Theory Bounded_Functions

(* Author: Maximilian Schäffeler, adapted from HOL-Analysis.Bounded_Continuous_Function *)

section ‹Bounded Functions›

theory Bounded_Functions
  imports
    "HOL.Topological_Spaces"
    "HOL-Analysis.Uniform_Limit"
    "HOL-Probability.Probability"
begin

subsection ‹Definition›

definitiontag important› "bfun = {f. bounded (range f)}"

typedef (overloaded) ('a, 'b) bfun ("(_ b _)" [22] 21) =
  "bfun::('a  'b :: metric_space) set"
  morphisms apply_bfun Bfun
  by (fastforce simp: bounded_def bfun_def)

declare [[coercion "apply_bfun :: ('a b ('b :: metric_space))  'a  'b"]]

setup_lifting type_definition_bfun

lemma bounded_apply_bfun[intro, simp]: "bounded ((apply_bfun x) ` X)"
  using apply_bfun by (fastforce simp: bfun_def bounded_def)

lemma apply_bfun_bdd_above[simp, intro]: 
  fixes f :: "'c b real"
  shows "bdd_above (f ` X)"
  by (auto intro: bounded_imp_bdd_above)

lemma bfun_eqI[intro]: "(x. apply_bfun f x = apply_bfun g x)  f = g"
  by transfer auto

lemma bfun_eqD[dest]: "f = g  (x. apply_bfun f x = apply_bfun g x)"
  by auto

lemma bfunE:
  assumes "f  bfun"
  obtains g where "f = apply_bfun g"
  by (blast intro: apply_bfun_cases assms)

lemma const_bfun: "(λx. b)  bfun"
  by (auto simp: bfun_def image_def)

lift_definition const_bfun::"'b  ('a b ('b :: metric_space))" is "λ(c::'b) _. c"
  by (rule const_bfun)

lemma bounded_dist_le_SUP_dist:
  "bounded (range f)  bounded (range g)  dist (f x) (g x)  (SUP x. dist (f x) (g x))"
  by (auto intro!: cSUP_upper bounded_imp_bdd_above bounded_dist_comp)

instantiation bfun :: (type, metric_space) metric_space
begin

lift_definitiontag important› dist_bfun :: "('a b 'b)  ('a b 'b)  real"
  is "λf g. (SUP x. dist (f x) (g x))" .

definition uniformity_bfun :: "(('a b 'b) × 'a b 'b) filter"
  where "uniformity_bfun = (INF e{0 <..}. principal {(x, y). dist x y < e})"

definition open_bfun :: "('a b 'b) set  bool"
  where "open_bfun S = (xS. F (x', y) in uniformity. x' = x  y  S)"

lemma dist_bounded:
  fixes f g :: "'a b 'b"
  shows "dist (f x) (g x)  dist f g"
  by transfer (auto intro!: bounded_dist_le_SUP_dist simp: bfun_def)

lemma dist_bound:
  fixes f g :: "'a b ('b :: metric_space)"
  assumes "x. dist (f x) (g x)  b"
  shows "dist f g  b"
  using assms
  by transfer (auto intro!: cSUP_least)

lemma dist_fun_lt_imp_dist_val_lt:
  fixes f g :: "'a b 'b"
  assumes "dist f g < e"
  shows "dist (f x) (g x) < e"
  using dist_bounded assms
  by (rule le_less_trans)

instance
proof
  fix f g h :: "'a b 'b"
  show "dist f g = 0  f = g"
  proof
    have "x. dist (f x) (g x)  dist f g"
      by (rule dist_bounded)
    also assume "dist f g = 0"
    finally show "f = g"
      by (auto simp: apply_bfun_inject[symmetric])
  qed (auto simp: dist_bfun_def intro!: cSup_eq)
  show "dist f g  dist f h + dist g h"
  proof (rule dist_bound)
    fix x
    have "dist (f x) (g x)  dist (f x) (h x) + dist (g x) (h x)"
      by (rule dist_triangle2)
    also have "dist (f x) (h x)  dist f h"
      by (rule dist_bounded)
    also have "dist (g x) (h x)  dist g h"
      by (rule dist_bounded)
    finally show "dist (f x) (g x)  dist f h + dist g h"
      by simp
  qed
qed (rule open_bfun_def uniformity_bfun_def)+

end


lift_definition PiC::"'a set  ('a  ('b :: metric_space) set)  ('a b 'b) set"
  is "λI X. Pi I X  bfun"
  by auto

lemma mem_PiC_iff: "x  PiC I X  apply_bfun x  Pi I X"
  by transfer simp

lemmas mem_PiCD = mem_PiC_iff[THEN iffD1]
  and mem_PiCI = mem_PiC_iff[THEN iffD2]

