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/-
Copyright (c) 2022 Wrenna Robson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Wrenna Robson
-/
import Mathlib.Topology.MetricSpace.Basic
#align_import topology.metric_space.infsep from "leanprover-community/mathlib"@"5316314b553dcf8c6716541851517c1a9715e22b"
/-!
# Infimum separation
This file defines the extended infimum separation of a set. This is approximately dual to the
diameter of a set, but where the extended diameter of a set is the supremum of the extended distance
between elements of the set, the extended infimum separation is the infimum of the (extended)
distance between *distinct* elements in the set.
We also define the infimum separation as the cast of the extended infimum separation to the reals.
This is the infimum of the distance between distinct elements of the set when in a pseudometric
space.
All lemmas and definitions are in the `Set` namespace to give access to dot notation.
## Main definitions
* `Set.einfsep`: Extended infimum separation of a set.
* `Set.infsep`: Infimum separation of a set (when in a pseudometric space).
!-/
variable {α β : Type*}
namespace Set
section Einfsep
open ENNReal
open Function
/-- The "extended infimum separation" of a set with an edist function. -/
noncomputable def einfsep [EDist α] (s : Set α) : ℝ≥0∞ :=
⨅ (x ∈ s) (y ∈ s) (_ : x ≠ y), edist x y
#align set.einfsep Set.einfsep
section EDist
variable [EDist α] {x y : α} {s t : Set α}
theorem le_einfsep_iff {d} :
d ≤ s.einfsep ↔ ∀ x ∈ s, ∀ y ∈ s, x ≠ y → d ≤ edist x y := by
simp_rw [einfsep, le_iInf_iff]
#align set.le_einfsep_iff Set.le_einfsep_iff
| Mathlib/Topology/MetricSpace/Infsep.lean | 55 | 56 | theorem einfsep_zero : s.einfsep = 0 ↔ ∀ C > 0, ∃ x ∈ s, ∃ y ∈ s, x ≠ y ∧ edist x y < C := by |
simp_rw [einfsep, ← _root_.bot_eq_zero, iInf_eq_bot, iInf_lt_iff, exists_prop]
|
/-
Copyright (c) 2022 Scott Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Scott Morrison, Oleksandr Manzyuk
-/
import Mathlib.CategoryTheory.Bicategory.Basic
import Mathlib.CategoryTheory.Monoidal.Mon_
import Mathlib.CategoryTheory.Limits.Preserves.Shapes.Equalizers
#align_import category_theory.monoidal.Bimod from "leanprover-community/mathlib"@"4698e35ca56a0d4fa53aa5639c3364e0a77f4eba"
/-!
# The category of bimodule objects over a pair of monoid objects.
-/
universe v₁ v₂ u₁ u₂
open CategoryTheory
open CategoryTheory.MonoidalCategory
variable {C : Type u₁} [Category.{v₁} C] [MonoidalCategory.{v₁} C]
section
open CategoryTheory.Limits
variable [HasCoequalizers C]
section
variable [∀ X : C, PreservesColimitsOfSize.{0, 0} (tensorLeft X)]
theorem id_tensor_π_preserves_coequalizer_inv_desc {W X Y Z : C} (f g : X ⟶ Y) (h : Z ⊗ Y ⟶ W)
(wh : (Z ◁ f) ≫ h = (Z ◁ g) ≫ h) :
(Z ◁ coequalizer.π f g) ≫
(PreservesCoequalizer.iso (tensorLeft Z) f g).inv ≫ coequalizer.desc h wh =
h :=
map_π_preserves_coequalizer_inv_desc (tensorLeft Z) f g h wh
#align id_tensor_π_preserves_coequalizer_inv_desc id_tensor_π_preserves_coequalizer_inv_desc
theorem id_tensor_π_preserves_coequalizer_inv_colimMap_desc {X Y Z X' Y' Z' : C} (f g : X ⟶ Y)
(f' g' : X' ⟶ Y') (p : Z ⊗ X ⟶ X') (q : Z ⊗ Y ⟶ Y') (wf : (Z ◁ f) ≫ q = p ≫ f')
(wg : (Z ◁ g) ≫ q = p ≫ g') (h : Y' ⟶ Z') (wh : f' ≫ h = g' ≫ h) :
(Z ◁ coequalizer.π f g) ≫
(PreservesCoequalizer.iso (tensorLeft Z) f g).inv ≫
colimMap (parallelPairHom (Z ◁ f) (Z ◁ g) f' g' p q wf wg) ≫ coequalizer.desc h wh =
q ≫ h :=
map_π_preserves_coequalizer_inv_colimMap_desc (tensorLeft Z) f g f' g' p q wf wg h wh
#align id_tensor_π_preserves_coequalizer_inv_colim_map_desc id_tensor_π_preserves_coequalizer_inv_colimMap_desc
end
section
variable [∀ X : C, PreservesColimitsOfSize.{0, 0} (tensorRight X)]
theorem π_tensor_id_preserves_coequalizer_inv_desc {W X Y Z : C} (f g : X ⟶ Y) (h : Y ⊗ Z ⟶ W)
(wh : (f ▷ Z) ≫ h = (g ▷ Z) ≫ h) :
(coequalizer.π f g ▷ Z) ≫
(PreservesCoequalizer.iso (tensorRight Z) f g).inv ≫ coequalizer.desc h wh =
h :=
map_π_preserves_coequalizer_inv_desc (tensorRight Z) f g h wh
#align π_tensor_id_preserves_coequalizer_inv_desc π_tensor_id_preserves_coequalizer_inv_desc
theorem π_tensor_id_preserves_coequalizer_inv_colimMap_desc {X Y Z X' Y' Z' : C} (f g : X ⟶ Y)
(f' g' : X' ⟶ Y') (p : X ⊗ Z ⟶ X') (q : Y ⊗ Z ⟶ Y') (wf : (f ▷ Z) ≫ q = p ≫ f')
(wg : (g ▷ Z) ≫ q = p ≫ g') (h : Y' ⟶ Z') (wh : f' ≫ h = g' ≫ h) :
(coequalizer.π f g ▷ Z) ≫
(PreservesCoequalizer.iso (tensorRight Z) f g).inv ≫
colimMap (parallelPairHom (f ▷ Z) (g ▷ Z) f' g' p q wf wg) ≫ coequalizer.desc h wh =
q ≫ h :=
map_π_preserves_coequalizer_inv_colimMap_desc (tensorRight Z) f g f' g' p q wf wg h wh
#align π_tensor_id_preserves_coequalizer_inv_colim_map_desc π_tensor_id_preserves_coequalizer_inv_colimMap_desc
end
end
/-- A bimodule object for a pair of monoid objects, all internal to some monoidal category. -/
structure Bimod (A B : Mon_ C) where
X : C
actLeft : A.X ⊗ X ⟶ X
one_actLeft : (A.one ▷ X) ≫ actLeft = (λ_ X).hom := by aesop_cat
left_assoc :
(A.mul ▷ X) ≫ actLeft = (α_ A.X A.X X).hom ≫ (A.X ◁ actLeft) ≫ actLeft := by aesop_cat
actRight : X ⊗ B.X ⟶ X
actRight_one : (X ◁ B.one) ≫ actRight = (ρ_ X).hom := by aesop_cat
right_assoc :
(X ◁ B.mul) ≫ actRight = (α_ X B.X B.X).inv ≫ (actRight ▷ B.X) ≫ actRight := by
aesop_cat
middle_assoc :
(actLeft ▷ B.X) ≫ actRight = (α_ A.X X B.X).hom ≫ (A.X ◁ actRight) ≫ actLeft := by
aesop_cat
set_option linter.uppercaseLean3 false in
#align Bimod Bimod
attribute [reassoc (attr := simp)] Bimod.one_actLeft Bimod.actRight_one Bimod.left_assoc
Bimod.right_assoc Bimod.middle_assoc
namespace Bimod
variable {A B : Mon_ C} (M : Bimod A B)
/-- A morphism of bimodule objects. -/
@[ext]
structure Hom (M N : Bimod A B) where
hom : M.X ⟶ N.X
left_act_hom : M.actLeft ≫ hom = (A.X ◁ hom) ≫ N.actLeft := by aesop_cat
right_act_hom : M.actRight ≫ hom = (hom ▷ B.X) ≫ N.actRight := by aesop_cat
set_option linter.uppercaseLean3 false in
#align Bimod.hom Bimod.Hom
attribute [reassoc (attr := simp)] Hom.left_act_hom Hom.right_act_hom
/-- The identity morphism on a bimodule object. -/
@[simps]
def id' (M : Bimod A B) : Hom M M where hom := 𝟙 M.X
set_option linter.uppercaseLean3 false in
#align Bimod.id' Bimod.id'
instance homInhabited (M : Bimod A B) : Inhabited (Hom M M) :=
⟨id' M⟩
set_option linter.uppercaseLean3 false in
#align Bimod.hom_inhabited Bimod.homInhabited
/-- Composition of bimodule object morphisms. -/
@[simps]
def comp {M N O : Bimod A B} (f : Hom M N) (g : Hom N O) : Hom M O where hom := f.hom ≫ g.hom
set_option linter.uppercaseLean3 false in
#align Bimod.comp Bimod.comp
instance : Category (Bimod A B) where
Hom M N := Hom M N
id := id'
comp f g := comp f g
-- Porting note: added because `Hom.ext` is not triggered automatically
@[ext]
lemma hom_ext {M N : Bimod A B} (f g : M ⟶ N) (h : f.hom = g.hom) : f = g :=
Hom.ext _ _ h
@[simp]
theorem id_hom' (M : Bimod A B) : (𝟙 M : Hom M M).hom = 𝟙 M.X :=
rfl
set_option linter.uppercaseLean3 false in
#align Bimod.id_hom' Bimod.id_hom'
@[simp]
theorem comp_hom' {M N K : Bimod A B} (f : M ⟶ N) (g : N ⟶ K) :
(f ≫ g : Hom M K).hom = f.hom ≫ g.hom :=
rfl
set_option linter.uppercaseLean3 false in
#align Bimod.comp_hom' Bimod.comp_hom'
/-- Construct an isomorphism of bimodules by giving an isomorphism between the underlying objects
and checking compatibility with left and right actions only in the forward direction.
-/
@[simps]
def isoOfIso {X Y : Mon_ C} {P Q : Bimod X Y} (f : P.X ≅ Q.X)
(f_left_act_hom : P.actLeft ≫ f.hom = (X.X ◁ f.hom) ≫ Q.actLeft)
(f_right_act_hom : P.actRight ≫ f.hom = (f.hom ▷ Y.X) ≫ Q.actRight) : P ≅ Q where
hom :=
{ hom := f.hom }
inv :=
{ hom := f.inv
left_act_hom := by
rw [← cancel_mono f.hom, Category.assoc, Category.assoc, Iso.inv_hom_id, Category.comp_id,
f_left_act_hom, ← Category.assoc, ← MonoidalCategory.whiskerLeft_comp, Iso.inv_hom_id,
MonoidalCategory.whiskerLeft_id, Category.id_comp]
right_act_hom := by
rw [← cancel_mono f.hom, Category.assoc, Category.assoc, Iso.inv_hom_id, Category.comp_id,
f_right_act_hom, ← Category.assoc, ← comp_whiskerRight, Iso.inv_hom_id,
MonoidalCategory.id_whiskerRight, Category.id_comp] }
hom_inv_id := by ext; dsimp; rw [Iso.hom_inv_id]
inv_hom_id := by ext; dsimp; rw [Iso.inv_hom_id]
set_option linter.uppercaseLean3 false in
#align Bimod.iso_of_iso Bimod.isoOfIso
variable (A)
/-- A monoid object as a bimodule over itself. -/
@[simps]
def regular : Bimod A A where
X := A.X
actLeft := A.mul
actRight := A.mul
set_option linter.uppercaseLean3 false in
#align Bimod.regular Bimod.regular
instance : Inhabited (Bimod A A) :=
⟨regular A⟩
/-- The forgetful functor from bimodule objects to the ambient category. -/
def forget : Bimod A B ⥤ C where
obj A := A.X
map f := f.hom
set_option linter.uppercaseLean3 false in
#align Bimod.forget Bimod.forget
open CategoryTheory.Limits
variable [HasCoequalizers C]
namespace TensorBimod
variable {R S T : Mon_ C} (P : Bimod R S) (Q : Bimod S T)
/-- The underlying object of the tensor product of two bimodules. -/
noncomputable def X : C :=
coequalizer (P.actRight ▷ Q.X) ((α_ _ _ _).hom ≫ (P.X ◁ Q.actLeft))
set_option linter.uppercaseLean3 false in
#align Bimod.tensor_Bimod.X Bimod.TensorBimod.X
section
variable [∀ X : C, PreservesColimitsOfSize.{0, 0} (tensorLeft X)]
/-- Left action for the tensor product of two bimodules. -/
noncomputable def actLeft : R.X ⊗ X P Q ⟶ X P Q :=
(PreservesCoequalizer.iso (tensorLeft R.X) _ _).inv ≫
colimMap
(parallelPairHom _ _ _ _
((α_ _ _ _).inv ≫ ((α_ _ _ _).inv ▷ _) ≫ (P.actLeft ▷ S.X ▷ Q.X))
((α_ _ _ _).inv ≫ (P.actLeft ▷ Q.X))
(by
dsimp
simp only [Category.assoc]
slice_lhs 1 2 => rw [associator_inv_naturality_middle]
slice_rhs 3 4 => rw [← comp_whiskerRight, middle_assoc, comp_whiskerRight]
coherence)
(by
dsimp
slice_lhs 1 1 => rw [MonoidalCategory.whiskerLeft_comp]
slice_lhs 2 3 => rw [associator_inv_naturality_right]
slice_lhs 3 4 => rw [whisker_exchange]
coherence))
set_option linter.uppercaseLean3 false in
#align Bimod.tensor_Bimod.act_left Bimod.TensorBimod.actLeft
theorem whiskerLeft_π_actLeft :
(R.X ◁ coequalizer.π _ _) ≫ actLeft P Q =
(α_ _ _ _).inv ≫ (P.actLeft ▷ Q.X) ≫ coequalizer.π _ _ := by
erw [map_π_preserves_coequalizer_inv_colimMap (tensorLeft _)]
simp only [Category.assoc]
set_option linter.uppercaseLean3 false in
#align Bimod.tensor_Bimod.id_tensor_π_act_left Bimod.TensorBimod.whiskerLeft_π_actLeft
theorem one_act_left' : (R.one ▷ _) ≫ actLeft P Q = (λ_ _).hom := by
refine (cancel_epi ((tensorLeft _).map (coequalizer.π _ _))).1 ?_
dsimp [X]
-- Porting note: had to replace `rw` by `erw`
slice_lhs 1 2 => erw [whisker_exchange]
slice_lhs 2 3 => rw [whiskerLeft_π_actLeft]
slice_lhs 1 2 => rw [associator_inv_naturality_left]
slice_lhs 2 3 => rw [← comp_whiskerRight, one_actLeft]
slice_rhs 1 2 => rw [leftUnitor_naturality]
coherence
set_option linter.uppercaseLean3 false in
#align Bimod.tensor_Bimod.one_act_left' Bimod.TensorBimod.one_act_left'
theorem left_assoc' :
(R.mul ▷ _) ≫ actLeft P Q = (α_ R.X R.X _).hom ≫ (R.X ◁ actLeft P Q) ≫ actLeft P Q := by
refine (cancel_epi ((tensorLeft _).map (coequalizer.π _ _))).1 ?_
dsimp [X]
slice_lhs 1 2 => rw [whisker_exchange]
slice_lhs 2 3 => rw [whiskerLeft_π_actLeft]
slice_lhs 1 2 => rw [associator_inv_naturality_left]
slice_lhs 2 3 => rw [← comp_whiskerRight, left_assoc, comp_whiskerRight, comp_whiskerRight]
slice_rhs 1 2 => rw [associator_naturality_right]
slice_rhs 2 3 =>
rw [← MonoidalCategory.whiskerLeft_comp, whiskerLeft_π_actLeft,
MonoidalCategory.whiskerLeft_comp, MonoidalCategory.whiskerLeft_comp]
slice_rhs 4 5 => rw [whiskerLeft_π_actLeft]
slice_rhs 3 4 => rw [associator_inv_naturality_middle]
coherence
set_option linter.uppercaseLean3 false in
#align Bimod.tensor_Bimod.left_assoc' Bimod.TensorBimod.left_assoc'
end
section
variable [∀ X : C, PreservesColimitsOfSize.{0, 0} (tensorRight X)]
/-- Right action for the tensor product of two bimodules. -/
noncomputable def actRight : X P Q ⊗ T.X ⟶ X P Q :=
(PreservesCoequalizer.iso (tensorRight T.X) _ _).inv ≫
colimMap
(parallelPairHom _ _ _ _
((α_ _ _ _).hom ≫ (α_ _ _ _).hom ≫ (P.X ◁ S.X ◁ Q.actRight) ≫ (α_ _ _ _).inv)
((α_ _ _ _).hom ≫ (P.X ◁ Q.actRight))
(by
dsimp
slice_lhs 1 2 => rw [associator_naturality_left]
slice_lhs 2 3 => rw [← whisker_exchange]
simp)
(by
dsimp
simp only [comp_whiskerRight, whisker_assoc, Category.assoc, Iso.inv_hom_id_assoc]
slice_lhs 3 4 =>
rw [← MonoidalCategory.whiskerLeft_comp, middle_assoc,
MonoidalCategory.whiskerLeft_comp]
simp))
set_option linter.uppercaseLean3 false in
#align Bimod.tensor_Bimod.act_right Bimod.TensorBimod.actRight
theorem π_tensor_id_actRight :
(coequalizer.π _ _ ▷ T.X) ≫ actRight P Q =
(α_ _ _ _).hom ≫ (P.X ◁ Q.actRight) ≫ coequalizer.π _ _ := by
erw [map_π_preserves_coequalizer_inv_colimMap (tensorRight _)]
simp only [Category.assoc]
set_option linter.uppercaseLean3 false in
#align Bimod.tensor_Bimod.π_tensor_id_act_right Bimod.TensorBimod.π_tensor_id_actRight
theorem actRight_one' : (_ ◁ T.one) ≫ actRight P Q = (ρ_ _).hom := by
refine (cancel_epi ((tensorRight _).map (coequalizer.π _ _))).1 ?_
dsimp [X]
-- Porting note: had to replace `rw` by `erw`
slice_lhs 1 2 =>erw [← whisker_exchange]
slice_lhs 2 3 => rw [π_tensor_id_actRight]
slice_lhs 1 2 => rw [associator_naturality_right]
slice_lhs 2 3 => rw [← MonoidalCategory.whiskerLeft_comp, actRight_one]
simp
set_option linter.uppercaseLean3 false in
#align Bimod.tensor_Bimod.act_right_one' Bimod.TensorBimod.actRight_one'
theorem right_assoc' :
(_ ◁ T.mul) ≫ actRight P Q =
(α_ _ T.X T.X).inv ≫ (actRight P Q ▷ T.X) ≫ actRight P Q := by
refine (cancel_epi ((tensorRight _).map (coequalizer.π _ _))).1 ?_
dsimp [X]
-- Porting note: had to replace some `rw` by `erw`
slice_lhs 1 2 => rw [← whisker_exchange]
slice_lhs 2 3 => rw [π_tensor_id_actRight]
slice_lhs 1 2 => rw [associator_naturality_right]
slice_lhs 2 3 => rw [← MonoidalCategory.whiskerLeft_comp, right_assoc,
MonoidalCategory.whiskerLeft_comp, MonoidalCategory.whiskerLeft_comp]
slice_rhs 1 2 => rw [associator_inv_naturality_left]
slice_rhs 2 3 => rw [← comp_whiskerRight, π_tensor_id_actRight, comp_whiskerRight,
comp_whiskerRight]
slice_rhs 4 5 => rw [π_tensor_id_actRight]
simp
set_option linter.uppercaseLean3 false in
#align Bimod.tensor_Bimod.right_assoc' Bimod.TensorBimod.right_assoc'
end
section
variable [∀ X : C, PreservesColimitsOfSize.{0, 0} (tensorLeft X)]
variable [∀ X : C, PreservesColimitsOfSize.{0, 0} (tensorRight X)]
theorem middle_assoc' :
(actLeft P Q ▷ T.X) ≫ actRight P Q =
(α_ R.X _ T.X).hom ≫ (R.X ◁ actRight P Q) ≫ actLeft P Q := by
refine (cancel_epi ((tensorLeft _ ⋙ tensorRight _).map (coequalizer.π _ _))).1 ?_
dsimp [X]
slice_lhs 1 2 => rw [← comp_whiskerRight, whiskerLeft_π_actLeft, comp_whiskerRight,
comp_whiskerRight]
slice_lhs 3 4 => rw [π_tensor_id_actRight]
slice_lhs 2 3 => rw [associator_naturality_left]
-- Porting note: had to replace `rw` by `erw`
slice_rhs 1 2 => rw [associator_naturality_middle]
slice_rhs 2 3 => rw [← MonoidalCategory.whiskerLeft_comp, π_tensor_id_actRight,
MonoidalCategory.whiskerLeft_comp, MonoidalCategory.whiskerLeft_comp]
slice_rhs 4 5 => rw [whiskerLeft_π_actLeft]
slice_rhs 3 4 => rw [associator_inv_naturality_right]
slice_rhs 4 5 => rw [whisker_exchange]
simp
set_option linter.uppercaseLean3 false in
#align Bimod.tensor_Bimod.middle_assoc' Bimod.TensorBimod.middle_assoc'
end
end TensorBimod
section
variable [∀ X : C, PreservesColimitsOfSize.{0, 0} (tensorLeft X)]
variable [∀ X : C, PreservesColimitsOfSize.{0, 0} (tensorRight X)]
/-- Tensor product of two bimodule objects as a bimodule object. -/
@[simps]
noncomputable def tensorBimod {X Y Z : Mon_ C} (M : Bimod X Y) (N : Bimod Y Z) : Bimod X Z where
X := TensorBimod.X M N
actLeft := TensorBimod.actLeft M N
actRight := TensorBimod.actRight M N
one_actLeft := TensorBimod.one_act_left' M N
actRight_one := TensorBimod.actRight_one' M N
left_assoc := TensorBimod.left_assoc' M N
right_assoc := TensorBimod.right_assoc' M N
middle_assoc := TensorBimod.middle_assoc' M N
set_option linter.uppercaseLean3 false in
#align Bimod.tensor_Bimod Bimod.tensorBimod
/-- Left whiskering for morphisms of bimodule objects. -/
@[simps]
noncomputable def whiskerLeft {X Y Z : Mon_ C} (M : Bimod X Y) {N₁ N₂ : Bimod Y Z} (f : N₁ ⟶ N₂) :
M.tensorBimod N₁ ⟶ M.tensorBimod N₂ where
hom :=
colimMap
(parallelPairHom _ _ _ _ (_ ◁ f.hom) (_ ◁ f.hom)
(by rw [whisker_exchange])
(by
simp only [Category.assoc, tensor_whiskerLeft, Iso.inv_hom_id_assoc,
Iso.cancel_iso_hom_left]
slice_lhs 1 2 => rw [← MonoidalCategory.whiskerLeft_comp, Hom.left_act_hom]
simp))
left_act_hom := by
refine (cancel_epi ((tensorLeft _).map (coequalizer.π _ _))).1 ?_
dsimp
slice_lhs 1 2 => rw [TensorBimod.whiskerLeft_π_actLeft]
slice_lhs 3 4 => rw [ι_colimMap, parallelPairHom_app_one]
slice_rhs 1 2 => rw [← MonoidalCategory.whiskerLeft_comp, ι_colimMap, parallelPairHom_app_one,
MonoidalCategory.whiskerLeft_comp]
slice_rhs 2 3 => rw [TensorBimod.whiskerLeft_π_actLeft]
slice_rhs 1 2 => rw [associator_inv_naturality_right]
slice_rhs 2 3 => rw [whisker_exchange]
simp
right_act_hom := by
refine (cancel_epi ((tensorRight _).map (coequalizer.π _ _))).1 ?_
dsimp
slice_lhs 1 2 => rw [TensorBimod.π_tensor_id_actRight]
slice_lhs 3 4 => rw [ι_colimMap, parallelPairHom_app_one]
slice_lhs 2 3 => rw [← MonoidalCategory.whiskerLeft_comp, Hom.right_act_hom]
slice_rhs 1 2 =>
rw [← comp_whiskerRight, ι_colimMap, parallelPairHom_app_one, comp_whiskerRight]
slice_rhs 2 3 => rw [TensorBimod.π_tensor_id_actRight]
simp
/-- Right whiskering for morphisms of bimodule objects. -/
@[simps]
noncomputable def whiskerRight {X Y Z : Mon_ C} {M₁ M₂ : Bimod X Y} (f : M₁ ⟶ M₂) (N : Bimod Y Z) :
M₁.tensorBimod N ⟶ M₂.tensorBimod N where
hom :=
colimMap
(parallelPairHom _ _ _ _ (f.hom ▷ _ ▷ _) (f.hom ▷ _)
(by rw [← comp_whiskerRight, Hom.right_act_hom, comp_whiskerRight])
(by
slice_lhs 2 3 => rw [whisker_exchange]
simp))
left_act_hom := by
refine (cancel_epi ((tensorLeft _).map (coequalizer.π _ _))).1 ?_
dsimp
slice_lhs 1 2 => rw [TensorBimod.whiskerLeft_π_actLeft]
slice_lhs 3 4 => rw [ι_colimMap, parallelPairHom_app_one]
slice_lhs 2 3 => rw [← comp_whiskerRight, Hom.left_act_hom]
slice_rhs 1 2 => rw [← MonoidalCategory.whiskerLeft_comp, ι_colimMap, parallelPairHom_app_one,
MonoidalCategory.whiskerLeft_comp]
slice_rhs 2 3 => rw [TensorBimod.whiskerLeft_π_actLeft]
slice_rhs 1 2 => rw [associator_inv_naturality_middle]
simp
right_act_hom := by
refine (cancel_epi ((tensorRight _).map (coequalizer.π _ _))).1 ?_
dsimp
slice_lhs 1 2 => rw [TensorBimod.π_tensor_id_actRight]
slice_lhs 3 4 => rw [ι_colimMap, parallelPairHom_app_one]
slice_lhs 2 3 => rw [whisker_exchange]
slice_rhs 1 2 => rw [← comp_whiskerRight, ι_colimMap, parallelPairHom_app_one,
comp_whiskerRight]
slice_rhs 2 3 => rw [TensorBimod.π_tensor_id_actRight]
simp
end
namespace AssociatorBimod
variable [∀ X : C, PreservesColimitsOfSize.{0, 0} (tensorLeft X)]
variable [∀ X : C, PreservesColimitsOfSize.{0, 0} (tensorRight X)]
variable {R S T U : Mon_ C} (P : Bimod R S) (Q : Bimod S T) (L : Bimod T U)
/-- An auxiliary morphism for the definition of the underlying morphism of the forward component of
the associator isomorphism. -/
noncomputable def homAux : (P.tensorBimod Q).X ⊗ L.X ⟶ (P.tensorBimod (Q.tensorBimod L)).X :=
(PreservesCoequalizer.iso (tensorRight L.X) _ _).inv ≫
coequalizer.desc ((α_ _ _ _).hom ≫ (P.X ◁ coequalizer.π _ _) ≫ coequalizer.π _ _)
(by
dsimp; dsimp [TensorBimod.X]
slice_lhs 1 2 => rw [associator_naturality_left]
slice_lhs 2 3 => rw [← whisker_exchange]
slice_lhs 3 4 => rw [coequalizer.condition]
slice_lhs 2 3 => rw [associator_naturality_right]
slice_lhs 3 4 =>
rw [← MonoidalCategory.whiskerLeft_comp,
TensorBimod.whiskerLeft_π_actLeft, MonoidalCategory.whiskerLeft_comp]
simp)
set_option linter.uppercaseLean3 false in
#align Bimod.associator_Bimod.hom_aux Bimod.AssociatorBimod.homAux
/-- The underlying morphism of the forward component of the associator isomorphism. -/
noncomputable def hom :
((P.tensorBimod Q).tensorBimod L).X ⟶ (P.tensorBimod (Q.tensorBimod L)).X :=
coequalizer.desc (homAux P Q L)
(by
dsimp [homAux]
refine (cancel_epi ((tensorRight _ ⋙ tensorRight _).map (coequalizer.π _ _))).1 ?_
dsimp [TensorBimod.X]
slice_lhs 1 2 => rw [← comp_whiskerRight, TensorBimod.π_tensor_id_actRight,
comp_whiskerRight, comp_whiskerRight]
slice_lhs 3 5 => rw [π_tensor_id_preserves_coequalizer_inv_desc]
slice_lhs 2 3 => rw [associator_naturality_middle]
slice_lhs 3 4 =>
rw [← MonoidalCategory.whiskerLeft_comp, coequalizer.condition,
MonoidalCategory.whiskerLeft_comp, MonoidalCategory.whiskerLeft_comp]
slice_rhs 1 2 => rw [associator_naturality_left]
slice_rhs 2 3 => rw [← whisker_exchange]
slice_rhs 3 5 => rw [π_tensor_id_preserves_coequalizer_inv_desc]
simp)
set_option linter.uppercaseLean3 false in
#align Bimod.associator_Bimod.hom Bimod.AssociatorBimod.hom
theorem hom_left_act_hom' :
((P.tensorBimod Q).tensorBimod L).actLeft ≫ hom P Q L =
(R.X ◁ hom P Q L) ≫ (P.tensorBimod (Q.tensorBimod L)).actLeft := by
dsimp; dsimp [hom, homAux]
refine (cancel_epi ((tensorLeft _).map (coequalizer.π _ _))).1 ?_
rw [tensorLeft_map]
slice_lhs 1 2 => rw [TensorBimod.whiskerLeft_π_actLeft]
slice_lhs 3 4 => rw [coequalizer.π_desc]
slice_rhs 1 2 => rw [← MonoidalCategory.whiskerLeft_comp, coequalizer.π_desc,
MonoidalCategory.whiskerLeft_comp]
refine (cancel_epi ((tensorRight _ ⋙ tensorLeft _).map (coequalizer.π _ _))).1 ?_
dsimp; dsimp [TensorBimod.X]
slice_lhs 1 2 => rw [associator_inv_naturality_middle]
slice_lhs 2 3 =>
rw [← comp_whiskerRight, TensorBimod.whiskerLeft_π_actLeft,
comp_whiskerRight, comp_whiskerRight]
slice_lhs 4 6 => rw [π_tensor_id_preserves_coequalizer_inv_desc]
slice_lhs 3 4 => rw [associator_naturality_left]
slice_rhs 1 3 =>
rw [← MonoidalCategory.whiskerLeft_comp, ← MonoidalCategory.whiskerLeft_comp,
π_tensor_id_preserves_coequalizer_inv_desc, MonoidalCategory.whiskerLeft_comp,
MonoidalCategory.whiskerLeft_comp]
slice_rhs 3 4 => erw [TensorBimod.whiskerLeft_π_actLeft P (Q.tensorBimod L)]
slice_rhs 2 3 => erw [associator_inv_naturality_right]
slice_rhs 3 4 => erw [whisker_exchange]
coherence
set_option linter.uppercaseLean3 false in
#align Bimod.associator_Bimod.hom_left_act_hom' Bimod.AssociatorBimod.hom_left_act_hom'
theorem hom_right_act_hom' :
((P.tensorBimod Q).tensorBimod L).actRight ≫ hom P Q L =
(hom P Q L ▷ U.X) ≫ (P.tensorBimod (Q.tensorBimod L)).actRight := by
dsimp; dsimp [hom, homAux]
refine (cancel_epi ((tensorRight _).map (coequalizer.π _ _))).1 ?_
rw [tensorRight_map]
slice_lhs 1 2 => rw [TensorBimod.π_tensor_id_actRight]
slice_lhs 3 4 => rw [coequalizer.π_desc]
slice_rhs 1 2 => rw [← comp_whiskerRight, coequalizer.π_desc, comp_whiskerRight]
refine (cancel_epi ((tensorRight _ ⋙ tensorRight _).map (coequalizer.π _ _))).1 ?_
dsimp; dsimp [TensorBimod.X]
slice_lhs 1 2 => rw [associator_naturality_left]
slice_lhs 2 3 => rw [← whisker_exchange]
slice_lhs 3 5 => rw [π_tensor_id_preserves_coequalizer_inv_desc]
slice_lhs 2 3 => rw [associator_naturality_right]
slice_rhs 1 3 =>
rw [← comp_whiskerRight, ← comp_whiskerRight, π_tensor_id_preserves_coequalizer_inv_desc,
comp_whiskerRight, comp_whiskerRight]
slice_rhs 3 4 => erw [TensorBimod.π_tensor_id_actRight P (Q.tensorBimod L)]
slice_rhs 2 3 => erw [associator_naturality_middle]
dsimp
slice_rhs 3 4 =>
rw [← MonoidalCategory.whiskerLeft_comp, TensorBimod.π_tensor_id_actRight,
MonoidalCategory.whiskerLeft_comp, MonoidalCategory.whiskerLeft_comp]
coherence
set_option linter.uppercaseLean3 false in
#align Bimod.associator_Bimod.hom_right_act_hom' Bimod.AssociatorBimod.hom_right_act_hom'
/-- An auxiliary morphism for the definition of the underlying morphism of the inverse component of
the associator isomorphism. -/
noncomputable def invAux : P.X ⊗ (Q.tensorBimod L).X ⟶ ((P.tensorBimod Q).tensorBimod L).X :=
(PreservesCoequalizer.iso (tensorLeft P.X) _ _).inv ≫
coequalizer.desc ((α_ _ _ _).inv ≫ (coequalizer.π _ _ ▷ L.X) ≫ coequalizer.π _ _)
(by
dsimp; dsimp [TensorBimod.X]
slice_lhs 1 2 => rw [associator_inv_naturality_middle]
rw [← Iso.inv_hom_id_assoc (α_ _ _ _) (P.X ◁ Q.actRight), comp_whiskerRight]
slice_lhs 3 4 =>
rw [← comp_whiskerRight, Category.assoc, ← TensorBimod.π_tensor_id_actRight,
comp_whiskerRight]
slice_lhs 4 5 => rw [coequalizer.condition]
slice_lhs 3 4 => rw [associator_naturality_left]
slice_rhs 1 2 => rw [MonoidalCategory.whiskerLeft_comp]
slice_rhs 2 3 => rw [associator_inv_naturality_right]
slice_rhs 3 4 => rw [whisker_exchange]
coherence)
set_option linter.uppercaseLean3 false in
#align Bimod.associator_Bimod.inv_aux Bimod.AssociatorBimod.invAux
/-- The underlying morphism of the inverse component of the associator isomorphism. -/
noncomputable def inv :
(P.tensorBimod (Q.tensorBimod L)).X ⟶ ((P.tensorBimod Q).tensorBimod L).X :=
coequalizer.desc (invAux P Q L)
(by
dsimp [invAux]
refine (cancel_epi ((tensorLeft _).map (coequalizer.π _ _))).1 ?_
dsimp [TensorBimod.X]
slice_lhs 1 2 => rw [whisker_exchange]
slice_lhs 2 4 => rw [id_tensor_π_preserves_coequalizer_inv_desc]
slice_lhs 1 2 => rw [associator_inv_naturality_left]
slice_lhs 2 3 =>
rw [← comp_whiskerRight, coequalizer.condition, comp_whiskerRight, comp_whiskerRight]
slice_rhs 1 2 => rw [associator_naturality_right]
slice_rhs 2 3 =>
rw [← MonoidalCategory.whiskerLeft_comp, TensorBimod.whiskerLeft_π_actLeft,
MonoidalCategory.whiskerLeft_comp, MonoidalCategory.whiskerLeft_comp]
slice_rhs 4 6 => rw [id_tensor_π_preserves_coequalizer_inv_desc]
slice_rhs 3 4 => rw [associator_inv_naturality_middle]
coherence)
set_option linter.uppercaseLean3 false in
#align Bimod.associator_Bimod.inv Bimod.AssociatorBimod.inv
theorem hom_inv_id : hom P Q L ≫ inv P Q L = 𝟙 _ := by
dsimp [hom, homAux, inv, invAux]
apply coequalizer.hom_ext
slice_lhs 1 2 => rw [coequalizer.π_desc]
refine (cancel_epi ((tensorRight _).map (coequalizer.π _ _))).1 ?_
rw [tensorRight_map]
slice_lhs 1 3 => rw [π_tensor_id_preserves_coequalizer_inv_desc]
slice_lhs 3 4 => rw [coequalizer.π_desc]
slice_lhs 2 4 => rw [id_tensor_π_preserves_coequalizer_inv_desc]
slice_lhs 1 3 => rw [Iso.hom_inv_id_assoc]
dsimp only [TensorBimod.X]
slice_rhs 2 3 => rw [Category.comp_id]
rfl
set_option linter.uppercaseLean3 false in
#align Bimod.associator_Bimod.hom_inv_id Bimod.AssociatorBimod.hom_inv_id
theorem inv_hom_id : inv P Q L ≫ hom P Q L = 𝟙 _ := by
dsimp [hom, homAux, inv, invAux]
apply coequalizer.hom_ext
slice_lhs 1 2 => rw [coequalizer.π_desc]
refine (cancel_epi ((tensorLeft _).map (coequalizer.π _ _))).1 ?_
rw [tensorLeft_map]
slice_lhs 1 3 => rw [id_tensor_π_preserves_coequalizer_inv_desc]
slice_lhs 3 4 => rw [coequalizer.π_desc]
slice_lhs 2 4 => rw [π_tensor_id_preserves_coequalizer_inv_desc]
slice_lhs 1 3 => rw [Iso.inv_hom_id_assoc]
dsimp only [TensorBimod.X]
slice_rhs 2 3 => rw [Category.comp_id]
rfl
set_option linter.uppercaseLean3 false in
#align Bimod.associator_Bimod.inv_hom_id Bimod.AssociatorBimod.inv_hom_id
end AssociatorBimod
namespace LeftUnitorBimod
variable {R S : Mon_ C} (P : Bimod R S)
/-- The underlying morphism of the forward component of the left unitor isomorphism. -/
noncomputable def hom : TensorBimod.X (regular R) P ⟶ P.X :=
coequalizer.desc P.actLeft (by dsimp; rw [Category.assoc, left_assoc])
set_option linter.uppercaseLean3 false in
#align Bimod.left_unitor_Bimod.hom Bimod.LeftUnitorBimod.hom
/-- The underlying morphism of the inverse component of the left unitor isomorphism. -/
noncomputable def inv : P.X ⟶ TensorBimod.X (regular R) P :=
(λ_ P.X).inv ≫ (R.one ▷ _) ≫ coequalizer.π _ _
set_option linter.uppercaseLean3 false in
#align Bimod.left_unitor_Bimod.inv Bimod.LeftUnitorBimod.inv
theorem hom_inv_id : hom P ≫ inv P = 𝟙 _ := by
dsimp only [hom, inv, TensorBimod.X]
ext; dsimp
slice_lhs 1 2 => rw [coequalizer.π_desc]
slice_lhs 1 2 => rw [leftUnitor_inv_naturality]
slice_lhs 2 3 => rw [whisker_exchange]
slice_lhs 3 3 => rw [← Iso.inv_hom_id_assoc (α_ R.X R.X P.X) (R.X ◁ P.actLeft)]
slice_lhs 4 6 => rw [← Category.assoc, ← coequalizer.condition]
slice_lhs 2 3 => rw [associator_inv_naturality_left]
slice_lhs 3 4 => rw [← comp_whiskerRight, Mon_.one_mul]
slice_rhs 1 2 => rw [Category.comp_id]
coherence
set_option linter.uppercaseLean3 false in
#align Bimod.left_unitor_Bimod.hom_inv_id Bimod.LeftUnitorBimod.hom_inv_id
| Mathlib/CategoryTheory/Monoidal/Bimod.lean | 680 | 683 | theorem inv_hom_id : inv P ≫ hom P = 𝟙 _ := by |
dsimp [hom, inv]
slice_lhs 3 4 => rw [coequalizer.π_desc]
rw [one_actLeft, Iso.inv_hom_id]
|
/-
Copyright (c) 2018 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Johannes Hölzl
-/
import Mathlib.MeasureTheory.Integral.Lebesgue
/-!
# Measure with a given density with respect to another measure
For a measure `μ` on `α` and a function `f : α → ℝ≥0∞`, we define a new measure `μ.withDensity f`.
On a measurable set `s`, that measure has value `∫⁻ a in s, f a ∂μ`.
An important result about `withDensity` is the Radon-Nikodym theorem. It states that, given measures
`μ, ν`, if `HaveLebesgueDecomposition μ ν` then `μ` is absolutely continuous with respect to
`ν` if and only if there exists a measurable function `f : α → ℝ≥0∞` such that
`μ = ν.withDensity f`.
See `MeasureTheory.Measure.absolutelyContinuous_iff_withDensity_rnDeriv_eq`.
-/
open Set hiding restrict restrict_apply
open Filter ENNReal NNReal MeasureTheory.Measure
namespace MeasureTheory
variable {α : Type*} {m0 : MeasurableSpace α} {μ : Measure α}
/-- Given a measure `μ : Measure α` and a function `f : α → ℝ≥0∞`, `μ.withDensity f` is the
measure such that for a measurable set `s` we have `μ.withDensity f s = ∫⁻ a in s, f a ∂μ`. -/
noncomputable
def Measure.withDensity {m : MeasurableSpace α} (μ : Measure α) (f : α → ℝ≥0∞) : Measure α :=
Measure.ofMeasurable (fun s _ => ∫⁻ a in s, f a ∂μ) (by simp) fun s hs hd =>
lintegral_iUnion hs hd _
#align measure_theory.measure.with_density MeasureTheory.Measure.withDensity
@[simp]
theorem withDensity_apply (f : α → ℝ≥0∞) {s : Set α} (hs : MeasurableSet s) :
μ.withDensity f s = ∫⁻ a in s, f a ∂μ :=
Measure.ofMeasurable_apply s hs
#align measure_theory.with_density_apply MeasureTheory.withDensity_apply
theorem withDensity_apply_le (f : α → ℝ≥0∞) (s : Set α) :
∫⁻ a in s, f a ∂μ ≤ μ.withDensity f s := by
let t := toMeasurable (μ.withDensity f) s
calc
∫⁻ a in s, f a ∂μ ≤ ∫⁻ a in t, f a ∂μ :=
lintegral_mono_set (subset_toMeasurable (withDensity μ f) s)
_ = μ.withDensity f t :=
(withDensity_apply f (measurableSet_toMeasurable (withDensity μ f) s)).symm
_ = μ.withDensity f s := measure_toMeasurable s
/-! In the next theorem, the s-finiteness assumption is necessary. Here is a counterexample
without this assumption. Let `α` be an uncountable space, let `x₀` be some fixed point, and consider
the σ-algebra made of those sets which are countable and do not contain `x₀`, and of their
complements. This is the σ-algebra generated by the sets `{x}` for `x ≠ x₀`. Define a measure equal
to `+∞` on nonempty sets. Let `s = {x₀}` and `f` the indicator of `sᶜ`. Then
* `∫⁻ a in s, f a ∂μ = 0`. Indeed, consider a simple function `g ≤ f`. It vanishes on `s`. Then
`∫⁻ a in s, g a ∂μ = 0`. Taking the supremum over `g` gives the claim.
* `μ.withDensity f s = +∞`. Indeed, this is the infimum of `μ.withDensity f t` over measurable sets
`t` containing `s`. As `s` is not measurable, such a set `t` contains a point `x ≠ x₀`. Then
`μ.withDensity f t ≥ μ.withDensity f {x} = ∫⁻ a in {x}, f a ∂μ = μ {x} = +∞`.
One checks that `μ.withDensity f = μ`, while `μ.restrict s` gives zero mass to sets not
containing `x₀`, and infinite mass to those that contain it. -/
theorem withDensity_apply' [SFinite μ] (f : α → ℝ≥0∞) (s : Set α) :
μ.withDensity f s = ∫⁻ a in s, f a ∂μ := by
apply le_antisymm ?_ (withDensity_apply_le f s)
let t := toMeasurable μ s
calc
μ.withDensity f s ≤ μ.withDensity f t := measure_mono (subset_toMeasurable μ s)
_ = ∫⁻ a in t, f a ∂μ := withDensity_apply f (measurableSet_toMeasurable μ s)
_ = ∫⁻ a in s, f a ∂μ := by congr 1; exact restrict_toMeasurable_of_sFinite s
@[simp]
lemma withDensity_zero_left (f : α → ℝ≥0∞) : (0 : Measure α).withDensity f = 0 := by
ext s hs
rw [withDensity_apply _ hs]
simp
theorem withDensity_congr_ae {f g : α → ℝ≥0∞} (h : f =ᵐ[μ] g) :
μ.withDensity f = μ.withDensity g := by
refine Measure.ext fun s hs => ?_
rw [withDensity_apply _ hs, withDensity_apply _ hs]
exact lintegral_congr_ae (ae_restrict_of_ae h)
#align measure_theory.with_density_congr_ae MeasureTheory.withDensity_congr_ae
lemma withDensity_mono {f g : α → ℝ≥0∞} (hfg : f ≤ᵐ[μ] g) :
μ.withDensity f ≤ μ.withDensity g := by
refine le_iff.2 fun s hs ↦ ?_
rw [withDensity_apply _ hs, withDensity_apply _ hs]
refine set_lintegral_mono_ae' hs ?_
filter_upwards [hfg] with x h_le using fun _ ↦ h_le
theorem withDensity_add_left {f : α → ℝ≥0∞} (hf : Measurable f) (g : α → ℝ≥0∞) :
μ.withDensity (f + g) = μ.withDensity f + μ.withDensity g := by
refine Measure.ext fun s hs => ?_
rw [withDensity_apply _ hs, Measure.add_apply, withDensity_apply _ hs, withDensity_apply _ hs,
← lintegral_add_left hf]
simp only [Pi.add_apply]
#align measure_theory.with_density_add_left MeasureTheory.withDensity_add_left
theorem withDensity_add_right (f : α → ℝ≥0∞) {g : α → ℝ≥0∞} (hg : Measurable g) :
μ.withDensity (f + g) = μ.withDensity f + μ.withDensity g := by
simpa only [add_comm] using withDensity_add_left hg f
#align measure_theory.with_density_add_right MeasureTheory.withDensity_add_right
theorem withDensity_add_measure {m : MeasurableSpace α} (μ ν : Measure α) (f : α → ℝ≥0∞) :
(μ + ν).withDensity f = μ.withDensity f + ν.withDensity f := by
ext1 s hs
simp only [withDensity_apply f hs, restrict_add, lintegral_add_measure, Measure.add_apply]
#align measure_theory.with_density_add_measure MeasureTheory.withDensity_add_measure
theorem withDensity_sum {ι : Type*} {m : MeasurableSpace α} (μ : ι → Measure α) (f : α → ℝ≥0∞) :
(sum μ).withDensity f = sum fun n => (μ n).withDensity f := by
ext1 s hs
simp_rw [sum_apply _ hs, withDensity_apply f hs, restrict_sum μ hs, lintegral_sum_measure]
#align measure_theory.with_density_sum MeasureTheory.withDensity_sum
theorem withDensity_smul (r : ℝ≥0∞) {f : α → ℝ≥0∞} (hf : Measurable f) :
μ.withDensity (r • f) = r • μ.withDensity f := by
refine Measure.ext fun s hs => ?_
rw [withDensity_apply _ hs, Measure.coe_smul, Pi.smul_apply, withDensity_apply _ hs,
smul_eq_mul, ← lintegral_const_mul r hf]
simp only [Pi.smul_apply, smul_eq_mul]
#align measure_theory.with_density_smul MeasureTheory.withDensity_smul
theorem withDensity_smul' (r : ℝ≥0∞) (f : α → ℝ≥0∞) (hr : r ≠ ∞) :
μ.withDensity (r • f) = r • μ.withDensity f := by
refine Measure.ext fun s hs => ?_
rw [withDensity_apply _ hs, Measure.coe_smul, Pi.smul_apply, withDensity_apply _ hs,
smul_eq_mul, ← lintegral_const_mul' r f hr]
simp only [Pi.smul_apply, smul_eq_mul]
#align measure_theory.with_density_smul' MeasureTheory.withDensity_smul'
theorem withDensity_smul_measure (r : ℝ≥0∞) (f : α → ℝ≥0∞) :
(r • μ).withDensity f = r • μ.withDensity f := by
ext s hs
rw [withDensity_apply _ hs, Measure.coe_smul, Pi.smul_apply, withDensity_apply _ hs,
smul_eq_mul, set_lintegral_smul_measure]
theorem isFiniteMeasure_withDensity {f : α → ℝ≥0∞} (hf : ∫⁻ a, f a ∂μ ≠ ∞) :
IsFiniteMeasure (μ.withDensity f) :=
{ measure_univ_lt_top := by
rwa [withDensity_apply _ MeasurableSet.univ, Measure.restrict_univ, lt_top_iff_ne_top] }
#align measure_theory.is_finite_measure_with_density MeasureTheory.isFiniteMeasure_withDensity
theorem withDensity_absolutelyContinuous {m : MeasurableSpace α} (μ : Measure α) (f : α → ℝ≥0∞) :
μ.withDensity f ≪ μ := by
refine AbsolutelyContinuous.mk fun s hs₁ hs₂ => ?_
rw [withDensity_apply _ hs₁]
exact set_lintegral_measure_zero _ _ hs₂
#align measure_theory.with_density_absolutely_continuous MeasureTheory.withDensity_absolutelyContinuous
@[simp]
theorem withDensity_zero : μ.withDensity 0 = 0 := by
ext1 s hs
simp [withDensity_apply _ hs]
#align measure_theory.with_density_zero MeasureTheory.withDensity_zero
@[simp]
theorem withDensity_one : μ.withDensity 1 = μ := by
ext1 s hs
simp [withDensity_apply _ hs]
#align measure_theory.with_density_one MeasureTheory.withDensity_one
@[simp]
| Mathlib/MeasureTheory/Measure/WithDensity.lean | 170 | 172 | theorem withDensity_const (c : ℝ≥0∞) : μ.withDensity (fun _ ↦ c) = c • μ := by |
ext1 s hs
simp [withDensity_apply _ hs]
|
/-
Copyright (c) 2022 Yaël Dillies, Bhavik Mehta. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yaël Dillies, Bhavik Mehta
-/
import Mathlib.Algebra.BigOperators.Ring
import Mathlib.Combinatorics.SimpleGraph.Density
import Mathlib.Data.Nat.Cast.Field
import Mathlib.Order.Partition.Equipartition
import Mathlib.SetTheory.Ordinal.Basic
#align_import combinatorics.simple_graph.regularity.uniform from "leanprover-community/mathlib"@"bf7ef0e83e5b7e6c1169e97f055e58a2e4e9d52d"
/-!
# Graph uniformity and uniform partitions
In this file we define uniformity of a pair of vertices in a graph and uniformity of a partition of
vertices of a graph. Both are also known as ε-regularity.
Finsets of vertices `s` and `t` are `ε`-uniform in a graph `G` if their edge density is at most
`ε`-far from the density of any big enough `s'` and `t'` where `s' ⊆ s`, `t' ⊆ t`.
The definition is pretty technical, but it amounts to the edges between `s` and `t` being "random"
The literature contains several definitions which are equivalent up to scaling `ε` by some constant
when the partition is equitable.
A partition `P` of the vertices is `ε`-uniform if the proportion of non `ε`-uniform pairs of parts
is less than `ε`.
## Main declarations
* `SimpleGraph.IsUniform`: Graph uniformity of a pair of finsets of vertices.
* `SimpleGraph.nonuniformWitness`: `G.nonuniformWitness ε s t` and `G.nonuniformWitness ε t s`
together witness the non-uniformity of `s` and `t`.
* `Finpartition.nonUniforms`: Non uniform pairs of parts of a partition.
* `Finpartition.IsUniform`: Uniformity of a partition.
* `Finpartition.nonuniformWitnesses`: For each non-uniform pair of parts of a partition, pick
witnesses of non-uniformity and dump them all together.
## References
[Yaël Dillies, Bhavik Mehta, *Formalising Szemerédi’s Regularity Lemma in Lean*][srl_itp]
-/
open Finset
variable {α 𝕜 : Type*} [LinearOrderedField 𝕜]
/-! ### Graph uniformity -/
namespace SimpleGraph
variable (G : SimpleGraph α) [DecidableRel G.Adj] (ε : 𝕜) {s t : Finset α} {a b : α}
/-- A pair of finsets of vertices is `ε`-uniform (aka `ε`-regular) iff their edge density is close
to the density of any big enough pair of subsets. Intuitively, the edges between them are
random-like. -/
def IsUniform (s t : Finset α) : Prop :=
∀ ⦃s'⦄, s' ⊆ s → ∀ ⦃t'⦄, t' ⊆ t → (s.card : 𝕜) * ε ≤ s'.card →
(t.card : 𝕜) * ε ≤ t'.card → |(G.edgeDensity s' t' : 𝕜) - (G.edgeDensity s t : 𝕜)| < ε
#align simple_graph.is_uniform SimpleGraph.IsUniform
variable {G ε}
instance IsUniform.instDecidableRel : DecidableRel (G.IsUniform ε) := by
unfold IsUniform; infer_instance
theorem IsUniform.mono {ε' : 𝕜} (h : ε ≤ ε') (hε : IsUniform G ε s t) : IsUniform G ε' s t :=
fun s' hs' t' ht' hs ht => by
refine (hε hs' ht' (le_trans ?_ hs) (le_trans ?_ ht)).trans_le h <;> gcongr
#align simple_graph.is_uniform.mono SimpleGraph.IsUniform.mono
theorem IsUniform.symm : Symmetric (IsUniform G ε) := fun s t h t' ht' s' hs' ht hs => by
rw [edgeDensity_comm _ t', edgeDensity_comm _ t]
exact h hs' ht' hs ht
#align simple_graph.is_uniform.symm SimpleGraph.IsUniform.symm
variable (G)
theorem isUniform_comm : IsUniform G ε s t ↔ IsUniform G ε t s :=
⟨fun h => h.symm, fun h => h.symm⟩
#align simple_graph.is_uniform_comm SimpleGraph.isUniform_comm
lemma isUniform_one : G.IsUniform (1 : 𝕜) s t := by
intro s' hs' t' ht' hs ht
rw [mul_one] at hs ht
rw [eq_of_subset_of_card_le hs' (Nat.cast_le.1 hs),
eq_of_subset_of_card_le ht' (Nat.cast_le.1 ht), sub_self, abs_zero]
exact zero_lt_one
#align simple_graph.is_uniform_one SimpleGraph.isUniform_one
variable {G}
lemma IsUniform.pos (hG : G.IsUniform ε s t) : 0 < ε :=
not_le.1 fun hε ↦ (hε.trans $ abs_nonneg _).not_lt $ hG (empty_subset _) (empty_subset _)
(by simpa using mul_nonpos_of_nonneg_of_nonpos (Nat.cast_nonneg _) hε)
(by simpa using mul_nonpos_of_nonneg_of_nonpos (Nat.cast_nonneg _) hε)
@[simp] lemma isUniform_singleton : G.IsUniform ε {a} {b} ↔ 0 < ε := by
refine ⟨IsUniform.pos, fun hε s' hs' t' ht' hs ht ↦ ?_⟩
rw [card_singleton, Nat.cast_one, one_mul] at hs ht
obtain rfl | rfl := Finset.subset_singleton_iff.1 hs'
· replace hs : ε ≤ 0 := by simpa using hs
exact (hε.not_le hs).elim
obtain rfl | rfl := Finset.subset_singleton_iff.1 ht'
· replace ht : ε ≤ 0 := by simpa using ht
exact (hε.not_le ht).elim
· rwa [sub_self, abs_zero]
#align simple_graph.is_uniform_singleton SimpleGraph.isUniform_singleton
theorem not_isUniform_zero : ¬G.IsUniform (0 : 𝕜) s t := fun h =>
(abs_nonneg _).not_lt <| h (empty_subset _) (empty_subset _) (by simp) (by simp)
#align simple_graph.not_is_uniform_zero SimpleGraph.not_isUniform_zero
theorem not_isUniform_iff :
¬G.IsUniform ε s t ↔ ∃ s', s' ⊆ s ∧ ∃ t', t' ⊆ t ∧ ↑s.card * ε ≤ s'.card ∧
↑t.card * ε ≤ t'.card ∧ ε ≤ |G.edgeDensity s' t' - G.edgeDensity s t| := by
unfold IsUniform
simp only [not_forall, not_lt, exists_prop, exists_and_left, Rat.cast_abs, Rat.cast_sub]
#align simple_graph.not_is_uniform_iff SimpleGraph.not_isUniform_iff
open scoped Classical
variable (G)
/-- An arbitrary pair of subsets witnessing the non-uniformity of `(s, t)`. If `(s, t)` is uniform,
returns `(s, t)`. Witnesses for `(s, t)` and `(t, s)` don't necessarily match. See
`SimpleGraph.nonuniformWitness`. -/
noncomputable def nonuniformWitnesses (ε : 𝕜) (s t : Finset α) : Finset α × Finset α :=
if h : ¬G.IsUniform ε s t then
((not_isUniform_iff.1 h).choose, (not_isUniform_iff.1 h).choose_spec.2.choose)
else (s, t)
#align simple_graph.nonuniform_witnesses SimpleGraph.nonuniformWitnesses
theorem left_nonuniformWitnesses_subset (h : ¬G.IsUniform ε s t) :
(G.nonuniformWitnesses ε s t).1 ⊆ s := by
rw [nonuniformWitnesses, dif_pos h]
exact (not_isUniform_iff.1 h).choose_spec.1
#align simple_graph.left_nonuniform_witnesses_subset SimpleGraph.left_nonuniformWitnesses_subset
theorem left_nonuniformWitnesses_card (h : ¬G.IsUniform ε s t) :
(s.card : 𝕜) * ε ≤ (G.nonuniformWitnesses ε s t).1.card := by
rw [nonuniformWitnesses, dif_pos h]
exact (not_isUniform_iff.1 h).choose_spec.2.choose_spec.2.1
#align simple_graph.left_nonuniform_witnesses_card SimpleGraph.left_nonuniformWitnesses_card
theorem right_nonuniformWitnesses_subset (h : ¬G.IsUniform ε s t) :
(G.nonuniformWitnesses ε s t).2 ⊆ t := by
rw [nonuniformWitnesses, dif_pos h]
exact (not_isUniform_iff.1 h).choose_spec.2.choose_spec.1
#align simple_graph.right_nonuniform_witnesses_subset SimpleGraph.right_nonuniformWitnesses_subset
theorem right_nonuniformWitnesses_card (h : ¬G.IsUniform ε s t) :
(t.card : 𝕜) * ε ≤ (G.nonuniformWitnesses ε s t).2.card := by
rw [nonuniformWitnesses, dif_pos h]
exact (not_isUniform_iff.1 h).choose_spec.2.choose_spec.2.2.1
#align simple_graph.right_nonuniform_witnesses_card SimpleGraph.right_nonuniformWitnesses_card
| Mathlib/Combinatorics/SimpleGraph/Regularity/Uniform.lean | 160 | 165 | theorem nonuniformWitnesses_spec (h : ¬G.IsUniform ε s t) :
ε ≤
|G.edgeDensity (G.nonuniformWitnesses ε s t).1 (G.nonuniformWitnesses ε s t).2 -
G.edgeDensity s t| := by |
rw [nonuniformWitnesses, dif_pos h]
exact (not_isUniform_iff.1 h).choose_spec.2.choose_spec.2.2.2
|
/-
Copyright (c) 2019 Anne Baanen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anne Baanen, Lu-Ming Zhang
-/
import Mathlib.Data.Matrix.Invertible
import Mathlib.LinearAlgebra.Matrix.Adjugate
import Mathlib.LinearAlgebra.FiniteDimensional
#align_import linear_algebra.matrix.nonsingular_inverse from "leanprover-community/mathlib"@"722b3b152ddd5e0cf21c0a29787c76596cb6b422"
/-!
# Nonsingular inverses
In this file, we define an inverse for square matrices of invertible determinant.
For matrices that are not square or not of full rank, there is a more general notion of
pseudoinverses which we do not consider here.
The definition of inverse used in this file is the adjugate divided by the determinant.
We show that dividing the adjugate by `det A` (if possible), giving a matrix `A⁻¹` (`nonsing_inv`),
will result in a multiplicative inverse to `A`.
Note that there are at least three different inverses in mathlib:
* `A⁻¹` (`Inv.inv`): alone, this satisfies no properties, although it is usually used in
conjunction with `Group` or `GroupWithZero`. On matrices, this is defined to be zero when no
inverse exists.
* `⅟A` (`invOf`): this is only available in the presence of `[Invertible A]`, which guarantees an
inverse exists.
* `Ring.inverse A`: this is defined on any `MonoidWithZero`, and just like `⁻¹` on matrices, is
defined to be zero when no inverse exists.
We start by working with `Invertible`, and show the main results:
* `Matrix.invertibleOfDetInvertible`
* `Matrix.detInvertibleOfInvertible`
* `Matrix.isUnit_iff_isUnit_det`
* `Matrix.mul_eq_one_comm`
After this we define `Matrix.inv` and show it matches `⅟A` and `Ring.inverse A`.
The rest of the results in the file are then about `A⁻¹`
## References
* https://en.wikipedia.org/wiki/Cramer's_rule#Finding_inverse_matrix
## Tags
matrix inverse, cramer, cramer's rule, adjugate
-/
namespace Matrix
universe u u' v
variable {l : Type*} {m : Type u} {n : Type u'} {α : Type v}
open Matrix Equiv Equiv.Perm Finset
/-! ### Matrices are `Invertible` iff their determinants are -/
section Invertible
variable [Fintype n] [DecidableEq n] [CommRing α]
variable (A : Matrix n n α) (B : Matrix n n α)
/-- If `A.det` has a constructive inverse, produce one for `A`. -/
def invertibleOfDetInvertible [Invertible A.det] : Invertible A where
invOf := ⅟ A.det • A.adjugate
mul_invOf_self := by
rw [mul_smul_comm, mul_adjugate, smul_smul, invOf_mul_self, one_smul]
invOf_mul_self := by
rw [smul_mul_assoc, adjugate_mul, smul_smul, invOf_mul_self, one_smul]
#align matrix.invertible_of_det_invertible Matrix.invertibleOfDetInvertible
theorem invOf_eq [Invertible A.det] [Invertible A] : ⅟ A = ⅟ A.det • A.adjugate := by
letI := invertibleOfDetInvertible A
convert (rfl : ⅟ A = _)
#align matrix.inv_of_eq Matrix.invOf_eq
/-- `A.det` is invertible if `A` has a left inverse. -/
def detInvertibleOfLeftInverse (h : B * A = 1) : Invertible A.det where
invOf := B.det
mul_invOf_self := by rw [mul_comm, ← det_mul, h, det_one]
invOf_mul_self := by rw [← det_mul, h, det_one]
#align matrix.det_invertible_of_left_inverse Matrix.detInvertibleOfLeftInverse
/-- `A.det` is invertible if `A` has a right inverse. -/
def detInvertibleOfRightInverse (h : A * B = 1) : Invertible A.det where
invOf := B.det
mul_invOf_self := by rw [← det_mul, h, det_one]
invOf_mul_self := by rw [mul_comm, ← det_mul, h, det_one]
#align matrix.det_invertible_of_right_inverse Matrix.detInvertibleOfRightInverse
/-- If `A` has a constructive inverse, produce one for `A.det`. -/
def detInvertibleOfInvertible [Invertible A] : Invertible A.det :=
detInvertibleOfLeftInverse A (⅟ A) (invOf_mul_self _)
#align matrix.det_invertible_of_invertible Matrix.detInvertibleOfInvertible
theorem det_invOf [Invertible A] [Invertible A.det] : (⅟ A).det = ⅟ A.det := by
letI := detInvertibleOfInvertible A
convert (rfl : _ = ⅟ A.det)
#align matrix.det_inv_of Matrix.det_invOf
/-- Together `Matrix.detInvertibleOfInvertible` and `Matrix.invertibleOfDetInvertible` form an
equivalence, although both sides of the equiv are subsingleton anyway. -/
@[simps]
def invertibleEquivDetInvertible : Invertible A ≃ Invertible A.det where
toFun := @detInvertibleOfInvertible _ _ _ _ _ A
invFun := @invertibleOfDetInvertible _ _ _ _ _ A
left_inv _ := Subsingleton.elim _ _
right_inv _ := Subsingleton.elim _ _
#align matrix.invertible_equiv_det_invertible Matrix.invertibleEquivDetInvertible
variable {A B}
theorem mul_eq_one_comm : A * B = 1 ↔ B * A = 1 :=
suffices ∀ A B : Matrix n n α, A * B = 1 → B * A = 1 from ⟨this A B, this B A⟩
fun A B h => by
letI : Invertible B.det := detInvertibleOfLeftInverse _ _ h
letI : Invertible B := invertibleOfDetInvertible B
calc
B * A = B * A * (B * ⅟ B) := by rw [mul_invOf_self, Matrix.mul_one]
_ = B * (A * B * ⅟ B) := by simp only [Matrix.mul_assoc]
_ = B * ⅟ B := by rw [h, Matrix.one_mul]
_ = 1 := mul_invOf_self B
#align matrix.mul_eq_one_comm Matrix.mul_eq_one_comm
variable (A B)
/-- We can construct an instance of invertible A if A has a left inverse. -/
def invertibleOfLeftInverse (h : B * A = 1) : Invertible A :=
⟨B, h, mul_eq_one_comm.mp h⟩
#align matrix.invertible_of_left_inverse Matrix.invertibleOfLeftInverse
/-- We can construct an instance of invertible A if A has a right inverse. -/
def invertibleOfRightInverse (h : A * B = 1) : Invertible A :=
⟨B, mul_eq_one_comm.mp h, h⟩
#align matrix.invertible_of_right_inverse Matrix.invertibleOfRightInverse
/-- Given a proof that `A.det` has a constructive inverse, lift `A` to `(Matrix n n α)ˣ`-/
def unitOfDetInvertible [Invertible A.det] : (Matrix n n α)ˣ :=
@unitOfInvertible _ _ A (invertibleOfDetInvertible A)
#align matrix.unit_of_det_invertible Matrix.unitOfDetInvertible
/-- When lowered to a prop, `Matrix.invertibleEquivDetInvertible` forms an `iff`. -/
theorem isUnit_iff_isUnit_det : IsUnit A ↔ IsUnit A.det := by
simp only [← nonempty_invertible_iff_isUnit, (invertibleEquivDetInvertible A).nonempty_congr]
#align matrix.is_unit_iff_is_unit_det Matrix.isUnit_iff_isUnit_det
@[simp]
theorem isUnits_det_units (A : (Matrix n n α)ˣ) : IsUnit (A : Matrix n n α).det :=
isUnit_iff_isUnit_det _ |>.mp A.isUnit
/-! #### Variants of the statements above with `IsUnit`-/
theorem isUnit_det_of_invertible [Invertible A] : IsUnit A.det :=
@isUnit_of_invertible _ _ _ (detInvertibleOfInvertible A)
#align matrix.is_unit_det_of_invertible Matrix.isUnit_det_of_invertible
variable {A B}
theorem isUnit_of_left_inverse (h : B * A = 1) : IsUnit A :=
⟨⟨A, B, mul_eq_one_comm.mp h, h⟩, rfl⟩
#align matrix.is_unit_of_left_inverse Matrix.isUnit_of_left_inverse
theorem exists_left_inverse_iff_isUnit : (∃ B, B * A = 1) ↔ IsUnit A :=
⟨fun ⟨_, h⟩ ↦ isUnit_of_left_inverse h, fun h ↦ have := h.invertible; ⟨⅟A, invOf_mul_self' A⟩⟩
theorem isUnit_of_right_inverse (h : A * B = 1) : IsUnit A :=
⟨⟨A, B, h, mul_eq_one_comm.mp h⟩, rfl⟩
#align matrix.is_unit_of_right_inverse Matrix.isUnit_of_right_inverse
theorem exists_right_inverse_iff_isUnit : (∃ B, A * B = 1) ↔ IsUnit A :=
⟨fun ⟨_, h⟩ ↦ isUnit_of_right_inverse h, fun h ↦ have := h.invertible; ⟨⅟A, mul_invOf_self' A⟩⟩
theorem isUnit_det_of_left_inverse (h : B * A = 1) : IsUnit A.det :=
@isUnit_of_invertible _ _ _ (detInvertibleOfLeftInverse _ _ h)
#align matrix.is_unit_det_of_left_inverse Matrix.isUnit_det_of_left_inverse
theorem isUnit_det_of_right_inverse (h : A * B = 1) : IsUnit A.det :=
@isUnit_of_invertible _ _ _ (detInvertibleOfRightInverse _ _ h)
#align matrix.is_unit_det_of_right_inverse Matrix.isUnit_det_of_right_inverse
theorem det_ne_zero_of_left_inverse [Nontrivial α] (h : B * A = 1) : A.det ≠ 0 :=
(isUnit_det_of_left_inverse h).ne_zero
#align matrix.det_ne_zero_of_left_inverse Matrix.det_ne_zero_of_left_inverse
theorem det_ne_zero_of_right_inverse [Nontrivial α] (h : A * B = 1) : A.det ≠ 0 :=
(isUnit_det_of_right_inverse h).ne_zero
#align matrix.det_ne_zero_of_right_inverse Matrix.det_ne_zero_of_right_inverse
end Invertible
section Inv
variable [Fintype n] [DecidableEq n] [CommRing α]
variable (A : Matrix n n α) (B : Matrix n n α)
theorem isUnit_det_transpose (h : IsUnit A.det) : IsUnit Aᵀ.det := by
rw [det_transpose]
exact h
#align matrix.is_unit_det_transpose Matrix.isUnit_det_transpose
/-! ### A noncomputable `Inv` instance -/
/-- The inverse of a square matrix, when it is invertible (and zero otherwise). -/
noncomputable instance inv : Inv (Matrix n n α) :=
⟨fun A => Ring.inverse A.det • A.adjugate⟩
theorem inv_def (A : Matrix n n α) : A⁻¹ = Ring.inverse A.det • A.adjugate :=
rfl
#align matrix.inv_def Matrix.inv_def
theorem nonsing_inv_apply_not_isUnit (h : ¬IsUnit A.det) : A⁻¹ = 0 := by
rw [inv_def, Ring.inverse_non_unit _ h, zero_smul]
#align matrix.nonsing_inv_apply_not_is_unit Matrix.nonsing_inv_apply_not_isUnit
theorem nonsing_inv_apply (h : IsUnit A.det) : A⁻¹ = (↑h.unit⁻¹ : α) • A.adjugate := by
rw [inv_def, ← Ring.inverse_unit h.unit, IsUnit.unit_spec]
#align matrix.nonsing_inv_apply Matrix.nonsing_inv_apply
/-- The nonsingular inverse is the same as `invOf` when `A` is invertible. -/
@[simp]
theorem invOf_eq_nonsing_inv [Invertible A] : ⅟ A = A⁻¹ := by
letI := detInvertibleOfInvertible A
rw [inv_def, Ring.inverse_invertible, invOf_eq]
#align matrix.inv_of_eq_nonsing_inv Matrix.invOf_eq_nonsing_inv
/-- Coercing the result of `Units.instInv` is the same as coercing first and applying the
nonsingular inverse. -/
@[simp, norm_cast]
theorem coe_units_inv (A : (Matrix n n α)ˣ) : ↑A⁻¹ = (A⁻¹ : Matrix n n α) := by
letI := A.invertible
rw [← invOf_eq_nonsing_inv, invOf_units]
#align matrix.coe_units_inv Matrix.coe_units_inv
/-- The nonsingular inverse is the same as the general `Ring.inverse`. -/
theorem nonsing_inv_eq_ring_inverse : A⁻¹ = Ring.inverse A := by
by_cases h_det : IsUnit A.det
· cases (A.isUnit_iff_isUnit_det.mpr h_det).nonempty_invertible
rw [← invOf_eq_nonsing_inv, Ring.inverse_invertible]
· have h := mt A.isUnit_iff_isUnit_det.mp h_det
rw [Ring.inverse_non_unit _ h, nonsing_inv_apply_not_isUnit A h_det]
#align matrix.nonsing_inv_eq_ring_inverse Matrix.nonsing_inv_eq_ring_inverse
theorem transpose_nonsing_inv : A⁻¹ᵀ = Aᵀ⁻¹ := by
rw [inv_def, inv_def, transpose_smul, det_transpose, adjugate_transpose]
#align matrix.transpose_nonsing_inv Matrix.transpose_nonsing_inv
theorem conjTranspose_nonsing_inv [StarRing α] : A⁻¹ᴴ = Aᴴ⁻¹ := by
rw [inv_def, inv_def, conjTranspose_smul, det_conjTranspose, adjugate_conjTranspose,
Ring.inverse_star]
#align matrix.conj_transpose_nonsing_inv Matrix.conjTranspose_nonsing_inv
/-- The `nonsing_inv` of `A` is a right inverse. -/
@[simp]
theorem mul_nonsing_inv (h : IsUnit A.det) : A * A⁻¹ = 1 := by
cases (A.isUnit_iff_isUnit_det.mpr h).nonempty_invertible
rw [← invOf_eq_nonsing_inv, mul_invOf_self]
#align matrix.mul_nonsing_inv Matrix.mul_nonsing_inv
/-- The `nonsing_inv` of `A` is a left inverse. -/
@[simp]
theorem nonsing_inv_mul (h : IsUnit A.det) : A⁻¹ * A = 1 := by
cases (A.isUnit_iff_isUnit_det.mpr h).nonempty_invertible
rw [← invOf_eq_nonsing_inv, invOf_mul_self]
#align matrix.nonsing_inv_mul Matrix.nonsing_inv_mul
instance [Invertible A] : Invertible A⁻¹ := by
rw [← invOf_eq_nonsing_inv]
infer_instance
@[simp]
theorem inv_inv_of_invertible [Invertible A] : A⁻¹⁻¹ = A := by
simp only [← invOf_eq_nonsing_inv, invOf_invOf]
#align matrix.inv_inv_of_invertible Matrix.inv_inv_of_invertible
@[simp]
theorem mul_nonsing_inv_cancel_right (B : Matrix m n α) (h : IsUnit A.det) : B * A * A⁻¹ = B := by
simp [Matrix.mul_assoc, mul_nonsing_inv A h]
#align matrix.mul_nonsing_inv_cancel_right Matrix.mul_nonsing_inv_cancel_right
@[simp]
theorem mul_nonsing_inv_cancel_left (B : Matrix n m α) (h : IsUnit A.det) : A * (A⁻¹ * B) = B := by
simp [← Matrix.mul_assoc, mul_nonsing_inv A h]
#align matrix.mul_nonsing_inv_cancel_left Matrix.mul_nonsing_inv_cancel_left
@[simp]
theorem nonsing_inv_mul_cancel_right (B : Matrix m n α) (h : IsUnit A.det) : B * A⁻¹ * A = B := by
simp [Matrix.mul_assoc, nonsing_inv_mul A h]
#align matrix.nonsing_inv_mul_cancel_right Matrix.nonsing_inv_mul_cancel_right
@[simp]
theorem nonsing_inv_mul_cancel_left (B : Matrix n m α) (h : IsUnit A.det) : A⁻¹ * (A * B) = B := by
simp [← Matrix.mul_assoc, nonsing_inv_mul A h]
#align matrix.nonsing_inv_mul_cancel_left Matrix.nonsing_inv_mul_cancel_left
@[simp]
theorem mul_inv_of_invertible [Invertible A] : A * A⁻¹ = 1 :=
mul_nonsing_inv A (isUnit_det_of_invertible A)
#align matrix.mul_inv_of_invertible Matrix.mul_inv_of_invertible
@[simp]
theorem inv_mul_of_invertible [Invertible A] : A⁻¹ * A = 1 :=
nonsing_inv_mul A (isUnit_det_of_invertible A)
#align matrix.inv_mul_of_invertible Matrix.inv_mul_of_invertible
@[simp]
theorem mul_inv_cancel_right_of_invertible (B : Matrix m n α) [Invertible A] : B * A * A⁻¹ = B :=
mul_nonsing_inv_cancel_right A B (isUnit_det_of_invertible A)
#align matrix.mul_inv_cancel_right_of_invertible Matrix.mul_inv_cancel_right_of_invertible
@[simp]
theorem mul_inv_cancel_left_of_invertible (B : Matrix n m α) [Invertible A] : A * (A⁻¹ * B) = B :=
mul_nonsing_inv_cancel_left A B (isUnit_det_of_invertible A)
#align matrix.mul_inv_cancel_left_of_invertible Matrix.mul_inv_cancel_left_of_invertible
@[simp]
theorem inv_mul_cancel_right_of_invertible (B : Matrix m n α) [Invertible A] : B * A⁻¹ * A = B :=
nonsing_inv_mul_cancel_right A B (isUnit_det_of_invertible A)
#align matrix.inv_mul_cancel_right_of_invertible Matrix.inv_mul_cancel_right_of_invertible
@[simp]
theorem inv_mul_cancel_left_of_invertible (B : Matrix n m α) [Invertible A] : A⁻¹ * (A * B) = B :=
nonsing_inv_mul_cancel_left A B (isUnit_det_of_invertible A)
#align matrix.inv_mul_cancel_left_of_invertible Matrix.inv_mul_cancel_left_of_invertible
theorem inv_mul_eq_iff_eq_mul_of_invertible (A B C : Matrix n n α) [Invertible A] :
A⁻¹ * B = C ↔ B = A * C :=
⟨fun h => by rw [← h, mul_inv_cancel_left_of_invertible],
fun h => by rw [h, inv_mul_cancel_left_of_invertible]⟩
#align matrix.inv_mul_eq_iff_eq_mul_of_invertible Matrix.inv_mul_eq_iff_eq_mul_of_invertible
theorem mul_inv_eq_iff_eq_mul_of_invertible (A B C : Matrix n n α) [Invertible A] :
B * A⁻¹ = C ↔ B = C * A :=
⟨fun h => by rw [← h, inv_mul_cancel_right_of_invertible],
fun h => by rw [h, mul_inv_cancel_right_of_invertible]⟩
#align matrix.mul_inv_eq_iff_eq_mul_of_invertible Matrix.mul_inv_eq_iff_eq_mul_of_invertible
lemma mul_right_injective_of_invertible [Invertible A] :
Function.Injective (fun (x : Matrix n m α) => A * x) :=
fun _ _ h => by simpa only [inv_mul_cancel_left_of_invertible] using congr_arg (A⁻¹ * ·) h
lemma mul_left_injective_of_invertible [Invertible A] :
Function.Injective (fun (x : Matrix m n α) => x * A) :=
fun a x hax => by simpa only [mul_inv_cancel_right_of_invertible] using congr_arg (· * A⁻¹) hax
lemma mul_right_inj_of_invertible [Invertible A] {x y : Matrix n m α} : A * x = A * y ↔ x = y :=
(mul_right_injective_of_invertible A).eq_iff
lemma mul_left_inj_of_invertible [Invertible A] {x y : Matrix m n α} : x * A = y * A ↔ x = y :=
(mul_left_injective_of_invertible A).eq_iff
end Inv
section InjectiveMul
variable [Fintype n] [Fintype m] [DecidableEq m] [CommRing α]
variable [Fintype l] [DecidableEq l]
lemma mul_left_injective_of_inv (A : Matrix m n α) (B : Matrix n m α) (h : A * B = 1) :
Function.Injective (fun x : Matrix l m α => x * A) := fun _ _ g => by
simpa only [Matrix.mul_assoc, Matrix.mul_one, h] using congr_arg (· * B) g
lemma mul_right_injective_of_inv (A : Matrix m n α) (B : Matrix n m α) (h : A * B = 1) :
Function.Injective (fun x : Matrix m l α => B * x) :=
fun _ _ g => by simpa only [← Matrix.mul_assoc, Matrix.one_mul, h] using congr_arg (A * ·) g
end InjectiveMul
section vecMul
variable [DecidableEq m] [DecidableEq n]
section Semiring
variable {R : Type*} [Semiring R]
theorem vecMul_surjective_iff_exists_left_inverse [Fintype m] [Finite n] {A : Matrix m n R} :
Function.Surjective A.vecMul ↔ ∃ B : Matrix n m R, B * A = 1 := by
cases nonempty_fintype n
refine ⟨fun h ↦ ?_, fun ⟨B, hBA⟩ y ↦ ⟨y ᵥ* B, by simp [hBA]⟩⟩
choose rows hrows using (h <| Pi.single · 1)
refine ⟨Matrix.of rows, Matrix.ext fun i j => ?_⟩
rw [mul_apply_eq_vecMul, one_eq_pi_single, ← hrows]
rfl
theorem mulVec_surjective_iff_exists_right_inverse [Finite m] [Fintype n] {A : Matrix m n R} :
Function.Surjective A.mulVec ↔ ∃ B : Matrix n m R, A * B = 1 := by
cases nonempty_fintype m
refine ⟨fun h ↦ ?_, fun ⟨B, hBA⟩ y ↦ ⟨B *ᵥ y, by simp [hBA]⟩⟩
choose cols hcols using (h <| Pi.single · 1)
refine ⟨(Matrix.of cols)ᵀ, Matrix.ext fun i j ↦ ?_⟩
rw [one_eq_pi_single, Pi.single_comm, ← hcols j]
rfl
end Semiring
variable {R K : Type*} [CommRing R] [Field K] [Fintype m]
theorem vecMul_surjective_iff_isUnit {A : Matrix m m R} :
Function.Surjective A.vecMul ↔ IsUnit A := by
rw [vecMul_surjective_iff_exists_left_inverse, exists_left_inverse_iff_isUnit]
theorem mulVec_surjective_iff_isUnit {A : Matrix m m R} :
Function.Surjective A.mulVec ↔ IsUnit A := by
rw [mulVec_surjective_iff_exists_right_inverse, exists_right_inverse_iff_isUnit]
theorem vecMul_injective_iff_isUnit {A : Matrix m m K} :
Function.Injective A.vecMul ↔ IsUnit A := by
refine ⟨fun h ↦ ?_, fun h ↦ ?_⟩
· rw [← vecMul_surjective_iff_isUnit]
exact LinearMap.surjective_of_injective (f := A.vecMulLinear) h
change Function.Injective A.vecMulLinear
rw [← LinearMap.ker_eq_bot, LinearMap.ker_eq_bot']
intro c hc
replace h := h.invertible
simpa using congr_arg A⁻¹.vecMulLinear hc
theorem mulVec_injective_iff_isUnit {A : Matrix m m K} :
Function.Injective A.mulVec ↔ IsUnit A := by
rw [← isUnit_transpose, ← vecMul_injective_iff_isUnit]
simp_rw [vecMul_transpose]
theorem linearIndependent_rows_iff_isUnit {A : Matrix m m K} :
LinearIndependent K (fun i ↦ A i) ↔ IsUnit A := by
rw [← transpose_transpose A, ← mulVec_injective_iff, ← coe_mulVecLin, mulVecLin_transpose,
transpose_transpose, ← vecMul_injective_iff_isUnit, coe_vecMulLinear]
theorem linearIndependent_cols_iff_isUnit {A : Matrix m m K} :
LinearIndependent K (fun i ↦ Aᵀ i) ↔ IsUnit A := by
rw [← transpose_transpose A, isUnit_transpose, linearIndependent_rows_iff_isUnit,
transpose_transpose]
theorem vecMul_surjective_of_invertible (A : Matrix m m R) [Invertible A] :
Function.Surjective A.vecMul :=
vecMul_surjective_iff_isUnit.2 <| isUnit_of_invertible A
theorem mulVec_surjective_of_invertible (A : Matrix m m R) [Invertible A] :
Function.Surjective A.mulVec :=
mulVec_surjective_iff_isUnit.2 <| isUnit_of_invertible A
theorem vecMul_injective_of_invertible (A : Matrix m m K) [Invertible A] :
Function.Injective A.vecMul :=
vecMul_injective_iff_isUnit.2 <| isUnit_of_invertible A
theorem mulVec_injective_of_invertible (A : Matrix m m K) [Invertible A] :
Function.Injective A.mulVec :=
mulVec_injective_iff_isUnit.2 <| isUnit_of_invertible A
theorem linearIndependent_rows_of_invertible (A : Matrix m m K) [Invertible A] :
LinearIndependent K (fun i ↦ A i) :=
linearIndependent_rows_iff_isUnit.2 <| isUnit_of_invertible A
theorem linearIndependent_cols_of_invertible (A : Matrix m m K) [Invertible A] :
LinearIndependent K (fun i ↦ Aᵀ i) :=
linearIndependent_cols_iff_isUnit.2 <| isUnit_of_invertible A
end vecMul
variable [Fintype n] [DecidableEq n] [CommRing α]
variable (A : Matrix n n α) (B : Matrix n n α)
theorem nonsing_inv_cancel_or_zero : A⁻¹ * A = 1 ∧ A * A⁻¹ = 1 ∨ A⁻¹ = 0 := by
by_cases h : IsUnit A.det
· exact Or.inl ⟨nonsing_inv_mul _ h, mul_nonsing_inv _ h⟩
· exact Or.inr (nonsing_inv_apply_not_isUnit _ h)
#align matrix.nonsing_inv_cancel_or_zero Matrix.nonsing_inv_cancel_or_zero
theorem det_nonsing_inv_mul_det (h : IsUnit A.det) : A⁻¹.det * A.det = 1 := by
rw [← det_mul, A.nonsing_inv_mul h, det_one]
#align matrix.det_nonsing_inv_mul_det Matrix.det_nonsing_inv_mul_det
@[simp]
theorem det_nonsing_inv : A⁻¹.det = Ring.inverse A.det := by
by_cases h : IsUnit A.det
· cases h.nonempty_invertible
letI := invertibleOfDetInvertible A
rw [Ring.inverse_invertible, ← invOf_eq_nonsing_inv, det_invOf]
cases isEmpty_or_nonempty n
· rw [det_isEmpty, det_isEmpty, Ring.inverse_one]
· rw [Ring.inverse_non_unit _ h, nonsing_inv_apply_not_isUnit _ h, det_zero ‹_›]
#align matrix.det_nonsing_inv Matrix.det_nonsing_inv
theorem isUnit_nonsing_inv_det (h : IsUnit A.det) : IsUnit A⁻¹.det :=
isUnit_of_mul_eq_one _ _ (A.det_nonsing_inv_mul_det h)
#align matrix.is_unit_nonsing_inv_det Matrix.isUnit_nonsing_inv_det
@[simp]
theorem nonsing_inv_nonsing_inv (h : IsUnit A.det) : A⁻¹⁻¹ = A :=
calc
A⁻¹⁻¹ = 1 * A⁻¹⁻¹ := by rw [Matrix.one_mul]
_ = A * A⁻¹ * A⁻¹⁻¹ := by rw [A.mul_nonsing_inv h]
_ = A := by
rw [Matrix.mul_assoc, A⁻¹.mul_nonsing_inv (A.isUnit_nonsing_inv_det h), Matrix.mul_one]
#align matrix.nonsing_inv_nonsing_inv Matrix.nonsing_inv_nonsing_inv
theorem isUnit_nonsing_inv_det_iff {A : Matrix n n α} : IsUnit A⁻¹.det ↔ IsUnit A.det := by
rw [Matrix.det_nonsing_inv, isUnit_ring_inverse]
#align matrix.is_unit_nonsing_inv_det_iff Matrix.isUnit_nonsing_inv_det_iff
-- `IsUnit.invertible` lifts the proposition `IsUnit A` to a constructive inverse of `A`.
/-- A version of `Matrix.invertibleOfDetInvertible` with the inverse defeq to `A⁻¹` that is
therefore noncomputable. -/
noncomputable def invertibleOfIsUnitDet (h : IsUnit A.det) : Invertible A :=
⟨A⁻¹, nonsing_inv_mul A h, mul_nonsing_inv A h⟩
#align matrix.invertible_of_is_unit_det Matrix.invertibleOfIsUnitDet
/-- A version of `Matrix.unitOfDetInvertible` with the inverse defeq to `A⁻¹` that is therefore
noncomputable. -/
noncomputable def nonsingInvUnit (h : IsUnit A.det) : (Matrix n n α)ˣ :=
@unitOfInvertible _ _ _ (invertibleOfIsUnitDet A h)
#align matrix.nonsing_inv_unit Matrix.nonsingInvUnit
theorem unitOfDetInvertible_eq_nonsingInvUnit [Invertible A.det] :
unitOfDetInvertible A = nonsingInvUnit A (isUnit_of_invertible _) := by
ext
rfl
#align matrix.unit_of_det_invertible_eq_nonsing_inv_unit Matrix.unitOfDetInvertible_eq_nonsingInvUnit
variable {A} {B}
/-- If matrix A is left invertible, then its inverse equals its left inverse. -/
theorem inv_eq_left_inv (h : B * A = 1) : A⁻¹ = B :=
letI := invertibleOfLeftInverse _ _ h
invOf_eq_nonsing_inv A ▸ invOf_eq_left_inv h
#align matrix.inv_eq_left_inv Matrix.inv_eq_left_inv
/-- If matrix A is right invertible, then its inverse equals its right inverse. -/
theorem inv_eq_right_inv (h : A * B = 1) : A⁻¹ = B :=
inv_eq_left_inv (mul_eq_one_comm.2 h)
#align matrix.inv_eq_right_inv Matrix.inv_eq_right_inv
section InvEqInv
variable {C : Matrix n n α}
/-- The left inverse of matrix A is unique when existing. -/
theorem left_inv_eq_left_inv (h : B * A = 1) (g : C * A = 1) : B = C := by
rw [← inv_eq_left_inv h, ← inv_eq_left_inv g]
#align matrix.left_inv_eq_left_inv Matrix.left_inv_eq_left_inv
/-- The right inverse of matrix A is unique when existing. -/
theorem right_inv_eq_right_inv (h : A * B = 1) (g : A * C = 1) : B = C := by
rw [← inv_eq_right_inv h, ← inv_eq_right_inv g]
#align matrix.right_inv_eq_right_inv Matrix.right_inv_eq_right_inv
/-- The right inverse of matrix A equals the left inverse of A when they exist. -/
theorem right_inv_eq_left_inv (h : A * B = 1) (g : C * A = 1) : B = C := by
rw [← inv_eq_right_inv h, ← inv_eq_left_inv g]
#align matrix.right_inv_eq_left_inv Matrix.right_inv_eq_left_inv
theorem inv_inj (h : A⁻¹ = B⁻¹) (h' : IsUnit A.det) : A = B := by
refine left_inv_eq_left_inv (mul_nonsing_inv _ h') ?_
rw [h]
refine mul_nonsing_inv _ ?_
rwa [← isUnit_nonsing_inv_det_iff, ← h, isUnit_nonsing_inv_det_iff]
#align matrix.inv_inj Matrix.inv_inj
end InvEqInv
variable (A)
@[simp]
theorem inv_zero : (0 : Matrix n n α)⁻¹ = 0 := by
cases' subsingleton_or_nontrivial α with ht ht
· simp [eq_iff_true_of_subsingleton]
rcases (Fintype.card n).zero_le.eq_or_lt with hc | hc
· rw [eq_comm, Fintype.card_eq_zero_iff] at hc
haveI := hc
ext i
exact (IsEmpty.false i).elim
· have hn : Nonempty n := Fintype.card_pos_iff.mp hc
refine nonsing_inv_apply_not_isUnit _ ?_
simp [hn]
#align matrix.inv_zero Matrix.inv_zero
noncomputable instance : InvOneClass (Matrix n n α) :=
{ Matrix.one, Matrix.inv with inv_one := inv_eq_left_inv (by simp) }
theorem inv_smul (k : α) [Invertible k] (h : IsUnit A.det) : (k • A)⁻¹ = ⅟ k • A⁻¹ :=
inv_eq_left_inv (by simp [h, smul_smul])
#align matrix.inv_smul Matrix.inv_smul
theorem inv_smul' (k : αˣ) (h : IsUnit A.det) : (k • A)⁻¹ = k⁻¹ • A⁻¹ :=
inv_eq_left_inv (by simp [h, smul_smul])
#align matrix.inv_smul' Matrix.inv_smul'
theorem inv_adjugate (A : Matrix n n α) (h : IsUnit A.det) : (adjugate A)⁻¹ = h.unit⁻¹ • A := by
refine inv_eq_left_inv ?_
rw [smul_mul, mul_adjugate, Units.smul_def, smul_smul, h.val_inv_mul, one_smul]
#align matrix.inv_adjugate Matrix.inv_adjugate
section Diagonal
/-- `diagonal v` is invertible if `v` is -/
def diagonalInvertible {α} [NonAssocSemiring α] (v : n → α) [Invertible v] :
Invertible (diagonal v) :=
Invertible.map (diagonalRingHom n α) v
#align matrix.diagonal_invertible Matrix.diagonalInvertible
theorem invOf_diagonal_eq {α} [Semiring α] (v : n → α) [Invertible v] [Invertible (diagonal v)] :
⅟ (diagonal v) = diagonal (⅟ v) := by
letI := diagonalInvertible v
-- Porting note: no longer need `haveI := Invertible.subsingleton (diagonal v)`
convert (rfl : ⅟ (diagonal v) = _)
#align matrix.inv_of_diagonal_eq Matrix.invOf_diagonal_eq
/-- `v` is invertible if `diagonal v` is -/
def invertibleOfDiagonalInvertible (v : n → α) [Invertible (diagonal v)] : Invertible v where
invOf := diag (⅟ (diagonal v))
invOf_mul_self :=
funext fun i => by
letI : Invertible (diagonal v).det := detInvertibleOfInvertible _
rw [invOf_eq, diag_smul, adjugate_diagonal, diag_diagonal]
dsimp
rw [mul_assoc, prod_erase_mul _ _ (Finset.mem_univ _), ← det_diagonal]
exact mul_invOf_self _
mul_invOf_self :=
funext fun i => by
letI : Invertible (diagonal v).det := detInvertibleOfInvertible _
rw [invOf_eq, diag_smul, adjugate_diagonal, diag_diagonal]
dsimp
rw [mul_left_comm, mul_prod_erase _ _ (Finset.mem_univ _), ← det_diagonal]
exact mul_invOf_self _
#align matrix.invertible_of_diagonal_invertible Matrix.invertibleOfDiagonalInvertible
/-- Together `Matrix.diagonalInvertible` and `Matrix.invertibleOfDiagonalInvertible` form an
equivalence, although both sides of the equiv are subsingleton anyway. -/
@[simps]
def diagonalInvertibleEquivInvertible (v : n → α) : Invertible (diagonal v) ≃ Invertible v where
toFun := @invertibleOfDiagonalInvertible _ _ _ _ _ _
invFun := @diagonalInvertible _ _ _ _ _ _
left_inv _ := Subsingleton.elim _ _
right_inv _ := Subsingleton.elim _ _
#align matrix.diagonal_invertible_equiv_invertible Matrix.diagonalInvertibleEquivInvertible
/-- When lowered to a prop, `Matrix.diagonalInvertibleEquivInvertible` forms an `iff`. -/
@[simp]
theorem isUnit_diagonal {v : n → α} : IsUnit (diagonal v) ↔ IsUnit v := by
simp only [← nonempty_invertible_iff_isUnit,
(diagonalInvertibleEquivInvertible v).nonempty_congr]
#align matrix.is_unit_diagonal Matrix.isUnit_diagonal
theorem inv_diagonal (v : n → α) : (diagonal v)⁻¹ = diagonal (Ring.inverse v) := by
rw [nonsing_inv_eq_ring_inverse]
by_cases h : IsUnit v
· have := isUnit_diagonal.mpr h
cases this.nonempty_invertible
cases h.nonempty_invertible
rw [Ring.inverse_invertible, Ring.inverse_invertible, invOf_diagonal_eq]
· have := isUnit_diagonal.not.mpr h
rw [Ring.inverse_non_unit _ h, Pi.zero_def, diagonal_zero, Ring.inverse_non_unit _ this]
#align matrix.inv_diagonal Matrix.inv_diagonal
end Diagonal
@[simp]
theorem inv_inv_inv (A : Matrix n n α) : A⁻¹⁻¹⁻¹ = A⁻¹ := by
by_cases h : IsUnit A.det
· rw [nonsing_inv_nonsing_inv _ h]
· simp [nonsing_inv_apply_not_isUnit _ h]
#align matrix.inv_inv_inv Matrix.inv_inv_inv
/-- The `Matrix` version of `inv_add_inv'` -/
theorem inv_add_inv {A B : Matrix n n α} (h : IsUnit A ↔ IsUnit B) :
A⁻¹ + B⁻¹ = A⁻¹ * (A + B) * B⁻¹ := by
simpa only [nonsing_inv_eq_ring_inverse] using Ring.inverse_add_inverse h
/-- The `Matrix` version of `inv_sub_inv'` -/
theorem inv_sub_inv {A B : Matrix n n α} (h : IsUnit A ↔ IsUnit B) :
A⁻¹ - B⁻¹ = A⁻¹ * (B - A) * B⁻¹ := by
simpa only [nonsing_inv_eq_ring_inverse] using Ring.inverse_sub_inverse h
theorem mul_inv_rev (A B : Matrix n n α) : (A * B)⁻¹ = B⁻¹ * A⁻¹ := by
simp only [inv_def]
rw [Matrix.smul_mul, Matrix.mul_smul, smul_smul, det_mul, adjugate_mul_distrib,
Ring.mul_inverse_rev]
#align matrix.mul_inv_rev Matrix.mul_inv_rev
/-- A version of `List.prod_inv_reverse` for `Matrix.inv`. -/
theorem list_prod_inv_reverse : ∀ l : List (Matrix n n α), l.prod⁻¹ = (l.reverse.map Inv.inv).prod
| [] => by rw [List.reverse_nil, List.map_nil, List.prod_nil, inv_one]
| A::Xs => by
rw [List.reverse_cons', List.map_concat, List.prod_concat, List.prod_cons,
mul_inv_rev, list_prod_inv_reverse Xs]
#align matrix.list_prod_inv_reverse Matrix.list_prod_inv_reverse
/-- One form of **Cramer's rule**. See `Matrix.mulVec_cramer` for a stronger form. -/
@[simp]
theorem det_smul_inv_mulVec_eq_cramer (A : Matrix n n α) (b : n → α) (h : IsUnit A.det) :
A.det • A⁻¹ *ᵥ b = cramer A b := by
rw [cramer_eq_adjugate_mulVec, A.nonsing_inv_apply h, ← smul_mulVec_assoc, smul_smul,
h.mul_val_inv, one_smul]
#align matrix.det_smul_inv_mul_vec_eq_cramer Matrix.det_smul_inv_mulVec_eq_cramer
/-- One form of **Cramer's rule**. See `Matrix.mulVec_cramer` for a stronger form. -/
@[simp]
theorem det_smul_inv_vecMul_eq_cramer_transpose (A : Matrix n n α) (b : n → α) (h : IsUnit A.det) :
A.det • b ᵥ* A⁻¹ = cramer Aᵀ b := by
rw [← A⁻¹.transpose_transpose, vecMul_transpose, transpose_nonsing_inv, ← det_transpose,
Aᵀ.det_smul_inv_mulVec_eq_cramer _ (isUnit_det_transpose A h)]
#align matrix.det_smul_inv_vec_mul_eq_cramer_transpose Matrix.det_smul_inv_vecMul_eq_cramer_transpose
/-! ### Inverses of permutated matrices
Note that the simp-normal form of `Matrix.reindex` is `Matrix.submatrix`, so we prove most of these
results about only the latter.
-/
section Submatrix
variable [Fintype m]
variable [DecidableEq m]
/-- `A.submatrix e₁ e₂` is invertible if `A` is -/
def submatrixEquivInvertible (A : Matrix m m α) (e₁ e₂ : n ≃ m) [Invertible A] :
Invertible (A.submatrix e₁ e₂) :=
invertibleOfRightInverse _ ((⅟ A).submatrix e₂ e₁) <| by
rw [Matrix.submatrix_mul_equiv, mul_invOf_self, submatrix_one_equiv]
#align matrix.submatrix_equiv_invertible Matrix.submatrixEquivInvertible
/-- `A` is invertible if `A.submatrix e₁ e₂` is -/
def invertibleOfSubmatrixEquivInvertible (A : Matrix m m α) (e₁ e₂ : n ≃ m)
[Invertible (A.submatrix e₁ e₂)] : Invertible A :=
invertibleOfRightInverse _ ((⅟ (A.submatrix e₁ e₂)).submatrix e₂.symm e₁.symm) <| by
have : A = (A.submatrix e₁ e₂).submatrix e₁.symm e₂.symm := by simp
-- Porting note: was
-- conv in _ * _ =>
-- congr
-- rw [this]
rw [congr_arg₂ (· * ·) this rfl]
rw [Matrix.submatrix_mul_equiv, mul_invOf_self, submatrix_one_equiv]
#align matrix.invertible_of_submatrix_equiv_invertible Matrix.invertibleOfSubmatrixEquivInvertible
theorem invOf_submatrix_equiv_eq (A : Matrix m m α) (e₁ e₂ : n ≃ m) [Invertible A]
[Invertible (A.submatrix e₁ e₂)] : ⅟ (A.submatrix e₁ e₂) = (⅟ A).submatrix e₂ e₁ := by
letI := submatrixEquivInvertible A e₁ e₂
-- Porting note: no longer need `haveI := Invertible.subsingleton (A.submatrix e₁ e₂)`
convert (rfl : ⅟ (A.submatrix e₁ e₂) = _)
#align matrix.inv_of_submatrix_equiv_eq Matrix.invOf_submatrix_equiv_eq
/-- Together `Matrix.submatrixEquivInvertible` and
`Matrix.invertibleOfSubmatrixEquivInvertible` form an equivalence, although both sides of the
equiv are subsingleton anyway. -/
@[simps]
def submatrixEquivInvertibleEquivInvertible (A : Matrix m m α) (e₁ e₂ : n ≃ m) :
Invertible (A.submatrix e₁ e₂) ≃ Invertible A where
toFun _ := invertibleOfSubmatrixEquivInvertible A e₁ e₂
invFun _ := submatrixEquivInvertible A e₁ e₂
left_inv _ := Subsingleton.elim _ _
right_inv _ := Subsingleton.elim _ _
#align matrix.submatrix_equiv_invertible_equiv_invertible Matrix.submatrixEquivInvertibleEquivInvertible
/-- When lowered to a prop, `Matrix.invertibleOfSubmatrixEquivInvertible` forms an `iff`. -/
@[simp]
theorem isUnit_submatrix_equiv {A : Matrix m m α} (e₁ e₂ : n ≃ m) :
IsUnit (A.submatrix e₁ e₂) ↔ IsUnit A := by
simp only [← nonempty_invertible_iff_isUnit,
(submatrixEquivInvertibleEquivInvertible A _ _).nonempty_congr]
#align matrix.is_unit_submatrix_equiv Matrix.isUnit_submatrix_equiv
@[simp]
theorem inv_submatrix_equiv (A : Matrix m m α) (e₁ e₂ : n ≃ m) :
(A.submatrix e₁ e₂)⁻¹ = A⁻¹.submatrix e₂ e₁ := by
by_cases h : IsUnit A
· cases h.nonempty_invertible
letI := submatrixEquivInvertible A e₁ e₂
rw [← invOf_eq_nonsing_inv, ← invOf_eq_nonsing_inv, invOf_submatrix_equiv_eq A]
· have := (isUnit_submatrix_equiv e₁ e₂).not.mpr h
simp_rw [nonsing_inv_eq_ring_inverse, Ring.inverse_non_unit _ h, Ring.inverse_non_unit _ this,
submatrix_zero, Pi.zero_apply]
#align matrix.inv_submatrix_equiv Matrix.inv_submatrix_equiv
theorem inv_reindex (e₁ e₂ : n ≃ m) (A : Matrix n n α) : (reindex e₁ e₂ A)⁻¹ = reindex e₂ e₁ A⁻¹ :=
inv_submatrix_equiv A e₁.symm e₂.symm
#align matrix.inv_reindex Matrix.inv_reindex
end Submatrix
/-! ### More results about determinants -/
section Det
variable [Fintype m] [DecidableEq m] [CommRing α]
/-- A variant of `Matrix.det_units_conj`. -/
| Mathlib/LinearAlgebra/Matrix/NonsingularInverse.lean | 797 | 798 | theorem det_conj {M : Matrix m m α} (h : IsUnit M) (N : Matrix m m α) :
det (M * N * M⁻¹) = det N := by | rw [← h.unit_spec, ← coe_units_inv, det_units_conj]
|
/-
Copyright (c) 2019 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel
-/
import Mathlib.Data.Complex.Module
import Mathlib.Data.Complex.Order
import Mathlib.Data.Complex.Exponential
import Mathlib.Analysis.RCLike.Basic
import Mathlib.Topology.Algebra.InfiniteSum.Module
import Mathlib.Topology.Instances.RealVectorSpace
#align_import analysis.complex.basic from "leanprover-community/mathlib"@"3f655f5297b030a87d641ad4e825af8d9679eb0b"
/-!
# Normed space structure on `ℂ`.
This file gathers basic facts on complex numbers of an analytic nature.
## Main results
This file registers `ℂ` as a normed field, expresses basic properties of the norm, and gives
tools on the real vector space structure of `ℂ`. Notably, in the namespace `Complex`,
it defines functions:
* `reCLM`
* `imCLM`
* `ofRealCLM`
* `conjCLE`
They are bundled versions of the real part, the imaginary part, the embedding of `ℝ` in `ℂ`, and
the complex conjugate as continuous `ℝ`-linear maps. The last two are also bundled as linear
isometries in `ofRealLI` and `conjLIE`.
We also register the fact that `ℂ` is an `RCLike` field.
-/
assert_not_exists Absorbs
noncomputable section
namespace Complex
variable {z : ℂ}
open ComplexConjugate Topology Filter
instance : Norm ℂ :=
⟨abs⟩
@[simp]
theorem norm_eq_abs (z : ℂ) : ‖z‖ = abs z :=
rfl
#align complex.norm_eq_abs Complex.norm_eq_abs
lemma norm_I : ‖I‖ = 1 := abs_I
theorem norm_exp_ofReal_mul_I (t : ℝ) : ‖exp (t * I)‖ = 1 := by
simp only [norm_eq_abs, abs_exp_ofReal_mul_I]
set_option linter.uppercaseLean3 false in
#align complex.norm_exp_of_real_mul_I Complex.norm_exp_ofReal_mul_I
instance instNormedAddCommGroup : NormedAddCommGroup ℂ :=
AddGroupNorm.toNormedAddCommGroup
{ abs with
map_zero' := map_zero abs
neg' := abs.map_neg
eq_zero_of_map_eq_zero' := fun _ => abs.eq_zero.1 }
instance : NormedField ℂ where
dist_eq _ _ := rfl
norm_mul' := map_mul abs
instance : DenselyNormedField ℂ where
lt_norm_lt r₁ r₂ h₀ hr :=
let ⟨x, h⟩ := exists_between hr
⟨x, by rwa [norm_eq_abs, abs_ofReal, abs_of_pos (h₀.trans_lt h.1)]⟩
instance {R : Type*} [NormedField R] [NormedAlgebra R ℝ] : NormedAlgebra R ℂ where
norm_smul_le r x := by
rw [← algebraMap_smul ℝ r x, real_smul, norm_mul, norm_eq_abs, abs_ofReal, ← Real.norm_eq_abs,
norm_algebraMap']
variable {E : Type*} [SeminormedAddCommGroup E] [NormedSpace ℂ E]
-- see Note [lower instance priority]
/-- The module structure from `Module.complexToReal` is a normed space. -/
instance (priority := 900) _root_.NormedSpace.complexToReal : NormedSpace ℝ E :=
NormedSpace.restrictScalars ℝ ℂ E
#align normed_space.complex_to_real NormedSpace.complexToReal
-- see Note [lower instance priority]
/-- The algebra structure from `Algebra.complexToReal` is a normed algebra. -/
instance (priority := 900) _root_.NormedAlgebra.complexToReal {A : Type*} [SeminormedRing A]
[NormedAlgebra ℂ A] : NormedAlgebra ℝ A :=
NormedAlgebra.restrictScalars ℝ ℂ A
theorem dist_eq (z w : ℂ) : dist z w = abs (z - w) :=
rfl
#align complex.dist_eq Complex.dist_eq
| Mathlib/Analysis/Complex/Basic.lean | 102 | 104 | theorem dist_eq_re_im (z w : ℂ) : dist z w = √((z.re - w.re) ^ 2 + (z.im - w.im) ^ 2) := by |
rw [sq, sq]
rfl
|
/-
Copyright (c) 2021 Kalle Kytölä. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kalle Kytölä
-/
import Mathlib.Topology.MetricSpace.HausdorffDistance
#align_import topology.metric_space.hausdorff_distance from "leanprover-community/mathlib"@"bc91ed7093bf098d253401e69df601fc33dde156"
/-!
# Thickenings in pseudo-metric spaces
## Main definitions
* `Metric.thickening δ s`, the open thickening by radius `δ` of a set `s` in a pseudo emetric space.
* `Metric.cthickening δ s`, the closed thickening by radius `δ` of a set `s` in a pseudo emetric
space.
## Main results
* `Disjoint.exists_thickenings`: two disjoint sets admit disjoint thickenings
* `Disjoint.exists_cthickenings`: two disjoint sets admit disjoint closed thickenings
* `IsCompact.exists_cthickening_subset_open`: if `s` is compact, `t` is open and `s ⊆ t`,
some `cthickening` of `s` is contained in `t`.
* `Metric.hasBasis_nhdsSet_cthickening`: the `cthickening`s of a compact set `K` form a basis
of the neighbourhoods of `K`
* `Metric.closure_eq_iInter_cthickening'`: the closure of a set equals the intersection
of its closed thickenings of positive radii accumulating at zero.
The same holds for open thickenings.
* `IsCompact.cthickening_eq_biUnion_closedBall`: if `s` is compact, `cthickening δ s` is the union
of `closedBall`s of radius `δ` around `x : E`.
-/
noncomputable section
open NNReal ENNReal Topology Set Filter Bornology
universe u v w
variable {ι : Sort*} {α : Type u} {β : Type v}
namespace Metric
section Thickening
variable [PseudoEMetricSpace α] {δ : ℝ} {s : Set α} {x : α}
open EMetric
/-- The (open) `δ`-thickening `Metric.thickening δ E` of a subset `E` in a pseudo emetric space
consists of those points that are at distance less than `δ` from some point of `E`. -/
def thickening (δ : ℝ) (E : Set α) : Set α :=
{ x : α | infEdist x E < ENNReal.ofReal δ }
#align metric.thickening Metric.thickening
theorem mem_thickening_iff_infEdist_lt : x ∈ thickening δ s ↔ infEdist x s < ENNReal.ofReal δ :=
Iff.rfl
#align metric.mem_thickening_iff_inf_edist_lt Metric.mem_thickening_iff_infEdist_lt
/-- An exterior point of a subset `E` (i.e., a point outside the closure of `E`) is not in the
(open) `δ`-thickening of `E` for small enough positive `δ`. -/
lemma eventually_not_mem_thickening_of_infEdist_pos {E : Set α} {x : α} (h : x ∉ closure E) :
∀ᶠ δ in 𝓝 (0 : ℝ), x ∉ Metric.thickening δ E := by
obtain ⟨ε, ⟨ε_pos, ε_lt⟩⟩ := exists_real_pos_lt_infEdist_of_not_mem_closure h
filter_upwards [eventually_lt_nhds ε_pos] with δ hδ
simp only [thickening, mem_setOf_eq, not_lt]
exact (ENNReal.ofReal_le_ofReal hδ.le).trans ε_lt.le
/-- The (open) thickening equals the preimage of an open interval under `EMetric.infEdist`. -/
theorem thickening_eq_preimage_infEdist (δ : ℝ) (E : Set α) :
thickening δ E = (infEdist · E) ⁻¹' Iio (ENNReal.ofReal δ) :=
rfl
#align metric.thickening_eq_preimage_inf_edist Metric.thickening_eq_preimage_infEdist
/-- The (open) thickening is an open set. -/
theorem isOpen_thickening {δ : ℝ} {E : Set α} : IsOpen (thickening δ E) :=
Continuous.isOpen_preimage continuous_infEdist _ isOpen_Iio
#align metric.is_open_thickening Metric.isOpen_thickening
/-- The (open) thickening of the empty set is empty. -/
@[simp]
theorem thickening_empty (δ : ℝ) : thickening δ (∅ : Set α) = ∅ := by
simp only [thickening, setOf_false, infEdist_empty, not_top_lt]
#align metric.thickening_empty Metric.thickening_empty
theorem thickening_of_nonpos (hδ : δ ≤ 0) (s : Set α) : thickening δ s = ∅ :=
eq_empty_of_forall_not_mem fun _ => ((ENNReal.ofReal_of_nonpos hδ).trans_le bot_le).not_lt
#align metric.thickening_of_nonpos Metric.thickening_of_nonpos
/-- The (open) thickening `Metric.thickening δ E` of a fixed subset `E` is an increasing function of
the thickening radius `δ`. -/
theorem thickening_mono {δ₁ δ₂ : ℝ} (hle : δ₁ ≤ δ₂) (E : Set α) :
thickening δ₁ E ⊆ thickening δ₂ E :=
preimage_mono (Iio_subset_Iio (ENNReal.ofReal_le_ofReal hle))
#align metric.thickening_mono Metric.thickening_mono
/-- The (open) thickening `Metric.thickening δ E` with a fixed thickening radius `δ` is
an increasing function of the subset `E`. -/
theorem thickening_subset_of_subset (δ : ℝ) {E₁ E₂ : Set α} (h : E₁ ⊆ E₂) :
thickening δ E₁ ⊆ thickening δ E₂ := fun _ hx => lt_of_le_of_lt (infEdist_anti h) hx
#align metric.thickening_subset_of_subset Metric.thickening_subset_of_subset
theorem mem_thickening_iff_exists_edist_lt {δ : ℝ} (E : Set α) (x : α) :
x ∈ thickening δ E ↔ ∃ z ∈ E, edist x z < ENNReal.ofReal δ :=
infEdist_lt_iff
#align metric.mem_thickening_iff_exists_edist_lt Metric.mem_thickening_iff_exists_edist_lt
/-- The frontier of the (open) thickening of a set is contained in an `EMetric.infEdist` level
set. -/
theorem frontier_thickening_subset (E : Set α) {δ : ℝ} :
frontier (thickening δ E) ⊆ { x : α | infEdist x E = ENNReal.ofReal δ } :=
frontier_lt_subset_eq continuous_infEdist continuous_const
#align metric.frontier_thickening_subset Metric.frontier_thickening_subset
theorem frontier_thickening_disjoint (A : Set α) :
Pairwise (Disjoint on fun r : ℝ => frontier (thickening r A)) := by
refine (pairwise_disjoint_on _).2 fun r₁ r₂ hr => ?_
rcases le_total r₁ 0 with h₁ | h₁
· simp [thickening_of_nonpos h₁]
refine ((disjoint_singleton.2 fun h => hr.ne ?_).preimage _).mono (frontier_thickening_subset _)
(frontier_thickening_subset _)
apply_fun ENNReal.toReal at h
rwa [ENNReal.toReal_ofReal h₁, ENNReal.toReal_ofReal (h₁.trans hr.le)] at h
#align metric.frontier_thickening_disjoint Metric.frontier_thickening_disjoint
/-- Any set is contained in the complement of the δ-thickening of the complement of its
δ-thickening. -/
lemma subset_compl_thickening_compl_thickening_self (δ : ℝ) (E : Set α) :
E ⊆ (thickening δ (thickening δ E)ᶜ)ᶜ := by
intro x x_in_E
simp only [thickening, mem_compl_iff, mem_setOf_eq, not_lt]
apply EMetric.le_infEdist.mpr fun y hy ↦ ?_
simp only [mem_compl_iff, mem_setOf_eq, not_lt] at hy
simpa only [edist_comm] using le_trans hy <| EMetric.infEdist_le_edist_of_mem x_in_E
/-- The δ-thickening of the complement of the δ-thickening of a set is contained in the complement
of the set. -/
lemma thickening_compl_thickening_self_subset_compl (δ : ℝ) (E : Set α) :
thickening δ (thickening δ E)ᶜ ⊆ Eᶜ := by
apply compl_subset_compl.mp
simpa only [compl_compl] using subset_compl_thickening_compl_thickening_self δ E
variable {X : Type u} [PseudoMetricSpace X]
-- Porting note (#10756): new lemma
theorem mem_thickening_iff_infDist_lt {E : Set X} {x : X} (h : E.Nonempty) :
x ∈ thickening δ E ↔ infDist x E < δ :=
lt_ofReal_iff_toReal_lt (infEdist_ne_top h)
/-- A point in a metric space belongs to the (open) `δ`-thickening of a subset `E` if and only if
it is at distance less than `δ` from some point of `E`. -/
theorem mem_thickening_iff {E : Set X} {x : X} : x ∈ thickening δ E ↔ ∃ z ∈ E, dist x z < δ := by
have key_iff : ∀ z : X, edist x z < ENNReal.ofReal δ ↔ dist x z < δ := fun z ↦ by
rw [dist_edist, lt_ofReal_iff_toReal_lt (edist_ne_top _ _)]
simp_rw [mem_thickening_iff_exists_edist_lt, key_iff]
#align metric.mem_thickening_iff Metric.mem_thickening_iff
@[simp]
theorem thickening_singleton (δ : ℝ) (x : X) : thickening δ ({x} : Set X) = ball x δ := by
ext
simp [mem_thickening_iff]
#align metric.thickening_singleton Metric.thickening_singleton
theorem ball_subset_thickening {x : X} {E : Set X} (hx : x ∈ E) (δ : ℝ) :
ball x δ ⊆ thickening δ E :=
Subset.trans (by simp [Subset.rfl]) (thickening_subset_of_subset δ <| singleton_subset_iff.mpr hx)
#align metric.ball_subset_thickening Metric.ball_subset_thickening
/-- The (open) `δ`-thickening `Metric.thickening δ E` of a subset `E` in a metric space equals the
union of balls of radius `δ` centered at points of `E`. -/
theorem thickening_eq_biUnion_ball {δ : ℝ} {E : Set X} : thickening δ E = ⋃ x ∈ E, ball x δ := by
ext x
simp only [mem_iUnion₂, exists_prop]
exact mem_thickening_iff
#align metric.thickening_eq_bUnion_ball Metric.thickening_eq_biUnion_ball
protected theorem _root_.Bornology.IsBounded.thickening {δ : ℝ} {E : Set X} (h : IsBounded E) :
IsBounded (thickening δ E) := by
rcases E.eq_empty_or_nonempty with rfl | ⟨x, hx⟩
· simp
· refine (isBounded_iff_subset_closedBall x).2 ⟨δ + diam E, fun y hy ↦ ?_⟩
calc
dist y x ≤ infDist y E + diam E := dist_le_infDist_add_diam (x := y) h hx
_ ≤ δ + diam E := add_le_add_right ((mem_thickening_iff_infDist_lt ⟨x, hx⟩).1 hy).le _
#align metric.bounded.thickening Bornology.IsBounded.thickening
end Thickening
section Cthickening
variable [PseudoEMetricSpace α] {δ ε : ℝ} {s t : Set α} {x : α}
open EMetric
/-- The closed `δ`-thickening `Metric.cthickening δ E` of a subset `E` in a pseudo emetric space
consists of those points that are at infimum distance at most `δ` from `E`. -/
def cthickening (δ : ℝ) (E : Set α) : Set α :=
{ x : α | infEdist x E ≤ ENNReal.ofReal δ }
#align metric.cthickening Metric.cthickening
@[simp]
theorem mem_cthickening_iff : x ∈ cthickening δ s ↔ infEdist x s ≤ ENNReal.ofReal δ :=
Iff.rfl
#align metric.mem_cthickening_iff Metric.mem_cthickening_iff
/-- An exterior point of a subset `E` (i.e., a point outside the closure of `E`) is not in the
closed `δ`-thickening of `E` for small enough positive `δ`. -/
lemma eventually_not_mem_cthickening_of_infEdist_pos {E : Set α} {x : α} (h : x ∉ closure E) :
∀ᶠ δ in 𝓝 (0 : ℝ), x ∉ Metric.cthickening δ E := by
obtain ⟨ε, ⟨ε_pos, ε_lt⟩⟩ := exists_real_pos_lt_infEdist_of_not_mem_closure h
filter_upwards [eventually_lt_nhds ε_pos] with δ hδ
simp only [cthickening, mem_setOf_eq, not_le]
exact ((ofReal_lt_ofReal_iff ε_pos).mpr hδ).trans ε_lt
theorem mem_cthickening_of_edist_le (x y : α) (δ : ℝ) (E : Set α) (h : y ∈ E)
(h' : edist x y ≤ ENNReal.ofReal δ) : x ∈ cthickening δ E :=
(infEdist_le_edist_of_mem h).trans h'
#align metric.mem_cthickening_of_edist_le Metric.mem_cthickening_of_edist_le
theorem mem_cthickening_of_dist_le {α : Type*} [PseudoMetricSpace α] (x y : α) (δ : ℝ) (E : Set α)
(h : y ∈ E) (h' : dist x y ≤ δ) : x ∈ cthickening δ E := by
apply mem_cthickening_of_edist_le x y δ E h
rw [edist_dist]
exact ENNReal.ofReal_le_ofReal h'
#align metric.mem_cthickening_of_dist_le Metric.mem_cthickening_of_dist_le
theorem cthickening_eq_preimage_infEdist (δ : ℝ) (E : Set α) :
cthickening δ E = (fun x => infEdist x E) ⁻¹' Iic (ENNReal.ofReal δ) :=
rfl
#align metric.cthickening_eq_preimage_inf_edist Metric.cthickening_eq_preimage_infEdist
/-- The closed thickening is a closed set. -/
theorem isClosed_cthickening {δ : ℝ} {E : Set α} : IsClosed (cthickening δ E) :=
IsClosed.preimage continuous_infEdist isClosed_Iic
#align metric.is_closed_cthickening Metric.isClosed_cthickening
/-- The closed thickening of the empty set is empty. -/
@[simp]
theorem cthickening_empty (δ : ℝ) : cthickening δ (∅ : Set α) = ∅ := by
simp only [cthickening, ENNReal.ofReal_ne_top, setOf_false, infEdist_empty, top_le_iff]
#align metric.cthickening_empty Metric.cthickening_empty
theorem cthickening_of_nonpos {δ : ℝ} (hδ : δ ≤ 0) (E : Set α) : cthickening δ E = closure E := by
ext x
simp [mem_closure_iff_infEdist_zero, cthickening, ENNReal.ofReal_eq_zero.2 hδ]
#align metric.cthickening_of_nonpos Metric.cthickening_of_nonpos
/-- The closed thickening with radius zero is the closure of the set. -/
@[simp]
theorem cthickening_zero (E : Set α) : cthickening 0 E = closure E :=
cthickening_of_nonpos le_rfl E
#align metric.cthickening_zero Metric.cthickening_zero
| Mathlib/Topology/MetricSpace/Thickening.lean | 253 | 254 | theorem cthickening_max_zero (δ : ℝ) (E : Set α) : cthickening (max 0 δ) E = cthickening δ E := by |
cases le_total δ 0 <;> simp [cthickening_of_nonpos, *]
|
/-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau
-/
import Mathlib.Algebra.Algebra.Operations
import Mathlib.Data.Fintype.Lattice
import Mathlib.RingTheory.Coprime.Lemmas
#align_import ring_theory.ideal.operations from "leanprover-community/mathlib"@"e7f0ddbf65bd7181a85edb74b64bdc35ba4bdc74"
/-!
# More operations on modules and ideals
-/
assert_not_exists Basis -- See `RingTheory.Ideal.Basis`
assert_not_exists Submodule.hasQuotient -- See `RingTheory.Ideal.QuotientOperations`
universe u v w x
open Pointwise
namespace Submodule
variable {R : Type u} {M : Type v} {M' F G : Type*}
section CommSemiring
variable [CommSemiring R] [AddCommMonoid M] [Module R M] [AddCommMonoid M'] [Module R M']
open Pointwise
instance hasSMul' : SMul (Ideal R) (Submodule R M) :=
⟨Submodule.map₂ (LinearMap.lsmul R M)⟩
#align submodule.has_smul' Submodule.hasSMul'
/-- This duplicates the global `smul_eq_mul`, but doesn't have to unfold anywhere near as much to
apply. -/
protected theorem _root_.Ideal.smul_eq_mul (I J : Ideal R) : I • J = I * J :=
rfl
#align ideal.smul_eq_mul Ideal.smul_eq_mul
variable (R M) in
/-- `Module.annihilator R M` is the ideal of all elements `r : R` such that `r • M = 0`. -/
def _root_.Module.annihilator : Ideal R := LinearMap.ker (LinearMap.lsmul R M)
theorem _root_.Module.mem_annihilator {r} : r ∈ Module.annihilator R M ↔ ∀ m : M, r • m = 0 :=
⟨fun h ↦ (congr($h ·)), (LinearMap.ext ·)⟩
theorem _root_.LinearMap.annihilator_le_of_injective (f : M →ₗ[R] M') (hf : Function.Injective f) :
Module.annihilator R M' ≤ Module.annihilator R M := fun x h ↦ by
rw [Module.mem_annihilator] at h ⊢; exact fun m ↦ hf (by rw [map_smul, h, f.map_zero])
theorem _root_.LinearMap.annihilator_le_of_surjective (f : M →ₗ[R] M')
(hf : Function.Surjective f) : Module.annihilator R M ≤ Module.annihilator R M' := fun x h ↦ by
rw [Module.mem_annihilator] at h ⊢
intro m; obtain ⟨m, rfl⟩ := hf m
rw [← map_smul, h, f.map_zero]
theorem _root_.LinearEquiv.annihilator_eq (e : M ≃ₗ[R] M') :
Module.annihilator R M = Module.annihilator R M' :=
(e.annihilator_le_of_surjective e.surjective).antisymm (e.annihilator_le_of_injective e.injective)
/-- `N.annihilator` is the ideal of all elements `r : R` such that `r • N = 0`. -/
abbrev annihilator (N : Submodule R M) : Ideal R :=
Module.annihilator R N
#align submodule.annihilator Submodule.annihilator
theorem annihilator_top : (⊤ : Submodule R M).annihilator = Module.annihilator R M :=
topEquiv.annihilator_eq
variable {I J : Ideal R} {N P : Submodule R M}
theorem mem_annihilator {r} : r ∈ N.annihilator ↔ ∀ n ∈ N, r • n = (0 : M) := by
simp_rw [annihilator, Module.mem_annihilator, Subtype.forall, Subtype.ext_iff]; rfl
#align submodule.mem_annihilator Submodule.mem_annihilator
theorem mem_annihilator' {r} : r ∈ N.annihilator ↔ N ≤ comap (r • (LinearMap.id : M →ₗ[R] M)) ⊥ :=
mem_annihilator.trans ⟨fun H n hn => (mem_bot R).2 <| H n hn, fun H _ hn => (mem_bot R).1 <| H hn⟩
#align submodule.mem_annihilator' Submodule.mem_annihilator'
theorem mem_annihilator_span (s : Set M) (r : R) :
r ∈ (Submodule.span R s).annihilator ↔ ∀ n : s, r • (n : M) = 0 := by
rw [Submodule.mem_annihilator]
constructor
· intro h n
exact h _ (Submodule.subset_span n.prop)
· intro h n hn
refine Submodule.span_induction hn ?_ ?_ ?_ ?_
· intro x hx
exact h ⟨x, hx⟩
· exact smul_zero _
· intro x y hx hy
rw [smul_add, hx, hy, zero_add]
· intro a x hx
rw [smul_comm, hx, smul_zero]
#align submodule.mem_annihilator_span Submodule.mem_annihilator_span
theorem mem_annihilator_span_singleton (g : M) (r : R) :
r ∈ (Submodule.span R ({g} : Set M)).annihilator ↔ r • g = 0 := by simp [mem_annihilator_span]
#align submodule.mem_annihilator_span_singleton Submodule.mem_annihilator_span_singleton
theorem annihilator_bot : (⊥ : Submodule R M).annihilator = ⊤ :=
(Ideal.eq_top_iff_one _).2 <| mem_annihilator'.2 bot_le
#align submodule.annihilator_bot Submodule.annihilator_bot
theorem annihilator_eq_top_iff : N.annihilator = ⊤ ↔ N = ⊥ :=
⟨fun H =>
eq_bot_iff.2 fun (n : M) hn =>
(mem_bot R).2 <| one_smul R n ▸ mem_annihilator.1 ((Ideal.eq_top_iff_one _).1 H) n hn,
fun H => H.symm ▸ annihilator_bot⟩
#align submodule.annihilator_eq_top_iff Submodule.annihilator_eq_top_iff
theorem annihilator_mono (h : N ≤ P) : P.annihilator ≤ N.annihilator := fun _ hrp =>
mem_annihilator.2 fun n hn => mem_annihilator.1 hrp n <| h hn
#align submodule.annihilator_mono Submodule.annihilator_mono
theorem annihilator_iSup (ι : Sort w) (f : ι → Submodule R M) :
annihilator (⨆ i, f i) = ⨅ i, annihilator (f i) :=
le_antisymm (le_iInf fun _ => annihilator_mono <| le_iSup _ _) fun _ H =>
mem_annihilator'.2 <|
iSup_le fun i =>
have := (mem_iInf _).1 H i
mem_annihilator'.1 this
#align submodule.annihilator_supr Submodule.annihilator_iSup
theorem smul_mem_smul {r} {n} (hr : r ∈ I) (hn : n ∈ N) : r • n ∈ I • N :=
apply_mem_map₂ _ hr hn
#align submodule.smul_mem_smul Submodule.smul_mem_smul
theorem smul_le {P : Submodule R M} : I • N ≤ P ↔ ∀ r ∈ I, ∀ n ∈ N, r • n ∈ P :=
map₂_le
#align submodule.smul_le Submodule.smul_le
@[simp, norm_cast]
lemma coe_set_smul : (I : Set R) • N = I • N :=
Submodule.set_smul_eq_of_le _ _ _
(fun _ _ hr hx => smul_mem_smul hr hx)
(smul_le.mpr fun _ hr _ hx => mem_set_smul_of_mem_mem hr hx)
@[elab_as_elim]
theorem smul_induction_on {p : M → Prop} {x} (H : x ∈ I • N) (smul : ∀ r ∈ I, ∀ n ∈ N, p (r • n))
(add : ∀ x y, p x → p y → p (x + y)) : p x := by
have H0 : p 0 := by simpa only [zero_smul] using smul 0 I.zero_mem 0 N.zero_mem
refine Submodule.iSup_induction (x := x) _ H ?_ H0 add
rintro ⟨i, hi⟩ m ⟨j, hj, hj'⟩
rw [← hj']
exact smul _ hi _ hj
#align submodule.smul_induction_on Submodule.smul_induction_on
/-- Dependent version of `Submodule.smul_induction_on`. -/
@[elab_as_elim]
theorem smul_induction_on' {x : M} (hx : x ∈ I • N) {p : ∀ x, x ∈ I • N → Prop}
(smul : ∀ (r : R) (hr : r ∈ I) (n : M) (hn : n ∈ N), p (r • n) (smul_mem_smul hr hn))
(add : ∀ x hx y hy, p x hx → p y hy → p (x + y) (Submodule.add_mem _ ‹_› ‹_›)) : p x hx := by
refine Exists.elim ?_ fun (h : x ∈ I • N) (H : p x h) => H
exact
smul_induction_on hx (fun a ha x hx => ⟨_, smul _ ha _ hx⟩) fun x y ⟨_, hx⟩ ⟨_, hy⟩ =>
⟨_, add _ _ _ _ hx hy⟩
#align submodule.smul_induction_on' Submodule.smul_induction_on'
theorem mem_smul_span_singleton {I : Ideal R} {m : M} {x : M} :
x ∈ I • span R ({m} : Set M) ↔ ∃ y ∈ I, y • m = x :=
⟨fun hx =>
smul_induction_on hx
(fun r hri n hnm =>
let ⟨s, hs⟩ := mem_span_singleton.1 hnm
⟨r * s, I.mul_mem_right _ hri, hs ▸ mul_smul r s m⟩)
fun m1 m2 ⟨y1, hyi1, hy1⟩ ⟨y2, hyi2, hy2⟩ =>
⟨y1 + y2, I.add_mem hyi1 hyi2, by rw [add_smul, hy1, hy2]⟩,
fun ⟨y, hyi, hy⟩ => hy ▸ smul_mem_smul hyi (subset_span <| Set.mem_singleton m)⟩
#align submodule.mem_smul_span_singleton Submodule.mem_smul_span_singleton
theorem smul_le_right : I • N ≤ N :=
smul_le.2 fun r _ _ => N.smul_mem r
#align submodule.smul_le_right Submodule.smul_le_right
theorem smul_mono (hij : I ≤ J) (hnp : N ≤ P) : I • N ≤ J • P :=
map₂_le_map₂ hij hnp
#align submodule.smul_mono Submodule.smul_mono
theorem smul_mono_left (h : I ≤ J) : I • N ≤ J • N :=
map₂_le_map₂_left h
#align submodule.smul_mono_left Submodule.smul_mono_left
instance : CovariantClass (Ideal R) (Submodule R M) HSMul.hSMul LE.le :=
⟨fun _ _ => map₂_le_map₂_right⟩
@[deprecated smul_mono_right (since := "2024-03-31")]
protected theorem smul_mono_right (h : N ≤ P) : I • N ≤ I • P :=
_root_.smul_mono_right I h
#align submodule.smul_mono_right Submodule.smul_mono_right
theorem map_le_smul_top (I : Ideal R) (f : R →ₗ[R] M) :
Submodule.map f I ≤ I • (⊤ : Submodule R M) := by
rintro _ ⟨y, hy, rfl⟩
rw [← mul_one y, ← smul_eq_mul, f.map_smul]
exact smul_mem_smul hy mem_top
#align submodule.map_le_smul_top Submodule.map_le_smul_top
@[simp]
theorem annihilator_smul (N : Submodule R M) : annihilator N • N = ⊥ :=
eq_bot_iff.2 (smul_le.2 fun _ => mem_annihilator.1)
#align submodule.annihilator_smul Submodule.annihilator_smul
@[simp]
theorem annihilator_mul (I : Ideal R) : annihilator I * I = ⊥ :=
annihilator_smul I
#align submodule.annihilator_mul Submodule.annihilator_mul
@[simp]
theorem mul_annihilator (I : Ideal R) : I * annihilator I = ⊥ := by rw [mul_comm, annihilator_mul]
#align submodule.mul_annihilator Submodule.mul_annihilator
variable (I J N P)
@[simp]
theorem smul_bot : I • (⊥ : Submodule R M) = ⊥ :=
map₂_bot_right _ _
#align submodule.smul_bot Submodule.smul_bot
@[simp]
theorem bot_smul : (⊥ : Ideal R) • N = ⊥ :=
map₂_bot_left _ _
#align submodule.bot_smul Submodule.bot_smul
@[simp]
theorem top_smul : (⊤ : Ideal R) • N = N :=
le_antisymm smul_le_right fun r hri => one_smul R r ▸ smul_mem_smul mem_top hri
#align submodule.top_smul Submodule.top_smul
theorem smul_sup : I • (N ⊔ P) = I • N ⊔ I • P :=
map₂_sup_right _ _ _ _
#align submodule.smul_sup Submodule.smul_sup
theorem sup_smul : (I ⊔ J) • N = I • N ⊔ J • N :=
map₂_sup_left _ _ _ _
#align submodule.sup_smul Submodule.sup_smul
protected theorem smul_assoc : (I • J) • N = I • J • N :=
le_antisymm
(smul_le.2 fun _ hrsij t htn =>
smul_induction_on hrsij
(fun r hr s hs =>
(@smul_eq_mul R _ r s).symm ▸ smul_smul r s t ▸ smul_mem_smul hr (smul_mem_smul hs htn))
fun x y => (add_smul x y t).symm ▸ Submodule.add_mem _)
(smul_le.2 fun r hr _ hsn =>
suffices J • N ≤ Submodule.comap (r • (LinearMap.id : M →ₗ[R] M)) ((I • J) • N) from this hsn
smul_le.2 fun s hs n hn =>
show r • s • n ∈ (I • J) • N from mul_smul r s n ▸ smul_mem_smul (smul_mem_smul hr hs) hn)
#align submodule.smul_assoc Submodule.smul_assoc
@[deprecated smul_inf_le (since := "2024-03-31")]
protected theorem smul_inf_le (M₁ M₂ : Submodule R M) :
I • (M₁ ⊓ M₂) ≤ I • M₁ ⊓ I • M₂ := smul_inf_le _ _ _
#align submodule.smul_inf_le Submodule.smul_inf_le
theorem smul_iSup {ι : Sort*} {I : Ideal R} {t : ι → Submodule R M} : I • iSup t = ⨆ i, I • t i :=
map₂_iSup_right _ _ _
#align submodule.smul_supr Submodule.smul_iSup
@[deprecated smul_iInf_le (since := "2024-03-31")]
protected theorem smul_iInf_le {ι : Sort*} {I : Ideal R} {t : ι → Submodule R M} :
I • iInf t ≤ ⨅ i, I • t i :=
smul_iInf_le
#align submodule.smul_infi_le Submodule.smul_iInf_le
variable (S : Set R) (T : Set M)
theorem span_smul_span : Ideal.span S • span R T = span R (⋃ (s ∈ S) (t ∈ T), {s • t}) :=
(map₂_span_span _ _ _ _).trans <| congr_arg _ <| Set.image2_eq_iUnion _ _ _
#align submodule.span_smul_span Submodule.span_smul_span
theorem ideal_span_singleton_smul (r : R) (N : Submodule R M) :
(Ideal.span {r} : Ideal R) • N = r • N := by
have : span R (⋃ (t : M) (_ : t ∈ N), {r • t}) = r • N := by
convert span_eq (r • N)
exact (Set.image_eq_iUnion _ (N : Set M)).symm
conv_lhs => rw [← span_eq N, span_smul_span]
simpa
#align submodule.ideal_span_singleton_smul Submodule.ideal_span_singleton_smul
theorem mem_of_span_top_of_smul_mem (M' : Submodule R M) (s : Set R) (hs : Ideal.span s = ⊤) (x : M)
(H : ∀ r : s, (r : R) • x ∈ M') : x ∈ M' := by
suffices (⊤ : Ideal R) • span R ({x} : Set M) ≤ M' by
rw [top_smul] at this
exact this (subset_span (Set.mem_singleton x))
rw [← hs, span_smul_span, span_le]
simpa using H
#align submodule.mem_of_span_top_of_smul_mem Submodule.mem_of_span_top_of_smul_mem
/-- Given `s`, a generating set of `R`, to check that an `x : M` falls in a
submodule `M'` of `x`, we only need to show that `r ^ n • x ∈ M'` for some `n` for each `r : s`. -/
theorem mem_of_span_eq_top_of_smul_pow_mem (M' : Submodule R M) (s : Set R) (hs : Ideal.span s = ⊤)
(x : M) (H : ∀ r : s, ∃ n : ℕ, ((r : R) ^ n : R) • x ∈ M') : x ∈ M' := by
obtain ⟨s', hs₁, hs₂⟩ := (Ideal.span_eq_top_iff_finite _).mp hs
replace H : ∀ r : s', ∃ n : ℕ, ((r : R) ^ n : R) • x ∈ M' := fun r => H ⟨_, hs₁ r.2⟩
choose n₁ n₂ using H
let N := s'.attach.sup n₁
have hs' := Ideal.span_pow_eq_top (s' : Set R) hs₂ N
apply M'.mem_of_span_top_of_smul_mem _ hs'
rintro ⟨_, r, hr, rfl⟩
convert M'.smul_mem (r ^ (N - n₁ ⟨r, hr⟩)) (n₂ ⟨r, hr⟩) using 1
simp only [Subtype.coe_mk, smul_smul, ← pow_add]
rw [tsub_add_cancel_of_le (Finset.le_sup (s'.mem_attach _) : n₁ ⟨r, hr⟩ ≤ N)]
#align submodule.mem_of_span_eq_top_of_smul_pow_mem Submodule.mem_of_span_eq_top_of_smul_pow_mem
variable {M' : Type w} [AddCommMonoid M'] [Module R M']
@[simp]
theorem map_smul'' (f : M →ₗ[R] M') : (I • N).map f = I • N.map f :=
le_antisymm
(map_le_iff_le_comap.2 <|
smul_le.2 fun r hr n hn =>
show f (r • n) ∈ I • N.map f from
(f.map_smul r n).symm ▸ smul_mem_smul hr (mem_map_of_mem hn)) <|
smul_le.2 fun r hr _ hn =>
let ⟨p, hp, hfp⟩ := mem_map.1 hn
hfp ▸ f.map_smul r p ▸ mem_map_of_mem (smul_mem_smul hr hp)
#align submodule.map_smul'' Submodule.map_smul''
open Pointwise in
@[simp]
theorem map_pointwise_smul (r : R) (N : Submodule R M) (f : M →ₗ[R] M') :
(r • N).map f = r • N.map f := by
simp_rw [← ideal_span_singleton_smul, map_smul'']
variable {I}
theorem mem_smul_span {s : Set M} {x : M} :
x ∈ I • Submodule.span R s ↔ x ∈ Submodule.span R (⋃ (a ∈ I) (b ∈ s), ({a • b} : Set M)) := by
rw [← I.span_eq, Submodule.span_smul_span, I.span_eq]
rfl
#align submodule.mem_smul_span Submodule.mem_smul_span
variable (I)
/-- If `x` is an `I`-multiple of the submodule spanned by `f '' s`,
then we can write `x` as an `I`-linear combination of the elements of `f '' s`. -/
theorem mem_ideal_smul_span_iff_exists_sum {ι : Type*} (f : ι → M) (x : M) :
x ∈ I • span R (Set.range f) ↔
∃ (a : ι →₀ R) (_ : ∀ i, a i ∈ I), (a.sum fun i c => c • f i) = x := by
constructor; swap
· rintro ⟨a, ha, rfl⟩
exact Submodule.sum_mem _ fun c _ => smul_mem_smul (ha c) <| subset_span <| Set.mem_range_self _
refine fun hx => span_induction (mem_smul_span.mp hx) ?_ ?_ ?_ ?_
· simp only [Set.mem_iUnion, Set.mem_range, Set.mem_singleton_iff]
rintro x ⟨y, hy, x, ⟨i, rfl⟩, rfl⟩
refine ⟨Finsupp.single i y, fun j => ?_, ?_⟩
· letI := Classical.decEq ι
rw [Finsupp.single_apply]
split_ifs
· assumption
· exact I.zero_mem
refine @Finsupp.sum_single_index ι R M _ _ i _ (fun i y => y • f i) ?_
simp
· exact ⟨0, fun _ => I.zero_mem, Finsupp.sum_zero_index⟩
· rintro x y ⟨ax, hax, rfl⟩ ⟨ay, hay, rfl⟩
refine ⟨ax + ay, fun i => I.add_mem (hax i) (hay i), Finsupp.sum_add_index' ?_ ?_⟩ <;>
intros <;> simp only [zero_smul, add_smul]
· rintro c x ⟨a, ha, rfl⟩
refine ⟨c • a, fun i => I.mul_mem_left c (ha i), ?_⟩
rw [Finsupp.sum_smul_index, Finsupp.smul_sum] <;> intros <;> simp only [zero_smul, mul_smul]
#align submodule.mem_ideal_smul_span_iff_exists_sum Submodule.mem_ideal_smul_span_iff_exists_sum
theorem mem_ideal_smul_span_iff_exists_sum' {ι : Type*} (s : Set ι) (f : ι → M) (x : M) :
x ∈ I • span R (f '' s) ↔
∃ (a : s →₀ R) (_ : ∀ i, a i ∈ I), (a.sum fun i c => c • f i) = x := by
rw [← Submodule.mem_ideal_smul_span_iff_exists_sum, ← Set.image_eq_range]
#align submodule.mem_ideal_smul_span_iff_exists_sum' Submodule.mem_ideal_smul_span_iff_exists_sum'
theorem mem_smul_top_iff (N : Submodule R M) (x : N) :
x ∈ I • (⊤ : Submodule R N) ↔ (x : M) ∈ I • N := by
change _ ↔ N.subtype x ∈ I • N
have : Submodule.map N.subtype (I • ⊤) = I • N := by
rw [Submodule.map_smul'', Submodule.map_top, Submodule.range_subtype]
rw [← this]
exact (Function.Injective.mem_set_image N.injective_subtype).symm
#align submodule.mem_smul_top_iff Submodule.mem_smul_top_iff
@[simp]
theorem smul_comap_le_comap_smul (f : M →ₗ[R] M') (S : Submodule R M') (I : Ideal R) :
I • S.comap f ≤ (I • S).comap f := by
refine Submodule.smul_le.mpr fun r hr x hx => ?_
rw [Submodule.mem_comap] at hx ⊢
rw [f.map_smul]
exact Submodule.smul_mem_smul hr hx
#align submodule.smul_comap_le_comap_smul Submodule.smul_comap_le_comap_smul
end CommSemiring
end Submodule
namespace Ideal
section Add
variable {R : Type u} [Semiring R]
@[simp]
theorem add_eq_sup {I J : Ideal R} : I + J = I ⊔ J :=
rfl
#align ideal.add_eq_sup Ideal.add_eq_sup
@[simp]
theorem zero_eq_bot : (0 : Ideal R) = ⊥ :=
rfl
#align ideal.zero_eq_bot Ideal.zero_eq_bot
@[simp]
theorem sum_eq_sup {ι : Type*} (s : Finset ι) (f : ι → Ideal R) : s.sum f = s.sup f :=
rfl
#align ideal.sum_eq_sup Ideal.sum_eq_sup
end Add
section MulAndRadical
variable {R : Type u} {ι : Type*} [CommSemiring R]
variable {I J K L : Ideal R}
instance : Mul (Ideal R) :=
⟨(· • ·)⟩
@[simp]
| Mathlib/RingTheory/Ideal/Operations.lean | 426 | 426 | theorem one_eq_top : (1 : Ideal R) = ⊤ := by | erw [Submodule.one_eq_range, LinearMap.range_id]
|
/-
Copyright (c) 2022 Joseph Myers. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joseph Myers
-/
import Mathlib.Geometry.Euclidean.Angle.Oriented.Affine
import Mathlib.Geometry.Euclidean.Angle.Unoriented.RightAngle
#align_import geometry.euclidean.angle.oriented.right_angle from "leanprover-community/mathlib"@"46b633fd842bef9469441c0209906f6dddd2b4f5"
/-!
# Oriented angles in right-angled triangles.
This file proves basic geometrical results about distances and oriented angles in (possibly
degenerate) right-angled triangles in real inner product spaces and Euclidean affine spaces.
-/
noncomputable section
open scoped EuclideanGeometry
open scoped Real
open scoped RealInnerProductSpace
namespace Orientation
open FiniteDimensional
variable {V : Type*} [NormedAddCommGroup V] [InnerProductSpace ℝ V]
variable [hd2 : Fact (finrank ℝ V = 2)] (o : Orientation ℝ V (Fin 2))
/-- An angle in a right-angled triangle expressed using `arccos`. -/
theorem oangle_add_right_eq_arccos_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
o.oangle x (x + y) = Real.arccos (‖x‖ / ‖x + y‖) := by
have hs : (o.oangle x (x + y)).sign = 1 := by
rw [oangle_sign_add_right, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs,
InnerProductGeometry.angle_add_eq_arccos_of_inner_eq_zero
(o.inner_eq_zero_of_oangle_eq_pi_div_two h)]
#align orientation.oangle_add_right_eq_arccos_of_oangle_eq_pi_div_two Orientation.oangle_add_right_eq_arccos_of_oangle_eq_pi_div_two
/-- An angle in a right-angled triangle expressed using `arccos`. -/
theorem oangle_add_left_eq_arccos_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
o.oangle (x + y) y = Real.arccos (‖y‖ / ‖x + y‖) := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
rw [add_comm]
exact (-o).oangle_add_right_eq_arccos_of_oangle_eq_pi_div_two h
#align orientation.oangle_add_left_eq_arccos_of_oangle_eq_pi_div_two Orientation.oangle_add_left_eq_arccos_of_oangle_eq_pi_div_two
/-- An angle in a right-angled triangle expressed using `arcsin`. -/
theorem oangle_add_right_eq_arcsin_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
o.oangle x (x + y) = Real.arcsin (‖y‖ / ‖x + y‖) := by
have hs : (o.oangle x (x + y)).sign = 1 := by
rw [oangle_sign_add_right, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs,
InnerProductGeometry.angle_add_eq_arcsin_of_inner_eq_zero
(o.inner_eq_zero_of_oangle_eq_pi_div_two h)
(Or.inl (o.left_ne_zero_of_oangle_eq_pi_div_two h))]
#align orientation.oangle_add_right_eq_arcsin_of_oangle_eq_pi_div_two Orientation.oangle_add_right_eq_arcsin_of_oangle_eq_pi_div_two
/-- An angle in a right-angled triangle expressed using `arcsin`. -/
theorem oangle_add_left_eq_arcsin_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
o.oangle (x + y) y = Real.arcsin (‖x‖ / ‖x + y‖) := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
rw [add_comm]
exact (-o).oangle_add_right_eq_arcsin_of_oangle_eq_pi_div_two h
#align orientation.oangle_add_left_eq_arcsin_of_oangle_eq_pi_div_two Orientation.oangle_add_left_eq_arcsin_of_oangle_eq_pi_div_two
/-- An angle in a right-angled triangle expressed using `arctan`. -/
theorem oangle_add_right_eq_arctan_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
o.oangle x (x + y) = Real.arctan (‖y‖ / ‖x‖) := by
have hs : (o.oangle x (x + y)).sign = 1 := by
rw [oangle_sign_add_right, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs,
InnerProductGeometry.angle_add_eq_arctan_of_inner_eq_zero
(o.inner_eq_zero_of_oangle_eq_pi_div_two h) (o.left_ne_zero_of_oangle_eq_pi_div_two h)]
#align orientation.oangle_add_right_eq_arctan_of_oangle_eq_pi_div_two Orientation.oangle_add_right_eq_arctan_of_oangle_eq_pi_div_two
/-- An angle in a right-angled triangle expressed using `arctan`. -/
theorem oangle_add_left_eq_arctan_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
o.oangle (x + y) y = Real.arctan (‖x‖ / ‖y‖) := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
rw [add_comm]
exact (-o).oangle_add_right_eq_arctan_of_oangle_eq_pi_div_two h
#align orientation.oangle_add_left_eq_arctan_of_oangle_eq_pi_div_two Orientation.oangle_add_left_eq_arctan_of_oangle_eq_pi_div_two
/-- The cosine of an angle in a right-angled triangle as a ratio of sides. -/
theorem cos_oangle_add_right_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
Real.Angle.cos (o.oangle x (x + y)) = ‖x‖ / ‖x + y‖ := by
have hs : (o.oangle x (x + y)).sign = 1 := by
rw [oangle_sign_add_right, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs, Real.Angle.cos_coe,
InnerProductGeometry.cos_angle_add_of_inner_eq_zero (o.inner_eq_zero_of_oangle_eq_pi_div_two h)]
#align orientation.cos_oangle_add_right_of_oangle_eq_pi_div_two Orientation.cos_oangle_add_right_of_oangle_eq_pi_div_two
/-- The cosine of an angle in a right-angled triangle as a ratio of sides. -/
theorem cos_oangle_add_left_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
Real.Angle.cos (o.oangle (x + y) y) = ‖y‖ / ‖x + y‖ := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
rw [add_comm]
exact (-o).cos_oangle_add_right_of_oangle_eq_pi_div_two h
#align orientation.cos_oangle_add_left_of_oangle_eq_pi_div_two Orientation.cos_oangle_add_left_of_oangle_eq_pi_div_two
/-- The sine of an angle in a right-angled triangle as a ratio of sides. -/
theorem sin_oangle_add_right_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
Real.Angle.sin (o.oangle x (x + y)) = ‖y‖ / ‖x + y‖ := by
have hs : (o.oangle x (x + y)).sign = 1 := by
rw [oangle_sign_add_right, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs, Real.Angle.sin_coe,
InnerProductGeometry.sin_angle_add_of_inner_eq_zero (o.inner_eq_zero_of_oangle_eq_pi_div_two h)
(Or.inl (o.left_ne_zero_of_oangle_eq_pi_div_two h))]
#align orientation.sin_oangle_add_right_of_oangle_eq_pi_div_two Orientation.sin_oangle_add_right_of_oangle_eq_pi_div_two
/-- The sine of an angle in a right-angled triangle as a ratio of sides. -/
theorem sin_oangle_add_left_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
Real.Angle.sin (o.oangle (x + y) y) = ‖x‖ / ‖x + y‖ := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
rw [add_comm]
exact (-o).sin_oangle_add_right_of_oangle_eq_pi_div_two h
#align orientation.sin_oangle_add_left_of_oangle_eq_pi_div_two Orientation.sin_oangle_add_left_of_oangle_eq_pi_div_two
/-- The tangent of an angle in a right-angled triangle as a ratio of sides. -/
theorem tan_oangle_add_right_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
Real.Angle.tan (o.oangle x (x + y)) = ‖y‖ / ‖x‖ := by
have hs : (o.oangle x (x + y)).sign = 1 := by
rw [oangle_sign_add_right, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs, Real.Angle.tan_coe,
InnerProductGeometry.tan_angle_add_of_inner_eq_zero (o.inner_eq_zero_of_oangle_eq_pi_div_two h)]
#align orientation.tan_oangle_add_right_of_oangle_eq_pi_div_two Orientation.tan_oangle_add_right_of_oangle_eq_pi_div_two
/-- The tangent of an angle in a right-angled triangle as a ratio of sides. -/
theorem tan_oangle_add_left_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = ↑(π / 2)) :
Real.Angle.tan (o.oangle (x + y) y) = ‖x‖ / ‖y‖ := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
rw [add_comm]
exact (-o).tan_oangle_add_right_of_oangle_eq_pi_div_two h
#align orientation.tan_oangle_add_left_of_oangle_eq_pi_div_two Orientation.tan_oangle_add_left_of_oangle_eq_pi_div_two
/-- The cosine of an angle in a right-angled triangle multiplied by the hypotenuse equals the
adjacent side. -/
theorem cos_oangle_add_right_mul_norm_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : Real.Angle.cos (o.oangle x (x + y)) * ‖x + y‖ = ‖x‖ := by
have hs : (o.oangle x (x + y)).sign = 1 := by
rw [oangle_sign_add_right, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs, Real.Angle.cos_coe,
InnerProductGeometry.cos_angle_add_mul_norm_of_inner_eq_zero
(o.inner_eq_zero_of_oangle_eq_pi_div_two h)]
#align orientation.cos_oangle_add_right_mul_norm_of_oangle_eq_pi_div_two Orientation.cos_oangle_add_right_mul_norm_of_oangle_eq_pi_div_two
/-- The cosine of an angle in a right-angled triangle multiplied by the hypotenuse equals the
adjacent side. -/
theorem cos_oangle_add_left_mul_norm_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : Real.Angle.cos (o.oangle (x + y) y) * ‖x + y‖ = ‖y‖ := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
rw [add_comm]
exact (-o).cos_oangle_add_right_mul_norm_of_oangle_eq_pi_div_two h
#align orientation.cos_oangle_add_left_mul_norm_of_oangle_eq_pi_div_two Orientation.cos_oangle_add_left_mul_norm_of_oangle_eq_pi_div_two
/-- The sine of an angle in a right-angled triangle multiplied by the hypotenuse equals the
opposite side. -/
theorem sin_oangle_add_right_mul_norm_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : Real.Angle.sin (o.oangle x (x + y)) * ‖x + y‖ = ‖y‖ := by
have hs : (o.oangle x (x + y)).sign = 1 := by
rw [oangle_sign_add_right, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs, Real.Angle.sin_coe,
InnerProductGeometry.sin_angle_add_mul_norm_of_inner_eq_zero
(o.inner_eq_zero_of_oangle_eq_pi_div_two h)]
#align orientation.sin_oangle_add_right_mul_norm_of_oangle_eq_pi_div_two Orientation.sin_oangle_add_right_mul_norm_of_oangle_eq_pi_div_two
/-- The sine of an angle in a right-angled triangle multiplied by the hypotenuse equals the
opposite side. -/
theorem sin_oangle_add_left_mul_norm_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : Real.Angle.sin (o.oangle (x + y) y) * ‖x + y‖ = ‖x‖ := by
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
rw [add_comm]
exact (-o).sin_oangle_add_right_mul_norm_of_oangle_eq_pi_div_two h
#align orientation.sin_oangle_add_left_mul_norm_of_oangle_eq_pi_div_two Orientation.sin_oangle_add_left_mul_norm_of_oangle_eq_pi_div_two
/-- The tangent of an angle in a right-angled triangle multiplied by the adjacent side equals
the opposite side. -/
theorem tan_oangle_add_right_mul_norm_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : Real.Angle.tan (o.oangle x (x + y)) * ‖x‖ = ‖y‖ := by
have hs : (o.oangle x (x + y)).sign = 1 := by
rw [oangle_sign_add_right, h, Real.Angle.sign_coe_pi_div_two]
rw [o.oangle_eq_angle_of_sign_eq_one hs, Real.Angle.tan_coe,
InnerProductGeometry.tan_angle_add_mul_norm_of_inner_eq_zero
(o.inner_eq_zero_of_oangle_eq_pi_div_two h)
(Or.inl (o.left_ne_zero_of_oangle_eq_pi_div_two h))]
#align orientation.tan_oangle_add_right_mul_norm_of_oangle_eq_pi_div_two Orientation.tan_oangle_add_right_mul_norm_of_oangle_eq_pi_div_two
/-- The tangent of an angle in a right-angled triangle multiplied by the adjacent side equals
the opposite side. -/
| Mathlib/Geometry/Euclidean/Angle/Oriented/RightAngle.lean | 196 | 200 | theorem tan_oangle_add_left_mul_norm_of_oangle_eq_pi_div_two {x y : V}
(h : o.oangle x y = ↑(π / 2)) : Real.Angle.tan (o.oangle (x + y) y) * ‖y‖ = ‖x‖ := by |
rw [← neg_inj, oangle_rev, ← oangle_neg_orientation_eq_neg, neg_inj] at h ⊢
rw [add_comm]
exact (-o).tan_oangle_add_right_mul_norm_of_oangle_eq_pi_div_two h
|
/-
Copyright (c) 2019 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Floris van Doorn
-/
import Mathlib.Analysis.Calculus.ContDiff.Defs
import Mathlib.Analysis.Calculus.FDeriv.Add
import Mathlib.Analysis.Calculus.FDeriv.Mul
import Mathlib.Analysis.Calculus.Deriv.Inverse
#align_import analysis.calculus.cont_diff from "leanprover-community/mathlib"@"3bce8d800a6f2b8f63fe1e588fd76a9ff4adcebe"
/-!
# Higher differentiability of usual operations
We prove that the usual operations (addition, multiplication, difference, composition, and
so on) preserve `C^n` functions. We also expand the API around `C^n` functions.
## Main results
* `ContDiff.comp` states that the composition of two `C^n` functions is `C^n`.
Similar results are given for `C^n` functions on domains.
## Notations
We use the notation `E [×n]→L[𝕜] F` for the space of continuous multilinear maps on `E^n` with
values in `F`. This is the space in which the `n`-th derivative of a function from `E` to `F` lives.
In this file, we denote `⊤ : ℕ∞` with `∞`.
## Tags
derivative, differentiability, higher derivative, `C^n`, multilinear, Taylor series, formal series
-/
noncomputable section
open scoped Classical NNReal Nat
local notation "∞" => (⊤ : ℕ∞)
universe u v w uD uE uF uG
attribute [local instance 1001]
NormedAddCommGroup.toAddCommGroup NormedSpace.toModule' AddCommGroup.toAddCommMonoid
open Set Fin Filter Function
open scoped Topology
variable {𝕜 : Type*} [NontriviallyNormedField 𝕜] {D : Type uD} [NormedAddCommGroup D]
[NormedSpace 𝕜 D] {E : Type uE} [NormedAddCommGroup E] [NormedSpace 𝕜 E] {F : Type uF}
[NormedAddCommGroup F] [NormedSpace 𝕜 F] {G : Type uG} [NormedAddCommGroup G] [NormedSpace 𝕜 G]
{X : Type*} [NormedAddCommGroup X] [NormedSpace 𝕜 X] {s s₁ t u : Set E} {f f₁ : E → F}
{g : F → G} {x x₀ : E} {c : F} {b : E × F → G} {m n : ℕ∞} {p : E → FormalMultilinearSeries 𝕜 E F}
/-! ### Constants -/
@[simp]
theorem iteratedFDerivWithin_zero_fun (hs : UniqueDiffOn 𝕜 s) (hx : x ∈ s) {i : ℕ} :
iteratedFDerivWithin 𝕜 i (fun _ : E ↦ (0 : F)) s x = 0 := by
induction i generalizing x with
| zero => ext; simp
| succ i IH =>
ext m
rw [iteratedFDerivWithin_succ_apply_left, fderivWithin_congr (fun _ ↦ IH) (IH hx)]
rw [fderivWithin_const_apply _ (hs x hx)]
rfl
@[simp]
theorem iteratedFDeriv_zero_fun {n : ℕ} : (iteratedFDeriv 𝕜 n fun _ : E ↦ (0 : F)) = 0 :=
funext fun x ↦ by simpa [← iteratedFDerivWithin_univ] using
iteratedFDerivWithin_zero_fun uniqueDiffOn_univ (mem_univ x)
#align iterated_fderiv_zero_fun iteratedFDeriv_zero_fun
theorem contDiff_zero_fun : ContDiff 𝕜 n fun _ : E => (0 : F) :=
contDiff_of_differentiable_iteratedFDeriv fun m _ => by
rw [iteratedFDeriv_zero_fun]
exact differentiable_const (0 : E[×m]→L[𝕜] F)
#align cont_diff_zero_fun contDiff_zero_fun
/-- Constants are `C^∞`.
-/
theorem contDiff_const {c : F} : ContDiff 𝕜 n fun _ : E => c := by
suffices h : ContDiff 𝕜 ∞ fun _ : E => c from h.of_le le_top
rw [contDiff_top_iff_fderiv]
refine ⟨differentiable_const c, ?_⟩
rw [fderiv_const]
exact contDiff_zero_fun
#align cont_diff_const contDiff_const
theorem contDiffOn_const {c : F} {s : Set E} : ContDiffOn 𝕜 n (fun _ : E => c) s :=
contDiff_const.contDiffOn
#align cont_diff_on_const contDiffOn_const
theorem contDiffAt_const {c : F} : ContDiffAt 𝕜 n (fun _ : E => c) x :=
contDiff_const.contDiffAt
#align cont_diff_at_const contDiffAt_const
theorem contDiffWithinAt_const {c : F} : ContDiffWithinAt 𝕜 n (fun _ : E => c) s x :=
contDiffAt_const.contDiffWithinAt
#align cont_diff_within_at_const contDiffWithinAt_const
@[nontriviality]
theorem contDiff_of_subsingleton [Subsingleton F] : ContDiff 𝕜 n f := by
rw [Subsingleton.elim f fun _ => 0]; exact contDiff_const
#align cont_diff_of_subsingleton contDiff_of_subsingleton
@[nontriviality]
theorem contDiffAt_of_subsingleton [Subsingleton F] : ContDiffAt 𝕜 n f x := by
rw [Subsingleton.elim f fun _ => 0]; exact contDiffAt_const
#align cont_diff_at_of_subsingleton contDiffAt_of_subsingleton
@[nontriviality]
theorem contDiffWithinAt_of_subsingleton [Subsingleton F] : ContDiffWithinAt 𝕜 n f s x := by
rw [Subsingleton.elim f fun _ => 0]; exact contDiffWithinAt_const
#align cont_diff_within_at_of_subsingleton contDiffWithinAt_of_subsingleton
@[nontriviality]
theorem contDiffOn_of_subsingleton [Subsingleton F] : ContDiffOn 𝕜 n f s := by
rw [Subsingleton.elim f fun _ => 0]; exact contDiffOn_const
#align cont_diff_on_of_subsingleton contDiffOn_of_subsingleton
theorem iteratedFDerivWithin_succ_const (n : ℕ) (c : F) (hs : UniqueDiffOn 𝕜 s) (hx : x ∈ s) :
iteratedFDerivWithin 𝕜 (n + 1) (fun _ : E ↦ c) s x = 0 := by
ext m
rw [iteratedFDerivWithin_succ_apply_right hs hx]
rw [iteratedFDerivWithin_congr (fun y hy ↦ fderivWithin_const_apply c (hs y hy)) hx]
rw [iteratedFDerivWithin_zero_fun hs hx]
simp [ContinuousMultilinearMap.zero_apply (R := 𝕜)]
theorem iteratedFDeriv_succ_const (n : ℕ) (c : F) :
(iteratedFDeriv 𝕜 (n + 1) fun _ : E ↦ c) = 0 :=
funext fun x ↦ by simpa [← iteratedFDerivWithin_univ] using
iteratedFDerivWithin_succ_const n c uniqueDiffOn_univ (mem_univ x)
#align iterated_fderiv_succ_const iteratedFDeriv_succ_const
theorem iteratedFDerivWithin_const_of_ne {n : ℕ} (hn : n ≠ 0) (c : F)
(hs : UniqueDiffOn 𝕜 s) (hx : x ∈ s) :
iteratedFDerivWithin 𝕜 n (fun _ : E ↦ c) s x = 0 := by
cases n with
| zero => contradiction
| succ n => exact iteratedFDerivWithin_succ_const n c hs hx
theorem iteratedFDeriv_const_of_ne {n : ℕ} (hn : n ≠ 0) (c : F) :
(iteratedFDeriv 𝕜 n fun _ : E ↦ c) = 0 :=
funext fun x ↦ by simpa [← iteratedFDerivWithin_univ] using
iteratedFDerivWithin_const_of_ne hn c uniqueDiffOn_univ (mem_univ x)
#align iterated_fderiv_const_of_ne iteratedFDeriv_const_of_ne
/-! ### Smoothness of linear functions -/
/-- Unbundled bounded linear functions are `C^∞`.
-/
theorem IsBoundedLinearMap.contDiff (hf : IsBoundedLinearMap 𝕜 f) : ContDiff 𝕜 n f := by
suffices h : ContDiff 𝕜 ∞ f from h.of_le le_top
rw [contDiff_top_iff_fderiv]
refine ⟨hf.differentiable, ?_⟩
simp_rw [hf.fderiv]
exact contDiff_const
#align is_bounded_linear_map.cont_diff IsBoundedLinearMap.contDiff
theorem ContinuousLinearMap.contDiff (f : E →L[𝕜] F) : ContDiff 𝕜 n f :=
f.isBoundedLinearMap.contDiff
#align continuous_linear_map.cont_diff ContinuousLinearMap.contDiff
theorem ContinuousLinearEquiv.contDiff (f : E ≃L[𝕜] F) : ContDiff 𝕜 n f :=
(f : E →L[𝕜] F).contDiff
#align continuous_linear_equiv.cont_diff ContinuousLinearEquiv.contDiff
theorem LinearIsometry.contDiff (f : E →ₗᵢ[𝕜] F) : ContDiff 𝕜 n f :=
f.toContinuousLinearMap.contDiff
#align linear_isometry.cont_diff LinearIsometry.contDiff
theorem LinearIsometryEquiv.contDiff (f : E ≃ₗᵢ[𝕜] F) : ContDiff 𝕜 n f :=
(f : E →L[𝕜] F).contDiff
#align linear_isometry_equiv.cont_diff LinearIsometryEquiv.contDiff
/-- The identity is `C^∞`.
-/
theorem contDiff_id : ContDiff 𝕜 n (id : E → E) :=
IsBoundedLinearMap.id.contDiff
#align cont_diff_id contDiff_id
theorem contDiffWithinAt_id {s x} : ContDiffWithinAt 𝕜 n (id : E → E) s x :=
contDiff_id.contDiffWithinAt
#align cont_diff_within_at_id contDiffWithinAt_id
theorem contDiffAt_id {x} : ContDiffAt 𝕜 n (id : E → E) x :=
contDiff_id.contDiffAt
#align cont_diff_at_id contDiffAt_id
theorem contDiffOn_id {s} : ContDiffOn 𝕜 n (id : E → E) s :=
contDiff_id.contDiffOn
#align cont_diff_on_id contDiffOn_id
/-- Bilinear functions are `C^∞`.
