Theory HOL-Analysis.Measure_Space

(*  Title:      HOL/Analysis/Measure_Space.thy
    Author:     Lawrence C Paulson
    Author:     Johannes Hölzl, TU München
    Author:     Armin Heller, TU München
*)

section ‹Measure Spaces›

theory Measure_Space
imports
  Measurable "HOL-Library.Extended_Nonnegative_Real"
begin

subsectiontag unimportant› "Relate extended reals and the indicator function"

lemma suminf_cmult_indicator:
  fixes f :: "nat  ennreal"
  assumes "disjoint_family A" "x  A i"
  shows "(n. f n * indicator (A n) x) = f i"
proof -
  have **: "n. f n * indicator (A n) x = (if n = i then f n else 0 :: ennreal)"
    using x  A i assms unfolding disjoint_family_on_def indicator_def by auto
  then have "n. (j<n. f j * indicator (A j) x) = (if i < n then f i else 0 :: ennreal)"
    by (auto simp: sum.If_cases)
  moreover have "(SUP n. if i < n then f i else 0) = (f i :: ennreal)"
  proof (rule SUP_eqI)
    fix y :: ennreal assume "n. n  UNIV  (if i < n then f i else 0)  y"
    from this[of "Suc i"] show "f i  y" by auto
  qed (use assms in simp)
  ultimately show ?thesis using assms
    by (simp add: suminf_eq_SUP)
qed

lemma suminf_indicator:
  assumes "disjoint_family A"
  shows "(n. indicator (A n) x :: ennreal) = indicator (i. A i) x"
proof cases
  assume *: "x  (i. A i)"
  then obtain i where "x  A i" by auto
  from suminf_cmult_indicator[OF assms(1), OF x  A i, of "λk. 1"]
  show ?thesis using * by simp
qed simp

lemma sum_indicator_disjoint_family:
  fixes f :: "'d  'e::semiring_1"
  assumes d: "disjoint_family_on A P" and "x  A j" and "finite P" and "j  P"
  shows "(iP. f i * indicator (A i) x) = f j"
proof -
  have "P  {i. x  A i} = {j}"
    using d x  A j j  P unfolding disjoint_family_on_def
    by auto
  with finite P show ?thesis
    by (simp add: indicator_def)
qed

text ‹
  The type for emeasure spaces is already defined in theoryHOL-Analysis.Sigma_Algebra, as it
  is also used to represent sigma algebras (with an arbitrary emeasure).
›

subsectiontag unimportant› "Extend binary sets"

lemma LIMSEQ_binaryset:
  assumes f: "f {} = 0"
  shows  "(λn. i<n. f (binaryset A B i))  f A + f B"
proof -
  have "(λn. i < Suc (Suc n). f (binaryset A B i)) = (λn. f A + f B)"
    proof
      fix n
      show "(i < Suc (Suc n). f (binaryset A B i)) = f A + f B"
        by (induct n)  (auto simp add: binaryset_def f)
    qed
  moreover
  have "  f A + f B" by (rule tendsto_const)
  ultimately have "(λn. i< n+2. f (binaryset A B i))  f A + f B"
    by simp
  thus ?thesis by (rule LIMSEQ_offset [where k=2])
qed

lemma binaryset_sums:
  assumes f: "f {} = 0"
  shows  "(λn. f (binaryset A B n)) sums (f A + f B)"
  using LIMSEQ_binaryset f sums_def by blast

lemma suminf_binaryset_eq:
  fixes f :: "'a set  'b::{comm_monoid_add, t2_space}"
  shows "f {} = 0  (n. f (binaryset A B n)) = f A + f B"
  by (metis binaryset_sums sums_unique)

subsectiontag unimportant› ‹Properties of a premeasure termμ

text ‹
  The definitions for constpositive and constcountably_additive should be here, by they are
  necessary to define typ'a measure in theoryHOL-Analysis.Sigma_Algebra.
›

definition subadditive where
  "subadditive M f  (xM. yM. x  y = {}  f (x  y)  f x + f y)"

lemma subadditiveD: "subadditive M f  x  y = {}  x  M  y  M  f (x  y)  f x + f y"
  by (auto simp add: subadditive_def)

definition countably_subadditive where
  "countably_subadditive M f 
    (A. range A  M  disjoint_family A  (i. A i)  M  (f (i. A i)  (i. f (A i))))"

lemma (in ring_of_sets) countably_subadditive_subadditive:
  fixes f :: "'a set  ennreal"
  assumes f: "positive M f" and cs: "countably_subadditive M f"
  shows  "subadditive M f"
proof (auto simp add: subadditive_def)
  fix x y
  assume x: "x  M" and y: "y  M" and "x  y = {}"
  hence "disjoint_family (binaryset x y)"
    by (auto simp add: disjoint_family_on_def binaryset_def)
  hence "range (binaryset x y)  M 
         (i. binaryset x y i)  M 
         f (i. binaryset x y i)  ( n. f (binaryset x y n))"
    using cs by (auto simp add: countably_subadditive_def)
  hence "{x,y,{}}  M  x  y  M 
         f (x  y)  ( n. f (binaryset x y n))"
    by (simp add: range_binaryset_eq UN_binaryset_eq)
  thus "f (x  y)   f x + f y" using f x y
    by (auto simp add: Un o_def suminf_binaryset_eq positive_def)
qed

definition additive where
  "additive M μ  (xM. yM. x  y = {}  μ (x  y) = μ x + μ y)"

definition increasing where
  "increasing M μ  (xM. yM. x  y  μ x  μ y)"

lemma positiveD1: "positive M f  f {} = 0" by (auto simp: positive_def)

lemma positiveD_empty:
  "positive M f  f {} = 0"
  by (auto simp add: positive_def)

lemma additiveD:
  "additive M f  x  y = {}  x  M  y  M  f (x  y) = f x + f y"
  by (auto simp add: additive_def)

lemma increasingD:
  "increasing M f  x  y  xM  yM  f x  f y"
  by (auto simp add: increasing_def)

lemma countably_additiveI[case_names countably]:
  "(A. range A  M; disjoint_family A; (i. A i)  M  (i. f(A i)) = f(i. A i))
   countably_additive M f"
  by (simp add: countably_additive_def)

lemma (in ring_of_sets) disjointed_additive:
  assumes f: "positive M f" "additive M f" and A: "range A  M" "incseq A"
  shows "(in. f (disjointed A i)) = f (A n)"
proof (induct n)
  case (Suc n)
  then have "(iSuc n. f (disjointed A i)) = f (A n) + f (disjointed A (Suc n))"
    by simp
  also have " = f (A n  disjointed A (Suc n))"
    using A by (subst f(2)[THEN additiveD]) (auto simp: disjointed_mono)
  also have "A n  disjointed A (Suc n) = A (Suc n)"
    using incseq A by (auto dest: incseq_SucD simp: disjointed_mono)
  finally show ?case .
qed simp

lemma (in ring_of_sets) additive_sum:
  fixes A:: "'i  'a set"
  assumes f: "positive M f" and ad: "additive M f" and "finite S"
      and A: "A`S  M"
      and disj: "disjoint_family_on A S"
  shows  "(iS. f (A i)) = f (iS. A i)"
  using finite S disj A
proof induct
  case empty show ?case using f by (simp add: positive_def)
next
  case (insert s S)
  then have "A s  (iS. A i) = {}"
    by (auto simp add: disjoint_family_on_def neq_iff)
  moreover
  have "A s  M" using insert by blast
  moreover have "(iS. A i)  M"
    using insert finite S by auto
  ultimately have "f (A s  (iS. A i)) = f (A s) + f(iS. A i)"
    using ad UNION_in_sets A by (auto simp add: additive_def)
  with insert show ?case using ad disjoint_family_on_mono[of S "insert s S" A]
    by (auto simp add: additive_def subset_insertI)
qed

lemma (in ring_of_sets) additive_increasing:
  fixes f :: "'a set  ennreal"
  assumes posf: "positive M f" and addf: "additive M f"
  shows "increasing M f"
proof (auto simp add: increasing_def)
  fix x y
  assume xy: "x  M" "y  M" "x  y"
  then have "y - x  M" by auto
  then have "f x + 0  f x + f (y-x)" by (intro add_left_mono zero_le)
  also have " = f (x  (y-x))"
    by (metis addf Diff_disjoint y - x  M additiveD xy(1))
  also have " = f y"
    by (metis Un_Diff_cancel Un_absorb1 xy(3))
  finally show "f x  f y" by simp
qed

lemma (in ring_of_sets) subadditive:
  fixes f :: "'a set  ennreal"
  assumes f: "positive M f" "additive M f" and A: "A`S  M" and S: "finite S"
  shows "f (iS. A i)  (iS. f (A i))"
using S A
proof (induct S)
  case empty thus ?case using f by (auto simp: positive_def)
next
  case (insert x F)
  hence in_M: "A x  M" "(iF. A i)  M" "(iF. A i) - A x  M" using A by force+
  have subs: "(iF. A i) - A x  (iF. A i)" by auto
  have "(i(insert x F). A i) = A x  ((iF. A i) - A x)" by auto
  hence "f (i(insert x F). A i) = f (A x  ((iF. A i) - A x))"
    by simp
  also have " = f (A x) + f ((iF. A i) - A x)"
    using f(2) by (rule additiveD) (insert in_M, auto)
  also have "  f (A x) + f (iF. A i)"
    using additive_increasing[OF f] in_M subs 
    by (simp add: increasingD)
  also have "  f (A x) + (iF. f (A i))" 
    using insert by (auto intro: add_left_mono)
  finally show "f (i(insert x F). A i)  (i(insert x F). f (A i))"
    by (simp add: insert)
qed

lemma (in ring_of_sets) countably_additive_additive:
  fixes f :: "'a set  ennreal"
  assumes posf: "positive M f" and ca: "countably_additive M f"
  shows "additive M f"
proof (auto simp add: additive_def)
  fix x y
  assume x: "x  M" and y: "y  M" and "x  y = {}"
  hence "disjoint_family (binaryset x y)"
    by (auto simp add: disjoint_family_on_def binaryset_def)
  hence "range (binaryset x y)  M 
         (i. binaryset x y i)  M 
         f (i. binaryset x y i) = ( n. f (binaryset x y n))"
    using ca by (simp add: countably_additive_def)
  hence "{x,y,{}}  M  x  y  M  f (x  y) = (n. f (binaryset x y n))"
    by (simp add: range_binaryset_eq UN_binaryset_eq)
  thus "f (x  y) = f x + f y" using posf x y
    by (auto simp add: Un suminf_binaryset_eq positive_def)
qed

lemma (in algebra) increasing_additive_bound:
  fixes A:: "nat  'a set" and  f :: "'a set  ennreal"
  assumes f: "positive M f" and ad: "additive M f"
      and inc: "increasing M f"
      and A: "range A  M"
      and disj: "disjoint_family A"
  shows  "(i. f (A i))  f Ω"
proof (safe intro!: suminf_le_const)
  fix N
  note disj_N = disjoint_family_on_mono[OF _ disj, of "{..<N}"]
  have "(i<N. f (A i)) = f (i{..<N}. A i)"
    using A by (intro additive_sum [OF f ad]) (auto simp: disj_N)
  also have "  f Ω" using space_closed A
    by (intro increasingD[OF inc] finite_UN) auto
  finally show "(i<N. f (A i))  f Ω" by simp
qed (insert f A, auto simp: positive_def)

lemma (in ring_of_sets) countably_additiveI_finite:
  fixes μ :: "'a set  ennreal"
  assumes "finite Ω" "positive M μ" "additive M μ"
  shows "countably_additive M μ"
proof (rule countably_additiveI)
  fix F :: "nat  'a set" assume F: "range F  M" "(i. F i)  M" and disj: "disjoint_family F"

  have "i. F i  {}  (x. x  F i)" by auto
  then obtain f where f: "i. F i  {}  f i  F i" by metis

  have finU: "finite (i. F i)"
    by (metis F(2) assms(1) infinite_super sets_into_space)

  have F_subset: "{i. μ (F i)  0}  {i. F i  {}}"
    by (auto simp: positiveD_empty[OF positive M μ])
  moreover have fin_not_empty: "finite {i. F i  {}}"
  proof (rule finite_imageD)
    from f have "f`{i. F i  {}}  (i. F i)" by auto
    then show "finite (f`{i. F i  {}})"
      by (simp add: finU finite_subset)
    show inj_f: "inj_on f {i. F i  {}}" 
      using f disj
      by (simp add: inj_on_def disjoint_family_on_def disjoint_iff) metis
  qed 
  ultimately have fin_not_0: "finite {i. μ (F i)  0}"
    by (rule finite_subset)

  have disj_not_empty: "disjoint_family_on F {i. F i  {}}"
    using disj by (auto simp: disjoint_family_on_def)

  from fin_not_0 have "(i. μ (F i)) = (i | μ (F i)  0. μ (F i))"
    by (rule suminf_finite) auto
  also have " = (i | F i  {}. μ (F i))"
    using fin_not_empty F_subset by (rule sum.mono_neutral_left) auto
  also have " = μ (i{i. F i  {}}. F i)"
    using positive M μ additive M μ fin_not_empty disj_not_empty F by (intro additive_sum) auto
  also have " = μ (i. F i)"
    by (rule arg_cong[where f=μ]) auto
  finally show "(i. μ (F i)) = μ (i. F i)" .
qed

lemma (in ring_of_sets) countably_additive_iff_continuous_from_below:
  fixes f :: "'a set  ennreal"
  assumes f: "positive M f" "additive M f"
  shows "countably_additive M f 
    (A. range A  M  incseq A  (i. A i)  M  (λi. f (A i))  f (i. A i))"
  unfolding countably_additive_def
proof safe
  assume count_sum: "A. range A  M  disjoint_family A  (A ` UNIV)  M  (i. f (A i)) = f ((A ` UNIV))"
  fix A :: "nat  'a set" assume A: "range A  M" "incseq A" "(i. A i)  M"
  then have dA: "range (disjointed A)  M" by (auto simp: range_disjointed_sets)
  with count_sum[THEN spec, of "disjointed A"] A(3)
  have f_UN: "(i. f (disjointed A i)) = f (i. A i)"
    by (auto simp: UN_disjointed_eq disjoint_family_disjointed)
  moreover have "(λn. (i<n. f (disjointed A i)))  (i. f (disjointed A i))"
    by (simp add: summable_LIMSEQ)
  from LIMSEQ_Suc[OF this]
  have "(λn. (in. f (disjointed A i)))  (i. f (disjointed A i))"
    unfolding lessThan_Suc_atMost .
  moreover have "n. (in. f (disjointed A i)) = f (A n)"
    using disjointed_additive[OF f A(1,2)] .
  ultimately show "(λi. f (A i))  f (i. A i)" by simp
next
  assume cont[rule_format]: "A. range A  M  incseq A  (i. A i)  M  (λi. f (A i))  f (i. A i)"
  fix A :: "nat  'a set" assume A: "range A  M" "disjoint_family A" "(i. A i)  M"
  have *: "(n. (i<n. A i)) = (i. A i)" by auto
  have "range (λi. i<i. A i)  M" "(i. i<i. A i)  M"
    using A * by auto
  then have "(λn. f (i<n. A i))  f (i. A i)"
    unfolding *[symmetric] by (force intro!: cont incseq_SucI)+
  moreover have "n. f (i<n. A i) = (i<n. f (A i))"
    using A
    by (intro additive_sum[OF f, symmetric]) (auto intro: disjoint_family_on_mono)
  ultimately
  have "(λi. f (A i)) sums f (i. A i)"
    unfolding sums_def by simp
  then show "(i. f (A i)) = f (i. A i)"
    by (metis sums_unique)
qed

lemma (in ring_of_sets) continuous_from_above_iff_empty_continuous:
  fixes f :: "'a set  ennreal"
  assumes f: "positive M f" "additive M f"
  shows "(A. range A  M  decseq A  (i. A i)  M  (i. f (A i)  )  (λi. f (A i))  f (i. A i))
      (A. range A  M  decseq A  (i. A i) = {}  (i. f (A i)  )  (λi. f (A i))  0)"
proof safe
  assume cont[rule_format]: "(A. range A  M  decseq A  (i. A i)  M  (i. f (A i)  )  (λi. f (A i))  f (i. A i))"
  fix A :: "nat  'a set" 
  assume A: "range A  M" "decseq A" "(i. A i) = {}" "i. f (A i)  "
  with cont[of A] show "(λi. f (A i))  0"
    using positive M f[unfolded positive_def] by auto
next
  assume cont[rule_format]: "A. range A  M  decseq A  (i. A i) = {}  (i. f (A i)  )  (λi. f (A i))  0"
  fix A :: "nat  'a set" 
  assume A: "range A  M" "decseq A" "(i. A i)  M" "i. f (A i)  "

  have f_mono: "a b. a  M  b  M  a  b  f a  f b"
    using additive_increasing[OF f] unfolding increasing_def by simp

  have decseq_fA: "decseq (λi. f (A i))"
    using A by (auto simp: decseq_def intro!: f_mono)
  have decseq: "decseq (λi. A i - (i. A i))"
    using A by (auto simp: decseq_def)
  then have decseq_f: "decseq (λi. f (A i - (i. A i)))"
    using A unfolding decseq_def by (auto intro!: f_mono Diff)
  have "f (x. A x)  f (A 0)"
    using A by (auto intro!: f_mono)
  then have f_Int_fin: "f (x. A x)  "
    using A by (auto simp: top_unique)
  have f_fin: "f (A i - (i. A i))  " for i
    using A by (metis Diff Diff_subset f_mono infinity_ennreal_def range_subsetD top_unique)
  have "(λi. f (A i - (i. A i)))  0"
  proof (intro cont[ OF _ decseq _ f_fin])
    show "range (λi. A i - (i. A i))  M" "(i. A i - (i. A i)) = {}"
      using A by auto
  qed
  with INF_Lim decseq_f have "(INF n. f (A n - (i. A i))) = 0" by metis
  moreover have "(INF n. f (i. A i)) = f (i. A i)"
    by auto
  ultimately have "(INF n. f (A n - (i. A i)) + f (i. A i)) = 0 + f (i. A i)"
    using A(4) f_fin f_Int_fin
    using INF_ennreal_add_const by presburger
  moreover {
    fix n
    have "f (A n - (i. A i)) + f (i. A i) = f ((A n - (i. A i))  (i. A i))"
      using A by (subst f(2)[THEN additiveD]) auto
    also have "(A n - (i. A i))  (i. A i) = A n"
      by auto
    finally have "f (A n - (i. A i)) + f (i. A i) = f (A n)" . }
  ultimately have "(INF n. f (A n)) = f (i. A i)"
    by simp
  with LIMSEQ_INF[OF decseq_fA]
  show "(λi. f (A i))  f (i. A i)" by simp
qed

lemma (in ring_of_sets) empty_continuous_imp_continuous_from_below:
  fixes f :: "'a set  ennreal"
  assumes f: "positive M f" "additive M f" "AM. f A  "
  assumes cont: "A. range A  M  decseq A  (i. A i) = {}  (λi. f (A i))  0"
  assumes A: "range A  M" "incseq A" "(i. A i)  M"
  shows "(λi. f (A i))  f (i. A i)"
proof -
  from A have "(λi. f ((i. A i) - A i))  0"
    by (intro cont[rule_format]) (auto simp: decseq_def incseq_def)
  moreover
  { fix i
    have "f ((i. A i) - A i  A i) = f ((i. A i) - A i) + f (A i)"
      using A by (intro f(2)[THEN additiveD]) auto
    also have "((i. A i) - A i)  A i = (i. A i)"
      by auto
    finally have "f ((i. A i) - A i) = f (i. A i) - f (A i)"
      using assms f by fastforce
  }
  moreover have "F i in sequentially. f (A i)  f (i. A i)"
    using increasingD[OF additive_increasing[OF f(1, 2)], of "A _" "i. A i"] A
    by (auto intro!: always_eventually simp: subset_eq)
  ultimately show "(λi. f (A i))  f (i. A i)"
    by (auto intro: ennreal_tendsto_const_minus)
qed

lemma (in ring_of_sets) empty_continuous_imp_countably_additive:
  fixes f :: "'a set  ennreal"
  assumes f: "positive M f" "additive M f" and fin: "AM. f A  "
  assumes cont: "A. range A  M  decseq A  (i. A i) = {}  (λi. f (A i))  0"
  shows "countably_additive M f"
  using countably_additive_iff_continuous_from_below[OF f]
  using empty_continuous_imp_continuous_from_below[OF f fin] cont
  by blast

subsectiontag unimportant› ‹Properties of constemeasure

lemma emeasure_positive: "positive (sets M) (emeasure M)"
  by (cases M) (auto simp: sets_def emeasure_def Abs_measure_inverse measure_space_def)

lemma emeasure_empty[simp, intro]: "emeasure M {} = 0"
  using emeasure_positive[of M] by (simp add: positive_def)

lemma emeasure_single_in_space: "emeasure M {x}  0  x  space M"
  using emeasure_notin_sets[of "{x}" M] by (auto dest: sets.sets_into_space zero_less_iff_neq_zero[THEN iffD2])

lemma emeasure_countably_additive: "countably_additive (sets M) (emeasure M)"
  by (cases M) (auto simp: sets_def emeasure_def Abs_measure_inverse measure_space_def)

lemma suminf_emeasure:
  "range A  sets M  disjoint_family A  (i. emeasure M (A i)) = emeasure M (i. A i)"
  using sets.countable_UN[of A UNIV M] emeasure_countably_additive[of M]
  by (simp add: countably_additive_def)

lemma sums_emeasure:
  "disjoint_family F  (i. F i  sets M)  (λi. emeasure M (F i)) sums emeasure M (i. F i)"
  unfolding sums_iff by (intro conjI suminf_emeasure) auto

lemma emeasure_additive: "additive (sets M) (emeasure M)"
  by (metis sets.countably_additive_additive emeasure_positive emeasure_countably_additive)

lemma plus_emeasure:
  "a  sets M  b  sets M  a  b = {}  emeasure M a + emeasure M b = emeasure M (a  b)"
  using additiveD[OF emeasure_additive] ..