lemma tendsto_bfun_uniform_limit:
  fixes f::"'i  'a b ('b :: metric_space)"
  assumes "(f  l) F"
  shows "uniform_limit UNIV f l F"
proof (rule uniform_limitI)
  fix e::real assume "e > 0"
  from tendstoD[OF assms this] have "F x in F. dist (f x) l < e" .
  then show "F n in F. xUNIV. dist ((f n) x) (l x) < e"
    by eventually_elim (auto simp: dist_fun_lt_imp_dist_val_lt)
qed

lemma uniform_limit_tendsto_bfun:
  fixes f::"'i  'a b ('b :: metric_space)"
    and l::"'a b 'b"
  assumes "uniform_limit UNIV f l F"
  shows "(f  l) F"
proof (rule tendstoI)
  fix e::real assume "e > 0"
  then have "e / 2 > 0" by simp
  from uniform_limitD[OF assms this]
  have "F i in F. x. dist (f i x) (l x) < e / 2" by simp
  then have "F x in F. dist (f x) l  e / 2"
    by eventually_elim (blast intro: dist_bound less_imp_le)
  then show "F x in F. dist (f x) l < e"
    by eventually_elim (use 0 < e in auto)
qed

subsectiontag unimportant› ‹Supremum Norm›

instantiationtag unimportant› bfun :: (type, real_normed_vector) real_vector
begin

lemma uminus_cont: "f  bfun  (λx. - f x)  bfun" for f::"'a  'b"
  by (auto simp: bfun_def)

lemma plus_cont: "f  bfun  g  bfun  (λx. f x + g x)  bfun" for f g::"'a  'b"
  by (auto simp: bfun_def bounded_plus_comp)

lemma minus_cont: "f  bfun  g  bfun  (λx. f x - g x)  bfun" for f g::"'a  'b"
  by (auto simp: bfun_def bounded_minus_comp)

lemma scaleR_cont: "f  bfun  (λx. a *R f x)  bfun" for f :: "'a  'b"
  by (auto simp: bfun_def bounded_scaleR_comp)

lemma bfun_normI[intro]: "(x. norm (f x)  b)  f  bfun"
  by (auto simp: bfun_def intro: boundedI)

lift_definition uminus_bfun::"('a b 'b)  ('a b 'b)" is "λf x. - f x"
  by (rule uminus_cont)

lift_definition plus_bfun::"('a b 'b)  ('a b 'b)  'a b 'b"  is "λf g x. f x + g x"
  by (rule plus_cont)

lift_definition minus_bfun::"('a b 'b)  ('a b 'b)  'a b 'b"  is "λf g x. f x - g x"
  by (rule minus_cont)

lift_definition zero_bfun::"'a b 'b" is "λ_. 0"
  by (rule const_bfun)

lemma const_bfun_0_eq_0[simp]: "const_bfun 0 = 0"
  by transfer simp

lift_definition scaleR_bfun::"real  ('a b 'b)  'a b 'b"  is "λr g x. r *R g x"
  by (rule scaleR_cont)

lemmas [simp] =
  const_bfun.rep_eq
  uminus_bfun.rep_eq
  plus_bfun.rep_eq
  minus_bfun.rep_eq
  zero_bfun.rep_eq
  scaleR_bfun.rep_eq

instance
  by standard (auto simp: algebra_simps)
end

lemma scaleR_cont': "f  bfun  (λx. a * f x)  bfun" for f :: "'a  real"
  using scaleR_cont[of f a] by auto

lemma bfun_norm_le_SUP_norm:
  "f  bfun  norm (f x)  (SUP x. norm (f x))"
  by (auto intro!: cSUP_upper bounded_imp_bdd_above simp: bfun_def bounded_norm_comp)


instantiationtag unimportant› bfun :: (type, real_normed_vector) real_normed_vector
begin

definition norm_bfun :: "('a, 'b) bfun  real"
  where "norm_bfun f = dist f 0"

definition "sgn (f::('a,'b) bfun) = f /R norm f"

instance
proof
  fix a :: real
  fix f g :: "('a, 'b) bfun"
  show "dist f g = norm (f - g)"
    unfolding norm_bfun_def
    by transfer (simp add: dist_norm)
  show "norm (f + g)  norm f + norm g"
    unfolding norm_bfun_def
    by transfer
      (auto intro!: cSUP_least norm_triangle_le add_mono bfun_norm_le_SUP_norm simp: dist_norm)
  show "norm (a *R f) = ¦a¦ * norm f"
    unfolding norm_bfun_def dist_bfun.rep_eq
    by (subst continuous_at_Sup_mono[of "λx. ¦a¦ * x"]) 
      (fastforce intro!: monoI mult_left_mono continuous_intros bounded_imp_bdd_above 
        simp: bounded_norm_comp image_comp)+
qed (auto simp: norm_bfun_def sgn_bfun_def)
end

