(* Title: HOL/Analysis/Convex_Euclidean_Space.thy
Author: L C Paulson, University of Cambridge
Author: Robert Himmelmann, TU Muenchen
Author: Bogdan Grechuk, University of Edinburgh
Author: Armin Heller, TU Muenchen
Author: Johannes Hoelzl, TU Muenchen
*)
section \<open>Convex Sets and Functions on (Normed) Euclidean Spaces\<close>
theory Convex_Euclidean_Space
imports
Convex
Topology_Euclidean_Space
begin
subsection\<^marker>\<open>tag unimportant\<close> \<open>Topological Properties of Convex Sets and Functions\<close>
lemma convex_supp_sum:
assumes "convex S" and 1: "supp_sum u I = 1"
and "\<And>i. i \<in> I \<Longrightarrow> 0 \<le> u i \<and> (u i = 0 \<or> f i \<in> S)"
shows "supp_sum (\<lambda>i. u i *\<^sub>R f i) I \<in> S"
proof -
have fin: "finite {i \<in> I. u i \<noteq> 0}"
using 1 sum.infinite by (force simp: supp_sum_def support_on_def)
then have eq: "supp_sum (\<lambda>i. u i *\<^sub>R f i) I = sum (\<lambda>i. u i *\<^sub>R f i) {i \<in> I. u i \<noteq> 0}"
by (force intro: sum.mono_neutral_left simp: supp_sum_def support_on_def)
show ?thesis
apply (simp add: eq)
apply (rule convex_sum [OF fin \<open>convex S\<close>])
using 1 assms apply (auto simp: supp_sum_def support_on_def)
done
qed
lemma closure_bounded_linear_image_subset:
assumes f: "bounded_linear f"
shows "f ` closure S \<subseteq> closure (f ` S)"
using linear_continuous_on [OF f] closed_closure closure_subset
by (rule image_closure_subset)
lemma closure_linear_image_subset:
fixes f :: "'m::euclidean_space \<Rightarrow> 'n::real_normed_vector"
assumes "linear f"
shows "f ` (closure S) \<subseteq> closure (f ` S)"
using assms unfolding linear_conv_bounded_linear
by (rule closure_bounded_linear_image_subset)
lemma closed_injective_linear_image:
fixes f :: "'a::euclidean_space \<Rightarrow> 'b::euclidean_space"
assumes S: "closed S" and f: "linear f" "inj f"
shows "closed (f ` S)"
proof -
obtain g where g: "linear g" "g \<circ> f = id"
using linear_injective_left_inverse [OF f] by blast
then have confg: "continuous_on (range f) g"
using linear_continuous_on linear_conv_bounded_linear by blast
have [simp]: "g ` f ` S = S"
using g by (simp add: image_comp)
have cgf: "closed (g ` f ` S)"
by (simp add: \<open>g \<circ> f = id\<close> S image_comp)
have [simp]: "(range f \<inter> g -` S) = f ` S"
using g unfolding o_def id_def image_def by auto metis+
show ?thesis
proof (rule closedin_closed_trans [of "range f"])
show "closedin (top_of_set (range f)) (f ` S)"
using continuous_closedin_preimage [OF confg cgf] by simp
show "closed (range f)"
apply (rule closed_injective_image_subspace)
using f apply (auto simp: linear_linear linear_injective_0)
done
qed
qed
lemma closed_injective_linear_image_eq:
fixes f :: "'a::euclidean_space \<Rightarrow> 'b::euclidean_space"
assumes f: "linear f" "inj f"
shows "(closed(image f s) \<longleftrightarrow> closed s)"
by (metis closed_injective_linear_image closure_eq closure_linear_image_subset closure_subset_eq f(1) f(2) inj_image_subset_iff)
lemma closure_injective_linear_image:
fixes f :: "'a::euclidean_space \<Rightarrow> 'b::euclidean_space"
shows "\<lbrakk>linear f; inj f\<rbrakk> \<Longrightarrow> f ` (closure S) = closure (f ` S)"
apply (rule subset_antisym)
apply (simp add: closure_linear_image_subset)
by (simp add: closure_minimal closed_injective_linear_image closure_subset image_mono)
lemma closure_bounded_linear_image:
fixes f :: "'a::euclidean_space \<Rightarrow> 'b::euclidean_space"
shows "\<lbrakk>linear f; bounded S\<rbrakk> \<Longrightarrow> f ` (closure S) = closure (f ` S)"
apply (rule subset_antisym, simp add: closure_linear_image_subset)
apply (rule closure_minimal, simp add: closure_subset image_mono)
by (meson bounded_closure closed_closure compact_continuous_image compact_eq_bounded_closed linear_continuous_on linear_conv_bounded_linear)
lemma closure_scaleR:
fixes S :: "'a::real_normed_vector set"
shows "((*\<^sub>R) c) ` (closure S) = closure (((*\<^sub>R) c) ` S)"
proof
show "((*\<^sub>R) c) ` (closure S) \<subseteq> closure (((*\<^sub>R) c) ` S)"
using bounded_linear_scaleR_right
by (rule closure_bounded_linear_image_subset)
show "closure (((*\<^sub>R) c) ` S) \<subseteq> ((*\<^sub>R) c) ` (closure S)"
by (intro closure_minimal image_mono closure_subset closed_scaling closed_closure)
qed
lemma sphere_eq_empty [simp]:
fixes a :: "'a::{real_normed_vector, perfect_space}"
shows "sphere a r = {} \<longleftrightarrow> r < 0"
by (auto simp: sphere_def dist_norm) (metis dist_norm le_less_linear vector_choose_dist)
lemma cone_closure:
fixes S :: "'a::real_normed_vector set"
assumes "cone S"
shows "cone (closure S)"
proof (cases "S = {}")
case True
then show ?thesis by auto
next
case False
then have "0 \<in> S \<and> (\<forall>c. c > 0 \<longrightarrow> (*\<^sub>R) c ` S = S)"
using cone_iff[of S] assms by auto
then have "0 \<in> closure S \<and> (\<forall>c. c > 0 \<longrightarrow> (*\<^sub>R) c ` closure S = closure S)"
using closure_subset by (auto simp: closure_scaleR)
then show ?thesis
using False cone_iff[of "closure S"] by auto
qed
corollary component_complement_connected:
fixes S :: "'a::real_normed_vector set"
assumes "connected S" "C \<in> components (-S)"
shows "connected(-C)"
using component_diff_connected [of S UNIV] assms
by (auto simp: Compl_eq_Diff_UNIV)
proposition clopen:
fixes S :: "'a :: real_normed_vector set"
shows "closed S \<and> open S \<longleftrightarrow> S = {} \<or> S = UNIV"
by (force intro!: connected_UNIV [unfolded connected_clopen, rule_format])
corollary compact_open:
fixes S :: "'a :: euclidean_space set"
shows "compact S \<and> open S \<longleftrightarrow> S = {}"
by (auto simp: compact_eq_bounded_closed clopen)
corollary finite_imp_not_open:
fixes S :: "'a::{real_normed_vector, perfect_space} set"
shows "\<lbrakk>finite S; open S\<rbrakk> \<Longrightarrow> S={}"
using clopen [of S] finite_imp_closed not_bounded_UNIV by blast
corollary empty_interior_finite:
fixes S :: "'a::{real_normed_vector, perfect_space} set"
shows "finite S \<Longrightarrow> interior S = {}"
by (metis interior_subset finite_subset open_interior [of S] finite_imp_not_open)
text \<open>Balls, being convex, are connected.\<close>
lemma convex_local_global_minimum:
fixes s :: "'a::real_normed_vector set"
assumes "e > 0"
and "convex_on s f"
and "ball x e \<subseteq> s"
and "\<forall>y\<in>ball x e. f x \<le> f y"
shows "\<forall>y\<in>s. f x \<le> f y"
proof (rule ccontr)
have "x \<in> s" using assms(1,3) by auto
assume "\<not> ?thesis"
then obtain y where "y\<in>s" and y: "f x > f y" by auto
then have xy: "0 < dist x y" by auto
then obtain u where "0 < u" "u \<le> 1" and u: "u < e / dist x y"
using field_lbound_gt_zero[of 1 "e / dist x y"] xy \<open>e>0\<close> by auto
then have "f ((1-u) *\<^sub>R x + u *\<^sub>R y) \<le> (1-u) * f x + u * f y"
using \<open>x\<in>s\<close> \<open>y\<in>s\<close>
using assms(2)[unfolded convex_on_def,
THEN bspec[where x=x], THEN bspec[where x=y], THEN spec[where x="1-u"]]
by auto
moreover
have *: "x - ((1 - u) *\<^sub>R x + u *\<^sub>R y) = u *\<^sub>R (x - y)"
by (simp add: algebra_simps)
have "(1 - u) *\<^sub>R x + u *\<^sub>R y \<in> ball x e"
unfolding mem_ball dist_norm
unfolding * and norm_scaleR and abs_of_pos[OF \<open>0<u\<close>]
unfolding dist_norm[symmetric]
using u
unfolding pos_less_divide_eq[OF xy]
by auto
then have "f x \<le> f ((1 - u) *\<^sub>R x + u *\<^sub>R y)"
using assms(4) by auto
ultimately show False
using mult_strict_left_mono[OF y \<open>u>0\<close>]
unfolding left_diff_distrib
by auto
qed
lemma convex_ball [iff]:
fixes x :: "'a::real_normed_vector"
shows "convex (ball x e)"
proof (auto simp: convex_def)
fix y z
assume yz: "dist x y < e" "dist x z < e"
fix u v :: real
assume uv: "0 \<le> u" "0 \<le> v" "u + v = 1"
have "dist x (u *\<^sub>R y + v *\<^sub>R z) \<le> u * dist x y + v * dist x z"
using uv yz
using convex_on_dist [of "ball x e" x, unfolded convex_on_def,
THEN bspec[where x=y], THEN bspec[where x=z]]
by auto
then show "dist x (u *\<^sub>R y + v *\<^sub>R z) < e"
using convex_bound_lt[OF yz uv] by auto
qed
lemma convex_cball [iff]:
fixes x :: "'a::real_normed_vector"
shows "convex (cball x e)"
proof -
{
fix y z
assume yz: "dist x y \<le> e" "dist x z \<le> e"
fix u v :: real
assume uv: "0 \<le> u" "0 \<le> v" "u + v = 1"
have "dist x (u *\<^sub>R y + v *\<^sub>R z) \<le> u * dist x y + v * dist x z"
using uv yz
using convex_on_dist [of "cball x e" x, unfolded convex_on_def,
THEN bspec[where x=y], THEN bspec[where x=z]]
by auto
then have "dist x (u *\<^sub>R y + v *\<^sub>R z) \<le> e"
using convex_bound_le[OF yz uv] by auto
}
then show ?thesis by (auto simp: convex_def Ball_def)
qed
lemma connected_ball [iff]:
fixes x :: "'a::real_normed_vector"
shows "connected (ball x e)"
using convex_connected convex_ball by auto
lemma connected_cball [iff]:
fixes x :: "'a::real_normed_vector"
shows "connected (cball x e)"
using convex_connected convex_cball by auto
lemma bounded_convex_hull:
fixes s :: "'a::real_normed_vector set"
assumes "bounded s"
shows "bounded (convex hull s)"
proof -
from assms obtain B where B: "\<forall>x\<in>s. norm x \<le> B"
unfolding bounded_iff by auto
show ?thesis
apply (rule bounded_subset[OF bounded_cball, of _ 0 B])
unfolding subset_hull[of convex, OF convex_cball]
unfolding subset_eq mem_cball dist_norm using B
apply auto
done
qed
lemma finite_imp_bounded_convex_hull:
fixes s :: "'a::real_normed_vector set"
shows "finite s \<Longrightarrow> bounded (convex hull s)"
using bounded_convex_hull finite_imp_bounded
by auto
lemma aff_dim_cball:
fixes a :: "'n::euclidean_space"
assumes "e > 0"
shows "aff_dim (cball a e) = int (DIM('n))"
proof -
have "(\<lambda>x. a + x) ` (cball 0 e) \<subseteq> cball a e"
unfolding cball_def dist_norm by auto
then have "aff_dim (cball (0 :: 'n::euclidean_space) e) \<le> aff_dim (cball a e)"
using aff_dim_translation_eq[of a "cball 0 e"]
aff_dim_subset[of "(+) a ` cball 0 e" "cball a e"]
by auto
moreover have "aff_dim (cball (0 :: 'n::euclidean_space) e) = int (DIM('n))"
using hull_inc[of "(0 :: 'n::euclidean_space)" "cball 0 e"]
centre_in_cball[of "(0 :: 'n::euclidean_space)"] assms
by (simp add: dim_cball[of e] aff_dim_zero[of "cball 0 e"])
ultimately show ?thesis
using aff_dim_le_DIM[of "cball a e"] by auto
qed
lemma aff_dim_open:
fixes S :: "'n::euclidean_space set"
assumes "open S"
and "S \<noteq> {}"
shows "aff_dim S = int (DIM('n))"
proof -
obtain x where "x \<in> S"
using assms by auto
then obtain e where e: "e > 0" "cball x e \<subseteq> S"
using open_contains_cball[of S] assms by auto
then have "aff_dim (cball x e) \<le> aff_dim S"
using aff_dim_subset by auto
with e show ?thesis
using aff_dim_cball[of e x] aff_dim_le_DIM[of S] by auto