lemma emeasure_Un:
  "A  sets M  B  sets M  emeasure M (A  B) = emeasure M A + emeasure M (B - A)"
  using plus_emeasure[of A M "B - A"] by auto

lemma emeasure_Un_Int:
  assumes "A  sets M" "B  sets M"
  shows "emeasure M A + emeasure M B = emeasure M (A  B) + emeasure M (A  B)"
proof -
  have "A = (A-B)  (A  B)" by auto
  then have "emeasure M A = emeasure M (A-B) + emeasure M (A  B)"
    by (metis Diff_Diff_Int Diff_disjoint assms plus_emeasure sets.Diff)
  moreover have "A  B = (A-B)  B" by auto
  then have "emeasure M (A  B) = emeasure M (A-B) + emeasure M B"
    by (metis Diff_disjoint Int_commute assms plus_emeasure sets.Diff)
  ultimately show ?thesis by (metis add.assoc add.commute)
qed

lemma sum_emeasure:
  "F`I  sets M  disjoint_family_on F I  finite I 
    (iI. emeasure M (F i)) = emeasure M (iI. F i)"
  by (metis sets.additive_sum emeasure_positive emeasure_additive)

lemma emeasure_mono:
  "a  b  b  sets M  emeasure M a  emeasure M b"
  by (metis zero_le sets.additive_increasing emeasure_additive emeasure_notin_sets emeasure_positive increasingD)

lemma emeasure_space:
  "emeasure M A  emeasure M (space M)"
  by (metis emeasure_mono emeasure_notin_sets sets.sets_into_space sets.top zero_le)

lemma emeasure_Diff:
  assumes "emeasure M B  "
  and "A  sets M" "B  sets M" and "B  A"
  shows "emeasure M (A - B) = emeasure M A - emeasure M B"
  by (smt (verit, best) add_diff_self_ennreal assms emeasure_Un emeasure_mono 
      ennreal_add_left_cancel le_iff_sup)

lemma emeasure_compl:
  "s  sets M  emeasure M s    emeasure M (space M - s) = emeasure M (space M) - emeasure M s"
  by (rule emeasure_Diff) (auto dest: sets.sets_into_space)

lemma Lim_emeasure_incseq:
  "range A  sets M  incseq A  (λi. (emeasure M (A i)))  emeasure M (i. A i)"
  using emeasure_countably_additive
  by (auto simp add: sets.countably_additive_iff_continuous_from_below emeasure_positive
    emeasure_additive)

lemma incseq_emeasure:
  assumes "range B  sets M" "incseq B"
  shows "incseq (λi. emeasure M (B i))"
  using assms by (auto simp: incseq_def intro!: emeasure_mono)

lemma SUP_emeasure_incseq:
  assumes A: "range A  sets M" "incseq A"
  shows "(SUP n. emeasure M (A n)) = emeasure M (i. A i)"
  using LIMSEQ_SUP[OF incseq_emeasure, OF A] Lim_emeasure_incseq[OF A]
  by (simp add: LIMSEQ_unique)

lemma decseq_emeasure:
  assumes "range B  sets M" "decseq B"
  shows "decseq (λi. emeasure M (B i))"
  using assms by (auto simp: decseq_def intro!: emeasure_mono)

lemma INF_emeasure_decseq:
  assumes A: "range A  sets M" and "decseq A"
  and finite: "i. emeasure M (A i)  "
  shows "(INF n. emeasure M (A n)) = emeasure M (i. A i)"
proof -
  have le_MI: "emeasure M (i. A i)  emeasure M (A 0)"
    using A by (auto intro!: emeasure_mono)
  hence *: "emeasure M (i. A i)  " using finite[of 0] by (auto simp: top_unique)

  have "emeasure M (A 0) - (INF n. emeasure M (A n)) = (SUP n. emeasure M (A 0) - emeasure M (A n))"
    by (simp add: ennreal_INF_const_minus)
  also have " = (SUP n. emeasure M (A 0 - A n))"
    using A finite decseq A[unfolded decseq_def] by (subst emeasure_Diff) auto
  also have " = emeasure M (i. A 0 - A i)"
  proof (rule SUP_emeasure_incseq)
    show "range (λn. A 0 - A n)  sets M"
      using A by auto
    show "incseq (λn. A 0 - A n)"
      using decseq A by (auto simp add: incseq_def decseq_def)
  qed
  also have " = emeasure M (A 0) - emeasure M (i. A i)"
    using A finite * by (simp, subst emeasure_Diff) auto
  finally show ?thesis
    by (smt (verit, best) Inf_lower diff_diff_ennreal le_MI finite range_eqI)
qed

lemma INF_emeasure_decseq':
  assumes A: "i. A i  sets M" and "decseq A"
  and finite: "i. emeasure M (A i)  "
  shows "(INF n. emeasure M (A n)) = emeasure M (i. A i)"
proof -
  from finite obtain i where i: "emeasure M (A i) < "
    by (auto simp: less_top)
  have fin: "i  j  emeasure M (A j) < " for j
    by (rule le_less_trans[OF emeasure_mono i]) (auto intro!: decseqD[OF decseq A] A)

  have "(INF n. emeasure M (A n)) = (INF n. emeasure M (A (n + i)))"
  proof (rule INF_eq)
    show "jUNIV. emeasure M (A (j + i))  emeasure M (A i')" for i'
      by (meson A decseq A decseq_def emeasure_mono iso_tuple_UNIV_I nat_le_iff_add)
  qed auto
  also have " = emeasure M (INF n. (A (n + i)))"
    using A decseq A fin by (intro INF_emeasure_decseq) (auto simp: decseq_def less_top)
  also have "(INF n. (A (n + i))) = (INF n. A n)"
    by (meson INF_eq UNIV_I assms(2) decseqD le_add1)
  finally show ?thesis .
qed

lemma emeasure_INT_decseq_subset:
  fixes F :: "nat  'a set"
  assumes I: "I  {}" and F: "i j. i  I  j  I  i  j  F j  F i"
  assumes F_sets[measurable]: "i. i  I  F i  sets M"
    and fin: "i. i  I  emeasure M (F i)  "
  shows "emeasure M (iI. F i) = (INF iI. emeasure M (F i))"
proof cases
  assume "finite I"
  have "(iI. F i) = F (Max I)"
    using I finite I by (intro antisym INF_lower INF_greatest F) auto
  moreover have "(INF iI. emeasure M (F i)) = emeasure M (F (Max I))"
    using I finite I by (intro antisym INF_lower INF_greatest F emeasure_mono) auto
  ultimately show ?thesis
    by simp
next
  assume "infinite I"
  define L where "L n = (LEAST i. i  I  i  n)" for n
  have L: "L n  I  n  L n" for n
    unfolding L_def
  proof (rule LeastI_ex)
    show "x. x  I  n  x"
      using infinite I finite_subset[of I "{..< n}"]
      by (rule_tac ccontr) (auto simp: not_le)
  qed
  have L_eq[simp]: "i  I  L i = i" for i
    unfolding L_def by (intro Least_equality) auto
  have L_mono: "i  j  L i  L j" for i j
    using L[of j] unfolding L_def by (intro Least_le) (auto simp: L_def)

  have "emeasure M (i. F (L i)) = (INF i. emeasure M (F (L i)))"
  proof (intro INF_emeasure_decseq[symmetric])
    show "decseq (λi. F (L i))"
      using L by (intro antimonoI F L_mono) auto
  qed (insert L fin, auto)
  also have " = (INF iI. emeasure M (F i))"
  proof (intro antisym INF_greatest)
    show "i  I  (INF i. emeasure M (F (L i)))  emeasure M (F i)" for i
      by (intro INF_lower2[of i]) auto
  qed (insert L, auto intro: INF_lower)
  also have "(i. F (L i)) = (iI. F i)"
  proof (intro antisym INF_greatest)
    show "i  I  (i. F (L i))  F i" for i
      by (intro INF_lower2[of i]) auto
  qed (insert L, auto)
  finally show ?thesis .
qed

lemma Lim_emeasure_decseq:
  assumes A: "range A  sets M" "decseq A" and fin: "i. emeasure M (A i)  "
  shows "(λi. emeasure M (A i))  emeasure M (i. A i)"
  using LIMSEQ_INF[OF decseq_emeasure, OF A]
  using INF_emeasure_decseq[OF A fin] by simp

lemma emeasure_lfp'[consumes 1, case_names cont measurable]:
  assumes "P M"
  assumes cont: "sup_continuous F"
  assumes *: "M A. P M  (N. P N  Measurable.pred N A)  Measurable.pred M (F A)"
  shows "emeasure M {xspace M. lfp F x} = (SUP i. emeasure M {xspace M. (F ^^ i) (λx. False) x})"
proof -
  have "emeasure M {xspace M. lfp F x} = emeasure M (i. {xspace M. (F ^^ i) (λx. False) x})"
    using sup_continuous_lfp[OF cont] by (auto simp add: bot_fun_def intro!: arg_cong2[where f=emeasure])
  moreover { fix i from P M have "{xspace M. (F ^^ i) (λx. False) x}  sets M"
    by (induct i arbitrary: M) (auto simp add: pred_def[symmetric] intro: *) }
  moreover have "incseq (λi. {xspace M. (F ^^ i) (λx. False) x})"
  proof (rule incseq_SucI)
    fix i
    have "(F ^^ i) (λx. False)  (F ^^ (Suc i)) (λx. False)"
    proof (induct i)
      case 0 show ?case by (simp add: le_fun_def)
    next
      case Suc thus ?case using monoD[OF sup_continuous_mono[OF cont] Suc] by auto
    qed
    then show "{x  space M. (F ^^ i) (λx. False) x}  {x  space M. (F ^^ Suc i) (λx. False) x}"
      by auto
  qed
  ultimately show ?thesis
    by (subst SUP_emeasure_incseq) auto
qed

lemma emeasure_lfp:
  assumes [simp]: "s. sets (M s) = sets N"
  assumes cont: "sup_continuous F" "sup_continuous f"
  assumes meas: "P. Measurable.pred N P  Measurable.pred N (F P)"
  assumes iter: "P s. Measurable.pred N P  P  lfp F  emeasure (M s) {xspace N. F P x} = f (λs. emeasure (M s) {xspace N. P x}) s"
  shows "emeasure (M s) {xspace N. lfp F x} = lfp f s"
proof (subst lfp_transfer_bounded[where α="λF s. emeasure (M s) {xspace N. F x}" and f=F , symmetric])
  fix C assume "incseq C" "i. Measurable.pred N (C i)"
  then show "(λs. emeasure (M s) {x  space N. (SUP i. C i) x}) = (SUP i. (λs. emeasure (M s) {x  space N. C i x}))"
    unfolding SUP_apply
    by (subst SUP_emeasure_incseq) (auto simp: mono_def fun_eq_iff intro!: arg_cong2[where f=emeasure])
qed (auto simp add: iter le_fun_def SUP_apply intro!: meas cont)

lemma emeasure_subadditive_finite:
  "finite I  A ` I  sets M  emeasure M (iI. A i)  (iI. emeasure M (A i))"
  by (rule sets.subadditive[OF emeasure_positive emeasure_additive]) auto

lemma emeasure_subadditive:
  "A  sets M  B  sets M  emeasure M (A  B)  emeasure M A + emeasure M B"
  using emeasure_subadditive_finite[of "{True, False}" "λTrue  A | False  B" M] by simp

lemma emeasure_subadditive_countably:
  assumes "range f  sets M"
  shows "emeasure M (i. f i)  (i. emeasure M (f i))"
proof -
  have "emeasure M (i. f i) = emeasure M (i. disjointed f i)"
    unfolding UN_disjointed_eq ..
  also have " = (i. emeasure M (disjointed f i))"
    using sets.range_disjointed_sets[OF assms] suminf_emeasure[of "disjointed f"]
    by (simp add:  disjoint_family_disjointed comp_def)
  also have "  (i. emeasure M (f i))"
    using sets.range_disjointed_sets[OF assms] assms
    by (auto intro!: suminf_le emeasure_mono disjointed_subset)
  finally show ?thesis .
qed

lemma emeasure_insert:
  assumes sets: "{x}  sets M" "A  sets M" and "x  A"
  shows "emeasure M (insert x A) = emeasure M {x} + emeasure M A"
proof -
  have "{x}  A = {}" using x  A by auto
  from plus_emeasure[OF sets this] show ?thesis by simp
qed

lemma emeasure_insert_ne:
  "A  {}  {x}  sets M  A  sets M  x  A  emeasure M (insert x A) = emeasure M {x} + emeasure M A"
  by (rule emeasure_insert)

lemma emeasure_eq_sum_singleton:
  assumes "finite S" "x. x  S  {x}  sets M"
  shows "emeasure M S = (xS. emeasure M {x})"
  using sum_emeasure[of "λx. {x}" S M] assms
  by (auto simp: disjoint_family_on_def subset_eq)

lemma sum_emeasure_cover:
  assumes "finite S" and "A  sets M" and br_in_M: "B ` S  sets M"
  assumes A: "A  (iS. B i)"
  assumes disj: "disjoint_family_on B S"
  shows "emeasure M A = (iS. emeasure M (A  (B i)))"
proof -
  have "(iS. emeasure M (A  (B i))) = emeasure M (iS. A  (B i))"
  proof (rule sum_emeasure)
    show "disjoint_family_on (λi. A  B i) S"
      using disjoint_family_on B S
      unfolding disjoint_family_on_def by auto
  qed (insert assms, auto)
  also have "(iS. A  (B i)) = A"
    using A by auto
  finally show ?thesis by simp
qed

lemma emeasure_eq_0:
  "N  sets M  emeasure M N = 0  K  N  emeasure M K = 0"
  by (metis emeasure_mono order_eq_iff zero_le)

lemma emeasure_UN_eq_0:
  assumes "i::nat. emeasure M (N i) = 0" and "range N  sets M"
  shows "emeasure M (i. N i) = 0"
proof -
  have "emeasure M (i. N i)  0"
    using emeasure_subadditive_countably[OF assms(2)] assms(1) by simp
  then show ?thesis
    by (auto intro: antisym zero_le)
qed

lemma measure_eqI_finite:
  assumes [simp]: "sets M = Pow A" "sets N = Pow A" and "finite A"
  assumes eq: "a. a  A  emeasure M {a} = emeasure N {a}"
  shows "M = N"
proof (rule measure_eqI)
  fix X assume "X  sets M"
  then have X: "X  A" by auto
  then have "emeasure M X = (aX. emeasure M {a})"
    using finite A by (subst emeasure_eq_sum_singleton) (auto dest: finite_subset)
  also have " = (aX. emeasure N {a})"
    using X eq by (auto intro!: sum.cong)
  also have " = emeasure N X"
    using X finite A by (subst emeasure_eq_sum_singleton) (auto dest: finite_subset)
  finally show "emeasure M X = emeasure N X" .
qed simp

lemma measure_eqI_generator_eq:
  fixes M N :: "'a measure" and E :: "'a set set" and A :: "nat  'a set"
  assumes "Int_stable E" "E  Pow Ω"
  and eq: "X. X  E  emeasure M X = emeasure N X"
  and M: "sets M = sigma_sets Ω E"
  and N: "sets N = sigma_sets Ω E"
  and A: "range A  E" "(i. A i) = Ω" "i. emeasure M (A i)  "
  shows "M = N"
proof -
  let   = "emeasure M" and  = "emeasure N"
  interpret S: sigma_algebra Ω "sigma_sets Ω E" by (rule sigma_algebra_sigma_sets) fact
  have "space M = Ω"
    using sets.top[of M] sets.space_closed[of M] S.top S.space_closed sets M = sigma_sets Ω E
    by blast

  { fix F D assume "F  E" and " F  "
    then have [intro]: "F  sigma_sets Ω E" by auto
    have " F  " using  F   F  E eq by simp
    assume "D  sets M"
    with Int_stable E E  Pow Ω have "emeasure M (F  D) = emeasure N (F  D)"
      unfolding M
    proof (induct rule: sigma_sets_induct_disjoint)
      case (basic A)
      then have "F  A  E" using Int_stable E F  E by (auto simp: Int_stable_def)
      then show ?case using eq by auto
    next
      case empty then show ?case by simp
    next
      case (compl A)
      then have **: "F  (Ω - A) = F - (F  A)"
        and [intro]: "F  A  sigma_sets Ω E"
        using F  E S.sets_into_space by (auto simp: M)
      have " (F  A)   F" by (auto intro!: emeasure_mono simp: M N)
      then have " (F  A)  " using  F   by (auto simp: top_unique)
      have " (F  A)   F" by (auto intro!: emeasure_mono simp: M N)
      then have " (F  A)  " using  F   by (auto simp: top_unique)
      then have " (F  (Ω - A)) =  F -  (F  A)" unfolding **
        using F  A  sigma_sets Ω E by (auto intro!: emeasure_Diff simp: M N)
      also have " =  F -  (F  A)" using eq F  E compl by simp
      also have " =  (F  (Ω - A))" unfolding **
        using F  A  sigma_sets Ω E  (F  A)  
        by (auto intro!: emeasure_Diff[symmetric] simp: M N)
      finally show ?case
        using space M = Ω by auto
    next
      case (union A)
      then have " (x. F  A x) =  (x. F  A x)"
        by (subst (1 2) suminf_emeasure[symmetric]) (auto simp: disjoint_family_on_def subset_eq M N)
      with A show ?case
        by auto
    qed }
  note * = this
  show "M = N"
  proof (rule measure_eqI)
    show "sets M = sets N"
      using M N by simp
    have [simp, intro]: "i. A i  sets M"
      using A(1) by (auto simp: subset_eq M)
    fix F assume "F  sets M"
    let ?D = "disjointed (λi. F  A i)"
    from space M = Ω have F_eq: "F = (i. ?D i)"
      using F  sets M[THEN sets.sets_into_space] A(2)[symmetric] by (auto simp: UN_disjointed_eq)
    have [simp, intro]: "i. ?D i  sets M"
      using sets.range_disjointed_sets[of "λi. F  A i" M] F  sets M
      by (auto simp: subset_eq)
    have "disjoint_family ?D"
      by (auto simp: disjoint_family_disjointed)
    moreover
    have "(i. emeasure M (?D i)) = (i. emeasure N (?D i))"
    proof (intro arg_cong[where f=suminf] ext)
      fix i
      have "A i  ?D i = ?D i"
        by (auto simp: disjointed_def)
      then show "emeasure M (?D i) = emeasure N (?D i)"
        using *[of "A i" "?D i", OF _ A(3)] A(1) by auto
    qed
    ultimately show "emeasure M F = emeasure N F"
      by (simp add: image_subset_iff sets M = sets N[symmetric] F_eq[symmetric] suminf_emeasure)
  qed
qed

lemma space_empty: "space M = {}  M = count_space {}"
  by (rule measure_eqI) (simp_all add: space_empty_iff)

lemma measure_eqI_generator_eq_countable:
  fixes M N :: "'a measure" and E :: "'a set set" and A :: "'a set set"
  assumes E: "Int_stable E" "E  Pow Ω" "X. X  E  emeasure M X = emeasure N X"
    and sets: "sets M = sigma_sets Ω E" "sets N = sigma_sets Ω E"
  and A: "A  E" "(A) = Ω" "countable A" "a. a  A  emeasure M a  "
  shows "M = N"
proof cases
  assume "Ω = {}"
  have *: "sigma_sets Ω E = sets (sigma Ω E)"
    using E(2) by simp
  have "space M = Ω" "space N = Ω"
    using sets E(2) unfolding * by (auto dest: sets_eq_imp_space_eq simp del: sets_measure_of)
  then show "M = N"
    unfolding Ω = {} by (auto dest: space_empty)
next
  assume "Ω  {}" with A = Ω have "A  {}" by auto
  from this countable A have rng: "range (from_nat_into A) = A"
    by (rule range_from_nat_into)
  show "M = N"
  proof (rule measure_eqI_generator_eq[OF E sets])
    show "range (from_nat_into A)  E"
      unfolding rng using A  E .
    show "(i. from_nat_into A i) = Ω"
      unfolding rng using A = Ω .
    show "emeasure M (from_nat_into A i)  " for i
      using rng by (intro A) auto
  qed
qed

lemma measure_of_of_measure: "measure_of (space M) (sets M) (emeasure M) = M"
proof (intro measure_eqI emeasure_measure_of_sigma)
  show "sigma_algebra (space M) (sets M)" ..
  show "positive (sets M) (emeasure M)"
    by (simp add: positive_def)
  show "countably_additive (sets M) (emeasure M)"
    by (simp add: emeasure_countably_additive)
qed simp_all

subsection μ›-null sets›

definitiontag important› null_sets :: "'a measure  'a set set" where
  "null_sets M = {Nsets M. emeasure M N = 0}"

lemma null_setsD1[dest]: "A  null_sets M  emeasure M A = 0"
  by (simp add: null_sets_def)

lemma null_setsD2[dest]: "A  null_sets M  A  sets M"
  unfolding null_sets_def by simp

lemma null_setsI[intro]: "emeasure M A = 0  A  sets M  A  null_sets M"
  unfolding null_sets_def by simp

interpretation null_sets: ring_of_sets "space M" "null_sets M" for M
proof (rule ring_of_setsI)
  show "null_sets M  Pow (space M)"
    using sets.sets_into_space by auto
  show "{}  null_sets M"
    by auto
  fix A B assume null_sets: "A  null_sets M" "B  null_sets M"
  then have sets: "A  sets M" "B  sets M"
    by auto
  then have *: "emeasure M (A  B)  emeasure M A + emeasure M B"
    "emeasure M (A - B)  emeasure M A"
    by (auto intro!: emeasure_subadditive emeasure_mono)
  then have "emeasure M B = 0" "emeasure M A = 0"
    using null_sets by auto
  with sets * show "A - B  null_sets M" "A  B  null_sets M"
    by (auto intro!: antisym zero_le)
qed

lemma UN_from_nat_into:
  assumes I: "countable I" "I  {}"
  shows "(iI. N i) = (i. N (from_nat_into I i))"
proof -
  have "(iI. N i) = (N ` range (from_nat_into I))"
    using I by simp
  also have " = (i. (N  from_nat_into I) i)"
    by simp
  finally show ?thesis by simp
qed

lemma null_sets_UN':
  assumes "countable I"
  assumes "i. i  I  N i  null_sets M"
  shows "(iI. N i)  null_sets M"
proof cases
  assume "I = {}" then show ?thesis by simp
next
  assume "I  {}"
  show ?thesis
  proof (intro conjI CollectI null_setsI)
    show "(iI. N i)  sets M"
      using assms by (intro sets.countable_UN') auto
    have "emeasure M (iI. N i)  (n. emeasure M (N (from_nat_into I n)))"
      unfolding UN_from_nat_into[OF countable I I  {}]
      using assms I  {} by (intro emeasure_subadditive_countably) (auto intro: from_nat_into)
    also have "(λn. emeasure M (N (from_nat_into I n))) = (λ_. 0)"
      using assms I  {} by (auto intro: from_nat_into)
    finally show "emeasure M (iI. N i) = 0"
      by (intro antisym zero_le) simp
  qed
qed

