, f z / g z),
    obtain ⟨x, hx, hgx⟩ : ∃ x ∈ t, 0 < g x := gpos,
    exact ⟨x, mem_filter.mpr ⟨hx, hgx⟩⟩ },
  have hg   : 0 < g i₀ := by { rw mem_filter at mem, exact mem.2 },
  have hi₀  : i₀ ∈ t   := filter_subset _ _ mem,
  let  k    : E → 𝕜    := λ z, f z - (f i₀ / g i₀) * g z,
  have hk   : k i₀ = 0 := by field_simp [k, ne_of_gt hg],
  have ksum : ∑ e in t.erase i₀, k e = 1,
  { calc ∑ e in t.erase i₀, k e = ∑ e in t, k e :
      by conv_rhs { rw [← insert_erase hi₀, sum_insert (not_mem_erase i₀ t), hk, zero_add] }
    ... = ∑ e in t, (f e - f i₀ / g i₀ * g e) : rfl
    ... = 1 : by rw [sum_sub_distrib, fsum, ← mul_sum, gsum, mul_zero, sub_zero] },
  refine ⟨⟨i₀, hi₀⟩, k, _, by convert ksum, _⟩,
  { simp only [and_imp, sub_nonneg, mem_erase, ne.def, subtype.coe_mk],
    intros e hei₀ het,
    by_cases hes : e ∈ s,
    { have hge : 0 < g e := by { rw mem_filter at hes, exact hes.2 },
      rw ← le_div_iff hge,
      exact w _ hes },
    { calc _ ≤ 0   : mul_nonpos_of_nonneg_of_nonpos _ _ -- prove two goals below
         ... ≤ f e : fpos e het,
      { apply div_nonneg (fpos i₀ (mem_of_subset (filter_subset _ t) mem)) (le_of_lt hg) },
      { simpa only [mem_filter, het, true_and, not_lt] using hes } } },
  { simp only [subtype.coe_mk, center_mass_eq_of_sum_1 _ id ksum, id],
    calc ∑ e in t.erase i₀, k e • e = ∑ e in t, k e • e : sum_erase _ (by rw [hk, zero_smul])
    ... = ∑ e in t, (f e - f i₀ / g i₀ * g e) • e : rfl
    ... = t.center_mass f id : _,
    simp only [sub_smul, mul_smul, sum_sub_distrib, ← smul_sum, gcombo, smul_zero,
      sub_zero, center_mass, fsum, inv_one, one_smul, id.def] }
end

variables {s : set E} {x : E} (hx : x ∈ convex_hull 𝕜 s)
include hx

/-- Given a point `x` in the convex hull of a set `s`, this is a finite subset of `s` of minimum
cardinality, whose convex hull contains `x`. -/
noncomputable def min_card_finset_of_mem_convex_hull : finset E :=
function.argmin_on finset.card nat.lt_wf { t | ↑t ⊆ s ∧ x ∈ convex_hull 𝕜 (t : set E) }
(by simpa only [convex_hull_eq_union_convex_hull_finite_subsets s, exists_prop, mem_Union] using hx)

lemma min_card_finset_of_mem_convex_hull_subseteq : ↑(min_card_finset_of_mem_convex_hull hx) ⊆ s :=
(function.argmin_on_mem _ _ { t : finset E | ↑t ⊆ s ∧ x ∈ convex_hull 𝕜 (t : set E) } _).1

lemma mem_min_card_finset_of_mem_convex_hull :
  x ∈ convex_hull 𝕜 (min_card_finset_of_mem_convex_hull hx : set E) :=
(function.argmin_on_mem _ _ { t : finset E | ↑t ⊆ s ∧ x ∈ convex_hull 𝕜 (t : set E) } _).2

lemma min_card_finset_of_mem_convex_hull_nonempty :
  (min_card_finset_of_mem_convex_hull hx).nonempty :=
begin
  rw [← finset.coe_nonempty, ← @convex_hull_nonempty_iff 𝕜],
  exact ⟨x, mem_min_card_finset_of_mem_convex_hull hx⟩,
end