qed
lemma low_dim_interior:
fixes S :: "'n::euclidean_space set"
assumes "\<not> aff_dim S = int (DIM('n))"
shows "interior S = {}"
proof -
have "aff_dim(interior S) \<le> aff_dim S"
using interior_subset aff_dim_subset[of "interior S" S] by auto
then show ?thesis
using aff_dim_open[of "interior S"] aff_dim_le_DIM[of S] assms by auto
qed
corollary empty_interior_lowdim:
fixes S :: "'n::euclidean_space set"
shows "dim S < DIM ('n) \<Longrightarrow> interior S = {}"
by (metis low_dim_interior affine_hull_UNIV dim_affine_hull less_not_refl dim_UNIV)
corollary aff_dim_nonempty_interior:
fixes S :: "'a::euclidean_space set"
shows "interior S \<noteq> {} \<Longrightarrow> aff_dim S = DIM('a)"
by (metis low_dim_interior)
subsection \<open>Relative interior of a set\<close>
definition\<^marker>\<open>tag important\<close> "rel_interior S =
{x. \<exists>T. openin (top_of_set (affine hull S)) T \<and> x \<in> T \<and> T \<subseteq> S}"
lemma rel_interior_mono:
"\<lbrakk>S \<subseteq> T; affine hull S = affine hull T\<rbrakk>
\<Longrightarrow> (rel_interior S) \<subseteq> (rel_interior T)"
by (auto simp: rel_interior_def)
lemma rel_interior_maximal:
"\<lbrakk>T \<subseteq> S; openin(top_of_set (affine hull S)) T\<rbrakk> \<Longrightarrow> T \<subseteq> (rel_interior S)"
by (auto simp: rel_interior_def)
lemma rel_interior:
"rel_interior S = {x \<in> S. \<exists>T. open T \<and> x \<in> T \<and> T \<inter> affine hull S \<subseteq> S}"
unfolding rel_interior_def[of S] openin_open[of "affine hull S"]
apply auto
proof -
fix x T
assume *: "x \<in> S" "open T" "x \<in> T" "T \<inter> affine hull S \<subseteq> S"
then have **: "x \<in> T \<inter> affine hull S"
using hull_inc by auto
show "\<exists>Tb. (\<exists>Ta. open Ta \<and> Tb = affine hull S \<inter> Ta) \<and> x \<in> Tb \<and> Tb \<subseteq> S"
apply (rule_tac x = "T \<inter> (affine hull S)" in exI)
using * **
apply auto
done
qed
lemma mem_rel_interior: "x \<in> rel_interior S \<longleftrightarrow> (\<exists>T. open T \<and> x \<in> T \<inter> S \<and> T \<inter> affine hull S \<subseteq> S)"
by (auto simp: rel_interior)
lemma mem_rel_interior_ball:
"x \<in> rel_interior S \<longleftrightarrow> x \<in> S \<and> (\<exists>e. e > 0 \<and> ball x e \<inter> affine hull S \<subseteq> S)"
apply (simp add: rel_interior, safe)
apply (force simp: open_contains_ball)
apply (rule_tac x = "ball x e" in exI, simp)
done
lemma rel_interior_ball:
"rel_interior S = {x \<in> S. \<exists>e. e > 0 \<and> ball x e \<inter> affine hull S \<subseteq> S}"
using mem_rel_interior_ball [of _ S] by auto
lemma mem_rel_interior_cball:
"x \<in> rel_interior S \<longleftrightarrow> x \<in> S \<and> (\<exists>e. e > 0 \<and> cball x e \<inter> affine hull S \<subseteq> S)"
apply (simp add: rel_interior, safe)
apply (force simp: open_contains_cball)
apply (rule_tac x = "ball x e" in exI)
apply (simp add: subset_trans [OF ball_subset_cball], auto)
done
lemma rel_interior_cball:
"rel_interior S = {x \<in> S. \<exists>e. e > 0 \<and> cball x e \<inter> affine hull S \<subseteq> S}"
using mem_rel_interior_cball [of _ S] by auto
lemma rel_interior_empty [simp]: "rel_interior {} = {}"
by (auto simp: rel_interior_def)
lemma affine_hull_sing [simp]: "affine hull {a :: 'n::euclidean_space} = {a}"
by (metis affine_hull_eq affine_sing)
lemma rel_interior_sing [simp]:
fixes a :: "'n::euclidean_space" shows "rel_interior {a} = {a}"
apply (auto simp: rel_interior_ball)
apply (rule_tac x=1 in exI, force)
done
lemma subset_rel_interior:
fixes S T :: "'n::euclidean_space set"
assumes "S \<subseteq> T"
and "affine hull S = affine hull T"
shows "rel_interior S \<subseteq> rel_interior T"
using assms by (auto simp: rel_interior_def)
lemma rel_interior_subset: "rel_interior S \<subseteq> S"
by (auto simp: rel_interior_def)
lemma rel_interior_subset_closure: "rel_interior S \<subseteq> closure S"
using rel_interior_subset by (auto simp: closure_def)
lemma interior_subset_rel_interior: "interior S \<subseteq> rel_interior S"
by (auto simp: rel_interior interior_def)
lemma interior_rel_interior:
fixes S :: "'n::euclidean_space set"
assumes "aff_dim S = int(DIM('n))"
shows "rel_interior S = interior S"
proof -
have "affine hull S = UNIV"
using assms affine_hull_UNIV[of S] by auto
then show ?thesis
unfolding rel_interior interior_def by auto
qed
lemma rel_interior_interior:
fixes S :: "'n::euclidean_space set"
assumes "affine hull S = UNIV"
shows "rel_interior S = interior S"
using assms unfolding rel_interior interior_def by auto
lemma rel_interior_open:
fixes S :: "'n::euclidean_space set"
assumes "open S"
shows "rel_interior S = S"
by (metis assms interior_eq interior_subset_rel_interior rel_interior_subset set_eq_subset)
lemma interior_ball [simp]: "interior (ball x e) = ball x e"
by (simp add: interior_open)
lemma interior_rel_interior_gen:
fixes S :: "'n::euclidean_space set"
shows "interior S = (if aff_dim S = int(DIM('n)) then rel_interior S else {})"
by (metis interior_rel_interior low_dim_interior)
lemma rel_interior_nonempty_interior:
fixes S :: "'n::euclidean_space set"
shows "interior S \<noteq> {} \<Longrightarrow> rel_interior S = interior S"
by (metis interior_rel_interior_gen)
lemma affine_hull_nonempty_interior:
fixes S :: "'n::euclidean_space set"
shows "interior S \<noteq> {} \<Longrightarrow> affine hull S = UNIV"
by (metis affine_hull_UNIV interior_rel_interior_gen)
lemma rel_interior_affine_hull [simp]:
fixes S :: "'n::euclidean_space set"
shows "rel_interior (affine hull S) = affine hull S"
proof -
have *: "rel_interior (affine hull S) \<subseteq> affine hull S"
using rel_interior_subset by auto
{
fix x
assume x: "x \<in> affine hull S"
define e :: real where "e = 1"
then have "e > 0" "ball x e \<inter> affine hull (affine hull S) \<subseteq> affine hull S"
using hull_hull[of _ S] by auto
then have "x \<in> rel_interior (affine hull S)"
using x rel_interior_ball[of "affine hull S"] by auto
}
then show ?thesis using * by auto
qed
lemma rel_interior_UNIV [simp]: "rel_interior (UNIV :: ('n::euclidean_space) set) = UNIV"
by (metis open_UNIV rel_interior_open)
lemma rel_interior_convex_shrink:
fixes S :: "'a::euclidean_space set"
assumes "convex S"
and "c \<in> rel_interior S"
and "x \<in> S"
and "0 < e"
and "e \<le> 1"
shows "x - e *\<^sub>R (x - c) \<in> rel_interior S"
proof -
obtain d where "d > 0" and d: "ball c d \<inter> affine hull S \<subseteq> S"
using assms(2) unfolding mem_rel_interior_ball by auto
{
fix y
assume as: "dist (x - e *\<^sub>R (x - c)) y < e * d" "y \<in> affine hull S"
have *: "y = (1 - (1 - e)) *\<^sub>R ((1 / e) *\<^sub>R y - ((1 - e) / e) *\<^sub>R x) + (1 - e) *\<^sub>R x"
using \<open>e > 0\<close> by (auto simp: scaleR_left_diff_distrib scaleR_right_diff_distrib)
have "x \<in> affine hull S"
using assms hull_subset[of S] by auto
moreover have "1 / e + - ((1 - e) / e) = 1"
using \<open>e > 0\<close> left_diff_distrib[of "1" "(1-e)" "1/e"] by auto
ultimately have **: "(1 / e) *\<^sub>R y - ((1 - e) / e) *\<^sub>R x \<in> affine hull S"
using as affine_affine_hull[of S] mem_affine[of "affine hull S" y x "(1 / e)" "-((1 - e) / e)"]
by (simp add: algebra_simps)
have "dist c ((1 / e) *\<^sub>R y - ((1 - e) / e) *\<^sub>R x) = \<bar>1/e\<bar> * norm (e *\<^sub>R c - y + (1 - e) *\<^sub>R x)"
unfolding dist_norm norm_scaleR[symmetric]
apply (rule arg_cong[where f=norm])
using \<open>e > 0\<close>
apply (auto simp: euclidean_eq_iff[where 'a='a] field_simps inner_simps)
done
also have "\<dots> = \<bar>1/e\<bar> * norm (x - e *\<^sub>R (x - c) - y)"
by (auto intro!:arg_cong[where f=norm] simp add: algebra_simps)
also have "\<dots> < d"
using as[unfolded dist_norm] and \<open>e > 0\<close>
by (auto simp:pos_divide_less_eq[OF \<open>e > 0\<close>] mult.commute)
finally have "y \<in> S"
apply (subst *)
apply (rule assms(1)[unfolded convex_alt,rule_format])
apply (rule d[THEN subsetD])
unfolding mem_ball
using assms(3-5) **
apply auto
done
}
then have "ball (x - e *\<^sub>R (x - c)) (e*d) \<inter> affine hull S \<subseteq> S"
by auto
moreover have "e * d > 0"
using \<open>e > 0\<close> \<open>d > 0\<close> by simp
moreover have c: "c \<in> S"
using assms rel_interior_subset by auto
moreover from c have "x - e *\<^sub>R (x - c) \<in> S"
using convexD_alt[of S x c e]
apply (simp add: algebra_simps)
using assms
apply auto
done
ultimately show ?thesis
using mem_rel_interior_ball[of "x - e *\<^sub>R (x - c)" S] \<open>e > 0\<close> by auto
qed
lemma interior_real_atLeast [simp]:
fixes a :: real
shows "interior {a..} = {a<..}"
proof -
{
fix y
assume "a < y"
then have "y \<in> interior {a..}"
apply (simp add: mem_interior)
apply (rule_tac x="(y-a)" in exI)
apply (auto simp: dist_norm)
done
}
moreover
{
fix y
assume "y \<in> interior {a..}"
then obtain e where e: "e > 0" "cball y e \<subseteq> {a..}"
using mem_interior_cball[of y "{a..}"] by auto
moreover from e have "y - e \<in> cball y e"
by (auto simp: cball_def dist_norm)
ultimately have "a \<le> y - e" by blast
then have "a < y" using e by auto
}
ultimately show ?thesis by auto
qed
lemma continuous_ge_on_Ioo:
assumes "continuous_on {c..d} g" "\<And>x. x \<in> {c<..<d} \<Longrightarrow> g x \<ge> a" "c < d" "x \<in> {c..d}"
shows "g (x::real) \<ge> (a::real)"
proof-
from assms(3) have "{c..d} = closure {c<..<d}" by (rule closure_greaterThanLessThan[symmetric])
also from assms(2) have "{c<..<d} \<subseteq> (g -` {a..} \<inter> {c..d})" by auto
hence "closure {c<..<d} \<subseteq> closure (g -` {a..} \<inter> {c..d})" by (rule closure_mono)
also from assms(1) have "closed (g -` {a..} \<inter> {c..d})"
by (auto simp: continuous_on_closed_vimage)
hence "closure (g -` {a..} \<inter> {c..d}) = g -` {a..} \<inter> {c..d}" by simp
finally show ?thesis using \<open>x \<in> {c..d}\<close> by auto
qed
lemma interior_real_atMost [simp]:
fixes a :: real
shows "interior {..a} = {..<a}"
proof -
{
fix y
assume "a > y"
then have "y \<in> interior {..a}"
apply (simp add: mem_interior)
apply (rule_tac x="(a-y)" in exI)
apply (auto simp: dist_norm)
done
}
moreover
{
fix y
assume "y \<in> interior {..a}"
then obtain e where e: "e > 0" "cball y e \<subseteq> {..a}"
using mem_interior_cball[of y "{..a}"] by auto
moreover from e have "y + e \<in> cball y e"
by (auto simp: cball_def dist_norm)
ultimately have "a \<ge> y + e" by auto
then have "a > y" using e by auto
}
ultimately show ?thesis by auto
qed
lemma interior_atLeastAtMost_real [simp]: "interior {a..b} = {a<..<b :: real}"
proof-
have "{a..b} = {a..} \<inter> {..b}" by auto
also have "interior \<dots> = {a<..} \<inter> {..<b}"
by (simp add: interior_real_atLeast interior_real_atMost)
also have "\<dots> = {a<..<b}" by auto
finally show ?thesis .
