How to define a semilattice of lists? - isabelle

I'm trying to define an upper semilattice:
A ≺ B
... ≺ C [B,B,B] ≺ C [B,B] ≺ C [B] ≺ B
C [A] ≺ C [B]
C [A,A] ≺ C [A,B] ≺ C [B,B]
C [A,A] ≺ C [B,A] ≺ C [B,B]
C [A,A,A] ≺ C [A,A,B] ≺ C [A,B,B] ≺ C [B,B,B]
C [A,A,A] ≺ C [A,B,A] ≺ C [A,B,B] ≺ C [B,B,B]
C [A,A,A] ≺ C [A,A,B] ≺ C [B,A,B] ≺ C [B,B,B]
C [A,A,A] ≺ C [B,A,A] ≺ C [B,A,B] ≺ C [B,B,B]
C [A,A,A] ≺ C [A,B,A] ≺ C [B,B,A] ≺ C [B,B,B]
C [A,A,A] ≺ C [B,A,A] ≺ C [B,B,A] ≺ C [B,B,B]
and so on...
I need to prohibit a direct relations of the form:
C [A,A] ≺ C [B,B]
C [A,A,B] ≺ C [B,B,B]
and so on...
Only one element must differ in preceding elements. I will define this indirect relations as a transitive closure.
I tried to define it as follows:
datatype t = A | B | C "t list"
definition "only_one p xs ys ≡
let xys = zip xs ys in
length xs = length ys ∧
list_all (λ(x, y). x = y ∨ p x y) xys ∧
length xs =
length (takeWhile (λ(x, y). x = y) xys) +
length (takeWhile (λ(x, y). x = y) (rev xys)) + 1"
inductive prec_t ("_ ≺ _" [65, 65] 65) where
"A ≺ B"
| "C [B] ≺ B"
| "C (xs#[B]) ≺ C xs"
| "only_one (λx y. x ≺ y) xs ys ⟹
C xs ≺ C ys"
But I get the following error:
Proof failed.
1. ⋀x y xa xb xs ys.
x (?x47 x y xa xb xs ys) (?x48 x y xa xb xs ys) ⟶
y (?x47 x y xa xb xs ys) (?x48 x y xa xb xs ys) ⟹
only_one x xs ys ⟶ only_one y xs ys
The error(s) above occurred for the goal statement⌂:
mono
(λp x1 x2.
x1 = A ∧ x2 = B ∨
x1 = C [B] ∧ x2 = B ∨
(∃xs. x1 = C (xs # [B]) ∧ x2 = C xs) ∨ (∃xs ys. x1 = C xs ∧ x2 = C ys ∧ only_one p xs ys))
Could you suggest how to fix it?
UPDATE
I redefined the condition checker as follows. But it doesn't help.
primrec only_one' :: "bool ⇒ ('a ⇒ 'a ⇒ bool) ⇒ 'a list ⇒ 'a list ⇒ bool" where
"only_one' found p xs [] = (case xs of [] ⇒ found | _ ⇒ False)"
| "only_one' found p xs (y # ys) = (case xs of [] ⇒ False | z # zs ⇒
if z = y then only_one' found p zs ys else
let found' = p z y in
if found ∧ found' then False else only_one' found' p zs ys)"
abbreviation "only_one ≡ only_one' False"
UPDATE 2
An inductive definition doesn't help too:
inductive only_one :: "bool ⇒ ('a ⇒ 'a ⇒ bool) ⇒ 'a list ⇒ 'a list ⇒ bool" where
"only_one True p [] []"
| "x = y ⟹
only_one found p xs ys ⟹
only_one found p (x#xs) (y#ys)"
| "p x y ⟹
found = False ⟹
only_one True p xs ys ⟹
only_one found p (x#xs) (y#ys)"

Your inductive definition is not accepted, since Isabelle does not know that only_one is monotone.
Therefore, the following code in front of your inductive definition should solve your problem.
lemma only_one_mono: "(⋀ x y. x ∈ set xs ⟹ y ∈ set ys ⟹ p x y ⟶ q x y) ⟹
only_one p xs ys ⟶ only_one q xs ys" sorry
declare only_one_mono[mono]
Best, René

Related

How to prove elimination rules using Isar?