-/
theorem IsBoundedBilinearMap.contDiff (hb : IsBoundedBilinearMap 𝕜 b) : ContDiff 𝕜 n b := by
suffices h : ContDiff 𝕜 ∞ b from h.of_le le_top
rw [contDiff_top_iff_fderiv]
refine ⟨hb.differentiable, ?_⟩
simp only [hb.fderiv]
exact hb.isBoundedLinearMap_deriv.contDiff
#align is_bounded_bilinear_map.cont_diff IsBoundedBilinearMap.contDiff
/-- If `f` admits a Taylor series `p` in a set `s`, and `g` is linear, then `g ∘ f` admits a Taylor
series whose `k`-th term is given by `g ∘ (p k)`. -/
theorem HasFTaylorSeriesUpToOn.continuousLinearMap_comp (g : F →L[𝕜] G)
(hf : HasFTaylorSeriesUpToOn n f p s) :
HasFTaylorSeriesUpToOn n (g ∘ f) (fun x k => g.compContinuousMultilinearMap (p x k)) s where
zero_eq x hx := congr_arg g (hf.zero_eq x hx)
fderivWithin m hm x hx := (ContinuousLinearMap.compContinuousMultilinearMapL 𝕜
(fun _ : Fin m => E) F G g).hasFDerivAt.comp_hasFDerivWithinAt x (hf.fderivWithin m hm x hx)
cont m hm := (ContinuousLinearMap.compContinuousMultilinearMapL 𝕜
(fun _ : Fin m => E) F G g).continuous.comp_continuousOn (hf.cont m hm)
#align has_ftaylor_series_up_to_on.continuous_linear_map_comp HasFTaylorSeriesUpToOn.continuousLinearMap_comp
/-- Composition by continuous linear maps on the left preserves `C^n` functions in a domain
at a point. -/
theorem ContDiffWithinAt.continuousLinearMap_comp (g : F →L[𝕜] G)
(hf : ContDiffWithinAt 𝕜 n f s x) : ContDiffWithinAt 𝕜 n (g ∘ f) s x := fun m hm ↦ by
rcases hf m hm with ⟨u, hu, p, hp⟩
exact ⟨u, hu, _, hp.continuousLinearMap_comp g⟩
#align cont_diff_within_at.continuous_linear_map_comp ContDiffWithinAt.continuousLinearMap_comp
/-- Composition by continuous linear maps on the left preserves `C^n` functions in a domain
at a point. -/
theorem ContDiffAt.continuousLinearMap_comp (g : F →L[𝕜] G) (hf : ContDiffAt 𝕜 n f x) :
ContDiffAt 𝕜 n (g ∘ f) x :=
ContDiffWithinAt.continuousLinearMap_comp g hf
#align cont_diff_at.continuous_linear_map_comp ContDiffAt.continuousLinearMap_comp
/-- Composition by continuous linear maps on the left preserves `C^n` functions on domains. -/
theorem ContDiffOn.continuousLinearMap_comp (g : F →L[𝕜] G) (hf : ContDiffOn 𝕜 n f s) :
ContDiffOn 𝕜 n (g ∘ f) s := fun x hx => (hf x hx).continuousLinearMap_comp g
#align cont_diff_on.continuous_linear_map_comp ContDiffOn.continuousLinearMap_comp
/-- Composition by continuous linear maps on the left preserves `C^n` functions. -/
theorem ContDiff.continuousLinearMap_comp {f : E → F} (g : F →L[𝕜] G) (hf : ContDiff 𝕜 n f) :
ContDiff 𝕜 n fun x => g (f x) :=
contDiffOn_univ.1 <| ContDiffOn.continuousLinearMap_comp _ (contDiffOn_univ.2 hf)
#align cont_diff.continuous_linear_map_comp ContDiff.continuousLinearMap_comp
/-- The iterated derivative within a set of the composition with a linear map on the left is
obtained by applying the linear map to the iterated derivative. -/
theorem ContinuousLinearMap.iteratedFDerivWithin_comp_left {f : E → F} (g : F →L[𝕜] G)
(hf : ContDiffOn 𝕜 n f s) (hs : UniqueDiffOn 𝕜 s) (hx : x ∈ s) {i : ℕ} (hi : (i : ℕ∞) ≤ n) :
iteratedFDerivWithin 𝕜 i (g ∘ f) s x =
g.compContinuousMultilinearMap (iteratedFDerivWithin 𝕜 i f s x) :=
(((hf.ftaylorSeriesWithin hs).continuousLinearMap_comp g).eq_iteratedFDerivWithin_of_uniqueDiffOn
hi hs hx).symm
#align continuous_linear_map.iterated_fderiv_within_comp_left ContinuousLinearMap.iteratedFDerivWithin_comp_left
/-- The iterated derivative of the composition with a linear map on the left is
obtained by applying the linear map to the iterated derivative. -/
theorem ContinuousLinearMap.iteratedFDeriv_comp_left {f : E → F} (g : F →L[𝕜] G)
(hf : ContDiff 𝕜 n f) (x : E) {i : ℕ} (hi : (i : ℕ∞) ≤ n) :
iteratedFDeriv 𝕜 i (g ∘ f) x = g.compContinuousMultilinearMap (iteratedFDeriv 𝕜 i f x) := by
simp only [← iteratedFDerivWithin_univ]
exact g.iteratedFDerivWithin_comp_left hf.contDiffOn uniqueDiffOn_univ (mem_univ x) hi
#align continuous_linear_map.iterated_fderiv_comp_left ContinuousLinearMap.iteratedFDeriv_comp_left
/-- The iterated derivative within a set of the composition with a linear equiv on the left is
obtained by applying the linear equiv to the iterated derivative. This is true without
differentiability assumptions. -/
theorem ContinuousLinearEquiv.iteratedFDerivWithin_comp_left (g : F ≃L[𝕜] G) (f : E → F)
(hs : UniqueDiffOn 𝕜 s) (hx : x ∈ s) (i : ℕ) :
iteratedFDerivWithin 𝕜 i (g ∘ f) s x =
(g : F →L[𝕜] G).compContinuousMultilinearMap (iteratedFDerivWithin 𝕜 i f s x) := by
induction' i with i IH generalizing x
· ext1 m
simp only [Nat.zero_eq, iteratedFDerivWithin_zero_apply, comp_apply,
ContinuousLinearMap.compContinuousMultilinearMap_coe, coe_coe]
· ext1 m
rw [iteratedFDerivWithin_succ_apply_left]
have Z : fderivWithin 𝕜 (iteratedFDerivWithin 𝕜 i (g ∘ f) s) s x =
fderivWithin 𝕜 (g.compContinuousMultilinearMapL (fun _ : Fin i => E) ∘
iteratedFDerivWithin 𝕜 i f s) s x :=
fderivWithin_congr' (@IH) hx
simp_rw [Z]
rw [(g.compContinuousMultilinearMapL fun _ : Fin i => E).comp_fderivWithin (hs x hx)]
simp only [ContinuousLinearMap.coe_comp', ContinuousLinearEquiv.coe_coe, comp_apply,
ContinuousLinearEquiv.compContinuousMultilinearMapL_apply,
ContinuousLinearMap.compContinuousMultilinearMap_coe, EmbeddingLike.apply_eq_iff_eq]
rw [iteratedFDerivWithin_succ_apply_left]
#align continuous_linear_equiv.iterated_fderiv_within_comp_left ContinuousLinearEquiv.iteratedFDerivWithin_comp_left
/-- Composition with a linear isometry on the left preserves the norm of the iterated
derivative within a set. -/
theorem LinearIsometry.norm_iteratedFDerivWithin_comp_left {f : E → F} (g : F →ₗᵢ[𝕜] G)
(hf : ContDiffOn 𝕜 n f s) (hs : UniqueDiffOn 𝕜 s) (hx : x ∈ s) {i : ℕ} (hi : (i : ℕ∞) ≤ n) :
‖iteratedFDerivWithin 𝕜 i (g ∘ f) s x‖ = ‖iteratedFDerivWithin 𝕜 i f s x‖ := by
have :
iteratedFDerivWithin 𝕜 i (g ∘ f) s x =
g.toContinuousLinearMap.compContinuousMultilinearMap (iteratedFDerivWithin 𝕜 i f s x) :=
g.toContinuousLinearMap.iteratedFDerivWithin_comp_left hf hs hx hi
rw [this]
apply LinearIsometry.norm_compContinuousMultilinearMap
#align linear_isometry.norm_iterated_fderiv_within_comp_left LinearIsometry.norm_iteratedFDerivWithin_comp_left
/-- Composition with a linear isometry on the left preserves the norm of the iterated
derivative. -/
theorem LinearIsometry.norm_iteratedFDeriv_comp_left {f : E → F} (g : F →ₗᵢ[𝕜] G)
(hf : ContDiff 𝕜 n f) (x : E) {i : ℕ} (hi : (i : ℕ∞) ≤ n) :
‖iteratedFDeriv 𝕜 i (g ∘ f) x‖ = ‖iteratedFDeriv 𝕜 i f x‖ := by
simp only [← iteratedFDerivWithin_univ]
exact g.norm_iteratedFDerivWithin_comp_left hf.contDiffOn uniqueDiffOn_univ (mem_univ x) hi
#align linear_isometry.norm_iterated_fderiv_comp_left LinearIsometry.norm_iteratedFDeriv_comp_left
/-- Composition with a linear isometry equiv on the left preserves the norm of the iterated
derivative within a set. -/
theorem LinearIsometryEquiv.norm_iteratedFDerivWithin_comp_left (g : F ≃ₗᵢ[𝕜] G) (f : E → F)
(hs : UniqueDiffOn 𝕜 s) (hx : x ∈ s) (i : ℕ) :
‖iteratedFDerivWithin 𝕜 i (g ∘ f) s x‖ = ‖iteratedFDerivWithin 𝕜 i f s x‖ := by
have :
iteratedFDerivWithin 𝕜 i (g ∘ f) s x =
(g : F →L[𝕜] G).compContinuousMultilinearMap (iteratedFDerivWithin 𝕜 i f s x) :=
g.toContinuousLinearEquiv.iteratedFDerivWithin_comp_left f hs hx i
rw [this]
apply LinearIsometry.norm_compContinuousMultilinearMap g.toLinearIsometry
#align linear_isometry_equiv.norm_iterated_fderiv_within_comp_left LinearIsometryEquiv.norm_iteratedFDerivWithin_comp_left
/-- Composition with a linear isometry equiv on the left preserves the norm of the iterated
derivative. -/
theorem LinearIsometryEquiv.norm_iteratedFDeriv_comp_left (g : F ≃ₗᵢ[𝕜] G) (f : E → F) (x : E)
(i : ℕ) : ‖iteratedFDeriv 𝕜 i (g ∘ f) x‖ = ‖iteratedFDeriv 𝕜 i f x‖ := by
rw [← iteratedFDerivWithin_univ, ← iteratedFDerivWithin_univ]
apply g.norm_iteratedFDerivWithin_comp_left f uniqueDiffOn_univ (mem_univ x) i
#align linear_isometry_equiv.norm_iterated_fderiv_comp_left LinearIsometryEquiv.norm_iteratedFDeriv_comp_left
/-- Composition by continuous linear equivs on the left respects higher differentiability at a
point in a domain. -/
theorem ContinuousLinearEquiv.comp_contDiffWithinAt_iff (e : F ≃L[𝕜] G) :
ContDiffWithinAt 𝕜 n (e ∘ f) s x ↔ ContDiffWithinAt 𝕜 n f s x :=
⟨fun H => by
simpa only [(· ∘ ·), e.symm.coe_coe, e.symm_apply_apply] using
H.continuousLinearMap_comp (e.symm : G →L[𝕜] F),
fun H => H.continuousLinearMap_comp (e : F →L[𝕜] G)⟩
#align continuous_linear_equiv.comp_cont_diff_within_at_iff ContinuousLinearEquiv.comp_contDiffWithinAt_iff
/-- Composition by continuous linear equivs on the left respects higher differentiability at a
point. -/
theorem ContinuousLinearEquiv.comp_contDiffAt_iff (e : F ≃L[𝕜] G) :
ContDiffAt 𝕜 n (e ∘ f) x ↔ ContDiffAt 𝕜 n f x := by
simp only [← contDiffWithinAt_univ, e.comp_contDiffWithinAt_iff]
#align continuous_linear_equiv.comp_cont_diff_at_iff ContinuousLinearEquiv.comp_contDiffAt_iff
/-- Composition by continuous linear equivs on the left respects higher differentiability on
domains. -/
theorem ContinuousLinearEquiv.comp_contDiffOn_iff (e : F ≃L[𝕜] G) :
ContDiffOn 𝕜 n (e ∘ f) s ↔ ContDiffOn 𝕜 n f s := by
simp [ContDiffOn, e.comp_contDiffWithinAt_iff]
#align continuous_linear_equiv.comp_cont_diff_on_iff ContinuousLinearEquiv.comp_contDiffOn_iff
/-- Composition by continuous linear equivs on the left respects higher differentiability. -/
theorem ContinuousLinearEquiv.comp_contDiff_iff (e : F ≃L[𝕜] G) :
ContDiff 𝕜 n (e ∘ f) ↔ ContDiff 𝕜 n f := by
simp only [← contDiffOn_univ, e.comp_contDiffOn_iff]
#align continuous_linear_equiv.comp_cont_diff_iff ContinuousLinearEquiv.comp_contDiff_iff
/-- If `f` admits a Taylor series `p` in a set `s`, and `g` is linear, then `f ∘ g` admits a Taylor
series in `g ⁻¹' s`, whose `k`-th term is given by `p k (g v₁, ..., g vₖ)` . -/
theorem HasFTaylorSeriesUpToOn.compContinuousLinearMap (hf : HasFTaylorSeriesUpToOn n f p s)
(g : G →L[𝕜] E) :
HasFTaylorSeriesUpToOn n (f ∘ g) (fun x k => (p (g x) k).compContinuousLinearMap fun _ => g)
(g ⁻¹' s) := by
let A : ∀ m : ℕ, (E[×m]→L[𝕜] F) → G[×m]→L[𝕜] F := fun m h => h.compContinuousLinearMap fun _ => g
have hA : ∀ m, IsBoundedLinearMap 𝕜 (A m) := fun m =>
isBoundedLinearMap_continuousMultilinearMap_comp_linear g
constructor
· intro x hx
simp only [(hf.zero_eq (g x) hx).symm, Function.comp_apply]
change (p (g x) 0 fun _ : Fin 0 => g 0) = p (g x) 0 0
rw [ContinuousLinearMap.map_zero]
rfl
· intro m hm x hx
convert (hA m).hasFDerivAt.comp_hasFDerivWithinAt x
((hf.fderivWithin m hm (g x) hx).comp x g.hasFDerivWithinAt (Subset.refl _))
ext y v
change p (g x) (Nat.succ m) (g ∘ cons y v) = p (g x) m.succ (cons (g y) (g ∘ v))
rw [comp_cons]
· intro m hm
exact (hA m).continuous.comp_continuousOn <| (hf.cont m hm).comp g.continuous.continuousOn <|
Subset.refl _
#align has_ftaylor_series_up_to_on.comp_continuous_linear_map HasFTaylorSeriesUpToOn.compContinuousLinearMap
/-- Composition by continuous linear maps on the right preserves `C^n` functions at a point on
a domain. -/
theorem ContDiffWithinAt.comp_continuousLinearMap {x : G} (g : G →L[𝕜] E)
(hf : ContDiffWithinAt 𝕜 n f s (g x)) : ContDiffWithinAt 𝕜 n (f ∘ g) (g ⁻¹' s) x := by
intro m hm
rcases hf m hm with ⟨u, hu, p, hp⟩
refine ⟨g ⁻¹' u, ?_, _, hp.compContinuousLinearMap g⟩
refine g.continuous.continuousWithinAt.tendsto_nhdsWithin ?_ hu
exact (mapsTo_singleton.2 <| mem_singleton _).union_union (mapsTo_preimage _ _)
#align cont_diff_within_at.comp_continuous_linear_map ContDiffWithinAt.comp_continuousLinearMap
/-- Composition by continuous linear maps on the right preserves `C^n` functions on domains. -/
theorem ContDiffOn.comp_continuousLinearMap (hf : ContDiffOn 𝕜 n f s) (g : G →L[𝕜] E) :
ContDiffOn 𝕜 n (f ∘ g) (g ⁻¹' s) := fun x hx => (hf (g x) hx).comp_continuousLinearMap g
#align cont_diff_on.comp_continuous_linear_map ContDiffOn.comp_continuousLinearMap
/-- Composition by continuous linear maps on the right preserves `C^n` functions. -/
theorem ContDiff.comp_continuousLinearMap {f : E → F} {g : G →L[𝕜] E} (hf : ContDiff 𝕜 n f) :
ContDiff 𝕜 n (f ∘ g) :=
contDiffOn_univ.1 <| ContDiffOn.comp_continuousLinearMap (contDiffOn_univ.2 hf) _
#align cont_diff.comp_continuous_linear_map ContDiff.comp_continuousLinearMap
/-- The iterated derivative within a set of the composition with a linear map on the right is
obtained by composing the iterated derivative with the linear map. -/
theorem ContinuousLinearMap.iteratedFDerivWithin_comp_right {f : E → F} (g : G →L[𝕜] E)
(hf : ContDiffOn 𝕜 n f s) (hs : UniqueDiffOn 𝕜 s) (h's : UniqueDiffOn 𝕜 (g ⁻¹' s)) {x : G}
(hx : g x ∈ s) {i : ℕ} (hi : (i : ℕ∞) ≤ n) :
iteratedFDerivWithin 𝕜 i (f ∘ g) (g ⁻¹' s) x =
(iteratedFDerivWithin 𝕜 i f s (g x)).compContinuousLinearMap fun _ => g :=
(((hf.ftaylorSeriesWithin hs).compContinuousLinearMap g).eq_iteratedFDerivWithin_of_uniqueDiffOn
hi h's hx).symm
#align continuous_linear_map.iterated_fderiv_within_comp_right ContinuousLinearMap.iteratedFDerivWithin_comp_right
/-- The iterated derivative within a set of the composition with a linear equiv on the right is
obtained by composing the iterated derivative with the linear equiv. -/
theorem ContinuousLinearEquiv.iteratedFDerivWithin_comp_right (g : G ≃L[𝕜] E) (f : E → F)
(hs : UniqueDiffOn 𝕜 s) {x : G} (hx : g x ∈ s) (i : ℕ) :
iteratedFDerivWithin 𝕜 i (f ∘ g) (g ⁻¹' s) x =
(iteratedFDerivWithin 𝕜 i f s (g x)).compContinuousLinearMap fun _ => g := by
induction' i with i IH generalizing x
· ext1
simp only [Nat.zero_eq, iteratedFDerivWithin_zero_apply, comp_apply,
ContinuousMultilinearMap.compContinuousLinearMap_apply]
· ext1 m
simp only [ContinuousMultilinearMap.compContinuousLinearMap_apply,
ContinuousLinearEquiv.coe_coe, iteratedFDerivWithin_succ_apply_left]
have : fderivWithin 𝕜 (iteratedFDerivWithin 𝕜 i (f ∘ g) (g ⁻¹' s)) (g ⁻¹' s) x =
fderivWithin 𝕜
(ContinuousMultilinearMap.compContinuousLinearMapEquivL _ (fun _x : Fin i => g) ∘
(iteratedFDerivWithin 𝕜 i f s ∘ g)) (g ⁻¹' s) x :=
fderivWithin_congr' (@IH) hx
rw [this, ContinuousLinearEquiv.comp_fderivWithin _ (g.uniqueDiffOn_preimage_iff.2 hs x hx)]
simp only [ContinuousLinearMap.coe_comp', ContinuousLinearEquiv.coe_coe, comp_apply,
ContinuousMultilinearMap.compContinuousLinearMapEquivL_apply,
ContinuousMultilinearMap.compContinuousLinearMap_apply]
rw [ContinuousLinearEquiv.comp_right_fderivWithin _ (g.uniqueDiffOn_preimage_iff.2 hs x hx),
ContinuousLinearMap.coe_comp', coe_coe, comp_apply, tail_def, tail_def]
#align continuous_linear_equiv.iterated_fderiv_within_comp_right ContinuousLinearEquiv.iteratedFDerivWithin_comp_right
/-- The iterated derivative of the composition with a linear map on the right is
obtained by composing the iterated derivative with the linear map. -/
theorem ContinuousLinearMap.iteratedFDeriv_comp_right (g : G →L[𝕜] E) {f : E → F}
(hf : ContDiff 𝕜 n f) (x : G) {i : ℕ} (hi : (i : ℕ∞) ≤ n) :
iteratedFDeriv 𝕜 i (f ∘ g) x =
(iteratedFDeriv 𝕜 i f (g x)).compContinuousLinearMap fun _ => g := by
simp only [← iteratedFDerivWithin_univ]
exact g.iteratedFDerivWithin_comp_right hf.contDiffOn uniqueDiffOn_univ uniqueDiffOn_univ
(mem_univ _) hi
#align continuous_linear_map.iterated_fderiv_comp_right ContinuousLinearMap.iteratedFDeriv_comp_right
/-- Composition with a linear isometry on the right preserves the norm of the iterated derivative
within a set. -/
theorem LinearIsometryEquiv.norm_iteratedFDerivWithin_comp_right (g : G ≃ₗᵢ[𝕜] E) (f : E → F)
(hs : UniqueDiffOn 𝕜 s) {x : G} (hx : g x ∈ s) (i : ℕ) :
‖iteratedFDerivWithin 𝕜 i (f ∘ g) (g ⁻¹' s) x‖ = ‖iteratedFDerivWithin 𝕜 i f s (g x)‖ := by
have : iteratedFDerivWithin 𝕜 i (f ∘ g) (g ⁻¹' s) x =
(iteratedFDerivWithin 𝕜 i f s (g x)).compContinuousLinearMap fun _ => g :=
g.toContinuousLinearEquiv.iteratedFDerivWithin_comp_right f hs hx i
rw [this, ContinuousMultilinearMap.norm_compContinuous_linearIsometryEquiv]
#align linear_isometry_equiv.norm_iterated_fderiv_within_comp_right LinearIsometryEquiv.norm_iteratedFDerivWithin_comp_right
/-- Composition with a linear isometry on the right preserves the norm of the iterated derivative
within a set. -/
theorem LinearIsometryEquiv.norm_iteratedFDeriv_comp_right (g : G ≃ₗᵢ[𝕜] E) (f : E → F) (x : G)
(i : ℕ) : ‖iteratedFDeriv 𝕜 i (f ∘ g) x‖ = ‖iteratedFDeriv 𝕜 i f (g x)‖ := by
simp only [← iteratedFDerivWithin_univ]
apply g.norm_iteratedFDerivWithin_comp_right f uniqueDiffOn_univ (mem_univ (g x)) i
#align linear_isometry_equiv.norm_iterated_fderiv_comp_right LinearIsometryEquiv.norm_iteratedFDeriv_comp_right
/-- Composition by continuous linear equivs on the right respects higher differentiability at a
point in a domain. -/
theorem ContinuousLinearEquiv.contDiffWithinAt_comp_iff (e : G ≃L[𝕜] E) :
ContDiffWithinAt 𝕜 n (f ∘ e) (e ⁻¹' s) (e.symm x) ↔ ContDiffWithinAt 𝕜 n f s x := by
constructor
· intro H
simpa [← preimage_comp, (· ∘ ·)] using H.comp_continuousLinearMap (e.symm : E →L[𝕜] G)
· intro H
rw [← e.apply_symm_apply x, ← e.coe_coe] at H
exact H.comp_continuousLinearMap _
#align continuous_linear_equiv.cont_diff_within_at_comp_iff ContinuousLinearEquiv.contDiffWithinAt_comp_iff
/-- Composition by continuous linear equivs on the right respects higher differentiability at a
point. -/
theorem ContinuousLinearEquiv.contDiffAt_comp_iff (e : G ≃L[𝕜] E) :
ContDiffAt 𝕜 n (f ∘ e) (e.symm x) ↔ ContDiffAt 𝕜 n f x := by
rw [← contDiffWithinAt_univ, ← contDiffWithinAt_univ, ← preimage_univ]
exact e.contDiffWithinAt_comp_iff
#align continuous_linear_equiv.cont_diff_at_comp_iff ContinuousLinearEquiv.contDiffAt_comp_iff
/-- Composition by continuous linear equivs on the right respects higher differentiability on
domains. -/
theorem ContinuousLinearEquiv.contDiffOn_comp_iff (e : G ≃L[𝕜] E) :
ContDiffOn 𝕜 n (f ∘ e) (e ⁻¹' s) ↔ ContDiffOn 𝕜 n f s :=
⟨fun H => by simpa [(· ∘ ·)] using H.comp_continuousLinearMap (e.symm : E →L[𝕜] G), fun H =>
H.comp_continuousLinearMap (e : G →L[𝕜] E)⟩
#align continuous_linear_equiv.cont_diff_on_comp_iff ContinuousLinearEquiv.contDiffOn_comp_iff
/-- Composition by continuous linear equivs on the right respects higher differentiability. -/
theorem ContinuousLinearEquiv.contDiff_comp_iff (e : G ≃L[𝕜] E) :
ContDiff 𝕜 n (f ∘ e) ↔ ContDiff 𝕜 n f := by
rw [← contDiffOn_univ, ← contDiffOn_univ, ← preimage_univ]
exact e.contDiffOn_comp_iff
#align continuous_linear_equiv.cont_diff_comp_iff ContinuousLinearEquiv.contDiff_comp_iff
/-- If two functions `f` and `g` admit Taylor series `p` and `q` in a set `s`, then the cartesian
product of `f` and `g` admits the cartesian product of `p` and `q` as a Taylor series. -/
theorem HasFTaylorSeriesUpToOn.prod (hf : HasFTaylorSeriesUpToOn n f p s) {g : E → G}
{q : E → FormalMultilinearSeries 𝕜 E G} (hg : HasFTaylorSeriesUpToOn n g q s) :
HasFTaylorSeriesUpToOn n (fun y => (f y, g y)) (fun y k => (p y k).prod (q y k)) s := by
set L := fun m => ContinuousMultilinearMap.prodL 𝕜 (fun _ : Fin m => E) F G
constructor
· intro x hx; rw [← hf.zero_eq x hx, ← hg.zero_eq x hx]; rfl
· intro m hm x hx
convert (L m).hasFDerivAt.comp_hasFDerivWithinAt x
((hf.fderivWithin m hm x hx).prod (hg.fderivWithin m hm x hx))
· intro m hm
exact (L m).continuous.comp_continuousOn ((hf.cont m hm).prod (hg.cont m hm))
#align has_ftaylor_series_up_to_on.prod HasFTaylorSeriesUpToOn.prod
/-- The cartesian product of `C^n` functions at a point in a domain is `C^n`. -/
theorem ContDiffWithinAt.prod {s : Set E} {f : E → F} {g : E → G} (hf : ContDiffWithinAt 𝕜 n f s x)
(hg : ContDiffWithinAt 𝕜 n g s x) : ContDiffWithinAt 𝕜 n (fun x : E => (f x, g x)) s x := by
intro m hm
rcases hf m hm with ⟨u, hu, p, hp⟩
rcases hg m hm with ⟨v, hv, q, hq⟩
exact
⟨u ∩ v, Filter.inter_mem hu hv, _,
(hp.mono inter_subset_left).prod (hq.mono inter_subset_right)⟩
#align cont_diff_within_at.prod ContDiffWithinAt.prod
/-- The cartesian product of `C^n` functions on domains is `C^n`. -/
theorem ContDiffOn.prod {s : Set E} {f : E → F} {g : E → G} (hf : ContDiffOn 𝕜 n f s)
(hg : ContDiffOn 𝕜 n g s) : ContDiffOn 𝕜 n (fun x : E => (f x, g x)) s := fun x hx =>
(hf x hx).prod (hg x hx)
#align cont_diff_on.prod ContDiffOn.prod
/-- The cartesian product of `C^n` functions at a point is `C^n`. -/
theorem ContDiffAt.prod {f : E → F} {g : E → G} (hf : ContDiffAt 𝕜 n f x)
(hg : ContDiffAt 𝕜 n g x) : ContDiffAt 𝕜 n (fun x : E => (f x, g x)) x :=
contDiffWithinAt_univ.1 <|
ContDiffWithinAt.prod (contDiffWithinAt_univ.2 hf) (contDiffWithinAt_univ.2 hg)
#align cont_diff_at.prod ContDiffAt.prod
/-- The cartesian product of `C^n` functions is `C^n`. -/
theorem ContDiff.prod {f : E → F} {g : E → G} (hf : ContDiff 𝕜 n f) (hg : ContDiff 𝕜 n g) :
ContDiff 𝕜 n fun x : E => (f x, g x) :=
contDiffOn_univ.1 <| ContDiffOn.prod (contDiffOn_univ.2 hf) (contDiffOn_univ.2 hg)
#align cont_diff.prod ContDiff.prod
/-!
### Composition of `C^n` functions
We show that the composition of `C^n` functions is `C^n`. One way to prove it would be to write
the `n`-th derivative of the composition (this is Faà di Bruno's formula) and check its continuity,
but this is very painful. Instead, we go for a simple inductive proof. Assume it is done for `n`.
Then, to check it for `n+1`, one needs to check that the derivative of `g ∘ f` is `C^n`, i.e.,
that `Dg(f x) ⬝ Df(x)` is `C^n`. The term `Dg (f x)` is the composition of two `C^n` functions, so
it is `C^n` by the inductive assumption. The term `Df(x)` is also `C^n`. Then, the matrix
multiplication is the application of a bilinear map (which is `C^∞`, and therefore `C^n`) to
`x ↦ (Dg(f x), Df x)`. As the composition of two `C^n` maps, it is again `C^n`, and we are done.
There is a subtlety in this argument: we apply the inductive assumption to functions on other Banach
spaces. In maths, one would say: prove by induction over `n` that, for all `C^n` maps between all
pairs of Banach spaces, their composition is `C^n`. In Lean, this is fine as long as the spaces
stay in the same universe. This is not the case in the above argument: if `E` lives in universe `u`
and `F` lives in universe `v`, then linear maps from `E` to `F` (to which the derivative of `f`
belongs) is in universe `max u v`. If one could quantify over finitely many universes, the above
proof would work fine, but this is not the case. One could still write the proof considering spaces
in any universe in `u, v, w, max u v, max v w, max u v w`, but it would be extremely tedious and
lead to a lot of duplication. Instead, we formulate the above proof when all spaces live in the same
universe (where everything is fine), and then we deduce the general result by lifting all our spaces
to a common universe through `ULift`. This lifting is done through a continuous linear equiv.
We have already proved that composing with such a linear equiv does not change the fact of
being `C^n`, which concludes the proof.
-/
/-- Auxiliary lemma proving that the composition of `C^n` functions on domains is `C^n` when all
spaces live in the same universe. Use instead `ContDiffOn.comp` which removes the universe
assumption (but is deduced from this one). -/
private theorem ContDiffOn.comp_same_univ {Eu : Type u} [NormedAddCommGroup Eu] [NormedSpace 𝕜 Eu]
{Fu : Type u} [NormedAddCommGroup Fu] [NormedSpace 𝕜 Fu] {Gu : Type u} [NormedAddCommGroup Gu]
[NormedSpace 𝕜 Gu] {s : Set Eu} {t : Set Fu} {g : Fu → Gu} {f : Eu → Fu}
(hg : ContDiffOn 𝕜 n g t) (hf : ContDiffOn 𝕜 n f s) (st : s ⊆ f ⁻¹' t) :
ContDiffOn 𝕜 n (g ∘ f) s := by
induction' n using ENat.nat_induction with n IH Itop generalizing Eu Fu Gu
· rw [contDiffOn_zero] at hf hg ⊢
exact ContinuousOn.comp hg hf st
· rw [contDiffOn_succ_iff_hasFDerivWithinAt] at hg ⊢
intro x hx
rcases (contDiffOn_succ_iff_hasFDerivWithinAt.1 hf) x hx with ⟨u, hu, f', hf', f'_diff⟩
rcases hg (f x) (st hx) with ⟨v, hv, g', hg', g'_diff⟩
rw [insert_eq_of_mem hx] at hu ⊢
have xu : x ∈ u := mem_of_mem_nhdsWithin hx hu
let w := s ∩ (u ∩ f ⁻¹' v)
have wv : w ⊆ f ⁻¹' v := fun y hy => hy.2.2
have wu : w ⊆ u := fun y hy => hy.2.1
have ws : w ⊆ s := fun y hy => hy.1
refine ⟨w, ?_, fun y => (g' (f y)).comp (f' y), ?_, ?_⟩
· show w ∈ 𝓝[s] x
apply Filter.inter_mem self_mem_nhdsWithin
apply Filter.inter_mem hu
apply ContinuousWithinAt.preimage_mem_nhdsWithin'
· rw [← continuousWithinAt_inter' hu]
exact (hf' x xu).differentiableWithinAt.continuousWithinAt.mono inter_subset_right
· apply nhdsWithin_mono _ _ hv
exact Subset.trans (image_subset_iff.mpr st) (subset_insert (f x) t)
· show ∀ y ∈ w, HasFDerivWithinAt (g ∘ f) ((g' (f y)).comp (f' y)) w y
rintro y ⟨-, yu, yv⟩
exact (hg' (f y) yv).comp y ((hf' y yu).mono wu) wv
· show ContDiffOn 𝕜 n (fun y => (g' (f y)).comp (f' y)) w
have A : ContDiffOn 𝕜 n (fun y => g' (f y)) w :=
IH g'_diff ((hf.of_le (WithTop.coe_le_coe.2 (Nat.le_succ n))).mono ws) wv
have B : ContDiffOn 𝕜 n f' w := f'_diff.mono wu
have C : ContDiffOn 𝕜 n (fun y => (g' (f y), f' y)) w := A.prod B
have D : ContDiffOn 𝕜 n (fun p : (Fu →L[𝕜] Gu) × (Eu →L[𝕜] Fu) => p.1.comp p.2) univ :=
isBoundedBilinearMap_comp.contDiff.contDiffOn
exact IH D C (subset_univ _)
· rw [contDiffOn_top] at hf hg ⊢
exact fun n => Itop n (hg n) (hf n) st
/-- The composition of `C^n` functions on domains is `C^n`. -/
theorem ContDiffOn.comp {s : Set E} {t : Set F} {g : F → G} {f : E → F} (hg : ContDiffOn 𝕜 n g t)
(hf : ContDiffOn 𝕜 n f s) (st : s ⊆ f ⁻¹' t) : ContDiffOn 𝕜 n (g ∘ f) s := by
/- we lift all the spaces to a common universe, as we have already proved the result in this
situation. -/
let Eu : Type max uE uF uG := ULift.{max uF uG} E
let Fu : Type max uE uF uG := ULift.{max uE uG} F
let Gu : Type max uE uF uG := ULift.{max uE uF} G
-- declare the isomorphisms
have isoE : Eu ≃L[𝕜] E := ContinuousLinearEquiv.ulift
have isoF : Fu ≃L[𝕜] F := ContinuousLinearEquiv.ulift
have isoG : Gu ≃L[𝕜] G := ContinuousLinearEquiv.ulift
-- lift the functions to the new spaces, check smoothness there, and then go back.
let fu : Eu → Fu := (isoF.symm ∘ f) ∘ isoE
have fu_diff : ContDiffOn 𝕜 n fu (isoE ⁻¹' s) := by
rwa [isoE.contDiffOn_comp_iff, isoF.symm.comp_contDiffOn_iff]
let gu : Fu → Gu := (isoG.symm ∘ g) ∘ isoF
have gu_diff : ContDiffOn 𝕜 n gu (isoF ⁻¹' t) := by
rwa [isoF.contDiffOn_comp_iff, isoG.symm.comp_contDiffOn_iff]
have main : ContDiffOn 𝕜 n (gu ∘ fu) (isoE ⁻¹' s) := by
apply ContDiffOn.comp_same_univ gu_diff fu_diff
intro y hy
simp only [fu, ContinuousLinearEquiv.coe_apply, Function.comp_apply, mem_preimage]
rw [isoF.apply_symm_apply (f (isoE y))]
exact st hy
have : gu ∘ fu = (isoG.symm ∘ g ∘ f) ∘ isoE := by
ext y
simp only [fu, gu, Function.comp_apply]
rw [isoF.apply_symm_apply (f (isoE y))]
rwa [this, isoE.contDiffOn_comp_iff, isoG.symm.comp_contDiffOn_iff] at main
#align cont_diff_on.comp ContDiffOn.comp
/-- The composition of `C^n` functions on domains is `C^n`. -/
theorem ContDiffOn.comp' {s : Set E} {t : Set F} {g : F → G} {f : E → F} (hg : ContDiffOn 𝕜 n g t)
(hf : ContDiffOn 𝕜 n f s) : ContDiffOn 𝕜 n (g ∘ f) (s ∩ f ⁻¹' t) :=
hg.comp (hf.mono inter_subset_left) inter_subset_right
#align cont_diff_on.comp' ContDiffOn.comp'
/-- The composition of a `C^n` function on a domain with a `C^n` function is `C^n`. -/
theorem ContDiff.comp_contDiffOn {s : Set E} {g : F → G} {f : E → F} (hg : ContDiff 𝕜 n g)
(hf : ContDiffOn 𝕜 n f s) : ContDiffOn 𝕜 n (g ∘ f) s :=
(contDiffOn_univ.2 hg).comp hf subset_preimage_univ
#align cont_diff.comp_cont_diff_on ContDiff.comp_contDiffOn
/-- The composition of `C^n` functions is `C^n`. -/
theorem ContDiff.comp {g : F → G} {f : E → F} (hg : ContDiff 𝕜 n g) (hf : ContDiff 𝕜 n f) :
ContDiff 𝕜 n (g ∘ f) :=
contDiffOn_univ.1 <| ContDiffOn.comp (contDiffOn_univ.2 hg) (contDiffOn_univ.2 hf) (subset_univ _)
#align cont_diff.comp ContDiff.comp
/-- The composition of `C^n` functions at points in domains is `C^n`. -/
theorem ContDiffWithinAt.comp {s : Set E} {t : Set F} {g : F → G} {f : E → F} (x : E)
(hg : ContDiffWithinAt 𝕜 n g t (f x)) (hf : ContDiffWithinAt 𝕜 n f s x) (st : s ⊆ f ⁻¹' t) :
ContDiffWithinAt 𝕜 n (g ∘ f) s x := by
intro m hm
rcases hg.contDiffOn hm with ⟨u, u_nhd, _, hu⟩
rcases hf.contDiffOn hm with ⟨v, v_nhd, vs, hv⟩
have xmem : x ∈ f ⁻¹' u ∩ v :=
⟨(mem_of_mem_nhdsWithin (mem_insert (f x) _) u_nhd : _),
mem_of_mem_nhdsWithin (mem_insert x s) v_nhd⟩
have : f ⁻¹' u ∈ 𝓝[insert x s] x := by
apply hf.continuousWithinAt.insert_self.preimage_mem_nhdsWithin'
apply nhdsWithin_mono _ _ u_nhd
rw [image_insert_eq]
exact insert_subset_insert (image_subset_iff.mpr st)
have Z :=
(hu.comp (hv.mono inter_subset_right) inter_subset_left).contDiffWithinAt
xmem m le_rfl
have : 𝓝[f ⁻¹' u ∩ v] x = 𝓝[insert x s] x := by
have A : f ⁻¹' u ∩ v = insert x s ∩ (f ⁻¹' u ∩ v) := by
apply Subset.antisymm _ inter_subset_right
rintro y ⟨hy1, hy2⟩
simpa only [mem_inter_iff, mem_preimage, hy2, and_true, true_and, vs hy2] using hy1
rw [A, ← nhdsWithin_restrict'']
exact Filter.inter_mem this v_nhd
rwa [insert_eq_of_mem xmem, this] at Z
#align cont_diff_within_at.comp ContDiffWithinAt.comp
/-- The composition of `C^n` functions at points in domains is `C^n`,
with a weaker condition on `s` and `t`. -/
theorem ContDiffWithinAt.comp_of_mem {s : Set E} {t : Set F} {g : F → G} {f : E → F} (x : E)
(hg : ContDiffWithinAt 𝕜 n g t (f x)) (hf : ContDiffWithinAt 𝕜 n f s x)
(hs : t ∈ 𝓝[f '' s] f x) : ContDiffWithinAt 𝕜 n (g ∘ f) s x :=
(hg.mono_of_mem hs).comp x hf (subset_preimage_image f s)
#align cont_diff_within_at.comp_of_mem ContDiffWithinAt.comp_of_mem
/-- The composition of `C^n` functions at points in domains is `C^n`. -/
theorem ContDiffWithinAt.comp' {s : Set E} {t : Set F} {g : F → G} {f : E → F} (x : E)
(hg : ContDiffWithinAt 𝕜 n g t (f x)) (hf : ContDiffWithinAt 𝕜 n f s x) :
ContDiffWithinAt 𝕜 n (g ∘ f) (s ∩ f ⁻¹' t) x :=
hg.comp x (hf.mono inter_subset_left) inter_subset_right
#align cont_diff_within_at.comp' ContDiffWithinAt.comp'
theorem ContDiffAt.comp_contDiffWithinAt {n} (x : E) (hg : ContDiffAt 𝕜 n g (f x))
(hf : ContDiffWithinAt 𝕜 n f s x) : ContDiffWithinAt 𝕜 n (g ∘ f) s x :=
hg.comp x hf (mapsTo_univ _ _)
#align cont_diff_at.comp_cont_diff_within_at ContDiffAt.comp_contDiffWithinAt
/-- The composition of `C^n` functions at points is `C^n`. -/
nonrec theorem ContDiffAt.comp (x : E) (hg : ContDiffAt 𝕜 n g (f x)) (hf : ContDiffAt 𝕜 n f x) :
ContDiffAt 𝕜 n (g ∘ f) x :=
hg.comp x hf subset_preimage_univ
#align cont_diff_at.comp ContDiffAt.comp
theorem ContDiff.comp_contDiffWithinAt {g : F → G} {f : E → F} (h : ContDiff 𝕜 n g)
(hf : ContDiffWithinAt 𝕜 n f t x) : ContDiffWithinAt 𝕜 n (g ∘ f) t x :=
haveI : ContDiffWithinAt 𝕜 n g univ (f x) := h.contDiffAt.contDiffWithinAt
this.comp x hf (subset_univ _)
#align cont_diff.comp_cont_diff_within_at ContDiff.comp_contDiffWithinAt
theorem ContDiff.comp_contDiffAt {g : F → G} {f : E → F} (x : E) (hg : ContDiff 𝕜 n g)
(hf : ContDiffAt 𝕜 n f x) : ContDiffAt 𝕜 n (g ∘ f) x :=
hg.comp_contDiffWithinAt hf
#align cont_diff.comp_cont_diff_at ContDiff.comp_contDiffAt
/-!
### Smoothness of projections
-/
/-- The first projection in a product is `C^∞`. -/
theorem contDiff_fst : ContDiff 𝕜 n (Prod.fst : E × F → E) :=
IsBoundedLinearMap.contDiff IsBoundedLinearMap.fst
#align cont_diff_fst contDiff_fst
/-- Postcomposing `f` with `Prod.fst` is `C^n` -/
theorem ContDiff.fst {f : E → F × G} (hf : ContDiff 𝕜 n f) : ContDiff 𝕜 n fun x => (f x).1 :=
contDiff_fst.comp hf
#align cont_diff.fst ContDiff.fst
/-- Precomposing `f` with `Prod.fst` is `C^n` -/
theorem ContDiff.fst' {f : E → G} (hf : ContDiff 𝕜 n f) : ContDiff 𝕜 n fun x : E × F => f x.1 :=
hf.comp contDiff_fst
#align cont_diff.fst' ContDiff.fst'
/-- The first projection on a domain in a product is `C^∞`. -/
theorem contDiffOn_fst {s : Set (E × F)} : ContDiffOn 𝕜 n (Prod.fst : E × F → E) s :=
ContDiff.contDiffOn contDiff_fst
#align cont_diff_on_fst contDiffOn_fst
theorem ContDiffOn.fst {f : E → F × G} {s : Set E} (hf : ContDiffOn 𝕜 n f s) :
ContDiffOn 𝕜 n (fun x => (f x).1) s :=
contDiff_fst.comp_contDiffOn hf
#align cont_diff_on.fst ContDiffOn.fst
/-- The first projection at a point in a product is `C^∞`. -/
theorem contDiffAt_fst {p : E × F} : ContDiffAt 𝕜 n (Prod.fst : E × F → E) p :=
contDiff_fst.contDiffAt
#align cont_diff_at_fst contDiffAt_fst
/-- Postcomposing `f` with `Prod.fst` is `C^n` at `(x, y)` -/
theorem ContDiffAt.fst {f : E → F × G} {x : E} (hf : ContDiffAt 𝕜 n f x) :
ContDiffAt 𝕜 n (fun x => (f x).1) x :=
contDiffAt_fst.comp x hf
#align cont_diff_at.fst ContDiffAt.fst
/-- Precomposing `f` with `Prod.fst` is `C^n` at `(x, y)` -/
theorem ContDiffAt.fst' {f : E → G} {x : E} {y : F} (hf : ContDiffAt 𝕜 n f x) :
ContDiffAt 𝕜 n (fun x : E × F => f x.1) (x, y) :=
ContDiffAt.comp (x, y) hf contDiffAt_fst
#align cont_diff_at.fst' ContDiffAt.fst'
/-- Precomposing `f` with `Prod.fst` is `C^n` at `x : E × F` -/
theorem ContDiffAt.fst'' {f : E → G} {x : E × F} (hf : ContDiffAt 𝕜 n f x.1) :
ContDiffAt 𝕜 n (fun x : E × F => f x.1) x :=
hf.comp x contDiffAt_fst
#align cont_diff_at.fst'' ContDiffAt.fst''
/-- The first projection within a domain at a point in a product is `C^∞`. -/
theorem contDiffWithinAt_fst {s : Set (E × F)} {p : E × F} :
ContDiffWithinAt 𝕜 n (Prod.fst : E × F → E) s p :=
contDiff_fst.contDiffWithinAt
#align cont_diff_within_at_fst contDiffWithinAt_fst
/-- The second projection in a product is `C^∞`. -/
theorem contDiff_snd : ContDiff 𝕜 n (Prod.snd : E × F → F) :=
IsBoundedLinearMap.contDiff IsBoundedLinearMap.snd
#align cont_diff_snd contDiff_snd
/-- Postcomposing `f` with `Prod.snd` is `C^n` -/
theorem ContDiff.snd {f : E → F × G} (hf : ContDiff 𝕜 n f) : ContDiff 𝕜 n fun x => (f x).2 :=
contDiff_snd.comp hf
#align cont_diff.snd ContDiff.snd
/-- Precomposing `f` with `Prod.snd` is `C^n` -/
theorem ContDiff.snd' {f : F → G} (hf : ContDiff 𝕜 n f) : ContDiff 𝕜 n fun x : E × F => f x.2 :=
hf.comp contDiff_snd
#align cont_diff.snd' ContDiff.snd'
/-- The second projection on a domain in a product is `C^∞`. -/
theorem contDiffOn_snd {s : Set (E × F)} : ContDiffOn 𝕜 n (Prod.snd : E × F → F) s :=
ContDiff.contDiffOn contDiff_snd
#align cont_diff_on_snd contDiffOn_snd
theorem ContDiffOn.snd {f : E → F × G} {s : Set E} (hf : ContDiffOn 𝕜 n f s) :
ContDiffOn 𝕜 n (fun x => (f x).2) s :=
contDiff_snd.comp_contDiffOn hf
#align cont_diff_on.snd ContDiffOn.snd
/-- The second projection at a point in a product is `C^∞`. -/
theorem contDiffAt_snd {p : E × F} : ContDiffAt 𝕜 n (Prod.snd : E × F → F) p :=
contDiff_snd.contDiffAt
#align cont_diff_at_snd contDiffAt_snd
/-- Postcomposing `f` with `Prod.snd` is `C^n` at `x` -/
theorem ContDiffAt.snd {f : E → F × G} {x : E} (hf : ContDiffAt 𝕜 n f x) :
ContDiffAt 𝕜 n (fun x => (f x).2) x :=
contDiffAt_snd.comp x hf
#align cont_diff_at.snd ContDiffAt.snd
/-- Precomposing `f` with `Prod.snd` is `C^n` at `(x, y)` -/
theorem ContDiffAt.snd' {f : F → G} {x : E} {y : F} (hf : ContDiffAt 𝕜 n f y) :
ContDiffAt 𝕜 n (fun x : E × F => f x.2) (x, y) :=
ContDiffAt.comp (x, y) hf contDiffAt_snd
#align cont_diff_at.snd' ContDiffAt.snd'
/-- Precomposing `f` with `Prod.snd` is `C^n` at `x : E × F` -/
theorem ContDiffAt.snd'' {f : F → G} {x : E × F} (hf : ContDiffAt 𝕜 n f x.2) :
ContDiffAt 𝕜 n (fun x : E × F => f x.2) x :=
hf.comp x contDiffAt_snd
#align cont_diff_at.snd'' ContDiffAt.snd''
/-- The second projection within a domain at a point in a product is `C^∞`. -/
theorem contDiffWithinAt_snd {s : Set (E × F)} {p : E × F} :
ContDiffWithinAt 𝕜 n (Prod.snd : E × F → F) s p :=
contDiff_snd.contDiffWithinAt
#align cont_diff_within_at_snd contDiffWithinAt_snd
section NAry
variable {E₁ E₂ E₃ E₄ : Type*}
variable [NormedAddCommGroup E₁] [NormedAddCommGroup E₂] [NormedAddCommGroup E₃]
[NormedAddCommGroup E₄] [NormedSpace 𝕜 E₁] [NormedSpace 𝕜 E₂] [NormedSpace 𝕜 E₃]
[NormedSpace 𝕜 E₄]
theorem ContDiff.comp₂ {g : E₁ × E₂ → G} {f₁ : F → E₁} {f₂ : F → E₂} (hg : ContDiff 𝕜 n g)
(hf₁ : ContDiff 𝕜 n f₁) (hf₂ : ContDiff 𝕜 n f₂) : ContDiff 𝕜 n fun x => g (f₁ x, f₂ x) :=
hg.comp <| hf₁.prod hf₂
#align cont_diff.comp₂ ContDiff.comp₂
theorem ContDiff.comp₃ {g : E₁ × E₂ × E₃ → G} {f₁ : F → E₁} {f₂ : F → E₂} {f₃ : F → E₃}
(hg : ContDiff 𝕜 n g) (hf₁ : ContDiff 𝕜 n f₁) (hf₂ : ContDiff 𝕜 n f₂) (hf₃ : ContDiff 𝕜 n f₃) :
ContDiff 𝕜 n fun x => g (f₁ x, f₂ x, f₃ x) :=
hg.comp₂ hf₁ <| hf₂.prod hf₃
#align cont_diff.comp₃ ContDiff.comp₃
theorem ContDiff.comp_contDiff_on₂ {g : E₁ × E₂ → G} {f₁ : F → E₁} {f₂ : F → E₂} {s : Set F}
(hg : ContDiff 𝕜 n g) (hf₁ : ContDiffOn 𝕜 n f₁ s) (hf₂ : ContDiffOn 𝕜 n f₂ s) :
ContDiffOn 𝕜 n (fun x => g (f₁ x, f₂ x)) s :=
hg.comp_contDiffOn <| hf₁.prod hf₂
#align cont_diff.comp_cont_diff_on₂ ContDiff.comp_contDiff_on₂
theorem ContDiff.comp_contDiff_on₃ {g : E₁ × E₂ × E₃ → G} {f₁ : F → E₁} {f₂ : F → E₂} {f₃ : F → E₃}
{s : Set F} (hg : ContDiff 𝕜 n g) (hf₁ : ContDiffOn 𝕜 n f₁ s) (hf₂ : ContDiffOn 𝕜 n f₂ s)
(hf₃ : ContDiffOn 𝕜 n f₃ s) : ContDiffOn 𝕜 n (fun x => g (f₁ x, f₂ x, f₃ x)) s :=
hg.comp_contDiff_on₂ hf₁ <| hf₂.prod hf₃
#align cont_diff.comp_cont_diff_on₃ ContDiff.comp_contDiff_on₃
end NAry
section SpecificBilinearMaps
theorem ContDiff.clm_comp {g : X → F →L[𝕜] G} {f : X → E →L[𝕜] F} (hg : ContDiff 𝕜 n g)
(hf : ContDiff 𝕜 n f) : ContDiff 𝕜 n fun x => (g x).comp (f x) :=
isBoundedBilinearMap_comp.contDiff.comp₂ hg hf
#align cont_diff.clm_comp ContDiff.clm_comp
theorem ContDiffOn.clm_comp {g : X → F →L[𝕜] G} {f : X → E →L[𝕜] F} {s : Set X}
(hg : ContDiffOn 𝕜 n g s) (hf : ContDiffOn 𝕜 n f s) :
ContDiffOn 𝕜 n (fun x => (g x).comp (f x)) s :=
isBoundedBilinearMap_comp.contDiff.comp_contDiff_on₂ hg hf
#align cont_diff_on.clm_comp ContDiffOn.clm_comp
theorem ContDiff.clm_apply {f : E → F →L[𝕜] G} {g : E → F} {n : ℕ∞} (hf : ContDiff 𝕜 n f)
(hg : ContDiff 𝕜 n g) : ContDiff 𝕜 n fun x => (f x) (g x) :=
isBoundedBilinearMap_apply.contDiff.comp₂ hf hg
#align cont_diff.clm_apply ContDiff.clm_apply
theorem ContDiffOn.clm_apply {f : E → F →L[𝕜] G} {g : E → F} {n : ℕ∞} (hf : ContDiffOn 𝕜 n f s)
(hg : ContDiffOn 𝕜 n g s) : ContDiffOn 𝕜 n (fun x => (f x) (g x)) s :=
isBoundedBilinearMap_apply.contDiff.comp_contDiff_on₂ hf hg
#align cont_diff_on.clm_apply ContDiffOn.clm_apply
-- Porting note: In Lean 3 we had to give implicit arguments in proofs like the following,
-- to speed up elaboration. In Lean 4 this isn't necessary anymore.
theorem ContDiff.smulRight {f : E → F →L[𝕜] 𝕜} {g : E → G} {n : ℕ∞} (hf : ContDiff 𝕜 n f)
(hg : ContDiff 𝕜 n g) : ContDiff 𝕜 n fun x => (f x).smulRight (g x) :=
isBoundedBilinearMap_smulRight.contDiff.comp₂ hf hg
#align cont_diff.smul_right ContDiff.smulRight
end SpecificBilinearMaps
section ClmApplyConst
/-- Application of a `ContinuousLinearMap` to a constant commutes with `iteratedFDerivWithin`. -/
theorem iteratedFDerivWithin_clm_apply_const_apply
{s : Set E} (hs : UniqueDiffOn 𝕜 s) {n : ℕ∞} {c : E → F →L[𝕜] G} (hc : ContDiffOn 𝕜 n c s)
{i : ℕ} (hi : i ≤ n) {x : E} (hx : x ∈ s) {u : F} {m : Fin i → E} :
(iteratedFDerivWithin 𝕜 i (fun y ↦ (c y) u) s x) m = (iteratedFDerivWithin 𝕜 i c s x) m u := by
induction i generalizing x with
| zero => simp
| succ i ih =>
replace hi : i < n := lt_of_lt_of_le (by norm_cast; simp) hi
have h_deriv_apply : DifferentiableOn 𝕜 (iteratedFDerivWithin 𝕜 i (fun y ↦ (c y) u) s) s :=
(hc.clm_apply contDiffOn_const).differentiableOn_iteratedFDerivWithin hi hs
have h_deriv : DifferentiableOn 𝕜 (iteratedFDerivWithin 𝕜 i c s) s :=
hc.differentiableOn_iteratedFDerivWithin hi hs
simp only [iteratedFDerivWithin_succ_apply_left]
rw [← fderivWithin_continuousMultilinear_apply_const_apply (hs x hx) (h_deriv_apply x hx)]
rw [fderivWithin_congr' (fun x hx ↦ ih hi.le hx) hx]
rw [fderivWithin_clm_apply (hs x hx) (h_deriv.continuousMultilinear_apply_const _ x hx)
(differentiableWithinAt_const u)]
rw [fderivWithin_const_apply _ (hs x hx)]
simp only [ContinuousLinearMap.flip_apply, ContinuousLinearMap.comp_zero, zero_add]
rw [fderivWithin_continuousMultilinear_apply_const_apply (hs x hx) (h_deriv x hx)]
/-- Application of a `ContinuousLinearMap` to a constant commutes with `iteratedFDeriv`. -/
theorem iteratedFDeriv_clm_apply_const_apply
{n : ℕ∞} {c : E → F →L[𝕜] G} (hc : ContDiff 𝕜 n c)
{i : ℕ} (hi : i ≤ n) {x : E} {u : F} {m : Fin i → E} :
(iteratedFDeriv 𝕜 i (fun y ↦ (c y) u) x) m = (iteratedFDeriv 𝕜 i c x) m u := by
simp only [← iteratedFDerivWithin_univ]
exact iteratedFDerivWithin_clm_apply_const_apply uniqueDiffOn_univ hc.contDiffOn hi (mem_univ _)
end ClmApplyConst
/-- The natural equivalence `(E × F) × G ≃ E × (F × G)` is smooth.
Warning: if you think you need this lemma, it is likely that you can simplify your proof by
reformulating the lemma that you're applying next using the tips in
Note [continuity lemma statement]
-/
theorem contDiff_prodAssoc : ContDiff 𝕜 ⊤ <| Equiv.prodAssoc E F G :=
(LinearIsometryEquiv.prodAssoc 𝕜 E F G).contDiff
#align cont_diff_prod_assoc contDiff_prodAssoc
/-- The natural equivalence `E × (F × G) ≃ (E × F) × G` is smooth.
Warning: see remarks attached to `contDiff_prodAssoc`
-/
theorem contDiff_prodAssoc_symm : ContDiff 𝕜 ⊤ <| (Equiv.prodAssoc E F G).symm :=
(LinearIsometryEquiv.prodAssoc 𝕜 E F G).symm.contDiff
#align cont_diff_prod_assoc_symm contDiff_prodAssoc_symm
/-! ### Bundled derivatives are smooth -/
/-- One direction of `contDiffWithinAt_succ_iff_hasFDerivWithinAt`, but where all derivatives
taken within the same set. Version for partial derivatives / functions with parameters. `f x` is a
`C^n+1` family of functions and `g x` is a `C^n` family of points, then the derivative of `f x` at
`g x` depends in a `C^n` way on `x`. We give a general version of this fact relative to sets which
may not have unique derivatives, in the following form. If `f : E × F → G` is `C^n+1` at
`(x₀, g(x₀))` in `(s ∪ {x₀}) × t ⊆ E × F` and `g : E → F` is `C^n` at `x₀` within some set `s ⊆ E`,
then there is a function `f' : E → F →L[𝕜] G` that is `C^n` at `x₀` within `s` such that for all `x`
sufficiently close to `x₀` within `s ∪ {x₀}` the function `y ↦ f x y` has derivative `f' x` at `g x`
within `t ⊆ F`. For convenience, we return an explicit set of `x`'s where this holds that is a
subset of `s ∪ {x₀}`. We need one additional condition, namely that `t` is a neighborhood of
`g(x₀)` within `g '' s`. -/
theorem ContDiffWithinAt.hasFDerivWithinAt_nhds {f : E → F → G} {g : E → F} {t : Set F} {n : ℕ}
{x₀ : E} (hf : ContDiffWithinAt 𝕜 (n + 1) (uncurry f) (insert x₀ s ×ˢ t) (x₀, g x₀))
(hg : ContDiffWithinAt 𝕜 n g s x₀) (hgt : t ∈ 𝓝[g '' s] g x₀) :
∃ v ∈ 𝓝[insert x₀ s] x₀, v ⊆ insert x₀ s ∧ ∃ f' : E → F →L[𝕜] G,
(∀ x ∈ v, HasFDerivWithinAt (f x) (f' x) t (g x)) ∧
ContDiffWithinAt 𝕜 n (fun x => f' x) s x₀ := by
have hst : insert x₀ s ×ˢ t ∈ 𝓝[(fun x => (x, g x)) '' s] (x₀, g x₀) := by
refine nhdsWithin_mono _ ?_ (nhdsWithin_prod self_mem_nhdsWithin hgt)
simp_rw [image_subset_iff, mk_preimage_prod, preimage_id', subset_inter_iff, subset_insert,
true_and_iff, subset_preimage_image]
obtain ⟨v, hv, hvs, f', hvf', hf'⟩ := contDiffWithinAt_succ_iff_hasFDerivWithinAt'.mp hf
refine
⟨(fun z => (z, g z)) ⁻¹' v ∩ insert x₀ s, ?_, inter_subset_right, fun z =>
(f' (z, g z)).comp (ContinuousLinearMap.inr 𝕜 E F), ?_, ?_⟩
· refine inter_mem ?_ self_mem_nhdsWithin
have := mem_of_mem_nhdsWithin (mem_insert _ _) hv
refine mem_nhdsWithin_insert.mpr ⟨this, ?_⟩
refine (continuousWithinAt_id.prod hg.continuousWithinAt).preimage_mem_nhdsWithin' ?_
rw [← nhdsWithin_le_iff] at hst hv ⊢
exact (hst.trans <| nhdsWithin_mono _ <| subset_insert _ _).trans hv
· intro z hz
have := hvf' (z, g z) hz.1
refine this.comp _ (hasFDerivAt_prod_mk_right _ _).hasFDerivWithinAt ?_
exact mapsTo'.mpr (image_prod_mk_subset_prod_right hz.2)
· exact (hf'.continuousLinearMap_comp <| (ContinuousLinearMap.compL 𝕜 F (E × F) G).flip
(ContinuousLinearMap.inr 𝕜 E F)).comp_of_mem x₀ (contDiffWithinAt_id.prod hg) hst
#align cont_diff_within_at.has_fderiv_within_at_nhds ContDiffWithinAt.hasFDerivWithinAt_nhds
/-- The most general lemma stating that `x ↦ fderivWithin 𝕜 (f x) t (g x)` is `C^n`
at a point within a set.
To show that `x ↦ D_yf(x,y)g(x)` (taken within `t`) is `C^m` at `x₀` within `s`, we require that
* `f` is `C^n` at `(x₀, g(x₀))` within `(s ∪ {x₀}) × t` for `n ≥ m+1`.
* `g` is `C^m` at `x₀` within `s`;
* Derivatives are unique at `g(x)` within `t` for `x` sufficiently close to `x₀` within `s ∪ {x₀}`;
* `t` is a neighborhood of `g(x₀)` within `g '' s`; -/
theorem ContDiffWithinAt.fderivWithin'' {f : E → F → G} {g : E → F} {t : Set F} {n : ℕ∞}
(hf : ContDiffWithinAt 𝕜 n (Function.uncurry f) (insert x₀ s ×ˢ t) (x₀, g x₀))
(hg : ContDiffWithinAt 𝕜 m g s x₀)
(ht : ∀ᶠ x in 𝓝[insert x₀ s] x₀, UniqueDiffWithinAt 𝕜 t (g x)) (hmn : m + 1 ≤ n)
(hgt : t ∈ 𝓝[g '' s] g x₀) :
ContDiffWithinAt 𝕜 m (fun x => fderivWithin 𝕜 (f x) t (g x)) s x₀ := by
have : ∀ k : ℕ, (k : ℕ∞) ≤ m →
ContDiffWithinAt 𝕜 k (fun x => fderivWithin 𝕜 (f x) t (g x)) s x₀ := fun k hkm ↦ by
obtain ⟨v, hv, -, f', hvf', hf'⟩ :=
(hf.of_le <| (add_le_add_right hkm 1).trans hmn).hasFDerivWithinAt_nhds (hg.of_le hkm) hgt
refine hf'.congr_of_eventuallyEq_insert ?_
filter_upwards [hv, ht]
exact fun y hy h2y => (hvf' y hy).fderivWithin h2y
induction' m with m
· obtain rfl := eq_top_iff.mpr hmn
rw [contDiffWithinAt_top]
exact fun m => this m le_top
exact this _ le_rfl
#align cont_diff_within_at.fderiv_within'' ContDiffWithinAt.fderivWithin''
/-- A special case of `ContDiffWithinAt.fderivWithin''` where we require that `s ⊆ g⁻¹(t)`. -/
theorem ContDiffWithinAt.fderivWithin' {f : E → F → G} {g : E → F} {t : Set F} {n : ℕ∞}
(hf : ContDiffWithinAt 𝕜 n (Function.uncurry f) (insert x₀ s ×ˢ t) (x₀, g x₀))
(hg : ContDiffWithinAt 𝕜 m g s x₀)
(ht : ∀ᶠ x in 𝓝[insert x₀ s] x₀, UniqueDiffWithinAt 𝕜 t (g x)) (hmn : m + 1 ≤ n)
(hst : s ⊆ g ⁻¹' t) : ContDiffWithinAt 𝕜 m (fun x => fderivWithin 𝕜 (f x) t (g x)) s x₀ :=
hf.fderivWithin'' hg ht hmn <| mem_of_superset self_mem_nhdsWithin <| image_subset_iff.mpr hst
#align cont_diff_within_at.fderiv_within' ContDiffWithinAt.fderivWithin'
/-- A special case of `ContDiffWithinAt.fderivWithin'` where we require that `x₀ ∈ s` and there
are unique derivatives everywhere within `t`. -/
protected theorem ContDiffWithinAt.fderivWithin {f : E → F → G} {g : E → F} {t : Set F} {n : ℕ∞}
(hf : ContDiffWithinAt 𝕜 n (Function.uncurry f) (s ×ˢ t) (x₀, g x₀))
(hg : ContDiffWithinAt 𝕜 m g s x₀) (ht : UniqueDiffOn 𝕜 t) (hmn : m + 1 ≤ n) (hx₀ : x₀ ∈ s)
(hst : s ⊆ g ⁻¹' t) : ContDiffWithinAt 𝕜 m (fun x => fderivWithin 𝕜 (f x) t (g x)) s x₀ := by
rw [← insert_eq_self.mpr hx₀] at hf
refine hf.fderivWithin' hg ?_ hmn hst
rw [insert_eq_self.mpr hx₀]
exact eventually_of_mem self_mem_nhdsWithin fun x hx => ht _ (hst hx)
#align cont_diff_within_at.fderiv_within ContDiffWithinAt.fderivWithin
/-- `x ↦ fderivWithin 𝕜 (f x) t (g x) (k x)` is smooth at a point within a set. -/
theorem ContDiffWithinAt.fderivWithin_apply {f : E → F → G} {g k : E → F} {t : Set F} {n : ℕ∞}
(hf : ContDiffWithinAt 𝕜 n (Function.uncurry f) (s ×ˢ t) (x₀, g x₀))
(hg : ContDiffWithinAt 𝕜 m g s x₀) (hk : ContDiffWithinAt 𝕜 m k s x₀) (ht : UniqueDiffOn 𝕜 t)
(hmn : m + 1 ≤ n) (hx₀ : x₀ ∈ s) (hst : s ⊆ g ⁻¹' t) :
ContDiffWithinAt 𝕜 m (fun x => fderivWithin 𝕜 (f x) t (g x) (k x)) s x₀ :=
(contDiff_fst.clm_apply contDiff_snd).contDiffAt.comp_contDiffWithinAt x₀
((hf.fderivWithin hg ht hmn hx₀ hst).prod hk)
#align cont_diff_within_at.fderiv_within_apply ContDiffWithinAt.fderivWithin_apply
/-- `fderivWithin 𝕜 f s` is smooth at `x₀` within `s`. -/
theorem ContDiffWithinAt.fderivWithin_right (hf : ContDiffWithinAt 𝕜 n f s x₀)
(hs : UniqueDiffOn 𝕜 s) (hmn : (m + 1 : ℕ∞) ≤ n) (hx₀s : x₀ ∈ s) :
ContDiffWithinAt 𝕜 m (fderivWithin 𝕜 f s) s x₀ :=
ContDiffWithinAt.fderivWithin
(ContDiffWithinAt.comp (x₀, x₀) hf contDiffWithinAt_snd <| prod_subset_preimage_snd s s)
contDiffWithinAt_id hs hmn hx₀s (by rw [preimage_id'])
#align cont_diff_within_at.fderiv_within_right ContDiffWithinAt.fderivWithin_right
-- TODO: can we make a version of `ContDiffWithinAt.fderivWithin` for iterated derivatives?
theorem ContDiffWithinAt.iteratedFderivWithin_right {i : ℕ} (hf : ContDiffWithinAt 𝕜 n f s x₀)
(hs : UniqueDiffOn 𝕜 s) (hmn : (m + i : ℕ∞) ≤ n) (hx₀s : x₀ ∈ s) :
ContDiffWithinAt 𝕜 m (iteratedFDerivWithin 𝕜 i f s) s x₀ := by
induction' i with i hi generalizing m
· rw [ENat.coe_zero, add_zero] at hmn
exact (hf.of_le hmn).continuousLinearMap_comp
((continuousMultilinearCurryFin0 𝕜 E F).symm : _ →L[𝕜] E [×0]→L[𝕜] F)
· rw [Nat.cast_succ, add_comm _ 1, ← add_assoc] at hmn
exact ((hi hmn).fderivWithin_right hs le_rfl hx₀s).continuousLinearMap_comp
(continuousMultilinearCurryLeftEquiv 𝕜 (fun _ : Fin (i+1) ↦ E) F : _ →L[𝕜] E [×(i+1)]→L[𝕜] F)
/-- `x ↦ fderiv 𝕜 (f x) (g x)` is smooth at `x₀`. -/
protected theorem ContDiffAt.fderiv {f : E → F → G} {g : E → F} {n : ℕ∞}
(hf : ContDiffAt 𝕜 n (Function.uncurry f) (x₀, g x₀)) (hg : ContDiffAt 𝕜 m g x₀)
(hmn : m + 1 ≤ n) : ContDiffAt 𝕜 m (fun x => fderiv 𝕜 (f x) (g x)) x₀ := by
simp_rw [← fderivWithin_univ]
refine (ContDiffWithinAt.fderivWithin hf.contDiffWithinAt hg.contDiffWithinAt uniqueDiffOn_univ
hmn (mem_univ x₀) ?_).contDiffAt univ_mem
rw [preimage_univ]
#align cont_diff_at.fderiv ContDiffAt.fderiv
/-- `fderiv 𝕜 f` is smooth at `x₀`. -/
theorem ContDiffAt.fderiv_right (hf : ContDiffAt 𝕜 n f x₀) (hmn : (m + 1 : ℕ∞) ≤ n) :
ContDiffAt 𝕜 m (fderiv 𝕜 f) x₀ :=
ContDiffAt.fderiv (ContDiffAt.comp (x₀, x₀) hf contDiffAt_snd) contDiffAt_id hmn
#align cont_diff_at.fderiv_right ContDiffAt.fderiv_right
theorem ContDiffAt.iteratedFDeriv_right {i : ℕ} (hf : ContDiffAt 𝕜 n f x₀)
(hmn : (m + i : ℕ∞) ≤ n) : ContDiffAt 𝕜 m (iteratedFDeriv 𝕜 i f) x₀ := by
rw [← iteratedFDerivWithin_univ, ← contDiffWithinAt_univ] at *
exact hf.iteratedFderivWithin_right uniqueDiffOn_univ hmn trivial
/-- `x ↦ fderiv 𝕜 (f x) (g x)` is smooth. -/
protected theorem ContDiff.fderiv {f : E → F → G} {g : E → F} {n m : ℕ∞}
(hf : ContDiff 𝕜 m <| Function.uncurry f) (hg : ContDiff 𝕜 n g) (hnm : n + 1 ≤ m) :
ContDiff 𝕜 n fun x => fderiv 𝕜 (f x) (g x) :=
contDiff_iff_contDiffAt.mpr fun _ => hf.contDiffAt.fderiv hg.contDiffAt hnm
#align cont_diff.fderiv ContDiff.fderiv
/-- `fderiv 𝕜 f` is smooth. -/
theorem ContDiff.fderiv_right (hf : ContDiff 𝕜 n f) (hmn : (m + 1 : ℕ∞) ≤ n) :
ContDiff 𝕜 m (fderiv 𝕜 f) :=
contDiff_iff_contDiffAt.mpr fun _x => hf.contDiffAt.fderiv_right hmn
#align cont_diff.fderiv_right ContDiff.fderiv_right
theorem ContDiff.iteratedFDeriv_right {i : ℕ} (hf : ContDiff 𝕜 n f)
(hmn : (m + i : ℕ∞) ≤ n) : ContDiff 𝕜 m (iteratedFDeriv 𝕜 i f) :=
contDiff_iff_contDiffAt.mpr fun _x => hf.contDiffAt.iteratedFDeriv_right hmn
/-- `x ↦ fderiv 𝕜 (f x) (g x)` is continuous. -/
theorem Continuous.fderiv {f : E → F → G} {g : E → F} {n : ℕ∞}
(hf : ContDiff 𝕜 n <| Function.uncurry f) (hg : Continuous g) (hn : 1 ≤ n) :
Continuous fun x => fderiv 𝕜 (f x) (g x) :=
(hf.fderiv (contDiff_zero.mpr hg) hn).continuous
#align continuous.fderiv Continuous.fderiv
/-- `x ↦ fderiv 𝕜 (f x) (g x) (k x)` is smooth. -/
theorem ContDiff.fderiv_apply {f : E → F → G} {g k : E → F} {n m : ℕ∞}
(hf : ContDiff 𝕜 m <| Function.uncurry f) (hg : ContDiff 𝕜 n g) (hk : ContDiff 𝕜 n k)
(hnm : n + 1 ≤ m) : ContDiff 𝕜 n fun x => fderiv 𝕜 (f x) (g x) (k x) :=
(hf.fderiv hg hnm).clm_apply hk
#align cont_diff.fderiv_apply ContDiff.fderiv_apply
/-- The bundled derivative of a `C^{n+1}` function is `C^n`. -/
theorem contDiffOn_fderivWithin_apply {m n : ℕ∞} {s : Set E} {f : E → F} (hf : ContDiffOn 𝕜 n f s)
(hs : UniqueDiffOn 𝕜 s) (hmn : m + 1 ≤ n) :
ContDiffOn 𝕜 m (fun p : E × E => (fderivWithin 𝕜 f s p.1 : E →L[𝕜] F) p.2) (s ×ˢ univ) :=
((hf.fderivWithin hs hmn).comp contDiffOn_fst (prod_subset_preimage_fst _ _)).clm_apply
contDiffOn_snd
#align cont_diff_on_fderiv_within_apply contDiffOn_fderivWithin_apply
/-- If a function is at least `C^1`, its bundled derivative (mapping `(x, v)` to `Df(x) v`) is
continuous. -/
theorem ContDiffOn.continuousOn_fderivWithin_apply (hf : ContDiffOn 𝕜 n f s) (hs : UniqueDiffOn 𝕜 s)
(hn : 1 ≤ n) :
ContinuousOn (fun p : E × E => (fderivWithin 𝕜 f s p.1 : E → F) p.2) (s ×ˢ univ) :=
(contDiffOn_fderivWithin_apply hf hs <| by rwa [zero_add]).continuousOn
#align cont_diff_on.continuous_on_fderiv_within_apply ContDiffOn.continuousOn_fderivWithin_apply
/-- The bundled derivative of a `C^{n+1}` function is `C^n`. -/
theorem ContDiff.contDiff_fderiv_apply {f : E → F} (hf : ContDiff 𝕜 n f) (hmn : m + 1 ≤ n) :
ContDiff 𝕜 m fun p : E × E => (fderiv 𝕜 f p.1 : E →L[𝕜] F) p.2 := by
rw [← contDiffOn_univ] at hf ⊢
rw [← fderivWithin_univ, ← univ_prod_univ]
exact contDiffOn_fderivWithin_apply hf uniqueDiffOn_univ hmn
#align cont_diff.cont_diff_fderiv_apply ContDiff.contDiff_fderiv_apply
/-!
### Smoothness of functions `f : E → Π i, F' i`
-/
section Pi
variable {ι ι' : Type*} [Fintype ι] [Fintype ι'] {F' : ι → Type*} [∀ i, NormedAddCommGroup (F' i)]
[∀ i, NormedSpace 𝕜 (F' i)] {φ : ∀ i, E → F' i} {p' : ∀ i, E → FormalMultilinearSeries 𝕜 E (F' i)}
{Φ : E → ∀ i, F' i} {P' : E → FormalMultilinearSeries 𝕜 E (∀ i, F' i)}
theorem hasFTaylorSeriesUpToOn_pi :
HasFTaylorSeriesUpToOn n (fun x i => φ i x)
(fun x m => ContinuousMultilinearMap.pi fun i => p' i x m) s ↔
∀ i, HasFTaylorSeriesUpToOn n (φ i) (p' i) s := by
set pr := @ContinuousLinearMap.proj 𝕜 _ ι F' _ _ _
letI : ∀ (m : ℕ) (i : ι), NormedSpace 𝕜 (E[×m]→L[𝕜] F' i) := fun m i => inferInstance
set L : ∀ m : ℕ, (∀ i, E[×m]→L[𝕜] F' i) ≃ₗᵢ[𝕜] E[×m]→L[𝕜] ∀ i, F' i := fun m =>
ContinuousMultilinearMap.piₗᵢ _ _
refine ⟨fun h i => ?_, fun h => ⟨fun x hx => ?_, ?_, ?_⟩⟩
· convert h.continuousLinearMap_comp (pr i)
· ext1 i
exact (h i).zero_eq x hx
· intro m hm x hx
have := hasFDerivWithinAt_pi.2 fun i => (h i).fderivWithin m hm x hx
convert (L m).hasFDerivAt.comp_hasFDerivWithinAt x this
· intro m hm
have := continuousOn_pi.2 fun i => (h i).cont m hm
convert (L m).continuous.comp_continuousOn this
#align has_ftaylor_series_up_to_on_pi hasFTaylorSeriesUpToOn_pi
@[simp]
theorem hasFTaylorSeriesUpToOn_pi' :
HasFTaylorSeriesUpToOn n Φ P' s ↔
∀ i, HasFTaylorSeriesUpToOn n (fun x => Φ x i)
(fun x m => (@ContinuousLinearMap.proj 𝕜 _ ι F' _ _ _ i).compContinuousMultilinearMap
(P' x m)) s := by
convert hasFTaylorSeriesUpToOn_pi (𝕜 := 𝕜) (φ := fun i x ↦ Φ x i); ext; rfl
#align has_ftaylor_series_up_to_on_pi' hasFTaylorSeriesUpToOn_pi'
theorem contDiffWithinAt_pi :
ContDiffWithinAt 𝕜 n Φ s x ↔ ∀ i, ContDiffWithinAt 𝕜 n (fun x => Φ x i) s x := by
set pr := @ContinuousLinearMap.proj 𝕜 _ ι F' _ _ _
refine ⟨fun h i => h.continuousLinearMap_comp (pr i), fun h m hm => ?_⟩
choose u hux p hp using fun i => h i m hm
exact ⟨⋂ i, u i, Filter.iInter_mem.2 hux, _,
hasFTaylorSeriesUpToOn_pi.2 fun i => (hp i).mono <| iInter_subset _ _⟩
#align cont_diff_within_at_pi contDiffWithinAt_pi
theorem contDiffOn_pi : ContDiffOn 𝕜 n Φ s ↔ ∀ i, ContDiffOn 𝕜 n (fun x => Φ x i) s :=
⟨fun h _ x hx => contDiffWithinAt_pi.1 (h x hx) _, fun h x hx =>
contDiffWithinAt_pi.2 fun i => h i x hx⟩
#align cont_diff_on_pi contDiffOn_pi
theorem contDiffAt_pi : ContDiffAt 𝕜 n Φ x ↔ ∀ i, ContDiffAt 𝕜 n (fun x => Φ x i) x :=
contDiffWithinAt_pi
#align cont_diff_at_pi contDiffAt_pi
| Mathlib/Analysis/Calculus/ContDiff/Basic.lean | 1,227 | 1,228 | theorem contDiff_pi : ContDiff 𝕜 n Φ ↔ ∀ i, ContDiff 𝕜 n fun x => Φ x i := by |
simp only [← contDiffOn_univ, contDiffOn_pi]
|
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes
-/
import Mathlib.Algebra.CharP.Two
import Mathlib.Data.Nat.Factorization.Basic
import Mathlib.Data.Nat.Periodic
import Mathlib.Data.ZMod.Basic
import Mathlib.Tactic.Monotonicity
#align_import data.nat.totient from "leanprover-community/mathlib"@"5cc2dfdd3e92f340411acea4427d701dc7ed26f8"
/-!
# Euler's totient function
This file defines [Euler's totient function](https://en.wikipedia.org/wiki/Euler's_totient_function)
`Nat.totient n` which counts the number of naturals less than `n` that are coprime with `n`.
We prove the divisor sum formula, namely that `n` equals `φ` summed over the divisors of `n`. See
`sum_totient`. We also prove two lemmas to help compute totients, namely `totient_mul` and
`totient_prime_pow`.
-/
open Finset
namespace Nat
/-- Euler's totient function. This counts the number of naturals strictly less than `n` which are
coprime with `n`. -/
def totient (n : ℕ) : ℕ :=
((range n).filter n.Coprime).card
#align nat.totient Nat.totient
@[inherit_doc]
scoped notation "φ" => Nat.totient
@[simp]
theorem totient_zero : φ 0 = 0 :=
rfl
#align nat.totient_zero Nat.totient_zero
@[simp]
theorem totient_one : φ 1 = 1 := rfl
#align nat.totient_one Nat.totient_one
theorem totient_eq_card_coprime (n : ℕ) : φ n = ((range n).filter n.Coprime).card :=
rfl
#align nat.totient_eq_card_coprime Nat.totient_eq_card_coprime
/-- A characterisation of `Nat.totient` that avoids `Finset`. -/
theorem totient_eq_card_lt_and_coprime (n : ℕ) : φ n = Nat.card { m | m < n ∧ n.Coprime m } := by
let e : { m | m < n ∧ n.Coprime m } ≃ Finset.filter n.Coprime (Finset.range n) :=
{ toFun := fun m => ⟨m, by simpa only [Finset.mem_filter, Finset.mem_range] using m.property⟩
invFun := fun m => ⟨m, by simpa only [Finset.mem_filter, Finset.mem_range] using m.property⟩
left_inv := fun m => by simp only [Subtype.coe_mk, Subtype.coe_eta]
right_inv := fun m => by simp only [Subtype.coe_mk, Subtype.coe_eta] }
rw [totient_eq_card_coprime, card_congr e, card_eq_fintype_card, Fintype.card_coe]
#align nat.totient_eq_card_lt_and_coprime Nat.totient_eq_card_lt_and_coprime
theorem totient_le (n : ℕ) : φ n ≤ n :=
((range n).card_filter_le _).trans_eq (card_range n)
#align nat.totient_le Nat.totient_le
theorem totient_lt (n : ℕ) (hn : 1 < n) : φ n < n :=
(card_lt_card (filter_ssubset.2 ⟨0, by simp [hn.ne', pos_of_gt hn]⟩)).trans_eq (card_range n)
#align nat.totient_lt Nat.totient_lt
@[simp]
theorem totient_eq_zero : ∀ {n : ℕ}, φ n = 0 ↔ n = 0
| 0 => by decide
| n + 1 =>
suffices ∃ x < n + 1, (n + 1).gcd x = 1 by simpa [totient, filter_eq_empty_iff]
⟨1 % (n + 1), mod_lt _ n.succ_pos, by rw [gcd_comm, ← gcd_rec, gcd_one_right]⟩
@[simp] theorem totient_pos {n : ℕ} : 0 < φ n ↔ 0 < n := by simp [pos_iff_ne_zero]
#align nat.totient_pos Nat.totient_pos
theorem filter_coprime_Ico_eq_totient (a n : ℕ) :
((Ico n (n + a)).filter (Coprime a)).card = totient a := by
rw [totient, filter_Ico_card_eq_of_periodic, count_eq_card_filter_range]
exact periodic_coprime a
#align nat.filter_coprime_Ico_eq_totient Nat.filter_coprime_Ico_eq_totient
theorem Ico_filter_coprime_le {a : ℕ} (k n : ℕ) (a_pos : 0 < a) :
((Ico k (k + n)).filter (Coprime a)).card ≤ totient a * (n / a + 1) := by
conv_lhs => rw [← Nat.mod_add_div n a]
induction' n / a with i ih
· rw [← filter_coprime_Ico_eq_totient a k]
simp only [add_zero, mul_one, mul_zero, le_of_lt (mod_lt n a_pos),
Nat.zero_eq, zero_add]
-- Porting note: below line was `mono`
refine Finset.card_mono ?_
refine monotone_filter_left a.Coprime ?_
simp only [Finset.le_eq_subset]
exact Ico_subset_Ico rfl.le (add_le_add_left (le_of_lt (mod_lt n a_pos)) k)
simp only [mul_succ]
simp_rw [← add_assoc] at ih ⊢
calc
(filter a.Coprime (Ico k (k + n % a + a * i + a))).card = (filter a.Coprime
(Ico k (k + n % a + a * i) ∪ Ico (k + n % a + a * i) (k + n % a + a * i + a))).card := by
congr
rw [Ico_union_Ico_eq_Ico]
· rw [add_assoc]
exact le_self_add
exact le_self_add
_ ≤ (filter a.Coprime (Ico k (k + n % a + a * i))).card + a.totient := by
rw [filter_union, ← filter_coprime_Ico_eq_totient a (k + n % a + a * i)]
apply card_union_le
_ ≤ a.totient * i + a.totient + a.totient := add_le_add_right ih (totient a)
#align nat.Ico_filter_coprime_le Nat.Ico_filter_coprime_le
open ZMod
/-- Note this takes an explicit `Fintype ((ZMod n)ˣ)` argument to avoid trouble with instance
diamonds. -/
@[simp]
theorem _root_.ZMod.card_units_eq_totient (n : ℕ) [NeZero n] [Fintype (ZMod n)ˣ] :
Fintype.card (ZMod n)ˣ = φ n :=
calc
Fintype.card (ZMod n)ˣ = Fintype.card { x : ZMod n // x.val.Coprime n } :=
Fintype.card_congr ZMod.unitsEquivCoprime
_ = φ n := by
obtain ⟨m, rfl⟩ : ∃ m, n = m + 1 := exists_eq_succ_of_ne_zero NeZero.out
simp only [totient, Finset.card_eq_sum_ones, Fintype.card_subtype, Finset.sum_filter, ←
Fin.sum_univ_eq_sum_range, @Nat.coprime_comm (m + 1)]
rfl
#align zmod.card_units_eq_totient ZMod.card_units_eq_totient
theorem totient_even {n : ℕ} (hn : 2 < n) : Even n.totient := by
haveI : Fact (1 < n) := ⟨one_lt_two.trans hn⟩
haveI : NeZero n := NeZero.of_gt hn
suffices 2 = orderOf (-1 : (ZMod n)ˣ) by
rw [← ZMod.card_units_eq_totient, even_iff_two_dvd, this]
exact orderOf_dvd_card
rw [← orderOf_units, Units.coe_neg_one, orderOf_neg_one, ringChar.eq (ZMod n) n, if_neg hn.ne']
#align nat.totient_even Nat.totient_even
theorem totient_mul {m n : ℕ} (h : m.Coprime n) : φ (m * n) = φ m * φ n :=
if hmn0 : m * n = 0 then by
cases' Nat.mul_eq_zero.1 hmn0 with h h <;>
simp only [totient_zero, mul_zero, zero_mul, h]
else by
haveI : NeZero (m * n) := ⟨hmn0⟩
haveI : NeZero m := ⟨left_ne_zero_of_mul hmn0⟩
haveI : NeZero n := ⟨right_ne_zero_of_mul hmn0⟩
simp only [← ZMod.card_units_eq_totient]
rw [Fintype.card_congr (Units.mapEquiv (ZMod.chineseRemainder h).toMulEquiv).toEquiv,
Fintype.card_congr (@MulEquiv.prodUnits (ZMod m) (ZMod n) _ _).toEquiv, Fintype.card_prod]
#align nat.totient_mul Nat.totient_mul
/-- For `d ∣ n`, the totient of `n/d` equals the number of values `k < n` such that `gcd n k = d` -/
theorem totient_div_of_dvd {n d : ℕ} (hnd : d ∣ n) :
φ (n / d) = (filter (fun k : ℕ => n.gcd k = d) (range n)).card := by
rcases d.eq_zero_or_pos with (rfl | hd0); · simp [eq_zero_of_zero_dvd hnd]
rcases hnd with ⟨x, rfl⟩
rw [Nat.mul_div_cancel_left x hd0]
apply Finset.card_bij fun k _ => d * k
· simp only [mem_filter, mem_range, and_imp, Coprime]
refine fun a ha1 ha2 => ⟨(mul_lt_mul_left hd0).2 ha1, ?_⟩
rw [gcd_mul_left, ha2, mul_one]
· simp [hd0.ne']
· simp only [mem_filter, mem_range, exists_prop, and_imp]
refine fun b hb1 hb2 => ?_
have : d ∣ b := by
rw [← hb2]
apply gcd_dvd_right
rcases this with ⟨q, rfl⟩
refine ⟨q, ⟨⟨(mul_lt_mul_left hd0).1 hb1, ?_⟩, rfl⟩⟩
rwa [gcd_mul_left, mul_right_eq_self_iff hd0] at hb2
#align nat.totient_div_of_dvd Nat.totient_div_of_dvd
theorem sum_totient (n : ℕ) : n.divisors.sum φ = n := by
rcases n.eq_zero_or_pos with (rfl | hn)
· simp
rw [← sum_div_divisors n φ]
have : n = ∑ d ∈ n.divisors, (filter (fun k : ℕ => n.gcd k = d) (range n)).card := by
nth_rw 1 [← card_range n]
refine card_eq_sum_card_fiberwise fun x _ => mem_divisors.2 ⟨?_, hn.ne'⟩
apply gcd_dvd_left
nth_rw 3 [this]
exact sum_congr rfl fun x hx => totient_div_of_dvd (dvd_of_mem_divisors hx)
#align nat.sum_totient Nat.sum_totient
theorem sum_totient' (n : ℕ) : (∑ m ∈ (range n.succ).filter (· ∣ n), φ m) = n := by
convert sum_totient _ using 1
simp only [Nat.divisors, sum_filter, range_eq_Ico]
rw [sum_eq_sum_Ico_succ_bot] <;> simp
#align nat.sum_totient' Nat.sum_totient'
/-- When `p` is prime, then the totient of `p ^ (n + 1)` is `p ^ n * (p - 1)` -/
| Mathlib/Data/Nat/Totient.lean | 191 | 217 | theorem totient_prime_pow_succ {p : ℕ} (hp : p.Prime) (n : ℕ) : φ (p ^ (n + 1)) = p ^ n * (p - 1) :=
calc
φ (p ^ (n + 1)) = ((range (p ^ (n + 1))).filter (Coprime (p ^ (n + 1)))).card :=
totient_eq_card_coprime _
_ = (range (p ^ (n + 1)) \ (range (p ^ n)).image (· * p)).card :=
(congr_arg card
(by
rw [sdiff_eq_filter]
apply filter_congr
simp only [mem_range, mem_filter, coprime_pow_left_iff n.succ_pos, mem_image, not_exists,
hp.coprime_iff_not_dvd]
intro a ha
constructor
· intro hap b h; rcases h with ⟨_, rfl⟩
exact hap (dvd_mul_left _ _)
· rintro h ⟨b, rfl⟩
rw [pow_succ'] at ha
exact h b ⟨lt_of_mul_lt_mul_left ha (zero_le _), mul_comm _ _⟩))
_ = _ := by |
have h1 : Function.Injective (· * p) := mul_left_injective₀ hp.ne_zero
have h2 : (range (p ^ n)).image (· * p) ⊆ range (p ^ (n + 1)) := fun a => by
simp only [mem_image, mem_range, exists_imp]
rintro b ⟨h, rfl⟩
rw [Nat.pow_succ]
exact (mul_lt_mul_right hp.pos).2 h
rw [card_sdiff h2, Finset.card_image_of_injective _ h1, card_range, card_range, ←
one_mul (p ^ n), pow_succ', ← tsub_mul, one_mul, mul_comm]
|
/-
Copyright (c) 2018 Patrick Massot. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Patrick Massot, Johannes Hölzl, Yaël Dillies
-/
import Mathlib.Analysis.Normed.Group.Seminorm
import Mathlib.Order.LiminfLimsup
import Mathlib.Topology.Instances.Rat
import Mathlib.Topology.MetricSpace.Algebra
import Mathlib.Topology.MetricSpace.IsometricSMul
import Mathlib.Topology.Sequences
#align_import analysis.normed.group.basic from "leanprover-community/mathlib"@"41bef4ae1254365bc190aee63b947674d2977f01"
/-!
# Normed (semi)groups
In this file we define 10 classes:
* `Norm`, `NNNorm`: auxiliary classes endowing a type `α` with a function `norm : α → ℝ`
(notation: `‖x‖`) and `nnnorm : α → ℝ≥0` (notation: `‖x‖₊`), respectively;
* `Seminormed...Group`: A seminormed (additive) (commutative) group is an (additive) (commutative)
group with a norm and a compatible pseudometric space structure:
`∀ x y, dist x y = ‖x / y‖` or `∀ x y, dist x y = ‖x - y‖`, depending on the group operation.
* `Normed...Group`: A normed (additive) (commutative) group is an (additive) (commutative) group
with a norm and a compatible metric space structure.
We also prove basic properties of (semi)normed groups and provide some instances.
## TODO
This file is huge; move material into separate files,
such as `Mathlib/Analysis/Normed/Group/Lemmas.lean`.
## Notes
The current convention `dist x y = ‖x - y‖` means that the distance is invariant under right
addition, but actions in mathlib are usually from the left. This means we might want to change it to
`dist x y = ‖-x + y‖`.
The normed group hierarchy would lend itself well to a mixin design (that is, having
`SeminormedGroup` and `SeminormedAddGroup` not extend `Group` and `AddGroup`), but we choose not
to for performance concerns.
## Tags
normed group
-/
variable {𝓕 𝕜 α ι κ E F G : Type*}
open Filter Function Metric Bornology
open ENNReal Filter NNReal Uniformity Pointwise Topology
/-- Auxiliary class, endowing a type `E` with a function `norm : E → ℝ` with notation `‖x‖`. This
class is designed to be extended in more interesting classes specifying the properties of the norm.
-/
@[notation_class]
class Norm (E : Type*) where
/-- the `ℝ`-valued norm function. -/
norm : E → ℝ
#align has_norm Norm
/-- Auxiliary class, endowing a type `α` with a function `nnnorm : α → ℝ≥0` with notation `‖x‖₊`. -/
@[notation_class]
class NNNorm (E : Type*) where
/-- the `ℝ≥0`-valued norm function. -/
nnnorm : E → ℝ≥0
#align has_nnnorm NNNorm
export Norm (norm)
export NNNorm (nnnorm)
@[inherit_doc]
notation "‖" e "‖" => norm e
@[inherit_doc]
notation "‖" e "‖₊" => nnnorm e
/-- A seminormed group is an additive group endowed with a norm for which `dist x y = ‖x - y‖`
defines a pseudometric space structure. -/
class SeminormedAddGroup (E : Type*) extends Norm E, AddGroup E, PseudoMetricSpace E where
dist := fun x y => ‖x - y‖
/-- The distance function is induced by the norm. -/
dist_eq : ∀ x y, dist x y = ‖x - y‖ := by aesop
#align seminormed_add_group SeminormedAddGroup
/-- A seminormed group is a group endowed with a norm for which `dist x y = ‖x / y‖` defines a
pseudometric space structure. -/
@[to_additive]
class SeminormedGroup (E : Type*) extends Norm E, Group E, PseudoMetricSpace E where
dist := fun x y => ‖x / y‖
/-- The distance function is induced by the norm. -/
dist_eq : ∀ x y, dist x y = ‖x / y‖ := by aesop
#align seminormed_group SeminormedGroup
/-- A normed group is an additive group endowed with a norm for which `dist x y = ‖x - y‖` defines a
metric space structure. -/
class NormedAddGroup (E : Type*) extends Norm E, AddGroup E, MetricSpace E where
dist := fun x y => ‖x - y‖
/-- The distance function is induced by the norm. -/
dist_eq : ∀ x y, dist x y = ‖x - y‖ := by aesop
#align normed_add_group NormedAddGroup
/-- A normed group is a group endowed with a norm for which `dist x y = ‖x / y‖` defines a metric
space structure. -/
@[to_additive]
class NormedGroup (E : Type*) extends Norm E, Group E, MetricSpace E where
dist := fun x y => ‖x / y‖
/-- The distance function is induced by the norm. -/
dist_eq : ∀ x y, dist x y = ‖x / y‖ := by aesop
#align normed_group NormedGroup
/-- A seminormed group is an additive group endowed with a norm for which `dist x y = ‖x - y‖`
defines a pseudometric space structure. -/
class SeminormedAddCommGroup (E : Type*) extends Norm E, AddCommGroup E,
PseudoMetricSpace E where
dist := fun x y => ‖x - y‖
/-- The distance function is induced by the norm. -/
dist_eq : ∀ x y, dist x y = ‖x - y‖ := by aesop
#align seminormed_add_comm_group SeminormedAddCommGroup
/-- A seminormed group is a group endowed with a norm for which `dist x y = ‖x / y‖`
defines a pseudometric space structure. -/
@[to_additive]
class SeminormedCommGroup (E : Type*) extends Norm E, CommGroup E, PseudoMetricSpace E where
dist := fun x y => ‖x / y‖
/-- The distance function is induced by the norm. -/
dist_eq : ∀ x y, dist x y = ‖x / y‖ := by aesop
#align seminormed_comm_group SeminormedCommGroup
/-- A normed group is an additive group endowed with a norm for which `dist x y = ‖x - y‖` defines a
metric space structure. -/
class NormedAddCommGroup (E : Type*) extends Norm E, AddCommGroup E, MetricSpace E where
dist := fun x y => ‖x - y‖
/-- The distance function is induced by the norm. -/
dist_eq : ∀ x y, dist x y = ‖x - y‖ := by aesop
#align normed_add_comm_group NormedAddCommGroup
/-- A normed group is a group endowed with a norm for which `dist x y = ‖x / y‖` defines a metric
space structure. -/
@[to_additive]
class NormedCommGroup (E : Type*) extends Norm E, CommGroup E, MetricSpace E where
dist := fun x y => ‖x / y‖
/-- The distance function is induced by the norm. -/
dist_eq : ∀ x y, dist x y = ‖x / y‖ := by aesop
#align normed_comm_group NormedCommGroup
-- See note [lower instance priority]
@[to_additive]
instance (priority := 100) NormedGroup.toSeminormedGroup [NormedGroup E] : SeminormedGroup E :=
{ ‹NormedGroup E› with }
#align normed_group.to_seminormed_group NormedGroup.toSeminormedGroup
#align normed_add_group.to_seminormed_add_group NormedAddGroup.toSeminormedAddGroup
-- See note [lower instance priority]
@[to_additive]
instance (priority := 100) NormedCommGroup.toSeminormedCommGroup [NormedCommGroup E] :
SeminormedCommGroup E :=
{ ‹NormedCommGroup E› with }
#align normed_comm_group.to_seminormed_comm_group NormedCommGroup.toSeminormedCommGroup
#align normed_add_comm_group.to_seminormed_add_comm_group NormedAddCommGroup.toSeminormedAddCommGroup
-- See note [lower instance priority]
@[to_additive]
instance (priority := 100) SeminormedCommGroup.toSeminormedGroup [SeminormedCommGroup E] :
SeminormedGroup E :=
{ ‹SeminormedCommGroup E› with }
#align seminormed_comm_group.to_seminormed_group SeminormedCommGroup.toSeminormedGroup
#align seminormed_add_comm_group.to_seminormed_add_group SeminormedAddCommGroup.toSeminormedAddGroup
-- See note [lower instance priority]
@[to_additive]
instance (priority := 100) NormedCommGroup.toNormedGroup [NormedCommGroup E] : NormedGroup E :=
{ ‹NormedCommGroup E› with }
#align normed_comm_group.to_normed_group NormedCommGroup.toNormedGroup
#align normed_add_comm_group.to_normed_add_group NormedAddCommGroup.toNormedAddGroup
-- See note [reducible non-instances]
/-- Construct a `NormedGroup` from a `SeminormedGroup` satisfying `∀ x, ‖x‖ = 0 → x = 1`. This
avoids having to go back to the `(Pseudo)MetricSpace` level when declaring a `NormedGroup`
instance as a special case of a more general `SeminormedGroup` instance. -/
@[to_additive (attr := reducible) "Construct a `NormedAddGroup` from a `SeminormedAddGroup`
satisfying `∀ x, ‖x‖ = 0 → x = 0`. This avoids having to go back to the `(Pseudo)MetricSpace`
level when declaring a `NormedAddGroup` instance as a special case of a more general
`SeminormedAddGroup` instance."]
def NormedGroup.ofSeparation [SeminormedGroup E] (h : ∀ x : E, ‖x‖ = 0 → x = 1) :
NormedGroup E where
dist_eq := ‹SeminormedGroup E›.dist_eq
toMetricSpace :=
{ eq_of_dist_eq_zero := fun hxy =>
div_eq_one.1 <| h _ <| by exact (‹SeminormedGroup E›.dist_eq _ _).symm.trans hxy }
-- Porting note: the `rwa` no longer worked, but it was easy enough to provide the term.
-- however, notice that if you make `x` and `y` accessible, then the following does work:
-- `have := ‹SeminormedGroup E›.dist_eq x y; rwa [← this]`, so I'm not sure why the `rwa`
-- was broken.
#align normed_group.of_separation NormedGroup.ofSeparation
#align normed_add_group.of_separation NormedAddGroup.ofSeparation
-- See note [reducible non-instances]
/-- Construct a `NormedCommGroup` from a `SeminormedCommGroup` satisfying
`∀ x, ‖x‖ = 0 → x = 1`. This avoids having to go back to the `(Pseudo)MetricSpace` level when
declaring a `NormedCommGroup` instance as a special case of a more general `SeminormedCommGroup`
instance. -/
@[to_additive (attr := reducible) "Construct a `NormedAddCommGroup` from a
`SeminormedAddCommGroup` satisfying `∀ x, ‖x‖ = 0 → x = 0`. This avoids having to go back to the
`(Pseudo)MetricSpace` level when declaring a `NormedAddCommGroup` instance as a special case
of a more general `SeminormedAddCommGroup` instance."]
def NormedCommGroup.ofSeparation [SeminormedCommGroup E] (h : ∀ x : E, ‖x‖ = 0 → x = 1) :
NormedCommGroup E :=
{ ‹SeminormedCommGroup E›, NormedGroup.ofSeparation h with }
#align normed_comm_group.of_separation NormedCommGroup.ofSeparation
#align normed_add_comm_group.of_separation NormedAddCommGroup.ofSeparation
-- See note [reducible non-instances]
/-- Construct a seminormed group from a multiplication-invariant distance. -/
@[to_additive (attr := reducible)
"Construct a seminormed group from a translation-invariant distance."]
def SeminormedGroup.ofMulDist [Norm E] [Group E] [PseudoMetricSpace E]
(h₁ : ∀ x : E, ‖x‖ = dist x 1) (h₂ : ∀ x y z : E, dist x y ≤ dist (x * z) (y * z)) :
SeminormedGroup E where
dist_eq x y := by
rw [h₁]; apply le_antisymm
· simpa only [div_eq_mul_inv, ← mul_right_inv y] using h₂ _ _ _
· simpa only [div_mul_cancel, one_mul] using h₂ (x / y) 1 y
#align seminormed_group.of_mul_dist SeminormedGroup.ofMulDist
#align seminormed_add_group.of_add_dist SeminormedAddGroup.ofAddDist
-- See note [reducible non-instances]
/-- Construct a seminormed group from a multiplication-invariant pseudodistance. -/
@[to_additive (attr := reducible)
"Construct a seminormed group from a translation-invariant pseudodistance."]
def SeminormedGroup.ofMulDist' [Norm E] [Group E] [PseudoMetricSpace E]
(h₁ : ∀ x : E, ‖x‖ = dist x 1) (h₂ : ∀ x y z : E, dist (x * z) (y * z) ≤ dist x y) :
SeminormedGroup E where
dist_eq x y := by
rw [h₁]; apply le_antisymm
· simpa only [div_mul_cancel, one_mul] using h₂ (x / y) 1 y
· simpa only [div_eq_mul_inv, ← mul_right_inv y] using h₂ _ _ _
#align seminormed_group.of_mul_dist' SeminormedGroup.ofMulDist'
#align seminormed_add_group.of_add_dist' SeminormedAddGroup.ofAddDist'
-- See note [reducible non-instances]
/-- Construct a seminormed group from a multiplication-invariant pseudodistance. -/
@[to_additive (attr := reducible)
"Construct a seminormed group from a translation-invariant pseudodistance."]
def SeminormedCommGroup.ofMulDist [Norm E] [CommGroup E] [PseudoMetricSpace E]
(h₁ : ∀ x : E, ‖x‖ = dist x 1) (h₂ : ∀ x y z : E, dist x y ≤ dist (x * z) (y * z)) :
SeminormedCommGroup E :=
{ SeminormedGroup.ofMulDist h₁ h₂ with
mul_comm := mul_comm }
#align seminormed_comm_group.of_mul_dist SeminormedCommGroup.ofMulDist
#align seminormed_add_comm_group.of_add_dist SeminormedAddCommGroup.ofAddDist
-- See note [reducible non-instances]
/-- Construct a seminormed group from a multiplication-invariant pseudodistance. -/
@[to_additive (attr := reducible)
"Construct a seminormed group from a translation-invariant pseudodistance."]
def SeminormedCommGroup.ofMulDist' [Norm E] [CommGroup E] [PseudoMetricSpace E]
(h₁ : ∀ x : E, ‖x‖ = dist x 1) (h₂ : ∀ x y z : E, dist (x * z) (y * z) ≤ dist x y) :
SeminormedCommGroup E :=
{ SeminormedGroup.ofMulDist' h₁ h₂ with
mul_comm := mul_comm }
#align seminormed_comm_group.of_mul_dist' SeminormedCommGroup.ofMulDist'
#align seminormed_add_comm_group.of_add_dist' SeminormedAddCommGroup.ofAddDist'
-- See note [reducible non-instances]
/-- Construct a normed group from a multiplication-invariant distance. -/
@[to_additive (attr := reducible)
"Construct a normed group from a translation-invariant distance."]
def NormedGroup.ofMulDist [Norm E] [Group E] [MetricSpace E] (h₁ : ∀ x : E, ‖x‖ = dist x 1)
(h₂ : ∀ x y z : E, dist x y ≤ dist (x * z) (y * z)) : NormedGroup E :=
{ SeminormedGroup.ofMulDist h₁ h₂ with
eq_of_dist_eq_zero := eq_of_dist_eq_zero }
#align normed_group.of_mul_dist NormedGroup.ofMulDist
#align normed_add_group.of_add_dist NormedAddGroup.ofAddDist
-- See note [reducible non-instances]
/-- Construct a normed group from a multiplication-invariant pseudodistance. -/
@[to_additive (attr := reducible)
"Construct a normed group from a translation-invariant pseudodistance."]
def NormedGroup.ofMulDist' [Norm E] [Group E] [MetricSpace E] (h₁ : ∀ x : E, ‖x‖ = dist x 1)
(h₂ : ∀ x y z : E, dist (x * z) (y * z) ≤ dist x y) : NormedGroup E :=
{ SeminormedGroup.ofMulDist' h₁ h₂ with
eq_of_dist_eq_zero := eq_of_dist_eq_zero }
#align normed_group.of_mul_dist' NormedGroup.ofMulDist'
#align normed_add_group.of_add_dist' NormedAddGroup.ofAddDist'
-- See note [reducible non-instances]
/-- Construct a normed group from a multiplication-invariant pseudodistance. -/
@[to_additive (attr := reducible)
"Construct a normed group from a translation-invariant pseudodistance."]
def NormedCommGroup.ofMulDist [Norm E] [CommGroup E] [MetricSpace E]
(h₁ : ∀ x : E, ‖x‖ = dist x 1) (h₂ : ∀ x y z : E, dist x y ≤ dist (x * z) (y * z)) :
NormedCommGroup E :=
{ NormedGroup.ofMulDist h₁ h₂ with
mul_comm := mul_comm }
#align normed_comm_group.of_mul_dist NormedCommGroup.ofMulDist
#align normed_add_comm_group.of_add_dist NormedAddCommGroup.ofAddDist
-- See note [reducible non-instances]
/-- Construct a normed group from a multiplication-invariant pseudodistance. -/
@[to_additive (attr := reducible)
"Construct a normed group from a translation-invariant pseudodistance."]
def NormedCommGroup.ofMulDist' [Norm E] [CommGroup E] [MetricSpace E]
(h₁ : ∀ x : E, ‖x‖ = dist x 1) (h₂ : ∀ x y z : E, dist (x * z) (y * z) ≤ dist x y) :
NormedCommGroup E :=
{ NormedGroup.ofMulDist' h₁ h₂ with
mul_comm := mul_comm }
#align normed_comm_group.of_mul_dist' NormedCommGroup.ofMulDist'
#align normed_add_comm_group.of_add_dist' NormedAddCommGroup.ofAddDist'
-- See note [reducible non-instances]
/-- Construct a seminormed group from a seminorm, i.e., registering the pseudodistance and the
pseudometric space structure from the seminorm properties. Note that in most cases this instance
creates bad definitional equalities (e.g., it does not take into account a possibly existing
`UniformSpace` instance on `E`). -/
@[to_additive (attr := reducible)
"Construct a seminormed group from a seminorm, i.e., registering the pseudodistance
and the pseudometric space structure from the seminorm properties. Note that in most cases this
instance creates bad definitional equalities (e.g., it does not take into account a possibly
existing `UniformSpace` instance on `E`)."]
def GroupSeminorm.toSeminormedGroup [Group E] (f : GroupSeminorm E) : SeminormedGroup E where
dist x y := f (x / y)
norm := f
dist_eq x y := rfl
dist_self x := by simp only [div_self', map_one_eq_zero]
dist_triangle := le_map_div_add_map_div f
dist_comm := map_div_rev f
edist_dist x y := by exact ENNReal.coe_nnreal_eq _
-- Porting note: how did `mathlib3` solve this automatically?
#align group_seminorm.to_seminormed_group GroupSeminorm.toSeminormedGroup
#align add_group_seminorm.to_seminormed_add_group AddGroupSeminorm.toSeminormedAddGroup
-- See note [reducible non-instances]
/-- Construct a seminormed group from a seminorm, i.e., registering the pseudodistance and the
pseudometric space structure from the seminorm properties. Note that in most cases this instance
creates bad definitional equalities (e.g., it does not take into account a possibly existing
`UniformSpace` instance on `E`). -/
@[to_additive (attr := reducible)
"Construct a seminormed group from a seminorm, i.e., registering the pseudodistance
and the pseudometric space structure from the seminorm properties. Note that in most cases this
instance creates bad definitional equalities (e.g., it does not take into account a possibly
existing `UniformSpace` instance on `E`)."]
def GroupSeminorm.toSeminormedCommGroup [CommGroup E] (f : GroupSeminorm E) :
SeminormedCommGroup E :=
{ f.toSeminormedGroup with
mul_comm := mul_comm }
#align group_seminorm.to_seminormed_comm_group GroupSeminorm.toSeminormedCommGroup
#align add_group_seminorm.to_seminormed_add_comm_group AddGroupSeminorm.toSeminormedAddCommGroup
-- See note [reducible non-instances]
/-- Construct a normed group from a norm, i.e., registering the distance and the metric space
structure from the norm properties. Note that in most cases this instance creates bad definitional
equalities (e.g., it does not take into account a possibly existing `UniformSpace` instance on
`E`). -/
@[to_additive (attr := reducible)
"Construct a normed group from a norm, i.e., registering the distance and the metric
space structure from the norm properties. Note that in most cases this instance creates bad
definitional equalities (e.g., it does not take into account a possibly existing `UniformSpace`
instance on `E`)."]
def GroupNorm.toNormedGroup [Group E] (f : GroupNorm E) : NormedGroup E :=
{ f.toGroupSeminorm.toSeminormedGroup with
eq_of_dist_eq_zero := fun h => div_eq_one.1 <| eq_one_of_map_eq_zero f h }
#align group_norm.to_normed_group GroupNorm.toNormedGroup
#align add_group_norm.to_normed_add_group AddGroupNorm.toNormedAddGroup
-- See note [reducible non-instances]
/-- Construct a normed group from a norm, i.e., registering the distance and the metric space
structure from the norm properties. Note that in most cases this instance creates bad definitional
equalities (e.g., it does not take into account a possibly existing `UniformSpace` instance on
`E`). -/
@[to_additive (attr := reducible)
"Construct a normed group from a norm, i.e., registering the distance and the metric
space structure from the norm properties. Note that in most cases this instance creates bad
definitional equalities (e.g., it does not take into account a possibly existing `UniformSpace`
instance on `E`)."]
def GroupNorm.toNormedCommGroup [CommGroup E] (f : GroupNorm E) : NormedCommGroup E :=
{ f.toNormedGroup with
mul_comm := mul_comm }
#align group_norm.to_normed_comm_group GroupNorm.toNormedCommGroup
#align add_group_norm.to_normed_add_comm_group AddGroupNorm.toNormedAddCommGroup
instance PUnit.normedAddCommGroup : NormedAddCommGroup PUnit where
norm := Function.const _ 0
dist_eq _ _ := rfl
@[simp]
theorem PUnit.norm_eq_zero (r : PUnit) : ‖r‖ = 0 :=
rfl
#align punit.norm_eq_zero PUnit.norm_eq_zero
section SeminormedGroup
variable [SeminormedGroup E] [SeminormedGroup F] [SeminormedGroup G] {s : Set E}
{a a₁ a₂ b b₁ b₂ : E} {r r₁ r₂ : ℝ}
@[to_additive]
theorem dist_eq_norm_div (a b : E) : dist a b = ‖a / b‖ :=
SeminormedGroup.dist_eq _ _
#align dist_eq_norm_div dist_eq_norm_div
#align dist_eq_norm_sub dist_eq_norm_sub
@[to_additive]
theorem dist_eq_norm_div' (a b : E) : dist a b = ‖b / a‖ := by rw [dist_comm, dist_eq_norm_div]
#align dist_eq_norm_div' dist_eq_norm_div'
#align dist_eq_norm_sub' dist_eq_norm_sub'
alias dist_eq_norm := dist_eq_norm_sub
#align dist_eq_norm dist_eq_norm
alias dist_eq_norm' := dist_eq_norm_sub'
#align dist_eq_norm' dist_eq_norm'
@[to_additive]
instance NormedGroup.to_isometricSMul_right : IsometricSMul Eᵐᵒᵖ E :=
⟨fun a => Isometry.of_dist_eq fun b c => by simp [dist_eq_norm_div]⟩
#align normed_group.to_has_isometric_smul_right NormedGroup.to_isometricSMul_right
#align normed_add_group.to_has_isometric_vadd_right NormedAddGroup.to_isometricVAdd_right
@[to_additive (attr := simp)]
theorem dist_one_right (a : E) : dist a 1 = ‖a‖ := by rw [dist_eq_norm_div, div_one]
#align dist_one_right dist_one_right
#align dist_zero_right dist_zero_right
@[to_additive]
theorem inseparable_one_iff_norm {a : E} : Inseparable a 1 ↔ ‖a‖ = 0 := by
rw [Metric.inseparable_iff, dist_one_right]
@[to_additive (attr := simp)]
theorem dist_one_left : dist (1 : E) = norm :=
funext fun a => by rw [dist_comm, dist_one_right]
#align dist_one_left dist_one_left
#align dist_zero_left dist_zero_left
@[to_additive]
theorem Isometry.norm_map_of_map_one {f : E → F} (hi : Isometry f) (h₁ : f 1 = 1) (x : E) :
‖f x‖ = ‖x‖ := by rw [← dist_one_right, ← h₁, hi.dist_eq, dist_one_right]
#align isometry.norm_map_of_map_one Isometry.norm_map_of_map_one
#align isometry.norm_map_of_map_zero Isometry.norm_map_of_map_zero
@[to_additive (attr := simp) comap_norm_atTop]
theorem comap_norm_atTop' : comap norm atTop = cobounded E := by
simpa only [dist_one_right] using comap_dist_right_atTop (1 : E)
@[to_additive Filter.HasBasis.cobounded_of_norm]
lemma Filter.HasBasis.cobounded_of_norm' {ι : Sort*} {p : ι → Prop} {s : ι → Set ℝ}
(h : HasBasis atTop p s) : HasBasis (cobounded E) p fun i ↦ norm ⁻¹' s i :=
comap_norm_atTop' (E := E) ▸ h.comap _
@[to_additive Filter.hasBasis_cobounded_norm]
lemma Filter.hasBasis_cobounded_norm' : HasBasis (cobounded E) (fun _ ↦ True) ({x | · ≤ ‖x‖}) :=
atTop_basis.cobounded_of_norm'
@[to_additive (attr := simp) tendsto_norm_atTop_iff_cobounded]
theorem tendsto_norm_atTop_iff_cobounded' {f : α → E} {l : Filter α} :
Tendsto (‖f ·‖) l atTop ↔ Tendsto f l (cobounded E) := by
rw [← comap_norm_atTop', tendsto_comap_iff]; rfl
@[to_additive tendsto_norm_cobounded_atTop]
theorem tendsto_norm_cobounded_atTop' : Tendsto norm (cobounded E) atTop :=
tendsto_norm_atTop_iff_cobounded'.2 tendsto_id
@[to_additive eventually_cobounded_le_norm]
lemma eventually_cobounded_le_norm' (a : ℝ) : ∀ᶠ x in cobounded E, a ≤ ‖x‖ :=
tendsto_norm_cobounded_atTop'.eventually_ge_atTop a
@[to_additive tendsto_norm_cocompact_atTop]
theorem tendsto_norm_cocompact_atTop' [ProperSpace E] : Tendsto norm (cocompact E) atTop :=
cobounded_eq_cocompact (α := E) ▸ tendsto_norm_cobounded_atTop'
#align tendsto_norm_cocompact_at_top' tendsto_norm_cocompact_atTop'
#align tendsto_norm_cocompact_at_top tendsto_norm_cocompact_atTop
@[to_additive]
theorem norm_div_rev (a b : E) : ‖a / b‖ = ‖b / a‖ := by
simpa only [dist_eq_norm_div] using dist_comm a b
#align norm_div_rev norm_div_rev
#align norm_sub_rev norm_sub_rev
@[to_additive (attr := simp) norm_neg]
theorem norm_inv' (a : E) : ‖a⁻¹‖ = ‖a‖ := by simpa using norm_div_rev 1 a
#align norm_inv' norm_inv'
#align norm_neg norm_neg
open scoped symmDiff in
@[to_additive]
theorem dist_mulIndicator (s t : Set α) (f : α → E) (x : α) :
dist (s.mulIndicator f x) (t.mulIndicator f x) = ‖(s ∆ t).mulIndicator f x‖ := by
rw [dist_eq_norm_div, Set.apply_mulIndicator_symmDiff norm_inv']
@[to_additive (attr := simp)]
theorem dist_mul_self_right (a b : E) : dist b (a * b) = ‖a‖ := by
rw [← dist_one_left, ← dist_mul_right 1 a b, one_mul]
#align dist_mul_self_right dist_mul_self_right
#align dist_add_self_right dist_add_self_right
@[to_additive (attr := simp)]
theorem dist_mul_self_left (a b : E) : dist (a * b) b = ‖a‖ := by
rw [dist_comm, dist_mul_self_right]
#align dist_mul_self_left dist_mul_self_left
#align dist_add_self_left dist_add_self_left
@[to_additive (attr := simp)]
theorem dist_div_eq_dist_mul_left (a b c : E) : dist (a / b) c = dist a (c * b) := by
rw [← dist_mul_right _ _ b, div_mul_cancel]
#align dist_div_eq_dist_mul_left dist_div_eq_dist_mul_left
#align dist_sub_eq_dist_add_left dist_sub_eq_dist_add_left
@[to_additive (attr := simp)]
theorem dist_div_eq_dist_mul_right (a b c : E) : dist a (b / c) = dist (a * c) b := by
rw [← dist_mul_right _ _ c, div_mul_cancel]
#align dist_div_eq_dist_mul_right dist_div_eq_dist_mul_right
#align dist_sub_eq_dist_add_right dist_sub_eq_dist_add_right
@[to_additive (attr := simp)]
lemma Filter.inv_cobounded : (cobounded E)⁻¹ = cobounded E := by
simp only [← comap_norm_atTop', ← Filter.comap_inv, comap_comap, (· ∘ ·), norm_inv']
/-- In a (semi)normed group, inversion `x ↦ x⁻¹` tends to infinity at infinity. -/
@[to_additive "In a (semi)normed group, negation `x ↦ -x` tends to infinity at infinity."]
theorem Filter.tendsto_inv_cobounded : Tendsto Inv.inv (cobounded E) (cobounded E) :=
inv_cobounded.le
#align filter.tendsto_inv_cobounded Filter.tendsto_inv_cobounded
#align filter.tendsto_neg_cobounded Filter.tendsto_neg_cobounded
/-- **Triangle inequality** for the norm. -/
@[to_additive norm_add_le "**Triangle inequality** for the norm."]
theorem norm_mul_le' (a b : E) : ‖a * b‖ ≤ ‖a‖ + ‖b‖ := by
simpa [dist_eq_norm_div] using dist_triangle a 1 b⁻¹
#align norm_mul_le' norm_mul_le'
#align norm_add_le norm_add_le
@[to_additive]
theorem norm_mul_le_of_le (h₁ : ‖a₁‖ ≤ r₁) (h₂ : ‖a₂‖ ≤ r₂) : ‖a₁ * a₂‖ ≤ r₁ + r₂ :=
(norm_mul_le' a₁ a₂).trans <| add_le_add h₁ h₂
#align norm_mul_le_of_le norm_mul_le_of_le
#align norm_add_le_of_le norm_add_le_of_le
@[to_additive norm_add₃_le]
theorem norm_mul₃_le (a b c : E) : ‖a * b * c‖ ≤ ‖a‖ + ‖b‖ + ‖c‖ :=
norm_mul_le_of_le (norm_mul_le' _ _) le_rfl
#align norm_mul₃_le norm_mul₃_le
#align norm_add₃_le norm_add₃_le
@[to_additive]
lemma norm_div_le_norm_div_add_norm_div (a b c : E) : ‖a / c‖ ≤ ‖a / b‖ + ‖b / c‖ := by
simpa only [dist_eq_norm_div] using dist_triangle a b c
@[to_additive (attr := simp) norm_nonneg]
theorem norm_nonneg' (a : E) : 0 ≤ ‖a‖ := by
rw [← dist_one_right]
exact dist_nonneg
#align norm_nonneg' norm_nonneg'
#align norm_nonneg norm_nonneg
@[to_additive (attr := simp) abs_norm]
theorem abs_norm' (z : E) : |‖z‖| = ‖z‖ := abs_of_nonneg <| norm_nonneg' _
#align abs_norm abs_norm
namespace Mathlib.Meta.Positivity
open Lean Meta Qq Function
/-- Extension for the `positivity` tactic: multiplicative norms are nonnegative, via
`norm_nonneg'`. -/
@[positivity Norm.norm _]
def evalMulNorm : PositivityExt where eval {u α} _zα _pα e := do
match u, α, e with
| 0, ~q(ℝ), ~q(@Norm.norm $β $instDist $a) =>
let _inst ← synthInstanceQ q(SeminormedGroup $β)
assertInstancesCommute
pure (.nonnegative q(norm_nonneg' $a))
| _, _, _ => throwError "not ‖ · ‖"
/-- Extension for the `positivity` tactic: additive norms are nonnegative, via `norm_nonneg`. -/
@[positivity Norm.norm _]
def evalAddNorm : PositivityExt where eval {u α} _zα _pα e := do
match u, α, e with
| 0, ~q(ℝ), ~q(@Norm.norm $β $instDist $a) =>
let _inst ← synthInstanceQ q(SeminormedAddGroup $β)
assertInstancesCommute
pure (.nonnegative q(norm_nonneg $a))
| _, _, _ => throwError "not ‖ · ‖"
end Mathlib.Meta.Positivity
@[to_additive (attr := simp) norm_zero]
theorem norm_one' : ‖(1 : E)‖ = 0 := by rw [← dist_one_right, dist_self]
#align norm_one' norm_one'
#align norm_zero norm_zero
@[to_additive]
theorem ne_one_of_norm_ne_zero : ‖a‖ ≠ 0 → a ≠ 1 :=
mt <| by
rintro rfl
exact norm_one'
#align ne_one_of_norm_ne_zero ne_one_of_norm_ne_zero
#align ne_zero_of_norm_ne_zero ne_zero_of_norm_ne_zero
@[to_additive (attr := nontriviality) norm_of_subsingleton]
theorem norm_of_subsingleton' [Subsingleton E] (a : E) : ‖a‖ = 0 := by
rw [Subsingleton.elim a 1, norm_one']
#align norm_of_subsingleton' norm_of_subsingleton'
#align norm_of_subsingleton norm_of_subsingleton
@[to_additive zero_lt_one_add_norm_sq]
theorem zero_lt_one_add_norm_sq' (x : E) : 0 < 1 + ‖x‖ ^ 2 := by
positivity
#align zero_lt_one_add_norm_sq' zero_lt_one_add_norm_sq'
#align zero_lt_one_add_norm_sq zero_lt_one_add_norm_sq
@[to_additive]
theorem norm_div_le (a b : E) : ‖a / b‖ ≤ ‖a‖ + ‖b‖ := by
simpa [dist_eq_norm_div] using dist_triangle a 1 b
#align norm_div_le norm_div_le
#align norm_sub_le norm_sub_le
@[to_additive]
theorem norm_div_le_of_le {r₁ r₂ : ℝ} (H₁ : ‖a₁‖ ≤ r₁) (H₂ : ‖a₂‖ ≤ r₂) : ‖a₁ / a₂‖ ≤ r₁ + r₂ :=
(norm_div_le a₁ a₂).trans <| add_le_add H₁ H₂
#align norm_div_le_of_le norm_div_le_of_le
#align norm_sub_le_of_le norm_sub_le_of_le
@[to_additive dist_le_norm_add_norm]
theorem dist_le_norm_add_norm' (a b : E) : dist a b ≤ ‖a‖ + ‖b‖ := by
rw [dist_eq_norm_div]
apply norm_div_le
#align dist_le_norm_add_norm' dist_le_norm_add_norm'
#align dist_le_norm_add_norm dist_le_norm_add_norm
@[to_additive abs_norm_sub_norm_le]
theorem abs_norm_sub_norm_le' (a b : E) : |‖a‖ - ‖b‖| ≤ ‖a / b‖ := by
simpa [dist_eq_norm_div] using abs_dist_sub_le a b 1
#align abs_norm_sub_norm_le' abs_norm_sub_norm_le'
#align abs_norm_sub_norm_le abs_norm_sub_norm_le
@[to_additive norm_sub_norm_le]
theorem norm_sub_norm_le' (a b : E) : ‖a‖ - ‖b‖ ≤ ‖a / b‖ :=
(le_abs_self _).trans (abs_norm_sub_norm_le' a b)
#align norm_sub_norm_le' norm_sub_norm_le'
#align norm_sub_norm_le norm_sub_norm_le
@[to_additive dist_norm_norm_le]
theorem dist_norm_norm_le' (a b : E) : dist ‖a‖ ‖b‖ ≤ ‖a / b‖ :=
abs_norm_sub_norm_le' a b
#align dist_norm_norm_le' dist_norm_norm_le'
#align dist_norm_norm_le dist_norm_norm_le
@[to_additive]
theorem norm_le_norm_add_norm_div' (u v : E) : ‖u‖ ≤ ‖v‖ + ‖u / v‖ := by
rw [add_comm]
refine (norm_mul_le' _ _).trans_eq' ?_
rw [div_mul_cancel]
#align norm_le_norm_add_norm_div' norm_le_norm_add_norm_div'
#align norm_le_norm_add_norm_sub' norm_le_norm_add_norm_sub'
@[to_additive]
theorem norm_le_norm_add_norm_div (u v : E) : ‖v‖ ≤ ‖u‖ + ‖u / v‖ := by
rw [norm_div_rev]
exact norm_le_norm_add_norm_div' v u
#align norm_le_norm_add_norm_div norm_le_norm_add_norm_div
#align norm_le_norm_add_norm_sub norm_le_norm_add_norm_sub
alias norm_le_insert' := norm_le_norm_add_norm_sub'
#align norm_le_insert' norm_le_insert'
alias norm_le_insert := norm_le_norm_add_norm_sub
#align norm_le_insert norm_le_insert
@[to_additive]
theorem norm_le_mul_norm_add (u v : E) : ‖u‖ ≤ ‖u * v‖ + ‖v‖ :=
calc
‖u‖ = ‖u * v / v‖ := by rw [mul_div_cancel_right]
_ ≤ ‖u * v‖ + ‖v‖ := norm_div_le _ _
#align norm_le_mul_norm_add norm_le_mul_norm_add
#align norm_le_add_norm_add norm_le_add_norm_add
@[to_additive ball_eq]
theorem ball_eq' (y : E) (ε : ℝ) : ball y ε = { x | ‖x / y‖ < ε } :=
Set.ext fun a => by simp [dist_eq_norm_div]
#align ball_eq' ball_eq'
#align ball_eq ball_eq
@[to_additive]
theorem ball_one_eq (r : ℝ) : ball (1 : E) r = { x | ‖x‖ < r } :=
Set.ext fun a => by simp
#align ball_one_eq ball_one_eq
#align ball_zero_eq ball_zero_eq
@[to_additive mem_ball_iff_norm]
theorem mem_ball_iff_norm'' : b ∈ ball a r ↔ ‖b / a‖ < r := by rw [mem_ball, dist_eq_norm_div]
#align mem_ball_iff_norm'' mem_ball_iff_norm''
#align mem_ball_iff_norm mem_ball_iff_norm
@[to_additive mem_ball_iff_norm']
theorem mem_ball_iff_norm''' : b ∈ ball a r ↔ ‖a / b‖ < r := by rw [mem_ball', dist_eq_norm_div]
#align mem_ball_iff_norm''' mem_ball_iff_norm'''
#align mem_ball_iff_norm' mem_ball_iff_norm'
@[to_additive] -- Porting note (#10618): `simp` can prove it
theorem mem_ball_one_iff : a ∈ ball (1 : E) r ↔ ‖a‖ < r := by rw [mem_ball, dist_one_right]
#align mem_ball_one_iff mem_ball_one_iff
#align mem_ball_zero_iff mem_ball_zero_iff
@[to_additive mem_closedBall_iff_norm]
theorem mem_closedBall_iff_norm'' : b ∈ closedBall a r ↔ ‖b / a‖ ≤ r := by
rw [mem_closedBall, dist_eq_norm_div]
#align mem_closed_ball_iff_norm'' mem_closedBall_iff_norm''
#align mem_closed_ball_iff_norm mem_closedBall_iff_norm
@[to_additive] -- Porting note (#10618): `simp` can prove it
theorem mem_closedBall_one_iff : a ∈ closedBall (1 : E) r ↔ ‖a‖ ≤ r := by
rw [mem_closedBall, dist_one_right]
#align mem_closed_ball_one_iff mem_closedBall_one_iff
#align mem_closed_ball_zero_iff mem_closedBall_zero_iff
@[to_additive mem_closedBall_iff_norm']
theorem mem_closedBall_iff_norm''' : b ∈ closedBall a r ↔ ‖a / b‖ ≤ r := by
rw [mem_closedBall', dist_eq_norm_div]
#align mem_closed_ball_iff_norm''' mem_closedBall_iff_norm'''
#align mem_closed_ball_iff_norm' mem_closedBall_iff_norm'
@[to_additive norm_le_of_mem_closedBall]
theorem norm_le_of_mem_closedBall' (h : b ∈ closedBall a r) : ‖b‖ ≤ ‖a‖ + r :=
(norm_le_norm_add_norm_div' _ _).trans <| add_le_add_left (by rwa [← dist_eq_norm_div]) _
#align norm_le_of_mem_closed_ball' norm_le_of_mem_closedBall'
#align norm_le_of_mem_closed_ball norm_le_of_mem_closedBall
@[to_additive norm_le_norm_add_const_of_dist_le]
theorem norm_le_norm_add_const_of_dist_le' : dist a b ≤ r → ‖a‖ ≤ ‖b‖ + r :=
norm_le_of_mem_closedBall'
#align norm_le_norm_add_const_of_dist_le' norm_le_norm_add_const_of_dist_le'
#align norm_le_norm_add_const_of_dist_le norm_le_norm_add_const_of_dist_le
@[to_additive norm_lt_of_mem_ball]
theorem norm_lt_of_mem_ball' (h : b ∈ ball a r) : ‖b‖ < ‖a‖ + r :=
(norm_le_norm_add_norm_div' _ _).trans_lt <| add_lt_add_left (by rwa [← dist_eq_norm_div]) _
#align norm_lt_of_mem_ball' norm_lt_of_mem_ball'
#align norm_lt_of_mem_ball norm_lt_of_mem_ball
@[to_additive]
theorem norm_div_sub_norm_div_le_norm_div (u v w : E) : ‖u / w‖ - ‖v / w‖ ≤ ‖u / v‖ := by
simpa only [div_div_div_cancel_right'] using norm_sub_norm_le' (u / w) (v / w)
#align norm_div_sub_norm_div_le_norm_div norm_div_sub_norm_div_le_norm_div
#align norm_sub_sub_norm_sub_le_norm_sub norm_sub_sub_norm_sub_le_norm_sub
@[to_additive isBounded_iff_forall_norm_le]
theorem isBounded_iff_forall_norm_le' : Bornology.IsBounded s ↔ ∃ C, ∀ x ∈ s, ‖x‖ ≤ C := by
simpa only [Set.subset_def, mem_closedBall_one_iff] using isBounded_iff_subset_closedBall (1 : E)
#align bounded_iff_forall_norm_le' isBounded_iff_forall_norm_le'
#align bounded_iff_forall_norm_le isBounded_iff_forall_norm_le
alias ⟨Bornology.IsBounded.exists_norm_le', _⟩ := isBounded_iff_forall_norm_le'
#align metric.bounded.exists_norm_le' Bornology.IsBounded.exists_norm_le'
alias ⟨Bornology.IsBounded.exists_norm_le, _⟩ := isBounded_iff_forall_norm_le
#align metric.bounded.exists_norm_le Bornology.IsBounded.exists_norm_le
attribute [to_additive existing exists_norm_le] Bornology.IsBounded.exists_norm_le'
@[to_additive exists_pos_norm_le]
theorem Bornology.IsBounded.exists_pos_norm_le' (hs : IsBounded s) : ∃ R > 0, ∀ x ∈ s, ‖x‖ ≤ R :=
let ⟨R₀, hR₀⟩ := hs.exists_norm_le'
⟨max R₀ 1, by positivity, fun x hx => (hR₀ x hx).trans <| le_max_left _ _⟩
#align metric.bounded.exists_pos_norm_le' Bornology.IsBounded.exists_pos_norm_le'
#align metric.bounded.exists_pos_norm_le Bornology.IsBounded.exists_pos_norm_le
@[to_additive Bornology.IsBounded.exists_pos_norm_lt]
theorem Bornology.IsBounded.exists_pos_norm_lt' (hs : IsBounded s) : ∃ R > 0, ∀ x ∈ s, ‖x‖ < R :=
let ⟨R, hR₀, hR⟩ := hs.exists_pos_norm_le'
⟨R + 1, by positivity, fun x hx ↦ (hR x hx).trans_lt (lt_add_one _)⟩
@[to_additive (attr := simp 1001) mem_sphere_iff_norm]
-- Porting note: increase priority so the left-hand side doesn't reduce
theorem mem_sphere_iff_norm' : b ∈ sphere a r ↔ ‖b / a‖ = r := by simp [dist_eq_norm_div]
#align mem_sphere_iff_norm' mem_sphere_iff_norm'
#align mem_sphere_iff_norm mem_sphere_iff_norm
@[to_additive] -- `simp` can prove this
theorem mem_sphere_one_iff_norm : a ∈ sphere (1 : E) r ↔ ‖a‖ = r := by simp [dist_eq_norm_div]
#align mem_sphere_one_iff_norm mem_sphere_one_iff_norm
#align mem_sphere_zero_iff_norm mem_sphere_zero_iff_norm
@[to_additive (attr := simp) norm_eq_of_mem_sphere]
theorem norm_eq_of_mem_sphere' (x : sphere (1 : E) r) : ‖(x : E)‖ = r :=
mem_sphere_one_iff_norm.mp x.2
#align norm_eq_of_mem_sphere' norm_eq_of_mem_sphere'
#align norm_eq_of_mem_sphere norm_eq_of_mem_sphere
@[to_additive]
theorem ne_one_of_mem_sphere (hr : r ≠ 0) (x : sphere (1 : E) r) : (x : E) ≠ 1 :=
ne_one_of_norm_ne_zero <| by rwa [norm_eq_of_mem_sphere' x]
#align ne_one_of_mem_sphere ne_one_of_mem_sphere
#align ne_zero_of_mem_sphere ne_zero_of_mem_sphere
@[to_additive ne_zero_of_mem_unit_sphere]
theorem ne_one_of_mem_unit_sphere (x : sphere (1 : E) 1) : (x : E) ≠ 1 :=
ne_one_of_mem_sphere one_ne_zero _
#align ne_one_of_mem_unit_sphere ne_one_of_mem_unit_sphere
#align ne_zero_of_mem_unit_sphere ne_zero_of_mem_unit_sphere
variable (E)
/-- The norm of a seminormed group as a group seminorm. -/
@[to_additive "The norm of a seminormed group as an additive group seminorm."]
def normGroupSeminorm : GroupSeminorm E :=
⟨norm, norm_one', norm_mul_le', norm_inv'⟩
#align norm_group_seminorm normGroupSeminorm
#align norm_add_group_seminorm normAddGroupSeminorm
@[to_additive (attr := simp)]
theorem coe_normGroupSeminorm : ⇑(normGroupSeminorm E) = norm :=
rfl
#align coe_norm_group_seminorm coe_normGroupSeminorm
#align coe_norm_add_group_seminorm coe_normAddGroupSeminorm
variable {E}
@[to_additive]
theorem NormedCommGroup.tendsto_nhds_one {f : α → E} {l : Filter α} :
Tendsto f l (𝓝 1) ↔ ∀ ε > 0, ∀ᶠ x in l, ‖f x‖ < ε :=
Metric.tendsto_nhds.trans <| by simp only [dist_one_right]
#align normed_comm_group.tendsto_nhds_one NormedCommGroup.tendsto_nhds_one
#align normed_add_comm_group.tendsto_nhds_zero NormedAddCommGroup.tendsto_nhds_zero
@[to_additive]
theorem NormedCommGroup.tendsto_nhds_nhds {f : E → F} {x : E} {y : F} :
Tendsto f (𝓝 x) (𝓝 y) ↔ ∀ ε > 0, ∃ δ > 0, ∀ x', ‖x' / x‖ < δ → ‖f x' / y‖ < ε := by
simp_rw [Metric.tendsto_nhds_nhds, dist_eq_norm_div]
#align normed_comm_group.tendsto_nhds_nhds NormedCommGroup.tendsto_nhds_nhds
#align normed_add_comm_group.tendsto_nhds_nhds NormedAddCommGroup.tendsto_nhds_nhds
@[to_additive]
theorem NormedCommGroup.cauchySeq_iff [Nonempty α] [SemilatticeSup α] {u : α → E} :
CauchySeq u ↔ ∀ ε > 0, ∃ N, ∀ m, N ≤ m → ∀ n, N ≤ n → ‖u m / u n‖ < ε := by
simp [Metric.cauchySeq_iff, dist_eq_norm_div]
#align normed_comm_group.cauchy_seq_iff NormedCommGroup.cauchySeq_iff
#align normed_add_comm_group.cauchy_seq_iff NormedAddCommGroup.cauchySeq_iff
@[to_additive]
theorem NormedCommGroup.nhds_basis_norm_lt (x : E) :
(𝓝 x).HasBasis (fun ε : ℝ => 0 < ε) fun ε => { y | ‖y / x‖ < ε } := by
simp_rw [← ball_eq']
exact Metric.nhds_basis_ball
#align normed_comm_group.nhds_basis_norm_lt NormedCommGroup.nhds_basis_norm_lt
#align normed_add_comm_group.nhds_basis_norm_lt NormedAddCommGroup.nhds_basis_norm_lt
@[to_additive]
theorem NormedCommGroup.nhds_one_basis_norm_lt :
(𝓝 (1 : E)).HasBasis (fun ε : ℝ => 0 < ε) fun ε => { y | ‖y‖ < ε } := by
convert NormedCommGroup.nhds_basis_norm_lt (1 : E)
simp
#align normed_comm_group.nhds_one_basis_norm_lt NormedCommGroup.nhds_one_basis_norm_lt
#align normed_add_comm_group.nhds_zero_basis_norm_lt NormedAddCommGroup.nhds_zero_basis_norm_lt
@[to_additive]
theorem NormedCommGroup.uniformity_basis_dist :
(𝓤 E).HasBasis (fun ε : ℝ => 0 < ε) fun ε => { p : E × E | ‖p.fst / p.snd‖ < ε } := by
convert Metric.uniformity_basis_dist (α := E) using 1
simp [dist_eq_norm_div]
#align normed_comm_group.uniformity_basis_dist NormedCommGroup.uniformity_basis_dist
#align normed_add_comm_group.uniformity_basis_dist NormedAddCommGroup.uniformity_basis_dist
open Finset
variable [FunLike 𝓕 E F]
/-- A homomorphism `f` of seminormed groups is Lipschitz, if there exists a constant `C` such that
for all `x`, one has `‖f x‖ ≤ C * ‖x‖`. The analogous condition for a linear map of
(semi)normed spaces is in `Mathlib/Analysis/NormedSpace/OperatorNorm.lean`. -/
@[to_additive "A homomorphism `f` of seminormed groups is Lipschitz, if there exists a constant
`C` such that for all `x`, one has `‖f x‖ ≤ C * ‖x‖`. The analogous condition for a linear map of
(semi)normed spaces is in `Mathlib/Analysis/NormedSpace/OperatorNorm.lean`."]
theorem MonoidHomClass.lipschitz_of_bound [MonoidHomClass 𝓕 E F] (f : 𝓕) (C : ℝ)
(h : ∀ x, ‖f x‖ ≤ C * ‖x‖) : LipschitzWith (Real.toNNReal C) f :=
LipschitzWith.of_dist_le' fun x y => by simpa only [dist_eq_norm_div, map_div] using h (x / y)
#align monoid_hom_class.lipschitz_of_bound MonoidHomClass.lipschitz_of_bound
#align add_monoid_hom_class.lipschitz_of_bound AddMonoidHomClass.lipschitz_of_bound
@[to_additive]
theorem lipschitzOnWith_iff_norm_div_le {f : E → F} {C : ℝ≥0} :
LipschitzOnWith C f s ↔ ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → ‖f x / f y‖ ≤ C * ‖x / y‖ := by
simp only [lipschitzOnWith_iff_dist_le_mul, dist_eq_norm_div]
#align lipschitz_on_with_iff_norm_div_le lipschitzOnWith_iff_norm_div_le
#align lipschitz_on_with_iff_norm_sub_le lipschitzOnWith_iff_norm_sub_le
alias ⟨LipschitzOnWith.norm_div_le, _⟩ := lipschitzOnWith_iff_norm_div_le
#align lipschitz_on_with.norm_div_le LipschitzOnWith.norm_div_le
attribute [to_additive] LipschitzOnWith.norm_div_le
@[to_additive]
theorem LipschitzOnWith.norm_div_le_of_le {f : E → F} {C : ℝ≥0} (h : LipschitzOnWith C f s)
(ha : a ∈ s) (hb : b ∈ s) (hr : ‖a / b‖ ≤ r) : ‖f a / f b‖ ≤ C * r :=
(h.norm_div_le ha hb).trans <| by gcongr
#align lipschitz_on_with.norm_div_le_of_le LipschitzOnWith.norm_div_le_of_le
#align lipschitz_on_with.norm_sub_le_of_le LipschitzOnWith.norm_sub_le_of_le
@[to_additive]
theorem lipschitzWith_iff_norm_div_le {f : E → F} {C : ℝ≥0} :
LipschitzWith C f ↔ ∀ x y, ‖f x / f y‖ ≤ C * ‖x / y‖ := by
simp only [lipschitzWith_iff_dist_le_mul, dist_eq_norm_div]
#align lipschitz_with_iff_norm_div_le lipschitzWith_iff_norm_div_le
#align lipschitz_with_iff_norm_sub_le lipschitzWith_iff_norm_sub_le
alias ⟨LipschitzWith.norm_div_le, _⟩ := lipschitzWith_iff_norm_div_le
#align lipschitz_with.norm_div_le LipschitzWith.norm_div_le
attribute [to_additive] LipschitzWith.norm_div_le
@[to_additive]
theorem LipschitzWith.norm_div_le_of_le {f : E → F} {C : ℝ≥0} (h : LipschitzWith C f)
(hr : ‖a / b‖ ≤ r) : ‖f a / f b‖ ≤ C * r :=
(h.norm_div_le _ _).trans <| by gcongr
#align lipschitz_with.norm_div_le_of_le LipschitzWith.norm_div_le_of_le
#align lipschitz_with.norm_sub_le_of_le LipschitzWith.norm_sub_le_of_le
/-- A homomorphism `f` of seminormed groups is continuous, if there exists a constant `C` such that
for all `x`, one has `‖f x‖ ≤ C * ‖x‖`. -/
@[to_additive "A homomorphism `f` of seminormed groups is continuous, if there exists a constant `C`
such that for all `x`, one has `‖f x‖ ≤ C * ‖x‖`"]
theorem MonoidHomClass.continuous_of_bound [MonoidHomClass 𝓕 E F] (f : 𝓕) (C : ℝ)
(h : ∀ x, ‖f x‖ ≤ C * ‖x‖) : Continuous f :=
(MonoidHomClass.lipschitz_of_bound f C h).continuous
#align monoid_hom_class.continuous_of_bound MonoidHomClass.continuous_of_bound
#align add_monoid_hom_class.continuous_of_bound AddMonoidHomClass.continuous_of_bound
@[to_additive]
theorem MonoidHomClass.uniformContinuous_of_bound [MonoidHomClass 𝓕 E F] (f : 𝓕) (C : ℝ)
(h : ∀ x, ‖f x‖ ≤ C * ‖x‖) : UniformContinuous f :=
(MonoidHomClass.lipschitz_of_bound f C h).uniformContinuous
#align monoid_hom_class.uniform_continuous_of_bound MonoidHomClass.uniformContinuous_of_bound
#align add_monoid_hom_class.uniform_continuous_of_bound AddMonoidHomClass.uniformContinuous_of_bound
@[to_additive IsCompact.exists_bound_of_continuousOn]
theorem IsCompact.exists_bound_of_continuousOn' [TopologicalSpace α] {s : Set α} (hs : IsCompact s)
{f : α → E} (hf : ContinuousOn f s) : ∃ C, ∀ x ∈ s, ‖f x‖ ≤ C :=
(isBounded_iff_forall_norm_le'.1 (hs.image_of_continuousOn hf).isBounded).imp fun _C hC _x hx =>
hC _ <| Set.mem_image_of_mem _ hx
#align is_compact.exists_bound_of_continuous_on' IsCompact.exists_bound_of_continuousOn'
#align is_compact.exists_bound_of_continuous_on IsCompact.exists_bound_of_continuousOn
@[to_additive]
theorem HasCompactMulSupport.exists_bound_of_continuous [TopologicalSpace α]
{f : α → E} (hf : HasCompactMulSupport f) (h'f : Continuous f) : ∃ C, ∀ x, ‖f x‖ ≤ C := by
simpa using (hf.isCompact_range h'f).isBounded.exists_norm_le'
@[to_additive]
theorem MonoidHomClass.isometry_iff_norm [MonoidHomClass 𝓕 E F] (f : 𝓕) :
Isometry f ↔ ∀ x, ‖f x‖ = ‖x‖ := by
simp only [isometry_iff_dist_eq, dist_eq_norm_div, ← map_div]
refine ⟨fun h x => ?_, fun h x y => h _⟩
simpa using h x 1
#align monoid_hom_class.isometry_iff_norm MonoidHomClass.isometry_iff_norm
#align add_monoid_hom_class.isometry_iff_norm AddMonoidHomClass.isometry_iff_norm
alias ⟨_, MonoidHomClass.isometry_of_norm⟩ := MonoidHomClass.isometry_iff_norm
#align monoid_hom_class.isometry_of_norm MonoidHomClass.isometry_of_norm
attribute [to_additive] MonoidHomClass.isometry_of_norm
section NNNorm
-- See note [lower instance priority]
@[to_additive]
instance (priority := 100) SeminormedGroup.toNNNorm : NNNorm E :=
⟨fun a => ⟨‖a‖, norm_nonneg' a⟩⟩
#align seminormed_group.to_has_nnnorm SeminormedGroup.toNNNorm
#align seminormed_add_group.to_has_nnnorm SeminormedAddGroup.toNNNorm
@[to_additive (attr := simp, norm_cast) coe_nnnorm]
theorem coe_nnnorm' (a : E) : (‖a‖₊ : ℝ) = ‖a‖ :=
rfl
#align coe_nnnorm' coe_nnnorm'
#align coe_nnnorm coe_nnnorm
@[to_additive (attr := simp) coe_comp_nnnorm]
theorem coe_comp_nnnorm' : (toReal : ℝ≥0 → ℝ) ∘ (nnnorm : E → ℝ≥0) = norm :=
rfl
#align coe_comp_nnnorm' coe_comp_nnnorm'
#align coe_comp_nnnorm coe_comp_nnnorm
@[to_additive norm_toNNReal]
theorem norm_toNNReal' : ‖a‖.toNNReal = ‖a‖₊ :=
@Real.toNNReal_coe ‖a‖₊
#align norm_to_nnreal' norm_toNNReal'
#align norm_to_nnreal norm_toNNReal
@[to_additive]
theorem nndist_eq_nnnorm_div (a b : E) : nndist a b = ‖a / b‖₊ :=
NNReal.eq <| dist_eq_norm_div _ _
#align nndist_eq_nnnorm_div nndist_eq_nnnorm_div
#align nndist_eq_nnnorm_sub nndist_eq_nnnorm_sub
alias nndist_eq_nnnorm := nndist_eq_nnnorm_sub
#align nndist_eq_nnnorm nndist_eq_nnnorm
@[to_additive (attr := simp) nnnorm_zero]
theorem nnnorm_one' : ‖(1 : E)‖₊ = 0 :=
NNReal.eq norm_one'
#align nnnorm_one' nnnorm_one'
#align nnnorm_zero nnnorm_zero
@[to_additive]
theorem ne_one_of_nnnorm_ne_zero {a : E} : ‖a‖₊ ≠ 0 → a ≠ 1 :=
mt <| by
rintro rfl
exact nnnorm_one'
#align ne_one_of_nnnorm_ne_zero ne_one_of_nnnorm_ne_zero
#align ne_zero_of_nnnorm_ne_zero ne_zero_of_nnnorm_ne_zero
@[to_additive nnnorm_add_le]
theorem nnnorm_mul_le' (a b : E) : ‖a * b‖₊ ≤ ‖a‖₊ + ‖b‖₊ :=
NNReal.coe_le_coe.1 <| norm_mul_le' a b
#align nnnorm_mul_le' nnnorm_mul_le'
#align nnnorm_add_le nnnorm_add_le
@[to_additive (attr := simp) nnnorm_neg]
theorem nnnorm_inv' (a : E) : ‖a⁻¹‖₊ = ‖a‖₊ :=
NNReal.eq <| norm_inv' a
#align nnnorm_inv' nnnorm_inv'
#align nnnorm_neg nnnorm_neg
open scoped symmDiff in
@[to_additive]
theorem nndist_mulIndicator (s t : Set α) (f : α → E) (x : α) :
nndist (s.mulIndicator f x) (t.mulIndicator f x) = ‖(s ∆ t).mulIndicator f x‖₊ :=
NNReal.eq <| dist_mulIndicator s t f x
@[to_additive]
theorem nnnorm_div_le (a b : E) : ‖a / b‖₊ ≤ ‖a‖₊ + ‖b‖₊ :=
NNReal.coe_le_coe.1 <| norm_div_le _ _
#align nnnorm_div_le nnnorm_div_le
#align nnnorm_sub_le nnnorm_sub_le
@[to_additive nndist_nnnorm_nnnorm_le]
theorem nndist_nnnorm_nnnorm_le' (a b : E) : nndist ‖a‖₊ ‖b‖₊ ≤ ‖a / b‖₊ :=
NNReal.coe_le_coe.1 <| dist_norm_norm_le' a b
#align nndist_nnnorm_nnnorm_le' nndist_nnnorm_nnnorm_le'
#align nndist_nnnorm_nnnorm_le nndist_nnnorm_nnnorm_le
@[to_additive]
theorem nnnorm_le_nnnorm_add_nnnorm_div (a b : E) : ‖b‖₊ ≤ ‖a‖₊ + ‖a / b‖₊ :=
norm_le_norm_add_norm_div _ _
#align nnnorm_le_nnnorm_add_nnnorm_div nnnorm_le_nnnorm_add_nnnorm_div
#align nnnorm_le_nnnorm_add_nnnorm_sub nnnorm_le_nnnorm_add_nnnorm_sub
@[to_additive]
theorem nnnorm_le_nnnorm_add_nnnorm_div' (a b : E) : ‖a‖₊ ≤ ‖b‖₊ + ‖a / b‖₊ :=
norm_le_norm_add_norm_div' _ _
#align nnnorm_le_nnnorm_add_nnnorm_div' nnnorm_le_nnnorm_add_nnnorm_div'
#align nnnorm_le_nnnorm_add_nnnorm_sub' nnnorm_le_nnnorm_add_nnnorm_sub'
alias nnnorm_le_insert' := nnnorm_le_nnnorm_add_nnnorm_sub'
#align nnnorm_le_insert' nnnorm_le_insert'
alias nnnorm_le_insert := nnnorm_le_nnnorm_add_nnnorm_sub
#align nnnorm_le_insert nnnorm_le_insert
@[to_additive]
theorem nnnorm_le_mul_nnnorm_add (a b : E) : ‖a‖₊ ≤ ‖a * b‖₊ + ‖b‖₊ :=
norm_le_mul_norm_add _ _
#align nnnorm_le_mul_nnnorm_add nnnorm_le_mul_nnnorm_add
#align nnnorm_le_add_nnnorm_add nnnorm_le_add_nnnorm_add
@[to_additive ofReal_norm_eq_coe_nnnorm]
theorem ofReal_norm_eq_coe_nnnorm' (a : E) : ENNReal.ofReal ‖a‖ = ‖a‖₊ :=
ENNReal.ofReal_eq_coe_nnreal _
#align of_real_norm_eq_coe_nnnorm' ofReal_norm_eq_coe_nnnorm'
#align of_real_norm_eq_coe_nnnorm ofReal_norm_eq_coe_nnnorm
/-- The non negative norm seen as an `ENNReal` and then as a `Real` is equal to the norm. -/
@[to_additive toReal_coe_nnnorm "The non negative norm seen as an `ENNReal` and
then as a `Real` is equal to the norm."]
theorem toReal_coe_nnnorm' (a : E) : (‖a‖₊ : ℝ≥0∞).toReal = ‖a‖ := rfl
@[to_additive]
theorem edist_eq_coe_nnnorm_div (a b : E) : edist a b = ‖a / b‖₊ := by
rw [edist_dist, dist_eq_norm_div, ofReal_norm_eq_coe_nnnorm']
#align edist_eq_coe_nnnorm_div edist_eq_coe_nnnorm_div
#align edist_eq_coe_nnnorm_sub edist_eq_coe_nnnorm_sub
@[to_additive edist_eq_coe_nnnorm]
theorem edist_eq_coe_nnnorm' (x : E) : edist x 1 = (‖x‖₊ : ℝ≥0∞) := by
rw [edist_eq_coe_nnnorm_div, div_one]
#align edist_eq_coe_nnnorm' edist_eq_coe_nnnorm'
#align edist_eq_coe_nnnorm edist_eq_coe_nnnorm
open scoped symmDiff in
@[to_additive]
theorem edist_mulIndicator (s t : Set α) (f : α → E) (x : α) :
edist (s.mulIndicator f x) (t.mulIndicator f x) = ‖(s ∆ t).mulIndicator f x‖₊ := by
rw [edist_nndist, nndist_mulIndicator]
@[to_additive]
theorem mem_emetric_ball_one_iff {r : ℝ≥0∞} : a ∈ EMetric.ball (1 : E) r ↔ ↑‖a‖₊ < r := by
rw [EMetric.mem_ball, edist_eq_coe_nnnorm']
#align mem_emetric_ball_one_iff mem_emetric_ball_one_iff
#align mem_emetric_ball_zero_iff mem_emetric_ball_zero_iff
@[to_additive]
theorem MonoidHomClass.lipschitz_of_bound_nnnorm [MonoidHomClass 𝓕 E F] (f : 𝓕) (C : ℝ≥0)
(h : ∀ x, ‖f x‖₊ ≤ C * ‖x‖₊) : LipschitzWith C f :=
@Real.toNNReal_coe C ▸ MonoidHomClass.lipschitz_of_bound f C h
#align monoid_hom_class.lipschitz_of_bound_nnnorm MonoidHomClass.lipschitz_of_bound_nnnorm
#align add_monoid_hom_class.lipschitz_of_bound_nnnorm AddMonoidHomClass.lipschitz_of_bound_nnnorm
@[to_additive]
theorem MonoidHomClass.antilipschitz_of_bound [MonoidHomClass 𝓕 E F] (f : 𝓕) {K : ℝ≥0}
(h : ∀ x, ‖x‖ ≤ K * ‖f x‖) : AntilipschitzWith K f :=
AntilipschitzWith.of_le_mul_dist fun x y => by
simpa only [dist_eq_norm_div, map_div] using h (x / y)
#align monoid_hom_class.antilipschitz_of_bound MonoidHomClass.antilipschitz_of_bound
#align add_monoid_hom_class.antilipschitz_of_bound AddMonoidHomClass.antilipschitz_of_bound
@[to_additive LipschitzWith.norm_le_mul]
theorem LipschitzWith.norm_le_mul' {f : E → F} {K : ℝ≥0} (h : LipschitzWith K f) (hf : f 1 = 1)
(x) : ‖f x‖ ≤ K * ‖x‖ := by simpa only [dist_one_right, hf] using h.dist_le_mul x 1
#align lipschitz_with.norm_le_mul' LipschitzWith.norm_le_mul'
#align lipschitz_with.norm_le_mul LipschitzWith.norm_le_mul
@[to_additive LipschitzWith.nnorm_le_mul]
theorem LipschitzWith.nnorm_le_mul' {f : E → F} {K : ℝ≥0} (h : LipschitzWith K f) (hf : f 1 = 1)
(x) : ‖f x‖₊ ≤ K * ‖x‖₊ :=
h.norm_le_mul' hf x
#align lipschitz_with.nnorm_le_mul' LipschitzWith.nnorm_le_mul'
#align lipschitz_with.nnorm_le_mul LipschitzWith.nnorm_le_mul
@[to_additive AntilipschitzWith.le_mul_norm]
theorem AntilipschitzWith.le_mul_norm' {f : E → F} {K : ℝ≥0} (h : AntilipschitzWith K f)
(hf : f 1 = 1) (x) : ‖x‖ ≤ K * ‖f x‖ := by
simpa only [dist_one_right, hf] using h.le_mul_dist x 1
#align antilipschitz_with.le_mul_norm' AntilipschitzWith.le_mul_norm'
#align antilipschitz_with.le_mul_norm AntilipschitzWith.le_mul_norm
@[to_additive AntilipschitzWith.le_mul_nnnorm]
theorem AntilipschitzWith.le_mul_nnnorm' {f : E → F} {K : ℝ≥0} (h : AntilipschitzWith K f)
(hf : f 1 = 1) (x) : ‖x‖₊ ≤ K * ‖f x‖₊ :=
h.le_mul_norm' hf x
#align antilipschitz_with.le_mul_nnnorm' AntilipschitzWith.le_mul_nnnorm'
#align antilipschitz_with.le_mul_nnnorm AntilipschitzWith.le_mul_nnnorm
@[to_additive]
theorem OneHomClass.bound_of_antilipschitz [OneHomClass 𝓕 E F] (f : 𝓕) {K : ℝ≥0}
(h : AntilipschitzWith K f) (x) : ‖x‖ ≤ K * ‖f x‖ :=
h.le_mul_nnnorm' (map_one f) x
#align one_hom_class.bound_of_antilipschitz OneHomClass.bound_of_antilipschitz
#align zero_hom_class.bound_of_antilipschitz ZeroHomClass.bound_of_antilipschitz
@[to_additive]
theorem Isometry.nnnorm_map_of_map_one {f : E → F} (hi : Isometry f) (h₁ : f 1 = 1) (x : E) :
‖f x‖₊ = ‖x‖₊ :=
Subtype.ext <| hi.norm_map_of_map_one h₁ x
end NNNorm
@[to_additive]
theorem tendsto_iff_norm_div_tendsto_zero {f : α → E} {a : Filter α} {b : E} :
Tendsto f a (𝓝 b) ↔ Tendsto (fun e => ‖f e / b‖) a (𝓝 0) := by
simp only [← dist_eq_norm_div, ← tendsto_iff_dist_tendsto_zero]
#align tendsto_iff_norm_tendsto_one tendsto_iff_norm_div_tendsto_zero
#align tendsto_iff_norm_tendsto_zero tendsto_iff_norm_sub_tendsto_zero
@[to_additive]
theorem tendsto_one_iff_norm_tendsto_zero {f : α → E} {a : Filter α} :
Tendsto f a (𝓝 1) ↔ Tendsto (‖f ·‖) a (𝓝 0) :=
tendsto_iff_norm_div_tendsto_zero.trans <| by simp only [div_one]
#align tendsto_one_iff_norm_tendsto_one tendsto_one_iff_norm_tendsto_zero
#align tendsto_zero_iff_norm_tendsto_zero tendsto_zero_iff_norm_tendsto_zero
@[to_additive]
theorem comap_norm_nhds_one : comap norm (𝓝 0) = 𝓝 (1 : E) := by
simpa only [dist_one_right] using nhds_comap_dist (1 : E)
#align comap_norm_nhds_one comap_norm_nhds_one
#align comap_norm_nhds_zero comap_norm_nhds_zero
/-- Special case of the sandwich theorem: if the norm of `f` is eventually bounded by a real
function `a` which tends to `0`, then `f` tends to `1` (neutral element of `SeminormedGroup`).
In this pair of lemmas (`squeeze_one_norm'` and `squeeze_one_norm`), following a convention of
similar lemmas in `Topology.MetricSpace.Basic` and `Topology.Algebra.Order`, the `'` version is
phrased using "eventually" and the non-`'` version is phrased absolutely. -/
@[to_additive "Special case of the sandwich theorem: if the norm of `f` is eventually bounded by a
real function `a` which tends to `0`, then `f` tends to `0`. In this pair of lemmas
(`squeeze_zero_norm'` and `squeeze_zero_norm`), following a convention of similar lemmas in
`Topology.MetricSpace.PseudoMetric` and `Topology.Algebra.Order`, the `'` version is phrased using
\"eventually\" and the non-`'` version is phrased absolutely."]
theorem squeeze_one_norm' {f : α → E} {a : α → ℝ} {t₀ : Filter α} (h : ∀ᶠ n in t₀, ‖f n‖ ≤ a n)
(h' : Tendsto a t₀ (𝓝 0)) : Tendsto f t₀ (𝓝 1) :=
tendsto_one_iff_norm_tendsto_zero.2 <|
squeeze_zero' (eventually_of_forall fun _n => norm_nonneg' _) h h'
#align squeeze_one_norm' squeeze_one_norm'
#align squeeze_zero_norm' squeeze_zero_norm'
/-- Special case of the sandwich theorem: if the norm of `f` is bounded by a real function `a` which
tends to `0`, then `f` tends to `1`. -/
@[to_additive "Special case of the sandwich theorem: if the norm of `f` is bounded by a real
function `a` which tends to `0`, then `f` tends to `0`."]
theorem squeeze_one_norm {f : α → E} {a : α → ℝ} {t₀ : Filter α} (h : ∀ n, ‖f n‖ ≤ a n) :
Tendsto a t₀ (𝓝 0) → Tendsto f t₀ (𝓝 1) :=
squeeze_one_norm' <| eventually_of_forall h
#align squeeze_one_norm squeeze_one_norm
#align squeeze_zero_norm squeeze_zero_norm
@[to_additive]
theorem tendsto_norm_div_self (x : E) : Tendsto (fun a => ‖a / x‖) (𝓝 x) (𝓝 0) := by
simpa [dist_eq_norm_div] using
tendsto_id.dist (tendsto_const_nhds : Tendsto (fun _a => (x : E)) (𝓝 x) _)
#align tendsto_norm_div_self tendsto_norm_div_self
#align tendsto_norm_sub_self tendsto_norm_sub_self
@[to_additive tendsto_norm]
theorem tendsto_norm' {x : E} : Tendsto (fun a => ‖a‖) (𝓝 x) (𝓝 ‖x‖) := by
simpa using tendsto_id.dist (tendsto_const_nhds : Tendsto (fun _a => (1 : E)) _ _)
#align tendsto_norm' tendsto_norm'
#align tendsto_norm tendsto_norm
@[to_additive]
theorem tendsto_norm_one : Tendsto (fun a : E => ‖a‖) (𝓝 1) (𝓝 0) := by
simpa using tendsto_norm_div_self (1 : E)
#align tendsto_norm_one tendsto_norm_one
#align tendsto_norm_zero tendsto_norm_zero
@[to_additive (attr := continuity) continuous_norm]
theorem continuous_norm' : Continuous fun a : E => ‖a‖ := by
simpa using continuous_id.dist (continuous_const : Continuous fun _a => (1 : E))
#align continuous_norm' continuous_norm'
#align continuous_norm continuous_norm
@[to_additive (attr := continuity) continuous_nnnorm]
theorem continuous_nnnorm' : Continuous fun a : E => ‖a‖₊ :=
continuous_norm'.subtype_mk _
#align continuous_nnnorm' continuous_nnnorm'
#align continuous_nnnorm continuous_nnnorm
@[to_additive lipschitzWith_one_norm]
theorem lipschitzWith_one_norm' : LipschitzWith 1 (norm : E → ℝ) := by
simpa only [dist_one_left] using LipschitzWith.dist_right (1 : E)
#align lipschitz_with_one_norm' lipschitzWith_one_norm'
#align lipschitz_with_one_norm lipschitzWith_one_norm
@[to_additive lipschitzWith_one_nnnorm]
theorem lipschitzWith_one_nnnorm' : LipschitzWith 1 (NNNorm.nnnorm : E → ℝ≥0) :=
lipschitzWith_one_norm'
#align lipschitz_with_one_nnnorm' lipschitzWith_one_nnnorm'
#align lipschitz_with_one_nnnorm lipschitzWith_one_nnnorm
@[to_additive uniformContinuous_norm]
theorem uniformContinuous_norm' : UniformContinuous (norm : E → ℝ) :=
lipschitzWith_one_norm'.uniformContinuous
#align uniform_continuous_norm' uniformContinuous_norm'
#align uniform_continuous_norm uniformContinuous_norm
@[to_additive uniformContinuous_nnnorm]
theorem uniformContinuous_nnnorm' : UniformContinuous fun a : E => ‖a‖₊ :=
uniformContinuous_norm'.subtype_mk _
#align uniform_continuous_nnnorm' uniformContinuous_nnnorm'
#align uniform_continuous_nnnorm uniformContinuous_nnnorm
@[to_additive]
theorem mem_closure_one_iff_norm {x : E} : x ∈ closure ({1} : Set E) ↔ ‖x‖ = 0 := by
rw [← closedBall_zero', mem_closedBall_one_iff, (norm_nonneg' x).le_iff_eq]
#align mem_closure_one_iff_norm mem_closure_one_iff_norm
#align mem_closure_zero_iff_norm mem_closure_zero_iff_norm
@[to_additive]
theorem closure_one_eq : closure ({1} : Set E) = { x | ‖x‖ = 0 } :=
Set.ext fun _x => mem_closure_one_iff_norm
#align closure_one_eq closure_one_eq
#align closure_zero_eq closure_zero_eq
/-- A helper lemma used to prove that the (scalar or usual) product of a function that tends to one
and a bounded function tends to one. This lemma is formulated for any binary operation
`op : E → F → G` with an estimate `‖op x y‖ ≤ A * ‖x‖ * ‖y‖` for some constant A instead of
multiplication so that it can be applied to `(*)`, `flip (*)`, `(•)`, and `flip (•)`. -/
@[to_additive "A helper lemma used to prove that the (scalar or usual) product of a function that
tends to zero and a bounded function tends to zero. This lemma is formulated for any binary
operation `op : E → F → G` with an estimate `‖op x y‖ ≤ A * ‖x‖ * ‖y‖` for some constant A instead
of multiplication so that it can be applied to `(*)`, `flip (*)`, `(•)`, and `flip (•)`."]
theorem Filter.Tendsto.op_one_isBoundedUnder_le' {f : α → E} {g : α → F} {l : Filter α}
(hf : Tendsto f l (𝓝 1)) (hg : IsBoundedUnder (· ≤ ·) l (norm ∘ g)) (op : E → F → G)
(h_op : ∃ A, ∀ x y, ‖op x y‖ ≤ A * ‖x‖ * ‖y‖) : Tendsto (fun x => op (f x) (g x)) l (𝓝 1) := by
cases' h_op with A h_op
rcases hg with ⟨C, hC⟩; rw [eventually_map] at hC
rw [NormedCommGroup.tendsto_nhds_one] at hf ⊢
intro ε ε₀
rcases exists_pos_mul_lt ε₀ (A * C) with ⟨δ, δ₀, hδ⟩
filter_upwards [hf δ δ₀, hC] with i hf hg
refine (h_op _ _).trans_lt ?_
rcases le_total A 0 with hA | hA
· exact (mul_nonpos_of_nonpos_of_nonneg (mul_nonpos_of_nonpos_of_nonneg hA <| norm_nonneg' _) <|
norm_nonneg' _).trans_lt ε₀
calc
A * ‖f i‖ * ‖g i‖ ≤ A * δ * C := by gcongr; exact hg
_ = A * C * δ := mul_right_comm _ _ _
_ < ε := hδ
#align filter.tendsto.op_one_is_bounded_under_le' Filter.Tendsto.op_one_isBoundedUnder_le'
#align filter.tendsto.op_zero_is_bounded_under_le' Filter.Tendsto.op_zero_isBoundedUnder_le'
/-- A helper lemma used to prove that the (scalar or usual) product of a function that tends to one
and a bounded function tends to one. This lemma is formulated for any binary operation
`op : E → F → G` with an estimate `‖op x y‖ ≤ ‖x‖ * ‖y‖` instead of multiplication so that it
can be applied to `(*)`, `flip (*)`, `(•)`, and `flip (•)`. -/
@[to_additive "A helper lemma used to prove that the (scalar or usual) product of a function that
tends to zero and a bounded function tends to zero. This lemma is formulated for any binary
operation `op : E → F → G` with an estimate `‖op x y‖ ≤ ‖x‖ * ‖y‖` instead of multiplication so
that it can be applied to `(*)`, `flip (*)`, `(•)`, and `flip (•)`."]
theorem Filter.Tendsto.op_one_isBoundedUnder_le {f : α → E} {g : α → F} {l : Filter α}
(hf : Tendsto f l (𝓝 1)) (hg : IsBoundedUnder (· ≤ ·) l (norm ∘ g)) (op : E → F → G)
(h_op : ∀ x y, ‖op x y‖ ≤ ‖x‖ * ‖y‖) : Tendsto (fun x => op (f x) (g x)) l (𝓝 1) :=
hf.op_one_isBoundedUnder_le' hg op ⟨1, fun x y => (one_mul ‖x‖).symm ▸ h_op x y⟩
#align filter.tendsto.op_one_is_bounded_under_le Filter.Tendsto.op_one_isBoundedUnder_le
#align filter.tendsto.op_zero_is_bounded_under_le Filter.Tendsto.op_zero_isBoundedUnder_le
section
variable {l : Filter α} {f : α → E}
@[to_additive Filter.Tendsto.norm]
theorem Filter.Tendsto.norm' (h : Tendsto f l (𝓝 a)) : Tendsto (fun x => ‖f x‖) l (𝓝 ‖a‖) :=
tendsto_norm'.comp h
#align filter.tendsto.norm' Filter.Tendsto.norm'
#align filter.tendsto.norm Filter.Tendsto.norm
@[to_additive Filter.Tendsto.nnnorm]
theorem Filter.Tendsto.nnnorm' (h : Tendsto f l (𝓝 a)) : Tendsto (fun x => ‖f x‖₊) l (𝓝 ‖a‖₊) :=
Tendsto.comp continuous_nnnorm'.continuousAt h
#align filter.tendsto.nnnorm' Filter.Tendsto.nnnorm'
#align filter.tendsto.nnnorm Filter.Tendsto.nnnorm
end
section
variable [TopologicalSpace α] {f : α → E}
@[to_additive (attr := fun_prop) Continuous.norm]
theorem Continuous.norm' : Continuous f → Continuous fun x => ‖f x‖ :=
continuous_norm'.comp
#align continuous.norm' Continuous.norm'
#align continuous.norm Continuous.norm
@[to_additive (attr := fun_prop) Continuous.nnnorm]
theorem Continuous.nnnorm' : Continuous f → Continuous fun x => ‖f x‖₊ :=
continuous_nnnorm'.comp
#align continuous.nnnorm' Continuous.nnnorm'
#align continuous.nnnorm Continuous.nnnorm
@[to_additive (attr := fun_prop) ContinuousAt.norm]
theorem ContinuousAt.norm' {a : α} (h : ContinuousAt f a) : ContinuousAt (fun x => ‖f x‖) a :=
Tendsto.norm' h
#align continuous_at.norm' ContinuousAt.norm'
#align continuous_at.norm ContinuousAt.norm
@[to_additive (attr := fun_prop) ContinuousAt.nnnorm]
theorem ContinuousAt.nnnorm' {a : α} (h : ContinuousAt f a) : ContinuousAt (fun x => ‖f x‖₊) a :=
Tendsto.nnnorm' h
#align continuous_at.nnnorm' ContinuousAt.nnnorm'
#align continuous_at.nnnorm ContinuousAt.nnnorm
@[to_additive ContinuousWithinAt.norm]
theorem ContinuousWithinAt.norm' {s : Set α} {a : α} (h : ContinuousWithinAt f s a) :
ContinuousWithinAt (fun x => ‖f x‖) s a :=
Tendsto.norm' h
#align continuous_within_at.norm' ContinuousWithinAt.norm'
#align continuous_within_at.norm ContinuousWithinAt.norm
@[to_additive ContinuousWithinAt.nnnorm]
theorem ContinuousWithinAt.nnnorm' {s : Set α} {a : α} (h : ContinuousWithinAt f s a) :
ContinuousWithinAt (fun x => ‖f x‖₊) s a :=
Tendsto.nnnorm' h
#align continuous_within_at.nnnorm' ContinuousWithinAt.nnnorm'
#align continuous_within_at.nnnorm ContinuousWithinAt.nnnorm
@[to_additive (attr := fun_prop) ContinuousOn.norm]
theorem ContinuousOn.norm' {s : Set α} (h : ContinuousOn f s) : ContinuousOn (fun x => ‖f x‖) s :=
fun x hx => (h x hx).norm'
#align continuous_on.norm' ContinuousOn.norm'
#align continuous_on.norm ContinuousOn.norm
@[to_additive (attr := fun_prop) ContinuousOn.nnnorm]
theorem ContinuousOn.nnnorm' {s : Set α} (h : ContinuousOn f s) :
ContinuousOn (fun x => ‖f x‖₊) s := fun x hx => (h x hx).nnnorm'
#align continuous_on.nnnorm' ContinuousOn.nnnorm'
#align continuous_on.nnnorm ContinuousOn.nnnorm
end
/-- If `‖y‖ → ∞`, then we can assume `y ≠ x` for any fixed `x`. -/
@[to_additive eventually_ne_of_tendsto_norm_atTop "If `‖y‖→∞`, then we can assume `y≠x` for any
fixed `x`"]
theorem eventually_ne_of_tendsto_norm_atTop' {l : Filter α} {f : α → E}
(h : Tendsto (fun y => ‖f y‖) l atTop) (x : E) : ∀ᶠ y in l, f y ≠ x :=
(h.eventually_ne_atTop _).mono fun _x => ne_of_apply_ne norm
#align eventually_ne_of_tendsto_norm_at_top' eventually_ne_of_tendsto_norm_atTop'
#align eventually_ne_of_tendsto_norm_at_top eventually_ne_of_tendsto_norm_atTop
@[to_additive]
theorem SeminormedCommGroup.mem_closure_iff :
a ∈ closure s ↔ ∀ ε, 0 < ε → ∃ b ∈ s, ‖a / b‖ < ε := by
simp [Metric.mem_closure_iff, dist_eq_norm_div]
#align seminormed_comm_group.mem_closure_iff SeminormedCommGroup.mem_closure_iff
#align seminormed_add_comm_group.mem_closure_iff SeminormedAddCommGroup.mem_closure_iff
@[to_additive norm_le_zero_iff']
theorem norm_le_zero_iff''' [T0Space E] {a : E} : ‖a‖ ≤ 0 ↔ a = 1 := by
letI : NormedGroup E :=
{ ‹SeminormedGroup E› with toMetricSpace := MetricSpace.ofT0PseudoMetricSpace E }
rw [← dist_one_right, dist_le_zero]
#align norm_le_zero_iff''' norm_le_zero_iff'''
#align norm_le_zero_iff' norm_le_zero_iff'
@[to_additive norm_eq_zero']
theorem norm_eq_zero''' [T0Space E] {a : E} : ‖a‖ = 0 ↔ a = 1 :=
(norm_nonneg' a).le_iff_eq.symm.trans norm_le_zero_iff'''
#align norm_eq_zero''' norm_eq_zero'''
#align norm_eq_zero' norm_eq_zero'
@[to_additive norm_pos_iff']
theorem norm_pos_iff''' [T0Space E] {a : E} : 0 < ‖a‖ ↔ a ≠ 1 := by
rw [← not_le, norm_le_zero_iff''']
#align norm_pos_iff''' norm_pos_iff'''
#align norm_pos_iff' norm_pos_iff'
@[to_additive]
theorem SeminormedGroup.tendstoUniformlyOn_one {f : ι → κ → G} {s : Set κ} {l : Filter ι} :
TendstoUniformlyOn f 1 l s ↔ ∀ ε > 0, ∀ᶠ i in l, ∀ x ∈ s, ‖f i x‖ < ε := by
#adaptation_note /-- nightly-2024-03-11.