qed
lemma interior_atLeastLessThan [simp]:
fixes a::real shows "interior {a..<b} = {a<..<b}"
by (metis atLeastLessThan_def greaterThanLessThan_def interior_atLeastAtMost_real interior_Int interior_interior interior_real_atLeast)
lemma interior_lessThanAtMost [simp]:
fixes a::real shows "interior {a<..b} = {a<..<b}"
by (metis atLeastAtMost_def greaterThanAtMost_def interior_atLeastAtMost_real interior_Int
interior_interior interior_real_atLeast)
lemma interior_greaterThanLessThan_real [simp]: "interior {a<..<b} = {a<..<b :: real}"
by (metis interior_atLeastAtMost_real interior_interior)
lemma frontier_real_atMost [simp]:
fixes a :: real
shows "frontier {..a} = {a}"
unfolding frontier_def by (auto simp: interior_real_atMost)
lemma frontier_real_atLeast [simp]: "frontier {a..} = {a::real}"
by (auto simp: frontier_def)
lemma frontier_real_greaterThan [simp]: "frontier {a<..} = {a::real}"
by (auto simp: interior_open frontier_def)
lemma frontier_real_lessThan [simp]: "frontier {..<a} = {a::real}"
by (auto simp: interior_open frontier_def)
lemma rel_interior_real_box [simp]:
fixes a b :: real
assumes "a < b"
shows "rel_interior {a .. b} = {a <..< b}"
proof -
have "box a b \<noteq> {}"
using assms
unfolding set_eq_iff
by (auto intro!: exI[of _ "(a + b) / 2"] simp: box_def)
then show ?thesis
using interior_rel_interior_gen[of "cbox a b", symmetric]
by (simp split: if_split_asm del: box_real add: box_real[symmetric] interior_cbox)
qed
lemma rel_interior_real_semiline [simp]:
fixes a :: real
shows "rel_interior {a..} = {a<..}"
proof -
have *: "{a<..} \<noteq> {}"
unfolding set_eq_iff by (auto intro!: exI[of _ "a + 1"])
then show ?thesis using interior_real_atLeast interior_rel_interior_gen[of "{a..}"]
by (auto split: if_split_asm)
qed
subsubsection \<open>Relative open sets\<close>
definition\<^marker>\<open>tag important\<close> "rel_open S \<longleftrightarrow> rel_interior S = S"
lemma rel_open: "rel_open S \<longleftrightarrow> openin (top_of_set (affine hull S)) S"
unfolding rel_open_def rel_interior_def
apply auto
using openin_subopen[of "top_of_set (affine hull S)" S]
apply auto
done
lemma openin_rel_interior: "openin (top_of_set (affine hull S)) (rel_interior S)"
apply (simp add: rel_interior_def)
apply (subst openin_subopen, blast)
done
lemma openin_set_rel_interior:
"openin (top_of_set S) (rel_interior S)"
by (rule openin_subset_trans [OF openin_rel_interior rel_interior_subset hull_subset])
lemma affine_rel_open:
fixes S :: "'n::euclidean_space set"
assumes "affine S"
shows "rel_open S"
unfolding rel_open_def
using assms rel_interior_affine_hull[of S] affine_hull_eq[of S]
by metis
lemma affine_closed:
fixes S :: "'n::euclidean_space set"
assumes "affine S"
shows "closed S"
proof -
{
assume "S \<noteq> {}"
then obtain L where L: "subspace L" "affine_parallel S L"
using assms affine_parallel_subspace[of S] by auto
then obtain a where a: "S = ((+) a ` L)"
using affine_parallel_def[of L S] affine_parallel_commut by auto
from L have "closed L" using closed_subspace by auto
then have "closed S"
using closed_translation a by auto
}
then show ?thesis by auto
qed
lemma closure_affine_hull:
fixes S :: "'n::euclidean_space set"
shows "closure S \<subseteq> affine hull S"
by (intro closure_minimal hull_subset affine_closed affine_affine_hull)
lemma closure_same_affine_hull [simp]:
fixes S :: "'n::euclidean_space set"
shows "affine hull (closure S) = affine hull S"
proof -
have "affine hull (closure S) \<subseteq> affine hull S"
using hull_mono[of "closure S" "affine hull S" "affine"]
closure_affine_hull[of S] hull_hull[of "affine" S]
by auto
moreover have "affine hull (closure S) \<supseteq> affine hull S"
using hull_mono[of "S" "closure S" "affine"] closure_subset by auto
ultimately show ?thesis by auto
qed
lemma closure_aff_dim [simp]:
fixes S :: "'n::euclidean_space set"
shows "aff_dim (closure S) = aff_dim S"
proof -
have "aff_dim S \<le> aff_dim (closure S)"
using aff_dim_subset closure_subset by auto
moreover have "aff_dim (closure S) \<le> aff_dim (affine hull S)"
using aff_dim_subset closure_affine_hull by blast
moreover have "aff_dim (affine hull S) = aff_dim S"
using aff_dim_affine_hull by auto
ultimately show ?thesis by auto
qed
lemma rel_interior_closure_convex_shrink:
fixes S :: "_::euclidean_space set"
assumes "convex S"
and "c \<in> rel_interior S"
and "x \<in> closure S"
and "e > 0"
and "e \<le> 1"
shows "x - e *\<^sub>R (x - c) \<in> rel_interior S"
proof -
obtain d where "d > 0" and d: "ball c d \<inter> affine hull S \<subseteq> S"
using assms(2) unfolding mem_rel_interior_ball by auto
have "\<exists>y \<in> S. norm (y - x) * (1 - e) < e * d"
proof (cases "x \<in> S")
case True
then show ?thesis using \<open>e > 0\<close> \<open>d > 0\<close>
apply (rule_tac bexI[where x=x], auto)
done
next
case False
then have x: "x islimpt S"
using assms(3)[unfolded closure_def] by auto
show ?thesis
proof (cases "e = 1")
case True
obtain y where "y \<in> S" "y \<noteq> x" "dist y x < 1"
using x[unfolded islimpt_approachable,THEN spec[where x=1]] by auto
then show ?thesis
apply (rule_tac x=y in bexI)
unfolding True
using \<open>d > 0\<close>
apply auto
done
next
case False
then have "0 < e * d / (1 - e)" and *: "1 - e > 0"
using \<open>e \<le> 1\<close> \<open>e > 0\<close> \<open>d > 0\<close> by auto
then obtain y where "y \<in> S" "y \<noteq> x" "dist y x < e * d / (1 - e)"
using x[unfolded islimpt_approachable,THEN spec[where x="e*d / (1 - e)"]] by auto
then show ?thesis
apply (rule_tac x=y in bexI)
unfolding dist_norm
using pos_less_divide_eq[OF *]
apply auto
done
qed
qed
then obtain y where "y \<in> S" and y: "norm (y - x) * (1 - e) < e * d"
by auto
define z where "z = c + ((1 - e) / e) *\<^sub>R (x - y)"
have *: "x - e *\<^sub>R (x - c) = y - e *\<^sub>R (y - z)"
unfolding z_def using \<open>e > 0\<close>
by (auto simp: scaleR_right_diff_distrib scaleR_right_distrib scaleR_left_diff_distrib)
have zball: "z \<in> ball c d"
using mem_ball z_def dist_norm[of c]
using y and assms(4,5)
by (auto simp:field_simps norm_minus_commute)
have "x \<in> affine hull S"
using closure_affine_hull assms by auto
moreover have "y \<in> affine hull S"
using \<open>y \<in> S\<close> hull_subset[of S] by auto
moreover have "c \<in> affine hull S"
using assms rel_interior_subset hull_subset[of S] by auto
ultimately have "z \<in> affine hull S"
using z_def affine_affine_hull[of S]
mem_affine_3_minus [of "affine hull S" c x y "(1 - e) / e"]
assms
by (auto simp: field_simps)
then have "z \<in> S" using d zball by auto
obtain d1 where "d1 > 0" and d1: "ball z d1 \<le> ball c d"
using zball open_ball[of c d] openE[of "ball c d" z] by auto
then have "ball z d1 \<inter> affine hull S \<subseteq> ball c d \<inter> affine hull S"
by auto
then have "ball z d1 \<inter> affine hull S \<subseteq> S"
using d by auto
then have "z \<in> rel_interior S"
using mem_rel_interior_ball using \<open>d1 > 0\<close> \<open>z \<in> S\<close> by auto
then have "y - e *\<^sub>R (y - z) \<in> rel_interior S"
using rel_interior_convex_shrink[of S z y e] assms \<open>y \<in> S\<close> by auto
then show ?thesis using * by auto
qed
lemma rel_interior_eq:
"rel_interior s = s \<longleftrightarrow> openin(top_of_set (affine hull s)) s"
using rel_open rel_open_def by blast
lemma rel_interior_openin:
"openin(top_of_set (affine hull s)) s \<Longrightarrow> rel_interior s = s"
by (simp add: rel_interior_eq)
lemma rel_interior_affine:
fixes S :: "'n::euclidean_space set"
shows "affine S \<Longrightarrow> rel_interior S = S"
using affine_rel_open rel_open_def by auto
lemma rel_interior_eq_closure:
fixes S :: "'n::euclidean_space set"
shows "rel_interior S = closure S \<longleftrightarrow> affine S"
proof (cases "S = {}")
case True
then show ?thesis
by auto
next
case False show ?thesis
proof
assume eq: "rel_interior S = closure S"
have "S = {} \<or> S = affine hull S"
apply (rule connected_clopen [THEN iffD1, rule_format])
apply (simp add: affine_imp_convex convex_connected)
apply (rule conjI)
apply (metis eq closure_subset openin_rel_interior rel_interior_subset subset_antisym)
apply (metis closed_subset closure_subset_eq eq hull_subset rel_interior_subset)
done
with False have "affine hull S = S"
by auto
then show "affine S"
by (metis affine_hull_eq)
next
assume "affine S"
then show "rel_interior S = closure S"
by (simp add: rel_interior_affine affine_closed)
qed
qed
subsubsection\<^marker>\<open>tag unimportant\<close>\<open>Relative interior preserves under linear transformations\<close>
lemma rel_interior_translation_aux:
fixes a :: "'n::euclidean_space"
shows "((\<lambda>x. a + x) ` rel_interior S) \<subseteq> rel_interior ((\<lambda>x. a + x) ` S)"
proof -
{
fix x
assume x: "x \<in> rel_interior S"
then obtain T where "open T" "x \<in> T \<inter> S" "T \<inter> affine hull S \<subseteq> S"
using mem_rel_interior[of x S] by auto
then have "open ((\<lambda>x. a + x) ` T)"
and "a + x \<in> ((\<lambda>x. a + x) ` T) \<inter> ((\<lambda>x. a + x) ` S)"
and "((\<lambda>x. a + x) ` T) \<inter> affine hull ((\<lambda>x. a + x) ` S) \<subseteq> (\<lambda>x. a + x) ` S"
using affine_hull_translation[of a S] open_translation[of T a] x by auto
then have "a + x \<in> rel_interior ((\<lambda>x. a + x) ` S)"
using mem_rel_interior[of "a+x" "((\<lambda>x. a + x) ` S)"] by auto
}
then show ?thesis by auto
qed
lemma rel_interior_translation:
fixes a :: "'n::euclidean_space"
shows "rel_interior ((\<lambda>x. a + x) ` S) = (\<lambda>x. a + x) ` rel_interior S"
proof -
have "(\<lambda>x. (-a) + x) ` rel_interior ((\<lambda>x. a + x) ` S) \<subseteq> rel_interior S"
using rel_interior_translation_aux[of "-a" "(\<lambda>x. a + x) ` S"]
translation_assoc[of "-a" "a"]
by auto
then have "((\<lambda>x. a + x) ` rel_interior S) \<supseteq> rel_interior ((\<lambda>x. a + x) ` S)"
using translation_inverse_subset[of a "rel_interior ((+) a ` S)" "rel_interior S"]
by auto
then show ?thesis
using rel_interior_translation_aux[of a S] by auto
qed
lemma affine_hull_linear_image:
assumes "bounded_linear f"
shows "f ` (affine hull s) = affine hull f ` s"
proof -
interpret f: bounded_linear f by fact
have "affine {x. f x \<in> affine hull f ` s}"
unfolding affine_def
by (auto simp: f.scaleR f.add affine_affine_hull[unfolded affine_def, rule_format])
moreover have "affine {x. x \<in> f ` (affine hull s)}"
using affine_affine_hull[unfolded affine_def, of s]
unfolding affine_def by (auto simp: f.scaleR [symmetric] f.add [symmetric])
ultimately show ?thesis
by (auto simp: hull_inc elim!: hull_induct)
qed
lemma rel_interior_injective_on_span_linear_image:
fixes f :: "'m::euclidean_space \<Rightarrow> 'n::euclidean_space"
and S :: "'m::euclidean_space set"
assumes "bounded_linear f"
and "inj_on f (span S)"
shows "rel_interior (f ` S) = f ` (rel_interior S)"
proof -
{
fix z
assume z: "z \<in> rel_interior (f ` S)"
then have "z \<in> f ` S"
using rel_interior_subset[of "f ` S"] by auto
then obtain x where x: "x \<in> S" "f x = z" by auto
obtain e2 where e2: "e2 > 0" "cball z e2 \<inter> affine hull (f ` S) \<subseteq> (f ` S)"
using z rel_interior_cball[of "f ` S"] by auto
obtain K where K: "K > 0" "\<And>x. norm (f x) \<le> norm x * K"
using assms Real_Vector_Spaces.bounded_linear.pos_bounded[of f] by auto
define e1 where "e1 = 1 / K"
then have e1: "e1 > 0" "\<And>x. e1 * norm (f x) \<le> norm x"
using K pos_le_divide_eq[of e1] by auto
define e where "e = e1 * e2"
then have "e > 0" using e1 e2 by auto
{
fix y
assume y: "y \<in> cball x e \<inter> affine hull S"
then have h1: "f y \<in> affine hull (f ` S)"
using affine_hull_linear_image[of f S] assms by auto
from y have "norm (x-y) \<le> e1 * e2"
using cball_def[of x e] dist_norm[of x y] e_def by auto
moreover have "f x - f y = f (x - y)"
using assms linear_diff[of f x y] linear_conv_bounded_linear[of f] by auto
moreover have "e1 * norm (f (x-y)) \<le> norm (x - y)"
using e1 by auto
ultimately have "e1 * norm ((f x)-(f y)) \<le> e1 * e2"
by auto
then have "f y \<in> cball z e2"
using cball_def[of "f x" e2] dist_norm[of "f x" "f y"] e1 x by auto
then have "f y \<in> f ` S"
using y e2 h1 by auto
then have "y \<in> S"
using assms y hull_subset[of S] affine_hull_subset_span