lemma norm_bfun_def': "norm f = (x. norm ((f :: 'a b 'b :: real_normed_vector) x))"
  by(subst norm_conv_dist, simp add: dist_bfun.rep_eq)

lemma norm_le_norm_bfun: "norm (apply_bfun f x)  norm f"
  by (simp add: apply_bfun bfun_norm_le_SUP_norm norm_bfun_def dist_bfun_def)

lemma abs_le_norm_bfun: "abs (apply_bfun f x)  norm f"
  by (subst real_norm_def[symmetric]) (rule norm_le_norm_bfun)

lemma le_norm_bfun: "apply_bfun f x  norm f"
  using abs_ge_self abs_le_norm_bfun
  by (rule order.trans)

subsection ‹Complete Space›

lemma tendsto_add: "P  (L :: 'a :: real_normed_vector)  (λn. P n + c)  L + c"
  by (intro tendsto_intros)

lemma lim_add: "convergent P  lim (λn. P n + (c :: 'a ::real_normed_vector)) = lim P + c"
  by (auto intro: limI dest: Bounded_Functions.tendsto_add simp add: convergent_LIMSEQ_iff)

lemma complete_bfun: 
  assumes cauchy_f: "Cauchy (f :: nat  ('a,  'b :: {complete_space, real_normed_vector}) bfun)"
  shows "convergent f"
proof -
  let ?f = "λx. lim (λn. f n x)"

  from cauchy_f have cauchy_fx: "Cauchy (λn. f n x)" for x
    by(fastforce intro: dist_fun_lt_imp_dist_val_lt CauchyI' dest: metric_CauchyD)+

  hence conv_fx: "convergent (λn. f n x)" for x
    by(auto intro: Cauchy_convergent)

  have lim_f_bfun: "?f  bfun"
  proof -
    have "b. x. norm (lim (λn. f n x))  b"
    proof -
      obtain N b where dist_N: "dist (f n x) (f m x) < b" if "n  N" " m  N" for x m n
        using metric_CauchyD[OF cauchy_f zero_less_numeral]  dist_fun_lt_imp_dist_val_lt
        by metis
      have aux: "norm (lim (λn. f n x))  b + norm (f N x)" for x
      proof-
        from conv_fx[unfolded convergent_LIMSEQ_iff]
        have tendsto_f_N: "(λn. f (n + N) x)  ?f x"
          by (auto dest: LIMSEQ_ignore_initial_segment)
        hence tendsto_f_dist: "(λn. dist (f (n + N) x) (f N x))  dist (?f x) (f N x)"
          by (auto intro: tendsto_intros)
        have "dist (f (n + N) x) (f N x)  b" for n
          by (auto intro!: less_imp_le simp: dist_N)
        hence "dist (?f x) (f N x)  b"
          using lim_le[OF convergentI[OF tendsto_f_dist]]
          by (auto simp: limI[OF tendsto_f_dist, symmetric])
        thus "norm (?f x)  b + norm (f N x)"
          using norm_triangle_ineq2 order_trans
          by (fastforce simp: dist_norm)
      qed
      show ?thesis
        by (auto intro!: exI[of _ "b + norm (f N)"] order.trans[OF aux] norm_le_norm_bfun)
    qed
    thus ?thesis
      by (auto intro: boundedI simp: bfun_def)
  qed

  hence bfun_lim_f_inv: "apply_bfun (Bfun ?f) = ?f"
    using bfun.Bfun_inverse by blast