Originally this was `simp_rw` instead of `simp only`,
but this creates a bad proof term with nested `OfNat.ofNat` that trips up `@[to_additive]`. -/
simp only [tendstoUniformlyOn_iff, Pi.one_apply, dist_one_left]
#align seminormed_group.tendsto_uniformly_on_one SeminormedGroup.tendstoUniformlyOn_one
#align seminormed_add_group.tendsto_uniformly_on_zero SeminormedAddGroup.tendstoUniformlyOn_zero
@[to_additive]
theorem SeminormedGroup.uniformCauchySeqOnFilter_iff_tendstoUniformlyOnFilter_one {f : ι → κ → G}
{l : Filter ι} {l' : Filter κ} :
UniformCauchySeqOnFilter f l l' ↔
TendstoUniformlyOnFilter (fun n : ι × ι => fun z => f n.fst z / f n.snd z) 1 (l ×ˢ l) l' := by
refine ⟨fun hf u hu => ?_, fun hf u hu => ?_⟩
· obtain ⟨ε, hε, H⟩ := uniformity_basis_dist.mem_uniformity_iff.mp hu
refine
(hf { p : G × G | dist p.fst p.snd < ε } <| dist_mem_uniformity hε).mono fun x hx =>
H 1 (f x.fst.fst x.snd / f x.fst.snd x.snd) ?_
simpa [dist_eq_norm_div, norm_div_rev] using hx
· obtain ⟨ε, hε, H⟩ := uniformity_basis_dist.mem_uniformity_iff.mp hu
refine
(hf { p : G × G | dist p.fst p.snd < ε } <| dist_mem_uniformity hε).mono fun x hx =>
H (f x.fst.fst x.snd) (f x.fst.snd x.snd) ?_
simpa [dist_eq_norm_div, norm_div_rev] using hx
#align seminormed_group.uniform_cauchy_seq_on_filter_iff_tendsto_uniformly_on_filter_one SeminormedGroup.uniformCauchySeqOnFilter_iff_tendstoUniformlyOnFilter_one
#align seminormed_add_group.uniform_cauchy_seq_on_filter_iff_tendsto_uniformly_on_filter_zero SeminormedAddGroup.uniformCauchySeqOnFilter_iff_tendstoUniformlyOnFilter_zero
@[to_additive]
theorem SeminormedGroup.uniformCauchySeqOn_iff_tendstoUniformlyOn_one {f : ι → κ → G} {s : Set κ}
{l : Filter ι} :
UniformCauchySeqOn f l s ↔
TendstoUniformlyOn (fun n : ι × ι => fun z => f n.fst z / f n.snd z) 1 (l ×ˢ l) s := by
rw [tendstoUniformlyOn_iff_tendstoUniformlyOnFilter,
uniformCauchySeqOn_iff_uniformCauchySeqOnFilter,
SeminormedGroup.uniformCauchySeqOnFilter_iff_tendstoUniformlyOnFilter_one]
#align seminormed_group.uniform_cauchy_seq_on_iff_tendsto_uniformly_on_one SeminormedGroup.uniformCauchySeqOn_iff_tendstoUniformlyOn_one
#align seminormed_add_group.uniform_cauchy_seq_on_iff_tendsto_uniformly_on_zero SeminormedAddGroup.uniformCauchySeqOn_iff_tendstoUniformlyOn_zero
end SeminormedGroup
section Induced
variable (E F)
variable [FunLike 𝓕 E F]
-- See note [reducible non-instances]
/-- A group homomorphism from a `Group` to a `SeminormedGroup` induces a `SeminormedGroup`
structure on the domain. -/
@[to_additive (attr := reducible) "A group homomorphism from an `AddGroup` to a
`SeminormedAddGroup` induces a `SeminormedAddGroup` structure on the domain."]
def SeminormedGroup.induced [Group E] [SeminormedGroup F] [MonoidHomClass 𝓕 E F] (f : 𝓕) :
SeminormedGroup E :=
{ PseudoMetricSpace.induced f toPseudoMetricSpace with
-- Porting note: needed to add the instance explicitly, and `‹PseudoMetricSpace F›` failed
norm := fun x => ‖f x‖
dist_eq := fun x y => by simp only [map_div, ← dist_eq_norm_div]; rfl }
#align seminormed_group.induced SeminormedGroup.induced
#align seminormed_add_group.induced SeminormedAddGroup.induced
-- See note [reducible non-instances]
/-- A group homomorphism from a `CommGroup` to a `SeminormedGroup` induces a
`SeminormedCommGroup` structure on the domain. -/
@[to_additive (attr := reducible) "A group homomorphism from an `AddCommGroup` to a
`SeminormedAddGroup` induces a `SeminormedAddCommGroup` structure on the domain."]
def SeminormedCommGroup.induced
[CommGroup E] [SeminormedGroup F] [MonoidHomClass 𝓕 E F] (f : 𝓕) :
SeminormedCommGroup E :=
{ SeminormedGroup.induced E F f with
mul_comm := mul_comm }
#align seminormed_comm_group.induced SeminormedCommGroup.induced
#align seminormed_add_comm_group.induced SeminormedAddCommGroup.induced
-- See note [reducible non-instances].
/-- An injective group homomorphism from a `Group` to a `NormedGroup` induces a `NormedGroup`
structure on the domain. -/
@[to_additive (attr := reducible) "An injective group homomorphism from an `AddGroup` to a
`NormedAddGroup` induces a `NormedAddGroup` structure on the domain."]
def NormedGroup.induced
[Group E] [NormedGroup F] [MonoidHomClass 𝓕 E F] (f : 𝓕) (h : Injective f) :
NormedGroup E :=
{ SeminormedGroup.induced E F f, MetricSpace.induced f h _ with }
#align normed_group.induced NormedGroup.induced
#align normed_add_group.induced NormedAddGroup.induced
-- See note [reducible non-instances].
/-- An injective group homomorphism from a `CommGroup` to a `NormedGroup` induces a
`NormedCommGroup` structure on the domain. -/
@[to_additive (attr := reducible) "An injective group homomorphism from a `CommGroup` to a
`NormedCommGroup` induces a `NormedCommGroup` structure on the domain."]
def NormedCommGroup.induced [CommGroup E] [NormedGroup F] [MonoidHomClass 𝓕 E F] (f : 𝓕)
(h : Injective f) : NormedCommGroup E :=
{ SeminormedGroup.induced E F f, MetricSpace.induced f h _ with
mul_comm := mul_comm }
#align normed_comm_group.induced NormedCommGroup.induced
#align normed_add_comm_group.induced NormedAddCommGroup.induced
end Induced
section SeminormedCommGroup
variable [SeminormedCommGroup E] [SeminormedCommGroup F] {a a₁ a₂ b b₁ b₂ : E} {r r₁ r₂ : ℝ}
@[to_additive]
instance NormedGroup.to_isometricSMul_left : IsometricSMul E E :=
⟨fun a => Isometry.of_dist_eq fun b c => by simp [dist_eq_norm_div]⟩
#align normed_group.to_has_isometric_smul_left NormedGroup.to_isometricSMul_left
#align normed_add_group.to_has_isometric_vadd_left NormedAddGroup.to_isometricVAdd_left
@[to_additive]
theorem dist_inv (x y : E) : dist x⁻¹ y = dist x y⁻¹ := by
simp_rw [dist_eq_norm_div, ← norm_inv' (x⁻¹ / y), inv_div, div_inv_eq_mul, mul_comm]
#align dist_inv dist_inv
#align dist_neg dist_neg
@[to_additive (attr := simp)]
theorem dist_self_mul_right (a b : E) : dist a (a * b) = ‖b‖ := by
rw [← dist_one_left, ← dist_mul_left a 1 b, mul_one]
#align dist_self_mul_right dist_self_mul_right
#align dist_self_add_right dist_self_add_right
@[to_additive (attr := simp)]
theorem dist_self_mul_left (a b : E) : dist (a * b) a = ‖b‖ := by
rw [dist_comm, dist_self_mul_right]
#align dist_self_mul_left dist_self_mul_left
#align dist_self_add_left dist_self_add_left
@[to_additive (attr := simp 1001)]
-- porting note (#10618): increase priority because `simp` can prove this
theorem dist_self_div_right (a b : E) : dist a (a / b) = ‖b‖ := by
rw [div_eq_mul_inv, dist_self_mul_right, norm_inv']
#align dist_self_div_right dist_self_div_right
#align dist_self_sub_right dist_self_sub_right
@[to_additive (attr := simp 1001)]
-- porting note (#10618): increase priority because `simp` can prove this
theorem dist_self_div_left (a b : E) : dist (a / b) a = ‖b‖ := by
rw [dist_comm, dist_self_div_right]
#align dist_self_div_left dist_self_div_left
#align dist_self_sub_left dist_self_sub_left
@[to_additive]
theorem dist_mul_mul_le (a₁ a₂ b₁ b₂ : E) : dist (a₁ * a₂) (b₁ * b₂) ≤ dist a₁ b₁ + dist a₂ b₂ := by
simpa only [dist_mul_left, dist_mul_right] using dist_triangle (a₁ * a₂) (b₁ * a₂) (b₁ * b₂)
#align dist_mul_mul_le dist_mul_mul_le
#align dist_add_add_le dist_add_add_le
@[to_additive]
theorem dist_mul_mul_le_of_le (h₁ : dist a₁ b₁ ≤ r₁) (h₂ : dist a₂ b₂ ≤ r₂) :
dist (a₁ * a₂) (b₁ * b₂) ≤ r₁ + r₂ :=
(dist_mul_mul_le a₁ a₂ b₁ b₂).trans <| add_le_add h₁ h₂
#align dist_mul_mul_le_of_le dist_mul_mul_le_of_le
#align dist_add_add_le_of_le dist_add_add_le_of_le
@[to_additive]
| Mathlib/Analysis/Normed/Group/Basic.lean | 1,582 | 1,583 | theorem dist_div_div_le (a₁ a₂ b₁ b₂ : E) : dist (a₁ / a₂) (b₁ / b₂) ≤ dist a₁ b₁ + dist a₂ b₂ := by |
simpa only [div_eq_mul_inv, dist_inv_inv] using dist_mul_mul_le a₁ a₂⁻¹ b₁ b₂⁻¹
|
/-
Copyright (c) 2022 Eric Wieser. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Eric Wieser
-/
import Mathlib.Data.DFinsupp.Interval
import Mathlib.Data.DFinsupp.Multiset
import Mathlib.Order.Interval.Finset.Nat
#align_import data.multiset.interval from "leanprover-community/mathlib"@"1d29de43a5ba4662dd33b5cfeecfc2a27a5a8a29"
/-!
# Finite intervals of multisets
This file provides the `LocallyFiniteOrder` instance for `Multiset α` and calculates the
cardinality of its finite intervals.
## Implementation notes
We implement the intervals via the intervals on `DFinsupp`, rather than via filtering
`Multiset.Powerset`; this is because `(Multiset.replicate n x).Powerset` has `2^n` entries not `n+1`
entries as it contains duplicates. We do not go via `Finsupp` as this would be noncomputable, and
multisets are typically used computationally.
-/
open Finset DFinsupp Function
open Pointwise
variable {α : Type*}
namespace Multiset
variable [DecidableEq α] (s t : Multiset α)
instance instLocallyFiniteOrder : LocallyFiniteOrder (Multiset α) :=
LocallyFiniteOrder.ofIcc (Multiset α)
(fun s t => (Finset.Icc (toDFinsupp s) (toDFinsupp t)).map
Multiset.equivDFinsupp.toEquiv.symm.toEmbedding)
fun s t x => by simp
theorem Icc_eq :
Finset.Icc s t = (Finset.Icc (toDFinsupp s) (toDFinsupp t)).map
Multiset.equivDFinsupp.toEquiv.symm.toEmbedding :=
rfl
#align multiset.Icc_eq Multiset.Icc_eq
theorem uIcc_eq :
uIcc s t =
(uIcc (toDFinsupp s) (toDFinsupp t)).map Multiset.equivDFinsupp.toEquiv.symm.toEmbedding :=
(Icc_eq _ _).trans <| by simp [uIcc]
#align multiset.uIcc_eq Multiset.uIcc_eq
theorem card_Icc :
(Finset.Icc s t).card = ∏ i ∈ s.toFinset ∪ t.toFinset, (t.count i + 1 - s.count i) := by
simp_rw [Icc_eq, Finset.card_map, DFinsupp.card_Icc, Nat.card_Icc, Multiset.toDFinsupp_apply,
toDFinsupp_support]
#align multiset.card_Icc Multiset.card_Icc
theorem card_Ico :
(Finset.Ico s t).card = ∏ i ∈ s.toFinset ∪ t.toFinset, (t.count i + 1 - s.count i) - 1 := by
rw [Finset.card_Ico_eq_card_Icc_sub_one, card_Icc]
#align multiset.card_Ico Multiset.card_Ico
theorem card_Ioc :
(Finset.Ioc s t).card = ∏ i ∈ s.toFinset ∪ t.toFinset, (t.count i + 1 - s.count i) - 1 := by
rw [Finset.card_Ioc_eq_card_Icc_sub_one, card_Icc]
#align multiset.card_Ioc Multiset.card_Ioc
theorem card_Ioo :
(Finset.Ioo s t).card = ∏ i ∈ s.toFinset ∪ t.toFinset, (t.count i + 1 - s.count i) - 2 := by
rw [Finset.card_Ioo_eq_card_Icc_sub_two, card_Icc]
#align multiset.card_Ioo Multiset.card_Ioo
| Mathlib/Data/Multiset/Interval.lean | 77 | 80 | theorem card_uIcc :
(uIcc s t).card = ∏ i ∈ s.toFinset ∪ t.toFinset, ((t.count i - s.count i : ℤ).natAbs + 1) := by |
simp_rw [uIcc_eq, Finset.card_map, DFinsupp.card_uIcc, Nat.card_uIcc, Multiset.toDFinsupp_apply,
toDFinsupp_support]
|
/-
Copyright (c) 2021 Rémy Degenne. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Zhouhang Zhou, Yury Kudryashov, Sébastien Gouëzel, Rémy Degenne
-/
import Mathlib.MeasureTheory.Function.SimpleFuncDenseLp
#align_import measure_theory.integral.set_to_l1 from "leanprover-community/mathlib"@"f2ce6086713c78a7f880485f7917ea547a215982"
/-!
# Extension of a linear function from indicators to L1
Let `T : Set α → E →L[ℝ] F` be additive for measurable sets with finite measure, in the sense that
for `s, t` two such sets, `s ∩ t = ∅ → T (s ∪ t) = T s + T t`. `T` is akin to a bilinear map on
`Set α × E`, or a linear map on indicator functions.
This file constructs an extension of `T` to integrable simple functions, which are finite sums of
indicators of measurable sets with finite measure, then to integrable functions, which are limits of
integrable simple functions.
The main result is a continuous linear map `(α →₁[μ] E) →L[ℝ] F`. This extension process is used to
define the Bochner integral in the `MeasureTheory.Integral.Bochner` file and the conditional
expectation of an integrable function in `MeasureTheory.Function.ConditionalExpectation`.
## Main Definitions
- `FinMeasAdditive μ T`: the property that `T` is additive on measurable sets with finite measure.
For two such sets, `s ∩ t = ∅ → T (s ∪ t) = T s + T t`.
- `DominatedFinMeasAdditive μ T C`: `FinMeasAdditive μ T ∧ ∀ s, ‖T s‖ ≤ C * (μ s).toReal`.
This is the property needed to perform the extension from indicators to L1.
- `setToL1 (hT : DominatedFinMeasAdditive μ T C) : (α →₁[μ] E) →L[ℝ] F`: the extension of `T`
from indicators to L1.
- `setToFun μ T (hT : DominatedFinMeasAdditive μ T C) (f : α → E) : F`: a version of the
extension which applies to functions (with value 0 if the function is not integrable).
## Properties
For most properties of `setToFun`, we provide two lemmas. One version uses hypotheses valid on
all sets, like `T = T'`, and a second version which uses a primed name uses hypotheses on
measurable sets with finite measure, like `∀ s, MeasurableSet s → μ s < ∞ → T s = T' s`.
The lemmas listed here don't show all hypotheses. Refer to the actual lemmas for details.
Linearity:
- `setToFun_zero_left : setToFun μ 0 hT f = 0`
- `setToFun_add_left : setToFun μ (T + T') _ f = setToFun μ T hT f + setToFun μ T' hT' f`
- `setToFun_smul_left : setToFun μ (fun s ↦ c • (T s)) (hT.smul c) f = c • setToFun μ T hT f`
- `setToFun_zero : setToFun μ T hT (0 : α → E) = 0`
- `setToFun_neg : setToFun μ T hT (-f) = - setToFun μ T hT f`
If `f` and `g` are integrable:
- `setToFun_add : setToFun μ T hT (f + g) = setToFun μ T hT f + setToFun μ T hT g`
- `setToFun_sub : setToFun μ T hT (f - g) = setToFun μ T hT f - setToFun μ T hT g`
If `T` is verifies `∀ c : 𝕜, ∀ s x, T s (c • x) = c • T s x`:
- `setToFun_smul : setToFun μ T hT (c • f) = c • setToFun μ T hT f`
Other:
- `setToFun_congr_ae (h : f =ᵐ[μ] g) : setToFun μ T hT f = setToFun μ T hT g`
- `setToFun_measure_zero (h : μ = 0) : setToFun μ T hT f = 0`
If the space is a `NormedLatticeAddCommGroup` and `T` is such that `0 ≤ T s x` for `0 ≤ x`, we
also prove order-related properties:
- `setToFun_mono_left (h : ∀ s x, T s x ≤ T' s x) : setToFun μ T hT f ≤ setToFun μ T' hT' f`
- `setToFun_nonneg (hf : 0 ≤ᵐ[μ] f) : 0 ≤ setToFun μ T hT f`
- `setToFun_mono (hfg : f ≤ᵐ[μ] g) : setToFun μ T hT f ≤ setToFun μ T hT g`
## Implementation notes
The starting object `T : Set α → E →L[ℝ] F` matters only through its restriction on measurable sets
with finite measure. Its value on other sets is ignored.
-/
noncomputable section
open scoped Classical Topology NNReal ENNReal MeasureTheory Pointwise
open Set Filter TopologicalSpace ENNReal EMetric
namespace MeasureTheory
variable {α E F F' G 𝕜 : Type*} {p : ℝ≥0∞} [NormedAddCommGroup E] [NormedSpace ℝ E]
[NormedAddCommGroup F] [NormedSpace ℝ F] [NormedAddCommGroup F'] [NormedSpace ℝ F']
[NormedAddCommGroup G] {m : MeasurableSpace α} {μ : Measure α}
local infixr:25 " →ₛ " => SimpleFunc
open Finset
section FinMeasAdditive
/-- A set function is `FinMeasAdditive` if its value on the union of two disjoint measurable
sets with finite measure is the sum of its values on each set. -/
def FinMeasAdditive {β} [AddMonoid β] {_ : MeasurableSpace α} (μ : Measure α) (T : Set α → β) :
Prop :=
∀ s t, MeasurableSet s → MeasurableSet t → μ s ≠ ∞ → μ t ≠ ∞ → s ∩ t = ∅ → T (s ∪ t) = T s + T t
#align measure_theory.fin_meas_additive MeasureTheory.FinMeasAdditive
namespace FinMeasAdditive
variable {β : Type*} [AddCommMonoid β] {T T' : Set α → β}
theorem zero : FinMeasAdditive μ (0 : Set α → β) := fun s t _ _ _ _ _ => by simp
#align measure_theory.fin_meas_additive.zero MeasureTheory.FinMeasAdditive.zero
theorem add (hT : FinMeasAdditive μ T) (hT' : FinMeasAdditive μ T') :
FinMeasAdditive μ (T + T') := by
intro s t hs ht hμs hμt hst
simp only [hT s t hs ht hμs hμt hst, hT' s t hs ht hμs hμt hst, Pi.add_apply]
abel
#align measure_theory.fin_meas_additive.add MeasureTheory.FinMeasAdditive.add
theorem smul [Monoid 𝕜] [DistribMulAction 𝕜 β] (hT : FinMeasAdditive μ T) (c : 𝕜) :
FinMeasAdditive μ fun s => c • T s := fun s t hs ht hμs hμt hst => by
simp [hT s t hs ht hμs hμt hst]
#align measure_theory.fin_meas_additive.smul MeasureTheory.FinMeasAdditive.smul
theorem of_eq_top_imp_eq_top {μ' : Measure α} (h : ∀ s, MeasurableSet s → μ s = ∞ → μ' s = ∞)
(hT : FinMeasAdditive μ T) : FinMeasAdditive μ' T := fun s t hs ht hμ's hμ't hst =>
hT s t hs ht (mt (h s hs) hμ's) (mt (h t ht) hμ't) hst
#align measure_theory.fin_meas_additive.of_eq_top_imp_eq_top MeasureTheory.FinMeasAdditive.of_eq_top_imp_eq_top
theorem of_smul_measure (c : ℝ≥0∞) (hc_ne_top : c ≠ ∞) (hT : FinMeasAdditive (c • μ) T) :
FinMeasAdditive μ T := by
refine of_eq_top_imp_eq_top (fun s _ hμs => ?_) hT
rw [Measure.smul_apply, smul_eq_mul, ENNReal.mul_eq_top] at hμs
simp only [hc_ne_top, or_false_iff, Ne, false_and_iff] at hμs
exact hμs.2
#align measure_theory.fin_meas_additive.of_smul_measure MeasureTheory.FinMeasAdditive.of_smul_measure
theorem smul_measure (c : ℝ≥0∞) (hc_ne_zero : c ≠ 0) (hT : FinMeasAdditive μ T) :
FinMeasAdditive (c • μ) T := by
refine of_eq_top_imp_eq_top (fun s _ hμs => ?_) hT
rw [Measure.smul_apply, smul_eq_mul, ENNReal.mul_eq_top]
simp only [hc_ne_zero, true_and_iff, Ne, not_false_iff]
exact Or.inl hμs
#align measure_theory.fin_meas_additive.smul_measure MeasureTheory.FinMeasAdditive.smul_measure
theorem smul_measure_iff (c : ℝ≥0∞) (hc_ne_zero : c ≠ 0) (hc_ne_top : c ≠ ∞) :
FinMeasAdditive (c • μ) T ↔ FinMeasAdditive μ T :=
⟨fun hT => of_smul_measure c hc_ne_top hT, fun hT => smul_measure c hc_ne_zero hT⟩
#align measure_theory.fin_meas_additive.smul_measure_iff MeasureTheory.FinMeasAdditive.smul_measure_iff
theorem map_empty_eq_zero {β} [AddCancelMonoid β] {T : Set α → β} (hT : FinMeasAdditive μ T) :
T ∅ = 0 := by
have h_empty : μ ∅ ≠ ∞ := (measure_empty.le.trans_lt ENNReal.coe_lt_top).ne
specialize hT ∅ ∅ MeasurableSet.empty MeasurableSet.empty h_empty h_empty (Set.inter_empty ∅)
rw [Set.union_empty] at hT
nth_rw 1 [← add_zero (T ∅)] at hT
exact (add_left_cancel hT).symm
#align measure_theory.fin_meas_additive.map_empty_eq_zero MeasureTheory.FinMeasAdditive.map_empty_eq_zero
theorem map_iUnion_fin_meas_set_eq_sum (T : Set α → β) (T_empty : T ∅ = 0)
(h_add : FinMeasAdditive μ T) {ι} (S : ι → Set α) (sι : Finset ι)
(hS_meas : ∀ i, MeasurableSet (S i)) (hSp : ∀ i ∈ sι, μ (S i) ≠ ∞)
(h_disj : ∀ᵉ (i ∈ sι) (j ∈ sι), i ≠ j → Disjoint (S i) (S j)) :
T (⋃ i ∈ sι, S i) = ∑ i ∈ sι, T (S i) := by
revert hSp h_disj
refine Finset.induction_on sι ?_ ?_
· simp only [Finset.not_mem_empty, IsEmpty.forall_iff, iUnion_false, iUnion_empty, sum_empty,
forall₂_true_iff, imp_true_iff, forall_true_left, not_false_iff, T_empty]
intro a s has h hps h_disj
rw [Finset.sum_insert has, ← h]
swap; · exact fun i hi => hps i (Finset.mem_insert_of_mem hi)
swap;
· exact fun i hi j hj hij =>
h_disj i (Finset.mem_insert_of_mem hi) j (Finset.mem_insert_of_mem hj) hij
rw [←
h_add (S a) (⋃ i ∈ s, S i) (hS_meas a) (measurableSet_biUnion _ fun i _ => hS_meas i)
(hps a (Finset.mem_insert_self a s))]
· congr; convert Finset.iSup_insert a s S
· exact
((measure_biUnion_finset_le _ _).trans_lt <|
ENNReal.sum_lt_top fun i hi => hps i <| Finset.mem_insert_of_mem hi).ne
· simp_rw [Set.inter_iUnion]
refine iUnion_eq_empty.mpr fun i => iUnion_eq_empty.mpr fun hi => ?_
rw [← Set.disjoint_iff_inter_eq_empty]
refine h_disj a (Finset.mem_insert_self a s) i (Finset.mem_insert_of_mem hi) fun hai => ?_
rw [← hai] at hi
exact has hi
#align measure_theory.fin_meas_additive.map_Union_fin_meas_set_eq_sum MeasureTheory.FinMeasAdditive.map_iUnion_fin_meas_set_eq_sum
end FinMeasAdditive
/-- A `FinMeasAdditive` set function whose norm on every set is less than the measure of the
set (up to a multiplicative constant). -/
def DominatedFinMeasAdditive {β} [SeminormedAddCommGroup β] {_ : MeasurableSpace α} (μ : Measure α)
(T : Set α → β) (C : ℝ) : Prop :=
FinMeasAdditive μ T ∧ ∀ s, MeasurableSet s → μ s < ∞ → ‖T s‖ ≤ C * (μ s).toReal
#align measure_theory.dominated_fin_meas_additive MeasureTheory.DominatedFinMeasAdditive
namespace DominatedFinMeasAdditive
variable {β : Type*} [SeminormedAddCommGroup β] {T T' : Set α → β} {C C' : ℝ}
theorem zero {m : MeasurableSpace α} (μ : Measure α) (hC : 0 ≤ C) :
DominatedFinMeasAdditive μ (0 : Set α → β) C := by
refine ⟨FinMeasAdditive.zero, fun s _ _ => ?_⟩
rw [Pi.zero_apply, norm_zero]
exact mul_nonneg hC toReal_nonneg
#align measure_theory.dominated_fin_meas_additive.zero MeasureTheory.DominatedFinMeasAdditive.zero
theorem eq_zero_of_measure_zero {β : Type*} [NormedAddCommGroup β] {T : Set α → β} {C : ℝ}
(hT : DominatedFinMeasAdditive μ T C) {s : Set α} (hs : MeasurableSet s) (hs_zero : μ s = 0) :
T s = 0 := by
refine norm_eq_zero.mp ?_
refine ((hT.2 s hs (by simp [hs_zero])).trans (le_of_eq ?_)).antisymm (norm_nonneg _)
rw [hs_zero, ENNReal.zero_toReal, mul_zero]
#align measure_theory.dominated_fin_meas_additive.eq_zero_of_measure_zero MeasureTheory.DominatedFinMeasAdditive.eq_zero_of_measure_zero
theorem eq_zero {β : Type*} [NormedAddCommGroup β] {T : Set α → β} {C : ℝ} {m : MeasurableSpace α}
(hT : DominatedFinMeasAdditive (0 : Measure α) T C) {s : Set α} (hs : MeasurableSet s) :
T s = 0 :=
eq_zero_of_measure_zero hT hs (by simp only [Measure.coe_zero, Pi.zero_apply])
#align measure_theory.dominated_fin_meas_additive.eq_zero MeasureTheory.DominatedFinMeasAdditive.eq_zero
theorem add (hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C') :
DominatedFinMeasAdditive μ (T + T') (C + C') := by
refine ⟨hT.1.add hT'.1, fun s hs hμs => ?_⟩
rw [Pi.add_apply, add_mul]
exact (norm_add_le _ _).trans (add_le_add (hT.2 s hs hμs) (hT'.2 s hs hμs))
#align measure_theory.dominated_fin_meas_additive.add MeasureTheory.DominatedFinMeasAdditive.add
theorem smul [NormedField 𝕜] [NormedSpace 𝕜 β] (hT : DominatedFinMeasAdditive μ T C) (c : 𝕜) :
DominatedFinMeasAdditive μ (fun s => c • T s) (‖c‖ * C) := by
refine ⟨hT.1.smul c, fun s hs hμs => ?_⟩
dsimp only
rw [norm_smul, mul_assoc]
exact mul_le_mul le_rfl (hT.2 s hs hμs) (norm_nonneg _) (norm_nonneg _)
#align measure_theory.dominated_fin_meas_additive.smul MeasureTheory.DominatedFinMeasAdditive.smul
theorem of_measure_le {μ' : Measure α} (h : μ ≤ μ') (hT : DominatedFinMeasAdditive μ T C)
(hC : 0 ≤ C) : DominatedFinMeasAdditive μ' T C := by
have h' : ∀ s, μ s = ∞ → μ' s = ∞ := fun s hs ↦ top_unique <| hs.symm.trans_le (h _)
refine ⟨hT.1.of_eq_top_imp_eq_top fun s _ ↦ h' s, fun s hs hμ's ↦ ?_⟩
have hμs : μ s < ∞ := (h s).trans_lt hμ's
calc
‖T s‖ ≤ C * (μ s).toReal := hT.2 s hs hμs
_ ≤ C * (μ' s).toReal := by gcongr; exacts [hμ's.ne, h _]
#align measure_theory.dominated_fin_meas_additive.of_measure_le MeasureTheory.DominatedFinMeasAdditive.of_measure_le
theorem add_measure_right {_ : MeasurableSpace α} (μ ν : Measure α)
(hT : DominatedFinMeasAdditive μ T C) (hC : 0 ≤ C) : DominatedFinMeasAdditive (μ + ν) T C :=
of_measure_le (Measure.le_add_right le_rfl) hT hC
#align measure_theory.dominated_fin_meas_additive.add_measure_right MeasureTheory.DominatedFinMeasAdditive.add_measure_right
theorem add_measure_left {_ : MeasurableSpace α} (μ ν : Measure α)
(hT : DominatedFinMeasAdditive ν T C) (hC : 0 ≤ C) : DominatedFinMeasAdditive (μ + ν) T C :=
of_measure_le (Measure.le_add_left le_rfl) hT hC
#align measure_theory.dominated_fin_meas_additive.add_measure_left MeasureTheory.DominatedFinMeasAdditive.add_measure_left
theorem of_smul_measure (c : ℝ≥0∞) (hc_ne_top : c ≠ ∞) (hT : DominatedFinMeasAdditive (c • μ) T C) :
DominatedFinMeasAdditive μ T (c.toReal * C) := by
have h : ∀ s, MeasurableSet s → c • μ s = ∞ → μ s = ∞ := by
intro s _ hcμs
simp only [hc_ne_top, Algebra.id.smul_eq_mul, ENNReal.mul_eq_top, or_false_iff, Ne,
false_and_iff] at hcμs
exact hcμs.2
refine ⟨hT.1.of_eq_top_imp_eq_top (μ := c • μ) h, fun s hs hμs => ?_⟩
have hcμs : c • μ s ≠ ∞ := mt (h s hs) hμs.ne
rw [smul_eq_mul] at hcμs
simp_rw [DominatedFinMeasAdditive, Measure.smul_apply, smul_eq_mul, toReal_mul] at hT
refine (hT.2 s hs hcμs.lt_top).trans (le_of_eq ?_)
ring
#align measure_theory.dominated_fin_meas_additive.of_smul_measure MeasureTheory.DominatedFinMeasAdditive.of_smul_measure
theorem of_measure_le_smul {μ' : Measure α} (c : ℝ≥0∞) (hc : c ≠ ∞) (h : μ ≤ c • μ')
(hT : DominatedFinMeasAdditive μ T C) (hC : 0 ≤ C) :
DominatedFinMeasAdditive μ' T (c.toReal * C) :=
(hT.of_measure_le h hC).of_smul_measure c hc
#align measure_theory.dominated_fin_meas_additive.of_measure_le_smul MeasureTheory.DominatedFinMeasAdditive.of_measure_le_smul
end DominatedFinMeasAdditive
end FinMeasAdditive
namespace SimpleFunc
/-- Extend `Set α → (F →L[ℝ] F')` to `(α →ₛ F) → F'`. -/
def setToSimpleFunc {_ : MeasurableSpace α} (T : Set α → F →L[ℝ] F') (f : α →ₛ F) : F' :=
∑ x ∈ f.range, T (f ⁻¹' {x}) x
#align measure_theory.simple_func.set_to_simple_func MeasureTheory.SimpleFunc.setToSimpleFunc
@[simp]
theorem setToSimpleFunc_zero {m : MeasurableSpace α} (f : α →ₛ F) :
setToSimpleFunc (0 : Set α → F →L[ℝ] F') f = 0 := by simp [setToSimpleFunc]
#align measure_theory.simple_func.set_to_simple_func_zero MeasureTheory.SimpleFunc.setToSimpleFunc_zero
theorem setToSimpleFunc_zero' {T : Set α → E →L[ℝ] F'}
(h_zero : ∀ s, MeasurableSet s → μ s < ∞ → T s = 0) (f : α →ₛ E) (hf : Integrable f μ) :
setToSimpleFunc T f = 0 := by
simp_rw [setToSimpleFunc]
refine sum_eq_zero fun x _ => ?_
by_cases hx0 : x = 0
· simp [hx0]
rw [h_zero (f ⁻¹' ({x} : Set E)) (measurableSet_fiber _ _)
(measure_preimage_lt_top_of_integrable f hf hx0),
ContinuousLinearMap.zero_apply]
#align measure_theory.simple_func.set_to_simple_func_zero' MeasureTheory.SimpleFunc.setToSimpleFunc_zero'
@[simp]
theorem setToSimpleFunc_zero_apply {m : MeasurableSpace α} (T : Set α → F →L[ℝ] F') :
setToSimpleFunc T (0 : α →ₛ F) = 0 := by
cases isEmpty_or_nonempty α <;> simp [setToSimpleFunc]
#align measure_theory.simple_func.set_to_simple_func_zero_apply MeasureTheory.SimpleFunc.setToSimpleFunc_zero_apply
theorem setToSimpleFunc_eq_sum_filter {m : MeasurableSpace α} (T : Set α → F →L[ℝ] F')
(f : α →ₛ F) :
setToSimpleFunc T f = ∑ x ∈ f.range.filter fun x => x ≠ 0, (T (f ⁻¹' {x})) x := by
symm
refine sum_filter_of_ne fun x _ => mt fun hx0 => ?_
rw [hx0]
exact ContinuousLinearMap.map_zero _
#align measure_theory.simple_func.set_to_simple_func_eq_sum_filter MeasureTheory.SimpleFunc.setToSimpleFunc_eq_sum_filter
theorem map_setToSimpleFunc (T : Set α → F →L[ℝ] F') (h_add : FinMeasAdditive μ T) {f : α →ₛ G}
(hf : Integrable f μ) {g : G → F} (hg : g 0 = 0) :
(f.map g).setToSimpleFunc T = ∑ x ∈ f.range, T (f ⁻¹' {x}) (g x) := by
have T_empty : T ∅ = 0 := h_add.map_empty_eq_zero
have hfp : ∀ x ∈ f.range, x ≠ 0 → μ (f ⁻¹' {x}) ≠ ∞ := fun x _ hx0 =>
(measure_preimage_lt_top_of_integrable f hf hx0).ne
simp only [setToSimpleFunc, range_map]
refine Finset.sum_image' _ fun b hb => ?_
rcases mem_range.1 hb with ⟨a, rfl⟩
by_cases h0 : g (f a) = 0
· simp_rw [h0]
rw [ContinuousLinearMap.map_zero, Finset.sum_eq_zero fun x hx => ?_]
rw [mem_filter] at hx
rw [hx.2, ContinuousLinearMap.map_zero]
have h_left_eq :
T (map g f ⁻¹' {g (f a)}) (g (f a)) =
T (f ⁻¹' (f.range.filter fun b => g b = g (f a))) (g (f a)) := by
congr; rw [map_preimage_singleton]
rw [h_left_eq]
have h_left_eq' :
T (f ⁻¹' (filter (fun b : G => g b = g (f a)) f.range)) (g (f a)) =
T (⋃ y ∈ filter (fun b : G => g b = g (f a)) f.range, f ⁻¹' {y}) (g (f a)) := by
congr; rw [← Finset.set_biUnion_preimage_singleton]
rw [h_left_eq']
rw [h_add.map_iUnion_fin_meas_set_eq_sum T T_empty]
· simp only [sum_apply, ContinuousLinearMap.coe_sum']
refine Finset.sum_congr rfl fun x hx => ?_
rw [mem_filter] at hx
rw [hx.2]
· exact fun i => measurableSet_fiber _ _
· intro i hi
rw [mem_filter] at hi
refine hfp i hi.1 fun hi0 => ?_
rw [hi0, hg] at hi
exact h0 hi.2.symm
· intro i _j hi _ hij
rw [Set.disjoint_iff]
intro x hx
rw [Set.mem_inter_iff, Set.mem_preimage, Set.mem_preimage, Set.mem_singleton_iff,
Set.mem_singleton_iff] at hx
rw [← hx.1, ← hx.2] at hij
exact absurd rfl hij
#align measure_theory.simple_func.map_set_to_simple_func MeasureTheory.SimpleFunc.map_setToSimpleFunc
theorem setToSimpleFunc_congr' (T : Set α → E →L[ℝ] F) (h_add : FinMeasAdditive μ T) {f g : α →ₛ E}
(hf : Integrable f μ) (hg : Integrable g μ)
(h : Pairwise fun x y => T (f ⁻¹' {x} ∩ g ⁻¹' {y}) = 0) :
f.setToSimpleFunc T = g.setToSimpleFunc T :=
show ((pair f g).map Prod.fst).setToSimpleFunc T = ((pair f g).map Prod.snd).setToSimpleFunc T by
have h_pair : Integrable (f.pair g) μ := integrable_pair hf hg
rw [map_setToSimpleFunc T h_add h_pair Prod.fst_zero]
rw [map_setToSimpleFunc T h_add h_pair Prod.snd_zero]
refine Finset.sum_congr rfl fun p hp => ?_
rcases mem_range.1 hp with ⟨a, rfl⟩
by_cases eq : f a = g a
· dsimp only [pair_apply]; rw [eq]
· have : T (pair f g ⁻¹' {(f a, g a)}) = 0 := by
have h_eq : T ((⇑(f.pair g)) ⁻¹' {(f a, g a)}) = T (f ⁻¹' {f a} ∩ g ⁻¹' {g a}) := by
congr; rw [pair_preimage_singleton f g]
rw [h_eq]
exact h eq
simp only [this, ContinuousLinearMap.zero_apply, pair_apply]
#align measure_theory.simple_func.set_to_simple_func_congr' MeasureTheory.SimpleFunc.setToSimpleFunc_congr'
theorem setToSimpleFunc_congr (T : Set α → E →L[ℝ] F)
(h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0) (h_add : FinMeasAdditive μ T) {f g : α →ₛ E}
(hf : Integrable f μ) (h : f =ᵐ[μ] g) : f.setToSimpleFunc T = g.setToSimpleFunc T := by
refine setToSimpleFunc_congr' T h_add hf ((integrable_congr h).mp hf) ?_
refine fun x y hxy => h_zero _ ((measurableSet_fiber f x).inter (measurableSet_fiber g y)) ?_
rw [EventuallyEq, ae_iff] at h
refine measure_mono_null (fun z => ?_) h
simp_rw [Set.mem_inter_iff, Set.mem_setOf_eq, Set.mem_preimage, Set.mem_singleton_iff]
intro h
rwa [h.1, h.2]
#align measure_theory.simple_func.set_to_simple_func_congr MeasureTheory.SimpleFunc.setToSimpleFunc_congr
theorem setToSimpleFunc_congr_left (T T' : Set α → E →L[ℝ] F)
(h : ∀ s, MeasurableSet s → μ s < ∞ → T s = T' s) (f : α →ₛ E) (hf : Integrable f μ) :
setToSimpleFunc T f = setToSimpleFunc T' f := by
simp_rw [setToSimpleFunc]
refine sum_congr rfl fun x _ => ?_
by_cases hx0 : x = 0
· simp [hx0]
· rw [h (f ⁻¹' {x}) (SimpleFunc.measurableSet_fiber _ _)
(SimpleFunc.measure_preimage_lt_top_of_integrable _ hf hx0)]
#align measure_theory.simple_func.set_to_simple_func_congr_left MeasureTheory.SimpleFunc.setToSimpleFunc_congr_left
theorem setToSimpleFunc_add_left {m : MeasurableSpace α} (T T' : Set α → F →L[ℝ] F') {f : α →ₛ F} :
setToSimpleFunc (T + T') f = setToSimpleFunc T f + setToSimpleFunc T' f := by
simp_rw [setToSimpleFunc, Pi.add_apply]
push_cast
simp_rw [Pi.add_apply, sum_add_distrib]
#align measure_theory.simple_func.set_to_simple_func_add_left MeasureTheory.SimpleFunc.setToSimpleFunc_add_left
theorem setToSimpleFunc_add_left' (T T' T'' : Set α → E →L[ℝ] F)
(h_add : ∀ s, MeasurableSet s → μ s < ∞ → T'' s = T s + T' s) {f : α →ₛ E}
(hf : Integrable f μ) : setToSimpleFunc T'' f = setToSimpleFunc T f + setToSimpleFunc T' f := by
simp_rw [setToSimpleFunc_eq_sum_filter]
suffices
∀ x ∈ filter (fun x : E => x ≠ 0) f.range, T'' (f ⁻¹' {x}) = T (f ⁻¹' {x}) + T' (f ⁻¹' {x}) by
rw [← sum_add_distrib]
refine Finset.sum_congr rfl fun x hx => ?_
rw [this x hx]
push_cast
rw [Pi.add_apply]
intro x hx
refine
h_add (f ⁻¹' {x}) (measurableSet_preimage _ _) (measure_preimage_lt_top_of_integrable _ hf ?_)
rw [mem_filter] at hx
exact hx.2
#align measure_theory.simple_func.set_to_simple_func_add_left' MeasureTheory.SimpleFunc.setToSimpleFunc_add_left'
theorem setToSimpleFunc_smul_left {m : MeasurableSpace α} (T : Set α → F →L[ℝ] F') (c : ℝ)
(f : α →ₛ F) : setToSimpleFunc (fun s => c • T s) f = c • setToSimpleFunc T f := by
simp_rw [setToSimpleFunc, ContinuousLinearMap.smul_apply, smul_sum]
#align measure_theory.simple_func.set_to_simple_func_smul_left MeasureTheory.SimpleFunc.setToSimpleFunc_smul_left
theorem setToSimpleFunc_smul_left' (T T' : Set α → E →L[ℝ] F') (c : ℝ)
(h_smul : ∀ s, MeasurableSet s → μ s < ∞ → T' s = c • T s) {f : α →ₛ E} (hf : Integrable f μ) :
setToSimpleFunc T' f = c • setToSimpleFunc T f := by
simp_rw [setToSimpleFunc_eq_sum_filter]
suffices ∀ x ∈ filter (fun x : E => x ≠ 0) f.range, T' (f ⁻¹' {x}) = c • T (f ⁻¹' {x}) by
rw [smul_sum]
refine Finset.sum_congr rfl fun x hx => ?_
rw [this x hx]
rfl
intro x hx
refine
h_smul (f ⁻¹' {x}) (measurableSet_preimage _ _) (measure_preimage_lt_top_of_integrable _ hf ?_)
rw [mem_filter] at hx
exact hx.2
#align measure_theory.simple_func.set_to_simple_func_smul_left' MeasureTheory.SimpleFunc.setToSimpleFunc_smul_left'
theorem setToSimpleFunc_add (T : Set α → E →L[ℝ] F) (h_add : FinMeasAdditive μ T) {f g : α →ₛ E}
(hf : Integrable f μ) (hg : Integrable g μ) :
setToSimpleFunc T (f + g) = setToSimpleFunc T f + setToSimpleFunc T g :=
have hp_pair : Integrable (f.pair g) μ := integrable_pair hf hg
calc
setToSimpleFunc T (f + g) = ∑ x ∈ (pair f g).range, T (pair f g ⁻¹' {x}) (x.fst + x.snd) := by
rw [add_eq_map₂, map_setToSimpleFunc T h_add hp_pair]; simp
_ = ∑ x ∈ (pair f g).range, (T (pair f g ⁻¹' {x}) x.fst + T (pair f g ⁻¹' {x}) x.snd) :=
(Finset.sum_congr rfl fun a _ => ContinuousLinearMap.map_add _ _ _)
_ = (∑ x ∈ (pair f g).range, T (pair f g ⁻¹' {x}) x.fst) +
∑ x ∈ (pair f g).range, T (pair f g ⁻¹' {x}) x.snd := by
rw [Finset.sum_add_distrib]
_ = ((pair f g).map Prod.fst).setToSimpleFunc T +
((pair f g).map Prod.snd).setToSimpleFunc T := by
rw [map_setToSimpleFunc T h_add hp_pair Prod.snd_zero,
map_setToSimpleFunc T h_add hp_pair Prod.fst_zero]
#align measure_theory.simple_func.set_to_simple_func_add MeasureTheory.SimpleFunc.setToSimpleFunc_add
theorem setToSimpleFunc_neg (T : Set α → E →L[ℝ] F) (h_add : FinMeasAdditive μ T) {f : α →ₛ E}
(hf : Integrable f μ) : setToSimpleFunc T (-f) = -setToSimpleFunc T f :=
calc
setToSimpleFunc T (-f) = setToSimpleFunc T (f.map Neg.neg) := rfl
_ = -setToSimpleFunc T f := by
rw [map_setToSimpleFunc T h_add hf neg_zero, setToSimpleFunc, ← sum_neg_distrib]
exact Finset.sum_congr rfl fun x _ => ContinuousLinearMap.map_neg _ _
#align measure_theory.simple_func.set_to_simple_func_neg MeasureTheory.SimpleFunc.setToSimpleFunc_neg
theorem setToSimpleFunc_sub (T : Set α → E →L[ℝ] F) (h_add : FinMeasAdditive μ T) {f g : α →ₛ E}
(hf : Integrable f μ) (hg : Integrable g μ) :
setToSimpleFunc T (f - g) = setToSimpleFunc T f - setToSimpleFunc T g := by
rw [sub_eq_add_neg, setToSimpleFunc_add T h_add hf, setToSimpleFunc_neg T h_add hg,
sub_eq_add_neg]
rw [integrable_iff] at hg ⊢
intro x hx_ne
change μ (Neg.neg ∘ g ⁻¹' {x}) < ∞
rw [preimage_comp, neg_preimage, Set.neg_singleton]
refine hg (-x) ?_
simp [hx_ne]
#align measure_theory.simple_func.set_to_simple_func_sub MeasureTheory.SimpleFunc.setToSimpleFunc_sub
theorem setToSimpleFunc_smul_real (T : Set α → E →L[ℝ] F) (h_add : FinMeasAdditive μ T) (c : ℝ)
{f : α →ₛ E} (hf : Integrable f μ) : setToSimpleFunc T (c • f) = c • setToSimpleFunc T f :=
calc
setToSimpleFunc T (c • f) = ∑ x ∈ f.range, T (f ⁻¹' {x}) (c • x) := by
rw [smul_eq_map c f, map_setToSimpleFunc T h_add hf]; dsimp only; rw [smul_zero]
_ = ∑ x ∈ f.range, c • T (f ⁻¹' {x}) x :=
(Finset.sum_congr rfl fun b _ => by rw [ContinuousLinearMap.map_smul (T (f ⁻¹' {b})) c b])
_ = c • setToSimpleFunc T f := by simp only [setToSimpleFunc, smul_sum, smul_smul, mul_comm]
#align measure_theory.simple_func.set_to_simple_func_smul_real MeasureTheory.SimpleFunc.setToSimpleFunc_smul_real
theorem setToSimpleFunc_smul {E} [NormedAddCommGroup E] [NormedField 𝕜] [NormedSpace 𝕜 E]
[NormedSpace ℝ E] [NormedSpace 𝕜 F] (T : Set α → E →L[ℝ] F) (h_add : FinMeasAdditive μ T)
(h_smul : ∀ c : 𝕜, ∀ s x, T s (c • x) = c • T s x) (c : 𝕜) {f : α →ₛ E} (hf : Integrable f μ) :
setToSimpleFunc T (c • f) = c • setToSimpleFunc T f :=
calc
setToSimpleFunc T (c • f) = ∑ x ∈ f.range, T (f ⁻¹' {x}) (c • x) := by
rw [smul_eq_map c f, map_setToSimpleFunc T h_add hf]; dsimp only; rw [smul_zero]
_ = ∑ x ∈ f.range, c • T (f ⁻¹' {x}) x := Finset.sum_congr rfl fun b _ => by rw [h_smul]
_ = c • setToSimpleFunc T f := by simp only [setToSimpleFunc, smul_sum, smul_smul, mul_comm]
#align measure_theory.simple_func.set_to_simple_func_smul MeasureTheory.SimpleFunc.setToSimpleFunc_smul
section Order
variable {G' G'' : Type*} [NormedLatticeAddCommGroup G''] [NormedSpace ℝ G'']
[NormedLatticeAddCommGroup G'] [NormedSpace ℝ G']
theorem setToSimpleFunc_mono_left {m : MeasurableSpace α} (T T' : Set α → F →L[ℝ] G'')
(hTT' : ∀ s x, T s x ≤ T' s x) (f : α →ₛ F) : setToSimpleFunc T f ≤ setToSimpleFunc T' f := by
simp_rw [setToSimpleFunc]; exact sum_le_sum fun i _ => hTT' _ i
#align measure_theory.simple_func.set_to_simple_func_mono_left MeasureTheory.SimpleFunc.setToSimpleFunc_mono_left
theorem setToSimpleFunc_mono_left' (T T' : Set α → E →L[ℝ] G'')
(hTT' : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, T s x ≤ T' s x) (f : α →ₛ E)
(hf : Integrable f μ) : setToSimpleFunc T f ≤ setToSimpleFunc T' f := by
refine sum_le_sum fun i _ => ?_
by_cases h0 : i = 0
· simp [h0]
· exact hTT' _ (measurableSet_fiber _ _) (measure_preimage_lt_top_of_integrable _ hf h0) i
#align measure_theory.simple_func.set_to_simple_func_mono_left' MeasureTheory.SimpleFunc.setToSimpleFunc_mono_left'
theorem setToSimpleFunc_nonneg {m : MeasurableSpace α} (T : Set α → G' →L[ℝ] G'')
(hT_nonneg : ∀ s x, 0 ≤ x → 0 ≤ T s x) (f : α →ₛ G') (hf : 0 ≤ f) :
0 ≤ setToSimpleFunc T f := by
refine sum_nonneg fun i hi => hT_nonneg _ i ?_
rw [mem_range] at hi
obtain ⟨y, hy⟩ := Set.mem_range.mp hi
rw [← hy]
refine le_trans ?_ (hf y)
simp
#align measure_theory.simple_func.set_to_simple_func_nonneg MeasureTheory.SimpleFunc.setToSimpleFunc_nonneg
theorem setToSimpleFunc_nonneg' (T : Set α → G' →L[ℝ] G'')
(hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) (f : α →ₛ G') (hf : 0 ≤ f)
(hfi : Integrable f μ) : 0 ≤ setToSimpleFunc T f := by
refine sum_nonneg fun i hi => ?_
by_cases h0 : i = 0
· simp [h0]
refine
hT_nonneg _ (measurableSet_fiber _ _) (measure_preimage_lt_top_of_integrable _ hfi h0) i ?_
rw [mem_range] at hi
obtain ⟨y, hy⟩ := Set.mem_range.mp hi
rw [← hy]
convert hf y
#align measure_theory.simple_func.set_to_simple_func_nonneg' MeasureTheory.SimpleFunc.setToSimpleFunc_nonneg'
theorem setToSimpleFunc_mono {T : Set α → G' →L[ℝ] G''} (h_add : FinMeasAdditive μ T)
(hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f g : α →ₛ G'}
(hfi : Integrable f μ) (hgi : Integrable g μ) (hfg : f ≤ g) :
setToSimpleFunc T f ≤ setToSimpleFunc T g := by
rw [← sub_nonneg, ← setToSimpleFunc_sub T h_add hgi hfi]
refine setToSimpleFunc_nonneg' T hT_nonneg _ ?_ (hgi.sub hfi)
intro x
simp only [coe_sub, sub_nonneg, coe_zero, Pi.zero_apply, Pi.sub_apply]
exact hfg x
#align measure_theory.simple_func.set_to_simple_func_mono MeasureTheory.SimpleFunc.setToSimpleFunc_mono
end Order
theorem norm_setToSimpleFunc_le_sum_opNorm {m : MeasurableSpace α} (T : Set α → F' →L[ℝ] F)
(f : α →ₛ F') : ‖f.setToSimpleFunc T‖ ≤ ∑ x ∈ f.range, ‖T (f ⁻¹' {x})‖ * ‖x‖ :=
calc
‖∑ x ∈ f.range, T (f ⁻¹' {x}) x‖ ≤ ∑ x ∈ f.range, ‖T (f ⁻¹' {x}) x‖ := norm_sum_le _ _
_ ≤ ∑ x ∈ f.range, ‖T (f ⁻¹' {x})‖ * ‖x‖ := by
refine Finset.sum_le_sum fun b _ => ?_; simp_rw [ContinuousLinearMap.le_opNorm]
#align measure_theory.simple_func.norm_set_to_simple_func_le_sum_op_norm MeasureTheory.SimpleFunc.norm_setToSimpleFunc_le_sum_opNorm
@[deprecated (since := "2024-02-02")]
alias norm_setToSimpleFunc_le_sum_op_norm := norm_setToSimpleFunc_le_sum_opNorm
theorem norm_setToSimpleFunc_le_sum_mul_norm (T : Set α → F →L[ℝ] F') {C : ℝ}
(hT_norm : ∀ s, MeasurableSet s → ‖T s‖ ≤ C * (μ s).toReal) (f : α →ₛ F) :
‖f.setToSimpleFunc T‖ ≤ C * ∑ x ∈ f.range, (μ (f ⁻¹' {x})).toReal * ‖x‖ :=
calc
‖f.setToSimpleFunc T‖ ≤ ∑ x ∈ f.range, ‖T (f ⁻¹' {x})‖ * ‖x‖ :=
norm_setToSimpleFunc_le_sum_opNorm T f
_ ≤ ∑ x ∈ f.range, C * (μ (f ⁻¹' {x})).toReal * ‖x‖ := by
gcongr
exact hT_norm _ <| SimpleFunc.measurableSet_fiber _ _
_ ≤ C * ∑ x ∈ f.range, (μ (f ⁻¹' {x})).toReal * ‖x‖ := by simp_rw [mul_sum, ← mul_assoc]; rfl
#align measure_theory.simple_func.norm_set_to_simple_func_le_sum_mul_norm MeasureTheory.SimpleFunc.norm_setToSimpleFunc_le_sum_mul_norm
theorem norm_setToSimpleFunc_le_sum_mul_norm_of_integrable (T : Set α → E →L[ℝ] F') {C : ℝ}
(hT_norm : ∀ s, MeasurableSet s → μ s < ∞ → ‖T s‖ ≤ C * (μ s).toReal) (f : α →ₛ E)
(hf : Integrable f μ) :
‖f.setToSimpleFunc T‖ ≤ C * ∑ x ∈ f.range, (μ (f ⁻¹' {x})).toReal * ‖x‖ :=
calc
‖f.setToSimpleFunc T‖ ≤ ∑ x ∈ f.range, ‖T (f ⁻¹' {x})‖ * ‖x‖ :=
norm_setToSimpleFunc_le_sum_opNorm T f
_ ≤ ∑ x ∈ f.range, C * (μ (f ⁻¹' {x})).toReal * ‖x‖ := by
refine Finset.sum_le_sum fun b hb => ?_
obtain rfl | hb := eq_or_ne b 0
· simp
gcongr
exact hT_norm _ (SimpleFunc.measurableSet_fiber _ _) <|
SimpleFunc.measure_preimage_lt_top_of_integrable _ hf hb
_ ≤ C * ∑ x ∈ f.range, (μ (f ⁻¹' {x})).toReal * ‖x‖ := by simp_rw [mul_sum, ← mul_assoc]; rfl
#align measure_theory.simple_func.norm_set_to_simple_func_le_sum_mul_norm_of_integrable MeasureTheory.SimpleFunc.norm_setToSimpleFunc_le_sum_mul_norm_of_integrable
theorem setToSimpleFunc_indicator (T : Set α → F →L[ℝ] F') (hT_empty : T ∅ = 0)
{m : MeasurableSpace α} {s : Set α} (hs : MeasurableSet s) (x : F) :
SimpleFunc.setToSimpleFunc T
(SimpleFunc.piecewise s hs (SimpleFunc.const α x) (SimpleFunc.const α 0)) =
T s x := by
obtain rfl | hs_empty := s.eq_empty_or_nonempty
· simp only [hT_empty, ContinuousLinearMap.zero_apply, piecewise_empty, const_zero,
setToSimpleFunc_zero_apply]
simp_rw [setToSimpleFunc]
obtain rfl | hs_univ := eq_or_ne s univ
· haveI hα := hs_empty.to_type
simp [← Function.const_def]
rw [range_indicator hs hs_empty hs_univ]
by_cases hx0 : x = 0
· simp_rw [hx0]; simp
rw [sum_insert]
swap; · rw [Finset.mem_singleton]; exact hx0
rw [sum_singleton, (T _).map_zero, add_zero]
congr
simp only [coe_piecewise, piecewise_eq_indicator, coe_const, Function.const_zero,
piecewise_eq_indicator]
rw [indicator_preimage, ← Function.const_def, preimage_const_of_mem]
swap; · exact Set.mem_singleton x
rw [← Function.const_zero, ← Function.const_def, preimage_const_of_not_mem]
swap; · rw [Set.mem_singleton_iff]; exact Ne.symm hx0
simp
#align measure_theory.simple_func.set_to_simple_func_indicator MeasureTheory.SimpleFunc.setToSimpleFunc_indicator
theorem setToSimpleFunc_const' [Nonempty α] (T : Set α → F →L[ℝ] F') (x : F)
{m : MeasurableSpace α} : SimpleFunc.setToSimpleFunc T (SimpleFunc.const α x) = T univ x := by
simp only [setToSimpleFunc, range_const, Set.mem_singleton, preimage_const_of_mem,
sum_singleton, ← Function.const_def, coe_const]
#align measure_theory.simple_func.set_to_simple_func_const' MeasureTheory.SimpleFunc.setToSimpleFunc_const'
theorem setToSimpleFunc_const (T : Set α → F →L[ℝ] F') (hT_empty : T ∅ = 0) (x : F)
{m : MeasurableSpace α} : SimpleFunc.setToSimpleFunc T (SimpleFunc.const α x) = T univ x := by
cases isEmpty_or_nonempty α
· have h_univ_empty : (univ : Set α) = ∅ := Subsingleton.elim _ _
rw [h_univ_empty, hT_empty]
simp only [setToSimpleFunc, ContinuousLinearMap.zero_apply, sum_empty,
range_eq_empty_of_isEmpty]
· exact setToSimpleFunc_const' T x
#align measure_theory.simple_func.set_to_simple_func_const MeasureTheory.SimpleFunc.setToSimpleFunc_const
end SimpleFunc
namespace L1
set_option linter.uppercaseLean3 false
open AEEqFun Lp.simpleFunc Lp
namespace SimpleFunc
theorem norm_eq_sum_mul (f : α →₁ₛ[μ] G) :
‖f‖ = ∑ x ∈ (toSimpleFunc f).range, (μ (toSimpleFunc f ⁻¹' {x})).toReal * ‖x‖ := by
rw [norm_toSimpleFunc, snorm_one_eq_lintegral_nnnorm]
have h_eq := SimpleFunc.map_apply (fun x => (‖x‖₊ : ℝ≥0∞)) (toSimpleFunc f)
simp_rw [← h_eq]
rw [SimpleFunc.lintegral_eq_lintegral, SimpleFunc.map_lintegral, ENNReal.toReal_sum]
· congr
ext1 x
rw [ENNReal.toReal_mul, mul_comm, ← ofReal_norm_eq_coe_nnnorm,
ENNReal.toReal_ofReal (norm_nonneg _)]
· intro x _
by_cases hx0 : x = 0
· rw [hx0]; simp
· exact
ENNReal.mul_ne_top ENNReal.coe_ne_top
(SimpleFunc.measure_preimage_lt_top_of_integrable _ (SimpleFunc.integrable f) hx0).ne
#align measure_theory.L1.simple_func.norm_eq_sum_mul MeasureTheory.L1.SimpleFunc.norm_eq_sum_mul
section SetToL1S
variable [NormedField 𝕜] [NormedSpace 𝕜 E]
attribute [local instance] Lp.simpleFunc.module
attribute [local instance] Lp.simpleFunc.normedSpace
/-- Extend `Set α → (E →L[ℝ] F')` to `(α →₁ₛ[μ] E) → F'`. -/
def setToL1S (T : Set α → E →L[ℝ] F) (f : α →₁ₛ[μ] E) : F :=
(toSimpleFunc f).setToSimpleFunc T
#align measure_theory.L1.simple_func.set_to_L1s MeasureTheory.L1.SimpleFunc.setToL1S
theorem setToL1S_eq_setToSimpleFunc (T : Set α → E →L[ℝ] F) (f : α →₁ₛ[μ] E) :
setToL1S T f = (toSimpleFunc f).setToSimpleFunc T :=
rfl
#align measure_theory.L1.simple_func.set_to_L1s_eq_set_to_simple_func MeasureTheory.L1.SimpleFunc.setToL1S_eq_setToSimpleFunc
@[simp]
theorem setToL1S_zero_left (f : α →₁ₛ[μ] E) : setToL1S (0 : Set α → E →L[ℝ] F) f = 0 :=
SimpleFunc.setToSimpleFunc_zero _
#align measure_theory.L1.simple_func.set_to_L1s_zero_left MeasureTheory.L1.SimpleFunc.setToL1S_zero_left
theorem setToL1S_zero_left' {T : Set α → E →L[ℝ] F}
(h_zero : ∀ s, MeasurableSet s → μ s < ∞ → T s = 0) (f : α →₁ₛ[μ] E) : setToL1S T f = 0 :=
SimpleFunc.setToSimpleFunc_zero' h_zero _ (SimpleFunc.integrable f)
#align measure_theory.L1.simple_func.set_to_L1s_zero_left' MeasureTheory.L1.SimpleFunc.setToL1S_zero_left'
theorem setToL1S_congr (T : Set α → E →L[ℝ] F) (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0)
(h_add : FinMeasAdditive μ T) {f g : α →₁ₛ[μ] E} (h : toSimpleFunc f =ᵐ[μ] toSimpleFunc g) :
setToL1S T f = setToL1S T g :=
SimpleFunc.setToSimpleFunc_congr T h_zero h_add (SimpleFunc.integrable f) h
#align measure_theory.L1.simple_func.set_to_L1s_congr MeasureTheory.L1.SimpleFunc.setToL1S_congr
theorem setToL1S_congr_left (T T' : Set α → E →L[ℝ] F)
(h : ∀ s, MeasurableSet s → μ s < ∞ → T s = T' s) (f : α →₁ₛ[μ] E) :
setToL1S T f = setToL1S T' f :=
SimpleFunc.setToSimpleFunc_congr_left T T' h (simpleFunc.toSimpleFunc f) (SimpleFunc.integrable f)
#align measure_theory.L1.simple_func.set_to_L1s_congr_left MeasureTheory.L1.SimpleFunc.setToL1S_congr_left
/-- `setToL1S` does not change if we replace the measure `μ` by `μ'` with `μ ≪ μ'`. The statement
uses two functions `f` and `f'` because they have to belong to different types, but morally these
are the same function (we have `f =ᵐ[μ] f'`). -/
theorem setToL1S_congr_measure {μ' : Measure α} (T : Set α → E →L[ℝ] F)
(h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0) (h_add : FinMeasAdditive μ T) (hμ : μ ≪ μ')
(f : α →₁ₛ[μ] E) (f' : α →₁ₛ[μ'] E) (h : (f : α → E) =ᵐ[μ] f') :
setToL1S T f = setToL1S T f' := by
refine SimpleFunc.setToSimpleFunc_congr T h_zero h_add (SimpleFunc.integrable f) ?_
refine (toSimpleFunc_eq_toFun f).trans ?_
suffices (f' : α → E) =ᵐ[μ] simpleFunc.toSimpleFunc f' from h.trans this
have goal' : (f' : α → E) =ᵐ[μ'] simpleFunc.toSimpleFunc f' := (toSimpleFunc_eq_toFun f').symm
exact hμ.ae_eq goal'
#align measure_theory.L1.simple_func.set_to_L1s_congr_measure MeasureTheory.L1.SimpleFunc.setToL1S_congr_measure
theorem setToL1S_add_left (T T' : Set α → E →L[ℝ] F) (f : α →₁ₛ[μ] E) :
setToL1S (T + T') f = setToL1S T f + setToL1S T' f :=
SimpleFunc.setToSimpleFunc_add_left T T'
#align measure_theory.L1.simple_func.set_to_L1s_add_left MeasureTheory.L1.SimpleFunc.setToL1S_add_left
theorem setToL1S_add_left' (T T' T'' : Set α → E →L[ℝ] F)
(h_add : ∀ s, MeasurableSet s → μ s < ∞ → T'' s = T s + T' s) (f : α →₁ₛ[μ] E) :
setToL1S T'' f = setToL1S T f + setToL1S T' f :=
SimpleFunc.setToSimpleFunc_add_left' T T' T'' h_add (SimpleFunc.integrable f)
#align measure_theory.L1.simple_func.set_to_L1s_add_left' MeasureTheory.L1.SimpleFunc.setToL1S_add_left'
theorem setToL1S_smul_left (T : Set α → E →L[ℝ] F) (c : ℝ) (f : α →₁ₛ[μ] E) :
setToL1S (fun s => c • T s) f = c • setToL1S T f :=
SimpleFunc.setToSimpleFunc_smul_left T c _
#align measure_theory.L1.simple_func.set_to_L1s_smul_left MeasureTheory.L1.SimpleFunc.setToL1S_smul_left
theorem setToL1S_smul_left' (T T' : Set α → E →L[ℝ] F) (c : ℝ)
(h_smul : ∀ s, MeasurableSet s → μ s < ∞ → T' s = c • T s) (f : α →₁ₛ[μ] E) :
setToL1S T' f = c • setToL1S T f :=
SimpleFunc.setToSimpleFunc_smul_left' T T' c h_smul (SimpleFunc.integrable f)
#align measure_theory.L1.simple_func.set_to_L1s_smul_left' MeasureTheory.L1.SimpleFunc.setToL1S_smul_left'
theorem setToL1S_add (T : Set α → E →L[ℝ] F) (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0)
(h_add : FinMeasAdditive μ T) (f g : α →₁ₛ[μ] E) :
setToL1S T (f + g) = setToL1S T f + setToL1S T g := by
simp_rw [setToL1S]
rw [← SimpleFunc.setToSimpleFunc_add T h_add (SimpleFunc.integrable f)
(SimpleFunc.integrable g)]
exact
SimpleFunc.setToSimpleFunc_congr T h_zero h_add (SimpleFunc.integrable _)
(add_toSimpleFunc f g)
#align measure_theory.L1.simple_func.set_to_L1s_add MeasureTheory.L1.SimpleFunc.setToL1S_add
theorem setToL1S_neg {T : Set α → E →L[ℝ] F} (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0)
(h_add : FinMeasAdditive μ T) (f : α →₁ₛ[μ] E) : setToL1S T (-f) = -setToL1S T f := by
simp_rw [setToL1S]
have : simpleFunc.toSimpleFunc (-f) =ᵐ[μ] ⇑(-simpleFunc.toSimpleFunc f) :=
neg_toSimpleFunc f
rw [SimpleFunc.setToSimpleFunc_congr T h_zero h_add (SimpleFunc.integrable _) this]
exact SimpleFunc.setToSimpleFunc_neg T h_add (SimpleFunc.integrable f)
#align measure_theory.L1.simple_func.set_to_L1s_neg MeasureTheory.L1.SimpleFunc.setToL1S_neg
theorem setToL1S_sub {T : Set α → E →L[ℝ] F} (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0)
(h_add : FinMeasAdditive μ T) (f g : α →₁ₛ[μ] E) :
setToL1S T (f - g) = setToL1S T f - setToL1S T g := by
rw [sub_eq_add_neg, setToL1S_add T h_zero h_add, setToL1S_neg h_zero h_add, sub_eq_add_neg]
#align measure_theory.L1.simple_func.set_to_L1s_sub MeasureTheory.L1.SimpleFunc.setToL1S_sub
theorem setToL1S_smul_real (T : Set α → E →L[ℝ] F)
(h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0) (h_add : FinMeasAdditive μ T) (c : ℝ)
(f : α →₁ₛ[μ] E) : setToL1S T (c • f) = c • setToL1S T f := by
simp_rw [setToL1S]
rw [← SimpleFunc.setToSimpleFunc_smul_real T h_add c (SimpleFunc.integrable f)]
refine SimpleFunc.setToSimpleFunc_congr T h_zero h_add (SimpleFunc.integrable _) ?_
exact smul_toSimpleFunc c f
#align measure_theory.L1.simple_func.set_to_L1s_smul_real MeasureTheory.L1.SimpleFunc.setToL1S_smul_real
theorem setToL1S_smul {E} [NormedAddCommGroup E] [NormedSpace ℝ E] [NormedSpace 𝕜 E]
[NormedSpace 𝕜 F] (T : Set α → E →L[ℝ] F) (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0)
(h_add : FinMeasAdditive μ T) (h_smul : ∀ c : 𝕜, ∀ s x, T s (c • x) = c • T s x) (c : 𝕜)
(f : α →₁ₛ[μ] E) : setToL1S T (c • f) = c • setToL1S T f := by
simp_rw [setToL1S]
rw [← SimpleFunc.setToSimpleFunc_smul T h_add h_smul c (SimpleFunc.integrable f)]
refine SimpleFunc.setToSimpleFunc_congr T h_zero h_add (SimpleFunc.integrable _) ?_
exact smul_toSimpleFunc c f
#align measure_theory.L1.simple_func.set_to_L1s_smul MeasureTheory.L1.SimpleFunc.setToL1S_smul
theorem norm_setToL1S_le (T : Set α → E →L[ℝ] F) {C : ℝ}
(hT_norm : ∀ s, MeasurableSet s → μ s < ∞ → ‖T s‖ ≤ C * (μ s).toReal) (f : α →₁ₛ[μ] E) :
‖setToL1S T f‖ ≤ C * ‖f‖ := by
rw [setToL1S, norm_eq_sum_mul f]
exact
SimpleFunc.norm_setToSimpleFunc_le_sum_mul_norm_of_integrable T hT_norm _
(SimpleFunc.integrable f)
#align measure_theory.L1.simple_func.norm_set_to_L1s_le MeasureTheory.L1.SimpleFunc.norm_setToL1S_le
theorem setToL1S_indicatorConst {T : Set α → E →L[ℝ] F} {s : Set α}
(h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0) (h_add : FinMeasAdditive μ T)
(hs : MeasurableSet s) (hμs : μ s < ∞) (x : E) :
setToL1S T (simpleFunc.indicatorConst 1 hs hμs.ne x) = T s x := by
have h_empty : T ∅ = 0 := h_zero _ MeasurableSet.empty measure_empty
rw [setToL1S_eq_setToSimpleFunc]
refine Eq.trans ?_ (SimpleFunc.setToSimpleFunc_indicator T h_empty hs x)
refine SimpleFunc.setToSimpleFunc_congr T h_zero h_add (SimpleFunc.integrable _) ?_
exact toSimpleFunc_indicatorConst hs hμs.ne x
#align measure_theory.L1.simple_func.set_to_L1s_indicator_const MeasureTheory.L1.SimpleFunc.setToL1S_indicatorConst
theorem setToL1S_const [IsFiniteMeasure μ] {T : Set α → E →L[ℝ] F}
(h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0) (h_add : FinMeasAdditive μ T) (x : E) :
setToL1S T (simpleFunc.indicatorConst 1 MeasurableSet.univ (measure_ne_top μ _) x) = T univ x :=
setToL1S_indicatorConst h_zero h_add MeasurableSet.univ (measure_lt_top _ _) x
#align measure_theory.L1.simple_func.set_to_L1s_const MeasureTheory.L1.SimpleFunc.setToL1S_const
section Order
variable {G'' G' : Type*} [NormedLatticeAddCommGroup G'] [NormedSpace ℝ G']
[NormedLatticeAddCommGroup G''] [NormedSpace ℝ G''] {T : Set α → G'' →L[ℝ] G'}
theorem setToL1S_mono_left {T T' : Set α → E →L[ℝ] G''} (hTT' : ∀ s x, T s x ≤ T' s x)
(f : α →₁ₛ[μ] E) : setToL1S T f ≤ setToL1S T' f :=
SimpleFunc.setToSimpleFunc_mono_left T T' hTT' _
#align measure_theory.L1.simple_func.set_to_L1s_mono_left MeasureTheory.L1.SimpleFunc.setToL1S_mono_left
theorem setToL1S_mono_left' {T T' : Set α → E →L[ℝ] G''}
(hTT' : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, T s x ≤ T' s x) (f : α →₁ₛ[μ] E) :
setToL1S T f ≤ setToL1S T' f :=
SimpleFunc.setToSimpleFunc_mono_left' T T' hTT' _ (SimpleFunc.integrable f)
#align measure_theory.L1.simple_func.set_to_L1s_mono_left' MeasureTheory.L1.SimpleFunc.setToL1S_mono_left'
theorem setToL1S_nonneg (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0)
(h_add : FinMeasAdditive μ T)
(hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f : α →₁ₛ[μ] G''}
(hf : 0 ≤ f) : 0 ≤ setToL1S T f := by
simp_rw [setToL1S]
obtain ⟨f', hf', hff'⟩ : ∃ f' : α →ₛ G'', 0 ≤ f' ∧ simpleFunc.toSimpleFunc f =ᵐ[μ] f' := by
obtain ⟨f'', hf'', hff''⟩ := exists_simpleFunc_nonneg_ae_eq hf
exact ⟨f'', hf'', (Lp.simpleFunc.toSimpleFunc_eq_toFun f).trans hff''⟩
rw [SimpleFunc.setToSimpleFunc_congr _ h_zero h_add (SimpleFunc.integrable _) hff']
exact
SimpleFunc.setToSimpleFunc_nonneg' T hT_nonneg _ hf' ((SimpleFunc.integrable f).congr hff')
#align measure_theory.L1.simple_func.set_to_L1s_nonneg MeasureTheory.L1.SimpleFunc.setToL1S_nonneg
theorem setToL1S_mono (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0)
(h_add : FinMeasAdditive μ T)
(hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f g : α →₁ₛ[μ] G''}
(hfg : f ≤ g) : setToL1S T f ≤ setToL1S T g := by
rw [← sub_nonneg] at hfg ⊢
rw [← setToL1S_sub h_zero h_add]
exact setToL1S_nonneg h_zero h_add hT_nonneg hfg
#align measure_theory.L1.simple_func.set_to_L1s_mono MeasureTheory.L1.SimpleFunc.setToL1S_mono
end Order
variable [NormedSpace 𝕜 F]
variable (α E μ 𝕜)
/-- Extend `Set α → E →L[ℝ] F` to `(α →₁ₛ[μ] E) →L[𝕜] F`. -/
def setToL1SCLM' {T : Set α → E →L[ℝ] F} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C)
(h_smul : ∀ c : 𝕜, ∀ s x, T s (c • x) = c • T s x) : (α →₁ₛ[μ] E) →L[𝕜] F :=
LinearMap.mkContinuous
⟨⟨setToL1S T, setToL1S_add T (fun _ => hT.eq_zero_of_measure_zero) hT.1⟩,
setToL1S_smul T (fun _ => hT.eq_zero_of_measure_zero) hT.1 h_smul⟩
C fun f => norm_setToL1S_le T hT.2 f
#align measure_theory.L1.simple_func.set_to_L1s_clm' MeasureTheory.L1.SimpleFunc.setToL1SCLM'
/-- Extend `Set α → E →L[ℝ] F` to `(α →₁ₛ[μ] E) →L[ℝ] F`. -/
def setToL1SCLM {T : Set α → E →L[ℝ] F} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C) :
(α →₁ₛ[μ] E) →L[ℝ] F :=
LinearMap.mkContinuous
⟨⟨setToL1S T, setToL1S_add T (fun _ => hT.eq_zero_of_measure_zero) hT.1⟩,
setToL1S_smul_real T (fun _ => hT.eq_zero_of_measure_zero) hT.1⟩
C fun f => norm_setToL1S_le T hT.2 f
#align measure_theory.L1.simple_func.set_to_L1s_clm MeasureTheory.L1.SimpleFunc.setToL1SCLM
variable {α E μ 𝕜}
variable {T T' T'' : Set α → E →L[ℝ] F} {C C' C'' : ℝ}
@[simp]
theorem setToL1SCLM_zero_left (hT : DominatedFinMeasAdditive μ (0 : Set α → E →L[ℝ] F) C)
(f : α →₁ₛ[μ] E) : setToL1SCLM α E μ hT f = 0 :=
setToL1S_zero_left _
#align measure_theory.L1.simple_func.set_to_L1s_clm_zero_left MeasureTheory.L1.SimpleFunc.setToL1SCLM_zero_left
theorem setToL1SCLM_zero_left' (hT : DominatedFinMeasAdditive μ T C)
(h_zero : ∀ s, MeasurableSet s → μ s < ∞ → T s = 0) (f : α →₁ₛ[μ] E) :
setToL1SCLM α E μ hT f = 0 :=
setToL1S_zero_left' h_zero f
#align measure_theory.L1.simple_func.set_to_L1s_clm_zero_left' MeasureTheory.L1.SimpleFunc.setToL1SCLM_zero_left'
theorem setToL1SCLM_congr_left (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (h : T = T') (f : α →₁ₛ[μ] E) :
setToL1SCLM α E μ hT f = setToL1SCLM α E μ hT' f :=
setToL1S_congr_left T T' (fun _ _ _ => by rw [h]) f
#align measure_theory.L1.simple_func.set_to_L1s_clm_congr_left MeasureTheory.L1.SimpleFunc.setToL1SCLM_congr_left
theorem setToL1SCLM_congr_left' (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (h : ∀ s, MeasurableSet s → μ s < ∞ → T s = T' s)
(f : α →₁ₛ[μ] E) : setToL1SCLM α E μ hT f = setToL1SCLM α E μ hT' f :=
setToL1S_congr_left T T' h f
#align measure_theory.L1.simple_func.set_to_L1s_clm_congr_left' MeasureTheory.L1.SimpleFunc.setToL1SCLM_congr_left'
theorem setToL1SCLM_congr_measure {μ' : Measure α} (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ' T C') (hμ : μ ≪ μ') (f : α →₁ₛ[μ] E) (f' : α →₁ₛ[μ'] E)
(h : (f : α → E) =ᵐ[μ] f') : setToL1SCLM α E μ hT f = setToL1SCLM α E μ' hT' f' :=
setToL1S_congr_measure T (fun _ => hT.eq_zero_of_measure_zero) hT.1 hμ _ _ h
#align measure_theory.L1.simple_func.set_to_L1s_clm_congr_measure MeasureTheory.L1.SimpleFunc.setToL1SCLM_congr_measure
theorem setToL1SCLM_add_left (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (f : α →₁ₛ[μ] E) :
setToL1SCLM α E μ (hT.add hT') f = setToL1SCLM α E μ hT f + setToL1SCLM α E μ hT' f :=
setToL1S_add_left T T' f
#align measure_theory.L1.simple_func.set_to_L1s_clm_add_left MeasureTheory.L1.SimpleFunc.setToL1SCLM_add_left
theorem setToL1SCLM_add_left' (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (hT'' : DominatedFinMeasAdditive μ T'' C'')
(h_add : ∀ s, MeasurableSet s → μ s < ∞ → T'' s = T s + T' s) (f : α →₁ₛ[μ] E) :
setToL1SCLM α E μ hT'' f = setToL1SCLM α E μ hT f + setToL1SCLM α E μ hT' f :=
setToL1S_add_left' T T' T'' h_add f
#align measure_theory.L1.simple_func.set_to_L1s_clm_add_left' MeasureTheory.L1.SimpleFunc.setToL1SCLM_add_left'
theorem setToL1SCLM_smul_left (c : ℝ) (hT : DominatedFinMeasAdditive μ T C) (f : α →₁ₛ[μ] E) :
setToL1SCLM α E μ (hT.smul c) f = c • setToL1SCLM α E μ hT f :=
setToL1S_smul_left T c f
#align measure_theory.L1.simple_func.set_to_L1s_clm_smul_left MeasureTheory.L1.SimpleFunc.setToL1SCLM_smul_left
theorem setToL1SCLM_smul_left' (c : ℝ) (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C')
(h_smul : ∀ s, MeasurableSet s → μ s < ∞ → T' s = c • T s) (f : α →₁ₛ[μ] E) :
setToL1SCLM α E μ hT' f = c • setToL1SCLM α E μ hT f :=
setToL1S_smul_left' T T' c h_smul f
#align measure_theory.L1.simple_func.set_to_L1s_clm_smul_left' MeasureTheory.L1.SimpleFunc.setToL1SCLM_smul_left'
theorem norm_setToL1SCLM_le {T : Set α → E →L[ℝ] F} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C)
(hC : 0 ≤ C) : ‖setToL1SCLM α E μ hT‖ ≤ C :=
LinearMap.mkContinuous_norm_le _ hC _
#align measure_theory.L1.simple_func.norm_set_to_L1s_clm_le MeasureTheory.L1.SimpleFunc.norm_setToL1SCLM_le
theorem norm_setToL1SCLM_le' {T : Set α → E →L[ℝ] F} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C) :
‖setToL1SCLM α E μ hT‖ ≤ max C 0 :=
LinearMap.mkContinuous_norm_le' _ _
#align measure_theory.L1.simple_func.norm_set_to_L1s_clm_le' MeasureTheory.L1.SimpleFunc.norm_setToL1SCLM_le'
theorem setToL1SCLM_const [IsFiniteMeasure μ] {T : Set α → E →L[ℝ] F} {C : ℝ}
(hT : DominatedFinMeasAdditive μ T C) (x : E) :
setToL1SCLM α E μ hT (simpleFunc.indicatorConst 1 MeasurableSet.univ (measure_ne_top μ _) x) =
T univ x :=
setToL1S_const (fun _ => hT.eq_zero_of_measure_zero) hT.1 x
#align measure_theory.L1.simple_func.set_to_L1s_clm_const MeasureTheory.L1.SimpleFunc.setToL1SCLM_const
section Order
variable {G' G'' : Type*} [NormedLatticeAddCommGroup G''] [NormedSpace ℝ G'']
[NormedLatticeAddCommGroup G'] [NormedSpace ℝ G']
theorem setToL1SCLM_mono_left {T T' : Set α → E →L[ℝ] G''} {C C' : ℝ}
(hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C')
(hTT' : ∀ s x, T s x ≤ T' s x) (f : α →₁ₛ[μ] E) :
setToL1SCLM α E μ hT f ≤ setToL1SCLM α E μ hT' f :=
SimpleFunc.setToSimpleFunc_mono_left T T' hTT' _
#align measure_theory.L1.simple_func.set_to_L1s_clm_mono_left MeasureTheory.L1.SimpleFunc.setToL1SCLM_mono_left
theorem setToL1SCLM_mono_left' {T T' : Set α → E →L[ℝ] G''} {C C' : ℝ}
(hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C')
(hTT' : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, T s x ≤ T' s x) (f : α →₁ₛ[μ] E) :
setToL1SCLM α E μ hT f ≤ setToL1SCLM α E μ hT' f :=
SimpleFunc.setToSimpleFunc_mono_left' T T' hTT' _ (SimpleFunc.integrable f)
#align measure_theory.L1.simple_func.set_to_L1s_clm_mono_left' MeasureTheory.L1.SimpleFunc.setToL1SCLM_mono_left'
theorem setToL1SCLM_nonneg {T : Set α → G' →L[ℝ] G''} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C)
(hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f : α →₁ₛ[μ] G'}
(hf : 0 ≤ f) : 0 ≤ setToL1SCLM α G' μ hT f :=
setToL1S_nonneg (fun _ => hT.eq_zero_of_measure_zero) hT.1 hT_nonneg hf
#align measure_theory.L1.simple_func.set_to_L1s_clm_nonneg MeasureTheory.L1.SimpleFunc.setToL1SCLM_nonneg
theorem setToL1SCLM_mono {T : Set α → G' →L[ℝ] G''} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C)
(hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f g : α →₁ₛ[μ] G'}
(hfg : f ≤ g) : setToL1SCLM α G' μ hT f ≤ setToL1SCLM α G' μ hT g :=
setToL1S_mono (fun _ => hT.eq_zero_of_measure_zero) hT.1 hT_nonneg hfg
#align measure_theory.L1.simple_func.set_to_L1s_clm_mono MeasureTheory.L1.SimpleFunc.setToL1SCLM_mono
end Order
end SetToL1S
end SimpleFunc
open SimpleFunc
section SetToL1
attribute [local instance] Lp.simpleFunc.module
attribute [local instance] Lp.simpleFunc.normedSpace
variable (𝕜) [NontriviallyNormedField 𝕜] [NormedSpace 𝕜 E] [NormedSpace 𝕜 F] [CompleteSpace F]
{T T' T'' : Set α → E →L[ℝ] F} {C C' C'' : ℝ}
/-- Extend `set α → (E →L[ℝ] F)` to `(α →₁[μ] E) →L[𝕜] F`. -/
def setToL1' (hT : DominatedFinMeasAdditive μ T C)
(h_smul : ∀ c : 𝕜, ∀ s x, T s (c • x) = c • T s x) : (α →₁[μ] E) →L[𝕜] F :=
(setToL1SCLM' α E 𝕜 μ hT h_smul).extend (coeToLp α E 𝕜) (simpleFunc.denseRange one_ne_top)
simpleFunc.uniformInducing
#align measure_theory.L1.set_to_L1' MeasureTheory.L1.setToL1'
variable {𝕜}
/-- Extend `Set α → E →L[ℝ] F` to `(α →₁[μ] E) →L[ℝ] F`. -/
def setToL1 (hT : DominatedFinMeasAdditive μ T C) : (α →₁[μ] E) →L[ℝ] F :=
(setToL1SCLM α E μ hT).extend (coeToLp α E ℝ) (simpleFunc.denseRange one_ne_top)
simpleFunc.uniformInducing
#align measure_theory.L1.set_to_L1 MeasureTheory.L1.setToL1
theorem setToL1_eq_setToL1SCLM (hT : DominatedFinMeasAdditive μ T C) (f : α →₁ₛ[μ] E) :
setToL1 hT f = setToL1SCLM α E μ hT f :=
uniformly_extend_of_ind simpleFunc.uniformInducing (simpleFunc.denseRange one_ne_top)
(setToL1SCLM α E μ hT).uniformContinuous _
#align measure_theory.L1.set_to_L1_eq_set_to_L1s_clm MeasureTheory.L1.setToL1_eq_setToL1SCLM
theorem setToL1_eq_setToL1' (hT : DominatedFinMeasAdditive μ T C)
(h_smul : ∀ c : 𝕜, ∀ s x, T s (c • x) = c • T s x) (f : α →₁[μ] E) :
setToL1 hT f = setToL1' 𝕜 hT h_smul f :=
rfl
#align measure_theory.L1.set_to_L1_eq_set_to_L1' MeasureTheory.L1.setToL1_eq_setToL1'
@[simp]
theorem setToL1_zero_left (hT : DominatedFinMeasAdditive μ (0 : Set α → E →L[ℝ] F) C)
(f : α →₁[μ] E) : setToL1 hT f = 0 := by
suffices setToL1 hT = 0 by rw [this]; simp
refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ hT) _ _ _ _ ?_
ext1 f
rw [setToL1SCLM_zero_left hT f, ContinuousLinearMap.zero_comp, ContinuousLinearMap.zero_apply]
#align measure_theory.L1.set_to_L1_zero_left MeasureTheory.L1.setToL1_zero_left
theorem setToL1_zero_left' (hT : DominatedFinMeasAdditive μ T C)
(h_zero : ∀ s, MeasurableSet s → μ s < ∞ → T s = 0) (f : α →₁[μ] E) : setToL1 hT f = 0 := by
suffices setToL1 hT = 0 by rw [this]; simp
refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ hT) _ _ _ _ ?_
ext1 f
rw [setToL1SCLM_zero_left' hT h_zero f, ContinuousLinearMap.zero_comp,
ContinuousLinearMap.zero_apply]
#align measure_theory.L1.set_to_L1_zero_left' MeasureTheory.L1.setToL1_zero_left'
theorem setToL1_congr_left (T T' : Set α → E →L[ℝ] F) {C C' : ℝ}
(hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C') (h : T = T')
(f : α →₁[μ] E) : setToL1 hT f = setToL1 hT' f := by
suffices setToL1 hT = setToL1 hT' by rw [this]
refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ hT) _ _ _ _ ?_
ext1 f
suffices setToL1 hT' f = setToL1SCLM α E μ hT f by rw [← this]; rfl
rw [setToL1_eq_setToL1SCLM]
exact setToL1SCLM_congr_left hT' hT h.symm f
#align measure_theory.L1.set_to_L1_congr_left MeasureTheory.L1.setToL1_congr_left
theorem setToL1_congr_left' (T T' : Set α → E →L[ℝ] F) {C C' : ℝ}
(hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C')
(h : ∀ s, MeasurableSet s → μ s < ∞ → T s = T' s) (f : α →₁[μ] E) :
setToL1 hT f = setToL1 hT' f := by
suffices setToL1 hT = setToL1 hT' by rw [this]
refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ hT) _ _ _ _ ?_
ext1 f
suffices setToL1 hT' f = setToL1SCLM α E μ hT f by rw [← this]; rfl
rw [setToL1_eq_setToL1SCLM]
exact (setToL1SCLM_congr_left' hT hT' h f).symm
#align measure_theory.L1.set_to_L1_congr_left' MeasureTheory.L1.setToL1_congr_left'
theorem setToL1_add_left (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (f : α →₁[μ] E) :
setToL1 (hT.add hT') f = setToL1 hT f + setToL1 hT' f := by
suffices setToL1 (hT.add hT') = setToL1 hT + setToL1 hT' by
rw [this, ContinuousLinearMap.add_apply]
refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ (hT.add hT')) _ _ _ _ ?_
ext1 f
suffices setToL1 hT f + setToL1 hT' f = setToL1SCLM α E μ (hT.add hT') f by
rw [← this]; rfl
rw [setToL1_eq_setToL1SCLM, setToL1_eq_setToL1SCLM, setToL1SCLM_add_left hT hT']
#align measure_theory.L1.set_to_L1_add_left MeasureTheory.L1.setToL1_add_left
theorem setToL1_add_left' (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (hT'' : DominatedFinMeasAdditive μ T'' C'')
(h_add : ∀ s, MeasurableSet s → μ s < ∞ → T'' s = T s + T' s) (f : α →₁[μ] E) :
setToL1 hT'' f = setToL1 hT f + setToL1 hT' f := by
suffices setToL1 hT'' = setToL1 hT + setToL1 hT' by rw [this, ContinuousLinearMap.add_apply]
refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ hT'') _ _ _ _ ?_
ext1 f
suffices setToL1 hT f + setToL1 hT' f = setToL1SCLM α E μ hT'' f by rw [← this]; congr
rw [setToL1_eq_setToL1SCLM, setToL1_eq_setToL1SCLM,
setToL1SCLM_add_left' hT hT' hT'' h_add]
#align measure_theory.L1.set_to_L1_add_left' MeasureTheory.L1.setToL1_add_left'
theorem setToL1_smul_left (hT : DominatedFinMeasAdditive μ T C) (c : ℝ) (f : α →₁[μ] E) :
setToL1 (hT.smul c) f = c • setToL1 hT f := by
suffices setToL1 (hT.smul c) = c • setToL1 hT by rw [this, ContinuousLinearMap.smul_apply]
refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ (hT.smul c)) _ _ _ _ ?_
ext1 f
suffices c • setToL1 hT f = setToL1SCLM α E μ (hT.smul c) f by rw [← this]; congr
rw [setToL1_eq_setToL1SCLM, setToL1SCLM_smul_left c hT]
#align measure_theory.L1.set_to_L1_smul_left MeasureTheory.L1.setToL1_smul_left
theorem setToL1_smul_left' (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (c : ℝ)
(h_smul : ∀ s, MeasurableSet s → μ s < ∞ → T' s = c • T s) (f : α →₁[μ] E) :
setToL1 hT' f = c • setToL1 hT f := by
suffices setToL1 hT' = c • setToL1 hT by rw [this, ContinuousLinearMap.smul_apply]
refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ hT') _ _ _ _ ?_
ext1 f
suffices c • setToL1 hT f = setToL1SCLM α E μ hT' f by rw [← this]; congr
rw [setToL1_eq_setToL1SCLM, setToL1SCLM_smul_left' c hT hT' h_smul]
#align measure_theory.L1.set_to_L1_smul_left' MeasureTheory.L1.setToL1_smul_left'
theorem setToL1_smul (hT : DominatedFinMeasAdditive μ T C)
(h_smul : ∀ c : 𝕜, ∀ s x, T s (c • x) = c • T s x) (c : 𝕜) (f : α →₁[μ] E) :
setToL1 hT (c • f) = c • setToL1 hT f := by
rw [setToL1_eq_setToL1' hT h_smul, setToL1_eq_setToL1' hT h_smul]
exact ContinuousLinearMap.map_smul _ _ _
#align measure_theory.L1.set_to_L1_smul MeasureTheory.L1.setToL1_smul
theorem setToL1_simpleFunc_indicatorConst (hT : DominatedFinMeasAdditive μ T C) {s : Set α}
(hs : MeasurableSet s) (hμs : μ s < ∞) (x : E) :
setToL1 hT (simpleFunc.indicatorConst 1 hs hμs.ne x) = T s x := by
rw [setToL1_eq_setToL1SCLM]
exact setToL1S_indicatorConst (fun s => hT.eq_zero_of_measure_zero) hT.1 hs hμs x
#align measure_theory.L1.set_to_L1_simple_func_indicator_const MeasureTheory.L1.setToL1_simpleFunc_indicatorConst
theorem setToL1_indicatorConstLp (hT : DominatedFinMeasAdditive μ T C) {s : Set α}
(hs : MeasurableSet s) (hμs : μ s ≠ ∞) (x : E) :
setToL1 hT (indicatorConstLp 1 hs hμs x) = T s x := by
rw [← Lp.simpleFunc.coe_indicatorConst hs hμs x]
exact setToL1_simpleFunc_indicatorConst hT hs hμs.lt_top x
#align measure_theory.L1.set_to_L1_indicator_const_Lp MeasureTheory.L1.setToL1_indicatorConstLp
theorem setToL1_const [IsFiniteMeasure μ] (hT : DominatedFinMeasAdditive μ T C) (x : E) :
setToL1 hT (indicatorConstLp 1 MeasurableSet.univ (measure_ne_top _ _) x) = T univ x :=
setToL1_indicatorConstLp hT MeasurableSet.univ (measure_ne_top _ _) x
#align measure_theory.L1.set_to_L1_const MeasureTheory.L1.setToL1_const
section Order
variable {G' G'' : Type*} [NormedLatticeAddCommGroup G''] [NormedSpace ℝ G''] [CompleteSpace G'']
[NormedLatticeAddCommGroup G'] [NormedSpace ℝ G']
theorem setToL1_mono_left' {T T' : Set α → E →L[ℝ] G''} {C C' : ℝ}
(hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C')
(hTT' : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, T s x ≤ T' s x) (f : α →₁[μ] E) :
setToL1 hT f ≤ setToL1 hT' f := by
induction f using Lp.induction (hp_ne_top := one_ne_top) with
| @h_ind c s hs hμs =>
rw [setToL1_simpleFunc_indicatorConst hT hs hμs, setToL1_simpleFunc_indicatorConst hT' hs hμs]
exact hTT' s hs hμs c
| @h_add f g hf hg _ hf_le hg_le =>
rw [(setToL1 hT).map_add, (setToL1 hT').map_add]
exact add_le_add hf_le hg_le
| h_closed => exact isClosed_le (setToL1 hT).continuous (setToL1 hT').continuous
#align measure_theory.L1.set_to_L1_mono_left' MeasureTheory.L1.setToL1_mono_left'
theorem setToL1_mono_left {T T' : Set α → E →L[ℝ] G''} {C C' : ℝ}
(hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C')
(hTT' : ∀ s x, T s x ≤ T' s x) (f : α →₁[μ] E) : setToL1 hT f ≤ setToL1 hT' f :=
setToL1_mono_left' hT hT' (fun s _ _ x => hTT' s x) f
#align measure_theory.L1.set_to_L1_mono_left MeasureTheory.L1.setToL1_mono_left
theorem setToL1_nonneg {T : Set α → G' →L[ℝ] G''} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C)
(hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f : α →₁[μ] G'}
(hf : 0 ≤ f) : 0 ≤ setToL1 hT f := by
suffices ∀ f : { g : α →₁[μ] G' // 0 ≤ g }, 0 ≤ setToL1 hT f from
this (⟨f, hf⟩ : { g : α →₁[μ] G' // 0 ≤ g })
refine fun g =>
@isClosed_property { g : α →₁ₛ[μ] G' // 0 ≤ g } { g : α →₁[μ] G' // 0 ≤ g } _ _
(fun g => 0 ≤ setToL1 hT g)
(denseRange_coeSimpleFuncNonnegToLpNonneg 1 μ G' one_ne_top) ?_ ?_ g
· exact isClosed_le continuous_zero ((setToL1 hT).continuous.comp continuous_induced_dom)
· intro g
have : (coeSimpleFuncNonnegToLpNonneg 1 μ G' g : α →₁[μ] G') = (g : α →₁ₛ[μ] G') := rfl
rw [this, setToL1_eq_setToL1SCLM]
exact setToL1S_nonneg (fun s => hT.eq_zero_of_measure_zero) hT.1 hT_nonneg g.2
#align measure_theory.L1.set_to_L1_nonneg MeasureTheory.L1.setToL1_nonneg
theorem setToL1_mono {T : Set α → G' →L[ℝ] G''} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C)
(hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f g : α →₁[μ] G'}
(hfg : f ≤ g) : setToL1 hT f ≤ setToL1 hT g := by
rw [← sub_nonneg] at hfg ⊢
rw [← (setToL1 hT).map_sub]
exact setToL1_nonneg hT hT_nonneg hfg
#align measure_theory.L1.set_to_L1_mono MeasureTheory.L1.setToL1_mono
end Order
theorem norm_setToL1_le_norm_setToL1SCLM (hT : DominatedFinMeasAdditive μ T C) :
‖setToL1 hT‖ ≤ ‖setToL1SCLM α E μ hT‖ :=
calc
‖setToL1 hT‖ ≤ (1 : ℝ≥0) * ‖setToL1SCLM α E μ hT‖ := by
refine
ContinuousLinearMap.opNorm_extend_le (setToL1SCLM α E μ hT) (coeToLp α E ℝ)
(simpleFunc.denseRange one_ne_top) fun x => le_of_eq ?_
rw [NNReal.coe_one, one_mul]
rfl
_ = ‖setToL1SCLM α E μ hT‖ := by rw [NNReal.coe_one, one_mul]
#align measure_theory.L1.norm_set_to_L1_le_norm_set_to_L1s_clm MeasureTheory.L1.norm_setToL1_le_norm_setToL1SCLM
theorem norm_setToL1_le_mul_norm (hT : DominatedFinMeasAdditive μ T C) (hC : 0 ≤ C)
(f : α →₁[μ] E) : ‖setToL1 hT f‖ ≤ C * ‖f‖ :=
calc
‖setToL1 hT f‖ ≤ ‖setToL1SCLM α E μ hT‖ * ‖f‖ :=
ContinuousLinearMap.le_of_opNorm_le _ (norm_setToL1_le_norm_setToL1SCLM hT) _
_ ≤ C * ‖f‖ := mul_le_mul (norm_setToL1SCLM_le hT hC) le_rfl (norm_nonneg _) hC
#align measure_theory.L1.norm_set_to_L1_le_mul_norm MeasureTheory.L1.norm_setToL1_le_mul_norm
theorem norm_setToL1_le_mul_norm' (hT : DominatedFinMeasAdditive μ T C) (f : α →₁[μ] E) :
‖setToL1 hT f‖ ≤ max C 0 * ‖f‖ :=
calc
‖setToL1 hT f‖ ≤ ‖setToL1SCLM α E μ hT‖ * ‖f‖ :=
ContinuousLinearMap.le_of_opNorm_le _ (norm_setToL1_le_norm_setToL1SCLM hT) _
_ ≤ max C 0 * ‖f‖ :=
mul_le_mul (norm_setToL1SCLM_le' hT) le_rfl (norm_nonneg _) (le_max_right _ _)
#align measure_theory.L1.norm_set_to_L1_le_mul_norm' MeasureTheory.L1.norm_setToL1_le_mul_norm'
theorem norm_setToL1_le (hT : DominatedFinMeasAdditive μ T C) (hC : 0 ≤ C) : ‖setToL1 hT‖ ≤ C :=
ContinuousLinearMap.opNorm_le_bound _ hC (norm_setToL1_le_mul_norm hT hC)
#align measure_theory.L1.norm_set_to_L1_le MeasureTheory.L1.norm_setToL1_le
theorem norm_setToL1_le' (hT : DominatedFinMeasAdditive μ T C) : ‖setToL1 hT‖ ≤ max C 0 :=
ContinuousLinearMap.opNorm_le_bound _ (le_max_right _ _) (norm_setToL1_le_mul_norm' hT)
#align measure_theory.L1.norm_set_to_L1_le' MeasureTheory.L1.norm_setToL1_le'
theorem setToL1_lipschitz (hT : DominatedFinMeasAdditive μ T C) :
LipschitzWith (Real.toNNReal C) (setToL1 hT) :=
(setToL1 hT).lipschitz.weaken (norm_setToL1_le' hT)
#align measure_theory.L1.set_to_L1_lipschitz MeasureTheory.L1.setToL1_lipschitz
/-- If `fs i → f` in `L1`, then `setToL1 hT (fs i) → setToL1 hT f`. -/
theorem tendsto_setToL1 (hT : DominatedFinMeasAdditive μ T C) (f : α →₁[μ] E) {ι}
(fs : ι → α →₁[μ] E) {l : Filter ι} (hfs : Tendsto fs l (𝓝 f)) :
Tendsto (fun i => setToL1 hT (fs i)) l (𝓝 <| setToL1 hT f) :=
((setToL1 hT).continuous.tendsto _).comp hfs
#align measure_theory.L1.tendsto_set_to_L1 MeasureTheory.L1.tendsto_setToL1
end SetToL1
end L1
section Function
set_option linter.uppercaseLean3 false
variable [CompleteSpace F] {T T' T'' : Set α → E →L[ℝ] F} {C C' C'' : ℝ} {f g : α → E}
variable (μ T)
/-- Extend `T : Set α → E →L[ℝ] F` to `(α → E) → F` (for integrable functions `α → E`). We set it to
0 if the function is not integrable. -/
def setToFun (hT : DominatedFinMeasAdditive μ T C) (f : α → E) : F :=
if hf : Integrable f μ then L1.setToL1 hT (hf.toL1 f) else 0
#align measure_theory.set_to_fun MeasureTheory.setToFun
variable {μ T}
theorem setToFun_eq (hT : DominatedFinMeasAdditive μ T C) (hf : Integrable f μ) :
setToFun μ T hT f = L1.setToL1 hT (hf.toL1 f) :=
dif_pos hf
#align measure_theory.set_to_fun_eq MeasureTheory.setToFun_eq
theorem L1.setToFun_eq_setToL1 (hT : DominatedFinMeasAdditive μ T C) (f : α →₁[μ] E) :
setToFun μ T hT f = L1.setToL1 hT f := by
rw [setToFun_eq hT (L1.integrable_coeFn f), Integrable.toL1_coeFn]
#align measure_theory.L1.set_to_fun_eq_set_to_L1 MeasureTheory.L1.setToFun_eq_setToL1
theorem setToFun_undef (hT : DominatedFinMeasAdditive μ T C) (hf : ¬Integrable f μ) :
setToFun μ T hT f = 0 :=
dif_neg hf
#align measure_theory.set_to_fun_undef MeasureTheory.setToFun_undef
theorem setToFun_non_aEStronglyMeasurable (hT : DominatedFinMeasAdditive μ T C)
(hf : ¬AEStronglyMeasurable f μ) : setToFun μ T hT f = 0 :=
setToFun_undef hT (not_and_of_not_left _ hf)
#align measure_theory.set_to_fun_non_ae_strongly_measurable MeasureTheory.setToFun_non_aEStronglyMeasurable
theorem setToFun_congr_left (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (h : T = T') (f : α → E) :
setToFun μ T hT f = setToFun μ T' hT' f := by
by_cases hf : Integrable f μ
· simp_rw [setToFun_eq _ hf, L1.setToL1_congr_left T T' hT hT' h]
· simp_rw [setToFun_undef _ hf]
#align measure_theory.set_to_fun_congr_left MeasureTheory.setToFun_congr_left
theorem setToFun_congr_left' (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (h : ∀ s, MeasurableSet s → μ s < ∞ → T s = T' s)
(f : α → E) : setToFun μ T hT f = setToFun μ T' hT' f := by
by_cases hf : Integrable f μ
· simp_rw [setToFun_eq _ hf, L1.setToL1_congr_left' T T' hT hT' h]
· simp_rw [setToFun_undef _ hf]
#align measure_theory.set_to_fun_congr_left' MeasureTheory.setToFun_congr_left'
theorem setToFun_add_left (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (f : α → E) :
setToFun μ (T + T') (hT.add hT') f = setToFun μ T hT f + setToFun μ T' hT' f := by
by_cases hf : Integrable f μ
· simp_rw [setToFun_eq _ hf, L1.setToL1_add_left hT hT']
· simp_rw [setToFun_undef _ hf, add_zero]
#align measure_theory.set_to_fun_add_left MeasureTheory.setToFun_add_left
theorem setToFun_add_left' (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (hT'' : DominatedFinMeasAdditive μ T'' C'')
(h_add : ∀ s, MeasurableSet s → μ s < ∞ → T'' s = T s + T' s) (f : α → E) :
setToFun μ T'' hT'' f = setToFun μ T hT f + setToFun μ T' hT' f := by
by_cases hf : Integrable f μ
· simp_rw [setToFun_eq _ hf, L1.setToL1_add_left' hT hT' hT'' h_add]
· simp_rw [setToFun_undef _ hf, add_zero]
#align measure_theory.set_to_fun_add_left' MeasureTheory.setToFun_add_left'
theorem setToFun_smul_left (hT : DominatedFinMeasAdditive μ T C) (c : ℝ) (f : α → E) :
setToFun μ (fun s => c • T s) (hT.smul c) f = c • setToFun μ T hT f := by
by_cases hf : Integrable f μ
· simp_rw [setToFun_eq _ hf, L1.setToL1_smul_left hT c]
· simp_rw [setToFun_undef _ hf, smul_zero]
#align measure_theory.set_to_fun_smul_left MeasureTheory.setToFun_smul_left
theorem setToFun_smul_left' (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (c : ℝ)
(h_smul : ∀ s, MeasurableSet s → μ s < ∞ → T' s = c • T s) (f : α → E) :
setToFun μ T' hT' f = c • setToFun μ T hT f := by
by_cases hf : Integrable f μ
· simp_rw [setToFun_eq _ hf, L1.setToL1_smul_left' hT hT' c h_smul]
· simp_rw [setToFun_undef _ hf, smul_zero]
#align measure_theory.set_to_fun_smul_left' MeasureTheory.setToFun_smul_left'
@[simp]
theorem setToFun_zero (hT : DominatedFinMeasAdditive μ T C) : setToFun μ T hT (0 : α → E) = 0 := by
erw [setToFun_eq hT (integrable_zero _ _ _), Integrable.toL1_zero, ContinuousLinearMap.map_zero]
#align measure_theory.set_to_fun_zero MeasureTheory.setToFun_zero
@[simp]
theorem setToFun_zero_left {hT : DominatedFinMeasAdditive μ (0 : Set α → E →L[ℝ] F) C} :
setToFun μ 0 hT f = 0 := by
by_cases hf : Integrable f μ
· rw [setToFun_eq hT hf]; exact L1.setToL1_zero_left hT _
· exact setToFun_undef hT hf
#align measure_theory.set_to_fun_zero_left MeasureTheory.setToFun_zero_left
theorem setToFun_zero_left' (hT : DominatedFinMeasAdditive μ T C)
(h_zero : ∀ s, MeasurableSet s → μ s < ∞ → T s = 0) : setToFun μ T hT f = 0 := by
by_cases hf : Integrable f μ
· rw [setToFun_eq hT hf]; exact L1.setToL1_zero_left' hT h_zero _
· exact setToFun_undef hT hf
#align measure_theory.set_to_fun_zero_left' MeasureTheory.setToFun_zero_left'
theorem setToFun_add (hT : DominatedFinMeasAdditive μ T C) (hf : Integrable f μ)
(hg : Integrable g μ) : setToFun μ T hT (f + g) = setToFun μ T hT f + setToFun μ T hT g := by
rw [setToFun_eq hT (hf.add hg), setToFun_eq hT hf, setToFun_eq hT hg, Integrable.toL1_add,
(L1.setToL1 hT).map_add]
#align measure_theory.set_to_fun_add MeasureTheory.setToFun_add
theorem setToFun_finset_sum' (hT : DominatedFinMeasAdditive μ T C) {ι} (s : Finset ι)
{f : ι → α → E} (hf : ∀ i ∈ s, Integrable (f i) μ) :
setToFun μ T hT (∑ i ∈ s, f i) = ∑ i ∈ s, setToFun μ T hT (f i) := by
revert hf
refine Finset.induction_on s ?_ ?_
· intro _
simp only [setToFun_zero, Finset.sum_empty]
· intro i s his ih hf
simp only [his, Finset.sum_insert, not_false_iff]
rw [setToFun_add hT (hf i (Finset.mem_insert_self i s)) _]
· rw [ih fun i hi => hf i (Finset.mem_insert_of_mem hi)]
· convert integrable_finset_sum s fun i hi => hf i (Finset.mem_insert_of_mem hi) with x
simp
#align measure_theory.set_to_fun_finset_sum' MeasureTheory.setToFun_finset_sum'
theorem setToFun_finset_sum (hT : DominatedFinMeasAdditive μ T C) {ι} (s : Finset ι) {f : ι → α → E}
(hf : ∀ i ∈ s, Integrable (f i) μ) :
(setToFun μ T hT fun a => ∑ i ∈ s, f i a) = ∑ i ∈ s, setToFun μ T hT (f i) := by
convert setToFun_finset_sum' hT s hf with a; simp
#align measure_theory.set_to_fun_finset_sum MeasureTheory.setToFun_finset_sum
theorem setToFun_neg (hT : DominatedFinMeasAdditive μ T C) (f : α → E) :
setToFun μ T hT (-f) = -setToFun μ T hT f := by
by_cases hf : Integrable f μ
· rw [setToFun_eq hT hf, setToFun_eq hT hf.neg, Integrable.toL1_neg,
(L1.setToL1 hT).map_neg]
· rw [setToFun_undef hT hf, setToFun_undef hT, neg_zero]
rwa [← integrable_neg_iff] at hf
#align measure_theory.set_to_fun_neg MeasureTheory.setToFun_neg
theorem setToFun_sub (hT : DominatedFinMeasAdditive μ T C) (hf : Integrable f μ)
(hg : Integrable g μ) : setToFun μ T hT (f - g) = setToFun μ T hT f - setToFun μ T hT g := by
rw [sub_eq_add_neg, sub_eq_add_neg, setToFun_add hT hf hg.neg, setToFun_neg hT g]
#align measure_theory.set_to_fun_sub MeasureTheory.setToFun_sub
theorem setToFun_smul [NontriviallyNormedField 𝕜] [NormedSpace 𝕜 E] [NormedSpace 𝕜 F]
(hT : DominatedFinMeasAdditive μ T C) (h_smul : ∀ c : 𝕜, ∀ s x, T s (c • x) = c • T s x) (c : 𝕜)
(f : α → E) : setToFun μ T hT (c • f) = c • setToFun μ T hT f := by
by_cases hf : Integrable f μ
· rw [setToFun_eq hT hf, setToFun_eq hT, Integrable.toL1_smul',
L1.setToL1_smul hT h_smul c _]
· by_cases hr : c = 0
· rw [hr]; simp
· have hf' : ¬Integrable (c • f) μ := by rwa [integrable_smul_iff hr f]
rw [setToFun_undef hT hf, setToFun_undef hT hf', smul_zero]
#align measure_theory.set_to_fun_smul MeasureTheory.setToFun_smul
theorem setToFun_congr_ae (hT : DominatedFinMeasAdditive μ T C) (h : f =ᵐ[μ] g) :
setToFun μ T hT f = setToFun μ T hT g := by
by_cases hfi : Integrable f μ
· have hgi : Integrable g μ := hfi.congr h
rw [setToFun_eq hT hfi, setToFun_eq hT hgi, (Integrable.toL1_eq_toL1_iff f g hfi hgi).2 h]
· have hgi : ¬Integrable g μ := by rw [integrable_congr h] at hfi; exact hfi
rw [setToFun_undef hT hfi, setToFun_undef hT hgi]
#align measure_theory.set_to_fun_congr_ae MeasureTheory.setToFun_congr_ae
theorem setToFun_measure_zero (hT : DominatedFinMeasAdditive μ T C) (h : μ = 0) :
setToFun μ T hT f = 0 := by
have : f =ᵐ[μ] 0 := by simp [h, EventuallyEq]
rw [setToFun_congr_ae hT this, setToFun_zero]
#align measure_theory.set_to_fun_measure_zero MeasureTheory.setToFun_measure_zero
theorem setToFun_measure_zero' (hT : DominatedFinMeasAdditive μ T C)
(h : ∀ s, MeasurableSet s → μ s < ∞ → μ s = 0) : setToFun μ T hT f = 0 :=
setToFun_zero_left' hT fun s hs hμs => hT.eq_zero_of_measure_zero hs (h s hs hμs)
#align measure_theory.set_to_fun_measure_zero' MeasureTheory.setToFun_measure_zero'
theorem setToFun_toL1 (hT : DominatedFinMeasAdditive μ T C) (hf : Integrable f μ) :
setToFun μ T hT (hf.toL1 f) = setToFun μ T hT f :=
setToFun_congr_ae hT hf.coeFn_toL1
#align measure_theory.set_to_fun_to_L1 MeasureTheory.setToFun_toL1
| Mathlib/MeasureTheory/Integral/SetToL1.lean | 1,433 | 1,438 | theorem setToFun_indicator_const (hT : DominatedFinMeasAdditive μ T C) {s : Set α}
(hs : MeasurableSet s) (hμs : μ s ≠ ∞) (x : E) :
setToFun μ T hT (s.indicator fun _ => x) = T s x := by |
rw [setToFun_congr_ae hT (@indicatorConstLp_coeFn _ _ _ 1 _ _ _ hs hμs x).symm]
rw [L1.setToFun_eq_setToL1 hT]
exact L1.setToL1_indicatorConstLp hT hs hμs x
|
/-
Copyright (c) 2021 Luke Kershaw. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Luke Kershaw, Joël Riou
-/
import Mathlib.Algebra.Homology.ShortComplex.Basic
import Mathlib.CategoryTheory.Limits.Constructions.FiniteProductsOfBinaryProducts
import Mathlib.CategoryTheory.Triangulated.TriangleShift
#align_import category_theory.triangulated.pretriangulated from "leanprover-community/mathlib"@"6876fa15e3158ff3e4a4e2af1fb6e1945c6e8803"
/-!
# Pretriangulated Categories
This file contains the definition of pretriangulated categories and triangulated functors
between them.
## Implementation Notes
We work under the assumption that pretriangulated categories are preadditive categories,
but not necessarily additive categories, as is assumed in some sources.
TODO: generalise this to n-angulated categories as in https://arxiv.org/abs/1006.4592
-/
noncomputable section
open CategoryTheory Preadditive Limits
universe v v₀ v₁ v₂ u u₀ u₁ u₂
namespace CategoryTheory
open Category Pretriangulated ZeroObject
/-
We work in a preadditive category `C` equipped with an additive shift.
-/
variable (C : Type u) [Category.{v} C] [HasZeroObject C] [HasShift C ℤ] [Preadditive C]
/-- A preadditive category `C` with an additive shift, and a class of "distinguished triangles"
relative to that shift is called pretriangulated if the following hold:
* Any triangle that is isomorphic to a distinguished triangle is also distinguished.
* Any triangle of the form `(X,X,0,id,0,0)` is distinguished.
* For any morphism `f : X ⟶ Y` there exists a distinguished triangle of the form `(X,Y,Z,f,g,h)`.
* The triangle `(X,Y,Z,f,g,h)` is distinguished if and only if `(Y,Z,X⟦1⟧,g,h,-f⟦1⟧)` is.
* Given a diagram:
```
f g h
X ───> Y ───> Z ───> X⟦1⟧
│ │ │
│a │b │a⟦1⟧'
V V V
X' ───> Y' ───> Z' ───> X'⟦1⟧
f' g' h'
```
where the left square commutes, and whose rows are distinguished triangles,
there exists a morphism `c : Z ⟶ Z'` such that `(a,b,c)` is a triangle morphism.
See <https://stacks.math.columbia.edu/tag/0145>
-/
class Pretriangulated [∀ n : ℤ, Functor.Additive (shiftFunctor C n)] where
/-- a class of triangle which are called `distinguished` -/
distinguishedTriangles : Set (Triangle C)
/-- a triangle that is isomorphic to a distinguished triangle is distinguished -/
isomorphic_distinguished :
∀ T₁ ∈ distinguishedTriangles, ∀ (T₂) (_ : T₂ ≅ T₁), T₂ ∈ distinguishedTriangles
/-- obvious triangles `X ⟶ X ⟶ 0 ⟶ X⟦1⟧` are distinguished -/
contractible_distinguished : ∀ X : C, contractibleTriangle X ∈ distinguishedTriangles
/-- any morphism `X ⟶ Y` is part of a distinguished triangle `X ⟶ Y ⟶ Z ⟶ X⟦1⟧` -/
distinguished_cocone_triangle :
∀ {X Y : C} (f : X ⟶ Y),
∃ (Z : C) (g : Y ⟶ Z) (h : Z ⟶ X⟦(1 : ℤ)⟧), Triangle.mk f g h ∈ distinguishedTriangles
/-- a triangle is distinguished iff it is so after rotating it -/
rotate_distinguished_triangle :
∀ T : Triangle C, T ∈ distinguishedTriangles ↔ T.rotate ∈ distinguishedTriangles
/-- given two distinguished triangle, a commutative square
can be extended as morphism of triangles -/
complete_distinguished_triangle_morphism :
∀ (T₁ T₂ : Triangle C) (_ : T₁ ∈ distinguishedTriangles) (_ : T₂ ∈ distinguishedTriangles)
(a : T₁.obj₁ ⟶ T₂.obj₁) (b : T₁.obj₂ ⟶ T₂.obj₂) (_ : T₁.mor₁ ≫ b = a ≫ T₂.mor₁),
∃ c : T₁.obj₃ ⟶ T₂.obj₃, T₁.mor₂ ≫ c = b ≫ T₂.mor₂ ∧ T₁.mor₃ ≫ a⟦1⟧' = c ≫ T₂.mor₃
#align category_theory.pretriangulated CategoryTheory.Pretriangulated
namespace Pretriangulated
variable [∀ n : ℤ, Functor.Additive (CategoryTheory.shiftFunctor C n)] [hC : Pretriangulated C]
-- Porting note: increased the priority so that we can write `T ∈ distTriang C`, and
-- not just `T ∈ (distTriang C)`
/-- distinguished triangles in a pretriangulated category -/
notation:60 "distTriang " C => @distinguishedTriangles C _ _ _ _ _ _
variable {C}
lemma distinguished_iff_of_iso {T₁ T₂ : Triangle C} (e : T₁ ≅ T₂) :
(T₁ ∈ distTriang C) ↔ T₂ ∈ distTriang C :=
⟨fun hT₁ => isomorphic_distinguished _ hT₁ _ e.symm,
fun hT₂ => isomorphic_distinguished _ hT₂ _ e⟩
/-- Given any distinguished triangle `T`, then we know `T.rotate` is also distinguished.
-/
theorem rot_of_distTriang (T : Triangle C) (H : T ∈ distTriang C) : T.rotate ∈ distTriang C :=
(rotate_distinguished_triangle T).mp H
#align category_theory.pretriangulated.rot_of_dist_triangle CategoryTheory.Pretriangulated.rot_of_distTriang
/-- Given any distinguished triangle `T`, then we know `T.inv_rotate` is also distinguished.
-/
theorem inv_rot_of_distTriang (T : Triangle C) (H : T ∈ distTriang C) :
T.invRotate ∈ distTriang C :=
(rotate_distinguished_triangle T.invRotate).mpr
(isomorphic_distinguished T H T.invRotate.rotate (invRotCompRot.app T))
#align category_theory.pretriangulated.inv_rot_of_dist_triangle CategoryTheory.Pretriangulated.inv_rot_of_distTriang
/-- Given any distinguished triangle
```
f g h
X ───> Y ───> Z ───> X⟦1⟧
```
the composition `f ≫ g = 0`.
See <https://stacks.math.columbia.edu/tag/0146>
-/
@[reassoc]
theorem comp_distTriang_mor_zero₁₂ (T) (H : T ∈ (distTriang C)) : T.mor₁ ≫ T.mor₂ = 0 := by
obtain ⟨c, hc⟩ :=
complete_distinguished_triangle_morphism _ _ (contractible_distinguished T.obj₁) H (𝟙 T.obj₁)
T.mor₁ rfl
simpa only [contractibleTriangle_mor₂, zero_comp] using hc.left.symm
#align category_theory.pretriangulated.comp_dist_triangle_mor_zero₁₂ CategoryTheory.Pretriangulated.comp_distTriang_mor_zero₁₂
/-- Given any distinguished triangle
```
f g h
X ───> Y ───> Z ───> X⟦1⟧
```
the composition `g ≫ h = 0`.
See <https://stacks.math.columbia.edu/tag/0146>
-/
@[reassoc]
theorem comp_distTriang_mor_zero₂₃ (T : Triangle C) (H : T ∈ distTriang C) :
T.mor₂ ≫ T.mor₃ = 0 :=
comp_distTriang_mor_zero₁₂ T.rotate (rot_of_distTriang T H)
#align category_theory.pretriangulated.comp_dist_triangle_mor_zero₂₃ CategoryTheory.Pretriangulated.comp_distTriang_mor_zero₂₃
/-- Given any distinguished triangle
```
f g h
X ───> Y ───> Z ───> X⟦1⟧
```
the composition `h ≫ f⟦1⟧ = 0`.
See <https://stacks.math.columbia.edu/tag/0146>
-/
@[reassoc]
| Mathlib/CategoryTheory/Triangulated/Pretriangulated.lean | 156 | 159 | theorem comp_distTriang_mor_zero₃₁ (T : Triangle C) (H : T ∈ distTriang C) :
T.mor₃ ≫ T.mor₁⟦1⟧' = 0 := by |
have H₂ := rot_of_distTriang T.rotate (rot_of_distTriang T H)
simpa using comp_distTriang_mor_zero₁₂ T.rotate.rotate H₂
|
/-
Copyright (c) 2017 Microsoft Corporation. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Logic.Relation
import Mathlib.Data.Option.Basic
import Mathlib.Data.Seq.Seq
#align_import data.seq.wseq from "leanprover-community/mathlib"@"a7e36e48519ab281320c4d192da6a7b348ce40ad"
/-!
# Partially defined possibly infinite lists
This file provides a `WSeq α` type representing partially defined possibly infinite lists
(referred here as weak sequences).
-/
namespace Stream'
open Function
universe u v w
/-
coinductive WSeq (α : Type u) : Type u
| nil : WSeq α
| cons : α → WSeq α → WSeq α
| think : WSeq α → WSeq α
-/
/-- Weak sequences.
While the `Seq` structure allows for lists which may not be finite,
a weak sequence also allows the computation of each element to
involve an indeterminate amount of computation, including possibly
an infinite loop. This is represented as a regular `Seq` interspersed
with `none` elements to indicate that computation is ongoing.
This model is appropriate for Haskell style lazy lists, and is closed
under most interesting computation patterns on infinite lists,
but conversely it is difficult to extract elements from it. -/
def WSeq (α) :=
Seq (Option α)
#align stream.wseq Stream'.WSeq
/-
coinductive WSeq (α : Type u) : Type u
| nil : WSeq α
| cons : α → WSeq α → WSeq α
| think : WSeq α → WSeq α
-/
namespace WSeq
variable {α : Type u} {β : Type v} {γ : Type w}
/-- Turn a sequence into a weak sequence -/
@[coe]
def ofSeq : Seq α → WSeq α :=
(· <$> ·) some
#align stream.wseq.of_seq Stream'.WSeq.ofSeq
/-- Turn a list into a weak sequence -/
@[coe]
def ofList (l : List α) : WSeq α :=
ofSeq l
#align stream.wseq.of_list Stream'.WSeq.ofList
/-- Turn a stream into a weak sequence -/
@[coe]
def ofStream (l : Stream' α) : WSeq α :=
ofSeq l
#align stream.wseq.of_stream Stream'.WSeq.ofStream
instance coeSeq : Coe (Seq α) (WSeq α) :=
⟨ofSeq⟩
#align stream.wseq.coe_seq Stream'.WSeq.coeSeq
instance coeList : Coe (List α) (WSeq α) :=
⟨ofList⟩
#align stream.wseq.coe_list Stream'.WSeq.coeList
instance coeStream : Coe (Stream' α) (WSeq α) :=
⟨ofStream⟩
#align stream.wseq.coe_stream Stream'.WSeq.coeStream
/-- The empty weak sequence -/
def nil : WSeq α :=
Seq.nil
#align stream.wseq.nil Stream'.WSeq.nil
instance inhabited : Inhabited (WSeq α) :=
⟨nil⟩
#align stream.wseq.inhabited Stream'.WSeq.inhabited
/-- Prepend an element to a weak sequence -/
def cons (a : α) : WSeq α → WSeq α :=
Seq.cons (some a)
#align stream.wseq.cons Stream'.WSeq.cons
/-- Compute for one tick, without producing any elements -/
def think : WSeq α → WSeq α :=
Seq.cons none
#align stream.wseq.think Stream'.WSeq.think
/-- Destruct a weak sequence, to (eventually possibly) produce either
`none` for `nil` or `some (a, s)` if an element is produced. -/
def destruct : WSeq α → Computation (Option (α × WSeq α)) :=
Computation.corec fun s =>
match Seq.destruct s with
| none => Sum.inl none
| some (none, s') => Sum.inr s'
| some (some a, s') => Sum.inl (some (a, s'))
#align stream.wseq.destruct Stream'.WSeq.destruct
/-- Recursion principle for weak sequences, compare with `List.recOn`. -/
def recOn {C : WSeq α → Sort v} (s : WSeq α) (h1 : C nil) (h2 : ∀ x s, C (cons x s))
(h3 : ∀ s, C (think s)) : C s :=
Seq.recOn s h1 fun o => Option.recOn o h3 h2
#align stream.wseq.rec_on Stream'.WSeq.recOn
/-- membership for weak sequences-/
protected def Mem (a : α) (s : WSeq α) :=
Seq.Mem (some a) s
#align stream.wseq.mem Stream'.WSeq.Mem
instance membership : Membership α (WSeq α) :=
⟨WSeq.Mem⟩
#align stream.wseq.has_mem Stream'.WSeq.membership
theorem not_mem_nil (a : α) : a ∉ @nil α :=
Seq.not_mem_nil (some a)
#align stream.wseq.not_mem_nil Stream'.WSeq.not_mem_nil
/-- Get the head of a weak sequence. This involves a possibly
infinite computation. -/
def head (s : WSeq α) : Computation (Option α) :=
Computation.map (Prod.fst <$> ·) (destruct s)
#align stream.wseq.head Stream'.WSeq.head
/-- Encode a computation yielding a weak sequence into additional
`think` constructors in a weak sequence -/
def flatten : Computation (WSeq α) → WSeq α :=
Seq.corec fun c =>
match Computation.destruct c with
| Sum.inl s => Seq.omap (return ·) (Seq.destruct s)
| Sum.inr c' => some (none, c')
#align stream.wseq.flatten Stream'.WSeq.flatten
/-- Get the tail of a weak sequence. This doesn't need a `Computation`
wrapper, unlike `head`, because `flatten` allows us to hide this
in the construction of the weak sequence itself. -/
def tail (s : WSeq α) : WSeq α :=
flatten <| (fun o => Option.recOn o nil Prod.snd) <$> destruct s
#align stream.wseq.tail Stream'.WSeq.tail
/-- drop the first `n` elements from `s`. -/
def drop (s : WSeq α) : ℕ → WSeq α
| 0 => s
| n + 1 => tail (drop s n)
#align stream.wseq.drop Stream'.WSeq.drop
/-- Get the nth element of `s`. -/
def get? (s : WSeq α) (n : ℕ) : Computation (Option α) :=
head (drop s n)
#align stream.wseq.nth Stream'.WSeq.get?
/-- Convert `s` to a list (if it is finite and completes in finite time). -/
def toList (s : WSeq α) : Computation (List α) :=
@Computation.corec (List α) (List α × WSeq α)
(fun ⟨l, s⟩ =>
match Seq.destruct s with
| none => Sum.inl l.reverse
| some (none, s') => Sum.inr (l, s')
| some (some a, s') => Sum.inr (a::l, s'))
([], s)
#align stream.wseq.to_list Stream'.WSeq.toList
/-- Get the length of `s` (if it is finite and completes in finite time). -/
def length (s : WSeq α) : Computation ℕ :=
@Computation.corec ℕ (ℕ × WSeq α)
(fun ⟨n, s⟩ =>
match Seq.destruct s with
| none => Sum.inl n
| some (none, s') => Sum.inr (n, s')
| some (some _, s') => Sum.inr (n + 1, s'))
(0, s)
#align stream.wseq.length Stream'.WSeq.length
/-- A weak sequence is finite if `toList s` terminates. Equivalently,
it is a finite number of `think` and `cons` applied to `nil`. -/
class IsFinite (s : WSeq α) : Prop where
out : (toList s).Terminates
#align stream.wseq.is_finite Stream'.WSeq.IsFinite
instance toList_terminates (s : WSeq α) [h : IsFinite s] : (toList s).Terminates :=
h.out
#align stream.wseq.to_list_terminates Stream'.WSeq.toList_terminates
/-- Get the list corresponding to a finite weak sequence. -/
def get (s : WSeq α) [IsFinite s] : List α :=
(toList s).get
#align stream.wseq.get Stream'.WSeq.get
/-- A weak sequence is *productive* if it never stalls forever - there are
always a finite number of `think`s between `cons` constructors.
The sequence itself is allowed to be infinite though. -/
class Productive (s : WSeq α) : Prop where
get?_terminates : ∀ n, (get? s n).Terminates
#align stream.wseq.productive Stream'.WSeq.Productive
#align stream.wseq.productive.nth_terminates Stream'.WSeq.Productive.get?_terminates
theorem productive_iff (s : WSeq α) : Productive s ↔ ∀ n, (get? s n).Terminates :=
⟨fun h => h.1, fun h => ⟨h⟩⟩
#align stream.wseq.productive_iff Stream'.WSeq.productive_iff
instance get?_terminates (s : WSeq α) [h : Productive s] : ∀ n, (get? s n).Terminates :=
h.get?_terminates
#align stream.wseq.nth_terminates Stream'.WSeq.get?_terminates
instance head_terminates (s : WSeq α) [Productive s] : (head s).Terminates :=
s.get?_terminates 0
#align stream.wseq.head_terminates Stream'.WSeq.head_terminates
/-- Replace the `n`th element of `s` with `a`. -/
def updateNth (s : WSeq α) (n : ℕ) (a : α) : WSeq α :=
@Seq.corec (Option α) (ℕ × WSeq α)
(fun ⟨n, s⟩ =>
match Seq.destruct s, n with
| none, _ => none
| some (none, s'), n => some (none, n, s')
| some (some a', s'), 0 => some (some a', 0, s')
| some (some _, s'), 1 => some (some a, 0, s')
| some (some a', s'), n + 2 => some (some a', n + 1, s'))
(n + 1, s)
#align stream.wseq.update_nth Stream'.WSeq.updateNth
/-- Remove the `n`th element of `s`. -/
def removeNth (s : WSeq α) (n : ℕ) : WSeq α :=
@Seq.corec (Option α) (ℕ × WSeq α)
(fun ⟨n, s⟩ =>
match Seq.destruct s, n with
| none, _ => none
| some (none, s'), n => some (none, n, s')
| some (some a', s'), 0 => some (some a', 0, s')
| some (some _, s'), 1 => some (none, 0, s')
| some (some a', s'), n + 2 => some (some a', n + 1, s'))
(n + 1, s)
#align stream.wseq.remove_nth Stream'.WSeq.removeNth
/-- Map the elements of `s` over `f`, removing any values that yield `none`. -/
def filterMap (f : α → Option β) : WSeq α → WSeq β :=
Seq.corec fun s =>
match Seq.destruct s with
| none => none
| some (none, s') => some (none, s')
| some (some a, s') => some (f a, s')
#align stream.wseq.filter_map Stream'.WSeq.filterMap
/-- Select the elements of `s` that satisfy `p`. -/
def filter (p : α → Prop) [DecidablePred p] : WSeq α → WSeq α :=
filterMap fun a => if p a then some a else none
#align stream.wseq.filter Stream'.WSeq.filter
-- example of infinite list manipulations
/-- Get the first element of `s` satisfying `p`. -/
def find (p : α → Prop) [DecidablePred p] (s : WSeq α) : Computation (Option α) :=
head <| filter p s
#align stream.wseq.find Stream'.WSeq.find
/-- Zip a function over two weak sequences -/
def zipWith (f : α → β → γ) (s1 : WSeq α) (s2 : WSeq β) : WSeq γ :=
@Seq.corec (Option γ) (WSeq α × WSeq β)
(fun ⟨s1, s2⟩ =>
match Seq.destruct s1, Seq.destruct s2 with
| some (none, s1'), some (none, s2') => some (none, s1', s2')
| some (some _, _), some (none, s2') => some (none, s1, s2')
| some (none, s1'), some (some _, _) => some (none, s1', s2)
| some (some a1, s1'), some (some a2, s2') => some (some (f a1 a2), s1', s2')
| _, _ => none)
(s1, s2)
#align stream.wseq.zip_with Stream'.WSeq.zipWith
/-- Zip two weak sequences into a single sequence of pairs -/
def zip : WSeq α → WSeq β → WSeq (α × β) :=
zipWith Prod.mk
#align stream.wseq.zip Stream'.WSeq.zip
/-- Get the list of indexes of elements of `s` satisfying `p` -/
def findIndexes (p : α → Prop) [DecidablePred p] (s : WSeq α) : WSeq ℕ :=
(zip s (Stream'.nats : WSeq ℕ)).filterMap fun ⟨a, n⟩ => if p a then some n else none
#align stream.wseq.find_indexes Stream'.WSeq.findIndexes
/-- Get the index of the first element of `s` satisfying `p` -/
def findIndex (p : α → Prop) [DecidablePred p] (s : WSeq α) : Computation ℕ :=
(fun o => Option.getD o 0) <$> head (findIndexes p s)
#align stream.wseq.find_index Stream'.WSeq.findIndex
/-- Get the index of the first occurrence of `a` in `s` -/
def indexOf [DecidableEq α] (a : α) : WSeq α → Computation ℕ :=
findIndex (Eq a)
#align stream.wseq.index_of Stream'.WSeq.indexOf
/-- Get the indexes of occurrences of `a` in `s` -/
def indexesOf [DecidableEq α] (a : α) : WSeq α → WSeq ℕ :=
findIndexes (Eq a)
#align stream.wseq.indexes_of Stream'.WSeq.indexesOf
/-- `union s1 s2` is a weak sequence which interleaves `s1` and `s2` in
some order (nondeterministically). -/
def union (s1 s2 : WSeq α) : WSeq α :=
@Seq.corec (Option α) (WSeq α × WSeq α)
(fun ⟨s1, s2⟩ =>
match Seq.destruct s1, Seq.destruct s2 with
| none, none => none
| some (a1, s1'), none => some (a1, s1', nil)
| none, some (a2, s2') => some (a2, nil, s2')
| some (none, s1'), some (none, s2') => some (none, s1', s2')
| some (some a1, s1'), some (none, s2') => some (some a1, s1', s2')
| some (none, s1'), some (some a2, s2') => some (some a2, s1', s2')
| some (some a1, s1'), some (some a2, s2') => some (some a1, cons a2 s1', s2'))
(s1, s2)
#align stream.wseq.union Stream'.WSeq.union
/-- Returns `true` if `s` is `nil` and `false` if `s` has an element -/
def isEmpty (s : WSeq α) : Computation Bool :=
Computation.map Option.isNone <| head s
#align stream.wseq.is_empty Stream'.WSeq.isEmpty
/-- Calculate one step of computation -/
def compute (s : WSeq α) : WSeq α :=
match Seq.destruct s with
| some (none, s') => s'
| _ => s
#align stream.wseq.compute Stream'.WSeq.compute
/-- Get the first `n` elements of a weak sequence -/
def take (s : WSeq α) (n : ℕ) : WSeq α :=
@Seq.corec (Option α) (ℕ × WSeq α)
(fun ⟨n, s⟩ =>
match n, Seq.destruct s with
| 0, _ => none
| _ + 1, none => none
| m + 1, some (none, s') => some (none, m + 1, s')
| m + 1, some (some a, s') => some (some a, m, s'))
(n, s)
#align stream.wseq.take Stream'.WSeq.take
/-- Split the sequence at position `n` into a finite initial segment
and the weak sequence tail -/
def splitAt (s : WSeq α) (n : ℕ) : Computation (List α × WSeq α) :=
@Computation.corec (List α × WSeq α) (ℕ × List α × WSeq α)
(fun ⟨n, l, s⟩ =>
match n, Seq.destruct s with
| 0, _ => Sum.inl (l.reverse, s)
| _ + 1, none => Sum.inl (l.reverse, s)
| _ + 1, some (none, s') => Sum.inr (n, l, s')
| m + 1, some (some a, s') => Sum.inr (m, a::l, s'))
(n, [], s)
#align stream.wseq.split_at Stream'.WSeq.splitAt
/-- Returns `true` if any element of `s` satisfies `p` -/
def any (s : WSeq α) (p : α → Bool) : Computation Bool :=
Computation.corec
(fun s : WSeq α =>
match Seq.destruct s with
| none => Sum.inl false
| some (none, s') => Sum.inr s'
| some (some a, s') => if p a then Sum.inl true else Sum.inr s')
s
#align stream.wseq.any Stream'.WSeq.any
/-- Returns `true` if every element of `s` satisfies `p` -/
def all (s : WSeq α) (p : α → Bool) : Computation Bool :=
Computation.corec
(fun s : WSeq α =>
match Seq.destruct s with
| none => Sum.inl true
| some (none, s') => Sum.inr s'
| some (some a, s') => if p a then Sum.inr s' else Sum.inl false)
s
#align stream.wseq.all Stream'.WSeq.all
/-- Apply a function to the elements of the sequence to produce a sequence
of partial results. (There is no `scanr` because this would require
working from the end of the sequence, which may not exist.) -/
def scanl (f : α → β → α) (a : α) (s : WSeq β) : WSeq α :=
cons a <|
@Seq.corec (Option α) (α × WSeq β)
(fun ⟨a, s⟩ =>
match Seq.destruct s with
| none => none
| some (none, s') => some (none, a, s')
| some (some b, s') =>
let a' := f a b
some (some a', a', s'))
(a, s)
#align stream.wseq.scanl Stream'.WSeq.scanl
/-- Get the weak sequence of initial segments of the input sequence -/
def inits (s : WSeq α) : WSeq (List α) :=
cons [] <|
@Seq.corec (Option (List α)) (Batteries.DList α × WSeq α)
(fun ⟨l, s⟩ =>
match Seq.destruct s with
| none => none
| some (none, s') => some (none, l, s')
| some (some a, s') =>
let l' := l.push a
some (some l'.toList, l', s'))
(Batteries.DList.empty, s)
#align stream.wseq.inits Stream'.WSeq.inits
/-- Like take, but does not wait for a result. Calculates `n` steps of
computation and returns the sequence computed so far -/
def collect (s : WSeq α) (n : ℕ) : List α :=
(Seq.take n s).filterMap id
#align stream.wseq.collect Stream'.WSeq.collect
/-- Append two weak sequences. As with `Seq.append`, this may not use
the second sequence if the first one takes forever to compute -/
def append : WSeq α → WSeq α → WSeq α :=
Seq.append
#align stream.wseq.append Stream'.WSeq.append
/-- Map a function over a weak sequence -/
def map (f : α → β) : WSeq α → WSeq β :=
Seq.map (Option.map f)
#align stream.wseq.map Stream'.WSeq.map
/-- Flatten a sequence of weak sequences. (Note that this allows
empty sequences, unlike `Seq.join`.) -/
def join (S : WSeq (WSeq α)) : WSeq α :=
Seq.join
((fun o : Option (WSeq α) =>
match o with
| none => Seq1.ret none
| some s => (none, s)) <$>
S)
#align stream.wseq.join Stream'.WSeq.join
/-- Monadic bind operator for weak sequences -/
def bind (s : WSeq α) (f : α → WSeq β) : WSeq β :=
join (map f s)
#align stream.wseq.bind Stream'.WSeq.bind
/-- lift a relation to a relation over weak sequences -/
@[simp]
def LiftRelO (R : α → β → Prop) (C : WSeq α → WSeq β → Prop) :
Option (α × WSeq α) → Option (β × WSeq β) → Prop
| none, none => True
| some (a, s), some (b, t) => R a b ∧ C s t
| _, _ => False
#align stream.wseq.lift_rel_o Stream'.WSeq.LiftRelO
theorem LiftRelO.imp {R S : α → β → Prop} {C D : WSeq α → WSeq β → Prop} (H1 : ∀ a b, R a b → S a b)
(H2 : ∀ s t, C s t → D s t) : ∀ {o p}, LiftRelO R C o p → LiftRelO S D o p
| none, none, _ => trivial
| some (_, _), some (_, _), h => And.imp (H1 _ _) (H2 _ _) h
| none, some _, h => False.elim h
| some (_, _), none, h => False.elim h
#align stream.wseq.lift_rel_o.imp Stream'.WSeq.LiftRelO.imp
theorem LiftRelO.imp_right (R : α → β → Prop) {C D : WSeq α → WSeq β → Prop}
(H : ∀ s t, C s t → D s t) {o p} : LiftRelO R C o p → LiftRelO R D o p :=
LiftRelO.imp (fun _ _ => id) H
#align stream.wseq.lift_rel_o.imp_right Stream'.WSeq.LiftRelO.imp_right
/-- Definition of bisimilarity for weak sequences-/
@[simp]
def BisimO (R : WSeq α → WSeq α → Prop) : Option (α × WSeq α) → Option (α × WSeq α) → Prop :=
LiftRelO (· = ·) R
#align stream.wseq.bisim_o Stream'.WSeq.BisimO
theorem BisimO.imp {R S : WSeq α → WSeq α → Prop} (H : ∀ s t, R s t → S s t) {o p} :
BisimO R o p → BisimO S o p :=
LiftRelO.imp_right _ H
#align stream.wseq.bisim_o.imp Stream'.WSeq.BisimO.imp
/-- Two weak sequences are `LiftRel R` related if they are either both empty,
or they are both nonempty and the heads are `R` related and the tails are
`LiftRel R` related. (This is a coinductive definition.) -/
def LiftRel (R : α → β → Prop) (s : WSeq α) (t : WSeq β) : Prop :=
∃ C : WSeq α → WSeq β → Prop,
C s t ∧ ∀ {s t}, C s t → Computation.LiftRel (LiftRelO R C) (destruct s) (destruct t)
#align stream.wseq.lift_rel Stream'.WSeq.LiftRel
/-- If two sequences are equivalent, then they have the same values and
the same computational behavior (i.e. if one loops forever then so does
the other), although they may differ in the number of `think`s needed to
arrive at the answer. -/
def Equiv : WSeq α → WSeq α → Prop :=
LiftRel (· = ·)
#align stream.wseq.equiv Stream'.WSeq.Equiv
theorem liftRel_destruct {R : α → β → Prop} {s : WSeq α} {t : WSeq β} :
LiftRel R s t → Computation.LiftRel (LiftRelO R (LiftRel R)) (destruct s) (destruct t)
| ⟨R, h1, h2⟩ => by
refine Computation.LiftRel.imp ?_ _ _ (h2 h1)
apply LiftRelO.imp_right
exact fun s' t' h' => ⟨R, h', @h2⟩
#align stream.wseq.lift_rel_destruct Stream'.WSeq.liftRel_destruct
theorem liftRel_destruct_iff {R : α → β → Prop} {s : WSeq α} {t : WSeq β} :
LiftRel R s t ↔ Computation.LiftRel (LiftRelO R (LiftRel R)) (destruct s) (destruct t) :=
⟨liftRel_destruct, fun h =>
⟨fun s t =>
LiftRel R s t ∨ Computation.LiftRel (LiftRelO R (LiftRel R)) (destruct s) (destruct t),
Or.inr h, fun {s t} h => by
have h : Computation.LiftRel (LiftRelO R (LiftRel R)) (destruct s) (destruct t) := by
cases' h with h h
· exact liftRel_destruct h
· assumption
apply Computation.LiftRel.imp _ _ _ h
intro a b
apply LiftRelO.imp_right
intro s t
apply Or.inl⟩⟩
#align stream.wseq.lift_rel_destruct_iff Stream'.WSeq.liftRel_destruct_iff
-- Porting note: To avoid ambiguous notation, `~` became `~ʷ`.
infixl:50 " ~ʷ " => Equiv
theorem destruct_congr {s t : WSeq α} :
s ~ʷ t → Computation.LiftRel (BisimO (· ~ʷ ·)) (destruct s) (destruct t) :=
liftRel_destruct
#align stream.wseq.destruct_congr Stream'.WSeq.destruct_congr
theorem destruct_congr_iff {s t : WSeq α} :
s ~ʷ t ↔ Computation.LiftRel (BisimO (· ~ʷ ·)) (destruct s) (destruct t) :=
liftRel_destruct_iff
#align stream.wseq.destruct_congr_iff Stream'.WSeq.destruct_congr_iff
theorem LiftRel.refl (R : α → α → Prop) (H : Reflexive R) : Reflexive (LiftRel R) := fun s => by
refine ⟨(· = ·), rfl, fun {s t} (h : s = t) => ?_⟩
rw [← h]
apply Computation.LiftRel.refl
intro a
cases' a with a
· simp
· cases a
simp only [LiftRelO, and_true]
apply H
#align stream.wseq.lift_rel.refl Stream'.WSeq.LiftRel.refl
theorem LiftRelO.swap (R : α → β → Prop) (C) :
swap (LiftRelO R C) = LiftRelO (swap R) (swap C) := by
funext x y
rcases x with ⟨⟩ | ⟨hx, jx⟩ <;> rcases y with ⟨⟩ | ⟨hy, jy⟩ <;> rfl
#align stream.wseq.lift_rel_o.swap Stream'.WSeq.LiftRelO.swap
theorem LiftRel.swap_lem {R : α → β → Prop} {s1 s2} (h : LiftRel R s1 s2) :
LiftRel (swap R) s2 s1 := by
refine ⟨swap (LiftRel R), h, fun {s t} (h : LiftRel R t s) => ?_⟩
rw [← LiftRelO.swap, Computation.LiftRel.swap]
apply liftRel_destruct h
#align stream.wseq.lift_rel.swap_lem Stream'.WSeq.LiftRel.swap_lem
theorem LiftRel.swap (R : α → β → Prop) : swap (LiftRel R) = LiftRel (swap R) :=
funext fun _ => funext fun _ => propext ⟨LiftRel.swap_lem, LiftRel.swap_lem⟩
#align stream.wseq.lift_rel.swap Stream'.WSeq.LiftRel.swap
theorem LiftRel.symm (R : α → α → Prop) (H : Symmetric R) : Symmetric (LiftRel R) :=
fun s1 s2 (h : Function.swap (LiftRel R) s2 s1) => by rwa [LiftRel.swap, H.swap_eq] at h
#align stream.wseq.lift_rel.symm Stream'.WSeq.LiftRel.symm
theorem LiftRel.trans (R : α → α → Prop) (H : Transitive R) : Transitive (LiftRel R) :=
fun s t u h1 h2 => by
refine ⟨fun s u => ∃ t, LiftRel R s t ∧ LiftRel R t u, ⟨t, h1, h2⟩, fun {s u} h => ?_⟩
rcases h with ⟨t, h1, h2⟩
have h1 := liftRel_destruct h1
have h2 := liftRel_destruct h2
refine
Computation.liftRel_def.2
⟨(Computation.terminates_of_liftRel h1).trans (Computation.terminates_of_liftRel h2),
fun {a c} ha hc => ?_⟩
rcases h1.left ha with ⟨b, hb, t1⟩
have t2 := Computation.rel_of_liftRel h2 hb hc
cases' a with a <;> cases' c with c
· trivial
· cases b
· cases t2
· cases t1
· cases a
cases' b with b
· cases t1
· cases b
cases t2
· cases' a with a s
cases' b with b
· cases t1
cases' b with b t
cases' c with c u
cases' t1 with ab st
cases' t2 with bc tu
exact ⟨H ab bc, t, st, tu⟩
#align stream.wseq.lift_rel.trans Stream'.WSeq.LiftRel.trans
theorem LiftRel.equiv (R : α → α → Prop) : Equivalence R → Equivalence (LiftRel R)
| ⟨refl, symm, trans⟩ => ⟨LiftRel.refl R refl, @(LiftRel.symm R @symm), @(LiftRel.trans R @trans)⟩
#align stream.wseq.lift_rel.equiv Stream'.WSeq.LiftRel.equiv
@[refl]
theorem Equiv.refl : ∀ s : WSeq α, s ~ʷ s :=
LiftRel.refl (· = ·) Eq.refl
#align stream.wseq.equiv.refl Stream'.WSeq.Equiv.refl
@[symm]
theorem Equiv.symm : ∀ {s t : WSeq α}, s ~ʷ t → t ~ʷ s :=
@(LiftRel.symm (· = ·) (@Eq.symm _))
#align stream.wseq.equiv.symm Stream'.WSeq.Equiv.symm
@[trans]
theorem Equiv.trans : ∀ {s t u : WSeq α}, s ~ʷ t → t ~ʷ u → s ~ʷ u :=
@(LiftRel.trans (· = ·) (@Eq.trans _))
#align stream.wseq.equiv.trans Stream'.WSeq.Equiv.trans
theorem Equiv.equivalence : Equivalence (@Equiv α) :=
⟨@Equiv.refl _, @Equiv.symm _, @Equiv.trans _⟩
#align stream.wseq.equiv.equivalence Stream'.WSeq.Equiv.equivalence
open Computation
@[simp]
theorem destruct_nil : destruct (nil : WSeq α) = Computation.pure none :=
Computation.destruct_eq_pure rfl
#align stream.wseq.destruct_nil Stream'.WSeq.destruct_nil
@[simp]
theorem destruct_cons (a : α) (s) : destruct (cons a s) = Computation.pure (some (a, s)) :=
Computation.destruct_eq_pure <| by simp [destruct, cons, Computation.rmap]
#align stream.wseq.destruct_cons Stream'.WSeq.destruct_cons
@[simp]
theorem destruct_think (s : WSeq α) : destruct (think s) = (destruct s).think :=
Computation.destruct_eq_think <| by simp [destruct, think, Computation.rmap]
#align stream.wseq.destruct_think Stream'.WSeq.destruct_think
@[simp]
theorem seq_destruct_nil : Seq.destruct (nil : WSeq α) = none :=
Seq.destruct_nil
#align stream.wseq.seq_destruct_nil Stream'.WSeq.seq_destruct_nil
@[simp]
theorem seq_destruct_cons (a : α) (s) : Seq.destruct (cons a s) = some (some a, s) :=
Seq.destruct_cons _ _
#align stream.wseq.seq_destruct_cons Stream'.WSeq.seq_destruct_cons
@[simp]
theorem seq_destruct_think (s : WSeq α) : Seq.destruct (think s) = some (none, s) :=
Seq.destruct_cons _ _
#align stream.wseq.seq_destruct_think Stream'.WSeq.seq_destruct_think
@[simp]
theorem head_nil : head (nil : WSeq α) = Computation.pure none := by simp [head]
#align stream.wseq.head_nil Stream'.WSeq.head_nil
@[simp]
theorem head_cons (a : α) (s) : head (cons a s) = Computation.pure (some a) := by simp [head]
#align stream.wseq.head_cons Stream'.WSeq.head_cons
@[simp]
theorem head_think (s : WSeq α) : head (think s) = (head s).think := by simp [head]
#align stream.wseq.head_think Stream'.WSeq.head_think
@[simp]
theorem flatten_pure (s : WSeq α) : flatten (Computation.pure s) = s := by
refine Seq.eq_of_bisim (fun s1 s2 => flatten (Computation.pure s2) = s1) ?_ rfl
intro s' s h
rw [← h]
simp only [Seq.BisimO, flatten, Seq.omap, pure_def, Seq.corec_eq, destruct_pure]
cases Seq.destruct s with
| none => simp
| some val =>
cases' val with o s'
simp
#align stream.wseq.flatten_ret Stream'.WSeq.flatten_pure
@[simp]
theorem flatten_think (c : Computation (WSeq α)) : flatten c.think = think (flatten c) :=
Seq.destruct_eq_cons <| by simp [flatten, think]
#align stream.wseq.flatten_think Stream'.WSeq.flatten_think
@[simp]
theorem destruct_flatten (c : Computation (WSeq α)) : destruct (flatten c) = c >>= destruct := by
refine
Computation.eq_of_bisim
(fun c1 c2 => c1 = c2 ∨ ∃ c, c1 = destruct (flatten c) ∧ c2 = Computation.bind c destruct) ?_
(Or.inr ⟨c, rfl, rfl⟩)
intro c1 c2 h
exact
match c1, c2, h with
| c, _, Or.inl rfl => by cases c.destruct <;> simp
| _, _, Or.inr ⟨c, rfl, rfl⟩ => by
induction' c using Computation.recOn with a c' <;> simp
· cases (destruct a).destruct <;> simp
· exact Or.inr ⟨c', rfl, rfl⟩
#align stream.wseq.destruct_flatten Stream'.WSeq.destruct_flatten
theorem head_terminates_iff (s : WSeq α) : Terminates (head s) ↔ Terminates (destruct s) :=
terminates_map_iff _ (destruct s)
#align stream.wseq.head_terminates_iff Stream'.WSeq.head_terminates_iff
@[simp]
theorem tail_nil : tail (nil : WSeq α) = nil := by simp [tail]
#align stream.wseq.tail_nil Stream'.WSeq.tail_nil
@[simp]
theorem tail_cons (a : α) (s) : tail (cons a s) = s := by simp [tail]
#align stream.wseq.tail_cons Stream'.WSeq.tail_cons
@[simp]
theorem tail_think (s : WSeq α) : tail (think s) = (tail s).think := by simp [tail]
#align stream.wseq.tail_think Stream'.WSeq.tail_think
@[simp]
theorem dropn_nil (n) : drop (nil : WSeq α) n = nil := by induction n <;> simp [*, drop]
#align stream.wseq.dropn_nil Stream'.WSeq.dropn_nil
@[simp]
theorem dropn_cons (a : α) (s) (n) : drop (cons a s) (n + 1) = drop s n := by
induction n with
| zero => simp [drop]
| succ n n_ih =>
-- porting note (#10745): was `simp [*, drop]`.
simp [drop, ← n_ih]
#align stream.wseq.dropn_cons Stream'.WSeq.dropn_cons
@[simp]
theorem dropn_think (s : WSeq α) (n) : drop (think s) n = (drop s n).think := by
induction n <;> simp [*, drop]
#align stream.wseq.dropn_think Stream'.WSeq.dropn_think
theorem dropn_add (s : WSeq α) (m) : ∀ n, drop s (m + n) = drop (drop s m) n
| 0 => rfl
| n + 1 => congr_arg tail (dropn_add s m n)
#align stream.wseq.dropn_add Stream'.WSeq.dropn_add
theorem dropn_tail (s : WSeq α) (n) : drop (tail s) n = drop s (n + 1) := by
rw [Nat.add_comm]
symm
apply dropn_add
#align stream.wseq.dropn_tail Stream'.WSeq.dropn_tail
theorem get?_add (s : WSeq α) (m n) : get? s (m + n) = get? (drop s m) n :=
congr_arg head (dropn_add _ _ _)
#align stream.wseq.nth_add Stream'.WSeq.get?_add
theorem get?_tail (s : WSeq α) (n) : get? (tail s) n = get? s (n + 1) :=
congr_arg head (dropn_tail _ _)
#align stream.wseq.nth_tail Stream'.WSeq.get?_tail
@[simp]
theorem join_nil : join nil = (nil : WSeq α) :=
Seq.join_nil
#align stream.wseq.join_nil Stream'.WSeq.join_nil
@[simp]
theorem join_think (S : WSeq (WSeq α)) : join (think S) = think (join S) := by
simp only [join, think]
dsimp only [(· <$> ·)]
simp [join, Seq1.ret]
#align stream.wseq.join_think Stream'.WSeq.join_think
@[simp]
theorem join_cons (s : WSeq α) (S) : join (cons s S) = think (append s (join S)) := by
simp only [join, think]
dsimp only [(· <$> ·)]
simp [join, cons, append]
#align stream.wseq.join_cons Stream'.WSeq.join_cons
@[simp]
theorem nil_append (s : WSeq α) : append nil s = s :=
Seq.nil_append _
#align stream.wseq.nil_append Stream'.WSeq.nil_append
@[simp]
theorem cons_append (a : α) (s t) : append (cons a s) t = cons a (append s t) :=
Seq.cons_append _ _ _
#align stream.wseq.cons_append Stream'.WSeq.cons_append
@[simp]
theorem think_append (s t : WSeq α) : append (think s) t = think (append s t) :=
Seq.cons_append _ _ _
#align stream.wseq.think_append Stream'.WSeq.think_append
@[simp]
theorem append_nil (s : WSeq α) : append s nil = s :=
Seq.append_nil _
#align stream.wseq.append_nil Stream'.WSeq.append_nil
@[simp]
theorem append_assoc (s t u : WSeq α) : append (append s t) u = append s (append t u) :=
Seq.append_assoc _ _ _
#align stream.wseq.append_assoc Stream'.WSeq.append_assoc
/-- auxiliary definition of tail over weak sequences-/
@[simp]
def tail.aux : Option (α × WSeq α) → Computation (Option (α × WSeq α))
| none => Computation.pure none
| some (_, s) => destruct s
#align stream.wseq.tail.aux Stream'.WSeq.tail.aux
theorem destruct_tail (s : WSeq α) : destruct (tail s) = destruct s >>= tail.aux := by
simp only [tail, destruct_flatten, tail.aux]; rw [← bind_pure_comp, LawfulMonad.bind_assoc]
apply congr_arg; ext1 (_ | ⟨a, s⟩) <;> apply (@pure_bind Computation _ _ _ _ _ _).trans _ <;> simp
#align stream.wseq.destruct_tail Stream'.WSeq.destruct_tail
/-- auxiliary definition of drop over weak sequences-/
@[simp]
def drop.aux : ℕ → Option (α × WSeq α) → Computation (Option (α × WSeq α))
| 0 => Computation.pure
| n + 1 => fun a => tail.aux a >>= drop.aux n
#align stream.wseq.drop.aux Stream'.WSeq.drop.aux
theorem drop.aux_none : ∀ n, @drop.aux α n none = Computation.pure none
| 0 => rfl
| n + 1 =>
show Computation.bind (Computation.pure none) (drop.aux n) = Computation.pure none by
rw [ret_bind, drop.aux_none n]
#align stream.wseq.drop.aux_none Stream'.WSeq.drop.aux_none
theorem destruct_dropn : ∀ (s : WSeq α) (n), destruct (drop s n) = destruct s >>= drop.aux n
| s, 0 => (bind_pure' _).symm
| s, n + 1 => by
rw [← dropn_tail, destruct_dropn _ n, destruct_tail, LawfulMonad.bind_assoc]
rfl
#align stream.wseq.destruct_dropn Stream'.WSeq.destruct_dropn
theorem head_terminates_of_head_tail_terminates (s : WSeq α) [T : Terminates (head (tail s))] :
Terminates (head s) :=
(head_terminates_iff _).2 <| by
rcases (head_terminates_iff _).1 T with ⟨⟨a, h⟩⟩
simp? [tail] at h says simp only [tail, destruct_flatten] at h
rcases exists_of_mem_bind h with ⟨s', h1, _⟩
unfold Functor.map at h1
exact
let ⟨t, h3, _⟩ := Computation.exists_of_mem_map h1
Computation.terminates_of_mem h3
#align stream.wseq.head_terminates_of_head_tail_terminates Stream'.WSeq.head_terminates_of_head_tail_terminates
theorem destruct_some_of_destruct_tail_some {s : WSeq α} {a} (h : some a ∈ destruct (tail s)) :
∃ a', some a' ∈ destruct s := by
unfold tail Functor.map at h; simp only [destruct_flatten] at h
rcases exists_of_mem_bind h with ⟨t, tm, td⟩; clear h
rcases Computation.exists_of_mem_map tm with ⟨t', ht', ht2⟩; clear tm
cases' t' with t' <;> rw [← ht2] at td <;> simp only [destruct_nil] at td
· have := mem_unique td (ret_mem _)
contradiction
· exact ⟨_, ht'⟩
#align stream.wseq.destruct_some_of_destruct_tail_some Stream'.WSeq.destruct_some_of_destruct_tail_some
theorem head_some_of_head_tail_some {s : WSeq α} {a} (h : some a ∈ head (tail s)) :
∃ a', some a' ∈ head s := by
unfold head at h
rcases Computation.exists_of_mem_map h with ⟨o, md, e⟩; clear h
cases' o with o <;> [injection e; injection e with h']; clear h'
cases' destruct_some_of_destruct_tail_some md with a am
exact ⟨_, Computation.mem_map (@Prod.fst α (WSeq α) <$> ·) am⟩
#align stream.wseq.head_some_of_head_tail_some Stream'.WSeq.head_some_of_head_tail_some
theorem head_some_of_get?_some {s : WSeq α} {a n} (h : some a ∈ get? s n) :
∃ a', some a' ∈ head s := by
induction n generalizing a with
| zero => exact ⟨_, h⟩
| succ n IH =>
let ⟨a', h'⟩ := head_some_of_head_tail_some h
exact IH h'
#align stream.wseq.head_some_of_nth_some Stream'.WSeq.head_some_of_get?_some
instance productive_tail (s : WSeq α) [Productive s] : Productive (tail s) :=
⟨fun n => by rw [get?_tail]; infer_instance⟩
#align stream.wseq.productive_tail Stream'.WSeq.productive_tail
instance productive_dropn (s : WSeq α) [Productive s] (n) : Productive (drop s n) :=
⟨fun m => by rw [← get?_add]; infer_instance⟩
#align stream.wseq.productive_dropn Stream'.WSeq.productive_dropn
/-- Given a productive weak sequence, we can collapse all the `think`s to
produce a sequence. -/
def toSeq (s : WSeq α) [Productive s] : Seq α :=
⟨fun n => (get? s n).get,
fun {n} h => by
cases e : Computation.get (get? s (n + 1))
· assumption
have := Computation.mem_of_get_eq _ e
simp? [get?] at this h says simp only [get?] at this h
cases' head_some_of_head_tail_some this with a' h'
have := mem_unique h' (@Computation.mem_of_get_eq _ _ _ _ h)
contradiction⟩
#align stream.wseq.to_seq Stream'.WSeq.toSeq
theorem get?_terminates_le {s : WSeq α} {m n} (h : m ≤ n) :
Terminates (get? s n) → Terminates (get? s m) := by
induction' h with m' _ IH
exacts [id, fun T => IH (@head_terminates_of_head_tail_terminates _ _ T)]
#align stream.wseq.nth_terminates_le Stream'.WSeq.get?_terminates_le
theorem head_terminates_of_get?_terminates {s : WSeq α} {n} :
Terminates (get? s n) → Terminates (head s) :=
get?_terminates_le (Nat.zero_le n)
#align stream.wseq.head_terminates_of_nth_terminates Stream'.WSeq.head_terminates_of_get?_terminates
theorem destruct_terminates_of_get?_terminates {s : WSeq α} {n} (T : Terminates (get? s n)) :
Terminates (destruct s) :=
(head_terminates_iff _).1 <| head_terminates_of_get?_terminates T
#align stream.wseq.destruct_terminates_of_nth_terminates Stream'.WSeq.destruct_terminates_of_get?_terminates
theorem mem_rec_on {C : WSeq α → Prop} {a s} (M : a ∈ s) (h1 : ∀ b s', a = b ∨ C s' → C (cons b s'))
(h2 : ∀ s, C s → C (think s)) : C s := by
apply Seq.mem_rec_on M
intro o s' h; cases' o with b
· apply h2
cases h
· contradiction
· assumption
· apply h1
apply Or.imp_left _ h
intro h
injection h
#align stream.wseq.mem_rec_on Stream'.WSeq.mem_rec_on
@[simp]
theorem mem_think (s : WSeq α) (a) : a ∈ think s ↔ a ∈ s := by
cases' s with f al
change (some (some a) ∈ some none::f) ↔ some (some a) ∈ f
constructor <;> intro h
· apply (Stream'.eq_or_mem_of_mem_cons h).resolve_left
intro
injections
· apply Stream'.mem_cons_of_mem _ h
#align stream.wseq.mem_think Stream'.WSeq.mem_think
theorem eq_or_mem_iff_mem {s : WSeq α} {a a' s'} :
some (a', s') ∈ destruct s → (a ∈ s ↔ a = a' ∨ a ∈ s') := by
generalize e : destruct s = c; intro h
revert s
apply Computation.memRecOn h <;> [skip; intro c IH] <;> intro s <;>
induction' s using WSeq.recOn with x s s <;>
intro m <;>
have := congr_arg Computation.destruct m <;>
simp at this
· cases' this with i1 i2
rw [i1, i2]
cases' s' with f al
dsimp only [cons, (· ∈ ·), WSeq.Mem, Seq.Mem, Seq.cons]
have h_a_eq_a' : a = a' ↔ some (some a) = some (some a') := by simp
rw [h_a_eq_a']
refine ⟨Stream'.eq_or_mem_of_mem_cons, fun o => ?_⟩
· cases' o with e m
· rw [e]
apply Stream'.mem_cons
· exact Stream'.mem_cons_of_mem _ m
· simp [IH this]
#align stream.wseq.eq_or_mem_iff_mem Stream'.WSeq.eq_or_mem_iff_mem
@[simp]
theorem mem_cons_iff (s : WSeq α) (b) {a} : a ∈ cons b s ↔ a = b ∨ a ∈ s :=
eq_or_mem_iff_mem <| by simp [ret_mem]
#align stream.wseq.mem_cons_iff Stream'.WSeq.mem_cons_iff
theorem mem_cons_of_mem {s : WSeq α} (b) {a} (h : a ∈ s) : a ∈ cons b s :=
(mem_cons_iff _ _).2 (Or.inr h)
#align stream.wseq.mem_cons_of_mem Stream'.WSeq.mem_cons_of_mem
theorem mem_cons (s : WSeq α) (a) : a ∈ cons a s :=
(mem_cons_iff _ _).2 (Or.inl rfl)
#align stream.wseq.mem_cons Stream'.WSeq.mem_cons
theorem mem_of_mem_tail {s : WSeq α} {a} : a ∈ tail s → a ∈ s := by
intro h; have := h; cases' h with n e; revert s; simp only [Stream'.get]
induction' n with n IH <;> intro s <;> induction' s using WSeq.recOn with x s s <;>
simp <;> intro m e <;>
injections
· exact Or.inr m
· exact Or.inr m
· apply IH m
rw [e]
cases tail s
rfl
#align stream.wseq.mem_of_mem_tail Stream'.WSeq.mem_of_mem_tail
theorem mem_of_mem_dropn {s : WSeq α} {a} : ∀ {n}, a ∈ drop s n → a ∈ s
| 0, h => h
| n + 1, h => @mem_of_mem_dropn s a n (mem_of_mem_tail h)
#align stream.wseq.mem_of_mem_dropn Stream'.WSeq.mem_of_mem_dropn
theorem get?_mem {s : WSeq α} {a n} : some a ∈ get? s n → a ∈ s := by
revert s; induction' n with n IH <;> intro s h
· -- Porting note: This line is required to infer metavariables in
-- `Computation.exists_of_mem_map`.
dsimp only [get?, head] at h
rcases Computation.exists_of_mem_map h with ⟨o, h1, h2⟩
cases' o with o
· injection h2
injection h2 with h'
cases' o with a' s'
exact (eq_or_mem_iff_mem h1).2 (Or.inl h'.symm)
· have := @IH (tail s)
rw [get?_tail] at this
exact mem_of_mem_tail (this h)
#align stream.wseq.nth_mem Stream'.WSeq.get?_mem
theorem exists_get?_of_mem {s : WSeq α} {a} (h : a ∈ s) : ∃ n, some a ∈ get? s n := by
apply mem_rec_on h
· intro a' s' h
cases' h with h h
· exists 0
simp only [get?, drop, head_cons]
rw [h]
apply ret_mem
· cases' h with n h
exists n + 1
-- porting note (#10745): was `simp [get?]`.
simpa [get?]