Here is a simple theory:
datatype t1 = A | B | C
datatype t2 = D | E t1 | F | G
inductive R where
"R A B"
| "R B C"
inductive_cases [elim]: "R x B" "R x A" "R x C"
inductive S where
"S D (E _)"
| "R x y ⟹ S (E x) (E y)"
inductive_cases [elim]: "S x D" "S x (E y)"
I can prove lemma elim using two helper lemmas:
lemma tranclp_S_x_E:
"S⇧+⇧+ x (E y) ⟹ x = D ∨ (∃z. x = E z)"
by (induct rule: converse_tranclp_induct; auto)
(* Let's assume that it's proven *)
lemma reflect_tranclp_E:
"S⇧+⇧+ (E x) (E y) ⟹ R⇧+⇧+ x y"
sorry
lemma elim:
"S⇧+⇧+ x (E y) ⟹
(x = D ⟹ P) ⟹ (⋀z. x = E z ⟹ R⇧+⇧+ z y ⟹ P) ⟹ P"
using reflect_tranclp_E tranclp_S_x_E by blast
I need to prove elim using Isar:
lemma elim:
assumes "S⇧+⇧+ x (E y)"
shows "(x = D ⟹ P) ⟹ (⋀z. x = E z ⟹ R⇧+⇧+ z y ⟹ P) ⟹ P"
proof -
assume "S⇧+⇧+ x (E y)"
then obtain z where "x = D ∨ x = E z"
by (induct rule: converse_tranclp_induct; auto)
also have "S⇧+⇧+ (E z) (E y) ⟹ R⇧+⇧+ z y"
sorry
finally show ?thesis
But I get the following errors:
No matching trans rules for calculation:
x = D ∨ x = E z
S⇧+⇧+ (E z) (E y) ⟹ R⇧+⇧+ z y
Failed to refine any pending goal
Local statement fails to refine any pending goal
Failed attempt to solve goal by exported rule:
(S⇧+⇧+ x (E y)) ⟹ P
How to fix them?
I guess that this lemma could have a simpler proof. But I need to prove it in two steps:
Show the possible values of x
Show that E reflects transitive closure
I think also that this lemma could be proven by cases on x. But my real data types have too many cases. So, it's not a preferred solution.
This variant seems to work:
lemma elim:
assumes "S⇧+⇧+ x (E y)"
and "x = D ⟹ P"
and "⋀z. x = E z ⟹ R⇧+⇧+ z y ⟹ P"
shows "P"
proof -
have "S⇧+⇧+ x (E y)" by (simp add: assms(1))
then obtain z where "x = D ∨ x = E z"
by (induct rule: converse_tranclp_induct; auto)
moreover
have "S⇧+⇧+ (E z) (E y) ⟹ R⇧+⇧+ z y"
sorry
ultimately show ?thesis
using assms by auto
qed
Assumptions should be separated from the goal.
As a first statement I shoud use have instead of assume. It's not a new assumption, just the existing one.
Instead of finally I should use ultimately. It seems that the later one has a simpler application logic.

What kind of functions preserve properties of closure?

