(* Title: HOL/Analysis/Embed_Measure.thy
Author: Manuel Eberl, TU München
Defines measure embeddings with injective functions, i.e. lifting a measure on some values
to a measure on "tagged" values (e.g. embed_measure M Inl lifts a measure on values 'a to a
measure on the left part of the sum type 'a + 'b)
*)
section \<open>Embedding Measure Spaces with a Function\<close>
theory Embed_Measure
imports Binary_Product_Measure
begin
text \<open>
Given a measure space on some carrier set \<open>\<Omega>\<close> and a function \<open>f\<close>, we can define a push-forward
measure on the carrier set \<open>f(\<Omega>)\<close> whose \<open>\<sigma>\<close>-algebra is the one generated by mapping \<open>f\<close> over
the original sigma algebra.
This is useful e.\,g.\ when \<open>f\<close> is injective, i.\,e.\ it is some kind of ``tagging'' function.
For instance, suppose we have some algebraaic datatype of values with various constructors,
including a constructor \<open>RealVal\<close> for real numbers. Then \<open>embed_measure\<close> allows us to lift a
measure on real numbers to the appropriate subset of that algebraic datatype.
\<close>
definition\<^marker>\<open>tag important\<close> embed_measure :: "'a measure \<Rightarrow> ('a \<Rightarrow> 'b) \<Rightarrow> 'b measure" where
"embed_measure M f = measure_of (f ` space M) {f ` A |A. A \ sets M}
(\<lambda>A. emeasure M (f -` A \<inter> space M))"
lemma space_embed_measure: "space (embed_measure M f) = f ` space M"
unfolding embed_measure_def
by (subst space_measure_of) (auto dest: sets.sets_into_space)
lemma sets_embed_measure':
assumes inj: "inj_on f (space M)"
shows "sets (embed_measure M f) = {f ` A |A. A \ sets M}"
unfolding embed_measure_def
proof (intro sigma_algebra.sets_measure_of_eq sigma_algebra_iff2[THEN iffD2] conjI allI ballI impI)
fix s assume "s \ {f ` A |A. A \ sets M}"
then obtain s' where s'_props: "s = f ` s'" "s' \ sets M" by auto
hence "f ` space M - s = f ` (space M - s')" using inj
by (auto dest: inj_onD sets.sets_into_space)
also have "... \ {f ` A |A. A \ sets M}" using s'_props by auto
finally show "f ` space M - s \ {f ` A |A. A \ sets M}" .
next
fix A :: "nat \ _" assume "range A \ {f ` A |A. A \ sets M}"
then obtain A' where A': "\i. A i = f ` A' i" "\i. A' i \ sets M"
by (auto simp: subset_eq choice_iff)
then have "(\x. f ` A' x) = f ` (\x. A' x)" by blast
with A' show "(\i. A i) \ {f ` A |A. A \ sets M}"
by simp blast
qed (auto dest: sets.sets_into_space)
lemma the_inv_into_vimage:
"inj_on f X \ A \ X \ the_inv_into X f -` A \ (f`X) = f ` A"
by (auto simp: the_inv_into_f_f)
lemma sets_embed_eq_vimage_algebra:
assumes "inj_on f (space M)"
shows "sets (embed_measure M f) = sets (vimage_algebra (f`space M) (the_inv_into (space M) f) M)"
by (auto simp: sets_embed_measure'[OF assms] Pi_iff the_inv_into_f_f assms sets_vimage_algebra2 Setcompr_eq_image
dest: sets.sets_into_space
intro!: image_cong the_inv_into_vimage[symmetric])
lemma sets_embed_measure:
assumes inj: "inj f"
shows "sets (embed_measure M f) = {f ` A |A. A \ sets M}"
using assms by (subst sets_embed_measure') (auto intro!: inj_onI dest: injD)
lemma in_sets_embed_measure: "A \ sets M \ f ` A \ sets (embed_measure M f)"
unfolding embed_measure_def
by (intro in_measure_of) (auto dest: sets.sets_into_space)
lemma measurable_embed_measure1:
assumes g: "(\x. g (f x)) \ measurable M N"
shows "g \ measurable (embed_measure M f) N"
unfolding measurable_def
proof safe
fix A assume "A \ sets N"
with g have "(\x. g (f x)) -` A \ space M \ sets M"
by (rule measurable_sets)
then have "f ` ((\x. g (f x)) -` A \ space M) \ sets (embed_measure M f)"
by (rule in_sets_embed_measure)
also have "f ` ((\x. g (f x)) -` A \ space M) = g -` A \ space (embed_measure M f)"
by (auto simp: space_embed_measure)
finally show "g -` A \ space (embed_measure M f) \ sets (embed_measure M f)" .
qed (insert measurable_space[OF assms], auto simp: space_embed_measure)
lemma measurable_embed_measure2':
assumes "inj_on f (space M)"
shows "f \ measurable M (embed_measure M f)"
proof-
{
fix A assume A: "A \ sets M"
also from A have "A = A \ space M" by auto
also have "... = f -` f ` A \ space M" using A assms
by (auto dest: inj_onD sets.sets_into_space)
finally have "f -` f ` A \ space M \ sets M" .