lemma null_sets_UN[intro]:
  "(i::'i::countable. N i  null_sets M)  (i. N i)  null_sets M"
  by (rule null_sets_UN') auto

lemma null_set_Int1:
  assumes "B  null_sets M" "A  sets M" shows "A  B  null_sets M"
proof (intro CollectI conjI null_setsI)
  show "emeasure M (A  B) = 0" using assms
    by (intro emeasure_eq_0[of B _ "A  B"]) auto
qed (insert assms, auto)

lemma null_set_Int2:
  assumes "B  null_sets M" "A  sets M" shows "B  A  null_sets M"
  using assms by (subst Int_commute) (rule null_set_Int1)

lemma emeasure_Diff_null_set:
  assumes "B  null_sets M" "A  sets M"
  shows "emeasure M (A - B) = emeasure M A"
proof -
  have *: "A - B = (A - (A  B))" by auto
  have "A  B  null_sets M" using assms by (rule null_set_Int1)
  then show ?thesis
    unfolding * using assms
    by (subst emeasure_Diff) auto
qed

lemma null_set_Diff:
  assumes "B  null_sets M" "A  sets M" shows "B - A  null_sets M"
proof (intro CollectI conjI null_setsI)
  show "emeasure M (B - A) = 0" using assms by (intro emeasure_eq_0[of B _ "B - A"]) auto
qed (insert assms, auto)

lemma emeasure_Un_null_set:
  assumes "A  sets M" "B  null_sets M"
  shows "emeasure M (A  B) = emeasure M A"
proof -
  have *: "A  B = A  (B - A)" by auto
  have "B - A  null_sets M" using assms(2,1) by (rule null_set_Diff)
  then show ?thesis
    unfolding * using assms
    by (subst plus_emeasure[symmetric]) auto
qed

lemma emeasure_Un':
  assumes "A  sets M" "B  sets M" "A  B  null_sets M"
  shows   "emeasure M (A  B) = emeasure M A + emeasure M B"
proof -
  have "A  B = A  (B - A  B)" by blast
  also have "emeasure M  = emeasure M A + emeasure M (B - A  B)"
    using assms by (subst plus_emeasure) auto
  also have "emeasure M (B - A  B) = emeasure M B"
    using assms by (intro emeasure_Diff_null_set) auto
  finally show ?thesis .
qed

subsection ‹The almost everywhere filter (i.e.\ quantifier)›

definitiontag important› ae_filter :: "'a measure  'a filter" where
  "ae_filter M = (INF Nnull_sets M. principal (space M - N))"

abbreviation almost_everywhere :: "'a measure  ('a  bool)  bool" where
  "almost_everywhere M P  eventually P (ae_filter M)"

syntax
  "_almost_everywhere" :: "pttrn  'a  bool  bool" ("AE _ in _. _" [0,0,10] 10)

translations
  "AE x in M. P"  "CONST almost_everywhere M (λx. P)"

abbreviation
  "set_almost_everywhere A M P  AE x in M. x  A  P x"

syntax
  "_set_almost_everywhere" :: "pttrn  'a set  'a  bool  bool"
  ("AE __ in _./ _" [0,0,0,10] 10)

translations
  "AE xA in M. P"  "CONST set_almost_everywhere A M (λx. P)"

lemma eventually_ae_filter: "eventually P (ae_filter M)  (Nnull_sets M. {x  space M. ¬ P x}  N)"
  unfolding ae_filter_def by (subst eventually_INF_base) (auto simp: eventually_principal subset_eq)

lemma AE_I':
  "N  null_sets M  {xspace M. ¬ P x}  N  (AE x in M. P x)"
  unfolding eventually_ae_filter by auto

lemma AE_iff_null:
  assumes "{xspace M. ¬ P x}  sets M" (is "?P  sets M")
  shows "(AE x in M. P x)  {xspace M. ¬ P x}  null_sets M"
proof
  assume "AE x in M. P x" then obtain N where N: "N  sets M" "?P  N" "emeasure M N = 0"
    unfolding eventually_ae_filter by auto
  have "emeasure M ?P  emeasure M N"
    using assms N(1,2) by (auto intro: emeasure_mono)
  then have "emeasure M ?P = 0"
    unfolding emeasure M N = 0 by auto
  then show "?P  null_sets M" using assms by auto
next
  assume "?P  null_sets M" with assms show "AE x in M. P x" by (auto intro: AE_I')
qed

lemma AE_iff_null_sets:
  "N  sets M  N  null_sets M  (AE x in M. x  N)"
  using Int_absorb1[OF sets.sets_into_space, of N M]
  by (subst AE_iff_null) (auto simp: Int_def[symmetric])

lemma ae_filter_eq_bot_iff: "ae_filter M = bot  emeasure M (space M) = 0"
proof -
  have "ae_filter M = bot  (AE x in M. False)"
    using trivial_limit_def by blast
  also have "  space M  null_sets M"
    by (simp add: AE_iff_null_sets eventually_ae_filter)
  also have "  emeasure M (space M) = 0"
    by auto
  finally show ?thesis .
qed

lemma AE_not_in:
  "N  null_sets M  AE x in M. x  N"
  by (metis AE_iff_null_sets null_setsD2)

lemma AE_iff_measurable:
  "N  sets M  {xspace M. ¬ P x} = N  (AE x in M. P x)  emeasure M N = 0"
  using AE_iff_null[of _ P] by auto

lemma AE_E[consumes 1]:
  assumes "AE x in M. P x"
  obtains N where "{x  space M. ¬ P x}  N" "emeasure M N = 0" "N  sets M"
  using assms unfolding eventually_ae_filter by auto

lemma AE_E2:
  assumes "AE x in M. P x"
  shows "emeasure M {xspace M. ¬ P x} = 0"
  by (metis (mono_tags, lifting) AE_iff_null assms emeasure_notin_sets null_setsD1)

lemma AE_E3:
  assumes "AE x in M. P x"
  obtains N where "x. x  space M - N  P x" "N  null_sets M"
using assms unfolding eventually_ae_filter by auto

lemma AE_I:
  assumes "{x  space M. ¬ P x}  N" "emeasure M N = 0" "N  sets M"
  shows "AE x in M. P x"
  using assms unfolding eventually_ae_filter by auto

lemma AE_mp[elim!]:
  assumes AE_P: "AE x in M. P x" and AE_imp: "AE x in M. P x  Q x"
  shows "AE x in M. Q x"
  using assms by (fact eventually_rev_mp)

text ‹The next lemma is convenient to combine with a lemma whose conclusion is of the
form AE x in M. P x = Q x›: for such a lemma, there is no [symmetric]› variant,
but using AE_symmetric[OF…]› will replace it.›

(* depricated replace by laws about eventually *)
lemma
  shows AE_iffI: "AE x in M. P x  AE x in M. P x  Q x  AE x in M. Q x"
    and AE_disjI1: "AE x in M. P x  AE x in M. P x  Q x"
    and AE_disjI2: "AE x in M. Q x  AE x in M. P x  Q x"
    and AE_conjI: "AE x in M. P x  AE x in M. Q x  AE x in M. P x  Q x"
    and AE_conj_iff[simp]: "(AE x in M. P x  Q x)  (AE x in M. P x)  (AE x in M. Q x)"
  by auto

lemma AE_symmetric:
  assumes "AE x in M. P x = Q x"
  shows "AE x in M. Q x = P x"
  using assms by auto

lemma AE_impI:
  "(P  AE x in M. Q x)  AE x in M. P  Q x"
  by fastforce

lemma AE_measure:
  assumes AE: "AE x in M. P x" and sets: "{xspace M. P x}  sets M" (is "?P  sets M")
  shows "emeasure M {xspace M. P x} = emeasure M (space M)"
proof -
  from AE_E[OF AE] obtain N
    where N: "{x  space M. ¬ P x}  N" "emeasure M N = 0" "N  sets M"
    by auto
  with sets have "emeasure M (space M)  emeasure M (?P  N)"
    by (intro emeasure_mono) auto
  also have "  emeasure M ?P + emeasure M N"
    using sets N by (intro emeasure_subadditive) auto
  also have " = emeasure M ?P" using N by simp
  finally show "emeasure M ?P = emeasure M (space M)"
    using emeasure_space[of M "?P"] by auto
qed

lemma AE_space: "AE x in M. x  space M"
  by (rule AE_I[where N="{}"]) auto

lemma AE_I2[simp, intro]:
  "(x. x  space M  P x)  AE x in M. P x"
  using AE_space by force

lemma AE_Ball_mp:
  "xspace M. P x  AE x in M. P x  Q x  AE x in M. Q x"
  by auto

lemma AE_cong[cong]:
  "(x. x  space M  P x  Q x)  (AE x in M. P x)  (AE x in M. Q x)"
  by auto

lemma AE_cong_simp: "M = N  (x. x  space N =simp=> P x = Q x)  (AE x in M. P x)  (AE x in N. Q x)"
  by (auto simp: simp_implies_def)

lemma AE_all_countable:
  "(AE x in M. i. P i x)  (i::'i::countable. AE x in M. P i x)"
proof
  assume "i. AE x in M. P i x"
  from this[unfolded eventually_ae_filter Bex_def, THEN choice]
  obtain N where N: "i. N i  null_sets M" "i. {xspace M. ¬ P i x}  N i" by auto
  have "{xspace M. ¬ (i. P i x)}  (i. {xspace M. ¬ P i x})" by auto
  also have "  (i. N i)" using N by auto
  finally have "{xspace M. ¬ (i. P i x)}  (i. N i)" .
  moreover from N have "(i. N i)  null_sets M"
    by (intro null_sets_UN) auto
  ultimately show "AE x in M. i. P i x"
    unfolding eventually_ae_filter by auto
qed auto

lemma AE_ball_countable:
  assumes [intro]: "countable X"
  shows "(AE x in M. yX. P x y)  (yX. AE x in M. P x y)"
proof
  assume "yX. AE x in M. P x y"
  from this[unfolded eventually_ae_filter Bex_def, THEN bchoice]
  obtain N where N: "y. y  X  N y  null_sets M" "y. y  X  {xspace M. ¬ P x y}  N y"
    by auto
  have "{xspace M. ¬ (yX. P x y)}  (yX. {xspace M. ¬ P x y})"
    by auto
  also have "  (yX. N y)"
    using N by auto
  finally have "{xspace M. ¬ (yX. P x y)}  (yX. N y)" .
  moreover from N have "(yX. N y)  null_sets M"
    by (intro null_sets_UN') auto
  ultimately show "AE x in M. yX. P x y"
    unfolding eventually_ae_filter by auto
qed auto

lemma AE_ball_countable':
  "(N. N  I  AE x in M. P N x)  countable I  AE x in M. N  I. P N x"
  unfolding AE_ball_countable by simp

lemma AE_pairwise: "countable F  pairwise (λA B. AE x in M. R x A B) F  (AE x in M. pairwise (R x) F)"
  unfolding pairwise_alt by (simp add: AE_ball_countable)

lemma AE_discrete_difference:
  assumes X: "countable X"
  assumes null: "x. x  X  emeasure M {x} = 0"
  assumes sets: "x. x  X  {x}  sets M"
  shows "AE x in M. x  X"
proof -
  have "(xX. {x})  null_sets M"
    using assms by (intro null_sets_UN') auto
  from AE_not_in[OF this] show "AE x in M. x  X"
    by auto
qed

lemma AE_finite_all:
  assumes f: "finite S" shows "(AE x in M. iS. P i x)  (iS. AE x in M. P i x)"
  using f by induct auto

lemma AE_finite_allI:
  assumes "finite S"
  shows "(s. s  S  AE x in M. Q s x)  AE x in M. sS. Q s x"
  using AE_finite_all[OF finite S] by auto

lemma emeasure_mono_AE:
  assumes imp: "AE x in M. x  A  x  B"
    and B: "B  sets M"
  shows "emeasure M A  emeasure M B"
proof cases
  assume A: "A  sets M"
  from imp obtain N where N: "{xspace M. ¬ (x  A  x  B)}  N" "N  null_sets M"
    by (auto simp: eventually_ae_filter)
  have "emeasure M A = emeasure M (A - N)"
    using N A by (subst emeasure_Diff_null_set) auto
  also have "emeasure M (A - N)  emeasure M (B - N)"
    using N A B sets.sets_into_space by (auto intro!: emeasure_mono)
  also have "emeasure M (B - N) = emeasure M B"
    using N B by (subst emeasure_Diff_null_set) auto
  finally show ?thesis .
qed (simp add: emeasure_notin_sets)

lemma emeasure_eq_AE:
  assumes iff: "AE x in M. x  A  x  B"
  assumes A: "A  sets M" and B: "B  sets M"
  shows "emeasure M A = emeasure M B"
  using assms by (safe intro!: antisym emeasure_mono_AE) auto

lemma emeasure_Collect_eq_AE:
  "AE x in M. P x  Q x  Measurable.pred M Q  Measurable.pred M P 
   emeasure M {xspace M. P x} = emeasure M {xspace M. Q x}"
   by (intro emeasure_eq_AE) auto

lemma emeasure_eq_0_AE: "AE x in M. ¬ P x  emeasure M {xspace M. P x} = 0"
  using AE_iff_measurable[OF _ refl, of M "λx. ¬ P x"]
  by (cases "{xspace M. P x}  sets M") (simp_all add: emeasure_notin_sets)

lemma emeasure_0_AE:
  assumes "emeasure M (space M) = 0"
  shows "AE x in M. P x"
using eventually_ae_filter assms by blast

lemma emeasure_add_AE:
  assumes [measurable]: "A  sets M" "B  sets M" "C  sets M"
  assumes 1: "AE x in M. x  C  x  A  x  B"
  assumes 2: "AE x in M. ¬ (x  A  x  B)"
  shows "emeasure M C = emeasure M A + emeasure M B"
proof -
  have "emeasure M C = emeasure M (A  B)"
    by (rule emeasure_eq_AE) (insert 1, auto)
  also have " = emeasure M A + emeasure M (B - A)"
    by (subst plus_emeasure) auto
  also have "emeasure M (B - A) = emeasure M B"
    by (rule emeasure_eq_AE) (insert 2, auto)
  finally show ?thesis .
qed

subsection σ›-finite Measures›

localetag important› sigma_finite_measure =
  fixes M :: "'a measure"
  assumes sigma_finite_countable:
    "A::'a set set. countable A  A  sets M  (A) = space M  (aA. emeasure M a  )"

lemma (in sigma_finite_measure) sigma_finite:
  obtains A :: "nat  'a set"
  where "range A  sets M" "(i. A i) = space M" "i. emeasure M (A i)  "
proof -
  obtain A :: "'a set set" where
    [simp]: "countable A" and
    A: "A  sets M" "(A) = space M" "a. a  A  emeasure M a  "
    using sigma_finite_countable by metis
  show thesis
  proof cases
    assume "A = {}" with (A) = space M show thesis
      by (intro that[of "λ_. {}"]) auto
  next
    assume "A  {}"
    show thesis
    proof
      show "range (from_nat_into A)  sets M"
        using A  {} A by auto
      have "(i. from_nat_into A i) = A"
        using range_from_nat_into[OF A  {} countable A] by auto
      with A show "(i. from_nat_into A i) = space M"
        by auto
    qed (intro A from_nat_into A  {})
  qed
qed

lemma (in sigma_finite_measure) sigma_finite_disjoint:
  obtains A :: "nat  'a set"
  where "range A  sets M" "(i. A i) = space M" "i. emeasure M (A i)  " "disjoint_family A"
proof -
  obtain A :: "nat  'a set" where
    range: "range A  sets M" and
    space: "(i. A i) = space M" and
    measure: "i. emeasure M (A i)  "
    using sigma_finite by blast
  show thesis
  proof (rule that[of "disjointed A"])
    show "range (disjointed A)  sets M"
      by (rule sets.range_disjointed_sets[OF range])
    show "(i. disjointed A i) = space M"
      and "disjoint_family (disjointed A)"
      using disjoint_family_disjointed UN_disjointed_eq[of A] space range
      by auto
    show "emeasure M (disjointed A i)  " for i
    proof -
      have "emeasure M (disjointed A i)  emeasure M (A i)"
        using range disjointed_subset[of A i] by (auto intro!: emeasure_mono)
      then show ?thesis using measure[of i] by (auto simp: top_unique)
    qed
  qed
qed

lemma (in sigma_finite_measure) sigma_finite_incseq:
  obtains A :: "nat  'a set"
  where "range A  sets M" "(i. A i) = space M" "i. emeasure M (A i)  " "incseq A"
proof -
  obtain F :: "nat  'a set" where
    F: "range F  sets M" "(i. F i) = space M" "i. emeasure M (F i)  "
    using sigma_finite by blast
  show thesis
  proof (rule that[of "λn. in. F i"])
    show "range (λn. in. F i)  sets M"
      using F by (force simp: incseq_def)
    show "(n. in. F i) = space M"
    proof -
      from F have "x. x  space M  i. x  F i" by auto
      with F show ?thesis by fastforce
    qed
    show "emeasure M (in. F i)  " for n
    proof -
      have "emeasure M (in. F i)  (in. emeasure M (F i))"
        using F by (auto intro!: emeasure_subadditive_finite)
      also have " < "
        using F by (auto simp: sum_Pinfty less_top)
      finally show ?thesis by simp
    qed
    show "incseq (λn. in. F i)"
      by (force simp: incseq_def)
  qed
qed

lemma (in sigma_finite_measure) approx_PInf_emeasure_with_finite:
  fixes C::real
  assumes W_meas: "W  sets M"
      and W_inf: "emeasure M W = "
  obtains Z where "Z  sets M" "Z  W" "emeasure M Z < " "emeasure M Z > C"
proof -
  obtain A :: "nat  'a set"
    where A: "range A  sets M" "(i. A i) = space M" "i. emeasure M (A i)  " "incseq A"
    using sigma_finite_incseq by blast
  define B where "B = (λi. W  A i)"
  have B_meas: "i. B i  sets M" using W_meas range A  sets M B_def by blast
  have b: "i. B i  W" using B_def by blast

  { fix i
    have "emeasure M (B i)  emeasure M (A i)"
      using A by (intro emeasure_mono) (auto simp: B_def)
    also have "emeasure M (A i) < "
      using i. emeasure M (A i)   by (simp add: less_top)
    finally have "emeasure M (B i) < " . }
  note c = this

  have "W = (i. B i)" using B_def (i. A i) = space M W_meas by auto
  moreover have "incseq B" using B_def incseq A by (simp add: incseq_def subset_eq)
  ultimately have "(λi. emeasure M (B i))  emeasure M W" using W_meas B_meas
    by (simp add: B_meas Lim_emeasure_incseq image_subset_iff)
  then have "(λi. emeasure M (B i))  " using W_inf by simp
  from order_tendstoD(1)[OF this, of C]
  obtain i where d: "emeasure M (B i) > C"
    by (auto simp: eventually_sequentially)
  have "B i  sets M" "B i  W" "emeasure M (B i) < " "emeasure M (B i) > C"
    using B_meas b c d by auto
  then show ?thesis using that by blast
qed

subsection ‹Measure space induced by distribution of constmeasurable-functions›

definitiontag important› distr :: "'a measure  'b measure  ('a  'b)  'b measure" where
"distr M N f =
  measure_of (space N) (sets N) (λA. emeasure M (f -` A  space M))"

lemma
  shows sets_distr[simp, measurable_cong]: "sets (distr M N f) = sets N"
    and space_distr[simp]: "space (distr M N f) = space N"
  by (auto simp: distr_def)

lemma
  shows measurable_distr_eq1[simp]: "measurable (distr Mf Nf f) Mf' = measurable Nf Mf'"
    and measurable_distr_eq2[simp]: "measurable Mg' (distr Mg Ng g) = measurable Mg' Ng"
  by (auto simp: measurable_def)

lemma distr_cong:
  "M = K  sets N = sets L  (x. x  space M  f x = g x)  distr M N f = distr K L g"
  using sets_eq_imp_space_eq[of N L] by (simp add: distr_def Int_def cong: rev_conj_cong)

lemma emeasure_distr:
  fixes f :: "'a  'b"
  assumes f: "f  measurable M N" and A: "A  sets N"
  shows "emeasure (distr M N f) A = emeasure M (f -` A  space M)" (is "_ =  A")
  unfolding distr_def
proof (rule emeasure_measure_of_sigma)
  show "positive (sets N) "
    by (auto simp: positive_def)

  show "countably_additive (sets N) "
  proof (intro countably_additiveI)
    fix A :: "nat  'b set" assume "range A  sets N" "disjoint_family A"
    then have A: "i. A i  sets N" "(i. A i)  sets N" by auto
    then have *: "range (λi. f -` (A i)  space M)  sets M"
      using f by (auto simp: measurable_def)
    moreover have "(i. f -`  A i  space M)  sets M"
      using * by blast
    moreover have **: "disjoint_family (λi. f -` A i  space M)"
      using disjoint_family A by (auto simp: disjoint_family_on_def)
    ultimately show "(i.  (A i)) =  (i. A i)"
      using suminf_emeasure[OF _ **] A f
      by (auto simp: comp_def vimage_UN)
  qed
  show "sigma_algebra (space N) (sets N)" ..
qed fact

lemma emeasure_Collect_distr:
  assumes X[measurable]: "X  measurable M N" "Measurable.pred N P"
  shows "emeasure (distr M N X) {xspace N. P x} = emeasure M {xspace M. P (X x)}"
  by (subst emeasure_distr)
     (auto intro!: arg_cong2[where f=emeasure] X(1)[THEN measurable_space])

lemma emeasure_lfp2[consumes 1, case_names cont f measurable]:
  assumes "P M"
  assumes cont: "sup_continuous F"
  assumes f: "M. P M  f  measurable M' M"
  assumes *: "M A. P M  (N. P N  Measurable.pred N A)  Measurable.pred M (F A)"
  shows "emeasure M' {xspace M'. lfp F (f x)} = (SUP i. emeasure M' {xspace M'. (F ^^ i) (λx. False) (f x)})"
proof (subst (1 2) emeasure_Collect_distr[symmetric, where X=f])
  show "f  measurable M' M"  "f  measurable M' M"
    using f[OF P M] by auto
  { fix i show "Measurable.pred M ((F ^^ i) (λx. False))"
    using P M by (induction i arbitrary: M) (auto intro!: *) }
  show "Measurable.pred M (lfp F)"
    using P M cont * by (rule measurable_lfp_coinduct[of P])