inj_on_image_mem_iff [OF \<open>inj_on f (span S)\<close>]
by (metis Int_iff span_superset subsetCE)
}
then have "z \<in> f ` (rel_interior S)"
using mem_rel_interior_cball[of x S] \<open>e > 0\<close> x by auto
}
moreover
{
fix x
assume x: "x \<in> rel_interior S"
then obtain e2 where e2: "e2 > 0" "cball x e2 \<inter> affine hull S \<subseteq> S"
using rel_interior_cball[of S] by auto
have "x \<in> S" using x rel_interior_subset by auto
then have *: "f x \<in> f ` S" by auto
have "\<forall>x\<in>span S. f x = 0 \<longrightarrow> x = 0"
using assms subspace_span linear_conv_bounded_linear[of f]
linear_injective_on_subspace_0[of f "span S"]
by auto
then obtain e1 where e1: "e1 > 0" "\<forall>x \<in> span S. e1 * norm x \<le> norm (f x)"
using assms injective_imp_isometric[of "span S" f]
subspace_span[of S] closed_subspace[of "span S"]
by auto
define e where "e = e1 * e2"
hence "e > 0" using e1 e2 by auto
{
fix y
assume y: "y \<in> cball (f x) e \<inter> affine hull (f ` S)"
then have "y \<in> f ` (affine hull S)"
using affine_hull_linear_image[of f S] assms by auto
then obtain xy where xy: "xy \<in> affine hull S" "f xy = y" by auto
with y have "norm (f x - f xy) \<le> e1 * e2"
using cball_def[of "f x" e] dist_norm[of "f x" y] e_def by auto
moreover have "f x - f xy = f (x - xy)"
using assms linear_diff[of f x xy] linear_conv_bounded_linear[of f] by auto
moreover have *: "x - xy \<in> span S"
using subspace_diff[of "span S" x xy] subspace_span \<open>x \<in> S\<close> xy
affine_hull_subset_span[of S] span_superset
by auto
moreover from * have "e1 * norm (x - xy) \<le> norm (f (x - xy))"
using e1 by auto
ultimately have "e1 * norm (x - xy) \<le> e1 * e2"
by auto
then have "xy \<in> cball x e2"
using cball_def[of x e2] dist_norm[of x xy] e1 by auto
then have "y \<in> f ` S"
using xy e2 by auto
}
then have "f x \<in> rel_interior (f ` S)"
using mem_rel_interior_cball[of "(f x)" "(f ` S)"] * \<open>e > 0\<close> by auto
}
ultimately show ?thesis by auto
qed
lemma rel_interior_injective_linear_image:
fixes f :: "'m::euclidean_space \<Rightarrow> 'n::euclidean_space"
assumes "bounded_linear f"
and "inj f"
shows "rel_interior (f ` S) = f ` (rel_interior S)"
using assms rel_interior_injective_on_span_linear_image[of f S]
subset_inj_on[of f "UNIV" "span S"]
by auto
subsection\<^marker>\<open>tag unimportant\<close> \<open>Openness and compactness are preserved by convex hull operation\<close>
lemma open_convex_hull[intro]:
fixes S :: "'a::real_normed_vector set"
assumes "open S"
shows "open (convex hull S)"
proof (clarsimp simp: open_contains_cball convex_hull_explicit)
fix T and u :: "'a\<Rightarrow>real"
assume obt: "finite T" "T\<subseteq>S" "\<forall>x\<in>T. 0 \<le> u x" "sum u T = 1"
from assms[unfolded open_contains_cball] obtain b
where b: "\<And>x. x\<in>S \<Longrightarrow> 0 < b x \<and> cball x (b x) \<subseteq> S" by metis
have "b ` T \<noteq> {}"
using obt by auto
define i where "i = b ` T"
let ?\<Phi> = "\<lambda>y. \<exists>F. finite F \<and> F \<subseteq> S \<and> (\<exists>u. (\<forall>x\<in>F. 0 \<le> u x) \<and> sum u F = 1 \<and> (\<Sum>v\<in>F. u v *\<^sub>R v) = y)"
let ?a = "\<Sum>v\<in>T. u v *\<^sub>R v"
show "\<exists>e > 0. cball ?a e \<subseteq> {y. ?\<Phi> y}"
proof (intro exI subsetI conjI)
show "0 < Min i"
unfolding i_def and Min_gr_iff[OF finite_imageI[OF obt(1)] \<open>b ` T\<noteq>{}\<close>]
using b \<open>T\<subseteq>S\<close> by auto
next
fix y
assume "y \<in> cball ?a (Min i)"
then have y: "norm (?a - y) \<le> Min i"
unfolding dist_norm[symmetric] by auto
{ fix x
assume "x \<in> T"
then have "Min i \<le> b x"
by (simp add: i_def obt(1))
then have "x + (y - ?a) \<in> cball x (b x)"
using y unfolding mem_cball dist_norm by auto
moreover have "x \<in> S"
using \<open>x\<in>T\<close> \<open>T\<subseteq>S\<close> by auto
ultimately have "x + (y - ?a) \<in> S"
using y b by blast
}
moreover
have *: "inj_on (\<lambda>v. v + (y - ?a)) T"
unfolding inj_on_def by auto
have "(\<Sum>v\<in>(\<lambda>v. v + (y - ?a)) ` T. u (v - (y - ?a)) *\<^sub>R v) = y"
unfolding sum.reindex[OF *] o_def using obt(4)
by (simp add: sum.distrib sum_subtractf scaleR_left.sum[symmetric] scaleR_right_distrib)
ultimately show "y \<in> {y. ?\<Phi> y}"
proof (intro CollectI exI conjI)
show "finite ((\<lambda>v. v + (y - ?a)) ` T)"
by (simp add: obt(1))
show "sum (\<lambda>v. u (v - (y - ?a))) ((\<lambda>v. v + (y - ?a)) ` T) = 1"
unfolding sum.reindex[OF *] o_def using obt(4) by auto
qed (use obt(1, 3) in auto)
qed
qed
lemma compact_convex_combinations:
fixes S T :: "'a::real_normed_vector set"
assumes "compact S" "compact T"
shows "compact { (1 - u) *\<^sub>R x + u *\<^sub>R y | x y u. 0 \<le> u \<and> u \<le> 1 \<and> x \<in> S \<and> y \<in> T}"
proof -
let ?X = "{0..1} \<times> S \<times> T"
let ?h = "(\<lambda>z. (1 - fst z) *\<^sub>R fst (snd z) + fst z *\<^sub>R snd (snd z))"
have *: "{ (1 - u) *\<^sub>R x + u *\<^sub>R y | x y u. 0 \<le> u \<and> u \<le> 1 \<and> x \<in> S \<and> y \<in> T} = ?h ` ?X"
by force
have "continuous_on ?X (\<lambda>z. (1 - fst z) *\<^sub>R fst (snd z) + fst z *\<^sub>R snd (snd z))"
unfolding continuous_on by (rule ballI) (intro tendsto_intros)
with assms show ?thesis
by (simp add: * compact_Times compact_continuous_image)
qed
lemma finite_imp_compact_convex_hull:
fixes S :: "'a::real_normed_vector set"
assumes "finite S"
shows "compact (convex hull S)"
proof (cases "S = {}")
case True
then show ?thesis by simp
next
case False
with assms show ?thesis
proof (induct rule: finite_ne_induct)
case (singleton x)
show ?case by simp
next
case (insert x A)
let ?f = "\<lambda>(u, y::'a). u *\<^sub>R x + (1 - u) *\<^sub>R y"
let ?T = "{0..1::real} \<times> (convex hull A)"
have "continuous_on ?T ?f"
unfolding split_def continuous_on by (intro ballI tendsto_intros)
moreover have "compact ?T"
by (intro compact_Times compact_Icc insert)
ultimately have "compact (?f ` ?T)"
by (rule compact_continuous_image)
also have "?f ` ?T = convex hull (insert x A)"
unfolding convex_hull_insert [OF \<open>A \<noteq> {}\<close>]
apply safe
apply (rule_tac x=a in exI, simp)
apply (rule_tac x="1 - a" in exI, simp, fast)
apply (rule_tac x="(u, b)" in image_eqI, simp_all)
done
finally show "compact (convex hull (insert x A))" .
qed
qed
lemma compact_convex_hull:
fixes S :: "'a::euclidean_space set"
assumes "compact S"
shows "compact (convex hull S)"
proof (cases "S = {}")
case True
then show ?thesis using compact_empty by simp
next
case False
then obtain w where "w \<in> S" by auto
show ?thesis
unfolding caratheodory[of S]
proof (induct ("DIM('a) + 1"))
case 0
have *: "{x.\<exists>sa. finite sa \<and> sa \<subseteq> S \<and> card sa \<le> 0 \<and> x \<in> convex hull sa} = {}"
using compact_empty by auto
from 0 show ?case unfolding * by simp
next
case (Suc n)
show ?case
proof (cases "n = 0")
case True
have "{x. \<exists>T. finite T \<and> T \<subseteq> S \<and> card T \<le> Suc n \<and> x \<in> convex hull T} = S"
unfolding set_eq_iff and mem_Collect_eq
proof (rule, rule)
fix x
assume "\<exists>T. finite T \<and> T \<subseteq> S \<and> card T \<le> Suc n \<and> x \<in> convex hull T"
then obtain T where T: "finite T" "T \<subseteq> S" "card T \<le> Suc n" "x \<in> convex hull T"
by auto
show "x \<in> S"
proof (cases "card T = 0")
case True
then show ?thesis
using T(4) unfolding card_0_eq[OF T(1)] by simp
next
case False
then have "card T = Suc 0" using T(3) \<open>n=0\<close> by auto
then obtain a where "T = {a}" unfolding card_Suc_eq by auto
then show ?thesis using T(2,4) by simp
qed
next
fix x assume "x\<in>S"
then show "\<exists>T. finite T \<and> T \<subseteq> S \<and> card T \<le> Suc n \<and> x \<in> convex hull T"
apply (rule_tac x="{x}" in exI)
unfolding convex_hull_singleton
apply auto
done
qed
then show ?thesis using assms by simp
next
case False
have "{x. \<exists>T. finite T \<and> T \<subseteq> S \<and> card T \<le> Suc n \<and> x \<in> convex hull T} =
{(1 - u) *\<^sub>R x + u *\<^sub>R y | x y u.
0 \<le> u \<and> u \<le> 1 \<and> x \<in> S \<and> y \<in> {x. \<exists>T. finite T \<and> T \<subseteq> S \<and> card T \<le> n \<and> x \<in> convex hull T}}"
unfolding set_eq_iff and mem_Collect_eq
proof (rule, rule)
fix x
assume "\<exists>u v c. x = (1 - c) *\<^sub>R u + c *\<^sub>R v \<and>
0 \<le> c \<and> c \<le> 1 \<and> u \<in> S \<and> (\<exists>T. finite T \<and> T \<subseteq> S \<and> card T \<le> n \<and> v \<in> convex hull T)"
then obtain u v c T where obt: "x = (1 - c) *\<^sub>R u + c *\<^sub>R v"
"0 \<le> c \<and> c \<le> 1" "u \<in> S" "finite T" "T \<subseteq> S" "card T \<le> n" "v \<in> convex hull T"
by auto
moreover have "(1 - c) *\<^sub>R u + c *\<^sub>R v \<in> convex hull insert u T"
apply (rule convexD_alt)
using obt(2) and convex_convex_hull and hull_subset[of "insert u T" convex]
using obt(7) and hull_mono[of T "insert u T"]
apply auto
done
ultimately show "\<exists>T. finite T \<and> T \<subseteq> S \<and> card T \<le> Suc n \<and> x \<in> convex hull T"
apply (rule_tac x="insert u T" in exI)
apply (auto simp: card_insert_if)
done
next
fix x
assume "\<exists>T. finite T \<and> T \<subseteq> S \<and> card T \<le> Suc n \<and> x \<in> convex hull T"
then obtain T where T: "finite T" "T \<subseteq> S" "card T \<le> Suc n" "x \<in> convex hull T"
by auto
show "\<exists>u v c. x = (1 - c) *\<^sub>R u + c *\<^sub>R v \<and>
0 \<le> c \<and> c \<le> 1 \<and> u \<in> S \<and> (\<exists>T. finite T \<and> T \<subseteq> S \<and> card T \<le> n \<and> v \<in> convex hull T)"
proof (cases "card T = Suc n")
case False
then have "card T \<le> n" using T(3) by auto
then show ?thesis
apply (rule_tac x=w in exI, rule_tac x=x in exI, rule_tac x=1 in exI)
using \<open>w\<in>S\<close> and T
apply (auto intro!: exI[where x=T])
done
next
case True
then obtain a u where au: "T = insert a u" "a\<notin>u"
apply (drule_tac card_eq_SucD, auto)
done
show ?thesis
proof (cases "u = {}")
case True
then have "x = a" using T(4)[unfolded au] by auto
show ?thesis unfolding \<open>x = a\<close>
apply (rule_tac x=a in exI)
apply (rule_tac x=a in exI)
apply (rule_tac x=1 in exI)
using T and \<open>n \<noteq> 0\<close>
unfolding au
apply (auto intro!: exI[where x="{a}"])
done
next
case False
obtain ux vx b where obt: "ux\<ge>0" "vx\<ge>0" "ux + vx = 1"
"b \<in> convex hull u" "x = ux *\<^sub>R a + vx *\<^sub>R b"
using T(4)[unfolded au convex_hull_insert[OF False]]
by auto
have *: "1 - vx = ux" using obt(3) by auto
show ?thesis
apply (rule_tac x=a in exI)
apply (rule_tac x=b in exI)
apply (rule_tac x=vx in exI)
using obt and T(1-3)
unfolding au and * using card_insert_disjoint[OF _ au(2)]
apply (auto intro!: exI[where x=u])
done
qed
qed
qed
then show ?thesis
using compact_convex_combinations[OF assms Suc] by simp
qed
qed
qed
subsection\<^marker>\<open>tag unimportant\<close> \<open>Extremal points of a simplex are some vertices\<close>
lemma dist_increases_online:
fixes a b d :: "'a::real_inner"
assumes "d \<noteq> 0"
shows "dist a (b + d) > dist a b \<or> dist a (b - d) > dist a b"
proof (cases "inner a d - inner b d > 0")
case True
then have "0 < inner d d + (inner a d * 2 - inner b d * 2)"
apply (rule_tac add_pos_pos)
using assms
apply auto
done
then show ?thesis
apply (rule_tac disjI2)
unfolding dist_norm and norm_eq_sqrt_inner and real_sqrt_less_iff
apply (simp add: algebra_simps inner_commute)
done
next
case False
then have "0 < inner d d + (inner b d * 2 - inner a d * 2)"
apply (rule_tac add_pos_nonneg)
using assms
apply auto
done
then show ?thesis
apply (rule_tac disjI1)
unfolding dist_norm and norm_eq_sqrt_inner and real_sqrt_less_iff
apply (simp add: algebra_simps inner_commute)
done
qed
lemma norm_increases_online:
fixes d :: "'a::real_inner"
shows "d \<noteq> 0 \<Longrightarrow> norm (a + d) > norm a \<or> norm(a - d) > norm a"
using dist_increases_online[of d a 0] unfolding dist_norm by auto
lemma simplex_furthest_lt:
fixes S :: "'a::real_inner set"
assumes "finite S"
shows "\<forall>x \<in> convex hull S. x \<notin> S \<longrightarrow> (\<exists>y \<in> convex hull S. norm (x - a) < norm(y - a))"
using assms
proof induct
fix x S
assume as: "finite S" "x\<notin>S" "\<forall>x\<in>convex hull S. x \<notin> S \<longrightarrow> (\<exists>y\<in>convex hull S. norm (x - a) < norm (y - a))"