· intro s' h
cases' h with n h
exists n
simp only [get?, dropn_think, head_think]
apply think_mem h
#align stream.wseq.exists_nth_of_mem Stream'.WSeq.exists_get?_of_mem
theorem exists_dropn_of_mem {s : WSeq α} {a} (h : a ∈ s) :
∃ n s', some (a, s') ∈ destruct (drop s n) :=
let ⟨n, h⟩ := exists_get?_of_mem h
⟨n, by
rcases (head_terminates_iff _).1 ⟨⟨_, h⟩⟩ with ⟨⟨o, om⟩⟩
have := Computation.mem_unique (Computation.mem_map _ om) h
cases' o with o
· injection this
injection this with i
cases' o with a' s'
dsimp at i
rw [i] at om
exact ⟨_, om⟩⟩
#align stream.wseq.exists_dropn_of_mem Stream'.WSeq.exists_dropn_of_mem
theorem liftRel_dropn_destruct {R : α → β → Prop} {s t} (H : LiftRel R s t) :
∀ n, Computation.LiftRel (LiftRelO R (LiftRel R)) (destruct (drop s n)) (destruct (drop t n))
| 0 => liftRel_destruct H
| n + 1 => by
simp only [LiftRelO, drop, Nat.add_eq, Nat.add_zero, destruct_tail, tail.aux]
apply liftRel_bind
· apply liftRel_dropn_destruct H n
exact fun {a b} o =>
match a, b, o with
| none, none, _ => by
-- Porting note: These 2 theorems should be excluded.
simp [-liftRel_pure_left, -liftRel_pure_right]
| some (a, s), some (b, t), ⟨_, h2⟩ => by simpa [tail.aux] using liftRel_destruct h2
#align stream.wseq.lift_rel_dropn_destruct Stream'.WSeq.liftRel_dropn_destruct
theorem exists_of_liftRel_left {R : α → β → Prop} {s t} (H : LiftRel R s t) {a} (h : a ∈ s) :
∃ b, b ∈ t ∧ R a b := by
let ⟨n, h⟩ := exists_get?_of_mem h
-- Porting note: This line is required to infer metavariables in
-- `Computation.exists_of_mem_map`.
dsimp only [get?, head] at h
let ⟨some (_, s'), sd, rfl⟩ := Computation.exists_of_mem_map h
let ⟨some (b, t'), td, ⟨ab, _⟩⟩ := (liftRel_dropn_destruct H n).left sd
exact ⟨b, get?_mem (Computation.mem_map (Prod.fst.{v, v} <$> ·) td), ab⟩
#align stream.wseq.exists_of_lift_rel_left Stream'.WSeq.exists_of_liftRel_left
theorem exists_of_liftRel_right {R : α → β → Prop} {s t} (H : LiftRel R s t) {b} (h : b ∈ t) :
∃ a, a ∈ s ∧ R a b := by rw [← LiftRel.swap] at H; exact exists_of_liftRel_left H h
#align stream.wseq.exists_of_lift_rel_right Stream'.WSeq.exists_of_liftRel_right
theorem head_terminates_of_mem {s : WSeq α} {a} (h : a ∈ s) : Terminates (head s) :=
let ⟨_, h⟩ := exists_get?_of_mem h
head_terminates_of_get?_terminates ⟨⟨_, h⟩⟩
#align stream.wseq.head_terminates_of_mem Stream'.WSeq.head_terminates_of_mem
theorem of_mem_append {s₁ s₂ : WSeq α} {a : α} : a ∈ append s₁ s₂ → a ∈ s₁ ∨ a ∈ s₂ :=
Seq.of_mem_append
#align stream.wseq.of_mem_append Stream'.WSeq.of_mem_append
theorem mem_append_left {s₁ s₂ : WSeq α} {a : α} : a ∈ s₁ → a ∈ append s₁ s₂ :=
Seq.mem_append_left
#align stream.wseq.mem_append_left Stream'.WSeq.mem_append_left
theorem exists_of_mem_map {f} {b : β} : ∀ {s : WSeq α}, b ∈ map f s → ∃ a, a ∈ s ∧ f a = b
| ⟨g, al⟩, h => by
let ⟨o, om, oe⟩ := Seq.exists_of_mem_map h
cases' o with a
· injection oe
injection oe with h'
exact ⟨a, om, h'⟩
#align stream.wseq.exists_of_mem_map Stream'.WSeq.exists_of_mem_map
@[simp]
theorem liftRel_nil (R : α → β → Prop) : LiftRel R nil nil := by
rw [liftRel_destruct_iff]
-- Porting note: These 2 theorems should be excluded.
simp [-liftRel_pure_left, -liftRel_pure_right]
#align stream.wseq.lift_rel_nil Stream'.WSeq.liftRel_nil
@[simp]
theorem liftRel_cons (R : α → β → Prop) (a b s t) :
LiftRel R (cons a s) (cons b t) ↔ R a b ∧ LiftRel R s t := by
rw [liftRel_destruct_iff]
-- Porting note: These 2 theorems should be excluded.
simp [-liftRel_pure_left, -liftRel_pure_right]
#align stream.wseq.lift_rel_cons Stream'.WSeq.liftRel_cons
@[simp]
theorem liftRel_think_left (R : α → β → Prop) (s t) : LiftRel R (think s) t ↔ LiftRel R s t := by
rw [liftRel_destruct_iff, liftRel_destruct_iff]; simp
#align stream.wseq.lift_rel_think_left Stream'.WSeq.liftRel_think_left
@[simp]
theorem liftRel_think_right (R : α → β → Prop) (s t) : LiftRel R s (think t) ↔ LiftRel R s t := by
rw [liftRel_destruct_iff, liftRel_destruct_iff]; simp
#align stream.wseq.lift_rel_think_right Stream'.WSeq.liftRel_think_right
theorem cons_congr {s t : WSeq α} (a : α) (h : s ~ʷ t) : cons a s ~ʷ cons a t := by
unfold Equiv; simpa using h
#align stream.wseq.cons_congr Stream'.WSeq.cons_congr
| Mathlib/Data/Seq/WSeq.lean | 1,119 | 1,119 | theorem think_equiv (s : WSeq α) : think s ~ʷ s := by | unfold Equiv; simpa using Equiv.refl _
|
/-
Copyright (c) 2020 Johan Commelin. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kevin Buzzard, Johan Commelin, Patrick Massot
-/
import Mathlib.Algebra.Order.Group.Basic
import Mathlib.Algebra.Order.Ring.Basic
import Mathlib.RingTheory.Ideal.Maps
import Mathlib.Tactic.TFAE
#align_import ring_theory.valuation.basic from "leanprover-community/mathlib"@"2196ab363eb097c008d4497125e0dde23fb36db2"
/-!
# The basics of valuation theory.
The basic theory of valuations (non-archimedean norms) on a commutative ring,
following T. Wedhorn's unpublished notes “Adic Spaces” ([wedhorn_adic]).
The definition of a valuation we use here is Definition 1.22 of [wedhorn_adic].
A valuation on a ring `R` is a monoid homomorphism `v` to a linearly ordered
commutative monoid with zero, that in addition satisfies the following two axioms:
* `v 0 = 0`
* `∀ x y, v (x + y) ≤ max (v x) (v y)`
`Valuation R Γ₀`is the type of valuations `R → Γ₀`, with a coercion to the underlying
function. If `v` is a valuation from `R` to `Γ₀` then the induced group
homomorphism `units(R) → Γ₀` is called `unit_map v`.
The equivalence "relation" `IsEquiv v₁ v₂ : Prop` defined in 1.27 of [wedhorn_adic] is not strictly
speaking a relation, because `v₁ : Valuation R Γ₁` and `v₂ : Valuation R Γ₂` might
not have the same type. This corresponds in ZFC to the set-theoretic difficulty
that the class of all valuations (as `Γ₀` varies) on a ring `R` is not a set.
The "relation" is however reflexive, symmetric and transitive in the obvious
sense. Note that we use 1.27(iii) of [wedhorn_adic] as the definition of equivalence.
## Main definitions
* `Valuation R Γ₀`, the type of valuations on `R` with values in `Γ₀`
* `Valuation.IsEquiv`, the heterogeneous equivalence relation on valuations
* `Valuation.supp`, the support of a valuation
* `AddValuation R Γ₀`, the type of additive valuations on `R` with values in a
linearly ordered additive commutative group with a top element, `Γ₀`.
## Implementation Details
`AddValuation R Γ₀` is implemented as `Valuation R (Multiplicative Γ₀)ᵒᵈ`.
## Notation
In the `DiscreteValuation` locale:
* `ℕₘ₀` is a shorthand for `WithZero (Multiplicative ℕ)`
* `ℤₘ₀` is a shorthand for `WithZero (Multiplicative ℤ)`
## TODO
If ever someone extends `Valuation`, we should fully comply to the `DFunLike` by migrating the
boilerplate lemmas to `ValuationClass`.
-/
open scoped Classical
open Function Ideal
noncomputable section
variable {K F R : Type*} [DivisionRing K]
section
variable (F R) (Γ₀ : Type*) [LinearOrderedCommMonoidWithZero Γ₀] [Ring R]
--porting note (#5171): removed @[nolint has_nonempty_instance]
/-- The type of `Γ₀`-valued valuations on `R`.
When you extend this structure, make sure to extend `ValuationClass`. -/
structure Valuation extends R →*₀ Γ₀ where
/-- The valuation of a a sum is less that the sum of the valuations -/
map_add_le_max' : ∀ x y, toFun (x + y) ≤ max (toFun x) (toFun y)
#align valuation Valuation
/-- `ValuationClass F α β` states that `F` is a type of valuations.
You should also extend this typeclass when you extend `Valuation`. -/
class ValuationClass (F) (R Γ₀ : outParam Type*) [LinearOrderedCommMonoidWithZero Γ₀] [Ring R]
[FunLike F R Γ₀]
extends MonoidWithZeroHomClass F R Γ₀ : Prop where
/-- The valuation of a a sum is less that the sum of the valuations -/
map_add_le_max (f : F) (x y : R) : f (x + y) ≤ max (f x) (f y)
#align valuation_class ValuationClass
export ValuationClass (map_add_le_max)
instance [FunLike F R Γ₀] [ValuationClass F R Γ₀] : CoeTC F (Valuation R Γ₀) :=
⟨fun f =>
{ toFun := f
map_one' := map_one f
map_zero' := map_zero f
map_mul' := map_mul f
map_add_le_max' := map_add_le_max f }⟩
end
namespace Valuation
variable {Γ₀ : Type*}
variable {Γ'₀ : Type*}
variable {Γ''₀ : Type*} [LinearOrderedCommMonoidWithZero Γ''₀]
section Basic
variable [Ring R]
section Monoid
variable [LinearOrderedCommMonoidWithZero Γ₀] [LinearOrderedCommMonoidWithZero Γ'₀]
instance : FunLike (Valuation R Γ₀) R Γ₀ where
coe f := f.toFun
coe_injective' f g h := by
obtain ⟨⟨⟨_,_⟩, _⟩, _⟩ := f
congr
instance : ValuationClass (Valuation R Γ₀) R Γ₀ where
map_mul f := f.map_mul'
map_one f := f.map_one'
map_zero f := f.map_zero'
map_add_le_max f := f.map_add_le_max'
@[simp]
theorem coe_mk (f : R →*₀ Γ₀) (h) : ⇑(Valuation.mk f h) = f := rfl
theorem toFun_eq_coe (v : Valuation R Γ₀) : v.toFun = v := rfl
#align valuation.to_fun_eq_coe Valuation.toFun_eq_coe
@[simp] -- Porting note: requested by simpNF as toFun_eq_coe LHS simplifies
theorem toMonoidWithZeroHom_coe_eq_coe (v : Valuation R Γ₀) :
(v.toMonoidWithZeroHom : R → Γ₀) = v := rfl
@[ext]
theorem ext {v₁ v₂ : Valuation R Γ₀} (h : ∀ r, v₁ r = v₂ r) : v₁ = v₂ :=
DFunLike.ext _ _ h
#align valuation.ext Valuation.ext
variable (v : Valuation R Γ₀) {x y z : R}
@[simp, norm_cast]
theorem coe_coe : ⇑(v : R →*₀ Γ₀) = v := rfl
#align valuation.coe_coe Valuation.coe_coe
-- @[simp] Porting note (#10618): simp can prove this
theorem map_zero : v 0 = 0 :=
v.map_zero'
#align valuation.map_zero Valuation.map_zero
-- @[simp] Porting note (#10618): simp can prove this
theorem map_one : v 1 = 1 :=
v.map_one'
#align valuation.map_one Valuation.map_one
-- @[simp] Porting note (#10618): simp can prove this
theorem map_mul : ∀ x y, v (x * y) = v x * v y :=
v.map_mul'
#align valuation.map_mul Valuation.map_mul
-- Porting note: LHS side simplified so created map_add'
theorem map_add : ∀ x y, v (x + y) ≤ max (v x) (v y) :=
v.map_add_le_max'
#align valuation.map_add Valuation.map_add
@[simp]
theorem map_add' : ∀ x y, v (x + y) ≤ v x ∨ v (x + y) ≤ v y := by
intro x y
rw [← le_max_iff, ← ge_iff_le]
apply map_add
theorem map_add_le {x y g} (hx : v x ≤ g) (hy : v y ≤ g) : v (x + y) ≤ g :=
le_trans (v.map_add x y) <| max_le hx hy
#align valuation.map_add_le Valuation.map_add_le
theorem map_add_lt {x y g} (hx : v x < g) (hy : v y < g) : v (x + y) < g :=
lt_of_le_of_lt (v.map_add x y) <| max_lt hx hy
#align valuation.map_add_lt Valuation.map_add_lt
| Mathlib/RingTheory/Valuation/Basic.lean | 187 | 193 | theorem map_sum_le {ι : Type*} {s : Finset ι} {f : ι → R} {g : Γ₀} (hf : ∀ i ∈ s, v (f i) ≤ g) :
v (∑ i ∈ s, f i) ≤ g := by |
refine
Finset.induction_on s (fun _ => v.map_zero ▸ zero_le')
(fun a s has ih hf => ?_) hf
rw [Finset.forall_mem_insert] at hf; rw [Finset.sum_insert has]
exact v.map_add_le hf.1 (ih hf.2)
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro, Yury Kudryashov
-/
import Mathlib.Order.Filter.Interval
import Mathlib.Order.Interval.Set.Pi
import Mathlib.Tactic.TFAE
import Mathlib.Tactic.NormNum
import Mathlib.Topology.Order.LeftRight
import Mathlib.Topology.Order.OrderClosed
#align_import topology.order.basic from "leanprover-community/mathlib"@"3efd324a3a31eaa40c9d5bfc669c4fafee5f9423"
/-!
# Theory of topology on ordered spaces
## Main definitions
The order topology on an ordered space is the topology generated by all open intervals (or
equivalently by those of the form `(-∞, a)` and `(b, +∞)`). We define it as `Preorder.topology α`.
However, we do *not* register it as an instance (as many existing ordered types already have
topologies, which would be equal but not definitionally equal to `Preorder.topology α`). Instead,
we introduce a class `OrderTopology α` (which is a `Prop`, also known as a mixin) saying that on
the type `α` having already a topological space structure and a preorder structure, the topological
structure is equal to the order topology.
We prove many basic properties of such topologies.
## Main statements
This file contains the proofs of the following facts. For exact requirements
(`OrderClosedTopology` vs `OrderTopology`, `Preorder` vs `PartialOrder` vs `LinearOrder` etc)
see their statements.
* `exists_Ioc_subset_of_mem_nhds`, `exists_Ico_subset_of_mem_nhds` : if `x < y`, then any
neighborhood of `x` includes an interval `[x, z)` for some `z ∈ (x, y]`, and any neighborhood
of `y` includes an interval `(z, y]` for some `z ∈ [x, y)`.
* `tendsto_of_tendsto_of_tendsto_of_le_of_le` : theorem known as squeeze theorem,
sandwich theorem, theorem of Carabinieri, and two policemen (and a drunk) theorem; if `g` and `h`
both converge to `a`, and eventually `g x ≤ f x ≤ h x`, then `f` converges to `a`.
## Implementation notes
We do _not_ register the order topology as an instance on a preorder (or even on a linear order).
Indeed, on many such spaces, a topology has already been constructed in a different way (think
of the discrete spaces `ℕ` or `ℤ`, or `ℝ` that could inherit a topology as the completion of `ℚ`),
and is in general not defeq to the one generated by the intervals. We make it available as a
definition `Preorder.topology α` though, that can be registered as an instance when necessary, or
for specific types.
-/
open Set Filter TopologicalSpace Topology Function
open OrderDual (toDual ofDual)
universe u v w
variable {α : Type u} {β : Type v} {γ : Type w}
-- Porting note (#11215): TODO: define `Preorder.topology` before `OrderTopology` and reuse the def
/-- The order topology on an ordered type is the topology generated by open intervals. We register
it on a preorder, but it is mostly interesting in linear orders, where it is also order-closed.
We define it as a mixin. If you want to introduce the order topology on a preorder, use
`Preorder.topology`. -/
class OrderTopology (α : Type*) [t : TopologicalSpace α] [Preorder α] : Prop where
/-- The topology is generated by open intervals `Set.Ioi _` and `Set.Iio _`. -/
topology_eq_generate_intervals : t = generateFrom { s | ∃ a, s = Ioi a ∨ s = Iio a }
#align order_topology OrderTopology
/-- (Order) topology on a partial order `α` generated by the subbase of open intervals
`(a, ∞) = { x ∣ a < x }, (-∞ , b) = {x ∣ x < b}` for all `a, b` in `α`. We do not register it as an
instance as many ordered sets are already endowed with the same topology, most often in a non-defeq
way though. Register as a local instance when necessary. -/
def Preorder.topology (α : Type*) [Preorder α] : TopologicalSpace α :=
generateFrom { s : Set α | ∃ a : α, s = { b : α | a < b } ∨ s = { b : α | b < a } }
#align preorder.topology Preorder.topology
section OrderTopology
section Preorder
variable [TopologicalSpace α] [Preorder α] [t : OrderTopology α]
instance : OrderTopology αᵒᵈ :=
⟨by
convert OrderTopology.topology_eq_generate_intervals (α := α) using 6
apply or_comm⟩
theorem isOpen_iff_generate_intervals {s : Set α} :
IsOpen s ↔ GenerateOpen { s | ∃ a, s = Ioi a ∨ s = Iio a } s := by
rw [t.topology_eq_generate_intervals]; rfl
#align is_open_iff_generate_intervals isOpen_iff_generate_intervals
theorem isOpen_lt' (a : α) : IsOpen { b : α | a < b } :=
isOpen_iff_generate_intervals.2 <| .basic _ ⟨a, .inl rfl⟩
#align is_open_lt' isOpen_lt'
theorem isOpen_gt' (a : α) : IsOpen { b : α | b < a } :=
isOpen_iff_generate_intervals.2 <| .basic _ ⟨a, .inr rfl⟩
#align is_open_gt' isOpen_gt'
theorem lt_mem_nhds {a b : α} (h : a < b) : ∀ᶠ x in 𝓝 b, a < x :=
(isOpen_lt' _).mem_nhds h
#align lt_mem_nhds lt_mem_nhds
theorem le_mem_nhds {a b : α} (h : a < b) : ∀ᶠ x in 𝓝 b, a ≤ x :=
(lt_mem_nhds h).mono fun _ => le_of_lt
#align le_mem_nhds le_mem_nhds
theorem gt_mem_nhds {a b : α} (h : a < b) : ∀ᶠ x in 𝓝 a, x < b :=
(isOpen_gt' _).mem_nhds h
#align gt_mem_nhds gt_mem_nhds
theorem ge_mem_nhds {a b : α} (h : a < b) : ∀ᶠ x in 𝓝 a, x ≤ b :=
(gt_mem_nhds h).mono fun _ => le_of_lt
#align ge_mem_nhds ge_mem_nhds
theorem nhds_eq_order (a : α) : 𝓝 a = (⨅ b ∈ Iio a, 𝓟 (Ioi b)) ⊓ ⨅ b ∈ Ioi a, 𝓟 (Iio b) := by
rw [t.topology_eq_generate_intervals, nhds_generateFrom]
simp_rw [mem_setOf_eq, @and_comm (a ∈ _), exists_or, or_and_right, iInf_or, iInf_and, iInf_exists,
iInf_inf_eq, iInf_comm (ι := Set α), iInf_iInf_eq_left, mem_Ioi, mem_Iio]
#align nhds_eq_order nhds_eq_order
theorem tendsto_order {f : β → α} {a : α} {x : Filter β} :
Tendsto f x (𝓝 a) ↔ (∀ a' < a, ∀ᶠ b in x, a' < f b) ∧ ∀ a' > a, ∀ᶠ b in x, f b < a' := by
simp only [nhds_eq_order a, tendsto_inf, tendsto_iInf, tendsto_principal]; rfl
#align tendsto_order tendsto_order
instance tendstoIccClassNhds (a : α) : TendstoIxxClass Icc (𝓝 a) (𝓝 a) := by
simp only [nhds_eq_order, iInf_subtype']
refine
((hasBasis_iInf_principal_finite _).inf (hasBasis_iInf_principal_finite _)).tendstoIxxClass
fun s _ => ?_
refine ((ordConnected_biInter ?_).inter (ordConnected_biInter ?_)).out <;> intro _ _
exacts [ordConnected_Ioi, ordConnected_Iio]
#align tendsto_Icc_class_nhds tendstoIccClassNhds
instance tendstoIcoClassNhds (a : α) : TendstoIxxClass Ico (𝓝 a) (𝓝 a) :=
tendstoIxxClass_of_subset fun _ _ => Ico_subset_Icc_self
#align tendsto_Ico_class_nhds tendstoIcoClassNhds
instance tendstoIocClassNhds (a : α) : TendstoIxxClass Ioc (𝓝 a) (𝓝 a) :=
tendstoIxxClass_of_subset fun _ _ => Ioc_subset_Icc_self
#align tendsto_Ioc_class_nhds tendstoIocClassNhds
instance tendstoIooClassNhds (a : α) : TendstoIxxClass Ioo (𝓝 a) (𝓝 a) :=
tendstoIxxClass_of_subset fun _ _ => Ioo_subset_Icc_self
#align tendsto_Ioo_class_nhds tendstoIooClassNhds
/-- **Squeeze theorem** (also known as **sandwich theorem**). This version assumes that inequalities
hold eventually for the filter. -/
theorem tendsto_of_tendsto_of_tendsto_of_le_of_le' {f g h : β → α} {b : Filter β} {a : α}
(hg : Tendsto g b (𝓝 a)) (hh : Tendsto h b (𝓝 a)) (hgf : ∀ᶠ b in b, g b ≤ f b)
(hfh : ∀ᶠ b in b, f b ≤ h b) : Tendsto f b (𝓝 a) :=
(hg.Icc hh).of_smallSets <| hgf.and hfh
#align tendsto_of_tendsto_of_tendsto_of_le_of_le' tendsto_of_tendsto_of_tendsto_of_le_of_le'
/-- **Squeeze theorem** (also known as **sandwich theorem**). This version assumes that inequalities
hold everywhere. -/
theorem tendsto_of_tendsto_of_tendsto_of_le_of_le {f g h : β → α} {b : Filter β} {a : α}
(hg : Tendsto g b (𝓝 a)) (hh : Tendsto h b (𝓝 a)) (hgf : g ≤ f) (hfh : f ≤ h) :
Tendsto f b (𝓝 a) :=
tendsto_of_tendsto_of_tendsto_of_le_of_le' hg hh (eventually_of_forall hgf)
(eventually_of_forall hfh)
#align tendsto_of_tendsto_of_tendsto_of_le_of_le tendsto_of_tendsto_of_tendsto_of_le_of_le
theorem nhds_order_unbounded {a : α} (hu : ∃ u, a < u) (hl : ∃ l, l < a) :
𝓝 a = ⨅ (l) (_ : l < a) (u) (_ : a < u), 𝓟 (Ioo l u) := by
simp only [nhds_eq_order, ← inf_biInf, ← biInf_inf, *, ← inf_principal, ← Ioi_inter_Iio]; rfl
#align nhds_order_unbounded nhds_order_unbounded
theorem tendsto_order_unbounded {f : β → α} {a : α} {x : Filter β} (hu : ∃ u, a < u)
(hl : ∃ l, l < a) (h : ∀ l u, l < a → a < u → ∀ᶠ b in x, l < f b ∧ f b < u) :
Tendsto f x (𝓝 a) := by
simp only [nhds_order_unbounded hu hl, tendsto_iInf, tendsto_principal]
exact fun l hl u => h l u hl
#align tendsto_order_unbounded tendsto_order_unbounded
end Preorder
instance tendstoIxxNhdsWithin {α : Type*} [TopologicalSpace α] (a : α) {s t : Set α}
{Ixx} [TendstoIxxClass Ixx (𝓝 a) (𝓝 a)] [TendstoIxxClass Ixx (𝓟 s) (𝓟 t)] :
TendstoIxxClass Ixx (𝓝[s] a) (𝓝[t] a) :=
Filter.tendstoIxxClass_inf
#align tendsto_Ixx_nhds_within tendstoIxxNhdsWithin
instance tendstoIccClassNhdsPi {ι : Type*} {α : ι → Type*} [∀ i, Preorder (α i)]
[∀ i, TopologicalSpace (α i)] [∀ i, OrderTopology (α i)] (f : ∀ i, α i) :
TendstoIxxClass Icc (𝓝 f) (𝓝 f) := by
constructor
conv in (𝓝 f).smallSets => rw [nhds_pi, Filter.pi]
simp only [smallSets_iInf, smallSets_comap_eq_comap_image, tendsto_iInf, tendsto_comap_iff]
intro i
have : Tendsto (fun g : ∀ i, α i => g i) (𝓝 f) (𝓝 (f i)) := (continuous_apply i).tendsto f
refine (this.comp tendsto_fst).Icc (this.comp tendsto_snd) |>.smallSets_mono ?_
filter_upwards [] using fun ⟨f, g⟩ ↦ image_subset_iff.mpr fun p hp ↦ ⟨hp.1 i, hp.2 i⟩
#align tendsto_Icc_class_nhds_pi tendstoIccClassNhdsPi
-- Porting note (#10756): new lemma
theorem induced_topology_le_preorder [Preorder α] [Preorder β] [TopologicalSpace β]
[OrderTopology β] {f : α → β} (hf : ∀ {x y}, f x < f y ↔ x < y) :
induced f ‹TopologicalSpace β› ≤ Preorder.topology α := by
let _ := Preorder.topology α; have : OrderTopology α := ⟨rfl⟩
refine le_of_nhds_le_nhds fun x => ?_
simp only [nhds_eq_order, nhds_induced, comap_inf, comap_iInf, comap_principal, Ioi, Iio, ← hf]
refine inf_le_inf (le_iInf₂ fun a ha => ?_) (le_iInf₂ fun a ha => ?_)
exacts [iInf₂_le (f a) ha, iInf₂_le (f a) ha]
-- Porting note (#10756): new lemma
theorem induced_topology_eq_preorder [Preorder α] [Preorder β] [TopologicalSpace β]
[OrderTopology β] {f : α → β} (hf : ∀ {x y}, f x < f y ↔ x < y)
(H₁ : ∀ {a b x}, b < f a → ¬(b < f x) → ∃ y, y < a ∧ b ≤ f y)
(H₂ : ∀ {a b x}, f a < b → ¬(f x < b) → ∃ y, a < y ∧ f y ≤ b) :
induced f ‹TopologicalSpace β› = Preorder.topology α := by
let _ := Preorder.topology α; have : OrderTopology α := ⟨rfl⟩
refine le_antisymm (induced_topology_le_preorder hf) ?_
refine le_of_nhds_le_nhds fun a => ?_
simp only [nhds_eq_order, nhds_induced, comap_inf, comap_iInf, comap_principal]
refine inf_le_inf (le_iInf₂ fun b hb => ?_) (le_iInf₂ fun b hb => ?_)
· rcases em (∃ x, ¬(b < f x)) with (⟨x, hx⟩ | hb)
· rcases H₁ hb hx with ⟨y, hya, hyb⟩
exact iInf₂_le_of_le y hya (principal_mono.2 fun z hz => hyb.trans_lt (hf.2 hz))
· push_neg at hb
exact le_principal_iff.2 (univ_mem' hb)
· rcases em (∃ x, ¬(f x < b)) with (⟨x, hx⟩ | hb)
· rcases H₂ hb hx with ⟨y, hya, hyb⟩
exact iInf₂_le_of_le y hya (principal_mono.2 fun z hz => (hf.2 hz).trans_le hyb)
· push_neg at hb
exact le_principal_iff.2 (univ_mem' hb)
theorem induced_orderTopology' {α : Type u} {β : Type v} [Preorder α] [ta : TopologicalSpace β]
[Preorder β] [OrderTopology β] (f : α → β) (hf : ∀ {x y}, f x < f y ↔ x < y)
(H₁ : ∀ {a x}, x < f a → ∃ b < a, x ≤ f b) (H₂ : ∀ {a x}, f a < x → ∃ b > a, f b ≤ x) :
@OrderTopology _ (induced f ta) _ :=
let _ := induced f ta
⟨induced_topology_eq_preorder hf (fun h _ => H₁ h) (fun h _ => H₂ h)⟩
#align induced_order_topology' induced_orderTopology'
theorem induced_orderTopology {α : Type u} {β : Type v} [Preorder α] [ta : TopologicalSpace β]
[Preorder β] [OrderTopology β] (f : α → β) (hf : ∀ {x y}, f x < f y ↔ x < y)
(H : ∀ {x y}, x < y → ∃ a, x < f a ∧ f a < y) : @OrderTopology _ (induced f ta) _ :=
induced_orderTopology' f (hf)
(fun xa => let ⟨b, xb, ba⟩ := H xa; ⟨b, hf.1 ba, le_of_lt xb⟩)
fun ax => let ⟨b, ab, bx⟩ := H ax; ⟨b, hf.1 ab, le_of_lt bx⟩
#align induced_order_topology induced_orderTopology
/-- The topology induced by a strictly monotone function with order-connected range is the preorder
topology. -/
nonrec theorem StrictMono.induced_topology_eq_preorder {α β : Type*} [LinearOrder α]
[LinearOrder β] [t : TopologicalSpace β] [OrderTopology β] {f : α → β}
(hf : StrictMono f) (hc : OrdConnected (range f)) : t.induced f = Preorder.topology α := by
refine induced_topology_eq_preorder hf.lt_iff_lt (fun h₁ h₂ => ?_) fun h₁ h₂ => ?_
· rcases hc.out (mem_range_self _) (mem_range_self _) ⟨not_lt.1 h₂, h₁.le⟩ with ⟨y, rfl⟩
exact ⟨y, hf.lt_iff_lt.1 h₁, le_rfl⟩
· rcases hc.out (mem_range_self _) (mem_range_self _) ⟨h₁.le, not_lt.1 h₂⟩ with ⟨y, rfl⟩
exact ⟨y, hf.lt_iff_lt.1 h₁, le_rfl⟩
/-- A strictly monotone function between linear orders with order topology is a topological
embedding provided that the range of `f` is order-connected. -/
theorem StrictMono.embedding_of_ordConnected {α β : Type*} [LinearOrder α] [LinearOrder β]
[TopologicalSpace α] [h : OrderTopology α] [TopologicalSpace β] [OrderTopology β] {f : α → β}
(hf : StrictMono f) (hc : OrdConnected (range f)) : Embedding f :=
⟨⟨h.1.trans <| Eq.symm <| hf.induced_topology_eq_preorder hc⟩, hf.injective⟩
/-- On a `Set.OrdConnected` subset of a linear order, the order topology for the restriction of the
order is the same as the restriction to the subset of the order topology. -/
instance orderTopology_of_ordConnected {α : Type u} [TopologicalSpace α] [LinearOrder α]
[OrderTopology α] {t : Set α} [ht : OrdConnected t] : OrderTopology t :=
⟨(Subtype.strictMono_coe t).induced_topology_eq_preorder <| by
rwa [← @Subtype.range_val _ t] at ht⟩
#align order_topology_of_ord_connected orderTopology_of_ordConnected
theorem nhdsWithin_Ici_eq'' [TopologicalSpace α] [Preorder α] [OrderTopology α] (a : α) :
𝓝[≥] a = (⨅ (u) (_ : a < u), 𝓟 (Iio u)) ⊓ 𝓟 (Ici a) := by
rw [nhdsWithin, nhds_eq_order]
refine le_antisymm (inf_le_inf_right _ inf_le_right) (le_inf (le_inf ?_ inf_le_left) inf_le_right)
exact inf_le_right.trans (le_iInf₂ fun l hl => principal_mono.2 <| Ici_subset_Ioi.2 hl)
#align nhds_within_Ici_eq'' nhdsWithin_Ici_eq''
theorem nhdsWithin_Iic_eq'' [TopologicalSpace α] [Preorder α] [OrderTopology α] (a : α) :
𝓝[≤] a = (⨅ l < a, 𝓟 (Ioi l)) ⊓ 𝓟 (Iic a) :=
nhdsWithin_Ici_eq'' (toDual a)
#align nhds_within_Iic_eq'' nhdsWithin_Iic_eq''
theorem nhdsWithin_Ici_eq' [TopologicalSpace α] [Preorder α] [OrderTopology α] {a : α}
(ha : ∃ u, a < u) : 𝓝[≥] a = ⨅ (u) (_ : a < u), 𝓟 (Ico a u) := by
simp only [nhdsWithin_Ici_eq'', biInf_inf ha, inf_principal, Iio_inter_Ici]
#align nhds_within_Ici_eq' nhdsWithin_Ici_eq'
theorem nhdsWithin_Iic_eq' [TopologicalSpace α] [Preorder α] [OrderTopology α] {a : α}
(ha : ∃ l, l < a) : 𝓝[≤] a = ⨅ l < a, 𝓟 (Ioc l a) := by
simp only [nhdsWithin_Iic_eq'', biInf_inf ha, inf_principal, Ioi_inter_Iic]
#align nhds_within_Iic_eq' nhdsWithin_Iic_eq'
theorem nhdsWithin_Ici_basis' [TopologicalSpace α] [LinearOrder α] [OrderTopology α] {a : α}
(ha : ∃ u, a < u) : (𝓝[≥] a).HasBasis (fun u => a < u) fun u => Ico a u :=
(nhdsWithin_Ici_eq' ha).symm ▸
hasBasis_biInf_principal
(fun b hb c hc => ⟨min b c, lt_min hb hc, Ico_subset_Ico_right (min_le_left _ _),
Ico_subset_Ico_right (min_le_right _ _)⟩)
ha
#align nhds_within_Ici_basis' nhdsWithin_Ici_basis'
theorem nhdsWithin_Iic_basis' [TopologicalSpace α] [LinearOrder α] [OrderTopology α] {a : α}
(ha : ∃ l, l < a) : (𝓝[≤] a).HasBasis (fun l => l < a) fun l => Ioc l a := by
convert nhdsWithin_Ici_basis' (α := αᵒᵈ) ha using 2
exact dual_Ico.symm
#align nhds_within_Iic_basis' nhdsWithin_Iic_basis'
theorem nhdsWithin_Ici_basis [TopologicalSpace α] [LinearOrder α] [OrderTopology α] [NoMaxOrder α]
(a : α) : (𝓝[≥] a).HasBasis (fun u => a < u) fun u => Ico a u :=
nhdsWithin_Ici_basis' (exists_gt a)
#align nhds_within_Ici_basis nhdsWithin_Ici_basis
theorem nhdsWithin_Iic_basis [TopologicalSpace α] [LinearOrder α] [OrderTopology α] [NoMinOrder α]
(a : α) : (𝓝[≤] a).HasBasis (fun l => l < a) fun l => Ioc l a :=
nhdsWithin_Iic_basis' (exists_lt a)
#align nhds_within_Iic_basis nhdsWithin_Iic_basis
| Mathlib/Topology/Order/Basic.lean | 322 | 323 | theorem nhds_top_order [TopologicalSpace α] [Preorder α] [OrderTop α] [OrderTopology α] :
𝓝 (⊤ : α) = ⨅ (l) (h₂ : l < ⊤), 𝓟 (Ioi l) := by | simp [nhds_eq_order (⊤ : α)]
|
/-
Copyright (c) 2015 Microsoft Corporation. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Leonardo de Moura
-/
import Mathlib.Data.Stream.Defs
import Mathlib.Logic.Function.Basic
import Mathlib.Init.Data.List.Basic
import Mathlib.Data.List.Basic
#align_import data.stream.init from "leanprover-community/mathlib"@"207cfac9fcd06138865b5d04f7091e46d9320432"
/-!
# Streams a.k.a. infinite lists a.k.a. infinite sequences
Porting note:
This file used to be in the core library. It was moved to `mathlib` and renamed to `init` to avoid
name clashes. -/
set_option autoImplicit true
open Nat Function Option
namespace Stream'
variable {α : Type u} {β : Type v} {δ : Type w}
instance [Inhabited α] : Inhabited (Stream' α) :=
⟨Stream'.const default⟩
protected theorem eta (s : Stream' α) : (head s::tail s) = s :=
funext fun i => by cases i <;> rfl
#align stream.eta Stream'.eta
@[ext]
protected theorem ext {s₁ s₂ : Stream' α} : (∀ n, get s₁ n = get s₂ n) → s₁ = s₂ :=
fun h => funext h
#align stream.ext Stream'.ext
@[simp]
theorem get_zero_cons (a : α) (s : Stream' α) : get (a::s) 0 = a :=
rfl
#align stream.nth_zero_cons Stream'.get_zero_cons
@[simp]
theorem head_cons (a : α) (s : Stream' α) : head (a::s) = a :=
rfl
#align stream.head_cons Stream'.head_cons
@[simp]
theorem tail_cons (a : α) (s : Stream' α) : tail (a::s) = s :=
rfl
#align stream.tail_cons Stream'.tail_cons
@[simp]
theorem get_drop (n m : Nat) (s : Stream' α) : get (drop m s) n = get s (n + m) :=
rfl
#align stream.nth_drop Stream'.get_drop
theorem tail_eq_drop (s : Stream' α) : tail s = drop 1 s :=
rfl
#align stream.tail_eq_drop Stream'.tail_eq_drop
@[simp]
theorem drop_drop (n m : Nat) (s : Stream' α) : drop n (drop m s) = drop (n + m) s := by
ext; simp [Nat.add_assoc]
#align stream.drop_drop Stream'.drop_drop
@[simp] theorem get_tail {s : Stream' α} : s.tail.get n = s.get (n + 1) := rfl
@[simp] theorem tail_drop' {s : Stream' α} : tail (drop i s) = s.drop (i+1) := by
ext; simp [Nat.add_comm, Nat.add_assoc, Nat.add_left_comm]
@[simp] theorem drop_tail' {s : Stream' α} : drop i (tail s) = s.drop (i+1) := rfl
theorem tail_drop (n : Nat) (s : Stream' α) : tail (drop n s) = drop n (tail s) := by simp
#align stream.tail_drop Stream'.tail_drop
theorem get_succ (n : Nat) (s : Stream' α) : get s (succ n) = get (tail s) n :=
rfl
#align stream.nth_succ Stream'.get_succ
@[simp]
theorem get_succ_cons (n : Nat) (s : Stream' α) (x : α) : get (x::s) n.succ = get s n :=
rfl
#align stream.nth_succ_cons Stream'.get_succ_cons
@[simp] theorem drop_zero {s : Stream' α} : s.drop 0 = s := rfl
theorem drop_succ (n : Nat) (s : Stream' α) : drop (succ n) s = drop n (tail s) :=
rfl
#align stream.drop_succ Stream'.drop_succ
theorem head_drop (a : Stream' α) (n : ℕ) : (a.drop n).head = a.get n := by simp
#align stream.head_drop Stream'.head_drop
theorem cons_injective2 : Function.Injective2 (cons : α → Stream' α → Stream' α) := fun x y s t h =>
⟨by rw [← get_zero_cons x s, h, get_zero_cons],
Stream'.ext fun n => by rw [← get_succ_cons n _ x, h, get_succ_cons]⟩
#align stream.cons_injective2 Stream'.cons_injective2
theorem cons_injective_left (s : Stream' α) : Function.Injective fun x => cons x s :=
cons_injective2.left _
#align stream.cons_injective_left Stream'.cons_injective_left
theorem cons_injective_right (x : α) : Function.Injective (cons x) :=
cons_injective2.right _
#align stream.cons_injective_right Stream'.cons_injective_right
theorem all_def (p : α → Prop) (s : Stream' α) : All p s = ∀ n, p (get s n) :=
rfl
#align stream.all_def Stream'.all_def
theorem any_def (p : α → Prop) (s : Stream' α) : Any p s = ∃ n, p (get s n) :=
rfl
#align stream.any_def Stream'.any_def
@[simp]
theorem mem_cons (a : α) (s : Stream' α) : a ∈ a::s :=
Exists.intro 0 rfl
#align stream.mem_cons Stream'.mem_cons
theorem mem_cons_of_mem {a : α} {s : Stream' α} (b : α) : a ∈ s → a ∈ b::s := fun ⟨n, h⟩ =>
Exists.intro (succ n) (by rw [get_succ, tail_cons, h])
#align stream.mem_cons_of_mem Stream'.mem_cons_of_mem
theorem eq_or_mem_of_mem_cons {a b : α} {s : Stream' α} : (a ∈ b::s) → a = b ∨ a ∈ s :=
fun ⟨n, h⟩ => by
cases' n with n'
· left
exact h
· right
rw [get_succ, tail_cons] at h
exact ⟨n', h⟩
#align stream.eq_or_mem_of_mem_cons Stream'.eq_or_mem_of_mem_cons
theorem mem_of_get_eq {n : Nat} {s : Stream' α} {a : α} : a = get s n → a ∈ s := fun h =>
Exists.intro n h
#align stream.mem_of_nth_eq Stream'.mem_of_get_eq
section Map
variable (f : α → β)
theorem drop_map (n : Nat) (s : Stream' α) : drop n (map f s) = map f (drop n s) :=
Stream'.ext fun _ => rfl
#align stream.drop_map Stream'.drop_map
@[simp]
theorem get_map (n : Nat) (s : Stream' α) : get (map f s) n = f (get s n) :=
rfl
#align stream.nth_map Stream'.get_map
theorem tail_map (s : Stream' α) : tail (map f s) = map f (tail s) := rfl
#align stream.tail_map Stream'.tail_map
@[simp]
theorem head_map (s : Stream' α) : head (map f s) = f (head s) :=
rfl
#align stream.head_map Stream'.head_map
theorem map_eq (s : Stream' α) : map f s = f (head s)::map f (tail s) := by
rw [← Stream'.eta (map f s), tail_map, head_map]
#align stream.map_eq Stream'.map_eq
theorem map_cons (a : α) (s : Stream' α) : map f (a::s) = f a::map f s := by
rw [← Stream'.eta (map f (a::s)), map_eq]; rfl
#align stream.map_cons Stream'.map_cons
@[simp]
theorem map_id (s : Stream' α) : map id s = s :=
rfl
#align stream.map_id Stream'.map_id
@[simp]
theorem map_map (g : β → δ) (f : α → β) (s : Stream' α) : map g (map f s) = map (g ∘ f) s :=
rfl
#align stream.map_map Stream'.map_map
@[simp]
theorem map_tail (s : Stream' α) : map f (tail s) = tail (map f s) :=
rfl
#align stream.map_tail Stream'.map_tail
theorem mem_map {a : α} {s : Stream' α} : a ∈ s → f a ∈ map f s := fun ⟨n, h⟩ =>
Exists.intro n (by rw [get_map, h])
#align stream.mem_map Stream'.mem_map
theorem exists_of_mem_map {f} {b : β} {s : Stream' α} : b ∈ map f s → ∃ a, a ∈ s ∧ f a = b :=
fun ⟨n, h⟩ => ⟨get s n, ⟨n, rfl⟩, h.symm⟩
#align stream.exists_of_mem_map Stream'.exists_of_mem_map
end Map
section Zip
variable (f : α → β → δ)
theorem drop_zip (n : Nat) (s₁ : Stream' α) (s₂ : Stream' β) :
drop n (zip f s₁ s₂) = zip f (drop n s₁) (drop n s₂) :=
Stream'.ext fun _ => rfl
#align stream.drop_zip Stream'.drop_zip
@[simp]
theorem get_zip (n : Nat) (s₁ : Stream' α) (s₂ : Stream' β) :
get (zip f s₁ s₂) n = f (get s₁ n) (get s₂ n) :=
rfl
#align stream.nth_zip Stream'.get_zip
theorem head_zip (s₁ : Stream' α) (s₂ : Stream' β) : head (zip f s₁ s₂) = f (head s₁) (head s₂) :=
rfl
#align stream.head_zip Stream'.head_zip
theorem tail_zip (s₁ : Stream' α) (s₂ : Stream' β) :
tail (zip f s₁ s₂) = zip f (tail s₁) (tail s₂) :=
rfl
#align stream.tail_zip Stream'.tail_zip
theorem zip_eq (s₁ : Stream' α) (s₂ : Stream' β) :
zip f s₁ s₂ = f (head s₁) (head s₂)::zip f (tail s₁) (tail s₂) := by
rw [← Stream'.eta (zip f s₁ s₂)]; rfl
#align stream.zip_eq Stream'.zip_eq
@[simp]
theorem get_enum (s : Stream' α) (n : ℕ) : get (enum s) n = (n, s.get n) :=
rfl
#align stream.nth_enum Stream'.get_enum
theorem enum_eq_zip (s : Stream' α) : enum s = zip Prod.mk nats s :=
rfl
#align stream.enum_eq_zip Stream'.enum_eq_zip
end Zip
@[simp]
theorem mem_const (a : α) : a ∈ const a :=
Exists.intro 0 rfl
#align stream.mem_const Stream'.mem_const
theorem const_eq (a : α) : const a = a::const a := by
apply Stream'.ext; intro n
cases n <;> rfl
#align stream.const_eq Stream'.const_eq
@[simp]
theorem tail_const (a : α) : tail (const a) = const a :=
suffices tail (a::const a) = const a by rwa [← const_eq] at this
rfl
#align stream.tail_const Stream'.tail_const
@[simp]
theorem map_const (f : α → β) (a : α) : map f (const a) = const (f a) :=
rfl
#align stream.map_const Stream'.map_const
@[simp]
theorem get_const (n : Nat) (a : α) : get (const a) n = a :=
rfl
#align stream.nth_const Stream'.get_const
@[simp]
theorem drop_const (n : Nat) (a : α) : drop n (const a) = const a :=
Stream'.ext fun _ => rfl
#align stream.drop_const Stream'.drop_const
@[simp]
theorem head_iterate (f : α → α) (a : α) : head (iterate f a) = a :=
rfl
#align stream.head_iterate Stream'.head_iterate
theorem get_succ_iterate' (n : Nat) (f : α → α) (a : α) :
get (iterate f a) (succ n) = f (get (iterate f a) n) := rfl
theorem tail_iterate (f : α → α) (a : α) : tail (iterate f a) = iterate f (f a) := by
ext n
rw [get_tail]
induction' n with n' ih
· rfl
· rw [get_succ_iterate', ih, get_succ_iterate']
#align stream.tail_iterate Stream'.tail_iterate
theorem iterate_eq (f : α → α) (a : α) : iterate f a = a::iterate f (f a) := by
rw [← Stream'.eta (iterate f a)]
rw [tail_iterate]; rfl
#align stream.iterate_eq Stream'.iterate_eq
@[simp]
theorem get_zero_iterate (f : α → α) (a : α) : get (iterate f a) 0 = a :=
rfl
#align stream.nth_zero_iterate Stream'.get_zero_iterate
theorem get_succ_iterate (n : Nat) (f : α → α) (a : α) :
get (iterate f a) (succ n) = get (iterate f (f a)) n := by rw [get_succ, tail_iterate]
#align stream.nth_succ_iterate Stream'.get_succ_iterate
section Bisim
variable (R : Stream' α → Stream' α → Prop)
/-- equivalence relation -/
local infixl:50 " ~ " => R
/-- Streams `s₁` and `s₂` are defined to be bisimulations if
their heads are equal and tails are bisimulations. -/
def IsBisimulation :=
∀ ⦃s₁ s₂⦄, s₁ ~ s₂ →
head s₁ = head s₂ ∧ tail s₁ ~ tail s₂
#align stream.is_bisimulation Stream'.IsBisimulation
theorem get_of_bisim (bisim : IsBisimulation R) :
∀ {s₁ s₂} (n), s₁ ~ s₂ → get s₁ n = get s₂ n ∧ drop (n + 1) s₁ ~ drop (n + 1) s₂
| _, _, 0, h => bisim h
| _, _, n + 1, h =>
match bisim h with
| ⟨_, trel⟩ => get_of_bisim bisim n trel
#align stream.nth_of_bisim Stream'.get_of_bisim
-- If two streams are bisimilar, then they are equal
theorem eq_of_bisim (bisim : IsBisimulation R) : ∀ {s₁ s₂}, s₁ ~ s₂ → s₁ = s₂ := fun r =>
Stream'.ext fun n => And.left (get_of_bisim R bisim n r)
#align stream.eq_of_bisim Stream'.eq_of_bisim
end Bisim
theorem bisim_simple (s₁ s₂ : Stream' α) :
head s₁ = head s₂ → s₁ = tail s₁ → s₂ = tail s₂ → s₁ = s₂ := fun hh ht₁ ht₂ =>
eq_of_bisim (fun s₁ s₂ => head s₁ = head s₂ ∧ s₁ = tail s₁ ∧ s₂ = tail s₂)
(fun s₁ s₂ ⟨h₁, h₂, h₃⟩ => by
constructor
· exact h₁
rw [← h₂, ← h₃]
(repeat' constructor) <;> assumption)
(And.intro hh (And.intro ht₁ ht₂))
#align stream.bisim_simple Stream'.bisim_simple
theorem coinduction {s₁ s₂ : Stream' α} :
head s₁ = head s₂ →
(∀ (β : Type u) (fr : Stream' α → β),
fr s₁ = fr s₂ → fr (tail s₁) = fr (tail s₂)) → s₁ = s₂ :=
fun hh ht =>
eq_of_bisim
(fun s₁ s₂ =>
head s₁ = head s₂ ∧
∀ (β : Type u) (fr : Stream' α → β), fr s₁ = fr s₂ → fr (tail s₁) = fr (tail s₂))
(fun s₁ s₂ h =>
have h₁ : head s₁ = head s₂ := And.left h
have h₂ : head (tail s₁) = head (tail s₂) := And.right h α (@head α) h₁
have h₃ :
∀ (β : Type u) (fr : Stream' α → β),
fr (tail s₁) = fr (tail s₂) → fr (tail (tail s₁)) = fr (tail (tail s₂)) :=
fun β fr => And.right h β fun s => fr (tail s)
And.intro h₁ (And.intro h₂ h₃))
(And.intro hh ht)
#align stream.coinduction Stream'.coinduction
@[simp]
theorem iterate_id (a : α) : iterate id a = const a :=
coinduction rfl fun β fr ch => by rw [tail_iterate, tail_const]; exact ch
#align stream.iterate_id Stream'.iterate_id
theorem map_iterate (f : α → α) (a : α) : iterate f (f a) = map f (iterate f a) := by
funext n
induction' n with n' ih
· rfl
· unfold map iterate get
rw [map, get] at ih
rw [iterate]
exact congrArg f ih
#align stream.map_iterate Stream'.map_iterate
section Corec
theorem corec_def (f : α → β) (g : α → α) (a : α) : corec f g a = map f (iterate g a) :=
rfl
#align stream.corec_def Stream'.corec_def
theorem corec_eq (f : α → β) (g : α → α) (a : α) : corec f g a = f a::corec f g (g a) := by
rw [corec_def, map_eq, head_iterate, tail_iterate]; rfl
#align stream.corec_eq Stream'.corec_eq
theorem corec_id_id_eq_const (a : α) : corec id id a = const a := by
rw [corec_def, map_id, iterate_id]
#align stream.corec_id_id_eq_const Stream'.corec_id_id_eq_const
theorem corec_id_f_eq_iterate (f : α → α) (a : α) : corec id f a = iterate f a :=
rfl
#align stream.corec_id_f_eq_iterate Stream'.corec_id_f_eq_iterate
end Corec
section Corec'
theorem corec'_eq (f : α → β × α) (a : α) : corec' f a = (f a).1::corec' f (f a).2 :=
corec_eq _ _ _
#align stream.corec'_eq Stream'.corec'_eq
end Corec'
theorem unfolds_eq (g : α → β) (f : α → α) (a : α) : unfolds g f a = g a::unfolds g f (f a) := by
unfold unfolds; rw [corec_eq]
#align stream.unfolds_eq Stream'.unfolds_eq
theorem get_unfolds_head_tail : ∀ (n : Nat) (s : Stream' α),
get (unfolds head tail s) n = get s n := by
intro n; induction' n with n' ih
· intro s
rfl
· intro s
rw [get_succ, get_succ, unfolds_eq, tail_cons, ih]
#align stream.nth_unfolds_head_tail Stream'.get_unfolds_head_tail
theorem unfolds_head_eq : ∀ s : Stream' α, unfolds head tail s = s := fun s =>
Stream'.ext fun n => get_unfolds_head_tail n s
#align stream.unfolds_head_eq Stream'.unfolds_head_eq
theorem interleave_eq (s₁ s₂ : Stream' α) : s₁ ⋈ s₂ = head s₁::head s₂::(tail s₁ ⋈ tail s₂) := by
let t := tail s₁ ⋈ tail s₂
show s₁ ⋈ s₂ = head s₁::head s₂::t
unfold interleave; unfold corecOn; rw [corec_eq]; dsimp; rw [corec_eq]; rfl
#align stream.interleave_eq Stream'.interleave_eq
theorem tail_interleave (s₁ s₂ : Stream' α) : tail (s₁ ⋈ s₂) = s₂ ⋈ tail s₁ := by
unfold interleave corecOn; rw [corec_eq]; rfl
#align stream.tail_interleave Stream'.tail_interleave
theorem interleave_tail_tail (s₁ s₂ : Stream' α) : tail s₁ ⋈ tail s₂ = tail (tail (s₁ ⋈ s₂)) := by
rw [interleave_eq s₁ s₂]; rfl
#align stream.interleave_tail_tail Stream'.interleave_tail_tail
theorem get_interleave_left : ∀ (n : Nat) (s₁ s₂ : Stream' α),
get (s₁ ⋈ s₂) (2 * n) = get s₁ n
| 0, s₁, s₂ => rfl
| n + 1, s₁, s₂ => by
change get (s₁ ⋈ s₂) (succ (succ (2 * n))) = get s₁ (succ n)
rw [get_succ, get_succ, interleave_eq, tail_cons, tail_cons]
rw [get_interleave_left n (tail s₁) (tail s₂)]
rfl
#align stream.nth_interleave_left Stream'.get_interleave_left
theorem get_interleave_right : ∀ (n : Nat) (s₁ s₂ : Stream' α),
get (s₁ ⋈ s₂) (2 * n + 1) = get s₂ n
| 0, s₁, s₂ => rfl
| n + 1, s₁, s₂ => by
change get (s₁ ⋈ s₂) (succ (succ (2 * n + 1))) = get s₂ (succ n)
rw [get_succ, get_succ, interleave_eq, tail_cons, tail_cons,
get_interleave_right n (tail s₁) (tail s₂)]
rfl
#align stream.nth_interleave_right Stream'.get_interleave_right
theorem mem_interleave_left {a : α} {s₁ : Stream' α} (s₂ : Stream' α) : a ∈ s₁ → a ∈ s₁ ⋈ s₂ :=
fun ⟨n, h⟩ => Exists.intro (2 * n) (by rw [h, get_interleave_left])
#align stream.mem_interleave_left Stream'.mem_interleave_left
theorem mem_interleave_right {a : α} {s₁ : Stream' α} (s₂ : Stream' α) : a ∈ s₂ → a ∈ s₁ ⋈ s₂ :=
fun ⟨n, h⟩ => Exists.intro (2 * n + 1) (by rw [h, get_interleave_right])
#align stream.mem_interleave_right Stream'.mem_interleave_right
theorem odd_eq (s : Stream' α) : odd s = even (tail s) :=
rfl
#align stream.odd_eq Stream'.odd_eq
@[simp]
theorem head_even (s : Stream' α) : head (even s) = head s :=
rfl
#align stream.head_even Stream'.head_even
theorem tail_even (s : Stream' α) : tail (even s) = even (tail (tail s)) := by
unfold even
rw [corec_eq]
rfl
#align stream.tail_even Stream'.tail_even
theorem even_cons_cons (a₁ a₂ : α) (s : Stream' α) : even (a₁::a₂::s) = a₁::even s := by
unfold even
rw [corec_eq]; rfl
#align stream.even_cons_cons Stream'.even_cons_cons
theorem even_tail (s : Stream' α) : even (tail s) = odd s :=
rfl
#align stream.even_tail Stream'.even_tail
theorem even_interleave (s₁ s₂ : Stream' α) : even (s₁ ⋈ s₂) = s₁ :=
eq_of_bisim (fun s₁' s₁ => ∃ s₂, s₁' = even (s₁ ⋈ s₂))
(fun s₁' s₁ ⟨s₂, h₁⟩ => by
rw [h₁]
constructor
· rfl
· exact ⟨tail s₂, by rw [interleave_eq, even_cons_cons, tail_cons]⟩)
(Exists.intro s₂ rfl)
#align stream.even_interleave Stream'.even_interleave
theorem interleave_even_odd (s₁ : Stream' α) : even s₁ ⋈ odd s₁ = s₁ :=
eq_of_bisim (fun s' s => s' = even s ⋈ odd s)
(fun s' s (h : s' = even s ⋈ odd s) => by
rw [h]; constructor
· rfl
· simp [odd_eq, odd_eq, tail_interleave, tail_even])
rfl
#align stream.interleave_even_odd Stream'.interleave_even_odd
theorem get_even : ∀ (n : Nat) (s : Stream' α), get (even s) n = get s (2 * n)
| 0, s => rfl
| succ n, s => by
change get (even s) (succ n) = get s (succ (succ (2 * n)))
rw [get_succ, get_succ, tail_even, get_even n]; rfl
#align stream.nth_even Stream'.get_even
theorem get_odd : ∀ (n : Nat) (s : Stream' α), get (odd s) n = get s (2 * n + 1) := fun n s => by
rw [odd_eq, get_even]; rfl
#align stream.nth_odd Stream'.get_odd
theorem mem_of_mem_even (a : α) (s : Stream' α) : a ∈ even s → a ∈ s := fun ⟨n, h⟩ =>
Exists.intro (2 * n) (by rw [h, get_even])
#align stream.mem_of_mem_even Stream'.mem_of_mem_even
theorem mem_of_mem_odd (a : α) (s : Stream' α) : a ∈ odd s → a ∈ s := fun ⟨n, h⟩ =>
Exists.intro (2 * n + 1) (by rw [h, get_odd])
#align stream.mem_of_mem_odd Stream'.mem_of_mem_odd
theorem nil_append_stream (s : Stream' α) : appendStream' [] s = s :=
rfl
#align stream.nil_append_stream Stream'.nil_append_stream
theorem cons_append_stream (a : α) (l : List α) (s : Stream' α) :
appendStream' (a::l) s = a::appendStream' l s :=
rfl
#align stream.cons_append_stream Stream'.cons_append_stream
theorem append_append_stream : ∀ (l₁ l₂ : List α) (s : Stream' α),
l₁ ++ l₂ ++ₛ s = l₁ ++ₛ (l₂ ++ₛ s)
| [], l₂, s => rfl
| List.cons a l₁, l₂, s => by
rw [List.cons_append, cons_append_stream, cons_append_stream, append_append_stream l₁]
#align stream.append_append_stream Stream'.append_append_stream
theorem map_append_stream (f : α → β) :
∀ (l : List α) (s : Stream' α), map f (l ++ₛ s) = List.map f l ++ₛ map f s
| [], s => rfl
| List.cons a l, s => by
rw [cons_append_stream, List.map_cons, map_cons, cons_append_stream, map_append_stream f l]
#align stream.map_append_stream Stream'.map_append_stream
theorem drop_append_stream : ∀ (l : List α) (s : Stream' α), drop l.length (l ++ₛ s) = s
| [], s => by rfl
| List.cons a l, s => by
rw [List.length_cons, drop_succ, cons_append_stream, tail_cons, drop_append_stream l s]
#align stream.drop_append_stream Stream'.drop_append_stream
theorem append_stream_head_tail (s : Stream' α) : [head s] ++ₛ tail s = s := by
rw [cons_append_stream, nil_append_stream, Stream'.eta]
#align stream.append_stream_head_tail Stream'.append_stream_head_tail
theorem mem_append_stream_right : ∀ {a : α} (l : List α) {s : Stream' α}, a ∈ s → a ∈ l ++ₛ s
| _, [], _, h => h
| a, List.cons _ l, s, h =>
have ih : a ∈ l ++ₛ s := mem_append_stream_right l h
mem_cons_of_mem _ ih
#align stream.mem_append_stream_right Stream'.mem_append_stream_right
theorem mem_append_stream_left : ∀ {a : α} {l : List α} (s : Stream' α), a ∈ l → a ∈ l ++ₛ s
| _, [], _, h => absurd h (List.not_mem_nil _)
| a, List.cons b l, s, h =>
Or.elim (List.eq_or_mem_of_mem_cons h) (fun aeqb : a = b => Exists.intro 0 aeqb)
fun ainl : a ∈ l => mem_cons_of_mem b (mem_append_stream_left s ainl)
#align stream.mem_append_stream_left Stream'.mem_append_stream_left
@[simp]
theorem take_zero (s : Stream' α) : take 0 s = [] :=
rfl
#align stream.take_zero Stream'.take_zero
-- This lemma used to be simp, but we removed it from the simp set because:
-- 1) It duplicates the (often large) `s` term, resulting in large tactic states.
-- 2) It conflicts with the very useful `dropLast_take` lemma below (causing nonconfluence).
theorem take_succ (n : Nat) (s : Stream' α) : take (succ n) s = head s::take n (tail s) :=
rfl
#align stream.take_succ Stream'.take_succ
@[simp] theorem take_succ_cons (n : Nat) (s : Stream' α) : take (n+1) (a::s) = a :: take n s := rfl
theorem take_succ' {s : Stream' α} : ∀ n, s.take (n+1) = s.take n ++ [s.get n]
| 0 => rfl
| n+1 => by rw [take_succ, take_succ' n, ← List.cons_append, ← take_succ, get_tail]
@[simp]
theorem length_take (n : ℕ) (s : Stream' α) : (take n s).length = n := by
induction n generalizing s <;> simp [*, take_succ]
#align stream.length_take Stream'.length_take
@[simp]
theorem take_take {s : Stream' α} : ∀ {m n}, (s.take n).take m = s.take (min n m)
| 0, n => by rw [Nat.min_zero, List.take_zero, take_zero]
| m, 0 => by rw [Nat.zero_min, take_zero, List.take_nil]
| m+1, n+1 => by rw [take_succ, List.take_cons, Nat.succ_min_succ, take_succ, take_take]
@[simp] theorem concat_take_get {s : Stream' α} : s.take n ++ [s.get n] = s.take (n+1) :=
(take_succ' n).symm
theorem get?_take {s : Stream' α} : ∀ {k n}, k < n → (s.take n).get? k = s.get k
| 0, n+1, _ => rfl
| k+1, n+1, h => by rw [take_succ, List.get?, get?_take (Nat.lt_of_succ_lt_succ h), get_succ]
theorem get?_take_succ (n : Nat) (s : Stream' α) :
List.get? (take (succ n) s) n = some (get s n) :=
get?_take (Nat.lt_succ_self n)
#align stream.nth_take_succ Stream'.get?_take_succ
@[simp] theorem dropLast_take {xs : Stream' α} :
(Stream'.take n xs).dropLast = Stream'.take (n-1) xs := by
cases n with
| zero => simp
| succ n => rw [take_succ', List.dropLast_concat, Nat.add_one_sub_one]
@[simp]
theorem append_take_drop : ∀ (n : Nat) (s : Stream' α),
appendStream' (take n s) (drop n s) = s := by
intro n
induction' n with n' ih
· intro s
rfl
· intro s
rw [take_succ, drop_succ, cons_append_stream, ih (tail s), Stream'.eta]
#align stream.append_take_drop Stream'.append_take_drop
-- Take theorem reduces a proof of equality of infinite streams to an
-- induction over all their finite approximations.
theorem take_theorem (s₁ s₂ : Stream' α) : (∀ n : Nat, take n s₁ = take n s₂) → s₁ = s₂ := by
intro h; apply Stream'.ext; intro n
induction' n with n _
· have aux := h 1
simp? [take] at aux says
simp only [take, List.cons.injEq, and_true] at aux
exact aux
· have h₁ : some (get s₁ (succ n)) = some (get s₂ (succ n)) := by
rw [← get?_take_succ, ← get?_take_succ, h (succ (succ n))]
injection h₁
#align stream.take_theorem Stream'.take_theorem
protected theorem cycle_g_cons (a : α) (a₁ : α) (l₁ : List α) (a₀ : α) (l₀ : List α) :
Stream'.cycleG (a, a₁::l₁, a₀, l₀) = (a₁, l₁, a₀, l₀) :=
rfl
#align stream.cycle_g_cons Stream'.cycle_g_cons
theorem cycle_eq : ∀ (l : List α) (h : l ≠ []), cycle l h = l ++ₛ cycle l h
| [], h => absurd rfl h
| List.cons a l, _ =>
have gen : ∀ l' a', corec Stream'.cycleF Stream'.cycleG (a', l', a, l) =
(a'::l') ++ₛ corec Stream'.cycleF Stream'.cycleG (a, l, a, l) := by
intro l'
induction' l' with a₁ l₁ ih
· intros
rw [corec_eq]
rfl
· intros
rw [corec_eq, Stream'.cycle_g_cons, ih a₁]
rfl
gen l a
#align stream.cycle_eq Stream'.cycle_eq
theorem mem_cycle {a : α} {l : List α} : ∀ h : l ≠ [], a ∈ l → a ∈ cycle l h := fun h ainl => by
rw [cycle_eq]; exact mem_append_stream_left _ ainl
#align stream.mem_cycle Stream'.mem_cycle
@[simp]
theorem cycle_singleton (a : α) : cycle [a] (by simp) = const a :=
coinduction rfl fun β fr ch => by rwa [cycle_eq, const_eq]
#align stream.cycle_singleton Stream'.cycle_singleton
theorem tails_eq (s : Stream' α) : tails s = tail s::tails (tail s) := by
unfold tails; rw [corec_eq]; rfl
#align stream.tails_eq Stream'.tails_eq
@[simp]
| Mathlib/Data/Stream/Init.lean | 674 | 679 | theorem get_tails : ∀ (n : Nat) (s : Stream' α), get (tails s) n = drop n (tail s) := by |
intro n; induction' n with n' ih
· intros
rfl
· intro s
rw [get_succ, drop_succ, tails_eq, tail_cons, ih]
|
/-
Copyright (c) 2020 Adam Topaz. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Adam Topaz
-/
import Mathlib.Algebra.FreeAlgebra
import Mathlib.Algebra.RingQuot
import Mathlib.Algebra.TrivSqZeroExt
import Mathlib.Algebra.Algebra.Operations
import Mathlib.LinearAlgebra.Multilinear.Basic
#align_import linear_algebra.tensor_algebra.basic from "leanprover-community/mathlib"@"b8d2eaa69d69ce8f03179a5cda774fc0cde984e4"
/-!
# Tensor Algebras
Given a commutative semiring `R`, and an `R`-module `M`, we construct the tensor algebra of `M`.
This is the free `R`-algebra generated (`R`-linearly) by the module `M`.
## Notation
1. `TensorAlgebra R M` is the tensor algebra itself. It is endowed with an R-algebra structure.
2. `TensorAlgebra.ι R` is the canonical R-linear map `M → TensorAlgebra R M`.
3. Given a linear map `f : M → A` to an R-algebra `A`, `lift R f` is the lift of `f` to an
`R`-algebra morphism `TensorAlgebra R M → A`.
## Theorems
1. `ι_comp_lift` states that the composition `(lift R f) ∘ (ι R)` is identical to `f`.
2. `lift_unique` states that whenever an R-algebra morphism `g : TensorAlgebra R M → A` is
given whose composition with `ι R` is `f`, then one has `g = lift R f`.
3. `hom_ext` is a variant of `lift_unique` in the form of an extensionality theorem.
4. `lift_comp_ι` is a combination of `ι_comp_lift` and `lift_unique`. It states that the lift
of the composition of an algebra morphism with `ι` is the algebra morphism itself.
## Implementation details
As noted above, the tensor algebra of `M` is constructed as the free `R`-algebra generated by `M`,
modulo the additional relations making the inclusion of `M` into an `R`-linear map.
-/
variable (R : Type*) [CommSemiring R]
variable (M : Type*) [AddCommMonoid M] [Module R M]
namespace TensorAlgebra
/-- An inductively defined relation on `Pre R M` used to force the initial algebra structure on
the associated quotient.
-/
inductive Rel : FreeAlgebra R M → FreeAlgebra R M → Prop
-- force `ι` to be linear
| add {a b : M} : Rel (FreeAlgebra.ι R (a + b)) (FreeAlgebra.ι R a + FreeAlgebra.ι R b)
| smul {r : R} {a : M} :
Rel (FreeAlgebra.ι R (r • a)) (algebraMap R (FreeAlgebra R M) r * FreeAlgebra.ι R a)
#align tensor_algebra.rel TensorAlgebra.Rel
end TensorAlgebra
/-- The tensor algebra of the module `M` over the commutative semiring `R`.
-/
def TensorAlgebra :=
RingQuot (TensorAlgebra.Rel R M)
#align tensor_algebra TensorAlgebra
-- Porting note: Expanded `deriving Inhabited, Semiring, Algebra`
instance : Inhabited (TensorAlgebra R M) := RingQuot.instInhabited _
instance : Semiring (TensorAlgebra R M) := RingQuot.instSemiring _
-- `IsScalarTower` is not needed, but the instance isn't really canonical without it.
@[nolint unusedArguments]
instance instAlgebra {R A M} [CommSemiring R] [AddCommMonoid M] [CommSemiring A]
[Algebra R A] [Module R M] [Module A M]
[IsScalarTower R A M] :
Algebra R (TensorAlgebra A M) :=
RingQuot.instAlgebra _
-- verify there is no diamond
-- but doesn't work at `reducible_and_instances` #10906
example : (algebraNat : Algebra ℕ (TensorAlgebra R M)) = instAlgebra := rfl
instance {R S A M} [CommSemiring R] [CommSemiring S] [AddCommMonoid M] [CommSemiring A]
[Algebra R A] [Algebra S A] [Module R M] [Module S M] [Module A M]
[IsScalarTower R A M] [IsScalarTower S A M] :
SMulCommClass R S (TensorAlgebra A M) :=
RingQuot.instSMulCommClass _
instance {R S A M} [CommSemiring R] [CommSemiring S] [AddCommMonoid M] [CommSemiring A]
[SMul R S] [Algebra R A] [Algebra S A] [Module R M] [Module S M] [Module A M]
[IsScalarTower R A M] [IsScalarTower S A M] [IsScalarTower R S A] :
IsScalarTower R S (TensorAlgebra A M) :=
RingQuot.instIsScalarTower _
namespace TensorAlgebra
instance {S : Type*} [CommRing S] [Module S M] : Ring (TensorAlgebra S M) :=
RingQuot.instRing (Rel S M)
-- verify there is no diamond
-- but doesn't work at `reducible_and_instances` #10906
variable (S M : Type) [CommRing S] [AddCommGroup M] [Module S M] in
example : (algebraInt _ : Algebra ℤ (TensorAlgebra S M)) = instAlgebra := rfl
variable {M}
/-- The canonical linear map `M →ₗ[R] TensorAlgebra R M`.
-/
irreducible_def ι : M →ₗ[R] TensorAlgebra R M :=
{ toFun := fun m => RingQuot.mkAlgHom R _ (FreeAlgebra.ι R m)
map_add' := fun x y => by
rw [← (RingQuot.mkAlgHom R (Rel R M)).map_add]
exact RingQuot.mkAlgHom_rel R Rel.add
map_smul' := fun r x => by
rw [← (RingQuot.mkAlgHom R (Rel R M)).map_smul]
exact RingQuot.mkAlgHom_rel R Rel.smul }
#align tensor_algebra.ι TensorAlgebra.ι
theorem ringQuot_mkAlgHom_freeAlgebra_ι_eq_ι (m : M) :
RingQuot.mkAlgHom R (Rel R M) (FreeAlgebra.ι R m) = ι R m := by
rw [ι]
rfl
#align tensor_algebra.ring_quot_mk_alg_hom_free_algebra_ι_eq_ι TensorAlgebra.ringQuot_mkAlgHom_freeAlgebra_ι_eq_ι
-- Porting note: Changed `irreducible_def` to `def` to get `@[simps symm_apply]` to work
/-- Given a linear map `f : M → A` where `A` is an `R`-algebra, `lift R f` is the unique lift
of `f` to a morphism of `R`-algebras `TensorAlgebra R M → A`.
-/
@[simps symm_apply]
def lift {A : Type*} [Semiring A] [Algebra R A] : (M →ₗ[R] A) ≃ (TensorAlgebra R M →ₐ[R] A) :=
{ toFun :=
RingQuot.liftAlgHom R ∘ fun f =>
⟨FreeAlgebra.lift R (⇑f), fun x y (h : Rel R M x y) => by
induction h <;>
simp only [Algebra.smul_def, FreeAlgebra.lift_ι_apply, LinearMap.map_smulₛₗ,
RingHom.id_apply, map_mul, AlgHom.commutes, map_add]⟩
invFun := fun F => F.toLinearMap.comp (ι R)
left_inv := fun f => by
rw [ι]
ext1 x
exact (RingQuot.liftAlgHom_mkAlgHom_apply _ _ _ _).trans (FreeAlgebra.lift_ι_apply f x)
right_inv := fun F =>
RingQuot.ringQuot_ext' _ _ _ <|
FreeAlgebra.hom_ext <|
funext fun x => by
rw [ι]
exact
(RingQuot.liftAlgHom_mkAlgHom_apply _ _ _ _).trans (FreeAlgebra.lift_ι_apply _ _) }
#align tensor_algebra.lift TensorAlgebra.lift
variable {R}
@[simp]
| Mathlib/LinearAlgebra/TensorAlgebra/Basic.lean | 153 | 155 | theorem ι_comp_lift {A : Type*} [Semiring A] [Algebra R A] (f : M →ₗ[R] A) :
(lift R f).toLinearMap.comp (ι R) = f := by |
convert (lift R).symm_apply_apply f
|
/-
Copyright (c) 2021 Anne Baanen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anne Baanen
-/
import Mathlib.GroupTheory.QuotientGroup
import Mathlib.RingTheory.DedekindDomain.Ideal
#align_import ring_theory.class_group from "leanprover-community/mathlib"@"565eb991e264d0db702722b4bde52ee5173c9950"
/-!
# The ideal class group
This file defines the ideal class group `ClassGroup R` of fractional ideals of `R`
inside its field of fractions.
## Main definitions
- `toPrincipalIdeal` sends an invertible `x : K` to an invertible fractional ideal
- `ClassGroup` is the quotient of invertible fractional ideals modulo `toPrincipalIdeal.range`
- `ClassGroup.mk0` sends a nonzero integral ideal in a Dedekind domain to its class
## Main results
- `ClassGroup.mk0_eq_mk0_iff` shows the equivalence with the "classical" definition,
where `I ~ J` iff `x I = y J` for `x y ≠ (0 : R)`
## Implementation details
The definition of `ClassGroup R` involves `FractionRing R`. However, the API should be completely
identical no matter the choice of field of fractions for `R`.
-/
variable {R K L : Type*} [CommRing R]
variable [Field K] [Field L] [DecidableEq L]
variable [Algebra R K] [IsFractionRing R K]
variable [Algebra K L] [FiniteDimensional K L]
variable [Algebra R L] [IsScalarTower R K L]
open scoped nonZeroDivisors
open IsLocalization IsFractionRing FractionalIdeal Units
section
variable (R K)
/-- `toPrincipalIdeal R K x` sends `x ≠ 0 : K` to the fractional `R`-ideal generated by `x` -/
irreducible_def toPrincipalIdeal : Kˣ →* (FractionalIdeal R⁰ K)ˣ :=
{ toFun := fun x =>
⟨spanSingleton _ x, spanSingleton _ x⁻¹, by
simp only [spanSingleton_one, Units.mul_inv', spanSingleton_mul_spanSingleton], by
simp only [spanSingleton_one, Units.inv_mul', spanSingleton_mul_spanSingleton]⟩
map_mul' := fun x y =>
ext (by simp only [Units.val_mk, Units.val_mul, spanSingleton_mul_spanSingleton])
map_one' := ext (by simp only [spanSingleton_one, Units.val_mk, Units.val_one]) }
#align to_principal_ideal toPrincipalIdeal
variable {R K}
@[simp]
theorem coe_toPrincipalIdeal (x : Kˣ) :
(toPrincipalIdeal R K x : FractionalIdeal R⁰ K) = spanSingleton _ (x : K) := by
simp only [toPrincipalIdeal]; rfl
#align coe_to_principal_ideal coe_toPrincipalIdeal
@[simp]
theorem toPrincipalIdeal_eq_iff {I : (FractionalIdeal R⁰ K)ˣ} {x : Kˣ} :
toPrincipalIdeal R K x = I ↔ spanSingleton R⁰ (x : K) = I := by
simp only [toPrincipalIdeal]; exact Units.ext_iff
#align to_principal_ideal_eq_iff toPrincipalIdeal_eq_iff
theorem mem_principal_ideals_iff {I : (FractionalIdeal R⁰ K)ˣ} :
I ∈ (toPrincipalIdeal R K).range ↔ ∃ x : K, spanSingleton R⁰ x = I := by
simp only [MonoidHom.mem_range, toPrincipalIdeal_eq_iff]
constructor <;> rintro ⟨x, hx⟩
· exact ⟨x, hx⟩
· refine ⟨Units.mk0 x ?_, hx⟩
rintro rfl
simp [I.ne_zero.symm] at hx
#align mem_principal_ideals_iff mem_principal_ideals_iff
instance PrincipalIdeals.normal : (toPrincipalIdeal R K).range.Normal :=
Subgroup.normal_of_comm _
#align principal_ideals.normal PrincipalIdeals.normal
end
variable (R)
variable [IsDomain R]
/-- The ideal class group of `R` is the group of invertible fractional ideals
modulo the principal ideals. -/
def ClassGroup :=
(FractionalIdeal R⁰ (FractionRing R))ˣ ⧸ (toPrincipalIdeal R (FractionRing R)).range
#align class_group ClassGroup
noncomputable instance : CommGroup (ClassGroup R) :=
QuotientGroup.Quotient.commGroup (toPrincipalIdeal R (FractionRing R)).range
noncomputable instance : Inhabited (ClassGroup R) := ⟨1⟩
variable {R}
/-- Send a nonzero fractional ideal to the corresponding class in the class group. -/
noncomputable def ClassGroup.mk : (FractionalIdeal R⁰ K)ˣ →* ClassGroup R :=
(QuotientGroup.mk' (toPrincipalIdeal R (FractionRing R)).range).comp
(Units.map (FractionalIdeal.canonicalEquiv R⁰ K (FractionRing R)))
#align class_group.mk ClassGroup.mk
-- Can't be `@[simp]` because it can't figure out the quotient relation.
theorem ClassGroup.Quot_mk_eq_mk (I : (FractionalIdeal R⁰ (FractionRing R))ˣ) :
Quot.mk _ I = ClassGroup.mk I := by
rw [ClassGroup.mk, canonicalEquiv_self, RingEquiv.coe_monoidHom_refl, Units.map_id]
-- This used to be `rw`, but we need `erw` after leanprover/lean4#2644
erw [MonoidHom.comp_apply]
rw [MonoidHom.id_apply, QuotientGroup.mk'_apply]
rfl
theorem ClassGroup.mk_eq_mk {I J : (FractionalIdeal R⁰ <| FractionRing R)ˣ} :
ClassGroup.mk I = ClassGroup.mk J ↔
∃ x : (FractionRing R)ˣ, I * toPrincipalIdeal R (FractionRing R) x = J := by
erw [QuotientGroup.mk'_eq_mk', canonicalEquiv_self, Units.map_id, Set.exists_range_iff]
rfl
#align class_group.mk_eq_mk ClassGroup.mk_eq_mk
theorem ClassGroup.mk_eq_mk_of_coe_ideal {I J : (FractionalIdeal R⁰ <| FractionRing R)ˣ}
{I' J' : Ideal R} (hI : (I : FractionalIdeal R⁰ <| FractionRing R) = I')
(hJ : (J : FractionalIdeal R⁰ <| FractionRing R) = J') :
ClassGroup.mk I = ClassGroup.mk J ↔
∃ x y : R, x ≠ 0 ∧ y ≠ 0 ∧ Ideal.span {x} * I' = Ideal.span {y} * J' := by
rw [ClassGroup.mk_eq_mk]
constructor
· rintro ⟨x, rfl⟩
rw [Units.val_mul, hI, coe_toPrincipalIdeal, mul_comm,
spanSingleton_mul_coeIdeal_eq_coeIdeal] at hJ
exact ⟨_, _, sec_fst_ne_zero (R := R) le_rfl x.ne_zero,
sec_snd_ne_zero (R := R) le_rfl (x : FractionRing R), hJ⟩
· rintro ⟨x, y, hx, hy, h⟩
have : IsUnit (mk' (FractionRing R) x ⟨y, mem_nonZeroDivisors_of_ne_zero hy⟩) := by
simpa only [isUnit_iff_ne_zero, ne_eq, mk'_eq_zero_iff_eq_zero] using hx
refine ⟨this.unit, ?_⟩
rw [mul_comm, ← Units.eq_iff, Units.val_mul, coe_toPrincipalIdeal]
convert
(mk'_mul_coeIdeal_eq_coeIdeal (FractionRing R) <| mem_nonZeroDivisors_of_ne_zero hy).2 h
#align class_group.mk_eq_mk_of_coe_ideal ClassGroup.mk_eq_mk_of_coe_ideal
theorem ClassGroup.mk_eq_one_of_coe_ideal {I : (FractionalIdeal R⁰ <| FractionRing R)ˣ}
{I' : Ideal R} (hI : (I : FractionalIdeal R⁰ <| FractionRing R) = I') :
ClassGroup.mk I = 1 ↔ ∃ x : R, x ≠ 0 ∧ I' = Ideal.span {x} := by
rw [← _root_.map_one (ClassGroup.mk (R := R) (K := FractionRing R)),
ClassGroup.mk_eq_mk_of_coe_ideal hI (?_ : _ = ↑(⊤ : Ideal R))]
any_goals rfl
constructor
· rintro ⟨x, y, hx, hy, h⟩
rw [Ideal.mul_top] at h
rcases Ideal.mem_span_singleton_mul.mp ((Ideal.span_singleton_le_iff_mem _).mp h.ge) with
⟨i, _hi, rfl⟩
rw [← Ideal.span_singleton_mul_span_singleton, Ideal.span_singleton_mul_right_inj hx] at h
exact ⟨i, right_ne_zero_of_mul hy, h⟩
· rintro ⟨x, hx, rfl⟩
exact ⟨1, x, one_ne_zero, hx, by rw [Ideal.span_singleton_one, Ideal.top_mul, Ideal.mul_top]⟩
#align class_group.mk_eq_one_of_coe_ideal ClassGroup.mk_eq_one_of_coe_ideal
variable (K)
/-- Induction principle for the class group: to show something holds for all `x : ClassGroup R`,
we can choose a fraction field `K` and show it holds for the equivalence class of each
`I : FractionalIdeal R⁰ K`. -/
@[elab_as_elim]
theorem ClassGroup.induction {P : ClassGroup R → Prop}
(h : ∀ I : (FractionalIdeal R⁰ K)ˣ, P (ClassGroup.mk I)) (x : ClassGroup R) : P x :=
QuotientGroup.induction_on x fun I => by
have : I = (Units.mapEquiv (canonicalEquiv R⁰ K (FractionRing R)).toMulEquiv)
(Units.mapEquiv (canonicalEquiv R⁰ (FractionRing R) K).toMulEquiv I) := by
simp [← Units.eq_iff]
rw [congr_arg (QuotientGroup.mk (s := (toPrincipalIdeal R (FractionRing R)).range)) this]
exact h _
#align class_group.induction ClassGroup.induction
/-- The definition of the class group does not depend on the choice of field of fractions. -/
noncomputable def ClassGroup.equiv :
ClassGroup R ≃* (FractionalIdeal R⁰ K)ˣ ⧸ (toPrincipalIdeal R K).range := by
haveI : Subgroup.map
(Units.mapEquiv (canonicalEquiv R⁰ (FractionRing R) K).toMulEquiv).toMonoidHom
(toPrincipalIdeal R (FractionRing R)).range = (toPrincipalIdeal R K).range := by
ext I
simp only [Subgroup.mem_map, mem_principal_ideals_iff]
constructor
· rintro ⟨I, ⟨x, hx⟩, rfl⟩
refine ⟨FractionRing.algEquiv R K x, ?_⟩
simp only [RingEquiv.toMulEquiv_eq_coe, MulEquiv.coe_toMonoidHom, coe_mapEquiv, ← hx,
RingEquiv.coe_toMulEquiv, canonicalEquiv_spanSingleton]
rfl
· rintro ⟨x, hx⟩
refine ⟨Units.mapEquiv (canonicalEquiv R⁰ K (FractionRing R)).toMulEquiv I,
⟨(FractionRing.algEquiv R K).symm x, ?_⟩, Units.ext ?_⟩
· simp only [RingEquiv.toMulEquiv_eq_coe, coe_mapEquiv, ← hx, RingEquiv.coe_toMulEquiv,
canonicalEquiv_spanSingleton]
rfl
· simp only [RingEquiv.toMulEquiv_eq_coe, MulEquiv.coe_toMonoidHom, coe_mapEquiv,
RingEquiv.coe_toMulEquiv, canonicalEquiv_canonicalEquiv, canonicalEquiv_self,
RingEquiv.refl_apply]
exact @QuotientGroup.congr (FractionalIdeal R⁰ (FractionRing R))ˣ _ (FractionalIdeal R⁰ K)ˣ _
(toPrincipalIdeal R (FractionRing R)).range (toPrincipalIdeal R K).range _ _
(Units.mapEquiv (FractionalIdeal.canonicalEquiv R⁰ (FractionRing R) K).toMulEquiv) this
#align class_group.equiv ClassGroup.equiv
@[simp]
theorem ClassGroup.equiv_mk (K' : Type*) [Field K'] [Algebra R K'] [IsFractionRing R K']
(I : (FractionalIdeal R⁰ K)ˣ) :
ClassGroup.equiv K' (ClassGroup.mk I) =
QuotientGroup.mk' _ (Units.mapEquiv (↑(FractionalIdeal.canonicalEquiv R⁰ K K')) I) := by
-- This used to be `rw`, but we need `erw` after leanprover/lean4#2644
erw [ClassGroup.equiv, ClassGroup.mk, MonoidHom.comp_apply, QuotientGroup.congr_mk']
congr
rw [← Units.eq_iff, Units.coe_mapEquiv, Units.coe_mapEquiv, Units.coe_map]
exact FractionalIdeal.canonicalEquiv_canonicalEquiv _ _ _ _ _
#align class_group.equiv_mk ClassGroup.equiv_mk
@[simp]
theorem ClassGroup.mk_canonicalEquiv (K' : Type*) [Field K'] [Algebra R K'] [IsFractionRing R K']
(I : (FractionalIdeal R⁰ K)ˣ) :
ClassGroup.mk (Units.map (↑(canonicalEquiv R⁰ K K')) I : (FractionalIdeal R⁰ K')ˣ) =
ClassGroup.mk I := by
-- This used to be `rw`, but we need `erw` after leanprover/lean4#2644
erw [ClassGroup.mk, MonoidHom.comp_apply, ← MonoidHom.comp_apply (Units.map _),
← Units.map_comp, ← RingEquiv.coe_monoidHom_trans,
FractionalIdeal.canonicalEquiv_trans_canonicalEquiv]
rfl
#align class_group.mk_canonical_equiv ClassGroup.mk_canonicalEquiv
/-- Send a nonzero integral ideal to an invertible fractional ideal. -/
noncomputable def FractionalIdeal.mk0 [IsDedekindDomain R] :
(Ideal R)⁰ →* (FractionalIdeal R⁰ K)ˣ where
toFun I := Units.mk0 I (coeIdeal_ne_zero.mpr <| mem_nonZeroDivisors_iff_ne_zero.mp I.2)
map_one' := by simp
map_mul' x y := by simp
#align fractional_ideal.mk0 FractionalIdeal.mk0
@[simp]
theorem FractionalIdeal.coe_mk0 [IsDedekindDomain R] (I : (Ideal R)⁰) :
(FractionalIdeal.mk0 K I : FractionalIdeal R⁰ K) = I := rfl
#align fractional_ideal.coe_mk0 FractionalIdeal.coe_mk0
theorem FractionalIdeal.canonicalEquiv_mk0 [IsDedekindDomain R] (K' : Type*) [Field K']
[Algebra R K'] [IsFractionRing R K'] (I : (Ideal R)⁰) :
FractionalIdeal.canonicalEquiv R⁰ K K' (FractionalIdeal.mk0 K I) =
FractionalIdeal.mk0 K' I := by
simp only [FractionalIdeal.coe_mk0, FractionalIdeal.canonicalEquiv_coeIdeal]
#align fractional_ideal.canonical_equiv_mk0 FractionalIdeal.canonicalEquiv_mk0
@[simp]
theorem FractionalIdeal.map_canonicalEquiv_mk0 [IsDedekindDomain R] (K' : Type*) [Field K']
[Algebra R K'] [IsFractionRing R K'] (I : (Ideal R)⁰) :
Units.map (↑(FractionalIdeal.canonicalEquiv R⁰ K K')) (FractionalIdeal.mk0 K I) =
FractionalIdeal.mk0 K' I :=
Units.ext (FractionalIdeal.canonicalEquiv_mk0 K K' I)
#align fractional_ideal.map_canonical_equiv_mk0 FractionalIdeal.map_canonicalEquiv_mk0
/-- Send a nonzero ideal to the corresponding class in the class group. -/
noncomputable def ClassGroup.mk0 [IsDedekindDomain R] : (Ideal R)⁰ →* ClassGroup R :=
ClassGroup.mk.comp (FractionalIdeal.mk0 (FractionRing R))
#align class_group.mk0 ClassGroup.mk0
@[simp]
theorem ClassGroup.mk_mk0 [IsDedekindDomain R] (I : (Ideal R)⁰) :
ClassGroup.mk (FractionalIdeal.mk0 K I) = ClassGroup.mk0 I := by
rw [ClassGroup.mk0, MonoidHom.comp_apply, ← ClassGroup.mk_canonicalEquiv K (FractionRing R),
FractionalIdeal.map_canonicalEquiv_mk0]
#align class_group.mk_mk0 ClassGroup.mk_mk0
@[simp]
theorem ClassGroup.equiv_mk0 [IsDedekindDomain R] (I : (Ideal R)⁰) :
ClassGroup.equiv K (ClassGroup.mk0 I) =
QuotientGroup.mk' (toPrincipalIdeal R K).range (FractionalIdeal.mk0 K I) := by
rw [ClassGroup.mk0, MonoidHom.comp_apply, ClassGroup.equiv_mk]
congr 1
simp [← Units.eq_iff]
#align class_group.equiv_mk0 ClassGroup.equiv_mk0
theorem ClassGroup.mk0_eq_mk0_iff_exists_fraction_ring [IsDedekindDomain R] {I J : (Ideal R)⁰} :
ClassGroup.mk0 I =
ClassGroup.mk0 J ↔ ∃ (x : _) (_ : x ≠ (0 : K)), spanSingleton R⁰ x * I = J := by
refine (ClassGroup.equiv K).injective.eq_iff.symm.trans ?_
simp only [ClassGroup.equiv_mk0, QuotientGroup.mk'_eq_mk', mem_principal_ideals_iff,
Units.ext_iff, Units.val_mul, FractionalIdeal.coe_mk0, exists_prop]
constructor
· rintro ⟨X, ⟨x, hX⟩, hx⟩
refine ⟨x, ?_, ?_⟩
· rintro rfl; simp [X.ne_zero.symm] at hX
simpa only [hX, mul_comm] using hx
· rintro ⟨x, hx, eq_J⟩
refine ⟨Units.mk0 _ (spanSingleton_ne_zero_iff.mpr hx), ⟨x, rfl⟩, ?_⟩
simpa only [mul_comm] using eq_J
#align class_group.mk0_eq_mk0_iff_exists_fraction_ring ClassGroup.mk0_eq_mk0_iff_exists_fraction_ring
variable {K}
theorem ClassGroup.mk0_eq_mk0_iff [IsDedekindDomain R] {I J : (Ideal R)⁰} :
ClassGroup.mk0 I = ClassGroup.mk0 J ↔
∃ (x y : R) (_hx : x ≠ 0) (_hy : y ≠ 0), Ideal.span {x} * (I : Ideal R) =
Ideal.span {y} * J := by
refine (ClassGroup.mk0_eq_mk0_iff_exists_fraction_ring (FractionRing R)).trans ⟨?_, ?_⟩
· rintro ⟨z, hz, h⟩
obtain ⟨x, ⟨y, hy⟩, rfl⟩ := IsLocalization.mk'_surjective R⁰ z
refine ⟨x, y, ?_, mem_nonZeroDivisors_iff_ne_zero.mp hy, ?_⟩
· rintro hx; apply hz
rw [hx, IsFractionRing.mk'_eq_div, _root_.map_zero, zero_div]
· exact (FractionalIdeal.mk'_mul_coeIdeal_eq_coeIdeal _ hy).mp h
· rintro ⟨x, y, hx, hy, h⟩
have hy' : y ∈ R⁰ := mem_nonZeroDivisors_iff_ne_zero.mpr hy
refine ⟨IsLocalization.mk' _ x ⟨y, hy'⟩, ?_, ?_⟩
· contrapose! hx
rwa [mk'_eq_iff_eq_mul, zero_mul, ← (algebraMap R (FractionRing R)).map_zero,
(IsFractionRing.injective R (FractionRing R)).eq_iff] at hx
· exact (FractionalIdeal.mk'_mul_coeIdeal_eq_coeIdeal _ hy').mpr h
#align class_group.mk0_eq_mk0_iff ClassGroup.mk0_eq_mk0_iff
/-- Maps a nonzero fractional ideal to an integral representative in the class group. -/
noncomputable def ClassGroup.integralRep (I : FractionalIdeal R⁰ (FractionRing R)) :
Ideal R := I.num
theorem ClassGroup.integralRep_mem_nonZeroDivisors
{I : FractionalIdeal R⁰ (FractionRing R)} (hI : I ≠ 0) :
I.num ∈ (Ideal R)⁰ := by
rwa [mem_nonZeroDivisors_iff_ne_zero, ne_eq, FractionalIdeal.num_eq_zero_iff]
theorem ClassGroup.mk0_integralRep [IsDedekindDomain R]
(I : (FractionalIdeal R⁰ (FractionRing R))ˣ) :
ClassGroup.mk0 ⟨ClassGroup.integralRep I, ClassGroup.integralRep_mem_nonZeroDivisors I.ne_zero⟩
= ClassGroup.mk I := by
rw [← ClassGroup.mk_mk0 (FractionRing R), eq_comm, ClassGroup.mk_eq_mk]
have fd_ne_zero : (algebraMap R (FractionRing R)) I.1.den ≠ 0 := by
exact IsFractionRing.to_map_ne_zero_of_mem_nonZeroDivisors (SetLike.coe_mem _)
refine ⟨Units.mk0 (algebraMap R _ I.1.den) fd_ne_zero, ?_⟩
apply Units.ext
rw [mul_comm, val_mul, coe_toPrincipalIdeal, val_mk0]
exact FractionalIdeal.den_mul_self_eq_num' R⁰ (FractionRing R) I
theorem ClassGroup.mk0_surjective [IsDedekindDomain R] :
Function.Surjective (ClassGroup.mk0 : (Ideal R)⁰ → ClassGroup R) := by
rintro ⟨I⟩
refine ⟨⟨ClassGroup.integralRep I.1, ClassGroup.integralRep_mem_nonZeroDivisors I.ne_zero⟩, ?_⟩
rw [ClassGroup.mk0_integralRep, ClassGroup.Quot_mk_eq_mk]
#align class_group.mk0_surjective ClassGroup.mk0_surjective
theorem ClassGroup.mk_eq_one_iff {I : (FractionalIdeal R⁰ K)ˣ} :
ClassGroup.mk I = 1 ↔ (I : Submodule R K).IsPrincipal := by
rw [← (ClassGroup.equiv K).injective.eq_iff]
simp only [equiv_mk, canonicalEquiv_self, RingEquiv.coe_mulEquiv_refl, QuotientGroup.mk'_apply,
_root_.map_one, QuotientGroup.eq_one_iff, MonoidHom.mem_range, ext_iff, coe_toPrincipalIdeal,
coe_mapEquiv, MulEquiv.refl_apply]
refine ⟨fun ⟨x, hx⟩ => ⟨⟨x, by rw [← hx, coe_spanSingleton]⟩⟩, ?_⟩
intro hI
obtain ⟨x, hx⟩ := @Submodule.IsPrincipal.principal _ _ _ _ _ _ hI
have hx' : (I : FractionalIdeal R⁰ K) = spanSingleton R⁰ x := by
apply Subtype.coe_injective
simp only [val_eq_coe, hx, coe_spanSingleton]
refine ⟨Units.mk0 x ?_, ?_⟩
· intro x_eq; apply Units.ne_zero I; simp [hx', x_eq]
· simp [hx']
#align class_group.mk_eq_one_iff ClassGroup.mk_eq_one_iff
theorem ClassGroup.mk0_eq_one_iff [IsDedekindDomain R] {I : Ideal R} (hI : I ∈ (Ideal R)⁰) :
ClassGroup.mk0 ⟨I, hI⟩ = 1 ↔ I.IsPrincipal :=
ClassGroup.mk_eq_one_iff.trans (coeSubmodule_isPrincipal R _)
#align class_group.mk0_eq_one_iff ClassGroup.mk0_eq_one_iff
theorem ClassGroup.mk0_eq_mk0_inv_iff [IsDedekindDomain R] {I J : (Ideal R)⁰} :
ClassGroup.mk0 I = (ClassGroup.mk0 J)⁻¹ ↔
∃ x ≠ (0 : R), I * J = Ideal.span {x} := by
rw [eq_inv_iff_mul_eq_one, ← _root_.map_mul, ClassGroup.mk0_eq_one_iff,
Submodule.isPrincipal_iff, Submonoid.coe_mul]
refine ⟨fun ⟨a, ha⟩ ↦ ⟨a, ?_, ha⟩, fun ⟨a, _, ha⟩ ↦ ⟨a, ha⟩⟩
by_contra!
rw [this, Submodule.span_zero_singleton] at ha
exact nonZeroDivisors.coe_ne_zero _ <| J.prop _ ha
/-- The class group of principal ideal domain is finite (in fact a singleton).
See `ClassGroup.fintypeOfAdmissibleOfFinite` for a finiteness proof that works for rings of integers
of global fields.
-/
noncomputable instance [IsPrincipalIdealRing R] : Fintype (ClassGroup R) where
elems := {1}
complete := by
refine ClassGroup.induction (R := R) (FractionRing R) (fun I => ?_)
rw [Finset.mem_singleton]
exact ClassGroup.mk_eq_one_iff.mpr (I : FractionalIdeal R⁰ (FractionRing R)).isPrincipal
/-- The class number of a principal ideal domain is `1`. -/
theorem card_classGroup_eq_one [IsPrincipalIdealRing R] : Fintype.card (ClassGroup R) = 1 := by
rw [Fintype.card_eq_one_iff]
use 1
refine ClassGroup.induction (R := R) (FractionRing R) (fun I => ?_)
exact ClassGroup.mk_eq_one_iff.mpr (I : FractionalIdeal R⁰ (FractionRing R)).isPrincipal
#align card_class_group_eq_one card_classGroup_eq_one
/-- The class number is `1` iff the ring of integers is a principal ideal domain. -/
| Mathlib/RingTheory/ClassGroup.lean | 400 | 409 | theorem card_classGroup_eq_one_iff [IsDedekindDomain R] [Fintype (ClassGroup R)] :
Fintype.card (ClassGroup R) = 1 ↔ IsPrincipalIdealRing R := by |
constructor; swap; · intros; convert card_classGroup_eq_one (R := R)
rw [Fintype.card_eq_one_iff]
rintro ⟨I, hI⟩
have eq_one : ∀ J : ClassGroup R, J = 1 := fun J => (hI J).trans (hI 1).symm
refine ⟨fun I => ?_⟩
by_cases hI : I = ⊥
· rw [hI]; exact bot_isPrincipal
· exact (ClassGroup.mk0_eq_one_iff (mem_nonZeroDivisors_iff_ne_zero.mpr hI)).mp (eq_one _)
|
/-
Copyright (c) 2018 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Jens Wagemaker, Aaron Anderson
-/
import Mathlib.Algebra.BigOperators.Associated
import Mathlib.Algebra.GCDMonoid.Basic
import Mathlib.Data.Finsupp.Multiset
import Mathlib.Data.Nat.Factors
import Mathlib.RingTheory.Noetherian
import Mathlib.RingTheory.Multiplicity
#align_import ring_theory.unique_factorization_domain from "leanprover-community/mathlib"@"570e9f4877079b3a923135b3027ac3be8695ab8c"
/-!
# Unique factorization
## Main Definitions
* `WfDvdMonoid` holds for `Monoid`s for which a strict divisibility relation is
well-founded.
* `UniqueFactorizationMonoid` holds for `WfDvdMonoid`s where
`Irreducible` is equivalent to `Prime`
## To do
* set up the complete lattice structure on `FactorSet`.
-/
variable {α : Type*}
local infixl:50 " ~ᵤ " => Associated
/-- Well-foundedness of the strict version of |, which is equivalent to the descending chain
condition on divisibility and to the ascending chain condition on
principal ideals in an integral domain.
-/
class WfDvdMonoid (α : Type*) [CommMonoidWithZero α] : Prop where
wellFounded_dvdNotUnit : WellFounded (@DvdNotUnit α _)
#align wf_dvd_monoid WfDvdMonoid
export WfDvdMonoid (wellFounded_dvdNotUnit)
-- see Note [lower instance priority]
instance (priority := 100) IsNoetherianRing.wfDvdMonoid [CommRing α] [IsDomain α]
[IsNoetherianRing α] : WfDvdMonoid α :=
⟨by
convert InvImage.wf (fun a => Ideal.span ({a} : Set α)) (wellFounded_submodule_gt _ _)
ext
exact Ideal.span_singleton_lt_span_singleton.symm⟩
#align is_noetherian_ring.wf_dvd_monoid IsNoetherianRing.wfDvdMonoid
namespace WfDvdMonoid
variable [CommMonoidWithZero α]
open Associates Nat
theorem of_wfDvdMonoid_associates (_ : WfDvdMonoid (Associates α)) : WfDvdMonoid α :=
⟨(mk_surjective.wellFounded_iff mk_dvdNotUnit_mk_iff.symm).2 wellFounded_dvdNotUnit⟩
#align wf_dvd_monoid.of_wf_dvd_monoid_associates WfDvdMonoid.of_wfDvdMonoid_associates
variable [WfDvdMonoid α]
instance wfDvdMonoid_associates : WfDvdMonoid (Associates α) :=
⟨(mk_surjective.wellFounded_iff mk_dvdNotUnit_mk_iff.symm).1 wellFounded_dvdNotUnit⟩
#align wf_dvd_monoid.wf_dvd_monoid_associates WfDvdMonoid.wfDvdMonoid_associates
theorem wellFounded_associates : WellFounded ((· < ·) : Associates α → Associates α → Prop) :=
Subrelation.wf dvdNotUnit_of_lt wellFounded_dvdNotUnit
#align wf_dvd_monoid.well_founded_associates WfDvdMonoid.wellFounded_associates
-- Porting note: elab_as_elim can only be global and cannot be changed on an imported decl
-- attribute [local elab_as_elim] WellFounded.fix
theorem exists_irreducible_factor {a : α} (ha : ¬IsUnit a) (ha0 : a ≠ 0) :
∃ i, Irreducible i ∧ i ∣ a :=
let ⟨b, hs, hr⟩ := wellFounded_dvdNotUnit.has_min { b | b ∣ a ∧ ¬IsUnit b } ⟨a, dvd_rfl, ha⟩
⟨b,
⟨hs.2, fun c d he =>
let h := dvd_trans ⟨d, he⟩ hs.1
or_iff_not_imp_left.2 fun hc =>
of_not_not fun hd => hr c ⟨h, hc⟩ ⟨ne_zero_of_dvd_ne_zero ha0 h, d, hd, he⟩⟩,
hs.1⟩
#align wf_dvd_monoid.exists_irreducible_factor WfDvdMonoid.exists_irreducible_factor
@[elab_as_elim]
theorem induction_on_irreducible {P : α → Prop} (a : α) (h0 : P 0) (hu : ∀ u : α, IsUnit u → P u)
(hi : ∀ a i : α, a ≠ 0 → Irreducible i → P a → P (i * a)) : P a :=
haveI := Classical.dec
wellFounded_dvdNotUnit.fix
(fun a ih =>
if ha0 : a = 0 then ha0.substr h0
else
if hau : IsUnit a then hu a hau
else
let ⟨i, hii, b, hb⟩ := exists_irreducible_factor hau ha0
let hb0 : b ≠ 0 := ne_zero_of_dvd_ne_zero ha0 ⟨i, mul_comm i b ▸ hb⟩
hb.symm ▸ hi b i hb0 hii <| ih b ⟨hb0, i, hii.1, mul_comm i b ▸ hb⟩)
a
#align wf_dvd_monoid.induction_on_irreducible WfDvdMonoid.induction_on_irreducible
theorem exists_factors (a : α) :
a ≠ 0 → ∃ f : Multiset α, (∀ b ∈ f, Irreducible b) ∧ Associated f.prod a :=
induction_on_irreducible a (fun h => (h rfl).elim)
(fun u hu _ => ⟨0, fun _ h => False.elim (Multiset.not_mem_zero _ h), hu.unit, one_mul _⟩)
fun a i ha0 hi ih _ =>
let ⟨s, hs⟩ := ih ha0
⟨i ::ₘ s, fun b H => (Multiset.mem_cons.1 H).elim (fun h => h.symm ▸ hi) (hs.1 b), by
rw [s.prod_cons i]
exact hs.2.mul_left i⟩
#align wf_dvd_monoid.exists_factors WfDvdMonoid.exists_factors
theorem not_unit_iff_exists_factors_eq (a : α) (hn0 : a ≠ 0) :
¬IsUnit a ↔ ∃ f : Multiset α, (∀ b ∈ f, Irreducible b) ∧ f.prod = a ∧ f ≠ ∅ :=
⟨fun hnu => by
obtain ⟨f, hi, u, rfl⟩ := exists_factors a hn0
obtain ⟨b, h⟩ := Multiset.exists_mem_of_ne_zero fun h : f = 0 => hnu <| by simp [h]
classical
refine ⟨(f.erase b).cons (b * u), fun a ha => ?_, ?_, Multiset.cons_ne_zero⟩
· obtain rfl | ha := Multiset.mem_cons.1 ha
exacts [Associated.irreducible ⟨u, rfl⟩ (hi b h), hi a (Multiset.mem_of_mem_erase ha)]
· rw [Multiset.prod_cons, mul_comm b, mul_assoc, Multiset.prod_erase h, mul_comm],
fun ⟨f, hi, he, hne⟩ =>
let ⟨b, h⟩ := Multiset.exists_mem_of_ne_zero hne
not_isUnit_of_not_isUnit_dvd (hi b h).not_unit <| he ▸ Multiset.dvd_prod h⟩
#align wf_dvd_monoid.not_unit_iff_exists_factors_eq WfDvdMonoid.not_unit_iff_exists_factors_eq
theorem isRelPrime_of_no_irreducible_factors {x y : α} (nonzero : ¬(x = 0 ∧ y = 0))
(H : ∀ z : α, Irreducible z → z ∣ x → ¬z ∣ y) : IsRelPrime x y :=
isRelPrime_of_no_nonunits_factors nonzero fun _z znu znz zx zy ↦
have ⟨i, h1, h2⟩ := exists_irreducible_factor znu znz
H i h1 (h2.trans zx) (h2.trans zy)
end WfDvdMonoid
theorem WfDvdMonoid.of_wellFounded_associates [CancelCommMonoidWithZero α]
(h : WellFounded ((· < ·) : Associates α → Associates α → Prop)) : WfDvdMonoid α :=
WfDvdMonoid.of_wfDvdMonoid_associates
⟨by
convert h
ext
exact Associates.dvdNotUnit_iff_lt⟩
#align wf_dvd_monoid.of_well_founded_associates WfDvdMonoid.of_wellFounded_associates
theorem WfDvdMonoid.iff_wellFounded_associates [CancelCommMonoidWithZero α] :
WfDvdMonoid α ↔ WellFounded ((· < ·) : Associates α → Associates α → Prop) :=
⟨by apply WfDvdMonoid.wellFounded_associates, WfDvdMonoid.of_wellFounded_associates⟩
#align wf_dvd_monoid.iff_well_founded_associates WfDvdMonoid.iff_wellFounded_associates
theorem WfDvdMonoid.max_power_factor' [CommMonoidWithZero α] [WfDvdMonoid α] {a₀ x : α}
(h : a₀ ≠ 0) (hx : ¬IsUnit x) : ∃ (n : ℕ) (a : α), ¬x ∣ a ∧ a₀ = x ^ n * a := by
obtain ⟨a, ⟨n, rfl⟩, hm⟩ := wellFounded_dvdNotUnit.has_min
{a | ∃ n, x ^ n * a = a₀} ⟨a₀, 0, by rw [pow_zero, one_mul]⟩
refine ⟨n, a, ?_, rfl⟩; rintro ⟨d, rfl⟩
exact hm d ⟨n + 1, by rw [pow_succ, mul_assoc]⟩
⟨(right_ne_zero_of_mul <| right_ne_zero_of_mul h), x, hx, mul_comm _ _⟩
theorem WfDvdMonoid.max_power_factor [CommMonoidWithZero α] [WfDvdMonoid α] {a₀ x : α}
(h : a₀ ≠ 0) (hx : Irreducible x) : ∃ (n : ℕ) (a : α), ¬x ∣ a ∧ a₀ = x ^ n * a :=
max_power_factor' h hx.not_unit
theorem multiplicity.finite_of_not_isUnit [CancelCommMonoidWithZero α] [WfDvdMonoid α]
{a b : α} (ha : ¬IsUnit a) (hb : b ≠ 0) : multiplicity.Finite a b := by
obtain ⟨n, c, ndvd, rfl⟩ := WfDvdMonoid.max_power_factor' hb ha
exact ⟨n, by rwa [pow_succ, mul_dvd_mul_iff_left (left_ne_zero_of_mul hb)]⟩
section Prio
-- set_option default_priority 100
-- see Note [default priority]
/-- unique factorization monoids.
These are defined as `CancelCommMonoidWithZero`s with well-founded strict divisibility
relations, but this is equivalent to more familiar definitions:
Each element (except zero) is uniquely represented as a multiset of irreducible factors.
Uniqueness is only up to associated elements.
Each element (except zero) is non-uniquely represented as a multiset
of prime factors.
To define a UFD using the definition in terms of multisets
of irreducible factors, use the definition `of_exists_unique_irreducible_factors`
To define a UFD using the definition in terms of multisets
of prime factors, use the definition `of_exists_prime_factors`
-/
class UniqueFactorizationMonoid (α : Type*) [CancelCommMonoidWithZero α] extends WfDvdMonoid α :
Prop where
protected irreducible_iff_prime : ∀ {a : α}, Irreducible a ↔ Prime a
#align unique_factorization_monoid UniqueFactorizationMonoid
/-- Can't be an instance because it would cause a loop `ufm → WfDvdMonoid → ufm → ...`. -/
theorem ufm_of_decomposition_of_wfDvdMonoid [CancelCommMonoidWithZero α] [WfDvdMonoid α]
[DecompositionMonoid α] : UniqueFactorizationMonoid α :=
{ ‹WfDvdMonoid α› with irreducible_iff_prime := irreducible_iff_prime }
#align ufm_of_gcd_of_wf_dvd_monoid ufm_of_decomposition_of_wfDvdMonoid
@[deprecated] alias ufm_of_gcd_of_wfDvdMonoid := ufm_of_decomposition_of_wfDvdMonoid
instance Associates.ufm [CancelCommMonoidWithZero α] [UniqueFactorizationMonoid α] :
UniqueFactorizationMonoid (Associates α) :=
{ (WfDvdMonoid.wfDvdMonoid_associates : WfDvdMonoid (Associates α)) with
irreducible_iff_prime := by
rw [← Associates.irreducible_iff_prime_iff]
apply UniqueFactorizationMonoid.irreducible_iff_prime }
#align associates.ufm Associates.ufm
end Prio
namespace UniqueFactorizationMonoid
variable [CancelCommMonoidWithZero α] [UniqueFactorizationMonoid α]
theorem exists_prime_factors (a : α) :
a ≠ 0 → ∃ f : Multiset α, (∀ b ∈ f, Prime b) ∧ f.prod ~ᵤ a := by
simp_rw [← UniqueFactorizationMonoid.irreducible_iff_prime]
apply WfDvdMonoid.exists_factors a
#align unique_factorization_monoid.exists_prime_factors UniqueFactorizationMonoid.exists_prime_factors
instance : DecompositionMonoid α where
primal a := by
obtain rfl | ha := eq_or_ne a 0; · exact isPrimal_zero
obtain ⟨f, hf, u, rfl⟩ := exists_prime_factors a ha
exact ((Submonoid.isPrimal α).multiset_prod_mem f (hf · ·|>.isPrimal)).mul u.isUnit.isPrimal
lemma exists_prime_iff :
(∃ (p : α), Prime p) ↔ ∃ (x : α), x ≠ 0 ∧ ¬ IsUnit x := by
refine ⟨fun ⟨p, hp⟩ ↦ ⟨p, hp.ne_zero, hp.not_unit⟩, fun ⟨x, hx₀, hxu⟩ ↦ ?_⟩
obtain ⟨f, hf, -⟩ := WfDvdMonoid.exists_irreducible_factor hxu hx₀
exact ⟨f, UniqueFactorizationMonoid.irreducible_iff_prime.mp hf⟩
@[elab_as_elim]
theorem induction_on_prime {P : α → Prop} (a : α) (h₁ : P 0) (h₂ : ∀ x : α, IsUnit x → P x)
(h₃ : ∀ a p : α, a ≠ 0 → Prime p → P a → P (p * a)) : P a := by
simp_rw [← UniqueFactorizationMonoid.irreducible_iff_prime] at h₃
exact WfDvdMonoid.induction_on_irreducible a h₁ h₂ h₃
#align unique_factorization_monoid.induction_on_prime UniqueFactorizationMonoid.induction_on_prime
end UniqueFactorizationMonoid
theorem prime_factors_unique [CancelCommMonoidWithZero α] :
∀ {f g : Multiset α},
(∀ x ∈ f, Prime x) → (∀ x ∈ g, Prime x) → f.prod ~ᵤ g.prod → Multiset.Rel Associated f g := by
classical
intro f
induction' f using Multiset.induction_on with p f ih
· intros g _ hg h
exact Multiset.rel_zero_left.2 <|
Multiset.eq_zero_of_forall_not_mem fun x hx =>
have : IsUnit g.prod := by simpa [associated_one_iff_isUnit] using h.symm
(hg x hx).not_unit <|
isUnit_iff_dvd_one.2 <| (Multiset.dvd_prod hx).trans (isUnit_iff_dvd_one.1 this)
· intros g hf hg hfg
let ⟨b, hbg, hb⟩ :=
(exists_associated_mem_of_dvd_prod (hf p (by simp)) fun q hq => hg _ hq) <|
hfg.dvd_iff_dvd_right.1 (show p ∣ (p ::ₘ f).prod by simp)
haveI := Classical.decEq α
rw [← Multiset.cons_erase hbg]
exact
Multiset.Rel.cons hb
(ih (fun q hq => hf _ (by simp [hq]))
(fun {q} (hq : q ∈ g.erase b) => hg q (Multiset.mem_of_mem_erase hq))
(Associated.of_mul_left
(by rwa [← Multiset.prod_cons, ← Multiset.prod_cons, Multiset.cons_erase hbg]) hb
(hf p (by simp)).ne_zero))
#align prime_factors_unique prime_factors_unique
namespace UniqueFactorizationMonoid
variable [CancelCommMonoidWithZero α] [UniqueFactorizationMonoid α]
theorem factors_unique {f g : Multiset α} (hf : ∀ x ∈ f, Irreducible x)
(hg : ∀ x ∈ g, Irreducible x) (h : f.prod ~ᵤ g.prod) : Multiset.Rel Associated f g :=
prime_factors_unique (fun x hx => UniqueFactorizationMonoid.irreducible_iff_prime.mp (hf x hx))
(fun x hx => UniqueFactorizationMonoid.irreducible_iff_prime.mp (hg x hx)) h
#align unique_factorization_monoid.factors_unique UniqueFactorizationMonoid.factors_unique
end UniqueFactorizationMonoid
/-- If an irreducible has a prime factorization,
then it is an associate of one of its prime factors. -/
theorem prime_factors_irreducible [CancelCommMonoidWithZero α] {a : α} {f : Multiset α}
(ha : Irreducible a) (pfa : (∀ b ∈ f, Prime b) ∧ f.prod ~ᵤ a) : ∃ p, a ~ᵤ p ∧ f = {p} := by
haveI := Classical.decEq α
refine @Multiset.induction_on _
(fun g => (g.prod ~ᵤ a) → (∀ b ∈ g, Prime b) → ∃ p, a ~ᵤ p ∧ g = {p}) f ?_ ?_ pfa.2 pfa.1
· intro h; exact (ha.not_unit (associated_one_iff_isUnit.1 (Associated.symm h))).elim
· rintro p s _ ⟨u, hu⟩ hs
use p
have hs0 : s = 0 := by
by_contra hs0
obtain ⟨q, hq⟩ := Multiset.exists_mem_of_ne_zero hs0
apply (hs q (by simp [hq])).2.1
refine (ha.isUnit_or_isUnit (?_ : _ = p * ↑u * (s.erase q).prod * _)).resolve_left ?_
· rw [mul_right_comm _ _ q, mul_assoc, ← Multiset.prod_cons, Multiset.cons_erase hq, ← hu,
mul_comm, mul_comm p _, mul_assoc]
simp
apply mt isUnit_of_mul_isUnit_left (mt isUnit_of_mul_isUnit_left _)
apply (hs p (Multiset.mem_cons_self _ _)).2.1
simp only [mul_one, Multiset.prod_cons, Multiset.prod_zero, hs0] at *
exact ⟨Associated.symm ⟨u, hu⟩, rfl⟩
#align prime_factors_irreducible prime_factors_irreducible
section ExistsPrimeFactors
variable [CancelCommMonoidWithZero α]
variable (pf : ∀ a : α, a ≠ 0 → ∃ f : Multiset α, (∀ b ∈ f, Prime b) ∧ f.prod ~ᵤ a)
theorem WfDvdMonoid.of_exists_prime_factors : WfDvdMonoid α :=
⟨by
classical
refine RelHomClass.wellFounded
(RelHom.mk ?_ ?_ : (DvdNotUnit : α → α → Prop) →r ((· < ·) : ℕ∞ → ℕ∞ → Prop)) wellFounded_lt
· intro a
by_cases h : a = 0
· exact ⊤
exact ↑(Multiset.card (Classical.choose (pf a h)))
rintro a b ⟨ane0, ⟨c, hc, b_eq⟩⟩
rw [dif_neg ane0]
by_cases h : b = 0
· simp [h, lt_top_iff_ne_top]
· rw [dif_neg h]
erw [WithTop.coe_lt_coe]
have cne0 : c ≠ 0 := by
refine mt (fun con => ?_) h
rw [b_eq, con, mul_zero]
calc
Multiset.card (Classical.choose (pf a ane0)) <
_ + Multiset.card (Classical.choose (pf c cne0)) :=
lt_add_of_pos_right _
(Multiset.card_pos.mpr fun con => hc (associated_one_iff_isUnit.mp ?_))
_ = Multiset.card (Classical.choose (pf a ane0) + Classical.choose (pf c cne0)) :=
(Multiset.card_add _ _).symm
_ = Multiset.card (Classical.choose (pf b h)) :=
Multiset.card_eq_card_of_rel
(prime_factors_unique ?_ (Classical.choose_spec (pf _ h)).1 ?_)
· convert (Classical.choose_spec (pf c cne0)).2.symm
rw [con, Multiset.prod_zero]
· intro x hadd
rw [Multiset.mem_add] at hadd
cases' hadd with h h <;> apply (Classical.choose_spec (pf _ _)).1 _ h <;> assumption
· rw [Multiset.prod_add]
trans a * c
· apply Associated.mul_mul <;> apply (Classical.choose_spec (pf _ _)).2 <;> assumption
· rw [← b_eq]
apply (Classical.choose_spec (pf _ _)).2.symm; assumption⟩
#align wf_dvd_monoid.of_exists_prime_factors WfDvdMonoid.of_exists_prime_factors
theorem irreducible_iff_prime_of_exists_prime_factors {p : α} : Irreducible p ↔ Prime p := by
by_cases hp0 : p = 0
· simp [hp0]
refine ⟨fun h => ?_, Prime.irreducible⟩
obtain ⟨f, hf⟩ := pf p hp0
obtain ⟨q, hq, rfl⟩ := prime_factors_irreducible h hf
rw [hq.prime_iff]
exact hf.1 q (Multiset.mem_singleton_self _)
#align irreducible_iff_prime_of_exists_prime_factors irreducible_iff_prime_of_exists_prime_factors
theorem UniqueFactorizationMonoid.of_exists_prime_factors : UniqueFactorizationMonoid α :=
{ WfDvdMonoid.of_exists_prime_factors pf with
irreducible_iff_prime := irreducible_iff_prime_of_exists_prime_factors pf }
#align unique_factorization_monoid.of_exists_prime_factors UniqueFactorizationMonoid.of_exists_prime_factors
end ExistsPrimeFactors
theorem UniqueFactorizationMonoid.iff_exists_prime_factors [CancelCommMonoidWithZero α] :
UniqueFactorizationMonoid α ↔
∀ a : α, a ≠ 0 → ∃ f : Multiset α, (∀ b ∈ f, Prime b) ∧ f.prod ~ᵤ a :=
⟨fun h => @UniqueFactorizationMonoid.exists_prime_factors _ _ h,
UniqueFactorizationMonoid.of_exists_prime_factors⟩
#align unique_factorization_monoid.iff_exists_prime_factors UniqueFactorizationMonoid.iff_exists_prime_factors
section
variable {β : Type*} [CancelCommMonoidWithZero α] [CancelCommMonoidWithZero β]
theorem MulEquiv.uniqueFactorizationMonoid (e : α ≃* β) (hα : UniqueFactorizationMonoid α) :
UniqueFactorizationMonoid β := by
rw [UniqueFactorizationMonoid.iff_exists_prime_factors] at hα ⊢
intro a ha
obtain ⟨w, hp, u, h⟩ :=
hα (e.symm a) fun h =>
ha <| by
convert← map_zero e
simp [← h]
exact
⟨w.map e, fun b hb =>
let ⟨c, hc, he⟩ := Multiset.mem_map.1 hb
he ▸ e.prime_iff.1 (hp c hc),
Units.map e.toMonoidHom u,
by
erw [Multiset.prod_hom, ← e.map_mul, h]
simp⟩
#align mul_equiv.unique_factorization_monoid MulEquiv.uniqueFactorizationMonoid
theorem MulEquiv.uniqueFactorizationMonoid_iff (e : α ≃* β) :
UniqueFactorizationMonoid α ↔ UniqueFactorizationMonoid β :=
⟨e.uniqueFactorizationMonoid, e.symm.uniqueFactorizationMonoid⟩
#align mul_equiv.unique_factorization_monoid_iff MulEquiv.uniqueFactorizationMonoid_iff
end
theorem irreducible_iff_prime_of_exists_unique_irreducible_factors [CancelCommMonoidWithZero α]
(eif : ∀ a : α, a ≠ 0 → ∃ f : Multiset α, (∀ b ∈ f, Irreducible b) ∧ f.prod ~ᵤ a)
(uif :
∀ f g : Multiset α,
(∀ x ∈ f, Irreducible x) →
(∀ x ∈ g, Irreducible x) → f.prod ~ᵤ g.prod → Multiset.Rel Associated f g)
(p : α) : Irreducible p ↔ Prime p :=
letI := Classical.decEq α
⟨ fun hpi =>
⟨hpi.ne_zero, hpi.1, fun a b ⟨x, hx⟩ =>
if hab0 : a * b = 0 then
(eq_zero_or_eq_zero_of_mul_eq_zero hab0).elim (fun ha0 => by simp [ha0]) fun hb0 => by
simp [hb0]
else by
have hx0 : x ≠ 0 := fun hx0 => by simp_all
have ha0 : a ≠ 0 := left_ne_zero_of_mul hab0
have hb0 : b ≠ 0 := right_ne_zero_of_mul hab0
cases' eif x hx0 with fx hfx
cases' eif a ha0 with fa hfa
cases' eif b hb0 with fb hfb
have h : Multiset.Rel Associated (p ::ₘ fx) (fa + fb) := by
apply uif
· exact fun i hi => (Multiset.mem_cons.1 hi).elim (fun hip => hip.symm ▸ hpi) (hfx.1 _)
· exact fun i hi => (Multiset.mem_add.1 hi).elim (hfa.1 _) (hfb.1 _)
calc
Multiset.prod (p ::ₘ fx) ~ᵤ a * b := by
rw [hx, Multiset.prod_cons]; exact hfx.2.mul_left _
_ ~ᵤ fa.prod * fb.prod := hfa.2.symm.mul_mul hfb.2.symm
_ = _ := by rw [Multiset.prod_add]
exact
let ⟨q, hqf, hq⟩ := Multiset.exists_mem_of_rel_of_mem h (Multiset.mem_cons_self p _)
(Multiset.mem_add.1 hqf).elim
(fun hqa =>
Or.inl <| hq.dvd_iff_dvd_left.2 <| hfa.2.dvd_iff_dvd_right.1 (Multiset.dvd_prod hqa))
fun hqb =>
Or.inr <| hq.dvd_iff_dvd_left.2 <| hfb.2.dvd_iff_dvd_right.1 (Multiset.dvd_prod hqb)⟩,
Prime.irreducible⟩
#align irreducible_iff_prime_of_exists_unique_irreducible_factors irreducible_iff_prime_of_exists_unique_irreducible_factors
theorem UniqueFactorizationMonoid.of_exists_unique_irreducible_factors [CancelCommMonoidWithZero α]
(eif : ∀ a : α, a ≠ 0 → ∃ f : Multiset α, (∀ b ∈ f, Irreducible b) ∧ f.prod ~ᵤ a)
(uif :
∀ f g : Multiset α,
(∀ x ∈ f, Irreducible x) →
(∀ x ∈ g, Irreducible x) → f.prod ~ᵤ g.prod → Multiset.Rel Associated f g) :
UniqueFactorizationMonoid α :=
UniqueFactorizationMonoid.of_exists_prime_factors
(by
convert eif using 7
simp_rw [irreducible_iff_prime_of_exists_unique_irreducible_factors eif uif])
#align unique_factorization_monoid.of_exists_unique_irreducible_factors UniqueFactorizationMonoid.of_exists_unique_irreducible_factors
namespace UniqueFactorizationMonoid
variable [CancelCommMonoidWithZero α]
variable [UniqueFactorizationMonoid α]
open Classical in
/-- Noncomputably determines the multiset of prime factors. -/
noncomputable def factors (a : α) : Multiset α :=
if h : a = 0 then 0 else Classical.choose (UniqueFactorizationMonoid.exists_prime_factors a h)
#align unique_factorization_monoid.factors UniqueFactorizationMonoid.factors
theorem factors_prod {a : α} (ane0 : a ≠ 0) : Associated (factors a).prod a := by
rw [factors, dif_neg ane0]
exact (Classical.choose_spec (exists_prime_factors a ane0)).2
#align unique_factorization_monoid.factors_prod UniqueFactorizationMonoid.factors_prod
@[simp]
theorem factors_zero : factors (0 : α) = 0 := by simp [factors]
#align unique_factorization_monoid.factors_zero UniqueFactorizationMonoid.factors_zero
theorem ne_zero_of_mem_factors {p a : α} (h : p ∈ factors a) : a ≠ 0 := by
rintro rfl
simp at h
#align unique_factorization_monoid.ne_zero_of_mem_factors UniqueFactorizationMonoid.ne_zero_of_mem_factors
theorem dvd_of_mem_factors {p a : α} (h : p ∈ factors a) : p ∣ a :=
dvd_trans (Multiset.dvd_prod h) (Associated.dvd (factors_prod (ne_zero_of_mem_factors h)))
#align unique_factorization_monoid.dvd_of_mem_factors UniqueFactorizationMonoid.dvd_of_mem_factors
theorem prime_of_factor {a : α} (x : α) (hx : x ∈ factors a) : Prime x := by
have ane0 := ne_zero_of_mem_factors hx
rw [factors, dif_neg ane0] at hx
exact (Classical.choose_spec (UniqueFactorizationMonoid.exists_prime_factors a ane0)).1 x hx
#align unique_factorization_monoid.prime_of_factor UniqueFactorizationMonoid.prime_of_factor
theorem irreducible_of_factor {a : α} : ∀ x : α, x ∈ factors a → Irreducible x := fun x h =>
(prime_of_factor x h).irreducible
#align unique_factorization_monoid.irreducible_of_factor UniqueFactorizationMonoid.irreducible_of_factor
@[simp]
theorem factors_one : factors (1 : α) = 0 := by
nontriviality α using factors
rw [← Multiset.rel_zero_right]
refine factors_unique irreducible_of_factor (fun x hx => (Multiset.not_mem_zero x hx).elim) ?_
rw [Multiset.prod_zero]
exact factors_prod one_ne_zero
#align unique_factorization_monoid.factors_one UniqueFactorizationMonoid.factors_one
theorem exists_mem_factors_of_dvd {a p : α} (ha0 : a ≠ 0) (hp : Irreducible p) :
p ∣ a → ∃ q ∈ factors a, p ~ᵤ q := fun ⟨b, hb⟩ =>
have hb0 : b ≠ 0 := fun hb0 => by simp_all
have : Multiset.Rel Associated (p ::ₘ factors b) (factors a) :=
factors_unique
(fun x hx => (Multiset.mem_cons.1 hx).elim (fun h => h.symm ▸ hp) (irreducible_of_factor _))
irreducible_of_factor
(Associated.symm <|
calc
Multiset.prod (factors a) ~ᵤ a := factors_prod ha0
_ = p * b := hb
_ ~ᵤ Multiset.prod (p ::ₘ factors b) := by
rw [Multiset.prod_cons]; exact (factors_prod hb0).symm.mul_left _
)
Multiset.exists_mem_of_rel_of_mem this (by simp)
#align unique_factorization_monoid.exists_mem_factors_of_dvd UniqueFactorizationMonoid.exists_mem_factors_of_dvd
theorem exists_mem_factors {x : α} (hx : x ≠ 0) (h : ¬IsUnit x) : ∃ p, p ∈ factors x := by
obtain ⟨p', hp', hp'x⟩ := WfDvdMonoid.exists_irreducible_factor h hx
obtain ⟨p, hp, _⟩ := exists_mem_factors_of_dvd hx hp' hp'x
exact ⟨p, hp⟩
#align unique_factorization_monoid.exists_mem_factors UniqueFactorizationMonoid.exists_mem_factors
open Classical in
theorem factors_mul {x y : α} (hx : x ≠ 0) (hy : y ≠ 0) :
Multiset.Rel Associated (factors (x * y)) (factors x + factors y) := by
refine
factors_unique irreducible_of_factor
(fun a ha =>
(Multiset.mem_add.mp ha).by_cases (irreducible_of_factor _) (irreducible_of_factor _))
((factors_prod (mul_ne_zero hx hy)).trans ?_)
rw [Multiset.prod_add]
exact (Associated.mul_mul (factors_prod hx) (factors_prod hy)).symm
#align unique_factorization_monoid.factors_mul UniqueFactorizationMonoid.factors_mul
theorem factors_pow {x : α} (n : ℕ) :
Multiset.Rel Associated (factors (x ^ n)) (n • factors x) := by
match n with
| 0 => rw [zero_smul, pow_zero, factors_one, Multiset.rel_zero_right]
| n+1 =>
by_cases h0 : x = 0
· simp [h0, zero_pow n.succ_ne_zero, smul_zero]
· rw [pow_succ', succ_nsmul']
refine Multiset.Rel.trans _ (factors_mul h0 (pow_ne_zero n h0)) ?_
refine Multiset.Rel.add ?_ <| factors_pow n
exact Multiset.rel_refl_of_refl_on fun y _ => Associated.refl _
#align unique_factorization_monoid.factors_pow UniqueFactorizationMonoid.factors_pow
@[simp]
theorem factors_pos (x : α) (hx : x ≠ 0) : 0 < factors x ↔ ¬IsUnit x := by
constructor
· intro h hx
obtain ⟨p, hp⟩ := Multiset.exists_mem_of_ne_zero h.ne'
exact (prime_of_factor _ hp).not_unit (isUnit_of_dvd_unit (dvd_of_mem_factors hp) hx)
· intro h
obtain ⟨p, hp⟩ := exists_mem_factors hx h
exact
bot_lt_iff_ne_bot.mpr
(mt Multiset.eq_zero_iff_forall_not_mem.mp (not_forall.mpr ⟨p, not_not.mpr hp⟩))
#align unique_factorization_monoid.factors_pos UniqueFactorizationMonoid.factors_pos
open Multiset in
theorem factors_pow_count_prod [DecidableEq α] {x : α} (hx : x ≠ 0) :
(∏ p ∈ (factors x).toFinset, p ^ (factors x).count p) ~ᵤ x :=
calc
_ = prod (∑ a ∈ toFinset (factors x), count a (factors x) • {a}) := by
simp only [prod_sum, prod_nsmul, prod_singleton]
_ = prod (factors x) := by rw [toFinset_sum_count_nsmul_eq (factors x)]
_ ~ᵤ x := factors_prod hx
end UniqueFactorizationMonoid
namespace UniqueFactorizationMonoid
variable [CancelCommMonoidWithZero α] [NormalizationMonoid α]
variable [UniqueFactorizationMonoid α]
/-- Noncomputably determines the multiset of prime factors. -/
noncomputable def normalizedFactors (a : α) : Multiset α :=
Multiset.map normalize <| factors a
#align unique_factorization_monoid.normalized_factors UniqueFactorizationMonoid.normalizedFactors
/-- An arbitrary choice of factors of `x : M` is exactly the (unique) normalized set of factors,
if `M` has a trivial group of units. -/
@[simp]
theorem factors_eq_normalizedFactors {M : Type*} [CancelCommMonoidWithZero M]
[UniqueFactorizationMonoid M] [Unique Mˣ] (x : M) : factors x = normalizedFactors x := by
unfold normalizedFactors
convert (Multiset.map_id (factors x)).symm
ext p
exact normalize_eq p
#align unique_factorization_monoid.factors_eq_normalized_factors UniqueFactorizationMonoid.factors_eq_normalizedFactors
theorem normalizedFactors_prod {a : α} (ane0 : a ≠ 0) :
Associated (normalizedFactors a).prod a := by
rw [normalizedFactors, factors, dif_neg ane0]
refine Associated.trans ?_ (Classical.choose_spec (exists_prime_factors a ane0)).2
rw [← Associates.mk_eq_mk_iff_associated, ← Associates.prod_mk, ← Associates.prod_mk,
Multiset.map_map]
congr 2
ext
rw [Function.comp_apply, Associates.mk_normalize]
#align unique_factorization_monoid.normalized_factors_prod UniqueFactorizationMonoid.normalizedFactors_prod
theorem prime_of_normalized_factor {a : α} : ∀ x : α, x ∈ normalizedFactors a → Prime x := by
rw [normalizedFactors, factors]
split_ifs with ane0; · simp
intro x hx; rcases Multiset.mem_map.1 hx with ⟨y, ⟨hy, rfl⟩⟩
rw [(normalize_associated _).prime_iff]
exact (Classical.choose_spec (UniqueFactorizationMonoid.exists_prime_factors a ane0)).1 y hy
#align unique_factorization_monoid.prime_of_normalized_factor UniqueFactorizationMonoid.prime_of_normalized_factor
theorem irreducible_of_normalized_factor {a : α} :
∀ x : α, x ∈ normalizedFactors a → Irreducible x := fun x h =>
(prime_of_normalized_factor x h).irreducible
#align unique_factorization_monoid.irreducible_of_normalized_factor UniqueFactorizationMonoid.irreducible_of_normalized_factor
theorem normalize_normalized_factor {a : α} :
∀ x : α, x ∈ normalizedFactors a → normalize x = x := by
rw [normalizedFactors, factors]
split_ifs with h; · simp
intro x hx
obtain ⟨y, _, rfl⟩ := Multiset.mem_map.1 hx
apply normalize_idem
#align unique_factorization_monoid.normalize_normalized_factor UniqueFactorizationMonoid.normalize_normalized_factor
theorem normalizedFactors_irreducible {a : α} (ha : Irreducible a) :
normalizedFactors a = {normalize a} := by
obtain ⟨p, a_assoc, hp⟩ :=
prime_factors_irreducible ha ⟨prime_of_normalized_factor, normalizedFactors_prod ha.ne_zero⟩
have p_mem : p ∈ normalizedFactors a := by
rw [hp]
exact Multiset.mem_singleton_self _
convert hp
rwa [← normalize_normalized_factor p p_mem, normalize_eq_normalize_iff, dvd_dvd_iff_associated]
#align unique_factorization_monoid.normalized_factors_irreducible UniqueFactorizationMonoid.normalizedFactors_irreducible
theorem normalizedFactors_eq_of_dvd (a : α) :
∀ᵉ (p ∈ normalizedFactors a) (q ∈ normalizedFactors a), p ∣ q → p = q := by
intro p hp q hq hdvd
convert normalize_eq_normalize hdvd
((prime_of_normalized_factor _ hp).irreducible.dvd_symm
(prime_of_normalized_factor _ hq).irreducible hdvd) <;>
apply (normalize_normalized_factor _ ‹_›).symm
#align unique_factorization_monoid.normalized_factors_eq_of_dvd UniqueFactorizationMonoid.normalizedFactors_eq_of_dvd
theorem exists_mem_normalizedFactors_of_dvd {a p : α} (ha0 : a ≠ 0) (hp : Irreducible p) :
p ∣ a → ∃ q ∈ normalizedFactors a, p ~ᵤ q := fun ⟨b, hb⟩ =>
have hb0 : b ≠ 0 := fun hb0 => by simp_all
have : Multiset.Rel Associated (p ::ₘ normalizedFactors b) (normalizedFactors a) :=
factors_unique
(fun x hx =>
(Multiset.mem_cons.1 hx).elim (fun h => h.symm ▸ hp) (irreducible_of_normalized_factor _))
irreducible_of_normalized_factor
(Associated.symm <|
calc
Multiset.prod (normalizedFactors a) ~ᵤ a := normalizedFactors_prod ha0
_ = p * b := hb
_ ~ᵤ Multiset.prod (p ::ₘ normalizedFactors b) := by
rw [Multiset.prod_cons]
exact (normalizedFactors_prod hb0).symm.mul_left _
)
Multiset.exists_mem_of_rel_of_mem this (by simp)
#align unique_factorization_monoid.exists_mem_normalized_factors_of_dvd UniqueFactorizationMonoid.exists_mem_normalizedFactors_of_dvd
theorem exists_mem_normalizedFactors {x : α} (hx : x ≠ 0) (h : ¬IsUnit x) :
∃ p, p ∈ normalizedFactors x := by
obtain ⟨p', hp', hp'x⟩ := WfDvdMonoid.exists_irreducible_factor h hx
obtain ⟨p, hp, _⟩ := exists_mem_normalizedFactors_of_dvd hx hp' hp'x
exact ⟨p, hp⟩
#align unique_factorization_monoid.exists_mem_normalized_factors UniqueFactorizationMonoid.exists_mem_normalizedFactors
@[simp]
theorem normalizedFactors_zero : normalizedFactors (0 : α) = 0 := by
simp [normalizedFactors, factors]
#align unique_factorization_monoid.normalized_factors_zero UniqueFactorizationMonoid.normalizedFactors_zero
@[simp]
theorem normalizedFactors_one : normalizedFactors (1 : α) = 0 := by
cases' subsingleton_or_nontrivial α with h h
· dsimp [normalizedFactors, factors]
simp [Subsingleton.elim (1:α) 0]
· rw [← Multiset.rel_zero_right]
apply factors_unique irreducible_of_normalized_factor
· intro x hx
exfalso
apply Multiset.not_mem_zero x hx
· apply normalizedFactors_prod one_ne_zero
#align unique_factorization_monoid.normalized_factors_one UniqueFactorizationMonoid.normalizedFactors_one
@[simp]
theorem normalizedFactors_mul {x y : α} (hx : x ≠ 0) (hy : y ≠ 0) :
normalizedFactors (x * y) = normalizedFactors x + normalizedFactors y := by
have h : (normalize : α → α) = Associates.out ∘ Associates.mk := by
ext
rw [Function.comp_apply, Associates.out_mk]
rw [← Multiset.map_id' (normalizedFactors (x * y)), ← Multiset.map_id' (normalizedFactors x), ←
Multiset.map_id' (normalizedFactors y), ← Multiset.map_congr rfl normalize_normalized_factor, ←
Multiset.map_congr rfl normalize_normalized_factor, ←
Multiset.map_congr rfl normalize_normalized_factor, ← Multiset.map_add, h, ←
Multiset.map_map Associates.out, eq_comm, ← Multiset.map_map Associates.out]
refine congr rfl ?_
apply Multiset.map_mk_eq_map_mk_of_rel
apply factors_unique
· intro x hx
rcases Multiset.mem_add.1 hx with (hx | hx) <;> exact irreducible_of_normalized_factor x hx
· exact irreducible_of_normalized_factor
· rw [Multiset.prod_add]
exact
((normalizedFactors_prod hx).mul_mul (normalizedFactors_prod hy)).trans
(normalizedFactors_prod (mul_ne_zero hx hy)).symm
#align unique_factorization_monoid.normalized_factors_mul UniqueFactorizationMonoid.normalizedFactors_mul
@[simp]
theorem normalizedFactors_pow {x : α} (n : ℕ) :
normalizedFactors (x ^ n) = n • normalizedFactors x := by
induction' n with n ih
· simp
by_cases h0 : x = 0
· simp [h0, zero_pow n.succ_ne_zero, smul_zero]
rw [pow_succ', succ_nsmul', normalizedFactors_mul h0 (pow_ne_zero _ h0), ih]
#align unique_factorization_monoid.normalized_factors_pow UniqueFactorizationMonoid.normalizedFactors_pow
theorem _root_.Irreducible.normalizedFactors_pow {p : α} (hp : Irreducible p) (k : ℕ) :
normalizedFactors (p ^ k) = Multiset.replicate k (normalize p) := by
rw [UniqueFactorizationMonoid.normalizedFactors_pow, normalizedFactors_irreducible hp,
Multiset.nsmul_singleton]
#align irreducible.normalized_factors_pow Irreducible.normalizedFactors_pow
theorem normalizedFactors_prod_eq (s : Multiset α) (hs : ∀ a ∈ s, Irreducible a) :
normalizedFactors s.prod = s.map normalize := by
induction' s using Multiset.induction with a s ih
· rw [Multiset.prod_zero, normalizedFactors_one, Multiset.map_zero]
· have ia := hs a (Multiset.mem_cons_self a _)
have ib := fun b h => hs b (Multiset.mem_cons_of_mem h)
obtain rfl | ⟨b, hb⟩ := s.empty_or_exists_mem
· rw [Multiset.cons_zero, Multiset.prod_singleton, Multiset.map_singleton,
normalizedFactors_irreducible ia]
haveI := nontrivial_of_ne b 0 (ib b hb).ne_zero
rw [Multiset.prod_cons, Multiset.map_cons,
normalizedFactors_mul ia.ne_zero (Multiset.prod_ne_zero fun h => (ib 0 h).ne_zero rfl),
normalizedFactors_irreducible ia, ih ib, Multiset.singleton_add]
#align unique_factorization_monoid.normalized_factors_prod_eq UniqueFactorizationMonoid.normalizedFactors_prod_eq
theorem dvd_iff_normalizedFactors_le_normalizedFactors {x y : α} (hx : x ≠ 0) (hy : y ≠ 0) :
x ∣ y ↔ normalizedFactors x ≤ normalizedFactors y := by
constructor
· rintro ⟨c, rfl⟩
simp [hx, right_ne_zero_of_mul hy]
· rw [← (normalizedFactors_prod hx).dvd_iff_dvd_left, ←
(normalizedFactors_prod hy).dvd_iff_dvd_right]
apply Multiset.prod_dvd_prod_of_le
#align unique_factorization_monoid.dvd_iff_normalized_factors_le_normalized_factors UniqueFactorizationMonoid.dvd_iff_normalizedFactors_le_normalizedFactors
theorem associated_iff_normalizedFactors_eq_normalizedFactors {x y : α} (hx : x ≠ 0) (hy : y ≠ 0) :
x ~ᵤ y ↔ normalizedFactors x = normalizedFactors y := by
refine
⟨fun h => ?_, fun h =>
(normalizedFactors_prod hx).symm.trans (_root_.trans (by rw [h]) (normalizedFactors_prod hy))⟩
apply le_antisymm <;> rw [← dvd_iff_normalizedFactors_le_normalizedFactors]
all_goals simp [*, h.dvd, h.symm.dvd]
#align unique_factorization_monoid.associated_iff_normalized_factors_eq_normalized_factors UniqueFactorizationMonoid.associated_iff_normalizedFactors_eq_normalizedFactors
theorem normalizedFactors_of_irreducible_pow {p : α} (hp : Irreducible p) (k : ℕ) :
normalizedFactors (p ^ k) = Multiset.replicate k (normalize p) := by
rw [normalizedFactors_pow, normalizedFactors_irreducible hp, Multiset.nsmul_singleton]
#align unique_factorization_monoid.normalized_factors_of_irreducible_pow UniqueFactorizationMonoid.normalizedFactors_of_irreducible_pow
theorem zero_not_mem_normalizedFactors (x : α) : (0 : α) ∉ normalizedFactors x := fun h =>
Prime.ne_zero (prime_of_normalized_factor _ h) rfl
#align unique_factorization_monoid.zero_not_mem_normalized_factors UniqueFactorizationMonoid.zero_not_mem_normalizedFactors
theorem dvd_of_mem_normalizedFactors {a p : α} (H : p ∈ normalizedFactors a) : p ∣ a := by
by_cases hcases : a = 0
· rw [hcases]
exact dvd_zero p
· exact dvd_trans (Multiset.dvd_prod H) (Associated.dvd (normalizedFactors_prod hcases))
#align unique_factorization_monoid.dvd_of_mem_normalized_factors UniqueFactorizationMonoid.dvd_of_mem_normalizedFactors
theorem mem_normalizedFactors_iff [Unique αˣ] {p x : α} (hx : x ≠ 0) :
p ∈ normalizedFactors x ↔ Prime p ∧ p ∣ x := by
constructor
· intro h
exact ⟨prime_of_normalized_factor p h, dvd_of_mem_normalizedFactors h⟩
· rintro ⟨hprime, hdvd⟩
obtain ⟨q, hqmem, hqeq⟩ := exists_mem_normalizedFactors_of_dvd hx hprime.irreducible hdvd
rw [associated_iff_eq] at hqeq
exact hqeq ▸ hqmem
theorem exists_associated_prime_pow_of_unique_normalized_factor {p r : α}
(h : ∀ {m}, m ∈ normalizedFactors r → m = p) (hr : r ≠ 0) : ∃ i : ℕ, Associated (p ^ i) r := by
use Multiset.card.toFun (normalizedFactors r)
have := UniqueFactorizationMonoid.normalizedFactors_prod hr
rwa [Multiset.eq_replicate_of_mem fun b => h, Multiset.prod_replicate] at this
#align unique_factorization_monoid.exists_associated_prime_pow_of_unique_normalized_factor UniqueFactorizationMonoid.exists_associated_prime_pow_of_unique_normalized_factor
theorem normalizedFactors_prod_of_prime [Nontrivial α] [Unique αˣ] {m : Multiset α}
(h : ∀ p ∈ m, Prime p) : normalizedFactors m.prod = m := by
simpa only [← Multiset.rel_eq, ← associated_eq_eq] using
prime_factors_unique prime_of_normalized_factor h
(normalizedFactors_prod (m.prod_ne_zero_of_prime h))
#align unique_factorization_monoid.normalized_factors_prod_of_prime UniqueFactorizationMonoid.normalizedFactors_prod_of_prime
theorem mem_normalizedFactors_eq_of_associated {a b c : α} (ha : a ∈ normalizedFactors c)
(hb : b ∈ normalizedFactors c) (h : Associated a b) : a = b := by
rw [← normalize_normalized_factor a ha, ← normalize_normalized_factor b hb,
normalize_eq_normalize_iff]
exact Associated.dvd_dvd h
#align unique_factorization_monoid.mem_normalized_factors_eq_of_associated UniqueFactorizationMonoid.mem_normalizedFactors_eq_of_associated
@[simp]
theorem normalizedFactors_pos (x : α) (hx : x ≠ 0) : 0 < normalizedFactors x ↔ ¬IsUnit x := by
constructor
· intro h hx
obtain ⟨p, hp⟩ := Multiset.exists_mem_of_ne_zero h.ne'
exact
(prime_of_normalized_factor _ hp).not_unit
(isUnit_of_dvd_unit (dvd_of_mem_normalizedFactors hp) hx)
· intro h
obtain ⟨p, hp⟩ := exists_mem_normalizedFactors hx h
exact
bot_lt_iff_ne_bot.mpr
(mt Multiset.eq_zero_iff_forall_not_mem.mp (not_forall.mpr ⟨p, not_not.mpr hp⟩))
#align unique_factorization_monoid.normalized_factors_pos UniqueFactorizationMonoid.normalizedFactors_pos
theorem dvdNotUnit_iff_normalizedFactors_lt_normalizedFactors {x y : α} (hx : x ≠ 0) (hy : y ≠ 0) :
DvdNotUnit x y ↔ normalizedFactors x < normalizedFactors y := by
constructor
· rintro ⟨_, c, hc, rfl⟩
simp only [hx, right_ne_zero_of_mul hy, normalizedFactors_mul, Ne, not_false_iff,
lt_add_iff_pos_right, normalizedFactors_pos, hc]
· intro h
exact
dvdNotUnit_of_dvd_of_not_dvd
((dvd_iff_normalizedFactors_le_normalizedFactors hx hy).mpr h.le)
(mt (dvd_iff_normalizedFactors_le_normalizedFactors hy hx).mp h.not_le)
#align unique_factorization_monoid.dvd_not_unit_iff_normalized_factors_lt_normalized_factors UniqueFactorizationMonoid.dvdNotUnit_iff_normalizedFactors_lt_normalizedFactors
theorem normalizedFactors_multiset_prod (s : Multiset α) (hs : 0 ∉ s) :
normalizedFactors (s.prod) = (s.map normalizedFactors).sum := by
cases subsingleton_or_nontrivial α
· obtain rfl : s = 0 := by
apply Multiset.eq_zero_of_forall_not_mem
intro _
convert hs
simp
induction s using Multiset.induction with
| empty => simp
| cons _ _ IH =>
rw [Multiset.prod_cons, Multiset.map_cons, Multiset.sum_cons, normalizedFactors_mul, IH]
· exact fun h ↦ hs (Multiset.mem_cons_of_mem h)
· exact fun h ↦ hs (h ▸ Multiset.mem_cons_self _ _)
· apply Multiset.prod_ne_zero
exact fun h ↦ hs (Multiset.mem_cons_of_mem h)
end UniqueFactorizationMonoid
namespace UniqueFactorizationMonoid
open scoped Classical
open Multiset Associates
variable [CancelCommMonoidWithZero α] [UniqueFactorizationMonoid α]
/-- Noncomputably defines a `normalizationMonoid` structure on a `UniqueFactorizationMonoid`. -/
protected noncomputable def normalizationMonoid : NormalizationMonoid α :=
normalizationMonoidOfMonoidHomRightInverse
{ toFun := fun a : Associates α =>
if a = 0 then 0
else
((normalizedFactors a).map
(Classical.choose mk_surjective.hasRightInverse : Associates α → α)).prod
map_one' := by nontriviality α; simp
map_mul' := fun x y => by
by_cases hx : x = 0
· simp [hx]
by_cases hy : y = 0
· simp [hy]
simp [hx, hy] }
(by
intro x
dsimp
by_cases hx : x = 0
· simp [hx]
have h : Associates.mkMonoidHom ∘ Classical.choose mk_surjective.hasRightInverse =
(id : Associates α → Associates α) := by
ext x
rw [Function.comp_apply, mkMonoidHom_apply,
Classical.choose_spec mk_surjective.hasRightInverse x]
rfl
rw [if_neg hx, ← mkMonoidHom_apply, MonoidHom.map_multiset_prod, map_map, h, map_id, ←
associated_iff_eq]
apply normalizedFactors_prod hx)
#align unique_factorization_monoid.normalization_monoid UniqueFactorizationMonoid.normalizationMonoid
end UniqueFactorizationMonoid
namespace UniqueFactorizationMonoid
variable {R : Type*} [CancelCommMonoidWithZero R] [UniqueFactorizationMonoid R]
theorem isRelPrime_iff_no_prime_factors {a b : R} (ha : a ≠ 0) :
IsRelPrime a b ↔ ∀ ⦃d⦄, d ∣ a → d ∣ b → ¬Prime d :=
⟨fun h _ ha hb ↦ (·.not_unit <| h ha hb), fun h ↦ WfDvdMonoid.isRelPrime_of_no_irreducible_factors
(ha ·.1) fun _ irr ha hb ↦ h ha hb (UniqueFactorizationMonoid.irreducible_iff_prime.mp irr)⟩
#align unique_factorization_monoid.no_factors_of_no_prime_factors UniqueFactorizationMonoid.isRelPrime_iff_no_prime_factors
/-- Euclid's lemma: if `a ∣ b * c` and `a` and `c` have no common prime factors, `a ∣ b`.
Compare `IsCoprime.dvd_of_dvd_mul_left`. -/
theorem dvd_of_dvd_mul_left_of_no_prime_factors {a b c : R} (ha : a ≠ 0)
(h : ∀ ⦃d⦄, d ∣ a → d ∣ c → ¬Prime d) : a ∣ b * c → a ∣ b :=
((isRelPrime_iff_no_prime_factors ha).mpr h).dvd_of_dvd_mul_right
#align unique_factorization_monoid.dvd_of_dvd_mul_left_of_no_prime_factors UniqueFactorizationMonoid.dvd_of_dvd_mul_left_of_no_prime_factors
/-- Euclid's lemma: if `a ∣ b * c` and `a` and `b` have no common prime factors, `a ∣ c`.
Compare `IsCoprime.dvd_of_dvd_mul_right`. -/
theorem dvd_of_dvd_mul_right_of_no_prime_factors {a b c : R} (ha : a ≠ 0)
(no_factors : ∀ {d}, d ∣ a → d ∣ b → ¬Prime d) : a ∣ b * c → a ∣ c := by
simpa [mul_comm b c] using dvd_of_dvd_mul_left_of_no_prime_factors ha @no_factors
#align unique_factorization_monoid.dvd_of_dvd_mul_right_of_no_prime_factors UniqueFactorizationMonoid.dvd_of_dvd_mul_right_of_no_prime_factors
/-- If `a ≠ 0, b` are elements of a unique factorization domain, then dividing
out their common factor `c'` gives `a'` and `b'` with no factors in common. -/
theorem exists_reduced_factors :
∀ a ≠ (0 : R), ∀ b,
∃ a' b' c', IsRelPrime a' b' ∧ c' * a' = a ∧ c' * b' = b := by
intro a
refine induction_on_prime a ?_ ?_ ?_
· intros
contradiction
· intro a a_unit _ b
use a, b, 1
constructor
· intro p p_dvd_a _
exact isUnit_of_dvd_unit p_dvd_a a_unit
· simp
· intro a p a_ne_zero p_prime ih_a pa_ne_zero b
by_cases h : p ∣ b
· rcases h with ⟨b, rfl⟩
obtain ⟨a', b', c', no_factor, ha', hb'⟩ := ih_a a_ne_zero b
refine ⟨a', b', p * c', @no_factor, ?_, ?_⟩
· rw [mul_assoc, ha']
· rw [mul_assoc, hb']
· obtain ⟨a', b', c', coprime, rfl, rfl⟩ := ih_a a_ne_zero b
refine ⟨p * a', b', c', ?_, mul_left_comm _ _ _, rfl⟩
intro q q_dvd_pa' q_dvd_b'
cases' p_prime.left_dvd_or_dvd_right_of_dvd_mul q_dvd_pa' with p_dvd_q q_dvd_a'
· have : p ∣ c' * b' := dvd_mul_of_dvd_right (p_dvd_q.trans q_dvd_b') _
contradiction
exact coprime q_dvd_a' q_dvd_b'
#align unique_factorization_monoid.exists_reduced_factors UniqueFactorizationMonoid.exists_reduced_factors
theorem exists_reduced_factors' (a b : R) (hb : b ≠ 0) :
∃ a' b' c', IsRelPrime a' b' ∧ c' * a' = a ∧ c' * b' = b :=
let ⟨b', a', c', no_factor, hb, ha⟩ := exists_reduced_factors b hb a
⟨a', b', c', fun _ hpb hpa => no_factor hpa hpb, ha, hb⟩
#align unique_factorization_monoid.exists_reduced_factors' UniqueFactorizationMonoid.exists_reduced_factors'
theorem pow_right_injective {a : R} (ha0 : a ≠ 0) (ha1 : ¬IsUnit a) :
Function.Injective (a ^ · : ℕ → R) := by
letI := Classical.decEq R
intro i j hij
letI : Nontrivial R := ⟨⟨a, 0, ha0⟩⟩
letI : NormalizationMonoid R := UniqueFactorizationMonoid.normalizationMonoid
obtain ⟨p', hp', dvd'⟩ := WfDvdMonoid.exists_irreducible_factor ha1 ha0
obtain ⟨p, mem, _⟩ := exists_mem_normalizedFactors_of_dvd ha0 hp' dvd'
have := congr_arg (fun x => Multiset.count p (normalizedFactors x)) hij
simp only [normalizedFactors_pow, Multiset.count_nsmul] at this
exact mul_right_cancel₀ (Multiset.count_ne_zero.mpr mem) this
#align unique_factorization_monoid.pow_right_injective UniqueFactorizationMonoid.pow_right_injective
theorem pow_eq_pow_iff {a : R} (ha0 : a ≠ 0) (ha1 : ¬IsUnit a) {i j : ℕ} : a ^ i = a ^ j ↔ i = j :=
(pow_right_injective ha0 ha1).eq_iff
#align unique_factorization_monoid.pow_eq_pow_iff UniqueFactorizationMonoid.pow_eq_pow_iff
section multiplicity
variable [NormalizationMonoid R]
variable [DecidableRel (Dvd.dvd : R → R → Prop)]
open multiplicity Multiset
theorem le_multiplicity_iff_replicate_le_normalizedFactors {a b : R} {n : ℕ} (ha : Irreducible a)
(hb : b ≠ 0) :
↑n ≤ multiplicity a b ↔ replicate n (normalize a) ≤ normalizedFactors b := by
rw [← pow_dvd_iff_le_multiplicity]
revert b
induction' n with n ih; · simp
intro b hb
constructor
· rintro ⟨c, rfl⟩
rw [Ne, pow_succ', mul_assoc, mul_eq_zero, not_or] at hb
rw [pow_succ', mul_assoc, normalizedFactors_mul hb.1 hb.2, replicate_succ,
normalizedFactors_irreducible ha, singleton_add, cons_le_cons_iff, ← ih hb.2]
apply Dvd.intro _ rfl
· rw [Multiset.le_iff_exists_add]
rintro ⟨u, hu⟩
rw [← (normalizedFactors_prod hb).dvd_iff_dvd_right, hu, prod_add, prod_replicate]
exact (Associated.pow_pow <| associated_normalize a).dvd.trans (Dvd.intro u.prod rfl)
#align unique_factorization_monoid.le_multiplicity_iff_replicate_le_normalized_factors UniqueFactorizationMonoid.le_multiplicity_iff_replicate_le_normalizedFactors
/-- The multiplicity of an irreducible factor of a nonzero element is exactly the number of times
the normalized factor occurs in the `normalizedFactors`.
See also `count_normalizedFactors_eq` which expands the definition of `multiplicity`
to produce a specification for `count (normalizedFactors _) _`..
-/
theorem multiplicity_eq_count_normalizedFactors [DecidableEq R] {a b : R} (ha : Irreducible a)
(hb : b ≠ 0) : multiplicity a b = (normalizedFactors b).count (normalize a) := by
apply le_antisymm
· apply PartENat.le_of_lt_add_one
rw [← Nat.cast_one, ← Nat.cast_add, lt_iff_not_ge, ge_iff_le,
le_multiplicity_iff_replicate_le_normalizedFactors ha hb, ← le_count_iff_replicate_le]
simp
rw [le_multiplicity_iff_replicate_le_normalizedFactors ha hb, ← le_count_iff_replicate_le]
#align unique_factorization_monoid.multiplicity_eq_count_normalized_factors UniqueFactorizationMonoid.multiplicity_eq_count_normalizedFactors
/-- The number of times an irreducible factor `p` appears in `normalizedFactors x` is defined by
the number of times it divides `x`.
See also `multiplicity_eq_count_normalizedFactors` if `n` is given by `multiplicity p x`.
-/
theorem count_normalizedFactors_eq [DecidableEq R] {p x : R} (hp : Irreducible p)
(hnorm : normalize p = p) {n : ℕ} (hle : p ^ n ∣ x) (hlt : ¬p ^ (n + 1) ∣ x) :
(normalizedFactors x).count p = n := by
letI : DecidableRel ((· ∣ ·) : R → R → Prop) := fun _ _ => Classical.propDecidable _
by_cases hx0 : x = 0
· simp [hx0] at hlt
rw [← PartENat.natCast_inj]
convert (multiplicity_eq_count_normalizedFactors hp hx0).symm
· exact hnorm.symm
exact (multiplicity.eq_coe_iff.mpr ⟨hle, hlt⟩).symm
#align unique_factorization_monoid.count_normalized_factors_eq UniqueFactorizationMonoid.count_normalizedFactors_eq
/-- The number of times an irreducible factor `p` appears in `normalizedFactors x` is defined by
the number of times it divides `x`. This is a slightly more general version of
`UniqueFactorizationMonoid.count_normalizedFactors_eq` that allows `p = 0`.
See also `multiplicity_eq_count_normalizedFactors` if `n` is given by `multiplicity p x`.
-/
theorem count_normalizedFactors_eq' [DecidableEq R] {p x : R} (hp : p = 0 ∨ Irreducible p)
(hnorm : normalize p = p) {n : ℕ} (hle : p ^ n ∣ x) (hlt : ¬p ^ (n + 1) ∣ x) :
(normalizedFactors x).count p = n := by
rcases hp with (rfl | hp)
· cases n
· exact count_eq_zero.2 (zero_not_mem_normalizedFactors _)
· rw [zero_pow (Nat.succ_ne_zero _)] at hle hlt
exact absurd hle hlt
· exact count_normalizedFactors_eq hp hnorm hle hlt
#align unique_factorization_monoid.count_normalized_factors_eq' UniqueFactorizationMonoid.count_normalizedFactors_eq'
/-- Deprecated. Use `WfDvdMonoid.max_power_factor` instead. -/
@[deprecated WfDvdMonoid.max_power_factor]
theorem max_power_factor {a₀ x : R} (h : a₀ ≠ 0) (hx : Irreducible x) :
∃ n : ℕ, ∃ a : R, ¬x ∣ a ∧ a₀ = x ^ n * a := WfDvdMonoid.max_power_factor h hx
#align unique_factorization_monoid.max_power_factor UniqueFactorizationMonoid.max_power_factor
end multiplicity
section Multiplicative
variable [CancelCommMonoidWithZero α] [UniqueFactorizationMonoid α]
variable {β : Type*} [CancelCommMonoidWithZero β]
theorem prime_pow_coprime_prod_of_coprime_insert [DecidableEq α] {s : Finset α} (i : α → ℕ) (p : α)
(hps : p ∉ s) (is_prime : ∀ q ∈ insert p s, Prime q)
(is_coprime : ∀ᵉ (q ∈ insert p s) (q' ∈ insert p s), q ∣ q' → q = q') :
IsRelPrime (p ^ i p) (∏ p' ∈ s, p' ^ i p') := by
have hp := is_prime _ (Finset.mem_insert_self _ _)
refine (isRelPrime_iff_no_prime_factors <| pow_ne_zero _ hp.ne_zero).mpr ?_
intro d hdp hdprod hd
apply hps
replace hdp := hd.dvd_of_dvd_pow hdp
obtain ⟨q, q_mem', hdq⟩ := hd.exists_mem_multiset_dvd hdprod
obtain ⟨q, q_mem, rfl⟩ := Multiset.mem_map.mp q_mem'
replace hdq := hd.dvd_of_dvd_pow hdq
have : p ∣ q := dvd_trans (hd.irreducible.dvd_symm hp.irreducible hdp) hdq
convert q_mem
rw [Finset.mem_val,
is_coprime _ (Finset.mem_insert_self p s) _ (Finset.mem_insert_of_mem q_mem) this]
#align unique_factorization_monoid.prime_pow_coprime_prod_of_coprime_insert UniqueFactorizationMonoid.prime_pow_coprime_prod_of_coprime_insert
/-- If `P` holds for units and powers of primes,
and `P x ∧ P y` for coprime `x, y` implies `P (x * y)`,
then `P` holds on a product of powers of distinct primes. -/
-- @[elab_as_elim] Porting note: commented out
theorem induction_on_prime_power {P : α → Prop} (s : Finset α) (i : α → ℕ)
(is_prime : ∀ p ∈ s, Prime p) (is_coprime : ∀ᵉ (p ∈ s) (q ∈ s), p ∣ q → p = q)
(h1 : ∀ {x}, IsUnit x → P x) (hpr : ∀ {p} (i : ℕ), Prime p → P (p ^ i))
(hcp : ∀ {x y}, IsRelPrime x y → P x → P y → P (x * y)) :
P (∏ p ∈ s, p ^ i p) := by
letI := Classical.decEq α
induction' s using Finset.induction_on with p f' hpf' ih
· simpa using h1 isUnit_one
rw [Finset.prod_insert hpf']
exact
hcp (prime_pow_coprime_prod_of_coprime_insert i p hpf' is_prime is_coprime)
(hpr (i p) (is_prime _ (Finset.mem_insert_self _ _)))
(ih (fun q hq => is_prime _ (Finset.mem_insert_of_mem hq)) fun q hq q' hq' =>
is_coprime _ (Finset.mem_insert_of_mem hq) _ (Finset.mem_insert_of_mem hq'))
#align unique_factorization_monoid.induction_on_prime_power UniqueFactorizationMonoid.induction_on_prime_power
/-- If `P` holds for `0`, units and powers of primes,
and `P x ∧ P y` for coprime `x, y` implies `P (x * y)`,
then `P` holds on all `a : α`. -/
@[elab_as_elim]
| Mathlib/RingTheory/UniqueFactorizationDomain.lean | 1,117 | 1,132 | theorem induction_on_coprime {P : α → Prop} (a : α) (h0 : P 0) (h1 : ∀ {x}, IsUnit x → P x)
(hpr : ∀ {p} (i : ℕ), Prime p → P (p ^ i))
(hcp : ∀ {x y}, IsRelPrime x y → P x → P y → P (x * y)) : P a := by |
letI := Classical.decEq α
have P_of_associated : ∀ {x y}, Associated x y → P x → P y := by
rintro x y ⟨u, rfl⟩ hx
exact hcp (fun p _ hpx => isUnit_of_dvd_unit hpx u.isUnit) hx (h1 u.isUnit)
by_cases ha0 : a = 0
· rwa [ha0]
haveI : Nontrivial α := ⟨⟨_, _, ha0⟩⟩
letI : NormalizationMonoid α := UniqueFactorizationMonoid.normalizationMonoid
refine P_of_associated (normalizedFactors_prod ha0) ?_
rw [← (normalizedFactors a).map_id, Finset.prod_multiset_map_count]
refine induction_on_prime_power _ _ ?_ ?_ @h1 @hpr @hcp <;> simp only [Multiset.mem_toFinset]
· apply prime_of_normalized_factor
· apply normalizedFactors_eq_of_dvd
|
/-
Copyright (c) 2022 Michael Stoll. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Michael Stoll
-/
import Mathlib.NumberTheory.LegendreSymbol.JacobiSymbol
#align_import number_theory.legendre_symbol.norm_num from "leanprover-community/mathlib"@"e2621d935895abe70071ab828a4ee6e26a52afe4"
/-!
# A `norm_num` extension for Jacobi and Legendre symbols
We extend the `norm_num` tactic so that it can be used to provably compute
the value of the Jacobi symbol `J(a | b)` or the Legendre symbol `legendreSym p a` when
the arguments are numerals.
## Implementation notes
We use the Law of Quadratic Reciprocity for the Jacobi symbol to compute the value of `J(a | b)`
efficiently, roughly comparable in effort with the euclidean algorithm for the computation
of the gcd of `a` and `b`. More precisely, the computation is done in the following steps.
* Use `J(a | 0) = 1` (an artifact of the definition) and `J(a | 1) = 1` to deal
with corner cases.
* Use `J(a | b) = J(a % b | b)` to reduce to the case that `a` is a natural number.
We define a version of the Jacobi symbol restricted to natural numbers for use in
the following steps; see `NormNum.jacobiSymNat`. (But we'll continue to write `J(a | b)`
in this description.)
* Remove powers of two from `b`. This is done via `J(2a | 2b) = 0` and
`J(2a+1 | 2b) = J(2a+1 | b)` (another artifact of the definition).
* Now `0 ≤ a < b` and `b` is odd. If `b = 1`, then the value is `1`.
If `a = 0` (and `b > 1`), then the value is `0`. Otherwise, we remove powers of two from `a`
via `J(4a | b) = J(a | b)` and `J(2a | b) = ±J(a | b)`, where the sign is determined
by the residue class of `b` mod 8, to reduce to `a` odd.
* Once `a` is odd, we use Quadratic Reciprocity (QR) in the form
`J(a | b) = ±J(b % a | a)`, where the sign is determined by the residue classes
of `a` and `b` mod 4. We are then back in the previous case.
We provide customized versions of these results for the various reduction steps,
where we encode the residue classes mod 2, mod 4, or mod 8 by using hypotheses like
`a % n = b`. In this way, the only divisions we have to compute and prove
are the ones occurring in the use of QR above.
-/
section Lemmas
namespace Mathlib.Meta.NormNum
/-- The Jacobi symbol restricted to natural numbers in both arguments. -/
def jacobiSymNat (a b : ℕ) : ℤ :=
jacobiSym a b
#align norm_num.jacobi_sym_nat Mathlib.Meta.NormNum.jacobiSymNat
/-!
### API Lemmas
We repeat part of the API for `jacobiSym` with `NormNum.jacobiSymNat` and without implicit
arguments, in a form that is suitable for constructing proofs in `norm_num`.
-/
/-- Base cases: `b = 0`, `b = 1`, `a = 0`, `a = 1`. -/
theorem jacobiSymNat.zero_right (a : ℕ) : jacobiSymNat a 0 = 1 := by
rw [jacobiSymNat, jacobiSym.zero_right]
#align norm_num.jacobi_sym_nat.zero_right Mathlib.Meta.NormNum.jacobiSymNat.zero_right
theorem jacobiSymNat.one_right (a : ℕ) : jacobiSymNat a 1 = 1 := by
rw [jacobiSymNat, jacobiSym.one_right]
#align norm_num.jacobi_sym_nat.one_right Mathlib.Meta.NormNum.jacobiSymNat.one_right
theorem jacobiSymNat.zero_left (b : ℕ) (hb : Nat.beq (b / 2) 0 = false) : jacobiSymNat 0 b = 0 := by
rw [jacobiSymNat, Nat.cast_zero, jacobiSym.zero_left ?_]
calc
1 < 2 * 1 := by decide
_ ≤ 2 * (b / 2) :=
Nat.mul_le_mul_left _ (Nat.succ_le.mpr (Nat.pos_of_ne_zero (Nat.ne_of_beq_eq_false hb)))
_ ≤ b := Nat.mul_div_le b 2
#align norm_num.jacobi_sym_nat.zero_left_even Mathlib.Meta.NormNum.jacobiSymNat.zero_left
#align norm_num.jacobi_sym_nat.zero_left_odd Mathlib.Meta.NormNum.jacobiSymNat.zero_left
| Mathlib/Tactic/NormNum/LegendreSymbol.lean | 86 | 87 | theorem jacobiSymNat.one_left (b : ℕ) : jacobiSymNat 1 b = 1 := by |
rw [jacobiSymNat, Nat.cast_one, jacobiSym.one_left]
|
/-
Copyright (c) 2014 Jeremy Avigad. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jeremy Avigad, Andrew Zipperer, Haitao Zhang, Minchao Wu, Yury Kudryashov
-/
import Mathlib.Data.Set.Prod
import Mathlib.Logic.Function.Conjugate
#align_import data.set.function from "leanprover-community/mathlib"@"996b0ff959da753a555053a480f36e5f264d4207"
/-!
# Functions over sets
## Main definitions
### Predicate
* `Set.EqOn f₁ f₂ s` : functions `f₁` and `f₂` are equal at every point of `s`;
* `Set.MapsTo f s t` : `f` sends every point of `s` to a point of `t`;
* `Set.InjOn f s` : restriction of `f` to `s` is injective;
* `Set.SurjOn f s t` : every point in `s` has a preimage in `s`;
* `Set.BijOn f s t` : `f` is a bijection between `s` and `t`;
* `Set.LeftInvOn f' f s` : for every `x ∈ s` we have `f' (f x) = x`;
* `Set.RightInvOn f' f t` : for every `y ∈ t` we have `f (f' y) = y`;
* `Set.InvOn f' f s t` : `f'` is a two-side inverse of `f` on `s` and `t`, i.e.
we have `Set.LeftInvOn f' f s` and `Set.RightInvOn f' f t`.