  have "emeasure (distr M' M f) {x  space (distr M' M f). lfp F x} =
    (SUP i. emeasure (distr M' M f) {x  space (distr M' M f). (F ^^ i) (λx. False) x})"
    using P M
  proof (coinduction arbitrary: M rule: emeasure_lfp')
    case (measurable A N) then have "N. P N  Measurable.pred (distr M' N f) A"
      by metis
    then have "N. P N  Measurable.pred N A"
      by simp
    with P N[THEN *] show ?case
      by auto
  qed fact
  then show "emeasure (distr M' M f) {x  space M. lfp F x} =
    (SUP i. emeasure (distr M' M f) {x  space M. (F ^^ i) (λx. False) x})"
   by simp
qed

lemma distr_id[simp]: "distr N N (λx. x) = N"
  by (rule measure_eqI) (auto simp: emeasure_distr)

lemma distr_id2: "sets M = sets N  distr N M (λx. x) = N"
  by (rule measure_eqI) (auto simp: emeasure_distr)

lemma measure_distr:
  "f  measurable M N  S  sets N  measure (distr M N f) S = measure M (f -` S  space M)"
  by (simp add: emeasure_distr measure_def)

lemma distr_cong_AE:
  assumes 1: "M = K" "sets N = sets L" and
    2: "(AE x in M. f x = g x)" and "f  measurable M N" and "g  measurable K L"
  shows "distr M N f = distr K L g"
proof (rule measure_eqI)
  fix A assume "A  sets (distr M N f)"
  with assms show "emeasure (distr M N f) A = emeasure (distr K L g) A"
    by (auto simp add: emeasure_distr intro!: emeasure_eq_AE measurable_sets)
qed (insert 1, simp)

lemma AE_distrD:
  assumes f: "f  measurable M M'"
    and AE: "AE x in distr M M' f. P x"
  shows "AE x in M. P (f x)"
proof -
  from AE[THEN AE_E] obtain N
    where "{x  space (distr M M' f). ¬ P x}  N"
      "emeasure (distr M M' f) N = 0"
      "N  sets (distr M M' f)"
    by auto
  with f show ?thesis
    by (simp add: eventually_ae_filter, intro bexI[of _ "f -` N  space M"])
       (auto simp: emeasure_distr measurable_def)
qed

lemma AE_distr_iff:
  assumes f[measurable]: "f  measurable M N" and P[measurable]: "{x  space N. P x}  sets N"
  shows "(AE x in distr M N f. P x)  (AE x in M. P (f x))"
proof (subst (1 2) AE_iff_measurable[OF _ refl])
  have "f -` {xspace N. ¬ P x}  space M = {x  space M. ¬ P (f x)}"
    using f[THEN measurable_space] by auto
  then show "(emeasure (distr M N f) {x  space (distr M N f). ¬ P x} = 0) =
    (emeasure M {x  space M. ¬ P (f x)} = 0)"
    by (simp add: emeasure_distr)
qed auto

lemma null_sets_distr_iff:
  "f  measurable M N  A  null_sets (distr M N f)  f -` A  space M  null_sets M  A  sets N"
  by (auto simp add: null_sets_def emeasure_distr)

proposition distr_distr:
  "g  measurable N L  f  measurable M N  distr (distr M N f) L g = distr M L (g  f)"
  by (auto simp add: emeasure_distr measurable_space
           intro!: arg_cong[where f="emeasure M"] measure_eqI)

subsectiontag unimportant› ‹Real measure values›

lemma ring_of_finite_sets: "ring_of_sets (space M) {Asets M. emeasure M A  top}"
proof (rule ring_of_setsI)
  show "a  {A  sets M. emeasure M A  top}  b  {A  sets M. emeasure M A  top} 
    a  b  {A  sets M. emeasure M A  top}" for a b
    using emeasure_subadditive[of a M b] by (auto simp: top_unique)

  show "a  {A  sets M. emeasure M A  top}  b  {A  sets M. emeasure M A  top} 
    a - b  {A  sets M. emeasure M A  top}" for a b
    using emeasure_mono[of "a - b" a M] by (auto simp: top_unique)
qed (auto dest: sets.sets_into_space)

lemma measure_nonneg[simp]: "0  measure M A"
  unfolding measure_def by auto

lemma measure_nonneg' [simp]: "¬ measure M A < 0"
  using measure_nonneg not_le by blast

lemma zero_less_measure_iff: "0 < measure M A  measure M A  0"
  using measure_nonneg[of M A] by (auto simp add: le_less)

lemma measure_le_0_iff: "measure M X  0  measure M X = 0"
  using measure_nonneg[of M X] by linarith

lemma measure_empty[simp]: "measure M {} = 0"
  unfolding measure_def by (simp add: zero_ennreal.rep_eq)

lemma emeasure_eq_ennreal_measure:
  "emeasure M A  top  emeasure M A = ennreal (measure M A)"
  by (cases "emeasure M A" rule: ennreal_cases) (auto simp: measure_def)

lemma measure_zero_top: "emeasure M A = top  measure M A = 0"
  by (simp add: measure_def)

lemma measure_eq_emeasure_eq_ennreal: "0  x  emeasure M A = ennreal x  measure M A = x"
  using emeasure_eq_ennreal_measure[of M A]
  by (cases "A  M") (auto simp: measure_notin_sets emeasure_notin_sets)

lemma enn2real_plus:"a < top  b < top  enn2real (a + b) = enn2real a + enn2real b"
  by (simp add: enn2real_def plus_ennreal.rep_eq real_of_ereal_add less_top
           del: real_of_ereal_enn2ereal)

lemma enn2real_sum:"(i. i  I  f i < top)  enn2real (sum f I) = sum (enn2real  f) I"
  by (induction I rule: infinite_finite_induct) (auto simp: enn2real_plus)

lemma measure_eq_AE:
  assumes iff: "AE x in M. x  A  x  B"
  assumes A: "A  sets M" and B: "B  sets M"
  shows "measure M A = measure M B"
  using assms emeasure_eq_AE[OF assms] by (simp add: measure_def)

lemma measure_Union:
  "emeasure M A    emeasure M B    A  sets M  B  sets M  A  B = {} 
    measure M (A  B) = measure M A + measure M B"
  by (simp add: measure_def plus_emeasure[symmetric] enn2real_plus less_top)

lemma measure_finite_Union:
  "finite S  A`S  sets M  disjoint_family_on A S  (i. i  S  emeasure M (A i)  ) 
    measure M (iS. A i) = (iS. measure M (A i))"
  by (induction S rule: finite_induct)
     (auto simp: disjoint_family_on_insert measure_Union sum_emeasure[symmetric] sets.countable_UN'[OF countable_finite])

lemma measure_Diff:
  assumes finite: "emeasure M A  "
  and measurable: "A  sets M" "B  sets M" "B  A"
  shows "measure M (A - B) = measure M A - measure M B"
proof -
  have "emeasure M (A - B)  emeasure M A" "emeasure M B  emeasure M A"
    using measurable by (auto intro!: emeasure_mono)
  hence "measure M ((A - B)  B) = measure M (A - B) + measure M B"
    using measurable finite by (rule_tac measure_Union) (auto simp: top_unique)
  thus ?thesis using B  A by (auto simp: Un_absorb2)
qed

lemma measure_UNION:
  assumes measurable: "range A  sets M" "disjoint_family A"
  assumes finite: "emeasure M (i. A i)  "
  shows "(λi. measure M (A i)) sums (measure M (i. A i))"
proof -
  have "(λi. emeasure M (A i)) sums (emeasure M (i. A i))"
    unfolding suminf_emeasure[OF measurable, symmetric] by (simp add: summable_sums)
  moreover
  { fix i
    have "emeasure M (A i)  emeasure M (i. A i)"
      using measurable by (auto intro!: emeasure_mono)
    then have "emeasure M (A i) = ennreal ((measure M (A i)))"
      using finite by (intro emeasure_eq_ennreal_measure) (auto simp: top_unique) }
  ultimately show ?thesis using finite
    by (subst (asm) (2) emeasure_eq_ennreal_measure) simp_all
qed

lemma measure_subadditive:
  assumes measurable: "A  sets M" "B  sets M"
  and fin: "emeasure M A  " "emeasure M B  "
  shows "measure M (A  B)  measure M A + measure M B"
proof -
  have "emeasure M (A  B)  "
    using emeasure_subadditive[OF measurable] fin by (auto simp: top_unique)
  then show "(measure M (A  B))  (measure M A) + (measure M B)"
    unfolding measure_def
    by (metis emeasure_subadditive[OF measurable] fin   enn2real_mono enn2real_plus 
        ennreal_add_less_top infinity_ennreal_def less_top)
qed

lemma measure_subadditive_finite:
  assumes A: "finite I" "A`I  sets M" and fin: "i. i  I  emeasure M (A i)  "
  shows "measure M (iI. A i)  (iI. measure M (A i))"
proof -
  { have "emeasure M (iI. A i)  (iI. emeasure M (A i))"
      using emeasure_subadditive_finite[OF A] .
    also have " < "
      using fin by (simp add: less_top A)
    finally have "emeasure M (iI. A i)  top" by simp }
  note * = this
  show ?thesis
    using emeasure_subadditive_finite[OF A] fin
    unfolding emeasure_eq_ennreal_measure[OF *]
    by (simp_all add: sum_nonneg emeasure_eq_ennreal_measure)
qed

lemma measure_subadditive_countably:
  assumes A: "range A  sets M" and fin: "(i. emeasure M (A i))  "
  shows "measure M (i. A i)  (i. measure M (A i))"
proof -
  have **: "i. emeasure M (A i)  top"
    using fin ennreal_suminf_lessD[of "λi. emeasure M (A i)"] by (simp add: less_top)
  have ge0: "(i. Sigma_Algebra.measure M (A i))  0"
    using fin emeasure_eq_ennreal_measure[OF **]
    by (metis infinity_ennreal_def measure_nonneg suminf_cong suminf_nonneg summable_suminf_not_top)
  have "emeasure M (i. A i)  top"
    by (metis A emeasure_subadditive_countably fin infinity_ennreal_def neq_top_trans)
  then have "ennreal (measure M (i. A i)) = emeasure M (i. A i)"
    by (rule emeasure_eq_ennreal_measure[symmetric])
  also have "  (i. emeasure M (A i))"
    using emeasure_subadditive_countably[OF A] .
  also have " = ennreal (i. measure M (A i))"
    using fin unfolding emeasure_eq_ennreal_measure[OF **]
    by (subst suminf_ennreal) (auto simp: **)
  finally show ?thesis
    using ge0 ennreal_le_iff by blast
qed

lemma measure_Un_null_set: "A  sets M  B  null_sets M  measure M (A  B) = measure M A"
  by (simp add: measure_def emeasure_Un_null_set)

lemma measure_Diff_null_set: "A  sets M  B  null_sets M  measure M (A - B) = measure M A"
  by (simp add: measure_def emeasure_Diff_null_set)

lemma measure_eq_sum_singleton:
  "finite S  (x. x  S  {x}  sets M)  (x. x  S  emeasure M {x}  ) 
    measure M S = (xS. measure M {x})"
  using emeasure_eq_sum_singleton[of S M]
  by (intro measure_eq_emeasure_eq_ennreal) (auto simp: sum_nonneg emeasure_eq_ennreal_measure)

lemma Lim_measure_incseq:
  assumes A: "range A  sets M" "incseq A" and fin: "emeasure M (i. A i)  "
  shows "(λi. measure M (A i))  measure M (i. A i)"
proof (rule tendsto_ennrealD)
  have "ennreal (measure M (i. A i)) = emeasure M (i. A i)"
    using fin by (auto simp: emeasure_eq_ennreal_measure)
  moreover have "ennreal (measure M (A i)) = emeasure M (A i)" for i
    using assms emeasure_mono[of "A _" "i. A i" M]
    by (intro emeasure_eq_ennreal_measure[symmetric]) (auto simp: less_top UN_upper intro: le_less_trans)
  ultimately show "(λx. ennreal (measure M (A x)))  ennreal (measure M (i. A i))"
    using A by (auto intro!: Lim_emeasure_incseq)
qed auto

lemma Lim_measure_decseq:
  assumes A: "range A  sets M" "decseq A" and fin: "i. emeasure M (A i)  "
  shows "(λn. measure M (A n))  measure M (i. A i)"
proof (rule tendsto_ennrealD)
  have "ennreal (measure M (i. A i)) = emeasure M (i. A i)"
    using fin[of 0] A emeasure_mono[of "i. A i" "A 0" M]
    by (auto intro!: emeasure_eq_ennreal_measure[symmetric] simp: INT_lower less_top intro: le_less_trans)
  moreover have "ennreal (measure M (A i)) = emeasure M (A i)" for i
    using A fin[of i] by (intro emeasure_eq_ennreal_measure[symmetric]) auto
  ultimately show "(λx. ennreal (measure M (A x)))  ennreal (measure M (i. A i))"
    using fin A by (auto intro!: Lim_emeasure_decseq)
qed auto

subsection ‹Set of measurable sets with finite measure›

definitiontag important› fmeasurable :: "'a measure  'a set set" where
"fmeasurable M = {Asets M. emeasure M A < }"

lemma fmeasurableD[dest, measurable_dest]: "A  fmeasurable M  A  sets M"
  by (auto simp: fmeasurable_def)

lemma fmeasurableD2: "A  fmeasurable M  emeasure M A  top"
  by (auto simp: fmeasurable_def)

lemma fmeasurableI: "A  sets M  emeasure M A <   A  fmeasurable M"
  by (auto simp: fmeasurable_def)

lemma fmeasurableI_null_sets: "A  null_sets M  A  fmeasurable M"
  by (auto simp: fmeasurable_def)

lemma fmeasurableI2: "A  fmeasurable M  B  A  B  sets M  B  fmeasurable M"
  using emeasure_mono[of B A M] by (auto simp: fmeasurable_def)

lemma measure_mono_fmeasurable:
  "A  B  A  sets M  B  fmeasurable M  measure M A  measure M B"
  by (auto simp: measure_def fmeasurable_def intro!: emeasure_mono enn2real_mono)

lemma emeasure_eq_measure2: "A  fmeasurable M  emeasure M A = measure M A"
  by (simp add: emeasure_eq_ennreal_measure fmeasurable_def less_top)

interpretation fmeasurable: ring_of_sets "space M" "fmeasurable M"
proof (rule ring_of_setsI)
  show "fmeasurable M  Pow (space M)" "{}  fmeasurable M"
    by (auto simp: fmeasurable_def dest: sets.sets_into_space)
  fix a b assume *: "a  fmeasurable M" "b  fmeasurable M"
  then have "emeasure M (a  b)  emeasure M a + emeasure M b"
    by (intro emeasure_subadditive) auto
  also have " < top"
    using * by (auto simp: fmeasurable_def)
  finally show  "a  b  fmeasurable M"
    using * by (auto intro: fmeasurableI)
  show "a - b  fmeasurable M"
    using emeasure_mono[of "a - b" a M] * by (auto simp: fmeasurable_def)
qed

subsectiontag unimportant›‹Measurable sets formed by unions and intersections›

lemma fmeasurable_Diff: "A  fmeasurable M  B  sets M  A - B  fmeasurable M"
  using fmeasurableI2[of A M "A - B"] by auto

lemma fmeasurable_Int_fmeasurable:
   "S  fmeasurable M; T  sets M  (S  T)  fmeasurable M"
  by (meson fmeasurableD fmeasurableI2 inf_le1 sets.Int)

lemma fmeasurable_UN:
  assumes "countable I" "i. i  I  F i  A" "i. i  I  F i  sets M" "A  fmeasurable M"
  shows "(iI. F i)  fmeasurable M"
proof (rule fmeasurableI2)
  show "A  fmeasurable M" "(iI. F i)  A" using assms by auto
  show "(iI. F i)  sets M"
    using assms by (intro sets.countable_UN') auto
qed

lemma fmeasurable_INT:
  assumes "countable I" "i  I" "i. i  I  F i  sets M" "F i  fmeasurable M"
  shows "(iI. F i)  fmeasurable M"
proof (rule fmeasurableI2)
  show "F i  fmeasurable M" "(iI. F i)  F i"
    using assms by auto
  show "(iI. F i)  sets M"
    using assms by (intro sets.countable_INT') auto
qed

lemma measurable_measure_Diff:
  assumes "A  fmeasurable M" "B  sets M" "B  A"
  shows "measure M (A - B) = measure M A - measure M B"
  by (simp add: assms fmeasurableD fmeasurableD2 measure_Diff)

lemma measurable_Un_null_set:
  assumes "B  null_sets M"
  shows "(A  B  fmeasurable M  A  sets M)  A  fmeasurable M"
  using assms  by (fastforce simp add: fmeasurable.Un fmeasurableI_null_sets intro: fmeasurableI2)

lemma measurable_Diff_null_set:
  assumes "B  null_sets M"
  shows "(A - B)  fmeasurable M  A  sets M  A  fmeasurable M"
  using assms
  by (metis Un_Diff_cancel2 fmeasurable.Diff fmeasurableD fmeasurableI_null_sets measurable_Un_null_set)

lemma fmeasurable_Diff_D:
    assumes m: "T - S  fmeasurable M" "S  fmeasurable M" and sub: "S  T"
    shows "T  fmeasurable M"
proof -
  have "T = S  (T - S)"
    using assms by blast
  then show ?thesis
    by (metis m fmeasurable.Un)
qed

lemma measure_Un2:
  "A  fmeasurable M  B  fmeasurable M  measure M (A  B) = measure M A + measure M (B - A)"
  using measure_Union[of M A "B - A"] by (auto simp: fmeasurableD2 fmeasurable.Diff)

lemma measure_Un3:
  assumes "A  fmeasurable M" "B  fmeasurable M"
  shows "measure M (A  B) = measure M A + measure M B - measure M (A  B)"
proof -
  have "measure M (A  B) = measure M A + measure M (B - A)"
    using assms by (rule measure_Un2)
  also have "B - A = B - (A  B)"
    by auto
  also have "measure M (B - (A  B)) = measure M B - measure M (A  B)"
    using assms by (intro measure_Diff) (auto simp: fmeasurable_def)
  finally show ?thesis
    by simp
qed

lemma measure_Un_AE:
  "AE x in M. x  A  x  B  A  fmeasurable M  B  fmeasurable M 
  measure M (A  B) = measure M A + measure M B"
  by (subst measure_Un2) (auto intro!: measure_eq_AE)

lemma measure_UNION_AE:
  assumes I: "finite I"
  shows "(i. i  I  F i  fmeasurable M)  pairwise (λi j. AE x in M. x  F i  x  F j) I 
    measure M (iI. F i) = (iI. measure M (F i))"
  unfolding AE_pairwise[OF countable_finite, OF I]
  using I
proof (induction I rule: finite_induct)
  case (insert x I)
  have "measure M (F x  (F ` I)) = measure M (F x) + measure M ((F ` I))"
    by (rule measure_Un_AE) (use insert in auto simp: pairwise_insert)
    with insert show ?case
      by (simp add: pairwise_insert )
qed simp

lemma measure_UNION':
  "finite I  (i. i  I  F i  fmeasurable M)  pairwise (λi j. disjnt (F i) (F j)) I 
    measure M (iI. F i) = (iI. measure M (F i))"
  by (intro measure_UNION_AE) (auto simp: disjnt_def elim!: pairwise_mono intro!: always_eventually)

lemma measure_Union_AE:
  "finite F  (S. S  F  S  fmeasurable M)  pairwise (λS T. AE x in M. x  S  x  T) F 
    measure M (F) = (SF. measure M S)"
  using measure_UNION_AE[of F "λx. x" M] by simp

lemma measure_Union':
  "finite F  (S. S  F  S  fmeasurable M)  pairwise disjnt F  measure M (F) = (SF. measure M S)"
  using measure_UNION'[of F "λx. x" M] by simp

lemma measure_Un_le:
  assumes "A  sets M" "B  sets M" shows "measure M (A  B)  measure M A + measure M B"
proof cases
  assume "A  fmeasurable M  B  fmeasurable M"
  with measure_subadditive[of A M B] assms show ?thesis
    by (auto simp: fmeasurableD2)
next
  assume "¬ (A  fmeasurable M  B  fmeasurable M)"
  then have "A  B  fmeasurable M"
    using fmeasurableI2[of "A  B" M A] fmeasurableI2[of "A  B" M B] assms by auto
  with assms show ?thesis
    by (auto simp: fmeasurable_def measure_def less_top[symmetric])
qed

lemma measure_UNION_le:
  "finite I  (i. i  I  F i  sets M)  measure M (iI. F i)  (iI. measure M (F i))"
proof (induction I rule: finite_induct)
  case (insert i I)
  then have "measure M (iinsert i I. F i) = measure M (F i   (F ` I))"
    by simp
  also from insert have "measure M (F i   (F ` I))  measure M (F i) + measure M ( (F ` I))"
    by (intro measure_Un_le sets.finite_Union) auto
  also have "measure M (iI. F i)  (iI. measure M (F i))"
    using insert by auto
  finally show ?case
    using insert by simp
qed simp

lemma measure_Union_le:
  "finite F  (S. S  F  S  sets M)  measure M (F)  (SF. measure M S)"
  using measure_UNION_le[of F "λx. x" M] by simp

text‹Version for indexed union over a countable set›
lemma
  assumes "countable I" and I: "i. i  I  A i  fmeasurable M"
    and bound: "I'. I'  I  finite I'  measure M (iI'. A i)  B"
  shows fmeasurable_UN_bound: "(iI. A i)  fmeasurable M" (is ?fm)
    and measure_UN_bound: "measure M (iI. A i)  B" (is ?m)
proof -
  have "B  0"
    using bound by force
  have "?fm  ?m"
  proof cases
    assume "I = {}"
    with B  0 show ?thesis
      by simp
  next
    assume "I  {}"
    have "(iI. A i) = (i. (ni. A (from_nat_into I n)))"
      by (subst range_from_nat_into[symmetric, OF I  {} countable I]) auto
    then have "emeasure M (iI. A i) = emeasure M (i. (ni. A (from_nat_into I n)))" by simp
    also have " = (SUP i. emeasure M (ni. A (from_nat_into I n)))"
      using I I  {}[THEN from_nat_into] by (intro SUP_emeasure_incseq[symmetric]) (fastforce simp: incseq_Suc_iff)+
    also have "  B"
    proof (intro SUP_least)
      fix i :: nat
      have "emeasure M (ni. A (from_nat_into I n)) = measure M (ni. A (from_nat_into I n))"
        using I I  {}[THEN from_nat_into] by (intro emeasure_eq_measure2 fmeasurable.finite_UN) auto
      also have " = measure M (nfrom_nat_into I ` {..i}. A n)"
        by simp
      also have "  B"
        by (intro ennreal_leI bound) (auto intro:  from_nat_into[OF I  {}])
      finally show "emeasure M (ni. A (from_nat_into I n))  ennreal B" .
    qed
    finally have *: "emeasure M (iI. A i)  B" .
    then have ?fm
      using I countable I by (intro fmeasurableI conjI) (auto simp: less_top[symmetric] top_unique)
    with * 0B show ?thesis
      by (simp add: emeasure_eq_measure2)
  qed
  then show ?fm ?m by auto
qed