I'm trying to prove the following lemmas:
lemma tranclp_fun_preserve:
"(⋀x y. x ≠ y ⟹ f x ≠ f y) ⟹
(⋀x y. f x ≠ f y ⟹ x ≠ y) ⟹
(⋀x y. f x = f y ⟹ x = y) ⟹
(λ x y. P x y)⇧+⇧+ (f x) (f y) ⟹ (λ x y. P (f x) (f y))⇧+⇧+ x y"
apply (erule tranclp.cases)
apply blast
lemma tranclp_fun_preserve2:
"(⋀x y. x ≠ y ⟹ f x ≠ f y) ⟹
(⋀x y. f x ≠ f y ⟹ x ≠ y) ⟹
(⋀x y. f x = f y ⟹ x = y) ⟹
(λ x y. P (f x) (f y))⇧+⇧+ x y ⟹ (λ x y. P x y)⇧+⇧+ (f x) (f y)"
apply (erule tranclp.cases)
apply blast
However, I'm stuck. Should I choose another set of assumptions for the function f? Could you suggest how to prove the lemmas tranclp_fun_preserve and tranclp_fun_preserve2?
UPDATE
My function is injective with a special property described at the end. I'm afraid that the following example is too long. However, I want to make it a little bit more realistic. Here are two auxiliary types errorable and nullable:
(*** errorable ***)
notation
bot ("⊥")
typedef 'a errorable ("_⇩⊥" [21] 21) = "UNIV :: 'a option set" ..
definition errorable :: "'a ⇒ 'a errorable" ("_⇩⊥" [1000] 1000) where
"errorable x = Abs_errorable (Some x)"
instantiation errorable :: (type) bot
begin
definition "⊥ ≡ Abs_errorable None"
instance ..
end
free_constructors case_errorable for
errorable
| "⊥ :: 'a errorable"
apply (metis Rep_errorable_inverse bot_errorable_def errorable_def not_Some_eq)
apply (metis Abs_errorable_inverse UNIV_I errorable_def option.inject)
by (simp add: Abs_errorable_inject bot_errorable_def errorable_def)
(*** nullable ***)
class opt =
fixes null :: "'a" ("ε")
typedef 'a nullable ("_⇩□" [21] 21) = "UNIV :: 'a option set" ..
definition nullable :: "'a ⇒ 'a nullable" ("_⇩□" [1000] 1000) where
"nullable x = Abs_nullable (Some x)"
instantiation nullable :: (type) opt
begin
definition "ε ≡ Abs_nullable None"
instance ..
end
free_constructors case_nullable for
nullable
| "ε :: 'a nullable"
apply (metis Rep_nullable_inverse null_nullable_def nullable_def option.collapse)
apply (simp add: Abs_nullable_inject nullable_def)
by (metis Abs_nullable_inverse UNIV_I null_nullable_def nullable_def option.distinct(1))
Two kinds of values:
datatype any = BoolVal "bool⇩⊥" | NatVal "nat⇩⊥" | RealVal "real⇩⊥" | InvalidAny unit
datatype oany = OBoolVal "bool⇩⊥⇩□" | ONatVal "nat⇩⊥⇩□" | ORealVal "real⇩⊥⇩□" | OInvalidAny "unit⇩□"
Here is a concrete example of the function f (any_to_oany), it's injective:
inductive any_oany :: "any ⇒ oany ⇒ bool" where
"any_oany (BoolVal x) (OBoolVal x⇩□)"
| "any_oany (NatVal x) (ONatVal x⇩□)"
| "any_oany (RealVal x) (ORealVal x⇩□)"
| "any_oany (InvalidAny x) (OInvalidAny x⇩□)"
fun any_to_oany :: "any ⇒ oany" where
"any_to_oany (BoolVal x) = (OBoolVal x⇩□)"
| "any_to_oany (NatVal x) = (ONatVal x⇩□)"
| "any_to_oany (RealVal x) = (ORealVal x⇩□)"
| "any_to_oany (InvalidAny x) = (OInvalidAny x⇩□)"
lemma any_oany_eq_fun:
"any_oany x y ⟷ any_to_oany x = y"
by (cases x; cases y; auto simp: any_oany.simps)
Here is a concrete example of the relation P (cast_oany):
inductive cast_any :: "any ⇒ any ⇒ bool" where
"cast_any (BoolVal ⊥) (InvalidAny ())"
| "cast_any (NatVal ⊥) (RealVal ⊥)"
| "cast_any (NatVal x⇩⊥) (RealVal (real x)⇩⊥)"
| "cast_any (RealVal ⊥) (InvalidAny ())"
inductive cast_oany :: "oany ⇒ oany ⇒ bool" where
"cast_any x y ⟹ any_oany x ox ⟹ any_oany y oy ⟹
cast_oany ox oy"
| "cast_oany (OBoolVal ε) (OInvalidAny ε)"
| "cast_oany (ONatVal ε) (ORealVal ε)"
| "cast_oany (ORealVal ε) (OInvalidAny ε)"
I proved equivalence of cast_any and cast_oany on any:
lemma cast_any_implies_cast_oany:
"cast_any x y ⟹ cast_oany (any_to_oany x) (any_to_oany y)"
by (simp add: any_oany_eq_fun cast_oany.intros(1))
lemma cast_oany_implies_cast_any:
"cast_oany (any_to_oany x) (any_to_oany y) ⟹ cast_any x y"
by (cases x; cases y; simp add: any_oany.simps cast_oany.simps)
And my final goal is to prove similar lemmas for the transitive closures of these relations:
lemma trancl_cast_oany_implies_cast_any:
"cast_oany⇧+⇧+ (any_to_oany x) (any_to_oany y) ⟹ cast_any⇧+⇧+ x y"
lemma trancl_cast_any_implies_cast_oany:
"cast_any⇧+⇧+ x y ⟹ cast_oany⇧+⇧+ (any_to_oany x) (any_to_oany y)"
I proved the following intermediate lemmas:
lemma trancl_cast_oany_implies_cast_any':
"(λx y. cast_oany (any_to_oany x) (any_to_oany y))⇧+⇧+ x y ⟹
cast_any⇧+⇧+ x y"
apply (erule tranclp_trans_induct)
apply (simp add: cast_oany_implies_cast_any tranclp.r_into_trancl)
by auto
lemma trancl_cast_any_implies_cast_oany':
"cast_any⇧+⇧+ x y ⟹
(λx y. cast_oany (any_to_oany x) (any_to_oany y))⇧+⇧+ x y"
apply (erule tranclp_trans_induct)
apply (simp add: cast_any_implies_cast_oany tranclp.r_into_trancl)
by auto
At last, if I could prove the following lemmas from the original question, then I will able to prove my goal lemmas.
lemma tranclp_fun_preserve:
"cast_oany⇧+⇧+ (any_to_oany x) (any_to_oany y) ⟹
(λx y. cast_oany (any_to_oany x) (any_to_oany y))⇧+⇧+ x y"
lemma tranclp_fun_preserve2:
"(λx y. cast_oany (any_to_oany x) (any_to_oany y))⇧+⇧+ x y ⟹
cast_oany⇧+⇧+ (any_to_oany x) (any_to_oany y)"
In this paragraph I provide an important property of the function any_to_oany. The set of oany values consists of two parts:
nulls (OBoolVal ε, ONatVal ε, ORealVal ε, OInvalidAny ε)
all other values.
The relation cast_oany relates the values inside the first part and inside the second part separately. There is no relation between the values from different parts. The function any_to_oany maps values only to the second part. I don't know what is the right name of this property: subsets 1 and 2 are "closed" with respect to the relation cast_oany. And the function any_to_oany maps values only to one subset, and it's bijective on this subset.
The answer presented below is a substantial revision of the original answer. The original answer is available through the revision history.
Effectively, in the course of the initial revisions it was established that the question comes down to merely proving that bijective functions between two sets preserve the properties of closure. The solution below presents the relevant proofs without the application-specific context (the answer also combines some of the amendments to the original answer that were made by the author of the thread):
section ‹Extension of the theory #{text Transitive_Closure}›
theory Transitive_Closure_Ext
imports
Complex_Main
"HOL-Library.FuncSet"
begin
lemma trancl_subset_trancl: "r ⊆ s⇧+ ⟹ r⇧+ ⊆ s⇧+"
by (metis subsetI trancl_id trancl_mono trans_trancl)
lemma mono_tranclp[mono]: "(⋀a b. R a b ⟶ S a b) ⟹ R⇧+⇧+ a b ⟶ S⇧+⇧+ a b"
apply(rule) using trancl_mono[to_pred] by blast
lemma tranclp_mono: "R ≤ S ⟹ R⇧+⇧+ ≤ S⇧+⇧+"
by (metis (full_types) mono_tranclp predicate2D predicate2I)
lemma preserve_tranclp:
assumes "⋀x y. R x y ⟹ S (f x) (f y)"
shows "R⇧+⇧+ x y ⟹ S⇧+⇧+ (f x) (f y)"
proof -
assume Rpp: "R⇧+⇧+ x y"
define P where P: "P = (λx y. S⇧+⇧+ (f x) (f y))"
define r where r: "r = (λx y. S (f x) (f y))"
have major: "r⇧+⇧+ x y"
by (insert assms Rpp r; erule tranclp_trans_induct; auto)
have cases_1: "r x y ⟹ P x y" for x y unfolding r P by simp
have cases_2: "r⇧+⇧+ x y ⟹ P x y ⟹ r⇧+⇧+ y z ⟹ P y z ⟹ P x z" for x y z
unfolding P by simp
from major cases_1 cases_2 have "P x y" by (rule tranclp_trans_induct)
thus "S⇧+⇧+ (f x) (f y)" unfolding P .
qed
lemma preserve_trancl:
assumes "map_prod f f ` r ⊆ s"
shows "map_prod f f ` r⇧+ ⊆ s⇧+"
proof -
from assms have "(x, y) ∈ r ⟶ (f x, f y) ∈ s" for x y by auto
then have "(x, y) ∈ r⇧+ ⟶ (f x, f y) ∈ s⇧+" for x y
by (metis preserve_tranclp[to_set])
thus "map_prod f f ` r⇧+ ⊆ s⇧+" by clarsimp
qed
lemma preserve_tranclp_inv:
assumes bij_f: "bij_betw f a b"
and R: "⋀x y. R x y ⟹ (x, y) ∈ a × a"
and S: "⋀x y. S x y ⟹ (x, y) ∈ b × b"
and S_R: "⋀x y. (x, y) ∈ a × a ⟹ S (f x) (f y) ⟹ R x y"
shows "(x, y) ∈ a × a ⟹ S⇧+⇧+ (f x) (f y) ⟹ R⇧+⇧+ x y"
proof -