}
thus ?thesis using assms unfolding embed_measure_def
by (intro measurable_measure_of) (auto dest: sets.sets_into_space)
qed
lemma measurable_embed_measure2:
assumes [simp]: "inj f" shows "f \ measurable M (embed_measure M f)"
by (auto simp: inj_vimage_image_eq embed_measure_def
intro!: measurable_measure_of dest: sets.sets_into_space)
lemma embed_measure_eq_distr':
assumes "inj_on f (space M)"
shows "embed_measure M f = distr M (embed_measure M f) f"
proof-
have "distr M (embed_measure M f) f =
measure_of (f ` space M) {f ` A |A. A \<in> sets M}
(\<lambda>A. emeasure M (f -` A \<inter> space M))" unfolding distr_def
by (simp add: space_embed_measure sets_embed_measure'[OF assms])
also have "... = embed_measure M f" unfolding embed_measure_def ..
finally show ?thesis ..
qed
lemma embed_measure_eq_distr:
"inj f \ embed_measure M f = distr M (embed_measure M f) f"
by (rule embed_measure_eq_distr') (auto intro!: inj_onI dest: injD)
lemma nn_integral_embed_measure':
"inj_on f (space M) \ g \ borel_measurable (embed_measure M f) \
nn_integral (embed_measure M f) g = nn_integral M (\<lambda>x. g (f x))"
apply (subst embed_measure_eq_distr', simp)
apply (subst nn_integral_distr)
apply (simp_all add: measurable_embed_measure2')
done
lemma nn_integral_embed_measure:
"inj f \ g \ borel_measurable (embed_measure M f) \
nn_integral (embed_measure M f) g = nn_integral M (\<lambda>x. g (f x))"
by(erule nn_integral_embed_measure'[OF subset_inj_on]) simp
lemma emeasure_embed_measure':
assumes "inj_on f (space M)" "A \ sets (embed_measure M f)"
shows "emeasure (embed_measure M f) A = emeasure M (f -` A \ space M)"
by (subst embed_measure_eq_distr'[OF assms(1)])
(simp add: emeasure_distr[OF measurable_embed_measure2'[OF assms(1)] assms(2)])
lemma emeasure_embed_measure:
assumes "inj f" "A \ sets (embed_measure M f)"
shows "emeasure (embed_measure M f) A = emeasure M (f -` A \ space M)"
using assms by (intro emeasure_embed_measure') (auto intro!: inj_onI dest: injD)
lemma embed_measure_comp:
assumes [simp]: "inj f" "inj g"
shows "embed_measure (embed_measure M f) g = embed_measure M (g \ f)"
proof-
have [simp]: "inj (\x. g (f x))" by (subst o_def[symmetric]) (auto intro: inj_compose)
note measurable_embed_measure2[measurable]
have "embed_measure (embed_measure M f) g =
distr M (embed_measure (embed_measure M f) g) (g \<circ> f)"
by (subst (1 2) embed_measure_eq_distr)
(simp_all add: distr_distr sets_embed_measure cong: distr_cong)
also have "... = embed_measure M (g \ f)"
by (subst (3) embed_measure_eq_distr, simp add: o_def, rule distr_cong)
(auto simp: sets_embed_measure o_def image_image[symmetric]
intro: inj_compose cong: distr_cong)
finally show ?thesis .
qed
lemma sigma_finite_embed_measure:
assumes "sigma_finite_measure M" and inj: "inj f"
shows "sigma_finite_measure (embed_measure M f)"
proof -
from assms(1) interpret sigma_finite_measure M .