### Functions
* `Set.restrict f s` : restrict the domain of `f` to the set `s`;
* `Set.codRestrict f s h` : given `h : ∀ x, f x ∈ s`, restrict the codomain of `f` to the set `s`;
* `Set.MapsTo.restrict f s t h`: given `h : MapsTo f s t`, restrict the domain of `f` to `s`
and the codomain to `t`.
-/
variable {α β γ : Type*} {ι : Sort*} {π : α → Type*}
open Equiv Equiv.Perm Function
namespace Set
/-! ### Restrict -/
section restrict
/-- Restrict domain of a function `f` to a set `s`. Same as `Subtype.restrict` but this version
takes an argument `↥s` instead of `Subtype s`. -/
def restrict (s : Set α) (f : ∀ a : α, π a) : ∀ a : s, π a := fun x => f x
#align set.restrict Set.restrict
theorem restrict_eq (f : α → β) (s : Set α) : s.restrict f = f ∘ Subtype.val :=
rfl
#align set.restrict_eq Set.restrict_eq
@[simp]
theorem restrict_apply (f : α → β) (s : Set α) (x : s) : s.restrict f x = f x :=
rfl
#align set.restrict_apply Set.restrict_apply
theorem restrict_eq_iff {f : ∀ a, π a} {s : Set α} {g : ∀ a : s, π a} :
restrict s f = g ↔ ∀ (a) (ha : a ∈ s), f a = g ⟨a, ha⟩ :=
funext_iff.trans Subtype.forall
#align set.restrict_eq_iff Set.restrict_eq_iff
theorem eq_restrict_iff {s : Set α} {f : ∀ a : s, π a} {g : ∀ a, π a} :
f = restrict s g ↔ ∀ (a) (ha : a ∈ s), f ⟨a, ha⟩ = g a :=
funext_iff.trans Subtype.forall
#align set.eq_restrict_iff Set.eq_restrict_iff
@[simp]
theorem range_restrict (f : α → β) (s : Set α) : Set.range (s.restrict f) = f '' s :=
(range_comp _ _).trans <| congr_arg (f '' ·) Subtype.range_coe
#align set.range_restrict Set.range_restrict
theorem image_restrict (f : α → β) (s t : Set α) :
s.restrict f '' (Subtype.val ⁻¹' t) = f '' (t ∩ s) := by
rw [restrict_eq, image_comp, image_preimage_eq_inter_range, Subtype.range_coe]
#align set.image_restrict Set.image_restrict
@[simp]
theorem restrict_dite {s : Set α} [∀ x, Decidable (x ∈ s)] (f : ∀ a ∈ s, β)
(g : ∀ a ∉ s, β) :
(s.restrict fun a => if h : a ∈ s then f a h else g a h) = (fun a : s => f a a.2) :=
funext fun a => dif_pos a.2
#align set.restrict_dite Set.restrict_dite
@[simp]
theorem restrict_dite_compl {s : Set α} [∀ x, Decidable (x ∈ s)] (f : ∀ a ∈ s, β)
(g : ∀ a ∉ s, β) :
(sᶜ.restrict fun a => if h : a ∈ s then f a h else g a h) = (fun a : (sᶜ : Set α) => g a a.2) :=
funext fun a => dif_neg a.2
#align set.restrict_dite_compl Set.restrict_dite_compl
@[simp]
theorem restrict_ite (f g : α → β) (s : Set α) [∀ x, Decidable (x ∈ s)] :
(s.restrict fun a => if a ∈ s then f a else g a) = s.restrict f :=
restrict_dite _ _
#align set.restrict_ite Set.restrict_ite
@[simp]
theorem restrict_ite_compl (f g : α → β) (s : Set α) [∀ x, Decidable (x ∈ s)] :
(sᶜ.restrict fun a => if a ∈ s then f a else g a) = sᶜ.restrict g :=
restrict_dite_compl _ _
#align set.restrict_ite_compl Set.restrict_ite_compl
@[simp]
theorem restrict_piecewise (f g : α → β) (s : Set α) [∀ x, Decidable (x ∈ s)] :
s.restrict (piecewise s f g) = s.restrict f :=
restrict_ite _ _ _
#align set.restrict_piecewise Set.restrict_piecewise
@[simp]
theorem restrict_piecewise_compl (f g : α → β) (s : Set α) [∀ x, Decidable (x ∈ s)] :
sᶜ.restrict (piecewise s f g) = sᶜ.restrict g :=
restrict_ite_compl _ _ _
#align set.restrict_piecewise_compl Set.restrict_piecewise_compl
theorem restrict_extend_range (f : α → β) (g : α → γ) (g' : β → γ) :
(range f).restrict (extend f g g') = fun x => g x.coe_prop.choose := by
classical
exact restrict_dite _ _
#align set.restrict_extend_range Set.restrict_extend_range
@[simp]
theorem restrict_extend_compl_range (f : α → β) (g : α → γ) (g' : β → γ) :
(range f)ᶜ.restrict (extend f g g') = g' ∘ Subtype.val := by
classical
exact restrict_dite_compl _ _
#align set.restrict_extend_compl_range Set.restrict_extend_compl_range
theorem range_extend_subset (f : α → β) (g : α → γ) (g' : β → γ) :
range (extend f g g') ⊆ range g ∪ g' '' (range f)ᶜ := by
classical
rintro _ ⟨y, rfl⟩
rw [extend_def]
split_ifs with h
exacts [Or.inl (mem_range_self _), Or.inr (mem_image_of_mem _ h)]
#align set.range_extend_subset Set.range_extend_subset
theorem range_extend {f : α → β} (hf : Injective f) (g : α → γ) (g' : β → γ) :
range (extend f g g') = range g ∪ g' '' (range f)ᶜ := by
refine (range_extend_subset _ _ _).antisymm ?_
rintro z (⟨x, rfl⟩ | ⟨y, hy, rfl⟩)
exacts [⟨f x, hf.extend_apply _ _ _⟩, ⟨y, extend_apply' _ _ _ hy⟩]
#align set.range_extend Set.range_extend
/-- Restrict codomain of a function `f` to a set `s`. Same as `Subtype.coind` but this version
has codomain `↥s` instead of `Subtype s`. -/
def codRestrict (f : ι → α) (s : Set α) (h : ∀ x, f x ∈ s) : ι → s := fun x => ⟨f x, h x⟩
#align set.cod_restrict Set.codRestrict
@[simp]
theorem val_codRestrict_apply (f : ι → α) (s : Set α) (h : ∀ x, f x ∈ s) (x : ι) :
(codRestrict f s h x : α) = f x :=
rfl
#align set.coe_cod_restrict_apply Set.val_codRestrict_apply
@[simp]
theorem restrict_comp_codRestrict {f : ι → α} {g : α → β} {b : Set α} (h : ∀ x, f x ∈ b) :
b.restrict g ∘ b.codRestrict f h = g ∘ f :=
rfl
#align set.restrict_comp_cod_restrict Set.restrict_comp_codRestrict
@[simp]
theorem injective_codRestrict {f : ι → α} {s : Set α} (h : ∀ x, f x ∈ s) :
Injective (codRestrict f s h) ↔ Injective f := by
simp only [Injective, Subtype.ext_iff, val_codRestrict_apply]
#align set.injective_cod_restrict Set.injective_codRestrict
alias ⟨_, _root_.Function.Injective.codRestrict⟩ := injective_codRestrict
#align function.injective.cod_restrict Function.Injective.codRestrict
end restrict
/-! ### Equality on a set -/
section equality
variable {s s₁ s₂ : Set α} {t t₁ t₂ : Set β} {p : Set γ} {f f₁ f₂ f₃ : α → β} {g g₁ g₂ : β → γ}
{f' f₁' f₂' : β → α} {g' : γ → β} {a : α} {b : β}
@[simp]
theorem eqOn_empty (f₁ f₂ : α → β) : EqOn f₁ f₂ ∅ := fun _ => False.elim
#align set.eq_on_empty Set.eqOn_empty
@[simp]
theorem eqOn_singleton : Set.EqOn f₁ f₂ {a} ↔ f₁ a = f₂ a := by
simp [Set.EqOn]
#align set.eq_on_singleton Set.eqOn_singleton
@[simp]
theorem eqOn_univ (f₁ f₂ : α → β) : EqOn f₁ f₂ univ ↔ f₁ = f₂ := by
simp [EqOn, funext_iff]
@[simp]
theorem restrict_eq_restrict_iff : restrict s f₁ = restrict s f₂ ↔ EqOn f₁ f₂ s :=
restrict_eq_iff
#align set.restrict_eq_restrict_iff Set.restrict_eq_restrict_iff
@[symm]
theorem EqOn.symm (h : EqOn f₁ f₂ s) : EqOn f₂ f₁ s := fun _ hx => (h hx).symm
#align set.eq_on.symm Set.EqOn.symm
theorem eqOn_comm : EqOn f₁ f₂ s ↔ EqOn f₂ f₁ s :=
⟨EqOn.symm, EqOn.symm⟩
#align set.eq_on_comm Set.eqOn_comm
-- This can not be tagged as `@[refl]` with the current argument order.
-- See note below at `EqOn.trans`.
theorem eqOn_refl (f : α → β) (s : Set α) : EqOn f f s := fun _ _ => rfl
#align set.eq_on_refl Set.eqOn_refl
-- Note: this was formerly tagged with `@[trans]`, and although the `trans` attribute accepted it
-- the `trans` tactic could not use it.
-- An update to the trans tactic coming in mathlib4#7014 will reject this attribute.
-- It can be restored by changing the argument order from `EqOn f₁ f₂ s` to `EqOn s f₁ f₂`.
-- This change will be made separately: [zulip](https://leanprover.zulipchat.com/#narrow/stream/287929-mathlib4/topic/Reordering.20arguments.20of.20.60Set.2EEqOn.60/near/390467581).
theorem EqOn.trans (h₁ : EqOn f₁ f₂ s) (h₂ : EqOn f₂ f₃ s) : EqOn f₁ f₃ s := fun _ hx =>
(h₁ hx).trans (h₂ hx)
#align set.eq_on.trans Set.EqOn.trans
theorem EqOn.image_eq (heq : EqOn f₁ f₂ s) : f₁ '' s = f₂ '' s :=
image_congr heq
#align set.eq_on.image_eq Set.EqOn.image_eq
/-- Variant of `EqOn.image_eq`, for one function being the identity. -/
theorem EqOn.image_eq_self {f : α → α} (h : Set.EqOn f id s) : f '' s = s := by
rw [h.image_eq, image_id]
theorem EqOn.inter_preimage_eq (heq : EqOn f₁ f₂ s) (t : Set β) : s ∩ f₁ ⁻¹' t = s ∩ f₂ ⁻¹' t :=
ext fun x => and_congr_right_iff.2 fun hx => by rw [mem_preimage, mem_preimage, heq hx]
#align set.eq_on.inter_preimage_eq Set.EqOn.inter_preimage_eq
theorem EqOn.mono (hs : s₁ ⊆ s₂) (hf : EqOn f₁ f₂ s₂) : EqOn f₁ f₂ s₁ := fun _ hx => hf (hs hx)
#align set.eq_on.mono Set.EqOn.mono
@[simp]
theorem eqOn_union : EqOn f₁ f₂ (s₁ ∪ s₂) ↔ EqOn f₁ f₂ s₁ ∧ EqOn f₁ f₂ s₂ :=
forall₂_or_left
#align set.eq_on_union Set.eqOn_union
theorem EqOn.union (h₁ : EqOn f₁ f₂ s₁) (h₂ : EqOn f₁ f₂ s₂) : EqOn f₁ f₂ (s₁ ∪ s₂) :=
eqOn_union.2 ⟨h₁, h₂⟩
#align set.eq_on.union Set.EqOn.union
theorem EqOn.comp_left (h : s.EqOn f₁ f₂) : s.EqOn (g ∘ f₁) (g ∘ f₂) := fun _ ha =>
congr_arg _ <| h ha
#align set.eq_on.comp_left Set.EqOn.comp_left
@[simp]
theorem eqOn_range {ι : Sort*} {f : ι → α} {g₁ g₂ : α → β} :
EqOn g₁ g₂ (range f) ↔ g₁ ∘ f = g₂ ∘ f :=
forall_mem_range.trans <| funext_iff.symm
#align set.eq_on_range Set.eqOn_range
alias ⟨EqOn.comp_eq, _⟩ := eqOn_range
#align set.eq_on.comp_eq Set.EqOn.comp_eq
end equality
/-! ### Congruence lemmas for monotonicity and antitonicity -/
section Order
variable {s : Set α} {f₁ f₂ : α → β} [Preorder α] [Preorder β]
theorem _root_.MonotoneOn.congr (h₁ : MonotoneOn f₁ s) (h : s.EqOn f₁ f₂) : MonotoneOn f₂ s := by
intro a ha b hb hab
rw [← h ha, ← h hb]
exact h₁ ha hb hab
#align monotone_on.congr MonotoneOn.congr
theorem _root_.AntitoneOn.congr (h₁ : AntitoneOn f₁ s) (h : s.EqOn f₁ f₂) : AntitoneOn f₂ s :=
h₁.dual_right.congr h
#align antitone_on.congr AntitoneOn.congr
theorem _root_.StrictMonoOn.congr (h₁ : StrictMonoOn f₁ s) (h : s.EqOn f₁ f₂) :
StrictMonoOn f₂ s := by
intro a ha b hb hab
rw [← h ha, ← h hb]
exact h₁ ha hb hab
#align strict_mono_on.congr StrictMonoOn.congr
theorem _root_.StrictAntiOn.congr (h₁ : StrictAntiOn f₁ s) (h : s.EqOn f₁ f₂) : StrictAntiOn f₂ s :=
h₁.dual_right.congr h
#align strict_anti_on.congr StrictAntiOn.congr
theorem EqOn.congr_monotoneOn (h : s.EqOn f₁ f₂) : MonotoneOn f₁ s ↔ MonotoneOn f₂ s :=
⟨fun h₁ => h₁.congr h, fun h₂ => h₂.congr h.symm⟩
#align set.eq_on.congr_monotone_on Set.EqOn.congr_monotoneOn
theorem EqOn.congr_antitoneOn (h : s.EqOn f₁ f₂) : AntitoneOn f₁ s ↔ AntitoneOn f₂ s :=
⟨fun h₁ => h₁.congr h, fun h₂ => h₂.congr h.symm⟩
#align set.eq_on.congr_antitone_on Set.EqOn.congr_antitoneOn
theorem EqOn.congr_strictMonoOn (h : s.EqOn f₁ f₂) : StrictMonoOn f₁ s ↔ StrictMonoOn f₂ s :=
⟨fun h₁ => h₁.congr h, fun h₂ => h₂.congr h.symm⟩
#align set.eq_on.congr_strict_mono_on Set.EqOn.congr_strictMonoOn
theorem EqOn.congr_strictAntiOn (h : s.EqOn f₁ f₂) : StrictAntiOn f₁ s ↔ StrictAntiOn f₂ s :=
⟨fun h₁ => h₁.congr h, fun h₂ => h₂.congr h.symm⟩
#align set.eq_on.congr_strict_anti_on Set.EqOn.congr_strictAntiOn
end Order
/-! ### Monotonicity lemmas-/
section Mono
variable {s s₁ s₂ : Set α} {f f₁ f₂ : α → β} [Preorder α] [Preorder β]
theorem _root_.MonotoneOn.mono (h : MonotoneOn f s) (h' : s₂ ⊆ s) : MonotoneOn f s₂ :=
fun _ hx _ hy => h (h' hx) (h' hy)
#align monotone_on.mono MonotoneOn.mono
theorem _root_.AntitoneOn.mono (h : AntitoneOn f s) (h' : s₂ ⊆ s) : AntitoneOn f s₂ :=
fun _ hx _ hy => h (h' hx) (h' hy)
#align antitone_on.mono AntitoneOn.mono
theorem _root_.StrictMonoOn.mono (h : StrictMonoOn f s) (h' : s₂ ⊆ s) : StrictMonoOn f s₂ :=
fun _ hx _ hy => h (h' hx) (h' hy)
#align strict_mono_on.mono StrictMonoOn.mono
theorem _root_.StrictAntiOn.mono (h : StrictAntiOn f s) (h' : s₂ ⊆ s) : StrictAntiOn f s₂ :=
fun _ hx _ hy => h (h' hx) (h' hy)
#align strict_anti_on.mono StrictAntiOn.mono
protected theorem _root_.MonotoneOn.monotone (h : MonotoneOn f s) :
Monotone (f ∘ Subtype.val : s → β) :=
fun x y hle => h x.coe_prop y.coe_prop hle
#align monotone_on.monotone MonotoneOn.monotone
protected theorem _root_.AntitoneOn.monotone (h : AntitoneOn f s) :
Antitone (f ∘ Subtype.val : s → β) :=
fun x y hle => h x.coe_prop y.coe_prop hle
#align antitone_on.monotone AntitoneOn.monotone
protected theorem _root_.StrictMonoOn.strictMono (h : StrictMonoOn f s) :
StrictMono (f ∘ Subtype.val : s → β) :=
fun x y hlt => h x.coe_prop y.coe_prop hlt
#align strict_mono_on.strict_mono StrictMonoOn.strictMono
protected theorem _root_.StrictAntiOn.strictAnti (h : StrictAntiOn f s) :
StrictAnti (f ∘ Subtype.val : s → β) :=
fun x y hlt => h x.coe_prop y.coe_prop hlt
#align strict_anti_on.strict_anti StrictAntiOn.strictAnti
end Mono
variable {s s₁ s₂ : Set α} {t t₁ t₂ : Set β} {p : Set γ} {f f₁ f₂ f₃ : α → β} {g g₁ g₂ : β → γ}
{f' f₁' f₂' : β → α} {g' : γ → β} {a : α} {b : β}
section MapsTo
theorem MapsTo.restrict_commutes (f : α → β) (s : Set α) (t : Set β) (h : MapsTo f s t) :
Subtype.val ∘ h.restrict f s t = f ∘ Subtype.val :=
rfl
@[simp]
theorem MapsTo.val_restrict_apply (h : MapsTo f s t) (x : s) : (h.restrict f s t x : β) = f x :=
rfl
#align set.maps_to.coe_restrict_apply Set.MapsTo.val_restrict_apply
theorem MapsTo.coe_iterate_restrict {f : α → α} (h : MapsTo f s s) (x : s) (k : ℕ) :
h.restrict^[k] x = f^[k] x := by
induction' k with k ih; · simp
simp only [iterate_succ', comp_apply, val_restrict_apply, ih]
/-- Restricting the domain and then the codomain is the same as `MapsTo.restrict`. -/
@[simp]
theorem codRestrict_restrict (h : ∀ x : s, f x ∈ t) :
codRestrict (s.restrict f) t h = MapsTo.restrict f s t fun x hx => h ⟨x, hx⟩ :=
rfl
#align set.cod_restrict_restrict Set.codRestrict_restrict
/-- Reverse of `Set.codRestrict_restrict`. -/
theorem MapsTo.restrict_eq_codRestrict (h : MapsTo f s t) :
h.restrict f s t = codRestrict (s.restrict f) t fun x => h x.2 :=
rfl
#align set.maps_to.restrict_eq_cod_restrict Set.MapsTo.restrict_eq_codRestrict
theorem MapsTo.coe_restrict (h : Set.MapsTo f s t) :
Subtype.val ∘ h.restrict f s t = s.restrict f :=
rfl
#align set.maps_to.coe_restrict Set.MapsTo.coe_restrict
theorem MapsTo.range_restrict (f : α → β) (s : Set α) (t : Set β) (h : MapsTo f s t) :
range (h.restrict f s t) = Subtype.val ⁻¹' (f '' s) :=
Set.range_subtype_map f h
#align set.maps_to.range_restrict Set.MapsTo.range_restrict
theorem mapsTo_iff_exists_map_subtype : MapsTo f s t ↔ ∃ g : s → t, ∀ x : s, f x = g x :=
⟨fun h => ⟨h.restrict f s t, fun _ => rfl⟩, fun ⟨g, hg⟩ x hx => by
erw [hg ⟨x, hx⟩]
apply Subtype.coe_prop⟩
#align set.maps_to_iff_exists_map_subtype Set.mapsTo_iff_exists_map_subtype
theorem mapsTo' : MapsTo f s t ↔ f '' s ⊆ t :=
image_subset_iff.symm
#align set.maps_to' Set.mapsTo'
theorem mapsTo_prod_map_diagonal : MapsTo (Prod.map f f) (diagonal α) (diagonal β) :=
diagonal_subset_iff.2 fun _ => rfl
#align set.maps_to_prod_map_diagonal Set.mapsTo_prod_map_diagonal
theorem MapsTo.subset_preimage {f : α → β} {s : Set α} {t : Set β} (hf : MapsTo f s t) :
s ⊆ f ⁻¹' t :=
hf
#align set.maps_to.subset_preimage Set.MapsTo.subset_preimage
@[simp]
theorem mapsTo_singleton {x : α} : MapsTo f {x} t ↔ f x ∈ t :=
singleton_subset_iff
#align set.maps_to_singleton Set.mapsTo_singleton
theorem mapsTo_empty (f : α → β) (t : Set β) : MapsTo f ∅ t :=
empty_subset _
#align set.maps_to_empty Set.mapsTo_empty
@[simp] theorem mapsTo_empty_iff : MapsTo f s ∅ ↔ s = ∅ := by
simp [mapsTo', subset_empty_iff]
/-- If `f` maps `s` to `t` and `s` is non-empty, `t` is non-empty. -/
theorem MapsTo.nonempty (h : MapsTo f s t) (hs : s.Nonempty) : t.Nonempty :=
(hs.image f).mono (mapsTo'.mp h)
theorem MapsTo.image_subset (h : MapsTo f s t) : f '' s ⊆ t :=
mapsTo'.1 h
#align set.maps_to.image_subset Set.MapsTo.image_subset
theorem MapsTo.congr (h₁ : MapsTo f₁ s t) (h : EqOn f₁ f₂ s) : MapsTo f₂ s t := fun _ hx =>
h hx ▸ h₁ hx
#align set.maps_to.congr Set.MapsTo.congr
theorem EqOn.comp_right (hg : t.EqOn g₁ g₂) (hf : s.MapsTo f t) : s.EqOn (g₁ ∘ f) (g₂ ∘ f) :=
fun _ ha => hg <| hf ha
#align set.eq_on.comp_right Set.EqOn.comp_right
theorem EqOn.mapsTo_iff (H : EqOn f₁ f₂ s) : MapsTo f₁ s t ↔ MapsTo f₂ s t :=
⟨fun h => h.congr H, fun h => h.congr H.symm⟩
#align set.eq_on.maps_to_iff Set.EqOn.mapsTo_iff
theorem MapsTo.comp (h₁ : MapsTo g t p) (h₂ : MapsTo f s t) : MapsTo (g ∘ f) s p := fun _ h =>
h₁ (h₂ h)
#align set.maps_to.comp Set.MapsTo.comp
theorem mapsTo_id (s : Set α) : MapsTo id s s := fun _ => id
#align set.maps_to_id Set.mapsTo_id
theorem MapsTo.iterate {f : α → α} {s : Set α} (h : MapsTo f s s) : ∀ n, MapsTo f^[n] s s
| 0 => fun _ => id
| n + 1 => (MapsTo.iterate h n).comp h
#align set.maps_to.iterate Set.MapsTo.iterate
theorem MapsTo.iterate_restrict {f : α → α} {s : Set α} (h : MapsTo f s s) (n : ℕ) :
(h.restrict f s s)^[n] = (h.iterate n).restrict _ _ _ := by
funext x
rw [Subtype.ext_iff, MapsTo.val_restrict_apply]
induction' n with n ihn generalizing x
· rfl
· simp [Nat.iterate, ihn]
#align set.maps_to.iterate_restrict Set.MapsTo.iterate_restrict
lemma mapsTo_of_subsingleton' [Subsingleton β] (f : α → β) (h : s.Nonempty → t.Nonempty) :
MapsTo f s t :=
fun a ha ↦ Subsingleton.mem_iff_nonempty.2 <| h ⟨a, ha⟩
#align set.maps_to_of_subsingleton' Set.mapsTo_of_subsingleton'
lemma mapsTo_of_subsingleton [Subsingleton α] (f : α → α) (s : Set α) : MapsTo f s s :=
mapsTo_of_subsingleton' _ id
#align set.maps_to_of_subsingleton Set.mapsTo_of_subsingleton
theorem MapsTo.mono (hf : MapsTo f s₁ t₁) (hs : s₂ ⊆ s₁) (ht : t₁ ⊆ t₂) : MapsTo f s₂ t₂ :=
fun _ hx => ht (hf <| hs hx)
#align set.maps_to.mono Set.MapsTo.mono
theorem MapsTo.mono_left (hf : MapsTo f s₁ t) (hs : s₂ ⊆ s₁) : MapsTo f s₂ t := fun _ hx =>
hf (hs hx)
#align set.maps_to.mono_left Set.MapsTo.mono_left
theorem MapsTo.mono_right (hf : MapsTo f s t₁) (ht : t₁ ⊆ t₂) : MapsTo f s t₂ := fun _ hx =>
ht (hf hx)
#align set.maps_to.mono_right Set.MapsTo.mono_right
theorem MapsTo.union_union (h₁ : MapsTo f s₁ t₁) (h₂ : MapsTo f s₂ t₂) :
MapsTo f (s₁ ∪ s₂) (t₁ ∪ t₂) := fun _ hx =>
hx.elim (fun hx => Or.inl <| h₁ hx) fun hx => Or.inr <| h₂ hx
#align set.maps_to.union_union Set.MapsTo.union_union
theorem MapsTo.union (h₁ : MapsTo f s₁ t) (h₂ : MapsTo f s₂ t) : MapsTo f (s₁ ∪ s₂) t :=
union_self t ▸ h₁.union_union h₂
#align set.maps_to.union Set.MapsTo.union
@[simp]
theorem mapsTo_union : MapsTo f (s₁ ∪ s₂) t ↔ MapsTo f s₁ t ∧ MapsTo f s₂ t :=
⟨fun h =>
⟨h.mono subset_union_left (Subset.refl t),
h.mono subset_union_right (Subset.refl t)⟩,
fun h => h.1.union h.2⟩
#align set.maps_to_union Set.mapsTo_union
theorem MapsTo.inter (h₁ : MapsTo f s t₁) (h₂ : MapsTo f s t₂) : MapsTo f s (t₁ ∩ t₂) := fun _ hx =>
⟨h₁ hx, h₂ hx⟩
#align set.maps_to.inter Set.MapsTo.inter
theorem MapsTo.inter_inter (h₁ : MapsTo f s₁ t₁) (h₂ : MapsTo f s₂ t₂) :
MapsTo f (s₁ ∩ s₂) (t₁ ∩ t₂) := fun _ hx => ⟨h₁ hx.1, h₂ hx.2⟩
#align set.maps_to.inter_inter Set.MapsTo.inter_inter
@[simp]
theorem mapsTo_inter : MapsTo f s (t₁ ∩ t₂) ↔ MapsTo f s t₁ ∧ MapsTo f s t₂ :=
⟨fun h =>
⟨h.mono (Subset.refl s) inter_subset_left,
h.mono (Subset.refl s) inter_subset_right⟩,
fun h => h.1.inter h.2⟩
#align set.maps_to_inter Set.mapsTo_inter
theorem mapsTo_univ (f : α → β) (s : Set α) : MapsTo f s univ := fun _ _ => trivial
#align set.maps_to_univ Set.mapsTo_univ
theorem mapsTo_range (f : α → β) (s : Set α) : MapsTo f s (range f) :=
(mapsTo_image f s).mono (Subset.refl s) (image_subset_range _ _)
#align set.maps_to_range Set.mapsTo_range
@[simp]
theorem mapsTo_image_iff {f : α → β} {g : γ → α} {s : Set γ} {t : Set β} :
MapsTo f (g '' s) t ↔ MapsTo (f ∘ g) s t :=
⟨fun h c hc => h ⟨c, hc, rfl⟩, fun h _ ⟨_, hc⟩ => hc.2 ▸ h hc.1⟩
#align set.maps_image_to Set.mapsTo_image_iff
@[deprecated (since := "2023-12-25")]
lemma maps_image_to (f : α → β) (g : γ → α) (s : Set γ) (t : Set β) :
MapsTo f (g '' s) t ↔ MapsTo (f ∘ g) s t :=
mapsTo_image_iff
lemma MapsTo.comp_left (g : β → γ) (hf : MapsTo f s t) : MapsTo (g ∘ f) s (g '' t) :=
fun x hx ↦ ⟨f x, hf hx, rfl⟩
#align set.maps_to.comp_left Set.MapsTo.comp_left
lemma MapsTo.comp_right {s : Set β} {t : Set γ} (hg : MapsTo g s t) (f : α → β) :
MapsTo (g ∘ f) (f ⁻¹' s) t := fun _ hx ↦ hg hx
#align set.maps_to.comp_right Set.MapsTo.comp_right
@[simp]
lemma mapsTo_univ_iff : MapsTo f univ t ↔ ∀ x, f x ∈ t :=
⟨fun h _ => h (mem_univ _), fun h x _ => h x⟩
@[deprecated (since := "2023-12-25")]
theorem maps_univ_to (f : α → β) (s : Set β) : MapsTo f univ s ↔ ∀ a, f a ∈ s :=
mapsTo_univ_iff
#align set.maps_univ_to Set.maps_univ_to
@[simp]
lemma mapsTo_range_iff {g : ι → α} : MapsTo f (range g) t ↔ ∀ i, f (g i) ∈ t :=
forall_mem_range
@[deprecated mapsTo_range_iff (since := "2023-12-25")]
theorem maps_range_to (f : α → β) (g : γ → α) (s : Set β) :
MapsTo f (range g) s ↔ MapsTo (f ∘ g) univ s := by rw [← image_univ, mapsTo_image_iff]
#align set.maps_range_to Set.maps_range_to
theorem surjective_mapsTo_image_restrict (f : α → β) (s : Set α) :
Surjective ((mapsTo_image f s).restrict f s (f '' s)) := fun ⟨_, x, hs, hxy⟩ =>
⟨⟨x, hs⟩, Subtype.ext hxy⟩
#align set.surjective_maps_to_image_restrict Set.surjective_mapsTo_image_restrict
theorem MapsTo.mem_iff (h : MapsTo f s t) (hc : MapsTo f sᶜ tᶜ) {x} : f x ∈ t ↔ x ∈ s :=
⟨fun ht => by_contra fun hs => hc hs ht, fun hx => h hx⟩
#align set.maps_to.mem_iff Set.MapsTo.mem_iff
end MapsTo
/-! ### Restriction onto preimage -/
section
variable (t)
variable (f s) in
theorem image_restrictPreimage :
t.restrictPreimage f '' (Subtype.val ⁻¹' s) = Subtype.val ⁻¹' (f '' s) := by
delta Set.restrictPreimage
rw [← (Subtype.coe_injective).image_injective.eq_iff, ← image_comp, MapsTo.restrict_commutes,
image_comp, Subtype.image_preimage_coe, Subtype.image_preimage_coe, image_preimage_inter]
variable (f) in
theorem range_restrictPreimage : range (t.restrictPreimage f) = Subtype.val ⁻¹' range f := by
simp only [← image_univ, ← image_restrictPreimage, preimage_univ]
#align set.range_restrict_preimage Set.range_restrictPreimage
variable {U : ι → Set β}
lemma restrictPreimage_injective (hf : Injective f) : Injective (t.restrictPreimage f) :=
fun _ _ e => Subtype.coe_injective <| hf <| Subtype.mk.inj e
#align set.restrict_preimage_injective Set.restrictPreimage_injective
lemma restrictPreimage_surjective (hf : Surjective f) : Surjective (t.restrictPreimage f) :=
fun x => ⟨⟨_, ((hf x).choose_spec.symm ▸ x.2 : _ ∈ t)⟩, Subtype.ext (hf x).choose_spec⟩
#align set.restrict_preimage_surjective Set.restrictPreimage_surjective
lemma restrictPreimage_bijective (hf : Bijective f) : Bijective (t.restrictPreimage f) :=
⟨t.restrictPreimage_injective hf.1, t.restrictPreimage_surjective hf.2⟩
#align set.restrict_preimage_bijective Set.restrictPreimage_bijective
alias _root_.Function.Injective.restrictPreimage := Set.restrictPreimage_injective
alias _root_.Function.Surjective.restrictPreimage := Set.restrictPreimage_surjective
alias _root_.Function.Bijective.restrictPreimage := Set.restrictPreimage_bijective
#align function.bijective.restrict_preimage Function.Bijective.restrictPreimage
#align function.surjective.restrict_preimage Function.Surjective.restrictPreimage
#align function.injective.restrict_preimage Function.Injective.restrictPreimage
end
/-! ### Injectivity on a set -/
section injOn
theorem Subsingleton.injOn (hs : s.Subsingleton) (f : α → β) : InjOn f s := fun _ hx _ hy _ =>
hs hx hy
#align set.subsingleton.inj_on Set.Subsingleton.injOn
@[simp]
theorem injOn_empty (f : α → β) : InjOn f ∅ :=
subsingleton_empty.injOn f
#align set.inj_on_empty Set.injOn_empty
@[simp]
theorem injOn_singleton (f : α → β) (a : α) : InjOn f {a} :=
subsingleton_singleton.injOn f
#align set.inj_on_singleton Set.injOn_singleton
@[simp] lemma injOn_pair {b : α} : InjOn f {a, b} ↔ f a = f b → a = b := by unfold InjOn; aesop
theorem InjOn.eq_iff {x y} (h : InjOn f s) (hx : x ∈ s) (hy : y ∈ s) : f x = f y ↔ x = y :=
⟨h hx hy, fun h => h ▸ rfl⟩
#align set.inj_on.eq_iff Set.InjOn.eq_iff
theorem InjOn.ne_iff {x y} (h : InjOn f s) (hx : x ∈ s) (hy : y ∈ s) : f x ≠ f y ↔ x ≠ y :=
(h.eq_iff hx hy).not
#align set.inj_on.ne_iff Set.InjOn.ne_iff
alias ⟨_, InjOn.ne⟩ := InjOn.ne_iff
#align set.inj_on.ne Set.InjOn.ne
theorem InjOn.congr (h₁ : InjOn f₁ s) (h : EqOn f₁ f₂ s) : InjOn f₂ s := fun _ hx _ hy =>
h hx ▸ h hy ▸ h₁ hx hy
#align set.inj_on.congr Set.InjOn.congr
theorem EqOn.injOn_iff (H : EqOn f₁ f₂ s) : InjOn f₁ s ↔ InjOn f₂ s :=
⟨fun h => h.congr H, fun h => h.congr H.symm⟩
#align set.eq_on.inj_on_iff Set.EqOn.injOn_iff
theorem InjOn.mono (h : s₁ ⊆ s₂) (ht : InjOn f s₂) : InjOn f s₁ := fun _ hx _ hy H =>
ht (h hx) (h hy) H
#align set.inj_on.mono Set.InjOn.mono
theorem injOn_union (h : Disjoint s₁ s₂) :
InjOn f (s₁ ∪ s₂) ↔ InjOn f s₁ ∧ InjOn f s₂ ∧ ∀ x ∈ s₁, ∀ y ∈ s₂, f x ≠ f y := by
refine ⟨fun H => ⟨H.mono subset_union_left, H.mono subset_union_right, ?_⟩, ?_⟩
· intro x hx y hy hxy
obtain rfl : x = y := H (Or.inl hx) (Or.inr hy) hxy
exact h.le_bot ⟨hx, hy⟩
· rintro ⟨h₁, h₂, h₁₂⟩
rintro x (hx | hx) y (hy | hy) hxy
exacts [h₁ hx hy hxy, (h₁₂ _ hx _ hy hxy).elim, (h₁₂ _ hy _ hx hxy.symm).elim, h₂ hx hy hxy]
#align set.inj_on_union Set.injOn_union
theorem injOn_insert {f : α → β} {s : Set α} {a : α} (has : a ∉ s) :
Set.InjOn f (insert a s) ↔ Set.InjOn f s ∧ f a ∉ f '' s := by
rw [← union_singleton, injOn_union (disjoint_singleton_right.2 has)]
simp
#align set.inj_on_insert Set.injOn_insert
theorem injective_iff_injOn_univ : Injective f ↔ InjOn f univ :=
⟨fun h _ _ _ _ hxy => h hxy, fun h _ _ heq => h trivial trivial heq⟩
#align set.injective_iff_inj_on_univ Set.injective_iff_injOn_univ
theorem injOn_of_injective (h : Injective f) {s : Set α} : InjOn f s := fun _ _ _ _ hxy => h hxy
#align set.inj_on_of_injective Set.injOn_of_injective
alias _root_.Function.Injective.injOn := injOn_of_injective
#align function.injective.inj_on Function.Injective.injOn
-- A specialization of `injOn_of_injective` for `Subtype.val`.
theorem injOn_subtype_val {s : Set { x // p x }} : Set.InjOn Subtype.val s :=
Subtype.coe_injective.injOn
lemma injOn_id (s : Set α) : InjOn id s := injective_id.injOn
#align set.inj_on_id Set.injOn_id
theorem InjOn.comp (hg : InjOn g t) (hf : InjOn f s) (h : MapsTo f s t) : InjOn (g ∘ f) s :=
fun _ hx _ hy heq => hf hx hy <| hg (h hx) (h hy) heq
#align set.inj_on.comp Set.InjOn.comp
lemma InjOn.image_of_comp (h : InjOn (g ∘ f) s) : InjOn g (f '' s) :=
forall_mem_image.2 fun _x hx ↦ forall_mem_image.2 fun _y hy heq ↦ congr_arg f <| h hx hy heq
lemma InjOn.iterate {f : α → α} {s : Set α} (h : InjOn f s) (hf : MapsTo f s s) :
∀ n, InjOn f^[n] s
| 0 => injOn_id _
| (n + 1) => (h.iterate hf n).comp h hf
#align set.inj_on.iterate Set.InjOn.iterate
lemma injOn_of_subsingleton [Subsingleton α] (f : α → β) (s : Set α) : InjOn f s :=
(injective_of_subsingleton _).injOn
#align set.inj_on_of_subsingleton Set.injOn_of_subsingleton
theorem _root_.Function.Injective.injOn_range (h : Injective (g ∘ f)) : InjOn g (range f) := by
rintro _ ⟨x, rfl⟩ _ ⟨y, rfl⟩ H
exact congr_arg f (h H)
#align function.injective.inj_on_range Function.Injective.injOn_range
theorem injOn_iff_injective : InjOn f s ↔ Injective (s.restrict f) :=
⟨fun H a b h => Subtype.eq <| H a.2 b.2 h, fun H a as b bs h =>
congr_arg Subtype.val <| @H ⟨a, as⟩ ⟨b, bs⟩ h⟩
#align set.inj_on_iff_injective Set.injOn_iff_injective
alias ⟨InjOn.injective, _⟩ := Set.injOn_iff_injective
#align set.inj_on.injective Set.InjOn.injective
theorem MapsTo.restrict_inj (h : MapsTo f s t) : Injective (h.restrict f s t) ↔ InjOn f s := by
rw [h.restrict_eq_codRestrict, injective_codRestrict, injOn_iff_injective]
#align set.maps_to.restrict_inj Set.MapsTo.restrict_inj
theorem exists_injOn_iff_injective [Nonempty β] :
(∃ f : α → β, InjOn f s) ↔ ∃ f : s → β, Injective f :=
⟨fun ⟨f, hf⟩ => ⟨_, hf.injective⟩,
fun ⟨f, hf⟩ => by
lift f to α → β using trivial
exact ⟨f, injOn_iff_injective.2 hf⟩⟩
#align set.exists_inj_on_iff_injective Set.exists_injOn_iff_injective
theorem injOn_preimage {B : Set (Set β)} (hB : B ⊆ 𝒫 range f) : InjOn (preimage f) B :=
fun s hs t ht hst => (preimage_eq_preimage' (@hB s hs) (@hB t ht)).1 hst
-- Porting note: is there a semi-implicit variable problem with `⊆`?
#align set.inj_on_preimage Set.injOn_preimage
theorem InjOn.mem_of_mem_image {x} (hf : InjOn f s) (hs : s₁ ⊆ s) (h : x ∈ s) (h₁ : f x ∈ f '' s₁) :
x ∈ s₁ :=
let ⟨_, h', Eq⟩ := h₁
hf (hs h') h Eq ▸ h'
#align set.inj_on.mem_of_mem_image Set.InjOn.mem_of_mem_image
theorem InjOn.mem_image_iff {x} (hf : InjOn f s) (hs : s₁ ⊆ s) (hx : x ∈ s) :
f x ∈ f '' s₁ ↔ x ∈ s₁ :=
⟨hf.mem_of_mem_image hs hx, mem_image_of_mem f⟩
#align set.inj_on.mem_image_iff Set.InjOn.mem_image_iff
theorem InjOn.preimage_image_inter (hf : InjOn f s) (hs : s₁ ⊆ s) : f ⁻¹' (f '' s₁) ∩ s = s₁ :=
ext fun _ => ⟨fun ⟨h₁, h₂⟩ => hf.mem_of_mem_image hs h₂ h₁, fun h => ⟨mem_image_of_mem _ h, hs h⟩⟩
#align set.inj_on.preimage_image_inter Set.InjOn.preimage_image_inter
theorem EqOn.cancel_left (h : s.EqOn (g ∘ f₁) (g ∘ f₂)) (hg : t.InjOn g) (hf₁ : s.MapsTo f₁ t)
(hf₂ : s.MapsTo f₂ t) : s.EqOn f₁ f₂ := fun _ ha => hg (hf₁ ha) (hf₂ ha) (h ha)
#align set.eq_on.cancel_left Set.EqOn.cancel_left
theorem InjOn.cancel_left (hg : t.InjOn g) (hf₁ : s.MapsTo f₁ t) (hf₂ : s.MapsTo f₂ t) :
s.EqOn (g ∘ f₁) (g ∘ f₂) ↔ s.EqOn f₁ f₂ :=
⟨fun h => h.cancel_left hg hf₁ hf₂, EqOn.comp_left⟩
#align set.inj_on.cancel_left Set.InjOn.cancel_left
lemma InjOn.image_inter {s t u : Set α} (hf : u.InjOn f) (hs : s ⊆ u) (ht : t ⊆ u) :
f '' (s ∩ t) = f '' s ∩ f '' t := by
apply Subset.antisymm (image_inter_subset _ _ _)
intro x ⟨⟨y, ys, hy⟩, ⟨z, zt, hz⟩⟩
have : y = z := by
apply hf (hs ys) (ht zt)
rwa [← hz] at hy
rw [← this] at zt
exact ⟨y, ⟨ys, zt⟩, hy⟩
#align set.inj_on.image_inter Set.InjOn.image_inter
lemma InjOn.image (h : s.InjOn f) : s.powerset.InjOn (image f) :=
fun s₁ hs₁ s₂ hs₂ h' ↦ by rw [← h.preimage_image_inter hs₁, h', h.preimage_image_inter hs₂]
theorem InjOn.image_eq_image_iff (h : s.InjOn f) (h₁ : s₁ ⊆ s) (h₂ : s₂ ⊆ s) :
f '' s₁ = f '' s₂ ↔ s₁ = s₂ :=
h.image.eq_iff h₁ h₂
lemma InjOn.image_subset_image_iff (h : s.InjOn f) (h₁ : s₁ ⊆ s) (h₂ : s₂ ⊆ s) :
f '' s₁ ⊆ f '' s₂ ↔ s₁ ⊆ s₂ := by
refine' ⟨fun h' ↦ _, image_subset _⟩
rw [← h.preimage_image_inter h₁, ← h.preimage_image_inter h₂]
exact inter_subset_inter_left _ (preimage_mono h')
lemma InjOn.image_ssubset_image_iff (h : s.InjOn f) (h₁ : s₁ ⊆ s) (h₂ : s₂ ⊆ s) :
f '' s₁ ⊂ f '' s₂ ↔ s₁ ⊂ s₂ := by
simp_rw [ssubset_def, h.image_subset_image_iff h₁ h₂, h.image_subset_image_iff h₂ h₁]
-- TODO: can this move to a better place?
theorem _root_.Disjoint.image {s t u : Set α} {f : α → β} (h : Disjoint s t) (hf : u.InjOn f)
(hs : s ⊆ u) (ht : t ⊆ u) : Disjoint (f '' s) (f '' t) := by
rw [disjoint_iff_inter_eq_empty] at h ⊢
rw [← hf.image_inter hs ht, h, image_empty]
#align disjoint.image Disjoint.image
lemma InjOn.image_diff {t : Set α} (h : s.InjOn f) : f '' (s \ t) = f '' s \ f '' (s ∩ t) := by
refine subset_antisymm (subset_diff.2 ⟨image_subset f diff_subset, ?_⟩)
(diff_subset_iff.2 (by rw [← image_union, inter_union_diff]))
exact Disjoint.image disjoint_sdiff_inter h diff_subset inter_subset_left
lemma InjOn.image_diff_subset {f : α → β} {t : Set α} (h : InjOn f s) (hst : t ⊆ s) :
f '' (s \ t) = f '' s \ f '' t := by
rw [h.image_diff, inter_eq_self_of_subset_right hst]
theorem InjOn.imageFactorization_injective (h : InjOn f s) :
Injective (s.imageFactorization f) :=
fun ⟨x, hx⟩ ⟨y, hy⟩ h' ↦ by simpa [imageFactorization, h.eq_iff hx hy] using h'
@[simp] theorem imageFactorization_injective_iff : Injective (s.imageFactorization f) ↔ InjOn f s :=
⟨fun h x hx y hy _ ↦ by simpa using @h ⟨x, hx⟩ ⟨y, hy⟩ (by simpa [imageFactorization]),
InjOn.imageFactorization_injective⟩
end injOn
section graphOn
@[simp] lemma graphOn_empty (f : α → β) : graphOn f ∅ = ∅ := image_empty _
@[simp]
lemma graphOn_union (f : α → β) (s t : Set α) : graphOn f (s ∪ t) = graphOn f s ∪ graphOn f t :=
image_union ..
@[simp]
lemma graphOn_singleton (f : α → β) (x : α) : graphOn f {x} = {(x, f x)} :=
image_singleton ..
@[simp]
lemma graphOn_insert (f : α → β) (x : α) (s : Set α) :
graphOn f (insert x s) = insert (x, f x) (graphOn f s) :=
image_insert_eq ..
@[simp]
lemma image_fst_graphOn (f : α → β) (s : Set α) : Prod.fst '' graphOn f s = s := by
simp [graphOn, image_image]
lemma exists_eq_graphOn_image_fst [Nonempty β] {s : Set (α × β)} :
(∃ f : α → β, s = graphOn f (Prod.fst '' s)) ↔ InjOn Prod.fst s := by
refine ⟨?_, fun h ↦ ?_⟩
· rintro ⟨f, hf⟩
rw [hf]
exact InjOn.image_of_comp <| injOn_id _
· have : ∀ x ∈ Prod.fst '' s, ∃ y, (x, y) ∈ s := forall_mem_image.2 fun (x, y) h ↦ ⟨y, h⟩
choose! f hf using this
rw [forall_mem_image] at hf
use f
rw [graphOn, image_image, EqOn.image_eq_self]
exact fun x hx ↦ h (hf hx) hx rfl
lemma exists_eq_graphOn [Nonempty β] {s : Set (α × β)} :
(∃ f t, s = graphOn f t) ↔ InjOn Prod.fst s :=
.trans ⟨fun ⟨f, t, hs⟩ ↦ ⟨f, by rw [hs, image_fst_graphOn]⟩, fun ⟨f, hf⟩ ↦ ⟨f, _, hf⟩⟩
exists_eq_graphOn_image_fst
end graphOn
/-! ### Surjectivity on a set -/
section surjOn
theorem SurjOn.subset_range (h : SurjOn f s t) : t ⊆ range f :=
Subset.trans h <| image_subset_range f s
#align set.surj_on.subset_range Set.SurjOn.subset_range
theorem surjOn_iff_exists_map_subtype :
SurjOn f s t ↔ ∃ (t' : Set β) (g : s → t'), t ⊆ t' ∧ Surjective g ∧ ∀ x : s, f x = g x :=
⟨fun h =>
⟨_, (mapsTo_image f s).restrict f s _, h, surjective_mapsTo_image_restrict _ _, fun _ => rfl⟩,
fun ⟨t', g, htt', hg, hfg⟩ y hy =>
let ⟨x, hx⟩ := hg ⟨y, htt' hy⟩
⟨x, x.2, by rw [hfg, hx, Subtype.coe_mk]⟩⟩
#align set.surj_on_iff_exists_map_subtype Set.surjOn_iff_exists_map_subtype
theorem surjOn_empty (f : α → β) (s : Set α) : SurjOn f s ∅ :=
empty_subset _
#align set.surj_on_empty Set.surjOn_empty
@[simp] theorem surjOn_empty_iff : SurjOn f ∅ t ↔ t = ∅ := by
simp [SurjOn, subset_empty_iff]
@[simp] lemma surjOn_singleton : SurjOn f s {b} ↔ b ∈ f '' s := singleton_subset_iff
#align set.surj_on_singleton Set.surjOn_singleton
theorem surjOn_image (f : α → β) (s : Set α) : SurjOn f s (f '' s) :=
Subset.rfl
#align set.surj_on_image Set.surjOn_image
theorem SurjOn.comap_nonempty (h : SurjOn f s t) (ht : t.Nonempty) : s.Nonempty :=
(ht.mono h).of_image
#align set.surj_on.comap_nonempty Set.SurjOn.comap_nonempty
theorem SurjOn.congr (h : SurjOn f₁ s t) (H : EqOn f₁ f₂ s) : SurjOn f₂ s t := by
rwa [SurjOn, ← H.image_eq]
#align set.surj_on.congr Set.SurjOn.congr
theorem EqOn.surjOn_iff (h : EqOn f₁ f₂ s) : SurjOn f₁ s t ↔ SurjOn f₂ s t :=
⟨fun H => H.congr h, fun H => H.congr h.symm⟩
#align set.eq_on.surj_on_iff Set.EqOn.surjOn_iff
theorem SurjOn.mono (hs : s₁ ⊆ s₂) (ht : t₁ ⊆ t₂) (hf : SurjOn f s₁ t₂) : SurjOn f s₂ t₁ :=
Subset.trans ht <| Subset.trans hf <| image_subset _ hs
#align set.surj_on.mono Set.SurjOn.mono
theorem SurjOn.union (h₁ : SurjOn f s t₁) (h₂ : SurjOn f s t₂) : SurjOn f s (t₁ ∪ t₂) := fun _ hx =>
hx.elim (fun hx => h₁ hx) fun hx => h₂ hx
#align set.surj_on.union Set.SurjOn.union
theorem SurjOn.union_union (h₁ : SurjOn f s₁ t₁) (h₂ : SurjOn f s₂ t₂) :
SurjOn f (s₁ ∪ s₂) (t₁ ∪ t₂) :=
(h₁.mono subset_union_left (Subset.refl _)).union
(h₂.mono subset_union_right (Subset.refl _))
#align set.surj_on.union_union Set.SurjOn.union_union
| Mathlib/Data/Set/Function.lean | 906 | 912 | theorem SurjOn.inter_inter (h₁ : SurjOn f s₁ t₁) (h₂ : SurjOn f s₂ t₂) (h : InjOn f (s₁ ∪ s₂)) :
SurjOn f (s₁ ∩ s₂) (t₁ ∩ t₂) := by |
intro y hy
rcases h₁ hy.1 with ⟨x₁, hx₁, rfl⟩
rcases h₂ hy.2 with ⟨x₂, hx₂, heq⟩
obtain rfl : x₁ = x₂ := h (Or.inl hx₁) (Or.inr hx₂) heq.symm
exact mem_image_of_mem f ⟨hx₁, hx₂⟩
|
/-
Copyright (c) 2020 Aaron Anderson, Jalex Stark, Kyle Miller. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Aaron Anderson, Jalex Stark, Kyle Miller, Alena Gusakov
-/
import Mathlib.Algebra.Order.Ring.Defs
import Mathlib.Combinatorics.SimpleGraph.Basic
import Mathlib.Data.Sym.Card
/-!
# Definitions for finite and locally finite graphs
This file defines finite versions of `edgeSet`, `neighborSet` and `incidenceSet` and proves some
of their basic properties. It also defines the notion of a locally finite graph, which is one
whose vertices have finite degree.
The design for finiteness is that each definition takes the smallest finiteness assumption
necessary. For example, `SimpleGraph.neighborFinset v` only requires that `v` have
finitely many neighbors.
## Main definitions
* `SimpleGraph.edgeFinset` is the `Finset` of edges in a graph, if `edgeSet` is finite
* `SimpleGraph.neighborFinset` is the `Finset` of vertices adjacent to a given vertex,
if `neighborSet` is finite
* `SimpleGraph.incidenceFinset` is the `Finset` of edges containing a given vertex,
if `incidenceSet` is finite
## Naming conventions
If the vertex type of a graph is finite, we refer to its cardinality as `CardVerts`
or `card_verts`.
## Implementation notes
* A locally finite graph is one with instances `Π v, Fintype (G.neighborSet v)`.
* Given instances `DecidableRel G.Adj` and `Fintype V`, then the graph
is locally finite, too.
-/
open Finset Function
namespace SimpleGraph
variable {V : Type*} (G : SimpleGraph V) {e : Sym2 V}
section EdgeFinset
variable {G₁ G₂ : SimpleGraph V} [Fintype G.edgeSet] [Fintype G₁.edgeSet] [Fintype G₂.edgeSet]
/-- The `edgeSet` of the graph as a `Finset`. -/
abbrev edgeFinset : Finset (Sym2 V) :=
Set.toFinset G.edgeSet
#align simple_graph.edge_finset SimpleGraph.edgeFinset
@[norm_cast]
theorem coe_edgeFinset : (G.edgeFinset : Set (Sym2 V)) = G.edgeSet :=
Set.coe_toFinset _
#align simple_graph.coe_edge_finset SimpleGraph.coe_edgeFinset
variable {G}
theorem mem_edgeFinset : e ∈ G.edgeFinset ↔ e ∈ G.edgeSet :=
Set.mem_toFinset
#align simple_graph.mem_edge_finset SimpleGraph.mem_edgeFinset
theorem not_isDiag_of_mem_edgeFinset : e ∈ G.edgeFinset → ¬e.IsDiag :=
not_isDiag_of_mem_edgeSet _ ∘ mem_edgeFinset.1
#align simple_graph.not_is_diag_of_mem_edge_finset SimpleGraph.not_isDiag_of_mem_edgeFinset
theorem edgeFinset_inj : G₁.edgeFinset = G₂.edgeFinset ↔ G₁ = G₂ := by simp
#align simple_graph.edge_finset_inj SimpleGraph.edgeFinset_inj
theorem edgeFinset_subset_edgeFinset : G₁.edgeFinset ⊆ G₂.edgeFinset ↔ G₁ ≤ G₂ := by simp
#align simple_graph.edge_finset_subset_edge_finset SimpleGraph.edgeFinset_subset_edgeFinset
theorem edgeFinset_ssubset_edgeFinset : G₁.edgeFinset ⊂ G₂.edgeFinset ↔ G₁ < G₂ := by simp
#align simple_graph.edge_finset_ssubset_edge_finset SimpleGraph.edgeFinset_ssubset_edgeFinset
@[gcongr] alias ⟨_, edgeFinset_mono⟩ := edgeFinset_subset_edgeFinset
#align simple_graph.edge_finset_mono SimpleGraph.edgeFinset_mono
alias ⟨_, edgeFinset_strict_mono⟩ := edgeFinset_ssubset_edgeFinset
#align simple_graph.edge_finset_strict_mono SimpleGraph.edgeFinset_strict_mono
attribute [mono] edgeFinset_mono edgeFinset_strict_mono
@[simp]
theorem edgeFinset_bot : (⊥ : SimpleGraph V).edgeFinset = ∅ := by simp [edgeFinset]
#align simple_graph.edge_finset_bot SimpleGraph.edgeFinset_bot
@[simp]
theorem edgeFinset_sup [Fintype (edgeSet (G₁ ⊔ G₂))] [DecidableEq V] :
(G₁ ⊔ G₂).edgeFinset = G₁.edgeFinset ∪ G₂.edgeFinset := by simp [edgeFinset]
#align simple_graph.edge_finset_sup SimpleGraph.edgeFinset_sup
@[simp]
theorem edgeFinset_inf [DecidableEq V] : (G₁ ⊓ G₂).edgeFinset = G₁.edgeFinset ∩ G₂.edgeFinset := by
simp [edgeFinset]
#align simple_graph.edge_finset_inf SimpleGraph.edgeFinset_inf
@[simp]
theorem edgeFinset_sdiff [DecidableEq V] :
(G₁ \ G₂).edgeFinset = G₁.edgeFinset \ G₂.edgeFinset := by simp [edgeFinset]
#align simple_graph.edge_finset_sdiff SimpleGraph.edgeFinset_sdiff
theorem edgeFinset_card : G.edgeFinset.card = Fintype.card G.edgeSet :=
Set.toFinset_card _
#align simple_graph.edge_finset_card SimpleGraph.edgeFinset_card
@[simp]
theorem edgeSet_univ_card : (univ : Finset G.edgeSet).card = G.edgeFinset.card :=
Fintype.card_of_subtype G.edgeFinset fun _ => mem_edgeFinset
#align simple_graph.edge_set_univ_card SimpleGraph.edgeSet_univ_card
variable [Fintype V]
@[simp]
theorem edgeFinset_top [DecidableEq V] :
(⊤ : SimpleGraph V).edgeFinset = univ.filter fun e => ¬e.IsDiag := by
rw [← coe_inj]; simp
/-- The complete graph on `n` vertices has `n.choose 2` edges. -/
theorem card_edgeFinset_top_eq_card_choose_two [DecidableEq V] :
(⊤ : SimpleGraph V).edgeFinset.card = (Fintype.card V).choose 2 := by
simp_rw [Set.toFinset_card, edgeSet_top, Set.coe_setOf, ← Sym2.card_subtype_not_diag]
/-- Any graph on `n` vertices has at most `n.choose 2` edges. -/
theorem card_edgeFinset_le_card_choose_two : G.edgeFinset.card ≤ (Fintype.card V).choose 2 := by
classical
rw [← card_edgeFinset_top_eq_card_choose_two]
exact card_le_card (edgeFinset_mono le_top)
end EdgeFinset
theorem edgeFinset_deleteEdges [DecidableEq V] [Fintype G.edgeSet] (s : Finset (Sym2 V))
[Fintype (G.deleteEdges s).edgeSet] :
(G.deleteEdges s).edgeFinset = G.edgeFinset \ s := by
ext e
simp [edgeSet_deleteEdges]
#align simple_graph.edge_finset_delete_edges SimpleGraph.edgeFinset_deleteEdges
section DeleteFar
-- Porting note: added `Fintype (Sym2 V)` argument.
variable {𝕜 : Type*} [OrderedRing 𝕜] [Fintype V] [Fintype (Sym2 V)]
[Fintype G.edgeSet] {p : SimpleGraph V → Prop} {r r₁ r₂ : 𝕜}
/-- A graph is `r`-*delete-far* from a property `p` if we must delete at least `r` edges from it to
get a graph with the property `p`. -/
def DeleteFar (p : SimpleGraph V → Prop) (r : 𝕜) : Prop :=
∀ ⦃s⦄, s ⊆ G.edgeFinset → p (G.deleteEdges s) → r ≤ s.card
#align simple_graph.delete_far SimpleGraph.DeleteFar
variable {G}
theorem deleteFar_iff :
G.DeleteFar p r ↔ ∀ ⦃H : SimpleGraph _⦄ [DecidableRel H.Adj],
H ≤ G → p H → r ≤ G.edgeFinset.card - H.edgeFinset.card := by
classical
refine ⟨fun h H _ hHG hH ↦ ?_, fun h s hs hG ↦ ?_⟩
· have := h (sdiff_subset (t := H.edgeFinset))
simp only [deleteEdges_sdiff_eq_of_le hHG, edgeFinset_mono hHG, card_sdiff,
card_le_card, coe_sdiff, coe_edgeFinset, Nat.cast_sub] at this
exact this hH
· classical
simpa [card_sdiff hs, edgeFinset_deleteEdges, -Set.toFinset_card, Nat.cast_sub,
card_le_card hs] using h (G.deleteEdges_le s) hG
#align simple_graph.delete_far_iff SimpleGraph.deleteFar_iff
alias ⟨DeleteFar.le_card_sub_card, _⟩ := deleteFar_iff
#align simple_graph.delete_far.le_card_sub_card SimpleGraph.DeleteFar.le_card_sub_card
theorem DeleteFar.mono (h : G.DeleteFar p r₂) (hr : r₁ ≤ r₂) : G.DeleteFar p r₁ := fun _ hs hG =>
hr.trans <| h hs hG
#align simple_graph.delete_far.mono SimpleGraph.DeleteFar.mono
end DeleteFar
section FiniteAt
/-!
## Finiteness at a vertex
This section contains definitions and lemmas concerning vertices that
have finitely many adjacent vertices. We denote this condition by
`Fintype (G.neighborSet v)`.
We define `G.neighborFinset v` to be the `Finset` version of `G.neighborSet v`.
Use `neighborFinset_eq_filter` to rewrite this definition as a `Finset.filter` expression.
-/
variable (v) [Fintype (G.neighborSet v)]
/-- `G.neighbors v` is the `Finset` version of `G.Adj v` in case `G` is
locally finite at `v`. -/
def neighborFinset : Finset V :=
(G.neighborSet v).toFinset
#align simple_graph.neighbor_finset SimpleGraph.neighborFinset
theorem neighborFinset_def : G.neighborFinset v = (G.neighborSet v).toFinset :=
rfl
#align simple_graph.neighbor_finset_def SimpleGraph.neighborFinset_def
@[simp]
theorem mem_neighborFinset (w : V) : w ∈ G.neighborFinset v ↔ G.Adj v w :=
Set.mem_toFinset
#align simple_graph.mem_neighbor_finset SimpleGraph.mem_neighborFinset
theorem not_mem_neighborFinset_self : v ∉ G.neighborFinset v := by simp
#align simple_graph.not_mem_neighbor_finset_self SimpleGraph.not_mem_neighborFinset_self
theorem neighborFinset_disjoint_singleton : Disjoint (G.neighborFinset v) {v} :=
Finset.disjoint_singleton_right.mpr <| not_mem_neighborFinset_self _ _
#align simple_graph.neighbor_finset_disjoint_singleton SimpleGraph.neighborFinset_disjoint_singleton
theorem singleton_disjoint_neighborFinset : Disjoint {v} (G.neighborFinset v) :=
Finset.disjoint_singleton_left.mpr <| not_mem_neighborFinset_self _ _
#align simple_graph.singleton_disjoint_neighbor_finset SimpleGraph.singleton_disjoint_neighborFinset
/-- `G.degree v` is the number of vertices adjacent to `v`. -/
def degree : ℕ :=
(G.neighborFinset v).card
#align simple_graph.degree SimpleGraph.degree
-- Porting note: in Lean 3 we could do `simp [← degree]`, but that gives
-- "invalid '←' modifier, 'SimpleGraph.degree' is a declaration name to be unfolded".
-- In any case, having this lemma is good since there's no guarantee we won't still change
-- the definition of `degree`.
@[simp]
theorem card_neighborFinset_eq_degree : (G.neighborFinset v).card = G.degree v := rfl
@[simp]
theorem card_neighborSet_eq_degree : Fintype.card (G.neighborSet v) = G.degree v :=
(Set.toFinset_card _).symm
#align simple_graph.card_neighbor_set_eq_degree SimpleGraph.card_neighborSet_eq_degree
theorem degree_pos_iff_exists_adj : 0 < G.degree v ↔ ∃ w, G.Adj v w := by
simp only [degree, card_pos, Finset.Nonempty, mem_neighborFinset]
#align simple_graph.degree_pos_iff_exists_adj SimpleGraph.degree_pos_iff_exists_adj
theorem degree_compl [Fintype (Gᶜ.neighborSet v)] [Fintype V] :
Gᶜ.degree v = Fintype.card V - 1 - G.degree v := by
classical
rw [← card_neighborSet_union_compl_neighborSet G v, Set.toFinset_union]
simp [card_union_of_disjoint (Set.disjoint_toFinset.mpr (compl_neighborSet_disjoint G v))]
#align simple_graph.degree_compl SimpleGraph.degree_compl
instance incidenceSetFintype [DecidableEq V] : Fintype (G.incidenceSet v) :=
Fintype.ofEquiv (G.neighborSet v) (G.incidenceSetEquivNeighborSet v).symm
#align simple_graph.incidence_set_fintype SimpleGraph.incidenceSetFintype
/-- This is the `Finset` version of `incidenceSet`. -/
def incidenceFinset [DecidableEq V] : Finset (Sym2 V) :=
(G.incidenceSet v).toFinset
#align simple_graph.incidence_finset SimpleGraph.incidenceFinset
@[simp]
theorem card_incidenceSet_eq_degree [DecidableEq V] :
Fintype.card (G.incidenceSet v) = G.degree v := by
rw [Fintype.card_congr (G.incidenceSetEquivNeighborSet v)]
simp
#align simple_graph.card_incidence_set_eq_degree SimpleGraph.card_incidenceSet_eq_degree
@[simp]
theorem card_incidenceFinset_eq_degree [DecidableEq V] :
(G.incidenceFinset v).card = G.degree v := by
rw [← G.card_incidenceSet_eq_degree]
apply Set.toFinset_card
#align simple_graph.card_incidence_finset_eq_degree SimpleGraph.card_incidenceFinset_eq_degree
@[simp]
theorem mem_incidenceFinset [DecidableEq V] (e : Sym2 V) :
e ∈ G.incidenceFinset v ↔ e ∈ G.incidenceSet v :=
Set.mem_toFinset
#align simple_graph.mem_incidence_finset SimpleGraph.mem_incidenceFinset
theorem incidenceFinset_eq_filter [DecidableEq V] [Fintype G.edgeSet] :
G.incidenceFinset v = G.edgeFinset.filter (Membership.mem v) := by
ext e
refine Sym2.ind (fun x y => ?_) e
simp [mk'_mem_incidenceSet_iff]
#align simple_graph.incidence_finset_eq_filter SimpleGraph.incidenceFinset_eq_filter
end FiniteAt
section LocallyFinite
/-- A graph is locally finite if every vertex has a finite neighbor set. -/
abbrev LocallyFinite :=
∀ v : V, Fintype (G.neighborSet v)
#align simple_graph.locally_finite SimpleGraph.LocallyFinite
variable [LocallyFinite G]
/-- A locally finite simple graph is regular of degree `d` if every vertex has degree `d`. -/
def IsRegularOfDegree (d : ℕ) : Prop :=
∀ v : V, G.degree v = d
#align simple_graph.is_regular_of_degree SimpleGraph.IsRegularOfDegree
variable {G}
theorem IsRegularOfDegree.degree_eq {d : ℕ} (h : G.IsRegularOfDegree d) (v : V) : G.degree v = d :=
h v
#align simple_graph.is_regular_of_degree.degree_eq SimpleGraph.IsRegularOfDegree.degree_eq
theorem IsRegularOfDegree.compl [Fintype V] [DecidableEq V] {G : SimpleGraph V} [DecidableRel G.Adj]
{k : ℕ} (h : G.IsRegularOfDegree k) : Gᶜ.IsRegularOfDegree (Fintype.card V - 1 - k) := by
intro v
rw [degree_compl, h v]
#align simple_graph.is_regular_of_degree.compl SimpleGraph.IsRegularOfDegree.compl
end LocallyFinite
section Finite
variable [Fintype V]
instance neighborSetFintype [DecidableRel G.Adj] (v : V) : Fintype (G.neighborSet v) :=
@Subtype.fintype _ _
(by
simp_rw [mem_neighborSet]
infer_instance)
_
#align simple_graph.neighbor_set_fintype SimpleGraph.neighborSetFintype
theorem neighborFinset_eq_filter {v : V} [DecidableRel G.Adj] :
G.neighborFinset v = Finset.univ.filter (G.Adj v) := by
ext
simp
#align simple_graph.neighbor_finset_eq_filter SimpleGraph.neighborFinset_eq_filter
theorem neighborFinset_compl [DecidableEq V] [DecidableRel G.Adj] (v : V) :
Gᶜ.neighborFinset v = (G.neighborFinset v)ᶜ \ {v} := by
simp only [neighborFinset, neighborSet_compl, Set.toFinset_diff, Set.toFinset_compl,
Set.toFinset_singleton]
#align simple_graph.neighbor_finset_compl SimpleGraph.neighborFinset_compl
@[simp]
theorem complete_graph_degree [DecidableEq V] (v : V) :
(⊤ : SimpleGraph V).degree v = Fintype.card V - 1 := by
erw [degree, neighborFinset_eq_filter, filter_ne, card_erase_of_mem (mem_univ v), card_univ]
#align simple_graph.complete_graph_degree SimpleGraph.complete_graph_degree
theorem bot_degree (v : V) : (⊥ : SimpleGraph V).degree v = 0 := by
erw [degree, neighborFinset_eq_filter, filter_False]
exact Finset.card_empty
#align simple_graph.bot_degree SimpleGraph.bot_degree
theorem IsRegularOfDegree.top [DecidableEq V] :
(⊤ : SimpleGraph V).IsRegularOfDegree (Fintype.card V - 1) := by
intro v
simp
#align simple_graph.is_regular_of_degree.top SimpleGraph.IsRegularOfDegree.top
/-- The minimum degree of all vertices (and `0` if there are no vertices).
The key properties of this are given in `exists_minimal_degree_vertex`, `minDegree_le_degree`
and `le_minDegree_of_forall_le_degree`. -/
def minDegree [DecidableRel G.Adj] : ℕ :=
WithTop.untop' 0 (univ.image fun v => G.degree v).min
#align simple_graph.min_degree SimpleGraph.minDegree
/-- There exists a vertex of minimal degree. Note the assumption of being nonempty is necessary, as
the lemma implies there exists a vertex. -/
theorem exists_minimal_degree_vertex [DecidableRel G.Adj] [Nonempty V] :
∃ v, G.minDegree = G.degree v := by
obtain ⟨t, ht : _ = _⟩ := min_of_nonempty (univ_nonempty.image fun v => G.degree v)
obtain ⟨v, _, rfl⟩ := mem_image.mp (mem_of_min ht)
exact ⟨v, by simp [minDegree, ht]⟩
#align simple_graph.exists_minimal_degree_vertex SimpleGraph.exists_minimal_degree_vertex
/-- The minimum degree in the graph is at most the degree of any particular vertex. -/
theorem minDegree_le_degree [DecidableRel G.Adj] (v : V) : G.minDegree ≤ G.degree v := by
obtain ⟨t, ht⟩ := Finset.min_of_mem (mem_image_of_mem (fun v => G.degree v) (mem_univ v))
have := Finset.min_le_of_eq (mem_image_of_mem _ (mem_univ v)) ht
rwa [minDegree, ht]
#align simple_graph.min_degree_le_degree SimpleGraph.minDegree_le_degree
/-- In a nonempty graph, if `k` is at most the degree of every vertex, it is at most the minimum
degree. Note the assumption that the graph is nonempty is necessary as long as `G.minDegree` is
defined to be a natural. -/
| Mathlib/Combinatorics/SimpleGraph/Finite.lean | 383 | 387 | theorem le_minDegree_of_forall_le_degree [DecidableRel G.Adj] [Nonempty V] (k : ℕ)
(h : ∀ v, k ≤ G.degree v) : k ≤ G.minDegree := by |
rcases G.exists_minimal_degree_vertex with ⟨v, hv⟩
rw [hv]
apply h
|
/-
Copyright (c) 2020 Alexander Bentkamp. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Alexander Bentkamp
-/
import Mathlib.Algebra.Algebra.Spectrum
import Mathlib.LinearAlgebra.GeneralLinearGroup
import Mathlib.LinearAlgebra.FiniteDimensional
import Mathlib.RingTheory.Nilpotent.Basic
#align_import linear_algebra.eigenspace.basic from "leanprover-community/mathlib"@"6b0169218d01f2837d79ea2784882009a0da1aa1"
/-!
# Eigenvectors and eigenvalues
This file defines eigenspaces, eigenvalues, and eigenvalues, as well as their generalized
counterparts. We follow Axler's approach [axler2015] because it allows us to derive many properties
without choosing a basis and without using matrices.
An eigenspace of a linear map `f` for a scalar `μ` is the kernel of the map `(f - μ • id)`. The
nonzero elements of an eigenspace are eigenvectors `x`. They have the property `f x = μ • x`. If
there are eigenvectors for a scalar `μ`, the scalar `μ` is called an eigenvalue.
There is no consensus in the literature whether `0` is an eigenvector. Our definition of
`HasEigenvector` permits only nonzero vectors. For an eigenvector `x` that may also be `0`, we
write `x ∈ f.eigenspace μ`.
A generalized eigenspace of a linear map `f` for a natural number `k` and a scalar `μ` is the kernel
of the map `(f - μ • id) ^ k`. The nonzero elements of a generalized eigenspace are generalized
eigenvectors `x`. If there are generalized eigenvectors for a natural number `k` and a scalar `μ`,
the scalar `μ` is called a generalized eigenvalue.
The fact that the eigenvalues are the roots of the minimal polynomial is proved in
`LinearAlgebra.Eigenspace.Minpoly`.
The existence of eigenvalues over an algebraically closed field
(and the fact that the generalized eigenspaces then span) is deferred to
`LinearAlgebra.Eigenspace.IsAlgClosed`.
## References
* [Sheldon Axler, *Linear Algebra Done Right*][axler2015]
* https://en.wikipedia.org/wiki/Eigenvalues_and_eigenvectors
## Tags
eigenspace, eigenvector, eigenvalue, eigen
-/
universe u v w
namespace Module
namespace End
open FiniteDimensional Set
variable {K R : Type v} {V M : Type w} [CommRing R] [AddCommGroup M] [Module R M] [Field K]
[AddCommGroup V] [Module K V]
/-- The submodule `eigenspace f μ` for a linear map `f` and a scalar `μ` consists of all vectors `x`
such that `f x = μ • x`. (Def 5.36 of [axler2015])-/
def eigenspace (f : End R M) (μ : R) : Submodule R M :=
LinearMap.ker (f - algebraMap R (End R M) μ)
#align module.End.eigenspace Module.End.eigenspace
@[simp]
theorem eigenspace_zero (f : End R M) : f.eigenspace 0 = LinearMap.ker f := by simp [eigenspace]
#align module.End.eigenspace_zero Module.End.eigenspace_zero
/-- A nonzero element of an eigenspace is an eigenvector. (Def 5.7 of [axler2015]) -/
def HasEigenvector (f : End R M) (μ : R) (x : M) : Prop :=
x ∈ eigenspace f μ ∧ x ≠ 0
#align module.End.has_eigenvector Module.End.HasEigenvector
/-- A scalar `μ` is an eigenvalue for a linear map `f` if there are nonzero vectors `x`
such that `f x = μ • x`. (Def 5.5 of [axler2015]) -/
def HasEigenvalue (f : End R M) (a : R) : Prop :=
eigenspace f a ≠ ⊥
#align module.End.has_eigenvalue Module.End.HasEigenvalue
/-- The eigenvalues of the endomorphism `f`, as a subtype of `R`. -/
def Eigenvalues (f : End R M) : Type _ :=
{ μ : R // f.HasEigenvalue μ }
#align module.End.eigenvalues Module.End.Eigenvalues
@[coe]
def Eigenvalues.val (f : Module.End R M) : Eigenvalues f → R := Subtype.val
instance Eigenvalues.instCoeOut {f : Module.End R M} : CoeOut (Eigenvalues f) R where
coe := Eigenvalues.val f
instance Eigenvalues.instDecidableEq [DecidableEq R] (f : Module.End R M) :
DecidableEq (Eigenvalues f) :=
inferInstanceAs (DecidableEq (Subtype (fun x : R => HasEigenvalue f x)))
theorem hasEigenvalue_of_hasEigenvector {f : End R M} {μ : R} {x : M} (h : HasEigenvector f μ x) :
HasEigenvalue f μ := by
rw [HasEigenvalue, Submodule.ne_bot_iff]
use x; exact h
#align module.End.has_eigenvalue_of_has_eigenvector Module.End.hasEigenvalue_of_hasEigenvector
theorem mem_eigenspace_iff {f : End R M} {μ : R} {x : M} : x ∈ eigenspace f μ ↔ f x = μ • x := by
rw [eigenspace, LinearMap.mem_ker, LinearMap.sub_apply, algebraMap_end_apply, sub_eq_zero]
#align module.End.mem_eigenspace_iff Module.End.mem_eigenspace_iff
theorem HasEigenvector.apply_eq_smul {f : End R M} {μ : R} {x : M} (hx : f.HasEigenvector μ x) :
f x = μ • x :=
mem_eigenspace_iff.mp hx.1
#align module.End.has_eigenvector.apply_eq_smul Module.End.HasEigenvector.apply_eq_smul
theorem HasEigenvector.pow_apply {f : End R M} {μ : R} {v : M} (hv : f.HasEigenvector μ v) (n : ℕ) :
(f ^ n) v = μ ^ n • v := by
induction n <;> simp [*, pow_succ f, hv.apply_eq_smul, smul_smul, pow_succ' μ]
theorem HasEigenvalue.exists_hasEigenvector {f : End R M} {μ : R} (hμ : f.HasEigenvalue μ) :
∃ v, f.HasEigenvector μ v :=
Submodule.exists_mem_ne_zero_of_ne_bot hμ
#align module.End.has_eigenvalue.exists_has_eigenvector Module.End.HasEigenvalue.exists_hasEigenvector
lemma HasEigenvalue.pow {f : End R M} {μ : R} (h : f.HasEigenvalue μ) (n : ℕ) :
(f ^ n).HasEigenvalue (μ ^ n) := by
rw [HasEigenvalue, Submodule.ne_bot_iff]
obtain ⟨m : M, hm⟩ := h.exists_hasEigenvector
exact ⟨m, by simpa [mem_eigenspace_iff] using hm.pow_apply n, hm.2⟩
/-- A nilpotent endomorphism has nilpotent eigenvalues.
See also `LinearMap.isNilpotent_trace_of_isNilpotent`. -/
lemma HasEigenvalue.isNilpotent_of_isNilpotent [NoZeroSMulDivisors R M] {f : End R M}
(hfn : IsNilpotent f) {μ : R} (hf : f.HasEigenvalue μ) :
IsNilpotent μ := by
obtain ⟨m : M, hm⟩ := hf.exists_hasEigenvector
obtain ⟨n : ℕ, hn : f ^ n = 0⟩ := hfn
exact ⟨n, by simpa [hn, hm.2, eq_comm (a := (0 : M))] using hm.pow_apply n⟩
theorem HasEigenvalue.mem_spectrum {f : End R M} {μ : R} (hμ : HasEigenvalue f μ) :
μ ∈ spectrum R f := by
refine spectrum.mem_iff.mpr fun h_unit => ?_
set f' := LinearMap.GeneralLinearGroup.toLinearEquiv h_unit.unit
rcases hμ.exists_hasEigenvector with ⟨v, hv⟩
refine hv.2 ((LinearMap.ker_eq_bot'.mp f'.ker) v (?_ : μ • v - f v = 0))
rw [hv.apply_eq_smul, sub_self]
#align module.End.mem_spectrum_of_has_eigenvalue Module.End.HasEigenvalue.mem_spectrum
theorem hasEigenvalue_iff_mem_spectrum [FiniteDimensional K V] {f : End K V} {μ : K} :
f.HasEigenvalue μ ↔ μ ∈ spectrum K f := by
rw [spectrum.mem_iff, IsUnit.sub_iff, LinearMap.isUnit_iff_ker_eq_bot, HasEigenvalue, eigenspace]
#align module.End.has_eigenvalue_iff_mem_spectrum Module.End.hasEigenvalue_iff_mem_spectrum
alias ⟨_, HasEigenvalue.of_mem_spectrum⟩ := hasEigenvalue_iff_mem_spectrum
theorem eigenspace_div (f : End K V) (a b : K) (hb : b ≠ 0) :
eigenspace f (a / b) = LinearMap.ker (b • f - algebraMap K (End K V) a) :=
calc
eigenspace f (a / b) = eigenspace f (b⁻¹ * a) := by rw [div_eq_mul_inv, mul_comm]
_ = LinearMap.ker (f - (b⁻¹ * a) • LinearMap.id) := by rw [eigenspace]; rfl
_ = LinearMap.ker (f - b⁻¹ • a • LinearMap.id) := by rw [smul_smul]
_ = LinearMap.ker (f - b⁻¹ • algebraMap K (End K V) a) := rfl
_ = LinearMap.ker (b • (f - b⁻¹ • algebraMap K (End K V) a)) := by
rw [LinearMap.ker_smul _ b hb]
_ = LinearMap.ker (b • f - algebraMap K (End K V) a) := by rw [smul_sub, smul_inv_smul₀ hb]
#align module.End.eigenspace_div Module.End.eigenspace_div
/-- The generalized eigenspace for a linear map `f`, a scalar `μ`, and an exponent `k ∈ ℕ` is the
kernel of `(f - μ • id) ^ k`. (Def 8.10 of [axler2015]). Furthermore, a generalized eigenspace for
some exponent `k` is contained in the generalized eigenspace for exponents larger than `k`. -/
def genEigenspace (f : End R M) (μ : R) : ℕ →o Submodule R M where
toFun k := LinearMap.ker ((f - algebraMap R (End R M) μ) ^ k)
monotone' k m hm := by
simp only [← pow_sub_mul_pow _ hm]
exact
LinearMap.ker_le_ker_comp ((f - algebraMap R (End R M) μ) ^ k)
((f - algebraMap R (End R M) μ) ^ (m - k))
#align module.End.generalized_eigenspace Module.End.genEigenspace
@[simp]
theorem mem_genEigenspace (f : End R M) (μ : R) (k : ℕ) (m : M) :
m ∈ f.genEigenspace μ k ↔ ((f - μ • (1 : End R M)) ^ k) m = 0 := Iff.rfl
#align module.End.mem_generalized_eigenspace Module.End.mem_genEigenspace
@[simp]
theorem genEigenspace_zero (f : End R M) (k : ℕ) :
f.genEigenspace 0 k = LinearMap.ker (f ^ k) := by
simp [Module.End.genEigenspace]
#align module.End.generalized_eigenspace_zero Module.End.genEigenspace_zero
/-- A nonzero element of a generalized eigenspace is a generalized eigenvector.
(Def 8.9 of [axler2015])-/
def HasGenEigenvector (f : End R M) (μ : R) (k : ℕ) (x : M) : Prop :=
x ≠ 0 ∧ x ∈ genEigenspace f μ k
#align module.End.has_generalized_eigenvector Module.End.HasGenEigenvector
/-- A scalar `μ` is a generalized eigenvalue for a linear map `f` and an exponent `k ∈ ℕ` if there
are generalized eigenvectors for `f`, `k`, and `μ`. -/
def HasGenEigenvalue (f : End R M) (μ : R) (k : ℕ) : Prop :=
genEigenspace f μ k ≠ ⊥
#align module.End.has_generalized_eigenvalue Module.End.HasGenEigenvalue
/-- The generalized eigenrange for a linear map `f`, a scalar `μ`, and an exponent `k ∈ ℕ` is the
range of `(f - μ • id) ^ k`. -/
def genEigenrange (f : End R M) (μ : R) (k : ℕ) : Submodule R M :=
LinearMap.range ((f - algebraMap R (End R M) μ) ^ k)
#align module.End.generalized_eigenrange Module.End.genEigenrange
/-- The exponent of a generalized eigenvalue is never 0. -/
theorem exp_ne_zero_of_hasGenEigenvalue {f : End R M} {μ : R} {k : ℕ}
(h : f.HasGenEigenvalue μ k) : k ≠ 0 := by
rintro rfl
exact h LinearMap.ker_id
#align module.End.exp_ne_zero_of_has_generalized_eigenvalue Module.End.exp_ne_zero_of_hasGenEigenvalue
/-- The union of the kernels of `(f - μ • id) ^ k` over all `k`. -/
def maxGenEigenspace (f : End R M) (μ : R) : Submodule R M :=
⨆ k, f.genEigenspace μ k
#align module.End.maximal_generalized_eigenspace Module.End.maxGenEigenspace
theorem genEigenspace_le_maximal (f : End R M) (μ : R) (k : ℕ) :
f.genEigenspace μ k ≤ f.maxGenEigenspace μ :=
le_iSup _ _
#align module.End.generalized_eigenspace_le_maximal Module.End.genEigenspace_le_maximal
@[simp]
theorem mem_maxGenEigenspace (f : End R M) (μ : R) (m : M) :
m ∈ f.maxGenEigenspace μ ↔ ∃ k : ℕ, ((f - μ • (1 : End R M)) ^ k) m = 0 := by
simp only [maxGenEigenspace, ← mem_genEigenspace, Submodule.mem_iSup_of_chain]
#align module.End.mem_maximal_generalized_eigenspace Module.End.mem_maxGenEigenspace
/-- If there exists a natural number `k` such that the kernel of `(f - μ • id) ^ k` is the
maximal generalized eigenspace, then this value is the least such `k`. If not, this value is not
meaningful. -/
noncomputable def maxGenEigenspaceIndex (f : End R M) (μ : R) :=
monotonicSequenceLimitIndex (f.genEigenspace μ)
#align module.End.maximal_generalized_eigenspace_index Module.End.maxGenEigenspaceIndex
/-- For an endomorphism of a Noetherian module, the maximal eigenspace is always of the form kernel
`(f - μ • id) ^ k` for some `k`. -/
theorem maxGenEigenspace_eq [h : IsNoetherian R M] (f : End R M) (μ : R) :
maxGenEigenspace f μ =
f.genEigenspace μ (maxGenEigenspaceIndex f μ) := by
rw [isNoetherian_iff_wellFounded] at h
exact (WellFounded.iSup_eq_monotonicSequenceLimit h (f.genEigenspace μ) : _)
#align module.End.maximal_generalized_eigenspace_eq Module.End.maxGenEigenspace_eq
/-- A generalized eigenvalue for some exponent `k` is also
a generalized eigenvalue for exponents larger than `k`. -/
theorem hasGenEigenvalue_of_hasGenEigenvalue_of_le {f : End R M} {μ : R} {k : ℕ}
{m : ℕ} (hm : k ≤ m) (hk : f.HasGenEigenvalue μ k) :
f.HasGenEigenvalue μ m := by
unfold HasGenEigenvalue at *
contrapose! hk
rw [← le_bot_iff, ← hk]
exact (f.genEigenspace μ).monotone hm
#align module.End.has_generalized_eigenvalue_of_has_generalized_eigenvalue_of_le Module.End.hasGenEigenvalue_of_hasGenEigenvalue_of_le
/-- The eigenspace is a subspace of the generalized eigenspace. -/
theorem eigenspace_le_genEigenspace {f : End R M} {μ : R} {k : ℕ} (hk : 0 < k) :
f.eigenspace μ ≤ f.genEigenspace μ k :=
(f.genEigenspace μ).monotone (Nat.succ_le_of_lt hk)
#align module.End.eigenspace_le_generalized_eigenspace Module.End.eigenspace_le_genEigenspace
/-- All eigenvalues are generalized eigenvalues. -/
theorem hasGenEigenvalue_of_hasEigenvalue {f : End R M} {μ : R} {k : ℕ} (hk : 0 < k)
(hμ : f.HasEigenvalue μ) : f.HasGenEigenvalue μ k := by
apply hasGenEigenvalue_of_hasGenEigenvalue_of_le hk
rw [HasGenEigenvalue, genEigenspace, OrderHom.coe_mk, pow_one]
exact hμ
#align module.End.has_generalized_eigenvalue_of_has_eigenvalue Module.End.hasGenEigenvalue_of_hasEigenvalue
/-- All generalized eigenvalues are eigenvalues. -/
theorem hasEigenvalue_of_hasGenEigenvalue {f : End R M} {μ : R} {k : ℕ}
(hμ : f.HasGenEigenvalue μ k) : f.HasEigenvalue μ := by
intro contra; apply hμ
erw [LinearMap.ker_eq_bot] at contra ⊢; rw [LinearMap.coe_pow]
exact Function.Injective.iterate contra k
#align module.End.has_eigenvalue_of_has_generalized_eigenvalue Module.End.hasEigenvalue_of_hasGenEigenvalue
/-- Generalized eigenvalues are actually just eigenvalues. -/
@[simp]
theorem hasGenEigenvalue_iff_hasEigenvalue {f : End R M} {μ : R} {k : ℕ} (hk : 0 < k) :
f.HasGenEigenvalue μ k ↔ f.HasEigenvalue μ :=
⟨hasEigenvalue_of_hasGenEigenvalue, hasGenEigenvalue_of_hasEigenvalue hk⟩
#align module.End.has_generalized_eigenvalue_iff_has_eigenvalue Module.End.hasGenEigenvalue_iff_hasEigenvalue
/-- Every generalized eigenvector is a generalized eigenvector for exponent `finrank K V`.
(Lemma 8.11 of [axler2015]) -/
theorem genEigenspace_le_genEigenspace_finrank [FiniteDimensional K V] (f : End K V)
(μ : K) (k : ℕ) : f.genEigenspace μ k ≤ f.genEigenspace μ (finrank K V) :=
ker_pow_le_ker_pow_finrank _ _
#align module.End.generalized_eigenspace_le_generalized_eigenspace_finrank Module.End.genEigenspace_le_genEigenspace_finrank
@[simp] theorem iSup_genEigenspace_eq_genEigenspace_finrank
[FiniteDimensional K V] (f : End K V) (μ : K) :
⨆ k, f.genEigenspace μ k = f.genEigenspace μ (finrank K V) :=
le_antisymm (iSup_le (genEigenspace_le_genEigenspace_finrank f μ)) (le_iSup _ _)
/-- Generalized eigenspaces for exponents at least `finrank K V` are equal to each other. -/
theorem genEigenspace_eq_genEigenspace_finrank_of_le [FiniteDimensional K V]
(f : End K V) (μ : K) {k : ℕ} (hk : finrank K V ≤ k) :
f.genEigenspace μ k = f.genEigenspace μ (finrank K V) :=
ker_pow_eq_ker_pow_finrank_of_le hk
#align module.End.generalized_eigenspace_eq_generalized_eigenspace_finrank_of_le Module.End.genEigenspace_eq_genEigenspace_finrank_of_le
lemma mapsTo_genEigenspace_of_comm {f g : End R M} (h : Commute f g) (μ : R) (k : ℕ) :
MapsTo g (f.genEigenspace μ k) (f.genEigenspace μ k) := by
replace h : Commute ((f - μ • (1 : End R M)) ^ k) g :=
(h.sub_left <| Algebra.commute_algebraMap_left μ g).pow_left k
intro x hx
simp only [SetLike.mem_coe, mem_genEigenspace] at hx ⊢
rw [← LinearMap.comp_apply, ← LinearMap.mul_eq_comp, h.eq, LinearMap.mul_eq_comp,
LinearMap.comp_apply, hx, map_zero]
lemma mapsTo_iSup_genEigenspace_of_comm {f g : End R M} (h : Commute f g) (μ : R) :
MapsTo g ↑(⨆ k, f.genEigenspace μ k) ↑(⨆ k, f.genEigenspace μ k) := by
simp only [MapsTo, Submodule.coe_iSup_of_chain, mem_iUnion, SetLike.mem_coe]
rintro x ⟨k, hk⟩
exact ⟨k, f.mapsTo_genEigenspace_of_comm h μ k hk⟩
/-- The restriction of `f - μ • 1` to the `k`-fold generalized `μ`-eigenspace is nilpotent. -/
lemma isNilpotent_restrict_sub_algebraMap (f : End R M) (μ : R) (k : ℕ)
(h : MapsTo (f - algebraMap R (End R M) μ)
(f.genEigenspace μ k) (f.genEigenspace μ k) :=
mapsTo_genEigenspace_of_comm (Algebra.mul_sub_algebraMap_commutes f μ) μ k) :
IsNilpotent ((f - algebraMap R (End R M) μ).restrict h) := by
use k
ext
simp [LinearMap.restrict_apply, LinearMap.pow_restrict _]
/-- The restriction of `f - μ • 1` to the generalized `μ`-eigenspace is nilpotent. -/
lemma isNilpotent_restrict_iSup_sub_algebraMap [IsNoetherian R M] (f : End R M) (μ : R)
(h : MapsTo (f - algebraMap R (End R M) μ)
↑(⨆ k, f.genEigenspace μ k) ↑(⨆ k, f.genEigenspace μ k) :=
mapsTo_iSup_genEigenspace_of_comm (Algebra.mul_sub_algebraMap_commutes f μ) μ) :
IsNilpotent ((f - algebraMap R (End R M) μ).restrict h) := by
obtain ⟨l, hl⟩ : ∃ l, ⨆ k, f.genEigenspace μ k = f.genEigenspace μ l :=
⟨_, maxGenEigenspace_eq f μ⟩
use l
ext ⟨x, hx⟩
simpa [hl, LinearMap.restrict_apply, LinearMap.pow_restrict _] using hx
lemma disjoint_genEigenspace [NoZeroSMulDivisors R M]
(f : End R M) {μ₁ μ₂ : R} (hμ : μ₁ ≠ μ₂) (k l : ℕ) :
Disjoint (f.genEigenspace μ₁ k) (f.genEigenspace μ₂ l) := by
nontriviality M
have := NoZeroSMulDivisors.isReduced R M
rw [disjoint_iff]
set p := f.genEigenspace μ₁ k ⊓ f.genEigenspace μ₂ l
by_contra hp
replace hp : Nontrivial p := Submodule.nontrivial_iff_ne_bot.mpr hp
let f₁ : End R p := (f - algebraMap R (End R M) μ₁).restrict <| MapsTo.inter_inter
(mapsTo_genEigenspace_of_comm (Algebra.mul_sub_algebraMap_commutes f μ₁) μ₁ k)
(mapsTo_genEigenspace_of_comm (Algebra.mul_sub_algebraMap_commutes f μ₁) μ₂ l)
let f₂ : End R p := (f - algebraMap R (End R M) μ₂).restrict <| MapsTo.inter_inter
(mapsTo_genEigenspace_of_comm (Algebra.mul_sub_algebraMap_commutes f μ₂) μ₁ k)
(mapsTo_genEigenspace_of_comm (Algebra.mul_sub_algebraMap_commutes f μ₂) μ₂ l)
have : IsNilpotent (f₂ - f₁) := by
apply Commute.isNilpotent_sub (x := f₂) (y := f₁) _ ⟨l, ?_⟩ ⟨k, ?_⟩
· ext; simp [f₁, f₂, smul_sub, sub_sub, smul_comm μ₁, add_sub_left_comm]
all_goals ext ⟨x, _, _⟩; simpa [LinearMap.restrict_apply, LinearMap.pow_restrict _] using ‹_›
have hf₁₂ : f₂ - f₁ = algebraMap R (End R p) (μ₁ - μ₂) := by ext; simp [f₁, f₂, sub_smul]
rw [hf₁₂, IsNilpotent.map_iff (NoZeroSMulDivisors.algebraMap_injective R (End R p)),
isNilpotent_iff_eq_zero, sub_eq_zero] at this
contradiction
lemma disjoint_iSup_genEigenspace [NoZeroSMulDivisors R M]
(f : End R M) {μ₁ μ₂ : R} (hμ : μ₁ ≠ μ₂) :
Disjoint (⨆ k, f.genEigenspace μ₁ k) (⨆ k, f.genEigenspace μ₂ k) := by
simp_rw [(f.genEigenspace μ₁).mono.directed_le.disjoint_iSup_left,
(f.genEigenspace μ₂).mono.directed_le.disjoint_iSup_right]
exact disjoint_genEigenspace f hμ
lemma injOn_genEigenspace [NoZeroSMulDivisors R M] (f : End R M) :
InjOn (⨆ k, f.genEigenspace · k) {μ | ⨆ k, f.genEigenspace μ k ≠ ⊥} := by
rintro μ₁ _ μ₂ hμ₂ (hμ₁₂ : ⨆ k, f.genEigenspace μ₁ k = ⨆ k, f.genEigenspace μ₂ k)
by_contra contra
apply hμ₂
simpa only [hμ₁₂, disjoint_self] using f.disjoint_iSup_genEigenspace contra
theorem independent_genEigenspace [NoZeroSMulDivisors R M] (f : End R M) :
CompleteLattice.Independent (fun μ ↦ ⨆ k, f.genEigenspace μ k) := by
classical
suffices ∀ μ (s : Finset R), μ ∉ s → Disjoint (⨆ k, f.genEigenspace μ k)
(s.sup fun μ ↦ ⨆ k, f.genEigenspace μ k) by
simp_rw [CompleteLattice.independent_iff_supIndep_of_injOn f.injOn_genEigenspace,
Finset.supIndep_iff_disjoint_erase]
exact fun s μ _ ↦ this _ _ (s.not_mem_erase μ)
intro μ₁ s
induction' s using Finset.induction_on with μ₂ s _ ih
· simp
intro hμ₁₂
obtain ⟨hμ₁₂ : μ₁ ≠ μ₂, hμ₁ : μ₁ ∉ s⟩ := by rwa [Finset.mem_insert, not_or] at hμ₁₂
specialize ih hμ₁
rw [Finset.sup_insert, disjoint_iff, Submodule.eq_bot_iff]
rintro x ⟨hx, hx'⟩
simp only [SetLike.mem_coe] at hx hx'
suffices x ∈ ⨆ k, genEigenspace f μ₂ k by
rw [← Submodule.mem_bot (R := R), ← (f.disjoint_iSup_genEigenspace hμ₁₂).eq_bot]
exact ⟨hx, this⟩
obtain ⟨y, hy, z, hz, rfl⟩ := Submodule.mem_sup.mp hx'; clear hx'
let g := f - algebraMap R (End R M) μ₂
obtain ⟨k : ℕ, hk : (g ^ k) y = 0⟩ := by simpa using hy
have hyz : (g ^ k) (y + z) ∈
(⨆ k, genEigenspace f μ₁ k) ⊓ s.sup fun μ ↦ ⨆ k, f.genEigenspace μ k := by
refine ⟨f.mapsTo_iSup_genEigenspace_of_comm ?_ μ₁ hx, ?_⟩
· exact Algebra.mul_sub_algebraMap_pow_commutes f μ₂ k
· rw [SetLike.mem_coe, map_add, hk, zero_add]
suffices (s.sup fun μ ↦ ⨆ k, f.genEigenspace μ k).map (g ^ k) ≤
s.sup fun μ ↦ ⨆ k, f.genEigenspace μ k by exact this (Submodule.mem_map_of_mem hz)
simp_rw [Finset.sup_eq_iSup, Submodule.map_iSup (ι := R), Submodule.map_iSup (ι := _ ∈ s)]
refine iSup₂_mono fun μ _ ↦ ?_
rintro - ⟨u, hu, rfl⟩
refine f.mapsTo_iSup_genEigenspace_of_comm ?_ μ hu
exact Algebra.mul_sub_algebraMap_pow_commutes f μ₂ k
rw [ih.eq_bot, Submodule.mem_bot] at hyz
simp_rw [Submodule.mem_iSup_of_chain, mem_genEigenspace]
exact ⟨k, hyz⟩
/-- The eigenspaces of a linear operator form an independent family of subspaces of `M`. That is,
any eigenspace has trivial intersection with the span of all the other eigenspaces. -/
theorem eigenspaces_independent [NoZeroSMulDivisors R M] (f : End R M) :
CompleteLattice.Independent f.eigenspace :=
f.independent_genEigenspace.mono fun μ ↦ le_iSup (genEigenspace f μ) 1
/-- Eigenvectors corresponding to distinct eigenvalues of a linear operator are linearly
independent. (Lemma 5.10 of [axler2015])
We use the eigenvalues as indexing set to ensure that there is only one eigenvector for each
eigenvalue in the image of `xs`. -/
theorem eigenvectors_linearIndependent [NoZeroSMulDivisors R M]
(f : End R M) (μs : Set R) (xs : μs → M)
(h_eigenvec : ∀ μ : μs, f.HasEigenvector μ (xs μ)) : LinearIndependent R xs :=
CompleteLattice.Independent.linearIndependent _
(f.eigenspaces_independent.comp Subtype.coe_injective) (fun μ => (h_eigenvec μ).1) fun μ =>
(h_eigenvec μ).2
#align module.End.eigenvectors_linear_independent Module.End.eigenvectors_linearIndependent
/-- If `f` maps a subspace `p` into itself, then the generalized eigenspace of the restriction
of `f` to `p` is the part of the generalized eigenspace of `f` that lies in `p`. -/
theorem genEigenspace_restrict (f : End R M) (p : Submodule R M) (k : ℕ) (μ : R)
(hfp : ∀ x : M, x ∈ p → f x ∈ p) :
genEigenspace (LinearMap.restrict f hfp) μ k =
Submodule.comap p.subtype (f.genEigenspace μ k) := by
simp only [genEigenspace, OrderHom.coe_mk, ← LinearMap.ker_comp]
induction' k with k ih
· rw [pow_zero, pow_zero, LinearMap.one_eq_id]
apply (Submodule.ker_subtype _).symm
· erw [pow_succ, pow_succ, LinearMap.ker_comp, LinearMap.ker_comp, ih, ← LinearMap.ker_comp,
LinearMap.comp_assoc]
#align module.End.generalized_eigenspace_restrict Module.End.genEigenspace_restrict
lemma _root_.Submodule.inf_genEigenspace (f : End R M) (p : Submodule R M) {k : ℕ} {μ : R}
(hfp : ∀ x : M, x ∈ p → f x ∈ p) :
p ⊓ f.genEigenspace μ k =
(genEigenspace (LinearMap.restrict f hfp) μ k).map p.subtype := by
rw [f.genEigenspace_restrict _ _ _ hfp, Submodule.map_comap_eq, Submodule.range_subtype]
/-- If `p` is an invariant submodule of an endomorphism `f`, then the `μ`-eigenspace of the
restriction of `f` to `p` is a submodule of the `μ`-eigenspace of `f`. -/
theorem eigenspace_restrict_le_eigenspace (f : End R M) {p : Submodule R M} (hfp : ∀ x ∈ p, f x ∈ p)
(μ : R) : (eigenspace (f.restrict hfp) μ).map p.subtype ≤ f.eigenspace μ := by
rintro a ⟨x, hx, rfl⟩
simp only [SetLike.mem_coe, mem_eigenspace_iff, LinearMap.restrict_apply] at hx ⊢
exact congr_arg Subtype.val hx
#align module.End.eigenspace_restrict_le_eigenspace Module.End.eigenspace_restrict_le_eigenspace
/-- Generalized eigenrange and generalized eigenspace for exponent `finrank K V` are disjoint. -/
| Mathlib/LinearAlgebra/Eigenspace/Basic.lean | 468 | 483 | theorem generalized_eigenvec_disjoint_range_ker [FiniteDimensional K V] (f : End K V) (μ : K) :
Disjoint (f.genEigenrange μ (finrank K V))
(f.genEigenspace μ (finrank K V)) := by |
have h :=
calc
Submodule.comap ((f - algebraMap _ _ μ) ^ finrank K V)
(f.genEigenspace μ (finrank K V)) =
LinearMap.ker ((f - algebraMap _ _ μ) ^ finrank K V *
(f - algebraMap K (End K V) μ) ^ finrank K V) := by
rw [genEigenspace, OrderHom.coe_mk, ← LinearMap.ker_comp]; rfl
_ = f.genEigenspace μ (finrank K V + finrank K V) := by rw [← pow_add]; rfl
_ = f.genEigenspace μ (finrank K V) := by
rw [genEigenspace_eq_genEigenspace_finrank_of_le]; omega
rw [disjoint_iff_inf_le, genEigenrange, LinearMap.range_eq_map,
Submodule.map_inf_eq_map_inf_comap, top_inf_eq, h]
apply Submodule.map_comap_le
|
/-
Copyright (c) 2020 Joseph Myers. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joseph Myers
-/
import Mathlib.Data.Set.Pointwise.Interval
import Mathlib.LinearAlgebra.AffineSpace.Basic
import Mathlib.LinearAlgebra.BilinearMap
import Mathlib.LinearAlgebra.Pi
import Mathlib.LinearAlgebra.Prod
#align_import linear_algebra.affine_space.affine_map from "leanprover-community/mathlib"@"bd1fc183335ea95a9519a1630bcf901fe9326d83"
/-!
# Affine maps
This file defines affine maps.
## Main definitions
* `AffineMap` is the type of affine maps between two affine spaces with the same ring `k`. Various
basic examples of affine maps are defined, including `const`, `id`, `lineMap` and `homothety`.
## Notations
* `P1 →ᵃ[k] P2` is a notation for `AffineMap k P1 P2`;
* `AffineSpace V P`: a localized notation for `AddTorsor V P` defined in
`LinearAlgebra.AffineSpace.Basic`.
## Implementation notes
`outParam` is used in the definition of `[AddTorsor V P]` to make `V` an implicit argument
(deduced from `P`) in most cases. As for modules, `k` is an explicit argument rather than implied by
`P` or `V`.
This file only provides purely algebraic definitions and results. Those depending on analysis or
topology are defined elsewhere; see `Analysis.NormedSpace.AddTorsor` and
`Topology.Algebra.Affine`.
## References
* https://en.wikipedia.org/wiki/Affine_space
* https://en.wikipedia.org/wiki/Principal_homogeneous_space
-/
open Affine
/-- An `AffineMap k P1 P2` (notation: `P1 →ᵃ[k] P2`) is a map from `P1` to `P2` that
induces a corresponding linear map from `V1` to `V2`. -/
structure AffineMap (k : Type*) {V1 : Type*} (P1 : Type*) {V2 : Type*} (P2 : Type*) [Ring k]
[AddCommGroup V1] [Module k V1] [AffineSpace V1 P1] [AddCommGroup V2] [Module k V2]
[AffineSpace V2 P2] where
toFun : P1 → P2
linear : V1 →ₗ[k] V2
map_vadd' : ∀ (p : P1) (v : V1), toFun (v +ᵥ p) = linear v +ᵥ toFun p
#align affine_map AffineMap
/-- An `AffineMap k P1 P2` (notation: `P1 →ᵃ[k] P2`) is a map from `P1` to `P2` that
induces a corresponding linear map from `V1` to `V2`. -/
notation:25 P1 " →ᵃ[" k:25 "] " P2:0 => AffineMap k P1 P2
instance AffineMap.instFunLike (k : Type*) {V1 : Type*} (P1 : Type*) {V2 : Type*} (P2 : Type*)
[Ring k] [AddCommGroup V1] [Module k V1] [AffineSpace V1 P1] [AddCommGroup V2] [Module k V2]
[AffineSpace V2 P2] : FunLike (P1 →ᵃ[k] P2) P1 P2 where
coe := AffineMap.toFun
coe_injective' := fun ⟨f, f_linear, f_add⟩ ⟨g, g_linear, g_add⟩ => fun (h : f = g) => by
cases' (AddTorsor.nonempty : Nonempty P1) with p
congr with v
apply vadd_right_cancel (f p)
erw [← f_add, h, ← g_add]
#align affine_map.fun_like AffineMap.instFunLike
instance AffineMap.hasCoeToFun (k : Type*) {V1 : Type*} (P1 : Type*) {V2 : Type*} (P2 : Type*)
[Ring k] [AddCommGroup V1] [Module k V1] [AffineSpace V1 P1] [AddCommGroup V2] [Module k V2]
[AffineSpace V2 P2] : CoeFun (P1 →ᵃ[k] P2) fun _ => P1 → P2 :=
DFunLike.hasCoeToFun
#align affine_map.has_coe_to_fun AffineMap.hasCoeToFun
namespace LinearMap
variable {k : Type*} {V₁ : Type*} {V₂ : Type*} [Ring k] [AddCommGroup V₁] [Module k V₁]
[AddCommGroup V₂] [Module k V₂] (f : V₁ →ₗ[k] V₂)
/-- Reinterpret a linear map as an affine map. -/
def toAffineMap : V₁ →ᵃ[k] V₂ where
toFun := f
linear := f
map_vadd' p v := f.map_add v p
#align linear_map.to_affine_map LinearMap.toAffineMap
@[simp]
theorem coe_toAffineMap : ⇑f.toAffineMap = f :=
rfl
#align linear_map.coe_to_affine_map LinearMap.coe_toAffineMap
@[simp]
theorem toAffineMap_linear : f.toAffineMap.linear = f :=
rfl
#align linear_map.to_affine_map_linear LinearMap.toAffineMap_linear
end LinearMap
namespace AffineMap
variable {k : Type*} {V1 : Type*} {P1 : Type*} {V2 : Type*} {P2 : Type*} {V3 : Type*}
{P3 : Type*} {V4 : Type*} {P4 : Type*} [Ring k] [AddCommGroup V1] [Module k V1]
[AffineSpace V1 P1] [AddCommGroup V2] [Module k V2] [AffineSpace V2 P2] [AddCommGroup V3]
[Module k V3] [AffineSpace V3 P3] [AddCommGroup V4] [Module k V4] [AffineSpace V4 P4]
/-- Constructing an affine map and coercing back to a function
produces the same map. -/
@[simp]
theorem coe_mk (f : P1 → P2) (linear add) : ((mk f linear add : P1 →ᵃ[k] P2) : P1 → P2) = f :=
rfl
#align affine_map.coe_mk AffineMap.coe_mk
/-- `toFun` is the same as the result of coercing to a function. -/
@[simp]
theorem toFun_eq_coe (f : P1 →ᵃ[k] P2) : f.toFun = ⇑f :=
rfl
#align affine_map.to_fun_eq_coe AffineMap.toFun_eq_coe
/-- An affine map on the result of adding a vector to a point produces
the same result as the linear map applied to that vector, added to the
affine map applied to that point. -/
@[simp]
theorem map_vadd (f : P1 →ᵃ[k] P2) (p : P1) (v : V1) : f (v +ᵥ p) = f.linear v +ᵥ f p :=
f.map_vadd' p v
#align affine_map.map_vadd AffineMap.map_vadd
/-- The linear map on the result of subtracting two points is the
result of subtracting the result of the affine map on those two
points. -/
@[simp]
theorem linearMap_vsub (f : P1 →ᵃ[k] P2) (p1 p2 : P1) : f.linear (p1 -ᵥ p2) = f p1 -ᵥ f p2 := by
conv_rhs => rw [← vsub_vadd p1 p2, map_vadd, vadd_vsub]
#align affine_map.linear_map_vsub AffineMap.linearMap_vsub
/-- Two affine maps are equal if they coerce to the same function. -/
@[ext]
theorem ext {f g : P1 →ᵃ[k] P2} (h : ∀ p, f p = g p) : f = g :=
DFunLike.ext _ _ h
#align affine_map.ext AffineMap.ext
theorem ext_iff {f g : P1 →ᵃ[k] P2} : f = g ↔ ∀ p, f p = g p :=
⟨fun h _ => h ▸ rfl, ext⟩
#align affine_map.ext_iff AffineMap.ext_iff
theorem coeFn_injective : @Function.Injective (P1 →ᵃ[k] P2) (P1 → P2) (⇑) :=
DFunLike.coe_injective
#align affine_map.coe_fn_injective AffineMap.coeFn_injective
protected theorem congr_arg (f : P1 →ᵃ[k] P2) {x y : P1} (h : x = y) : f x = f y :=
congr_arg _ h
#align affine_map.congr_arg AffineMap.congr_arg
protected theorem congr_fun {f g : P1 →ᵃ[k] P2} (h : f = g) (x : P1) : f x = g x :=
h ▸ rfl
#align affine_map.congr_fun AffineMap.congr_fun
/-- Two affine maps are equal if they have equal linear maps and are equal at some point. -/
theorem ext_linear {f g : P1 →ᵃ[k] P2} (h₁ : f.linear = g.linear) {p : P1} (h₂ : f p = g p) :
f = g := by
ext q
have hgl : g.linear (q -ᵥ p) = toFun g ((q -ᵥ p) +ᵥ q) -ᵥ toFun g q := by simp
have := f.map_vadd' q (q -ᵥ p)
rw [h₁, hgl, toFun_eq_coe, map_vadd, linearMap_vsub, h₂] at this
simp at this
exact this
/-- Two affine maps are equal if they have equal linear maps and are equal at some point. -/
theorem ext_linear_iff {f g : P1 →ᵃ[k] P2} : f = g ↔ (f.linear = g.linear) ∧ (∃ p, f p = g p) :=
⟨fun h ↦ ⟨congrArg _ h, by inhabit P1; exact default, by rw [h]⟩,
fun h ↦ Exists.casesOn h.2 fun _ hp ↦ ext_linear h.1 hp⟩
variable (k P1)
/-- The constant function as an `AffineMap`. -/
def const (p : P2) : P1 →ᵃ[k] P2 where
toFun := Function.const P1 p
linear := 0
map_vadd' _ _ :=
letI : AddAction V2 P2 := inferInstance
by simp
#align affine_map.const AffineMap.const
@[simp]
theorem coe_const (p : P2) : ⇑(const k P1 p) = Function.const P1 p :=
rfl
#align affine_map.coe_const AffineMap.coe_const
-- Porting note (#10756): new theorem
@[simp]
theorem const_apply (p : P2) (q : P1) : (const k P1 p) q = p := rfl
@[simp]
theorem const_linear (p : P2) : (const k P1 p).linear = 0 :=
rfl
#align affine_map.const_linear AffineMap.const_linear
variable {k P1}
theorem linear_eq_zero_iff_exists_const (f : P1 →ᵃ[k] P2) :
f.linear = 0 ↔ ∃ q, f = const k P1 q := by
refine ⟨fun h => ?_, fun h => ?_⟩
· use f (Classical.arbitrary P1)
ext
rw [coe_const, Function.const_apply, ← @vsub_eq_zero_iff_eq V2, ← f.linearMap_vsub, h,
LinearMap.zero_apply]
· rcases h with ⟨q, rfl⟩
exact const_linear k P1 q
#align affine_map.linear_eq_zero_iff_exists_const AffineMap.linear_eq_zero_iff_exists_const
instance nonempty : Nonempty (P1 →ᵃ[k] P2) :=
(AddTorsor.nonempty : Nonempty P2).map <| const k P1
#align affine_map.nonempty AffineMap.nonempty
/-- Construct an affine map by verifying the relation between the map and its linear part at one
base point. Namely, this function takes a map `f : P₁ → P₂`, a linear map `f' : V₁ →ₗ[k] V₂`, and
a point `p` such that for any other point `p'` we have `f p' = f' (p' -ᵥ p) +ᵥ f p`. -/
def mk' (f : P1 → P2) (f' : V1 →ₗ[k] V2) (p : P1) (h : ∀ p' : P1, f p' = f' (p' -ᵥ p) +ᵥ f p) :
P1 →ᵃ[k] P2 where
toFun := f
linear := f'
map_vadd' p' v := by rw [h, h p', vadd_vsub_assoc, f'.map_add, vadd_vadd]
#align affine_map.mk' AffineMap.mk'
@[simp]
theorem coe_mk' (f : P1 → P2) (f' : V1 →ₗ[k] V2) (p h) : ⇑(mk' f f' p h) = f :=
rfl
#align affine_map.coe_mk' AffineMap.coe_mk'
@[simp]
theorem mk'_linear (f : P1 → P2) (f' : V1 →ₗ[k] V2) (p h) : (mk' f f' p h).linear = f' :=
rfl
#align affine_map.mk'_linear AffineMap.mk'_linear
section SMul
variable {R : Type*} [Monoid R] [DistribMulAction R V2] [SMulCommClass k R V2]
/-- The space of affine maps to a module inherits an `R`-action from the action on its codomain. -/
instance mulAction : MulAction R (P1 →ᵃ[k] V2) where
-- Porting note: `map_vadd` is `simp`, but we still have to pass it explicitly
smul c f := ⟨c • ⇑f, c • f.linear, fun p v => by simp [smul_add, map_vadd f]⟩
one_smul f := ext fun p => one_smul _ _
mul_smul c₁ c₂ f := ext fun p => mul_smul _ _ _
@[simp, norm_cast]
theorem coe_smul (c : R) (f : P1 →ᵃ[k] V2) : ⇑(c • f) = c • ⇑f :=
rfl
#align affine_map.coe_smul AffineMap.coe_smul
@[simp]
theorem smul_linear (t : R) (f : P1 →ᵃ[k] V2) : (t • f).linear = t • f.linear :=
rfl
#align affine_map.smul_linear AffineMap.smul_linear
instance isCentralScalar [DistribMulAction Rᵐᵒᵖ V2] [IsCentralScalar R V2] :
IsCentralScalar R (P1 →ᵃ[k] V2) where
op_smul_eq_smul _r _x := ext fun _ => op_smul_eq_smul _ _
end SMul
instance : Zero (P1 →ᵃ[k] V2) where zero := ⟨0, 0, fun _ _ => (zero_vadd _ _).symm⟩
instance : Add (P1 →ᵃ[k] V2) where
add f g := ⟨f + g, f.linear + g.linear, fun p v => by simp [add_add_add_comm]⟩
instance : Sub (P1 →ᵃ[k] V2) where
sub f g := ⟨f - g, f.linear - g.linear, fun p v => by simp [sub_add_sub_comm]⟩
instance : Neg (P1 →ᵃ[k] V2) where
neg f := ⟨-f, -f.linear, fun p v => by simp [add_comm, map_vadd f]⟩
@[simp, norm_cast]
theorem coe_zero : ⇑(0 : P1 →ᵃ[k] V2) = 0 :=
rfl
#align affine_map.coe_zero AffineMap.coe_zero
@[simp, norm_cast]
theorem coe_add (f g : P1 →ᵃ[k] V2) : ⇑(f + g) = f + g :=
rfl
#align affine_map.coe_add AffineMap.coe_add
@[simp, norm_cast]
theorem coe_neg (f : P1 →ᵃ[k] V2) : ⇑(-f) = -f :=
rfl
#align affine_map.coe_neg AffineMap.coe_neg
@[simp, norm_cast]
theorem coe_sub (f g : P1 →ᵃ[k] V2) : ⇑(f - g) = f - g :=
rfl
#align affine_map.coe_sub AffineMap.coe_sub
@[simp]
theorem zero_linear : (0 : P1 →ᵃ[k] V2).linear = 0 :=
rfl
#align affine_map.zero_linear AffineMap.zero_linear
@[simp]
theorem add_linear (f g : P1 →ᵃ[k] V2) : (f + g).linear = f.linear + g.linear :=
rfl
#align affine_map.add_linear AffineMap.add_linear
@[simp]
theorem sub_linear (f g : P1 →ᵃ[k] V2) : (f - g).linear = f.linear - g.linear :=
rfl
#align affine_map.sub_linear AffineMap.sub_linear
@[simp]
theorem neg_linear (f : P1 →ᵃ[k] V2) : (-f).linear = -f.linear :=
rfl
#align affine_map.neg_linear AffineMap.neg_linear
/-- The set of affine maps to a vector space is an additive commutative group. -/
instance : AddCommGroup (P1 →ᵃ[k] V2) :=
coeFn_injective.addCommGroup _ coe_zero coe_add coe_neg coe_sub (fun _ _ => coe_smul _ _)
fun _ _ => coe_smul _ _
/-- The space of affine maps from `P1` to `P2` is an affine space over the space of affine maps
from `P1` to the vector space `V2` corresponding to `P2`. -/
instance : AffineSpace (P1 →ᵃ[k] V2) (P1 →ᵃ[k] P2) where
vadd f g :=
⟨fun p => f p +ᵥ g p, f.linear + g.linear,
fun p v => by simp [vadd_vadd, add_right_comm]⟩
zero_vadd f := ext fun p => zero_vadd _ (f p)
add_vadd f₁ f₂ f₃ := ext fun p => add_vadd (f₁ p) (f₂ p) (f₃ p)
vsub f g :=
⟨fun p => f p -ᵥ g p, f.linear - g.linear, fun p v => by
simp [vsub_vadd_eq_vsub_sub, vadd_vsub_assoc, add_sub, sub_add_eq_add_sub]⟩
vsub_vadd' f g := ext fun p => vsub_vadd (f p) (g p)
vadd_vsub' f g := ext fun p => vadd_vsub (f p) (g p)
@[simp]
theorem vadd_apply (f : P1 →ᵃ[k] V2) (g : P1 →ᵃ[k] P2) (p : P1) : (f +ᵥ g) p = f p +ᵥ g p :=
rfl
#align affine_map.vadd_apply AffineMap.vadd_apply
@[simp]
theorem vsub_apply (f g : P1 →ᵃ[k] P2) (p : P1) : (f -ᵥ g : P1 →ᵃ[k] V2) p = f p -ᵥ g p :=
rfl
#align affine_map.vsub_apply AffineMap.vsub_apply
/-- `Prod.fst` as an `AffineMap`. -/
def fst : P1 × P2 →ᵃ[k] P1 where
toFun := Prod.fst
linear := LinearMap.fst k V1 V2
map_vadd' _ _ := rfl
#align affine_map.fst AffineMap.fst
@[simp]
theorem coe_fst : ⇑(fst : P1 × P2 →ᵃ[k] P1) = Prod.fst :=
rfl
#align affine_map.coe_fst AffineMap.coe_fst
@[simp]
theorem fst_linear : (fst : P1 × P2 →ᵃ[k] P1).linear = LinearMap.fst k V1 V2 :=
rfl
#align affine_map.fst_linear AffineMap.fst_linear
/-- `Prod.snd` as an `AffineMap`. -/
def snd : P1 × P2 →ᵃ[k] P2 where
toFun := Prod.snd
linear := LinearMap.snd k V1 V2
map_vadd' _ _ := rfl
#align affine_map.snd AffineMap.snd
@[simp]
theorem coe_snd : ⇑(snd : P1 × P2 →ᵃ[k] P2) = Prod.snd :=
rfl
#align affine_map.coe_snd AffineMap.coe_snd
@[simp]
theorem snd_linear : (snd : P1 × P2 →ᵃ[k] P2).linear = LinearMap.snd k V1 V2 :=
rfl
#align affine_map.snd_linear AffineMap.snd_linear
variable (k P1)
/-- Identity map as an affine map. -/
nonrec def id : P1 →ᵃ[k] P1 where
toFun := id
linear := LinearMap.id
map_vadd' _ _ := rfl
#align affine_map.id AffineMap.id
/-- The identity affine map acts as the identity. -/
@[simp]
theorem coe_id : ⇑(id k P1) = _root_.id :=
rfl
#align affine_map.coe_id AffineMap.coe_id
@[simp]
theorem id_linear : (id k P1).linear = LinearMap.id :=
rfl
#align affine_map.id_linear AffineMap.id_linear
variable {P1}
/-- The identity affine map acts as the identity. -/
theorem id_apply (p : P1) : id k P1 p = p :=
rfl
#align affine_map.id_apply AffineMap.id_apply
variable {k}
instance : Inhabited (P1 →ᵃ[k] P1) :=
⟨id k P1⟩
/-- Composition of affine maps. -/
def comp (f : P2 →ᵃ[k] P3) (g : P1 →ᵃ[k] P2) : P1 →ᵃ[k] P3 where
toFun := f ∘ g
linear := f.linear.comp g.linear
map_vadd' := by
intro p v
rw [Function.comp_apply, g.map_vadd, f.map_vadd]
rfl
#align affine_map.comp AffineMap.comp
/-- Composition of affine maps acts as applying the two functions. -/
@[simp]
theorem coe_comp (f : P2 →ᵃ[k] P3) (g : P1 →ᵃ[k] P2) : ⇑(f.comp g) = f ∘ g :=
rfl
#align affine_map.coe_comp AffineMap.coe_comp
/-- Composition of affine maps acts as applying the two functions. -/
theorem comp_apply (f : P2 →ᵃ[k] P3) (g : P1 →ᵃ[k] P2) (p : P1) : f.comp g p = f (g p) :=
rfl
#align affine_map.comp_apply AffineMap.comp_apply
@[simp]
theorem comp_id (f : P1 →ᵃ[k] P2) : f.comp (id k P1) = f :=
ext fun _ => rfl
#align affine_map.comp_id AffineMap.comp_id
@[simp]
theorem id_comp (f : P1 →ᵃ[k] P2) : (id k P2).comp f = f :=
ext fun _ => rfl
#align affine_map.id_comp AffineMap.id_comp
theorem comp_assoc (f₃₄ : P3 →ᵃ[k] P4) (f₂₃ : P2 →ᵃ[k] P3) (f₁₂ : P1 →ᵃ[k] P2) :
(f₃₄.comp f₂₃).comp f₁₂ = f₃₄.comp (f₂₃.comp f₁₂) :=
rfl
#align affine_map.comp_assoc AffineMap.comp_assoc
instance : Monoid (P1 →ᵃ[k] P1) where
one := id k P1
mul := comp
one_mul := id_comp
mul_one := comp_id
mul_assoc := comp_assoc
@[simp]
theorem coe_mul (f g : P1 →ᵃ[k] P1) : ⇑(f * g) = f ∘ g :=
rfl
#align affine_map.coe_mul AffineMap.coe_mul
@[simp]
theorem coe_one : ⇑(1 : P1 →ᵃ[k] P1) = _root_.id :=
rfl
#align affine_map.coe_one AffineMap.coe_one
/-- `AffineMap.linear` on endomorphisms is a `MonoidHom`. -/
@[simps]
def linearHom : (P1 →ᵃ[k] P1) →* V1 →ₗ[k] V1 where
toFun := linear
map_one' := rfl
map_mul' _ _ := rfl
#align affine_map.linear_hom AffineMap.linearHom
@[simp]
theorem linear_injective_iff (f : P1 →ᵃ[k] P2) :
Function.Injective f.linear ↔ Function.Injective f := by
obtain ⟨p⟩ := (inferInstance : Nonempty P1)
have h : ⇑f.linear = (Equiv.vaddConst (f p)).symm ∘ f ∘ Equiv.vaddConst p := by
ext v
simp [f.map_vadd, vadd_vsub_assoc]
rw [h, Equiv.comp_injective, Equiv.injective_comp]
#align affine_map.linear_injective_iff AffineMap.linear_injective_iff
@[simp]
theorem linear_surjective_iff (f : P1 →ᵃ[k] P2) :
Function.Surjective f.linear ↔ Function.Surjective f := by
obtain ⟨p⟩ := (inferInstance : Nonempty P1)
have h : ⇑f.linear = (Equiv.vaddConst (f p)).symm ∘ f ∘ Equiv.vaddConst p := by
ext v
simp [f.map_vadd, vadd_vsub_assoc]
rw [h, Equiv.comp_surjective, Equiv.surjective_comp]
#align affine_map.linear_surjective_iff AffineMap.linear_surjective_iff
@[simp]
theorem linear_bijective_iff (f : P1 →ᵃ[k] P2) :
Function.Bijective f.linear ↔ Function.Bijective f :=
and_congr f.linear_injective_iff f.linear_surjective_iff
#align affine_map.linear_bijective_iff AffineMap.linear_bijective_iff
theorem image_vsub_image {s t : Set P1} (f : P1 →ᵃ[k] P2) :
f '' s -ᵥ f '' t = f.linear '' (s -ᵥ t) := by
ext v
-- Porting note: `simp` needs `Set.mem_vsub` to be an expression
simp only [(Set.mem_vsub), Set.mem_image,
exists_exists_and_eq_and, exists_and_left, ← f.linearMap_vsub]
constructor
· rintro ⟨x, hx, y, hy, hv⟩
exact ⟨x -ᵥ y, ⟨x, hx, y, hy, rfl⟩, hv⟩
· rintro ⟨-, ⟨x, hx, y, hy, rfl⟩, rfl⟩
exact ⟨x, hx, y, hy, rfl⟩
#align affine_map.image_vsub_image AffineMap.image_vsub_image
/-! ### Definition of `AffineMap.lineMap` and lemmas about it -/
/-- The affine map from `k` to `P1` sending `0` to `p₀` and `1` to `p₁`. -/
def lineMap (p₀ p₁ : P1) : k →ᵃ[k] P1 :=
((LinearMap.id : k →ₗ[k] k).smulRight (p₁ -ᵥ p₀)).toAffineMap +ᵥ const k k p₀
#align affine_map.line_map AffineMap.lineMap
theorem coe_lineMap (p₀ p₁ : P1) : (lineMap p₀ p₁ : k → P1) = fun c => c • (p₁ -ᵥ p₀) +ᵥ p₀ :=
rfl
#align affine_map.coe_line_map AffineMap.coe_lineMap
theorem lineMap_apply (p₀ p₁ : P1) (c : k) : lineMap p₀ p₁ c = c • (p₁ -ᵥ p₀) +ᵥ p₀ :=
rfl
#align affine_map.line_map_apply AffineMap.lineMap_apply
theorem lineMap_apply_module' (p₀ p₁ : V1) (c : k) : lineMap p₀ p₁ c = c • (p₁ - p₀) + p₀ :=
rfl
#align affine_map.line_map_apply_module' AffineMap.lineMap_apply_module'
| Mathlib/LinearAlgebra/AffineSpace/AffineMap.lean | 528 | 529 | theorem lineMap_apply_module (p₀ p₁ : V1) (c : k) : lineMap p₀ p₁ c = (1 - c) • p₀ + c • p₁ := by |
simp [lineMap_apply_module', smul_sub, sub_smul]; abel
|
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Joey van Langen, Casper Putz
-/
import Mathlib.FieldTheory.Separable
import Mathlib.RingTheory.IntegralDomain
import Mathlib.Algebra.CharP.Reduced
import Mathlib.Tactic.ApplyFun
#align_import field_theory.finite.basic from "leanprover-community/mathlib"@"12a85fac627bea918960da036049d611b1a3ee43"
/-!
# Finite fields
This file contains basic results about finite fields.
Throughout most of this file, `K` denotes a finite field
and `q` is notation for the cardinality of `K`.
See `RingTheory.IntegralDomain` for the fact that the unit group of a finite field is a
cyclic group, as well as the fact that every finite integral domain is a field
(`Fintype.fieldOfDomain`).
## Main results
1. `Fintype.card_units`: The unit group of a finite field has cardinality `q - 1`.
2. `sum_pow_units`: The sum of `x^i`, where `x` ranges over the units of `K`, is
- `q-1` if `q-1 ∣ i`
- `0` otherwise
3. `FiniteField.card`: The cardinality `q` is a power of the characteristic of `K`.
See `FiniteField.card'` for a variant.
## Notation
Throughout most of this file, `K` denotes a finite field
and `q` is notation for the cardinality of `K`.
## Implementation notes
While `Fintype Kˣ` can be inferred from `Fintype K` in the presence of `DecidableEq K`,
in this file we take the `Fintype Kˣ` argument directly to reduce the chance of typeclass
diamonds, as `Fintype` carries data.
-/
variable {K : Type*} {R : Type*}
local notation "q" => Fintype.card K
open Finset
open scoped Polynomial
namespace FiniteField
section Polynomial
variable [CommRing R] [IsDomain R]
open Polynomial
/-- The cardinality of a field is at most `n` times the cardinality of the image of a degree `n`
polynomial -/
theorem card_image_polynomial_eval [DecidableEq R] [Fintype R] {p : R[X]} (hp : 0 < p.degree) :
Fintype.card R ≤ natDegree p * (univ.image fun x => eval x p).card :=
Finset.card_le_mul_card_image _ _ (fun a _ =>
calc
_ = (p - C a).roots.toFinset.card :=
congr_arg card (by simp [Finset.ext_iff, ← mem_roots_sub_C hp])
_ ≤ Multiset.card (p - C a).roots := Multiset.toFinset_card_le _
_ ≤ _ := card_roots_sub_C' hp)
#align finite_field.card_image_polynomial_eval FiniteField.card_image_polynomial_eval
/-- If `f` and `g` are quadratic polynomials, then the `f.eval a + g.eval b = 0` has a solution. -/
theorem exists_root_sum_quadratic [Fintype R] {f g : R[X]} (hf2 : degree f = 2) (hg2 : degree g = 2)
(hR : Fintype.card R % 2 = 1) : ∃ a b, f.eval a + g.eval b = 0 :=
letI := Classical.decEq R
suffices ¬Disjoint (univ.image fun x : R => eval x f)
(univ.image fun x : R => eval x (-g)) by
simp only [disjoint_left, mem_image] at this
push_neg at this
rcases this with ⟨x, ⟨a, _, ha⟩, ⟨b, _, hb⟩⟩
exact ⟨a, b, by rw [ha, ← hb, eval_neg, neg_add_self]⟩
fun hd : Disjoint _ _ =>
lt_irrefl (2 * ((univ.image fun x : R => eval x f) ∪ univ.image fun x : R => eval x (-g)).card) <|
calc 2 * ((univ.image fun x : R => eval x f) ∪ univ.image fun x : R => eval x (-g)).card
≤ 2 * Fintype.card R := Nat.mul_le_mul_left _ (Finset.card_le_univ _)
_ = Fintype.card R + Fintype.card R := two_mul _
_ < natDegree f * (univ.image fun x : R => eval x f).card +
natDegree (-g) * (univ.image fun x : R => eval x (-g)).card :=
(add_lt_add_of_lt_of_le
(lt_of_le_of_ne (card_image_polynomial_eval (by rw [hf2]; decide))
(mt (congr_arg (· % 2)) (by simp [natDegree_eq_of_degree_eq_some hf2, hR])))
(card_image_polynomial_eval (by rw [degree_neg, hg2]; decide)))
_ = 2 * ((univ.image fun x : R => eval x f) ∪ univ.image fun x : R => eval x (-g)).card := by
rw [card_union_of_disjoint hd];
simp [natDegree_eq_of_degree_eq_some hf2, natDegree_eq_of_degree_eq_some hg2, mul_add]
#align finite_field.exists_root_sum_quadratic FiniteField.exists_root_sum_quadratic
end Polynomial
theorem prod_univ_units_id_eq_neg_one [CommRing K] [IsDomain K] [Fintype Kˣ] :
∏ x : Kˣ, x = (-1 : Kˣ) := by
classical
have : (∏ x ∈ (@univ Kˣ _).erase (-1), x) = 1 :=
prod_involution (fun x _ => x⁻¹) (by simp)
(fun a => by simp (config := { contextual := true }) [Units.inv_eq_self_iff])
(fun a => by simp [@inv_eq_iff_eq_inv _ _ a]) (by simp)
rw [← insert_erase (mem_univ (-1 : Kˣ)), prod_insert (not_mem_erase _ _), this, mul_one]
#align finite_field.prod_univ_units_id_eq_neg_one FiniteField.prod_univ_units_id_eq_neg_one
set_option backward.synthInstance.canonInstances false in -- See https://github.com/leanprover-community/mathlib4/issues/12532
theorem card_cast_subgroup_card_ne_zero [Ring K] [NoZeroDivisors K] [Nontrivial K]
(G : Subgroup Kˣ) [Fintype G] : (Fintype.card G : K) ≠ 0 := by
let n := Fintype.card G
intro nzero
have ⟨p, char_p⟩ := CharP.exists K
have hd : p ∣ n := (CharP.cast_eq_zero_iff K p n).mp nzero
cases CharP.char_is_prime_or_zero K p with
| inr pzero =>
exact (Fintype.card_pos).ne' <| Nat.eq_zero_of_zero_dvd <| pzero ▸ hd
| inl pprime =>
have fact_pprime := Fact.mk pprime
-- G has an element x of order p by Cauchy's theorem
have ⟨x, hx⟩ := exists_prime_orderOf_dvd_card p hd
-- F has an element u (= ↑↑x) of order p
let u := ((x : Kˣ) : K)
have hu : orderOf u = p := by rwa [orderOf_units, Subgroup.orderOf_coe]
-- u ^ p = 1 implies (u - 1) ^ p = 0 and hence u = 1 ...
have h : u = 1 := by
rw [← sub_left_inj, sub_self 1]
apply pow_eq_zero (n := p)
rw [sub_pow_char_of_commute, one_pow, ← hu, pow_orderOf_eq_one, sub_self]
exact Commute.one_right u
-- ... meaning x didn't have order p after all, contradiction
apply pprime.one_lt.ne
rw [← hu, h, orderOf_one]
/-- The sum of a nontrivial subgroup of the units of a field is zero. -/
theorem sum_subgroup_units_eq_zero [Ring K] [NoZeroDivisors K]
{G : Subgroup Kˣ} [Fintype G] (hg : G ≠ ⊥) :
∑ x : G, (x.val : K) = 0 := by
rw [Subgroup.ne_bot_iff_exists_ne_one] at hg
rcases hg with ⟨a, ha⟩
-- The action of a on G as an embedding
let a_mul_emb : G ↪ G := mulLeftEmbedding a
-- ... and leaves G unchanged
have h_unchanged : Finset.univ.map a_mul_emb = Finset.univ := by simp
-- Therefore the sum of x over a G is the sum of a x over G
have h_sum_map := Finset.univ.sum_map a_mul_emb fun x => ((x : Kˣ) : K)
-- ... and the former is the sum of x over G.
-- By algebraic manipulation, we have Σ G, x = ∑ G, a x = a ∑ G, x
simp only [a_mul_emb, h_unchanged, Function.Embedding.coeFn_mk, Function.Embedding.toFun_eq_coe,
mulLeftEmbedding_apply, Submonoid.coe_mul, Subgroup.coe_toSubmonoid, Units.val_mul,
← Finset.mul_sum] at h_sum_map
-- thus one of (a - 1) or ∑ G, x is zero
have hzero : (((a : Kˣ) : K) - 1) = 0 ∨ ∑ x : ↥G, ((x : Kˣ) : K) = 0 := by
rw [← mul_eq_zero, sub_mul, ← h_sum_map, one_mul, sub_self]
apply Or.resolve_left hzero
contrapose! ha
ext
rwa [← sub_eq_zero]
/-- The sum of a subgroup of the units of a field is 1 if the subgroup is trivial and 1 otherwise -/
@[simp]
theorem sum_subgroup_units [Ring K] [NoZeroDivisors K]
{G : Subgroup Kˣ} [Fintype G] [Decidable (G = ⊥)] :
∑ x : G, (x.val : K) = if G = ⊥ then 1 else 0 := by
by_cases G_bot : G = ⊥
· subst G_bot
simp only [ite_true, Subgroup.mem_bot, Fintype.card_ofSubsingleton, Nat.cast_ite, Nat.cast_one,
Nat.cast_zero, univ_unique, Set.default_coe_singleton, sum_singleton, Units.val_one]
· simp only [G_bot, ite_false]
exact sum_subgroup_units_eq_zero G_bot
@[simp]
theorem sum_subgroup_pow_eq_zero [CommRing K] [NoZeroDivisors K]
{G : Subgroup Kˣ} [Fintype G] {k : ℕ} (k_pos : k ≠ 0) (k_lt_card_G : k < Fintype.card G) :
∑ x : G, ((x : Kˣ) : K) ^ k = 0 := by
nontriviality K
have := NoZeroDivisors.to_isDomain K
rcases (exists_pow_ne_one_of_isCyclic k_pos k_lt_card_G) with ⟨a, ha⟩
rw [Finset.sum_eq_multiset_sum]
have h_multiset_map :
Finset.univ.val.map (fun x : G => ((x : Kˣ) : K) ^ k) =
Finset.univ.val.map (fun x : G => ((x : Kˣ) : K) ^ k * ((a : Kˣ) : K) ^ k) := by
simp_rw [← mul_pow]
have as_comp :
(fun x : ↥G => (((x : Kˣ) : K) * ((a : Kˣ) : K)) ^ k)
= (fun x : ↥G => ((x : Kˣ) : K) ^ k) ∘ fun x : ↥G => x * a := by
funext x
simp only [Function.comp_apply, Submonoid.coe_mul, Subgroup.coe_toSubmonoid, Units.val_mul]
rw [as_comp, ← Multiset.map_map]
congr
rw [eq_comm]
exact Multiset.map_univ_val_equiv (Equiv.mulRight a)
have h_multiset_map_sum : (Multiset.map (fun x : G => ((x : Kˣ) : K) ^ k) Finset.univ.val).sum =
(Multiset.map (fun x : G => ((x : Kˣ) : K) ^ k * ((a : Kˣ) : K) ^ k) Finset.univ.val).sum := by
rw [h_multiset_map]
rw [Multiset.sum_map_mul_right] at h_multiset_map_sum
have hzero : (((a : Kˣ) : K) ^ k - 1 : K)
* (Multiset.map (fun i : G => (i.val : K) ^ k) Finset.univ.val).sum = 0 := by
rw [sub_mul, mul_comm, ← h_multiset_map_sum, one_mul, sub_self]
rw [mul_eq_zero] at hzero
refine hzero.resolve_left fun h => ha ?_
ext
rw [← sub_eq_zero]
simp_rw [SubmonoidClass.coe_pow, Units.val_pow_eq_pow_val, OneMemClass.coe_one, Units.val_one, h]
section
variable [GroupWithZero K] [Fintype K]
| Mathlib/FieldTheory/Finite/Basic.lean | 216 | 223 | theorem pow_card_sub_one_eq_one (a : K) (ha : a ≠ 0) : a ^ (q - 1) = 1 := by |
calc
a ^ (Fintype.card K - 1) = (Units.mk0 a ha ^ (Fintype.card K - 1) : Kˣ).1 := by
rw [Units.val_pow_eq_pow_val, Units.val_mk0]
_ = 1 := by
classical
rw [← Fintype.card_units, pow_card_eq_one]
rfl
|
/-
Copyright (c) 2022 Jujian Zhang. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Markus Himmel, Scott Morrison, Jakob von Raumer, Joël Riou
-/
import Mathlib.CategoryTheory.Preadditive.ProjectiveResolution
import Mathlib.Algebra.Homology.HomotopyCategory
import Mathlib.Tactic.SuppressCompilation
/-!
# Abelian categories with enough projectives have projective resolutions
## Main results
When the underlying category is abelian:
* `CategoryTheory.ProjectiveResolution.lift`: Given `P : ProjectiveResolution X` and
`Q : ProjectiveResolution Y`, any morphism `X ⟶ Y` admits a lifting to a chain map
`P.complex ⟶ Q.complex`. It is a lifting in the sense that `P.ι` intertwines the lift and
the original morphism, see `CategoryTheory.ProjectiveResolution.lift_commutes`.
* `CategoryTheory.ProjectiveResolution.liftHomotopy`: Any two such descents are homotopic.
* `CategoryTheory.ProjectiveResolution.homotopyEquiv`: Any two projective resolutions of the same
object are homotopy equivalent.
* `CategoryTheory.projectiveResolutions`: If every object admits a projective resolution, we can
construct a functor `projectiveResolutions C : C ⥤ HomotopyCategory C (ComplexShape.down ℕ)`.
* `CategoryTheory.exact_d_f`: `Projective.d f` and `f` are exact.
* `CategoryTheory.ProjectiveResolution.of`: Hence, starting from an epimorphism `P ⟶ X`, where `P`
is projective, we can apply `Projective.d` repeatedly to obtain a projective resolution of `X`.
-/
suppress_compilation
noncomputable section
universe v u
namespace CategoryTheory
variable {C : Type u} [Category.{v} C]
open Category Limits Projective
set_option linter.uppercaseLean3 false -- `ProjectiveResolution`
namespace ProjectiveResolution
section
variable [HasZeroObject C] [HasZeroMorphisms C]
/-- Auxiliary construction for `lift`. -/
def liftFZero {Y Z : C} (f : Y ⟶ Z) (P : ProjectiveResolution Y) (Q : ProjectiveResolution Z) :
P.complex.X 0 ⟶ Q.complex.X 0 :=
Projective.factorThru (P.π.f 0 ≫ f) (Q.π.f 0)
#align category_theory.ProjectiveResolution.lift_f_zero CategoryTheory.ProjectiveResolution.liftFZero
end
section Abelian
variable [Abelian C]
lemma exact₀ {Z : C} (P : ProjectiveResolution Z) :
(ShortComplex.mk _ _ P.complex_d_comp_π_f_zero).Exact :=
ShortComplex.exact_of_g_is_cokernel _ P.isColimitCokernelCofork
/-- Auxiliary construction for `lift`. -/
def liftFOne {Y Z : C} (f : Y ⟶ Z) (P : ProjectiveResolution Y) (Q : ProjectiveResolution Z) :
P.complex.X 1 ⟶ Q.complex.X 1 :=
Q.exact₀.liftFromProjective (P.complex.d 1 0 ≫ liftFZero f P Q) (by simp [liftFZero])
#align category_theory.ProjectiveResolution.lift_f_one CategoryTheory.ProjectiveResolution.liftFOne
@[simp]
| Mathlib/CategoryTheory/Abelian/ProjectiveResolution.lean | 73 | 76 | theorem liftFOne_zero_comm {Y Z : C} (f : Y ⟶ Z) (P : ProjectiveResolution Y)
(Q : ProjectiveResolution Z) :
liftFOne f P Q ≫ Q.complex.d 1 0 = P.complex.d 1 0 ≫ liftFZero f P Q := by |
apply Q.exact₀.liftFromProjective_comp
|
/-
Copyright (c) 2018 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel
-/
import Mathlib.Order.ConditionallyCompleteLattice.Basic
import Mathlib.Data.Set.Finite
#align_import order.conditionally_complete_lattice.finset from "leanprover-community/mathlib"@"2445c98ae4b87eabebdde552593519b9b6dc350c"
/-!
# Conditionally complete lattices and finite sets.
-/
open Set
variable {ι α β γ : Type*}
section ConditionallyCompleteLinearOrder
variable [ConditionallyCompleteLinearOrder α] {s t : Set α} {a b : α}
theorem Finset.Nonempty.csSup_eq_max' {s : Finset α} (h : s.Nonempty) : sSup ↑s = s.max' h :=
eq_of_forall_ge_iff fun _ => (csSup_le_iff s.bddAbove h.to_set).trans (s.max'_le_iff h).symm
#align finset.nonempty.cSup_eq_max' Finset.Nonempty.csSup_eq_max'
theorem Finset.Nonempty.csInf_eq_min' {s : Finset α} (h : s.Nonempty) : sInf ↑s = s.min' h :=
@Finset.Nonempty.csSup_eq_max' αᵒᵈ _ s h
#align finset.nonempty.cInf_eq_min' Finset.Nonempty.csInf_eq_min'
theorem Finset.Nonempty.csSup_mem {s : Finset α} (h : s.Nonempty) : sSup (s : Set α) ∈ s := by
rw [h.csSup_eq_max']
exact s.max'_mem _
#align finset.nonempty.cSup_mem Finset.Nonempty.csSup_mem
theorem Finset.Nonempty.csInf_mem {s : Finset α} (h : s.Nonempty) : sInf (s : Set α) ∈ s :=
@Finset.Nonempty.csSup_mem αᵒᵈ _ _ h
#align finset.nonempty.cInf_mem Finset.Nonempty.csInf_mem
| Mathlib/Order/ConditionallyCompleteLattice/Finset.lean | 42 | 44 | theorem Set.Nonempty.csSup_mem (h : s.Nonempty) (hs : s.Finite) : sSup s ∈ s := by |
lift s to Finset α using hs
exact Finset.Nonempty.csSup_mem h
|
/-
Copyright (c) 2021 Rémy Degenne. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Zhouhang Zhou, Yury Kudryashov
-/
import Mathlib.MeasureTheory.Function.L1Space
import Mathlib.Analysis.NormedSpace.IndicatorFunction
#align_import measure_theory.integral.integrable_on from "leanprover-community/mathlib"@"8b8ba04e2f326f3f7cf24ad129beda58531ada61"
/-! # Functions integrable on a set and at a filter
We define `IntegrableOn f s μ := Integrable f (μ.restrict s)` and prove theorems like
`integrableOn_union : IntegrableOn f (s ∪ t) μ ↔ IntegrableOn f s μ ∧ IntegrableOn f t μ`.
Next we define a predicate `IntegrableAtFilter (f : α → E) (l : Filter α) (μ : Measure α)`
saying that `f` is integrable at some set `s ∈ l` and prove that a measurable function is integrable
at `l` with respect to `μ` provided that `f` is bounded above at `l ⊓ ae μ` and `μ` is finite
at `l`.
-/
noncomputable section
open Set Filter TopologicalSpace MeasureTheory Function
open scoped Classical Topology Interval Filter ENNReal MeasureTheory
variable {α β E F : Type*} [MeasurableSpace α]
section
variable [TopologicalSpace β] {l l' : Filter α} {f g : α → β} {μ ν : Measure α}
/-- A function `f` is strongly measurable at a filter `l` w.r.t. a measure `μ` if it is
ae strongly measurable w.r.t. `μ.restrict s` for some `s ∈ l`. -/
def StronglyMeasurableAtFilter (f : α → β) (l : Filter α) (μ : Measure α := by volume_tac) :=
∃ s ∈ l, AEStronglyMeasurable f (μ.restrict s)
#align strongly_measurable_at_filter StronglyMeasurableAtFilter
@[simp]
theorem stronglyMeasurableAt_bot {f : α → β} : StronglyMeasurableAtFilter f ⊥ μ :=
⟨∅, mem_bot, by simp⟩
#align strongly_measurable_at_bot stronglyMeasurableAt_bot
protected theorem StronglyMeasurableAtFilter.eventually (h : StronglyMeasurableAtFilter f l μ) :
∀ᶠ s in l.smallSets, AEStronglyMeasurable f (μ.restrict s) :=
(eventually_smallSets' fun _ _ => AEStronglyMeasurable.mono_set).2 h
#align strongly_measurable_at_filter.eventually StronglyMeasurableAtFilter.eventually
protected theorem StronglyMeasurableAtFilter.filter_mono (h : StronglyMeasurableAtFilter f l μ)
(h' : l' ≤ l) : StronglyMeasurableAtFilter f l' μ :=
let ⟨s, hsl, hs⟩ := h
⟨s, h' hsl, hs⟩
#align strongly_measurable_at_filter.filter_mono StronglyMeasurableAtFilter.filter_mono
protected theorem MeasureTheory.AEStronglyMeasurable.stronglyMeasurableAtFilter
(h : AEStronglyMeasurable f μ) : StronglyMeasurableAtFilter f l μ :=
⟨univ, univ_mem, by rwa [Measure.restrict_univ]⟩
#align measure_theory.ae_strongly_measurable.strongly_measurable_at_filter MeasureTheory.AEStronglyMeasurable.stronglyMeasurableAtFilter
theorem AeStronglyMeasurable.stronglyMeasurableAtFilter_of_mem {s}
(h : AEStronglyMeasurable f (μ.restrict s)) (hl : s ∈ l) : StronglyMeasurableAtFilter f l μ :=
⟨s, hl, h⟩
#align ae_strongly_measurable.strongly_measurable_at_filter_of_mem AeStronglyMeasurable.stronglyMeasurableAtFilter_of_mem
protected theorem MeasureTheory.StronglyMeasurable.stronglyMeasurableAtFilter
(h : StronglyMeasurable f) : StronglyMeasurableAtFilter f l μ :=
h.aestronglyMeasurable.stronglyMeasurableAtFilter
#align measure_theory.strongly_measurable.strongly_measurable_at_filter MeasureTheory.StronglyMeasurable.stronglyMeasurableAtFilter
end
namespace MeasureTheory
section NormedAddCommGroup
theorem hasFiniteIntegral_restrict_of_bounded [NormedAddCommGroup E] {f : α → E} {s : Set α}
{μ : Measure α} {C} (hs : μ s < ∞) (hf : ∀ᵐ x ∂μ.restrict s, ‖f x‖ ≤ C) :
HasFiniteIntegral f (μ.restrict s) :=
haveI : IsFiniteMeasure (μ.restrict s) := ⟨by rwa [Measure.restrict_apply_univ]⟩
hasFiniteIntegral_of_bounded hf
#align measure_theory.has_finite_integral_restrict_of_bounded MeasureTheory.hasFiniteIntegral_restrict_of_bounded
variable [NormedAddCommGroup E] {f g : α → E} {s t : Set α} {μ ν : Measure α}
/-- A function is `IntegrableOn` a set `s` if it is almost everywhere strongly measurable on `s`
and if the integral of its pointwise norm over `s` is less than infinity. -/
def IntegrableOn (f : α → E) (s : Set α) (μ : Measure α := by volume_tac) : Prop :=
Integrable f (μ.restrict s)
#align measure_theory.integrable_on MeasureTheory.IntegrableOn
theorem IntegrableOn.integrable (h : IntegrableOn f s μ) : Integrable f (μ.restrict s) :=
h
#align measure_theory.integrable_on.integrable MeasureTheory.IntegrableOn.integrable
@[simp]
theorem integrableOn_empty : IntegrableOn f ∅ μ := by simp [IntegrableOn, integrable_zero_measure]
#align measure_theory.integrable_on_empty MeasureTheory.integrableOn_empty
@[simp]
theorem integrableOn_univ : IntegrableOn f univ μ ↔ Integrable f μ := by
rw [IntegrableOn, Measure.restrict_univ]
#align measure_theory.integrable_on_univ MeasureTheory.integrableOn_univ
theorem integrableOn_zero : IntegrableOn (fun _ => (0 : E)) s μ :=
integrable_zero _ _ _
#align measure_theory.integrable_on_zero MeasureTheory.integrableOn_zero
@[simp]
theorem integrableOn_const {C : E} : IntegrableOn (fun _ => C) s μ ↔ C = 0 ∨ μ s < ∞ :=
integrable_const_iff.trans <| by rw [Measure.restrict_apply_univ]
#align measure_theory.integrable_on_const MeasureTheory.integrableOn_const
theorem IntegrableOn.mono (h : IntegrableOn f t ν) (hs : s ⊆ t) (hμ : μ ≤ ν) : IntegrableOn f s μ :=
h.mono_measure <| Measure.restrict_mono hs hμ
#align measure_theory.integrable_on.mono MeasureTheory.IntegrableOn.mono
theorem IntegrableOn.mono_set (h : IntegrableOn f t μ) (hst : s ⊆ t) : IntegrableOn f s μ :=
h.mono hst le_rfl
#align measure_theory.integrable_on.mono_set MeasureTheory.IntegrableOn.mono_set
theorem IntegrableOn.mono_measure (h : IntegrableOn f s ν) (hμ : μ ≤ ν) : IntegrableOn f s μ :=
h.mono (Subset.refl _) hμ
#align measure_theory.integrable_on.mono_measure MeasureTheory.IntegrableOn.mono_measure
theorem IntegrableOn.mono_set_ae (h : IntegrableOn f t μ) (hst : s ≤ᵐ[μ] t) : IntegrableOn f s μ :=
h.integrable.mono_measure <| Measure.restrict_mono_ae hst
#align measure_theory.integrable_on.mono_set_ae MeasureTheory.IntegrableOn.mono_set_ae
theorem IntegrableOn.congr_set_ae (h : IntegrableOn f t μ) (hst : s =ᵐ[μ] t) : IntegrableOn f s μ :=
h.mono_set_ae hst.le
#align measure_theory.integrable_on.congr_set_ae MeasureTheory.IntegrableOn.congr_set_ae
theorem IntegrableOn.congr_fun_ae (h : IntegrableOn f s μ) (hst : f =ᵐ[μ.restrict s] g) :
IntegrableOn g s μ :=
Integrable.congr h hst
#align measure_theory.integrable_on.congr_fun_ae MeasureTheory.IntegrableOn.congr_fun_ae
theorem integrableOn_congr_fun_ae (hst : f =ᵐ[μ.restrict s] g) :
IntegrableOn f s μ ↔ IntegrableOn g s μ :=
⟨fun h => h.congr_fun_ae hst, fun h => h.congr_fun_ae hst.symm⟩
#align measure_theory.integrable_on_congr_fun_ae MeasureTheory.integrableOn_congr_fun_ae
theorem IntegrableOn.congr_fun (h : IntegrableOn f s μ) (hst : EqOn f g s) (hs : MeasurableSet s) :
IntegrableOn g s μ :=
h.congr_fun_ae ((ae_restrict_iff' hs).2 (eventually_of_forall hst))
#align measure_theory.integrable_on.congr_fun MeasureTheory.IntegrableOn.congr_fun
theorem integrableOn_congr_fun (hst : EqOn f g s) (hs : MeasurableSet s) :
IntegrableOn f s μ ↔ IntegrableOn g s μ :=
⟨fun h => h.congr_fun hst hs, fun h => h.congr_fun hst.symm hs⟩
#align measure_theory.integrable_on_congr_fun MeasureTheory.integrableOn_congr_fun
theorem Integrable.integrableOn (h : Integrable f μ) : IntegrableOn f s μ :=
h.mono_measure <| Measure.restrict_le_self
#align measure_theory.integrable.integrable_on MeasureTheory.Integrable.integrableOn
theorem IntegrableOn.restrict (h : IntegrableOn f s μ) (hs : MeasurableSet s) :
IntegrableOn f s (μ.restrict t) := by
rw [IntegrableOn, Measure.restrict_restrict hs]; exact h.mono_set inter_subset_left
#align measure_theory.integrable_on.restrict MeasureTheory.IntegrableOn.restrict
theorem IntegrableOn.inter_of_restrict (h : IntegrableOn f s (μ.restrict t)) :
IntegrableOn f (s ∩ t) μ := by
have := h.mono_set (inter_subset_left (t := t))
rwa [IntegrableOn, μ.restrict_restrict_of_subset inter_subset_right] at this
lemma Integrable.piecewise [DecidablePred (· ∈ s)]
(hs : MeasurableSet s) (hf : IntegrableOn f s μ) (hg : IntegrableOn g sᶜ μ) :
Integrable (s.piecewise f g) μ := by
rw [IntegrableOn] at hf hg
rw [← memℒp_one_iff_integrable] at hf hg ⊢
exact Memℒp.piecewise hs hf hg
theorem IntegrableOn.left_of_union (h : IntegrableOn f (s ∪ t) μ) : IntegrableOn f s μ :=
h.mono_set subset_union_left
#align measure_theory.integrable_on.left_of_union MeasureTheory.IntegrableOn.left_of_union
theorem IntegrableOn.right_of_union (h : IntegrableOn f (s ∪ t) μ) : IntegrableOn f t μ :=
h.mono_set subset_union_right
#align measure_theory.integrable_on.right_of_union MeasureTheory.IntegrableOn.right_of_union
theorem IntegrableOn.union (hs : IntegrableOn f s μ) (ht : IntegrableOn f t μ) :
IntegrableOn f (s ∪ t) μ :=
(hs.add_measure ht).mono_measure <| Measure.restrict_union_le _ _
#align measure_theory.integrable_on.union MeasureTheory.IntegrableOn.union
@[simp]
theorem integrableOn_union : IntegrableOn f (s ∪ t) μ ↔ IntegrableOn f s μ ∧ IntegrableOn f t μ :=
⟨fun h => ⟨h.left_of_union, h.right_of_union⟩, fun h => h.1.union h.2⟩
#align measure_theory.integrable_on_union MeasureTheory.integrableOn_union
@[simp]
theorem integrableOn_singleton_iff {x : α} [MeasurableSingletonClass α] :
IntegrableOn f {x} μ ↔ f x = 0 ∨ μ {x} < ∞ := by
have : f =ᵐ[μ.restrict {x}] fun _ => f x := by
filter_upwards [ae_restrict_mem (measurableSet_singleton x)] with _ ha
simp only [mem_singleton_iff.1 ha]
rw [IntegrableOn, integrable_congr this, integrable_const_iff]
simp
#align measure_theory.integrable_on_singleton_iff MeasureTheory.integrableOn_singleton_iff
@[simp]
theorem integrableOn_finite_biUnion {s : Set β} (hs : s.Finite) {t : β → Set α} :
IntegrableOn f (⋃ i ∈ s, t i) μ ↔ ∀ i ∈ s, IntegrableOn f (t i) μ := by
refine hs.induction_on ?_ ?_
· simp
· intro a s _ _ hf; simp [hf, or_imp, forall_and]
#align measure_theory.integrable_on_finite_bUnion MeasureTheory.integrableOn_finite_biUnion
@[simp]
theorem integrableOn_finset_iUnion {s : Finset β} {t : β → Set α} :
IntegrableOn f (⋃ i ∈ s, t i) μ ↔ ∀ i ∈ s, IntegrableOn f (t i) μ :=
integrableOn_finite_biUnion s.finite_toSet
#align measure_theory.integrable_on_finset_Union MeasureTheory.integrableOn_finset_iUnion
@[simp]
| Mathlib/MeasureTheory/Integral/IntegrableOn.lean | 220 | 223 | theorem integrableOn_finite_iUnion [Finite β] {t : β → Set α} :
IntegrableOn f (⋃ i, t i) μ ↔ ∀ i, IntegrableOn f (t i) μ := by |
cases nonempty_fintype β
simpa using @integrableOn_finset_iUnion _ _ _ _ _ f μ Finset.univ t
|
/-
Copyright (c) 2019 Johan Commelin. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johan Commelin, Kenny Lau
-/
import Mathlib.Algebra.Polynomial.AlgebraMap
import Mathlib.Algebra.Polynomial.Basic
import Mathlib.RingTheory.Ideal.Maps
import Mathlib.RingTheory.MvPowerSeries.Basic
#align_import ring_theory.power_series.basic from "leanprover-community/mathlib"@"2d5739b61641ee4e7e53eca5688a08f66f2e6a60"
/-!
# Formal power series (in one variable)
This file defines (univariate) formal power series
and develops the basic properties of these objects.
A formal power series is to a polynomial like an infinite sum is to a finite sum.
Formal power series in one variable are defined from multivariate
power series as `PowerSeries R := MvPowerSeries Unit R`.
The file sets up the (semi)ring structure on univariate power series.
We provide the natural inclusion from polynomials to formal power series.
Additional results can be found in:
* `Mathlib.RingTheory.PowerSeries.Trunc`, truncation of power series;
* `Mathlib.RingTheory.PowerSeries.Inverse`, about inverses of power series,
and the fact that power series over a local ring form a local ring;
* `Mathlib.RingTheory.PowerSeries.Order`, the order of a power series at 0,
and application to the fact that power series over an integral domain
form an integral domain.
## Implementation notes
Because of its definition,
`PowerSeries R := MvPowerSeries Unit R`.
a lot of proofs and properties from the multivariate case
can be ported to the single variable case.
However, it means that formal power series are indexed by `Unit →₀ ℕ`,
which is of course canonically isomorphic to `ℕ`.
We then build some glue to treat formal power series as if they were indexed by `ℕ`.
Occasionally this leads to proofs that are uglier than expected.
-/
noncomputable section
open Finset (antidiagonal mem_antidiagonal)
/-- Formal power series over a coefficient type `R` -/
def PowerSeries (R : Type*) :=
MvPowerSeries Unit R
#align power_series PowerSeries
namespace PowerSeries
open Finsupp (single)
variable {R : Type*}
section
-- Porting note: not available in Lean 4
-- local reducible PowerSeries
/--
`R⟦X⟧` is notation for `PowerSeries R`,
the semiring of formal power series in one variable over a semiring `R`.
-/
scoped notation:9000 R "⟦X⟧" => PowerSeries R
instance [Inhabited R] : Inhabited R⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
instance [Zero R] : Zero R⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
instance [AddMonoid R] : AddMonoid R⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
instance [AddGroup R] : AddGroup R⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
instance [AddCommMonoid R] : AddCommMonoid R⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
instance [AddCommGroup R] : AddCommGroup R⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
instance [Semiring R] : Semiring R⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
instance [CommSemiring R] : CommSemiring R⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
instance [Ring R] : Ring R⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
instance [CommRing R] : CommRing R⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
instance [Nontrivial R] : Nontrivial R⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
instance {A} [Semiring R] [AddCommMonoid A] [Module R A] : Module R A⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
instance {A S} [Semiring R] [Semiring S] [AddCommMonoid A] [Module R A] [Module S A] [SMul R S]
[IsScalarTower R S A] : IsScalarTower R S A⟦X⟧ :=
Pi.isScalarTower
instance {A} [Semiring A] [CommSemiring R] [Algebra R A] : Algebra R A⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
end
section Semiring
variable (R) [Semiring R]
/-- The `n`th coefficient of a formal power series. -/
def coeff (n : ℕ) : R⟦X⟧ →ₗ[R] R :=
MvPowerSeries.coeff R (single () n)
#align power_series.coeff PowerSeries.coeff
/-- The `n`th monomial with coefficient `a` as formal power series. -/
def monomial (n : ℕ) : R →ₗ[R] R⟦X⟧ :=
MvPowerSeries.monomial R (single () n)
#align power_series.monomial PowerSeries.monomial
variable {R}
theorem coeff_def {s : Unit →₀ ℕ} {n : ℕ} (h : s () = n) : coeff R n = MvPowerSeries.coeff R s := by
erw [coeff, ← h, ← Finsupp.unique_single s]
#align power_series.coeff_def PowerSeries.coeff_def
/-- Two formal power series are equal if all their coefficients are equal. -/
@[ext]
theorem ext {φ ψ : R⟦X⟧} (h : ∀ n, coeff R n φ = coeff R n ψ) : φ = ψ :=
MvPowerSeries.ext fun n => by
rw [← coeff_def]
· apply h
rfl
#align power_series.ext PowerSeries.ext
/-- Two formal power series are equal if all their coefficients are equal. -/
theorem ext_iff {φ ψ : R⟦X⟧} : φ = ψ ↔ ∀ n, coeff R n φ = coeff R n ψ :=
⟨fun h n => congr_arg (coeff R n) h, ext⟩
#align power_series.ext_iff PowerSeries.ext_iff
instance [Subsingleton R] : Subsingleton R⟦X⟧ := by
simp only [subsingleton_iff, ext_iff]
exact fun _ _ _ ↦ (subsingleton_iff).mp (by infer_instance) _ _
/-- Constructor for formal power series. -/
def mk {R} (f : ℕ → R) : R⟦X⟧ := fun s => f (s ())
#align power_series.mk PowerSeries.mk
@[simp]
theorem coeff_mk (n : ℕ) (f : ℕ → R) : coeff R n (mk f) = f n :=
congr_arg f Finsupp.single_eq_same
#align power_series.coeff_mk PowerSeries.coeff_mk
theorem coeff_monomial (m n : ℕ) (a : R) : coeff R m (monomial R n a) = if m = n then a else 0 :=
calc
coeff R m (monomial R n a) = _ := MvPowerSeries.coeff_monomial _ _ _
_ = if m = n then a else 0 := by simp only [Finsupp.unique_single_eq_iff]
#align power_series.coeff_monomial PowerSeries.coeff_monomial
theorem monomial_eq_mk (n : ℕ) (a : R) : monomial R n a = mk fun m => if m = n then a else 0 :=
ext fun m => by rw [coeff_monomial, coeff_mk]
#align power_series.monomial_eq_mk PowerSeries.monomial_eq_mk
@[simp]
theorem coeff_monomial_same (n : ℕ) (a : R) : coeff R n (monomial R n a) = a :=
MvPowerSeries.coeff_monomial_same _ _
#align power_series.coeff_monomial_same PowerSeries.coeff_monomial_same
@[simp]
theorem coeff_comp_monomial (n : ℕ) : (coeff R n).comp (monomial R n) = LinearMap.id :=
LinearMap.ext <| coeff_monomial_same n
#align power_series.coeff_comp_monomial PowerSeries.coeff_comp_monomial
variable (R)
/-- The constant coefficient of a formal power series. -/
def constantCoeff : R⟦X⟧ →+* R :=
MvPowerSeries.constantCoeff Unit R
#align power_series.constant_coeff PowerSeries.constantCoeff
/-- The constant formal power series. -/
def C : R →+* R⟦X⟧ :=
MvPowerSeries.C Unit R
set_option linter.uppercaseLean3 false in
#align power_series.C PowerSeries.C
variable {R}
/-- The variable of the formal power series ring. -/
def X : R⟦X⟧ :=
MvPowerSeries.X ()
set_option linter.uppercaseLean3 false in
#align power_series.X PowerSeries.X
theorem commute_X (φ : R⟦X⟧) : Commute φ X :=
MvPowerSeries.commute_X _ _
set_option linter.uppercaseLean3 false in
#align power_series.commute_X PowerSeries.commute_X
@[simp]
theorem coeff_zero_eq_constantCoeff : ⇑(coeff R 0) = constantCoeff R := by
rw [coeff, Finsupp.single_zero]
rfl
#align power_series.coeff_zero_eq_constant_coeff PowerSeries.coeff_zero_eq_constantCoeff
theorem coeff_zero_eq_constantCoeff_apply (φ : R⟦X⟧) : coeff R 0 φ = constantCoeff R φ := by
rw [coeff_zero_eq_constantCoeff]
#align power_series.coeff_zero_eq_constant_coeff_apply PowerSeries.coeff_zero_eq_constantCoeff_apply
@[simp]
theorem monomial_zero_eq_C : ⇑(monomial R 0) = C R := by
-- This used to be `rw`, but we need `erw` after leanprover/lean4#2644
erw [monomial, Finsupp.single_zero, MvPowerSeries.monomial_zero_eq_C]
set_option linter.uppercaseLean3 false in
#align power_series.monomial_zero_eq_C PowerSeries.monomial_zero_eq_C
theorem monomial_zero_eq_C_apply (a : R) : monomial R 0 a = C R a := by simp
set_option linter.uppercaseLean3 false in
#align power_series.monomial_zero_eq_C_apply PowerSeries.monomial_zero_eq_C_apply
theorem coeff_C (n : ℕ) (a : R) : coeff R n (C R a : R⟦X⟧) = if n = 0 then a else 0 := by
rw [← monomial_zero_eq_C_apply, coeff_monomial]
set_option linter.uppercaseLean3 false in
#align power_series.coeff_C PowerSeries.coeff_C
@[simp]
theorem coeff_zero_C (a : R) : coeff R 0 (C R a) = a := by
rw [coeff_C, if_pos rfl]
set_option linter.uppercaseLean3 false in
#align power_series.coeff_zero_C PowerSeries.coeff_zero_C
theorem coeff_ne_zero_C {a : R} {n : ℕ} (h : n ≠ 0) : coeff R n (C R a) = 0 := by
rw [coeff_C, if_neg h]
@[simp]
theorem coeff_succ_C {a : R} {n : ℕ} : coeff R (n + 1) (C R a) = 0 :=
coeff_ne_zero_C n.succ_ne_zero
theorem C_injective : Function.Injective (C R) := by
intro a b H
have := (ext_iff (φ := C R a) (ψ := C R b)).mp H 0
rwa [coeff_zero_C, coeff_zero_C] at this
protected theorem subsingleton_iff : Subsingleton R⟦X⟧ ↔ Subsingleton R := by
refine ⟨fun h ↦ ?_, fun _ ↦ inferInstance⟩
rw [subsingleton_iff] at h ⊢
exact fun a b ↦ C_injective (h (C R a) (C R b))
theorem X_eq : (X : R⟦X⟧) = monomial R 1 1 :=
rfl
set_option linter.uppercaseLean3 false in
#align power_series.X_eq PowerSeries.X_eq
| Mathlib/RingTheory/PowerSeries/Basic.lean | 282 | 283 | theorem coeff_X (n : ℕ) : coeff R n (X : R⟦X⟧) = if n = 1 then 1 else 0 := by |
rw [X_eq, coeff_monomial]
|
/-
Copyright (c) 2024 Jeremy Tan. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jeremy Tan
-/
import Mathlib.Data.Int.Interval
import Mathlib.Data.Int.ModEq
import Mathlib.Data.Nat.Count
import Mathlib.Data.Rat.Floor
import Mathlib.Order.Interval.Finset.Nat
/-!
# Counting elements in an interval with given residue
The theorems in this file generalise `Nat.card_multiples` in `Mathlib.Data.Nat.Factorization.Basic`
to all integer intervals and any fixed residue (not just zero, which reduces to the multiples).
Theorems are given for `Ico` and `Ioc` intervals.