assume x_y_in_aa: "(x, y) ∈ a × a"
assume Spp: "S⇧+⇧+ (f x) (f y)"
define g where g: "g = the_inv_into a f"
define gr where gr: "gr = restrict g b"
define P where P: "P = (λx y. (x, y) ∈ b × b ⟶ R⇧+⇧+ (gr x) (gr y))"
from Spp have fx_fy_in_bb: "(f x, f y) ∈ b × b"
using S by (metis converse_tranclpE mem_Sigma_iff tranclp.cases)
have cases_1: "S x y ⟹ P x y" for x y unfolding P
proof(rule impI)
assume Sxy: "S x y" and xy_in_bb: "(x, y) ∈ b × b"
with bij_f have gr_in_aa: "(gr x, gr y) ∈ a × a"
unfolding gr g apply(auto)
using bij_betwE bij_betw_the_inv_into by blast+
from bij_f xy_in_bb have "x = f (gr x)" and "y = f (gr y)"
unfolding gr g using f_the_inv_into_f_bij_betw by fastforce+
with Sxy have S_fgrx_fgry: "S (f (gr x)) (f (gr y))" by simp
from gr_in_aa S_fgrx_fgry have "R (gr x) (gr y)" by (rule S_R)
thus "R⇧+⇧+ (gr x) (gr y)" ..
qed
with bij_f S have
"S⇧+⇧+ x y ⟹ S⇧+⇧+ y z ⟹ x ∈ b ⟹ z ∈ b ⟹ y ∈ b" for x y z
by (auto dest: SigmaD1 tranclpD)
with P have cases_2:
"S⇧+⇧+ x y ⟹ P x y ⟹ S⇧+⇧+ y z ⟹ P y z ⟹ P x z" for x y z
by auto
from Spp cases_1 cases_2 have "P (f x) (f y)" by (rule tranclp_trans_induct)
with bij_f fx_fy_in_bb x_y_in_aa show "R⇧+⇧+ x y"
unfolding P gr g restrict_def bij_betw_def by (simp add: the_inv_into_f_f)
qed
lemma preserve_trancl_inv:
assumes bij_f: "bij_betw f a b"
and r_in_aa: "r ⊆ a × a"
and s_in_bb: "s ⊆ b × b"
and s_r: "(map_prod f f -` s) ∩ (a × a) ⊆ r ∩ (a × a)"
shows "(map_prod f f -` s⇧+) ∩ (a × a) ⊆ r⇧+ ∩ (a × a)"
proof -
from r_in_aa have r_in_aa_set:
"(x, y) ∈ r ⟹ (x, y) ∈ a × a" for x y by auto
from s_in_bb have s_in_bb_set: "⋀x y. (x, y) ∈ s ⟹ (x, y) ∈ b × b" by auto
from s_r have s_r_set:
"(x, y) ∈ a × a ⟹ (f x, f y) ∈ s ⟹ (x, y) ∈ r" for x y
unfolding map_prod_def by auto
from bij_f r_in_aa_set s_in_bb_set s_r_set have
"(x, y) ∈ a × a ⟹ (f x, f y) ∈ s⇧+ ⟹ (x, y) ∈ r⇧+" for x y
by (rule preserve_tranclp_inv[to_set])
thus ?thesis unfolding map_prod_def by clarsimp
qed
lemma preserve_rtranclp:
assumes "⋀x y. R x y ⟹ S (f x) (f y)"
shows "R⇧*⇧* x y ⟹ S⇧*⇧* (f x) (f y)"
by (insert assms, metis Nitpick.rtranclp_unfold preserve_tranclp)
lemma preserve_rtrancl:
assumes "map_prod f f ` r ⊆ s"
shows "map_prod f f ` r⇧* ⊆ s⇧*"
proof -
from assms have "(x, y) ∈ r ⟶ (f x, f y) ∈ s" for x y by auto
then have "(x, y) ∈ r⇧* ⟶ (f x, f y) ∈ s⇧*" for x y
by (metis preserve_rtranclp[to_set])
thus "map_prod f f ` r⇧* ⊆ s⇧*" by clarsimp
qed
lemma preserve_rtranclp_inv:
assumes bij_f: "bij_betw f a b"
and "⋀x y. R x y ⟹ (x, y) ∈ a × a"
and "⋀x y. S x y ⟹ (x, y) ∈ b × b"
and "⋀x y. (x, y) ∈ a × a ⟹ S (f x) (f y) ⟹ R x y"
shows "(x, y) ∈ a × a ⟹ S⇧*⇧* (f x) (f y) ⟹ R⇧*⇧* x y"
proof -
assume xy_in_aa: "(x, y) ∈ a × a" and Spp: "S⇧*⇧* (f x) (f y)"
show "R⇧*⇧* x y"
proof(cases "f x ≠ f y")
case True show ?thesis
proof -
from True Spp obtain z where "S⇧*⇧* (f x) z" and "S z (f y)"
by (auto elim: rtranclp.cases)
then have "S⇧+⇧+ (f x) (f y)" by (rule rtranclp_into_tranclp1)
with assms xy_in_aa have "R⇧+⇧+ x y" by (rule preserve_tranclp_inv)
thus ?thesis by simp
qed
next
case False show ?thesis
proof -
from False xy_in_aa bij_f have "x = y"
unfolding bij_betw_def by (auto dest: SigmaD1 SigmaD2 inj_onD)
thus "R⇧*⇧* x y" by simp
qed
qed
qed
lemma preserve_rtrancl_inv:
assumes bij_f: "bij_betw f a b"
and r_in_aa: "r ⊆ a × a"
and s_in_bb: "s ⊆ b × b"
and as_s_r: "(map_prod f f -` s) ∩ (a × a) ⊆ r ∩ (a × a)"
shows "(map_prod f f -` s⇧*) ∩ (a × a) ⊆ r⇧* ∩ (a × a)"
proof -
from r_in_aa have r_in_aa_set:
"(x, y) ∈ r ⟹ (x, y) ∈ a × a" for x y by auto
from s_in_bb have s_in_bb_set:
"(x, y) ∈ s ⟹ (x, y) ∈ b × b" for x y by auto
from as_s_r have s_r:
"(x, y) ∈ a × a ⟹ (f x, f y) ∈ s ⟹ (x, y) ∈ r" for x y
unfolding map_prod_def by auto
from bij_f r_in_aa_set s_in_bb_set s_r have
"(x, y) ∈ a × a ⟹ (f x, f y) ∈ s⇧* ⟹ (x, y) ∈ r⇧*" for x y
by (rule preserve_rtranclp_inv[to_set])
thus ?thesis unfolding map_prod_def by clarsimp
qed
end