from sigma_finite_countable obtain A where
A_props: "countable A" "A \ sets M" "\A = space M" "\X. X\A \ emeasure M X \ \" by blast
from A_props have "countable ((`) f`A)" by auto
moreover
from inj and A_props have "(`) f`A \ sets (embed_measure M f)"
by (auto simp: sets_embed_measure)
moreover
from A_props and inj have "\((`) f`A) = space (embed_measure M f)"
by (auto simp: space_embed_measure intro!: imageI)
moreover
from A_props and inj have "\a\(`) f ` A. emeasure (embed_measure M f) a \ \"
by (intro ballI, subst emeasure_embed_measure)
(auto simp: inj_vimage_image_eq intro: in_sets_embed_measure)
ultimately show ?thesis by - (standard, blast)
qed
lemma embed_measure_count_space':
"inj_on f A \ embed_measure (count_space A) f = count_space (f`A)"
apply (subst distr_bij_count_space[of f A "f`A", symmetric])
apply (simp add: inj_on_def bij_betw_def)
apply (subst embed_measure_eq_distr')
apply simp
apply(auto 4 3 intro!: measure_eqI imageI simp add: sets_embed_measure' subset_image_iff)
apply (subst (1 2) emeasure_distr)
apply (auto simp: space_embed_measure sets_embed_measure')
done
lemma embed_measure_count_space:
"inj f \ embed_measure (count_space A) f = count_space (f`A)"
by(rule embed_measure_count_space')(erule subset_inj_on, simp)
lemma sets_embed_measure_alt:
"inj f \ sets (embed_measure M f) = ((`) f) ` sets M"
by (auto simp: sets_embed_measure)
lemma emeasure_embed_measure_image':
assumes "inj_on f (space M)" "X \ sets M"
shows "emeasure (embed_measure M f) (f`X) = emeasure M X"
proof-
from assms have "emeasure (embed_measure M f) (f`X) = emeasure M (f -` f ` X \ space M)"
by (subst emeasure_embed_measure') (auto simp: sets_embed_measure')
also from assms have "f -` f ` X \ space M = X" by (auto dest: inj_onD sets.sets_into_space)
finally show ?thesis .
qed
lemma emeasure_embed_measure_image:
"inj f \ X \ sets M \ emeasure (embed_measure M f) (f`X) = emeasure M X"
by (simp_all add: emeasure_embed_measure in_sets_embed_measure inj_vimage_image_eq)
lemma embed_measure_eq_iff:
assumes "inj f"
shows "embed_measure A f = embed_measure B f \ A = B" (is "?M = ?N \ _")
proof
from assms have I: "inj ((`) f)" by (auto intro: injI dest: injD)
assume asm: "?M = ?N"
hence "sets (embed_measure A f) = sets (embed_measure B f)" by simp
with assms have "sets A = sets B" by (simp only: I inj_image_eq_iff sets_embed_measure_alt)
moreover {
fix X assume "X \ sets A"
from asm have "emeasure ?M (f`X) = emeasure ?N (f`X)" by simp
with \<open>X \<in> sets A\<close> and \<open>sets A = sets B\<close> and assms
have "emeasure A X = emeasure B X" by (simp add: emeasure_embed_measure_image)
}
ultimately show "A = B" by (rule measure_eqI)
qed simp
lemma the_inv_into_in_Pi: "inj_on f A \ the_inv_into A f \ f ` A \ A"
by (auto simp: the_inv_into_f_f)
lemma map_prod_image: "map_prod f g ` (A \ B) = (f`A) \ (g`B)"
using map_prod_surj_on[OF refl refl] .