text‹Version for big union of a countable set›
lemma
  assumes "countable 𝒟"
    and meas: "D. D  𝒟  D  fmeasurable M"
    and bound:  ".   𝒟; finite   measure M ()  B"
 shows fmeasurable_Union_bound: "𝒟  fmeasurable M"  (is ?fm)
    and measure_Union_bound: "measure M (𝒟)  B"     (is ?m)
proof -
  have "B  0"
    using bound by force
  have "?fm  ?m"
  proof (cases "𝒟 = {}")
    case True
    with B  0 show ?thesis
      by auto
  next
    case False
    then obtain D :: "nat  'a set" where D: "𝒟 = range D"
      using countable 𝒟 uncountable_def by force
      have 1: "i. D i  fmeasurable M"
        by (simp add: D meas)
      have 2: "I'. finite I'  measure M (xI'. D x)  B"
        by (simp add: D bound image_subset_iff)
      show ?thesis
        unfolding D
        by (intro conjI fmeasurable_UN_bound [OF _ 1 2] measure_UN_bound [OF _ 1 2]) auto
    qed
    then show ?fm ?m by auto
qed

text‹Version for indexed union over the type of naturals›
lemma
  fixes S :: "nat  'a set"
  assumes S: "i. S i  fmeasurable M" and B: "n. measure M (in. S i)  B"
  shows fmeasurable_countable_Union: "(i. S i)  fmeasurable M"
    and measure_countable_Union_le: "measure M (i. S i)  B"
proof -
  have mB: "measure M (iI. S i)  B" if "finite I" for I
  proof -
    have "(iI. S i)  (iMax I. S i)"
      using Max_ge that by force
    then have "measure M (iI. S i)  measure M (i  Max I. S i)"
      by (rule measure_mono_fmeasurable) (use S in blast+)
    then show ?thesis
      using B order_trans by blast
  qed
  show "(i. S i)  fmeasurable M"
    by (auto intro: fmeasurable_UN_bound [OF _ S mB])
  show "measure M (n. S n)  B"
    by (auto intro: measure_UN_bound [OF _ S mB])
qed

lemma measure_diff_le_measure_setdiff:
  assumes "S  fmeasurable M" "T  fmeasurable M"
  shows "measure M S - measure M T  measure M (S - T)"
proof -
  have "measure M S  measure M ((S - T)  T)"
    by (simp add: assms fmeasurable.Un fmeasurableD measure_mono_fmeasurable)
  also have "  measure M (S - T) + measure M T"
    using assms by (blast intro: measure_Un_le)
  finally show ?thesis
    by (simp add: algebra_simps)
qed

lemma suminf_exist_split2:
  fixes f :: "nat  'a::real_normed_vector"
  assumes "summable f"
  shows "(λn. (k. f(k+n)))  0"
by (subst lim_sequentially, auto simp add: dist_norm suminf_exist_split[OF _ assms])

lemma emeasure_union_summable:
  assumes [measurable]: "n. A n  sets M"
    and "n. emeasure M (A n) < " "summable (λn. measure M (A n))"
  shows "emeasure M (n. A n) < " "emeasure M (n. A n)  (n. measure M (A n))"
proof -
  define B where "B = (λN. (n{..<N}. A n))"
  have [measurable]: "B N  sets M" for N unfolding B_def by auto
  have "(λN. emeasure M (B N))  emeasure M (N. B N)"
    apply (rule Lim_emeasure_incseq) unfolding B_def by (auto simp add: SUP_subset_mono incseq_def)
  moreover have "emeasure M (B N)  ennreal (n. measure M (A n))" for N
  proof -
    have *: "(n<N. measure M (A n))  (n. measure M (A n))"
      using assms(3) measure_nonneg sum_le_suminf by blast

    have "emeasure M (B N)  (n<N. emeasure M (A n))"
      unfolding B_def by (rule emeasure_subadditive_finite, auto)
    also have " = (n<N. ennreal(measure M (A n)))"
      using assms(2) by (simp add: emeasure_eq_ennreal_measure less_top)
    also have " = ennreal (n<N. measure M (A n))"
      by auto
    also have "  ennreal (n. measure M (A n))"
      using * by (auto simp: ennreal_leI)
    finally show ?thesis by simp
  qed
  ultimately have "emeasure M (N. B N)  ennreal (n. measure M (A n))"
    by (simp add: Lim_bounded)
  then show "emeasure M (n. A n)  (n. measure M (A n))"
    unfolding B_def by (metis UN_UN_flatten UN_lessThan_UNIV)
  then show "emeasure M (n. A n) < "
    by (auto simp: less_top[symmetric] top_unique)
qed

lemma borel_cantelli_limsup1:
  assumes [measurable]: "n. A n  sets M"
    and "n. emeasure M (A n) < " "summable (λn. measure M (A n))"
  shows "limsup A  null_sets M"
proof -
  have "emeasure M (limsup A)  0"
  proof (rule LIMSEQ_le_const)
    have "(λn. (k. measure M (A (k+n))))  0" by (rule suminf_exist_split2[OF assms(3)])
    then show "(λn. ennreal (k. measure M (A (k+n))))  0"
      unfolding ennreal_0[symmetric] by (intro tendsto_ennrealI)
    have "emeasure M (limsup A)  (k. measure M (A (k+n)))" for n
    proof -
      have I: "(k{n..}. A k) = (k. A (k+n))" by (auto, metis le_add_diff_inverse2, fastforce)
      have "emeasure M (limsup A)  emeasure M (k{n..}. A k)"
        by (rule emeasure_mono, auto simp add: limsup_INF_SUP)
      also have " = emeasure M (k. A (k+n))"
        using I by auto
      also have "  (k. measure M (A (k+n)))"
        apply (rule emeasure_union_summable)
        using assms summable_ignore_initial_segment[OF assms(3), of n] by auto
      finally show ?thesis by simp
    qed
    then show "N. nN. emeasure M (limsup A)  (k. measure M (A (k+n)))"
      by auto
  qed
  then show ?thesis using assms(1) measurable_limsup by auto
qed

lemma borel_cantelli_AE1:
  assumes [measurable]: "n. A n  sets M"
    and "n. emeasure M (A n) < " "summable (λn. measure M (A n))"
  shows "AE x in M. eventually (λn. x  space M - A n) sequentially"
proof -
  have "AE x in M. x  limsup A"
    using borel_cantelli_limsup1[OF assms] unfolding eventually_ae_filter by auto
  moreover have "F n in sequentially. x  A n" if "x  limsup A" for x
    using that  by (auto simp: limsup_INF_SUP eventually_sequentially)
  ultimately show ?thesis by auto
qed

subsection ‹Measure spaces with termemeasure M (space M) < 

localetag important› finite_measure = sigma_finite_measure M for M +
  assumes finite_emeasure_space: "emeasure M (space M)  top"

lemma finite_measureI[Pure.intro!]:
  "emeasure M (space M)    finite_measure M"
  proof qed (auto intro!: exI[of _ "{space M}"])

lemma (in finite_measure) emeasure_finite[simp, intro]: "emeasure M A  top"
  using finite_emeasure_space emeasure_space[of M A] by (auto simp: top_unique)

lemma (in finite_measure) fmeasurable_eq_sets: "fmeasurable M = sets M"
  by (auto simp: fmeasurable_def less_top[symmetric])

lemma (in finite_measure) emeasure_eq_measure: "emeasure M A = ennreal (measure M A)"
  by (intro emeasure_eq_ennreal_measure) simp

lemma (in finite_measure) emeasure_real: "r. 0  r  emeasure M A = ennreal r"
  using emeasure_finite[of A] by (cases "emeasure M A" rule: ennreal_cases) auto

lemma (in finite_measure) bounded_measure: "measure M A  measure M (space M)"
  using emeasure_space[of M A] emeasure_real[of A] emeasure_real[of "space M"] by (auto simp: measure_def)

lemma (in finite_measure) finite_measure_Diff:
  assumes sets: "A  sets M" "B  sets M" and "B  A"
  shows "measure M (A - B) = measure M A - measure M B"
  using measure_Diff[OF _ assms] by simp

lemma (in finite_measure) finite_measure_Union:
  assumes sets: "A  sets M" "B  sets M" and "A  B = {}"
  shows "measure M (A  B) = measure M A + measure M B"
  using measure_Union[OF _ _ assms] by simp

lemma (in finite_measure) finite_measure_finite_Union:
  assumes measurable: "finite S" "A`S  sets M" "disjoint_family_on A S"
  shows "measure M (iS. A i) = (iS. measure M (A i))"
  using measure_finite_Union[OF assms] by simp

lemma (in finite_measure) finite_measure_UNION:
  assumes A: "range A  sets M" "disjoint_family A"
  shows "(λi. measure M (A i)) sums (measure M (i. A i))"
  using measure_UNION[OF A] by simp

lemma (in finite_measure) finite_measure_mono:
  assumes "A  B" "B  sets M" shows "measure M A  measure M B"
  using emeasure_mono[OF assms] emeasure_real[of A] emeasure_real[of B] by (auto simp: measure_def)

lemma (in finite_measure) finite_measure_subadditive:
  assumes m: "A  sets M" "B  sets M"
  shows "measure M (A  B)  measure M A + measure M B"
  using measure_subadditive[OF m] by simp

lemma (in finite_measure) finite_measure_subadditive_finite:
  assumes "finite I" "A`I  sets M" shows "measure M (iI. A i)  (iI. measure M (A i))"
  using measure_subadditive_finite[OF assms] by simp

lemma (in finite_measure) finite_measure_subadditive_countably:
  "range A  sets M  summable (λi. measure M (A i))  measure M (i. A i)  (i. measure M (A i))"
  by (rule measure_subadditive_countably)
     (simp_all add: ennreal_suminf_neq_top emeasure_eq_measure)

lemma (in finite_measure) finite_measure_eq_sum_singleton:
  assumes "finite S" and *: "x. x  S  {x}  sets M"
  shows "measure M S = (xS. measure M {x})"
  using measure_eq_sum_singleton[OF assms] by simp

lemma (in finite_measure) finite_Lim_measure_incseq:
  assumes A: "range A  sets M" "incseq A"
  shows "(λi. measure M (A i))  measure M (i. A i)"
  using Lim_measure_incseq[OF A] by simp

lemma (in finite_measure) finite_Lim_measure_decseq:
  assumes A: "range A  sets M" "decseq A"
  shows "(λn. measure M (A n))  measure M (i. A i)"
  using Lim_measure_decseq[OF A] by simp

lemma (in finite_measure) finite_measure_compl:
  assumes S: "S  sets M"
  shows "measure M (space M - S) = measure M (space M) - measure M S"
  using measure_Diff[OF _ sets.top S sets.sets_into_space] S by simp

lemma (in finite_measure) finite_measure_mono_AE:
  assumes imp: "AE x in M. x  A  x  B" and B: "B  sets M"
  shows "measure M A  measure M B"
  using assms emeasure_mono_AE[OF imp B]
  by (simp add: emeasure_eq_measure)

lemma (in finite_measure) finite_measure_eq_AE:
  assumes iff: "AE x in M. x  A  x  B"
  assumes A: "A  sets M" and B: "B  sets M"
  shows "measure M A = measure M B"
  using assms emeasure_eq_AE[OF assms] by (simp add: emeasure_eq_measure)

lemma (in finite_measure) measure_increasing: "increasing M (measure M)"
  by (auto intro!: finite_measure_mono simp: increasing_def)

lemma (in finite_measure) measure_zero_union:
  assumes "s  sets M" "t  sets M" "measure M t = 0"
  shows "measure M (s  t) = measure M s"
using assms
proof -
  have "measure M (s  t)  measure M s"
    using finite_measure_subadditive[of s t] assms by auto
  moreover have "measure M (s  t)  measure M s"
    using assms by (blast intro: finite_measure_mono)
  ultimately show ?thesis by simp
qed

lemma (in finite_measure) measure_eq_compl:
  assumes "s  sets M" "t  sets M"
  assumes "measure M (space M - s) = measure M (space M - t)"
  shows "measure M s = measure M t"
  using assms finite_measure_compl by auto

lemma (in finite_measure) measure_eq_bigunion_image:
  assumes "range f  sets M" "range g  sets M"
  assumes "disjoint_family f" "disjoint_family g"
  assumes " n :: nat. measure M (f n) = measure M (g n)"
  shows "measure M (i. f i) = measure M (i. g i)"
using assms
proof -
  have a: "(λ i. measure M (f i)) sums (measure M (i. f i))"
    by (rule finite_measure_UNION[OF assms(1,3)])
  have b: "(λ i. measure M (g i)) sums (measure M (i. g i))"
    by (rule finite_measure_UNION[OF assms(2,4)])
  show ?thesis using sums_unique[OF b] sums_unique[OF a] assms by simp
qed

lemma (in finite_measure) measure_countably_zero:
  assumes "range c  sets M"
  assumes " i. measure M (c i) = 0"
  shows "measure M (i :: nat. c i) = 0"
proof (rule antisym)
  show "measure M (i :: nat. c i)  0"
    using finite_measure_subadditive_countably[OF assms(1)] by (simp add: assms(2))
qed simp

lemma (in finite_measure) measure_space_inter:
  assumes events:"s  sets M" "t  sets M"
  assumes "measure M t = measure M (space M)"
  shows "measure M (s  t) = measure M s"
proof -
  have "measure M ((space M - s)  (space M - t)) = measure M (space M - s)"
    using events assms finite_measure_compl[of "t"] by (auto intro!: measure_zero_union)
  also have "(space M - s)  (space M - t) = space M - (s  t)"
    by blast
  finally show "measure M (s  t) = measure M s"
    using events by (auto intro!: measure_eq_compl[of "s  t" s])
qed

lemma (in finite_measure) measure_equiprobable_finite_unions:
  assumes s: "finite s" "x. x  s  {x}  sets M"
  assumes " x y. x  s; y  s  measure M {x} = measure M {y}"
  shows "measure M s = real (card s) * measure M {SOME x. x  s}"
proof cases
  assume "s  {}"
  then have " x. x  s" by blast
  from someI_ex[OF this] assms
  have prob_some: " x. x  s  measure M {x} = measure M {SOME y. y  s}" by blast
  have "measure M s = ( x  s. measure M {x})"
    using finite_measure_eq_sum_singleton[OF s] by simp
  also have " = ( x  s. measure M {SOME y. y  s})" using prob_some by auto
  also have " = real (card s) * measure M {(SOME x. x  s)}"
    using sum_constant assms by simp
  finally show ?thesis by simp
qed simp

lemma (in finite_measure) measure_real_sum_image_fn:
  assumes "e  sets M"
  assumes " x. x  s  e  f x  sets M"
  assumes "finite s"
  assumes disjoint: " x y. x  s ; y  s ; x  y  f x  f y = {}"
  assumes upper: "space M  (i  s. f i)"
  shows "measure M e = ( x  s. measure M (e  f x))"
proof -
  have "e  (is. f i)"
    using e  sets M sets.sets_into_space upper by blast
  then have e: "e = (i  s. e  f i)"
    by auto
  hence "measure M e = measure M (i  s. e  f i)" by simp
  also have " = ( x  s. measure M (e  f x))"
  proof (rule finite_measure_finite_Union)
    show "finite s" by fact
    show "(λi. e  f i)`s  sets M" using assms(2) by auto
    show "disjoint_family_on (λi. e  f i) s"
      using disjoint by (auto simp: disjoint_family_on_def)
  qed
  finally show ?thesis .
qed

lemma (in finite_measure) measure_exclude:
  assumes "A  sets M" "B  sets M"
  assumes "measure M A = measure M (space M)" "A  B = {}"
  shows "measure M B = 0"
  using measure_space_inter[of B A] assms by (auto simp: ac_simps)
lemma (in finite_measure) finite_measure_distr:
  assumes f: "f  measurable M M'"
  shows "finite_measure (distr M M' f)"
proof (rule finite_measureI)
  have "f -` space M'  space M = space M" using f by (auto dest: measurable_space)
  with f show "emeasure (distr M M' f) (space (distr M M' f))  " by (auto simp: emeasure_distr)
qed

lemma emeasure_gfp[consumes 1, case_names cont measurable]:
  assumes sets[simp]: "s. sets (M s) = sets N"
  assumes "s. finite_measure (M s)"
  assumes cont: "inf_continuous F" "inf_continuous f"
  assumes meas: "P. Measurable.pred N P  Measurable.pred N (F P)"
  assumes iter: "P s. Measurable.pred N P  emeasure (M s) {xspace N. F P x} = f (λs. emeasure (M s) {xspace N. P x}) s"
  assumes bound: "P. f P  f (λs. emeasure (M s) (space (M s)))"
  shows "emeasure (M s) {xspace N. gfp F x} = gfp f s"
proof (subst gfp_transfer_bounded[where α="λF s. emeasure (M s) {xspace N. F x}" and P="Measurable.pred N", symmetric])
  interpret finite_measure "M s" for s by fact
  fix C assume "decseq C" "i. Measurable.pred N (C i)"
  then show "(λs. emeasure (M s) {x  space N. (INF i. C i) x}) = (INF i. (λs. emeasure (M s) {x  space N. C i x}))"
    unfolding INF_apply
    by (subst INF_emeasure_decseq) (auto simp: antimono_def fun_eq_iff intro!: arg_cong2[where f=emeasure])
next
  show "f x  (λs. emeasure (M s) {x  space N. F top x})" for x
    using bound[of x] sets_eq_imp_space_eq[OF sets] by (simp add: iter)
qed (auto simp add: iter le_fun_def INF_apply[abs_def] intro!: meas cont)

subsectiontag unimportant› ‹Counting space›

lemma strict_monoI_Suc:
  assumes "(n. f n < f (Suc n))" shows "strict_mono f"
  by (simp add: assms strict_mono_Suc_iff)

lemma emeasure_count_space:
  assumes "X  A" shows "emeasure (count_space A) X = (if finite X then of_nat (card X) else )"
    (is "_ = ?M X")
  unfolding count_space_def
proof (rule emeasure_measure_of_sigma)
  show "X  Pow A" using X  A by auto
  show "sigma_algebra A (Pow A)" by (rule sigma_algebra_Pow)
  show positive: "positive (Pow A) ?M"
    by (auto simp: positive_def)
  have additive: "additive (Pow A) ?M"
    by (auto simp: card_Un_disjoint additive_def)

  interpret ring_of_sets A "Pow A"
    by (rule ring_of_setsI) auto
  show "countably_additive (Pow A) ?M"
    unfolding countably_additive_iff_continuous_from_below[OF positive additive]
  proof safe
    fix F :: "nat  'a set" assume "incseq F"
    show "(λi. ?M (F i))  ?M (i. F i)"
    proof cases
      assume "i. ji. F i = F j"
      then obtain i where i: "ji. F i = F j" ..
      with incseq F have "F j  F i" for j
        by (cases "i  j") (auto simp: incseq_def)
      then have eq: "(i. F i) = F i"
        by auto
      with i show ?thesis
        by (auto intro!: Lim_transform_eventually[OF tendsto_const] eventually_sequentiallyI[where c=i])
    next
      assume "¬ (i. ji. F i = F j)"
      then obtain f where f: "i. i  f i" "i. F i  F (f i)" by metis
      then have "i. F i  F (f i)" using incseq F by (auto simp: incseq_def)
      with f have *: "i. F i  F (f i)" by auto

      have "incseq (λi. ?M (F i))"
        using incseq F unfolding incseq_def by (auto simp: card_mono dest: finite_subset)
      then have "(λi. ?M (F i))  (SUP n. ?M (F n))"
        by (rule LIMSEQ_SUP)

      moreover have "(SUP n. ?M (F n)) = top"
      proof (rule ennreal_SUP_eq_top)
        fix n :: nat show "k::natUNIV. of_nat n  ?M (F k)"
        proof (induct n)
          case (Suc n)
          then obtain k where "of_nat n  ?M (F k)" ..
          moreover have "finite (F k)  finite (F (f k))  card (F k) < card (F (f k))"
            using F k  F (f k) by (simp add: psubset_card_mono)
          moreover have "finite (F (f k))  finite (F k)"
            using k  f k incseq F by (auto simp: incseq_def dest: finite_subset)
          ultimately show ?case
            by (auto intro!: exI[of _ "f k"] simp del: of_nat_Suc)
        qed auto
      qed

      moreover
      have "inj (λn. F ((f ^^ n) 0))"
        by (intro strict_mono_imp_inj_on strict_monoI_Suc) (simp add: *)
      then have 1: "infinite (range (λi. F ((f ^^ i) 0)))"
        by (rule range_inj_infinite)
      have "infinite (Pow (i. F i))"
        by (rule infinite_super[OF _ 1]) auto
      then have "infinite (i. F i)"
        by auto
      ultimately show ?thesis by (simp only:) simp

    qed
  qed
qed

lemma distr_bij_count_space:
  assumes f: "bij_betw f A B"
  shows "distr (count_space A) (count_space B) f = count_space B"
proof (rule measure_eqI)
  have f': "f  measurable (count_space A) (count_space B)"
    using f unfolding Pi_def bij_betw_def by auto
  fix X assume "X  sets (distr (count_space A) (count_space B) f)"
  then have X: "X  sets (count_space B)" by auto
  moreover from X have "f -` X  A = the_inv_into A f ` X"
    using f by (auto simp: bij_betw_def subset_image_iff image_iff the_inv_into_f_f intro: the_inv_into_f_f[symmetric])
  moreover have "inj_on (the_inv_into A f) B"
    using X f by (auto simp: bij_betw_def inj_on_the_inv_into)
  with X have "inj_on (the_inv_into A f) X"
    by (auto intro: subset_inj_on)
  ultimately show "emeasure (distr (count_space A) (count_space B) f) X = emeasure (count_space B) X"
    using f unfolding emeasure_distr[OF f' X]
    by (subst (1 2) emeasure_count_space) (auto simp: card_image dest: finite_imageD)
qed simp