How do I write a custom induction rule over a parameterized inductive set?

I'm trying to write a custom induction rule for an inductive set. Unfortunately, when I try to apply it with induction rule: my_induct_rule, I get an extra, impossible to prove case. I have the following:
inductive iterate :: "('a ⇒ 'a ⇒ bool) ⇒ 'a ⇒ 'a ⇒ bool" for f where
iter_refl [simp]: "iterate f a a"
| iter_step [elim]: "f a b ⟹ iterate f b c ⟹ iterate f a c"
theorem my_iterate_induct: "iterate f x y ⟹ (⋀a. P a a) ⟹
(⋀a b c. f a b ⟹ iterate f b c ⟹ P b c ⟹ P a c) ⟹ P x y"
by (induction x y rule: iterate.induct) simp_all
lemma iter_step_backwards: "iterate f a b ⟹ f b c ⟹ iterate f a c"
proof (induction a b rule: my_iterate_induct)
...
qed
Obviously the custom induction rule doesn't give me any new power (my real use case is more complicated) but that's kinda the point. my_iterate_induct is exactly the same as the autogenerated iterate.induct rule, as far as I can tell, but inside the proof block I have the following goals:
goal (3 subgoals):
1. iterate ?f a b
2. ⋀a. iterate f a a ⟹ f a c ⟹ iterate f a c
3. ⋀a b ca. ?f a b ⟹ iterate ?f b ca ⟹
(iterate f b ca ⟹ f ca c ⟹ iterate f b c) ⟹ iterate f a ca ⟹
f ca c ⟹ iterate f a c
Goal 1 seems to rise from some failure to unify ?f with the actual argument f, but if I ignore the fact that the f is fixed and try induction f a b rule: my_iterate_induct I just get Failed to apply proof method, as expected. How do I get the nice behaviour that the regular iterate.induct provides?
You need to declare your custom induction rule as ‘consuming’ one premise using the consumes attribute (see the Isabelle/Isar reference manual, §6.5.1):
theorem my_iterate_induct [consumes 1]: "iterate f x y ⟹ (⋀a. P a a) ⟹
(⋀a b c. f a b ⟹ iterate f b c ⟹ P b c ⟹ P a c) ⟹ P x y"
by (induction x y rule: iterate.induct) simp_all