lemma map_prod_vimage: "map_prod f g -` (A \ B) = (f-`A) \ (g-`B)"
by auto
lemma embed_measure_prod:
assumes f: "inj f" and g: "inj g" and [simp]: "sigma_finite_measure M" "sigma_finite_measure N"
shows "embed_measure M f \\<^sub>M embed_measure N g = embed_measure (M \\<^sub>M N) (\(x, y). (f x, g y))"
(is "?L = _")
unfolding map_prod_def[symmetric]
proof (rule pair_measure_eqI)
have fg[simp]: "\A. inj_on (map_prod f g) A" "\A. inj_on f A" "\A. inj_on g A"
using f g by (auto simp: inj_on_def)
note complete_lattice_class.Sup_insert[simp del] ccSup_insert[simp del]
ccSUP_insert[simp del]
show sets: "sets ?L = sets (embed_measure (M \\<^sub>M N) (map_prod f g))"
unfolding map_prod_def[symmetric]
apply (simp add: sets_pair_eq_sets_fst_snd sets_embed_eq_vimage_algebra
cong: vimage_algebra_cong)
apply (subst sets_vimage_Sup_eq[where Y="space (M \\<^sub>M N)"])
apply (simp_all add: space_pair_measure[symmetric])
apply (auto simp add: the_inv_into_f_f
simp del: map_prod_simp
del: prod_fun_imageE) []
apply auto []
apply (subst (1 2 3 4 ) vimage_algebra_vimage_algebra_eq)
apply (simp_all add: the_inv_into_in_Pi Pi_iff[of snd] Pi_iff[of fst] space_pair_measure)
apply (simp_all add: Pi_iff[of snd] Pi_iff[of fst] the_inv_into_in_Pi vimage_algebra_vimage_algebra_eq
space_pair_measure[symmetric] map_prod_image[symmetric])
apply (intro arg_cong[where f=sets] arg_cong[where f=Sup] arg_cong2[where f=insert] vimage_algebra_cong)
apply (auto simp: map_prod_image the_inv_into_f_f
simp del: map_prod_simp del: prod_fun_imageE)
apply (simp_all add: the_inv_into_f_f space_pair_measure)
done
note measurable_embed_measure2[measurable]
fix A B assume AB: "A \ sets (embed_measure M f)" "B \ sets (embed_measure N g)"
moreover have "f -` A \ g -` B \ space (M \\<^sub>M N) = (f -` A \ space M) \ (g -` B \ space N)"
by (auto simp: space_pair_measure)
ultimately show "emeasure (embed_measure M f) A * emeasure (embed_measure N g) B =
emeasure (embed_measure (M \<Otimes>\<^sub>M N) (map_prod f g)) (A \<times> B)"
by (simp add: map_prod_vimage sets[symmetric] emeasure_embed_measure
sigma_finite_measure.emeasure_pair_measure_Times)
qed (insert assms, simp_all add: sigma_finite_embed_measure)
lemma mono_embed_measure:
"space M = space M' \ sets M \ sets M' \ sets (embed_measure M f) \ sets (embed_measure M' f)"
unfolding embed_measure_def
apply (subst (1 2) sets_measure_of)
apply (blast dest: sets.sets_into_space)
apply (blast dest: sets.sets_into_space)
apply simp
apply (intro sigma_sets_mono')
apply safe
apply (simp add: subset_eq)
apply metis
done
lemma density_embed_measure:
assumes inj: "inj f" and Mg[measurable]: "g \ borel_measurable (embed_measure M f)"
shows "density (embed_measure M f) g = embed_measure (density M (g \ f)) f" (is "?M1 = ?M2")
proof (rule measure_eqI)
fix X assume X: "X \ sets ?M1"
from inj have Mf[measurable]: "f \ measurable M (embed_measure M f)"
by (rule measurable_embed_measure2)
from Mg and X have "emeasure ?M1 X = \\<^sup>+ x. g x * indicator X x \embed_measure M f"
by (subst emeasure_density) simp_all
also from X have "... = \\<^sup>+ x. g (f x) * indicator X (f x) \M"
by (subst embed_measure_eq_distr[OF inj], subst nn_integral_distr) auto
also have "... = \\<^sup>+ x. g (f x) * indicator (f -` X \ space M) x \M"
by (intro nn_integral_cong) (auto split: split_indicator)
also from X have "... = emeasure (density M (g \ f)) (f -` X \ space M)"
by (subst emeasure_density) (simp_all add: measurable_comp[OF Mf Mg] measurable_sets[OF Mf])
also from X and inj have "... = emeasure ?M2 X"
by (subst emeasure_embed_measure) (simp_all add: sets_embed_measure)
finally show "emeasure ?M1 X = emeasure ?M2 X" .
qed (simp_all add: sets_embed_measure inj)
lemma density_embed_measure':
assumes inj: "inj f" and inv: "\x. f' (f x) = x" and Mg[measurable]: "g \ borel_measurable M"
shows "density (embed_measure M f) (g \ f') = embed_measure (density M g) f"
proof-
have "density (embed_measure M f) (g \ f') = embed_measure (density M (g \ f' \ f)) f"
by (rule density_embed_measure[OF inj])
(rule measurable_comp, rule measurable_embed_measure1, subst measurable_cong,
rule inv, rule measurable_ident_sets, simp, rule Mg)
also have "density M (g \ f' \ f) = density M g"
by (intro density_cong) (subst measurable_cong, simp add: o_def inv, simp_all add: Mg inv)
finally show ?thesis .