lemma emeasure_count_space_finite[simp]:
  "X  A  finite X  emeasure (count_space A) X = of_nat (card X)"
  using emeasure_count_space[of X A] by simp

lemma emeasure_count_space_infinite[simp]:
  "X  A  infinite X  emeasure (count_space A) X = "
  using emeasure_count_space[of X A] by simp

lemma measure_count_space: "measure (count_space A) X = (if X  A then of_nat (card X) else 0)"
  by (cases "finite X") (auto simp: measure_notin_sets ennreal_of_nat_eq_real_of_nat
                                    measure_zero_top measure_eq_emeasure_eq_ennreal)

lemma emeasure_count_space_eq_0:
  "emeasure (count_space A) X = 0  (X  A  X = {})"
proof cases
  assume X: "X  A"
  then show ?thesis
  proof (intro iffI impI)
    assume "emeasure (count_space A) X = 0"
    with X show "X = {}"
      by (subst (asm) emeasure_count_space) (auto split: if_split_asm)
  qed simp
qed (simp add: emeasure_notin_sets)

lemma null_sets_count_space: "null_sets (count_space A) = { {} }"
  unfolding null_sets_def by (auto simp add: emeasure_count_space_eq_0)

lemma AE_count_space: "(AE x in count_space A. P x)  (xA. P x)"
  unfolding eventually_ae_filter by (auto simp add: null_sets_count_space)

lemma sigma_finite_measure_count_space_countable:
  assumes A: "countable A"
  shows "sigma_finite_measure (count_space A)"
  proof qed (insert A, auto intro!: exI[of _ "(λa. {a}) ` A"])

lemma sigma_finite_measure_count_space:
  fixes A :: "'a::countable set" shows "sigma_finite_measure (count_space A)"
  by (rule sigma_finite_measure_count_space_countable) auto

lemma finite_measure_count_space:
  assumes [simp]: "finite A"
  shows "finite_measure (count_space A)"
  by rule simp

lemma sigma_finite_measure_count_space_finite:
  assumes A: "finite A" shows "sigma_finite_measure (count_space A)"
proof -
  interpret finite_measure "count_space A" using A by (rule finite_measure_count_space)
  show "sigma_finite_measure (count_space A)" ..
qed

subsectiontag unimportant› ‹Measure restricted to space›

lemma emeasure_restrict_space:
  assumes "Ω  space M  sets M" "A  Ω"
  shows "emeasure (restrict_space M Ω) A = emeasure M A"
proof (cases "A  sets M")
  case True
  show ?thesis
  proof (rule emeasure_measure_of[OF restrict_space_def])
    show "(∩) Ω ` sets M  Pow (Ω  space M)" "A  sets (restrict_space M Ω)"
      using A  Ω A  sets M sets.space_closed by (auto simp: sets_restrict_space)
    show "positive (sets (restrict_space M Ω)) (emeasure M)"
      by (auto simp: positive_def)
    show "countably_additive (sets (restrict_space M Ω)) (emeasure M)"
    proof (rule countably_additiveI)
      fix A :: "nat  _" assume "range A  sets (restrict_space M Ω)" "disjoint_family A"
      with assms have "i. A i  sets M" "i. A i  space M" "disjoint_family A"
        by (fastforce simp: sets_restrict_space_iff[OF assms(1)] image_subset_iff
                      dest: sets.sets_into_space)+
      then show "(i. emeasure M (A i)) = emeasure M (i. A i)"
        by (subst suminf_emeasure) (auto simp: disjoint_family_subset)
    qed
  qed
next
  case False
  with assms have "A  sets (restrict_space M Ω)"
    by (simp add: sets_restrict_space_iff)
  with False show ?thesis
    by (simp add: emeasure_notin_sets)
qed

lemma measure_restrict_space:
  assumes "Ω  space M  sets M" "A  Ω"
  shows "measure (restrict_space M Ω) A = measure M A"
  using emeasure_restrict_space[OF assms] by (simp add: measure_def)

lemma AE_restrict_space_iff:
  assumes "Ω  space M  sets M"
  shows "(AE x in restrict_space M Ω. P x)  (AE x in M. x  Ω  P x)"
proof -
  have ex_cong: "P Q f. (x. P x  Q x)  (x. Q x  P (f x))  (x. P x)  (x. Q x)"
    by auto
  { fix X assume X: "X  sets M" "emeasure M X = 0"
    then have "emeasure M (Ω  space M  X)  emeasure M X"
      by (intro emeasure_mono) auto
    then have "emeasure M (Ω  space M  X) = 0"
      using X by (auto intro!: antisym) }
  with assms show ?thesis
    unfolding eventually_ae_filter
    by (auto simp add: space_restrict_space null_sets_def sets_restrict_space_iff
                       emeasure_restrict_space cong: conj_cong
             intro!: ex_cong[where f="λX. (Ω  space M)  X"])
qed

lemma restrict_restrict_space:
  assumes "A  space M  sets M" "B  space M  sets M"
  shows "restrict_space (restrict_space M A) B = restrict_space M (A  B)" (is "?l = ?r")
proof (rule measure_eqI[symmetric])
  show "sets ?r = sets ?l"
    unfolding sets_restrict_space image_comp by (intro image_cong) auto
next
  fix X assume "X  sets (restrict_space M (A  B))"
  then obtain Y where "Y  sets M" "X = Y  A  B"
    by (auto simp: sets_restrict_space)
  with assms sets.Int[OF assms] show "emeasure ?r X = emeasure ?l X"
    by (subst (1 2) emeasure_restrict_space)
       (auto simp: space_restrict_space sets_restrict_space_iff emeasure_restrict_space ac_simps)
qed

lemma restrict_count_space: "restrict_space (count_space B) A = count_space (A  B)"
proof (rule measure_eqI)
  show "sets (restrict_space (count_space B) A) = sets (count_space (A  B))"
    by (subst sets_restrict_space) auto
  moreover fix X assume "X  sets (restrict_space (count_space B) A)"
  ultimately have "X  A  B" by auto
  then show "emeasure (restrict_space (count_space B) A) X = emeasure (count_space (A  B)) X"
    by (cases "finite X") (auto simp add: emeasure_restrict_space)
qed

lemma sigma_finite_measure_restrict_space:
  assumes "sigma_finite_measure M"
  and A: "A  sets M"
  shows "sigma_finite_measure (restrict_space M A)"
proof -
  interpret sigma_finite_measure M by fact
  from sigma_finite_countable obtain C
    where C: "countable C" "C  sets M" "(C) = space M" "aC. emeasure M a  "
    by blast
  let ?C = "(∩) A ` C"
  from C have "countable ?C" "?C  sets (restrict_space M A)" "(?C) = space (restrict_space M A)"
    by(auto simp add: sets_restrict_space space_restrict_space)
  moreover {
    fix a
    assume "a  ?C"
    then obtain a' where "a = A  a'" "a'  C" ..
    then have "emeasure (restrict_space M A) a  emeasure M a'"
      using A C by(auto simp add: emeasure_restrict_space intro: emeasure_mono)
    also have " < " using C(4)[rule_format, of a'] a'  C by (simp add: less_top)
    finally have "emeasure (restrict_space M A) a  " by simp }
  ultimately show ?thesis
    by unfold_locales (rule exI conjI|assumption|blast)+
qed

lemma finite_measure_restrict_space:
  assumes "finite_measure M"
  and A: "A  sets M"
  shows "finite_measure (restrict_space M A)"
proof -
  interpret finite_measure M by fact
  show ?thesis
    by(rule finite_measureI)(simp add: emeasure_restrict_space A space_restrict_space)
qed

lemma restrict_distr:
  assumes [measurable]: "f  measurable M N"
  assumes [simp]: "Ω  space N  sets N" and restrict: "f  space M  Ω"
  shows "restrict_space (distr M N f) Ω = distr M (restrict_space N Ω) f"
  (is "?l = ?r")
proof (rule measure_eqI)
  fix A assume "A  sets (restrict_space (distr M N f) Ω)"
  with restrict show "emeasure ?l A = emeasure ?r A"
    by (subst emeasure_distr)
       (auto simp: sets_restrict_space_iff emeasure_restrict_space emeasure_distr
             intro!: measurable_restrict_space2)
qed (simp add: sets_restrict_space)

lemma measure_eqI_restrict_generator:
  assumes E: "Int_stable E" "E  Pow Ω" "X. X  E  emeasure M X = emeasure N X"
  assumes sets_eq: "sets M = sets N" and Ω: "Ω  sets M"
  assumes "sets (restrict_space M Ω) = sigma_sets Ω E"
  assumes "sets (restrict_space N Ω) = sigma_sets Ω E"
  assumes ae: "AE x in M. x  Ω" "AE x in N. x  Ω"
  assumes A: "countable A" "A  {}" "A  E" "A = Ω" "a. a  A  emeasure M a  "
  shows "M = N"
proof (rule measure_eqI)
  fix X assume X: "X  sets M"
  then have "emeasure M X = emeasure (restrict_space M Ω) (X  Ω)"
    using ae Ω by (auto simp add: emeasure_restrict_space intro!: emeasure_eq_AE)
  also have "restrict_space M Ω = restrict_space N Ω"
  proof (rule measure_eqI_generator_eq)
    fix X assume "X  E"
    then show "emeasure (restrict_space M Ω) X = emeasure (restrict_space N Ω) X"
      using E Ω by (subst (1 2) emeasure_restrict_space) (auto simp: sets_eq sets_eq[THEN sets_eq_imp_space_eq])
  next
    show "range (from_nat_into A)  E" "(i. from_nat_into A i) = Ω"
      using A by (auto cong del: SUP_cong_simp)
  next
    fix i
    have "emeasure (restrict_space M Ω) (from_nat_into A i) = emeasure M (from_nat_into A i)"
      using A Ω by (subst emeasure_restrict_space)
                   (auto simp: sets_eq sets_eq[THEN sets_eq_imp_space_eq] intro: from_nat_into)
    with A show "emeasure (restrict_space M Ω) (from_nat_into A i)  "
      by (auto intro: from_nat_into)
  qed fact+
  also have "emeasure (restrict_space N Ω) (X  Ω) = emeasure N X"
    using X ae Ω by (auto simp add: emeasure_restrict_space sets_eq intro!: emeasure_eq_AE)
  finally show "emeasure M X = emeasure N X" .
qed fact

subsectiontag unimportant› ‹Null measure›

definition null_measure :: "'a measure  'a measure" where
"null_measure M = sigma (space M) (sets M)"

lemma space_null_measure[simp]: "space (null_measure M) = space M"
  by (simp add: null_measure_def)

lemma sets_null_measure[simp, measurable_cong]: "sets (null_measure M) = sets M"
  by (simp add: null_measure_def)

lemma emeasure_null_measure[simp]: "emeasure (null_measure M) X = 0"
  by (cases "X  sets M", rule emeasure_measure_of)
     (auto simp: positive_def countably_additive_def emeasure_notin_sets null_measure_def
           dest: sets.sets_into_space)

lemma measure_null_measure[simp]: "measure (null_measure M) X = 0"
  by (intro measure_eq_emeasure_eq_ennreal) auto

lemma null_measure_idem [simp]: "null_measure (null_measure M) = null_measure M"
  by(rule measure_eqI) simp_all

subsection ‹Scaling a measure›

definitiontag important› scale_measure :: "ennreal  'a measure  'a measure" where
"scale_measure r M = measure_of (space M) (sets M) (λA. r * emeasure M A)"

lemma space_scale_measure: "space (scale_measure r M) = space M"
  by (simp add: scale_measure_def)

lemma sets_scale_measure [simp, measurable_cong]: "sets (scale_measure r M) = sets M"
  by (simp add: scale_measure_def)

lemma emeasure_scale_measure [simp]:
  "emeasure (scale_measure r M) A = r * emeasure M A"
  (is "_ =  A")
proof(cases "A  sets M")
  case True
  show ?thesis unfolding scale_measure_def
  proof(rule emeasure_measure_of_sigma)
    show "sigma_algebra (space M) (sets M)" ..
    show "positive (sets M) " by (simp add: positive_def)
    show "countably_additive (sets M) "
    proof (rule countably_additiveI)
      fix A :: "nat  _"  assume *: "range A  sets M" "disjoint_family A"
      have "(i.  (A i)) = r * (i. emeasure M (A i))"
        by simp
      also have " =  (i. A i)" using * by(simp add: suminf_emeasure)
      finally show "(i.  (A i)) =  (i. A i)" .
    qed
  qed(fact True)
qed(simp add: emeasure_notin_sets)

lemma scale_measure_1 [simp]: "scale_measure 1 M = M"
  by(rule measure_eqI) simp_all

lemma scale_measure_0[simp]: "scale_measure 0 M = null_measure M"
  by(rule measure_eqI) simp_all

lemma measure_scale_measure [simp]: "0  r  measure (scale_measure r M) A = r * measure M A"
  using emeasure_scale_measure[of r M A]
    emeasure_eq_ennreal_measure[of M A]
    measure_eq_emeasure_eq_ennreal[of _ "scale_measure r M" A]
  by (cases "emeasure (scale_measure r M) A = top")
     (auto simp del: emeasure_scale_measure
           simp: ennreal_top_eq_mult_iff ennreal_mult_eq_top_iff measure_zero_top ennreal_mult[symmetric])

lemma scale_scale_measure [simp]:
  "scale_measure r (scale_measure r' M) = scale_measure (r * r') M"
  by (rule measure_eqI) (simp_all add: max_def mult.assoc)

lemma scale_null_measure [simp]: "scale_measure r (null_measure M) = null_measure M"
  by (rule measure_eqI) simp_all


subsection ‹Complete lattice structure on measures›

lemma (in finite_measure) finite_measure_Diff':
  "A  sets M  B  sets M  measure M (A - B) = measure M A - measure M (A  B)"
  using finite_measure_Diff[of A "A  B"] by (auto simp: Diff_Int)

lemma (in finite_measure) finite_measure_Union':
  "A  sets M  B  sets M  measure M (A  B) = measure M A + measure M (B - A)"
  using finite_measure_Union[of A "B - A"] by auto

lemma finite_unsigned_Hahn_decomposition:
  assumes "finite_measure M" "finite_measure N" and [simp]: "sets N = sets M"
  shows "Ysets M. (Xsets M. X  Y  N X  M X)  (Xsets M. X  Y = {}  M X  N X)"
proof -
  interpret M: finite_measure M by fact
  interpret N: finite_measure N by fact

  define d where "d X = measure M X - measure N X" for X

  have [intro]: "bdd_above (d`sets M)"
    using sets.sets_into_space[of _ M]
    by (intro bdd_aboveI[where M="measure M (space M)"])
       (auto simp: d_def field_simps subset_eq intro!: add_increasing M.finite_measure_mono)

  define γ where "γ = (SUP Xsets M. d X)"
  have le_γ[intro]: "X  sets M  d X  γ" for X
    by (auto simp: γ_def intro!: cSUP_upper)

  have "f. n. f n  sets M  d (f n) > γ - 1 / 2^n"
  proof (intro choice_iff[THEN iffD1] allI)
    fix n
    have "Xsets M. γ - 1 / 2^n < d X"
      unfolding γ_def by (intro less_cSUP_iff[THEN iffD1]) auto
    then show "y. y  sets M  γ - 1 / 2 ^ n < d y"
      by auto
  qed
  then obtain E where [measurable]: "E n  sets M" and E: "d (E n) > γ - 1 / 2^n" for n
    by auto

  define F where "F m n = (if m  n then i{m..n}. E i else space M)" for m n

  have [measurable]: "m  n  F m n  sets M" for m n
    by (auto simp: F_def)

  have 1: "γ - 2 / 2 ^ m + 1 / 2 ^ n  d (F m n)" if "m  n" for m n
    using that
  proof (induct rule: dec_induct)
    case base with E[of m] show ?case
      by (simp add: F_def field_simps)
  next
    case (step i)
    have F_Suc: "F m (Suc i) = F m i  E (Suc i)"
      using m  i by (auto simp: F_def le_Suc_eq)

    have "γ + (γ - 2 / 2^m + 1 / 2 ^ Suc i)  (γ - 1 / 2^Suc i) + (γ - 2 / 2^m + 1 / 2^i)"
      by (simp add: field_simps)
    also have "  d (E (Suc i)) + d (F m i)"
      using E[of "Suc i"] by (intro add_mono step) auto
    also have " = d (E (Suc i)) + d (F m i - E (Suc i)) + d (F m (Suc i))"
      using m  i by (simp add: d_def field_simps F_Suc M.finite_measure_Diff' N.finite_measure_Diff')
    also have " = d (E (Suc i)  F m i) + d (F m (Suc i))"
      using m  i by (simp add: d_def field_simps M.finite_measure_Union' N.finite_measure_Union')
    also have "  γ + d (F m (Suc i))"
      using m  i by auto
    finally show ?case
      by auto
  qed

  define F' where "F' m = (i{m..}. E i)" for m
  have F'_eq: "F' m = (i. F m (i + m))" for m
    by (fastforce simp: le_iff_add[of m] F'_def F_def)

  have [measurable]: "F' m  sets M" for m
    by (auto simp: F'_def)

  have γ_le: "γ - 0  d (m. F' m)"
  proof (rule LIMSEQ_le)
    show "(λn. γ - 2 / 2 ^ n)  γ - 0"
      by (intro tendsto_intros LIMSEQ_divide_realpow_zero) auto
    have "incseq F'"
      by (auto simp: incseq_def F'_def)
    then show "(λm. d (F' m))  d (m. F' m)"
      unfolding d_def
      by (intro tendsto_diff M.finite_Lim_measure_incseq N.finite_Lim_measure_incseq) auto

    have "γ - 2 / 2 ^ m + 0  d (F' m)" for m
    proof (rule LIMSEQ_le)
      have *: "decseq (λn. F m (n + m))"
        by (auto simp: decseq_def F_def)
      show "(λn. d (F m n))  d (F' m)"
        unfolding d_def F'_eq
        by (rule LIMSEQ_offset[where k=m])
           (auto intro!: tendsto_diff M.finite_Lim_measure_decseq N.finite_Lim_measure_decseq *)
      show "(λn. γ - 2 / 2 ^ m + 1 / 2 ^ n)  γ - 2 / 2 ^ m + 0"
        by (intro tendsto_add LIMSEQ_divide_realpow_zero tendsto_const) auto
      show "N. nN. γ - 2 / 2 ^ m + 1 / 2 ^ n  d (F m n)"
        using 1[of m] by (intro exI[of _ m]) auto
    qed
    then show "N. nN. γ - 2 / 2 ^ n  d (F' n)"
      by auto
  qed

  show ?thesis
  proof (safe intro!: bexI[of _ "m. F' m"])
    fix X assume [measurable]: "X  sets M" and X: "X  (m. F' m)"
    have "d (m. F' m) - d X = d ((m. F' m) - X)"
      using X by (auto simp: d_def M.finite_measure_Diff N.finite_measure_Diff)
    also have "  γ"
      by auto
    finally have "0  d X"
      using γ_le by auto
    then show "emeasure N X  emeasure M X"
      by (auto simp: d_def M.emeasure_eq_measure N.emeasure_eq_measure)
  next
    fix X assume [measurable]: "X  sets M" and X: "X  (m. F' m) = {}"
    then have "d (m. F' m) + d X = d (X  (m. F' m))"
      by (auto simp: d_def M.finite_measure_Union N.finite_measure_Union)
    also have "  γ"
      by auto
    finally have "d X  0"
      using γ_le by auto
    then show "emeasure M X  emeasure N X"
      by (auto simp: d_def M.emeasure_eq_measure N.emeasure_eq_measure)
  qed auto
qed

proposition unsigned_Hahn_decomposition:
  assumes [simp]: "sets N = sets M" and [measurable]: "A  sets M"
    and [simp]: "emeasure M A  top" "emeasure N A  top"
  shows "Ysets M. Y  A  (Xsets M. X  Y  N X  M X)  (Xsets M. X  A  X  Y = {}  M X  N X)"
proof -
  have "Ysets (restrict_space M A).
    (Xsets (restrict_space M A). X  Y  (restrict_space N A) X  (restrict_space M A) X) 
    (Xsets (restrict_space M A). X  Y = {}  (restrict_space M A) X  (restrict_space N A) X)"
  proof (rule finite_unsigned_Hahn_decomposition)
    show "finite_measure (restrict_space M A)" "finite_measure (restrict_space N A)"
      by (auto simp: space_restrict_space emeasure_restrict_space less_top intro!: finite_measureI)
  qed (simp add: sets_restrict_space)
  with assms show ?thesis
    by (metis Int_subset_iff emeasure_restrict_space sets.Int_space_eq2 sets_restrict_space_iff space_restrict_space)
qed

texttag important› ‹
  Define a lexicographical order on typemeasure, in the order space, sets and measure. The parts
  of the lexicographical order are point-wise ordered.
›

instantiation measure :: (type) order_bot
begin

inductive less_eq_measure :: "'a measure  'a measure  bool" where
  "space M  space N  less_eq_measure M N"
| "space M = space N  sets M  sets N  less_eq_measure M N"
| "space M = space N  sets M = sets N  emeasure M  emeasure N  less_eq_measure M N"

lemma le_measure_iff:
  "M  N  (if space M = space N then
    if sets M = sets N then emeasure M  emeasure N else sets M  sets N else space M  space N)"
  by (auto elim: less_eq_measure.cases intro: less_eq_measure.intros)

definitiontag important› less_measure :: "'a measure  'a measure  bool" where
  "less_measure M N  (M  N  ¬ N  M)"

definitiontag important› bot_measure :: "'a measure" where
  "bot_measure = sigma {} {}"

lemma
  shows space_bot[simp]: "space bot = {}"
    and sets_bot[simp]: "sets bot = {{}}"
    and emeasure_bot[simp]: "emeasure bot X = 0"
  by (auto simp: bot_measure_def sigma_sets_empty_eq emeasure_sigma)

instance
proof standard
  show "bot  a" for a :: "'a measure"
    by (simp add: le_measure_iff bot_measure_def sigma_sets_empty_eq emeasure_sigma le_fun_def)
qed (auto simp: le_measure_iff less_measure_def split: if_split_asm intro: measure_eqI)

end

proposition le_measure: "sets M = sets N  M  N  (Asets M. emeasure M A  emeasure N A)"
  by (metis emeasure_neq_0_sets le_fun_def le_measure_iff order_class.order_eq_iff sets_eq_imp_space_eq)

definitiontag important› sup_measure' :: "'a measure  'a measure  'a measure" where
"sup_measure' A B =
  measure_of (space A) (sets A)
    (λX. SUP Ysets A. emeasure A (X  Y) + emeasure B (X  - Y))"