lemma min_card_finset_of_mem_convex_hull_card_le_card
  {t : finset E} (ht₁ : ↑t ⊆ s) (ht₂ : x ∈ convex_hull 𝕜 (t : set E)) :
  (min_card_finset_of_mem_convex_hull hx).card ≤ t.card :=
function.argmin_on_le _ _ _ ⟨ht₁, ht₂⟩

lemma affine_independent_min_card_finset_of_mem_convex_hull :
  affine_independent 𝕜 (coe : min_card_finset_of_mem_convex_hull hx → E) :=
begin
  let k := (min_card_finset_of_mem_convex_hull hx).card - 1,
  have hk : (min_card_finset_of_mem_convex_hull hx).card = k + 1,
  { exact (nat.succ_pred_eq_of_pos
      (finset.card_pos.mpr (min_card_finset_of_mem_convex_hull_nonempty hx))).symm },
  classical,
  by_contra,
  obtain ⟨p, hp⟩ := mem_convex_hull_erase h (mem_min_card_finset_of_mem_convex_hull hx),
  have contra := min_card_finset_of_mem_convex_hull_card_le_card hx (set.subset.trans
    (finset.erase_subset ↑p (min_card_finset_of_mem_convex_hull hx))
    (min_card_finset_of_mem_convex_hull_subseteq hx)) hp,
  rw [← not_lt] at contra,
  apply contra,
  erw [card_erase_of_mem p.2, hk],
  exact lt_add_one _,
end

end caratheodory

variables {s : set E}

/-- **Carathéodory's convexity theorem** -/
lemma convex_hull_eq_union :
  convex_hull 𝕜 s =
  ⋃ (t : finset E) (hss : ↑t ⊆ s) (hai : affine_independent 𝕜 (coe : t → E)), convex_hull 𝕜 ↑t :=
begin
  apply set.subset.antisymm,
  { intros x hx,
    simp only [exists_prop, set.mem_Union],
    exact ⟨caratheodory.min_card_finset_of_mem_convex_hull hx,
           caratheodory.min_card_finset_of_mem_convex_hull_subseteq hx,
           caratheodory.affine_independent_min_card_finset_of_mem_convex_hull hx,
           caratheodory.mem_min_card_finset_of_mem_convex_hull hx⟩ },
  { iterate 3 { convert set.Union_subset _, intro },
    exact convex_hull_mono ‹_› }
end

/-- A more explicit version of `convex_hull_eq_union`. -/
theorem eq_pos_convex_span_of_mem_convex_hull {x : E} (hx : x ∈ convex_hull 𝕜 s) :
  ∃ (ι : Sort (u+1)) (_ : fintype ι), by exactI ∃ (z : ι → E) (w : ι → 𝕜)
    (hss : set.range z ⊆ s) (hai : affine_independent 𝕜 z)
    (hw : ∀ i, 0 < w i), ∑ i, w i = 1 ∧ ∑ i, w i • z i = x :=
begin
  rw convex_hull_eq_union at hx,
  simp only [exists_prop, set.mem_Union] at hx,
  obtain ⟨t, ht₁, ht₂, ht₃⟩ := hx,
  simp only [t.convex_hull_eq, exists_prop, set.mem_set_of_eq] at ht₃,
  obtain ⟨w, hw₁, hw₂, hw₃⟩ := ht₃,
  let t' := t.filter (λ i, w i ≠ 0),
  refine ⟨t', t'.fintype_coe_sort, (coe : t' → E), w ∘ (coe : t' → E), _, _, _, _, _⟩,
  { rw subtype.range_coe_subtype, exact subset.trans (finset.filter_subset _ t) ht₁ },
  { exact ht₂.comp_embedding
      ⟨_, inclusion_injective (finset.filter_subset (λ i, w i ≠ 0) t)⟩ },
  { exact λ i, (hw₁ _ (finset.mem_filter.mp i.2).1).lt_of_ne
      (finset.mem_filter.mp i.property).2.symm },
  { erw [finset.sum_attach, finset.sum_filter_ne_zero, hw₂] },
  { change ∑ (i : t') in t'.attach, (λ e, w e • e) ↑i = x,
    erw [finset.sum_attach, finset.sum_filter_of_ne],
    { rw t.center_mass_eq_of_sum_1 id hw₂ at hw₃, exact hw₃ },
    { intros e he hwe contra, apply hwe, rw [contra, zero_smul] } }
end