qed
lemma inj_on_image_subset_iff:
assumes "inj_on f C" "A \ C" "B \ C"
shows "f ` A \ f ` B \ A \ B"
proof (intro iffI subsetI)
fix x assume A: "f ` A \ f ` B" and B: "x \ A"
from B have "f x \ f ` A" by blast
with A have "f x \ f ` B" by blast
then obtain y where "f x = f y" and "y \ B" by blast
with assms and B have "x = y" by (auto dest: inj_onD)
with \<open>y \<in> B\<close> show "x \<in> B" by simp
qed auto
lemma AE_embed_measure':
assumes inj: "inj_on f (space M)"
shows "(AE x in embed_measure M f. P x) \ (AE x in M. P (f x))"
proof
let ?M = "embed_measure M f"
assume "AE x in ?M. P x"
then obtain A where A_props: "A \ sets ?M" "emeasure ?M A = 0" "{x\space ?M. \P x} \ A"
by (force elim: AE_E)
then obtain A' where A'_props: "A = f ` A'" "A' \ sets M" by (auto simp: sets_embed_measure' inj)
moreover have B: "{x\space ?M. \P x} = f ` {x\space M. \P (f x)}"
by (auto simp: inj space_embed_measure)
from A_props(3) have "{x\space M. \P (f x)} \ A'"
by (subst (asm) B, subst (asm) A'_props, subst (asm) inj_on_image_subset_iff[OF inj])
(insert A'_props, auto dest: sets.sets_into_space)
moreover from A_props A'_props have "emeasure M A' = 0"
by (simp add: emeasure_embed_measure_image' inj)
ultimately show "AE x in M. P (f x)" by (intro AE_I)
next
let ?M = "embed_measure M f"
assume "AE x in M. P (f x)"
then obtain A where A_props: "A \ sets M" "emeasure M A = 0" "{x\space M. \P (f x)} \ A"
by (force elim: AE_E)
hence "f`A \ sets ?M" "emeasure ?M (f`A) = 0" "{x\space ?M. \P x} \ f`A"
by (auto simp: space_embed_measure emeasure_embed_measure_image' sets_embed_measure' inj)
thus "AE x in ?M. P x" by (intro AE_I)
qed
lemma AE_embed_measure:
assumes inj: "inj f"
shows "(AE x in embed_measure M f. P x) \ (AE x in M. P (f x))"
using assms by (intro AE_embed_measure') (auto intro!: inj_onI dest: injD)
lemma nn_integral_monotone_convergence_SUP_countable:
fixes f :: "'a \ 'b \ ennreal"
assumes nonempty: "Y \ {}"
and chain: "Complete_Partial_Order.chain (\) (f ` Y)"
and countable: "countable B"
shows "(\\<^sup>+ x. (SUP i\Y. f i x) \count_space B) = (SUP i\Y. (\\<^sup>+ x. f i x \count_space B))"
(is "?lhs = ?rhs")
proof -
let ?f = "(\i x. f i (from_nat_into B x) * indicator (to_nat_on B ` B) x)"
have "?lhs = \\<^sup>+ x. (SUP i\Y. f i (from_nat_into B (to_nat_on B x))) \count_space B"
by(rule nn_integral_cong)(simp add: countable)
also have "\ = \\<^sup>+ x. (SUP i\Y. f i (from_nat_into B x)) \count_space (to_nat_on B ` B)"
by(simp add: embed_measure_count_space'[symmetric] inj_on_to_nat_on countable nn_integral_embed_measure' measurable_embed_measure1)
also have "\ = \\<^sup>+ x. (SUP i\Y. ?f i x) \count_space UNIV"
by(simp add: nn_integral_count_space_indicator ennreal_indicator[symmetric] SUP_mult_right_ennreal nonempty)
also have "\ = (SUP i\Y. \\<^sup>+ x. ?f i x \count_space UNIV)"
proof(rule nn_integral_monotone_convergence_SUP_nat)
show "Complete_Partial_Order.chain (\) (?f ` Y)"
by(rule chain_imageI[OF chain, unfolded image_image])(auto intro!: le_funI split: split_indicator dest: le_funD)
qed fact
also have "\ = (SUP i\Y. \\<^sup>+ x. f i (from_nat_into B x) \count_space (to_nat_on B ` B))"
by(simp add: nn_integral_count_space_indicator)
also have "\ = (SUP i\Y. \\<^sup>+ x. f i (from_nat_into B (to_nat_on B x)) \count_space B)"
by(simp add: embed_measure_count_space'[symmetric] inj_on_to_nat_on countable nn_integral_embed_measure' measurable_embed_measure1)
also have "\ = ?rhs"
by(intro arg_cong2[where f = "\A f. Sup (f ` A)"] ext nn_integral_cong_AE)(simp_all add: AE_count_space countable)
finally show ?thesis .
qed
end
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