  have "f  Bfun ?f"
  proof -
    have "e. e > 0  N. n  N. dist (Bfun ?f) (f n) < e"
    proof -
      fix e :: real
      assume "e > 0"
      hence "N. n  N. m  N. dist (f n) (f m) < 0.5 * e" (is "N. n  N. m  N. ?P n m N e")
        by(force intro!: metric_CauchyD[OF cauchy_f])
      then obtain N where dist_N: "?P n m N e" if "n  N" "m  N" for n m
        by auto
      have "n x. dist (?f x) (f (n + N) x)  0.5 * e"
      proof safe
        fix n x
        have "(λm. f m x)  ?f x"
          using conv_fx convergent_LIMSEQ_iff
          by blast
        hence tendsto_f_N: "(λm. f (m + N) x)  ?f x"
          using LIMSEQ_ignore_initial_segment
          by auto
        hence tendsto_f_dist: 
          "(λm. dist (f (m + N) x) (f (n + N) x))  dist (?f x) (f (n + N) x)"
          by (simp add: tendsto_dist)
        have "dist (f (m + N) x) (f (n + N) x) < 0.5 * e" for m
          by (fastforce intro!: dist_fun_lt_imp_dist_val_lt[OF dist_N])
        thus "dist (?f x) (f (n + N) x)  0.5 * e"
          by (fastforce intro: less_imp_le convergentI[OF tendsto_f_dist] intro!: lim_le
              simp only: limI[OF tendsto_f_dist, symmetric])
      qed
      hence "n. (SUP x. dist (?f x) (f (n + N) x))  0.5 * e"
        by (fastforce intro!: cSUP_least)
      hence aux: "n. dist (Bfun ?f) (f (n + N))  0.5 * e"
        unfolding dist_bfun_def
        by (simp add: bfun_lim_f_inv)
      have "0.5 * e < e"  by (simp add: 0 < e)
      hence "n. dist (Bfun ?f) (f (n + N)) < e"
        using aux le_less_trans by blast
      thus "N. nN. dist (Bfun ?f) (f n) < e"
        by (metis add.commute less_eqE)
    qed
    thus ?thesis
      by (simp add: dist_commute metric_LIMSEQ_I)
  qed
  thus "convergent f"
    unfolding convergent_def 
    by blast
qed

lemma norm_bound:
  fixes f :: "('a, 'b::real_normed_vector) bfun"
  assumes "x. norm (apply_bfun f x)  b"
  shows "norm f  b"
  using dist_bound[of f 0 b] assms
  by (simp add: dist_norm)

lemma bfun_bounded_norm_range: "bounded (range (λs. norm (apply_bfun v s)))"
proof -
  obtain b where "s. norm (v s)  b"
    using norm_le_norm_bfun
    by fast
  thus ?thesis
    by (simp add: bounded_norm_comp)
qed

instance bfun :: (type, banach) banach
  by standard (auto simp: complete_bfun)

lemma bfun_prob_space_integrable: 
  assumes "prob_space S" "v  borel_measurable S" 
  assumes "(v :: 'a  'b :: {second_countable_topology, banach})  bfun" 
  shows "integrable S v"
  using prob_space.finite_measure norm_le_norm_bfun[of "Bfun v"] Bfun_inverse[OF assms(3)] assms
  by (auto intro: finite_measure.integrable_const_bound)

lemma bfun_integral_bound: 
  assumes "(v :: 'a  'c :: {euclidean_space})  bfun"
  shows "(λS. x. v x (S :: 'a pmf))  bfun"
proof -
  obtain b where bH: "x. norm (v x)  b"
    using bfun_norm_le_SUP_norm assms by fast
  have "(x. norm (v x) S)  b" for S :: "'a pmf"
    using v  bfun bfun_def bounded_norm_comp bH bfun_prob_space_integrable
    by (fastforce intro!: prob_space.integral_le_const prob_space_measure_pmf simp: bfun_def)
  hence "S :: 'a pmf. norm (x. (v x) S)  b"
    using integral_norm_bound order_trans by blast
  thus ?thesis
    unfolding bfun_def 
    by (auto intro: boundedI)
qed

lemma scale_bfun[intro!]: "f  bfun  (λx. (k::real) * f x)  bfun"
  using scaleR_cont[of f k] by auto

lemma bfun_spec[intro]: "f  bfun  (λx. f (g x))  bfun"
  unfolding bfun_def bounded_def by auto

lemma apply_bfun_bfun[simp]: "apply_bfun f  bfun"
  using apply_bfun .

lemma bfun_integral_bound'[intro]: "(v :: 'a  'c :: {euclidean_space})  bfun 
      (λS. x. v x ((F S) :: 'a pmf))  bfun"
  using bfun_integral_bound
  by (subst bfun_spec[of _ F]) auto

lift_definition bfun_comp :: "('a  'b)  ('b b 'c::metric_space)  ('a b 'c)" is
  "λg bf x. bf (g x)"
  by auto


subsection ‹Order Instance›

class ordered_real_normed_vector = real_normed_vector + ordered_real_vector

instance real :: ordered_real_normed_vector 
  by standard

instantiation bfun :: (_,  ordered_real_normed_vector) ordered_real_normed_vector begin

definition "less_eq_bfun f g  x. apply_bfun f x  apply_bfun g x"
definition "less_bfun f g  x. apply_bfun f x  apply_bfun g x  (y. f y < g y)"