-/
open Finset Int
namespace Int
variable (a b : ℤ) {r : ℤ} (hr : 0 < r)
lemma Ico_filter_dvd_eq : (Ico a b).filter (r ∣ ·) =
(Ico ⌈a / (r : ℚ)⌉ ⌈b / (r : ℚ)⌉).map ⟨(· * r), mul_left_injective₀ hr.ne'⟩ := by
ext x
simp only [mem_map, mem_filter, mem_Ico, ceil_le, lt_ceil, div_le_iff, lt_div_iff,
dvd_iff_exists_eq_mul_left, cast_pos.2 hr, ← cast_mul, cast_lt, cast_le]
aesop
lemma Ioc_filter_dvd_eq : (Ioc a b).filter (r ∣ ·) =
(Ioc ⌊a / (r : ℚ)⌋ ⌊b / (r : ℚ)⌋).map ⟨(· * r), mul_left_injective₀ hr.ne'⟩ := by
ext x
simp only [mem_map, mem_filter, mem_Ioc, floor_lt, le_floor, div_lt_iff, le_div_iff,
dvd_iff_exists_eq_mul_left, cast_pos.2 hr, ← cast_mul, cast_lt, cast_le]
aesop
/-- There are `⌈b / r⌉ - ⌈a / r⌉` multiples of `r` in `[a, b)`, if `a ≤ b`. -/
theorem Ico_filter_dvd_card : ((Ico a b).filter (r ∣ ·)).card =
max (⌈b / (r : ℚ)⌉ - ⌈a / (r : ℚ)⌉) 0 := by
rw [Ico_filter_dvd_eq _ _ hr, card_map, card_Ico, toNat_eq_max]
/-- There are `⌊b / r⌋ - ⌊a / r⌋` multiples of `r` in `(a, b]`, if `a ≤ b`. -/
theorem Ioc_filter_dvd_card : ((Ioc a b).filter (r ∣ ·)).card =
max (⌊b / (r : ℚ)⌋ - ⌊a / (r : ℚ)⌋) 0 := by
rw [Ioc_filter_dvd_eq _ _ hr, card_map, card_Ioc, toNat_eq_max]
lemma Ico_filter_modEq_eq (v : ℤ) : (Ico a b).filter (· ≡ v [ZMOD r]) =
((Ico (a - v) (b - v)).filter (r ∣ ·)).map ⟨(· + v), add_left_injective v⟩ := by
ext x
simp_rw [mem_map, mem_filter, mem_Ico, Function.Embedding.coeFn_mk, ← eq_sub_iff_add_eq,
exists_eq_right, modEq_comm, modEq_iff_dvd, sub_lt_sub_iff_right, sub_le_sub_iff_right]
lemma Ioc_filter_modEq_eq (v : ℤ) : (Ioc a b).filter (· ≡ v [ZMOD r]) =
((Ioc (a - v) (b - v)).filter (r ∣ ·)).map ⟨(· + v), add_left_injective v⟩ := by
ext x
simp_rw [mem_map, mem_filter, mem_Ioc, Function.Embedding.coeFn_mk, ← eq_sub_iff_add_eq,
exists_eq_right, modEq_comm, modEq_iff_dvd, sub_lt_sub_iff_right, sub_le_sub_iff_right]
/-- There are `⌈(b - v) / r⌉ - ⌈(a - v) / r⌉` numbers congruent to `v` mod `r` in `[a, b)`,
if `a ≤ b`. -/
theorem Ico_filter_modEq_card (v : ℤ) : ((Ico a b).filter (· ≡ v [ZMOD r])).card =
max (⌈(b - v) / (r : ℚ)⌉ - ⌈(a - v) / (r : ℚ)⌉) 0 := by
simp [Ico_filter_modEq_eq, Ico_filter_dvd_eq, toNat_eq_max, hr]
/-- There are `⌊(b - v) / r⌋ - ⌊(a - v) / r⌋` numbers congruent to `v` mod `r` in `(a, b]`,
if `a ≤ b`. -/
| Mathlib/Data/Int/CardIntervalMod.lean | 71 | 73 | theorem Ioc_filter_modEq_card (v : ℤ) : ((Ioc a b).filter (· ≡ v [ZMOD r])).card =
max (⌊(b - v) / (r : ℚ)⌋ - ⌊(a - v) / (r : ℚ)⌋) 0 := by |
simp [Ioc_filter_modEq_eq, Ioc_filter_dvd_eq, toNat_eq_max, hr]
|
/-
Copyright (c) 2022 Andrew Yang. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Andrew Yang
-/
import Mathlib.LinearAlgebra.Matrix.Charpoly.Coeff
import Mathlib.LinearAlgebra.Matrix.ToLin
#align_import linear_algebra.matrix.charpoly.linear_map from "leanprover-community/mathlib"@"62c0a4ef1441edb463095ea02a06e87f3dfe135c"
/-!
# Cayley-Hamilton theorem for f.g. modules.
Given a fixed finite spanning set `b : ι → M` of an `R`-module `M`, we say that a matrix `M`
represents an endomorphism `f : M →ₗ[R] M` if the matrix as an endomorphism of `ι → R` commutes
with `f` via the projection `(ι → R) →ₗ[R] M` given by `b`.
We show that every endomorphism has a matrix representation, and if `f.range ≤ I • ⊤` for some
ideal `I`, we may furthermore obtain a matrix representation whose entries fall in `I`.
This is used to conclude the Cayley-Hamilton theorem for f.g. modules over arbitrary rings.
-/
variable {ι : Type*} [Fintype ι]
variable {M : Type*} [AddCommGroup M] (R : Type*) [CommRing R] [Module R M] (I : Ideal R)
variable (b : ι → M) (hb : Submodule.span R (Set.range b) = ⊤)
open Polynomial Matrix
/-- The composition of a matrix (as an endomorphism of `ι → R`) with the projection
`(ι → R) →ₗ[R] M`. -/
def PiToModule.fromMatrix [DecidableEq ι] : Matrix ι ι R →ₗ[R] (ι → R) →ₗ[R] M :=
(LinearMap.llcomp R _ _ _ (Fintype.total R R b)).comp algEquivMatrix'.symm.toLinearMap
#align pi_to_module.from_matrix PiToModule.fromMatrix
theorem PiToModule.fromMatrix_apply [DecidableEq ι] (A : Matrix ι ι R) (w : ι → R) :
PiToModule.fromMatrix R b A w = Fintype.total R R b (A *ᵥ w) :=
rfl
#align pi_to_module.from_matrix_apply PiToModule.fromMatrix_apply
theorem PiToModule.fromMatrix_apply_single_one [DecidableEq ι] (A : Matrix ι ι R) (j : ι) :
PiToModule.fromMatrix R b A (Pi.single j 1) = ∑ i : ι, A i j • b i := by
rw [PiToModule.fromMatrix_apply, Fintype.total_apply, Matrix.mulVec_single]
simp_rw [mul_one]
#align pi_to_module.from_matrix_apply_single_one PiToModule.fromMatrix_apply_single_one
/-- The endomorphisms of `M` acts on `(ι → R) →ₗ[R] M`, and takes the projection
to a `(ι → R) →ₗ[R] M`. -/
def PiToModule.fromEnd : Module.End R M →ₗ[R] (ι → R) →ₗ[R] M :=
LinearMap.lcomp _ _ (Fintype.total R R b)
#align pi_to_module.from_End PiToModule.fromEnd
theorem PiToModule.fromEnd_apply (f : Module.End R M) (w : ι → R) :
PiToModule.fromEnd R b f w = f (Fintype.total R R b w) :=
rfl
#align pi_to_module.from_End_apply PiToModule.fromEnd_apply
theorem PiToModule.fromEnd_apply_single_one [DecidableEq ι] (f : Module.End R M) (i : ι) :
PiToModule.fromEnd R b f (Pi.single i 1) = f (b i) := by
rw [PiToModule.fromEnd_apply]
congr
convert Fintype.total_apply_single (S := R) R b i (1 : R)
rw [one_smul]
#align pi_to_module.from_End_apply_single_one PiToModule.fromEnd_apply_single_one
theorem PiToModule.fromEnd_injective (hb : Submodule.span R (Set.range b) = ⊤) :
Function.Injective (PiToModule.fromEnd R b) := by
intro x y e
ext m
obtain ⟨m, rfl⟩ : m ∈ LinearMap.range (Fintype.total R R b) := by
rw [(Fintype.range_total R b).trans hb]
exact Submodule.mem_top
exact (LinearMap.congr_fun e m : _)
#align pi_to_module.from_End_injective PiToModule.fromEnd_injective
section
variable {R} [DecidableEq ι]
/-- We say that a matrix represents an endomorphism of `M` if the matrix acting on `ι → R` is
equal to `f` via the projection `(ι → R) →ₗ[R] M` given by a fixed (spanning) set. -/
def Matrix.Represents (A : Matrix ι ι R) (f : Module.End R M) : Prop :=
PiToModule.fromMatrix R b A = PiToModule.fromEnd R b f
#align matrix.represents Matrix.Represents
variable {b}
theorem Matrix.Represents.congr_fun {A : Matrix ι ι R} {f : Module.End R M} (h : A.Represents b f)
(x) : Fintype.total R R b (A *ᵥ x) = f (Fintype.total R R b x) :=
LinearMap.congr_fun h x
#align matrix.represents.congr_fun Matrix.Represents.congr_fun
theorem Matrix.represents_iff {A : Matrix ι ι R} {f : Module.End R M} :
A.Represents b f ↔ ∀ x, Fintype.total R R b (A *ᵥ x) = f (Fintype.total R R b x) :=
⟨fun e x => e.congr_fun x, fun H => LinearMap.ext fun x => H x⟩
#align matrix.represents_iff Matrix.represents_iff
theorem Matrix.represents_iff' {A : Matrix ι ι R} {f : Module.End R M} :
A.Represents b f ↔ ∀ j, ∑ i : ι, A i j • b i = f (b j) := by
constructor
· intro h i
have := LinearMap.congr_fun h (Pi.single i 1)
rwa [PiToModule.fromEnd_apply_single_one, PiToModule.fromMatrix_apply_single_one] at this
· intro h
-- Porting note: was `ext`
refine LinearMap.pi_ext' (fun i => LinearMap.ext_ring ?_)
simp_rw [LinearMap.comp_apply, LinearMap.coe_single, PiToModule.fromEnd_apply_single_one,
PiToModule.fromMatrix_apply_single_one]
apply h
#align matrix.represents_iff' Matrix.represents_iff'
theorem Matrix.Represents.mul {A A' : Matrix ι ι R} {f f' : Module.End R M} (h : A.Represents b f)
(h' : Matrix.Represents b A' f') : (A * A').Represents b (f * f') := by
delta Matrix.Represents PiToModule.fromMatrix
rw [LinearMap.comp_apply, AlgEquiv.toLinearMap_apply, _root_.map_mul]
ext
dsimp [PiToModule.fromEnd]
rw [← h'.congr_fun, ← h.congr_fun]
rfl
#align matrix.represents.mul Matrix.Represents.mul
| Mathlib/LinearAlgebra/Matrix/Charpoly/LinearMap.lean | 124 | 128 | theorem Matrix.Represents.one : (1 : Matrix ι ι R).Represents b 1 := by |
delta Matrix.Represents PiToModule.fromMatrix
rw [LinearMap.comp_apply, AlgEquiv.toLinearMap_apply, _root_.map_one]
ext
rfl
|
/-
Copyright (c) 2020 Anne Baanen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anne Baanen
-/
import Mathlib.LinearAlgebra.Matrix.BilinearForm
import Mathlib.LinearAlgebra.Matrix.Charpoly.Minpoly
import Mathlib.LinearAlgebra.Determinant
import Mathlib.LinearAlgebra.FiniteDimensional
import Mathlib.LinearAlgebra.Vandermonde
import Mathlib.LinearAlgebra.Trace
import Mathlib.FieldTheory.IsAlgClosed.AlgebraicClosure
import Mathlib.FieldTheory.PrimitiveElement
import Mathlib.FieldTheory.Galois
import Mathlib.RingTheory.PowerBasis
import Mathlib.FieldTheory.Minpoly.MinpolyDiv
#align_import ring_theory.trace from "leanprover-community/mathlib"@"3e068ece210655b7b9a9477c3aff38a492400aa1"
/-!
# Trace for (finite) ring extensions.
Suppose we have an `R`-algebra `S` with a finite basis. For each `s : S`,
the trace of the linear map given by multiplying by `s` gives information about
the roots of the minimal polynomial of `s` over `R`.
## Main definitions
* `Algebra.trace R S x`: the trace of an element `s` of an `R`-algebra `S`
* `Algebra.traceForm R S`: bilinear form sending `x`, `y` to the trace of `x * y`
* `Algebra.traceMatrix R b`: the matrix whose `(i j)`-th element is the trace of `b i * b j`.
* `Algebra.embeddingsMatrix A C b : Matrix κ (B →ₐ[A] C) C` is the matrix whose
`(i, σ)` coefficient is `σ (b i)`.
* `Algebra.embeddingsMatrixReindex A C b e : Matrix κ κ C` is the matrix whose `(i, j)`
coefficient is `σⱼ (b i)`, where `σⱼ : B →ₐ[A] C` is the embedding corresponding to `j : κ`
given by a bijection `e : κ ≃ (B →ₐ[A] C)`.
## Main results
* `trace_algebraMap_of_basis`, `trace_algebraMap`: if `x : K`, then `Tr_{L/K} x = [L : K] x`
* `trace_trace_of_basis`, `trace_trace`: `Tr_{L/K} (Tr_{F/L} x) = Tr_{F/K} x`
* `trace_eq_sum_roots`: the trace of `x : K(x)` is the sum of all conjugate roots of `x`
* `trace_eq_sum_embeddings`: the trace of `x : K(x)` is the sum of all embeddings of `x` into an
algebraically closed field
* `traceForm_nondegenerate`: the trace form over a separable extension is a nondegenerate
bilinear form
* `traceForm_dualBasis_powerBasis_eq`: The dual basis of a powerbasis `{1, x, x²...}` under the
trace form is `aᵢ / f'(x)`, with `f` being the minpoly of `x` and `f / (X - x) = ∑ aᵢxⁱ`.
## Implementation notes
Typically, the trace is defined specifically for finite field extensions.
The definition is as general as possible and the assumption that we have
fields or that the extension is finite is added to the lemmas as needed.
We only define the trace for left multiplication (`Algebra.leftMulMatrix`,
i.e. `LinearMap.mulLeft`).
For now, the definitions assume `S` is commutative, so the choice doesn't matter anyway.
## References
* https://en.wikipedia.org/wiki/Field_trace
-/
universe u v w z
variable {R S T : Type*} [CommRing R] [CommRing S] [CommRing T]
variable [Algebra R S] [Algebra R T]
variable {K L : Type*} [Field K] [Field L] [Algebra K L]
variable {ι κ : Type w} [Fintype ι]
open FiniteDimensional
open LinearMap (BilinForm)
open LinearMap
open Matrix
open scoped Matrix
namespace Algebra
variable (b : Basis ι R S)
variable (R S)
/-- The trace of an element `s` of an `R`-algebra is the trace of `(s * ·)`,
as an `R`-linear map. -/
noncomputable def trace : S →ₗ[R] R :=
(LinearMap.trace R S).comp (lmul R S).toLinearMap
#align algebra.trace Algebra.trace
variable {S}
-- Not a `simp` lemma since there are more interesting ways to rewrite `trace R S x`,
-- for example `trace_trace`
theorem trace_apply (x) : trace R S x = LinearMap.trace R S (lmul R S x) :=
rfl
#align algebra.trace_apply Algebra.trace_apply
theorem trace_eq_zero_of_not_exists_basis (h : ¬∃ s : Finset S, Nonempty (Basis s R S)) :
trace R S = 0 := by ext s; simp [trace_apply, LinearMap.trace, h]
#align algebra.trace_eq_zero_of_not_exists_basis Algebra.trace_eq_zero_of_not_exists_basis
variable {R}
-- Can't be a `simp` lemma because it depends on a choice of basis
theorem trace_eq_matrix_trace [DecidableEq ι] (b : Basis ι R S) (s : S) :
trace R S s = Matrix.trace (Algebra.leftMulMatrix b s) := by
rw [trace_apply, LinearMap.trace_eq_matrix_trace _ b, ← toMatrix_lmul_eq]; rfl
#align algebra.trace_eq_matrix_trace Algebra.trace_eq_matrix_trace
/-- If `x` is in the base field `K`, then the trace is `[L : K] * x`. -/
theorem trace_algebraMap_of_basis (x : R) : trace R S (algebraMap R S x) = Fintype.card ι • x := by
haveI := Classical.decEq ι
rw [trace_apply, LinearMap.trace_eq_matrix_trace R b, Matrix.trace]
convert Finset.sum_const x
simp [-coe_lmul_eq_mul]
#align algebra.trace_algebra_map_of_basis Algebra.trace_algebraMap_of_basis
/-- If `x` is in the base field `K`, then the trace is `[L : K] * x`.
(If `L` is not finite-dimensional over `K`, then `trace` and `finrank` return `0`.)
-/
@[simp]
theorem trace_algebraMap (x : K) : trace K L (algebraMap K L x) = finrank K L • x := by
by_cases H : ∃ s : Finset L, Nonempty (Basis s K L)
· rw [trace_algebraMap_of_basis H.choose_spec.some, finrank_eq_card_basis H.choose_spec.some]
· simp [trace_eq_zero_of_not_exists_basis K H, finrank_eq_zero_of_not_exists_basis_finset H]
#align algebra.trace_algebra_map Algebra.trace_algebraMap
theorem trace_trace_of_basis [Algebra S T] [IsScalarTower R S T] {ι κ : Type*} [Finite ι]
[Finite κ] (b : Basis ι R S) (c : Basis κ S T) (x : T) :
trace R S (trace S T x) = trace R T x := by
haveI := Classical.decEq ι
haveI := Classical.decEq κ
cases nonempty_fintype ι
cases nonempty_fintype κ
rw [trace_eq_matrix_trace (b.smul c), trace_eq_matrix_trace b, trace_eq_matrix_trace c,
Matrix.trace, Matrix.trace, Matrix.trace, ← Finset.univ_product_univ, Finset.sum_product]
refine Finset.sum_congr rfl fun i _ ↦ ?_
simp only [AlgHom.map_sum, smul_leftMulMatrix, Finset.sum_apply,
Matrix.diag, Finset.sum_apply
i (Finset.univ : Finset κ) fun y => leftMulMatrix b (leftMulMatrix c x y y)]
#align algebra.trace_trace_of_basis Algebra.trace_trace_of_basis
theorem trace_comp_trace_of_basis [Algebra S T] [IsScalarTower R S T] {ι κ : Type*} [Finite ι]
[Finite κ] (b : Basis ι R S) (c : Basis κ S T) :
(trace R S).comp ((trace S T).restrictScalars R) = trace R T := by
ext
rw [LinearMap.comp_apply, LinearMap.restrictScalars_apply, trace_trace_of_basis b c]
#align algebra.trace_comp_trace_of_basis Algebra.trace_comp_trace_of_basis
@[simp]
theorem trace_trace [Algebra K T] [Algebra L T] [IsScalarTower K L T] [FiniteDimensional K L]
[FiniteDimensional L T] (x : T) : trace K L (trace L T x) = trace K T x :=
trace_trace_of_basis (Basis.ofVectorSpace K L) (Basis.ofVectorSpace L T) x
#align algebra.trace_trace Algebra.trace_trace
@[simp]
theorem trace_comp_trace [Algebra K T] [Algebra L T] [IsScalarTower K L T] [FiniteDimensional K L]
[FiniteDimensional L T] : (trace K L).comp ((trace L T).restrictScalars K) = trace K T := by
ext; rw [LinearMap.comp_apply, LinearMap.restrictScalars_apply, trace_trace]
#align algebra.trace_comp_trace Algebra.trace_comp_trace
@[simp]
theorem trace_prod_apply [Module.Free R S] [Module.Free R T] [Module.Finite R S] [Module.Finite R T]
(x : S × T) : trace R (S × T) x = trace R S x.fst + trace R T x.snd := by
nontriviality R
let f := (lmul R S).toLinearMap.prodMap (lmul R T).toLinearMap
have : (lmul R (S × T)).toLinearMap = (prodMapLinear R S T S T R).comp f :=
LinearMap.ext₂ Prod.mul_def
simp_rw [trace, this]
exact trace_prodMap' _ _
#align algebra.trace_prod_apply Algebra.trace_prod_apply
theorem trace_prod [Module.Free R S] [Module.Free R T] [Module.Finite R S] [Module.Finite R T] :
trace R (S × T) = (trace R S).coprod (trace R T) :=
LinearMap.ext fun p => by rw [coprod_apply, trace_prod_apply]
#align algebra.trace_prod Algebra.trace_prod
section TraceForm
variable (R S)
/-- The `traceForm` maps `x y : S` to the trace of `x * y`.
It is a symmetric bilinear form and is nondegenerate if the extension is separable. -/
noncomputable def traceForm : BilinForm R S :=
LinearMap.compr₂ (lmul R S).toLinearMap (trace R S)
#align algebra.trace_form Algebra.traceForm
variable {S}
-- This is a nicer lemma than the one produced by `@[simps] def traceForm`.
@[simp]
theorem traceForm_apply (x y : S) : traceForm R S x y = trace R S (x * y) :=
rfl
#align algebra.trace_form_apply Algebra.traceForm_apply
theorem traceForm_isSymm : (traceForm R S).IsSymm := fun _ _ => congr_arg (trace R S) (mul_comm _ _)
#align algebra.trace_form_is_symm Algebra.traceForm_isSymm
theorem traceForm_toMatrix [DecidableEq ι] (i j) :
BilinForm.toMatrix b (traceForm R S) i j = trace R S (b i * b j) := by
rw [BilinForm.toMatrix_apply, traceForm_apply]
#align algebra.trace_form_to_matrix Algebra.traceForm_toMatrix
theorem traceForm_toMatrix_powerBasis (h : PowerBasis R S) :
BilinForm.toMatrix h.basis (traceForm R S) = of fun i j => trace R S (h.gen ^ (i.1 + j.1)) := by
ext; rw [traceForm_toMatrix, of_apply, pow_add, h.basis_eq_pow, h.basis_eq_pow]
#align algebra.trace_form_to_matrix_power_basis Algebra.traceForm_toMatrix_powerBasis
end TraceForm
end Algebra
section EqSumRoots
open Algebra Polynomial
variable {F : Type*} [Field F]
variable [Algebra K S] [Algebra K F]
/-- Given `pb : PowerBasis K S`, the trace of `pb.gen` is `-(minpoly K pb.gen).nextCoeff`. -/
theorem PowerBasis.trace_gen_eq_nextCoeff_minpoly [Nontrivial S] (pb : PowerBasis K S) :
Algebra.trace K S pb.gen = -(minpoly K pb.gen).nextCoeff := by
have d_pos : 0 < pb.dim := PowerBasis.dim_pos pb
have d_pos' : 0 < (minpoly K pb.gen).natDegree := by simpa
haveI : Nonempty (Fin pb.dim) := ⟨⟨0, d_pos⟩⟩
rw [trace_eq_matrix_trace pb.basis, trace_eq_neg_charpoly_coeff, charpoly_leftMulMatrix, ←
pb.natDegree_minpoly, Fintype.card_fin, ← nextCoeff_of_natDegree_pos d_pos']
#align power_basis.trace_gen_eq_next_coeff_minpoly PowerBasis.trace_gen_eq_nextCoeff_minpoly
/-- Given `pb : PowerBasis K S`, then the trace of `pb.gen` is
`((minpoly K pb.gen).aroots F).sum`. -/
theorem PowerBasis.trace_gen_eq_sum_roots [Nontrivial S] (pb : PowerBasis K S)
(hf : (minpoly K pb.gen).Splits (algebraMap K F)) :
algebraMap K F (trace K S pb.gen) = ((minpoly K pb.gen).aroots F).sum := by
rw [PowerBasis.trace_gen_eq_nextCoeff_minpoly, RingHom.map_neg, ←
nextCoeff_map (algebraMap K F).injective,
sum_roots_eq_nextCoeff_of_monic_of_split ((minpoly.monic (PowerBasis.isIntegral_gen _)).map _)
((splits_id_iff_splits _).2 hf),
neg_neg]
#align power_basis.trace_gen_eq_sum_roots PowerBasis.trace_gen_eq_sum_roots
namespace IntermediateField.AdjoinSimple
open IntermediateField
theorem trace_gen_eq_zero {x : L} (hx : ¬IsIntegral K x) :
Algebra.trace K K⟮x⟯ (AdjoinSimple.gen K x) = 0 := by
rw [trace_eq_zero_of_not_exists_basis, LinearMap.zero_apply]
contrapose! hx
obtain ⟨s, ⟨b⟩⟩ := hx
refine .of_mem_of_fg K⟮x⟯.toSubalgebra ?_ x ?_
· exact (Submodule.fg_iff_finiteDimensional _).mpr (FiniteDimensional.of_fintype_basis b)
· exact subset_adjoin K _ (Set.mem_singleton x)
#align intermediate_field.adjoin_simple.trace_gen_eq_zero IntermediateField.AdjoinSimple.trace_gen_eq_zero
theorem trace_gen_eq_sum_roots (x : L) (hf : (minpoly K x).Splits (algebraMap K F)) :
algebraMap K F (trace K K⟮x⟯ (AdjoinSimple.gen K x)) =
((minpoly K x).aroots F).sum := by
have injKxL := (algebraMap K⟮x⟯ L).injective
by_cases hx : IsIntegral K x; swap
· simp [minpoly.eq_zero hx, trace_gen_eq_zero hx, aroots_def]
rw [← adjoin.powerBasis_gen hx, (adjoin.powerBasis hx).trace_gen_eq_sum_roots] <;>
rw [adjoin.powerBasis_gen hx, ← minpoly.algebraMap_eq injKxL] <;>
try simp only [AdjoinSimple.algebraMap_gen _ _]
exact hf
#align intermediate_field.adjoin_simple.trace_gen_eq_sum_roots IntermediateField.AdjoinSimple.trace_gen_eq_sum_roots
end IntermediateField.AdjoinSimple
open IntermediateField
variable (K)
theorem trace_eq_trace_adjoin [FiniteDimensional K L] (x : L) :
Algebra.trace K L x = finrank K⟮x⟯ L • trace K K⟮x⟯ (AdjoinSimple.gen K x) := by
-- Porting note: `conv` was
-- `conv in x => rw [← IntermediateField.AdjoinSimple.algebraMap_gen K x]`
-- and it was after the first `rw`.
conv =>
lhs
rw [← IntermediateField.AdjoinSimple.algebraMap_gen K x]
rw [← trace_trace (L := K⟮x⟯), trace_algebraMap, LinearMap.map_smul_of_tower]
#align trace_eq_trace_adjoin trace_eq_trace_adjoin
variable {K}
theorem trace_eq_sum_roots [FiniteDimensional K L] {x : L}
(hF : (minpoly K x).Splits (algebraMap K F)) :
algebraMap K F (Algebra.trace K L x) =
finrank K⟮x⟯ L • ((minpoly K x).aroots F).sum := by
rw [trace_eq_trace_adjoin K x, Algebra.smul_def, RingHom.map_mul, ← Algebra.smul_def,
IntermediateField.AdjoinSimple.trace_gen_eq_sum_roots _ hF, IsScalarTower.algebraMap_smul]
#align trace_eq_sum_roots trace_eq_sum_roots
end EqSumRoots
variable {F : Type*} [Field F]
variable [Algebra R L] [Algebra L F] [Algebra R F] [IsScalarTower R L F]
open Polynomial
attribute [-instance] Field.toEuclideanDomain
theorem Algebra.isIntegral_trace [FiniteDimensional L F] {x : F} (hx : IsIntegral R x) :
IsIntegral R (Algebra.trace L F x) := by
have hx' : IsIntegral L x := hx.tower_top
rw [← isIntegral_algebraMap_iff (algebraMap L (AlgebraicClosure F)).injective, trace_eq_sum_roots]
· refine (IsIntegral.multiset_sum ?_).nsmul _
intro y hy
rw [mem_roots_map (minpoly.ne_zero hx')] at hy
use minpoly R x, minpoly.monic hx
rw [← aeval_def] at hy ⊢
exact minpoly.aeval_of_isScalarTower R x y hy
· apply IsAlgClosed.splits_codomain
#align algebra.is_integral_trace Algebra.isIntegral_trace
lemma Algebra.trace_eq_of_algEquiv {A B C : Type*} [CommRing A] [CommRing B] [CommRing C]
[Algebra A B] [Algebra A C] (e : B ≃ₐ[A] C) (x) :
Algebra.trace A C (e x) = Algebra.trace A B x := by
simp_rw [Algebra.trace_apply, ← LinearMap.trace_conj' _ e.toLinearEquiv]
congr; ext; simp [LinearEquiv.conj_apply]
lemma Algebra.trace_eq_of_ringEquiv {A B C : Type*} [CommRing A] [CommRing B] [CommRing C]
[Algebra A C] [Algebra B C] (e : A ≃+* B) (he : (algebraMap B C).comp e = algebraMap A C) (x) :
e (Algebra.trace A C x) = Algebra.trace B C x := by
classical
by_cases h : ∃ s : Finset C, Nonempty (Basis s B C)
· obtain ⟨s, ⟨b⟩⟩ := h
letI : Algebra A B := RingHom.toAlgebra e
letI : IsScalarTower A B C := IsScalarTower.of_algebraMap_eq' he.symm
rw [Algebra.trace_eq_matrix_trace b,
Algebra.trace_eq_matrix_trace (b.mapCoeffs e.symm (by simp [Algebra.smul_def, ← he]))]
show e.toAddMonoidHom _ = _
rw [AddMonoidHom.map_trace]
congr
ext i j
simp [leftMulMatrix_apply, LinearMap.toMatrix_apply]
rw [trace_eq_zero_of_not_exists_basis _ h, trace_eq_zero_of_not_exists_basis,
LinearMap.zero_apply, LinearMap.zero_apply, map_zero]
intro ⟨s, ⟨b⟩⟩
exact h ⟨s, ⟨b.mapCoeffs e (by simp [Algebra.smul_def, ← he])⟩⟩
lemma Algebra.trace_eq_of_equiv_equiv {A₁ B₁ A₂ B₂ : Type*} [CommRing A₁] [CommRing B₁]
[CommRing A₂] [CommRing B₂] [Algebra A₁ B₁] [Algebra A₂ B₂] (e₁ : A₁ ≃+* A₂) (e₂ : B₁ ≃+* B₂)
(he : RingHom.comp (algebraMap A₂ B₂) ↑e₁ = RingHom.comp ↑e₂ (algebraMap A₁ B₁)) (x) :
Algebra.trace A₁ B₁ x = e₁.symm (Algebra.trace A₂ B₂ (e₂ x)) := by
letI := (RingHom.comp (e₂ : B₁ →+* B₂) (algebraMap A₁ B₁)).toAlgebra
let e' : B₁ ≃ₐ[A₁] B₂ := { e₂ with commutes' := fun _ ↦ rfl }
rw [← Algebra.trace_eq_of_ringEquiv e₁ he, ← Algebra.trace_eq_of_algEquiv e',
RingEquiv.symm_apply_apply]
rfl
section EqSumEmbeddings
variable [Algebra K F] [IsScalarTower K L F]
open Algebra IntermediateField
variable (F) (E : Type*) [Field E] [Algebra K E]
theorem trace_eq_sum_embeddings_gen (pb : PowerBasis K L)
(hE : (minpoly K pb.gen).Splits (algebraMap K E)) (hfx : (minpoly K pb.gen).Separable) :
algebraMap K E (Algebra.trace K L pb.gen) =
(@Finset.univ _ (PowerBasis.AlgHom.fintype pb)).sum fun σ => σ pb.gen := by
letI := Classical.decEq E
-- Porting note: the following `letI` was not needed.
letI : Fintype (L →ₐ[K] E) := PowerBasis.AlgHom.fintype pb
rw [pb.trace_gen_eq_sum_roots hE, Fintype.sum_equiv pb.liftEquiv', Finset.sum_mem_multiset,
Finset.sum_eq_multiset_sum, Multiset.toFinset_val, Multiset.dedup_eq_self.mpr _,
Multiset.map_id]
· exact nodup_roots ((separable_map _).mpr hfx)
-- Porting note: the following goal does not exist in mathlib3.
· exact (fun x => x.1)
· intro x; rfl
· intro σ
rw [PowerBasis.liftEquiv'_apply_coe]
#align trace_eq_sum_embeddings_gen trace_eq_sum_embeddings_gen
variable [IsAlgClosed E]
theorem sum_embeddings_eq_finrank_mul [FiniteDimensional K F] [IsSeparable K F]
(pb : PowerBasis K L) :
∑ σ : F →ₐ[K] E, σ (algebraMap L F pb.gen) =
finrank L F •
(@Finset.univ _ (PowerBasis.AlgHom.fintype pb)).sum fun σ : L →ₐ[K] E => σ pb.gen := by
haveI : FiniteDimensional L F := FiniteDimensional.right K L F
haveI : IsSeparable L F := isSeparable_tower_top_of_isSeparable K L F
letI : Fintype (L →ₐ[K] E) := PowerBasis.AlgHom.fintype pb
letI : ∀ f : L →ₐ[K] E, Fintype (haveI := f.toRingHom.toAlgebra; AlgHom L F E) := ?_
· rw [Fintype.sum_equiv algHomEquivSigma (fun σ : F →ₐ[K] E => _) fun σ => σ.1 pb.gen, ←
Finset.univ_sigma_univ, Finset.sum_sigma, ← Finset.sum_nsmul]
· refine Finset.sum_congr rfl fun σ _ => ?_
letI : Algebra L E := σ.toRingHom.toAlgebra
-- Porting note: `Finset.card_univ` was inside `simp only`.
simp only [Finset.sum_const]
congr
rw [← AlgHom.card L F E]
exact Finset.card_univ (α := F →ₐ[L] E)
· intro σ
simp only [algHomEquivSigma, Equiv.coe_fn_mk, AlgHom.restrictDomain, AlgHom.comp_apply,
IsScalarTower.coe_toAlgHom']
#align sum_embeddings_eq_finrank_mul sum_embeddings_eq_finrank_mul
theorem trace_eq_sum_embeddings [FiniteDimensional K L] [IsSeparable K L] {x : L} :
algebraMap K E (Algebra.trace K L x) = ∑ σ : L →ₐ[K] E, σ x := by
have hx := IsSeparable.isIntegral K x
let pb := adjoin.powerBasis hx
rw [trace_eq_trace_adjoin K x, Algebra.smul_def, RingHom.map_mul, ← adjoin.powerBasis_gen hx,
trace_eq_sum_embeddings_gen E pb (IsAlgClosed.splits_codomain _)]
-- Porting note: the following `convert` was `exact`, with `← algebra.smul_def, algebra_map_smul`
-- in the previous `rw`.
· convert (sum_embeddings_eq_finrank_mul L E pb).symm
ext
simp
· haveI := isSeparable_tower_bot_of_isSeparable K K⟮x⟯ L
exact IsSeparable.separable K _
#align trace_eq_sum_embeddings trace_eq_sum_embeddings
theorem trace_eq_sum_automorphisms (x : L) [FiniteDimensional K L] [IsGalois K L] :
algebraMap K L (Algebra.trace K L x) = ∑ σ : L ≃ₐ[K] L, σ x := by
apply NoZeroSMulDivisors.algebraMap_injective L (AlgebraicClosure L)
rw [_root_.map_sum (algebraMap L (AlgebraicClosure L))]
rw [← Fintype.sum_equiv (Normal.algHomEquivAut K (AlgebraicClosure L) L)]
· rw [← trace_eq_sum_embeddings (AlgebraicClosure L)]
· simp only [algebraMap_eq_smul_one]
-- Porting note: `smul_one_smul` was in the `simp only`.
apply smul_one_smul
· intro σ
simp only [Normal.algHomEquivAut, AlgHom.restrictNormal', Equiv.coe_fn_mk,
AlgEquiv.coe_ofBijective, AlgHom.restrictNormal_commutes, id.map_eq_id, RingHom.id_apply]
#align trace_eq_sum_automorphisms trace_eq_sum_automorphisms
end EqSumEmbeddings
section DetNeZero
namespace Algebra
variable (A : Type u) {B : Type v} (C : Type z)
variable [CommRing A] [CommRing B] [Algebra A B] [CommRing C] [Algebra A C]
open Finset
/-- Given an `A`-algebra `B` and `b`, a `κ`-indexed family of elements of `B`, we define
`traceMatrix A b` as the matrix whose `(i j)`-th element is the trace of `b i * b j`. -/
noncomputable def traceMatrix (b : κ → B) : Matrix κ κ A :=
of fun i j => traceForm A B (b i) (b j)
#align algebra.trace_matrix Algebra.traceMatrix
-- TODO: set as an equation lemma for `traceMatrix`, see mathlib4#3024
@[simp]
theorem traceMatrix_apply (b : κ → B) (i j) : traceMatrix A b i j = traceForm A B (b i) (b j) :=
rfl
#align algebra.trace_matrix_apply Algebra.traceMatrix_apply
theorem traceMatrix_reindex {κ' : Type*} (b : Basis κ A B) (f : κ ≃ κ') :
traceMatrix A (b.reindex f) = reindex f f (traceMatrix A b) := by ext (x y); simp
#align algebra.trace_matrix_reindex Algebra.traceMatrix_reindex
variable {A}
theorem traceMatrix_of_matrix_vecMul [Fintype κ] (b : κ → B) (P : Matrix κ κ A) :
traceMatrix A (b ᵥ* P.map (algebraMap A B)) = Pᵀ * traceMatrix A b * P := by
ext (α β)
rw [traceMatrix_apply, vecMul, dotProduct, vecMul, dotProduct, Matrix.mul_apply,
BilinForm.sum_left,
Fintype.sum_congr _ _ fun i : κ =>
BilinForm.sum_right _ _ (b i * P.map (algebraMap A B) i α) fun y : κ =>
b y * P.map (algebraMap A B) y β,
sum_comm]
congr; ext x
rw [Matrix.mul_apply, sum_mul]
congr; ext y
rw [map_apply, traceForm_apply, mul_comm (b y), ← smul_def]
simp only [id.smul_eq_mul, RingHom.id_apply, map_apply, transpose_apply, LinearMap.map_smulₛₗ,
traceForm_apply, Algebra.smul_mul_assoc]
rw [mul_comm (b x), ← smul_def]
ring_nf
rw [mul_assoc]
simp [mul_comm]
#align algebra.trace_matrix_of_matrix_vec_mul Algebra.traceMatrix_of_matrix_vecMul
theorem traceMatrix_of_matrix_mulVec [Fintype κ] (b : κ → B) (P : Matrix κ κ A) :
traceMatrix A (P.map (algebraMap A B) *ᵥ b) = P * traceMatrix A b * Pᵀ := by
refine AddEquiv.injective (transposeAddEquiv κ κ A) ?_
rw [transposeAddEquiv_apply, transposeAddEquiv_apply, ← vecMul_transpose, ← transpose_map,
traceMatrix_of_matrix_vecMul, transpose_transpose]
#align algebra.trace_matrix_of_matrix_mul_vec Algebra.traceMatrix_of_matrix_mulVec
theorem traceMatrix_of_basis [Fintype κ] [DecidableEq κ] (b : Basis κ A B) :
traceMatrix A b = BilinForm.toMatrix b (traceForm A B) := by
ext (i j)
rw [traceMatrix_apply, traceForm_apply, traceForm_toMatrix]
#align algebra.trace_matrix_of_basis Algebra.traceMatrix_of_basis
theorem traceMatrix_of_basis_mulVec (b : Basis ι A B) (z : B) :
traceMatrix A b *ᵥ b.equivFun z = fun i => trace A B (z * b i) := by
ext i
rw [← col_apply (traceMatrix A b *ᵥ b.equivFun z) i Unit.unit, col_mulVec,
Matrix.mul_apply, traceMatrix]
simp only [col_apply, traceForm_apply]
conv_lhs =>
congr
rfl
ext
rw [mul_comm _ (b.equivFun z _), ← smul_eq_mul, of_apply, ← LinearMap.map_smul]
rw [← _root_.map_sum]
congr
conv_lhs =>
congr
rfl
ext
rw [← mul_smul_comm]
rw [← Finset.mul_sum, mul_comm z]
congr
rw [b.sum_equivFun]
#align algebra.trace_matrix_of_basis_mul_vec Algebra.traceMatrix_of_basis_mulVec
variable (A)
/-- `embeddingsMatrix A C b : Matrix κ (B →ₐ[A] C) C` is the matrix whose `(i, σ)` coefficient is
`σ (b i)`. It is mostly useful for fields when `Fintype.card κ = finrank A B` and `C` is
algebraically closed. -/
def embeddingsMatrix (b : κ → B) : Matrix κ (B →ₐ[A] C) C :=
of fun i (σ : B →ₐ[A] C) => σ (b i)
#align algebra.embeddings_matrix Algebra.embeddingsMatrix
-- TODO: set as an equation lemma for `embeddingsMatrix`, see mathlib4#3024
@[simp]
theorem embeddingsMatrix_apply (b : κ → B) (i) (σ : B →ₐ[A] C) :
embeddingsMatrix A C b i σ = σ (b i) :=
rfl
#align algebra.embeddings_matrix_apply Algebra.embeddingsMatrix_apply
/-- `embeddingsMatrixReindex A C b e : Matrix κ κ C` is the matrix whose `(i, j)` coefficient
is `σⱼ (b i)`, where `σⱼ : B →ₐ[A] C` is the embedding corresponding to `j : κ` given by a
bijection `e : κ ≃ (B →ₐ[A] C)`. It is mostly useful for fields and `C` is algebraically closed.
In this case, in presence of `h : Fintype.card κ = finrank A B`, one can take
`e := equivOfCardEq ((AlgHom.card A B C).trans h.symm)`. -/
def embeddingsMatrixReindex (b : κ → B) (e : κ ≃ (B →ₐ[A] C)) :=
reindex (Equiv.refl κ) e.symm (embeddingsMatrix A C b)
#align algebra.embeddings_matrix_reindex Algebra.embeddingsMatrixReindex
variable {A}
theorem embeddingsMatrixReindex_eq_vandermonde (pb : PowerBasis A B)
(e : Fin pb.dim ≃ (B →ₐ[A] C)) :
embeddingsMatrixReindex A C pb.basis e = (vandermonde fun i => e i pb.gen)ᵀ := by
ext i j
simp [embeddingsMatrixReindex, embeddingsMatrix]
#align algebra.embeddings_matrix_reindex_eq_vandermonde Algebra.embeddingsMatrixReindex_eq_vandermonde
section Field
variable (K) (E : Type z) [Field E]
variable [Algebra K E]
variable [Module.Finite K L] [IsSeparable K L] [IsAlgClosed E]
variable (b : κ → L) (pb : PowerBasis K L)
theorem traceMatrix_eq_embeddingsMatrix_mul_trans : (traceMatrix K b).map (algebraMap K E) =
embeddingsMatrix K E b * (embeddingsMatrix K E b)ᵀ := by
ext (i j); simp [trace_eq_sum_embeddings, embeddingsMatrix, Matrix.mul_apply]
#align algebra.trace_matrix_eq_embeddings_matrix_mul_trans Algebra.traceMatrix_eq_embeddingsMatrix_mul_trans
theorem traceMatrix_eq_embeddingsMatrixReindex_mul_trans [Fintype κ] (e : κ ≃ (L →ₐ[K] E)) :
(traceMatrix K b).map (algebraMap K E) =
embeddingsMatrixReindex K E b e * (embeddingsMatrixReindex K E b e)ᵀ := by
rw [traceMatrix_eq_embeddingsMatrix_mul_trans, embeddingsMatrixReindex, reindex_apply,
transpose_submatrix, ← submatrix_mul_transpose_submatrix, ← Equiv.coe_refl, Equiv.refl_symm]
#align algebra.trace_matrix_eq_embeddings_matrix_reindex_mul_trans Algebra.traceMatrix_eq_embeddingsMatrixReindex_mul_trans
end Field
end Algebra
open Algebra
variable (pb : PowerBasis K L)
| Mathlib/RingTheory/Trace.lean | 586 | 599 | theorem det_traceMatrix_ne_zero' [IsSeparable K L] : det (traceMatrix K pb.basis) ≠ 0 := by |
suffices algebraMap K (AlgebraicClosure L) (det (traceMatrix K pb.basis)) ≠ 0 by
refine mt (fun ht => ?_) this
rw [ht, RingHom.map_zero]
haveI : FiniteDimensional K L := pb.finite
let e : Fin pb.dim ≃ (L →ₐ[K] AlgebraicClosure L) := (Fintype.equivFinOfCardEq ?_).symm
· rw [RingHom.map_det, RingHom.mapMatrix_apply,
traceMatrix_eq_embeddingsMatrixReindex_mul_trans K _ _ e,
embeddingsMatrixReindex_eq_vandermonde, det_mul, det_transpose]
refine mt mul_self_eq_zero.mp ?_
simp only [det_vandermonde, Finset.prod_eq_zero_iff, not_exists, sub_eq_zero]
rintro i ⟨_, j, hij, h⟩
exact (Finset.mem_Ioi.mp hij).ne' (e.injective <| pb.algHom_ext h)
· rw [AlgHom.card, pb.finrank]
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro, Yury Kudryashov
-/
import Mathlib.Data.Set.Image
import Mathlib.Order.SuccPred.Relation
import Mathlib.Topology.Clopen
import Mathlib.Topology.Irreducible
#align_import topology.connected from "leanprover-community/mathlib"@"d101e93197bb5f6ea89bd7ba386b7f7dff1f3903"
/-!
# Connected subsets of topological spaces
In this file we define connected subsets of a topological spaces and various other properties and
classes related to connectivity.
## Main definitions
We define the following properties for sets in a topological space:
* `IsConnected`: a nonempty set that has no non-trivial open partition.
See also the section below in the module doc.
* `connectedComponent` is the connected component of an element in the space.
We also have a class stating that the whole space satisfies that property: `ConnectedSpace`
## On the definition of connected sets/spaces
In informal mathematics, connected spaces are assumed to be nonempty.
We formalise the predicate without that assumption as `IsPreconnected`.
In other words, the only difference is whether the empty space counts as connected.
There are good reasons to consider the empty space to be “too simple to be simple”
See also https://ncatlab.org/nlab/show/too+simple+to+be+simple,
and in particular
https://ncatlab.org/nlab/show/too+simple+to+be+simple#relationship_to_biased_definitions.
-/
open Set Function Topology TopologicalSpace Relation
open scoped Classical
universe u v
variable {α : Type u} {β : Type v} {ι : Type*} {π : ι → Type*} [TopologicalSpace α]
{s t u v : Set α}
section Preconnected
/-- A preconnected set is one where there is no non-trivial open partition. -/
def IsPreconnected (s : Set α) : Prop :=
∀ u v : Set α, IsOpen u → IsOpen v → s ⊆ u ∪ v → (s ∩ u).Nonempty → (s ∩ v).Nonempty →
(s ∩ (u ∩ v)).Nonempty
#align is_preconnected IsPreconnected
/-- A connected set is one that is nonempty and where there is no non-trivial open partition. -/
def IsConnected (s : Set α) : Prop :=
s.Nonempty ∧ IsPreconnected s
#align is_connected IsConnected
theorem IsConnected.nonempty {s : Set α} (h : IsConnected s) : s.Nonempty :=
h.1
#align is_connected.nonempty IsConnected.nonempty
theorem IsConnected.isPreconnected {s : Set α} (h : IsConnected s) : IsPreconnected s :=
h.2
#align is_connected.is_preconnected IsConnected.isPreconnected
theorem IsPreirreducible.isPreconnected {s : Set α} (H : IsPreirreducible s) : IsPreconnected s :=
fun _ _ hu hv _ => H _ _ hu hv
#align is_preirreducible.is_preconnected IsPreirreducible.isPreconnected
theorem IsIrreducible.isConnected {s : Set α} (H : IsIrreducible s) : IsConnected s :=
⟨H.nonempty, H.isPreirreducible.isPreconnected⟩
#align is_irreducible.is_connected IsIrreducible.isConnected
theorem isPreconnected_empty : IsPreconnected (∅ : Set α) :=
isPreirreducible_empty.isPreconnected
#align is_preconnected_empty isPreconnected_empty
theorem isConnected_singleton {x} : IsConnected ({x} : Set α) :=
isIrreducible_singleton.isConnected
#align is_connected_singleton isConnected_singleton
theorem isPreconnected_singleton {x} : IsPreconnected ({x} : Set α) :=
isConnected_singleton.isPreconnected
#align is_preconnected_singleton isPreconnected_singleton
theorem Set.Subsingleton.isPreconnected {s : Set α} (hs : s.Subsingleton) : IsPreconnected s :=
hs.induction_on isPreconnected_empty fun _ => isPreconnected_singleton
#align set.subsingleton.is_preconnected Set.Subsingleton.isPreconnected
/-- If any point of a set is joined to a fixed point by a preconnected subset,
then the original set is preconnected as well. -/
theorem isPreconnected_of_forall {s : Set α} (x : α)
(H : ∀ y ∈ s, ∃ t, t ⊆ s ∧ x ∈ t ∧ y ∈ t ∧ IsPreconnected t) : IsPreconnected s := by
rintro u v hu hv hs ⟨z, zs, zu⟩ ⟨y, ys, yv⟩
have xs : x ∈ s := by
rcases H y ys with ⟨t, ts, xt, -, -⟩
exact ts xt
-- Porting note (#11215): TODO: use `wlog xu : x ∈ u := hs xs using u v y z, v u z y`
cases hs xs with
| inl xu =>
rcases H y ys with ⟨t, ts, xt, yt, ht⟩
have := ht u v hu hv (ts.trans hs) ⟨x, xt, xu⟩ ⟨y, yt, yv⟩
exact this.imp fun z hz => ⟨ts hz.1, hz.2⟩
| inr xv =>
rcases H z zs with ⟨t, ts, xt, zt, ht⟩
have := ht v u hv hu (ts.trans <| by rwa [union_comm]) ⟨x, xt, xv⟩ ⟨z, zt, zu⟩
exact this.imp fun _ h => ⟨ts h.1, h.2.2, h.2.1⟩
#align is_preconnected_of_forall isPreconnected_of_forall
/-- If any two points of a set are contained in a preconnected subset,
then the original set is preconnected as well. -/
theorem isPreconnected_of_forall_pair {s : Set α}
(H : ∀ x ∈ s, ∀ y ∈ s, ∃ t, t ⊆ s ∧ x ∈ t ∧ y ∈ t ∧ IsPreconnected t) :
IsPreconnected s := by
rcases eq_empty_or_nonempty s with (rfl | ⟨x, hx⟩)
exacts [isPreconnected_empty, isPreconnected_of_forall x fun y => H x hx y]
#align is_preconnected_of_forall_pair isPreconnected_of_forall_pair
/-- A union of a family of preconnected sets with a common point is preconnected as well. -/
theorem isPreconnected_sUnion (x : α) (c : Set (Set α)) (H1 : ∀ s ∈ c, x ∈ s)
(H2 : ∀ s ∈ c, IsPreconnected s) : IsPreconnected (⋃₀ c) := by
apply isPreconnected_of_forall x
rintro y ⟨s, sc, ys⟩
exact ⟨s, subset_sUnion_of_mem sc, H1 s sc, ys, H2 s sc⟩
#align is_preconnected_sUnion isPreconnected_sUnion
theorem isPreconnected_iUnion {ι : Sort*} {s : ι → Set α} (h₁ : (⋂ i, s i).Nonempty)
(h₂ : ∀ i, IsPreconnected (s i)) : IsPreconnected (⋃ i, s i) :=
Exists.elim h₁ fun f hf => isPreconnected_sUnion f _ hf (forall_mem_range.2 h₂)
#align is_preconnected_Union isPreconnected_iUnion
theorem IsPreconnected.union (x : α) {s t : Set α} (H1 : x ∈ s) (H2 : x ∈ t) (H3 : IsPreconnected s)
(H4 : IsPreconnected t) : IsPreconnected (s ∪ t) :=
sUnion_pair s t ▸ isPreconnected_sUnion x {s, t} (by rintro r (rfl | rfl | h) <;> assumption)
(by rintro r (rfl | rfl | h) <;> assumption)
#align is_preconnected.union IsPreconnected.union
theorem IsPreconnected.union' {s t : Set α} (H : (s ∩ t).Nonempty) (hs : IsPreconnected s)
(ht : IsPreconnected t) : IsPreconnected (s ∪ t) := by
rcases H with ⟨x, hxs, hxt⟩
exact hs.union x hxs hxt ht
#align is_preconnected.union' IsPreconnected.union'
theorem IsConnected.union {s t : Set α} (H : (s ∩ t).Nonempty) (Hs : IsConnected s)
(Ht : IsConnected t) : IsConnected (s ∪ t) := by
rcases H with ⟨x, hx⟩
refine ⟨⟨x, mem_union_left t (mem_of_mem_inter_left hx)⟩, ?_⟩
exact Hs.isPreconnected.union x (mem_of_mem_inter_left hx) (mem_of_mem_inter_right hx)
Ht.isPreconnected
#align is_connected.union IsConnected.union
/-- The directed sUnion of a set S of preconnected subsets is preconnected. -/
theorem IsPreconnected.sUnion_directed {S : Set (Set α)} (K : DirectedOn (· ⊆ ·) S)
(H : ∀ s ∈ S, IsPreconnected s) : IsPreconnected (⋃₀ S) := by
rintro u v hu hv Huv ⟨a, ⟨s, hsS, has⟩, hau⟩ ⟨b, ⟨t, htS, hbt⟩, hbv⟩
obtain ⟨r, hrS, hsr, htr⟩ : ∃ r ∈ S, s ⊆ r ∧ t ⊆ r := K s hsS t htS
have Hnuv : (r ∩ (u ∩ v)).Nonempty :=
H _ hrS u v hu hv ((subset_sUnion_of_mem hrS).trans Huv) ⟨a, hsr has, hau⟩ ⟨b, htr hbt, hbv⟩
have Kruv : r ∩ (u ∩ v) ⊆ ⋃₀ S ∩ (u ∩ v) := inter_subset_inter_left _ (subset_sUnion_of_mem hrS)
exact Hnuv.mono Kruv
#align is_preconnected.sUnion_directed IsPreconnected.sUnion_directed
/-- The biUnion of a family of preconnected sets is preconnected if the graph determined by
whether two sets intersect is preconnected. -/
theorem IsPreconnected.biUnion_of_reflTransGen {ι : Type*} {t : Set ι} {s : ι → Set α}
(H : ∀ i ∈ t, IsPreconnected (s i))
(K : ∀ i, i ∈ t → ∀ j, j ∈ t → ReflTransGen (fun i j => (s i ∩ s j).Nonempty ∧ i ∈ t) i j) :
IsPreconnected (⋃ n ∈ t, s n) := by
let R := fun i j : ι => (s i ∩ s j).Nonempty ∧ i ∈ t
have P : ∀ i, i ∈ t → ∀ j, j ∈ t → ReflTransGen R i j →
∃ p, p ⊆ t ∧ i ∈ p ∧ j ∈ p ∧ IsPreconnected (⋃ j ∈ p, s j) := fun i hi j hj h => by
induction h with
| refl =>
refine ⟨{i}, singleton_subset_iff.mpr hi, mem_singleton i, mem_singleton i, ?_⟩
rw [biUnion_singleton]
exact H i hi
| @tail j k _ hjk ih =>
obtain ⟨p, hpt, hip, hjp, hp⟩ := ih hjk.2
refine ⟨insert k p, insert_subset_iff.mpr ⟨hj, hpt⟩, mem_insert_of_mem k hip,
mem_insert k p, ?_⟩
rw [biUnion_insert]
refine (H k hj).union' (hjk.1.mono ?_) hp
rw [inter_comm]
exact inter_subset_inter_right _ (subset_biUnion_of_mem hjp)
refine isPreconnected_of_forall_pair ?_
intro x hx y hy
obtain ⟨i : ι, hi : i ∈ t, hxi : x ∈ s i⟩ := mem_iUnion₂.1 hx
obtain ⟨j : ι, hj : j ∈ t, hyj : y ∈ s j⟩ := mem_iUnion₂.1 hy
obtain ⟨p, hpt, hip, hjp, hp⟩ := P i hi j hj (K i hi j hj)
exact ⟨⋃ j ∈ p, s j, biUnion_subset_biUnion_left hpt, mem_biUnion hip hxi,
mem_biUnion hjp hyj, hp⟩
#align is_preconnected.bUnion_of_refl_trans_gen IsPreconnected.biUnion_of_reflTransGen
/-- The biUnion of a family of preconnected sets is preconnected if the graph determined by
whether two sets intersect is preconnected. -/
theorem IsConnected.biUnion_of_reflTransGen {ι : Type*} {t : Set ι} {s : ι → Set α}
(ht : t.Nonempty) (H : ∀ i ∈ t, IsConnected (s i))
(K : ∀ i, i ∈ t → ∀ j, j ∈ t → ReflTransGen (fun i j : ι => (s i ∩ s j).Nonempty ∧ i ∈ t) i j) :
IsConnected (⋃ n ∈ t, s n) :=
⟨nonempty_biUnion.2 <| ⟨ht.some, ht.some_mem, (H _ ht.some_mem).nonempty⟩,
IsPreconnected.biUnion_of_reflTransGen (fun i hi => (H i hi).isPreconnected) K⟩
#align is_connected.bUnion_of_refl_trans_gen IsConnected.biUnion_of_reflTransGen
/-- Preconnectedness of the iUnion of a family of preconnected sets
indexed by the vertices of a preconnected graph,
where two vertices are joined when the corresponding sets intersect. -/
theorem IsPreconnected.iUnion_of_reflTransGen {ι : Type*} {s : ι → Set α}
(H : ∀ i, IsPreconnected (s i))
(K : ∀ i j, ReflTransGen (fun i j : ι => (s i ∩ s j).Nonempty) i j) :
IsPreconnected (⋃ n, s n) := by
rw [← biUnion_univ]
exact IsPreconnected.biUnion_of_reflTransGen (fun i _ => H i) fun i _ j _ => by
simpa [mem_univ] using K i j
#align is_preconnected.Union_of_refl_trans_gen IsPreconnected.iUnion_of_reflTransGen
theorem IsConnected.iUnion_of_reflTransGen {ι : Type*} [Nonempty ι] {s : ι → Set α}
(H : ∀ i, IsConnected (s i))
(K : ∀ i j, ReflTransGen (fun i j : ι => (s i ∩ s j).Nonempty) i j) : IsConnected (⋃ n, s n) :=
⟨nonempty_iUnion.2 <| Nonempty.elim ‹_› fun i : ι => ⟨i, (H _).nonempty⟩,
IsPreconnected.iUnion_of_reflTransGen (fun i => (H i).isPreconnected) K⟩
#align is_connected.Union_of_refl_trans_gen IsConnected.iUnion_of_reflTransGen
section SuccOrder
open Order
variable [LinearOrder β] [SuccOrder β] [IsSuccArchimedean β]
/-- The iUnion of connected sets indexed by a type with an archimedean successor (like `ℕ` or `ℤ`)
such that any two neighboring sets meet is preconnected. -/
theorem IsPreconnected.iUnion_of_chain {s : β → Set α} (H : ∀ n, IsPreconnected (s n))
(K : ∀ n, (s n ∩ s (succ n)).Nonempty) : IsPreconnected (⋃ n, s n) :=
IsPreconnected.iUnion_of_reflTransGen H fun i j =>
reflTransGen_of_succ _ (fun i _ => K i) fun i _ => by
rw [inter_comm]
exact K i
#align is_preconnected.Union_of_chain IsPreconnected.iUnion_of_chain
/-- The iUnion of connected sets indexed by a type with an archimedean successor (like `ℕ` or `ℤ`)
such that any two neighboring sets meet is connected. -/
theorem IsConnected.iUnion_of_chain [Nonempty β] {s : β → Set α} (H : ∀ n, IsConnected (s n))
(K : ∀ n, (s n ∩ s (succ n)).Nonempty) : IsConnected (⋃ n, s n) :=
IsConnected.iUnion_of_reflTransGen H fun i j =>
reflTransGen_of_succ _ (fun i _ => K i) fun i _ => by
rw [inter_comm]
exact K i
#align is_connected.Union_of_chain IsConnected.iUnion_of_chain
/-- The iUnion of preconnected sets indexed by a subset of a type with an archimedean successor
(like `ℕ` or `ℤ`) such that any two neighboring sets meet is preconnected. -/
theorem IsPreconnected.biUnion_of_chain {s : β → Set α} {t : Set β} (ht : OrdConnected t)
(H : ∀ n ∈ t, IsPreconnected (s n))
(K : ∀ n : β, n ∈ t → succ n ∈ t → (s n ∩ s (succ n)).Nonempty) :
IsPreconnected (⋃ n ∈ t, s n) := by
have h1 : ∀ {i j k : β}, i ∈ t → j ∈ t → k ∈ Ico i j → k ∈ t := fun hi hj hk =>
ht.out hi hj (Ico_subset_Icc_self hk)
have h2 : ∀ {i j k : β}, i ∈ t → j ∈ t → k ∈ Ico i j → succ k ∈ t := fun hi hj hk =>
ht.out hi hj ⟨hk.1.trans <| le_succ _, succ_le_of_lt hk.2⟩
have h3 : ∀ {i j k : β}, i ∈ t → j ∈ t → k ∈ Ico i j → (s k ∩ s (succ k)).Nonempty :=
fun hi hj hk => K _ (h1 hi hj hk) (h2 hi hj hk)
refine IsPreconnected.biUnion_of_reflTransGen H fun i hi j hj => ?_
exact reflTransGen_of_succ _ (fun k hk => ⟨h3 hi hj hk, h1 hi hj hk⟩) fun k hk =>
⟨by rw [inter_comm]; exact h3 hj hi hk, h2 hj hi hk⟩
#align is_preconnected.bUnion_of_chain IsPreconnected.biUnion_of_chain
/-- The iUnion of connected sets indexed by a subset of a type with an archimedean successor
(like `ℕ` or `ℤ`) such that any two neighboring sets meet is preconnected. -/
theorem IsConnected.biUnion_of_chain {s : β → Set α} {t : Set β} (hnt : t.Nonempty)
(ht : OrdConnected t) (H : ∀ n ∈ t, IsConnected (s n))
(K : ∀ n : β, n ∈ t → succ n ∈ t → (s n ∩ s (succ n)).Nonempty) : IsConnected (⋃ n ∈ t, s n) :=
⟨nonempty_biUnion.2 <| ⟨hnt.some, hnt.some_mem, (H _ hnt.some_mem).nonempty⟩,
IsPreconnected.biUnion_of_chain ht (fun i hi => (H i hi).isPreconnected) K⟩
#align is_connected.bUnion_of_chain IsConnected.biUnion_of_chain
end SuccOrder
/-- Theorem of bark and tree: if a set is within a preconnected set and its closure, then it is
preconnected as well. See also `IsConnected.subset_closure`. -/
protected theorem IsPreconnected.subset_closure {s : Set α} {t : Set α} (H : IsPreconnected s)
(Kst : s ⊆ t) (Ktcs : t ⊆ closure s) : IsPreconnected t :=
fun u v hu hv htuv ⟨_y, hyt, hyu⟩ ⟨_z, hzt, hzv⟩ =>
let ⟨p, hpu, hps⟩ := mem_closure_iff.1 (Ktcs hyt) u hu hyu
let ⟨q, hqv, hqs⟩ := mem_closure_iff.1 (Ktcs hzt) v hv hzv
let ⟨r, hrs, hruv⟩ := H u v hu hv (Subset.trans Kst htuv) ⟨p, hps, hpu⟩ ⟨q, hqs, hqv⟩
⟨r, Kst hrs, hruv⟩
#align is_preconnected.subset_closure IsPreconnected.subset_closure
/-- Theorem of bark and tree: if a set is within a connected set and its closure, then it is
connected as well. See also `IsPreconnected.subset_closure`. -/
protected theorem IsConnected.subset_closure {s : Set α} {t : Set α} (H : IsConnected s)
(Kst : s ⊆ t) (Ktcs : t ⊆ closure s) : IsConnected t :=
⟨Nonempty.mono Kst H.left, IsPreconnected.subset_closure H.right Kst Ktcs⟩
#align is_connected.subset_closure IsConnected.subset_closure
/-- The closure of a preconnected set is preconnected as well. -/
protected theorem IsPreconnected.closure {s : Set α} (H : IsPreconnected s) :
IsPreconnected (closure s) :=
IsPreconnected.subset_closure H subset_closure Subset.rfl
#align is_preconnected.closure IsPreconnected.closure
/-- The closure of a connected set is connected as well. -/
protected theorem IsConnected.closure {s : Set α} (H : IsConnected s) : IsConnected (closure s) :=
IsConnected.subset_closure H subset_closure <| Subset.rfl
#align is_connected.closure IsConnected.closure
/-- The image of a preconnected set is preconnected as well. -/
protected theorem IsPreconnected.image [TopologicalSpace β] {s : Set α} (H : IsPreconnected s)
(f : α → β) (hf : ContinuousOn f s) : IsPreconnected (f '' s) := by
-- Unfold/destruct definitions in hypotheses
rintro u v hu hv huv ⟨_, ⟨x, xs, rfl⟩, xu⟩ ⟨_, ⟨y, ys, rfl⟩, yv⟩
rcases continuousOn_iff'.1 hf u hu with ⟨u', hu', u'_eq⟩
rcases continuousOn_iff'.1 hf v hv with ⟨v', hv', v'_eq⟩
-- Reformulate `huv : f '' s ⊆ u ∪ v` in terms of `u'` and `v'`
replace huv : s ⊆ u' ∪ v' := by
rw [image_subset_iff, preimage_union] at huv
replace huv := subset_inter huv Subset.rfl
rw [union_inter_distrib_right, u'_eq, v'_eq, ← union_inter_distrib_right] at huv
exact (subset_inter_iff.1 huv).1
-- Now `s ⊆ u' ∪ v'`, so we can apply `‹IsPreconnected s›`
obtain ⟨z, hz⟩ : (s ∩ (u' ∩ v')).Nonempty := by
refine H u' v' hu' hv' huv ⟨x, ?_⟩ ⟨y, ?_⟩ <;> rw [inter_comm]
exacts [u'_eq ▸ ⟨xu, xs⟩, v'_eq ▸ ⟨yv, ys⟩]
rw [← inter_self s, inter_assoc, inter_left_comm s u', ← inter_assoc, inter_comm s, inter_comm s,
← u'_eq, ← v'_eq] at hz
exact ⟨f z, ⟨z, hz.1.2, rfl⟩, hz.1.1, hz.2.1⟩
#align is_preconnected.image IsPreconnected.image
/-- The image of a connected set is connected as well. -/
protected theorem IsConnected.image [TopologicalSpace β] {s : Set α} (H : IsConnected s) (f : α → β)
(hf : ContinuousOn f s) : IsConnected (f '' s) :=
⟨image_nonempty.mpr H.nonempty, H.isPreconnected.image f hf⟩
#align is_connected.image IsConnected.image
theorem isPreconnected_closed_iff {s : Set α} :
IsPreconnected s ↔ ∀ t t', IsClosed t → IsClosed t' →
s ⊆ t ∪ t' → (s ∩ t).Nonempty → (s ∩ t').Nonempty → (s ∩ (t ∩ t')).Nonempty :=
⟨by
rintro h t t' ht ht' htt' ⟨x, xs, xt⟩ ⟨y, ys, yt'⟩
rw [← not_disjoint_iff_nonempty_inter, ← subset_compl_iff_disjoint_right, compl_inter]
intro h'
have xt' : x ∉ t' := (h' xs).resolve_left (absurd xt)
have yt : y ∉ t := (h' ys).resolve_right (absurd yt')
have := h _ _ ht.isOpen_compl ht'.isOpen_compl h' ⟨y, ys, yt⟩ ⟨x, xs, xt'⟩
rw [← compl_union] at this
exact this.ne_empty htt'.disjoint_compl_right.inter_eq,
by
rintro h u v hu hv huv ⟨x, xs, xu⟩ ⟨y, ys, yv⟩
rw [← not_disjoint_iff_nonempty_inter, ← subset_compl_iff_disjoint_right, compl_inter]
intro h'
have xv : x ∉ v := (h' xs).elim (absurd xu) id
have yu : y ∉ u := (h' ys).elim id (absurd yv)
have := h _ _ hu.isClosed_compl hv.isClosed_compl h' ⟨y, ys, yu⟩ ⟨x, xs, xv⟩
rw [← compl_union] at this
exact this.ne_empty huv.disjoint_compl_right.inter_eq⟩
#align is_preconnected_closed_iff isPreconnected_closed_iff
theorem Inducing.isPreconnected_image [TopologicalSpace β] {s : Set α} {f : α → β}
(hf : Inducing f) : IsPreconnected (f '' s) ↔ IsPreconnected s := by
refine ⟨fun h => ?_, fun h => h.image _ hf.continuous.continuousOn⟩
rintro u v hu' hv' huv ⟨x, hxs, hxu⟩ ⟨y, hys, hyv⟩
rcases hf.isOpen_iff.1 hu' with ⟨u, hu, rfl⟩
rcases hf.isOpen_iff.1 hv' with ⟨v, hv, rfl⟩
replace huv : f '' s ⊆ u ∪ v := by rwa [image_subset_iff]
rcases h u v hu hv huv ⟨f x, mem_image_of_mem _ hxs, hxu⟩ ⟨f y, mem_image_of_mem _ hys, hyv⟩ with
⟨_, ⟨z, hzs, rfl⟩, hzuv⟩
exact ⟨z, hzs, hzuv⟩
#align inducing.is_preconnected_image Inducing.isPreconnected_image
/- TODO: The following lemmas about connection of preimages hold more generally for strict maps
(the quotient and subspace topologies of the image agree) whose fibers are preconnected. -/
theorem IsPreconnected.preimage_of_isOpenMap [TopologicalSpace β] {f : α → β} {s : Set β}
(hs : IsPreconnected s) (hinj : Function.Injective f) (hf : IsOpenMap f) (hsf : s ⊆ range f) :
IsPreconnected (f ⁻¹' s) := fun u v hu hv hsuv hsu hsv => by
replace hsf : f '' (f ⁻¹' s) = s := image_preimage_eq_of_subset hsf
obtain ⟨_, has, ⟨a, hau, rfl⟩, hav⟩ : (s ∩ (f '' u ∩ f '' v)).Nonempty := by
refine hs (f '' u) (f '' v) (hf u hu) (hf v hv) ?_ ?_ ?_
· simpa only [hsf, image_union] using image_subset f hsuv
· simpa only [image_preimage_inter] using hsu.image f
· simpa only [image_preimage_inter] using hsv.image f
· exact ⟨a, has, hau, hinj.mem_set_image.1 hav⟩
#align is_preconnected.preimage_of_open_map IsPreconnected.preimage_of_isOpenMap
theorem IsPreconnected.preimage_of_isClosedMap [TopologicalSpace β] {s : Set β}
(hs : IsPreconnected s) {f : α → β} (hinj : Function.Injective f) (hf : IsClosedMap f)
(hsf : s ⊆ range f) : IsPreconnected (f ⁻¹' s) :=
isPreconnected_closed_iff.2 fun u v hu hv hsuv hsu hsv => by
replace hsf : f '' (f ⁻¹' s) = s := image_preimage_eq_of_subset hsf
obtain ⟨_, has, ⟨a, hau, rfl⟩, hav⟩ : (s ∩ (f '' u ∩ f '' v)).Nonempty := by
refine isPreconnected_closed_iff.1 hs (f '' u) (f '' v) (hf u hu) (hf v hv) ?_ ?_ ?_
· simpa only [hsf, image_union] using image_subset f hsuv
· simpa only [image_preimage_inter] using hsu.image f
· simpa only [image_preimage_inter] using hsv.image f
· exact ⟨a, has, hau, hinj.mem_set_image.1 hav⟩
#align is_preconnected.preimage_of_closed_map IsPreconnected.preimage_of_isClosedMap
theorem IsConnected.preimage_of_isOpenMap [TopologicalSpace β] {s : Set β} (hs : IsConnected s)
{f : α → β} (hinj : Function.Injective f) (hf : IsOpenMap f) (hsf : s ⊆ range f) :
IsConnected (f ⁻¹' s) :=
⟨hs.nonempty.preimage' hsf, hs.isPreconnected.preimage_of_isOpenMap hinj hf hsf⟩
#align is_connected.preimage_of_open_map IsConnected.preimage_of_isOpenMap
theorem IsConnected.preimage_of_isClosedMap [TopologicalSpace β] {s : Set β} (hs : IsConnected s)
{f : α → β} (hinj : Function.Injective f) (hf : IsClosedMap f) (hsf : s ⊆ range f) :
IsConnected (f ⁻¹' s) :=
⟨hs.nonempty.preimage' hsf, hs.isPreconnected.preimage_of_isClosedMap hinj hf hsf⟩
#align is_connected.preimage_of_closed_map IsConnected.preimage_of_isClosedMap
theorem IsPreconnected.subset_or_subset (hu : IsOpen u) (hv : IsOpen v) (huv : Disjoint u v)
(hsuv : s ⊆ u ∪ v) (hs : IsPreconnected s) : s ⊆ u ∨ s ⊆ v := by
specialize hs u v hu hv hsuv
obtain hsu | hsu := (s ∩ u).eq_empty_or_nonempty
· exact Or.inr ((Set.disjoint_iff_inter_eq_empty.2 hsu).subset_right_of_subset_union hsuv)
· replace hs := mt (hs hsu)
simp_rw [Set.not_nonempty_iff_eq_empty, ← Set.disjoint_iff_inter_eq_empty,
disjoint_iff_inter_eq_empty.1 huv] at hs
exact Or.inl ((hs s.disjoint_empty).subset_left_of_subset_union hsuv)
#align is_preconnected.subset_or_subset IsPreconnected.subset_or_subset
theorem IsPreconnected.subset_left_of_subset_union (hu : IsOpen u) (hv : IsOpen v)
(huv : Disjoint u v) (hsuv : s ⊆ u ∪ v) (hsu : (s ∩ u).Nonempty) (hs : IsPreconnected s) :
s ⊆ u :=
Disjoint.subset_left_of_subset_union hsuv
(by
by_contra hsv
rw [not_disjoint_iff_nonempty_inter] at hsv
obtain ⟨x, _, hx⟩ := hs u v hu hv hsuv hsu hsv
exact Set.disjoint_iff.1 huv hx)
#align is_preconnected.subset_left_of_subset_union IsPreconnected.subset_left_of_subset_union
theorem IsPreconnected.subset_right_of_subset_union (hu : IsOpen u) (hv : IsOpen v)
(huv : Disjoint u v) (hsuv : s ⊆ u ∪ v) (hsv : (s ∩ v).Nonempty) (hs : IsPreconnected s) :
s ⊆ v :=
hs.subset_left_of_subset_union hv hu huv.symm (union_comm u v ▸ hsuv) hsv
#align is_preconnected.subset_right_of_subset_union IsPreconnected.subset_right_of_subset_union
-- Porting note: moved up
/-- Preconnected sets are either contained in or disjoint to any given clopen set. -/
theorem IsPreconnected.subset_isClopen {s t : Set α} (hs : IsPreconnected s) (ht : IsClopen t)
(hne : (s ∩ t).Nonempty) : s ⊆ t :=
hs.subset_left_of_subset_union ht.isOpen ht.compl.isOpen disjoint_compl_right (by simp) hne
#align is_preconnected.subset_clopen IsPreconnected.subset_isClopen
/-- If a preconnected set `s` intersects an open set `u`, and limit points of `u` inside `s` are
contained in `u`, then the whole set `s` is contained in `u`. -/
theorem IsPreconnected.subset_of_closure_inter_subset (hs : IsPreconnected s) (hu : IsOpen u)
(h'u : (s ∩ u).Nonempty) (h : closure u ∩ s ⊆ u) : s ⊆ u := by
have A : s ⊆ u ∪ (closure u)ᶜ := by
intro x hx
by_cases xu : x ∈ u
· exact Or.inl xu
· right
intro h'x
exact xu (h (mem_inter h'x hx))
apply hs.subset_left_of_subset_union hu isClosed_closure.isOpen_compl _ A h'u
exact disjoint_compl_right.mono_right (compl_subset_compl.2 subset_closure)
#align is_preconnected.subset_of_closure_inter_subset IsPreconnected.subset_of_closure_inter_subset
theorem IsPreconnected.prod [TopologicalSpace β] {s : Set α} {t : Set β} (hs : IsPreconnected s)
(ht : IsPreconnected t) : IsPreconnected (s ×ˢ t) := by
apply isPreconnected_of_forall_pair
rintro ⟨a₁, b₁⟩ ⟨ha₁, hb₁⟩ ⟨a₂, b₂⟩ ⟨ha₂, hb₂⟩
refine ⟨Prod.mk a₁ '' t ∪ flip Prod.mk b₂ '' s, ?_, .inl ⟨b₁, hb₁, rfl⟩, .inr ⟨a₂, ha₂, rfl⟩, ?_⟩
· rintro _ (⟨y, hy, rfl⟩ | ⟨x, hx, rfl⟩)
exacts [⟨ha₁, hy⟩, ⟨hx, hb₂⟩]
· exact (ht.image _ (Continuous.Prod.mk _).continuousOn).union (a₁, b₂) ⟨b₂, hb₂, rfl⟩
⟨a₁, ha₁, rfl⟩ (hs.image _ (continuous_id.prod_mk continuous_const).continuousOn)
#align is_preconnected.prod IsPreconnected.prod
theorem IsConnected.prod [TopologicalSpace β] {s : Set α} {t : Set β} (hs : IsConnected s)
(ht : IsConnected t) : IsConnected (s ×ˢ t) :=
⟨hs.1.prod ht.1, hs.2.prod ht.2⟩
#align is_connected.prod IsConnected.prod
theorem isPreconnected_univ_pi [∀ i, TopologicalSpace (π i)] {s : ∀ i, Set (π i)}
(hs : ∀ i, IsPreconnected (s i)) : IsPreconnected (pi univ s) := by
rintro u v uo vo hsuv ⟨f, hfs, hfu⟩ ⟨g, hgs, hgv⟩
rcases exists_finset_piecewise_mem_of_mem_nhds (uo.mem_nhds hfu) g with ⟨I, hI⟩
induction' I using Finset.induction_on with i I _ ihI
· refine ⟨g, hgs, ⟨?_, hgv⟩⟩
simpa using hI
· rw [Finset.piecewise_insert] at hI
have := I.piecewise_mem_set_pi hfs hgs
refine (hsuv this).elim ihI fun h => ?_
set S := update (I.piecewise f g) i '' s i
have hsub : S ⊆ pi univ s := by
refine image_subset_iff.2 fun z hz => ?_
rwa [update_preimage_univ_pi]
exact fun j _ => this j trivial
have hconn : IsPreconnected S :=
(hs i).image _ (continuous_const.update i continuous_id).continuousOn
have hSu : (S ∩ u).Nonempty := ⟨_, mem_image_of_mem _ (hfs _ trivial), hI⟩
have hSv : (S ∩ v).Nonempty := ⟨_, ⟨_, this _ trivial, update_eq_self _ _⟩, h⟩
refine (hconn u v uo vo (hsub.trans hsuv) hSu hSv).mono ?_
exact inter_subset_inter_left _ hsub
#align is_preconnected_univ_pi isPreconnected_univ_pi
@[simp]
theorem isConnected_univ_pi [∀ i, TopologicalSpace (π i)] {s : ∀ i, Set (π i)} :
IsConnected (pi univ s) ↔ ∀ i, IsConnected (s i) := by
simp only [IsConnected, ← univ_pi_nonempty_iff, forall_and, and_congr_right_iff]
refine fun hne => ⟨fun hc i => ?_, isPreconnected_univ_pi⟩
rw [← eval_image_univ_pi hne]
exact hc.image _ (continuous_apply _).continuousOn
#align is_connected_univ_pi isConnected_univ_pi
theorem Sigma.isConnected_iff [∀ i, TopologicalSpace (π i)] {s : Set (Σi, π i)} :
IsConnected s ↔ ∃ i t, IsConnected t ∧ s = Sigma.mk i '' t := by
refine ⟨fun hs => ?_, ?_⟩
· obtain ⟨⟨i, x⟩, hx⟩ := hs.nonempty
have : s ⊆ range (Sigma.mk i) :=
hs.isPreconnected.subset_isClopen isClopen_range_sigmaMk ⟨⟨i, x⟩, hx, x, rfl⟩
exact ⟨i, Sigma.mk i ⁻¹' s, hs.preimage_of_isOpenMap sigma_mk_injective isOpenMap_sigmaMk this,
(Set.image_preimage_eq_of_subset this).symm⟩
· rintro ⟨i, t, ht, rfl⟩
exact ht.image _ continuous_sigmaMk.continuousOn
#align sigma.is_connected_iff Sigma.isConnected_iff
theorem Sigma.isPreconnected_iff [hι : Nonempty ι] [∀ i, TopologicalSpace (π i)]
{s : Set (Σi, π i)} : IsPreconnected s ↔ ∃ i t, IsPreconnected t ∧ s = Sigma.mk i '' t := by
refine ⟨fun hs => ?_, ?_⟩
· obtain rfl | h := s.eq_empty_or_nonempty
· exact ⟨Classical.choice hι, ∅, isPreconnected_empty, (Set.image_empty _).symm⟩
· obtain ⟨a, t, ht, rfl⟩ := Sigma.isConnected_iff.1 ⟨h, hs⟩
exact ⟨a, t, ht.isPreconnected, rfl⟩
· rintro ⟨a, t, ht, rfl⟩
exact ht.image _ continuous_sigmaMk.continuousOn
#align sigma.is_preconnected_iff Sigma.isPreconnected_iff
| Mathlib/Topology/Connected/Basic.lean | 534 | 551 | theorem Sum.isConnected_iff [TopologicalSpace β] {s : Set (Sum α β)} :
IsConnected s ↔
(∃ t, IsConnected t ∧ s = Sum.inl '' t) ∨ ∃ t, IsConnected t ∧ s = Sum.inr '' t := by |
refine ⟨fun hs => ?_, ?_⟩
· obtain ⟨x | x, hx⟩ := hs.nonempty
· have h : s ⊆ range Sum.inl :=
hs.isPreconnected.subset_isClopen isClopen_range_inl ⟨.inl x, hx, x, rfl⟩
refine Or.inl ⟨Sum.inl ⁻¹' s, ?_, ?_⟩
· exact hs.preimage_of_isOpenMap Sum.inl_injective isOpenMap_inl h
· exact (image_preimage_eq_of_subset h).symm
· have h : s ⊆ range Sum.inr :=
hs.isPreconnected.subset_isClopen isClopen_range_inr ⟨.inr x, hx, x, rfl⟩
refine Or.inr ⟨Sum.inr ⁻¹' s, ?_, ?_⟩
· exact hs.preimage_of_isOpenMap Sum.inr_injective isOpenMap_inr h
· exact (image_preimage_eq_of_subset h).symm
· rintro (⟨t, ht, rfl⟩ | ⟨t, ht, rfl⟩)
· exact ht.image _ continuous_inl.continuousOn
· exact ht.image _ continuous_inr.continuousOn
|
/-
Copyright (c) 2021 Yury G. Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury G. Kudryashov, Alistair Tucker, Wen Yang
-/
import Mathlib.Order.Interval.Set.Image
import Mathlib.Order.CompleteLatticeIntervals
import Mathlib.Topology.Order.DenselyOrdered
import Mathlib.Topology.Order.Monotone
#align_import topology.algebra.order.intermediate_value from "leanprover-community/mathlib"@"4c19a16e4b705bf135cf9a80ac18fcc99c438514"
/-!
# Intermediate Value Theorem
In this file we prove the Intermediate Value Theorem: if `f : α → β` is a function defined on a
connected set `s` that takes both values `≤ a` and values `≥ a` on `s`, then it is equal to `a` at
some point of `s`. We also prove that intervals in a dense conditionally complete order are
preconnected and any preconnected set is an interval. Then we specialize IVT to functions continuous
on intervals.
## Main results
* `IsPreconnected_I??` : all intervals `I??` are preconnected,
* `IsPreconnected.intermediate_value`, `intermediate_value_univ` : Intermediate Value Theorem for
connected sets and connected spaces, respectively;
* `intermediate_value_Icc`, `intermediate_value_Icc'`: Intermediate Value Theorem for functions
on closed intervals.
### Miscellaneous facts
* `IsClosed.Icc_subset_of_forall_mem_nhdsWithin` : “Continuous induction” principle;
if `s ∩ [a, b]` is closed, `a ∈ s`, and for each `x ∈ [a, b) ∩ s` some of its right neighborhoods
is included `s`, then `[a, b] ⊆ s`.
* `IsClosed.Icc_subset_of_forall_exists_gt`, `IsClosed.mem_of_ge_of_forall_exists_gt` : two
other versions of the “continuous induction” principle.
* `ContinuousOn.StrictMonoOn_of_InjOn_Ioo` :
Every continuous injective `f : (a, b) → δ` is strictly monotone
or antitone (increasing or decreasing).
## Tags
intermediate value theorem, connected space, connected set
-/
open Filter OrderDual TopologicalSpace Function Set
open Topology Filter
universe u v w
/-!
### Intermediate value theorem on a (pre)connected space
In this section we prove the following theorem (see `IsPreconnected.intermediate_value₂`): if `f`
and `g` are two functions continuous on a preconnected set `s`, `f a ≤ g a` at some `a ∈ s` and
`g b ≤ f b` at some `b ∈ s`, then `f c = g c` at some `c ∈ s`. We prove several versions of this
statement, including the classical IVT that corresponds to a constant function `g`.
-/
section
variable {X : Type u} {α : Type v} [TopologicalSpace X] [LinearOrder α] [TopologicalSpace α]
[OrderClosedTopology α]
/-- Intermediate value theorem for two functions: if `f` and `g` are two continuous functions
on a preconnected space and `f a ≤ g a` and `g b ≤ f b`, then for some `x` we have `f x = g x`. -/
theorem intermediate_value_univ₂ [PreconnectedSpace X] {a b : X} {f g : X → α} (hf : Continuous f)
(hg : Continuous g) (ha : f a ≤ g a) (hb : g b ≤ f b) : ∃ x, f x = g x := by
obtain ⟨x, _, hfg, hgf⟩ : (univ ∩ { x | f x ≤ g x ∧ g x ≤ f x }).Nonempty :=
isPreconnected_closed_iff.1 PreconnectedSpace.isPreconnected_univ _ _ (isClosed_le hf hg)
(isClosed_le hg hf) (fun _ _ => le_total _ _) ⟨a, trivial, ha⟩ ⟨b, trivial, hb⟩
exact ⟨x, le_antisymm hfg hgf⟩
#align intermediate_value_univ₂ intermediate_value_univ₂
theorem intermediate_value_univ₂_eventually₁ [PreconnectedSpace X] {a : X} {l : Filter X} [NeBot l]
{f g : X → α} (hf : Continuous f) (hg : Continuous g) (ha : f a ≤ g a) (he : g ≤ᶠ[l] f) :
∃ x, f x = g x :=
let ⟨_, h⟩ := he.exists; intermediate_value_univ₂ hf hg ha h
#align intermediate_value_univ₂_eventually₁ intermediate_value_univ₂_eventually₁
theorem intermediate_value_univ₂_eventually₂ [PreconnectedSpace X] {l₁ l₂ : Filter X} [NeBot l₁]
[NeBot l₂] {f g : X → α} (hf : Continuous f) (hg : Continuous g) (he₁ : f ≤ᶠ[l₁] g)
(he₂ : g ≤ᶠ[l₂] f) : ∃ x, f x = g x :=
let ⟨_, h₁⟩ := he₁.exists
let ⟨_, h₂⟩ := he₂.exists
intermediate_value_univ₂ hf hg h₁ h₂
#align intermediate_value_univ₂_eventually₂ intermediate_value_univ₂_eventually₂
/-- Intermediate value theorem for two functions: if `f` and `g` are two functions continuous
on a preconnected set `s` and for some `a b ∈ s` we have `f a ≤ g a` and `g b ≤ f b`,
then for some `x ∈ s` we have `f x = g x`. -/
theorem IsPreconnected.intermediate_value₂ {s : Set X} (hs : IsPreconnected s) {a b : X}
(ha : a ∈ s) (hb : b ∈ s) {f g : X → α} (hf : ContinuousOn f s) (hg : ContinuousOn g s)
(ha' : f a ≤ g a) (hb' : g b ≤ f b) : ∃ x ∈ s, f x = g x :=
let ⟨x, hx⟩ :=
@intermediate_value_univ₂ s α _ _ _ _ (Subtype.preconnectedSpace hs) ⟨a, ha⟩ ⟨b, hb⟩ _ _
(continuousOn_iff_continuous_restrict.1 hf) (continuousOn_iff_continuous_restrict.1 hg) ha'
hb'
⟨x, x.2, hx⟩
#align is_preconnected.intermediate_value₂ IsPreconnected.intermediate_value₂
theorem IsPreconnected.intermediate_value₂_eventually₁ {s : Set X} (hs : IsPreconnected s) {a : X}
{l : Filter X} (ha : a ∈ s) [NeBot l] (hl : l ≤ 𝓟 s) {f g : X → α} (hf : ContinuousOn f s)
(hg : ContinuousOn g s) (ha' : f a ≤ g a) (he : g ≤ᶠ[l] f) : ∃ x ∈ s, f x = g x := by
rw [continuousOn_iff_continuous_restrict] at hf hg
obtain ⟨b, h⟩ :=
@intermediate_value_univ₂_eventually₁ _ _ _ _ _ _ (Subtype.preconnectedSpace hs) ⟨a, ha⟩ _
(comap_coe_neBot_of_le_principal hl) _ _ hf hg ha' (he.comap _)
exact ⟨b, b.prop, h⟩
#align is_preconnected.intermediate_value₂_eventually₁ IsPreconnected.intermediate_value₂_eventually₁
theorem IsPreconnected.intermediate_value₂_eventually₂ {s : Set X} (hs : IsPreconnected s)
{l₁ l₂ : Filter X} [NeBot l₁] [NeBot l₂] (hl₁ : l₁ ≤ 𝓟 s) (hl₂ : l₂ ≤ 𝓟 s) {f g : X → α}
(hf : ContinuousOn f s) (hg : ContinuousOn g s) (he₁ : f ≤ᶠ[l₁] g) (he₂ : g ≤ᶠ[l₂] f) :
∃ x ∈ s, f x = g x := by
rw [continuousOn_iff_continuous_restrict] at hf hg
obtain ⟨b, h⟩ :=
@intermediate_value_univ₂_eventually₂ _ _ _ _ _ _ (Subtype.preconnectedSpace hs) _ _
(comap_coe_neBot_of_le_principal hl₁) (comap_coe_neBot_of_le_principal hl₂) _ _ hf hg
(he₁.comap _) (he₂.comap _)
exact ⟨b, b.prop, h⟩
#align is_preconnected.intermediate_value₂_eventually₂ IsPreconnected.intermediate_value₂_eventually₂
/-- **Intermediate Value Theorem** for continuous functions on connected sets. -/
theorem IsPreconnected.intermediate_value {s : Set X} (hs : IsPreconnected s) {a b : X} (ha : a ∈ s)
(hb : b ∈ s) {f : X → α} (hf : ContinuousOn f s) : Icc (f a) (f b) ⊆ f '' s := fun _x hx =>
hs.intermediate_value₂ ha hb hf continuousOn_const hx.1 hx.2
#align is_preconnected.intermediate_value IsPreconnected.intermediate_value
theorem IsPreconnected.intermediate_value_Ico {s : Set X} (hs : IsPreconnected s) {a : X}
{l : Filter X} (ha : a ∈ s) [NeBot l] (hl : l ≤ 𝓟 s) {f : X → α} (hf : ContinuousOn f s) {v : α}
(ht : Tendsto f l (𝓝 v)) : Ico (f a) v ⊆ f '' s := fun _ h =>
hs.intermediate_value₂_eventually₁ ha hl hf continuousOn_const h.1
(eventually_ge_of_tendsto_gt h.2 ht)
#align is_preconnected.intermediate_value_Ico IsPreconnected.intermediate_value_Ico
theorem IsPreconnected.intermediate_value_Ioc {s : Set X} (hs : IsPreconnected s) {a : X}
{l : Filter X} (ha : a ∈ s) [NeBot l] (hl : l ≤ 𝓟 s) {f : X → α} (hf : ContinuousOn f s) {v : α}
(ht : Tendsto f l (𝓝 v)) : Ioc v (f a) ⊆ f '' s := fun _ h =>
(hs.intermediate_value₂_eventually₁ ha hl continuousOn_const hf h.2
(eventually_le_of_tendsto_lt h.1 ht)).imp fun _ h => h.imp_right Eq.symm
#align is_preconnected.intermediate_value_Ioc IsPreconnected.intermediate_value_Ioc
theorem IsPreconnected.intermediate_value_Ioo {s : Set X} (hs : IsPreconnected s) {l₁ l₂ : Filter X}
[NeBot l₁] [NeBot l₂] (hl₁ : l₁ ≤ 𝓟 s) (hl₂ : l₂ ≤ 𝓟 s) {f : X → α} (hf : ContinuousOn f s)
{v₁ v₂ : α} (ht₁ : Tendsto f l₁ (𝓝 v₁)) (ht₂ : Tendsto f l₂ (𝓝 v₂)) :
Ioo v₁ v₂ ⊆ f '' s := fun _ h =>
hs.intermediate_value₂_eventually₂ hl₁ hl₂ hf continuousOn_const
(eventually_le_of_tendsto_lt h.1 ht₁) (eventually_ge_of_tendsto_gt h.2 ht₂)
#align is_preconnected.intermediate_value_Ioo IsPreconnected.intermediate_value_Ioo
theorem IsPreconnected.intermediate_value_Ici {s : Set X} (hs : IsPreconnected s) {a : X}
{l : Filter X} (ha : a ∈ s) [NeBot l] (hl : l ≤ 𝓟 s) {f : X → α} (hf : ContinuousOn f s)
(ht : Tendsto f l atTop) : Ici (f a) ⊆ f '' s := fun y h =>
hs.intermediate_value₂_eventually₁ ha hl hf continuousOn_const h (tendsto_atTop.1 ht y)
#align is_preconnected.intermediate_value_Ici IsPreconnected.intermediate_value_Ici
theorem IsPreconnected.intermediate_value_Iic {s : Set X} (hs : IsPreconnected s) {a : X}
{l : Filter X} (ha : a ∈ s) [NeBot l] (hl : l ≤ 𝓟 s) {f : X → α} (hf : ContinuousOn f s)
(ht : Tendsto f l atBot) : Iic (f a) ⊆ f '' s := fun y h =>
(hs.intermediate_value₂_eventually₁ ha hl continuousOn_const hf h (tendsto_atBot.1 ht y)).imp
fun _ h => h.imp_right Eq.symm
#align is_preconnected.intermediate_value_Iic IsPreconnected.intermediate_value_Iic
theorem IsPreconnected.intermediate_value_Ioi {s : Set X} (hs : IsPreconnected s) {l₁ l₂ : Filter X}
[NeBot l₁] [NeBot l₂] (hl₁ : l₁ ≤ 𝓟 s) (hl₂ : l₂ ≤ 𝓟 s) {f : X → α} (hf : ContinuousOn f s)
{v : α} (ht₁ : Tendsto f l₁ (𝓝 v)) (ht₂ : Tendsto f l₂ atTop) : Ioi v ⊆ f '' s := fun y h =>
hs.intermediate_value₂_eventually₂ hl₁ hl₂ hf continuousOn_const
(eventually_le_of_tendsto_lt h ht₁) (tendsto_atTop.1 ht₂ y)
#align is_preconnected.intermediate_value_Ioi IsPreconnected.intermediate_value_Ioi
theorem IsPreconnected.intermediate_value_Iio {s : Set X} (hs : IsPreconnected s) {l₁ l₂ : Filter X}
[NeBot l₁] [NeBot l₂] (hl₁ : l₁ ≤ 𝓟 s) (hl₂ : l₂ ≤ 𝓟 s) {f : X → α} (hf : ContinuousOn f s)
{v : α} (ht₁ : Tendsto f l₁ atBot) (ht₂ : Tendsto f l₂ (𝓝 v)) : Iio v ⊆ f '' s := fun y h =>
hs.intermediate_value₂_eventually₂ hl₁ hl₂ hf continuousOn_const (tendsto_atBot.1 ht₁ y)
(eventually_ge_of_tendsto_gt h ht₂)
#align is_preconnected.intermediate_value_Iio IsPreconnected.intermediate_value_Iio
theorem IsPreconnected.intermediate_value_Iii {s : Set X} (hs : IsPreconnected s) {l₁ l₂ : Filter X}
[NeBot l₁] [NeBot l₂] (hl₁ : l₁ ≤ 𝓟 s) (hl₂ : l₂ ≤ 𝓟 s) {f : X → α} (hf : ContinuousOn f s)
(ht₁ : Tendsto f l₁ atBot) (ht₂ : Tendsto f l₂ atTop) : univ ⊆ f '' s := fun y _ =>
hs.intermediate_value₂_eventually₂ hl₁ hl₂ hf continuousOn_const (tendsto_atBot.1 ht₁ y)
(tendsto_atTop.1 ht₂ y)
set_option linter.uppercaseLean3 false in
#align is_preconnected.intermediate_value_Iii IsPreconnected.intermediate_value_Iii
/-- **Intermediate Value Theorem** for continuous functions on connected spaces. -/
theorem intermediate_value_univ [PreconnectedSpace X] (a b : X) {f : X → α} (hf : Continuous f) :
Icc (f a) (f b) ⊆ range f := fun _ hx => intermediate_value_univ₂ hf continuous_const hx.1 hx.2
#align intermediate_value_univ intermediate_value_univ
/-- **Intermediate Value Theorem** for continuous functions on connected spaces. -/
theorem mem_range_of_exists_le_of_exists_ge [PreconnectedSpace X] {c : α} {f : X → α}
(hf : Continuous f) (h₁ : ∃ a, f a ≤ c) (h₂ : ∃ b, c ≤ f b) : c ∈ range f :=
let ⟨a, ha⟩ := h₁; let ⟨b, hb⟩ := h₂; intermediate_value_univ a b hf ⟨ha, hb⟩
#align mem_range_of_exists_le_of_exists_ge mem_range_of_exists_le_of_exists_ge
/-!
### (Pre)connected sets in a linear order
In this section we prove the following results:
* `IsPreconnected.ordConnected`: any preconnected set `s` in a linear order is `OrdConnected`,
i.e. `a ∈ s` and `b ∈ s` imply `Icc a b ⊆ s`;
* `IsPreconnected.mem_intervals`: any preconnected set `s` in a conditionally complete linear order
is one of the intervals `Set.Icc`, `set.`Ico`, `set.Ioc`, `set.Ioo`, ``Set.Ici`, `Set.Iic`,
`Set.Ioi`, `Set.Iio`; note that this is false for non-complete orders: e.g., in `ℝ \ {0}`, the set
of positive numbers cannot be represented as `Set.Ioi _`.
-/
/-- If a preconnected set contains endpoints of an interval, then it includes the whole interval. -/
theorem IsPreconnected.Icc_subset {s : Set α} (hs : IsPreconnected s) {a b : α} (ha : a ∈ s)
(hb : b ∈ s) : Icc a b ⊆ s := by
simpa only [image_id] using hs.intermediate_value ha hb continuousOn_id
#align is_preconnected.Icc_subset IsPreconnected.Icc_subset
theorem IsPreconnected.ordConnected {s : Set α} (h : IsPreconnected s) : OrdConnected s :=
⟨fun _ hx _ hy => h.Icc_subset hx hy⟩
#align is_preconnected.ord_connected IsPreconnected.ordConnected
/-- If a preconnected set contains endpoints of an interval, then it includes the whole interval. -/
theorem IsConnected.Icc_subset {s : Set α} (hs : IsConnected s) {a b : α} (ha : a ∈ s)
(hb : b ∈ s) : Icc a b ⊆ s :=
hs.2.Icc_subset ha hb
#align is_connected.Icc_subset IsConnected.Icc_subset
/-- If preconnected set in a linear order space is unbounded below and above, then it is the whole
space. -/
theorem IsPreconnected.eq_univ_of_unbounded {s : Set α} (hs : IsPreconnected s) (hb : ¬BddBelow s)
(ha : ¬BddAbove s) : s = univ := by
refine eq_univ_of_forall fun x => ?_
obtain ⟨y, ys, hy⟩ : ∃ y ∈ s, y < x := not_bddBelow_iff.1 hb x
obtain ⟨z, zs, hz⟩ : ∃ z ∈ s, x < z := not_bddAbove_iff.1 ha x
exact hs.Icc_subset ys zs ⟨le_of_lt hy, le_of_lt hz⟩
#align is_preconnected.eq_univ_of_unbounded IsPreconnected.eq_univ_of_unbounded
end
variable {α : Type u} {β : Type v} {γ : Type w} [ConditionallyCompleteLinearOrder α]
[TopologicalSpace α] [OrderTopology α] [ConditionallyCompleteLinearOrder β] [TopologicalSpace β]
[OrderTopology β] [Nonempty γ]
/-- A bounded connected subset of a conditionally complete linear order includes the open interval
`(Inf s, Sup s)`. -/
theorem IsConnected.Ioo_csInf_csSup_subset {s : Set α} (hs : IsConnected s) (hb : BddBelow s)
(ha : BddAbove s) : Ioo (sInf s) (sSup s) ⊆ s := fun _x hx =>
let ⟨_y, ys, hy⟩ := (isGLB_lt_iff (isGLB_csInf hs.nonempty hb)).1 hx.1
let ⟨_z, zs, hz⟩ := (lt_isLUB_iff (isLUB_csSup hs.nonempty ha)).1 hx.2
hs.Icc_subset ys zs ⟨hy.le, hz.le⟩
#align is_connected.Ioo_cInf_cSup_subset IsConnected.Ioo_csInf_csSup_subset
theorem eq_Icc_csInf_csSup_of_connected_bdd_closed {s : Set α} (hc : IsConnected s)
(hb : BddBelow s) (ha : BddAbove s) (hcl : IsClosed s) : s = Icc (sInf s) (sSup s) :=
(subset_Icc_csInf_csSup hb ha).antisymm <|
hc.Icc_subset (hcl.csInf_mem hc.nonempty hb) (hcl.csSup_mem hc.nonempty ha)
#align eq_Icc_cInf_cSup_of_connected_bdd_closed eq_Icc_csInf_csSup_of_connected_bdd_closed
theorem IsPreconnected.Ioi_csInf_subset {s : Set α} (hs : IsPreconnected s) (hb : BddBelow s)
(ha : ¬BddAbove s) : Ioi (sInf s) ⊆ s := fun x hx =>
have sne : s.Nonempty := nonempty_of_not_bddAbove ha
let ⟨_y, ys, hy⟩ : ∃ y ∈ s, y < x := (isGLB_lt_iff (isGLB_csInf sne hb)).1 hx
let ⟨_z, zs, hz⟩ : ∃ z ∈ s, x < z := not_bddAbove_iff.1 ha x
hs.Icc_subset ys zs ⟨hy.le, hz.le⟩
#align is_preconnected.Ioi_cInf_subset IsPreconnected.Ioi_csInf_subset
theorem IsPreconnected.Iio_csSup_subset {s : Set α} (hs : IsPreconnected s) (hb : ¬BddBelow s)
(ha : BddAbove s) : Iio (sSup s) ⊆ s :=
IsPreconnected.Ioi_csInf_subset (α := αᵒᵈ) hs ha hb
#align is_preconnected.Iio_cSup_subset IsPreconnected.Iio_csSup_subset
/-- A preconnected set in a conditionally complete linear order is either one of the intervals
`[Inf s, Sup s]`, `[Inf s, Sup s)`, `(Inf s, Sup s]`, `(Inf s, Sup s)`, `[Inf s, +∞)`,
`(Inf s, +∞)`, `(-∞, Sup s]`, `(-∞, Sup s)`, `(-∞, +∞)`, or `∅`. The converse statement requires
`α` to be densely ordered. -/
theorem IsPreconnected.mem_intervals {s : Set α} (hs : IsPreconnected s) :
s ∈
({Icc (sInf s) (sSup s), Ico (sInf s) (sSup s), Ioc (sInf s) (sSup s), Ioo (sInf s) (sSup s),
Ici (sInf s), Ioi (sInf s), Iic (sSup s), Iio (sSup s), univ, ∅} : Set (Set α)) := by
rcases s.eq_empty_or_nonempty with (rfl | hne)
· apply_rules [Or.inr, mem_singleton]
have hs' : IsConnected s := ⟨hne, hs⟩
by_cases hb : BddBelow s <;> by_cases ha : BddAbove s
· refine mem_of_subset_of_mem ?_ <| mem_Icc_Ico_Ioc_Ioo_of_subset_of_subset
(hs'.Ioo_csInf_csSup_subset hb ha) (subset_Icc_csInf_csSup hb ha)
simp only [insert_subset_iff, mem_insert_iff, mem_singleton_iff, true_or, or_true,
singleton_subset_iff, and_self]
· refine Or.inr <| Or.inr <| Or.inr <| Or.inr ?_
cases'
mem_Ici_Ioi_of_subset_of_subset (hs.Ioi_csInf_subset hb ha) fun x hx => csInf_le hb hx with
hs hs
· exact Or.inl hs
· exact Or.inr (Or.inl hs)
· iterate 6 apply Or.inr
cases' mem_Iic_Iio_of_subset_of_subset (hs.Iio_csSup_subset hb ha) fun x hx => le_csSup ha hx
with hs hs
· exact Or.inl hs
· exact Or.inr (Or.inl hs)
· iterate 8 apply Or.inr
exact Or.inl (hs.eq_univ_of_unbounded hb ha)
#align is_preconnected.mem_intervals IsPreconnected.mem_intervals
/-- A preconnected set is either one of the intervals `Icc`, `Ico`, `Ioc`, `Ioo`, `Ici`, `Ioi`,
`Iic`, `Iio`, or `univ`, or `∅`. The converse statement requires `α` to be densely ordered. Though
one can represent `∅` as `(Inf ∅, Inf ∅)`, we include it into the list of possible cases to improve
readability. -/
theorem setOf_isPreconnected_subset_of_ordered :
{ s : Set α | IsPreconnected s } ⊆
-- bounded intervals
(range (uncurry Icc) ∪ range (uncurry Ico) ∪ range (uncurry Ioc) ∪ range (uncurry Ioo)) ∪
-- unbounded intervals and `univ`
(range Ici ∪ range Ioi ∪ range Iic ∪ range Iio ∪ {univ, ∅}) := by
intro s hs
rcases hs.mem_intervals with (hs | hs | hs | hs | hs | hs | hs | hs | hs | hs) <;> rw [hs] <;>
simp only [union_insert, union_singleton, mem_insert_iff, mem_union, mem_range, Prod.exists,
uncurry_apply_pair, exists_apply_eq_apply, true_or, or_true, exists_apply_eq_apply2]
#align set_of_is_preconnected_subset_of_ordered setOf_isPreconnected_subset_of_ordered
/-!
### Intervals are connected
In this section we prove that a closed interval (hence, any `OrdConnected` set) in a dense
conditionally complete linear order is preconnected.
-/
/-- A "continuous induction principle" for a closed interval: if a set `s` meets `[a, b]`
on a closed subset, contains `a`, and the set `s ∩ [a, b)` has no maximal point, then `b ∈ s`. -/
theorem IsClosed.mem_of_ge_of_forall_exists_gt {a b : α} {s : Set α} (hs : IsClosed (s ∩ Icc a b))
(ha : a ∈ s) (hab : a ≤ b) (hgt : ∀ x ∈ s ∩ Ico a b, (s ∩ Ioc x b).Nonempty) : b ∈ s := by
let S := s ∩ Icc a b
replace ha : a ∈ S := ⟨ha, left_mem_Icc.2 hab⟩
have Sbd : BddAbove S := ⟨b, fun z hz => hz.2.2⟩
let c := sSup (s ∩ Icc a b)
have c_mem : c ∈ S := hs.csSup_mem ⟨_, ha⟩ Sbd
have c_le : c ≤ b := csSup_le ⟨_, ha⟩ fun x hx => hx.2.2
cases' eq_or_lt_of_le c_le with hc hc
· exact hc ▸ c_mem.1
exfalso
rcases hgt c ⟨c_mem.1, c_mem.2.1, hc⟩ with ⟨x, xs, cx, xb⟩
exact not_lt_of_le (le_csSup Sbd ⟨xs, le_trans (le_csSup Sbd ha) (le_of_lt cx), xb⟩) cx
#align is_closed.mem_of_ge_of_forall_exists_gt IsClosed.mem_of_ge_of_forall_exists_gt
/-- A "continuous induction principle" for a closed interval: if a set `s` meets `[a, b]`
on a closed subset, contains `a`, and for any `a ≤ x < y ≤ b`, `x ∈ s`, the set `s ∩ (x, y]`
is not empty, then `[a, b] ⊆ s`. -/
theorem IsClosed.Icc_subset_of_forall_exists_gt {a b : α} {s : Set α} (hs : IsClosed (s ∩ Icc a b))
(ha : a ∈ s) (hgt : ∀ x ∈ s ∩ Ico a b, ∀ y ∈ Ioi x, (s ∩ Ioc x y).Nonempty) : Icc a b ⊆ s := by
intro y hy
have : IsClosed (s ∩ Icc a y) := by
suffices s ∩ Icc a y = s ∩ Icc a b ∩ Icc a y by
rw [this]
exact IsClosed.inter hs isClosed_Icc
rw [inter_assoc]
congr
exact (inter_eq_self_of_subset_right <| Icc_subset_Icc_right hy.2).symm
exact
IsClosed.mem_of_ge_of_forall_exists_gt this ha hy.1 fun x hx =>
hgt x ⟨hx.1, Ico_subset_Ico_right hy.2 hx.2⟩ y hx.2.2
#align is_closed.Icc_subset_of_forall_exists_gt IsClosed.Icc_subset_of_forall_exists_gt
variable [DenselyOrdered α] {a b : α}
/-- A "continuous induction principle" for a closed interval: if a set `s` meets `[a, b]`
on a closed subset, contains `a`, and for any `x ∈ s ∩ [a, b)` the set `s` includes some open
neighborhood of `x` within `(x, +∞)`, then `[a, b] ⊆ s`. -/
theorem IsClosed.Icc_subset_of_forall_mem_nhdsWithin {a b : α} {s : Set α}
(hs : IsClosed (s ∩ Icc a b)) (ha : a ∈ s) (hgt : ∀ x ∈ s ∩ Ico a b, s ∈ 𝓝[>] x) :
Icc a b ⊆ s := by
apply hs.Icc_subset_of_forall_exists_gt ha
rintro x ⟨hxs, hxab⟩ y hyxb
have : s ∩ Ioc x y ∈ 𝓝[>] x :=
inter_mem (hgt x ⟨hxs, hxab⟩) (Ioc_mem_nhdsWithin_Ioi ⟨le_rfl, hyxb⟩)
exact (nhdsWithin_Ioi_self_neBot' ⟨b, hxab.2⟩).nonempty_of_mem this
#align is_closed.Icc_subset_of_forall_mem_nhds_within IsClosed.Icc_subset_of_forall_mem_nhdsWithin
theorem isPreconnected_Icc_aux (x y : α) (s t : Set α) (hxy : x ≤ y) (hs : IsClosed s)
(ht : IsClosed t) (hab : Icc a b ⊆ s ∪ t) (hx : x ∈ Icc a b ∩ s) (hy : y ∈ Icc a b ∩ t) :
(Icc a b ∩ (s ∩ t)).Nonempty := by
have xyab : Icc x y ⊆ Icc a b := Icc_subset_Icc hx.1.1 hy.1.2
by_contra hst
suffices Icc x y ⊆ s from
hst ⟨y, xyab <| right_mem_Icc.2 hxy, this <| right_mem_Icc.2 hxy, hy.2⟩
apply (IsClosed.inter hs isClosed_Icc).Icc_subset_of_forall_mem_nhdsWithin hx.2
rintro z ⟨zs, hz⟩
have zt : z ∈ tᶜ := fun zt => hst ⟨z, xyab <| Ico_subset_Icc_self hz, zs, zt⟩
have : tᶜ ∩ Ioc z y ∈ 𝓝[>] z := by
rw [← nhdsWithin_Ioc_eq_nhdsWithin_Ioi hz.2]
exact mem_nhdsWithin.2 ⟨tᶜ, ht.isOpen_compl, zt, Subset.rfl⟩
apply mem_of_superset this
have : Ioc z y ⊆ s ∪ t := fun w hw => hab (xyab ⟨le_trans hz.1 (le_of_lt hw.1), hw.2⟩)
exact fun w ⟨wt, wzy⟩ => (this wzy).elim id fun h => (wt h).elim
#align is_preconnected_Icc_aux isPreconnected_Icc_aux
/-- A closed interval in a densely ordered conditionally complete linear order is preconnected. -/
theorem isPreconnected_Icc : IsPreconnected (Icc a b) :=
isPreconnected_closed_iff.2
(by
rintro s t hs ht hab ⟨x, hx⟩ ⟨y, hy⟩
-- This used to use `wlog`, but it was causing timeouts.
rcases le_total x y with h | h
· exact isPreconnected_Icc_aux x y s t h hs ht hab hx hy
· rw [inter_comm s t]
rw [union_comm s t] at hab
exact isPreconnected_Icc_aux y x t s h ht hs hab hy hx)
#align is_preconnected_Icc isPreconnected_Icc
theorem isPreconnected_uIcc : IsPreconnected (uIcc a b) :=
isPreconnected_Icc
#align is_preconnected_uIcc isPreconnected_uIcc
theorem Set.OrdConnected.isPreconnected {s : Set α} (h : s.OrdConnected) : IsPreconnected s :=
isPreconnected_of_forall_pair fun x hx y hy =>
⟨uIcc x y, h.uIcc_subset hx hy, left_mem_uIcc, right_mem_uIcc, isPreconnected_uIcc⟩
#align set.ord_connected.is_preconnected Set.OrdConnected.isPreconnected
theorem isPreconnected_iff_ordConnected {s : Set α} : IsPreconnected s ↔ OrdConnected s :=
⟨IsPreconnected.ordConnected, Set.OrdConnected.isPreconnected⟩
#align is_preconnected_iff_ord_connected isPreconnected_iff_ordConnected
theorem isPreconnected_Ici : IsPreconnected (Ici a) :=
ordConnected_Ici.isPreconnected
#align is_preconnected_Ici isPreconnected_Ici
theorem isPreconnected_Iic : IsPreconnected (Iic a) :=
ordConnected_Iic.isPreconnected
#align is_preconnected_Iic isPreconnected_Iic
theorem isPreconnected_Iio : IsPreconnected (Iio a) :=
ordConnected_Iio.isPreconnected
#align is_preconnected_Iio isPreconnected_Iio
theorem isPreconnected_Ioi : IsPreconnected (Ioi a) :=
ordConnected_Ioi.isPreconnected
#align is_preconnected_Ioi isPreconnected_Ioi
theorem isPreconnected_Ioo : IsPreconnected (Ioo a b) :=
ordConnected_Ioo.isPreconnected
#align is_preconnected_Ioo isPreconnected_Ioo
theorem isPreconnected_Ioc : IsPreconnected (Ioc a b) :=
ordConnected_Ioc.isPreconnected
#align is_preconnected_Ioc isPreconnected_Ioc
theorem isPreconnected_Ico : IsPreconnected (Ico a b) :=
ordConnected_Ico.isPreconnected
#align is_preconnected_Ico isPreconnected_Ico
theorem isConnected_Ici : IsConnected (Ici a) :=
⟨nonempty_Ici, isPreconnected_Ici⟩
#align is_connected_Ici isConnected_Ici
theorem isConnected_Iic : IsConnected (Iic a) :=
⟨nonempty_Iic, isPreconnected_Iic⟩
#align is_connected_Iic isConnected_Iic
theorem isConnected_Ioi [NoMaxOrder α] : IsConnected (Ioi a) :=
⟨nonempty_Ioi, isPreconnected_Ioi⟩
#align is_connected_Ioi isConnected_Ioi
theorem isConnected_Iio [NoMinOrder α] : IsConnected (Iio a) :=
⟨nonempty_Iio, isPreconnected_Iio⟩
#align is_connected_Iio isConnected_Iio
theorem isConnected_Icc (h : a ≤ b) : IsConnected (Icc a b) :=
⟨nonempty_Icc.2 h, isPreconnected_Icc⟩
#align is_connected_Icc isConnected_Icc
theorem isConnected_Ioo (h : a < b) : IsConnected (Ioo a b) :=
⟨nonempty_Ioo.2 h, isPreconnected_Ioo⟩
#align is_connected_Ioo isConnected_Ioo
theorem isConnected_Ioc (h : a < b) : IsConnected (Ioc a b) :=
⟨nonempty_Ioc.2 h, isPreconnected_Ioc⟩
#align is_connected_Ioc isConnected_Ioc
theorem isConnected_Ico (h : a < b) : IsConnected (Ico a b) :=
⟨nonempty_Ico.2 h, isPreconnected_Ico⟩
#align is_connected_Ico isConnected_Ico
instance (priority := 100) ordered_connected_space : PreconnectedSpace α :=
⟨ordConnected_univ.isPreconnected⟩
#align ordered_connected_space ordered_connected_space
/-- In a dense conditionally complete linear order, the set of preconnected sets is exactly
the set of the intervals `Icc`, `Ico`, `Ioc`, `Ioo`, `Ici`, `Ioi`, `Iic`, `Iio`, `(-∞, +∞)`,
or `∅`. Though one can represent `∅` as `(sInf s, sInf s)`, we include it into the list of
possible cases to improve readability. -/
theorem setOf_isPreconnected_eq_of_ordered :
{ s : Set α | IsPreconnected s } =
-- bounded intervals
range (uncurry Icc) ∪ range (uncurry Ico) ∪ range (uncurry Ioc) ∪ range (uncurry Ioo) ∪
-- unbounded intervals and `univ`
(range Ici ∪ range Ioi ∪ range Iic ∪ range Iio ∪ {univ, ∅}) := by
refine Subset.antisymm setOf_isPreconnected_subset_of_ordered ?_
simp only [subset_def, forall_mem_range, uncurry, or_imp, forall_and, mem_union,
mem_setOf_eq, insert_eq, mem_singleton_iff, forall_eq, forall_true_iff, and_true_iff,
isPreconnected_Icc, isPreconnected_Ico, isPreconnected_Ioc, isPreconnected_Ioo,
isPreconnected_Ioi, isPreconnected_Iio, isPreconnected_Ici, isPreconnected_Iic,
isPreconnected_univ, isPreconnected_empty]
#align set_of_is_preconnected_eq_of_ordered setOf_isPreconnected_eq_of_ordered
/-- This lemmas characterizes when a subset `s` of a densely ordered conditionally complete linear
order is totally disconnected with respect to the order topology: between any two distinct points
of `s` must lie a point not in `s`. -/
lemma isTotallyDisconnected_iff_lt {s : Set α} :
IsTotallyDisconnected s ↔ ∀ x ∈ s, ∀ y ∈ s, x < y → ∃ z ∉ s, z ∈ Ioo x y := by
simp only [IsTotallyDisconnected, isPreconnected_iff_ordConnected, ← not_nontrivial_iff,
nontrivial_iff_exists_lt, not_exists, not_and]
refine ⟨fun h x hx y hy hxy ↦ ?_, fun h t hts ht x hx y hy hxy ↦ ?_⟩
· simp_rw [← not_ordConnected_inter_Icc_iff hx hy]
exact fun hs ↦ h _ inter_subset_left hs _ ⟨hx, le_rfl, hxy.le⟩ _ ⟨hy, hxy.le, le_rfl⟩ hxy
· obtain ⟨z, h1z, h2z⟩ := h x (hts hx) y (hts hy) hxy
exact h1z <| hts <| ht.1 hx hy ⟨h2z.1.le, h2z.2.le⟩
/-!
### Intermediate Value Theorem on an interval
In this section we prove several versions of the Intermediate Value Theorem for a function
continuous on an interval.
-/
variable {δ : Type*} [LinearOrder δ] [TopologicalSpace δ] [OrderClosedTopology δ]
/-- **Intermediate Value Theorem** for continuous functions on closed intervals, case
`f a ≤ t ≤ f b`. -/
theorem intermediate_value_Icc {a b : α} (hab : a ≤ b) {f : α → δ} (hf : ContinuousOn f (Icc a b)) :
Icc (f a) (f b) ⊆ f '' Icc a b :=
isPreconnected_Icc.intermediate_value (left_mem_Icc.2 hab) (right_mem_Icc.2 hab) hf
#align intermediate_value_Icc intermediate_value_Icc
/-- **Intermediate Value Theorem** for continuous functions on closed intervals, case
`f a ≥ t ≥ f b`. -/
theorem intermediate_value_Icc' {a b : α} (hab : a ≤ b) {f : α → δ}
(hf : ContinuousOn f (Icc a b)) : Icc (f b) (f a) ⊆ f '' Icc a b :=
isPreconnected_Icc.intermediate_value (right_mem_Icc.2 hab) (left_mem_Icc.2 hab) hf
#align intermediate_value_Icc' intermediate_value_Icc'
/-- **Intermediate Value Theorem** for continuous functions on closed intervals, unordered case. -/
| Mathlib/Topology/Order/IntermediateValue.lean | 546 | 548 | theorem intermediate_value_uIcc {a b : α} {f : α → δ} (hf : ContinuousOn f (uIcc a b)) :
uIcc (f a) (f b) ⊆ f '' uIcc a b := by |
cases le_total (f a) (f b) <;> simp [*, isPreconnected_uIcc.intermediate_value]
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro, Patrick Massot
-/
import Mathlib.Topology.Maps
import Mathlib.Topology.NhdsSet
#align_import topology.constructions from "leanprover-community/mathlib"@"f7ebde7ee0d1505dfccac8644ae12371aa3c1c9f"
/-!
# Constructions of new topological spaces from old ones
This file constructs products, sums, subtypes and quotients of topological spaces
and sets up their basic theory, such as criteria for maps into or out of these
constructions to be continuous; descriptions of the open sets, neighborhood filters,
and generators of these constructions; and their behavior with respect to embeddings
and other specific classes of maps.
## Implementation note
The constructed topologies are defined using induced and coinduced topologies
along with the complete lattice structure on topologies. Their universal properties
(for example, a map `X → Y × Z` is continuous if and only if both projections
`X → Y`, `X → Z` are) follow easily using order-theoretic descriptions of
continuity. With more work we can also extract descriptions of the open sets,
neighborhood filters and so on.
## Tags
product, sum, disjoint union, subspace, quotient space
-/
noncomputable section
open scoped Classical
open Topology TopologicalSpace Set Filter Function
universe u v
variable {X : Type u} {Y : Type v} {Z W ε ζ : Type*}
section Constructions
instance instTopologicalSpaceSubtype {p : X → Prop} [t : TopologicalSpace X] :
TopologicalSpace (Subtype p) :=
induced (↑) t
instance {r : X → X → Prop} [t : TopologicalSpace X] : TopologicalSpace (Quot r) :=
coinduced (Quot.mk r) t
instance instTopologicalSpaceQuotient {s : Setoid X} [t : TopologicalSpace X] :
TopologicalSpace (Quotient s) :=
coinduced Quotient.mk' t
instance instTopologicalSpaceProd [t₁ : TopologicalSpace X] [t₂ : TopologicalSpace Y] :
TopologicalSpace (X × Y) :=
induced Prod.fst t₁ ⊓ induced Prod.snd t₂
instance instTopologicalSpaceSum [t₁ : TopologicalSpace X] [t₂ : TopologicalSpace Y] :
TopologicalSpace (X ⊕ Y) :=
coinduced Sum.inl t₁ ⊔ coinduced Sum.inr t₂
instance instTopologicalSpaceSigma {ι : Type*} {X : ι → Type v} [t₂ : ∀ i, TopologicalSpace (X i)] :
TopologicalSpace (Sigma X) :=
⨆ i, coinduced (Sigma.mk i) (t₂ i)
instance Pi.topologicalSpace {ι : Type*} {Y : ι → Type v} [t₂ : (i : ι) → TopologicalSpace (Y i)] :
TopologicalSpace ((i : ι) → Y i) :=
⨅ i, induced (fun f => f i) (t₂ i)
#align Pi.topological_space Pi.topologicalSpace
instance ULift.topologicalSpace [t : TopologicalSpace X] : TopologicalSpace (ULift.{v, u} X) :=
t.induced ULift.down
#align ulift.topological_space ULift.topologicalSpace
/-!
### `Additive`, `Multiplicative`
The topology on those type synonyms is inherited without change.
-/
section
variable [TopologicalSpace X]
open Additive Multiplicative
instance : TopologicalSpace (Additive X) := ‹TopologicalSpace X›
instance : TopologicalSpace (Multiplicative X) := ‹TopologicalSpace X›
instance [DiscreteTopology X] : DiscreteTopology (Additive X) := ‹DiscreteTopology X›
instance [DiscreteTopology X] : DiscreteTopology (Multiplicative X) := ‹DiscreteTopology X›
theorem continuous_ofMul : Continuous (ofMul : X → Additive X) := continuous_id
#align continuous_of_mul continuous_ofMul
theorem continuous_toMul : Continuous (toMul : Additive X → X) := continuous_id
#align continuous_to_mul continuous_toMul
theorem continuous_ofAdd : Continuous (ofAdd : X → Multiplicative X) := continuous_id
#align continuous_of_add continuous_ofAdd
theorem continuous_toAdd : Continuous (toAdd : Multiplicative X → X) := continuous_id
#align continuous_to_add continuous_toAdd
theorem isOpenMap_ofMul : IsOpenMap (ofMul : X → Additive X) := IsOpenMap.id
#align is_open_map_of_mul isOpenMap_ofMul
theorem isOpenMap_toMul : IsOpenMap (toMul : Additive X → X) := IsOpenMap.id
#align is_open_map_to_mul isOpenMap_toMul
theorem isOpenMap_ofAdd : IsOpenMap (ofAdd : X → Multiplicative X) := IsOpenMap.id
#align is_open_map_of_add isOpenMap_ofAdd
theorem isOpenMap_toAdd : IsOpenMap (toAdd : Multiplicative X → X) := IsOpenMap.id
#align is_open_map_to_add isOpenMap_toAdd
theorem isClosedMap_ofMul : IsClosedMap (ofMul : X → Additive X) := IsClosedMap.id
#align is_closed_map_of_mul isClosedMap_ofMul
theorem isClosedMap_toMul : IsClosedMap (toMul : Additive X → X) := IsClosedMap.id
#align is_closed_map_to_mul isClosedMap_toMul
theorem isClosedMap_ofAdd : IsClosedMap (ofAdd : X → Multiplicative X) := IsClosedMap.id
#align is_closed_map_of_add isClosedMap_ofAdd
theorem isClosedMap_toAdd : IsClosedMap (toAdd : Multiplicative X → X) := IsClosedMap.id
#align is_closed_map_to_add isClosedMap_toAdd
theorem nhds_ofMul (x : X) : 𝓝 (ofMul x) = map ofMul (𝓝 x) := rfl
#align nhds_of_mul nhds_ofMul
theorem nhds_ofAdd (x : X) : 𝓝 (ofAdd x) = map ofAdd (𝓝 x) := rfl
#align nhds_of_add nhds_ofAdd
theorem nhds_toMul (x : Additive X) : 𝓝 (toMul x) = map toMul (𝓝 x) := rfl
#align nhds_to_mul nhds_toMul
theorem nhds_toAdd (x : Multiplicative X) : 𝓝 (toAdd x) = map toAdd (𝓝 x) := rfl
#align nhds_to_add nhds_toAdd
end
/-!
### Order dual
The topology on this type synonym is inherited without change.
-/
section
variable [TopologicalSpace X]
open OrderDual
instance : TopologicalSpace Xᵒᵈ := ‹TopologicalSpace X›
instance [DiscreteTopology X] : DiscreteTopology Xᵒᵈ := ‹DiscreteTopology X›
theorem continuous_toDual : Continuous (toDual : X → Xᵒᵈ) := continuous_id
#align continuous_to_dual continuous_toDual
theorem continuous_ofDual : Continuous (ofDual : Xᵒᵈ → X) := continuous_id
#align continuous_of_dual continuous_ofDual
theorem isOpenMap_toDual : IsOpenMap (toDual : X → Xᵒᵈ) := IsOpenMap.id
#align is_open_map_to_dual isOpenMap_toDual
theorem isOpenMap_ofDual : IsOpenMap (ofDual : Xᵒᵈ → X) := IsOpenMap.id
#align is_open_map_of_dual isOpenMap_ofDual
theorem isClosedMap_toDual : IsClosedMap (toDual : X → Xᵒᵈ) := IsClosedMap.id
#align is_closed_map_to_dual isClosedMap_toDual
theorem isClosedMap_ofDual : IsClosedMap (ofDual : Xᵒᵈ → X) := IsClosedMap.id
#align is_closed_map_of_dual isClosedMap_ofDual
theorem nhds_toDual (x : X) : 𝓝 (toDual x) = map toDual (𝓝 x) := rfl
#align nhds_to_dual nhds_toDual
theorem nhds_ofDual (x : X) : 𝓝 (ofDual x) = map ofDual (𝓝 x) := rfl
#align nhds_of_dual nhds_ofDual
end
theorem Quotient.preimage_mem_nhds [TopologicalSpace X] [s : Setoid X] {V : Set <| Quotient s}
{x : X} (hs : V ∈ 𝓝 (Quotient.mk' x)) : Quotient.mk' ⁻¹' V ∈ 𝓝 x :=
preimage_nhds_coinduced hs
#align quotient.preimage_mem_nhds Quotient.preimage_mem_nhds
/-- The image of a dense set under `Quotient.mk'` is a dense set. -/
theorem Dense.quotient [Setoid X] [TopologicalSpace X] {s : Set X} (H : Dense s) :
Dense (Quotient.mk' '' s) :=
Quotient.surjective_Quotient_mk''.denseRange.dense_image continuous_coinduced_rng H
#align dense.quotient Dense.quotient
/-- The composition of `Quotient.mk'` and a function with dense range has dense range. -/
theorem DenseRange.quotient [Setoid X] [TopologicalSpace X] {f : Y → X} (hf : DenseRange f) :
DenseRange (Quotient.mk' ∘ f) :=
Quotient.surjective_Quotient_mk''.denseRange.comp hf continuous_coinduced_rng
#align dense_range.quotient DenseRange.quotient
theorem continuous_map_of_le {α : Type*} [TopologicalSpace α]
{s t : Setoid α} (h : s ≤ t) : Continuous (Setoid.map_of_le h) :=
continuous_coinduced_rng
theorem continuous_map_sInf {α : Type*} [TopologicalSpace α]
{S : Set (Setoid α)} {s : Setoid α} (h : s ∈ S) : Continuous (Setoid.map_sInf h) :=
continuous_coinduced_rng
instance {p : X → Prop} [TopologicalSpace X] [DiscreteTopology X] : DiscreteTopology (Subtype p) :=
⟨bot_unique fun s _ => ⟨(↑) '' s, isOpen_discrete _, preimage_image_eq _ Subtype.val_injective⟩⟩
instance Sum.discreteTopology [TopologicalSpace X] [TopologicalSpace Y] [h : DiscreteTopology X]
[hY : DiscreteTopology Y] : DiscreteTopology (X ⊕ Y) :=
⟨sup_eq_bot_iff.2 <| by simp [h.eq_bot, hY.eq_bot]⟩
#align sum.discrete_topology Sum.discreteTopology
instance Sigma.discreteTopology {ι : Type*} {Y : ι → Type v} [∀ i, TopologicalSpace (Y i)]
[h : ∀ i, DiscreteTopology (Y i)] : DiscreteTopology (Sigma Y) :=
⟨iSup_eq_bot.2 fun _ => by simp only [(h _).eq_bot, coinduced_bot]⟩
#align sigma.discrete_topology Sigma.discreteTopology
section Top
variable [TopologicalSpace X]
/-
The 𝓝 filter and the subspace topology.
-/
theorem mem_nhds_subtype (s : Set X) (x : { x // x ∈ s }) (t : Set { x // x ∈ s }) :
t ∈ 𝓝 x ↔ ∃ u ∈ 𝓝 (x : X), Subtype.val ⁻¹' u ⊆ t :=
mem_nhds_induced _ x t
#align mem_nhds_subtype mem_nhds_subtype
theorem nhds_subtype (s : Set X) (x : { x // x ∈ s }) : 𝓝 x = comap (↑) (𝓝 (x : X)) :=
nhds_induced _ x
#align nhds_subtype nhds_subtype
theorem nhdsWithin_subtype_eq_bot_iff {s t : Set X} {x : s} :
𝓝[((↑) : s → X) ⁻¹' t] x = ⊥ ↔ 𝓝[t] (x : X) ⊓ 𝓟 s = ⊥ := by
rw [inf_principal_eq_bot_iff_comap, nhdsWithin, nhdsWithin, comap_inf, comap_principal,
nhds_induced]
#align nhds_within_subtype_eq_bot_iff nhdsWithin_subtype_eq_bot_iff
theorem nhds_ne_subtype_eq_bot_iff {S : Set X} {x : S} :
𝓝[≠] x = ⊥ ↔ 𝓝[≠] (x : X) ⊓ 𝓟 S = ⊥ := by
rw [← nhdsWithin_subtype_eq_bot_iff, preimage_compl, ← image_singleton,
Subtype.coe_injective.preimage_image]
#align nhds_ne_subtype_eq_bot_iff nhds_ne_subtype_eq_bot_iff
theorem nhds_ne_subtype_neBot_iff {S : Set X} {x : S} :
(𝓝[≠] x).NeBot ↔ (𝓝[≠] (x : X) ⊓ 𝓟 S).NeBot := by
rw [neBot_iff, neBot_iff, not_iff_not, nhds_ne_subtype_eq_bot_iff]
#align nhds_ne_subtype_ne_bot_iff nhds_ne_subtype_neBot_iff
theorem discreteTopology_subtype_iff {S : Set X} :
DiscreteTopology S ↔ ∀ x ∈ S, 𝓝[≠] x ⊓ 𝓟 S = ⊥ := by
simp_rw [discreteTopology_iff_nhds_ne, SetCoe.forall', nhds_ne_subtype_eq_bot_iff]
#align discrete_topology_subtype_iff discreteTopology_subtype_iff
end Top
/-- A type synonym equipped with the topology whose open sets are the empty set and the sets with
finite complements. -/
def CofiniteTopology (X : Type*) := X
#align cofinite_topology CofiniteTopology
namespace CofiniteTopology
/-- The identity equivalence between `` and `CofiniteTopology `. -/
def of : X ≃ CofiniteTopology X :=
Equiv.refl X
#align cofinite_topology.of CofiniteTopology.of
instance [Inhabited X] : Inhabited (CofiniteTopology X) where default := of default
instance : TopologicalSpace (CofiniteTopology X) where
IsOpen s := s.Nonempty → Set.Finite sᶜ
isOpen_univ := by simp
isOpen_inter s t := by
rintro hs ht ⟨x, hxs, hxt⟩
rw [compl_inter]
exact (hs ⟨x, hxs⟩).union (ht ⟨x, hxt⟩)
isOpen_sUnion := by
rintro s h ⟨x, t, hts, hzt⟩
rw [compl_sUnion]
exact Finite.sInter (mem_image_of_mem _ hts) (h t hts ⟨x, hzt⟩)
theorem isOpen_iff {s : Set (CofiniteTopology X)} : IsOpen s ↔ s.Nonempty → sᶜ.Finite :=
Iff.rfl
#align cofinite_topology.is_open_iff CofiniteTopology.isOpen_iff
theorem isOpen_iff' {s : Set (CofiniteTopology X)} : IsOpen s ↔ s = ∅ ∨ sᶜ.Finite := by
simp only [isOpen_iff, nonempty_iff_ne_empty, or_iff_not_imp_left]
#align cofinite_topology.is_open_iff' CofiniteTopology.isOpen_iff'
theorem isClosed_iff {s : Set (CofiniteTopology X)} : IsClosed s ↔ s = univ ∨ s.Finite := by
simp only [← isOpen_compl_iff, isOpen_iff', compl_compl, compl_empty_iff]
#align cofinite_topology.is_closed_iff CofiniteTopology.isClosed_iff
theorem nhds_eq (x : CofiniteTopology X) : 𝓝 x = pure x ⊔ cofinite := by
ext U
rw [mem_nhds_iff]
constructor
· rintro ⟨V, hVU, V_op, haV⟩
exact mem_sup.mpr ⟨hVU haV, mem_of_superset (V_op ⟨_, haV⟩) hVU⟩
· rintro ⟨hU : x ∈ U, hU' : Uᶜ.Finite⟩
exact ⟨U, Subset.rfl, fun _ => hU', hU⟩
#align cofinite_topology.nhds_eq CofiniteTopology.nhds_eq
theorem mem_nhds_iff {x : CofiniteTopology X} {s : Set (CofiniteTopology X)} :
s ∈ 𝓝 x ↔ x ∈ s ∧ sᶜ.Finite := by simp [nhds_eq]
#align cofinite_topology.mem_nhds_iff CofiniteTopology.mem_nhds_iff
end CofiniteTopology
end Constructions
section Prod
variable [TopologicalSpace X] [TopologicalSpace Y] [TopologicalSpace Z] [TopologicalSpace W]
[TopologicalSpace ε] [TopologicalSpace ζ]
-- Porting note (#11215): TODO: Lean 4 fails to deduce implicit args
@[simp] theorem continuous_prod_mk {f : X → Y} {g : X → Z} :
(Continuous fun x => (f x, g x)) ↔ Continuous f ∧ Continuous g :=
(@continuous_inf_rng X (Y × Z) _ _ (TopologicalSpace.induced Prod.fst _)
(TopologicalSpace.induced Prod.snd _)).trans <|
continuous_induced_rng.and continuous_induced_rng
#align continuous_prod_mk continuous_prod_mk
@[continuity]
theorem continuous_fst : Continuous (@Prod.fst X Y) :=
(continuous_prod_mk.1 continuous_id).1
#align continuous_fst continuous_fst
/-- Postcomposing `f` with `Prod.fst` is continuous -/
@[fun_prop]
theorem Continuous.fst {f : X → Y × Z} (hf : Continuous f) : Continuous fun x : X => (f x).1 :=
continuous_fst.comp hf
#align continuous.fst Continuous.fst
/-- Precomposing `f` with `Prod.fst` is continuous -/
theorem Continuous.fst' {f : X → Z} (hf : Continuous f) : Continuous fun x : X × Y => f x.fst :=
hf.comp continuous_fst
#align continuous.fst' Continuous.fst'
theorem continuousAt_fst {p : X × Y} : ContinuousAt Prod.fst p :=
continuous_fst.continuousAt
#align continuous_at_fst continuousAt_fst
/-- Postcomposing `f` with `Prod.fst` is continuous at `x` -/
@[fun_prop]
theorem ContinuousAt.fst {f : X → Y × Z} {x : X} (hf : ContinuousAt f x) :
ContinuousAt (fun x : X => (f x).1) x :=
continuousAt_fst.comp hf
#align continuous_at.fst ContinuousAt.fst
/-- Precomposing `f` with `Prod.fst` is continuous at `(x, y)` -/
theorem ContinuousAt.fst' {f : X → Z} {x : X} {y : Y} (hf : ContinuousAt f x) :
ContinuousAt (fun x : X × Y => f x.fst) (x, y) :=
ContinuousAt.comp hf continuousAt_fst
#align continuous_at.fst' ContinuousAt.fst'
/-- Precomposing `f` with `Prod.fst` is continuous at `x : X × Y` -/
theorem ContinuousAt.fst'' {f : X → Z} {x : X × Y} (hf : ContinuousAt f x.fst) :
ContinuousAt (fun x : X × Y => f x.fst) x :=
hf.comp continuousAt_fst
#align continuous_at.fst'' ContinuousAt.fst''
theorem Filter.Tendsto.fst_nhds {l : Filter X} {f : X → Y × Z} {p : Y × Z}
(h : Tendsto f l (𝓝 p)) : Tendsto (fun a ↦ (f a).1) l (𝓝 <| p.1) :=
continuousAt_fst.tendsto.comp h
@[continuity]
theorem continuous_snd : Continuous (@Prod.snd X Y) :=
(continuous_prod_mk.1 continuous_id).2
#align continuous_snd continuous_snd
/-- Postcomposing `f` with `Prod.snd` is continuous -/
@[fun_prop]
theorem Continuous.snd {f : X → Y × Z} (hf : Continuous f) : Continuous fun x : X => (f x).2 :=
continuous_snd.comp hf
#align continuous.snd Continuous.snd
/-- Precomposing `f` with `Prod.snd` is continuous -/
theorem Continuous.snd' {f : Y → Z} (hf : Continuous f) : Continuous fun x : X × Y => f x.snd :=
hf.comp continuous_snd
#align continuous.snd' Continuous.snd'
theorem continuousAt_snd {p : X × Y} : ContinuousAt Prod.snd p :=
continuous_snd.continuousAt
#align continuous_at_snd continuousAt_snd
/-- Postcomposing `f` with `Prod.snd` is continuous at `x` -/
@[fun_prop]
theorem ContinuousAt.snd {f : X → Y × Z} {x : X} (hf : ContinuousAt f x) :
ContinuousAt (fun x : X => (f x).2) x :=
continuousAt_snd.comp hf
#align continuous_at.snd ContinuousAt.snd
/-- Precomposing `f` with `Prod.snd` is continuous at `(x, y)` -/
theorem ContinuousAt.snd' {f : Y → Z} {x : X} {y : Y} (hf : ContinuousAt f y) :
ContinuousAt (fun x : X × Y => f x.snd) (x, y) :=
ContinuousAt.comp hf continuousAt_snd
#align continuous_at.snd' ContinuousAt.snd'
/-- Precomposing `f` with `Prod.snd` is continuous at `x : X × Y` -/
theorem ContinuousAt.snd'' {f : Y → Z} {x : X × Y} (hf : ContinuousAt f x.snd) :
ContinuousAt (fun x : X × Y => f x.snd) x :=
hf.comp continuousAt_snd
#align continuous_at.snd'' ContinuousAt.snd''
theorem Filter.Tendsto.snd_nhds {l : Filter X} {f : X → Y × Z} {p : Y × Z}
(h : Tendsto f l (𝓝 p)) : Tendsto (fun a ↦ (f a).2) l (𝓝 <| p.2) :=
continuousAt_snd.tendsto.comp h
@[continuity, fun_prop]
theorem Continuous.prod_mk {f : Z → X} {g : Z → Y} (hf : Continuous f) (hg : Continuous g) :
Continuous fun x => (f x, g x) :=
continuous_prod_mk.2 ⟨hf, hg⟩
#align continuous.prod_mk Continuous.prod_mk
@[continuity]
theorem Continuous.Prod.mk (x : X) : Continuous fun y : Y => (x, y) :=
continuous_const.prod_mk continuous_id
#align continuous.prod.mk Continuous.Prod.mk
@[continuity]
theorem Continuous.Prod.mk_left (y : Y) : Continuous fun x : X => (x, y) :=
continuous_id.prod_mk continuous_const
#align continuous.prod.mk_left Continuous.Prod.mk_left
/-- If `f x y` is continuous in `x` for all `y ∈ s`,
then the set of `x` such that `f x` maps `s` to `t` is closed. -/
lemma IsClosed.setOf_mapsTo {α : Type*} {f : X → α → Z} {s : Set α} {t : Set Z} (ht : IsClosed t)
(hf : ∀ a ∈ s, Continuous (f · a)) : IsClosed {x | MapsTo (f x) s t} := by
simpa only [MapsTo, setOf_forall] using isClosed_biInter fun y hy ↦ ht.preimage (hf y hy)
theorem Continuous.comp₂ {g : X × Y → Z} (hg : Continuous g) {e : W → X} (he : Continuous e)
{f : W → Y} (hf : Continuous f) : Continuous fun w => g (e w, f w) :=
hg.comp <| he.prod_mk hf
#align continuous.comp₂ Continuous.comp₂
theorem Continuous.comp₃ {g : X × Y × Z → ε} (hg : Continuous g) {e : W → X} (he : Continuous e)
{f : W → Y} (hf : Continuous f) {k : W → Z} (hk : Continuous k) :
Continuous fun w => g (e w, f w, k w) :=
hg.comp₂ he <| hf.prod_mk hk
#align continuous.comp₃ Continuous.comp₃
theorem Continuous.comp₄ {g : X × Y × Z × ζ → ε} (hg : Continuous g) {e : W → X} (he : Continuous e)
{f : W → Y} (hf : Continuous f) {k : W → Z} (hk : Continuous k) {l : W → ζ}
(hl : Continuous l) : Continuous fun w => g (e w, f w, k w, l w) :=
hg.comp₃ he hf <| hk.prod_mk hl
#align continuous.comp₄ Continuous.comp₄
@[continuity]
theorem Continuous.prod_map {f : Z → X} {g : W → Y} (hf : Continuous f) (hg : Continuous g) :
Continuous fun p : Z × W => (f p.1, g p.2) :=
hf.fst'.prod_mk hg.snd'
#align continuous.prod_map Continuous.prod_map
/-- A version of `continuous_inf_dom_left` for binary functions -/
theorem continuous_inf_dom_left₂ {X Y Z} {f : X → Y → Z} {ta1 ta2 : TopologicalSpace X}
{tb1 tb2 : TopologicalSpace Y} {tc1 : TopologicalSpace Z}
(h : by haveI := ta1; haveI := tb1; exact Continuous fun p : X × Y => f p.1 p.2) : by
haveI := ta1 ⊓ ta2; haveI := tb1 ⊓ tb2; exact Continuous fun p : X × Y => f p.1 p.2 := by
have ha := @continuous_inf_dom_left _ _ id ta1 ta2 ta1 (@continuous_id _ (id _))
have hb := @continuous_inf_dom_left _ _ id tb1 tb2 tb1 (@continuous_id _ (id _))
have h_continuous_id := @Continuous.prod_map _ _ _ _ ta1 tb1 (ta1 ⊓ ta2) (tb1 ⊓ tb2) _ _ ha hb
exact @Continuous.comp _ _ _ (id _) (id _) _ _ _ h h_continuous_id
#align continuous_inf_dom_left₂ continuous_inf_dom_left₂
/-- A version of `continuous_inf_dom_right` for binary functions -/
theorem continuous_inf_dom_right₂ {X Y Z} {f : X → Y → Z} {ta1 ta2 : TopologicalSpace X}
{tb1 tb2 : TopologicalSpace Y} {tc1 : TopologicalSpace Z}
(h : by haveI := ta2; haveI := tb2; exact Continuous fun p : X × Y => f p.1 p.2) : by
haveI := ta1 ⊓ ta2; haveI := tb1 ⊓ tb2; exact Continuous fun p : X × Y => f p.1 p.2 := by
have ha := @continuous_inf_dom_right _ _ id ta1 ta2 ta2 (@continuous_id _ (id _))
have hb := @continuous_inf_dom_right _ _ id tb1 tb2 tb2 (@continuous_id _ (id _))
have h_continuous_id := @Continuous.prod_map _ _ _ _ ta2 tb2 (ta1 ⊓ ta2) (tb1 ⊓ tb2) _ _ ha hb
exact @Continuous.comp _ _ _ (id _) (id _) _ _ _ h h_continuous_id
#align continuous_inf_dom_right₂ continuous_inf_dom_right₂
/-- A version of `continuous_sInf_dom` for binary functions -/
theorem continuous_sInf_dom₂ {X Y Z} {f : X → Y → Z} {tas : Set (TopologicalSpace X)}
{tbs : Set (TopologicalSpace Y)} {tX : TopologicalSpace X} {tY : TopologicalSpace Y}
{tc : TopologicalSpace Z} (hX : tX ∈ tas) (hY : tY ∈ tbs)
(hf : Continuous fun p : X × Y => f p.1 p.2) : by
haveI := sInf tas; haveI := sInf tbs;
exact @Continuous _ _ _ tc fun p : X × Y => f p.1 p.2 := by
have hX := continuous_sInf_dom hX continuous_id
have hY := continuous_sInf_dom hY continuous_id
have h_continuous_id := @Continuous.prod_map _ _ _ _ tX tY (sInf tas) (sInf tbs) _ _ hX hY
exact @Continuous.comp _ _ _ (id _) (id _) _ _ _ hf h_continuous_id
#align continuous_Inf_dom₂ continuous_sInf_dom₂
theorem Filter.Eventually.prod_inl_nhds {p : X → Prop} {x : X} (h : ∀ᶠ x in 𝓝 x, p x) (y : Y) :
∀ᶠ x in 𝓝 (x, y), p (x : X × Y).1 :=
continuousAt_fst h
#align filter.eventually.prod_inl_nhds Filter.Eventually.prod_inl_nhds
theorem Filter.Eventually.prod_inr_nhds {p : Y → Prop} {y : Y} (h : ∀ᶠ x in 𝓝 y, p x) (x : X) :
∀ᶠ x in 𝓝 (x, y), p (x : X × Y).2 :=
continuousAt_snd h
#align filter.eventually.prod_inr_nhds Filter.Eventually.prod_inr_nhds
theorem Filter.Eventually.prod_mk_nhds {px : X → Prop} {x} (hx : ∀ᶠ x in 𝓝 x, px x) {py : Y → Prop}
{y} (hy : ∀ᶠ y in 𝓝 y, py y) : ∀ᶠ p in 𝓝 (x, y), px (p : X × Y).1 ∧ py p.2 :=
(hx.prod_inl_nhds y).and (hy.prod_inr_nhds x)
#align filter.eventually.prod_mk_nhds Filter.Eventually.prod_mk_nhds
theorem continuous_swap : Continuous (Prod.swap : X × Y → Y × X) :=
continuous_snd.prod_mk continuous_fst
#align continuous_swap continuous_swap
lemma isClosedMap_swap : IsClosedMap (Prod.swap : X × Y → Y × X) := fun s hs ↦ by
rw [image_swap_eq_preimage_swap]
exact hs.preimage continuous_swap
theorem Continuous.uncurry_left {f : X → Y → Z} (x : X) (h : Continuous (uncurry f)) :
Continuous (f x) :=
h.comp (Continuous.Prod.mk _)
#align continuous_uncurry_left Continuous.uncurry_left
theorem Continuous.uncurry_right {f : X → Y → Z} (y : Y) (h : Continuous (uncurry f)) :
Continuous fun a => f a y :=
h.comp (Continuous.Prod.mk_left _)
#align continuous_uncurry_right Continuous.uncurry_right
-- 2024-03-09
@[deprecated] alias continuous_uncurry_left := Continuous.uncurry_left
@[deprecated] alias continuous_uncurry_right := Continuous.uncurry_right
theorem continuous_curry {g : X × Y → Z} (x : X) (h : Continuous g) : Continuous (curry g x) :=
Continuous.uncurry_left x h
#align continuous_curry continuous_curry
theorem IsOpen.prod {s : Set X} {t : Set Y} (hs : IsOpen s) (ht : IsOpen t) : IsOpen (s ×ˢ t) :=
(hs.preimage continuous_fst).inter (ht.preimage continuous_snd)
#align is_open.prod IsOpen.prod
-- Porting note (#11215): TODO: Lean fails to find `t₁` and `t₂` by unification
theorem nhds_prod_eq {x : X} {y : Y} : 𝓝 (x, y) = 𝓝 x ×ˢ 𝓝 y := by
dsimp only [SProd.sprod]
rw [Filter.prod, instTopologicalSpaceProd, nhds_inf (t₁ := TopologicalSpace.induced Prod.fst _)
(t₂ := TopologicalSpace.induced Prod.snd _), nhds_induced, nhds_induced]
#align nhds_prod_eq nhds_prod_eq
-- Porting note: moved from `Topology.ContinuousOn`
theorem nhdsWithin_prod_eq (x : X) (y : Y) (s : Set X) (t : Set Y) :
𝓝[s ×ˢ t] (x, y) = 𝓝[s] x ×ˢ 𝓝[t] y := by
simp only [nhdsWithin, nhds_prod_eq, ← prod_inf_prod, prod_principal_principal]
#align nhds_within_prod_eq nhdsWithin_prod_eq
#noalign continuous_uncurry_of_discrete_topology
| Mathlib/Topology/Constructions.lean | 563 | 564 | theorem mem_nhds_prod_iff {x : X} {y : Y} {s : Set (X × Y)} :
s ∈ 𝓝 (x, y) ↔ ∃ u ∈ 𝓝 x, ∃ v ∈ 𝓝 y, u ×ˢ v ⊆ s := by | rw [nhds_prod_eq, mem_prod_iff]
|
/-
Copyright (c) 2014 Jeremy Avigad. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jeremy Avigad, Leonardo de Moura, Simon Hudon, Mario Carneiro
-/
import Aesop
import Mathlib.Algebra.Group.Defs
import Mathlib.Data.Nat.Defs
import Mathlib.Data.Int.Defs
import Mathlib.Logic.Function.Basic
import Mathlib.Tactic.Cases
import Mathlib.Tactic.SimpRw
import Mathlib.Tactic.SplitIfs
#align_import algebra.group.basic from "leanprover-community/mathlib"@"a07d750983b94c530ab69a726862c2ab6802b38c"
/-!
# Basic lemmas about semigroups, monoids, and groups
This file lists various basic lemmas about semigroups, monoids, and groups. Most proofs are
one-liners from the corresponding axioms. For the definitions of semigroups, monoids and groups, see
`Algebra/Group/Defs.lean`.
-/
assert_not_exists MonoidWithZero
assert_not_exists DenselyOrdered
open Function
universe u
variable {α β G M : Type*}
section ite
variable [Pow α β]
@[to_additive (attr := simp) dite_smul]
lemma pow_dite (p : Prop) [Decidable p] (a : α) (b : p → β) (c : ¬ p → β) :
a ^ (if h : p then b h else c h) = if h : p then a ^ b h else a ^ c h := by split_ifs <;> rfl
@[to_additive (attr := simp) smul_dite]
lemma dite_pow (p : Prop) [Decidable p] (a : p → α) (b : ¬ p → α) (c : β) :
(if h : p then a h else b h) ^ c = if h : p then a h ^ c else b h ^ c := by split_ifs <;> rfl
@[to_additive (attr := simp) ite_smul]
lemma pow_ite (p : Prop) [Decidable p] (a : α) (b c : β) :
a ^ (if p then b else c) = if p then a ^ b else a ^ c := pow_dite _ _ _ _
@[to_additive (attr := simp) smul_ite]
lemma ite_pow (p : Prop) [Decidable p] (a b : α) (c : β) :
(if p then a else b) ^ c = if p then a ^ c else b ^ c := dite_pow _ _ _ _
set_option linter.existingAttributeWarning false in
attribute [to_additive (attr := simp)] dite_smul smul_dite ite_smul smul_ite
end ite
section IsLeftCancelMul
variable [Mul G] [IsLeftCancelMul G]
@[to_additive]
theorem mul_right_injective (a : G) : Injective (a * ·) := fun _ _ ↦ mul_left_cancel
#align mul_right_injective mul_right_injective
#align add_right_injective add_right_injective
@[to_additive (attr := simp)]
theorem mul_right_inj (a : G) {b c : G} : a * b = a * c ↔ b = c :=
(mul_right_injective a).eq_iff
#align mul_right_inj mul_right_inj
#align add_right_inj add_right_inj
@[to_additive]
theorem mul_ne_mul_right (a : G) {b c : G} : a * b ≠ a * c ↔ b ≠ c :=
(mul_right_injective a).ne_iff
#align mul_ne_mul_right mul_ne_mul_right
#align add_ne_add_right add_ne_add_right
end IsLeftCancelMul
section IsRightCancelMul
variable [Mul G] [IsRightCancelMul G]
@[to_additive]
theorem mul_left_injective (a : G) : Function.Injective (· * a) := fun _ _ ↦ mul_right_cancel
#align mul_left_injective mul_left_injective
#align add_left_injective add_left_injective
@[to_additive (attr := simp)]
theorem mul_left_inj (a : G) {b c : G} : b * a = c * a ↔ b = c :=
(mul_left_injective a).eq_iff
#align mul_left_inj mul_left_inj
#align add_left_inj add_left_inj
@[to_additive]
theorem mul_ne_mul_left (a : G) {b c : G} : b * a ≠ c * a ↔ b ≠ c :=
(mul_left_injective a).ne_iff
#align mul_ne_mul_left mul_ne_mul_left
#align add_ne_add_left add_ne_add_left
end IsRightCancelMul
section Semigroup
variable [Semigroup α]
@[to_additive]
instance Semigroup.to_isAssociative : Std.Associative (α := α) (· * ·) := ⟨mul_assoc⟩
#align semigroup.to_is_associative Semigroup.to_isAssociative
#align add_semigroup.to_is_associative AddSemigroup.to_isAssociative
/-- Composing two multiplications on the left by `y` then `x`
is equal to a multiplication on the left by `x * y`.
-/
@[to_additive (attr := simp) "Composing two additions on the left by `y` then `x`
is equal to an addition on the left by `x + y`."]
theorem comp_mul_left (x y : α) : (x * ·) ∘ (y * ·) = (x * y * ·) := by
ext z
simp [mul_assoc]
#align comp_mul_left comp_mul_left
#align comp_add_left comp_add_left
/-- Composing two multiplications on the right by `y` and `x`
is equal to a multiplication on the right by `y * x`.
-/
@[to_additive (attr := simp) "Composing two additions on the right by `y` and `x`
is equal to an addition on the right by `y + x`."]
theorem comp_mul_right (x y : α) : (· * x) ∘ (· * y) = (· * (y * x)) := by
ext z
simp [mul_assoc]
#align comp_mul_right comp_mul_right
#align comp_add_right comp_add_right
end Semigroup
@[to_additive]
instance CommMagma.to_isCommutative [CommMagma G] : Std.Commutative (α := G) (· * ·) := ⟨mul_comm⟩
#align comm_semigroup.to_is_commutative CommMagma.to_isCommutative
#align add_comm_semigroup.to_is_commutative AddCommMagma.to_isCommutative
section MulOneClass
variable {M : Type u} [MulOneClass M]
@[to_additive]
theorem ite_mul_one {P : Prop} [Decidable P] {a b : M} :
ite P (a * b) 1 = ite P a 1 * ite P b 1 := by
by_cases h:P <;> simp [h]
#align ite_mul_one ite_mul_one
#align ite_add_zero ite_add_zero
@[to_additive]
theorem ite_one_mul {P : Prop} [Decidable P] {a b : M} :
ite P 1 (a * b) = ite P 1 a * ite P 1 b := by
by_cases h:P <;> simp [h]
#align ite_one_mul ite_one_mul
#align ite_zero_add ite_zero_add
@[to_additive]
theorem eq_one_iff_eq_one_of_mul_eq_one {a b : M} (h : a * b = 1) : a = 1 ↔ b = 1 := by
constructor <;> (rintro rfl; simpa using h)
#align eq_one_iff_eq_one_of_mul_eq_one eq_one_iff_eq_one_of_mul_eq_one
#align eq_zero_iff_eq_zero_of_add_eq_zero eq_zero_iff_eq_zero_of_add_eq_zero
@[to_additive]
theorem one_mul_eq_id : ((1 : M) * ·) = id :=
funext one_mul
#align one_mul_eq_id one_mul_eq_id
#align zero_add_eq_id zero_add_eq_id
@[to_additive]
theorem mul_one_eq_id : (· * (1 : M)) = id :=
funext mul_one
#align mul_one_eq_id mul_one_eq_id
#align add_zero_eq_id add_zero_eq_id
end MulOneClass
section CommSemigroup
variable [CommSemigroup G]
@[to_additive]
theorem mul_left_comm : ∀ a b c : G, a * (b * c) = b * (a * c) :=
left_comm Mul.mul mul_comm mul_assoc
#align mul_left_comm mul_left_comm
#align add_left_comm add_left_comm
@[to_additive]
theorem mul_right_comm : ∀ a b c : G, a * b * c = a * c * b :=
right_comm Mul.mul mul_comm mul_assoc
#align mul_right_comm mul_right_comm
#align add_right_comm add_right_comm
@[to_additive]
theorem mul_mul_mul_comm (a b c d : G) : a * b * (c * d) = a * c * (b * d) := by
simp only [mul_left_comm, mul_assoc]
#align mul_mul_mul_comm mul_mul_mul_comm
#align add_add_add_comm add_add_add_comm
@[to_additive]
theorem mul_rotate (a b c : G) : a * b * c = b * c * a := by
simp only [mul_left_comm, mul_comm]
#align mul_rotate mul_rotate
#align add_rotate add_rotate
@[to_additive]
theorem mul_rotate' (a b c : G) : a * (b * c) = b * (c * a) := by
simp only [mul_left_comm, mul_comm]
#align mul_rotate' mul_rotate'
#align add_rotate' add_rotate'
end CommSemigroup
section AddCommSemigroup
set_option linter.deprecated false
variable {M : Type u} [AddCommSemigroup M]
theorem bit0_add (a b : M) : bit0 (a + b) = bit0 a + bit0 b :=
add_add_add_comm _ _ _ _
#align bit0_add bit0_add
theorem bit1_add [One M] (a b : M) : bit1 (a + b) = bit0 a + bit1 b :=
(congr_arg (· + (1 : M)) <| bit0_add a b : _).trans (add_assoc _ _ _)
#align bit1_add bit1_add
theorem bit1_add' [One M] (a b : M) : bit1 (a + b) = bit1 a + bit0 b := by
rw [add_comm, bit1_add, add_comm]
#align bit1_add' bit1_add'
end AddCommSemigroup
section AddMonoid
set_option linter.deprecated false
variable {M : Type u} [AddMonoid M] {a b c : M}
@[simp]
theorem bit0_zero : bit0 (0 : M) = 0 :=
add_zero _
#align bit0_zero bit0_zero
@[simp]
theorem bit1_zero [One M] : bit1 (0 : M) = 1 := by rw [bit1, bit0_zero, zero_add]
#align bit1_zero bit1_zero
end AddMonoid
attribute [local simp] mul_assoc sub_eq_add_neg
section Monoid
variable [Monoid M] {a b c : M} {m n : ℕ}
@[to_additive boole_nsmul]
lemma pow_boole (P : Prop) [Decidable P] (a : M) :
(a ^ if P then 1 else 0) = if P then a else 1 := by simp only [pow_ite, pow_one, pow_zero]
#align pow_boole pow_boole
@[to_additive nsmul_add_sub_nsmul]
lemma pow_mul_pow_sub (a : M) (h : m ≤ n) : a ^ m * a ^ (n - m) = a ^ n := by
rw [← pow_add, Nat.add_comm, Nat.sub_add_cancel h]
#align pow_mul_pow_sub pow_mul_pow_sub
#align nsmul_add_sub_nsmul nsmul_add_sub_nsmul
@[to_additive sub_nsmul_nsmul_add]
lemma pow_sub_mul_pow (a : M) (h : m ≤ n) : a ^ (n - m) * a ^ m = a ^ n := by
rw [← pow_add, Nat.sub_add_cancel h]
#align pow_sub_mul_pow pow_sub_mul_pow
#align sub_nsmul_nsmul_add sub_nsmul_nsmul_add
@[to_additive sub_one_nsmul_add]
lemma mul_pow_sub_one (hn : n ≠ 0) (a : M) : a * a ^ (n - 1) = a ^ n := by
rw [← pow_succ', Nat.sub_add_cancel $ Nat.one_le_iff_ne_zero.2 hn]
@[to_additive add_sub_one_nsmul]
lemma pow_sub_one_mul (hn : n ≠ 0) (a : M) : a ^ (n - 1) * a = a ^ n := by
rw [← pow_succ, Nat.sub_add_cancel $ Nat.one_le_iff_ne_zero.2 hn]
/-- If `x ^ n = 1`, then `x ^ m` is the same as `x ^ (m % n)` -/
@[to_additive nsmul_eq_mod_nsmul "If `n • x = 0`, then `m • x` is the same as `(m % n) • x`"]
lemma pow_eq_pow_mod (m : ℕ) (ha : a ^ n = 1) : a ^ m = a ^ (m % n) := by
calc
a ^ m = a ^ (m % n + n * (m / n)) := by rw [Nat.mod_add_div]
_ = a ^ (m % n) := by simp [pow_add, pow_mul, ha]
#align pow_eq_pow_mod pow_eq_pow_mod
#align nsmul_eq_mod_nsmul nsmul_eq_mod_nsmul
@[to_additive] lemma pow_mul_pow_eq_one : ∀ n, a * b = 1 → a ^ n * b ^ n = 1
| 0, _ => by simp
| n + 1, h =>
calc
a ^ n.succ * b ^ n.succ = a ^ n * a * (b * b ^ n) := by rw [pow_succ, pow_succ']
_ = a ^ n * (a * b) * b ^ n := by simp only [mul_assoc]
_ = 1 := by simp [h, pow_mul_pow_eq_one]
#align pow_mul_pow_eq_one pow_mul_pow_eq_one
#align nsmul_add_nsmul_eq_zero nsmul_add_nsmul_eq_zero
end Monoid
section CommMonoid
variable [CommMonoid M] {x y z : M}
@[to_additive]
theorem inv_unique (hy : x * y = 1) (hz : x * z = 1) : y = z :=
left_inv_eq_right_inv (Trans.trans (mul_comm _ _) hy) hz
#align inv_unique inv_unique
#align neg_unique neg_unique
@[to_additive nsmul_add] lemma mul_pow (a b : M) : ∀ n, (a * b) ^ n = a ^ n * b ^ n
| 0 => by rw [pow_zero, pow_zero, pow_zero, one_mul]
| n + 1 => by rw [pow_succ', pow_succ', pow_succ', mul_pow, mul_mul_mul_comm]
#align mul_pow mul_pow
#align nsmul_add nsmul_add
end CommMonoid
section LeftCancelMonoid
variable {M : Type u} [LeftCancelMonoid M] {a b : M}
@[to_additive (attr := simp)]
theorem mul_right_eq_self : a * b = a ↔ b = 1 := calc
a * b = a ↔ a * b = a * 1 := by rw [mul_one]
_ ↔ b = 1 := mul_left_cancel_iff
#align mul_right_eq_self mul_right_eq_self
#align add_right_eq_self add_right_eq_self
@[to_additive (attr := simp)]
theorem self_eq_mul_right : a = a * b ↔ b = 1 :=
eq_comm.trans mul_right_eq_self
#align self_eq_mul_right self_eq_mul_right
#align self_eq_add_right self_eq_add_right
@[to_additive]
theorem mul_right_ne_self : a * b ≠ a ↔ b ≠ 1 := mul_right_eq_self.not
#align mul_right_ne_self mul_right_ne_self
#align add_right_ne_self add_right_ne_self
@[to_additive]
theorem self_ne_mul_right : a ≠ a * b ↔ b ≠ 1 := self_eq_mul_right.not
#align self_ne_mul_right self_ne_mul_right
#align self_ne_add_right self_ne_add_right
end LeftCancelMonoid
section RightCancelMonoid
variable {M : Type u} [RightCancelMonoid M] {a b : M}
@[to_additive (attr := simp)]
theorem mul_left_eq_self : a * b = b ↔ a = 1 := calc
a * b = b ↔ a * b = 1 * b := by rw [one_mul]
_ ↔ a = 1 := mul_right_cancel_iff
#align mul_left_eq_self mul_left_eq_self
#align add_left_eq_self add_left_eq_self
@[to_additive (attr := simp)]
theorem self_eq_mul_left : b = a * b ↔ a = 1 :=
eq_comm.trans mul_left_eq_self
#align self_eq_mul_left self_eq_mul_left
#align self_eq_add_left self_eq_add_left
@[to_additive]
theorem mul_left_ne_self : a * b ≠ b ↔ a ≠ 1 := mul_left_eq_self.not
#align mul_left_ne_self mul_left_ne_self
#align add_left_ne_self add_left_ne_self
@[to_additive]
theorem self_ne_mul_left : b ≠ a * b ↔ a ≠ 1 := self_eq_mul_left.not
#align self_ne_mul_left self_ne_mul_left
#align self_ne_add_left self_ne_add_left
end RightCancelMonoid
section CancelCommMonoid
variable [CancelCommMonoid α] {a b c d : α}
@[to_additive] lemma eq_iff_eq_of_mul_eq_mul (h : a * b = c * d) : a = c ↔ b = d := by aesop
@[to_additive] lemma ne_iff_ne_of_mul_eq_mul (h : a * b = c * d) : a ≠ c ↔ b ≠ d := by aesop
end CancelCommMonoid
section InvolutiveInv
variable [InvolutiveInv G] {a b : G}
@[to_additive (attr := simp)]
theorem inv_involutive : Function.Involutive (Inv.inv : G → G) :=
inv_inv
#align inv_involutive inv_involutive
#align neg_involutive neg_involutive
@[to_additive (attr := simp)]
theorem inv_surjective : Function.Surjective (Inv.inv : G → G) :=
inv_involutive.surjective
#align inv_surjective inv_surjective
#align neg_surjective neg_surjective
@[to_additive]
theorem inv_injective : Function.Injective (Inv.inv : G → G) :=
inv_involutive.injective
#align inv_injective inv_injective
#align neg_injective neg_injective
@[to_additive (attr := simp)]
theorem inv_inj : a⁻¹ = b⁻¹ ↔ a = b :=
inv_injective.eq_iff
#align inv_inj inv_inj
#align neg_inj neg_inj
@[to_additive]
theorem inv_eq_iff_eq_inv : a⁻¹ = b ↔ a = b⁻¹ :=
⟨fun h => h ▸ (inv_inv a).symm, fun h => h.symm ▸ inv_inv b⟩
#align inv_eq_iff_eq_inv inv_eq_iff_eq_inv
#align neg_eq_iff_eq_neg neg_eq_iff_eq_neg
variable (G)
@[to_additive]
theorem inv_comp_inv : Inv.inv ∘ Inv.inv = @id G :=
inv_involutive.comp_self
#align inv_comp_inv inv_comp_inv
#align neg_comp_neg neg_comp_neg
@[to_additive]
theorem leftInverse_inv : LeftInverse (fun a : G ↦ a⁻¹) fun a ↦ a⁻¹ :=
inv_inv
#align left_inverse_inv leftInverse_inv
#align left_inverse_neg leftInverse_neg
@[to_additive]
theorem rightInverse_inv : RightInverse (fun a : G ↦ a⁻¹) fun a ↦ a⁻¹ :=
inv_inv
#align right_inverse_inv rightInverse_inv
#align right_inverse_neg rightInverse_neg
end InvolutiveInv
section DivInvMonoid
variable [DivInvMonoid G] {a b c : G}
@[to_additive, field_simps] -- The attributes are out of order on purpose
theorem inv_eq_one_div (x : G) : x⁻¹ = 1 / x := by rw [div_eq_mul_inv, one_mul]
#align inv_eq_one_div inv_eq_one_div
#align neg_eq_zero_sub neg_eq_zero_sub
@[to_additive]
theorem mul_one_div (x y : G) : x * (1 / y) = x / y := by
rw [div_eq_mul_inv, one_mul, div_eq_mul_inv]
#align mul_one_div mul_one_div
#align add_zero_sub add_zero_sub
@[to_additive]
theorem mul_div_assoc (a b c : G) : a * b / c = a * (b / c) := by
rw [div_eq_mul_inv, div_eq_mul_inv, mul_assoc _ _ _]
#align mul_div_assoc mul_div_assoc
#align add_sub_assoc add_sub_assoc
@[to_additive, field_simps] -- The attributes are out of order on purpose
theorem mul_div_assoc' (a b c : G) : a * (b / c) = a * b / c :=
(mul_div_assoc _ _ _).symm
#align mul_div_assoc' mul_div_assoc'
#align add_sub_assoc' add_sub_assoc'
@[to_additive (attr := simp)]
theorem one_div (a : G) : 1 / a = a⁻¹ :=
(inv_eq_one_div a).symm
#align one_div one_div
#align zero_sub zero_sub
@[to_additive]
theorem mul_div (a b c : G) : a * (b / c) = a * b / c := by simp only [mul_assoc, div_eq_mul_inv]
#align mul_div mul_div
#align add_sub add_sub
@[to_additive]
theorem div_eq_mul_one_div (a b : G) : a / b = a * (1 / b) := by rw [div_eq_mul_inv, one_div]
#align div_eq_mul_one_div div_eq_mul_one_div
#align sub_eq_add_zero_sub sub_eq_add_zero_sub
end DivInvMonoid
section DivInvOneMonoid
variable [DivInvOneMonoid G]
@[to_additive (attr := simp)]
theorem div_one (a : G) : a / 1 = a := by simp [div_eq_mul_inv]
#align div_one div_one
#align sub_zero sub_zero
@[to_additive]
theorem one_div_one : (1 : G) / 1 = 1 :=
div_one _
#align one_div_one one_div_one
#align zero_sub_zero zero_sub_zero
end DivInvOneMonoid
section DivisionMonoid
variable [DivisionMonoid α] {a b c d : α}
attribute [local simp] mul_assoc div_eq_mul_inv
@[to_additive]
theorem eq_inv_of_mul_eq_one_right (h : a * b = 1) : b = a⁻¹ :=
(inv_eq_of_mul_eq_one_right h).symm
#align eq_inv_of_mul_eq_one_right eq_inv_of_mul_eq_one_right
#align eq_neg_of_add_eq_zero_right eq_neg_of_add_eq_zero_right
@[to_additive]
theorem eq_one_div_of_mul_eq_one_left (h : b * a = 1) : b = 1 / a := by
rw [eq_inv_of_mul_eq_one_left h, one_div]
#align eq_one_div_of_mul_eq_one_left eq_one_div_of_mul_eq_one_left
#align eq_zero_sub_of_add_eq_zero_left eq_zero_sub_of_add_eq_zero_left
@[to_additive]
theorem eq_one_div_of_mul_eq_one_right (h : a * b = 1) : b = 1 / a := by
rw [eq_inv_of_mul_eq_one_right h, one_div]
#align eq_one_div_of_mul_eq_one_right eq_one_div_of_mul_eq_one_right
#align eq_zero_sub_of_add_eq_zero_right eq_zero_sub_of_add_eq_zero_right
@[to_additive]
theorem eq_of_div_eq_one (h : a / b = 1) : a = b :=
inv_injective <| inv_eq_of_mul_eq_one_right <| by rwa [← div_eq_mul_inv]
#align eq_of_div_eq_one eq_of_div_eq_one
#align eq_of_sub_eq_zero eq_of_sub_eq_zero
lemma eq_of_inv_mul_eq_one (h : a⁻¹ * b = 1) : a = b := by simpa using eq_inv_of_mul_eq_one_left h
lemma eq_of_mul_inv_eq_one (h : a * b⁻¹ = 1) : a = b := by simpa using eq_inv_of_mul_eq_one_left h
@[to_additive]
theorem div_ne_one_of_ne : a ≠ b → a / b ≠ 1 :=
mt eq_of_div_eq_one
#align div_ne_one_of_ne div_ne_one_of_ne
#align sub_ne_zero_of_ne sub_ne_zero_of_ne
variable (a b c)
@[to_additive]
theorem one_div_mul_one_div_rev : 1 / a * (1 / b) = 1 / (b * a) := by simp
#align one_div_mul_one_div_rev one_div_mul_one_div_rev
#align zero_sub_add_zero_sub_rev zero_sub_add_zero_sub_rev
@[to_additive]
theorem inv_div_left : a⁻¹ / b = (b * a)⁻¹ := by simp
#align inv_div_left inv_div_left
#align neg_sub_left neg_sub_left
@[to_additive (attr := simp)]
theorem inv_div : (a / b)⁻¹ = b / a := by simp
#align inv_div inv_div
#align neg_sub neg_sub
@[to_additive]
theorem one_div_div : 1 / (a / b) = b / a := by simp
#align one_div_div one_div_div
#align zero_sub_sub zero_sub_sub
@[to_additive]
| Mathlib/Algebra/Group/Basic.lean | 564 | 564 | theorem one_div_one_div : 1 / (1 / a) = a := by | simp
|
/-
Copyright (c) 2015 Jeremy Avigad. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jeremy Avigad, Robert Y. Lewis, Yury G. Kudryashov
-/
import Mathlib.Algebra.Order.Monoid.OrderDual
import Mathlib.Tactic.Lift
import Mathlib.Tactic.Monotonicity.Attr
/-!