lemma assumes [simp]: "sets B = sets A"
  shows space_sup_measure'[simp]: "space (sup_measure' A B) = space A"
    and sets_sup_measure'[simp]: "sets (sup_measure' A B) = sets A"
  using sets_eq_imp_space_eq[OF assms] by (simp_all add: sup_measure'_def)

lemma emeasure_sup_measure':
  assumes sets_eq[simp]: "sets B = sets A" and [simp, intro]: "X  sets A"
  shows "emeasure (sup_measure' A B) X = (SUP Ysets A. emeasure A (X  Y) + emeasure B (X  - Y))"
    (is "_ = ?S X")
proof -
  note sets_eq_imp_space_eq[OF sets_eq, simp]
  show ?thesis
    using sup_measure'_def
  proof (rule emeasure_measure_of)
    let ?d = "λX Y. emeasure A (X  Y) + emeasure B (X  - Y)"
    show "countably_additive (sets (sup_measure' A B)) (λX. SUP Y  sets A. emeasure A (X  Y) + emeasure B (X  - Y))"
    proof (rule countably_additiveI, goal_cases)
      case (1 X)
      then have [measurable]: "i. X i  sets A" and "disjoint_family X"
        by auto
      have disjoint: "disjoint_family (λi. X i  Y)" "disjoint_family (λi. X i - Y)" for Y
        using "1"(2) disjoint_family_subset by fastforce+
      have "(i. ?S (X i)) = (SUP Ysets A. i. ?d (X i) Y)"
      proof (rule ennreal_suminf_SUP_eq_directed)
        fix J :: "nat set" and a b assume "finite J" and [measurable]: "a  sets A" "b  sets A"
        have "csets A. c  X i  (asets A. ?d (X i) a  ?d (X i) c)" for i
        proof cases
          assume "emeasure A (X i) = top  emeasure B (X i) = top"
          then show ?thesis
            by force
        next
          assume finite: "¬ (emeasure A (X i) = top  emeasure B (X i) = top)"
          then have "Ysets A. Y  X i  (Csets A. C  Y  B C  A C)  (Csets A. C  X i  C  Y = {}  A C  B C)"
            using unsigned_Hahn_decomposition[of B A "X i"] by simp
          then obtain Y where [measurable]: "Y  sets A" and [simp]: "Y  X i"
            and B_le_A: "C. C  sets A  C  Y  B C  A C"
            and A_le_B: "C. C  sets A  C  X i  C  Y = {}  A C  B C"
            by auto

          show ?thesis
          proof (intro bexI ballI conjI)
            fix a assume [measurable]: "a  sets A"
            have *: "(X i  a  Y  (X i  a - Y)) = X i  a" "(X i - a)  Y  (X i - a - Y) = X i  - a"
              for a Y by auto
            then have "?d (X i) a =
              (A (X i  a  Y) + A (X i  a  - Y)) + (B (X i  - a  Y) + B (X i  - a  - Y))"
              by (subst (1 2) plus_emeasure) (auto simp: Diff_eq[symmetric])
            also have "  (A (X i  a  Y) + B (X i  a  - Y)) + (A (X i  - a  Y) + B (X i  - a  - Y))"
              by (intro add_mono order_refl B_le_A A_le_B) (auto simp: Diff_eq[symmetric])
            also have "  (A (X i  Y  a) + A (X i  Y  - a)) + (B (X i  - Y  a) + B (X i  - Y  - a))"
              by (simp add: ac_simps)
            also have "  A (X i  Y) + B (X i  - Y)"
              by (subst (1 2) plus_emeasure) (auto simp: Diff_eq[symmetric] *)
            finally show "?d (X i) a  ?d (X i) Y" .
          qed auto
        qed
        then obtain C where [measurable]: "C i  sets A" and "C i  X i"
          and C: "a. a  sets A  ?d (X i) a  ?d (X i) (C i)" for i
          by metis
        have *: "X i  (i. C i) = X i  C i" for i
          using disjoint_family X i. C i  X i
          by (simp add: disjoint_family_on_def disjoint_iff_not_equal set_eq_iff) (metis subsetD)
        then have **: "X i  - (i. C i) = X i  - C i" for i by blast
        moreover have "(i. C i)  sets A"
          by fastforce
        ultimately show "csets A. iJ. ?d (X i) a  ?d (X i) c  ?d (X i) b  ?d (X i) c"
          by (metis "*" C a  sets A b  sets A)
      qed
      also have " = ?S (i. X i)"
      proof -
        have "Y. Y  sets A  (i. emeasure A (X i  Y) + emeasure B (X i  -Y)) 
                              = emeasure A (i. X i  Y) + emeasure B (i. X i  -Y)"
          using disjoint
          by (auto simp flip: suminf_add Diff_eq simp add: image_subset_iff suminf_emeasure)
        then show ?thesis by force
      qed
      finally show "(i. ?S (X i)) = ?S (i. X i)" .
    qed
  qed (auto dest: sets.sets_into_space simp: positive_def intro!: SUP_const)
qed

lemma le_emeasure_sup_measure'1:
  assumes "sets B = sets A" "X  sets A" shows "emeasure A X  emeasure (sup_measure' A B) X"
  by (subst emeasure_sup_measure'[OF assms]) (auto intro!: SUP_upper2[of "X"] assms)

lemma le_emeasure_sup_measure'2:
  assumes "sets B = sets A" "X  sets A" shows "emeasure B X  emeasure (sup_measure' A B) X"
  by (subst emeasure_sup_measure'[OF assms]) (auto intro!: SUP_upper2[of "{}"] assms)

lemma emeasure_sup_measure'_le2:
  assumes [simp]: "sets B = sets C" "sets A = sets C" and [measurable]: "X  sets C"
  assumes A: "Y. Y  X  Y  sets A  emeasure A Y  emeasure C Y"
  assumes B: "Y. Y  X  Y  sets A  emeasure B Y  emeasure C Y"
  shows "emeasure (sup_measure' A B) X  emeasure C X"
proof (subst emeasure_sup_measure')
  show "(SUP Ysets A. emeasure A (X  Y) + emeasure B (X  - Y))  emeasure C X"
    unfolding sets A = sets C
  proof (intro SUP_least)
    fix Y assume [measurable]: "Y  sets C"
    have [simp]: "X  Y  (X - Y) = X"
      by auto
    have "emeasure A (X  Y) + emeasure B (X  - Y)  emeasure C (X  Y) + emeasure C (X  - Y)"
      by (intro add_mono A B) (auto simp: Diff_eq[symmetric])
    also have " = emeasure C X"
      by (subst plus_emeasure) (auto simp: Diff_eq[symmetric])
    finally show "emeasure A (X  Y) + emeasure B (X  - Y)  emeasure C X" .
  qed
qed simp_all

definitiontag important› sup_lexord :: "'a  'a  ('a  'b::order)  'a  'a  'a" where
"sup_lexord A B k s c =
  (if k A = k B then c else
   if ¬ k A  k B  ¬ k B  k A then s else
   if k B  k A then A else B)"

lemma sup_lexord:
  "(k A < k B  P B)  (k B < k A  P A)  (k A = k B  P c) 
    (¬ k B  k A  ¬ k A  k B  P s)  P (sup_lexord A B k s c)"
  by (auto simp: sup_lexord_def)

lemmas le_sup_lexord = sup_lexord[where P="λa. c  a" for c]

lemma sup_lexord1: "k A = k B  sup_lexord A B k s c = c"
  by (simp add: sup_lexord_def)

lemma sup_lexord_commute: "sup_lexord A B k s c = sup_lexord B A k s c"
  by (auto simp: sup_lexord_def)

lemma sigma_sets_le_sets_iff: "(sigma_sets (space x) 𝒜  sets x) = (𝒜  sets x)"
  using sets.sigma_sets_subset[of 𝒜 x] by auto

lemma sigma_le_iff: "𝒜  Pow Ω  sigma Ω 𝒜  x  (Ω  space x  (space x = Ω  𝒜  sets x))"
  by (cases "Ω = space x")
     (simp_all add: eq_commute[of _ "sets x"] le_measure_iff emeasure_sigma le_fun_def
                    sigma_sets_superset_generator sigma_sets_le_sets_iff)

instantiation measure :: (type) semilattice_sup
begin

definitiontag important› sup_measure :: "'a measure  'a measure  'a measure" where
  "sup_measure A B =
    sup_lexord A B space (sigma (space A  space B) {})
      (sup_lexord A B sets (sigma (space A) (sets A  sets B)) (sup_measure' A B))"

instance
proof
  fix x y z :: "'a measure"
  show "x  sup x y"
    unfolding sup_measure_def
  proof (intro le_sup_lexord)
    assume "space x = space y"
    then have *: "sets x  sets y  Pow (space x)"
      using sets.space_closed by auto
    assume "¬ sets y  sets x" "¬ sets x  sets y"
    then have "sets x  sets x  sets y"
      by auto
    also have "  sigma (space x) (sets x  sets y)"
      by (subst sets_measure_of[OF *]) (rule sigma_sets_superset_generator)
    finally show "x  sigma (space x) (sets x  sets y)"
      by (simp add: space_measure_of[OF *] less_eq_measure.intros(2))
  next
    assume "¬ space y  space x" "¬ space x  space y"
    then show "x  sigma (space x  space y) {}"
      by (intro less_eq_measure.intros) auto
  next
    assume "sets x = sets y" then show "x  sup_measure' x y"
      by (simp add: le_measure le_emeasure_sup_measure'1)
  qed (auto intro: less_eq_measure.intros)
  show "y  sup x y"
    unfolding sup_measure_def
  proof (intro le_sup_lexord)
    assume **: "space x = space y"
    then have *: "sets x  sets y  Pow (space y)"
      using sets.space_closed by auto
    assume "¬ sets y  sets x" "¬ sets x  sets y"
    then have "sets y  sets x  sets y"
      by auto
    also have "  sigma (space y) (sets x  sets y)"
      by (subst sets_measure_of[OF *]) (rule sigma_sets_superset_generator)
    finally show "y  sigma (space x) (sets x  sets y)"
      by (simp add: ** space_measure_of[OF *] less_eq_measure.intros(2))
  next
    assume "¬ space y  space x" "¬ space x  space y"
    then show "y  sigma (space x  space y) {}"
      by (intro less_eq_measure.intros) auto
  next
    assume "sets x = sets y" then show "y  sup_measure' x y"
      by (simp add: le_measure le_emeasure_sup_measure'2)
  qed (auto intro: less_eq_measure.intros)
  show "x  y  z  y  sup x z  y"
    unfolding sup_measure_def
  proof (intro sup_lexord[where P="λx. x  y"])
    assume "x  y" "z  y" and [simp]: "space x = space z" "sets x = sets z"
    from x  y show "sup_measure' x z  y"
    proof cases
      case 1 then show ?thesis
        by (intro less_eq_measure.intros(1)) simp
    next
      case 2 then show ?thesis
        by (intro less_eq_measure.intros(2)) simp_all
    next
      case 3 with z  y x  y show ?thesis
        by (auto simp add: le_measure intro!: emeasure_sup_measure'_le2)
    qed
  next
    assume **: "x  y" "z  y" "space x = space z" "¬ sets z  sets x" "¬ sets x  sets z"
    then have *: "sets x  sets z  Pow (space x)"
      using sets.space_closed by auto
    show "sigma (space x) (sets x  sets z)  y"
      unfolding sigma_le_iff[OF *] using ** by (auto simp: le_measure_iff split: if_split_asm)
  next
    assume "x  y" "z  y" "¬ space z  space x" "¬ space x  space z"
    then have "space x  space y" "space z  space y"
      by (auto simp: le_measure_iff split: if_split_asm)
    then show "sigma (space x  space z) {}  y"
      by (simp add: sigma_le_iff)
  qed
qed

end

lemma space_empty_eq_bot: "space a = {}  a = bot"
  using space_empty[of a] by (auto intro!: measure_eqI)

lemma sets_eq_iff_bounded: "A  B  B  C  sets A = sets C  sets B = sets A"
  by (auto dest: sets_eq_imp_space_eq simp add: le_measure_iff split: if_split_asm)

lemma sets_sup: "sets A = sets M  sets B = sets M  sets (sup A B) = sets M"
  by (auto simp add: sup_measure_def sup_lexord_def dest: sets_eq_imp_space_eq)

lemma le_measureD1: "A  B  space A  space B"
  by (auto simp: le_measure_iff split: if_split_asm)

lemma le_measureD2: "A  B  space A = space B  sets A  sets B"
  by (auto simp: le_measure_iff split: if_split_asm)

lemma le_measureD3: "A  B  sets A = sets B  emeasure A X  emeasure B X"
  by (auto simp: le_measure_iff le_fun_def dest: sets_eq_imp_space_eq split: if_split_asm)

lemma UN_space_closed: "(sets ` S)  Pow ((space ` S))"
  using sets.space_closed by auto

definitiontag important›
  Sup_lexord :: "('a  'b::complete_lattice)  ('a set  'a)  ('a set  'a)  'a set  'a"
where
  "Sup_lexord k c s A =
  (let U = (SUP aA. k a)
   in if aA. k a = U then c {aA. k a = U} else s A)"

lemma Sup_lexord:
  "(a S. a  A  k a = (SUP aA. k a)  S = {a'A. k a' = k a}  P (c S))  ((a. a  A  k a  (SUP aA. k a))  P (s A)) 
    P (Sup_lexord k c s A)"
  by (auto simp: Sup_lexord_def Let_def)

lemma Sup_lexord1:
  assumes A: "A  {}" "(a. a  A  k a = (aA. k a))" "P (c A)"
  shows "P (Sup_lexord k c s A)"
  unfolding Sup_lexord_def Let_def
proof (clarsimp, safe)
  show "aA. k a  (xA. k x)  P (s A)"
    by (metis assms(1,2) ex_in_conv)
next
  fix a assume "a  A" "k a = (xA. k x)"
  then have "{a  A. k a = (xA. k x)} = {a  A. k a = k a}"
    by (metis A(2)[symmetric])
  then show "P (c {a  A. k a = (xA. k x)})"
    by (simp add: A(3))
qed

instantiation measure :: (type) complete_lattice
begin

interpretation sup_measure: comm_monoid_set sup "bot :: 'a measure"
  by standard (auto intro!: antisym)

lemma sup_measure_F_mono':
  "finite J  finite I  sup_measure.F id I  sup_measure.F id (I  J)"
proof (induction J rule: finite_induct)
  case empty then show ?case
    by simp
next
  case (insert i J)
  show ?case
  proof cases
    assume "i  I" with insert show ?thesis
      by (auto simp: insert_absorb)
  next
    assume "i  I"
    have "sup_measure.F id I  sup_measure.F id (I  J)"
      by (intro insert)
    also have "  sup_measure.F id (insert i (I  J))"
      using insert i  I by (subst sup_measure.insert) auto
    finally show ?thesis
      by auto
  qed
qed

lemma sup_measure_F_mono: "finite I  J  I  sup_measure.F id J  sup_measure.F id I"
  using sup_measure_F_mono'[of I J] by (auto simp: finite_subset Un_absorb1)

lemma sets_sup_measure_F:
  "finite I  I  {}  (i. i  I  sets i = sets M)  sets (sup_measure.F id I) = sets M"
  by (induction I rule: finite_ne_induct) (simp_all add: sets_sup)

definitiontag important› Sup_measure' :: "'a measure set  'a measure" where
"Sup_measure' M =
  measure_of (aM. space a) (aM. sets a)
    (λX. (SUP P{P. finite P  P  M }. sup_measure.F id P X))"

lemma space_Sup_measure'2: "space (Sup_measure' M) = (mM. space m)"
  unfolding Sup_measure'_def by (intro space_measure_of[OF UN_space_closed])

lemma sets_Sup_measure'2: "sets (Sup_measure' M) = sigma_sets (mM. space m) (mM. sets m)"
  unfolding Sup_measure'_def by (intro sets_measure_of[OF UN_space_closed])

lemma sets_Sup_measure':
  assumes sets_eq[simp]: "m. m  M  sets m = sets A" and "M  {}"
  shows "sets (Sup_measure' M) = sets A"
  using sets_eq[THEN sets_eq_imp_space_eq, simp] M  {} by (simp add: Sup_measure'_def)

lemma space_Sup_measure':
  assumes sets_eq[simp]: "m. m  M  sets m = sets A" and "M  {}"
  shows "space (Sup_measure' M) = space A"
  using sets_eq[THEN sets_eq_imp_space_eq, simp] M  {}
  by (simp add: Sup_measure'_def )

lemma emeasure_Sup_measure':
  assumes sets_eq[simp]: "m. m  M  sets m = sets A" and "X  sets A" "M  {}"
  shows "emeasure (Sup_measure' M) X = (SUP P{P. finite P  P  M}. sup_measure.F id P X)"
    (is "_ = ?S X")
  using Sup_measure'_def
proof (rule emeasure_measure_of)
  note sets_eq[THEN sets_eq_imp_space_eq, simp]
  have *: "sets (Sup_measure' M) = sets A" "space (Sup_measure' M) = space A"
    using M  {} by (simp_all add: Sup_measure'_def)
  let  = "sup_measure.F id"
  show "countably_additive (sets (Sup_measure' M)) ?S"
  proof (rule countably_additiveI, goal_cases)
    case (1 F)
    then have **: "range F  sets A"
      by (auto simp: *)
    show "(i. ?S (F i)) = ?S (i. F i)"
    proof (subst ennreal_suminf_SUP_eq_directed)
      fix i j and N :: "nat set" assume ij: "i  {P. finite P  P  M}" "j  {P. finite P  P  M}"
      have "(i  {}  sets ( i) = sets A)  (j  {}  sets ( j) = sets A) 
        (i  {}  j  {}  sets ( (i  j)) = sets A)"
        using ij by (intro impI sets_sup_measure_F conjI) auto
      then have " j (F n)   (i  j) (F n)   i (F n)   (i  j) (F n)" for n
        using ij
        by (cases "i = {}"; cases "j = {}")
           (auto intro!: le_measureD3 sup_measure_F_mono simp: sets_sup_measure_F
                 simp del: id_apply)
      with ij show "k{P. finite P  P  M}. nN.  i (F n)   k (F n)   j (F n)   k (F n)"
        by (safe intro!: bexI[of _ "i  j"]) auto
    next
      show "(SUP P  {P. finite P  P  M}. n.  P (F n)) = (SUP P  {P. finite P  P  M}.  P ((F ` UNIV)))"
      proof (intro arg_cong [of _ _ Sup] image_cong refl)
        fix i assume i: "i  {P. finite P  P  M}"
        show "(n.  i (F n)) =  i ((F ` UNIV))"
        proof cases
          assume "i  {}" with i ** show ?thesis
            by (smt (verit, best) "1"(2) Measure_Space.sets_sup_measure_F assms(1) mem_Collect_eq subset_eq suminf_cong suminf_emeasure)
        qed simp
      qed
    qed
  qed
  show "positive (sets (Sup_measure' M)) ?S"
    by (auto simp: positive_def bot_ennreal[symmetric])
  show "X  sets (Sup_measure' M)"
    using assms * by auto
qed (rule UN_space_closed)

definitiontag important› Sup_measure :: "'a measure set  'a measure" where
"Sup_measure =
  Sup_lexord space
    (Sup_lexord sets Sup_measure'
      (λU. sigma (uU. space u) (uU. sets u)))
    (λU. sigma (uU. space u) {})"

definitiontag important› Inf_measure :: "'a measure set  'a measure" where
  "Inf_measure A = Sup {x. aA. x  a}"

definitiontag important› inf_measure :: "'a measure  'a measure  'a measure" where
  "inf_measure a b = Inf {a, b}"

definitiontag important› top_measure :: "'a measure" where
  "top_measure = Inf {}"