show "\<forall>xa\<in>convex hull insert x S. xa \<notin> insert x S \<longrightarrow>
(\<exists>y\<in>convex hull insert x S. norm (xa - a) < norm (y - a))"
proof (intro impI ballI, cases "S = {}")
case False
fix y
assume y: "y \<in> convex hull insert x S" "y \<notin> insert x S"
obtain u v b where obt: "u\<ge>0" "v\<ge>0" "u + v = 1" "b \<in> convex hull S" "y = u *\<^sub>R x + v *\<^sub>R b"
using y(1)[unfolded convex_hull_insert[OF False]] by auto
show "\<exists>z\<in>convex hull insert x S. norm (y - a) < norm (z - a)"
proof (cases "y \<in> convex hull S")
case True
then obtain z where "z \<in> convex hull S" "norm (y - a) < norm (z - a)"
using as(3)[THEN bspec[where x=y]] and y(2) by auto
then show ?thesis
apply (rule_tac x=z in bexI)
unfolding convex_hull_insert[OF False]
apply auto
done
next
case False
show ?thesis
using obt(3)
proof (cases "u = 0", case_tac[!] "v = 0")
assume "u = 0" "v \<noteq> 0"
then have "y = b" using obt by auto
then show ?thesis using False and obt(4) by auto
next
assume "u \<noteq> 0" "v = 0"
then have "y = x" using obt by auto
then show ?thesis using y(2) by auto
next
assume "u \<noteq> 0" "v \<noteq> 0"
then obtain w where w: "w>0" "w<u" "w<v"
using field_lbound_gt_zero[of u v] and obt(1,2) by auto
have "x \<noteq> b"
proof
assume "x = b"
then have "y = b" unfolding obt(5)
using obt(3) by (auto simp: scaleR_left_distrib[symmetric])
then show False using obt(4) and False by simp
qed
then have *: "w *\<^sub>R (x - b) \<noteq> 0" using w(1) by auto
show ?thesis
using dist_increases_online[OF *, of a y]
proof (elim disjE)
assume "dist a y < dist a (y + w *\<^sub>R (x - b))"
then have "norm (y - a) < norm ((u + w) *\<^sub>R x + (v - w) *\<^sub>R b - a)"
unfolding dist_commute[of a]
unfolding dist_norm obt(5)
by (simp add: algebra_simps)
moreover have "(u + w) *\<^sub>R x + (v - w) *\<^sub>R b \<in> convex hull insert x S"
unfolding convex_hull_insert[OF \<open>S\<noteq>{}\<close>]
proof (intro CollectI conjI exI)
show "u + w \<ge> 0" "v - w \<ge> 0"
using obt(1) w by auto
qed (use obt in auto)
ultimately show ?thesis by auto
next
assume "dist a y < dist a (y - w *\<^sub>R (x - b))"
then have "norm (y - a) < norm ((u - w) *\<^sub>R x + (v + w) *\<^sub>R b - a)"
unfolding dist_commute[of a]
unfolding dist_norm obt(5)
by (simp add: algebra_simps)
moreover have "(u - w) *\<^sub>R x + (v + w) *\<^sub>R b \<in> convex hull insert x S"
unfolding convex_hull_insert[OF \<open>S\<noteq>{}\<close>]
proof (intro CollectI conjI exI)
show "u - w \<ge> 0" "v + w \<ge> 0"
using obt(1) w by auto
qed (use obt in auto)
ultimately show ?thesis by auto
qed
qed auto
qed
qed auto
qed (auto simp: assms)
lemma simplex_furthest_le:
fixes S :: "'a::real_inner set"
assumes "finite S"
and "S \<noteq> {}"
shows "\<exists>y\<in>S. \<forall>x\<in> convex hull S. norm (x - a) \<le> norm (y - a)"
proof -
have "convex hull S \<noteq> {}"
using hull_subset[of S convex] and assms(2) by auto
then obtain x where x: "x \<in> convex hull S" "\<forall>y\<in>convex hull S. norm (y - a) \<le> norm (x - a)"
using distance_attains_sup[OF finite_imp_compact_convex_hull[OF \<open>finite S\<close>], of a]
unfolding dist_commute[of a]
unfolding dist_norm
by auto
show ?thesis
proof (cases "x \<in> S")
case False
then obtain y where "y \<in> convex hull S" "norm (x - a) < norm (y - a)"
using simplex_furthest_lt[OF assms(1), THEN bspec[where x=x]] and x(1)
by auto
then show ?thesis
using x(2)[THEN bspec[where x=y]] by auto
next
case True
with x show ?thesis by auto
qed
qed
lemma simplex_furthest_le_exists:
fixes S :: "('a::real_inner) set"
shows "finite S \<Longrightarrow> \<forall>x\<in>(convex hull S). \<exists>y\<in>S. norm (x - a) \<le> norm (y - a)"
using simplex_furthest_le[of S] by (cases "S = {}") auto
lemma simplex_extremal_le:
fixes S :: "'a::real_inner set"
assumes "finite S"
and "S \<noteq> {}"
shows "\<exists>u\<in>S. \<exists>v\<in>S. \<forall>x\<in>convex hull S. \<forall>y \<in> convex hull S. norm (x - y) \<le> norm (u - v)"
proof -
have "convex hull S \<noteq> {}"
using hull_subset[of S convex] and assms(2) by auto
then obtain u v where obt: "u \<in> convex hull S" "v \<in> convex hull S"
"\<forall>x\<in>convex hull S. \<forall>y\<in>convex hull S. norm (x - y) \<le> norm (u - v)"
using compact_sup_maxdistance[OF finite_imp_compact_convex_hull[OF assms(1)]]
by (auto simp: dist_norm)
then show ?thesis
proof (cases "u\<notin>S \<or> v\<notin>S", elim disjE)
assume "u \<notin> S"
then obtain y where "y \<in> convex hull S" "norm (u - v) < norm (y - v)"
using simplex_furthest_lt[OF assms(1), THEN bspec[where x=u]] and obt(1)
by auto
then show ?thesis
using obt(3)[THEN bspec[where x=y], THEN bspec[where x=v]] and obt(2)
by auto
next
assume "v \<notin> S"
then obtain y where "y \<in> convex hull S" "norm (v - u) < norm (y - u)"
using simplex_furthest_lt[OF assms(1), THEN bspec[where x=v]] and obt(2)
by auto
then show ?thesis
using obt(3)[THEN bspec[where x=u], THEN bspec[where x=y]] and obt(1)
by (auto simp: norm_minus_commute)
qed auto
qed
lemma simplex_extremal_le_exists:
fixes S :: "'a::real_inner set"
shows "finite S \<Longrightarrow> x \<in> convex hull S \<Longrightarrow> y \<in> convex hull S \<Longrightarrow>
\<exists>u\<in>S. \<exists>v\<in>S. norm (x - y) \<le> norm (u - v)"
using convex_hull_empty simplex_extremal_le[of S]
by(cases "S = {}") auto
subsection \<open>Closest point of a convex set is unique, with a continuous projection\<close>
definition\<^marker>\<open>tag important\<close> closest_point :: "'a::{real_inner,heine_borel} set \<Rightarrow> 'a \<Rightarrow> 'a"
where "closest_point S a = (SOME x. x \<in> S \<and> (\<forall>y\<in>S. dist a x \<le> dist a y))"
lemma closest_point_exists:
assumes "closed S"
and "S \<noteq> {}"
shows "closest_point S a \<in> S"
and "\<forall>y\<in>S. dist a (closest_point S a) \<le> dist a y"
unfolding closest_point_def
apply(rule_tac[!] someI2_ex)
apply (auto intro: distance_attains_inf[OF assms(1,2), of a])
done
lemma closest_point_in_set: "closed S \<Longrightarrow> S \<noteq> {} \<Longrightarrow> closest_point S a \<in> S"
by (meson closest_point_exists)
lemma closest_point_le: "closed S \<Longrightarrow> x \<in> S \<Longrightarrow> dist a (closest_point S a) \<le> dist a x"
using closest_point_exists[of S] by auto
lemma closest_point_self:
assumes "x \<in> S"
shows "closest_point S x = x"
unfolding closest_point_def
apply (rule some1_equality, rule ex1I[of _ x])
using assms
apply auto
done
lemma closest_point_refl: "closed S \<Longrightarrow> S \<noteq> {} \<Longrightarrow> closest_point S x = x \<longleftrightarrow> x \<in> S"
using closest_point_in_set[of S x] closest_point_self[of x S]
by auto
lemma closer_points_lemma:
assumes "inner y z > 0"
shows "\<exists>u>0. \<forall>v>0. v \<le> u \<longrightarrow> norm(v *\<^sub>R z - y) < norm y"
proof -
have z: "inner z z > 0"
unfolding inner_gt_zero_iff using assms by auto
have "norm (v *\<^sub>R z - y) < norm y"
if "0 < v" and "v \<le> inner y z / inner z z" for v
unfolding norm_lt using z assms that
by (simp add: field_simps inner_diff inner_commute mult_strict_left_mono[OF _ \<open>0<v\<close>])
then show ?thesis
using assms z
by (rule_tac x = "inner y z / inner z z" in exI) auto
qed
lemma closer_point_lemma:
assumes "inner (y - x) (z - x) > 0"
shows "\<exists>u>0. u \<le> 1 \<and> dist (x + u *\<^sub>R (z - x)) y < dist x y"
proof -
obtain u where "u > 0"
and u: "\<forall>v>0. v \<le> u \<longrightarrow> norm (v *\<^sub>R (z - x) - (y - x)) < norm (y - x)"
using closer_points_lemma[OF assms] by auto
show ?thesis
apply (rule_tac x="min u 1" in exI)
using u[THEN spec[where x="min u 1"]] and \<open>u > 0\<close>
unfolding dist_norm by (auto simp: norm_minus_commute field_simps)
qed
lemma any_closest_point_dot:
assumes "convex S" "closed S" "x \<in> S" "y \<in> S" "\<forall>z\<in>S. dist a x \<le> dist a z"
shows "inner (a - x) (y - x) \<le> 0"
proof (rule ccontr)
assume "\<not> ?thesis"
then obtain u where u: "u>0" "u\<le>1" "dist (x + u *\<^sub>R (y - x)) a < dist x a"
using closer_point_lemma[of a x y] by auto
let ?z = "(1 - u) *\<^sub>R x + u *\<^sub>R y"
have "?z \<in> S"
using convexD_alt[OF assms(1,3,4), of u] using u by auto
then show False
using assms(5)[THEN bspec[where x="?z"]] and u(3)
by (auto simp: dist_commute algebra_simps)
qed
lemma any_closest_point_unique:
fixes x :: "'a::real_inner"
assumes "convex S" "closed S" "x \<in> S" "y \<in> S"
"\<forall>z\<in>S. dist a x \<le> dist a z" "\<forall>z\<in>S. dist a y \<le> dist a z"
shows "x = y"
using any_closest_point_dot[OF assms(1-4,5)] and any_closest_point_dot[OF assms(1-2,4,3,6)]
unfolding norm_pths(1) and norm_le_square
by (auto simp: algebra_simps)
lemma closest_point_unique:
assumes "convex S" "closed S" "x \<in> S" "\<forall>z\<in>S. dist a x \<le> dist a z"
shows "x = closest_point S a"
using any_closest_point_unique[OF assms(1-3) _ assms(4), of "closest_point S a"]
using closest_point_exists[OF assms(2)] and assms(3) by auto
lemma closest_point_dot:
assumes "convex S" "closed S" "x \<in> S"
shows "inner (a - closest_point S a) (x - closest_point S a) \<le> 0"
apply (rule any_closest_point_dot[OF assms(1,2) _ assms(3)])
using closest_point_exists[OF assms(2)] and assms(3)
apply auto
done
lemma closest_point_lt:
assumes "convex S" "closed S" "x \<in> S" "x \<noteq> closest_point S a"
shows "dist a (closest_point S a) < dist a x"
apply (rule ccontr)
apply (rule_tac notE[OF assms(4)])
apply (rule closest_point_unique[OF assms(1-3), of a])
using closest_point_le[OF assms(2), of _ a]
apply fastforce
done
lemma setdist_closest_point:
"\<lbrakk>closed S; S \<noteq> {}\<rbrakk> \<Longrightarrow> setdist {a} S = dist a (closest_point S a)"
apply (rule setdist_unique)
using closest_point_le
apply (auto simp: closest_point_in_set)
done
lemma closest_point_lipschitz:
assumes "convex S"
and "closed S" "S \<noteq> {}"
shows "dist (closest_point S x) (closest_point S y) \<le> dist x y"
proof -
have "inner (x - closest_point S x) (closest_point S y - closest_point S x) \<le> 0"
and "inner (y - closest_point S y) (closest_point S x - closest_point S y) \<le> 0"
apply (rule_tac[!] any_closest_point_dot[OF assms(1-2)])
using closest_point_exists[OF assms(2-3)]
apply auto
done
then show ?thesis unfolding dist_norm and norm_le
using inner_ge_zero[of "(x - closest_point S x) - (y - closest_point S y)"]
by (simp add: inner_add inner_diff inner_commute)
qed
lemma continuous_at_closest_point:
assumes "convex S"
and "closed S"
and "S \<noteq> {}"
shows "continuous (at x) (closest_point S)"
unfolding continuous_at_eps_delta
using le_less_trans[OF closest_point_lipschitz[OF assms]] by auto
lemma continuous_on_closest_point:
assumes "convex S"
and "closed S"
and "S \<noteq> {}"
shows "continuous_on t (closest_point S)"
by (metis continuous_at_imp_continuous_on continuous_at_closest_point[OF assms])
proposition closest_point_in_rel_interior:
assumes "closed S" "S \<noteq> {}" and x: "x \<in> affine hull S"
shows "closest_point S x \<in> rel_interior S \<longleftrightarrow> x \<in> rel_interior S"
proof (cases "x \<in> S")
case True
then show ?thesis
by (simp add: closest_point_self)
next
case False
then have "False" if asm: "closest_point S x \<in> rel_interior S"
proof -
obtain e where "e > 0" and clox: "closest_point S x \<in> S"
and e: "cball (closest_point S x) e \<inter> affine hull S \<subseteq> S"
using asm mem_rel_interior_cball by blast
then have clo_notx: "closest_point S x \<noteq> x"
using \<open>x \<notin> S\<close> by auto
define y where "y \<equiv> closest_point S x -
(min 1 (e / norm(closest_point S x - x))) *\<^sub>R (closest_point S x - x)"
have "x - y = (1 - min 1 (e / norm (closest_point S x - x))) *\<^sub>R (x - closest_point S x)"
by (simp add: y_def algebra_simps)
then have "norm (x - y) = abs ((1 - min 1 (e / norm (closest_point S x - x)))) * norm(x - closest_point S x)"
by simp
also have "\<dots> < norm(x - closest_point S x)"
using clo_notx \<open>e > 0\<close>
by (auto simp: mult_less_cancel_right2 divide_simps)
finally have no_less: "norm (x - y) < norm (x - closest_point S x)" .