# Lemmas about the interaction of power operations with order in terms of `CovariantClass`
-/
open Function
variable {β G M : Type*}
section Monoid
variable [Monoid M]
section Preorder
variable [Preorder M]
section Left
variable [CovariantClass M M (· * ·) (· ≤ ·)] {x : M}
@[to_additive (attr := mono, gcongr) nsmul_le_nsmul_right]
theorem pow_le_pow_left' [CovariantClass M M (swap (· * ·)) (· ≤ ·)] {a b : M} (hab : a ≤ b) :
∀ i : ℕ, a ^ i ≤ b ^ i
| 0 => by simp
| k + 1 => by
rw [pow_succ, pow_succ]
exact mul_le_mul' (pow_le_pow_left' hab k) hab
#align pow_le_pow_of_le_left' pow_le_pow_left'
#align nsmul_le_nsmul_of_le_right nsmul_le_nsmul_right
@[to_additive nsmul_nonneg]
theorem one_le_pow_of_one_le' {a : M} (H : 1 ≤ a) : ∀ n : ℕ, 1 ≤ a ^ n
| 0 => by simp
| k + 1 => by
rw [pow_succ]
exact one_le_mul (one_le_pow_of_one_le' H k) H
#align one_le_pow_of_one_le' one_le_pow_of_one_le'
#align nsmul_nonneg nsmul_nonneg
@[to_additive nsmul_nonpos]
theorem pow_le_one' {a : M} (H : a ≤ 1) (n : ℕ) : a ^ n ≤ 1 :=
@one_le_pow_of_one_le' Mᵒᵈ _ _ _ _ H n
#align pow_le_one' pow_le_one'
#align nsmul_nonpos nsmul_nonpos
@[to_additive (attr := gcongr) nsmul_le_nsmul_left]
theorem pow_le_pow_right' {a : M} {n m : ℕ} (ha : 1 ≤ a) (h : n ≤ m) : a ^ n ≤ a ^ m :=
let ⟨k, hk⟩ := Nat.le.dest h
calc
a ^ n ≤ a ^ n * a ^ k := le_mul_of_one_le_right' (one_le_pow_of_one_le' ha _)
_ = a ^ m := by rw [← hk, pow_add]
#align pow_le_pow' pow_le_pow_right'
#align nsmul_le_nsmul nsmul_le_nsmul_left
@[to_additive nsmul_le_nsmul_left_of_nonpos]
theorem pow_le_pow_right_of_le_one' {a : M} {n m : ℕ} (ha : a ≤ 1) (h : n ≤ m) : a ^ m ≤ a ^ n :=
pow_le_pow_right' (M := Mᵒᵈ) ha h
#align pow_le_pow_of_le_one' pow_le_pow_right_of_le_one'
#align nsmul_le_nsmul_of_nonpos nsmul_le_nsmul_left_of_nonpos
@[to_additive nsmul_pos]
theorem one_lt_pow' {a : M} (ha : 1 < a) {k : ℕ} (hk : k ≠ 0) : 1 < a ^ k := by
rcases Nat.exists_eq_succ_of_ne_zero hk with ⟨l, rfl⟩
clear hk
induction' l with l IH
· rw [pow_succ]; simpa using ha
· rw [pow_succ]
exact one_lt_mul'' IH ha
#align one_lt_pow' one_lt_pow'
#align nsmul_pos nsmul_pos
@[to_additive nsmul_neg]
theorem pow_lt_one' {a : M} (ha : a < 1) {k : ℕ} (hk : k ≠ 0) : a ^ k < 1 :=
@one_lt_pow' Mᵒᵈ _ _ _ _ ha k hk
#align pow_lt_one' pow_lt_one'
#align nsmul_neg nsmul_neg
@[to_additive (attr := gcongr) nsmul_lt_nsmul_left]
theorem pow_lt_pow_right' [CovariantClass M M (· * ·) (· < ·)] {a : M} {n m : ℕ} (ha : 1 < a)
(h : n < m) : a ^ n < a ^ m := by
rcases Nat.le.dest h with ⟨k, rfl⟩; clear h
rw [pow_add, pow_succ, mul_assoc, ← pow_succ']
exact lt_mul_of_one_lt_right' _ (one_lt_pow' ha k.succ_ne_zero)
#align pow_lt_pow_right' pow_lt_pow_right'
#align nsmul_lt_nsmul_left nsmul_lt_nsmul_left
@[to_additive nsmul_left_strictMono]
theorem pow_right_strictMono' [CovariantClass M M (· * ·) (· < ·)] {a : M} (ha : 1 < a) :
StrictMono ((a ^ ·) : ℕ → M) := fun _ _ => pow_lt_pow_right' ha
#align pow_strict_mono_left pow_right_strictMono'
#align nsmul_strict_mono_right nsmul_left_strictMono
@[to_additive Left.pow_nonneg]
theorem Left.one_le_pow_of_le (hx : 1 ≤ x) : ∀ {n : ℕ}, 1 ≤ x ^ n
| 0 => (pow_zero x).ge
| n + 1 => by
rw [pow_succ]
exact Left.one_le_mul (Left.one_le_pow_of_le hx) hx
#align left.one_le_pow_of_le Left.one_le_pow_of_le
#align left.pow_nonneg Left.pow_nonneg
@[to_additive Left.pow_nonpos]
theorem Left.pow_le_one_of_le (hx : x ≤ 1) : ∀ {n : ℕ}, x ^ n ≤ 1
| 0 => (pow_zero _).le
| n + 1 => by
rw [pow_succ]
exact Left.mul_le_one (Left.pow_le_one_of_le hx) hx
#align left.pow_le_one_of_le Left.pow_le_one_of_le
#align left.pow_nonpos Left.pow_nonpos
end Left
section Right
variable [CovariantClass M M (swap (· * ·)) (· ≤ ·)] {x : M}
@[to_additive Right.pow_nonneg]
theorem Right.one_le_pow_of_le (hx : 1 ≤ x) : ∀ {n : ℕ}, 1 ≤ x ^ n
| 0 => (pow_zero _).ge
| n + 1 => by
rw [pow_succ]
exact Right.one_le_mul (Right.one_le_pow_of_le hx) hx
#align right.one_le_pow_of_le Right.one_le_pow_of_le
#align right.pow_nonneg Right.pow_nonneg
@[to_additive Right.pow_nonpos]
theorem Right.pow_le_one_of_le (hx : x ≤ 1) : ∀ {n : ℕ}, x ^ n ≤ 1
| 0 => (pow_zero _).le
| n + 1 => by
rw [pow_succ]
exact Right.mul_le_one (Right.pow_le_one_of_le hx) hx
#align right.pow_le_one_of_le Right.pow_le_one_of_le
#align right.pow_nonpos Right.pow_nonpos
end Right
section CovariantLTSwap
variable [Preorder β] [CovariantClass M M (· * ·) (· < ·)]
[CovariantClass M M (swap (· * ·)) (· < ·)] {f : β → M} {n : ℕ}
@[to_additive StrictMono.const_nsmul]
theorem StrictMono.pow_const (hf : StrictMono f) : ∀ {n : ℕ}, n ≠ 0 → StrictMono (f · ^ n)
| 0, hn => (hn rfl).elim
| 1, _ => by simpa
| Nat.succ <| Nat.succ n, _ => by
simpa only [pow_succ] using (hf.pow_const n.succ_ne_zero).mul' hf
#align strict_mono.pow_const StrictMono.pow_const
#align strict_mono.const_nsmul StrictMono.const_nsmul
/-- See also `pow_left_strictMonoOn`. -/
@[to_additive nsmul_right_strictMono] -- Porting note: nolint to_additive_doc
theorem pow_left_strictMono (hn : n ≠ 0) : StrictMono (· ^ n : M → M) := strictMono_id.pow_const hn
#align pow_strict_mono_right' pow_left_strictMono
#align nsmul_strict_mono_left nsmul_right_strictMono
@[to_additive (attr := mono, gcongr) nsmul_lt_nsmul_right]
lemma pow_lt_pow_left' (hn : n ≠ 0) {a b : M} (hab : a < b) : a ^ n < b ^ n :=
pow_left_strictMono hn hab
end CovariantLTSwap
section CovariantLESwap
variable [Preorder β] [CovariantClass M M (· * ·) (· ≤ ·)]
[CovariantClass M M (swap (· * ·)) (· ≤ ·)]
@[to_additive Monotone.const_nsmul]
theorem Monotone.pow_const {f : β → M} (hf : Monotone f) : ∀ n : ℕ, Monotone fun a => f a ^ n
| 0 => by simpa using monotone_const
| n + 1 => by
simp_rw [pow_succ]
exact (Monotone.pow_const hf _).mul' hf
#align monotone.pow_right Monotone.pow_const
#align monotone.const_nsmul Monotone.const_nsmul
@[to_additive nsmul_right_mono]
theorem pow_left_mono (n : ℕ) : Monotone fun a : M => a ^ n := monotone_id.pow_const _
#align pow_mono_right pow_left_mono
#align nsmul_mono_left nsmul_right_mono
end CovariantLESwap
@[to_additive Left.pow_neg]
theorem Left.pow_lt_one_of_lt [CovariantClass M M (· * ·) (· < ·)] {n : ℕ} {x : M} (hn : 0 < n)
(h : x < 1) : x ^ n < 1 :=
Nat.le_induction ((pow_one _).trans_lt h)
(fun n _ ih => by
rw [pow_succ]
exact mul_lt_one ih h)
_ (Nat.succ_le_iff.2 hn)
#align left.pow_lt_one_of_lt Left.pow_lt_one_of_lt
#align left.pow_neg Left.pow_neg
@[to_additive Right.pow_neg]
theorem Right.pow_lt_one_of_lt [CovariantClass M M (swap (· * ·)) (· < ·)] {n : ℕ} {x : M}
(hn : 0 < n) (h : x < 1) : x ^ n < 1 :=
Nat.le_induction ((pow_one _).trans_lt h)
(fun n _ ih => by
rw [pow_succ]
exact Right.mul_lt_one ih h)
_ (Nat.succ_le_iff.2 hn)
#align right.pow_lt_one_of_lt Right.pow_lt_one_of_lt
#align right.pow_neg Right.pow_neg
end Preorder
section LinearOrder
variable [LinearOrder M]
section CovariantLE
variable [CovariantClass M M (· * ·) (· ≤ ·)]
-- This generalises to lattices. See `pow_two_semiclosed`
@[to_additive nsmul_nonneg_iff]
theorem one_le_pow_iff {x : M} {n : ℕ} (hn : n ≠ 0) : 1 ≤ x ^ n ↔ 1 ≤ x :=
⟨le_imp_le_of_lt_imp_lt fun h => pow_lt_one' h hn, fun h => one_le_pow_of_one_le' h n⟩
#align one_le_pow_iff one_le_pow_iff
#align nsmul_nonneg_iff nsmul_nonneg_iff
@[to_additive]
theorem pow_le_one_iff {x : M} {n : ℕ} (hn : n ≠ 0) : x ^ n ≤ 1 ↔ x ≤ 1 :=
@one_le_pow_iff Mᵒᵈ _ _ _ _ _ hn
#align pow_le_one_iff pow_le_one_iff
#align nsmul_nonpos_iff nsmul_nonpos_iff
@[to_additive nsmul_pos_iff]
theorem one_lt_pow_iff {x : M} {n : ℕ} (hn : n ≠ 0) : 1 < x ^ n ↔ 1 < x :=
lt_iff_lt_of_le_iff_le (pow_le_one_iff hn)
#align one_lt_pow_iff one_lt_pow_iff
#align nsmul_pos_iff nsmul_pos_iff
@[to_additive]
theorem pow_lt_one_iff {x : M} {n : ℕ} (hn : n ≠ 0) : x ^ n < 1 ↔ x < 1 :=
lt_iff_lt_of_le_iff_le (one_le_pow_iff hn)
#align pow_lt_one_iff pow_lt_one_iff
#align nsmul_neg_iff nsmul_neg_iff
@[to_additive]
theorem pow_eq_one_iff {x : M} {n : ℕ} (hn : n ≠ 0) : x ^ n = 1 ↔ x = 1 := by
simp only [le_antisymm_iff]
rw [pow_le_one_iff hn, one_le_pow_iff hn]
#align pow_eq_one_iff pow_eq_one_iff
#align nsmul_eq_zero_iff nsmul_eq_zero_iff
variable [CovariantClass M M (· * ·) (· < ·)] {a : M} {m n : ℕ}
@[to_additive nsmul_le_nsmul_iff_left]
theorem pow_le_pow_iff_right' (ha : 1 < a) : a ^ m ≤ a ^ n ↔ m ≤ n :=
(pow_right_strictMono' ha).le_iff_le
#align pow_le_pow_iff' pow_le_pow_iff_right'
#align nsmul_le_nsmul_iff nsmul_le_nsmul_iff_left
@[to_additive nsmul_lt_nsmul_iff_left]
theorem pow_lt_pow_iff_right' (ha : 1 < a) : a ^ m < a ^ n ↔ m < n :=
(pow_right_strictMono' ha).lt_iff_lt
#align pow_lt_pow_iff' pow_lt_pow_iff_right'
#align nsmul_lt_nsmul_iff nsmul_lt_nsmul_iff_left
end CovariantLE
section CovariantLESwap
variable [CovariantClass M M (· * ·) (· ≤ ·)] [CovariantClass M M (swap (· * ·)) (· ≤ ·)]
@[to_additive lt_of_nsmul_lt_nsmul_right]
theorem lt_of_pow_lt_pow_left' {a b : M} (n : ℕ) : a ^ n < b ^ n → a < b :=
(pow_left_mono _).reflect_lt
#align lt_of_pow_lt_pow' lt_of_pow_lt_pow_left'
#align lt_of_nsmul_lt_nsmul lt_of_nsmul_lt_nsmul_right
@[to_additive min_lt_of_add_lt_two_nsmul]
theorem min_lt_of_mul_lt_sq {a b c : M} (h : a * b < c ^ 2) : min a b < c := by
simpa using min_lt_max_of_mul_lt_mul (h.trans_eq <| pow_two _)
#align min_lt_of_mul_lt_sq min_lt_of_mul_lt_sq
#align min_lt_of_add_lt_two_nsmul min_lt_of_add_lt_two_nsmul
@[to_additive lt_max_of_two_nsmul_lt_add]
theorem lt_max_of_sq_lt_mul {a b c : M} (h : a ^ 2 < b * c) : a < max b c := by
simpa using min_lt_max_of_mul_lt_mul ((pow_two _).symm.trans_lt h)
#align lt_max_of_sq_lt_mul lt_max_of_sq_lt_mul
#align lt_max_of_two_nsmul_lt_add lt_max_of_two_nsmul_lt_add
end CovariantLESwap
section CovariantLTSwap
variable [CovariantClass M M (· * ·) (· < ·)] [CovariantClass M M (swap (· * ·)) (· < ·)]
@[to_additive le_of_nsmul_le_nsmul_right]
theorem le_of_pow_le_pow_left' {a b : M} {n : ℕ} (hn : n ≠ 0) : a ^ n ≤ b ^ n → a ≤ b :=
(pow_left_strictMono hn).le_iff_le.1
#align le_of_pow_le_pow' le_of_pow_le_pow_left'
#align le_of_nsmul_le_nsmul le_of_nsmul_le_nsmul_right
@[to_additive min_le_of_add_le_two_nsmul]
theorem min_le_of_mul_le_sq {a b c : M} (h : a * b ≤ c ^ 2) : min a b ≤ c := by
simpa using min_le_max_of_mul_le_mul (h.trans_eq <| pow_two _)
#align min_le_of_mul_le_sq min_le_of_mul_le_sq
#align min_le_of_add_le_two_nsmul min_le_of_add_le_two_nsmul
@[to_additive le_max_of_two_nsmul_le_add]
theorem le_max_of_sq_le_mul {a b c : M} (h : a ^ 2 ≤ b * c) : a ≤ max b c := by
simpa using min_le_max_of_mul_le_mul ((pow_two _).symm.trans_le h)
#align le_max_of_sq_le_mul le_max_of_sq_le_mul
#align le_max_of_two_nsmul_le_add le_max_of_two_nsmul_le_add
end CovariantLTSwap
@[to_additive Left.nsmul_neg_iff]
theorem Left.pow_lt_one_iff' [CovariantClass M M (· * ·) (· < ·)] {n : ℕ} {x : M} (hn : 0 < n) :
x ^ n < 1 ↔ x < 1 :=
haveI := covariantClass_le_of_lt M M (· * ·)
pow_lt_one_iff hn.ne'
#align left.nsmul_neg_iff Left.nsmul_neg_iff
theorem Left.pow_lt_one_iff [CovariantClass M M (· * ·) (· < ·)] {n : ℕ} {x : M} (hn : 0 < n) :
x ^ n < 1 ↔ x < 1 := Left.pow_lt_one_iff' hn
#align left.pow_lt_one_iff Left.pow_lt_one_iff
@[to_additive]
theorem Right.pow_lt_one_iff [CovariantClass M M (swap (· * ·)) (· < ·)] {n : ℕ} {x : M}
(hn : 0 < n) : x ^ n < 1 ↔ x < 1 :=
⟨fun H =>
not_le.mp fun k =>
haveI := covariantClass_le_of_lt M M (swap (· * ·))
H.not_le <| Right.one_le_pow_of_le k,
Right.pow_lt_one_of_lt hn⟩
#align right.pow_lt_one_iff Right.pow_lt_one_iff
#align right.nsmul_neg_iff Right.nsmul_neg_iff
end LinearOrder
end Monoid
section DivInvMonoid
variable [DivInvMonoid G] [Preorder G] [CovariantClass G G (· * ·) (· ≤ ·)]
@[to_additive zsmul_nonneg]
| Mathlib/Algebra/Order/Monoid/Unbundled/Pow.lean | 352 | 355 | theorem one_le_zpow {x : G} (H : 1 ≤ x) {n : ℤ} (hn : 0 ≤ n) : 1 ≤ x ^ n := by |
lift n to ℕ using hn
rw [zpow_natCast]
apply one_le_pow_of_one_le' H
|
/-
Copyright (c) 2020 Yury G. Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury G. Kudryashov
-/
import Mathlib.Algebra.Group.Pi.Lemmas
import Mathlib.Topology.Algebra.Monoid
import Mathlib.Topology.Homeomorph
#align_import topology.algebra.group_with_zero from "leanprover-community/mathlib"@"c10e724be91096453ee3db13862b9fb9a992fef2"
/-!
# Topological group with zero
In this file we define `HasContinuousInv₀` to be a mixin typeclass a type with `Inv` and
`Zero` (e.g., a `GroupWithZero`) such that `fun x ↦ x⁻¹` is continuous at all nonzero points. Any
normed (semi)field has this property. Currently the only example of `HasContinuousInv₀` in
`mathlib` which is not a normed field is the type `NNReal` (a.k.a. `ℝ≥0`) of nonnegative real
numbers.
Then we prove lemmas about continuity of `x ↦ x⁻¹` and `f / g` providing dot-style `*.inv₀` and
`*.div` operations on `Filter.Tendsto`, `ContinuousAt`, `ContinuousWithinAt`, `ContinuousOn`,
and `Continuous`. As a special case, we provide `*.div_const` operations that require only
`DivInvMonoid` and `ContinuousMul` instances.
All lemmas about `(⁻¹)` use `inv₀` in their names because lemmas without `₀` are used for
`TopologicalGroup`s. We also use `'` in the typeclass name `HasContinuousInv₀` for the sake of
consistency of notation.
On a `GroupWithZero` with continuous multiplication, we also define left and right multiplication
as homeomorphisms.
-/
open Topology Filter Function
/-!
### A `DivInvMonoid` with continuous multiplication
If `G₀` is a `DivInvMonoid` with continuous `(*)`, then `(/y)` is continuous for any `y`. In this
section we prove lemmas that immediately follow from this fact providing `*.div_const` dot-style
operations on `Filter.Tendsto`, `ContinuousAt`, `ContinuousWithinAt`, `ContinuousOn`, and
`Continuous`.
-/
variable {α β G₀ : Type*}
section DivConst
variable [DivInvMonoid G₀] [TopologicalSpace G₀] [ContinuousMul G₀] {f : α → G₀} {s : Set α}
{l : Filter α}
theorem Filter.Tendsto.div_const {x : G₀} (hf : Tendsto f l (𝓝 x)) (y : G₀) :
Tendsto (fun a => f a / y) l (𝓝 (x / y)) := by
simpa only [div_eq_mul_inv] using hf.mul tendsto_const_nhds
#align filter.tendsto.div_const Filter.Tendsto.div_const
variable [TopologicalSpace α]
nonrec theorem ContinuousAt.div_const {a : α} (hf : ContinuousAt f a) (y : G₀) :
ContinuousAt (fun x => f x / y) a :=
hf.div_const y
#align continuous_at.div_const ContinuousAt.div_const
nonrec theorem ContinuousWithinAt.div_const {a} (hf : ContinuousWithinAt f s a) (y : G₀) :
ContinuousWithinAt (fun x => f x / y) s a :=
hf.div_const _
#align continuous_within_at.div_const ContinuousWithinAt.div_const
theorem ContinuousOn.div_const (hf : ContinuousOn f s) (y : G₀) :
ContinuousOn (fun x => f x / y) s := by
simpa only [div_eq_mul_inv] using hf.mul continuousOn_const
#align continuous_on.div_const ContinuousOn.div_const
@[continuity]
theorem Continuous.div_const (hf : Continuous f) (y : G₀) : Continuous fun x => f x / y := by
simpa only [div_eq_mul_inv] using hf.mul continuous_const
#align continuous.div_const Continuous.div_const
end DivConst
/-- A type with `0` and `Inv` such that `fun x ↦ x⁻¹` is continuous at all nonzero points. Any
normed (semi)field has this property. -/
class HasContinuousInv₀ (G₀ : Type*) [Zero G₀] [Inv G₀] [TopologicalSpace G₀] : Prop where
/-- The map `fun x ↦ x⁻¹` is continuous at all nonzero points. -/
continuousAt_inv₀ : ∀ ⦃x : G₀⦄, x ≠ 0 → ContinuousAt Inv.inv x
#align has_continuous_inv₀ HasContinuousInv₀
export HasContinuousInv₀ (continuousAt_inv₀)
section Inv₀
variable [Zero G₀] [Inv G₀] [TopologicalSpace G₀] [HasContinuousInv₀ G₀] {l : Filter α} {f : α → G₀}
{s : Set α} {a : α}
/-!
### Continuity of `fun x ↦ x⁻¹` at a non-zero point
We define `HasContinuousInv₀` to be a `GroupWithZero` such that the operation `x ↦ x⁻¹`
is continuous at all nonzero points. In this section we prove dot-style `*.inv₀` lemmas for
`Filter.Tendsto`, `ContinuousAt`, `ContinuousWithinAt`, `ContinuousOn`, and `Continuous`.
-/
theorem tendsto_inv₀ {x : G₀} (hx : x ≠ 0) : Tendsto Inv.inv (𝓝 x) (𝓝 x⁻¹) :=
continuousAt_inv₀ hx
#align tendsto_inv₀ tendsto_inv₀
theorem continuousOn_inv₀ : ContinuousOn (Inv.inv : G₀ → G₀) {0}ᶜ := fun _x hx =>
(continuousAt_inv₀ hx).continuousWithinAt
#align continuous_on_inv₀ continuousOn_inv₀
/-- If a function converges to a nonzero value, its inverse converges to the inverse of this value.
We use the name `Filter.Tendsto.inv₀` as `Filter.Tendsto.inv` is already used in multiplicative
topological groups. -/
theorem Filter.Tendsto.inv₀ {a : G₀} (hf : Tendsto f l (𝓝 a)) (ha : a ≠ 0) :
Tendsto (fun x => (f x)⁻¹) l (𝓝 a⁻¹) :=
(tendsto_inv₀ ha).comp hf
#align filter.tendsto.inv₀ Filter.Tendsto.inv₀
variable [TopologicalSpace α]
nonrec theorem ContinuousWithinAt.inv₀ (hf : ContinuousWithinAt f s a) (ha : f a ≠ 0) :
ContinuousWithinAt (fun x => (f x)⁻¹) s a :=
hf.inv₀ ha
#align continuous_within_at.inv₀ ContinuousWithinAt.inv₀
@[fun_prop]
nonrec theorem ContinuousAt.inv₀ (hf : ContinuousAt f a) (ha : f a ≠ 0) :
ContinuousAt (fun x => (f x)⁻¹) a :=
hf.inv₀ ha
#align continuous_at.inv₀ ContinuousAt.inv₀
@[continuity, fun_prop]
theorem Continuous.inv₀ (hf : Continuous f) (h0 : ∀ x, f x ≠ 0) : Continuous fun x => (f x)⁻¹ :=
continuous_iff_continuousAt.2 fun x => (hf.tendsto x).inv₀ (h0 x)
#align continuous.inv₀ Continuous.inv₀
@[fun_prop]
theorem ContinuousOn.inv₀ (hf : ContinuousOn f s) (h0 : ∀ x ∈ s, f x ≠ 0) :
ContinuousOn (fun x => (f x)⁻¹) s := fun x hx => (hf x hx).inv₀ (h0 x hx)
#align continuous_on.inv₀ ContinuousOn.inv₀
end Inv₀
/-- If `G₀` is a group with zero with topology such that `x ↦ x⁻¹` is continuous at all nonzero
points. Then the coercion `G₀ˣ → G₀` is a topological embedding. -/
theorem Units.embedding_val₀ [GroupWithZero G₀] [TopologicalSpace G₀] [HasContinuousInv₀ G₀] :
Embedding (val : G₀ˣ → G₀) :=
embedding_val_mk <| (continuousOn_inv₀ (G₀ := G₀)).mono fun _ ↦ IsUnit.ne_zero
#align units.embedding_coe₀ Units.embedding_val₀
section NhdsInv
variable [GroupWithZero G₀] [TopologicalSpace G₀] [HasContinuousInv₀ G₀] {x : G₀}
lemma nhds_inv₀ (hx : x ≠ 0) : 𝓝 x⁻¹ = (𝓝 x)⁻¹ := by
refine le_antisymm (inv_le_iff_le_inv.1 ?_) (tendsto_inv₀ hx)
simpa only [inv_inv] using tendsto_inv₀ (inv_ne_zero hx)
lemma tendsto_inv_iff₀ {l : Filter α} {f : α → G₀} (hx : x ≠ 0) :
Tendsto (fun x ↦ (f x)⁻¹) l (𝓝 x⁻¹) ↔ Tendsto f l (𝓝 x) := by
simp only [nhds_inv₀ hx, ← Filter.comap_inv, tendsto_comap_iff, (· ∘ ·), inv_inv]
end NhdsInv
/-!
### Continuity of division
If `G₀` is a `GroupWithZero` with `x ↦ x⁻¹` continuous at all nonzero points and `(*)`, then
division `(/)` is continuous at any point where the denominator is continuous.
-/
section Div
variable [GroupWithZero G₀] [TopologicalSpace G₀] [HasContinuousInv₀ G₀] [ContinuousMul G₀]
{f g : α → G₀}
theorem Filter.Tendsto.div {l : Filter α} {a b : G₀} (hf : Tendsto f l (𝓝 a))
(hg : Tendsto g l (𝓝 b)) (hy : b ≠ 0) : Tendsto (f / g) l (𝓝 (a / b)) := by
simpa only [div_eq_mul_inv] using hf.mul (hg.inv₀ hy)
#align filter.tendsto.div Filter.Tendsto.div
theorem Filter.tendsto_mul_iff_of_ne_zero [T1Space G₀] {f g : α → G₀} {l : Filter α} {x y : G₀}
(hg : Tendsto g l (𝓝 y)) (hy : y ≠ 0) :
Tendsto (fun n => f n * g n) l (𝓝 <| x * y) ↔ Tendsto f l (𝓝 x) := by
refine ⟨fun hfg => ?_, fun hf => hf.mul hg⟩
rw [← mul_div_cancel_right₀ x hy]
refine Tendsto.congr' ?_ (hfg.div hg hy)
exact (hg.eventually_ne hy).mono fun n hn => mul_div_cancel_right₀ _ hn
#align filter.tendsto_mul_iff_of_ne_zero Filter.tendsto_mul_iff_of_ne_zero
variable [TopologicalSpace α] [TopologicalSpace β] {s : Set α} {a : α}
nonrec theorem ContinuousWithinAt.div (hf : ContinuousWithinAt f s a)
(hg : ContinuousWithinAt g s a) (h₀ : g a ≠ 0) : ContinuousWithinAt (f / g) s a :=
hf.div hg h₀
#align continuous_within_at.div ContinuousWithinAt.div
theorem ContinuousOn.div (hf : ContinuousOn f s) (hg : ContinuousOn g s) (h₀ : ∀ x ∈ s, g x ≠ 0) :
ContinuousOn (f / g) s := fun x hx => (hf x hx).div (hg x hx) (h₀ x hx)
#align continuous_on.div ContinuousOn.div
/-- Continuity at a point of the result of dividing two functions continuous at that point, where
the denominator is nonzero. -/
nonrec theorem ContinuousAt.div (hf : ContinuousAt f a) (hg : ContinuousAt g a) (h₀ : g a ≠ 0) :
ContinuousAt (f / g) a :=
hf.div hg h₀
#align continuous_at.div ContinuousAt.div
@[continuity]
theorem Continuous.div (hf : Continuous f) (hg : Continuous g) (h₀ : ∀ x, g x ≠ 0) :
Continuous (f / g) := by simpa only [div_eq_mul_inv] using hf.mul (hg.inv₀ h₀)
#align continuous.div Continuous.div
theorem continuousOn_div : ContinuousOn (fun p : G₀ × G₀ => p.1 / p.2) { p | p.2 ≠ 0 } :=
continuousOn_fst.div continuousOn_snd fun _ => id
#align continuous_on_div continuousOn_div
@[fun_prop]
theorem Continuous.div₀ (hf : Continuous f) (hg : Continuous g) (h₀ : ∀ x, g x ≠ 0) :
Continuous (fun x => f x / g x) := by
simpa only [div_eq_mul_inv] using hf.mul (hg.inv₀ h₀)
@[fun_prop]
theorem ContinuousAt.div₀ (hf : ContinuousAt f a) (hg : ContinuousAt g a) (h₀ : g a ≠ 0) :
ContinuousAt (fun x => f x / g x) a := ContinuousAt.div hf hg h₀
@[fun_prop]
theorem ContinuousOn.div₀ (hf : ContinuousOn f s) (hg : ContinuousOn g s) (h₀ : ∀ x ∈ s, g x ≠ 0) :
ContinuousOn (fun x => f x / g x) s := ContinuousOn.div hf hg h₀
/-- The function `f x / g x` is discontinuous when `g x = 0`. However, under appropriate
conditions, `h x (f x / g x)` is still continuous. The condition is that if `g a = 0` then `h x y`
must tend to `h a 0` when `x` tends to `a`, with no information about `y`. This is represented by
the `⊤` filter. Note: `tendsto_prod_top_iff` characterizes this convergence in uniform spaces. See
also `Filter.prod_top` and `Filter.mem_prod_top`. -/
| Mathlib/Topology/Algebra/GroupWithZero.lean | 236 | 245 | theorem ContinuousAt.comp_div_cases {f g : α → G₀} (h : α → G₀ → β) (hf : ContinuousAt f a)
(hg : ContinuousAt g a) (hh : g a ≠ 0 → ContinuousAt (↿h) (a, f a / g a))
(h2h : g a = 0 → Tendsto (↿h) (𝓝 a ×ˢ ⊤) (𝓝 (h a 0))) :
ContinuousAt (fun x => h x (f x / g x)) a := by |
show ContinuousAt (↿h ∘ fun x => (x, f x / g x)) a
by_cases hga : g a = 0
· rw [ContinuousAt]
simp_rw [comp_apply, hga, div_zero]
exact (h2h hga).comp (continuousAt_id.prod_mk tendsto_top)
· exact ContinuousAt.comp (hh hga) (continuousAt_id.prod (hf.div hg hga))
|
/-
Copyright (c) 2023 Scott Carnahan. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Scott Carnahan
-/
import Mathlib.Algebra.Group.NatPowAssoc
import Mathlib.Algebra.Polynomial.AlgebraMap
import Mathlib.Algebra.Polynomial.Induction
import Mathlib.Algebra.Polynomial.Eval
/-!
# Scalar-multiple polynomial evaluation
This file defines polynomial evaluation via scalar multiplication. Our polynomials have
coefficients in a semiring `R`, and we evaluate at a weak form of `R`-algebra, namely an additive
commutative monoid with an action of `R` and a notion of natural number power. This
is a generalization of `Algebra.Polynomial.Eval`.
## Main definitions
* `Polynomial.smeval`: function for evaluating a polynomial with coefficients in a `Semiring`
`R` at an element `x` of an `AddCommMonoid` `S` that has natural number powers and an `R`-action.
* `smeval.linearMap`: the `smeval` function as an `R`-linear map, when `S` is an `R`-module.
* `smeval.algebraMap`: the `smeval` function as an `R`-algebra map, when `S` is an `R`-algebra.
## Main results
* `smeval_monomial`: monomials evaluate as we expect.
* `smeval_add`, `smeval_smul`: linearity of evaluation, given an `R`-module.
* `smeval_mul`, `smeval_comp`: multiplicativity of evaluation, given power-associativity.
* `eval₂_eq_smeval`, `leval_eq_smeval.linearMap`, `aeval = smeval.algebraMap`, etc.: comparisons
## To do
* `smeval_neg` and `smeval_intCast` for `R` a ring and `S` an `AddCommGroup`.
* Nonunital evaluation for polynomials with vanishing constant term for `Pow S ℕ+` (different file?)
-/
namespace Polynomial
section MulActionWithZero
variable {R : Type*} [Semiring R] (r : R) (p : R[X]) {S : Type*} [AddCommMonoid S] [Pow S ℕ]
[MulActionWithZero R S] (x : S)
/-- Scalar multiplication together with taking a natural number power. -/
def smul_pow : ℕ → R → S := fun n r => r • x^n
/-- Evaluate a polynomial `p` in the scalar semiring `R` at an element `x` in the target `S` using
scalar multiple `R`-action. -/
irreducible_def smeval : S := p.sum (smul_pow x)
theorem smeval_eq_sum : p.smeval x = p.sum (smul_pow x) := by rw [smeval_def]
@[simp]
theorem smeval_C : (C r).smeval x = r • x ^ 0 := by
simp only [smeval_eq_sum, smul_pow, zero_smul, sum_C_index]
@[simp]
theorem smeval_monomial (n : ℕ) :
(monomial n r).smeval x = r • x ^ n := by
simp only [smeval_eq_sum, smul_pow, zero_smul, sum_monomial_index]
theorem eval_eq_smeval : p.eval r = p.smeval r := by
rw [eval_eq_sum, smeval_eq_sum]
rfl
theorem eval₂_eq_smeval (R : Type*) [Semiring R] {S : Type*} [Semiring S] (f : R →+* S) (p : R[X])
(x: S) : letI : Module R S := RingHom.toModule f
p.eval₂ f x = p.smeval x := by
letI : Module R S := RingHom.toModule f
rw [smeval_eq_sum, eval₂_eq_sum]
rfl
variable (R)
@[simp]
theorem smeval_zero : (0 : R[X]).smeval x = 0 := by
simp only [smeval_eq_sum, smul_pow, sum_zero_index]
@[simp]
theorem smeval_one : (1 : R[X]).smeval x = 1 • x ^ 0 := by
rw [← C_1, smeval_C]
simp only [Nat.cast_one, one_smul]
@[simp]
theorem smeval_X :
(X : R[X]).smeval x = x ^ 1 := by
simp only [smeval_eq_sum, smul_pow, zero_smul, sum_X_index, one_smul]
@[simp]
theorem smeval_X_pow {n : ℕ} :
(X ^ n : R[X]).smeval x = x ^ n := by
simp only [smeval_eq_sum, smul_pow, X_pow_eq_monomial, zero_smul, sum_monomial_index, one_smul]
end MulActionWithZero
section Module
variable (R : Type*) [Semiring R] (p q : R[X]) {S : Type*} [AddCommMonoid S] [Pow S ℕ] [Module R S]
(x : S)
@[simp]
theorem smeval_add : (p + q).smeval x = p.smeval x + q.smeval x := by
simp only [smeval_eq_sum, smul_pow]
refine sum_add_index p q (smul_pow x) (fun _ ↦ ?_) (fun _ _ _ ↦ ?_)
· rw [smul_pow, zero_smul]
· rw [smul_pow, smul_pow, smul_pow, add_smul]
theorem smeval_natCast (n : ℕ) : (n : R[X]).smeval x = n • x ^ 0 := by
induction' n with n ih
· simp only [smeval_zero, Nat.cast_zero, Nat.zero_eq, zero_smul]
· rw [n.cast_succ, smeval_add, ih, smeval_one, ← add_nsmul]
@[deprecated (since := "2024-04-17")]
alias smeval_nat_cast := smeval_natCast
@[simp]
theorem smeval_smul (r : R) : (r • p).smeval x = r • p.smeval x := by
induction p using Polynomial.induction_on' with
| h_add p q ph qh =>
rw [smul_add, smeval_add, ph, qh, ← smul_add, smeval_add]
| h_monomial n a =>
rw [smul_monomial, smeval_monomial, smeval_monomial, smul_assoc]
/-- `Polynomial.smeval` as a linear map. -/
def smeval.linearMap : R[X] →ₗ[R] S where
toFun f := f.smeval x
map_add' f g := by simp only [smeval_add]
map_smul' c f := by simp only [smeval_smul, smul_eq_mul, RingHom.id_apply]
@[simp]
theorem smeval.linearMap_apply : smeval.linearMap R x p = p.smeval x := rfl
theorem leval_coe_eq_smeval {R : Type*} [Semiring R] (r : R) :
⇑(leval r) = fun p => p.smeval r := by
rw [Function.funext_iff]
intro
rw [leval_apply, smeval_def, eval_eq_sum]
rfl
theorem leval_eq_smeval.linearMap {R : Type*} [Semiring R] (r : R) :
leval r = smeval.linearMap R r := by
refine LinearMap.ext ?_
intro
rw [leval_apply, smeval.linearMap_apply, eval_eq_smeval]
end Module
section Neg
variable (R : Type*) [Ring R] {S : Type*} [AddCommGroup S] [Pow S ℕ] [Module R S] (p q : R[X])
(x : S)
@[simp]
theorem smeval_neg : (-p).smeval x = - p.smeval x := by
have h : (p + -p).smeval x = 0 := by rw [add_neg_self, smeval_zero]
rw [smeval_add, add_eq_zero_iff_neg_eq] at h
exact id h.symm
@[simp]
theorem smeval_sub : (p - q).smeval x = p.smeval x - q.smeval x := by
rw [sub_eq_add_neg, smeval_add, smeval_neg, sub_eq_add_neg]
end Neg
section NatPowAssoc
/-!
In the module docstring for algebras at `Mathlib.Algebra.Algebra.Basic`, we see that
`[CommSemiring R] [Semiring S] [Module R S] [IsScalarTower R S S] [SMulCommClass R S S]` is an
equivalent way to express `[CommSemiring R] [Semiring S] [Algebra R S]` that allows one to relax
the defining structures independently. For non-associative power-associative algebras (e.g.,
octonions), we replace the `[Semiring S]` with `[NonAssocSemiring S] [Pow S ℕ] [NatPowAssoc S]`.
-/
variable (R : Type*) [Semiring R] {p : R[X]} (r : R) (p q : R[X]) {S : Type*}
[NonAssocSemiring S] [Module R S] [IsScalarTower R S S] [SMulCommClass R S S] [Pow S ℕ]
[NatPowAssoc S] (x : S)
| Mathlib/Algebra/Polynomial/Smeval.lean | 182 | 189 | theorem smeval_at_natCast (q : ℕ[X]): ∀(n : ℕ), q.smeval (n : S) = q.smeval n := by |
induction q using Polynomial.induction_on' with
| h_add p q ph qh =>
intro n
simp only [add_mul, smeval_add, ph, qh, Nat.cast_add]
| h_monomial n a =>
intro n
rw [smeval_monomial, smeval_monomial, nsmul_eq_mul, smul_eq_mul, Nat.cast_mul, Nat.cast_npow]
|
/-
Copyright (c) 2020 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes
-/
import Mathlib.Algebra.Group.Aut
import Mathlib.Algebra.Group.Subgroup.Basic
import Mathlib.Logic.Function.Basic
#align_import group_theory.semidirect_product from "leanprover-community/mathlib"@"f7fc89d5d5ff1db2d1242c7bb0e9062ce47ef47c"
/-!
# Semidirect product
This file defines semidirect products of groups, and the canonical maps in and out of the
semidirect product. The semidirect product of `N` and `G` given a hom `φ` from
`G` to the automorphism group of `N` is the product of sets with the group
`⟨n₁, g₁⟩ * ⟨n₂, g₂⟩ = ⟨n₁ * φ g₁ n₂, g₁ * g₂⟩`
## Key definitions
There are two homs into the semidirect product `inl : N →* N ⋊[φ] G` and
`inr : G →* N ⋊[φ] G`, and `lift` can be used to define maps `N ⋊[φ] G →* H`
out of the semidirect product given maps `f₁ : N →* H` and `f₂ : G →* H` that satisfy the
condition `∀ n g, f₁ (φ g n) = f₂ g * f₁ n * f₂ g⁻¹`
## Notation
This file introduces the global notation `N ⋊[φ] G` for `SemidirectProduct N G φ`
## Tags
group, semidirect product
-/
variable (N : Type*) (G : Type*) {H : Type*} [Group N] [Group G] [Group H]
/-- The semidirect product of groups `N` and `G`, given a map `φ` from `G` to the automorphism
group of `N`. It the product of sets with the group operation
`⟨n₁, g₁⟩ * ⟨n₂, g₂⟩ = ⟨n₁ * φ g₁ n₂, g₁ * g₂⟩` -/
@[ext]
structure SemidirectProduct (φ : G →* MulAut N) where
/-- The element of N -/
left : N
/-- The element of G -/
right : G
deriving DecidableEq
#align semidirect_product SemidirectProduct
-- Porting note: these lemmas are autogenerated by the inductive definition and are not
-- in simple form due to the existence of mk_eq_inl_mul_inr
attribute [nolint simpNF] SemidirectProduct.mk.injEq
attribute [nolint simpNF] SemidirectProduct.mk.sizeOf_spec
-- Porting note: unknown attribute
-- attribute [pp_using_anonymous_constructor] SemidirectProduct
@[inherit_doc]
notation:35 N " ⋊[" φ:35 "] " G:35 => SemidirectProduct N G φ
namespace SemidirectProduct
variable {N G}
variable {φ : G →* MulAut N}
instance : Mul (SemidirectProduct N G φ) where
mul a b := ⟨a.1 * φ a.2 b.1, a.2 * b.2⟩
lemma mul_def (a b : SemidirectProduct N G φ) : a * b = ⟨a.1 * φ a.2 b.1, a.2 * b.2⟩ := rfl
@[simp]
theorem mul_left (a b : N ⋊[φ] G) : (a * b).left = a.left * φ a.right b.left := rfl
#align semidirect_product.mul_left SemidirectProduct.mul_left
@[simp]
theorem mul_right (a b : N ⋊[φ] G) : (a * b).right = a.right * b.right := rfl
#align semidirect_product.mul_right SemidirectProduct.mul_right
instance : One (SemidirectProduct N G φ) where one := ⟨1, 1⟩
@[simp]
theorem one_left : (1 : N ⋊[φ] G).left = 1 := rfl
#align semidirect_product.one_left SemidirectProduct.one_left
@[simp]
theorem one_right : (1 : N ⋊[φ] G).right = 1 := rfl
#align semidirect_product.one_right SemidirectProduct.one_right
instance : Inv (SemidirectProduct N G φ) where
inv x := ⟨φ x.2⁻¹ x.1⁻¹, x.2⁻¹⟩
@[simp]
theorem inv_left (a : N ⋊[φ] G) : a⁻¹.left = φ a.right⁻¹ a.left⁻¹ := rfl
#align semidirect_product.inv_left SemidirectProduct.inv_left
@[simp]
theorem inv_right (a : N ⋊[φ] G) : a⁻¹.right = a.right⁻¹ := rfl
#align semidirect_product.inv_right SemidirectProduct.inv_right
instance : Group (N ⋊[φ] G) where
mul_assoc a b c := SemidirectProduct.ext _ _ (by simp [mul_assoc]) (by simp [mul_assoc])
one_mul a := SemidirectProduct.ext _ _ (by simp) (one_mul a.2)
mul_one a := SemidirectProduct.ext _ _ (by simp) (mul_one _)
mul_left_inv a := SemidirectProduct.ext _ _ (by simp) (by simp)
instance : Inhabited (N ⋊[φ] G) := ⟨1⟩
/-- The canonical map `N →* N ⋊[φ] G` sending `n` to `⟨n, 1⟩` -/
def inl : N →* N ⋊[φ] G where
toFun n := ⟨n, 1⟩
map_one' := rfl
map_mul' := by intros; ext <;>
simp only [mul_left, map_one, MulAut.one_apply, mul_right, mul_one]
#align semidirect_product.inl SemidirectProduct.inl
@[simp]
theorem left_inl (n : N) : (inl n : N ⋊[φ] G).left = n := rfl
#align semidirect_product.left_inl SemidirectProduct.left_inl
@[simp]
theorem right_inl (n : N) : (inl n : N ⋊[φ] G).right = 1 := rfl
#align semidirect_product.right_inl SemidirectProduct.right_inl
theorem inl_injective : Function.Injective (inl : N → N ⋊[φ] G) :=
Function.injective_iff_hasLeftInverse.2 ⟨left, left_inl⟩
#align semidirect_product.inl_injective SemidirectProduct.inl_injective
@[simp]
theorem inl_inj {n₁ n₂ : N} : (inl n₁ : N ⋊[φ] G) = inl n₂ ↔ n₁ = n₂ :=
inl_injective.eq_iff
#align semidirect_product.inl_inj SemidirectProduct.inl_inj
/-- The canonical map `G →* N ⋊[φ] G` sending `g` to `⟨1, g⟩` -/
def inr : G →* N ⋊[φ] G where
toFun g := ⟨1, g⟩
map_one' := rfl
map_mul' := by intros; ext <;> simp
#align semidirect_product.inr SemidirectProduct.inr
@[simp]
theorem left_inr (g : G) : (inr g : N ⋊[φ] G).left = 1 := rfl
#align semidirect_product.left_inr SemidirectProduct.left_inr
@[simp]
theorem right_inr (g : G) : (inr g : N ⋊[φ] G).right = g := rfl
#align semidirect_product.right_inr SemidirectProduct.right_inr
theorem inr_injective : Function.Injective (inr : G → N ⋊[φ] G) :=
Function.injective_iff_hasLeftInverse.2 ⟨right, right_inr⟩
#align semidirect_product.inr_injective SemidirectProduct.inr_injective
@[simp]
theorem inr_inj {g₁ g₂ : G} : (inr g₁ : N ⋊[φ] G) = inr g₂ ↔ g₁ = g₂ :=
inr_injective.eq_iff
#align semidirect_product.inr_inj SemidirectProduct.inr_inj
theorem inl_aut (g : G) (n : N) : (inl (φ g n) : N ⋊[φ] G) = inr g * inl n * inr g⁻¹ := by
ext <;> simp
#align semidirect_product.inl_aut SemidirectProduct.inl_aut
theorem inl_aut_inv (g : G) (n : N) : (inl ((φ g)⁻¹ n) : N ⋊[φ] G) = inr g⁻¹ * inl n * inr g := by
rw [← MonoidHom.map_inv, inl_aut, inv_inv]
#align semidirect_product.inl_aut_inv SemidirectProduct.inl_aut_inv
@[simp]
theorem mk_eq_inl_mul_inr (g : G) (n : N) : (⟨n, g⟩ : N ⋊[φ] G) = inl n * inr g := by ext <;> simp
#align semidirect_product.mk_eq_inl_mul_inr SemidirectProduct.mk_eq_inl_mul_inr
@[simp]
theorem inl_left_mul_inr_right (x : N ⋊[φ] G) : inl x.left * inr x.right = x := by ext <;> simp
#align semidirect_product.inl_left_mul_inr_right SemidirectProduct.inl_left_mul_inr_right
/-- The canonical projection map `N ⋊[φ] G →* G`, as a group hom. -/
def rightHom : N ⋊[φ] G →* G where
toFun := SemidirectProduct.right
map_one' := rfl
map_mul' _ _ := rfl
#align semidirect_product.right_hom SemidirectProduct.rightHom
@[simp]
theorem rightHom_eq_right : (rightHom : N ⋊[φ] G → G) = right := rfl
#align semidirect_product.right_hom_eq_right SemidirectProduct.rightHom_eq_right
@[simp]
theorem rightHom_comp_inl : (rightHom : N ⋊[φ] G →* G).comp inl = 1 := by ext; simp [rightHom]
#align semidirect_product.right_hom_comp_inl SemidirectProduct.rightHom_comp_inl
@[simp]
theorem rightHom_comp_inr : (rightHom : N ⋊[φ] G →* G).comp inr = MonoidHom.id _ := by
ext; simp [rightHom]
#align semidirect_product.right_hom_comp_inr SemidirectProduct.rightHom_comp_inr
@[simp]
theorem rightHom_inl (n : N) : rightHom (inl n : N ⋊[φ] G) = 1 := by simp [rightHom]
#align semidirect_product.right_hom_inl SemidirectProduct.rightHom_inl
@[simp]
theorem rightHom_inr (g : G) : rightHom (inr g : N ⋊[φ] G) = g := by simp [rightHom]
#align semidirect_product.right_hom_inr SemidirectProduct.rightHom_inr
theorem rightHom_surjective : Function.Surjective (rightHom : N ⋊[φ] G → G) :=
Function.surjective_iff_hasRightInverse.2 ⟨inr, rightHom_inr⟩
#align semidirect_product.right_hom_surjective SemidirectProduct.rightHom_surjective
theorem range_inl_eq_ker_rightHom : (inl : N →* N ⋊[φ] G).range = rightHom.ker :=
le_antisymm (fun _ ↦ by simp (config := { contextual := true }) [MonoidHom.mem_ker, eq_comm])
fun x hx ↦ ⟨x.left, by ext <;> simp_all [MonoidHom.mem_ker]⟩
#align semidirect_product.range_inl_eq_ker_right_hom SemidirectProduct.range_inl_eq_ker_rightHom
section lift
variable (f₁ : N →* H) (f₂ : G →* H)
(h : ∀ g, f₁.comp (φ g).toMonoidHom = (MulAut.conj (f₂ g)).toMonoidHom.comp f₁)
/-- Define a group hom `N ⋊[φ] G →* H`, by defining maps `N →* H` and `G →* H` -/
def lift (f₁ : N →* H) (f₂ : G →* H)
(h : ∀ g, f₁.comp (φ g).toMonoidHom = (MulAut.conj (f₂ g)).toMonoidHom.comp f₁) :
N ⋊[φ] G →* H where
toFun a := f₁ a.1 * f₂ a.2
map_one' := by simp
map_mul' a b := by
have := fun n g ↦ DFunLike.ext_iff.1 (h n) g
simp only [MulAut.conj_apply, MonoidHom.comp_apply, MulEquiv.coe_toMonoidHom] at this
simp only [mul_left, mul_right, map_mul, this, mul_assoc, inv_mul_cancel_left]
#align semidirect_product.lift SemidirectProduct.lift
@[simp]
theorem lift_inl (n : N) : lift f₁ f₂ h (inl n) = f₁ n := by simp [lift]
#align semidirect_product.lift_inl SemidirectProduct.lift_inl
@[simp]
theorem lift_comp_inl : (lift f₁ f₂ h).comp inl = f₁ := by ext; simp
#align semidirect_product.lift_comp_inl SemidirectProduct.lift_comp_inl
@[simp]
theorem lift_inr (g : G) : lift f₁ f₂ h (inr g) = f₂ g := by simp [lift]
#align semidirect_product.lift_inr SemidirectProduct.lift_inr
@[simp]
theorem lift_comp_inr : (lift f₁ f₂ h).comp inr = f₂ := by ext; simp
#align semidirect_product.lift_comp_inr SemidirectProduct.lift_comp_inr
theorem lift_unique (F : N ⋊[φ] G →* H) :
F = lift (F.comp inl) (F.comp inr) fun _ ↦ by ext; simp [inl_aut] := by
rw [DFunLike.ext_iff]
simp only [lift, MonoidHom.comp_apply, MonoidHom.coe_mk, OneHom.coe_mk, ← map_mul,
inl_left_mul_inr_right, forall_const]
#align semidirect_product.lift_unique SemidirectProduct.lift_unique
/-- Two maps out of the semidirect product are equal if they're equal after composition
with both `inl` and `inr` -/
theorem hom_ext {f g : N ⋊[φ] G →* H} (hl : f.comp inl = g.comp inl)
(hr : f.comp inr = g.comp inr) : f = g := by
rw [lift_unique f, lift_unique g]
simp only [*]
#align semidirect_product.hom_ext SemidirectProduct.hom_ext
end lift
section Map
variable {N₁ : Type*} {G₁ : Type*} [Group N₁] [Group G₁] {φ₁ : G₁ →* MulAut N₁}
/-- Define a map from `N ⋊[φ] G` to `N₁ ⋊[φ₁] G₁` given maps `N →* N₁` and `G →* G₁` that
satisfy a commutativity condition `∀ n g, f₁ (φ g n) = φ₁ (f₂ g) (f₁ n)`. -/
def map (f₁ : N →* N₁) (f₂ : G →* G₁)
(h : ∀ g : G, f₁.comp (φ g).toMonoidHom = (φ₁ (f₂ g)).toMonoidHom.comp f₁) :
N ⋊[φ] G →* N₁ ⋊[φ₁] G₁ where
toFun x := ⟨f₁ x.1, f₂ x.2⟩
map_one' := by simp
map_mul' x y := by
replace h := DFunLike.ext_iff.1 (h x.right) y.left
ext <;> simp_all
#align semidirect_product.map SemidirectProduct.map
variable (f₁ : N →* N₁) (f₂ : G →* G₁)
(h : ∀ g : G, f₁.comp (φ g).toMonoidHom = (φ₁ (f₂ g)).toMonoidHom.comp f₁)
@[simp]
theorem map_left (g : N ⋊[φ] G) : (map f₁ f₂ h g).left = f₁ g.left := rfl
#align semidirect_product.map_left SemidirectProduct.map_left
@[simp]
theorem map_right (g : N ⋊[φ] G) : (map f₁ f₂ h g).right = f₂ g.right := rfl
#align semidirect_product.map_right SemidirectProduct.map_right
@[simp]
theorem rightHom_comp_map : rightHom.comp (map f₁ f₂ h) = f₂.comp rightHom := rfl
#align semidirect_product.right_hom_comp_map SemidirectProduct.rightHom_comp_map
@[simp]
theorem map_inl (n : N) : map f₁ f₂ h (inl n) = inl (f₁ n) := by simp [map]
#align semidirect_product.map_inl SemidirectProduct.map_inl
@[simp]
theorem map_comp_inl : (map f₁ f₂ h).comp inl = inl.comp f₁ := by ext <;> simp
#align semidirect_product.map_comp_inl SemidirectProduct.map_comp_inl
@[simp]
| Mathlib/GroupTheory/SemidirectProduct.lean | 300 | 300 | theorem map_inr (g : G) : map f₁ f₂ h (inr g) = inr (f₂ g) := by | simp [map]
|
/-
Copyright (c) 2023 Eric Wieser. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Eric Wieser
-/
import Mathlib.Data.Int.Order.Units
import Mathlib.Data.ZMod.IntUnitsPower
import Mathlib.RingTheory.TensorProduct.Basic
import Mathlib.LinearAlgebra.DirectSum.TensorProduct
import Mathlib.Algebra.DirectSum.Algebra
/-!
# Graded tensor products over graded algebras
The graded tensor product $A \hat\otimes_R B$ is imbued with a multiplication defined on homogeneous
tensors by:
$$(a \otimes b) \cdot (a' \otimes b') = (-1)^{\deg a' \deg b} (a \cdot a') \otimes (b \cdot b')$$
where $A$ and $B$ are algebras graded by `ℕ`, `ℤ`, or `ZMod 2` (or more generally, any index
that satisfies `Module ι (Additive ℤˣ)`).
The results for internally-graded algebras (via `GradedAlgebra`) are elsewhere, as is the type
`GradedTensorProduct`.
## Main results
* `TensorProduct.gradedComm`: the symmetric braiding operator on the tensor product of
externally-graded rings.
* `TensorProduct.gradedMul`: the previously-described multiplication on externally-graded rings, as
a bilinear map.
## Implementation notes
Rather than implementing the multiplication directly as above, we first implement the canonical
non-trivial braiding sending $a \otimes b$ to $(-1)^{\deg a' \deg b} (b \otimes a)$, as the
multiplication follows trivially from this after some point-free nonsense.
## References
* https://math.stackexchange.com/q/202718/1896
* [*Algebra I*, Bourbaki : Chapter III, §4.7, example (2)][bourbaki1989]
-/
suppress_compilation
open scoped TensorProduct DirectSum
variable {R ι A B : Type*}
namespace TensorProduct
variable [CommSemiring ι] [Module ι (Additive ℤˣ)] [DecidableEq ι]
variable (𝒜 : ι → Type*) (ℬ : ι → Type*)
variable [CommRing R]
variable [∀ i, AddCommGroup (𝒜 i)] [∀ i, AddCommGroup (ℬ i)]
variable [∀ i, Module R (𝒜 i)] [∀ i, Module R (ℬ i)]
variable [DirectSum.GRing 𝒜] [DirectSum.GRing ℬ]
variable [DirectSum.GAlgebra R 𝒜] [DirectSum.GAlgebra R ℬ]
-- this helps with performance
instance (i : ι × ι) : Module R (𝒜 (Prod.fst i) ⊗[R] ℬ (Prod.snd i)) :=
TensorProduct.leftModule
open DirectSum (lof)
variable (R)
section gradedComm
local notation "𝒜ℬ" => (fun i : ι × ι => 𝒜 (Prod.fst i) ⊗[R] ℬ (Prod.snd i))
local notation "ℬ𝒜" => (fun i : ι × ι => ℬ (Prod.fst i) ⊗[R] 𝒜 (Prod.snd i))
/-- Auxliary construction used to build `TensorProduct.gradedComm`.
This operates on direct sums of tensors instead of tensors of direct sums. -/
def gradedCommAux : DirectSum _ 𝒜ℬ →ₗ[R] DirectSum _ ℬ𝒜 := by
refine DirectSum.toModule R _ _ fun i => ?_
have o := DirectSum.lof R _ ℬ𝒜 i.swap
have s : ℤˣ := ((-1 : ℤˣ)^(i.1* i.2 : ι) : ℤˣ)
exact (s • o) ∘ₗ (TensorProduct.comm R _ _).toLinearMap
@[simp]
theorem gradedCommAux_lof_tmul (i j : ι) (a : 𝒜 i) (b : ℬ j) :
gradedCommAux R 𝒜 ℬ (lof R _ 𝒜ℬ (i, j) (a ⊗ₜ b)) =
(-1 : ℤˣ)^(j * i) • lof R _ ℬ𝒜 (j, i) (b ⊗ₜ a) := by
rw [gradedCommAux]
dsimp
simp [mul_comm i j]
@[simp]
theorem gradedCommAux_comp_gradedCommAux :
gradedCommAux R 𝒜 ℬ ∘ₗ gradedCommAux R ℬ 𝒜 = LinearMap.id := by
ext i a b
dsimp
rw [gradedCommAux_lof_tmul, LinearMap.map_smul_of_tower, gradedCommAux_lof_tmul, smul_smul,
mul_comm i.2 i.1, Int.units_mul_self, one_smul]
/-- The braiding operation for tensor products of externally `ι`-graded algebras.
This sends $a ⊗ b$ to $(-1)^{\deg a' \deg b} (b ⊗ a)$. -/
def gradedComm :
(⨁ i, 𝒜 i) ⊗[R] (⨁ i, ℬ i) ≃ₗ[R] (⨁ i, ℬ i) ⊗[R] (⨁ i, 𝒜 i) := by
refine TensorProduct.directSum R R 𝒜 ℬ ≪≫ₗ ?_ ≪≫ₗ (TensorProduct.directSum R R ℬ 𝒜).symm
exact LinearEquiv.ofLinear (gradedCommAux _ _ _) (gradedCommAux _ _ _)
(gradedCommAux_comp_gradedCommAux _ _ _) (gradedCommAux_comp_gradedCommAux _ _ _)
/-- The braiding is symmetric. -/
@[simp]
theorem gradedComm_symm : (gradedComm R 𝒜 ℬ).symm = gradedComm R ℬ 𝒜 := by
rw [gradedComm, gradedComm, LinearEquiv.trans_symm, LinearEquiv.symm_symm]
ext
rfl
| Mathlib/LinearAlgebra/TensorProduct/Graded/External.lean | 116 | 124 | theorem gradedComm_of_tmul_of (i j : ι) (a : 𝒜 i) (b : ℬ j) :
gradedComm R 𝒜 ℬ (lof R _ 𝒜 i a ⊗ₜ lof R _ ℬ j b) =
(-1 : ℤˣ)^(j * i) • (lof R _ ℬ _ b ⊗ₜ lof R _ 𝒜 _ a) := by |
rw [gradedComm]
dsimp only [LinearEquiv.trans_apply, LinearEquiv.ofLinear_apply]
rw [TensorProduct.directSum_lof_tmul_lof, gradedCommAux_lof_tmul, Units.smul_def,
-- Note: #8386 specialized `map_smul` to `LinearEquiv.map_smul` to avoid timeouts.
zsmul_eq_smul_cast R, LinearEquiv.map_smul, TensorProduct.directSum_symm_lof_tmul,
← zsmul_eq_smul_cast, ← Units.smul_def]
|
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Johannes Hölzl, Scott Morrison, Jens Wagemaker
-/
import Mathlib.Algebra.Polynomial.Degree.Definitions
import Mathlib.Algebra.Polynomial.Induction
#align_import data.polynomial.eval from "leanprover-community/mathlib"@"728baa2f54e6062c5879a3e397ac6bac323e506f"
/-!
# Theory of univariate polynomials
The main defs here are `eval₂`, `eval`, and `map`.
We give several lemmas about their interaction with each other and with module operations.
-/
set_option linter.uppercaseLean3 false
noncomputable section
open Finset AddMonoidAlgebra
open Polynomial
namespace Polynomial
universe u v w y
variable {R : Type u} {S : Type v} {T : Type w} {ι : Type y} {a b : R} {m n : ℕ}
section Semiring
variable [Semiring R] {p q r : R[X]}
section
variable [Semiring S]
variable (f : R →+* S) (x : S)
/-- Evaluate a polynomial `p` given a ring hom `f` from the scalar ring
to the target and a value `x` for the variable in the target -/
irreducible_def eval₂ (p : R[X]) : S :=
p.sum fun e a => f a * x ^ e
#align polynomial.eval₂ Polynomial.eval₂
theorem eval₂_eq_sum {f : R →+* S} {x : S} : p.eval₂ f x = p.sum fun e a => f a * x ^ e := by
rw [eval₂_def]
#align polynomial.eval₂_eq_sum Polynomial.eval₂_eq_sum
theorem eval₂_congr {R S : Type*} [Semiring R] [Semiring S] {f g : R →+* S} {s t : S}
{φ ψ : R[X]} : f = g → s = t → φ = ψ → eval₂ f s φ = eval₂ g t ψ := by
rintro rfl rfl rfl; rfl
#align polynomial.eval₂_congr Polynomial.eval₂_congr
@[simp]
theorem eval₂_at_zero : p.eval₂ f 0 = f (coeff p 0) := by
simp (config := { contextual := true }) only [eval₂_eq_sum, zero_pow_eq, mul_ite, mul_zero,
mul_one, sum, Classical.not_not, mem_support_iff, sum_ite_eq', ite_eq_left_iff,
RingHom.map_zero, imp_true_iff, eq_self_iff_true]
#align polynomial.eval₂_at_zero Polynomial.eval₂_at_zero
@[simp]
theorem eval₂_zero : (0 : R[X]).eval₂ f x = 0 := by simp [eval₂_eq_sum]
#align polynomial.eval₂_zero Polynomial.eval₂_zero
@[simp]
theorem eval₂_C : (C a).eval₂ f x = f a := by simp [eval₂_eq_sum]
#align polynomial.eval₂_C Polynomial.eval₂_C
@[simp]
theorem eval₂_X : X.eval₂ f x = x := by simp [eval₂_eq_sum]
#align polynomial.eval₂_X Polynomial.eval₂_X
@[simp]
theorem eval₂_monomial {n : ℕ} {r : R} : (monomial n r).eval₂ f x = f r * x ^ n := by
simp [eval₂_eq_sum]
#align polynomial.eval₂_monomial Polynomial.eval₂_monomial
@[simp]
theorem eval₂_X_pow {n : ℕ} : (X ^ n).eval₂ f x = x ^ n := by
rw [X_pow_eq_monomial]
convert eval₂_monomial f x (n := n) (r := 1)
simp
#align polynomial.eval₂_X_pow Polynomial.eval₂_X_pow
@[simp]
theorem eval₂_add : (p + q).eval₂ f x = p.eval₂ f x + q.eval₂ f x := by
simp only [eval₂_eq_sum]
apply sum_add_index <;> simp [add_mul]
#align polynomial.eval₂_add Polynomial.eval₂_add
@[simp]
theorem eval₂_one : (1 : R[X]).eval₂ f x = 1 := by rw [← C_1, eval₂_C, f.map_one]
#align polynomial.eval₂_one Polynomial.eval₂_one
set_option linter.deprecated false in
@[simp]
theorem eval₂_bit0 : (bit0 p).eval₂ f x = bit0 (p.eval₂ f x) := by rw [bit0, eval₂_add, bit0]
#align polynomial.eval₂_bit0 Polynomial.eval₂_bit0
set_option linter.deprecated false in
@[simp]
theorem eval₂_bit1 : (bit1 p).eval₂ f x = bit1 (p.eval₂ f x) := by
rw [bit1, eval₂_add, eval₂_bit0, eval₂_one, bit1]
#align polynomial.eval₂_bit1 Polynomial.eval₂_bit1
@[simp]
theorem eval₂_smul (g : R →+* S) (p : R[X]) (x : S) {s : R} :
eval₂ g x (s • p) = g s * eval₂ g x p := by
have A : p.natDegree < p.natDegree.succ := Nat.lt_succ_self _
have B : (s • p).natDegree < p.natDegree.succ := (natDegree_smul_le _ _).trans_lt A
rw [eval₂_eq_sum, eval₂_eq_sum, sum_over_range' _ _ _ A, sum_over_range' _ _ _ B] <;>
simp [mul_sum, mul_assoc]
#align polynomial.eval₂_smul Polynomial.eval₂_smul
@[simp]
theorem eval₂_C_X : eval₂ C X p = p :=
Polynomial.induction_on' p (fun p q hp hq => by simp [hp, hq]) fun n x => by
rw [eval₂_monomial, ← smul_X_eq_monomial, C_mul']
#align polynomial.eval₂_C_X Polynomial.eval₂_C_X
/-- `eval₂AddMonoidHom (f : R →+* S) (x : S)` is the `AddMonoidHom` from
`R[X]` to `S` obtained by evaluating the pushforward of `p` along `f` at `x`. -/
@[simps]
def eval₂AddMonoidHom : R[X] →+ S where
toFun := eval₂ f x
map_zero' := eval₂_zero _ _
map_add' _ _ := eval₂_add _ _
#align polynomial.eval₂_add_monoid_hom Polynomial.eval₂AddMonoidHom
#align polynomial.eval₂_add_monoid_hom_apply Polynomial.eval₂AddMonoidHom_apply
@[simp]
theorem eval₂_natCast (n : ℕ) : (n : R[X]).eval₂ f x = n := by
induction' n with n ih
-- Porting note: `Nat.zero_eq` is required.
· simp only [eval₂_zero, Nat.cast_zero, Nat.zero_eq]
· rw [n.cast_succ, eval₂_add, ih, eval₂_one, n.cast_succ]
#align polynomial.eval₂_nat_cast Polynomial.eval₂_natCast
@[deprecated (since := "2024-04-17")]
alias eval₂_nat_cast := eval₂_natCast
-- See note [no_index around OfNat.ofNat]
@[simp]
lemma eval₂_ofNat {S : Type*} [Semiring S] (n : ℕ) [n.AtLeastTwo] (f : R →+* S) (a : S) :
(no_index (OfNat.ofNat n : R[X])).eval₂ f a = OfNat.ofNat n := by
simp [OfNat.ofNat]
variable [Semiring T]
theorem eval₂_sum (p : T[X]) (g : ℕ → T → R[X]) (x : S) :
(p.sum g).eval₂ f x = p.sum fun n a => (g n a).eval₂ f x := by
let T : R[X] →+ S :=
{ toFun := eval₂ f x
map_zero' := eval₂_zero _ _
map_add' := fun p q => eval₂_add _ _ }
have A : ∀ y, eval₂ f x y = T y := fun y => rfl
simp only [A]
rw [sum, map_sum, sum]
#align polynomial.eval₂_sum Polynomial.eval₂_sum
theorem eval₂_list_sum (l : List R[X]) (x : S) : eval₂ f x l.sum = (l.map (eval₂ f x)).sum :=
map_list_sum (eval₂AddMonoidHom f x) l
#align polynomial.eval₂_list_sum Polynomial.eval₂_list_sum
theorem eval₂_multiset_sum (s : Multiset R[X]) (x : S) :
eval₂ f x s.sum = (s.map (eval₂ f x)).sum :=
map_multiset_sum (eval₂AddMonoidHom f x) s
#align polynomial.eval₂_multiset_sum Polynomial.eval₂_multiset_sum
theorem eval₂_finset_sum (s : Finset ι) (g : ι → R[X]) (x : S) :
(∑ i ∈ s, g i).eval₂ f x = ∑ i ∈ s, (g i).eval₂ f x :=
map_sum (eval₂AddMonoidHom f x) _ _
#align polynomial.eval₂_finset_sum Polynomial.eval₂_finset_sum
theorem eval₂_ofFinsupp {f : R →+* S} {x : S} {p : R[ℕ]} :
eval₂ f x (⟨p⟩ : R[X]) = liftNC (↑f) (powersHom S x) p := by
simp only [eval₂_eq_sum, sum, toFinsupp_sum, support, coeff]
rfl
#align polynomial.eval₂_of_finsupp Polynomial.eval₂_ofFinsupp
theorem eval₂_mul_noncomm (hf : ∀ k, Commute (f <| q.coeff k) x) :
eval₂ f x (p * q) = eval₂ f x p * eval₂ f x q := by
rcases p with ⟨p⟩; rcases q with ⟨q⟩
simp only [coeff] at hf
simp only [← ofFinsupp_mul, eval₂_ofFinsupp]
exact liftNC_mul _ _ p q fun {k n} _hn => (hf k).pow_right n
#align polynomial.eval₂_mul_noncomm Polynomial.eval₂_mul_noncomm
@[simp]
theorem eval₂_mul_X : eval₂ f x (p * X) = eval₂ f x p * x := by
refine _root_.trans (eval₂_mul_noncomm _ _ fun k => ?_) (by rw [eval₂_X])
rcases em (k = 1) with (rfl | hk)
· simp
· simp [coeff_X_of_ne_one hk]
#align polynomial.eval₂_mul_X Polynomial.eval₂_mul_X
@[simp]
theorem eval₂_X_mul : eval₂ f x (X * p) = eval₂ f x p * x := by rw [X_mul, eval₂_mul_X]
#align polynomial.eval₂_X_mul Polynomial.eval₂_X_mul
theorem eval₂_mul_C' (h : Commute (f a) x) : eval₂ f x (p * C a) = eval₂ f x p * f a := by
rw [eval₂_mul_noncomm, eval₂_C]
intro k
by_cases hk : k = 0
· simp only [hk, h, coeff_C_zero, coeff_C_ne_zero]
· simp only [coeff_C_ne_zero hk, RingHom.map_zero, Commute.zero_left]
#align polynomial.eval₂_mul_C' Polynomial.eval₂_mul_C'
theorem eval₂_list_prod_noncomm (ps : List R[X])
(hf : ∀ p ∈ ps, ∀ (k), Commute (f <| coeff p k) x) :
eval₂ f x ps.prod = (ps.map (Polynomial.eval₂ f x)).prod := by
induction' ps using List.reverseRecOn with ps p ihp
· simp
· simp only [List.forall_mem_append, List.forall_mem_singleton] at hf
simp [eval₂_mul_noncomm _ _ hf.2, ihp hf.1]
#align polynomial.eval₂_list_prod_noncomm Polynomial.eval₂_list_prod_noncomm
/-- `eval₂` as a `RingHom` for noncommutative rings -/
@[simps]
def eval₂RingHom' (f : R →+* S) (x : S) (hf : ∀ a, Commute (f a) x) : R[X] →+* S where
toFun := eval₂ f x
map_add' _ _ := eval₂_add _ _
map_zero' := eval₂_zero _ _
map_mul' _p q := eval₂_mul_noncomm f x fun k => hf <| coeff q k
map_one' := eval₂_one _ _
#align polynomial.eval₂_ring_hom' Polynomial.eval₂RingHom'
end
/-!
We next prove that eval₂ is multiplicative
as long as target ring is commutative
(even if the source ring is not).
-/
section Eval₂
section
variable [Semiring S] (f : R →+* S) (x : S)
theorem eval₂_eq_sum_range :
p.eval₂ f x = ∑ i ∈ Finset.range (p.natDegree + 1), f (p.coeff i) * x ^ i :=
_root_.trans (congr_arg _ p.as_sum_range)
(_root_.trans (eval₂_finset_sum f _ _ x) (congr_arg _ (by simp)))
#align polynomial.eval₂_eq_sum_range Polynomial.eval₂_eq_sum_range
theorem eval₂_eq_sum_range' (f : R →+* S) {p : R[X]} {n : ℕ} (hn : p.natDegree < n) (x : S) :
eval₂ f x p = ∑ i ∈ Finset.range n, f (p.coeff i) * x ^ i := by
rw [eval₂_eq_sum, p.sum_over_range' _ _ hn]
intro i
rw [f.map_zero, zero_mul]
#align polynomial.eval₂_eq_sum_range' Polynomial.eval₂_eq_sum_range'
end
section
variable [CommSemiring S] (f : R →+* S) (x : S)
@[simp]
theorem eval₂_mul : (p * q).eval₂ f x = p.eval₂ f x * q.eval₂ f x :=
eval₂_mul_noncomm _ _ fun _k => Commute.all _ _
#align polynomial.eval₂_mul Polynomial.eval₂_mul
theorem eval₂_mul_eq_zero_of_left (q : R[X]) (hp : p.eval₂ f x = 0) : (p * q).eval₂ f x = 0 := by
rw [eval₂_mul f x]
exact mul_eq_zero_of_left hp (q.eval₂ f x)
#align polynomial.eval₂_mul_eq_zero_of_left Polynomial.eval₂_mul_eq_zero_of_left
theorem eval₂_mul_eq_zero_of_right (p : R[X]) (hq : q.eval₂ f x = 0) : (p * q).eval₂ f x = 0 := by
rw [eval₂_mul f x]
exact mul_eq_zero_of_right (p.eval₂ f x) hq
#align polynomial.eval₂_mul_eq_zero_of_right Polynomial.eval₂_mul_eq_zero_of_right
/-- `eval₂` as a `RingHom` -/
def eval₂RingHom (f : R →+* S) (x : S) : R[X] →+* S :=
{ eval₂AddMonoidHom f x with
map_one' := eval₂_one _ _
map_mul' := fun _ _ => eval₂_mul _ _ }
#align polynomial.eval₂_ring_hom Polynomial.eval₂RingHom
@[simp]
theorem coe_eval₂RingHom (f : R →+* S) (x) : ⇑(eval₂RingHom f x) = eval₂ f x :=
rfl
#align polynomial.coe_eval₂_ring_hom Polynomial.coe_eval₂RingHom
theorem eval₂_pow (n : ℕ) : (p ^ n).eval₂ f x = p.eval₂ f x ^ n :=
(eval₂RingHom _ _).map_pow _ _
#align polynomial.eval₂_pow Polynomial.eval₂_pow
theorem eval₂_dvd : p ∣ q → eval₂ f x p ∣ eval₂ f x q :=
(eval₂RingHom f x).map_dvd
#align polynomial.eval₂_dvd Polynomial.eval₂_dvd
theorem eval₂_eq_zero_of_dvd_of_eval₂_eq_zero (h : p ∣ q) (h0 : eval₂ f x p = 0) :
eval₂ f x q = 0 :=
zero_dvd_iff.mp (h0 ▸ eval₂_dvd f x h)
#align polynomial.eval₂_eq_zero_of_dvd_of_eval₂_eq_zero Polynomial.eval₂_eq_zero_of_dvd_of_eval₂_eq_zero
theorem eval₂_list_prod (l : List R[X]) (x : S) : eval₂ f x l.prod = (l.map (eval₂ f x)).prod :=
map_list_prod (eval₂RingHom f x) l
#align polynomial.eval₂_list_prod Polynomial.eval₂_list_prod
end
end Eval₂
section Eval
variable {x : R}
/-- `eval x p` is the evaluation of the polynomial `p` at `x` -/
def eval : R → R[X] → R :=
eval₂ (RingHom.id _)
#align polynomial.eval Polynomial.eval
| Mathlib/Algebra/Polynomial/Eval.lean | 322 | 324 | theorem eval_eq_sum : p.eval x = p.sum fun e a => a * x ^ e := by |
rw [eval, eval₂_eq_sum]
rfl
|
/-
Copyright (c) 2021 Rémy Degenne. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Rémy Degenne
-/
import Mathlib.Analysis.RCLike.Lemmas
import Mathlib.MeasureTheory.Function.StronglyMeasurable.Inner
import Mathlib.MeasureTheory.Integral.SetIntegral
#align_import measure_theory.function.l2_space from "leanprover-community/mathlib"@"83a66c8775fa14ee5180c85cab98e970956401ad"
/-! # `L^2` space
If `E` is an inner product space over `𝕜` (`ℝ` or `ℂ`), then `Lp E 2 μ`
(defined in `Mathlib.MeasureTheory.Function.LpSpace`)
is also an inner product space, with inner product defined as `inner f g = ∫ a, ⟪f a, g a⟫ ∂μ`.
### Main results
* `mem_L1_inner` : for `f` and `g` in `Lp E 2 μ`, the pointwise inner product `fun x ↦ ⟪f x, g x⟫`
belongs to `Lp 𝕜 1 μ`.
* `integrable_inner` : for `f` and `g` in `Lp E 2 μ`, the pointwise inner product
`fun x ↦ ⟪f x, g x⟫` is integrable.
* `L2.innerProductSpace` : `Lp E 2 μ` is an inner product space.
-/
set_option linter.uppercaseLean3 false
noncomputable section
open TopologicalSpace MeasureTheory MeasureTheory.Lp Filter
open scoped NNReal ENNReal MeasureTheory
namespace MeasureTheory
section
variable {α F : Type*} {m : MeasurableSpace α} {μ : Measure α} [NormedAddCommGroup F]
theorem Memℒp.integrable_sq {f : α → ℝ} (h : Memℒp f 2 μ) : Integrable (fun x => f x ^ 2) μ := by
simpa [← memℒp_one_iff_integrable] using h.norm_rpow two_ne_zero ENNReal.two_ne_top
#align measure_theory.mem_ℒp.integrable_sq MeasureTheory.Memℒp.integrable_sq
theorem memℒp_two_iff_integrable_sq_norm {f : α → F} (hf : AEStronglyMeasurable f μ) :
Memℒp f 2 μ ↔ Integrable (fun x => ‖f x‖ ^ 2) μ := by
rw [← memℒp_one_iff_integrable]
convert (memℒp_norm_rpow_iff hf two_ne_zero ENNReal.two_ne_top).symm
· simp
· rw [div_eq_mul_inv, ENNReal.mul_inv_cancel two_ne_zero ENNReal.two_ne_top]
#align measure_theory.mem_ℒp_two_iff_integrable_sq_norm MeasureTheory.memℒp_two_iff_integrable_sq_norm
theorem memℒp_two_iff_integrable_sq {f : α → ℝ} (hf : AEStronglyMeasurable f μ) :
Memℒp f 2 μ ↔ Integrable (fun x => f x ^ 2) μ := by
convert memℒp_two_iff_integrable_sq_norm hf using 3
simp
#align measure_theory.mem_ℒp_two_iff_integrable_sq MeasureTheory.memℒp_two_iff_integrable_sq
end
section InnerProductSpace
variable {α : Type*} {m : MeasurableSpace α} {p : ℝ≥0∞} {μ : Measure α}
variable {E 𝕜 : Type*} [RCLike 𝕜] [NormedAddCommGroup E] [InnerProductSpace 𝕜 E]
local notation "⟪" x ", " y "⟫" => @inner 𝕜 E _ x y
theorem Memℒp.const_inner (c : E) {f : α → E} (hf : Memℒp f p μ) : Memℒp (fun a => ⟪c, f a⟫) p μ :=
hf.of_le_mul (AEStronglyMeasurable.inner aestronglyMeasurable_const hf.1)
(eventually_of_forall fun _ => norm_inner_le_norm _ _)
#align measure_theory.mem_ℒp.const_inner MeasureTheory.Memℒp.const_inner
theorem Memℒp.inner_const {f : α → E} (hf : Memℒp f p μ) (c : E) : Memℒp (fun a => ⟪f a, c⟫) p μ :=
hf.of_le_mul (AEStronglyMeasurable.inner hf.1 aestronglyMeasurable_const)
(eventually_of_forall fun x => by rw [mul_comm]; exact norm_inner_le_norm _ _)
#align measure_theory.mem_ℒp.inner_const MeasureTheory.Memℒp.inner_const
variable {f : α → E}
theorem Integrable.const_inner (c : E) (hf : Integrable f μ) :
Integrable (fun x => ⟪c, f x⟫) μ := by
rw [← memℒp_one_iff_integrable] at hf ⊢; exact hf.const_inner c
#align measure_theory.integrable.const_inner MeasureTheory.Integrable.const_inner
theorem Integrable.inner_const (hf : Integrable f μ) (c : E) :
Integrable (fun x => ⟪f x, c⟫) μ := by
rw [← memℒp_one_iff_integrable] at hf ⊢; exact hf.inner_const c
#align measure_theory.integrable.inner_const MeasureTheory.Integrable.inner_const
variable [CompleteSpace E] [NormedSpace ℝ E]
theorem _root_.integral_inner {f : α → E} (hf : Integrable f μ) (c : E) :
∫ x, ⟪c, f x⟫ ∂μ = ⟪c, ∫ x, f x ∂μ⟫ :=
((innerSL 𝕜 c).restrictScalars ℝ).integral_comp_comm hf
#align integral_inner integral_inner
variable (𝕜)
-- variable binder update doesn't work for lemmas which refer to `𝕜` only via the notation
-- Porting note: removed because it causes ambiguity in the lemma below
-- local notation "⟪" x ", " y "⟫" => @inner 𝕜 E _ x y
theorem _root_.integral_eq_zero_of_forall_integral_inner_eq_zero (f : α → E) (hf : Integrable f μ)
(hf_int : ∀ c : E, ∫ x, ⟪c, f x⟫ ∂μ = 0) : ∫ x, f x ∂μ = 0 := by
specialize hf_int (∫ x, f x ∂μ); rwa [integral_inner hf, inner_self_eq_zero] at hf_int
#align integral_eq_zero_of_forall_integral_inner_eq_zero integral_eq_zero_of_forall_integral_inner_eq_zero
end InnerProductSpace
namespace L2
variable {α E F 𝕜 : Type*} [RCLike 𝕜] [MeasurableSpace α] {μ : Measure α} [NormedAddCommGroup E]
[InnerProductSpace 𝕜 E] [NormedAddCommGroup F]
local notation "⟪" x ", " y "⟫" => @inner 𝕜 _ _ x y
theorem snorm_rpow_two_norm_lt_top (f : Lp F 2 μ) : snorm (fun x => ‖f x‖ ^ (2 : ℝ)) 1 μ < ∞ := by
have h_two : ENNReal.ofReal (2 : ℝ) = 2 := by simp [zero_le_one]
rw [snorm_norm_rpow f zero_lt_two, one_mul, h_two]
exact ENNReal.rpow_lt_top_of_nonneg zero_le_two (Lp.snorm_ne_top f)
#align measure_theory.L2.snorm_rpow_two_norm_lt_top MeasureTheory.L2.snorm_rpow_two_norm_lt_top
theorem snorm_inner_lt_top (f g : α →₂[μ] E) : snorm (fun x : α => ⟪f x, g x⟫) 1 μ < ∞ := by
have h : ∀ x, ‖⟪f x, g x⟫‖ ≤ ‖‖f x‖ ^ (2 : ℝ) + ‖g x‖ ^ (2 : ℝ)‖ := by
intro x
rw [← @Nat.cast_two ℝ, Real.rpow_natCast, Real.rpow_natCast]
calc
‖⟪f x, g x⟫‖ ≤ ‖f x‖ * ‖g x‖ := norm_inner_le_norm _ _
_ ≤ 2 * ‖f x‖ * ‖g x‖ :=
(mul_le_mul_of_nonneg_right (le_mul_of_one_le_left (norm_nonneg _) one_le_two)
(norm_nonneg _))
-- TODO(kmill): the type ascription is getting around an elaboration error
_ ≤ ‖(‖f x‖ ^ 2 + ‖g x‖ ^ 2 : ℝ)‖ := (two_mul_le_add_sq _ _).trans (le_abs_self _)
refine (snorm_mono_ae (ae_of_all _ h)).trans_lt ((snorm_add_le ?_ ?_ le_rfl).trans_lt ?_)
· exact ((Lp.aestronglyMeasurable f).norm.aemeasurable.pow_const _).aestronglyMeasurable
· exact ((Lp.aestronglyMeasurable g).norm.aemeasurable.pow_const _).aestronglyMeasurable
rw [ENNReal.add_lt_top]
exact ⟨snorm_rpow_two_norm_lt_top f, snorm_rpow_two_norm_lt_top g⟩
#align measure_theory.L2.snorm_inner_lt_top MeasureTheory.L2.snorm_inner_lt_top
section InnerProductSpace
open scoped ComplexConjugate
instance : Inner 𝕜 (α →₂[μ] E) :=
⟨fun f g => ∫ a, ⟪f a, g a⟫ ∂μ⟩
theorem inner_def (f g : α →₂[μ] E) : ⟪f, g⟫ = ∫ a : α, ⟪f a, g a⟫ ∂μ :=
rfl
#align measure_theory.L2.inner_def MeasureTheory.L2.inner_def
theorem integral_inner_eq_sq_snorm (f : α →₂[μ] E) :
∫ a, ⟪f a, f a⟫ ∂μ = ENNReal.toReal (∫⁻ a, (‖f a‖₊ : ℝ≥0∞) ^ (2 : ℝ) ∂μ) := by
simp_rw [inner_self_eq_norm_sq_to_K]
norm_cast
rw [integral_eq_lintegral_of_nonneg_ae]
rotate_left
· exact Filter.eventually_of_forall fun x => sq_nonneg _
· exact ((Lp.aestronglyMeasurable f).norm.aemeasurable.pow_const _).aestronglyMeasurable
congr
ext1 x
have h_two : (2 : ℝ) = ((2 : ℕ) : ℝ) := by simp
rw [← Real.rpow_natCast _ 2, ← h_two, ←
ENNReal.ofReal_rpow_of_nonneg (norm_nonneg _) zero_le_two, ofReal_norm_eq_coe_nnnorm]
norm_cast
#align measure_theory.L2.integral_inner_eq_sq_snorm MeasureTheory.L2.integral_inner_eq_sq_snorm
private theorem norm_sq_eq_inner' (f : α →₂[μ] E) : ‖f‖ ^ 2 = RCLike.re ⟪f, f⟫ := by
have h_two : (2 : ℝ≥0∞).toReal = 2 := by simp
rw [inner_def, integral_inner_eq_sq_snorm, norm_def, ← ENNReal.toReal_pow, RCLike.ofReal_re,
ENNReal.toReal_eq_toReal (ENNReal.pow_ne_top (Lp.snorm_ne_top f)) _]
· rw [← ENNReal.rpow_natCast, snorm_eq_snorm' two_ne_zero ENNReal.two_ne_top, snorm', ←
ENNReal.rpow_mul, one_div, h_two]
simp
· refine (lintegral_rpow_nnnorm_lt_top_of_snorm'_lt_top zero_lt_two ?_).ne
rw [← h_two, ← snorm_eq_snorm' two_ne_zero ENNReal.two_ne_top]
exact Lp.snorm_lt_top f
theorem mem_L1_inner (f g : α →₂[μ] E) :
AEEqFun.mk (fun x => ⟪f x, g x⟫)
((Lp.aestronglyMeasurable f).inner (Lp.aestronglyMeasurable g)) ∈
Lp 𝕜 1 μ := by
simp_rw [mem_Lp_iff_snorm_lt_top, snorm_aeeqFun]; exact snorm_inner_lt_top f g
#align measure_theory.L2.mem_L1_inner MeasureTheory.L2.mem_L1_inner
theorem integrable_inner (f g : α →₂[μ] E) : Integrable (fun x : α => ⟪f x, g x⟫) μ :=
(integrable_congr
(AEEqFun.coeFn_mk (fun x => ⟪f x, g x⟫)
((Lp.aestronglyMeasurable f).inner (Lp.aestronglyMeasurable g)))).mp
(AEEqFun.integrable_iff_mem_L1.mpr (mem_L1_inner f g))
#align measure_theory.L2.integrable_inner MeasureTheory.L2.integrable_inner
private theorem add_left' (f f' g : α →₂[μ] E) : ⟪f + f', g⟫ = inner f g + inner f' g := by
simp_rw [inner_def, ← integral_add (integrable_inner f g) (integrable_inner f' g), ←
inner_add_left]
refine integral_congr_ae ((coeFn_add f f').mono fun x hx => ?_)
-- Porting note: was
-- congr
-- rwa [Pi.add_apply] at hx
simp only
rw [hx, Pi.add_apply]
private theorem smul_left' (f g : α →₂[μ] E) (r : 𝕜) : ⟪r • f, g⟫ = conj r * inner f g := by
rw [inner_def, inner_def, ← smul_eq_mul, ← integral_smul]
refine integral_congr_ae ((coeFn_smul r f).mono fun x hx => ?_)
simp only
rw [smul_eq_mul, ← inner_smul_left, hx, Pi.smul_apply]
-- Porting note: was
-- rw [smul_eq_mul, ← inner_smul_left]
-- congr
-- rwa [Pi.smul_apply] at hx
instance innerProductSpace : InnerProductSpace 𝕜 (α →₂[μ] E) where
norm_sq_eq_inner := norm_sq_eq_inner'
conj_symm _ _ := by simp_rw [inner_def, ← integral_conj, inner_conj_symm]
add_left := add_left'
smul_left := smul_left'
#align measure_theory.L2.inner_product_space MeasureTheory.L2.innerProductSpace
end InnerProductSpace
section IndicatorConstLp
variable (𝕜) {s : Set α}
/-- The inner product in `L2` of the indicator of a set `indicatorConstLp 2 hs hμs c` and `f` is
equal to the integral of the inner product over `s`: `∫ x in s, ⟪c, f x⟫ ∂μ`. -/
theorem inner_indicatorConstLp_eq_setIntegral_inner (f : Lp E 2 μ) (hs : MeasurableSet s) (c : E)
(hμs : μ s ≠ ∞) : (⟪indicatorConstLp 2 hs hμs c, f⟫ : 𝕜) = ∫ x in s, ⟪c, f x⟫ ∂μ := by
rw [inner_def, ← integral_add_compl hs (L2.integrable_inner _ f)]
have h_left : (∫ x in s, ⟪(indicatorConstLp 2 hs hμs c) x, f x⟫ ∂μ) = ∫ x in s, ⟪c, f x⟫ ∂μ := by
suffices h_ae_eq : ∀ᵐ x ∂μ, x ∈ s → ⟪indicatorConstLp 2 hs hμs c x, f x⟫ = ⟪c, f x⟫ from
setIntegral_congr_ae hs h_ae_eq
have h_indicator : ∀ᵐ x : α ∂μ, x ∈ s → indicatorConstLp 2 hs hμs c x = c :=
indicatorConstLp_coeFn_mem
refine h_indicator.mono fun x hx hxs => ?_
congr
exact hx hxs
have h_right : (∫ x in sᶜ, ⟪(indicatorConstLp 2 hs hμs c) x, f x⟫ ∂μ) = 0 := by
suffices h_ae_eq : ∀ᵐ x ∂μ, x ∉ s → ⟪indicatorConstLp 2 hs hμs c x, f x⟫ = 0 by
simp_rw [← Set.mem_compl_iff] at h_ae_eq
suffices h_int_zero :
(∫ x in sᶜ, inner (indicatorConstLp 2 hs hμs c x) (f x) ∂μ) = ∫ _ in sᶜ, (0 : 𝕜) ∂μ by
rw [h_int_zero]
simp
exact setIntegral_congr_ae hs.compl h_ae_eq
have h_indicator : ∀ᵐ x : α ∂μ, x ∉ s → indicatorConstLp 2 hs hμs c x = 0 :=
indicatorConstLp_coeFn_nmem
refine h_indicator.mono fun x hx hxs => ?_
rw [hx hxs]
exact inner_zero_left _
rw [h_left, h_right, add_zero]
#align measure_theory.L2.inner_indicator_const_Lp_eq_set_integral_inner MeasureTheory.L2.inner_indicatorConstLp_eq_setIntegral_inner
@[deprecated (since := "2024-04-17")]
alias inner_indicatorConstLp_eq_set_integral_inner :=
inner_indicatorConstLp_eq_setIntegral_inner
/-- The inner product in `L2` of the indicator of a set `indicatorConstLp 2 hs hμs c` and `f` is
equal to the inner product of the constant `c` and the integral of `f` over `s`. -/
| Mathlib/MeasureTheory/Function/L2Space.lean | 264 | 268 | theorem inner_indicatorConstLp_eq_inner_setIntegral [CompleteSpace E] [NormedSpace ℝ E]
(hs : MeasurableSet s) (hμs : μ s ≠ ∞) (c : E) (f : Lp E 2 μ) :
(⟪indicatorConstLp 2 hs hμs c, f⟫ : 𝕜) = ⟪c, ∫ x in s, f x ∂μ⟫ := by |
rw [← integral_inner (integrableOn_Lp_of_measure_ne_top f fact_one_le_two_ennreal.elim hμs),
L2.inner_indicatorConstLp_eq_setIntegral_inner]
|
/-
Copyright (c) 2021 Anatole Dedecker. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anatole Dedecker
-/
import Mathlib.Analysis.Normed.Order.Basic
import Mathlib.Analysis.Asymptotics.Asymptotics
import Mathlib.Analysis.NormedSpace.Basic
#align_import analysis.asymptotics.specific_asymptotics from "leanprover-community/mathlib"@"f2ce6086713c78a7f880485f7917ea547a215982"
/-!
# A collection of specific asymptotic results
This file contains specific lemmas about asymptotics which don't have their place in the general
theory developed in `Mathlib.Analysis.Asymptotics.Asymptotics`.
-/
open Filter Asymptotics
open Topology
section NormedField
/-- If `f : 𝕜 → E` is bounded in a punctured neighborhood of `a`, then `f(x) = o((x - a)⁻¹)` as
`x → a`, `x ≠ a`. -/
theorem Filter.IsBoundedUnder.isLittleO_sub_self_inv {𝕜 E : Type*} [NormedField 𝕜] [Norm E] {a : 𝕜}
{f : 𝕜 → E} (h : IsBoundedUnder (· ≤ ·) (𝓝[≠] a) (norm ∘ f)) :
f =o[𝓝[≠] a] fun x => (x - a)⁻¹ := by
refine (h.isBigO_const (one_ne_zero' ℝ)).trans_isLittleO (isLittleO_const_left.2 <| Or.inr ?_)
simp only [(· ∘ ·), norm_inv]
exact (tendsto_norm_sub_self_punctured_nhds a).inv_tendsto_zero
#align filter.is_bounded_under.is_o_sub_self_inv Filter.IsBoundedUnder.isLittleO_sub_self_inv
end NormedField
section LinearOrderedField
variable {𝕜 : Type*} [LinearOrderedField 𝕜]
theorem pow_div_pow_eventuallyEq_atTop {p q : ℕ} :
(fun x : 𝕜 => x ^ p / x ^ q) =ᶠ[atTop] fun x => x ^ ((p : ℤ) - q) := by
apply (eventually_gt_atTop (0 : 𝕜)).mono fun x hx => _
intro x hx
simp [zpow_sub₀ hx.ne']
#align pow_div_pow_eventually_eq_at_top pow_div_pow_eventuallyEq_atTop
theorem pow_div_pow_eventuallyEq_atBot {p q : ℕ} :
(fun x : 𝕜 => x ^ p / x ^ q) =ᶠ[atBot] fun x => x ^ ((p : ℤ) - q) := by
apply (eventually_lt_atBot (0 : 𝕜)).mono fun x hx => _
intro x hx
simp [zpow_sub₀ hx.ne]
#align pow_div_pow_eventually_eq_at_bot pow_div_pow_eventuallyEq_atBot
theorem tendsto_pow_div_pow_atTop_atTop {p q : ℕ} (hpq : q < p) :
Tendsto (fun x : 𝕜 => x ^ p / x ^ q) atTop atTop := by
rw [tendsto_congr' pow_div_pow_eventuallyEq_atTop]
apply tendsto_zpow_atTop_atTop
omega
#align tendsto_pow_div_pow_at_top_at_top tendsto_pow_div_pow_atTop_atTop
theorem tendsto_pow_div_pow_atTop_zero [TopologicalSpace 𝕜] [OrderTopology 𝕜] {p q : ℕ}
(hpq : p < q) : Tendsto (fun x : 𝕜 => x ^ p / x ^ q) atTop (𝓝 0) := by
rw [tendsto_congr' pow_div_pow_eventuallyEq_atTop]
apply tendsto_zpow_atTop_zero
omega
#align tendsto_pow_div_pow_at_top_zero tendsto_pow_div_pow_atTop_zero
end LinearOrderedField
section NormedLinearOrderedField
variable {𝕜 : Type*} [NormedLinearOrderedField 𝕜]
theorem Asymptotics.isLittleO_pow_pow_atTop_of_lt [OrderTopology 𝕜] {p q : ℕ} (hpq : p < q) :
(fun x : 𝕜 => x ^ p) =o[atTop] fun x => x ^ q := by
refine (isLittleO_iff_tendsto' ?_).mpr (tendsto_pow_div_pow_atTop_zero hpq)
exact (eventually_gt_atTop 0).mono fun x hx hxq => (pow_ne_zero q hx.ne' hxq).elim
#align asymptotics.is_o_pow_pow_at_top_of_lt Asymptotics.isLittleO_pow_pow_atTop_of_lt
theorem Asymptotics.IsBigO.trans_tendsto_norm_atTop {α : Type*} {u v : α → 𝕜} {l : Filter α}
(huv : u =O[l] v) (hu : Tendsto (fun x => ‖u x‖) l atTop) :
Tendsto (fun x => ‖v x‖) l atTop := by
rcases huv.exists_pos with ⟨c, hc, hcuv⟩
rw [IsBigOWith] at hcuv
convert Tendsto.atTop_div_const hc (tendsto_atTop_mono' l hcuv hu)
rw [mul_div_cancel_left₀ _ hc.ne.symm]
set_option linter.uppercaseLean3 false in
#align asymptotics.is_O.trans_tendsto_norm_at_top Asymptotics.IsBigO.trans_tendsto_norm_atTop
end NormedLinearOrderedField
section Real
open Finset
theorem Asymptotics.IsLittleO.sum_range {α : Type*} [NormedAddCommGroup α] {f : ℕ → α} {g : ℕ → ℝ}
(h : f =o[atTop] g) (hg : 0 ≤ g) (h'g : Tendsto (fun n => ∑ i ∈ range n, g i) atTop atTop) :
(fun n => ∑ i ∈ range n, f i) =o[atTop] fun n => ∑ i ∈ range n, g i := by
have A : ∀ i, ‖g i‖ = g i := fun i => Real.norm_of_nonneg (hg i)
have B : ∀ n, ‖∑ i ∈ range n, g i‖ = ∑ i ∈ range n, g i := fun n => by
rwa [Real.norm_eq_abs, abs_sum_of_nonneg']
apply isLittleO_iff.2 fun ε εpos => _
intro ε εpos
obtain ⟨N, hN⟩ : ∃ N : ℕ, ∀ b : ℕ, N ≤ b → ‖f b‖ ≤ ε / 2 * g b := by
simpa only [A, eventually_atTop] using isLittleO_iff.mp h (half_pos εpos)
have : (fun _ : ℕ => ∑ i ∈ range N, f i) =o[atTop] fun n : ℕ => ∑ i ∈ range n, g i := by
apply isLittleO_const_left.2
exact Or.inr (h'g.congr fun n => (B n).symm)
filter_upwards [isLittleO_iff.1 this (half_pos εpos), Ici_mem_atTop N] with n hn Nn
calc
‖∑ i ∈ range n, f i‖ = ‖(∑ i ∈ range N, f i) + ∑ i ∈ Ico N n, f i‖ := by
rw [sum_range_add_sum_Ico _ Nn]
_ ≤ ‖∑ i ∈ range N, f i‖ + ‖∑ i ∈ Ico N n, f i‖ := norm_add_le _ _
_ ≤ ‖∑ i ∈ range N, f i‖ + ∑ i ∈ Ico N n, ε / 2 * g i :=
(add_le_add le_rfl (norm_sum_le_of_le _ fun i hi => hN _ (mem_Ico.1 hi).1))
_ ≤ ‖∑ i ∈ range N, f i‖ + ∑ i ∈ range n, ε / 2 * g i := by
gcongr
apply sum_le_sum_of_subset_of_nonneg
· rw [range_eq_Ico]
exact Ico_subset_Ico (zero_le _) le_rfl
· intro i _ _
exact mul_nonneg (half_pos εpos).le (hg i)
_ ≤ ε / 2 * ‖∑ i ∈ range n, g i‖ + ε / 2 * ∑ i ∈ range n, g i := by rw [← mul_sum]; gcongr
_ = ε * ‖∑ i ∈ range n, g i‖ := by
simp only [B]
ring
#align asymptotics.is_o.sum_range Asymptotics.IsLittleO.sum_range
| Mathlib/Analysis/Asymptotics/SpecificAsymptotics.lean | 131 | 136 | theorem Asymptotics.isLittleO_sum_range_of_tendsto_zero {α : Type*} [NormedAddCommGroup α]
{f : ℕ → α} (h : Tendsto f atTop (𝓝 0)) :
(fun n => ∑ i ∈ range n, f i) =o[atTop] fun n => (n : ℝ) := by |
have := ((isLittleO_one_iff ℝ).2 h).sum_range fun i => zero_le_one
simp only [sum_const, card_range, Nat.smul_one_eq_cast] at this
exact this tendsto_natCast_atTop_atTop
|
/-
Copyright (c) 2022 Andrew Yang. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Andrew Yang
-/
import Mathlib.CategoryTheory.Adjunction.FullyFaithful
import Mathlib.CategoryTheory.Adjunction.Limits
import Mathlib.CategoryTheory.Limits.Shapes.CommSq
import Mathlib.CategoryTheory.Limits.Shapes.StrictInitial
import Mathlib.CategoryTheory.Limits.FunctorCategory
import Mathlib.CategoryTheory.Limits.Constructions.FiniteProductsOfBinaryProducts
#align_import category_theory.extensive from "leanprover-community/mathlib"@"178a32653e369dce2da68dc6b2694e385d484ef1"
/-!
# Universal colimits and van Kampen colimits
## Main definitions
- `CategoryTheory.IsUniversalColimit`: A (colimit) cocone over a diagram `F : J ⥤ C` is universal
if it is stable under pullbacks.
- `CategoryTheory.IsVanKampenColimit`: A (colimit) cocone over a diagram `F : J ⥤ C` is van
Kampen if for every cocone `c'` over the pullback of the diagram `F' : J ⥤ C'`,
`c'` is colimiting iff `c'` is the pullback of `c`.
## References
- https://ncatlab.org/nlab/show/van+Kampen+colimit
- [Stephen Lack and Paweł Sobociński, Adhesive Categories][adhesive2004]
-/
open CategoryTheory.Limits
namespace CategoryTheory
universe v' u' v u
variable {J : Type v'} [Category.{u'} J] {C : Type u} [Category.{v} C]
variable {K : Type*} [Category K] {D : Type*} [Category D]
section NatTrans
/-- A natural transformation is equifibered if every commutative square of the following form is
a pullback.
```
F(X) → F(Y)
↓ ↓
G(X) → G(Y)
```
-/
def NatTrans.Equifibered {F G : J ⥤ C} (α : F ⟶ G) : Prop :=
∀ ⦃i j : J⦄ (f : i ⟶ j), IsPullback (F.map f) (α.app i) (α.app j) (G.map f)
#align category_theory.nat_trans.equifibered CategoryTheory.NatTrans.Equifibered
theorem NatTrans.equifibered_of_isIso {F G : J ⥤ C} (α : F ⟶ G) [IsIso α] : Equifibered α :=
fun _ _ f => IsPullback.of_vert_isIso ⟨NatTrans.naturality _ f⟩
#align category_theory.nat_trans.equifibered_of_is_iso CategoryTheory.NatTrans.equifibered_of_isIso
theorem NatTrans.Equifibered.comp {F G H : J ⥤ C} {α : F ⟶ G} {β : G ⟶ H} (hα : Equifibered α)
(hβ : Equifibered β) : Equifibered (α ≫ β) :=
fun _ _ f => (hα f).paste_vert (hβ f)
#align category_theory.nat_trans.equifibered.comp CategoryTheory.NatTrans.Equifibered.comp
theorem NatTrans.Equifibered.whiskerRight {F G : J ⥤ C} {α : F ⟶ G} (hα : Equifibered α)
(H : C ⥤ D) [∀ (i j : J) (f : j ⟶ i), PreservesLimit (cospan (α.app i) (G.map f)) H] :
Equifibered (whiskerRight α H) :=
fun _ _ f => (hα f).map H
#align category_theory.nat_trans.equifibered.whisker_right CategoryTheory.NatTrans.Equifibered.whiskerRight
theorem NatTrans.Equifibered.whiskerLeft {K : Type*} [Category K] {F G : J ⥤ C} {α : F ⟶ G}
(hα : Equifibered α) (H : K ⥤ J) : Equifibered (whiskerLeft H α) :=
fun _ _ f => hα (H.map f)
theorem mapPair_equifibered {F F' : Discrete WalkingPair ⥤ C} (α : F ⟶ F') :
NatTrans.Equifibered α := by
rintro ⟨⟨⟩⟩ ⟨j⟩ ⟨⟨rfl : _ = j⟩⟩
all_goals
dsimp; simp only [Discrete.functor_map_id]
exact IsPullback.of_horiz_isIso ⟨by simp only [Category.comp_id, Category.id_comp]⟩
#align category_theory.map_pair_equifibered CategoryTheory.mapPair_equifibered
theorem NatTrans.equifibered_of_discrete {ι : Type*} {F G : Discrete ι ⥤ C}
(α : F ⟶ G) : NatTrans.Equifibered α := by
rintro ⟨i⟩ ⟨j⟩ ⟨⟨rfl : i = j⟩⟩
simp only [Discrete.functor_map_id]
exact IsPullback.of_horiz_isIso ⟨by rw [Category.id_comp, Category.comp_id]⟩
end NatTrans
/-- A (colimit) cocone over a diagram `F : J ⥤ C` is universal if it is stable under pullbacks. -/
def IsUniversalColimit {F : J ⥤ C} (c : Cocone F) : Prop :=
∀ ⦃F' : J ⥤ C⦄ (c' : Cocone F') (α : F' ⟶ F) (f : c'.pt ⟶ c.pt)
(_ : α ≫ c.ι = c'.ι ≫ (Functor.const J).map f) (_ : NatTrans.Equifibered α),
(∀ j : J, IsPullback (c'.ι.app j) (α.app j) f (c.ι.app j)) → Nonempty (IsColimit c')
#align category_theory.is_universal_colimit CategoryTheory.IsUniversalColimit
/-- A (colimit) cocone over a diagram `F : J ⥤ C` is van Kampen if for every cocone `c'` over the
pullback of the diagram `F' : J ⥤ C'`, `c'` is colimiting iff `c'` is the pullback of `c`.
TODO: Show that this is iff the functor `C ⥤ Catᵒᵖ` sending `x` to `C/x` preserves it.
TODO: Show that this is iff the inclusion functor `C ⥤ Span(C)` preserves it.
-/
def IsVanKampenColimit {F : J ⥤ C} (c : Cocone F) : Prop :=
∀ ⦃F' : J ⥤ C⦄ (c' : Cocone F') (α : F' ⟶ F) (f : c'.pt ⟶ c.pt)
(_ : α ≫ c.ι = c'.ι ≫ (Functor.const J).map f) (_ : NatTrans.Equifibered α),
Nonempty (IsColimit c') ↔ ∀ j : J, IsPullback (c'.ι.app j) (α.app j) f (c.ι.app j)
#align category_theory.is_van_kampen_colimit CategoryTheory.IsVanKampenColimit
theorem IsVanKampenColimit.isUniversal {F : J ⥤ C} {c : Cocone F} (H : IsVanKampenColimit c) :
IsUniversalColimit c :=
fun _ c' α f h hα => (H c' α f h hα).mpr
#align category_theory.is_van_kampen_colimit.is_universal CategoryTheory.IsVanKampenColimit.isUniversal
/-- A universal colimit is a colimit. -/
noncomputable def IsUniversalColimit.isColimit {F : J ⥤ C} {c : Cocone F}
(h : IsUniversalColimit c) : IsColimit c := by
refine ((h c (𝟙 F) (𝟙 c.pt : _) (by rw [Functor.map_id, Category.comp_id, Category.id_comp])
(NatTrans.equifibered_of_isIso _)) fun j => ?_).some
haveI : IsIso (𝟙 c.pt) := inferInstance
exact IsPullback.of_vert_isIso ⟨by erw [NatTrans.id_app, Category.comp_id, Category.id_comp]⟩
/-- A van Kampen colimit is a colimit. -/
noncomputable def IsVanKampenColimit.isColimit {F : J ⥤ C} {c : Cocone F}
(h : IsVanKampenColimit c) : IsColimit c :=
h.isUniversal.isColimit
#align category_theory.is_van_kampen_colimit.is_colimit CategoryTheory.IsVanKampenColimit.isColimit
theorem IsInitial.isVanKampenColimit [HasStrictInitialObjects C] {X : C} (h : IsInitial X) :
IsVanKampenColimit (asEmptyCocone X) := by
intro F' c' α f hf hα
have : F' = Functor.empty C := by apply Functor.hext <;> rintro ⟨⟨⟩⟩
subst this
haveI := h.isIso_to f
refine ⟨by rintro _ ⟨⟨⟩⟩,
fun _ => ⟨IsColimit.ofIsoColimit h (Cocones.ext (asIso f).symm <| by rintro ⟨⟨⟩⟩)⟩⟩
#align category_theory.is_initial.is_van_kampen_colimit CategoryTheory.IsInitial.isVanKampenColimit
section Functor
theorem IsUniversalColimit.of_iso {F : J ⥤ C} {c c' : Cocone F} (hc : IsUniversalColimit c)
(e : c ≅ c') : IsUniversalColimit c' := by
intro F' c'' α f h hα H
have : c'.ι ≫ (Functor.const J).map e.inv.hom = c.ι := by
ext j
exact e.inv.2 j
apply hc c'' α (f ≫ e.inv.1) (by rw [Functor.map_comp, ← reassoc_of% h, this]) hα
intro j
rw [← Category.comp_id (α.app j)]
have : IsIso e.inv.hom := Functor.map_isIso (Cocones.forget _) e.inv
exact (H j).paste_vert (IsPullback.of_vert_isIso ⟨by simp⟩)
theorem IsVanKampenColimit.of_iso {F : J ⥤ C} {c c' : Cocone F} (H : IsVanKampenColimit c)
(e : c ≅ c') : IsVanKampenColimit c' := by
intro F' c'' α f h hα
have : c'.ι ≫ (Functor.const J).map e.inv.hom = c.ι := by
ext j
exact e.inv.2 j
rw [H c'' α (f ≫ e.inv.1) (by rw [Functor.map_comp, ← reassoc_of% h, this]) hα]
apply forall_congr'
intro j
conv_lhs => rw [← Category.comp_id (α.app j)]
haveI : IsIso e.inv.hom := Functor.map_isIso (Cocones.forget _) e.inv
exact (IsPullback.of_vert_isIso ⟨by simp⟩).paste_vert_iff (NatTrans.congr_app h j).symm
#align category_theory.is_van_kampen_colimit.of_iso CategoryTheory.IsVanKampenColimit.of_iso
theorem IsVanKampenColimit.precompose_isIso {F G : J ⥤ C} (α : F ⟶ G) [IsIso α]
{c : Cocone G} (hc : IsVanKampenColimit c) :
IsVanKampenColimit ((Cocones.precompose α).obj c) := by
intros F' c' α' f e hα
refine (hc c' (α' ≫ α) f ((Category.assoc _ _ _).trans e)
(hα.comp (NatTrans.equifibered_of_isIso _))).trans ?_
apply forall_congr'
intro j
simp only [Functor.const_obj_obj, NatTrans.comp_app,
Cocones.precompose_obj_pt, Cocones.precompose_obj_ι]
have : IsPullback (α.app j ≫ c.ι.app j) (α.app j) (𝟙 _) (c.ι.app j) :=
IsPullback.of_vert_isIso ⟨Category.comp_id _⟩
rw [← IsPullback.paste_vert_iff this _, Category.comp_id]
exact (congr_app e j).symm
theorem IsUniversalColimit.precompose_isIso {F G : J ⥤ C} (α : F ⟶ G) [IsIso α]
{c : Cocone G} (hc : IsUniversalColimit c) :
IsUniversalColimit ((Cocones.precompose α).obj c) := by
intros F' c' α' f e hα H
apply (hc c' (α' ≫ α) f ((Category.assoc _ _ _).trans e)
(hα.comp (NatTrans.equifibered_of_isIso _)))
intro j
simp only [Functor.const_obj_obj, NatTrans.comp_app,
Cocones.precompose_obj_pt, Cocones.precompose_obj_ι]
rw [← Category.comp_id f]
exact (H j).paste_vert (IsPullback.of_vert_isIso ⟨Category.comp_id _⟩)
theorem IsVanKampenColimit.precompose_isIso_iff {F G : J ⥤ C} (α : F ⟶ G) [IsIso α]
{c : Cocone G} : IsVanKampenColimit ((Cocones.precompose α).obj c) ↔ IsVanKampenColimit c :=
⟨fun hc ↦ IsVanKampenColimit.of_iso (IsVanKampenColimit.precompose_isIso (inv α) hc)
(Cocones.ext (Iso.refl _) (by simp)),
IsVanKampenColimit.precompose_isIso α⟩
theorem IsUniversalColimit.of_mapCocone (G : C ⥤ D) {F : J ⥤ C} {c : Cocone F}
[PreservesLimitsOfShape WalkingCospan G] [ReflectsColimitsOfShape J G]
(hc : IsUniversalColimit (G.mapCocone c)) : IsUniversalColimit c :=
fun F' c' α f h hα H ↦
⟨ReflectsColimit.reflects (hc (G.mapCocone c') (whiskerRight α G) (G.map f)
(by ext j; simpa using G.congr_map (NatTrans.congr_app h j))
(hα.whiskerRight G) (fun j ↦ (H j).map G)).some⟩
theorem IsVanKampenColimit.of_mapCocone (G : C ⥤ D) {F : J ⥤ C} {c : Cocone F}
[∀ (i j : J) (X : C) (f : X ⟶ F.obj j) (g : i ⟶ j), PreservesLimit (cospan f (F.map g)) G]
[∀ (i : J) (X : C) (f : X ⟶ c.pt), PreservesLimit (cospan f (c.ι.app i)) G]
[ReflectsLimitsOfShape WalkingCospan G]
[PreservesColimitsOfShape J G]
[ReflectsColimitsOfShape J G]
(H : IsVanKampenColimit (G.mapCocone c)) : IsVanKampenColimit c := by
intro F' c' α f h hα
refine (Iff.trans ?_ (H (G.mapCocone c') (whiskerRight α G) (G.map f)
(by ext j; simpa using G.congr_map (NatTrans.congr_app h j))
(hα.whiskerRight G))).trans (forall_congr' fun j => ?_)
· exact ⟨fun h => ⟨isColimitOfPreserves G h.some⟩, fun h => ⟨isColimitOfReflects G h.some⟩⟩
· exact IsPullback.map_iff G (NatTrans.congr_app h.symm j)
#align category_theory.is_van_kampen_colimit.of_map CategoryTheory.IsVanKampenColimit.of_mapCocone
theorem IsVanKampenColimit.mapCocone_iff (G : C ⥤ D) {F : J ⥤ C} {c : Cocone F}
[G.IsEquivalence] : IsVanKampenColimit (G.mapCocone c) ↔ IsVanKampenColimit c :=
⟨IsVanKampenColimit.of_mapCocone G, fun hc ↦ by
let e : F ⋙ G ⋙ Functor.inv G ≅ F := NatIso.hcomp (Iso.refl F) G.asEquivalence.unitIso.symm
apply IsVanKampenColimit.of_mapCocone G.inv
apply (IsVanKampenColimit.precompose_isIso_iff e.inv).mp
exact hc.of_iso (Cocones.ext (G.asEquivalence.unitIso.app c.pt) (fun j => (by simp [e])))⟩
theorem IsUniversalColimit.whiskerEquivalence {K : Type*} [Category K] (e : J ≌ K)
{F : K ⥤ C} {c : Cocone F} (hc : IsUniversalColimit c) :
IsUniversalColimit (c.whisker e.functor) := by
intro F' c' α f e' hα H
convert hc (c'.whisker e.inverse) (whiskerLeft e.inverse α ≫ (e.invFunIdAssoc F).hom) f ?_
((hα.whiskerLeft _).comp (NatTrans.equifibered_of_isIso _)) ?_ using 1
· exact (IsColimit.whiskerEquivalenceEquiv e.symm).nonempty_congr
· convert congr_arg (whiskerLeft e.inverse) e'
ext
simp
· intro k
rw [← Category.comp_id f]
refine (H (e.inverse.obj k)).paste_vert ?_
have : IsIso (𝟙 (Cocone.whisker e.functor c).pt) := inferInstance
exact IsPullback.of_vert_isIso ⟨by simp⟩
theorem IsUniversalColimit.whiskerEquivalence_iff {K : Type*} [Category K] (e : J ≌ K)
{F : K ⥤ C} {c : Cocone F} :
IsUniversalColimit (c.whisker e.functor) ↔ IsUniversalColimit c :=
⟨fun hc ↦ ((hc.whiskerEquivalence e.symm).precompose_isIso (e.invFunIdAssoc F).inv).of_iso
(Cocones.ext (Iso.refl _) (by simp)), IsUniversalColimit.whiskerEquivalence e⟩
theorem IsVanKampenColimit.whiskerEquivalence {K : Type*} [Category K] (e : J ≌ K)
{F : K ⥤ C} {c : Cocone F} (hc : IsVanKampenColimit c) :
IsVanKampenColimit (c.whisker e.functor) := by
intro F' c' α f e' hα
convert hc (c'.whisker e.inverse) (whiskerLeft e.inverse α ≫ (e.invFunIdAssoc F).hom) f ?_
((hα.whiskerLeft _).comp (NatTrans.equifibered_of_isIso _)) using 1
· exact (IsColimit.whiskerEquivalenceEquiv e.symm).nonempty_congr
· simp only [Functor.const_obj_obj, Functor.comp_obj, Cocone.whisker_pt, Cocone.whisker_ι,
whiskerLeft_app, NatTrans.comp_app, Equivalence.invFunIdAssoc_hom_app, Functor.id_obj]
constructor
· intro H k
rw [← Category.comp_id f]
refine (H (e.inverse.obj k)).paste_vert ?_
have : IsIso (𝟙 (Cocone.whisker e.functor c).pt) := inferInstance
exact IsPullback.of_vert_isIso ⟨by simp⟩
· intro H j
have : α.app j
= F'.map (e.unit.app _) ≫ α.app _ ≫ F.map (e.counit.app (e.functor.obj j)) := by
simp [← Functor.map_comp]
rw [← Category.id_comp f, this]
refine IsPullback.paste_vert ?_ (H (e.functor.obj j))
exact IsPullback.of_vert_isIso ⟨by simp⟩
· ext k
simpa using congr_app e' (e.inverse.obj k)
theorem IsVanKampenColimit.whiskerEquivalence_iff {K : Type*} [Category K] (e : J ≌ K)
{F : K ⥤ C} {c : Cocone F} :
IsVanKampenColimit (c.whisker e.functor) ↔ IsVanKampenColimit c :=
⟨fun hc ↦ ((hc.whiskerEquivalence e.symm).precompose_isIso (e.invFunIdAssoc F).inv).of_iso
(Cocones.ext (Iso.refl _) (by simp)), IsVanKampenColimit.whiskerEquivalence e⟩
theorem isVanKampenColimit_of_evaluation [HasPullbacks D] [HasColimitsOfShape J D] (F : J ⥤ C ⥤ D)
(c : Cocone F) (hc : ∀ x : C, IsVanKampenColimit (((evaluation C D).obj x).mapCocone c)) :
IsVanKampenColimit c := by
intro F' c' α f e hα
have := fun x => hc x (((evaluation C D).obj x).mapCocone c') (whiskerRight α _)
(((evaluation C D).obj x).map f)
(by
ext y
dsimp
exact NatTrans.congr_app (NatTrans.congr_app e y) x)
(hα.whiskerRight _)
constructor
· rintro ⟨hc'⟩ j
refine ⟨⟨(NatTrans.congr_app e j).symm⟩, ⟨evaluationJointlyReflectsLimits _ ?_⟩⟩
refine fun x => (isLimitMapConePullbackConeEquiv _ _).symm ?_
exact ((this x).mp ⟨PreservesColimit.preserves hc'⟩ _).isLimit
· exact fun H => ⟨evaluationJointlyReflectsColimits _ fun x =>
((this x).mpr fun j => (H j).map ((evaluation C D).obj x)).some⟩
#align category_theory.is_van_kampen_colimit_of_evaluation CategoryTheory.isVanKampenColimit_of_evaluation
end Functor
section reflective
theorem IsUniversalColimit.map_reflective
{Gl : C ⥤ D} {Gr : D ⥤ C} (adj : Gl ⊣ Gr) [Gr.Full] [Gr.Faithful]
{F : J ⥤ D} {c : Cocone (F ⋙ Gr)}
(H : IsUniversalColimit c)
[∀ X (f : X ⟶ Gl.obj c.pt), HasPullback (Gr.map f) (adj.unit.app c.pt)]
[∀ X (f : X ⟶ Gl.obj c.pt), PreservesLimit (cospan (Gr.map f) (adj.unit.app c.pt)) Gl] :
IsUniversalColimit (Gl.mapCocone c) := by
have := adj.rightAdjointPreservesLimits
have : PreservesColimitsOfSize.{u', v'} Gl := adj.leftAdjointPreservesColimits
intros F' c' α f h hα hc'
have : HasPullback (Gl.map (Gr.map f)) (Gl.map (adj.unit.app c.pt)) :=
⟨⟨_, isLimitPullbackConeMapOfIsLimit _ pullback.condition
(IsPullback.of_hasPullback _ _).isLimit⟩⟩
let α' := α ≫ (Functor.associator _ _ _).hom ≫ whiskerLeft F adj.counit ≫ F.rightUnitor.hom
have hα' : NatTrans.Equifibered α' := hα.comp (NatTrans.equifibered_of_isIso _)
have hadj : ∀ X, Gl.map (adj.unit.app X) = inv (adj.counit.app _) := by
intro X
apply IsIso.eq_inv_of_inv_hom_id
exact adj.left_triangle_components _
haveI : ∀ X, IsIso (Gl.map (adj.unit.app X)) := by
simp_rw [hadj]
infer_instance
have hα'' : ∀ j, Gl.map (Gr.map <| α'.app j) = adj.counit.app _ ≫ α.app j := by
intro j
rw [← cancel_mono (adj.counit.app <| F.obj j)]
dsimp [α']
simp only [Category.comp_id, Adjunction.counit_naturality_assoc, Category.id_comp,
Adjunction.counit_naturality, Category.assoc, Functor.map_comp]
have hc'' : ∀ j, α.app j ≫ Gl.map (c.ι.app j) = c'.ι.app j ≫ f := NatTrans.congr_app h
let β := isoWhiskerLeft F' (asIso adj.counit) ≪≫ F'.rightUnitor
let c'' : Cocone (F' ⋙ Gr) := by
refine
{ pt := pullback (Gr.map f) (adj.unit.app _)
ι := { app := fun j ↦ pullback.lift (Gr.map <| c'.ι.app j) (Gr.map (α'.app j) ≫ c.ι.app j) ?_
naturality := ?_ } }
· rw [← Gr.map_comp, ← hc'']
erw [← adj.unit_naturality]
rw [Gl.map_comp, hα'']
dsimp
simp only [Category.assoc, Functor.map_comp, adj.right_triangle_components_assoc]
· intros i j g
dsimp [α']
ext
all_goals simp only [Category.comp_id, Category.id_comp, Category.assoc,
← Functor.map_comp, pullback.lift_fst, pullback.lift_snd, ← Functor.map_comp_assoc]
· congr 1
exact c'.w _
· rw [α.naturality_assoc]
dsimp
rw [adj.counit_naturality, ← Category.assoc, Gr.map_comp_assoc]
congr 1
exact c.w _
let cf : (Cocones.precompose β.hom).obj c' ⟶ Gl.mapCocone c'' := by
refine { hom := pullback.lift ?_ f ?_ ≫ (PreservesPullback.iso _ _ _).inv, w := ?_ }
· exact inv <| adj.counit.app c'.pt
· rw [IsIso.inv_comp_eq, ← adj.counit_naturality_assoc f, ← cancel_mono (adj.counit.app <|
Gl.obj c.pt), Category.assoc, Category.assoc, adj.left_triangle_components]
erw [Category.comp_id]
rfl
· intro j
rw [← Category.assoc, Iso.comp_inv_eq]
ext
all_goals simp only [PreservesPullback.iso_hom_fst, PreservesPullback.iso_hom_snd,
pullback.lift_fst, pullback.lift_snd, Category.assoc,
Functor.mapCocone_ι_app, ← Gl.map_comp]
· rw [IsIso.comp_inv_eq, adj.counit_naturality]
dsimp [β]
rw [Category.comp_id]
· rw [Gl.map_comp, hα'', Category.assoc, hc'']
dsimp [β]
rw [Category.comp_id, Category.assoc]
have : cf.hom ≫ (PreservesPullback.iso _ _ _).hom ≫ pullback.fst ≫ adj.counit.app _ = 𝟙 _ := by
simp only [IsIso.inv_hom_id, Iso.inv_hom_id_assoc, Category.assoc, pullback.lift_fst_assoc]
have : IsIso cf := by
apply @Cocones.cocone_iso_of_hom_iso (i := ?_)
rw [← IsIso.eq_comp_inv] at this
rw [this]
infer_instance
have ⟨Hc''⟩ := H c'' (whiskerRight α' Gr) pullback.snd ?_ (hα'.whiskerRight Gr) ?_
· exact ⟨IsColimit.precomposeHomEquiv β c' <|
(isColimitOfPreserves Gl Hc'').ofIsoColimit (asIso cf).symm⟩
· ext j
dsimp
simp only [Category.comp_id, Category.id_comp, Category.assoc,
Functor.map_comp, pullback.lift_snd]
· intro j
apply IsPullback.of_right _ _ (IsPullback.of_hasPullback _ _)
· dsimp [α']
simp only [Category.comp_id, Category.id_comp, Category.assoc, Functor.map_comp,
pullback.lift_fst]
rw [← Category.comp_id (Gr.map f)]
refine ((hc' j).map Gr).paste_vert (IsPullback.of_vert_isIso ⟨?_⟩)
rw [← adj.unit_naturality, Category.comp_id, ← Category.assoc,
← Category.id_comp (Gr.map ((Gl.mapCocone c).ι.app j))]
congr 1
rw [← cancel_mono (Gr.map (adj.counit.app (F.obj j)))]
dsimp
simp only [Category.comp_id, Adjunction.right_triangle_components, Category.id_comp,
Category.assoc]
· dsimp
simp only [Category.comp_id, Category.id_comp, Category.assoc, Functor.map_comp,
pullback.lift_snd]
| Mathlib/CategoryTheory/Limits/VanKampen.lean | 411 | 465 | theorem IsVanKampenColimit.map_reflective [HasColimitsOfShape J C]
{Gl : C ⥤ D} {Gr : D ⥤ C} (adj : Gl ⊣ Gr) [Gr.Full] [Gr.Faithful]
{F : J ⥤ D} {c : Cocone (F ⋙ Gr)} (H : IsVanKampenColimit c)
[∀ X (f : X ⟶ Gl.obj c.pt), HasPullback (Gr.map f) (adj.unit.app c.pt)]
[∀ X (f : X ⟶ Gl.obj c.pt), PreservesLimit (cospan (Gr.map f) (adj.unit.app c.pt)) Gl]
[∀ X i (f : X ⟶ c.pt), PreservesLimit (cospan f (c.ι.app i)) Gl] :
IsVanKampenColimit (Gl.mapCocone c) := by |
have := adj.rightAdjointPreservesLimits
have : PreservesColimitsOfSize.{u', v'} Gl := adj.leftAdjointPreservesColimits
intro F' c' α f h hα
refine ⟨?_, H.isUniversal.map_reflective adj c' α f h hα⟩
intro ⟨hc'⟩ j
let α' := α ≫ (Functor.associator _ _ _).hom ≫ whiskerLeft F adj.counit ≫ F.rightUnitor.hom
have hα' : NatTrans.Equifibered α' := hα.comp (NatTrans.equifibered_of_isIso _)
have hα'' : ∀ j, Gl.map (Gr.map <| α'.app j) = adj.counit.app _ ≫ α.app j := by
intro j
rw [← cancel_mono (adj.counit.app <| F.obj j)]
dsimp [α']
simp only [Category.comp_id, Adjunction.counit_naturality_assoc, Category.id_comp,
Adjunction.counit_naturality, Category.assoc, Functor.map_comp]
let β := isoWhiskerLeft F' (asIso adj.counit) ≪≫ F'.rightUnitor
let hl := (IsColimit.precomposeHomEquiv β c').symm hc'
let hr := isColimitOfPreserves Gl (colimit.isColimit <| F' ⋙ Gr)
have : α.app j = β.inv.app _ ≫ Gl.map (Gr.map <| α'.app j) := by
rw [hα'']
simp [β]
rw [this]
have : f = (hl.coconePointUniqueUpToIso hr).hom ≫
Gl.map (colimit.desc _ ⟨_, whiskerRight α' Gr ≫ c.2⟩) := by
symm
convert @IsColimit.coconePointUniqueUpToIso_hom_desc _ _ _ _ ((F' ⋙ Gr) ⋙ Gl)
(Gl.mapCocone ⟨_, (whiskerRight α' Gr ≫ c.2 : _)⟩) _ _ hl hr using 2
· apply hr.hom_ext
intro j
rw [hr.fac, Functor.mapCocone_ι_app, ← Gl.map_comp, colimit.cocone_ι, colimit.ι_desc]
rfl
· clear_value α'
apply hl.hom_ext
intro j
rw [hl.fac]
dsimp [β]
simp only [Category.comp_id, hα'', Category.assoc, Gl.map_comp]
congr 1
exact (NatTrans.congr_app h j).symm
rw [this]
have := ((H (colimit.cocone <| F' ⋙ Gr) (whiskerRight α' Gr)
(colimit.desc _ ⟨_, whiskerRight α' Gr ≫ c.2⟩) ?_ (hα'.whiskerRight Gr)).mp
⟨(getColimitCocone <| F' ⋙ Gr).2⟩ j).map Gl
· convert IsPullback.paste_vert _ this
refine IsPullback.of_vert_isIso ⟨?_⟩
rw [← IsIso.inv_comp_eq, ← Category.assoc, NatIso.inv_inv_app]
exact IsColimit.comp_coconePointUniqueUpToIso_hom hl hr _
· clear_value α'
ext j
simp
|
/-
Copyright (c) 2021 Floris van Doorn. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Floris van Doorn
-/
import Mathlib.Algebra.Group.Equiv.Basic
import Mathlib.Algebra.Ring.Basic
import Mathlib.Algebra.Order.Sub.Defs
import Mathlib.Order.Hom.Basic
#align_import algebra.order.sub.basic from "leanprover-community/mathlib"@"10b4e499f43088dd3bb7b5796184ad5216648ab1"
/-!
# Additional results about ordered Subtraction
-/
variable {α β : Type*}
section Add
variable [Preorder α] [Add α] [Sub α] [OrderedSub α] {a b c d : α}
| Mathlib/Algebra/Order/Sub/Basic.lean | 25 | 28 | theorem AddHom.le_map_tsub [Preorder β] [Add β] [Sub β] [OrderedSub β] (f : AddHom α β)
(hf : Monotone f) (a b : α) : f a - f b ≤ f (a - b) := by |
rw [tsub_le_iff_right, ← f.map_add]
exact hf le_tsub_add
|
/-
Copyright (c) 2022 Riccardo Brasca. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Riccardo Brasca
-/
import Mathlib.Data.Nat.Choose.Dvd
import Mathlib.RingTheory.IntegrallyClosed
import Mathlib.RingTheory.Norm
import Mathlib.RingTheory.Polynomial.Cyclotomic.Expand
#align_import ring_theory.polynomial.eisenstein.is_integral from "leanprover-community/mathlib"@"5bfbcca0a7ffdd21cf1682e59106d6c942434a32"
/-!
# Eisenstein polynomials
In this file we gather more miscellaneous results about Eisenstein polynomials
## Main results
* `mem_adjoin_of_smul_prime_pow_smul_of_minpoly_isEisensteinAt`: let `K` be the field of fraction
of an integrally closed domain `R` and let `L` be a separable extension of `K`, generated by an
integral power basis `B` such that the minimal polynomial of `B.gen` is Eisenstein at `p`. Given
`z : L` integral over `R`, if `p ^ n • z ∈ adjoin R {B.gen}`, then `z ∈ adjoin R {B.gen}`.
Together with `Algebra.discr_mul_isIntegral_mem_adjoin` this result often allows to compute the
ring of integers of `L`.
-/
universe u v w z
variable {R : Type u}
open Ideal Algebra Finset
open scoped Polynomial
section Cyclotomic
variable (p : ℕ)
local notation "𝓟" => Submodule.span ℤ {(p : ℤ)}
open Polynomial
theorem cyclotomic_comp_X_add_one_isEisensteinAt [hp : Fact p.Prime] :
((cyclotomic p ℤ).comp (X + 1)).IsEisensteinAt 𝓟 := by
refine Monic.isEisensteinAt_of_mem_of_not_mem ?_
(Ideal.IsPrime.ne_top <| (Ideal.span_singleton_prime (mod_cast hp.out.ne_zero)).2 <|
Nat.prime_iff_prime_int.1 hp.out) (fun {i hi} => ?_) ?_
· rw [show (X + 1 : ℤ[X]) = X + C 1 by simp]
refine (cyclotomic.monic p ℤ).comp (monic_X_add_C 1) fun h => ?_
rw [natDegree_X_add_C] at h
exact zero_ne_one h.symm
· rw [cyclotomic_prime, geom_sum_X_comp_X_add_one_eq_sum, ← lcoeff_apply, map_sum]
conv =>
congr
congr
next => skip
ext
rw [lcoeff_apply, ← C_eq_natCast, C_mul_X_pow_eq_monomial, coeff_monomial]
rw [natDegree_comp, show (X + 1 : ℤ[X]) = X + C 1 by simp, natDegree_X_add_C, mul_one,
natDegree_cyclotomic, Nat.totient_prime hp.out] at hi
simp only [hi.trans_le (Nat.sub_le _ _), sum_ite_eq', mem_range, if_true,
Ideal.submodule_span_eq, Ideal.mem_span_singleton, Int.natCast_dvd_natCast]
exact hp.out.dvd_choose_self i.succ_ne_zero (lt_tsub_iff_right.1 hi)
· rw [coeff_zero_eq_eval_zero, eval_comp, cyclotomic_prime, eval_add, eval_X, eval_one, zero_add,
eval_geom_sum, one_geom_sum, Ideal.submodule_span_eq, Ideal.span_singleton_pow,
Ideal.mem_span_singleton]
intro h
obtain ⟨k, hk⟩ := Int.natCast_dvd_natCast.1 h
rw [mul_assoc, mul_comm 1, mul_one] at hk
nth_rw 1 [← Nat.mul_one p] at hk
rw [mul_right_inj' hp.out.ne_zero] at hk
exact Nat.Prime.not_dvd_one hp.out (Dvd.intro k hk.symm)
set_option linter.uppercaseLean3 false in
#align cyclotomic_comp_X_add_one_is_eisenstein_at cyclotomic_comp_X_add_one_isEisensteinAt
theorem cyclotomic_prime_pow_comp_X_add_one_isEisensteinAt [hp : Fact p.Prime] (n : ℕ) :
((cyclotomic (p ^ (n + 1)) ℤ).comp (X + 1)).IsEisensteinAt 𝓟 := by
refine Monic.isEisensteinAt_of_mem_of_not_mem ?_
(Ideal.IsPrime.ne_top <| (Ideal.span_singleton_prime (mod_cast hp.out.ne_zero)).2 <|
Nat.prime_iff_prime_int.1 hp.out) ?_ ?_
· rw [show (X + 1 : ℤ[X]) = X + C 1 by simp]
refine (cyclotomic.monic _ ℤ).comp (monic_X_add_C 1) fun h => ?_
rw [natDegree_X_add_C] at h
exact zero_ne_one h.symm
· induction' n with n hn
· intro i hi
rw [Nat.zero_add, pow_one] at hi ⊢
exact (cyclotomic_comp_X_add_one_isEisensteinAt p).mem hi
· intro i hi
rw [Ideal.submodule_span_eq, Ideal.mem_span_singleton, ← ZMod.intCast_zmod_eq_zero_iff_dvd,
show ↑(_ : ℤ) = Int.castRingHom (ZMod p) _ by rfl, ← coeff_map, map_comp, map_cyclotomic,
Polynomial.map_add, map_X, Polynomial.map_one, pow_add, pow_one,
cyclotomic_mul_prime_dvd_eq_pow, pow_comp, ← ZMod.expand_card, coeff_expand hp.out.pos]
· simp only [ite_eq_right_iff]
rintro ⟨k, hk⟩
rw [natDegree_comp, show (X + 1 : ℤ[X]) = X + C 1 by simp, natDegree_X_add_C, mul_one,
natDegree_cyclotomic, Nat.totient_prime_pow hp.out (Nat.succ_pos _), Nat.add_one_sub_one]
at hn hi
rw [hk, pow_succ', mul_assoc] at hi
rw [hk, mul_comm, Nat.mul_div_cancel _ hp.out.pos]
replace hn := hn (lt_of_mul_lt_mul_left' hi)
rw [Ideal.submodule_span_eq, Ideal.mem_span_singleton, ← ZMod.intCast_zmod_eq_zero_iff_dvd,
show ↑(_ : ℤ) = Int.castRingHom (ZMod p) _ by rfl, ← coeff_map] at hn
simpa [map_comp] using hn
· exact ⟨p ^ n, by rw [pow_succ']⟩
· rw [coeff_zero_eq_eval_zero, eval_comp, cyclotomic_prime_pow_eq_geom_sum hp.out, eval_add,
eval_X, eval_one, zero_add, eval_finset_sum]
simp only [eval_pow, eval_X, one_pow, sum_const, card_range, Nat.smul_one_eq_cast,
submodule_span_eq, Ideal.submodule_span_eq, Ideal.span_singleton_pow,
Ideal.mem_span_singleton]
intro h
obtain ⟨k, hk⟩ := Int.natCast_dvd_natCast.1 h
rw [mul_assoc, mul_comm 1, mul_one] at hk
nth_rw 1 [← Nat.mul_one p] at hk
rw [mul_right_inj' hp.out.ne_zero] at hk
exact Nat.Prime.not_dvd_one hp.out (Dvd.intro k hk.symm)
set_option linter.uppercaseLean3 false in
#align cyclotomic_prime_pow_comp_X_add_one_is_eisenstein_at cyclotomic_prime_pow_comp_X_add_one_isEisensteinAt
end Cyclotomic
section IsIntegral
variable {K : Type v} {L : Type z} {p : R} [CommRing R] [Field K] [Field L]
variable [Algebra K L] [Algebra R L] [Algebra R K] [IsScalarTower R K L] [IsSeparable K L]
variable [IsDomain R] [IsFractionRing R K] [IsIntegrallyClosed R]
local notation "𝓟" => Submodule.span R {(p : R)}
open IsIntegrallyClosed PowerBasis Nat Polynomial IsScalarTower
/-- Let `K` be the field of fraction of an integrally closed domain `R` and let `L` be a separable
extension of `K`, generated by an integral power basis `B` such that the minimal polynomial of
`B.gen` is Eisenstein at `p`. Given `z : L` integral over `R`, if `Q : R[X]` is such that
`aeval B.gen Q = p • z`, then `p ∣ Q.coeff 0`. -/
theorem dvd_coeff_zero_of_aeval_eq_prime_smul_of_minpoly_isEisensteinAt {B : PowerBasis K L}
(hp : Prime p) (hBint : IsIntegral R B.gen) {z : L} {Q : R[X]} (hQ : aeval B.gen Q = p • z)
(hzint : IsIntegral R z) (hei : (minpoly R B.gen).IsEisensteinAt 𝓟) : p ∣ Q.coeff 0 := by
-- First define some abbreviations.
letI := B.finite
let P := minpoly R B.gen
obtain ⟨n, hn⟩ := Nat.exists_eq_succ_of_ne_zero B.dim_pos.ne'
have finrank_K_L : FiniteDimensional.finrank K L = B.dim := B.finrank
have deg_K_P : (minpoly K B.gen).natDegree = B.dim := B.natDegree_minpoly
have deg_R_P : P.natDegree = B.dim := by
rw [← deg_K_P, minpoly.isIntegrallyClosed_eq_field_fractions' K hBint,
(minpoly.monic hBint).natDegree_map (algebraMap R K)]
choose! f hf using
hei.isWeaklyEisensteinAt.exists_mem_adjoin_mul_eq_pow_natDegree_le (minpoly.aeval R B.gen)
(minpoly.monic hBint)
simp only [(minpoly.monic hBint).natDegree_map, deg_R_P] at hf
-- The Eisenstein condition shows that `p` divides `Q.coeff 0`
-- if `p^n.succ` divides the following multiple of `Q.coeff 0^n.succ`:
suffices
p ^ n.succ ∣ Q.coeff 0 ^ n.succ * ((-1) ^ (n.succ * n) * (minpoly R B.gen).coeff 0 ^ n) by
have hndiv : ¬p ^ 2 ∣ (minpoly R B.gen).coeff 0 := fun h =>
hei.not_mem ((span_singleton_pow p 2).symm ▸ Ideal.mem_span_singleton.2 h)
refine @Prime.dvd_of_pow_dvd_pow_mul_pow_of_square_not_dvd R _ _ _ _ n hp (?_ : _ ∣ _) hndiv
convert (IsUnit.dvd_mul_right ⟨(-1) ^ (n.succ * n), rfl⟩).mpr this using 1
push_cast
ring_nf
rw [mul_comm _ 2, pow_mul, neg_one_sq, one_pow, mul_one]
-- We claim the quotient of `Q^n * _` by `p^n` is the following `r`:
have aux : ∀ i ∈ (range (Q.natDegree + 1)).erase 0, B.dim ≤ i + n := by
intro i hi
simp only [mem_range, mem_erase] at hi
rw [hn]
exact le_add_pred_of_pos _ hi.1
have hintsum :
IsIntegral R
(z * B.gen ^ n - ∑ x ∈ (range (Q.natDegree + 1)).erase 0, Q.coeff x • f (x + n)) := by
refine (hzint.mul (hBint.pow _)).sub (.sum _ fun i hi => .smul _ ?_)
exact adjoin_le_integralClosure hBint (hf _ (aux i hi)).1
obtain ⟨r, hr⟩ := isIntegral_iff.1 (isIntegral_norm K hintsum)
use r
-- Do the computation in `K` so we can work in terms of `z` instead of `r`.
apply IsFractionRing.injective R K
simp only [_root_.map_mul, _root_.map_pow, _root_.map_neg, _root_.map_one]
-- Both sides are actually norms:
calc
_ = norm K (Q.coeff 0 • B.gen ^ n) := ?_
_ = norm K (p • (z * B.gen ^ n) -
∑ x ∈ (range (Q.natDegree + 1)).erase 0, p • Q.coeff x • f (x + n)) :=
(congr_arg (norm K) (eq_sub_of_add_eq ?_))
_ = _ := ?_
· simp only [Algebra.smul_def, algebraMap_apply R K L, Algebra.norm_algebraMap, _root_.map_mul,
_root_.map_pow, finrank_K_L, PowerBasis.norm_gen_eq_coeff_zero_minpoly,
minpoly.isIntegrallyClosed_eq_field_fractions' K hBint, coeff_map, ← hn]
ring
swap
· simp_rw [← smul_sum, ← smul_sub, Algebra.smul_def p, algebraMap_apply R K L, _root_.map_mul,
Algebra.norm_algebraMap, finrank_K_L, hr, ← hn]
calc
_ = (Q.coeff 0 • ↑1 + ∑ x ∈ (range (Q.natDegree + 1)).erase 0, Q.coeff x • B.gen ^ x) *
B.gen ^ n := ?_
_ = (Q.coeff 0 • B.gen ^ 0 +
∑ x ∈ (range (Q.natDegree + 1)).erase 0, Q.coeff x • B.gen ^ x) * B.gen ^ n := by
rw [_root_.pow_zero]
_ = aeval B.gen Q * B.gen ^ n := ?_
_ = _ := by rw [hQ, Algebra.smul_mul_assoc]
· have : ∀ i ∈ (range (Q.natDegree + 1)).erase 0,
Q.coeff i • (B.gen ^ i * B.gen ^ n) = p • Q.coeff i • f (i + n) := by
intro i hi
rw [← pow_add, ← (hf _ (aux i hi)).2, ← Algebra.smul_def, smul_smul, mul_comm _ p, smul_smul]
simp only [add_mul, smul_mul_assoc, one_mul, sum_mul, sum_congr rfl this]
· rw [aeval_eq_sum_range,
Finset.add_sum_erase (range (Q.natDegree + 1)) fun i => Q.coeff i • B.gen ^ i]
simp
#align dvd_coeff_zero_of_aeval_eq_prime_smul_of_minpoly_is_eiseinstein_at dvd_coeff_zero_of_aeval_eq_prime_smul_of_minpoly_isEisensteinAt
theorem mem_adjoin_of_dvd_coeff_of_dvd_aeval {A B : Type*} [CommSemiring A] [CommRing B]
[Algebra A B] [NoZeroSMulDivisors A B] {Q : A[X]} {p : A} {x z : B} (hp : p ≠ 0)
(hQ : ∀ i ∈ range (Q.natDegree + 1), p ∣ Q.coeff i) (hz : aeval x Q = p • z) :
z ∈ adjoin A ({x} : Set B) := by
choose! f hf using hQ
rw [aeval_eq_sum_range, sum_range] at hz
conv_lhs at hz =>
congr
next => skip
ext i
rw [hf i (mem_range.2 (Fin.is_lt i)), ← smul_smul]
rw [← smul_sum] at hz
rw [← smul_right_injective _ hp hz]
exact
Subalgebra.sum_mem _ fun _ _ =>
Subalgebra.smul_mem _ (Subalgebra.pow_mem _ (subset_adjoin (Set.mem_singleton _)) _) _
#align mem_adjoin_of_dvd_coeff_of_dvd_aeval mem_adjoin_of_dvd_coeff_of_dvd_aeval
/-- Let `K` be the field of fraction of an integrally closed domain `R` and let `L` be a separable
extension of `K`, generated by an integral power basis `B` such that the minimal polynomial of
`B.gen` is Eisenstein at `p`. Given `z : L` integral over `R`, if `p • z ∈ adjoin R {B.gen}`, then
`z ∈ adjoin R {B.gen}`. -/
| Mathlib/RingTheory/Polynomial/Eisenstein/IsIntegral.lean | 237 | 370 | theorem mem_adjoin_of_smul_prime_smul_of_minpoly_isEisensteinAt {B : PowerBasis K L}
(hp : Prime p) (hBint : IsIntegral R B.gen) {z : L} (hzint : IsIntegral R z)
(hz : p • z ∈ adjoin R ({B.gen} : Set L)) (hei : (minpoly R B.gen).IsEisensteinAt 𝓟) :
z ∈ adjoin R ({B.gen} : Set L) := by |
-- First define some abbreviations.
have hndiv : ¬p ^ 2 ∣ (minpoly R B.gen).coeff 0 := fun h =>
hei.not_mem ((span_singleton_pow p 2).symm ▸ Ideal.mem_span_singleton.2 h)
have := B.finite
set P := minpoly R B.gen with hP
obtain ⟨n, hn⟩ := Nat.exists_eq_succ_of_ne_zero B.dim_pos.ne'
haveI : NoZeroSMulDivisors R L := NoZeroSMulDivisors.trans R K L
let _ := P.map (algebraMap R L)
-- There is a polynomial `Q` such that `p • z = aeval B.gen Q`. We can assume that
-- `Q.degree < P.degree` and `Q ≠ 0`.
rw [adjoin_singleton_eq_range_aeval] at hz
obtain ⟨Q₁, hQ⟩ := hz
set Q := Q₁ %ₘ P with hQ₁
replace hQ : aeval B.gen Q = p • z := by
rw [← modByMonic_add_div Q₁ (minpoly.monic hBint)] at hQ
simpa using hQ
by_cases hQzero : Q = 0
· simp only [hQzero, Algebra.smul_def, zero_eq_mul, aeval_zero] at hQ
cases' hQ with H H₁
· have : Function.Injective (algebraMap R L) := by
rw [algebraMap_eq R K L]
exact (algebraMap K L).injective.comp (IsFractionRing.injective R K)
exfalso
exact hp.ne_zero ((injective_iff_map_eq_zero _).1 this _ H)
· rw [H₁]
exact Subalgebra.zero_mem _
-- It is enough to prove that all coefficients of `Q` are divisible by `p`, by induction.
-- The base case is `dvd_coeff_zero_of_aeval_eq_prime_smul_of_minpoly_isEisensteinAt`.
refine mem_adjoin_of_dvd_coeff_of_dvd_aeval hp.ne_zero (fun i => ?_) hQ
induction' i using Nat.case_strong_induction_on with j hind
· intro _
exact dvd_coeff_zero_of_aeval_eq_prime_smul_of_minpoly_isEisensteinAt hp hBint hQ hzint hei
· intro hj
convert hp.dvd_of_pow_dvd_pow_mul_pow_of_square_not_dvd (n := n) _ hndiv
-- Two technical results we will need about `P.natDegree` and `Q.natDegree`.
have H := degree_modByMonic_lt Q₁ (minpoly.monic hBint)
rw [← hQ₁, ← hP] at H
replace H := Nat.lt_iff_add_one_le.1
(lt_of_lt_of_le
(lt_of_le_of_lt (Nat.lt_iff_add_one_le.1 (Nat.lt_of_succ_lt_succ (mem_range.1 hj)))
(lt_succ_self _)) (Nat.lt_iff_add_one_le.1 ((natDegree_lt_natDegree_iff hQzero).2 H)))
have Hj : Q.natDegree + 1 = j + 1 + (Q.natDegree - j) := by
rw [← add_comm 1, ← add_comm 1, add_assoc, add_right_inj,
← Nat.add_sub_assoc (Nat.lt_of_succ_lt_succ (mem_range.1 hj)).le, add_comm,
Nat.add_sub_cancel]
-- By induction hypothesis we can find `g : ℕ → R` such that
-- `k ∈ range (j + 1) → Q.coeff k • B.gen ^ k = (algebraMap R L) p * g k • B.gen ^ k`-
choose! g hg using hind
replace hg : ∀ k ∈ range (j + 1), Q.coeff k • B.gen ^ k =
algebraMap R L p * g k • B.gen ^ k := by
intro k hk
rw [hg k (mem_range_succ_iff.1 hk)
(mem_range_succ_iff.2
(le_trans (mem_range_succ_iff.1 hk) (succ_le_iff.1 (mem_range_succ_iff.1 hj)).le)),
Algebra.smul_def, Algebra.smul_def, RingHom.map_mul, mul_assoc]
-- Since `minpoly R B.gen` is Eiseinstein, we can find `f : ℕ → L` such that
-- `(map (algebraMap R L) (minpoly R B.gen)).nat_degree ≤ i` implies `f i ∈ adjoin R {B.gen}`
-- and `(algebraMap R L) p * f i = B.gen ^ i`. We will also need `hf₁`, a reformulation of this
-- property.
choose! f hf using
IsWeaklyEisensteinAt.exists_mem_adjoin_mul_eq_pow_natDegree_le (minpoly.aeval R B.gen)
(minpoly.monic hBint) hei.isWeaklyEisensteinAt
have hf₁ : ∀ k ∈ (range (Q.natDegree - j)).erase 0,
Q.coeff (j + 1 + k) • B.gen ^ (j + 1 + k) * B.gen ^ (P.natDegree - (j + 2)) =
(algebraMap R L) p * Q.coeff (j + 1 + k) • f (k + P.natDegree - 1) := by
intro k hk
rw [smul_mul_assoc, ← pow_add, ← Nat.add_sub_assoc H, add_comm (j + 1) 1,
add_assoc (j + 1), add_comm _ (k + P.natDegree), Nat.add_sub_add_right,
← (hf (k + P.natDegree - 1) _).2, mul_smul_comm]
rw [(minpoly.monic hBint).natDegree_map, add_comm, Nat.add_sub_assoc, le_add_iff_nonneg_right]
· exact Nat.zero_le _
· refine one_le_iff_ne_zero.2 fun h => ?_
rw [h] at hk
simp at hk
-- The Eisenstein condition shows that `p` divides `Q.coeff j`
-- if `p^n.succ` divides the following multiple of `Q.coeff (succ j)^n.succ`:
suffices
p ^ n.succ ∣ Q.coeff (succ j) ^ n.succ *
(minpoly R B.gen).coeff 0 ^ (succ j + (P.natDegree - (j + 2))) by
convert this
rw [Nat.succ_eq_add_one, add_assoc, ← Nat.add_sub_assoc H, add_comm (j + 1),
Nat.add_sub_add_left, ← Nat.add_sub_assoc, Nat.add_sub_add_left, hP, ←
(minpoly.monic hBint).natDegree_map (algebraMap R K), ←
minpoly.isIntegrallyClosed_eq_field_fractions' K hBint, natDegree_minpoly, hn, Nat.sub_one,
Nat.pred_succ]
omega
-- Using `hQ : aeval B.gen Q = p • z`, we write `p • z` as a sum of terms of degree less than
-- `j+1`, that are multiples of `p` by induction, and terms of degree at least `j+1`.
rw [aeval_eq_sum_range, Hj, range_add, sum_union (disjoint_range_addLeftEmbedding _ _),
sum_congr rfl hg, add_comm] at hQ
-- We multiply this equality by `B.gen ^ (P.natDegree-(j+2))`, so we can use `hf₁` on the terms
-- we didn't know were multiples of `p`, and we take the norm on both sides.
replace hQ := congr_arg (fun x => x * B.gen ^ (P.natDegree - (j + 2))) hQ
simp_rw [sum_map, addLeftEmbedding_apply, add_mul, sum_mul, mul_assoc] at hQ
rw [← insert_erase
(mem_range.2 (tsub_pos_iff_lt.2 <| Nat.lt_of_succ_lt_succ <| mem_range.1 hj)),
sum_insert (not_mem_erase 0 _), add_zero, sum_congr rfl hf₁, ← mul_sum, ← mul_sum, add_assoc,
← mul_add, smul_mul_assoc, ← pow_add, Algebra.smul_def] at hQ
replace hQ := congr_arg (norm K) (eq_sub_of_add_eq hQ)
-- We obtain an equality of elements of `K`, but everything is integral, so we can move to `R`
-- and simplify `hQ`.
have hintsum : IsIntegral R (z * B.gen ^ (P.natDegree - (j + 2)) -
(∑ x ∈ (range (Q.natDegree - j)).erase 0,
Q.coeff (j + 1 + x) • f (x + P.natDegree - 1) +
∑ x ∈ range (j + 1), g x • B.gen ^ x * B.gen ^ (P.natDegree - (j + 2)))) := by
refine (hzint.mul (hBint.pow _)).sub
(.add (.sum _ fun k hk => .smul _ ?_)
(.sum _ fun k _ => .mul (.smul _ (.pow hBint _)) (hBint.pow _)))
refine adjoin_le_integralClosure hBint (hf _ ?_).1
rw [(minpoly.monic hBint).natDegree_map (algebraMap R L)]
rw [add_comm, Nat.add_sub_assoc, le_add_iff_nonneg_right]
· exact _root_.zero_le _
· refine one_le_iff_ne_zero.2 fun h => ?_
rw [h] at hk
simp at hk
obtain ⟨r, hr⟩ := isIntegral_iff.1 (isIntegral_norm K hintsum)
rw [Algebra.smul_def, mul_assoc, ← mul_sub, _root_.map_mul, algebraMap_apply R K L, map_pow,
Algebra.norm_algebraMap, _root_.map_mul, algebraMap_apply R K L, Algebra.norm_algebraMap,
finrank B, ← hr, PowerBasis.norm_gen_eq_coeff_zero_minpoly,
minpoly.isIntegrallyClosed_eq_field_fractions' K hBint, coeff_map,
show (-1 : K) = algebraMap R K (-1) by simp, ← map_pow, ← map_pow, ← _root_.map_mul, ←
map_pow, ← _root_.map_mul, ← map_pow, ← _root_.map_mul] at hQ
-- We can now finish the proof.
have hppdiv : p ^ B.dim ∣ p ^ B.dim * r := dvd_mul_of_dvd_left dvd_rfl _
rwa [← IsFractionRing.injective R K hQ, mul_comm, ← Units.coe_neg_one, mul_pow, ←
Units.val_pow_eq_pow_val, ← Units.val_pow_eq_pow_val, mul_assoc,
Units.dvd_mul_left, mul_comm, ← Nat.succ_eq_add_one, hn] at hppdiv
|
/-
Copyright (c) 2019 Zhouhang Zhou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Zhouhang Zhou, Sébastien Gouëzel, Frédéric Dupuis
-/
import Mathlib.Algebra.DirectSum.Module
import Mathlib.Analysis.Complex.Basic
import Mathlib.Analysis.Convex.Uniform
import Mathlib.Analysis.NormedSpace.Completion
import Mathlib.Analysis.NormedSpace.BoundedLinearMaps
#align_import analysis.inner_product_space.basic from "leanprover-community/mathlib"@"3f655f5297b030a87d641ad4e825af8d9679eb0b"
/-!
# Inner product space
This file defines inner product spaces and proves the basic properties. We do not formally
define Hilbert spaces, but they can be obtained using the set of assumptions
`[NormedAddCommGroup E] [InnerProductSpace 𝕜 E] [CompleteSpace E]`.
An inner product space is a vector space endowed with an inner product. It generalizes the notion of
dot product in `ℝ^n` and provides the means of defining the length of a vector and the angle between
two vectors. In particular vectors `x` and `y` are orthogonal if their inner product equals zero.
We define both the real and complex cases at the same time using the `RCLike` typeclass.
This file proves general results on inner product spaces. For the specific construction of an inner
product structure on `n → 𝕜` for `𝕜 = ℝ` or `ℂ`, see `EuclideanSpace` in
`Analysis.InnerProductSpace.PiL2`.
## Main results
- We define the class `InnerProductSpace 𝕜 E` extending `NormedSpace 𝕜 E` with a number of basic
properties, most notably the Cauchy-Schwarz inequality. Here `𝕜` is understood to be either `ℝ`
or `ℂ`, through the `RCLike` typeclass.
- We show that the inner product is continuous, `continuous_inner`, and bundle it as the
continuous sesquilinear map `innerSL` (see also `innerₛₗ` for the non-continuous version).
- We define `Orthonormal`, a predicate on a function `v : ι → E`, and prove the existence of a
maximal orthonormal set, `exists_maximal_orthonormal`. Bessel's inequality,
`Orthonormal.tsum_inner_products_le`, states that given an orthonormal set `v` and a vector `x`,
the sum of the norm-squares of the inner products `⟪v i, x⟫` is no more than the norm-square of
`x`. For the existence of orthonormal bases, Hilbert bases, etc., see the file
`Analysis.InnerProductSpace.projection`.
## Notation
We globally denote the real and complex inner products by `⟪·, ·⟫_ℝ` and `⟪·, ·⟫_ℂ` respectively.
We also provide two notation namespaces: `RealInnerProductSpace`, `ComplexInnerProductSpace`,
which respectively introduce the plain notation `⟪·, ·⟫` for the real and complex inner product.
## Implementation notes
We choose the convention that inner products are conjugate linear in the first argument and linear
in the second.
## Tags
inner product space, Hilbert space, norm
## References
* [Clément & Martin, *The Lax-Milgram Theorem. A detailed proof to be formalized in Coq*]
* [Clément & Martin, *A Coq formal proof of the Lax–Milgram theorem*]
The Coq code is available at the following address: <http://www.lri.fr/~sboldo/elfic/index.html>
-/
noncomputable section
open RCLike Real Filter
open Topology ComplexConjugate
open LinearMap (BilinForm)
variable {𝕜 E F : Type*} [RCLike 𝕜]
/-- Syntactic typeclass for types endowed with an inner product -/
class Inner (𝕜 E : Type*) where
/-- The inner product function. -/
inner : E → E → 𝕜
#align has_inner Inner
export Inner (inner)
/-- The inner product with values in `𝕜`. -/
notation3:max "⟪" x ", " y "⟫_" 𝕜:max => @inner 𝕜 _ _ x y
section Notations
/-- The inner product with values in `ℝ`. -/
scoped[RealInnerProductSpace] notation "⟪" x ", " y "⟫" => @inner ℝ _ _ x y
/-- The inner product with values in `ℂ`. -/
scoped[ComplexInnerProductSpace] notation "⟪" x ", " y "⟫" => @inner ℂ _ _ x y
end Notations
/-- An inner product space is a vector space with an additional operation called inner product.
The norm could be derived from the inner product, instead we require the existence of a norm and
the fact that `‖x‖^2 = re ⟪x, x⟫` to be able to put instances on `𝕂` or product
spaces.
To construct a norm from an inner product, see `InnerProductSpace.ofCore`.
-/
class InnerProductSpace (𝕜 : Type*) (E : Type*) [RCLike 𝕜] [NormedAddCommGroup E] extends
NormedSpace 𝕜 E, Inner 𝕜 E where
/-- The inner product induces the norm. -/
norm_sq_eq_inner : ∀ x : E, ‖x‖ ^ 2 = re (inner x x)
/-- The inner product is *hermitian*, taking the `conj` swaps the arguments. -/
conj_symm : ∀ x y, conj (inner y x) = inner x y
/-- The inner product is additive in the first coordinate. -/
add_left : ∀ x y z, inner (x + y) z = inner x z + inner y z
/-- The inner product is conjugate linear in the first coordinate. -/
smul_left : ∀ x y r, inner (r • x) y = conj r * inner x y
#align inner_product_space InnerProductSpace
/-!
### Constructing a normed space structure from an inner product
In the definition of an inner product space, we require the existence of a norm, which is equal
(but maybe not defeq) to the square root of the scalar product. This makes it possible to put
an inner product space structure on spaces with a preexisting norm (for instance `ℝ`), with good
properties. However, sometimes, one would like to define the norm starting only from a well-behaved
scalar product. This is what we implement in this paragraph, starting from a structure
`InnerProductSpace.Core` stating that we have a nice scalar product.
Our goal here is not to develop a whole theory with all the supporting API, as this will be done
below for `InnerProductSpace`. Instead, we implement the bare minimum to go as directly as
possible to the construction of the norm and the proof of the triangular inequality.
Warning: Do not use this `Core` structure if the space you are interested in already has a norm
instance defined on it, otherwise this will create a second non-defeq norm instance!
-/
/-- A structure requiring that a scalar product is positive definite and symmetric, from which one
can construct an `InnerProductSpace` instance in `InnerProductSpace.ofCore`. -/
-- @[nolint HasNonemptyInstance] porting note: I don't think we have this linter anymore
structure InnerProductSpace.Core (𝕜 : Type*) (F : Type*) [RCLike 𝕜] [AddCommGroup F]
[Module 𝕜 F] extends Inner 𝕜 F where
/-- The inner product is *hermitian*, taking the `conj` swaps the arguments. -/
conj_symm : ∀ x y, conj (inner y x) = inner x y
/-- The inner product is positive (semi)definite. -/
nonneg_re : ∀ x, 0 ≤ re (inner x x)
/-- The inner product is positive definite. -/
definite : ∀ x, inner x x = 0 → x = 0
/-- The inner product is additive in the first coordinate. -/
add_left : ∀ x y z, inner (x + y) z = inner x z + inner y z
/-- The inner product is conjugate linear in the first coordinate. -/
smul_left : ∀ x y r, inner (r • x) y = conj r * inner x y
#align inner_product_space.core InnerProductSpace.Core
/- We set `InnerProductSpace.Core` to be a class as we will use it as such in the construction
of the normed space structure that it produces. However, all the instances we will use will be
local to this proof. -/
attribute [class] InnerProductSpace.Core
/-- Define `InnerProductSpace.Core` from `InnerProductSpace`. Defined to reuse lemmas about
`InnerProductSpace.Core` for `InnerProductSpace`s. Note that the `Norm` instance provided by
`InnerProductSpace.Core.norm` is propositionally but not definitionally equal to the original
norm. -/
def InnerProductSpace.toCore [NormedAddCommGroup E] [c : InnerProductSpace 𝕜 E] :
InnerProductSpace.Core 𝕜 E :=
{ c with
nonneg_re := fun x => by
rw [← InnerProductSpace.norm_sq_eq_inner]
apply sq_nonneg
definite := fun x hx =>
norm_eq_zero.1 <| pow_eq_zero (n := 2) <| by
rw [InnerProductSpace.norm_sq_eq_inner (𝕜 := 𝕜) x, hx, map_zero] }
#align inner_product_space.to_core InnerProductSpace.toCore
namespace InnerProductSpace.Core
variable [AddCommGroup F] [Module 𝕜 F] [c : InnerProductSpace.Core 𝕜 F]
local notation "⟪" x ", " y "⟫" => @inner 𝕜 F _ x y
local notation "normSqK" => @RCLike.normSq 𝕜 _
local notation "reK" => @RCLike.re 𝕜 _
local notation "ext_iff" => @RCLike.ext_iff 𝕜 _
local postfix:90 "†" => starRingEnd _
/-- Inner product defined by the `InnerProductSpace.Core` structure. We can't reuse
`InnerProductSpace.Core.toInner` because it takes `InnerProductSpace.Core` as an explicit
argument. -/
def toInner' : Inner 𝕜 F :=
c.toInner
#align inner_product_space.core.to_has_inner' InnerProductSpace.Core.toInner'
attribute [local instance] toInner'
/-- The norm squared function for `InnerProductSpace.Core` structure. -/
def normSq (x : F) :=
reK ⟪x, x⟫
#align inner_product_space.core.norm_sq InnerProductSpace.Core.normSq
local notation "normSqF" => @normSq 𝕜 F _ _ _ _
theorem inner_conj_symm (x y : F) : ⟪y, x⟫† = ⟪x, y⟫ :=
c.conj_symm x y
#align inner_product_space.core.inner_conj_symm InnerProductSpace.Core.inner_conj_symm
theorem inner_self_nonneg {x : F} : 0 ≤ re ⟪x, x⟫ :=
c.nonneg_re _
#align inner_product_space.core.inner_self_nonneg InnerProductSpace.Core.inner_self_nonneg
theorem inner_self_im (x : F) : im ⟪x, x⟫ = 0 := by
rw [← @ofReal_inj 𝕜, im_eq_conj_sub]
simp [inner_conj_symm]
#align inner_product_space.core.inner_self_im InnerProductSpace.Core.inner_self_im
theorem inner_add_left (x y z : F) : ⟪x + y, z⟫ = ⟪x, z⟫ + ⟪y, z⟫ :=
c.add_left _ _ _
#align inner_product_space.core.inner_add_left InnerProductSpace.Core.inner_add_left
theorem inner_add_right (x y z : F) : ⟪x, y + z⟫ = ⟪x, y⟫ + ⟪x, z⟫ := by
rw [← inner_conj_symm, inner_add_left, RingHom.map_add]; simp only [inner_conj_symm]
#align inner_product_space.core.inner_add_right InnerProductSpace.Core.inner_add_right
theorem ofReal_normSq_eq_inner_self (x : F) : (normSqF x : 𝕜) = ⟪x, x⟫ := by
rw [ext_iff]
exact ⟨by simp only [ofReal_re]; rfl, by simp only [inner_self_im, ofReal_im]⟩
#align inner_product_space.core.coe_norm_sq_eq_inner_self InnerProductSpace.Core.ofReal_normSq_eq_inner_self
theorem inner_re_symm (x y : F) : re ⟪x, y⟫ = re ⟪y, x⟫ := by rw [← inner_conj_symm, conj_re]
#align inner_product_space.core.inner_re_symm InnerProductSpace.Core.inner_re_symm
theorem inner_im_symm (x y : F) : im ⟪x, y⟫ = -im ⟪y, x⟫ := by rw [← inner_conj_symm, conj_im]
#align inner_product_space.core.inner_im_symm InnerProductSpace.Core.inner_im_symm
theorem inner_smul_left (x y : F) {r : 𝕜} : ⟪r • x, y⟫ = r† * ⟪x, y⟫ :=
c.smul_left _ _ _
#align inner_product_space.core.inner_smul_left InnerProductSpace.Core.inner_smul_left
theorem inner_smul_right (x y : F) {r : 𝕜} : ⟪x, r • y⟫ = r * ⟪x, y⟫ := by
rw [← inner_conj_symm, inner_smul_left];
simp only [conj_conj, inner_conj_symm, RingHom.map_mul]
#align inner_product_space.core.inner_smul_right InnerProductSpace.Core.inner_smul_right
theorem inner_zero_left (x : F) : ⟪0, x⟫ = 0 := by
rw [← zero_smul 𝕜 (0 : F), inner_smul_left];
simp only [zero_mul, RingHom.map_zero]
#align inner_product_space.core.inner_zero_left InnerProductSpace.Core.inner_zero_left
theorem inner_zero_right (x : F) : ⟪x, 0⟫ = 0 := by
rw [← inner_conj_symm, inner_zero_left]; simp only [RingHom.map_zero]
#align inner_product_space.core.inner_zero_right InnerProductSpace.Core.inner_zero_right
theorem inner_self_eq_zero {x : F} : ⟪x, x⟫ = 0 ↔ x = 0 :=
⟨c.definite _, by
rintro rfl
exact inner_zero_left _⟩
#align inner_product_space.core.inner_self_eq_zero InnerProductSpace.Core.inner_self_eq_zero
theorem normSq_eq_zero {x : F} : normSqF x = 0 ↔ x = 0 :=
Iff.trans
(by simp only [normSq, ext_iff, map_zero, inner_self_im, eq_self_iff_true, and_true_iff])
(@inner_self_eq_zero 𝕜 _ _ _ _ _ x)
#align inner_product_space.core.norm_sq_eq_zero InnerProductSpace.Core.normSq_eq_zero
theorem inner_self_ne_zero {x : F} : ⟪x, x⟫ ≠ 0 ↔ x ≠ 0 :=
inner_self_eq_zero.not
#align inner_product_space.core.inner_self_ne_zero InnerProductSpace.Core.inner_self_ne_zero
theorem inner_self_ofReal_re (x : F) : (re ⟪x, x⟫ : 𝕜) = ⟪x, x⟫ := by
norm_num [ext_iff, inner_self_im]
set_option linter.uppercaseLean3 false in
#align inner_product_space.core.inner_self_re_to_K InnerProductSpace.Core.inner_self_ofReal_re
theorem norm_inner_symm (x y : F) : ‖⟪x, y⟫‖ = ‖⟪y, x⟫‖ := by rw [← inner_conj_symm, norm_conj]
#align inner_product_space.core.norm_inner_symm InnerProductSpace.Core.norm_inner_symm
theorem inner_neg_left (x y : F) : ⟪-x, y⟫ = -⟪x, y⟫ := by
rw [← neg_one_smul 𝕜 x, inner_smul_left]
simp
#align inner_product_space.core.inner_neg_left InnerProductSpace.Core.inner_neg_left
| Mathlib/Analysis/InnerProductSpace/Basic.lean | 282 | 283 | theorem inner_neg_right (x y : F) : ⟪x, -y⟫ = -⟪x, y⟫ := by |
rw [← inner_conj_symm, inner_neg_left]; simp only [RingHom.map_neg, inner_conj_symm]
|
/-
Copyright (c) 2014 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Algebra.Group.Support
import Mathlib.Algebra.Order.Monoid.WithTop
import Mathlib.Data.Nat.Cast.Field
#align_import algebra.char_zero.lemmas from "leanprover-community/mathlib"@"acee671f47b8e7972a1eb6f4eed74b4b3abce829"
/-!