instance
proof
  note UN_space_closed [simp]
  show upper: "x  Sup A" if x: "x  A" for x :: "'a measure" and A
    unfolding Sup_measure_def
  proof (intro Sup_lexord[where P="λy. x  y"])
    assume "a. a  A  space a  (aA. space a)"
    from this[OF x  A] x  A show "x  sigma (aA. space a) {}"
      by (intro less_eq_measure.intros) auto
  next
    fix a S assume "a  A" and a: "space a = (aA. space a)" and S: "S = {a'  A. space a' = space a}"
      and neq: "aa. aa  S  sets aa  (aS. sets a)"
    have sp_a: "space a = ((space ` S))"
      using aA by (auto simp: S)
    show "x  sigma ((space ` S)) ((sets ` S))"
    proof cases
      assume [simp]: "space x = space a"
      have "sets x  (aS. sets a)"
        using xA neq[of x] by (auto simp: S)
      also have "  sigma_sets (xS. space x) (xS. sets x)"
        by (rule sigma_sets_superset_generator)
      finally show ?thesis
        by (intro less_eq_measure.intros(2)) (simp_all add: sp_a)
    next
      assume "space x  space a"
      moreover have "space x  space a"
        unfolding a using xA by auto
      ultimately show ?thesis
        by (intro less_eq_measure.intros) (simp add: less_le sp_a)
    qed
  next
    fix a b S S' assume "a  A" and a: "space a = (aA. space a)" and S: "S = {a'  A. space a' = space a}"
      and "b  S" and b: "sets b = (aS. sets a)" and S': "S' = {a'  S. sets a' = sets b}"
    then have "S'  {}" "space b = space a"
      by auto
    have sets_eq: "x. x  S'  sets x = sets b"
      by (auto simp: S')
    note sets_eq[THEN sets_eq_imp_space_eq, simp]
    have *: "sets (Sup_measure' S') = sets b" "space (Sup_measure' S') = space b"
      using S'  {} by (simp_all add: Sup_measure'_def sets_eq)
    show "x  Sup_measure' S'"
    proof cases
      assume "x  S"
      with b  S have "space x = space b"
        by (simp add: S)
      show ?thesis
      proof cases
        assume "x  S'"
        show "x  Sup_measure' S'"
        proof (intro le_measure[THEN iffD2] ballI)
          show "sets x = sets (Sup_measure' S')"
            using xS' * by (simp add: S')
          fix X assume "X  sets x"
          show "emeasure x X  emeasure (Sup_measure' S') X"
          proof (subst emeasure_Sup_measure'[OF _ X  sets x])
            show "emeasure x X  (SUP P  {P. finite P  P  S'}. emeasure (sup_measure.F id P) X)"
              using xS' by (intro SUP_upper2[where i="{x}"]) auto
          qed (insert xS' S', auto)
        qed
      next
        assume "x  S'"
        then have "sets x  sets b"
          using xS by (auto simp: S')
        moreover have "sets x  sets b"
          using xS unfolding b by auto
        ultimately show ?thesis
          using * x  S
          by (intro less_eq_measure.intros(2))
             (simp_all add: * space x = space b less_le)
      qed
    next
      assume "x  S"
      with xA x  S space b = space a show ?thesis
        by (intro less_eq_measure.intros)
           (simp_all add: * less_le a SUP_upper S)
    qed
  qed
  show least: "Sup A  x" if x: "z. z  A  z  x" for x :: "'a measure" and A
    unfolding Sup_measure_def
  proof (intro Sup_lexord[where P="λy. y  x"])
    assume "a. a  A  space a  (aA. space a)"
    show "sigma ((space ` A)) {}  x"
      using x[THEN le_measureD1] by (subst sigma_le_iff) auto
  next
    fix a S assume "a  A" "space a = (aA. space a)" and S: "S = {a'  A. space a' = space a}"
      "a. a  S  sets a  (aS. sets a)"
    have "(space ` S)  space x"
      using S le_measureD1[OF x] by auto
    moreover
    have "(space ` S) = space a"
      using aA S by auto
    then have "space x = (space ` S)  (sets ` S)  sets x"
      using a  A le_measureD2[OF x] by (auto simp: S)
    ultimately show "sigma ((space ` S)) ((sets ` S))  x"
      by (subst sigma_le_iff) simp_all
  next
    fix a b S S' assume "a  A" and a: "space a = (aA. space a)" and S: "S = {a'  A. space a' = space a}"
      and "b  S" and b: "sets b = (aS. sets a)" and S': "S' = {a'  S. sets a' = sets b}"
    then have "S'  {}" "space b = space a"
      by auto
    have sets_eq: "x. x  S'  sets x = sets b"
      by (auto simp: S')
    note sets_eq[THEN sets_eq_imp_space_eq, simp]
    have *: "sets (Sup_measure' S') = sets b" "space (Sup_measure' S') = space b"
      using S'  {} by (simp_all add: Sup_measure'_def sets_eq)
    show "Sup_measure' S'  x"
    proof cases
      assume "space x = space a"
      show ?thesis
      proof cases
        assume **: "sets x = sets b"
        show ?thesis
        proof (intro le_measure[THEN iffD2] ballI)
          show ***: "sets (Sup_measure' S') = sets x"
            by (simp add: * **)
          fix X assume "X  sets (Sup_measure' S')"
          show "emeasure (Sup_measure' S') X  emeasure x X"
            unfolding ***
          proof (subst emeasure_Sup_measure'[OF _ X  sets (Sup_measure' S')])
            show "(SUP P  {P. finite P  P  S'}. emeasure (sup_measure.F id P) X)  emeasure x X"
            proof (safe intro!: SUP_least)
              fix P assume P: "finite P" "P  S'"
              show "emeasure (sup_measure.F id P) X  emeasure x X"
              proof cases
                assume "P = {}" then show ?thesis
                  by auto
              next
                assume "P  {}"
                from P have "finite P" "P  A"
                  unfolding S' S by (simp_all add: subset_eq)
                then have "sup_measure.F id P  x"
                  by (induction P) (auto simp: x)
                moreover have "sets (sup_measure.F id P) = sets x"
                  using finite P P  {} P  S' sets x = sets b
                  by (intro sets_sup_measure_F) (auto simp: S')
                ultimately show "emeasure (sup_measure.F id P) X  emeasure x X"
                  by (rule le_measureD3)
              qed
            qed
            show "m  S'  sets m = sets (Sup_measure' S')" for m
              unfolding * by (simp add: S')
          qed fact
        qed
      next
        assume "sets x  sets b"
        moreover have "sets b  sets x"
          unfolding b S using x[THEN le_measureD2] space x = space a by auto
        ultimately show "Sup_measure' S'  x"
          using space x = space a b  S
          by (intro less_eq_measure.intros(2)) (simp_all add: * S)
      qed
    next
      assume "space x  space a"
      then have "space a < space x"
        using le_measureD1[OF x[OF aA]] by auto
      then show "Sup_measure' S'  x"
        by (intro less_eq_measure.intros) (simp add: * space b = space a)
    qed
  qed
  show "Sup {} = (bot::'a measure)" "Inf {} = (top::'a measure)"
    by (auto intro!: antisym least simp: top_measure_def)
  show lower: "x  A  Inf A  x" for x :: "'a measure" and A
    unfolding Inf_measure_def by (intro least) auto
  show greatest: "(z. z  A  x  z)  x  Inf A" for x :: "'a measure" and A
    unfolding Inf_measure_def by (intro upper) auto
  show "inf x y  x" "inf x y  y" "x  y  x  z  x  inf y z" for x y z :: "'a measure"
    by (auto simp: inf_measure_def intro!: lower greatest)
qed

end

lemma sets_SUP:
  assumes "x. x  I  sets (M x) = sets N"
  shows "I  {}  sets (SUP iI. M i) = sets N"
  unfolding Sup_measure_def
  using assms assms[THEN sets_eq_imp_space_eq]
    sets_Sup_measure'[where A=N and M="M`I"]
  by (intro Sup_lexord1[where P="λx. sets x = sets N"]) auto

lemma emeasure_SUP:
  assumes sets: "i. i  I  sets (M i) = sets N" "X  sets N" "I  {}"
  shows "emeasure (SUP iI. M i) X = (SUP J{J. J  {}  finite J  J  I}. emeasure (SUP iJ. M i) X)"
proof -
  interpret sup_measure: comm_monoid_set sup "bot :: 'b measure"
    by standard (auto intro!: antisym)
  have eq: "finite J  sup_measure.F id J = (SUP iJ. i)" for J :: "'b measure set"
    by (induction J rule: finite_induct) auto
  have 1: "J  {}  J  I  sets (SUP xJ. M x) = sets N" for J
    by (intro sets_SUP sets) (auto )
  from I  {} obtain i where "iI" by auto
  have "Sup_measure' (M`I) X = (SUP P{P. finite P  P  M`I}. sup_measure.F id P X)"
    using sets by (intro emeasure_Sup_measure') auto
  also have "Sup_measure' (M`I) = (SUP iI. M i)"
    unfolding Sup_measure_def using I  {} sets sets(1)[THEN sets_eq_imp_space_eq]
    by (intro Sup_lexord1[where P="λx. _ = x"]) auto
  also have "(SUP P{P. finite P  P  M`I}. sup_measure.F id P X) =
    (SUP J{J. J  {}  finite J  J  I}. (SUP iJ. M i) X)"
  proof (intro SUP_eq)
    fix J assume "J  {P. finite P  P  M`I}"
    then obtain J' where J': "J'  I" "finite J'" and J: "J = M`J'" and "finite J"
      using finite_subset_image[of J M I] by auto
    show "j{J. J  {}  finite J  J  I}. sup_measure.F id J X  (SUP ij. M i) X"
    proof cases
      assume "J' = {}" with i  I show ?thesis
        by (auto simp add: J)
    next
      assume "J'  {}" with J J' show ?thesis
        by (intro bexI[of _ "J'"]) (auto simp add: eq simp del: id_apply)
    qed
  next
    fix J assume J: "J  {P. P  {}  finite P  P  I}"
    show "J'{J. finite J  J  M`I}. (SUP iJ. M i) X  sup_measure.F id J' X"
      using J by (intro bexI[of _ "M`J"]) (auto simp add: eq simp del: id_apply)
  qed
  finally show ?thesis .
qed

lemma emeasure_SUP_chain:
  assumes sets: "i. i  A  sets (M i) = sets N" "X  sets N"
  assumes ch: "Complete_Partial_Order.chain (≤) (M ` A)" and "A  {}"
  shows "emeasure (SUP iA. M i) X = (SUP iA. emeasure (M i) X)"
proof (subst emeasure_SUP[OF sets A  {}])
  show "(SUP J{J. J  {}  finite J  J  A}. emeasure (Sup (M ` J)) X) = (SUP iA. emeasure (M i) X)"
  proof (rule SUP_eq)
    fix J assume "J  {J. J  {}  finite J  J  A}"
    then have J: "Complete_Partial_Order.chain (≤) (M ` J)" "finite J" "J  {}" and "J  A"
      using ch[THEN chain_subset, of "M`J"] by auto
    with in_chain_finite[OF J(1)] obtain j where "j  J" "(SUP jJ. M j) = M j"
      by auto
    with J  A show "jA. emeasure (Sup (M ` J)) X  emeasure (M j) X"
      by auto
  next
    fix j assume "jA" then show "i{J. J  {}  finite J  J  A}. emeasure (M j) X  emeasure (Sup (M ` i)) X"
      by (intro bexI[of _ "{j}"]) auto
  qed
qed

subsubsectiontag unimportant› ‹Supremum of a set of σ›-algebras›

lemma space_Sup_eq_UN: "space (Sup M) = (xM. space x)" (is "?L=?R")
proof
  show "?L  ?R"
    using Sup_lexord[where P="λx. space x = _"]
    apply (clarsimp simp: Sup_measure_def)
    by (smt (verit) Sup_lexord_def UN_E mem_Collect_eq space_Sup_measure'2 space_measure_of_conv)
qed (use Sup_upper le_measureD1 in fastforce)


lemma sets_Sup_eq:
  assumes *: "m. m  M  space m = X" and "M  {}"
  shows "sets (Sup M) = sigma_sets X (xM. sets x)"
  unfolding Sup_measure_def
proof (rule Sup_lexord1 [OF M  {}])
  show "sets (Sup_lexord sets Sup_measure' (λU. sigma ( (space ` U)) ( (sets ` U))) M)
      = sigma_sets X ( (sets ` M))"
  apply (rule Sup_lexord)
  apply (metis (mono_tags, lifting) "*" empty_iff mem_Collect_eq sets.sigma_sets_eq sets_Sup_measure')
  by (metis "*" SUP_eq_const UN_space_closed assms(2) sets_measure_of)
qed (use * in blast)


lemma in_sets_Sup: "(m. m  M  space m = X)  m  M  A  sets m  A  sets (Sup M)"
  by (subst sets_Sup_eq[where X=X]) auto

lemma Sup_lexord_rel:
  assumes "i. i  I  k (A i) = k (B i)"
    "R (c (A ` {a  I. k (B a) = (SUP xI. k (B x))})) (c (B ` {a  I. k (B a) = (SUP xI. k (B x))}))"
    "R (s (A`I)) (s (B`I))"
  shows "R (Sup_lexord k c s (A`I)) (Sup_lexord k c s (B`I))"
proof -
  have "A ` {a  I. k (B a) = (SUP xI. k (B x))} =  {a  A ` I. k a = (SUP xI. k (B x))}"
    using assms(1) by auto
  moreover have "B ` {a  I. k (B a) = (SUP xI. k (B x))} =  {a  B ` I. k a = (SUP xI. k (B x))}"
    by auto
  ultimately show ?thesis
    using assms by (auto simp: Sup_lexord_def Let_def image_comp)
qed

lemma sets_SUP_cong:
  assumes eq: "i. i  I  sets (M i) = sets (N i)" 
  shows "sets (SUP iI. M i) = sets (SUP iI. N i)"
  unfolding Sup_measure_def
  using eq eq[THEN sets_eq_imp_space_eq]
  by (intro Sup_lexord_rel[where R="λx y. sets x = sets y"], simp_all add: sets_Sup_measure'2)

lemma sets_Sup_in_sets:
  assumes "M  {}"
  assumes "m. m  M  space m = space N"
  assumes "m. m  M  sets m  sets N"
  shows "sets (Sup M)  sets N"
proof -
  have *: "(space ` M) = space N"
    using assms by auto
  show ?thesis
    unfolding * using assms by (subst sets_Sup_eq[of M "space N"]) (auto intro!: sets.sigma_sets_subset)
qed

lemma measurable_Sup1:
  assumes m: "m  M" and f: "f  measurable m N"
    and const_space: "m n. m  M  n  M  space m = space n"
  shows "f  measurable (Sup M) N"
proof -
  have "space (Sup M) = space m"
    using m by (auto simp add: space_Sup_eq_UN dest: const_space)
  then show ?thesis
    using m f unfolding measurable_def by (auto intro: in_sets_Sup[OF const_space])
qed

lemma measurable_Sup2:
  assumes M: "M  {}"
  assumes f: "m. m  M  f  measurable N m"
    and const_space: "m n. m  M  n  M  space m = space n"
  shows "f  measurable N (Sup M)"
proof -
  from M obtain m where "m  M" by auto
  have space_eq: "n. n  M  space n = space m"
    by (intro const_space m  M)
  have eq: "sets (sigma ( (space ` M)) ( (sets ` M))) = sets (Sup M)"
    by (metis M SUP_eq_const UN_space_closed sets_Sup_eq sets_measure_of space_eq)
  have "f  measurable N (sigma (mM. space m) (mM. sets m))"
  proof (rule measurable_measure_of)
    show "f  space N  (space ` M)"
      using measurable_space[OF f] M by auto
  qed (auto intro: measurable_sets f dest: sets.sets_into_space)
  also have "measurable N (sigma (mM. space m) (mM. sets m)) = measurable N (Sup M)"
    using eq measurable_cong_sets by blast
  finally show ?thesis .
qed

lemma measurable_SUP2:
  "I  {}  (i. i  I  f  measurable N (M i)) 
    (i j. i  I  j  I  space (M i) = space (M j))  f  measurable N (SUP iI. M i)"
  by (auto intro!: measurable_Sup2)

lemma sets_Sup_sigma:
  assumes [simp]: "M  {}" and M: "m. m  M  m  Pow Ω"
  shows "sets (SUP mM. sigma Ω m) = sets (sigma Ω (M))"
proof -
  { fix a m assume "a  sigma_sets Ω m" "m  M"
    then have "a  sigma_sets Ω (M)"
      by induction (auto intro: sigma_sets.intros(2-)) }
  then have "sigma_sets Ω ( (sigma_sets Ω ` M)) = sigma_sets Ω ( M)"
    by (smt (verit, best) UN_iff Union_iff sigma_sets.Basic sigma_sets_eqI)
  then show "sets (SUP mM. sigma Ω m) = sets (sigma Ω (M))"
    by (subst sets_Sup_eq) (fastforce simp add: M Union_least)+
qed

lemma Sup_sigma:
  assumes [simp]: "M  {}" and M: "m. m  M  m  Pow Ω"
  shows "(SUP mM. sigma Ω m) = (sigma Ω (M))"
proof (intro antisym SUP_least)
  have *: "M  Pow Ω"
    using M by auto
  show "sigma Ω (M)  (SUP mM. sigma Ω m)"
  proof (intro less_eq_measure.intros(3))
    show "space (sigma Ω (M)) = space (SUP mM. sigma Ω m)"
         "sets (sigma Ω (M)) = sets (SUP mM. sigma Ω m)"
      by (auto simp add: M sets_Sup_sigma sets_eq_imp_space_eq space_measure_of_conv)
  qed (simp add: emeasure_sigma le_fun_def)
  fix m assume "m  M" then show "sigma Ω m  sigma Ω (M)"
    by (subst sigma_le_iff) (auto simp add: M *)
qed

lemma SUP_sigma_sigma:
  "M  {}  (m. m  M  f m  Pow Ω)  (SUP mM. sigma Ω (f m)) = sigma Ω (mM. f m)"
  using Sup_sigma[of "f`M" Ω] by (auto simp: image_comp)

lemma sets_vimage_Sup_eq:
  assumes *: "M  {}" "f  X  Y" "m. m  M  space m = Y"
  shows "sets (vimage_algebra X f (Sup M)) = sets (SUP m  M. vimage_algebra X f m)"
  (is "?L = ?R")
proof
  have "m. m  M  f  Sup (vimage_algebra X f ` M) M m"
    using assms
    by (smt (verit, del_insts) Pi_iff imageE image_eqI measurable_Sup1
            measurable_vimage_algebra1 space_vimage_algebra)
  then show "?L  ?R"
     by (intro sets_image_in_sets measurable_Sup2) (simp_all add: space_Sup_eq_UN *)
  show "?R  ?L"
    apply (intro sets_Sup_in_sets)
    apply (force simp add: * space_Sup_eq_UN sets_vimage_algebra2 intro: in_sets_Sup)+
    done
qed

lemma restrict_space_eq_vimage_algebra':
  "sets (restrict_space M Ω) = sets (vimage_algebra (Ω  space M) (λx. x) M)"
proof -
  have *: "{A  (Ω  space M) |A. A  sets M} = {A  Ω |A. A  sets M}"
    using sets.sets_into_space[of _ M] by blast

  show ?thesis
    unfolding restrict_space_def
    by (subst sets_measure_of)
       (auto simp add: image_subset_iff sets_vimage_algebra * dest: sets.sets_into_space intro!: arg_cong2[where f=sigma_sets])
qed

lemma sigma_le_sets:
  assumes [simp]: "A  Pow X" shows "sets (sigma X A)  sets N  X  sets N  A  sets N"
proof
  have "X  sigma_sets X A" "A  sigma_sets X A"
    by (auto intro: sigma_sets_top)
  moreover assume "sets (sigma X A)  sets N"
  ultimately show "X  sets N  A  sets N"
    by auto
next
  assume *: "X  sets N  A  sets N"
  { fix Y assume "Y  sigma_sets X A" from this * have "Y  sets N"
      by induction auto }
  then show "sets (sigma X A)  sets N"
    by auto
qed

lemma measurable_iff_sets:
  "f  measurable M N  (f  space M  space N  sets (vimage_algebra (space M) f N)  sets M)"
    unfolding measurable_def
    by (smt (verit, ccfv_threshold) mem_Collect_eq sets_vimage_algebra sigma_sets_le_sets_iff subset_eq)

lemma sets_vimage_algebra_space: "X  sets (vimage_algebra X f M)"
  using sets.top[of "vimage_algebra X f M"] by simp

lemma measurable_mono:
  assumes N: "sets N'  sets N" "space N = space N'"
  assumes M: "sets M  sets M'" "space M = space M'"
  shows "measurable M N  measurable M' N'"
  unfolding measurable_def
proof safe
  fix f A assume "f  space M  space N" "A  sets N'"
  moreover assume "ysets N. f -` y  space M  sets M" note this[THEN bspec, of A]
  ultimately show "f -` A  space M'  sets M'"
    using assms by auto
qed (use N M in auto)

lemma measurable_Sup_measurable:
  assumes f: "f  space N  A"
  shows "f  measurable N (Sup {M. space M = A  f  measurable N M})"
proof (rule measurable_Sup2)
  show "{M. space M = A  f  measurable N M}  {}"
    using f unfolding ex_in_conv[symmetric]
    by (intro exI[of _ "sigma A {}"]) (auto intro!: measurable_measure_of)
qed auto

lemma (in sigma_algebra) sigma_sets_subset':
  assumes a: "a  M" "Ω'  M"
  shows "sigma_sets Ω' a  M"
proof
  show "x  M" if x: "x  sigma_sets Ω' a" for x
    using x by (induct rule: sigma_sets.induct) (use a in auto)
qed

lemma in_sets_SUP: "i  I  (i. i  I  space (M i) = Y)  X  sets (M i)  X  sets (SUP iI. M i)"
  by (intro in_sets_Sup[where X=Y]) auto

lemma measurable_SUP1:
  "i  I  f  measurable (M i) N  (m n. m  I  n  I  space (M m) = space (M n)) 
    f  measurable (SUP iI. M i) N"
  by (auto intro: measurable_Sup1)

lemma sets_image_in_sets':
  assumes X: "X  sets N"
  assumes f: "A. A  sets M  f -` A  X  sets N"
  shows "sets (vimage_algebra X f M)  sets N"
  unfolding sets_vimage_algebra
  by (rule sets.sigma_sets_subset') (auto intro!: measurable_sets X f)

lemma mono_vimage_algebra:
  "sets M  sets N  sets (vimage_algebra X f M)  sets (vimage_algebra X f N)"
  using sets.top[of "sigma X {f -` A  X |A. A  sets N}"]
  unfolding vimage_algebra_def
  by (smt (verit, del_insts) space_measure_of sigma_le_sets Pow_iff inf_le2 mem_Collect_eq subset_eq)

lemma mono_restrict_space: "sets M  sets N  sets (restrict_space M X)  sets (restrict_space N X)"
  unfolding sets_restrict_space by (rule image_mono)

lemma sets_eq_bot: "sets M = {{}}  M = bot"
  by (metis measure_eqI emeasure_empty sets_bot singletonD)

lemma sets_eq_bot2: "{{}} = sets M  M = bot"
  using sets_eq_bot[of M] by blast


lemma (in finite_measure) countable_support:
  "countable {x. measure M {x}  0}"
proof cases
  assume "measure M (space M) = 0"
  then show ?thesis 
    by (metis (mono_tags, lifting) bounded_measure measure_le_0_iff Collect_empty_eq countable_empty) 
next
  let ?M = "measure M (space M)" and ?m = "λx. measure M {x}"
  assume "?M  0"
  then have *: "{x. ?m x  0} = (n. {x. ?M / Suc n < ?m x})"
    using reals_Archimedean[of "?m x / ?M" for x]
    by (auto simp: field_simps not_le[symmetric] divide_le_0_iff measure_le_0_iff)
  have **: "n. finite {x. ?M / Suc n < ?m x}"
  proof (rule ccontr)
    fix n assume "infinite {x. ?M / Suc n < ?m x}" (is "infinite ?X")
    then obtain X where "finite X" "card X = Suc (Suc n)" "X  ?X"
      by (metis infinite_arbitrarily_large)
    then have *: "x. x  X  ?M / Suc n  ?m x"
      by auto
    { fix x assume "x  X"
      from ?M  0 *[OF this] have "?m x  0" by (auto simp: field_simps measure_le_0_iff)
      then have "{x}  sets M" by (auto dest: measure_notin_sets) }
    note singleton_sets = this
    have "?M < (xX. ?M / Suc n)"
      using ?M  0
      by (simp add: card X = Suc (Suc n) field_simps less_le)
    also have "  (xX. ?m x)"
      by (rule sum_mono) fact
    also have " = measure M (xX. {x})"
      using singleton_sets finite X
      by (intro finite_measure_finite_Union[symmetric]) (auto simp: disjoint_family_on_def)
    finally have "?M < measure M (xX. {x})" .
    moreover have "measure M (xX. {x})  ?M"
      using singleton_sets[THEN sets.sets_into_space] by (intro finite_measure_mono) auto
    ultimately show False by simp
  qed
  show ?thesis
    unfolding * by (intro countable_UN countableI_type countable_finite[OF **])
qed

end