How to define a linear ordering on a type?

I'm trying to define a conjunction function for 4-valued logic (false, true, null, and error). In my case the conjunction is equivavlent to min function on linear order false < error < null < true.
datatype bool4 = JF | JT | BN | BE
instantiation bool4 :: linear_order
begin
fun leq_bool4 :: "bool4 ⇒ bool4 ⇒ bool" where
"leq_bool4 JF b = True"
| "leq_bool4 BE b = (b = BE ∨ b = BN ∨ b = JT)"
| "leq_bool4 BN b = (b = BN ∨ b = JT)"
| "leq_bool4 JT b = (b = JT)"
instance proof
fix x y z :: bool4
show "x ⊑ x"
by (induct x) simp_all
show "x ⊑ y ⟹ y ⊑ z ⟹ x ⊑ z"
by (induct x; induct y) simp_all
show "x ⊑ y ⟹ y ⊑ x ⟹ x = y"
by (induct x; induct y) simp_all
show "x ⊑ y ∨ y ⊑ x"
by (induct x; induct y) simp_all
qed
end
definition and4 :: "bool4 ⇒ bool4 ⇒ bool4" where
"and4 a b ≡ minimum a b"
I guess there must be an easier way to define a linear order in Isabelle HOL. Could you suggest a simplification of the theory?
You can use the "Datatype_Order_Generator" AFP entry.
Then it's as simple as importing "$AFP/Datatype_Order_Generator/Order_Generator" and declaring derive linorder "bool4". Note that the constructors must be declared in the order you want them when defining your datatype.
Details on how to download and use the AFP locally can be found here.

set integrable with functions multiplication

I'm trying to prove this lemma:
lemma set_integral_mult:
fixes f g :: "_ ⇒ _ :: {banach, second_countable_topology}"
assumes "set_integrable M A (λx. f x)" "set_integrable M A (λx. g x)"
shows "set_integrable M A (λx. f x * g x)"
and
lemma set_integral_mult1:
fixes f :: "_ ⇒ _ :: {banach, second_countable_topology}"
assumes "set_integrable M A (λx. f x)"
shows "set_integrable M A (λx. f x * f x)"
but I couldn't. I've seen that it is proved for addition and subtraction:
lemma set_integral_add [simp, intro]:
fixes f g :: "_ ⇒ _ :: {banach, second_countable_topology}"
assumes "set_integrable M A f" "set_integrable M A g"
shows "set_integrable M A (λx. f x + g x)"
and "LINT x:A|M. f x + g x = (LINT x:A|M. f x) + (LINT x:A|M. g x)"
using assms by (simp_all add: scaleR_add_right)
lemma set_integral_diff [simp, intro]:
assumes "set_integrable M A f" "set_integrable M A g"
shows "set_integrable M A (λx. f x - g x)" and "LINT x:A|M. f x - g x =
(LINT x:A|M. f x) - (LINT x:A|M. g x)"
using assms by (simp_all add: scaleR_diff_right)
or even for scalar multiplication but not for two functions multiplication?
The problem is that it is quite simply not true. The function f(x) = 1 / sqrt(x) is integrable on the set (0;1], and the integral has the value 2. Its square f(x)² = 1 / x on the other hand is not integrable on the set (0;1]. The integral diverges.

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