have "y \<in> affine hull S"
unfolding y_def
by (meson affine_affine_hull clox hull_subset mem_affine_3_minus2 subsetD x)
moreover have "dist (closest_point S x) y \<le> e"
using \<open>e > 0\<close> by (auto simp: y_def min_mult_distrib_right)
ultimately have "y \<in> S"
using subsetD [OF e] by simp
then have "dist x (closest_point S x) \<le> dist x y"
by (simp add: closest_point_le \<open>closed S\<close>)
with no_less show False
by (simp add: dist_norm)
qed
moreover have "x \<notin> rel_interior S"
using rel_interior_subset False by blast
ultimately show ?thesis by blast
qed
subsubsection\<^marker>\<open>tag unimportant\<close> \<open>Various point-to-set separating/supporting hyperplane theorems\<close>
lemma supporting_hyperplane_closed_point:
fixes z :: "'a::{real_inner,heine_borel}"
assumes "convex S"
and "closed S"
and "S \<noteq> {}"
and "z \<notin> S"
shows "\<exists>a b. \<exists>y\<in>S. inner a z < b \<and> inner a y = b \<and> (\<forall>x\<in>S. inner a x \<ge> b)"
proof -
obtain y where "y \<in> S" and y: "\<forall>x\<in>S. dist z y \<le> dist z x"
by (metis distance_attains_inf[OF assms(2-3)])
show ?thesis
proof (intro exI bexI conjI ballI)
show "(y - z) \<bullet> z < (y - z) \<bullet> y"
by (metis \<open>y \<in> S\<close> assms(4) diff_gt_0_iff_gt inner_commute inner_diff_left inner_gt_zero_iff right_minus_eq)
show "(y - z) \<bullet> y \<le> (y - z) \<bullet> x" if "x \<in> S" for x
proof (rule ccontr)
have *: "\<And>u. 0 \<le> u \<and> u \<le> 1 \<longrightarrow> dist z y \<le> dist z ((1 - u) *\<^sub>R y + u *\<^sub>R x)"
using assms(1)[unfolded convex_alt] and y and \<open>x\<in>S\<close> and \<open>y\<in>S\<close> by auto
assume "\<not> (y - z) \<bullet> y \<le> (y - z) \<bullet> x"
then obtain v where "v > 0" "v \<le> 1" "dist (y + v *\<^sub>R (x - y)) z < dist y z"
using closer_point_lemma[of z y x] by (auto simp: inner_diff)
then show False
using *[of v] by (auto simp: dist_commute algebra_simps)
qed
qed (use \<open>y \<in> S\<close> in auto)
qed
lemma separating_hyperplane_closed_point:
fixes z :: "'a::{real_inner,heine_borel}"
assumes "convex S"
and "closed S"
and "z \<notin> S"
shows "\<exists>a b. inner a z < b \<and> (\<forall>x\<in>S. inner a x > b)"
proof (cases "S = {}")
case True
then show ?thesis
by (simp add: gt_ex)
next
case False
obtain y where "y \<in> S" and y: "\<And>x. x \<in> S \<Longrightarrow> dist z y \<le> dist z x"
by (metis distance_attains_inf[OF assms(2) False])
show ?thesis
proof (intro exI conjI ballI)
show "(y - z) \<bullet> z < inner (y - z) z + (norm (y - z))\<^sup>2 / 2"
using \<open>y\<in>S\<close> \<open>z\<notin>S\<close> by auto
next
fix x
assume "x \<in> S"
have "False" if *: "0 < inner (z - y) (x - y)"
proof -
obtain u where "u > 0" "u \<le> 1" "dist (y + u *\<^sub>R (x - y)) z < dist y z"
using * closer_point_lemma by blast
then show False using y[of "y + u *\<^sub>R (x - y)"] convexD_alt [OF \<open>convex S\<close>]
using \<open>x\<in>S\<close> \<open>y\<in>S\<close> by (auto simp: dist_commute algebra_simps)
qed
moreover have "0 < (norm (y - z))\<^sup>2"
using \<open>y\<in>S\<close> \<open>z\<notin>S\<close> by auto
then have "0 < inner (y - z) (y - z)"
unfolding power2_norm_eq_inner by simp
ultimately show "(y - z) \<bullet> z + (norm (y - z))\<^sup>2 / 2 < (y - z) \<bullet> x"
by (force simp: field_simps power2_norm_eq_inner inner_commute inner_diff)
qed
qed
lemma separating_hyperplane_closed_0:
assumes "convex (S::('a::euclidean_space) set)"
and "closed S"
and "0 \<notin> S"
shows "\<exists>a b. a \<noteq> 0 \<and> 0 < b \<and> (\<forall>x\<in>S. inner a x > b)"
proof (cases "S = {}")
case True
have "(SOME i. i\<in>Basis) \<noteq> (0::'a)"
by (metis Basis_zero SOME_Basis)
then show ?thesis
using True zero_less_one by blast
next
case False
then show ?thesis
using False using separating_hyperplane_closed_point[OF assms]
by (metis all_not_in_conv inner_zero_left inner_zero_right less_eq_real_def not_le)
qed
subsubsection\<^marker>\<open>tag unimportant\<close> \<open>Now set-to-set for closed/compact sets\<close>
lemma separating_hyperplane_closed_compact:
fixes S :: "'a::euclidean_space set"
assumes "convex S"
and "closed S"
and "convex T"
and "compact T"
and "T \<noteq> {}"
and "S \<inter> T = {}"
shows "\<exists>a b. (\<forall>x\<in>S. inner a x < b) \<and> (\<forall>x\<in>T. inner a x > b)"
proof (cases "S = {}")
case True
obtain b where b: "b > 0" "\<forall>x\<in>T. norm x \<le> b"
using compact_imp_bounded[OF assms(4)] unfolding bounded_pos by auto
obtain z :: 'a where z: "norm z = b + 1"
using vector_choose_size[of "b + 1"] and b(1) by auto
then have "z \<notin> T" using b(2)[THEN bspec[where x=z]] by auto
then obtain a b where ab: "inner a z < b" "\<forall>x\<in>T. b < inner a x"
using separating_hyperplane_closed_point[OF assms(3) compact_imp_closed[OF assms(4)], of z]
by auto
then show ?thesis
using True by auto
next
case False
then obtain y where "y \<in> S" by auto
obtain a b where "0 < b" "\<forall>x \<in> (\<Union>x\<in> S. \<Union>y \<in> T. {x - y}). b < inner a x"
using separating_hyperplane_closed_point[OF convex_differences[OF assms(1,3)], of 0]
using closed_compact_differences[OF assms(2,4)]
using assms(6) by auto
then have ab: "\<forall>x\<in>S. \<forall>y\<in>T. b + inner a y < inner a x"
apply -
apply rule
apply rule
apply (erule_tac x="x - y" in ballE)
apply (auto simp: inner_diff)
done
define k where "k = (SUP x\<in>T. a \<bullet> x)"
show ?thesis
apply (rule_tac x="-a" in exI)
apply (rule_tac x="-(k + b / 2)" in exI)
apply (intro conjI ballI)
unfolding inner_minus_left and neg_less_iff_less
proof -
fix x assume "x \<in> T"
then have "inner a x - b / 2 < k"
unfolding k_def
proof (subst less_cSUP_iff)
show "T \<noteq> {}" by fact
show "bdd_above ((\<bullet>) a ` T)"
using ab[rule_format, of y] \<open>y \<in> S\<close>
by (intro bdd_aboveI2[where M="inner a y - b"]) (auto simp: field_simps intro: less_imp_le)
qed (auto intro!: bexI[of _ x] \<open>0<b\<close>)
then show "inner a x < k + b / 2"
by auto
next
fix x
assume "x \<in> S"
then have "k \<le> inner a x - b"
unfolding k_def
apply (rule_tac cSUP_least)
using assms(5)
using ab[THEN bspec[where x=x]]
apply auto
done
then show "k + b / 2 < inner a x"
using \<open>0 < b\<close> by auto
qed
qed
lemma separating_hyperplane_compact_closed:
fixes S :: "'a::euclidean_space set"
assumes "convex S"
and "compact S"
and "S \<noteq> {}"
and "convex T"
and "closed T"
and "S \<inter> T = {}"
shows "\<exists>a b. (\<forall>x\<in>S. inner a x < b) \<and> (\<forall>x\<in>T. inner a x > b)"
proof -
obtain a b where "(\<forall>x\<in>T. inner a x < b) \<and> (\<forall>x\<in>S. b < inner a x)"
using separating_hyperplane_closed_compact[OF assms(4-5,1-2,3)] and assms(6)
by auto
then show ?thesis
apply (rule_tac x="-a" in exI)
apply (rule_tac x="-b" in exI, auto)
done
qed
subsubsection\<^marker>\<open>tag unimportant\<close> \<open>General case without assuming closure and getting non-strict separation\<close>
lemma separating_hyperplane_set_0:
assumes "convex S" "(0::'a::euclidean_space) \<notin> S"
shows "\<exists>a. a \<noteq> 0 \<and> (\<forall>x\<in>S. 0 \<le> inner a x)"
proof -
let ?k = "\<lambda>c. {x::'a. 0 \<le> inner c x}"
have *: "frontier (cball 0 1) \<inter> \<Inter>f \<noteq> {}" if as: "f \<subseteq> ?k ` S" "finite f" for f
proof -
obtain c where c: "f = ?k ` c" "c \<subseteq> S" "finite c"
using finite_subset_image[OF as(2,1)] by auto
then obtain a b where ab: "a \<noteq> 0" "0 < b" "\<forall>x\<in>convex hull c. b < inner a x"
using separating_hyperplane_closed_0[OF convex_convex_hull, of c]
using finite_imp_compact_convex_hull[OF c(3), THEN compact_imp_closed] and assms(2)
using subset_hull[of convex, OF assms(1), symmetric, of c]
by force
then have "\<exists>x. norm x = 1 \<and> (\<forall>y\<in>c. 0 \<le> inner y x)"
apply (rule_tac x = "inverse(norm a) *\<^sub>R a" in exI)
using hull_subset[of c convex]
unfolding subset_eq and inner_scaleR
by (auto simp: inner_commute del: ballE elim!: ballE)
then show "frontier (cball 0 1) \<inter> \<Inter>f \<noteq> {}"
unfolding c(1) frontier_cball sphere_def dist_norm by auto
qed
have "frontier (cball 0 1) \<inter> (\<Inter>(?k ` S)) \<noteq> {}"
apply (rule compact_imp_fip)
apply (rule compact_frontier[OF compact_cball])
using * closed_halfspace_ge
by auto
then obtain x where "norm x = 1" "\<forall>y\<in>S. x\<in>?k y"
unfolding frontier_cball dist_norm sphere_def by auto
then show ?thesis
by (metis inner_commute mem_Collect_eq norm_eq_zero zero_neq_one)
qed
lemma separating_hyperplane_sets:
fixes S T :: "'a::euclidean_space set"
assumes "convex S"
and "convex T"
and "S \<noteq> {}"
and "T \<noteq> {}"
and "S \<inter> T = {}"
shows "\<exists>a b. a \<noteq> 0 \<and> (\<forall>x\<in>S. inner a x \<le> b) \<and> (\<forall>x\<in>T. inner a x \<ge> b)"
proof -
from separating_hyperplane_set_0[OF convex_differences[OF assms(2,1)]]
obtain a where "a \<noteq> 0" "\<forall>x\<in>{x - y |x y. x \<in> T \<and> y \<in> S}. 0 \<le> inner a x"
using assms(3-5) by force
then have *: "\<And>x y. x \<in> T \<Longrightarrow> y \<in> S \<Longrightarrow> inner a y \<le> inner a x"
by (force simp: inner_diff)
then have bdd: "bdd_above (((\<bullet>) a)`S)"
using \<open>T \<noteq> {}\<close> by (auto intro: bdd_aboveI2[OF *])
show ?thesis
using \<open>a\<noteq>0\<close>
by (intro exI[of _ a] exI[of _ "SUP x\<in>S. a \<bullet> x"])
(auto intro!: cSUP_upper bdd cSUP_least \<open>a \<noteq> 0\<close> \<open>S \<noteq> {}\<close> *)
qed
subsection\<^marker>\<open>tag unimportant\<close> \<open>More convexity generalities\<close>
lemma convex_closure [intro,simp]:
fixes S :: "'a::real_normed_vector set"
assumes "convex S"
shows "convex (closure S)"
apply (rule convexI)
apply (unfold closure_sequential, elim exE)
apply (rule_tac x="\<lambda>n. u *\<^sub>R xa n + v *\<^sub>R xb n" in exI)
apply (rule,rule)
apply (rule convexD [OF assms])
apply (auto del: tendsto_const intro!: tendsto_intros)
done
lemma convex_interior [intro,simp]:
fixes S :: "'a::real_normed_vector set"
assumes "convex S"
shows "convex (interior S)"
unfolding convex_alt Ball_def mem_interior
proof clarify
fix x y u
assume u: "0 \<le> u" "u \<le> (1::real)"
fix e d
assume ed: "ball x e \<subseteq> S" "ball y d \<subseteq> S" "0<d" "0<e"
show "\<exists>e>0. ball ((1 - u) *\<^sub>R x + u *\<^sub>R y) e \<subseteq> S"
proof (intro exI conjI subsetI)
fix z
assume "z \<in> ball ((1 - u) *\<^sub>R x + u *\<^sub>R y) (min d e)"
then have "(1- u) *\<^sub>R (z - u *\<^sub>R (y - x)) + u *\<^sub>R (z + (1 - u) *\<^sub>R (y - x)) \<in> S"