instance
proof (standard, goal_cases)
  case (1 x y)
  then show ?case
    by (auto dest: leD simp add: less_bfun_def less_eq_bfun_def)
      (metis order.not_eq_order_implies_strict)
qed (auto intro: order_trans antisym dest: leD not_le_imp_less 
    simp: less_eq_bfun_def less_bfun_def eq_iff scaleR_left_mono scaleR_right_mono)
end

lemma less_eq_bfunI[intro]: "(x. apply_bfun f x  apply_bfun g x)  f  g"
  unfolding less_eq_bfun_def
  by auto

lemma less_eq_bfunD[dest]: "f  g  (x. apply_bfun f x  apply_bfun g x)"
  unfolding less_eq_bfun_def
  by auto

subsection ‹Miscellaneous›
instantiation bfun :: (type, one) one begin

lift_definition one_bfun :: "'s b 'd::{metric_space, one}" is "λx. 1"
  using const_bfun .

instance
  by standard
end

declare one_bfun.rep_eq [simp]

lemma apply_bfun_one [simp]: "apply_bfun (1 :: _ b real) x = 1"
  using one_bfun.rep_eq
  by auto

lemma norm_bfun_one[simp]: "norm (1 :: 'a b real) = 1"
  unfolding norm_bfun_def' by auto


lemma range_bfunI[intro]: "bounded (range f)  f  bfun"
  by (simp add: bfun_def)

lemma finite_bfun[simp]: "(λ(i::_::finite). f i)  bfun"
  by (meson finite finite_imageI finite_imp_bounded range_bfunI)

lemma bounded_apply_bfun':
  assumes "bounded ((F :: 'c  'd b 'b::real_normed_vector) ` S)"
  shows "bounded ((λb. (F b) x) ` S)"
proof -
  obtain b where "xS. norm (F x)  b"
    by (meson assms bounded_pos image_eqI)
  thus "bounded ((λb. (F b) x) ` S)"
    by (fastforce intro: norm_le_norm_bfun dual_order.trans boundedI[of _ b])
qed


lemma bfun_tendsto_apply_bfun:
  assumes h: "(F :: (nat  'a b real))  (y :: 'a b real)"
  shows "(λn. F n x)  y x"
proof -
  have aux: "(λn. dist (F n) y)  0"
    using h
    using tendsto_dist_iff by blast
  have "n. dist (F n x) (y x)  dist (F n) y"
    unfolding dist_bfun_def
    using Bounded_Continuous_Function.bounded_dist_le_SUP_dist by fastforce
  hence "n. norm (dist (F n x) (y x))  norm(dist (F n) y)"
    by auto
  hence "(λn. dist (F n x) (y x))  0"
    by (subst Lim_transform_bound[OF _ aux]) auto
  thus ?thesis  
    using tendsto_dist_iff by blast
qed

subsection ‹Bounded Functions and Vectors›
lemma vec_bfun[simp, intro]: "($) x  bfun"
  using finite_bfun.

lemma norm_bfun_le_norm_vec: "norm (bfun.Bfun (($) (x :: real^'c :: finite)))  norm x"
proof -
  have "norm (bfun.Bfun (($) (x :: real^'c :: finite)))  (xa. ¦x $ xa¦)"
    unfolding norm_bfun_def dist_bfun_def
    by (auto simp: Bfun_inverse)
  also have "  norm x"
    using component_le_norm_cart
    by (auto intro: cSUP_least)
  finally show ?thesis 
    by auto
qed

lemma bounded_linear_bfun_nth: "bounded_linear f  bounded_linear (λv. bfun.Bfun (($) (f v)))"
  using order_trans[OF Finite_Cartesian_Product.norm_nth_le onorm, of f]
  by (auto simp: Bfun_inverse mult.commute linear_simps dist_bfun_def norm_bfun_def
      intro!: bounded_linear_intro cSup_least)

lemma norm_vec_le_norm_bfun: 
  "norm (vec_lambda (apply_bfun (x :: 'd::finite b real)))  norm x * card (UNIV :: 'd set)"
proof -
  have "norm (vec_lambda (apply_bfun x))  ( i  UNIV . ¦(apply_bfun x i)¦)"
    using L2_set_le_sum_abs
    unfolding norm_vec_def L2_set_def
    by auto
  also have "  (card (UNIV :: 'd set) * (xa. ¦apply_bfun x xa¦))"
    by (auto intro!: sum_bounded_above cSup_upper)
  finally show ?thesis
    by (simp add: norm_bfun_def dist_bfun_def mult.commute)
qed

end