apply (rule_tac assms[unfolded convex_alt, rule_format])
using ed(1,2) and u
unfolding subset_eq mem_ball Ball_def dist_norm
apply (auto simp: algebra_simps)
done
then show "z \<in> S"
using u by (auto simp: algebra_simps)
qed(insert u ed(3-4), auto)
qed
lemma convex_hull_eq_empty[simp]: "convex hull S = {} \<longleftrightarrow> S = {}"
using hull_subset[of S convex] convex_hull_empty by auto
subsection\<^marker>\<open>tag unimportant\<close> \<open>Convex set as intersection of halfspaces\<close>
lemma convex_halfspace_intersection:
fixes s :: "('a::euclidean_space) set"
assumes "closed s" "convex s"
shows "s = \<Inter>{h. s \<subseteq> h \<and> (\<exists>a b. h = {x. inner a x \<le> b})}"
apply (rule set_eqI, rule)
unfolding Inter_iff Ball_def mem_Collect_eq
apply (rule,rule,erule conjE)
proof -
fix x
assume "\<forall>xa. s \<subseteq> xa \<and> (\<exists>a b. xa = {x. inner a x \<le> b}) \<longrightarrow> x \<in> xa"
then have "\<forall>a b. s \<subseteq> {x. inner a x \<le> b} \<longrightarrow> x \<in> {x. inner a x \<le> b}"
by blast
then show "x \<in> s"
apply (rule_tac ccontr)
apply (drule separating_hyperplane_closed_point[OF assms(2,1)])
apply (erule exE)+
apply (erule_tac x="-a" in allE)
apply (erule_tac x="-b" in allE, auto)
done
qed auto
subsection\<^marker>\<open>tag unimportant\<close> \<open>Convexity of general and special intervals\<close>
lemma is_interval_convex:
fixes S :: "'a::euclidean_space set"
assumes "is_interval S"
shows "convex S"
proof (rule convexI)
fix x y and u v :: real
assume as: "x \<in> S" "y \<in> S" "0 \<le> u" "0 \<le> v" "u + v = 1"
then have *: "u = 1 - v" "1 - v \<ge> 0" and **: "v = 1 - u" "1 - u \<ge> 0"
by auto
{
fix a b
assume "\<not> b \<le> u * a + v * b"
then have "u * a < (1 - v) * b"
unfolding not_le using as(4) by (auto simp: field_simps)
then have "a < b"
unfolding * using as(4) *(2)
apply (rule_tac mult_left_less_imp_less[of "1 - v"])
apply (auto simp: field_simps)
done
then have "a \<le> u * a + v * b"
unfolding * using as(4)
by (auto simp: field_simps intro!:mult_right_mono)
}
moreover
{
fix a b
assume "\<not> u * a + v * b \<le> a"
then have "v * b > (1 - u) * a"
unfolding not_le using as(4) by (auto simp: field_simps)
then have "a < b"
unfolding * using as(4)
apply (rule_tac mult_left_less_imp_less)
apply (auto simp: field_simps)
done
then have "u * a + v * b \<le> b"
unfolding **
using **(2) as(3)
by (auto simp: field_simps intro!:mult_right_mono)
}
ultimately show "u *\<^sub>R x + v *\<^sub>R y \<in> S"
apply -
apply (rule assms[unfolded is_interval_def, rule_format, OF as(1,2)])
using as(3-) DIM_positive[where 'a='a]
apply (auto simp: inner_simps)
done
qed
lemma is_interval_connected:
fixes S :: "'a::euclidean_space set"
shows "is_interval S \<Longrightarrow> connected S"
using is_interval_convex convex_connected by auto
lemma convex_box [simp]: "convex (cbox a b)" "convex (box a (b::'a::euclidean_space))"
apply (rule_tac[!] is_interval_convex)+
using is_interval_box is_interval_cbox
apply auto
done
text\<open>A non-singleton connected set is perfect (i.e. has no isolated points). \<close>
lemma connected_imp_perfect:
fixes a :: "'a::metric_space"
assumes "connected S" "a \<in> S" and S: "\<And>x. S \<noteq> {x}"
shows "a islimpt S"
proof -
have False if "a \<in> T" "open T" "\<And>y. \<lbrakk>y \<in> S; y \<in> T\<rbrakk> \<Longrightarrow> y = a" for T
proof -
obtain e where "e > 0" and e: "cball a e \<subseteq> T"
using \<open>open T\<close> \<open>a \<in> T\<close> by (auto simp: open_contains_cball)
have "openin (top_of_set S) {a}"
unfolding openin_open using that \<open>a \<in> S\<close> by blast
moreover have "closedin (top_of_set S) {a}"
by (simp add: assms)
ultimately show "False"
using \<open>connected S\<close> connected_clopen S by blast
qed
then show ?thesis
unfolding islimpt_def by blast
qed
lemma connected_imp_perfect_aff_dim:
"\<lbrakk>connected S; aff_dim S \<noteq> 0; a \<in> S\<rbrakk> \<Longrightarrow> a islimpt S"
using aff_dim_sing connected_imp_perfect by blast
subsection\<^marker>\<open>tag unimportant\<close> \<open>On \<open>real\<close>, \<open>is_interval\<close>, \<open>convex\<close> and \<open>connected\<close> are all equivalent\<close>
lemma mem_is_interval_1_I:
fixes a b c::real
assumes "is_interval S"
assumes "a \<in> S" "c \<in> S"
assumes "a \<le> b" "b \<le> c"
shows "b \<in> S"
using assms is_interval_1 by blast
lemma is_interval_connected_1:
fixes s :: "real set"
shows "is_interval s \<longleftrightarrow> connected s"
apply rule
apply (rule is_interval_connected, assumption)
unfolding is_interval_1
apply rule
apply rule
apply rule
apply rule
apply (erule conjE)
apply (rule ccontr)
proof -
fix a b x
assume as: "connected s" "a \<in> s" "b \<in> s" "a \<le> x" "x \<le> b" "x \<notin> s"
then have *: "a < x" "x < b"
unfolding not_le [symmetric] by auto
let ?halfl = "{..<x} "
let ?halfr = "{x<..}"
{
fix y
assume "y \<in> s"
with \<open>x \<notin> s\<close> have "x \<noteq> y" by auto
then have "y \<in> ?halfr \<union> ?halfl" by auto
}
moreover have "a \<in> ?halfl" "b \<in> ?halfr" using * by auto
then have "?halfl \<inter> s \<noteq> {}" "?halfr \<inter> s \<noteq> {}"
using as(2-3) by auto
ultimately show False
apply (rule_tac notE[OF as(1)[unfolded connected_def]])
apply (rule_tac x = ?halfl in exI)
apply (rule_tac x = ?halfr in exI, rule)
apply (rule open_lessThan, rule)
apply (rule open_greaterThan, auto)
done
qed
lemma is_interval_convex_1:
fixes s :: "real set"
shows "is_interval s \<longleftrightarrow> convex s"
by (metis is_interval_convex convex_connected is_interval_connected_1)
lemma is_interval_ball_real: "is_interval (ball a b)" for a b::real
by (metis connected_ball is_interval_connected_1)
lemma connected_compact_interval_1:
"connected S \<and> compact S \<longleftrightarrow> (\<exists>a b. S = {a..b::real})"
by (auto simp: is_interval_connected_1 [symmetric] is_interval_compact)
lemma connected_convex_1:
fixes s :: "real set"
shows "connected s \<longleftrightarrow> convex s"
by (metis is_interval_convex convex_connected is_interval_connected_1)
lemma connected_convex_1_gen:
fixes s :: "'a :: euclidean_space set"
assumes "DIM('a) = 1"
shows "connected s \<longleftrightarrow> convex s"
proof -
obtain f:: "'a \<Rightarrow> real" where linf: "linear f" and "inj f"
using subspace_isomorphism[OF subspace_UNIV subspace_UNIV,
where 'a='a and 'b=real]
unfolding Euclidean_Space.dim_UNIV
by (auto simp: assms)
then have "f -` (f ` s) = s"
by (simp add: inj_vimage_image_eq)
then show ?thesis
by (metis connected_convex_1 convex_linear_vimage linf convex_connected connected_linear_image)
qed
lemma is_interval_cball_1[intro, simp]: "is_interval (cball a b)" for a b::real
by (simp add: is_interval_convex_1)
lemma [simp]:
fixes r s::real
shows is_interval_io: "is_interval {..<r}"
and is_interval_oi: "is_interval {r<..}"
and is_interval_oo: "is_interval {r<..<s}"
and is_interval_oc: "is_interval {r<..s}"
and is_interval_co: "is_interval {r..<s}"
by (simp_all add: is_interval_convex_1)
subsection\<^marker>\<open>tag unimportant\<close> \<open>Another intermediate value theorem formulation\<close>
lemma ivt_increasing_component_on_1:
fixes f :: "real \<Rightarrow> 'a::euclidean_space"
assumes "a \<le> b"
and "continuous_on {a..b} f"
and "(f a)\<bullet>k \<le> y" "y \<le> (f b)\<bullet>k"
shows "\<exists>x\<in>{a..b}. (f x)\<bullet>k = y"
proof -
have "f a \<in> f ` cbox a b" "f b \<in> f ` cbox a b"
apply (rule_tac[!] imageI)
using assms(1)
apply auto
done
then show ?thesis
using connected_ivt_component[of "f ` cbox a b" "f a" "f b" k y]
by (simp add: connected_continuous_image assms)
qed
lemma ivt_increasing_component_1:
fixes f :: "real \<Rightarrow> 'a::euclidean_space"
shows "a \<le> b \<Longrightarrow> \<forall>x\<in>{a..b}. continuous (at x) f \<Longrightarrow>
f a\<bullet>k \<le> y \<Longrightarrow> y \<le> f b\<bullet>k \<Longrightarrow> \<exists>x\<in>{a..b}. (f x)\<bullet>k = y"
by (rule ivt_increasing_component_on_1) (auto simp: continuous_at_imp_continuous_on)
lemma ivt_decreasing_component_on_1:
fixes f :: "real \<Rightarrow> 'a::euclidean_space"
assumes "a \<le> b"
and "continuous_on {a..b} f"
and "(f b)\<bullet>k \<le> y"
and "y \<le> (f a)\<bullet>k"
shows "\<exists>x\<in>{a..b}. (f x)\<bullet>k = y"
apply (subst neg_equal_iff_equal[symmetric])
using ivt_increasing_component_on_1[of a b "\<lambda>x. - f x" k "- y"]
using assms using continuous_on_minus
apply auto
done
lemma ivt_decreasing_component_1:
fixes f :: "real \<Rightarrow> 'a::euclidean_space"
shows "a \<le> b \<Longrightarrow> \<forall>x\<in>{a..b}. continuous (at x) f \<Longrightarrow>
f b\<bullet>k \<le> y \<Longrightarrow> y \<le> f a\<bullet>k \<Longrightarrow> \<exists>x\<in>{a..b}. (f x)\<bullet>k = y"
by (rule ivt_decreasing_component_on_1) (auto simp: continuous_at_imp_continuous_on)
subsection\<^marker>\<open>tag unimportant\<close> \<open>A bound within an interval\<close>
lemma convex_hull_eq_real_cbox:
fixes x y :: real assumes "x \<le> y"
shows "convex hull {x, y} = cbox x y"
proof (rule hull_unique)
show "{x, y} \<subseteq> cbox x y" using \<open>x \<le> y\<close> by auto
show "convex (cbox x y)"
by (rule convex_box)
next
fix S assume "{x, y} \<subseteq> S" and "convex S"
then show "cbox x y \<subseteq> S"
unfolding is_interval_convex_1 [symmetric] is_interval_def Basis_real_def
by - (clarify, simp (no_asm_use), fast)
qed
lemma unit_interval_convex_hull:
"cbox (0::'a::euclidean_space) One = convex hull {x. \<forall>i\<in>Basis. (x\<bullet>i = 0) \<or> (x\<bullet>i = 1)}"
(is "?int = convex hull ?points")
proof -
have One[simp]: "\<And>i. i \<in> Basis \<Longrightarrow> One \<bullet> i = 1"
by (simp add: inner_sum_left sum.If_cases inner_Basis)
have "?int = {x. \<forall>i\<in>Basis. x \<bullet> i \<in> cbox 0 1}"
by (auto simp: cbox_def)
also have "\<dots> = (\<Sum>i\<in>Basis. (\<lambda>x. x *\<^sub>R i) ` cbox 0 1)"
by (simp only: box_eq_set_sum_Basis)
also have "\<dots> = (\<Sum>i\<in>Basis. (\<lambda>x. x *\<^sub>R i) ` (convex hull {0, 1}))"
by (simp only: convex_hull_eq_real_cbox zero_le_one)
also have "\<dots> = (\<Sum>i\<in>Basis. convex hull ((\<lambda>x. x *\<^sub>R i) ` {0, 1}))"
by (simp add: convex_hull_linear_image)
also have "\<dots> = convex hull (\<Sum>i\<in>Basis. (\<lambda>x. x *\<^sub>R i) ` {0, 1})"
by (simp only: convex_hull_set_sum)
also have "\<dots> = convex hull {x. \<forall>i\<in>Basis. x\<bullet>i \<in> {0, 1}}"
by (simp only: box_eq_set_sum_Basis)
also have "convex hull {x. \<forall>i\<in>Basis. x\<bullet>i \<in> {0, 1}} = convex hull ?points"
by simp
finally show ?thesis .
qed
text \<open>And this is a finite set of vertices.\<close>
lemma unit_cube_convex_hull:
obtains S :: "'a::euclidean_space set"
where "finite S" and "cbox 0 (\<Sum>Basis) = convex hull S"
proof
show "finite {x::'a. \<forall>i\<in>Basis. x \<bullet> i = 0 \<or> x \<bullet> i = 1}"
proof (rule finite_subset, clarify)
show "finite ((\<lambda>S. \<Sum>i\<in>Basis. (if i \<in> S then 1 else 0) *\<^sub>R i) ` Pow Basis)"
using finite_Basis by blast
fix x :: 'a
assume as: "\<forall>i\<in>Basis. x \<bullet> i = 0 \<or> x \<bullet> i = 1"
show "x \<in> (\<lambda>S. \<Sum>i\<in>Basis. (if i\<in>S then 1 else 0) *\<^sub>R i) ` Pow Basis"
apply (rule image_eqI[where x="{i. i\<in>Basis \<and> x\<bullet>i = 1}"])
using as
apply (subst euclidean_eq_iff, auto)
done
qed
show "cbox 0 One = convex hull {x. \<forall>i\<in>Basis. x \<bullet> i = 0 \<or> x \<bullet> i = 1}"
using unit_interval_convex_hull by blast
qed
text \<open>Hence any cube (could do any nonempty interval).\<close>
lemma cube_convex_hull:
assumes "d > 0"
obtains S :: "'a::euclidean_space set" where
"finite S" and "cbox (x - (\<Sum>i\<in>Basis. d*\<^sub>Ri)) (x + (\<Sum>i\<in>Basis. d*\<^sub>Ri)) = convex hull S"
proof -
let ?d = "(\<Sum>i\<in>Basis. d *\<^sub>R i)::'a"
have *: "cbox (x - ?d) (x + ?d) = (\<lambda>y. x - ?d + (2 * d) *\<^sub>R y) ` cbox 0 (\<Sum>Basis)"
proof (intro set_eqI iffI)
fix y
assume "y \<in> cbox (x - ?d) (x + ?d)"
then have "inverse (2 * d) *\<^sub>R (y - (x - ?d)) \<in> cbox 0 (\<Sum>Basis)"
using assms by (simp add: mem_box field_simps inner_simps)
with \<open>0 < d\<close> show "y \<in> (\<lambda>y. x - sum ((*\<^sub>R) d) Basis + (2 * d) *\<^sub>R y) ` cbox 0 One"
by (auto intro: image_eqI[where x= "inverse (2 * d) *\<^sub>R (y - (x - ?d))"])
next
fix y
assume "y \<in> (\<lambda>y. x - ?d + (2 * d) *\<^sub>R y) ` cbox 0 One"
then obtain z where z: "z \<in> cbox 0 One" "y = x - ?d + (2*d) *\<^sub>R z"
by auto
then show "y \<in> cbox (x - ?d) (x + ?d)"
using z assms by (auto simp: mem_box inner_simps)
qed
obtain S where "finite S" "cbox 0 (\<Sum>Basis::'a) = convex hull S"
using unit_cube_convex_hull by auto
then show ?thesis
by (rule_tac that[of "(\<lambda>y. x - ?d + (2 * d) *\<^sub>R y)` S"]) (auto simp: convex_hull_affinity *)
qed
subsection\<^marker>\<open>tag unimportant\<close>\<open>Representation of any interval as a finite convex hull\<close>
lemma image_stretch_interval:
"(\<lambda>x. \<Sum>k\<in>Basis. (m k * (x\<bullet>k)) *\<^sub>R k) ` cbox a (b::'a::euclidean_space) =
(if (cbox a b) = {} then {} else
cbox (\<Sum>k\<in>Basis. (min (m k * (a\<bullet>k)) (m k * (b\<bullet>k))) *\<^sub>R k::'a)
(\<Sum>k\<in>Basis. (max (m k * (a\<bullet>k)) (m k * (b\<bullet>k))) *\<^sub>R k))"
proof cases
assume *: "cbox a b \<noteq> {}"
show ?thesis
unfolding box_ne_empty if_not_P[OF *]
apply (simp add: cbox_def image_Collect set_eq_iff euclidean_eq_iff[where 'a='a] ball_conj_distrib[symmetric])
apply (subst choice_Basis_iff[symmetric])
proof (intro allI ball_cong refl)
fix x i :: 'a assume "i \<in> Basis"
with * have a_le_b: "a \<bullet> i \<le> b \<bullet> i"
unfolding box_ne_empty by auto
show "(\<exists>xa. x \<bullet> i = m i * xa \<and> a \<bullet> i \<le> xa \<and> xa \<le> b \<bullet> i) \<longleftrightarrow>
min (m i * (a \<bullet> i)) (m i * (b \<bullet> i)) \<le> x \<bullet> i \<and> x \<bullet> i \<le> max (m i * (a \<bullet> i)) (m i * (b \<bullet> i))"
proof (cases "m i = 0")
case True
with a_le_b show ?thesis by auto
next
case False
then have *: "\<And>a b. a = m i * b \<longleftrightarrow> b = a / m i"
by (auto simp: field_simps)
from False have
"min (m i * (a \<bullet> i)) (m i * (b \<bullet> i)) = (if 0 < m i then m i * (a \<bullet> i) else m i * (b \<bullet> i))"
"max (m i * (a \<bullet> i)) (m i * (b \<bullet> i)) = (if 0 < m i then m i * (b \<bullet> i) else m i * (a \<bullet> i))"
using a_le_b by (auto simp: min_def max_def mult_le_cancel_left)
with False show ?thesis using a_le_b
unfolding * by (auto simp: le_divide_eq divide_le_eq ac_simps)
qed
qed
qed simp
lemma interval_image_stretch_interval:
"\<exists>u v. (\<lambda>x. \<Sum>k\<in>Basis. (m k * (x\<bullet>k))*\<^sub>R k) ` cbox a (b::'a::euclidean_space) = cbox u (v::'a::euclidean_space)"
unfolding image_stretch_interval by auto
lemma cbox_translation: "cbox (c + a) (c + b) = image (\<lambda>x. c + x) (cbox a b)"
using image_affinity_cbox [of 1 c a b]
using box_ne_empty [of "a+c" "b+c"] box_ne_empty [of a b]
by (auto simp: inner_left_distrib add.commute)
lemma cbox_image_unit_interval:
fixes a :: "'a::euclidean_space"
assumes "cbox a b \<noteq> {}"
shows "cbox a b =
(+) a ` (\<lambda>x. \<Sum>k\<in>Basis. ((b \<bullet> k - a \<bullet> k) * (x \<bullet> k)) *\<^sub>R k) ` cbox 0 One"
using assms
apply (simp add: box_ne_empty image_stretch_interval cbox_translation [symmetric])
apply (simp add: min_def max_def algebra_simps sum_subtractf euclidean_representation)
done
lemma closed_interval_as_convex_hull:
fixes a :: "'a::euclidean_space"
obtains S where "finite S" "cbox a b = convex hull S"
proof (cases "cbox a b = {}")
case True with convex_hull_empty that show ?thesis
by blast
next
case False
obtain S::"'a set" where "finite S" and eq: "cbox 0 One = convex hull S"
by (blast intro: unit_cube_convex_hull)
have lin: "linear (\<lambda>x. \<Sum>k\<in>Basis. ((b \<bullet> k - a \<bullet> k) * (x \<bullet> k)) *\<^sub>R k)"
by (rule linear_compose_sum) (auto simp: algebra_simps linearI)
have "finite ((+) a ` (\<lambda>x. \<Sum>k\<in>Basis. ((b \<bullet> k - a \<bullet> k) * (x \<bullet> k)) *\<^sub>R k) ` S)"
by (rule finite_imageI \<open>finite S\<close>)+
then show ?thesis
apply (rule that)
apply (simp add: convex_hull_translation convex_hull_linear_image [OF lin, symmetric])
apply (simp add: eq [symmetric] cbox_image_unit_interval [OF False])
done
qed
subsection\<^marker>\<open>tag unimportant\<close> \<open>Bounded convex function on open set is continuous\<close>
lemma convex_on_bounded_continuous:
fixes S :: "('a::real_normed_vector) set"
assumes "open S"
and "convex_on S f"
and "\<forall>x\<in>S. \<bar>f x\<bar> \<le> b"
shows "continuous_on S f"
apply (rule continuous_at_imp_continuous_on)
unfolding continuous_at_real_range
proof (rule,rule,rule)
fix x and e :: real
assume "x \<in> S" "e > 0"
define B where "B = \<bar>b\<bar> + 1"
then have B: "0 < B""\<And>x. x\<in>S \<Longrightarrow> \<bar>f x\<bar> \<le> B"
using assms(3) by auto
obtain k where "k > 0" and k: "cball x k \<subseteq> S"
using \<open>x \<in> S\<close> assms(1) open_contains_cball_eq by blast
show "\<exists>d>0. \<forall>x'. norm (x' - x) < d \<longrightarrow> \<bar>f x' - f x\<bar> < e"
proof (intro exI conjI allI impI)
fix y
assume as: "norm (y - x) < min (k / 2) (e / (2 * B) * k)"
show "\<bar>f y - f x\<bar> < e"
proof (cases "y = x")
case False
define t where "t = k / norm (y - x)"
have "2 < t" "0<t"
unfolding t_def using as False and \<open>k>0\<close>
by (auto simp:field_simps)
have "y \<in> S"
apply (rule k[THEN subsetD])
unfolding mem_cball dist_norm
apply (rule order_trans[of _ "2 * norm (x - y)"])
using as
by (auto simp: field_simps norm_minus_commute)
{
define w where "w = x + t *\<^sub>R (y - x)"
have "w \<in> S"
using \<open>k>0\<close> by (auto simp: dist_norm t_def w_def k[THEN subsetD])
have "(1 / t) *\<^sub>R x + - x + ((t - 1) / t) *\<^sub>R x = (1 / t - 1 + (t - 1) / t) *\<^sub>R x"
by (auto simp: algebra_simps)
also have "\<dots> = 0"
using \<open>t > 0\<close> by (auto simp:field_simps)
finally have w: "(1 / t) *\<^sub>R w + ((t - 1) / t) *\<^sub>R x = y"
unfolding w_def using False and \<open>t > 0\<close>
by (auto simp: algebra_simps)
have 2: "2 * B < e * t"
unfolding t_def using \<open>0 < e\<close> \<open>0 < k\<close> \<open>B > 0\<close> and as and False
by (auto simp:field_simps)
have "f y - f x \<le> (f w - f x) / t"
using assms(2)[unfolded convex_on_def,rule_format,of w x "1/t" "(t - 1)/t", unfolded w]
using \<open>0 < t\<close> \<open>2 < t\<close> and \<open>x \<in> S\<close> \<open>w \<in> S\<close>
by (auto simp:field_simps)
also have "... < e"
using B(2)[OF \<open>w\<in>S\<close>] and B(2)[OF \<open>x\<in>S\<close>] 2 \<open>t > 0\<close> by (auto simp: field_simps)
finally have th1: "f y - f x < e" .
}
moreover
{
define w where "w = x - t *\<^sub>R (y - x)"
have "w \<in> S"
using \<open>k > 0\<close> by (auto simp: dist_norm t_def w_def k[THEN subsetD])
have "(1 / (1 + t)) *\<^sub>R x + (t / (1 + t)) *\<^sub>R x = (1 / (1 + t) + t / (1 + t)) *\<^sub>R x"
by (auto simp: algebra_simps)
also have "\<dots> = x"
using \<open>t > 0\<close> by (auto simp:field_simps)
finally have w: "(1 / (1+t)) *\<^sub>R w + (t / (1 + t)) *\<^sub>R y = x"
unfolding w_def using False and \<open>t > 0\<close>
by (auto simp: algebra_simps)
have "2 * B < e * t"
unfolding t_def
using \<open>0 < e\<close> \<open>0 < k\<close> \<open>B > 0\<close> and as and False
by (auto simp:field_simps)
then have *: "(f w - f y) / t < e"
using B(2)[OF \<open>w\<in>S\<close>] and B(2)[OF \<open>y\<in>S\<close>]
using \<open>t > 0\<close>
by (auto simp:field_simps)
have "f x \<le> 1 / (1 + t) * f w + (t / (1 + t)) * f y"
using assms(2)[unfolded convex_on_def,rule_format,of w y "1/(1+t)" "t / (1+t)",unfolded w]
using \<open>0 < t\<close> \<open>2 < t\<close> and \<open>y \<in> S\<close> \<open>w \<in> S\<close>
by (auto simp:field_simps)
also have "\<dots> = (f w + t * f y) / (1 + t)"
using \<open>t > 0\<close> by (auto simp: divide_simps)
also have "\<dots> < e + f y"
using \<open>t > 0\<close> * \<open>e > 0\<close> by (auto simp: field_simps)
finally have "f x - f y < e" by auto
}
ultimately show ?thesis by auto
qed (insert \<open>0<e\<close>, auto)
qed (insert \<open>0<e\<close> \<open>0<k\<close> \<open>0<B\<close>, auto simp: field_simps)
qed
subsection\<^marker>\<open>tag unimportant\<close> \<open>Upper bound on a ball implies upper and lower bounds\<close>
lemma convex_bounds_lemma:
fixes x :: "'a::real_normed_vector"
assumes "convex_on (cball x e) f"
and "\<forall>y \<in> cball x e. f y \<le> b"
shows "\<forall>y \<in> cball x e. \<bar>f y\<bar> \<le> b + 2 * \<bar>f x\<bar>"
apply rule
proof (cases "0 \<le> e")
case True
fix y
assume y: "y \<in> cball x e"
define z where "z = 2 *\<^sub>R x - y"
have *: "x - (2 *\<^sub>R x - y) = y - x"
by (simp add: scaleR_2)
have z: "z \<in> cball x e"
using y unfolding z_def mem_cball dist_norm * by (auto simp: norm_minus_commute)
have "(1 / 2) *\<^sub>R y + (1 / 2) *\<^sub>R z = x"
unfolding z_def by (auto simp: algebra_simps)
then show "\<bar>f y\<bar> \<le> b + 2 * \<bar>f x\<bar>"
using assms(1)[unfolded convex_on_def,rule_format, OF y z, of "1/2" "1/2"]
using assms(2)[rule_format,OF y] assms(2)[rule_format,OF z]
by (auto simp:field_simps)
next
case False
fix y
assume "y \<in> cball x e"
then have "dist x y < 0"
using False unfolding mem_cball not_le by (auto simp del: dist_not_less_zero)
then show "\<bar>f y\<bar> \<le> b + 2 * \<bar>f x\<bar>"
using zero_le_dist[of x y] by auto
qed
subsubsection\<^marker>\<open>tag unimportant\<close> \<open>Hence a convex function on an open set is continuous\<close>
lemma real_of_nat_ge_one_iff: "1 \<le> real (n::nat) \<longleftrightarrow> 1 \<le> n"
by auto
lemma convex_on_continuous:
assumes "open (s::('a::euclidean_space) set)" "convex_on s f"
shows "continuous_on s f"
unfolding continuous_on_eq_continuous_at[OF assms(1)]
proof
note dimge1 = DIM_positive[where 'a='a]
fix x
assume "x \<in> s"
then obtain e where e: "cball x e \<subseteq> s" "e > 0"
using assms(1) unfolding open_contains_cball by auto
define d where "d = e / real DIM('a)"
have "0 < d"
unfolding d_def using \<open>e > 0\<close> dimge1 by auto
let ?d = "(\<Sum>i\<in>Basis. d *\<^sub>R i)::'a"
obtain c
where c: "finite c"
and c1: "convex hull c \<subseteq> cball x e"
and c2: "cball x d \<subseteq> convex hull c"
proof
define c where "c = (\<Sum>i\<in>Basis. (\<lambda>a. a *\<^sub>R i) ` {x\<bullet>i - d, x\<bullet>i + d})"
show "finite c"
unfolding c_def by (simp add: finite_set_sum)
have 1: "convex hull c = {a. \<forall>i\<in>Basis. a \<bullet> i \<in> cbox (x \<bullet> i - d) (x \<bullet> i + d)}"
unfolding box_eq_set_sum_Basis
unfolding c_def convex_hull_set_sum
apply (subst convex_hull_linear_image [symmetric])
apply (simp add: linear_iff scaleR_add_left)
apply (rule sum.cong [OF refl])
apply (rule image_cong [OF _ refl])
apply (rule convex_hull_eq_real_cbox)
apply (cut_tac \<open>0 < d\<close>, simp)
done
then have 2: "convex hull c = {a. \<forall>i\<in>Basis. a \<bullet> i \<in> cball (x \<bullet> i) d}"
by (simp add: dist_norm abs_le_iff algebra_simps)
show "cball x d \<subseteq> convex hull c"
unfolding 2
by (clarsimp simp: dist_norm) (metis inner_commute inner_diff_right norm_bound_Basis_le)
have e': "e = (\<Sum>(i::'a)\<in>Basis. d)"
by (simp add: d_def DIM_positive)
show "convex hull c \<subseteq> cball x e"
unfolding 2
apply clarsimp
apply (subst euclidean_dist_l2)
apply (rule order_trans [OF L2_set_le_sum])
apply (rule zero_le_dist)
unfolding e'
apply (rule sum_mono, simp)
done
qed
define k where "k = Max (f ` c)"
have "convex_on (convex hull c) f"
apply(rule convex_on_subset[OF assms(2)])
apply(rule subset_trans[OF c1 e(1)])
done
then have k: "\<forall>y\<in>convex hull c. f y \<le> k"
apply (rule_tac convex_on_convex_hull_bound, assumption)
by (simp add: k_def c)
have "e \<le> e * real DIM('a)"
using e(2) real_of_nat_ge_one_iff by auto
then have "d \<le> e"
by (simp add: d_def divide_simps)
then have dsube: "cball x d \<subseteq> cball x e"
by (rule subset_cball)
have conv: "convex_on (cball x d) f"
using \<open>convex_on (convex hull c) f\<close> c2 convex_on_subset by blast
then have "\<forall>y\<in>cball x d. \<bar>f y\<bar> \<le> k + 2 * \<bar>f x\<bar>"
by (rule convex_bounds_lemma) (use c2 k in blast)
then have "continuous_on (ball x d) f"
apply (rule_tac convex_on_bounded_continuous)
apply (rule open_ball, rule convex_on_subset[OF conv])
apply (rule ball_subset_cball, force)
done
then show "continuous (at x) f"
unfolding continuous_on_eq_continuous_at[OF open_ball]
using \<open>d > 0\<close> by auto
qed
end