# Characteristic zero (additional theorems)
A ring `R` is called of characteristic zero if every natural number `n` is non-zero when considered
as an element of `R`. Since this definition doesn't mention the multiplicative structure of `R`
except for the existence of `1` in this file characteristic zero is defined for additive monoids
with `1`.
## Main statements
* Characteristic zero implies that the additive monoid is infinite.
-/
open Function Set
namespace Nat
variable {R : Type*} [AddMonoidWithOne R] [CharZero R]
/-- `Nat.cast` as an embedding into monoids of characteristic `0`. -/
@[simps]
def castEmbedding : ℕ ↪ R :=
⟨Nat.cast, cast_injective⟩
#align nat.cast_embedding Nat.castEmbedding
#align nat.cast_embedding_apply Nat.castEmbedding_apply
@[simp]
theorem cast_pow_eq_one {R : Type*} [Semiring R] [CharZero R] (q : ℕ) (n : ℕ) (hn : n ≠ 0) :
(q : R) ^ n = 1 ↔ q = 1 := by
rw [← cast_pow, cast_eq_one]
exact pow_eq_one_iff hn
#align nat.cast_pow_eq_one Nat.cast_pow_eq_one
@[simp, norm_cast]
theorem cast_div_charZero {k : Type*} [DivisionSemiring k] [CharZero k] {m n : ℕ} (n_dvd : n ∣ m) :
((m / n : ℕ) : k) = m / n := by
rcases eq_or_ne n 0 with (rfl | hn)
· simp
· exact cast_div n_dvd (cast_ne_zero.2 hn)
#align nat.cast_div_char_zero Nat.cast_div_charZero
end Nat
section AddMonoidWithOne
variable {α M : Type*} [AddMonoidWithOne M] [CharZero M] {n : ℕ}
instance CharZero.NeZero.two : NeZero (2 : M) :=
⟨by
have : ((2 : ℕ) : M) ≠ 0 := Nat.cast_ne_zero.2 (by decide)
rwa [Nat.cast_two] at this⟩
#align char_zero.ne_zero.two CharZero.NeZero.two
namespace Function
lemma support_natCast (hn : n ≠ 0) : support (n : α → M) = univ :=
support_const <| Nat.cast_ne_zero.2 hn
#align function.support_nat_cast Function.support_natCast
@[deprecated (since := "2024-04-17")]
alias support_nat_cast := support_natCast
lemma mulSupport_natCast (hn : n ≠ 1) : mulSupport (n : α → M) = univ :=
mulSupport_const <| Nat.cast_ne_one.2 hn
#align function.mul_support_nat_cast Function.mulSupport_natCast
@[deprecated (since := "2024-04-17")]
alias mulSupport_nat_cast := mulSupport_natCast
end Function
end AddMonoidWithOne
section
variable {R : Type*} [NonAssocSemiring R] [NoZeroDivisors R] [CharZero R] {a : R}
@[simp]
theorem add_self_eq_zero {a : R} : a + a = 0 ↔ a = 0 := by
simp only [(two_mul a).symm, mul_eq_zero, two_ne_zero, false_or_iff]
#align add_self_eq_zero add_self_eq_zero
set_option linter.deprecated false
@[simp]
theorem bit0_eq_zero {a : R} : bit0 a = 0 ↔ a = 0 :=
add_self_eq_zero
#align bit0_eq_zero bit0_eq_zero
@[simp]
theorem zero_eq_bit0 {a : R} : 0 = bit0 a ↔ a = 0 := by
rw [eq_comm]
exact bit0_eq_zero
#align zero_eq_bit0 zero_eq_bit0
theorem bit0_ne_zero : bit0 a ≠ 0 ↔ a ≠ 0 :=
bit0_eq_zero.not
#align bit0_ne_zero bit0_ne_zero
theorem zero_ne_bit0 : 0 ≠ bit0 a ↔ a ≠ 0 :=
zero_eq_bit0.not
#align zero_ne_bit0 zero_ne_bit0
end
section
variable {R : Type*} [NonAssocRing R] [NoZeroDivisors R] [CharZero R]
@[simp] theorem neg_eq_self_iff {a : R} : -a = a ↔ a = 0 :=
neg_eq_iff_add_eq_zero.trans add_self_eq_zero
#align neg_eq_self_iff neg_eq_self_iff
@[simp] theorem eq_neg_self_iff {a : R} : a = -a ↔ a = 0 :=
eq_neg_iff_add_eq_zero.trans add_self_eq_zero
#align eq_neg_self_iff eq_neg_self_iff
theorem nat_mul_inj {n : ℕ} {a b : R} (h : (n : R) * a = (n : R) * b) : n = 0 ∨ a = b := by
rw [← sub_eq_zero, ← mul_sub, mul_eq_zero, sub_eq_zero] at h
exact mod_cast h
#align nat_mul_inj nat_mul_inj
theorem nat_mul_inj' {n : ℕ} {a b : R} (h : (n : R) * a = (n : R) * b) (w : n ≠ 0) : a = b := by
simpa [w] using nat_mul_inj h
#align nat_mul_inj' nat_mul_inj'
set_option linter.deprecated false
theorem bit0_injective : Function.Injective (bit0 : R → R) := fun a b h => by
dsimp [bit0] at h
simp only [(two_mul a).symm, (two_mul b).symm] at h
refine nat_mul_inj' ?_ two_ne_zero
exact mod_cast h
#align bit0_injective bit0_injective
theorem bit1_injective : Function.Injective (bit1 : R → R) := fun a b h => by
simp only [bit1, add_left_inj] at h
exact bit0_injective h
#align bit1_injective bit1_injective
@[simp]
theorem bit0_eq_bit0 {a b : R} : bit0 a = bit0 b ↔ a = b :=
bit0_injective.eq_iff
#align bit0_eq_bit0 bit0_eq_bit0
@[simp]
theorem bit1_eq_bit1 {a b : R} : bit1 a = bit1 b ↔ a = b :=
bit1_injective.eq_iff
#align bit1_eq_bit1 bit1_eq_bit1
@[simp]
theorem bit1_eq_one {a : R} : bit1 a = 1 ↔ a = 0 := by
rw [show (1 : R) = bit1 0 by simp, bit1_eq_bit1]
#align bit1_eq_one bit1_eq_one
@[simp]
theorem one_eq_bit1 {a : R} : 1 = bit1 a ↔ a = 0 := by
rw [eq_comm]
exact bit1_eq_one
#align one_eq_bit1 one_eq_bit1
end
section
variable {R : Type*} [DivisionRing R] [CharZero R]
@[simp] lemma half_add_self (a : R) : (a + a) / 2 = a := by
rw [← mul_two, mul_div_cancel_right₀ a two_ne_zero]
#align half_add_self half_add_self
@[simp]
theorem add_halves' (a : R) : a / 2 + a / 2 = a := by rw [← add_div, half_add_self]
#align add_halves' add_halves'
| Mathlib/Algebra/CharZero/Lemmas.lean | 185 | 185 | theorem sub_half (a : R) : a - a / 2 = a / 2 := by | rw [sub_eq_iff_eq_add, add_halves']
|
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Abhimanyu Pallavi Sudhir
-/
import Mathlib.Algebra.Order.CauSeq.BigOperators
import Mathlib.Data.Complex.Abs
import Mathlib.Data.Complex.BigOperators
import Mathlib.Data.Nat.Choose.Sum
#align_import data.complex.exponential from "leanprover-community/mathlib"@"a8b2226cfb0a79f5986492053fc49b1a0c6aeffb"
/-!
# Exponential, trigonometric and hyperbolic trigonometric functions
This file contains the definitions of the real and complex exponential, sine, cosine, tangent,
hyperbolic sine, hyperbolic cosine, and hyperbolic tangent functions.
-/
open CauSeq Finset IsAbsoluteValue
open scoped Classical ComplexConjugate
namespace Complex
theorem isCauSeq_abs_exp (z : ℂ) :
IsCauSeq _root_.abs fun n => ∑ m ∈ range n, abs (z ^ m / m.factorial) :=
let ⟨n, hn⟩ := exists_nat_gt (abs z)
have hn0 : (0 : ℝ) < n := lt_of_le_of_lt (abs.nonneg _) hn
IsCauSeq.series_ratio_test n (abs z / n) (div_nonneg (abs.nonneg _) (le_of_lt hn0))
(by rwa [div_lt_iff hn0, one_mul]) fun m hm => by
rw [abs_abs, abs_abs, Nat.factorial_succ, pow_succ', mul_comm m.succ, Nat.cast_mul, ← div_div,
mul_div_assoc, mul_div_right_comm, map_mul, map_div₀, abs_natCast]
gcongr
exact le_trans hm (Nat.le_succ _)
#align complex.is_cau_abs_exp Complex.isCauSeq_abs_exp
noncomputable section
theorem isCauSeq_exp (z : ℂ) : IsCauSeq abs fun n => ∑ m ∈ range n, z ^ m / m.factorial :=
(isCauSeq_abs_exp z).of_abv
#align complex.is_cau_exp Complex.isCauSeq_exp
/-- The Cauchy sequence consisting of partial sums of the Taylor series of
the complex exponential function -/
-- Porting note (#11180): removed `@[pp_nodot]`
def exp' (z : ℂ) : CauSeq ℂ Complex.abs :=
⟨fun n => ∑ m ∈ range n, z ^ m / m.factorial, isCauSeq_exp z⟩
#align complex.exp' Complex.exp'
/-- The complex exponential function, defined via its Taylor series -/
-- Porting note (#11180): removed `@[pp_nodot]`
-- Porting note: removed `irreducible` attribute, so I can prove things
def exp (z : ℂ) : ℂ :=
CauSeq.lim (exp' z)
#align complex.exp Complex.exp
/-- The complex sine function, defined via `exp` -/
-- Porting note (#11180): removed `@[pp_nodot]`
def sin (z : ℂ) : ℂ :=
(exp (-z * I) - exp (z * I)) * I / 2
#align complex.sin Complex.sin
/-- The complex cosine function, defined via `exp` -/
-- Porting note (#11180): removed `@[pp_nodot]`
def cos (z : ℂ) : ℂ :=
(exp (z * I) + exp (-z * I)) / 2
#align complex.cos Complex.cos
/-- The complex tangent function, defined as `sin z / cos z` -/
-- Porting note (#11180): removed `@[pp_nodot]`
def tan (z : ℂ) : ℂ :=
sin z / cos z
#align complex.tan Complex.tan
/-- The complex cotangent function, defined as `cos z / sin z` -/
def cot (z : ℂ) : ℂ :=
cos z / sin z
/-- The complex hyperbolic sine function, defined via `exp` -/
-- Porting note (#11180): removed `@[pp_nodot]`
def sinh (z : ℂ) : ℂ :=
(exp z - exp (-z)) / 2
#align complex.sinh Complex.sinh
/-- The complex hyperbolic cosine function, defined via `exp` -/
-- Porting note (#11180): removed `@[pp_nodot]`
def cosh (z : ℂ) : ℂ :=
(exp z + exp (-z)) / 2
#align complex.cosh Complex.cosh
/-- The complex hyperbolic tangent function, defined as `sinh z / cosh z` -/
-- Porting note (#11180): removed `@[pp_nodot]`
def tanh (z : ℂ) : ℂ :=
sinh z / cosh z
#align complex.tanh Complex.tanh
/-- scoped notation for the complex exponential function -/
scoped notation "cexp" => Complex.exp
end
end Complex
namespace Real
open Complex
noncomputable section
/-- The real exponential function, defined as the real part of the complex exponential -/
-- Porting note (#11180): removed `@[pp_nodot]`
nonrec def exp (x : ℝ) : ℝ :=
(exp x).re
#align real.exp Real.exp
/-- The real sine function, defined as the real part of the complex sine -/
-- Porting note (#11180): removed `@[pp_nodot]`
nonrec def sin (x : ℝ) : ℝ :=
(sin x).re
#align real.sin Real.sin
/-- The real cosine function, defined as the real part of the complex cosine -/
-- Porting note (#11180): removed `@[pp_nodot]`
nonrec def cos (x : ℝ) : ℝ :=
(cos x).re
#align real.cos Real.cos
/-- The real tangent function, defined as the real part of the complex tangent -/
-- Porting note (#11180): removed `@[pp_nodot]`
nonrec def tan (x : ℝ) : ℝ :=
(tan x).re
#align real.tan Real.tan
/-- The real cotangent function, defined as the real part of the complex cotangent -/
nonrec def cot (x : ℝ) : ℝ :=
(cot x).re
/-- The real hypebolic sine function, defined as the real part of the complex hyperbolic sine -/
-- Porting note (#11180): removed `@[pp_nodot]`
nonrec def sinh (x : ℝ) : ℝ :=
(sinh x).re
#align real.sinh Real.sinh
/-- The real hypebolic cosine function, defined as the real part of the complex hyperbolic cosine -/
-- Porting note (#11180): removed `@[pp_nodot]`
nonrec def cosh (x : ℝ) : ℝ :=
(cosh x).re
#align real.cosh Real.cosh
/-- The real hypebolic tangent function, defined as the real part of
the complex hyperbolic tangent -/
-- Porting note (#11180): removed `@[pp_nodot]`
nonrec def tanh (x : ℝ) : ℝ :=
(tanh x).re
#align real.tanh Real.tanh
/-- scoped notation for the real exponential function -/
scoped notation "rexp" => Real.exp
end
end Real
namespace Complex
variable (x y : ℂ)
@[simp]
theorem exp_zero : exp 0 = 1 := by
rw [exp]
refine lim_eq_of_equiv_const fun ε ε0 => ⟨1, fun j hj => ?_⟩
convert (config := .unfoldSameFun) ε0 -- Porting note: ε0 : ε > 0 but goal is _ < ε
cases' j with j j
· exact absurd hj (not_le_of_gt zero_lt_one)
· dsimp [exp']
induction' j with j ih
· dsimp [exp']; simp [show Nat.succ 0 = 1 from rfl]
· rw [← ih (by simp [Nat.succ_le_succ])]
simp only [sum_range_succ, pow_succ]
simp
#align complex.exp_zero Complex.exp_zero
theorem exp_add : exp (x + y) = exp x * exp y := by
have hj : ∀ j : ℕ, (∑ m ∈ range j, (x + y) ^ m / m.factorial) =
∑ i ∈ range j, ∑ k ∈ range (i + 1), x ^ k / k.factorial *
(y ^ (i - k) / (i - k).factorial) := by
intro j
refine Finset.sum_congr rfl fun m _ => ?_
rw [add_pow, div_eq_mul_inv, sum_mul]
refine Finset.sum_congr rfl fun I hi => ?_
have h₁ : (m.choose I : ℂ) ≠ 0 :=
Nat.cast_ne_zero.2 (pos_iff_ne_zero.1 (Nat.choose_pos (Nat.le_of_lt_succ (mem_range.1 hi))))
have h₂ := Nat.choose_mul_factorial_mul_factorial (Nat.le_of_lt_succ <| Finset.mem_range.1 hi)
rw [← h₂, Nat.cast_mul, Nat.cast_mul, mul_inv, mul_inv]
simp only [mul_left_comm (m.choose I : ℂ), mul_assoc, mul_left_comm (m.choose I : ℂ)⁻¹,
mul_comm (m.choose I : ℂ)]
rw [inv_mul_cancel h₁]
simp [div_eq_mul_inv, mul_comm, mul_assoc, mul_left_comm]
simp_rw [exp, exp', lim_mul_lim]
apply (lim_eq_lim_of_equiv _).symm
simp only [hj]
exact cauchy_product (isCauSeq_abs_exp x) (isCauSeq_exp y)
#align complex.exp_add Complex.exp_add
-- Porting note (#11445): new definition
/-- the exponential function as a monoid hom from `Multiplicative ℂ` to `ℂ` -/
noncomputable def expMonoidHom : MonoidHom (Multiplicative ℂ) ℂ :=
{ toFun := fun z => exp (Multiplicative.toAdd z),
map_one' := by simp,
map_mul' := by simp [exp_add] }
theorem exp_list_sum (l : List ℂ) : exp l.sum = (l.map exp).prod :=
map_list_prod (M := Multiplicative ℂ) expMonoidHom l
#align complex.exp_list_sum Complex.exp_list_sum
theorem exp_multiset_sum (s : Multiset ℂ) : exp s.sum = (s.map exp).prod :=
@MonoidHom.map_multiset_prod (Multiplicative ℂ) ℂ _ _ expMonoidHom s
#align complex.exp_multiset_sum Complex.exp_multiset_sum
theorem exp_sum {α : Type*} (s : Finset α) (f : α → ℂ) :
exp (∑ x ∈ s, f x) = ∏ x ∈ s, exp (f x) :=
map_prod (β := Multiplicative ℂ) expMonoidHom f s
#align complex.exp_sum Complex.exp_sum
lemma exp_nsmul (x : ℂ) (n : ℕ) : exp (n • x) = exp x ^ n :=
@MonoidHom.map_pow (Multiplicative ℂ) ℂ _ _ expMonoidHom _ _
theorem exp_nat_mul (x : ℂ) : ∀ n : ℕ, exp (n * x) = exp x ^ n
| 0 => by rw [Nat.cast_zero, zero_mul, exp_zero, pow_zero]
| Nat.succ n => by rw [pow_succ, Nat.cast_add_one, add_mul, exp_add, ← exp_nat_mul _ n, one_mul]
#align complex.exp_nat_mul Complex.exp_nat_mul
theorem exp_ne_zero : exp x ≠ 0 := fun h =>
zero_ne_one <| by rw [← exp_zero, ← add_neg_self x, exp_add, h]; simp
#align complex.exp_ne_zero Complex.exp_ne_zero
theorem exp_neg : exp (-x) = (exp x)⁻¹ := by
rw [← mul_right_inj' (exp_ne_zero x), ← exp_add]; simp [mul_inv_cancel (exp_ne_zero x)]
#align complex.exp_neg Complex.exp_neg
theorem exp_sub : exp (x - y) = exp x / exp y := by
simp [sub_eq_add_neg, exp_add, exp_neg, div_eq_mul_inv]
#align complex.exp_sub Complex.exp_sub
theorem exp_int_mul (z : ℂ) (n : ℤ) : Complex.exp (n * z) = Complex.exp z ^ n := by
cases n
· simp [exp_nat_mul]
· simp [exp_add, add_mul, pow_add, exp_neg, exp_nat_mul]
#align complex.exp_int_mul Complex.exp_int_mul
@[simp]
theorem exp_conj : exp (conj x) = conj (exp x) := by
dsimp [exp]
rw [← lim_conj]
refine congr_arg CauSeq.lim (CauSeq.ext fun _ => ?_)
dsimp [exp', Function.comp_def, cauSeqConj]
rw [map_sum (starRingEnd _)]
refine sum_congr rfl fun n _ => ?_
rw [map_div₀, map_pow, ← ofReal_natCast, conj_ofReal]
#align complex.exp_conj Complex.exp_conj
@[simp]
theorem ofReal_exp_ofReal_re (x : ℝ) : ((exp x).re : ℂ) = exp x :=
conj_eq_iff_re.1 <| by rw [← exp_conj, conj_ofReal]
#align complex.of_real_exp_of_real_re Complex.ofReal_exp_ofReal_re
@[simp, norm_cast]
theorem ofReal_exp (x : ℝ) : (Real.exp x : ℂ) = exp x :=
ofReal_exp_ofReal_re _
#align complex.of_real_exp Complex.ofReal_exp
@[simp]
theorem exp_ofReal_im (x : ℝ) : (exp x).im = 0 := by rw [← ofReal_exp_ofReal_re, ofReal_im]
#align complex.exp_of_real_im Complex.exp_ofReal_im
theorem exp_ofReal_re (x : ℝ) : (exp x).re = Real.exp x :=
rfl
#align complex.exp_of_real_re Complex.exp_ofReal_re
theorem two_sinh : 2 * sinh x = exp x - exp (-x) :=
mul_div_cancel₀ _ two_ne_zero
#align complex.two_sinh Complex.two_sinh
theorem two_cosh : 2 * cosh x = exp x + exp (-x) :=
mul_div_cancel₀ _ two_ne_zero
#align complex.two_cosh Complex.two_cosh
@[simp]
theorem sinh_zero : sinh 0 = 0 := by simp [sinh]
#align complex.sinh_zero Complex.sinh_zero
@[simp]
theorem sinh_neg : sinh (-x) = -sinh x := by simp [sinh, exp_neg, (neg_div _ _).symm, add_mul]
#align complex.sinh_neg Complex.sinh_neg
private theorem sinh_add_aux {a b c d : ℂ} :
(a - b) * (c + d) + (a + b) * (c - d) = 2 * (a * c - b * d) := by ring
theorem sinh_add : sinh (x + y) = sinh x * cosh y + cosh x * sinh y := by
rw [← mul_right_inj' (two_ne_zero' ℂ), two_sinh, exp_add, neg_add, exp_add, eq_comm, mul_add, ←
mul_assoc, two_sinh, mul_left_comm, two_sinh, ← mul_right_inj' (two_ne_zero' ℂ), mul_add,
mul_left_comm, two_cosh, ← mul_assoc, two_cosh]
exact sinh_add_aux
#align complex.sinh_add Complex.sinh_add
@[simp]
theorem cosh_zero : cosh 0 = 1 := by simp [cosh]
#align complex.cosh_zero Complex.cosh_zero
@[simp]
theorem cosh_neg : cosh (-x) = cosh x := by simp [add_comm, cosh, exp_neg]
#align complex.cosh_neg Complex.cosh_neg
private theorem cosh_add_aux {a b c d : ℂ} :
(a + b) * (c + d) + (a - b) * (c - d) = 2 * (a * c + b * d) := by ring
theorem cosh_add : cosh (x + y) = cosh x * cosh y + sinh x * sinh y := by
rw [← mul_right_inj' (two_ne_zero' ℂ), two_cosh, exp_add, neg_add, exp_add, eq_comm, mul_add, ←
mul_assoc, two_cosh, ← mul_assoc, two_sinh, ← mul_right_inj' (two_ne_zero' ℂ), mul_add,
mul_left_comm, two_cosh, mul_left_comm, two_sinh]
exact cosh_add_aux
#align complex.cosh_add Complex.cosh_add
theorem sinh_sub : sinh (x - y) = sinh x * cosh y - cosh x * sinh y := by
simp [sub_eq_add_neg, sinh_add, sinh_neg, cosh_neg]
#align complex.sinh_sub Complex.sinh_sub
theorem cosh_sub : cosh (x - y) = cosh x * cosh y - sinh x * sinh y := by
simp [sub_eq_add_neg, cosh_add, sinh_neg, cosh_neg]
#align complex.cosh_sub Complex.cosh_sub
theorem sinh_conj : sinh (conj x) = conj (sinh x) := by
rw [sinh, ← RingHom.map_neg, exp_conj, exp_conj, ← RingHom.map_sub, sinh, map_div₀]
-- Porting note: not nice
simp [← one_add_one_eq_two]
#align complex.sinh_conj Complex.sinh_conj
@[simp]
theorem ofReal_sinh_ofReal_re (x : ℝ) : ((sinh x).re : ℂ) = sinh x :=
conj_eq_iff_re.1 <| by rw [← sinh_conj, conj_ofReal]
#align complex.of_real_sinh_of_real_re Complex.ofReal_sinh_ofReal_re
@[simp, norm_cast]
theorem ofReal_sinh (x : ℝ) : (Real.sinh x : ℂ) = sinh x :=
ofReal_sinh_ofReal_re _
#align complex.of_real_sinh Complex.ofReal_sinh
@[simp]
theorem sinh_ofReal_im (x : ℝ) : (sinh x).im = 0 := by rw [← ofReal_sinh_ofReal_re, ofReal_im]
#align complex.sinh_of_real_im Complex.sinh_ofReal_im
theorem sinh_ofReal_re (x : ℝ) : (sinh x).re = Real.sinh x :=
rfl
#align complex.sinh_of_real_re Complex.sinh_ofReal_re
theorem cosh_conj : cosh (conj x) = conj (cosh x) := by
rw [cosh, ← RingHom.map_neg, exp_conj, exp_conj, ← RingHom.map_add, cosh, map_div₀]
-- Porting note: not nice
simp [← one_add_one_eq_two]
#align complex.cosh_conj Complex.cosh_conj
theorem ofReal_cosh_ofReal_re (x : ℝ) : ((cosh x).re : ℂ) = cosh x :=
conj_eq_iff_re.1 <| by rw [← cosh_conj, conj_ofReal]
#align complex.of_real_cosh_of_real_re Complex.ofReal_cosh_ofReal_re
@[simp, norm_cast]
theorem ofReal_cosh (x : ℝ) : (Real.cosh x : ℂ) = cosh x :=
ofReal_cosh_ofReal_re _
#align complex.of_real_cosh Complex.ofReal_cosh
@[simp]
theorem cosh_ofReal_im (x : ℝ) : (cosh x).im = 0 := by rw [← ofReal_cosh_ofReal_re, ofReal_im]
#align complex.cosh_of_real_im Complex.cosh_ofReal_im
@[simp]
theorem cosh_ofReal_re (x : ℝ) : (cosh x).re = Real.cosh x :=
rfl
#align complex.cosh_of_real_re Complex.cosh_ofReal_re
theorem tanh_eq_sinh_div_cosh : tanh x = sinh x / cosh x :=
rfl
#align complex.tanh_eq_sinh_div_cosh Complex.tanh_eq_sinh_div_cosh
@[simp]
theorem tanh_zero : tanh 0 = 0 := by simp [tanh]
#align complex.tanh_zero Complex.tanh_zero
@[simp]
theorem tanh_neg : tanh (-x) = -tanh x := by simp [tanh, neg_div]
#align complex.tanh_neg Complex.tanh_neg
theorem tanh_conj : tanh (conj x) = conj (tanh x) := by
rw [tanh, sinh_conj, cosh_conj, ← map_div₀, tanh]
#align complex.tanh_conj Complex.tanh_conj
@[simp]
theorem ofReal_tanh_ofReal_re (x : ℝ) : ((tanh x).re : ℂ) = tanh x :=
conj_eq_iff_re.1 <| by rw [← tanh_conj, conj_ofReal]
#align complex.of_real_tanh_of_real_re Complex.ofReal_tanh_ofReal_re
@[simp, norm_cast]
theorem ofReal_tanh (x : ℝ) : (Real.tanh x : ℂ) = tanh x :=
ofReal_tanh_ofReal_re _
#align complex.of_real_tanh Complex.ofReal_tanh
@[simp]
theorem tanh_ofReal_im (x : ℝ) : (tanh x).im = 0 := by rw [← ofReal_tanh_ofReal_re, ofReal_im]
#align complex.tanh_of_real_im Complex.tanh_ofReal_im
theorem tanh_ofReal_re (x : ℝ) : (tanh x).re = Real.tanh x :=
rfl
#align complex.tanh_of_real_re Complex.tanh_ofReal_re
@[simp]
theorem cosh_add_sinh : cosh x + sinh x = exp x := by
rw [← mul_right_inj' (two_ne_zero' ℂ), mul_add, two_cosh, two_sinh, add_add_sub_cancel, two_mul]
#align complex.cosh_add_sinh Complex.cosh_add_sinh
@[simp]
theorem sinh_add_cosh : sinh x + cosh x = exp x := by rw [add_comm, cosh_add_sinh]
#align complex.sinh_add_cosh Complex.sinh_add_cosh
@[simp]
theorem exp_sub_cosh : exp x - cosh x = sinh x :=
sub_eq_iff_eq_add.2 (sinh_add_cosh x).symm
#align complex.exp_sub_cosh Complex.exp_sub_cosh
@[simp]
theorem exp_sub_sinh : exp x - sinh x = cosh x :=
sub_eq_iff_eq_add.2 (cosh_add_sinh x).symm
#align complex.exp_sub_sinh Complex.exp_sub_sinh
@[simp]
theorem cosh_sub_sinh : cosh x - sinh x = exp (-x) := by
rw [← mul_right_inj' (two_ne_zero' ℂ), mul_sub, two_cosh, two_sinh, add_sub_sub_cancel, two_mul]
#align complex.cosh_sub_sinh Complex.cosh_sub_sinh
@[simp]
theorem sinh_sub_cosh : sinh x - cosh x = -exp (-x) := by rw [← neg_sub, cosh_sub_sinh]
#align complex.sinh_sub_cosh Complex.sinh_sub_cosh
@[simp]
theorem cosh_sq_sub_sinh_sq : cosh x ^ 2 - sinh x ^ 2 = 1 := by
rw [sq_sub_sq, cosh_add_sinh, cosh_sub_sinh, ← exp_add, add_neg_self, exp_zero]
#align complex.cosh_sq_sub_sinh_sq Complex.cosh_sq_sub_sinh_sq
theorem cosh_sq : cosh x ^ 2 = sinh x ^ 2 + 1 := by
rw [← cosh_sq_sub_sinh_sq x]
ring
#align complex.cosh_sq Complex.cosh_sq
theorem sinh_sq : sinh x ^ 2 = cosh x ^ 2 - 1 := by
rw [← cosh_sq_sub_sinh_sq x]
ring
#align complex.sinh_sq Complex.sinh_sq
theorem cosh_two_mul : cosh (2 * x) = cosh x ^ 2 + sinh x ^ 2 := by rw [two_mul, cosh_add, sq, sq]
#align complex.cosh_two_mul Complex.cosh_two_mul
theorem sinh_two_mul : sinh (2 * x) = 2 * sinh x * cosh x := by
rw [two_mul, sinh_add]
ring
#align complex.sinh_two_mul Complex.sinh_two_mul
theorem cosh_three_mul : cosh (3 * x) = 4 * cosh x ^ 3 - 3 * cosh x := by
have h1 : x + 2 * x = 3 * x := by ring
rw [← h1, cosh_add x (2 * x)]
simp only [cosh_two_mul, sinh_two_mul]
have h2 : sinh x * (2 * sinh x * cosh x) = 2 * cosh x * sinh x ^ 2 := by ring
rw [h2, sinh_sq]
ring
#align complex.cosh_three_mul Complex.cosh_three_mul
theorem sinh_three_mul : sinh (3 * x) = 4 * sinh x ^ 3 + 3 * sinh x := by
have h1 : x + 2 * x = 3 * x := by ring
rw [← h1, sinh_add x (2 * x)]
simp only [cosh_two_mul, sinh_two_mul]
have h2 : cosh x * (2 * sinh x * cosh x) = 2 * sinh x * cosh x ^ 2 := by ring
rw [h2, cosh_sq]
ring
#align complex.sinh_three_mul Complex.sinh_three_mul
@[simp]
theorem sin_zero : sin 0 = 0 := by simp [sin]
#align complex.sin_zero Complex.sin_zero
@[simp]
theorem sin_neg : sin (-x) = -sin x := by
simp [sin, sub_eq_add_neg, exp_neg, (neg_div _ _).symm, add_mul]
#align complex.sin_neg Complex.sin_neg
theorem two_sin : 2 * sin x = (exp (-x * I) - exp (x * I)) * I :=
mul_div_cancel₀ _ two_ne_zero
#align complex.two_sin Complex.two_sin
theorem two_cos : 2 * cos x = exp (x * I) + exp (-x * I) :=
mul_div_cancel₀ _ two_ne_zero
#align complex.two_cos Complex.two_cos
theorem sinh_mul_I : sinh (x * I) = sin x * I := by
rw [← mul_right_inj' (two_ne_zero' ℂ), two_sinh, ← mul_assoc, two_sin, mul_assoc, I_mul_I,
mul_neg_one, neg_sub, neg_mul_eq_neg_mul]
set_option linter.uppercaseLean3 false in
#align complex.sinh_mul_I Complex.sinh_mul_I
theorem cosh_mul_I : cosh (x * I) = cos x := by
rw [← mul_right_inj' (two_ne_zero' ℂ), two_cosh, two_cos, neg_mul_eq_neg_mul]
set_option linter.uppercaseLean3 false in
#align complex.cosh_mul_I Complex.cosh_mul_I
theorem tanh_mul_I : tanh (x * I) = tan x * I := by
rw [tanh_eq_sinh_div_cosh, cosh_mul_I, sinh_mul_I, mul_div_right_comm, tan]
set_option linter.uppercaseLean3 false in
#align complex.tanh_mul_I Complex.tanh_mul_I
theorem cos_mul_I : cos (x * I) = cosh x := by rw [← cosh_mul_I]; ring_nf; simp
set_option linter.uppercaseLean3 false in
#align complex.cos_mul_I Complex.cos_mul_I
theorem sin_mul_I : sin (x * I) = sinh x * I := by
have h : I * sin (x * I) = -sinh x := by
rw [mul_comm, ← sinh_mul_I]
ring_nf
simp
rw [← neg_neg (sinh x), ← h]
apply Complex.ext <;> simp
set_option linter.uppercaseLean3 false in
#align complex.sin_mul_I Complex.sin_mul_I
theorem tan_mul_I : tan (x * I) = tanh x * I := by
rw [tan, sin_mul_I, cos_mul_I, mul_div_right_comm, tanh_eq_sinh_div_cosh]
set_option linter.uppercaseLean3 false in
#align complex.tan_mul_I Complex.tan_mul_I
theorem sin_add : sin (x + y) = sin x * cos y + cos x * sin y := by
rw [← mul_left_inj' I_ne_zero, ← sinh_mul_I, add_mul, add_mul, mul_right_comm, ← sinh_mul_I,
mul_assoc, ← sinh_mul_I, ← cosh_mul_I, ← cosh_mul_I, sinh_add]
#align complex.sin_add Complex.sin_add
@[simp]
theorem cos_zero : cos 0 = 1 := by simp [cos]
#align complex.cos_zero Complex.cos_zero
@[simp]
theorem cos_neg : cos (-x) = cos x := by simp [cos, sub_eq_add_neg, exp_neg, add_comm]
#align complex.cos_neg Complex.cos_neg
private theorem cos_add_aux {a b c d : ℂ} :
(a + b) * (c + d) - (b - a) * (d - c) * -1 = 2 * (a * c + b * d) := by ring
theorem cos_add : cos (x + y) = cos x * cos y - sin x * sin y := by
rw [← cosh_mul_I, add_mul, cosh_add, cosh_mul_I, cosh_mul_I, sinh_mul_I, sinh_mul_I,
mul_mul_mul_comm, I_mul_I, mul_neg_one, sub_eq_add_neg]
#align complex.cos_add Complex.cos_add
theorem sin_sub : sin (x - y) = sin x * cos y - cos x * sin y := by
simp [sub_eq_add_neg, sin_add, sin_neg, cos_neg]
#align complex.sin_sub Complex.sin_sub
theorem cos_sub : cos (x - y) = cos x * cos y + sin x * sin y := by
simp [sub_eq_add_neg, cos_add, sin_neg, cos_neg]
#align complex.cos_sub Complex.cos_sub
theorem sin_add_mul_I (x y : ℂ) : sin (x + y * I) = sin x * cosh y + cos x * sinh y * I := by
rw [sin_add, cos_mul_I, sin_mul_I, mul_assoc]
set_option linter.uppercaseLean3 false in
#align complex.sin_add_mul_I Complex.sin_add_mul_I
theorem sin_eq (z : ℂ) : sin z = sin z.re * cosh z.im + cos z.re * sinh z.im * I := by
convert sin_add_mul_I z.re z.im; exact (re_add_im z).symm
#align complex.sin_eq Complex.sin_eq
theorem cos_add_mul_I (x y : ℂ) : cos (x + y * I) = cos x * cosh y - sin x * sinh y * I := by
rw [cos_add, cos_mul_I, sin_mul_I, mul_assoc]
set_option linter.uppercaseLean3 false in
#align complex.cos_add_mul_I Complex.cos_add_mul_I
theorem cos_eq (z : ℂ) : cos z = cos z.re * cosh z.im - sin z.re * sinh z.im * I := by
convert cos_add_mul_I z.re z.im; exact (re_add_im z).symm
#align complex.cos_eq Complex.cos_eq
theorem sin_sub_sin : sin x - sin y = 2 * sin ((x - y) / 2) * cos ((x + y) / 2) := by
have s1 := sin_add ((x + y) / 2) ((x - y) / 2)
have s2 := sin_sub ((x + y) / 2) ((x - y) / 2)
rw [div_add_div_same, add_sub, add_right_comm, add_sub_cancel_right, half_add_self] at s1
rw [div_sub_div_same, ← sub_add, add_sub_cancel_left, half_add_self] at s2
rw [s1, s2]
ring
#align complex.sin_sub_sin Complex.sin_sub_sin
theorem cos_sub_cos : cos x - cos y = -2 * sin ((x + y) / 2) * sin ((x - y) / 2) := by
have s1 := cos_add ((x + y) / 2) ((x - y) / 2)
have s2 := cos_sub ((x + y) / 2) ((x - y) / 2)
rw [div_add_div_same, add_sub, add_right_comm, add_sub_cancel_right, half_add_self] at s1
rw [div_sub_div_same, ← sub_add, add_sub_cancel_left, half_add_self] at s2
rw [s1, s2]
ring
#align complex.cos_sub_cos Complex.cos_sub_cos
theorem sin_add_sin : sin x + sin y = 2 * sin ((x + y) / 2) * cos ((x - y) / 2) := by
simpa using sin_sub_sin x (-y)
theorem cos_add_cos : cos x + cos y = 2 * cos ((x + y) / 2) * cos ((x - y) / 2) := by
calc
cos x + cos y = cos ((x + y) / 2 + (x - y) / 2) + cos ((x + y) / 2 - (x - y) / 2) := ?_
_ =
cos ((x + y) / 2) * cos ((x - y) / 2) - sin ((x + y) / 2) * sin ((x - y) / 2) +
(cos ((x + y) / 2) * cos ((x - y) / 2) + sin ((x + y) / 2) * sin ((x - y) / 2)) :=
?_
_ = 2 * cos ((x + y) / 2) * cos ((x - y) / 2) := ?_
· congr <;> field_simp
· rw [cos_add, cos_sub]
ring
#align complex.cos_add_cos Complex.cos_add_cos
theorem sin_conj : sin (conj x) = conj (sin x) := by
rw [← mul_left_inj' I_ne_zero, ← sinh_mul_I, ← conj_neg_I, ← RingHom.map_mul, ← RingHom.map_mul,
sinh_conj, mul_neg, sinh_neg, sinh_mul_I, mul_neg]
#align complex.sin_conj Complex.sin_conj
@[simp]
theorem ofReal_sin_ofReal_re (x : ℝ) : ((sin x).re : ℂ) = sin x :=
conj_eq_iff_re.1 <| by rw [← sin_conj, conj_ofReal]
#align complex.of_real_sin_of_real_re Complex.ofReal_sin_ofReal_re
@[simp, norm_cast]
theorem ofReal_sin (x : ℝ) : (Real.sin x : ℂ) = sin x :=
ofReal_sin_ofReal_re _
#align complex.of_real_sin Complex.ofReal_sin
@[simp]
theorem sin_ofReal_im (x : ℝ) : (sin x).im = 0 := by rw [← ofReal_sin_ofReal_re, ofReal_im]
#align complex.sin_of_real_im Complex.sin_ofReal_im
theorem sin_ofReal_re (x : ℝ) : (sin x).re = Real.sin x :=
rfl
#align complex.sin_of_real_re Complex.sin_ofReal_re
theorem cos_conj : cos (conj x) = conj (cos x) := by
rw [← cosh_mul_I, ← conj_neg_I, ← RingHom.map_mul, ← cosh_mul_I, cosh_conj, mul_neg, cosh_neg]
#align complex.cos_conj Complex.cos_conj
@[simp]
theorem ofReal_cos_ofReal_re (x : ℝ) : ((cos x).re : ℂ) = cos x :=
conj_eq_iff_re.1 <| by rw [← cos_conj, conj_ofReal]
#align complex.of_real_cos_of_real_re Complex.ofReal_cos_ofReal_re
@[simp, norm_cast]
theorem ofReal_cos (x : ℝ) : (Real.cos x : ℂ) = cos x :=
ofReal_cos_ofReal_re _
#align complex.of_real_cos Complex.ofReal_cos
@[simp]
theorem cos_ofReal_im (x : ℝ) : (cos x).im = 0 := by rw [← ofReal_cos_ofReal_re, ofReal_im]
#align complex.cos_of_real_im Complex.cos_ofReal_im
theorem cos_ofReal_re (x : ℝ) : (cos x).re = Real.cos x :=
rfl
#align complex.cos_of_real_re Complex.cos_ofReal_re
@[simp]
theorem tan_zero : tan 0 = 0 := by simp [tan]
#align complex.tan_zero Complex.tan_zero
theorem tan_eq_sin_div_cos : tan x = sin x / cos x :=
rfl
#align complex.tan_eq_sin_div_cos Complex.tan_eq_sin_div_cos
theorem tan_mul_cos {x : ℂ} (hx : cos x ≠ 0) : tan x * cos x = sin x := by
rw [tan_eq_sin_div_cos, div_mul_cancel₀ _ hx]
#align complex.tan_mul_cos Complex.tan_mul_cos
@[simp]
theorem tan_neg : tan (-x) = -tan x := by simp [tan, neg_div]
#align complex.tan_neg Complex.tan_neg
theorem tan_conj : tan (conj x) = conj (tan x) := by rw [tan, sin_conj, cos_conj, ← map_div₀, tan]
#align complex.tan_conj Complex.tan_conj
@[simp]
theorem ofReal_tan_ofReal_re (x : ℝ) : ((tan x).re : ℂ) = tan x :=
conj_eq_iff_re.1 <| by rw [← tan_conj, conj_ofReal]
#align complex.of_real_tan_of_real_re Complex.ofReal_tan_ofReal_re
@[simp, norm_cast]
theorem ofReal_tan (x : ℝ) : (Real.tan x : ℂ) = tan x :=
ofReal_tan_ofReal_re _
#align complex.of_real_tan Complex.ofReal_tan
@[simp]
theorem tan_ofReal_im (x : ℝ) : (tan x).im = 0 := by rw [← ofReal_tan_ofReal_re, ofReal_im]
#align complex.tan_of_real_im Complex.tan_ofReal_im
theorem tan_ofReal_re (x : ℝ) : (tan x).re = Real.tan x :=
rfl
#align complex.tan_of_real_re Complex.tan_ofReal_re
theorem cos_add_sin_I : cos x + sin x * I = exp (x * I) := by
rw [← cosh_add_sinh, sinh_mul_I, cosh_mul_I]
set_option linter.uppercaseLean3 false in
#align complex.cos_add_sin_I Complex.cos_add_sin_I
theorem cos_sub_sin_I : cos x - sin x * I = exp (-x * I) := by
rw [neg_mul, ← cosh_sub_sinh, sinh_mul_I, cosh_mul_I]
set_option linter.uppercaseLean3 false in
#align complex.cos_sub_sin_I Complex.cos_sub_sin_I
@[simp]
theorem sin_sq_add_cos_sq : sin x ^ 2 + cos x ^ 2 = 1 :=
Eq.trans (by rw [cosh_mul_I, sinh_mul_I, mul_pow, I_sq, mul_neg_one, sub_neg_eq_add, add_comm])
(cosh_sq_sub_sinh_sq (x * I))
#align complex.sin_sq_add_cos_sq Complex.sin_sq_add_cos_sq
@[simp]
theorem cos_sq_add_sin_sq : cos x ^ 2 + sin x ^ 2 = 1 := by rw [add_comm, sin_sq_add_cos_sq]
#align complex.cos_sq_add_sin_sq Complex.cos_sq_add_sin_sq
theorem cos_two_mul' : cos (2 * x) = cos x ^ 2 - sin x ^ 2 := by rw [two_mul, cos_add, ← sq, ← sq]
#align complex.cos_two_mul' Complex.cos_two_mul'
theorem cos_two_mul : cos (2 * x) = 2 * cos x ^ 2 - 1 := by
rw [cos_two_mul', eq_sub_iff_add_eq.2 (sin_sq_add_cos_sq x), ← sub_add, sub_add_eq_add_sub,
two_mul]
#align complex.cos_two_mul Complex.cos_two_mul
theorem sin_two_mul : sin (2 * x) = 2 * sin x * cos x := by
rw [two_mul, sin_add, two_mul, add_mul, mul_comm]
#align complex.sin_two_mul Complex.sin_two_mul
theorem cos_sq : cos x ^ 2 = 1 / 2 + cos (2 * x) / 2 := by
simp [cos_two_mul, div_add_div_same, mul_div_cancel_left₀, two_ne_zero, -one_div]
#align complex.cos_sq Complex.cos_sq
theorem cos_sq' : cos x ^ 2 = 1 - sin x ^ 2 := by rw [← sin_sq_add_cos_sq x, add_sub_cancel_left]
#align complex.cos_sq' Complex.cos_sq'
theorem sin_sq : sin x ^ 2 = 1 - cos x ^ 2 := by rw [← sin_sq_add_cos_sq x, add_sub_cancel_right]
#align complex.sin_sq Complex.sin_sq
theorem inv_one_add_tan_sq {x : ℂ} (hx : cos x ≠ 0) : (1 + tan x ^ 2)⁻¹ = cos x ^ 2 := by
rw [tan_eq_sin_div_cos, div_pow]
field_simp
#align complex.inv_one_add_tan_sq Complex.inv_one_add_tan_sq
theorem tan_sq_div_one_add_tan_sq {x : ℂ} (hx : cos x ≠ 0) :
tan x ^ 2 / (1 + tan x ^ 2) = sin x ^ 2 := by
simp only [← tan_mul_cos hx, mul_pow, ← inv_one_add_tan_sq hx, div_eq_mul_inv, one_mul]
#align complex.tan_sq_div_one_add_tan_sq Complex.tan_sq_div_one_add_tan_sq
theorem cos_three_mul : cos (3 * x) = 4 * cos x ^ 3 - 3 * cos x := by
have h1 : x + 2 * x = 3 * x := by ring
rw [← h1, cos_add x (2 * x)]
simp only [cos_two_mul, sin_two_mul, mul_add, mul_sub, mul_one, sq]
have h2 : 4 * cos x ^ 3 = 2 * cos x * cos x * cos x + 2 * cos x * cos x ^ 2 := by ring
rw [h2, cos_sq']
ring
#align complex.cos_three_mul Complex.cos_three_mul
theorem sin_three_mul : sin (3 * x) = 3 * sin x - 4 * sin x ^ 3 := by
have h1 : x + 2 * x = 3 * x := by ring
rw [← h1, sin_add x (2 * x)]
simp only [cos_two_mul, sin_two_mul, cos_sq']
have h2 : cos x * (2 * sin x * cos x) = 2 * sin x * cos x ^ 2 := by ring
rw [h2, cos_sq']
ring
#align complex.sin_three_mul Complex.sin_three_mul
theorem exp_mul_I : exp (x * I) = cos x + sin x * I :=
(cos_add_sin_I _).symm
set_option linter.uppercaseLean3 false in
#align complex.exp_mul_I Complex.exp_mul_I
theorem exp_add_mul_I : exp (x + y * I) = exp x * (cos y + sin y * I) := by rw [exp_add, exp_mul_I]
set_option linter.uppercaseLean3 false in
#align complex.exp_add_mul_I Complex.exp_add_mul_I
| Mathlib/Data/Complex/Exponential.lean | 779 | 780 | theorem exp_eq_exp_re_mul_sin_add_cos : exp x = exp x.re * (cos x.im + sin x.im * I) := by |
rw [← exp_add_mul_I, re_add_im]
|
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Abhimanyu Pallavi Sudhir, Jean Lo, Calle Sönne, Sébastien Gouëzel,
Rémy Degenne, David Loeffler
-/
import Mathlib.Analysis.SpecialFunctions.Pow.Real
#align_import analysis.special_functions.pow.nnreal from "leanprover-community/mathlib"@"4fa54b337f7d52805480306db1b1439c741848c8"
/-!
# Power function on `ℝ≥0` and `ℝ≥0∞`
We construct the power functions `x ^ y` where
* `x` is a nonnegative real number and `y` is a real number;
* `x` is a number from `[0, +∞]` (a.k.a. `ℝ≥0∞`) and `y` is a real number.
We also prove basic properties of these functions.
-/
noncomputable section
open scoped Classical
open Real NNReal ENNReal ComplexConjugate
open Finset Function Set
namespace NNReal
variable {w x y z : ℝ}
/-- The nonnegative real power function `x^y`, defined for `x : ℝ≥0` and `y : ℝ` as the
restriction of the real power function. For `x > 0`, it is equal to `exp (y log x)`. For `x = 0`,
one sets `0 ^ 0 = 1` and `0 ^ y = 0` for `y ≠ 0`. -/
noncomputable def rpow (x : ℝ≥0) (y : ℝ) : ℝ≥0 :=
⟨(x : ℝ) ^ y, Real.rpow_nonneg x.2 y⟩
#align nnreal.rpow NNReal.rpow
noncomputable instance : Pow ℝ≥0 ℝ :=
⟨rpow⟩
@[simp]
theorem rpow_eq_pow (x : ℝ≥0) (y : ℝ) : rpow x y = x ^ y :=
rfl
#align nnreal.rpow_eq_pow NNReal.rpow_eq_pow
@[simp, norm_cast]
theorem coe_rpow (x : ℝ≥0) (y : ℝ) : ((x ^ y : ℝ≥0) : ℝ) = (x : ℝ) ^ y :=
rfl
#align nnreal.coe_rpow NNReal.coe_rpow
@[simp]
theorem rpow_zero (x : ℝ≥0) : x ^ (0 : ℝ) = 1 :=
NNReal.eq <| Real.rpow_zero _
#align nnreal.rpow_zero NNReal.rpow_zero
@[simp]
theorem rpow_eq_zero_iff {x : ℝ≥0} {y : ℝ} : x ^ y = 0 ↔ x = 0 ∧ y ≠ 0 := by
rw [← NNReal.coe_inj, coe_rpow, ← NNReal.coe_eq_zero]
exact Real.rpow_eq_zero_iff_of_nonneg x.2
#align nnreal.rpow_eq_zero_iff NNReal.rpow_eq_zero_iff
@[simp]
theorem zero_rpow {x : ℝ} (h : x ≠ 0) : (0 : ℝ≥0) ^ x = 0 :=
NNReal.eq <| Real.zero_rpow h
#align nnreal.zero_rpow NNReal.zero_rpow
@[simp]
theorem rpow_one (x : ℝ≥0) : x ^ (1 : ℝ) = x :=
NNReal.eq <| Real.rpow_one _
#align nnreal.rpow_one NNReal.rpow_one
@[simp]
theorem one_rpow (x : ℝ) : (1 : ℝ≥0) ^ x = 1 :=
NNReal.eq <| Real.one_rpow _
#align nnreal.one_rpow NNReal.one_rpow
theorem rpow_add {x : ℝ≥0} (hx : x ≠ 0) (y z : ℝ) : x ^ (y + z) = x ^ y * x ^ z :=
NNReal.eq <| Real.rpow_add (pos_iff_ne_zero.2 hx) _ _
#align nnreal.rpow_add NNReal.rpow_add
theorem rpow_add' (x : ℝ≥0) {y z : ℝ} (h : y + z ≠ 0) : x ^ (y + z) = x ^ y * x ^ z :=
NNReal.eq <| Real.rpow_add' x.2 h
#align nnreal.rpow_add' NNReal.rpow_add'
/-- Variant of `NNReal.rpow_add'` that avoids having to prove `y + z = w` twice. -/
lemma rpow_of_add_eq (x : ℝ≥0) (hw : w ≠ 0) (h : y + z = w) : x ^ w = x ^ y * x ^ z := by
rw [← h, rpow_add']; rwa [h]
theorem rpow_mul (x : ℝ≥0) (y z : ℝ) : x ^ (y * z) = (x ^ y) ^ z :=
NNReal.eq <| Real.rpow_mul x.2 y z
#align nnreal.rpow_mul NNReal.rpow_mul
theorem rpow_neg (x : ℝ≥0) (y : ℝ) : x ^ (-y) = (x ^ y)⁻¹ :=
NNReal.eq <| Real.rpow_neg x.2 _
#align nnreal.rpow_neg NNReal.rpow_neg
theorem rpow_neg_one (x : ℝ≥0) : x ^ (-1 : ℝ) = x⁻¹ := by simp [rpow_neg]
#align nnreal.rpow_neg_one NNReal.rpow_neg_one
theorem rpow_sub {x : ℝ≥0} (hx : x ≠ 0) (y z : ℝ) : x ^ (y - z) = x ^ y / x ^ z :=
NNReal.eq <| Real.rpow_sub (pos_iff_ne_zero.2 hx) y z
#align nnreal.rpow_sub NNReal.rpow_sub
theorem rpow_sub' (x : ℝ≥0) {y z : ℝ} (h : y - z ≠ 0) : x ^ (y - z) = x ^ y / x ^ z :=
NNReal.eq <| Real.rpow_sub' x.2 h
#align nnreal.rpow_sub' NNReal.rpow_sub'
theorem rpow_inv_rpow_self {y : ℝ} (hy : y ≠ 0) (x : ℝ≥0) : (x ^ y) ^ (1 / y) = x := by
field_simp [← rpow_mul]
#align nnreal.rpow_inv_rpow_self NNReal.rpow_inv_rpow_self
theorem rpow_self_rpow_inv {y : ℝ} (hy : y ≠ 0) (x : ℝ≥0) : (x ^ (1 / y)) ^ y = x := by
field_simp [← rpow_mul]
#align nnreal.rpow_self_rpow_inv NNReal.rpow_self_rpow_inv
theorem inv_rpow (x : ℝ≥0) (y : ℝ) : x⁻¹ ^ y = (x ^ y)⁻¹ :=
NNReal.eq <| Real.inv_rpow x.2 y
#align nnreal.inv_rpow NNReal.inv_rpow
theorem div_rpow (x y : ℝ≥0) (z : ℝ) : (x / y) ^ z = x ^ z / y ^ z :=
NNReal.eq <| Real.div_rpow x.2 y.2 z
#align nnreal.div_rpow NNReal.div_rpow
theorem sqrt_eq_rpow (x : ℝ≥0) : sqrt x = x ^ (1 / (2 : ℝ)) := by
refine NNReal.eq ?_
push_cast
exact Real.sqrt_eq_rpow x.1
#align nnreal.sqrt_eq_rpow NNReal.sqrt_eq_rpow
@[simp, norm_cast]
theorem rpow_natCast (x : ℝ≥0) (n : ℕ) : x ^ (n : ℝ) = x ^ n :=
NNReal.eq <| by simpa only [coe_rpow, coe_pow] using Real.rpow_natCast x n
#align nnreal.rpow_nat_cast NNReal.rpow_natCast
@[deprecated (since := "2024-04-17")]
alias rpow_nat_cast := rpow_natCast
@[simp]
lemma rpow_ofNat (x : ℝ≥0) (n : ℕ) [n.AtLeastTwo] :
x ^ (no_index (OfNat.ofNat n) : ℝ) = x ^ (OfNat.ofNat n : ℕ) :=
rpow_natCast x n
theorem rpow_two (x : ℝ≥0) : x ^ (2 : ℝ) = x ^ 2 := rpow_ofNat x 2
#align nnreal.rpow_two NNReal.rpow_two
theorem mul_rpow {x y : ℝ≥0} {z : ℝ} : (x * y) ^ z = x ^ z * y ^ z :=
NNReal.eq <| Real.mul_rpow x.2 y.2
#align nnreal.mul_rpow NNReal.mul_rpow
/-- `rpow` as a `MonoidHom`-/
@[simps]
def rpowMonoidHom (r : ℝ) : ℝ≥0 →* ℝ≥0 where
toFun := (· ^ r)
map_one' := one_rpow _
map_mul' _x _y := mul_rpow
/-- `rpow` variant of `List.prod_map_pow` for `ℝ≥0`-/
theorem list_prod_map_rpow (l : List ℝ≥0) (r : ℝ) :
(l.map (· ^ r)).prod = l.prod ^ r :=
l.prod_hom (rpowMonoidHom r)
theorem list_prod_map_rpow' {ι} (l : List ι) (f : ι → ℝ≥0) (r : ℝ) :
(l.map (f · ^ r)).prod = (l.map f).prod ^ r := by
rw [← list_prod_map_rpow, List.map_map]; rfl
/-- `rpow` version of `Multiset.prod_map_pow` for `ℝ≥0`. -/
lemma multiset_prod_map_rpow {ι} (s : Multiset ι) (f : ι → ℝ≥0) (r : ℝ) :
(s.map (f · ^ r)).prod = (s.map f).prod ^ r :=
s.prod_hom' (rpowMonoidHom r) _
/-- `rpow` version of `Finset.prod_pow` for `ℝ≥0`. -/
lemma finset_prod_rpow {ι} (s : Finset ι) (f : ι → ℝ≥0) (r : ℝ) :
(∏ i ∈ s, f i ^ r) = (∏ i ∈ s, f i) ^ r :=
multiset_prod_map_rpow _ _ _
-- note: these don't really belong here, but they're much easier to prove in terms of the above
section Real
/-- `rpow` version of `List.prod_map_pow` for `Real`. -/
theorem _root_.Real.list_prod_map_rpow (l : List ℝ) (hl : ∀ x ∈ l, (0 : ℝ) ≤ x) (r : ℝ) :
(l.map (· ^ r)).prod = l.prod ^ r := by
lift l to List ℝ≥0 using hl
have := congr_arg ((↑) : ℝ≥0 → ℝ) (NNReal.list_prod_map_rpow l r)
push_cast at this
rw [List.map_map] at this ⊢
exact mod_cast this
theorem _root_.Real.list_prod_map_rpow' {ι} (l : List ι) (f : ι → ℝ)
(hl : ∀ i ∈ l, (0 : ℝ) ≤ f i) (r : ℝ) :
(l.map (f · ^ r)).prod = (l.map f).prod ^ r := by
rw [← Real.list_prod_map_rpow (l.map f) _ r, List.map_map]
· rfl
simpa using hl
/-- `rpow` version of `Multiset.prod_map_pow`. -/
theorem _root_.Real.multiset_prod_map_rpow {ι} (s : Multiset ι) (f : ι → ℝ)
(hs : ∀ i ∈ s, (0 : ℝ) ≤ f i) (r : ℝ) :
(s.map (f · ^ r)).prod = (s.map f).prod ^ r := by
induction' s using Quotient.inductionOn with l
simpa using Real.list_prod_map_rpow' l f hs r
/-- `rpow` version of `Finset.prod_pow`. -/
theorem _root_.Real.finset_prod_rpow
{ι} (s : Finset ι) (f : ι → ℝ) (hs : ∀ i ∈ s, 0 ≤ f i) (r : ℝ) :
(∏ i ∈ s, f i ^ r) = (∏ i ∈ s, f i) ^ r :=
Real.multiset_prod_map_rpow s.val f hs r
end Real
@[gcongr] theorem rpow_le_rpow {x y : ℝ≥0} {z : ℝ} (h₁ : x ≤ y) (h₂ : 0 ≤ z) : x ^ z ≤ y ^ z :=
Real.rpow_le_rpow x.2 h₁ h₂
#align nnreal.rpow_le_rpow NNReal.rpow_le_rpow
@[gcongr] theorem rpow_lt_rpow {x y : ℝ≥0} {z : ℝ} (h₁ : x < y) (h₂ : 0 < z) : x ^ z < y ^ z :=
Real.rpow_lt_rpow x.2 h₁ h₂
#align nnreal.rpow_lt_rpow NNReal.rpow_lt_rpow
theorem rpow_lt_rpow_iff {x y : ℝ≥0} {z : ℝ} (hz : 0 < z) : x ^ z < y ^ z ↔ x < y :=
Real.rpow_lt_rpow_iff x.2 y.2 hz
#align nnreal.rpow_lt_rpow_iff NNReal.rpow_lt_rpow_iff
theorem rpow_le_rpow_iff {x y : ℝ≥0} {z : ℝ} (hz : 0 < z) : x ^ z ≤ y ^ z ↔ x ≤ y :=
Real.rpow_le_rpow_iff x.2 y.2 hz
#align nnreal.rpow_le_rpow_iff NNReal.rpow_le_rpow_iff
theorem le_rpow_one_div_iff {x y : ℝ≥0} {z : ℝ} (hz : 0 < z) : x ≤ y ^ (1 / z) ↔ x ^ z ≤ y := by
rw [← rpow_le_rpow_iff hz, rpow_self_rpow_inv hz.ne']
#align nnreal.le_rpow_one_div_iff NNReal.le_rpow_one_div_iff
theorem rpow_one_div_le_iff {x y : ℝ≥0} {z : ℝ} (hz : 0 < z) : x ^ (1 / z) ≤ y ↔ x ≤ y ^ z := by
rw [← rpow_le_rpow_iff hz, rpow_self_rpow_inv hz.ne']
#align nnreal.rpow_one_div_le_iff NNReal.rpow_one_div_le_iff
@[gcongr] theorem rpow_lt_rpow_of_exponent_lt {x : ℝ≥0} {y z : ℝ} (hx : 1 < x) (hyz : y < z) :
x ^ y < x ^ z :=
Real.rpow_lt_rpow_of_exponent_lt hx hyz
#align nnreal.rpow_lt_rpow_of_exponent_lt NNReal.rpow_lt_rpow_of_exponent_lt
@[gcongr] theorem rpow_le_rpow_of_exponent_le {x : ℝ≥0} {y z : ℝ} (hx : 1 ≤ x) (hyz : y ≤ z) :
x ^ y ≤ x ^ z :=
Real.rpow_le_rpow_of_exponent_le hx hyz
#align nnreal.rpow_le_rpow_of_exponent_le NNReal.rpow_le_rpow_of_exponent_le
theorem rpow_lt_rpow_of_exponent_gt {x : ℝ≥0} {y z : ℝ} (hx0 : 0 < x) (hx1 : x < 1) (hyz : z < y) :
x ^ y < x ^ z :=
Real.rpow_lt_rpow_of_exponent_gt hx0 hx1 hyz
#align nnreal.rpow_lt_rpow_of_exponent_gt NNReal.rpow_lt_rpow_of_exponent_gt
theorem rpow_le_rpow_of_exponent_ge {x : ℝ≥0} {y z : ℝ} (hx0 : 0 < x) (hx1 : x ≤ 1) (hyz : z ≤ y) :
x ^ y ≤ x ^ z :=
Real.rpow_le_rpow_of_exponent_ge hx0 hx1 hyz
#align nnreal.rpow_le_rpow_of_exponent_ge NNReal.rpow_le_rpow_of_exponent_ge
theorem rpow_pos {p : ℝ} {x : ℝ≥0} (hx_pos : 0 < x) : 0 < x ^ p := by
have rpow_pos_of_nonneg : ∀ {p : ℝ}, 0 < p → 0 < x ^ p := by
intro p hp_pos
rw [← zero_rpow hp_pos.ne']
exact rpow_lt_rpow hx_pos hp_pos
rcases lt_trichotomy (0 : ℝ) p with (hp_pos | rfl | hp_neg)
· exact rpow_pos_of_nonneg hp_pos
· simp only [zero_lt_one, rpow_zero]
· rw [← neg_neg p, rpow_neg, inv_pos]
exact rpow_pos_of_nonneg (neg_pos.mpr hp_neg)
#align nnreal.rpow_pos NNReal.rpow_pos
theorem rpow_lt_one {x : ℝ≥0} {z : ℝ} (hx1 : x < 1) (hz : 0 < z) : x ^ z < 1 :=
Real.rpow_lt_one (coe_nonneg x) hx1 hz
#align nnreal.rpow_lt_one NNReal.rpow_lt_one
theorem rpow_le_one {x : ℝ≥0} {z : ℝ} (hx2 : x ≤ 1) (hz : 0 ≤ z) : x ^ z ≤ 1 :=
Real.rpow_le_one x.2 hx2 hz
#align nnreal.rpow_le_one NNReal.rpow_le_one
theorem rpow_lt_one_of_one_lt_of_neg {x : ℝ≥0} {z : ℝ} (hx : 1 < x) (hz : z < 0) : x ^ z < 1 :=
Real.rpow_lt_one_of_one_lt_of_neg hx hz
#align nnreal.rpow_lt_one_of_one_lt_of_neg NNReal.rpow_lt_one_of_one_lt_of_neg
theorem rpow_le_one_of_one_le_of_nonpos {x : ℝ≥0} {z : ℝ} (hx : 1 ≤ x) (hz : z ≤ 0) : x ^ z ≤ 1 :=
Real.rpow_le_one_of_one_le_of_nonpos hx hz
#align nnreal.rpow_le_one_of_one_le_of_nonpos NNReal.rpow_le_one_of_one_le_of_nonpos
theorem one_lt_rpow {x : ℝ≥0} {z : ℝ} (hx : 1 < x) (hz : 0 < z) : 1 < x ^ z :=
Real.one_lt_rpow hx hz
#align nnreal.one_lt_rpow NNReal.one_lt_rpow
theorem one_le_rpow {x : ℝ≥0} {z : ℝ} (h : 1 ≤ x) (h₁ : 0 ≤ z) : 1 ≤ x ^ z :=
Real.one_le_rpow h h₁
#align nnreal.one_le_rpow NNReal.one_le_rpow
theorem one_lt_rpow_of_pos_of_lt_one_of_neg {x : ℝ≥0} {z : ℝ} (hx1 : 0 < x) (hx2 : x < 1)
(hz : z < 0) : 1 < x ^ z :=
Real.one_lt_rpow_of_pos_of_lt_one_of_neg hx1 hx2 hz
#align nnreal.one_lt_rpow_of_pos_of_lt_one_of_neg NNReal.one_lt_rpow_of_pos_of_lt_one_of_neg
theorem one_le_rpow_of_pos_of_le_one_of_nonpos {x : ℝ≥0} {z : ℝ} (hx1 : 0 < x) (hx2 : x ≤ 1)
(hz : z ≤ 0) : 1 ≤ x ^ z :=
Real.one_le_rpow_of_pos_of_le_one_of_nonpos hx1 hx2 hz
#align nnreal.one_le_rpow_of_pos_of_le_one_of_nonpos NNReal.one_le_rpow_of_pos_of_le_one_of_nonpos
theorem rpow_le_self_of_le_one {x : ℝ≥0} {z : ℝ} (hx : x ≤ 1) (h_one_le : 1 ≤ z) : x ^ z ≤ x := by
rcases eq_bot_or_bot_lt x with (rfl | (h : 0 < x))
· have : z ≠ 0 := by linarith
simp [this]
nth_rw 2 [← NNReal.rpow_one x]
exact NNReal.rpow_le_rpow_of_exponent_ge h hx h_one_le
#align nnreal.rpow_le_self_of_le_one NNReal.rpow_le_self_of_le_one
theorem rpow_left_injective {x : ℝ} (hx : x ≠ 0) : Function.Injective fun y : ℝ≥0 => y ^ x :=
fun y z hyz => by simpa only [rpow_inv_rpow_self hx] using congr_arg (fun y => y ^ (1 / x)) hyz
#align nnreal.rpow_left_injective NNReal.rpow_left_injective
theorem rpow_eq_rpow_iff {x y : ℝ≥0} {z : ℝ} (hz : z ≠ 0) : x ^ z = y ^ z ↔ x = y :=
(rpow_left_injective hz).eq_iff
#align nnreal.rpow_eq_rpow_iff NNReal.rpow_eq_rpow_iff
theorem rpow_left_surjective {x : ℝ} (hx : x ≠ 0) : Function.Surjective fun y : ℝ≥0 => y ^ x :=
fun y => ⟨y ^ x⁻¹, by simp_rw [← rpow_mul, _root_.inv_mul_cancel hx, rpow_one]⟩
#align nnreal.rpow_left_surjective NNReal.rpow_left_surjective
theorem rpow_left_bijective {x : ℝ} (hx : x ≠ 0) : Function.Bijective fun y : ℝ≥0 => y ^ x :=
⟨rpow_left_injective hx, rpow_left_surjective hx⟩
#align nnreal.rpow_left_bijective NNReal.rpow_left_bijective
theorem eq_rpow_one_div_iff {x y : ℝ≥0} {z : ℝ} (hz : z ≠ 0) : x = y ^ (1 / z) ↔ x ^ z = y := by
rw [← rpow_eq_rpow_iff hz, rpow_self_rpow_inv hz]
#align nnreal.eq_rpow_one_div_iff NNReal.eq_rpow_one_div_iff
theorem rpow_one_div_eq_iff {x y : ℝ≥0} {z : ℝ} (hz : z ≠ 0) : x ^ (1 / z) = y ↔ x = y ^ z := by
rw [← rpow_eq_rpow_iff hz, rpow_self_rpow_inv hz]
#align nnreal.rpow_one_div_eq_iff NNReal.rpow_one_div_eq_iff
@[simp] lemma rpow_rpow_inv {y : ℝ} (hy : y ≠ 0) (x : ℝ≥0) : (x ^ y) ^ y⁻¹ = x := by
rw [← rpow_mul, mul_inv_cancel hy, rpow_one]
@[simp] lemma rpow_inv_rpow {y : ℝ} (hy : y ≠ 0) (x : ℝ≥0) : (x ^ y⁻¹) ^ y = x := by
rw [← rpow_mul, inv_mul_cancel hy, rpow_one]
theorem pow_rpow_inv_natCast (x : ℝ≥0) {n : ℕ} (hn : n ≠ 0) : (x ^ n) ^ (n⁻¹ : ℝ) = x := by
rw [← NNReal.coe_inj, coe_rpow, NNReal.coe_pow]
exact Real.pow_rpow_inv_natCast x.2 hn
#align nnreal.pow_nat_rpow_nat_inv NNReal.pow_rpow_inv_natCast
theorem rpow_inv_natCast_pow (x : ℝ≥0) {n : ℕ} (hn : n ≠ 0) : (x ^ (n⁻¹ : ℝ)) ^ n = x := by
rw [← NNReal.coe_inj, NNReal.coe_pow, coe_rpow]
exact Real.rpow_inv_natCast_pow x.2 hn
#align nnreal.rpow_nat_inv_pow_nat NNReal.rpow_inv_natCast_pow
theorem _root_.Real.toNNReal_rpow_of_nonneg {x y : ℝ} (hx : 0 ≤ x) :
Real.toNNReal (x ^ y) = Real.toNNReal x ^ y := by
nth_rw 1 [← Real.coe_toNNReal x hx]
rw [← NNReal.coe_rpow, Real.toNNReal_coe]
#align real.to_nnreal_rpow_of_nonneg Real.toNNReal_rpow_of_nonneg
theorem strictMono_rpow_of_pos {z : ℝ} (h : 0 < z) : StrictMono fun x : ℝ≥0 => x ^ z :=
fun x y hxy => by simp only [NNReal.rpow_lt_rpow hxy h, coe_lt_coe]
theorem monotone_rpow_of_nonneg {z : ℝ} (h : 0 ≤ z) : Monotone fun x : ℝ≥0 => x ^ z :=
h.eq_or_lt.elim (fun h0 => h0 ▸ by simp only [rpow_zero, monotone_const]) fun h0 =>
(strictMono_rpow_of_pos h0).monotone
/-- Bundles `fun x : ℝ≥0 => x ^ y` into an order isomorphism when `y : ℝ` is positive,
where the inverse is `fun x : ℝ≥0 => x ^ (1 / y)`. -/
@[simps! apply]
def orderIsoRpow (y : ℝ) (hy : 0 < y) : ℝ≥0 ≃o ℝ≥0 :=
(strictMono_rpow_of_pos hy).orderIsoOfRightInverse (fun x => x ^ y) (fun x => x ^ (1 / y))
fun x => by
dsimp
rw [← rpow_mul, one_div_mul_cancel hy.ne.symm, rpow_one]
theorem orderIsoRpow_symm_eq (y : ℝ) (hy : 0 < y) :
(orderIsoRpow y hy).symm = orderIsoRpow (1 / y) (one_div_pos.2 hy) := by
simp only [orderIsoRpow, one_div_one_div]; rfl
end NNReal
namespace ENNReal
/-- The real power function `x^y` on extended nonnegative reals, defined for `x : ℝ≥0∞` and
`y : ℝ` as the restriction of the real power function if `0 < x < ⊤`, and with the natural values
for `0` and `⊤` (i.e., `0 ^ x = 0` for `x > 0`, `1` for `x = 0` and `⊤` for `x < 0`, and
`⊤ ^ x = 1 / 0 ^ x`). -/
noncomputable def rpow : ℝ≥0∞ → ℝ → ℝ≥0∞
| some x, y => if x = 0 ∧ y < 0 then ⊤ else (x ^ y : ℝ≥0)
| none, y => if 0 < y then ⊤ else if y = 0 then 1 else 0
#align ennreal.rpow ENNReal.rpow
noncomputable instance : Pow ℝ≥0∞ ℝ :=
⟨rpow⟩
@[simp]
theorem rpow_eq_pow (x : ℝ≥0∞) (y : ℝ) : rpow x y = x ^ y :=
rfl
#align ennreal.rpow_eq_pow ENNReal.rpow_eq_pow
@[simp]
theorem rpow_zero {x : ℝ≥0∞} : x ^ (0 : ℝ) = 1 := by
cases x <;>
· dsimp only [(· ^ ·), Pow.pow, rpow]
simp [lt_irrefl]
#align ennreal.rpow_zero ENNReal.rpow_zero
theorem top_rpow_def (y : ℝ) : (⊤ : ℝ≥0∞) ^ y = if 0 < y then ⊤ else if y = 0 then 1 else 0 :=
rfl
#align ennreal.top_rpow_def ENNReal.top_rpow_def
@[simp]
theorem top_rpow_of_pos {y : ℝ} (h : 0 < y) : (⊤ : ℝ≥0∞) ^ y = ⊤ := by simp [top_rpow_def, h]
#align ennreal.top_rpow_of_pos ENNReal.top_rpow_of_pos
@[simp]
theorem top_rpow_of_neg {y : ℝ} (h : y < 0) : (⊤ : ℝ≥0∞) ^ y = 0 := by
simp [top_rpow_def, asymm h, ne_of_lt h]
#align ennreal.top_rpow_of_neg ENNReal.top_rpow_of_neg
@[simp]
| Mathlib/Analysis/SpecialFunctions/Pow/NNReal.lean | 417 | 420 | theorem zero_rpow_of_pos {y : ℝ} (h : 0 < y) : (0 : ℝ≥0∞) ^ y = 0 := by |
rw [← ENNReal.coe_zero, ← ENNReal.some_eq_coe]
dsimp only [(· ^ ·), rpow, Pow.pow]
simp [h, asymm h, ne_of_gt h]
|
/-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.RingTheory.Noetherian
import Mathlib.RingTheory.Artinian
#align_import algebra.lie.submodule from "leanprover-community/mathlib"@"9822b65bfc4ac74537d77ae318d27df1df662471"
/-!
# Lie submodules of a Lie algebra
In this file we define Lie submodules and Lie ideals, we construct the lattice structure on Lie
submodules and we use it to define various important operations, notably the Lie span of a subset
of a Lie module.
## Main definitions
* `LieSubmodule`
* `LieSubmodule.wellFounded_of_noetherian`
* `LieSubmodule.lieSpan`
* `LieSubmodule.map`
* `LieSubmodule.comap`
* `LieIdeal`
* `LieIdeal.map`
* `LieIdeal.comap`
## Tags
lie algebra, lie submodule, lie ideal, lattice structure
-/
universe u v w w₁ w₂
section LieSubmodule
variable (R : Type u) (L : Type v) (M : Type w)
variable [CommRing R] [LieRing L] [LieAlgebra R L] [AddCommGroup M] [Module R M]
variable [LieRingModule L M] [LieModule R L M]
/-- A Lie submodule of a Lie module is a submodule that is closed under the Lie bracket.
This is a sufficient condition for the subset itself to form a Lie module. -/
structure LieSubmodule extends Submodule R M where
lie_mem : ∀ {x : L} {m : M}, m ∈ carrier → ⁅x, m⁆ ∈ carrier
#align lie_submodule LieSubmodule
attribute [nolint docBlame] LieSubmodule.toSubmodule
attribute [coe] LieSubmodule.toSubmodule
namespace LieSubmodule
variable {R L M}
variable (N N' : LieSubmodule R L M)
instance : SetLike (LieSubmodule R L M) M where
coe s := s.carrier
coe_injective' N O h := by cases N; cases O; congr; exact SetLike.coe_injective' h
instance : AddSubgroupClass (LieSubmodule R L M) M where
add_mem {N} _ _ := N.add_mem'
zero_mem N := N.zero_mem'
neg_mem {N} x hx := show -x ∈ N.toSubmodule from neg_mem hx
instance instSMulMemClass : SMulMemClass (LieSubmodule R L M) R M where
smul_mem {s} c _ h := s.smul_mem' c h
/-- The zero module is a Lie submodule of any Lie module. -/
instance : Zero (LieSubmodule R L M) :=
⟨{ (0 : Submodule R M) with
lie_mem := fun {x m} h ↦ by rw [(Submodule.mem_bot R).1 h]; apply lie_zero }⟩
instance : Inhabited (LieSubmodule R L M) :=
⟨0⟩
instance coeSubmodule : CoeOut (LieSubmodule R L M) (Submodule R M) :=
⟨toSubmodule⟩
#align lie_submodule.coe_submodule LieSubmodule.coeSubmodule
-- Syntactic tautology
#noalign lie_submodule.to_submodule_eq_coe
@[norm_cast]
theorem coe_toSubmodule : ((N : Submodule R M) : Set M) = N :=
rfl
#align lie_submodule.coe_to_submodule LieSubmodule.coe_toSubmodule
-- Porting note (#10618): `simp` can prove this after `mem_coeSubmodule` is added to the simp set,
-- but `dsimp` can't.
@[simp, nolint simpNF]
theorem mem_carrier {x : M} : x ∈ N.carrier ↔ x ∈ (N : Set M) :=
Iff.rfl
#align lie_submodule.mem_carrier LieSubmodule.mem_carrier
theorem mem_mk_iff (S : Set M) (h₁ h₂ h₃ h₄) {x : M} :
x ∈ (⟨⟨⟨⟨S, h₁⟩, h₂⟩, h₃⟩, h₄⟩ : LieSubmodule R L M) ↔ x ∈ S :=
Iff.rfl
#align lie_submodule.mem_mk_iff LieSubmodule.mem_mk_iff
@[simp]
theorem mem_mk_iff' (p : Submodule R M) (h) {x : M} :
x ∈ (⟨p, h⟩ : LieSubmodule R L M) ↔ x ∈ p :=
Iff.rfl
@[simp]
theorem mem_coeSubmodule {x : M} : x ∈ (N : Submodule R M) ↔ x ∈ N :=
Iff.rfl
#align lie_submodule.mem_coe_submodule LieSubmodule.mem_coeSubmodule
theorem mem_coe {x : M} : x ∈ (N : Set M) ↔ x ∈ N :=
Iff.rfl
#align lie_submodule.mem_coe LieSubmodule.mem_coe
@[simp]
protected theorem zero_mem : (0 : M) ∈ N :=
zero_mem N
#align lie_submodule.zero_mem LieSubmodule.zero_mem
-- Porting note (#10618): @[simp] can prove this
theorem mk_eq_zero {x} (h : x ∈ N) : (⟨x, h⟩ : N) = 0 ↔ x = 0 :=
Subtype.ext_iff_val
#align lie_submodule.mk_eq_zero LieSubmodule.mk_eq_zero
@[simp]
theorem coe_toSet_mk (S : Set M) (h₁ h₂ h₃ h₄) :
((⟨⟨⟨⟨S, h₁⟩, h₂⟩, h₃⟩, h₄⟩ : LieSubmodule R L M) : Set M) = S :=
rfl
#align lie_submodule.coe_to_set_mk LieSubmodule.coe_toSet_mk
theorem coe_toSubmodule_mk (p : Submodule R M) (h) :
(({ p with lie_mem := h } : LieSubmodule R L M) : Submodule R M) = p := by cases p; rfl
#align lie_submodule.coe_to_submodule_mk LieSubmodule.coe_toSubmodule_mk
theorem coeSubmodule_injective :
Function.Injective (toSubmodule : LieSubmodule R L M → Submodule R M) := fun x y h ↦ by
cases x; cases y; congr
#align lie_submodule.coe_submodule_injective LieSubmodule.coeSubmodule_injective
@[ext]
theorem ext (h : ∀ m, m ∈ N ↔ m ∈ N') : N = N' :=
SetLike.ext h
#align lie_submodule.ext LieSubmodule.ext
@[simp]
theorem coe_toSubmodule_eq_iff : (N : Submodule R M) = (N' : Submodule R M) ↔ N = N' :=
coeSubmodule_injective.eq_iff
#align lie_submodule.coe_to_submodule_eq_iff LieSubmodule.coe_toSubmodule_eq_iff
/-- Copy of a `LieSubmodule` with a new `carrier` equal to the old one. Useful to fix definitional
equalities. -/
protected def copy (s : Set M) (hs : s = ↑N) : LieSubmodule R L M where
carrier := s
-- Porting note: all the proofs below were in term mode
zero_mem' := by exact hs.symm ▸ N.zero_mem'
add_mem' x y := by rw [hs] at x y ⊢; exact N.add_mem' x y
smul_mem' := by exact hs.symm ▸ N.smul_mem'
lie_mem := by exact hs.symm ▸ N.lie_mem
#align lie_submodule.copy LieSubmodule.copy
@[simp]
theorem coe_copy (S : LieSubmodule R L M) (s : Set M) (hs : s = ↑S) : (S.copy s hs : Set M) = s :=
rfl
#align lie_submodule.coe_copy LieSubmodule.coe_copy
theorem copy_eq (S : LieSubmodule R L M) (s : Set M) (hs : s = ↑S) : S.copy s hs = S :=
SetLike.coe_injective hs
#align lie_submodule.copy_eq LieSubmodule.copy_eq
instance : LieRingModule L N where
bracket (x : L) (m : N) := ⟨⁅x, m.val⁆, N.lie_mem m.property⟩
add_lie := by intro x y m; apply SetCoe.ext; apply add_lie
lie_add := by intro x m n; apply SetCoe.ext; apply lie_add
leibniz_lie := by intro x y m; apply SetCoe.ext; apply leibniz_lie
instance module' {S : Type*} [Semiring S] [SMul S R] [Module S M] [IsScalarTower S R M] :
Module S N :=
N.toSubmodule.module'
#align lie_submodule.module' LieSubmodule.module'
instance : Module R N :=
N.toSubmodule.module
instance {S : Type*} [Semiring S] [SMul S R] [SMul Sᵐᵒᵖ R] [Module S M] [Module Sᵐᵒᵖ M]
[IsScalarTower S R M] [IsScalarTower Sᵐᵒᵖ R M] [IsCentralScalar S M] : IsCentralScalar S N :=
N.toSubmodule.isCentralScalar
instance instLieModule : LieModule R L N where
lie_smul := by intro t x y; apply SetCoe.ext; apply lie_smul
smul_lie := by intro t x y; apply SetCoe.ext; apply smul_lie
@[simp, norm_cast]
theorem coe_zero : ((0 : N) : M) = (0 : M) :=
rfl
#align lie_submodule.coe_zero LieSubmodule.coe_zero
@[simp, norm_cast]
theorem coe_add (m m' : N) : (↑(m + m') : M) = (m : M) + (m' : M) :=
rfl
#align lie_submodule.coe_add LieSubmodule.coe_add
@[simp, norm_cast]
theorem coe_neg (m : N) : (↑(-m) : M) = -(m : M) :=
rfl
#align lie_submodule.coe_neg LieSubmodule.coe_neg
@[simp, norm_cast]
theorem coe_sub (m m' : N) : (↑(m - m') : M) = (m : M) - (m' : M) :=
rfl
#align lie_submodule.coe_sub LieSubmodule.coe_sub
@[simp, norm_cast]
theorem coe_smul (t : R) (m : N) : (↑(t • m) : M) = t • (m : M) :=
rfl
#align lie_submodule.coe_smul LieSubmodule.coe_smul
@[simp, norm_cast]
theorem coe_bracket (x : L) (m : N) : (↑⁅x, m⁆ : M) = ⁅x, ↑m⁆ :=
rfl
#align lie_submodule.coe_bracket LieSubmodule.coe_bracket
instance [Subsingleton M] : Unique (LieSubmodule R L M) :=
⟨⟨0⟩, fun _ ↦ (coe_toSubmodule_eq_iff _ _).mp (Subsingleton.elim _ _)⟩
end LieSubmodule
section LieIdeal
/-- An ideal of a Lie algebra is a Lie submodule of the Lie algebra as a Lie module over itself. -/
abbrev LieIdeal :=
LieSubmodule R L L
#align lie_ideal LieIdeal
theorem lie_mem_right (I : LieIdeal R L) (x y : L) (h : y ∈ I) : ⁅x, y⁆ ∈ I :=
I.lie_mem h
#align lie_mem_right lie_mem_right
theorem lie_mem_left (I : LieIdeal R L) (x y : L) (h : x ∈ I) : ⁅x, y⁆ ∈ I := by
rw [← lie_skew, ← neg_lie]; apply lie_mem_right; assumption
#align lie_mem_left lie_mem_left
/-- An ideal of a Lie algebra is a Lie subalgebra. -/
def lieIdealSubalgebra (I : LieIdeal R L) : LieSubalgebra R L :=
{ I.toSubmodule with lie_mem' := by intro x y _ hy; apply lie_mem_right; exact hy }
#align lie_ideal_subalgebra lieIdealSubalgebra
instance : Coe (LieIdeal R L) (LieSubalgebra R L) :=
⟨lieIdealSubalgebra R L⟩
@[simp]
theorem LieIdeal.coe_toSubalgebra (I : LieIdeal R L) : ((I : LieSubalgebra R L) : Set L) = I :=
rfl
#align lie_ideal.coe_to_subalgebra LieIdeal.coe_toSubalgebra
@[simp]
theorem LieIdeal.coe_to_lieSubalgebra_to_submodule (I : LieIdeal R L) :
((I : LieSubalgebra R L) : Submodule R L) = LieSubmodule.toSubmodule I :=
rfl
#align lie_ideal.coe_to_lie_subalgebra_to_submodule LieIdeal.coe_to_lieSubalgebra_to_submodule
/-- An ideal of `L` is a Lie subalgebra of `L`, so it is a Lie ring. -/
instance LieIdeal.lieRing (I : LieIdeal R L) : LieRing I :=
LieSubalgebra.lieRing R L ↑I
#align lie_ideal.lie_ring LieIdeal.lieRing
/-- Transfer the `LieAlgebra` instance from the coercion `LieIdeal → LieSubalgebra`. -/
instance LieIdeal.lieAlgebra (I : LieIdeal R L) : LieAlgebra R I :=
LieSubalgebra.lieAlgebra R L ↑I
#align lie_ideal.lie_algebra LieIdeal.lieAlgebra
/-- Transfer the `LieRingModule` instance from the coercion `LieIdeal → LieSubalgebra`. -/
instance LieIdeal.lieRingModule {R L : Type*} [CommRing R] [LieRing L] [LieAlgebra R L]
(I : LieIdeal R L) [LieRingModule L M] : LieRingModule I M :=
LieSubalgebra.lieRingModule (I : LieSubalgebra R L)
#align lie_ideal.lie_ring_module LieIdeal.lieRingModule
@[simp]
theorem LieIdeal.coe_bracket_of_module {R L : Type*} [CommRing R] [LieRing L] [LieAlgebra R L]
(I : LieIdeal R L) [LieRingModule L M] (x : I) (m : M) : ⁅x, m⁆ = ⁅(↑x : L), m⁆ :=
LieSubalgebra.coe_bracket_of_module (I : LieSubalgebra R L) x m
#align lie_ideal.coe_bracket_of_module LieIdeal.coe_bracket_of_module
/-- Transfer the `LieModule` instance from the coercion `LieIdeal → LieSubalgebra`. -/
instance LieIdeal.lieModule (I : LieIdeal R L) : LieModule R I M :=
LieSubalgebra.lieModule (I : LieSubalgebra R L)
#align lie_ideal.lie_module LieIdeal.lieModule
end LieIdeal
variable {R M}
theorem Submodule.exists_lieSubmodule_coe_eq_iff (p : Submodule R M) :
(∃ N : LieSubmodule R L M, ↑N = p) ↔ ∀ (x : L) (m : M), m ∈ p → ⁅x, m⁆ ∈ p := by
constructor
· rintro ⟨N, rfl⟩ _ _; exact N.lie_mem
· intro h; use { p with lie_mem := @h }
#align submodule.exists_lie_submodule_coe_eq_iff Submodule.exists_lieSubmodule_coe_eq_iff
namespace LieSubalgebra
variable {L}
variable (K : LieSubalgebra R L)
/-- Given a Lie subalgebra `K ⊆ L`, if we view `L` as a `K`-module by restriction, it contains
a distinguished Lie submodule for the action of `K`, namely `K` itself. -/
def toLieSubmodule : LieSubmodule R K L :=
{ (K : Submodule R L) with lie_mem := fun {x _} hy ↦ K.lie_mem x.property hy }
#align lie_subalgebra.to_lie_submodule LieSubalgebra.toLieSubmodule
@[simp]
theorem coe_toLieSubmodule : (K.toLieSubmodule : Submodule R L) = K := rfl
#align lie_subalgebra.coe_to_lie_submodule LieSubalgebra.coe_toLieSubmodule
variable {K}
@[simp]
theorem mem_toLieSubmodule (x : L) : x ∈ K.toLieSubmodule ↔ x ∈ K :=
Iff.rfl
#align lie_subalgebra.mem_to_lie_submodule LieSubalgebra.mem_toLieSubmodule
theorem exists_lieIdeal_coe_eq_iff :
(∃ I : LieIdeal R L, ↑I = K) ↔ ∀ x y : L, y ∈ K → ⁅x, y⁆ ∈ K := by
simp only [← coe_to_submodule_eq_iff, LieIdeal.coe_to_lieSubalgebra_to_submodule,
Submodule.exists_lieSubmodule_coe_eq_iff L]
exact Iff.rfl
#align lie_subalgebra.exists_lie_ideal_coe_eq_iff LieSubalgebra.exists_lieIdeal_coe_eq_iff
theorem exists_nested_lieIdeal_coe_eq_iff {K' : LieSubalgebra R L} (h : K ≤ K') :
(∃ I : LieIdeal R K', ↑I = ofLe h) ↔ ∀ x y : L, x ∈ K' → y ∈ K → ⁅x, y⁆ ∈ K := by
simp only [exists_lieIdeal_coe_eq_iff, coe_bracket, mem_ofLe]
constructor
· intro h' x y hx hy; exact h' ⟨x, hx⟩ ⟨y, h hy⟩ hy
· rintro h' ⟨x, hx⟩ ⟨y, hy⟩ hy'; exact h' x y hx hy'
#align lie_subalgebra.exists_nested_lie_ideal_coe_eq_iff LieSubalgebra.exists_nested_lieIdeal_coe_eq_iff
end LieSubalgebra
end LieSubmodule
namespace LieSubmodule
variable {R : Type u} {L : Type v} {M : Type w}
variable [CommRing R] [LieRing L] [LieAlgebra R L] [AddCommGroup M] [Module R M]
variable [LieRingModule L M] [LieModule R L M]
variable (N N' : LieSubmodule R L M) (I J : LieIdeal R L)
section LatticeStructure
open Set
theorem coe_injective : Function.Injective ((↑) : LieSubmodule R L M → Set M) :=
SetLike.coe_injective
#align lie_submodule.coe_injective LieSubmodule.coe_injective
@[simp, norm_cast]
theorem coeSubmodule_le_coeSubmodule : (N : Submodule R M) ≤ N' ↔ N ≤ N' :=
Iff.rfl
#align lie_submodule.coe_submodule_le_coe_submodule LieSubmodule.coeSubmodule_le_coeSubmodule
instance : Bot (LieSubmodule R L M) :=
⟨0⟩
@[simp]
theorem bot_coe : ((⊥ : LieSubmodule R L M) : Set M) = {0} :=
rfl
#align lie_submodule.bot_coe LieSubmodule.bot_coe
@[simp]
theorem bot_coeSubmodule : ((⊥ : LieSubmodule R L M) : Submodule R M) = ⊥ :=
rfl
#align lie_submodule.bot_coe_submodule LieSubmodule.bot_coeSubmodule
@[simp]
theorem coeSubmodule_eq_bot_iff : (N : Submodule R M) = ⊥ ↔ N = ⊥ := by
rw [← coe_toSubmodule_eq_iff, bot_coeSubmodule]
@[simp] theorem mk_eq_bot_iff {N : Submodule R M} {h} :
(⟨N, h⟩ : LieSubmodule R L M) = ⊥ ↔ N = ⊥ := by
rw [← coe_toSubmodule_eq_iff, bot_coeSubmodule]
@[simp]
theorem mem_bot (x : M) : x ∈ (⊥ : LieSubmodule R L M) ↔ x = 0 :=
mem_singleton_iff
#align lie_submodule.mem_bot LieSubmodule.mem_bot
instance : Top (LieSubmodule R L M) :=
⟨{ (⊤ : Submodule R M) with lie_mem := fun {x m} _ ↦ mem_univ ⁅x, m⁆ }⟩
@[simp]
theorem top_coe : ((⊤ : LieSubmodule R L M) : Set M) = univ :=
rfl
#align lie_submodule.top_coe LieSubmodule.top_coe
@[simp]
theorem top_coeSubmodule : ((⊤ : LieSubmodule R L M) : Submodule R M) = ⊤ :=
rfl
#align lie_submodule.top_coe_submodule LieSubmodule.top_coeSubmodule
@[simp]
theorem coeSubmodule_eq_top_iff : (N : Submodule R M) = ⊤ ↔ N = ⊤ := by
rw [← coe_toSubmodule_eq_iff, top_coeSubmodule]
@[simp] theorem mk_eq_top_iff {N : Submodule R M} {h} :
(⟨N, h⟩ : LieSubmodule R L M) = ⊤ ↔ N = ⊤ := by
rw [← coe_toSubmodule_eq_iff, top_coeSubmodule]
@[simp]
theorem mem_top (x : M) : x ∈ (⊤ : LieSubmodule R L M) :=
mem_univ x
#align lie_submodule.mem_top LieSubmodule.mem_top
instance : Inf (LieSubmodule R L M) :=
⟨fun N N' ↦
{ (N ⊓ N' : Submodule R M) with
lie_mem := fun h ↦ mem_inter (N.lie_mem h.1) (N'.lie_mem h.2) }⟩
instance : InfSet (LieSubmodule R L M) :=
⟨fun S ↦
{ toSubmodule := sInf {(s : Submodule R M) | s ∈ S}
lie_mem := fun {x m} h ↦ by
simp only [Submodule.mem_carrier, mem_iInter, Submodule.sInf_coe, mem_setOf_eq,
forall_apply_eq_imp_iff₂, forall_exists_index, and_imp] at h ⊢
intro N hN; apply N.lie_mem (h N hN) }⟩
@[simp]
theorem inf_coe : (↑(N ⊓ N') : Set M) = ↑N ∩ ↑N' :=
rfl
#align lie_submodule.inf_coe LieSubmodule.inf_coe
@[norm_cast, simp]
theorem inf_coe_toSubmodule :
(↑(N ⊓ N') : Submodule R M) = (N : Submodule R M) ⊓ (N' : Submodule R M) :=
rfl
#align lie_submodule.inf_coe_to_submodule LieSubmodule.inf_coe_toSubmodule
@[simp]
theorem sInf_coe_toSubmodule (S : Set (LieSubmodule R L M)) :
(↑(sInf S) : Submodule R M) = sInf {(s : Submodule R M) | s ∈ S} :=
rfl
#align lie_submodule.Inf_coe_to_submodule LieSubmodule.sInf_coe_toSubmodule
theorem sInf_coe_toSubmodule' (S : Set (LieSubmodule R L M)) :
(↑(sInf S) : Submodule R M) = ⨅ N ∈ S, (N : Submodule R M) := by
rw [sInf_coe_toSubmodule, ← Set.image, sInf_image]
@[simp]
theorem iInf_coe_toSubmodule {ι} (p : ι → LieSubmodule R L M) :
(↑(⨅ i, p i) : Submodule R M) = ⨅ i, (p i : Submodule R M) := by
rw [iInf, sInf_coe_toSubmodule]; ext; simp
@[simp]
theorem sInf_coe (S : Set (LieSubmodule R L M)) : (↑(sInf S) : Set M) = ⋂ s ∈ S, (s : Set M) := by
rw [← LieSubmodule.coe_toSubmodule, sInf_coe_toSubmodule, Submodule.sInf_coe]
ext m
simp only [mem_iInter, mem_setOf_eq, forall_apply_eq_imp_iff₂, exists_imp,
and_imp, SetLike.mem_coe, mem_coeSubmodule]
#align lie_submodule.Inf_coe LieSubmodule.sInf_coe
@[simp]
theorem iInf_coe {ι} (p : ι → LieSubmodule R L M) : (↑(⨅ i, p i) : Set M) = ⋂ i, ↑(p i) := by
rw [iInf, sInf_coe]; simp only [Set.mem_range, Set.iInter_exists, Set.iInter_iInter_eq']
@[simp]
theorem mem_iInf {ι} (p : ι → LieSubmodule R L M) {x} : (x ∈ ⨅ i, p i) ↔ ∀ i, x ∈ p i := by
rw [← SetLike.mem_coe, iInf_coe, Set.mem_iInter]; rfl
instance : Sup (LieSubmodule R L M) where
sup N N' :=
{ toSubmodule := (N : Submodule R M) ⊔ (N' : Submodule R M)
lie_mem := by
rintro x m (hm : m ∈ (N : Submodule R M) ⊔ (N' : Submodule R M))
change ⁅x, m⁆ ∈ (N : Submodule R M) ⊔ (N' : Submodule R M)
rw [Submodule.mem_sup] at hm ⊢
obtain ⟨y, hy, z, hz, rfl⟩ := hm
exact ⟨⁅x, y⁆, N.lie_mem hy, ⁅x, z⁆, N'.lie_mem hz, (lie_add _ _ _).symm⟩ }
instance : SupSet (LieSubmodule R L M) where
sSup S :=
{ toSubmodule := sSup {(p : Submodule R M) | p ∈ S}
lie_mem := by
intro x m (hm : m ∈ sSup {(p : Submodule R M) | p ∈ S})
change ⁅x, m⁆ ∈ sSup {(p : Submodule R M) | p ∈ S}
obtain ⟨s, hs, hsm⟩ := Submodule.mem_sSup_iff_exists_finset.mp hm
clear hm
classical
induction' s using Finset.induction_on with q t hqt ih generalizing m
· replace hsm : m = 0 := by simpa using hsm
simp [hsm]
· rw [Finset.iSup_insert] at hsm
obtain ⟨m', hm', u, hu, rfl⟩ := Submodule.mem_sup.mp hsm
rw [lie_add]
refine add_mem ?_ (ih (Subset.trans (by simp) hs) hu)
obtain ⟨p, hp, rfl⟩ : ∃ p ∈ S, ↑p = q := hs (Finset.mem_insert_self q t)
suffices p ≤ sSup {(p : Submodule R M) | p ∈ S} by exact this (p.lie_mem hm')
exact le_sSup ⟨p, hp, rfl⟩ }
@[norm_cast, simp]
theorem sup_coe_toSubmodule :
(↑(N ⊔ N') : Submodule R M) = (N : Submodule R M) ⊔ (N' : Submodule R M) := by
rfl
#align lie_submodule.sup_coe_to_submodule LieSubmodule.sup_coe_toSubmodule
@[simp]
theorem sSup_coe_toSubmodule (S : Set (LieSubmodule R L M)) :
(↑(sSup S) : Submodule R M) = sSup {(s : Submodule R M) | s ∈ S} :=
rfl
theorem sSup_coe_toSubmodule' (S : Set (LieSubmodule R L M)) :
(↑(sSup S) : Submodule R M) = ⨆ N ∈ S, (N : Submodule R M) := by
rw [sSup_coe_toSubmodule, ← Set.image, sSup_image]
@[simp]
theorem iSup_coe_toSubmodule {ι} (p : ι → LieSubmodule R L M) :
(↑(⨆ i, p i) : Submodule R M) = ⨆ i, (p i : Submodule R M) := by
rw [iSup, sSup_coe_toSubmodule]; ext; simp [Submodule.mem_sSup, Submodule.mem_iSup]
/-- The set of Lie submodules of a Lie module form a complete lattice. -/
instance : CompleteLattice (LieSubmodule R L M) :=
{ coeSubmodule_injective.completeLattice toSubmodule sup_coe_toSubmodule inf_coe_toSubmodule
sSup_coe_toSubmodule' sInf_coe_toSubmodule' rfl rfl with
toPartialOrder := SetLike.instPartialOrder }
theorem mem_iSup_of_mem {ι} {b : M} {N : ι → LieSubmodule R L M} (i : ι) (h : b ∈ N i) :
b ∈ ⨆ i, N i :=
(le_iSup N i) h
lemma iSup_induction {ι} (N : ι → LieSubmodule R L M) {C : M → Prop} {x : M}
(hx : x ∈ ⨆ i, N i) (hN : ∀ i, ∀ y ∈ N i, C y) (h0 : C 0)
(hadd : ∀ y z, C y → C z → C (y + z)) : C x := by
rw [← LieSubmodule.mem_coeSubmodule, LieSubmodule.iSup_coe_toSubmodule] at hx
exact Submodule.iSup_induction (C := C) (fun i ↦ (N i : Submodule R M)) hx hN h0 hadd
@[elab_as_elim]
theorem iSup_induction' {ι} (N : ι → LieSubmodule R L M) {C : (x : M) → (x ∈ ⨆ i, N i) → Prop}
(hN : ∀ (i) (x) (hx : x ∈ N i), C x (mem_iSup_of_mem i hx)) (h0 : C 0 (zero_mem _))
(hadd : ∀ x y hx hy, C x hx → C y hy → C (x + y) (add_mem ‹_› ‹_›)) {x : M}
(hx : x ∈ ⨆ i, N i) : C x hx := by
refine Exists.elim ?_ fun (hx : x ∈ ⨆ i, N i) (hc : C x hx) => hc
refine iSup_induction N (C := fun x : M ↦ ∃ (hx : x ∈ ⨆ i, N i), C x hx) hx
(fun i x hx => ?_) ?_ fun x y => ?_
· exact ⟨_, hN _ _ hx⟩
· exact ⟨_, h0⟩
· rintro ⟨_, Cx⟩ ⟨_, Cy⟩
exact ⟨_, hadd _ _ _ _ Cx Cy⟩
theorem disjoint_iff_coe_toSubmodule :
Disjoint N N' ↔ Disjoint (N : Submodule R M) (N' : Submodule R M) := by
rw [disjoint_iff, disjoint_iff, ← coe_toSubmodule_eq_iff, inf_coe_toSubmodule, bot_coeSubmodule,
← disjoint_iff]
theorem codisjoint_iff_coe_toSubmodule :
Codisjoint N N' ↔ Codisjoint (N : Submodule R M) (N' : Submodule R M) := by
rw [codisjoint_iff, codisjoint_iff, ← coe_toSubmodule_eq_iff, sup_coe_toSubmodule,
top_coeSubmodule, ← codisjoint_iff]
theorem isCompl_iff_coe_toSubmodule :
IsCompl N N' ↔ IsCompl (N : Submodule R M) (N' : Submodule R M) := by
simp only [isCompl_iff, disjoint_iff_coe_toSubmodule, codisjoint_iff_coe_toSubmodule]
theorem independent_iff_coe_toSubmodule {ι : Type*} {N : ι → LieSubmodule R L M} :
CompleteLattice.Independent N ↔ CompleteLattice.Independent fun i ↦ (N i : Submodule R M) := by
simp [CompleteLattice.independent_def, disjoint_iff_coe_toSubmodule]
theorem iSup_eq_top_iff_coe_toSubmodule {ι : Sort*} {N : ι → LieSubmodule R L M} :
⨆ i, N i = ⊤ ↔ ⨆ i, (N i : Submodule R M) = ⊤ := by
rw [← iSup_coe_toSubmodule, ← top_coeSubmodule (L := L), coe_toSubmodule_eq_iff]
instance : Add (LieSubmodule R L M) where add := Sup.sup
instance : Zero (LieSubmodule R L M) where zero := ⊥
instance : AddCommMonoid (LieSubmodule R L M) where
add_assoc := sup_assoc
zero_add := bot_sup_eq
add_zero := sup_bot_eq
add_comm := sup_comm
nsmul := nsmulRec
@[simp]
theorem add_eq_sup : N + N' = N ⊔ N' :=
rfl
#align lie_submodule.add_eq_sup LieSubmodule.add_eq_sup
@[simp]
theorem mem_inf (x : M) : x ∈ N ⊓ N' ↔ x ∈ N ∧ x ∈ N' := by
rw [← mem_coeSubmodule, ← mem_coeSubmodule, ← mem_coeSubmodule, inf_coe_toSubmodule,
Submodule.mem_inf]
#align lie_submodule.mem_inf LieSubmodule.mem_inf
theorem mem_sup (x : M) : x ∈ N ⊔ N' ↔ ∃ y ∈ N, ∃ z ∈ N', y + z = x := by
rw [← mem_coeSubmodule, sup_coe_toSubmodule, Submodule.mem_sup]; exact Iff.rfl
#align lie_submodule.mem_sup LieSubmodule.mem_sup
nonrec theorem eq_bot_iff : N = ⊥ ↔ ∀ m : M, m ∈ N → m = 0 := by rw [eq_bot_iff]; exact Iff.rfl
#align lie_submodule.eq_bot_iff LieSubmodule.eq_bot_iff
instance subsingleton_of_bot : Subsingleton (LieSubmodule R L ↑(⊥ : LieSubmodule R L M)) := by
apply subsingleton_of_bot_eq_top
ext ⟨x, hx⟩; change x ∈ ⊥ at hx; rw [Submodule.mem_bot] at hx; subst hx
simp only [true_iff_iff, eq_self_iff_true, Submodule.mk_eq_zero, LieSubmodule.mem_bot, mem_top]
#align lie_submodule.subsingleton_of_bot LieSubmodule.subsingleton_of_bot
instance : IsModularLattice (LieSubmodule R L M) where
sup_inf_le_assoc_of_le _ _ := by
simp only [← coeSubmodule_le_coeSubmodule, sup_coe_toSubmodule, inf_coe_toSubmodule]
exact IsModularLattice.sup_inf_le_assoc_of_le _
variable (R L M)
/-- The natural functor that forgets the action of `L` as an order embedding. -/
@[simps] def toSubmodule_orderEmbedding : LieSubmodule R L M ↪o Submodule R M :=
{ toFun := (↑)
inj' := coeSubmodule_injective
map_rel_iff' := Iff.rfl }
theorem wellFounded_of_noetherian [IsNoetherian R M] :
WellFounded ((· > ·) : LieSubmodule R L M → LieSubmodule R L M → Prop) :=
RelHomClass.wellFounded (toSubmodule_orderEmbedding R L M).dual.ltEmbedding <|
isNoetherian_iff_wellFounded.mp inferInstance
#align lie_submodule.well_founded_of_noetherian LieSubmodule.wellFounded_of_noetherian
theorem wellFounded_of_isArtinian [IsArtinian R M] :
WellFounded ((· < ·) : LieSubmodule R L M → LieSubmodule R L M → Prop) :=
RelHomClass.wellFounded (toSubmodule_orderEmbedding R L M).ltEmbedding <|
IsArtinian.wellFounded_submodule_lt R M
instance [IsArtinian R M] : IsAtomic (LieSubmodule R L M) :=
isAtomic_of_orderBot_wellFounded_lt <| wellFounded_of_isArtinian R L M
@[simp]
theorem subsingleton_iff : Subsingleton (LieSubmodule R L M) ↔ Subsingleton M :=
have h : Subsingleton (LieSubmodule R L M) ↔ Subsingleton (Submodule R M) := by
rw [← subsingleton_iff_bot_eq_top, ← subsingleton_iff_bot_eq_top, ← coe_toSubmodule_eq_iff,
top_coeSubmodule, bot_coeSubmodule]
h.trans <| Submodule.subsingleton_iff R
#align lie_submodule.subsingleton_iff LieSubmodule.subsingleton_iff
@[simp]
theorem nontrivial_iff : Nontrivial (LieSubmodule R L M) ↔ Nontrivial M :=
not_iff_not.mp
((not_nontrivial_iff_subsingleton.trans <| subsingleton_iff R L M).trans
not_nontrivial_iff_subsingleton.symm)
#align lie_submodule.nontrivial_iff LieSubmodule.nontrivial_iff
instance [Nontrivial M] : Nontrivial (LieSubmodule R L M) :=
(nontrivial_iff R L M).mpr ‹_›
theorem nontrivial_iff_ne_bot {N : LieSubmodule R L M} : Nontrivial N ↔ N ≠ ⊥ := by
constructor <;> contrapose!
· rintro rfl
⟨⟨m₁, h₁ : m₁ ∈ (⊥ : LieSubmodule R L M)⟩, ⟨m₂, h₂ : m₂ ∈ (⊥ : LieSubmodule R L M)⟩, h₁₂⟩
simp [(LieSubmodule.mem_bot _).mp h₁, (LieSubmodule.mem_bot _).mp h₂] at h₁₂
· rw [not_nontrivial_iff_subsingleton, LieSubmodule.eq_bot_iff]
rintro ⟨h⟩ m hm
simpa using h ⟨m, hm⟩ ⟨_, N.zero_mem⟩
#align lie_submodule.nontrivial_iff_ne_bot LieSubmodule.nontrivial_iff_ne_bot
variable {R L M}
section InclusionMaps
/-- The inclusion of a Lie submodule into its ambient space is a morphism of Lie modules. -/
def incl : N →ₗ⁅R,L⁆ M :=
{ Submodule.subtype (N : Submodule R M) with map_lie' := fun {_ _} ↦ rfl }
#align lie_submodule.incl LieSubmodule.incl
@[simp]
theorem incl_coe : (N.incl : N →ₗ[R] M) = (N : Submodule R M).subtype :=
rfl
#align lie_submodule.incl_coe LieSubmodule.incl_coe
@[simp]
theorem incl_apply (m : N) : N.incl m = m :=
rfl
#align lie_submodule.incl_apply LieSubmodule.incl_apply
theorem incl_eq_val : (N.incl : N → M) = Subtype.val :=
rfl
#align lie_submodule.incl_eq_val LieSubmodule.incl_eq_val
theorem injective_incl : Function.Injective N.incl := Subtype.coe_injective
variable {N N'} (h : N ≤ N')
/-- Given two nested Lie submodules `N ⊆ N'`,
the inclusion `N ↪ N'` is a morphism of Lie modules. -/
def inclusion : N →ₗ⁅R,L⁆ N' where
__ := Submodule.inclusion (show N.toSubmodule ≤ N'.toSubmodule from h)
map_lie' := rfl
#align lie_submodule.hom_of_le LieSubmodule.inclusion
@[simp]
theorem coe_inclusion (m : N) : (inclusion h m : M) = m :=
rfl
#align lie_submodule.coe_hom_of_le LieSubmodule.coe_inclusion
theorem inclusion_apply (m : N) : inclusion h m = ⟨m.1, h m.2⟩ :=
rfl
#align lie_submodule.hom_of_le_apply LieSubmodule.inclusion_apply
theorem inclusion_injective : Function.Injective (inclusion h) := fun x y ↦ by
simp only [inclusion_apply, imp_self, Subtype.mk_eq_mk, SetLike.coe_eq_coe]
#align lie_submodule.hom_of_le_injective LieSubmodule.inclusion_injective
end InclusionMaps
section LieSpan
variable (R L) (s : Set M)
/-- The `lieSpan` of a set `s ⊆ M` is the smallest Lie submodule of `M` that contains `s`. -/
def lieSpan : LieSubmodule R L M :=
sInf { N | s ⊆ N }
#align lie_submodule.lie_span LieSubmodule.lieSpan
variable {R L s}
theorem mem_lieSpan {x : M} : x ∈ lieSpan R L s ↔ ∀ N : LieSubmodule R L M, s ⊆ N → x ∈ N := by
change x ∈ (lieSpan R L s : Set M) ↔ _; erw [sInf_coe]; exact mem_iInter₂
#align lie_submodule.mem_lie_span LieSubmodule.mem_lieSpan
theorem subset_lieSpan : s ⊆ lieSpan R L s := by
intro m hm
erw [mem_lieSpan]
intro N hN
exact hN hm
#align lie_submodule.subset_lie_span LieSubmodule.subset_lieSpan
theorem submodule_span_le_lieSpan : Submodule.span R s ≤ lieSpan R L s := by
rw [Submodule.span_le]
apply subset_lieSpan
#align lie_submodule.submodule_span_le_lie_span LieSubmodule.submodule_span_le_lieSpan
@[simp]
theorem lieSpan_le {N} : lieSpan R L s ≤ N ↔ s ⊆ N := by
constructor
· exact Subset.trans subset_lieSpan
· intro hs m hm; rw [mem_lieSpan] at hm; exact hm _ hs
#align lie_submodule.lie_span_le LieSubmodule.lieSpan_le
theorem lieSpan_mono {t : Set M} (h : s ⊆ t) : lieSpan R L s ≤ lieSpan R L t := by
rw [lieSpan_le]
exact Subset.trans h subset_lieSpan
#align lie_submodule.lie_span_mono LieSubmodule.lieSpan_mono
theorem lieSpan_eq : lieSpan R L (N : Set M) = N :=
le_antisymm (lieSpan_le.mpr rfl.subset) subset_lieSpan
#align lie_submodule.lie_span_eq LieSubmodule.lieSpan_eq
theorem coe_lieSpan_submodule_eq_iff {p : Submodule R M} :
(lieSpan R L (p : Set M) : Submodule R M) = p ↔ ∃ N : LieSubmodule R L M, ↑N = p := by
rw [p.exists_lieSubmodule_coe_eq_iff L]; constructor <;> intro h
· intro x m hm; rw [← h, mem_coeSubmodule]; exact lie_mem _ (subset_lieSpan hm)
· rw [← coe_toSubmodule_mk p @h, coe_toSubmodule, coe_toSubmodule_eq_iff, lieSpan_eq]
#align lie_submodule.coe_lie_span_submodule_eq_iff LieSubmodule.coe_lieSpan_submodule_eq_iff
variable (R L M)
/-- `lieSpan` forms a Galois insertion with the coercion from `LieSubmodule` to `Set`. -/
protected def gi : GaloisInsertion (lieSpan R L : Set M → LieSubmodule R L M) (↑) where
choice s _ := lieSpan R L s
gc _ _ := lieSpan_le
le_l_u _ := subset_lieSpan
choice_eq _ _ := rfl
#align lie_submodule.gi LieSubmodule.gi
@[simp]
theorem span_empty : lieSpan R L (∅ : Set M) = ⊥ :=
(LieSubmodule.gi R L M).gc.l_bot
#align lie_submodule.span_empty LieSubmodule.span_empty
@[simp]
theorem span_univ : lieSpan R L (Set.univ : Set M) = ⊤ :=
eq_top_iff.2 <| SetLike.le_def.2 <| subset_lieSpan
#align lie_submodule.span_univ LieSubmodule.span_univ
theorem lieSpan_eq_bot_iff : lieSpan R L s = ⊥ ↔ ∀ m ∈ s, m = (0 : M) := by
rw [_root_.eq_bot_iff, lieSpan_le, bot_coe, subset_singleton_iff]
#align lie_submodule.lie_span_eq_bot_iff LieSubmodule.lieSpan_eq_bot_iff
variable {M}
theorem span_union (s t : Set M) : lieSpan R L (s ∪ t) = lieSpan R L s ⊔ lieSpan R L t :=
(LieSubmodule.gi R L M).gc.l_sup
#align lie_submodule.span_union LieSubmodule.span_union
theorem span_iUnion {ι} (s : ι → Set M) : lieSpan R L (⋃ i, s i) = ⨆ i, lieSpan R L (s i) :=
(LieSubmodule.gi R L M).gc.l_iSup
#align lie_submodule.span_Union LieSubmodule.span_iUnion
lemma isCompactElement_lieSpan_singleton (m : M) :
CompleteLattice.IsCompactElement (lieSpan R L {m}) := by
rw [CompleteLattice.isCompactElement_iff_le_of_directed_sSup_le]
intro s hne hdir hsup
replace hsup : m ∈ (↑(sSup s) : Set M) := (SetLike.le_def.mp hsup) (subset_lieSpan rfl)
suffices (↑(sSup s) : Set M) = ⋃ N ∈ s, ↑N by
obtain ⟨N : LieSubmodule R L M, hN : N ∈ s, hN' : m ∈ N⟩ := by
simp_rw [this, Set.mem_iUnion, SetLike.mem_coe, exists_prop] at hsup; assumption
exact ⟨N, hN, by simpa⟩
replace hne : Nonempty s := Set.nonempty_coe_sort.mpr hne
have := Submodule.coe_iSup_of_directed _ hdir.directed_val
simp_rw [← iSup_coe_toSubmodule, Set.iUnion_coe_set, coe_toSubmodule] at this
rw [← this, SetLike.coe_set_eq, sSup_eq_iSup, iSup_subtype]
@[simp]
lemma sSup_image_lieSpan_singleton : sSup ((fun x ↦ lieSpan R L {x}) '' N) = N := by
refine le_antisymm (sSup_le <| by simp) ?_
simp_rw [← coeSubmodule_le_coeSubmodule, sSup_coe_toSubmodule, Set.mem_image, SetLike.mem_coe]
refine fun m hm ↦ Submodule.mem_sSup.mpr fun N' hN' ↦ ?_
replace hN' : ∀ m ∈ N, lieSpan R L {m} ≤ N' := by simpa using hN'
exact hN' _ hm (subset_lieSpan rfl)
instance instIsCompactlyGenerated : IsCompactlyGenerated (LieSubmodule R L M) :=
⟨fun N ↦ ⟨(fun x ↦ lieSpan R L {x}) '' N, fun _ ⟨m, _, hm⟩ ↦
hm ▸ isCompactElement_lieSpan_singleton R L m, N.sSup_image_lieSpan_singleton⟩⟩
end LieSpan
end LatticeStructure
end LieSubmodule
section LieSubmoduleMapAndComap
variable {R : Type u} {L : Type v} {L' : Type w₂} {M : Type w} {M' : Type w₁}
variable [CommRing R] [LieRing L] [LieAlgebra R L] [LieRing L'] [LieAlgebra R L']
variable [AddCommGroup M] [Module R M] [LieRingModule L M] [LieModule R L M]
variable [AddCommGroup M'] [Module R M'] [LieRingModule L M'] [LieModule R L M']
namespace LieSubmodule
variable (f : M →ₗ⁅R,L⁆ M') (N N₂ : LieSubmodule R L M) (N' : LieSubmodule R L M')
/-- A morphism of Lie modules `f : M → M'` pushes forward Lie submodules of `M` to Lie submodules
of `M'`. -/
def map : LieSubmodule R L M' :=
{ (N : Submodule R M).map (f : M →ₗ[R] M') with
lie_mem := fun {x m'} h ↦ by
rcases h with ⟨m, hm, hfm⟩; use ⁅x, m⁆; constructor
· apply N.lie_mem hm
· norm_cast at hfm; simp [hfm] }
#align lie_submodule.map LieSubmodule.map
@[simp] theorem coe_map : (N.map f : Set M') = f '' N := rfl
@[simp]
theorem coeSubmodule_map : (N.map f : Submodule R M') = (N : Submodule R M).map (f : M →ₗ[R] M') :=
rfl
#align lie_submodule.coe_submodule_map LieSubmodule.coeSubmodule_map
/-- A morphism of Lie modules `f : M → M'` pulls back Lie submodules of `M'` to Lie submodules of
`M`. -/
def comap : LieSubmodule R L M :=
{ (N' : Submodule R M').comap (f : M →ₗ[R] M') with
lie_mem := fun {x m} h ↦ by
suffices ⁅x, f m⁆ ∈ N' by simp [this]
apply N'.lie_mem h }
#align lie_submodule.comap LieSubmodule.comap
@[simp]
theorem coeSubmodule_comap :
(N'.comap f : Submodule R M) = (N' : Submodule R M').comap (f : M →ₗ[R] M') :=
rfl
#align lie_submodule.coe_submodule_comap LieSubmodule.coeSubmodule_comap
variable {f N N₂ N'}
theorem map_le_iff_le_comap : map f N ≤ N' ↔ N ≤ comap f N' :=
Set.image_subset_iff
#align lie_submodule.map_le_iff_le_comap LieSubmodule.map_le_iff_le_comap
variable (f)
theorem gc_map_comap : GaloisConnection (map f) (comap f) := fun _ _ ↦ map_le_iff_le_comap
#align lie_submodule.gc_map_comap LieSubmodule.gc_map_comap
variable {f}
theorem map_inf_le : (N ⊓ N₂).map f ≤ N.map f ⊓ N₂.map f :=
Set.image_inter_subset f N N₂
theorem map_inf (hf : Function.Injective f) :
(N ⊓ N₂).map f = N.map f ⊓ N₂.map f :=
SetLike.coe_injective <| Set.image_inter hf
@[simp]
theorem map_sup : (N ⊔ N₂).map f = N.map f ⊔ N₂.map f :=
(gc_map_comap f).l_sup
#align lie_submodule.map_sup LieSubmodule.map_sup
@[simp]
theorem comap_inf {N₂' : LieSubmodule R L M'} :
(N' ⊓ N₂').comap f = N'.comap f ⊓ N₂'.comap f :=
rfl
@[simp]
theorem map_iSup {ι : Sort*} (N : ι → LieSubmodule R L M) :
(⨆ i, N i).map f = ⨆ i, (N i).map f :=
(gc_map_comap f : GaloisConnection (map f) (comap f)).l_iSup
@[simp]
theorem mem_map (m' : M') : m' ∈ N.map f ↔ ∃ m, m ∈ N ∧ f m = m' :=
Submodule.mem_map
#align lie_submodule.mem_map LieSubmodule.mem_map
theorem mem_map_of_mem {m : M} (h : m ∈ N) : f m ∈ N.map f :=
Set.mem_image_of_mem _ h
@[simp]
theorem mem_comap {m : M} : m ∈ comap f N' ↔ f m ∈ N' :=
Iff.rfl
#align lie_submodule.mem_comap LieSubmodule.mem_comap
theorem comap_incl_eq_top : N₂.comap N.incl = ⊤ ↔ N ≤ N₂ := by
rw [← LieSubmodule.coe_toSubmodule_eq_iff, LieSubmodule.coeSubmodule_comap, LieSubmodule.incl_coe,
LieSubmodule.top_coeSubmodule, Submodule.comap_subtype_eq_top, coeSubmodule_le_coeSubmodule]
#align lie_submodule.comap_incl_eq_top LieSubmodule.comap_incl_eq_top
theorem comap_incl_eq_bot : N₂.comap N.incl = ⊥ ↔ N ⊓ N₂ = ⊥ := by
simp only [← LieSubmodule.coe_toSubmodule_eq_iff, LieSubmodule.coeSubmodule_comap,
LieSubmodule.incl_coe, LieSubmodule.bot_coeSubmodule, ← Submodule.disjoint_iff_comap_eq_bot,
disjoint_iff, inf_coe_toSubmodule]
#align lie_submodule.comap_incl_eq_bot LieSubmodule.comap_incl_eq_bot
@[mono]
theorem map_mono (h : N ≤ N₂) : N.map f ≤ N₂.map f :=
Set.image_subset _ h
theorem map_comp
{M'' : Type*} [AddCommGroup M''] [Module R M''] [LieRingModule L M''] {g : M' →ₗ⁅R,L⁆ M''} :
N.map (g.comp f) = (N.map f).map g :=
SetLike.coe_injective <| by
simp only [← Set.image_comp, coe_map, LinearMap.coe_comp, LieModuleHom.coe_comp]
@[simp]
theorem map_id : N.map LieModuleHom.id = N := by ext; simp
@[simp] theorem map_bot :
(⊥ : LieSubmodule R L M).map f = ⊥ := by
ext m; simp [eq_comm]
lemma map_le_map_iff (hf : Function.Injective f) :
N.map f ≤ N₂.map f ↔ N ≤ N₂ :=
Set.image_subset_image_iff hf
lemma map_injective_of_injective (hf : Function.Injective f) :
Function.Injective (map f) := fun {N N'} h ↦
SetLike.coe_injective <| hf.image_injective <| by simp only [← coe_map, h]
/-- An injective morphism of Lie modules embeds the lattice of submodules of the domain into that
of the target. -/
@[simps] def mapOrderEmbedding {f : M →ₗ⁅R,L⁆ M'} (hf : Function.Injective f) :
LieSubmodule R L M ↪o LieSubmodule R L M' where
toFun := LieSubmodule.map f
inj' := map_injective_of_injective hf
map_rel_iff' := Set.image_subset_image_iff hf
variable (N) in
/-- For an injective morphism of Lie modules, any Lie submodule is equivalent to its image. -/
noncomputable def equivMapOfInjective (hf : Function.Injective f) :
N ≃ₗ⁅R,L⁆ N.map f :=
{ Submodule.equivMapOfInjective (f : M →ₗ[R] M') hf N with
-- Note: #8386 had to specify `invFun` explicitly this way, otherwise we'd get a type mismatch
invFun := by exact DFunLike.coe (Submodule.equivMapOfInjective (f : M →ₗ[R] M') hf N).symm
map_lie' := by rintro x ⟨m, hm : m ∈ N⟩; ext; exact f.map_lie x m }
/-- An equivalence of Lie modules yields an order-preserving equivalence of their lattices of Lie
Submodules. -/
@[simps] def orderIsoMapComap (e : M ≃ₗ⁅R,L⁆ M') :
LieSubmodule R L M ≃o LieSubmodule R L M' where
toFun := map e
invFun := comap e
left_inv := fun N ↦ by ext; simp
right_inv := fun N ↦ by ext; simp [e.apply_eq_iff_eq_symm_apply]
map_rel_iff' := fun {N N'} ↦ Set.image_subset_image_iff e.injective
end LieSubmodule
namespace LieIdeal
variable (f : L →ₗ⁅R⁆ L') (I I₂ : LieIdeal R L) (J : LieIdeal R L')
@[simp]
theorem top_coe_lieSubalgebra : ((⊤ : LieIdeal R L) : LieSubalgebra R L) = ⊤ :=
rfl
#align lie_ideal.top_coe_lie_subalgebra LieIdeal.top_coe_lieSubalgebra
/-- A morphism of Lie algebras `f : L → L'` pushes forward Lie ideals of `L` to Lie ideals of `L'`.
Note that unlike `LieSubmodule.map`, we must take the `lieSpan` of the image. Mathematically
this is because although `f` makes `L'` into a Lie module over `L`, in general the `L` submodules of
`L'` are not the same as the ideals of `L'`. -/
def map : LieIdeal R L' :=
LieSubmodule.lieSpan R L' <| (I : Submodule R L).map (f : L →ₗ[R] L')
#align lie_ideal.map LieIdeal.map
/-- A morphism of Lie algebras `f : L → L'` pulls back Lie ideals of `L'` to Lie ideals of `L`.
Note that `f` makes `L'` into a Lie module over `L` (turning `f` into a morphism of Lie modules)
and so this is a special case of `LieSubmodule.comap` but we do not exploit this fact. -/
def comap : LieIdeal R L :=
{ (J : Submodule R L').comap (f : L →ₗ[R] L') with
lie_mem := fun {x y} h ↦ by
suffices ⁅f x, f y⁆ ∈ J by
simp only [AddSubsemigroup.mem_carrier, AddSubmonoid.mem_toSubsemigroup,
Submodule.mem_toAddSubmonoid, Submodule.mem_comap, LieHom.coe_toLinearMap, LieHom.map_lie,
LieSubalgebra.mem_coe_submodule]
exact this
apply J.lie_mem h }
#align lie_ideal.comap LieIdeal.comap
@[simp]
theorem map_coeSubmodule (h : ↑(map f I) = f '' I) :
LieSubmodule.toSubmodule (map f I) = (LieSubmodule.toSubmodule I).map (f : L →ₗ[R] L') := by
rw [SetLike.ext'_iff, LieSubmodule.coe_toSubmodule, h, Submodule.map_coe]; rfl
#align lie_ideal.map_coe_submodule LieIdeal.map_coeSubmodule
@[simp]
theorem comap_coeSubmodule :
(LieSubmodule.toSubmodule (comap f J)) = (LieSubmodule.toSubmodule J).comap (f : L →ₗ[R] L') :=
rfl
#align lie_ideal.comap_coe_submodule LieIdeal.comap_coeSubmodule
theorem map_le : map f I ≤ J ↔ f '' I ⊆ J :=
LieSubmodule.lieSpan_le
#align lie_ideal.map_le LieIdeal.map_le
variable {f I I₂ J}
theorem mem_map {x : L} (hx : x ∈ I) : f x ∈ map f I := by
apply LieSubmodule.subset_lieSpan
use x
exact ⟨hx, rfl⟩
#align lie_ideal.mem_map LieIdeal.mem_map
@[simp]
theorem mem_comap {x : L} : x ∈ comap f J ↔ f x ∈ J :=
Iff.rfl
#align lie_ideal.mem_comap LieIdeal.mem_comap
theorem map_le_iff_le_comap : map f I ≤ J ↔ I ≤ comap f J := by
rw [map_le]
exact Set.image_subset_iff
#align lie_ideal.map_le_iff_le_comap LieIdeal.map_le_iff_le_comap
variable (f)
theorem gc_map_comap : GaloisConnection (map f) (comap f) := fun _ _ ↦ map_le_iff_le_comap
#align lie_ideal.gc_map_comap LieIdeal.gc_map_comap
variable {f}
@[simp]
theorem map_sup : (I ⊔ I₂).map f = I.map f ⊔ I₂.map f :=
(gc_map_comap f).l_sup
#align lie_ideal.map_sup LieIdeal.map_sup
theorem map_comap_le : map f (comap f J) ≤ J := by rw [map_le_iff_le_comap]
#align lie_ideal.map_comap_le LieIdeal.map_comap_le
/-- See also `LieIdeal.map_comap_eq`. -/
theorem comap_map_le : I ≤ comap f (map f I) := by rw [← map_le_iff_le_comap]
#align lie_ideal.comap_map_le LieIdeal.comap_map_le
@[mono]
theorem map_mono : Monotone (map f) := fun I₁ I₂ h ↦ by
rw [SetLike.le_def] at h
apply LieSubmodule.lieSpan_mono (Set.image_subset (⇑f) h)
#align lie_ideal.map_mono LieIdeal.map_mono
@[mono]
theorem comap_mono : Monotone (comap f) := fun J₁ J₂ h ↦ by
rw [← SetLike.coe_subset_coe] at h ⊢
dsimp only [SetLike.coe]
exact Set.preimage_mono h
#align lie_ideal.comap_mono LieIdeal.comap_mono
theorem map_of_image (h : f '' I = J) : I.map f = J := by
apply le_antisymm
· erw [LieSubmodule.lieSpan_le, Submodule.map_coe, h]
· rw [← SetLike.coe_subset_coe, ← h]; exact LieSubmodule.subset_lieSpan
#align lie_ideal.map_of_image LieIdeal.map_of_image
/-- Note that this is not a special case of `LieSubmodule.subsingleton_of_bot`. Indeed, given
`I : LieIdeal R L`, in general the two lattices `LieIdeal R I` and `LieSubmodule R L I` are
different (though the latter does naturally inject into the former).
In other words, in general, ideals of `I`, regarded as a Lie algebra in its own right, are not the
same as ideals of `L` contained in `I`. -/
instance subsingleton_of_bot : Subsingleton (LieIdeal R (⊥ : LieIdeal R L)) := by
apply subsingleton_of_bot_eq_top
ext ⟨x, hx⟩
rw [LieSubmodule.bot_coeSubmodule, Submodule.mem_bot] at hx
subst hx
simp only [Submodule.mk_eq_zero, LieSubmodule.mem_bot, LieSubmodule.mem_top]
#align lie_ideal.subsingleton_of_bot LieIdeal.subsingleton_of_bot
end LieIdeal
namespace LieHom
variable (f : L →ₗ⁅R⁆ L') (I : LieIdeal R L) (J : LieIdeal R L')
/-- The kernel of a morphism of Lie algebras, as an ideal in the domain. -/
def ker : LieIdeal R L :=
LieIdeal.comap f ⊥
#align lie_hom.ker LieHom.ker
/-- The range of a morphism of Lie algebras as an ideal in the codomain. -/
def idealRange : LieIdeal R L' :=
LieSubmodule.lieSpan R L' f.range
#align lie_hom.ideal_range LieHom.idealRange
theorem idealRange_eq_lieSpan_range : f.idealRange = LieSubmodule.lieSpan R L' f.range :=
rfl
#align lie_hom.ideal_range_eq_lie_span_range LieHom.idealRange_eq_lieSpan_range
theorem idealRange_eq_map : f.idealRange = LieIdeal.map f ⊤ := by
ext
simp only [idealRange, range_eq_map]
rfl
#align lie_hom.ideal_range_eq_map LieHom.idealRange_eq_map
/-- The condition that the range of a morphism of Lie algebras is an ideal. -/
def IsIdealMorphism : Prop :=
(f.idealRange : LieSubalgebra R L') = f.range
#align lie_hom.is_ideal_morphism LieHom.IsIdealMorphism
@[simp]
theorem isIdealMorphism_def : f.IsIdealMorphism ↔ (f.idealRange : LieSubalgebra R L') = f.range :=
Iff.rfl
#align lie_hom.is_ideal_morphism_def LieHom.isIdealMorphism_def
variable {f} in
theorem IsIdealMorphism.eq (hf : f.IsIdealMorphism) : f.idealRange = f.range := hf
theorem isIdealMorphism_iff : f.IsIdealMorphism ↔ ∀ (x : L') (y : L), ∃ z : L, ⁅x, f y⁆ = f z := by
simp only [isIdealMorphism_def, idealRange_eq_lieSpan_range, ←
LieSubalgebra.coe_to_submodule_eq_iff, ← f.range.coe_to_submodule,
LieIdeal.coe_to_lieSubalgebra_to_submodule, LieSubmodule.coe_lieSpan_submodule_eq_iff,
LieSubalgebra.mem_coe_submodule, mem_range, exists_imp,
Submodule.exists_lieSubmodule_coe_eq_iff]
constructor
· intro h x y; obtain ⟨z, hz⟩ := h x (f y) y rfl; use z; exact hz.symm
· intro h x y z hz; obtain ⟨w, hw⟩ := h x z; use w; rw [← hw, hz]
#align lie_hom.is_ideal_morphism_iff LieHom.isIdealMorphism_iff
theorem range_subset_idealRange : (f.range : Set L') ⊆ f.idealRange :=
LieSubmodule.subset_lieSpan
#align lie_hom.range_subset_ideal_range LieHom.range_subset_idealRange
theorem map_le_idealRange : I.map f ≤ f.idealRange := by
rw [f.idealRange_eq_map]
exact LieIdeal.map_mono le_top
#align lie_hom.map_le_ideal_range LieHom.map_le_idealRange
theorem ker_le_comap : f.ker ≤ J.comap f :=
LieIdeal.comap_mono bot_le
#align lie_hom.ker_le_comap LieHom.ker_le_comap
@[simp]
theorem ker_coeSubmodule : LieSubmodule.toSubmodule (ker f) = LinearMap.ker (f : L →ₗ[R] L') :=
rfl
#align lie_hom.ker_coe_submodule LieHom.ker_coeSubmodule
@[simp]
theorem mem_ker {x : L} : x ∈ ker f ↔ f x = 0 :=
show x ∈ LieSubmodule.toSubmodule (f.ker) ↔ _ by
simp only [ker_coeSubmodule, LinearMap.mem_ker, coe_toLinearMap]
#align lie_hom.mem_ker LieHom.mem_ker
theorem mem_idealRange (x : L) : f x ∈ idealRange f := by
rw [idealRange_eq_map]
exact LieIdeal.mem_map (LieSubmodule.mem_top x)
#align lie_hom.mem_ideal_range LieHom.mem_idealRange
@[simp]
| Mathlib/Algebra/Lie/Submodule.lean | 1,179 | 1,182 | theorem mem_idealRange_iff (h : IsIdealMorphism f) {y : L'} :
y ∈ idealRange f ↔ ∃ x : L, f x = y := by |
rw [f.isIdealMorphism_def] at h
rw [← LieSubmodule.mem_coe, ← LieIdeal.coe_toSubalgebra, h, f.range_coe, Set.mem_range]
|
/-
Copyright (c) 2023 David Loeffler. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: David Loeffler
-/
import Mathlib.Analysis.SpecialFunctions.JapaneseBracket
import Mathlib.Analysis.SpecialFunctions.Integrals
import Mathlib.MeasureTheory.Group.Integral
import Mathlib.MeasureTheory.Integral.IntegralEqImproper
import Mathlib.MeasureTheory.Measure.Lebesgue.Integral
#align_import analysis.special_functions.improper_integrals from "leanprover-community/mathlib"@"fd5edc43dc4f10b85abfe544b88f82cf13c5f844"
/-!
# Evaluation of specific improper integrals
This file contains some integrability results, and evaluations of integrals, over `ℝ` or over
half-infinite intervals in `ℝ`.
## See also
- `Mathlib.Analysis.SpecialFunctions.Integrals` -- integrals over finite intervals
- `Mathlib.Analysis.SpecialFunctions.Gaussian` -- integral of `exp (-x ^ 2)`
- `Mathlib.Analysis.SpecialFunctions.JapaneseBracket`-- integrability of `(1+‖x‖)^(-r)`.
-/
open Real Set Filter MeasureTheory intervalIntegral
open scoped Topology
theorem integrableOn_exp_Iic (c : ℝ) : IntegrableOn exp (Iic c) := by
refine
integrableOn_Iic_of_intervalIntegral_norm_bounded (exp c) c
(fun y => intervalIntegrable_exp.1) tendsto_id
(eventually_of_mem (Iic_mem_atBot 0) fun y _ => ?_)
simp_rw [norm_of_nonneg (exp_pos _).le, integral_exp, sub_le_self_iff]
exact (exp_pos _).le
#align integrable_on_exp_Iic integrableOn_exp_Iic
theorem integral_exp_Iic (c : ℝ) : ∫ x : ℝ in Iic c, exp x = exp c := by
refine
tendsto_nhds_unique
(intervalIntegral_tendsto_integral_Iic _ (integrableOn_exp_Iic _) tendsto_id) ?_
simp_rw [integral_exp, show 𝓝 (exp c) = 𝓝 (exp c - 0) by rw [sub_zero]]
exact tendsto_exp_atBot.const_sub _
#align integral_exp_Iic integral_exp_Iic
theorem integral_exp_Iic_zero : ∫ x : ℝ in Iic 0, exp x = 1 :=
exp_zero ▸ integral_exp_Iic 0
#align integral_exp_Iic_zero integral_exp_Iic_zero
| Mathlib/Analysis/SpecialFunctions/ImproperIntegrals.lean | 53 | 54 | theorem integral_exp_neg_Ioi (c : ℝ) : (∫ x : ℝ in Ioi c, exp (-x)) = exp (-c) := by |
simpa only [integral_comp_neg_Ioi] using integral_exp_Iic (-c)
|
/-
Copyright (c) 2021 Julian Kuelshammer. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Julian Kuelshammer
-/
import Mathlib.Data.ZMod.Quotient
import Mathlib.GroupTheory.NoncommPiCoprod
import Mathlib.GroupTheory.OrderOfElement
import Mathlib.Algebra.GCDMonoid.Finset
import Mathlib.Algebra.GCDMonoid.Nat
import Mathlib.Data.Nat.Factorization.Basic
import Mathlib.Tactic.ByContra
import Mathlib.Tactic.Peel
#align_import group_theory.exponent from "leanprover-community/mathlib"@"52fa514ec337dd970d71d8de8d0fd68b455a1e54"
/-!
# Exponent of a group
This file defines the exponent of a group, or more generally a monoid. For a group `G` it is defined
to be the minimal `n≥1` such that `g ^ n = 1` for all `g ∈ G`. For a finite group `G`,
it is equal to the lowest common multiple of the order of all elements of the group `G`.
## Main definitions
* `Monoid.ExponentExists` is a predicate on a monoid `G` saying that there is some positive `n`
such that `g ^ n = 1` for all `g ∈ G`.
* `Monoid.exponent` defines the exponent of a monoid `G` as the minimal positive `n` such that
`g ^ n = 1` for all `g ∈ G`, by convention it is `0` if no such `n` exists.
* `AddMonoid.ExponentExists` the additive version of `Monoid.ExponentExists`.
* `AddMonoid.exponent` the additive version of `Monoid.exponent`.
## Main results
* `Monoid.lcm_order_eq_exponent`: For a finite left cancel monoid `G`, the exponent is equal to the
`Finset.lcm` of the order of its elements.
* `Monoid.exponent_eq_iSup_orderOf(')`: For a commutative cancel monoid, the exponent is
equal to `⨆ g : G, orderOf g` (or zero if it has any order-zero elements).
* `Monoid.exponent_pi` and `Monoid.exponent_prod`: The exponent of a finite product of monoids is
the least common multiple (`Finset.lcm` and `lcm`, respectively) of the exponents of the
constituent monoids.
* `MonoidHom.exponent_dvd`: If `f : M₁ →⋆ M₂` is surjective, then the exponent of `M₂` divides the
exponent of `M₁`.
## TODO
* Refactor the characteristic of a ring to be the exponent of its underlying additive group.
-/
universe u
variable {G : Type u}
open scoped Classical
namespace Monoid
section Monoid
variable (G) [Monoid G]
/-- A predicate on a monoid saying that there is a positive integer `n` such that `g ^ n = 1`
for all `g`. -/
@[to_additive
"A predicate on an additive monoid saying that there is a positive integer `n` such\n
that `n • g = 0` for all `g`."]
def ExponentExists :=
∃ n, 0 < n ∧ ∀ g : G, g ^ n = 1
#align monoid.exponent_exists Monoid.ExponentExists
#align add_monoid.exponent_exists AddMonoid.ExponentExists
/-- The exponent of a group is the smallest positive integer `n` such that `g ^ n = 1` for all
`g ∈ G` if it exists, otherwise it is zero by convention. -/
@[to_additive
"The exponent of an additive group is the smallest positive integer `n` such that\n
`n • g = 0` for all `g ∈ G` if it exists, otherwise it is zero by convention."]
noncomputable def exponent :=
if h : ExponentExists G then Nat.find h else 0
#align monoid.exponent Monoid.exponent
#align add_monoid.exponent AddMonoid.exponent
variable {G}
@[simp]
theorem _root_.AddMonoid.exponent_additive :
AddMonoid.exponent (Additive G) = exponent G := rfl
@[simp]
theorem exponent_multiplicative {G : Type*} [AddMonoid G] :
exponent (Multiplicative G) = AddMonoid.exponent G := rfl
open MulOpposite in
@[to_additive (attr := simp)]
theorem _root_.MulOpposite.exponent : exponent (MulOpposite G) = exponent G := by
simp only [Monoid.exponent, ExponentExists]
congr!
all_goals exact ⟨(op_injective <| · <| op ·), (unop_injective <| · <| unop ·)⟩
@[to_additive]
theorem ExponentExists.isOfFinOrder (h : ExponentExists G) {g : G} : IsOfFinOrder g :=
isOfFinOrder_iff_pow_eq_one.mpr <| by peel 2 h; exact this g
@[to_additive]
theorem ExponentExists.orderOf_pos (h : ExponentExists G) (g : G) : 0 < orderOf g :=
h.isOfFinOrder.orderOf_pos
@[to_additive]
theorem exponent_ne_zero : exponent G ≠ 0 ↔ ExponentExists G := by
rw [exponent]
split_ifs with h
· simp [h, @not_lt_zero' ℕ]
--if this isn't done this way, `to_additive` freaks
· tauto
#align monoid.exponent_exists_iff_ne_zero Monoid.exponent_ne_zero
#align add_monoid.exponent_exists_iff_ne_zero AddMonoid.exponent_ne_zero
@[to_additive]
protected alias ⟨_, ExponentExists.exponent_ne_zero⟩ := exponent_ne_zero
@[to_additive (attr := deprecated (since := "2024-01-27"))]
theorem exponentExists_iff_ne_zero : ExponentExists G ↔ exponent G ≠ 0 := exponent_ne_zero.symm
@[to_additive]
theorem exponent_pos : 0 < exponent G ↔ ExponentExists G :=
pos_iff_ne_zero.trans exponent_ne_zero
@[to_additive]
protected alias ⟨_, ExponentExists.exponent_pos⟩ := exponent_pos
@[to_additive]
theorem exponent_eq_zero_iff : exponent G = 0 ↔ ¬ExponentExists G :=
exponent_ne_zero.not_right
#align monoid.exponent_eq_zero_iff Monoid.exponent_eq_zero_iff
#align add_monoid.exponent_eq_zero_iff AddMonoid.exponent_eq_zero_iff
@[to_additive exponent_eq_zero_addOrder_zero]
theorem exponent_eq_zero_of_order_zero {g : G} (hg : orderOf g = 0) : exponent G = 0 :=
exponent_eq_zero_iff.mpr fun h ↦ h.orderOf_pos g |>.ne' hg
#align monoid.exponent_eq_zero_of_order_zero Monoid.exponent_eq_zero_of_order_zero
#align add_monoid.exponent_eq_zero_of_order_zero AddMonoid.exponent_eq_zero_addOrder_zero
/-- The exponent is zero iff for all nonzero `n`, one can find a `g` such that `g ^ n ≠ 1`. -/
@[to_additive "The exponent is zero iff for all nonzero `n`, one can find a `g` such that
`n • g ≠ 0`."]
theorem exponent_eq_zero_iff_forall : exponent G = 0 ↔ ∀ n > 0, ∃ g : G, g ^ n ≠ 1 := by
rw [exponent_eq_zero_iff, ExponentExists]
push_neg
rfl
@[to_additive exponent_nsmul_eq_zero]
theorem pow_exponent_eq_one (g : G) : g ^ exponent G = 1 := by
by_cases h : ExponentExists G
· simp_rw [exponent, dif_pos h]
exact (Nat.find_spec h).2 g
· simp_rw [exponent, dif_neg h, pow_zero]
#align monoid.pow_exponent_eq_one Monoid.pow_exponent_eq_one
#align add_monoid.exponent_nsmul_eq_zero AddMonoid.exponent_nsmul_eq_zero
@[to_additive]
theorem pow_eq_mod_exponent {n : ℕ} (g : G) : g ^ n = g ^ (n % exponent G) :=
calc
g ^ n = g ^ (n % exponent G + exponent G * (n / exponent G)) := by rw [Nat.mod_add_div]
_ = g ^ (n % exponent G) := by simp [pow_add, pow_mul, pow_exponent_eq_one]
#align monoid.pow_eq_mod_exponent Monoid.pow_eq_mod_exponent
#align add_monoid.nsmul_eq_mod_exponent AddMonoid.nsmul_eq_mod_exponent
@[to_additive]
theorem exponent_pos_of_exists (n : ℕ) (hpos : 0 < n) (hG : ∀ g : G, g ^ n = 1) :
0 < exponent G :=
ExponentExists.exponent_pos ⟨n, hpos, hG⟩
#align monoid.exponent_pos_of_exists Monoid.exponent_pos_of_exists
#align add_monoid.exponent_pos_of_exists AddMonoid.exponent_pos_of_exists
@[to_additive]
theorem exponent_min' (n : ℕ) (hpos : 0 < n) (hG : ∀ g : G, g ^ n = 1) : exponent G ≤ n := by
rw [exponent, dif_pos]
· apply Nat.find_min'
exact ⟨hpos, hG⟩
· exact ⟨n, hpos, hG⟩
#align monoid.exponent_min' Monoid.exponent_min'
#align add_monoid.exponent_min' AddMonoid.exponent_min'
@[to_additive]
theorem exponent_min (m : ℕ) (hpos : 0 < m) (hm : m < exponent G) : ∃ g : G, g ^ m ≠ 1 := by
by_contra! h
have hcon : exponent G ≤ m := exponent_min' m hpos h
omega
#align monoid.exponent_min Monoid.exponent_min
#align add_monoid.exponent_min AddMonoid.exponent_min
@[to_additive AddMonoid.exp_eq_one_iff]
| Mathlib/GroupTheory/Exponent.lean | 193 | 200 | theorem exp_eq_one_iff : exponent G = 1 ↔ Subsingleton G := by |
refine ⟨fun eq_one => ⟨fun a b => ?a_eq_b⟩, fun h => le_antisymm ?le ?ge⟩
· rw [← pow_one a, ← pow_one b, ← eq_one, Monoid.pow_exponent_eq_one, Monoid.pow_exponent_eq_one]
· apply exponent_min' _ Nat.one_pos
simp [eq_iff_true_of_subsingleton]
· apply Nat.succ_le_of_lt
apply exponent_pos_of_exists 1 Nat.one_pos
simp [eq_iff_true_of_subsingleton]
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro
-/
import Mathlib.Data.Finset.Update
import Mathlib.Data.Prod.TProd
import Mathlib.GroupTheory.Coset
import Mathlib.Logic.Equiv.Fin
import Mathlib.MeasureTheory.MeasurableSpace.Defs
import Mathlib.Order.Filter.SmallSets
import Mathlib.Order.LiminfLimsup
import Mathlib.Data.Set.UnionLift
#align_import measure_theory.measurable_space from "leanprover-community/mathlib"@"001ffdc42920050657fd45bd2b8bfbec8eaaeb29"
/-!
# Measurable spaces and measurable functions
This file provides properties of measurable spaces and the functions and isomorphisms between them.
The definition of a measurable space is in `Mathlib/MeasureTheory/MeasurableSpace/Defs.lean`.
A measurable space is a set equipped with a σ-algebra, a collection of
subsets closed under complementation and countable union. A function
between measurable spaces is measurable if the preimage of each
measurable subset is measurable.
σ-algebras on a fixed set `α` form a complete lattice. Here we order
σ-algebras by writing `m₁ ≤ m₂` if every set which is `m₁`-measurable is
also `m₂`-measurable (that is, `m₁` is a subset of `m₂`). In particular, any
collection of subsets of `α` generates a smallest σ-algebra which
contains all of them. A function `f : α → β` induces a Galois connection
between the lattices of σ-algebras on `α` and `β`.
A measurable equivalence between measurable spaces is an equivalence
which respects the σ-algebras, that is, for which both directions of
the equivalence are measurable functions.
We say that a filter `f` is measurably generated if every set `s ∈ f` includes a measurable
set `t ∈ f`. This property is useful, e.g., to extract a measurable witness of `Filter.Eventually`.
## Notation
* We write `α ≃ᵐ β` for measurable equivalences between the measurable spaces `α` and `β`.
This should not be confused with `≃ₘ` which is used for diffeomorphisms between manifolds.
## Implementation notes
Measurability of a function `f : α → β` between measurable spaces is
defined in terms of the Galois connection induced by f.
## References
* <https://en.wikipedia.org/wiki/Measurable_space>
* <https://en.wikipedia.org/wiki/Sigma-algebra>
* <https://en.wikipedia.org/wiki/Dynkin_system>
## Tags
measurable space, σ-algebra, measurable function, measurable equivalence, dynkin system,
π-λ theorem, π-system
-/
open Set Encodable Function Equiv Filter MeasureTheory
universe uι
variable {α β γ δ δ' : Type*} {ι : Sort uι} {s t u : Set α}
namespace MeasurableSpace
section Functors
variable {m m₁ m₂ : MeasurableSpace α} {m' : MeasurableSpace β} {f : α → β} {g : β → α}
/-- The forward image of a measurable space under a function. `map f m` contains the sets
`s : Set β` whose preimage under `f` is measurable. -/
protected def map (f : α → β) (m : MeasurableSpace α) : MeasurableSpace β where
MeasurableSet' s := MeasurableSet[m] <| f ⁻¹' s
measurableSet_empty := m.measurableSet_empty
measurableSet_compl s hs := m.measurableSet_compl _ hs
measurableSet_iUnion f hf := by simpa only [preimage_iUnion] using m.measurableSet_iUnion _ hf
#align measurable_space.map MeasurableSpace.map
lemma map_def {s : Set β} : MeasurableSet[m.map f] s ↔ MeasurableSet[m] (f ⁻¹' s) := Iff.rfl
@[simp]
theorem map_id : m.map id = m :=
MeasurableSpace.ext fun _ => Iff.rfl
#align measurable_space.map_id MeasurableSpace.map_id
@[simp]
theorem map_comp {f : α → β} {g : β → γ} : (m.map f).map g = m.map (g ∘ f) :=
MeasurableSpace.ext fun _ => Iff.rfl
#align measurable_space.map_comp MeasurableSpace.map_comp
/-- The reverse image of a measurable space under a function. `comap f m` contains the sets
`s : Set α` such that `s` is the `f`-preimage of a measurable set in `β`. -/
protected def comap (f : α → β) (m : MeasurableSpace β) : MeasurableSpace α where
MeasurableSet' s := ∃ s', MeasurableSet[m] s' ∧ f ⁻¹' s' = s
measurableSet_empty := ⟨∅, m.measurableSet_empty, rfl⟩
measurableSet_compl := fun s ⟨s', h₁, h₂⟩ => ⟨s'ᶜ, m.measurableSet_compl _ h₁, h₂ ▸ rfl⟩
measurableSet_iUnion s hs :=
let ⟨s', hs'⟩ := Classical.axiom_of_choice hs
⟨⋃ i, s' i, m.measurableSet_iUnion _ fun i => (hs' i).left, by simp [hs']⟩
#align measurable_space.comap MeasurableSpace.comap
theorem comap_eq_generateFrom (m : MeasurableSpace β) (f : α → β) :
m.comap f = generateFrom { t | ∃ s, MeasurableSet s ∧ f ⁻¹' s = t } :=
(@generateFrom_measurableSet _ (.comap f m)).symm
#align measurable_space.comap_eq_generate_from MeasurableSpace.comap_eq_generateFrom
@[simp]
theorem comap_id : m.comap id = m :=
MeasurableSpace.ext fun s => ⟨fun ⟨_, hs', h⟩ => h ▸ hs', fun h => ⟨s, h, rfl⟩⟩
#align measurable_space.comap_id MeasurableSpace.comap_id
@[simp]
theorem comap_comp {f : β → α} {g : γ → β} : (m.comap f).comap g = m.comap (f ∘ g) :=
MeasurableSpace.ext fun _ =>
⟨fun ⟨_, ⟨u, h, hu⟩, ht⟩ => ⟨u, h, ht ▸ hu ▸ rfl⟩, fun ⟨t, h, ht⟩ => ⟨f ⁻¹' t, ⟨_, h, rfl⟩, ht⟩⟩
#align measurable_space.comap_comp MeasurableSpace.comap_comp
theorem comap_le_iff_le_map {f : α → β} : m'.comap f ≤ m ↔ m' ≤ m.map f :=
⟨fun h _s hs => h _ ⟨_, hs, rfl⟩, fun h _s ⟨_t, ht, heq⟩ => heq ▸ h _ ht⟩
#align measurable_space.comap_le_iff_le_map MeasurableSpace.comap_le_iff_le_map
theorem gc_comap_map (f : α → β) :
GaloisConnection (MeasurableSpace.comap f) (MeasurableSpace.map f) := fun _ _ =>
comap_le_iff_le_map
#align measurable_space.gc_comap_map MeasurableSpace.gc_comap_map
theorem map_mono (h : m₁ ≤ m₂) : m₁.map f ≤ m₂.map f :=
(gc_comap_map f).monotone_u h
#align measurable_space.map_mono MeasurableSpace.map_mono
theorem monotone_map : Monotone (MeasurableSpace.map f) := fun _ _ => map_mono
#align measurable_space.monotone_map MeasurableSpace.monotone_map
theorem comap_mono (h : m₁ ≤ m₂) : m₁.comap g ≤ m₂.comap g :=
(gc_comap_map g).monotone_l h
#align measurable_space.comap_mono MeasurableSpace.comap_mono
theorem monotone_comap : Monotone (MeasurableSpace.comap g) := fun _ _ h => comap_mono h
#align measurable_space.monotone_comap MeasurableSpace.monotone_comap
@[simp]
theorem comap_bot : (⊥ : MeasurableSpace α).comap g = ⊥ :=
(gc_comap_map g).l_bot
#align measurable_space.comap_bot MeasurableSpace.comap_bot
@[simp]
theorem comap_sup : (m₁ ⊔ m₂).comap g = m₁.comap g ⊔ m₂.comap g :=
(gc_comap_map g).l_sup
#align measurable_space.comap_sup MeasurableSpace.comap_sup
@[simp]
theorem comap_iSup {m : ι → MeasurableSpace α} : (⨆ i, m i).comap g = ⨆ i, (m i).comap g :=
(gc_comap_map g).l_iSup
#align measurable_space.comap_supr MeasurableSpace.comap_iSup
@[simp]
theorem map_top : (⊤ : MeasurableSpace α).map f = ⊤ :=
(gc_comap_map f).u_top
#align measurable_space.map_top MeasurableSpace.map_top
@[simp]
theorem map_inf : (m₁ ⊓ m₂).map f = m₁.map f ⊓ m₂.map f :=
(gc_comap_map f).u_inf
#align measurable_space.map_inf MeasurableSpace.map_inf
@[simp]
theorem map_iInf {m : ι → MeasurableSpace α} : (⨅ i, m i).map f = ⨅ i, (m i).map f :=
(gc_comap_map f).u_iInf
#align measurable_space.map_infi MeasurableSpace.map_iInf
theorem comap_map_le : (m.map f).comap f ≤ m :=
(gc_comap_map f).l_u_le _
#align measurable_space.comap_map_le MeasurableSpace.comap_map_le
theorem le_map_comap : m ≤ (m.comap g).map g :=
(gc_comap_map g).le_u_l _
#align measurable_space.le_map_comap MeasurableSpace.le_map_comap
end Functors
@[simp] theorem map_const {m} (b : β) : MeasurableSpace.map (fun _a : α ↦ b) m = ⊤ :=
eq_top_iff.2 <| fun s _ ↦ by rw [map_def]; by_cases h : b ∈ s <;> simp [h]
#align measurable_space.map_const MeasurableSpace.map_const
@[simp] theorem comap_const {m} (b : β) : MeasurableSpace.comap (fun _a : α => b) m = ⊥ :=
eq_bot_iff.2 <| by rintro _ ⟨s, -, rfl⟩; by_cases b ∈ s <;> simp [*]
#align measurable_space.comap_const MeasurableSpace.comap_const
theorem comap_generateFrom {f : α → β} {s : Set (Set β)} :
(generateFrom s).comap f = generateFrom (preimage f '' s) :=
le_antisymm
(comap_le_iff_le_map.2 <|
generateFrom_le fun _t hts => GenerateMeasurable.basic _ <| mem_image_of_mem _ <| hts)
(generateFrom_le fun _t ⟨u, hu, Eq⟩ => Eq ▸ ⟨u, GenerateMeasurable.basic _ hu, rfl⟩)
#align measurable_space.comap_generate_from MeasurableSpace.comap_generateFrom
end MeasurableSpace
section MeasurableFunctions
open MeasurableSpace
theorem measurable_iff_le_map {m₁ : MeasurableSpace α} {m₂ : MeasurableSpace β} {f : α → β} :
Measurable f ↔ m₂ ≤ m₁.map f :=
Iff.rfl
#align measurable_iff_le_map measurable_iff_le_map
alias ⟨Measurable.le_map, Measurable.of_le_map⟩ := measurable_iff_le_map
#align measurable.le_map Measurable.le_map
#align measurable.of_le_map Measurable.of_le_map
theorem measurable_iff_comap_le {m₁ : MeasurableSpace α} {m₂ : MeasurableSpace β} {f : α → β} :
Measurable f ↔ m₂.comap f ≤ m₁ :=
comap_le_iff_le_map.symm
#align measurable_iff_comap_le measurable_iff_comap_le
alias ⟨Measurable.comap_le, Measurable.of_comap_le⟩ := measurable_iff_comap_le
#align measurable.comap_le Measurable.comap_le
#align measurable.of_comap_le Measurable.of_comap_le
theorem comap_measurable {m : MeasurableSpace β} (f : α → β) : Measurable[m.comap f] f :=
fun s hs => ⟨s, hs, rfl⟩
#align comap_measurable comap_measurable
theorem Measurable.mono {ma ma' : MeasurableSpace α} {mb mb' : MeasurableSpace β} {f : α → β}
(hf : @Measurable α β ma mb f) (ha : ma ≤ ma') (hb : mb' ≤ mb) : @Measurable α β ma' mb' f :=
fun _t ht => ha _ <| hf <| hb _ ht
#align measurable.mono Measurable.mono
theorem measurable_id'' {m mα : MeasurableSpace α} (hm : m ≤ mα) : @Measurable α α mα m id :=
measurable_id.mono le_rfl hm
#align probability_theory.measurable_id'' measurable_id''
-- Porting note (#11215): TODO: add TC `DiscreteMeasurable` + instances
@[measurability]
theorem measurable_from_top [MeasurableSpace β] {f : α → β} : Measurable[⊤] f := fun _ _ => trivial
#align measurable_from_top measurable_from_top
theorem measurable_generateFrom [MeasurableSpace α] {s : Set (Set β)} {f : α → β}
(h : ∀ t ∈ s, MeasurableSet (f ⁻¹' t)) : @Measurable _ _ _ (generateFrom s) f :=
Measurable.of_le_map <| generateFrom_le h
#align measurable_generate_from measurable_generateFrom
variable {f g : α → β}
section TypeclassMeasurableSpace
variable [MeasurableSpace α] [MeasurableSpace β] [MeasurableSpace γ]
@[nontriviality, measurability]
theorem Subsingleton.measurable [Subsingleton α] : Measurable f := fun _ _ =>
@Subsingleton.measurableSet α _ _ _
#align subsingleton.measurable Subsingleton.measurable
@[nontriviality, measurability]
theorem measurable_of_subsingleton_codomain [Subsingleton β] (f : α → β) : Measurable f :=
fun s _ => Subsingleton.set_cases MeasurableSet.empty MeasurableSet.univ s
#align measurable_of_subsingleton_codomain measurable_of_subsingleton_codomain
@[to_additive (attr := measurability)]
theorem measurable_one [One α] : Measurable (1 : β → α) :=
@measurable_const _ _ _ _ 1
#align measurable_one measurable_one
#align measurable_zero measurable_zero
theorem measurable_of_empty [IsEmpty α] (f : α → β) : Measurable f :=
Subsingleton.measurable
#align measurable_of_empty measurable_of_empty
theorem measurable_of_empty_codomain [IsEmpty β] (f : α → β) : Measurable f :=
measurable_of_subsingleton_codomain f
#align measurable_of_empty_codomain measurable_of_empty_codomain
/-- A version of `measurable_const` that assumes `f x = f y` for all `x, y`. This version works
for functions between empty types. -/
theorem measurable_const' {f : β → α} (hf : ∀ x y, f x = f y) : Measurable f := by
nontriviality β
inhabit β
convert @measurable_const α β _ _ (f default) using 2
apply hf
#align measurable_const' measurable_const'
@[measurability]
theorem measurable_natCast [NatCast α] (n : ℕ) : Measurable (n : β → α) :=
@measurable_const α _ _ _ n
#align measurable_nat_cast measurable_natCast
@[measurability]
theorem measurable_intCast [IntCast α] (n : ℤ) : Measurable (n : β → α) :=
@measurable_const α _ _ _ n
#align measurable_int_cast measurable_intCast
theorem measurable_of_countable [Countable α] [MeasurableSingletonClass α] (f : α → β) :
Measurable f := fun s _ =>
(f ⁻¹' s).to_countable.measurableSet
#align measurable_of_countable measurable_of_countable
theorem measurable_of_finite [Finite α] [MeasurableSingletonClass α] (f : α → β) : Measurable f :=
measurable_of_countable f
#align measurable_of_finite measurable_of_finite
end TypeclassMeasurableSpace
variable {m : MeasurableSpace α}
@[measurability]
theorem Measurable.iterate {f : α → α} (hf : Measurable f) : ∀ n, Measurable f^[n]
| 0 => measurable_id
| n + 1 => (Measurable.iterate hf n).comp hf
#align measurable.iterate Measurable.iterate
variable {mβ : MeasurableSpace β}
@[measurability]
theorem measurableSet_preimage {t : Set β} (hf : Measurable f) (ht : MeasurableSet t) :
MeasurableSet (f ⁻¹' t) :=
hf ht
#align measurable_set_preimage measurableSet_preimage
-- Porting note (#10756): new theorem
protected theorem MeasurableSet.preimage {t : Set β} (ht : MeasurableSet t) (hf : Measurable f) :
MeasurableSet (f ⁻¹' t) :=
hf ht
@[measurability]
protected theorem Measurable.piecewise {_ : DecidablePred (· ∈ s)} (hs : MeasurableSet s)
(hf : Measurable f) (hg : Measurable g) : Measurable (piecewise s f g) := by
intro t ht
rw [piecewise_preimage]
exact hs.ite (hf ht) (hg ht)
#align measurable.piecewise Measurable.piecewise
/-- This is slightly different from `Measurable.piecewise`. It can be used to show
`Measurable (ite (x=0) 0 1)` by
`exact Measurable.ite (measurableSet_singleton 0) measurable_const measurable_const`,
but replacing `Measurable.ite` by `Measurable.piecewise` in that example proof does not work. -/
theorem Measurable.ite {p : α → Prop} {_ : DecidablePred p} (hp : MeasurableSet { a : α | p a })
(hf : Measurable f) (hg : Measurable g) : Measurable fun x => ite (p x) (f x) (g x) :=
Measurable.piecewise hp hf hg
#align measurable.ite Measurable.ite
@[measurability]
theorem Measurable.indicator [Zero β] (hf : Measurable f) (hs : MeasurableSet s) :
Measurable (s.indicator f) :=
hf.piecewise hs measurable_const
#align measurable.indicator Measurable.indicator
/-- The measurability of a set `A` is equivalent to the measurability of the indicator function
which takes a constant value `b ≠ 0` on a set `A` and `0` elsewhere. -/
lemma measurable_indicator_const_iff [Zero β] [MeasurableSingletonClass β] (b : β) [NeZero b] :
Measurable (s.indicator (fun (_ : α) ↦ b)) ↔ MeasurableSet s := by
constructor <;> intro h
· convert h (MeasurableSet.singleton (0 : β)).compl
ext a
simp [NeZero.ne b]
· exact measurable_const.indicator h
@[to_additive (attr := measurability)]
theorem measurableSet_mulSupport [One β] [MeasurableSingletonClass β] (hf : Measurable f) :
MeasurableSet (mulSupport f) :=
hf (measurableSet_singleton 1).compl
#align measurable_set_mul_support measurableSet_mulSupport
#align measurable_set_support measurableSet_support
/-- If a function coincides with a measurable function outside of a countable set, it is
measurable. -/
theorem Measurable.measurable_of_countable_ne [MeasurableSingletonClass α] (hf : Measurable f)
(h : Set.Countable { x | f x ≠ g x }) : Measurable g := by
intro t ht
have : g ⁻¹' t = g ⁻¹' t ∩ { x | f x = g x }ᶜ ∪ g ⁻¹' t ∩ { x | f x = g x } := by
simp [← inter_union_distrib_left]
rw [this]
refine (h.mono inter_subset_right).measurableSet.union ?_
have : g ⁻¹' t ∩ { x : α | f x = g x } = f ⁻¹' t ∩ { x : α | f x = g x } := by
ext x
simp (config := { contextual := true })
rw [this]
exact (hf ht).inter h.measurableSet.of_compl
#align measurable.measurable_of_countable_ne Measurable.measurable_of_countable_ne
end MeasurableFunctions
section Constructions
instance Empty.instMeasurableSpace : MeasurableSpace Empty := ⊤
#align empty.measurable_space Empty.instMeasurableSpace
instance PUnit.instMeasurableSpace : MeasurableSpace PUnit := ⊤
#align punit.measurable_space PUnit.instMeasurableSpace
instance Bool.instMeasurableSpace : MeasurableSpace Bool := ⊤
#align bool.measurable_space Bool.instMeasurableSpace
instance Prop.instMeasurableSpace : MeasurableSpace Prop := ⊤
#align Prop.measurable_space Prop.instMeasurableSpace
instance Nat.instMeasurableSpace : MeasurableSpace ℕ := ⊤
#align nat.measurable_space Nat.instMeasurableSpace
instance Fin.instMeasurableSpace (n : ℕ) : MeasurableSpace (Fin n) := ⊤
instance Int.instMeasurableSpace : MeasurableSpace ℤ := ⊤
#align int.measurable_space Int.instMeasurableSpace
instance Rat.instMeasurableSpace : MeasurableSpace ℚ := ⊤
#align rat.measurable_space Rat.instMeasurableSpace
instance Subsingleton.measurableSingletonClass {α} [MeasurableSpace α] [Subsingleton α] :
MeasurableSingletonClass α := by
refine ⟨fun i => ?_⟩
convert MeasurableSet.univ
simp [Set.eq_univ_iff_forall, eq_iff_true_of_subsingleton]
#noalign empty.measurable_singleton_class
#noalign punit.measurable_singleton_class
instance Bool.instMeasurableSingletonClass : MeasurableSingletonClass Bool := ⟨fun _ => trivial⟩
#align bool.measurable_singleton_class Bool.instMeasurableSingletonClass
instance Prop.instMeasurableSingletonClass : MeasurableSingletonClass Prop := ⟨fun _ => trivial⟩
#align Prop.measurable_singleton_class Prop.instMeasurableSingletonClass
instance Nat.instMeasurableSingletonClass : MeasurableSingletonClass ℕ := ⟨fun _ => trivial⟩
#align nat.measurable_singleton_class Nat.instMeasurableSingletonClass
instance Fin.instMeasurableSingletonClass (n : ℕ) : MeasurableSingletonClass (Fin n) :=
⟨fun _ => trivial⟩
instance Int.instMeasurableSingletonClass : MeasurableSingletonClass ℤ := ⟨fun _ => trivial⟩
#align int.measurable_singleton_class Int.instMeasurableSingletonClass
instance Rat.instMeasurableSingletonClass : MeasurableSingletonClass ℚ := ⟨fun _ => trivial⟩
#align rat.measurable_singleton_class Rat.instMeasurableSingletonClass
theorem measurable_to_countable [MeasurableSpace α] [Countable α] [MeasurableSpace β] {f : β → α}
(h : ∀ y, MeasurableSet (f ⁻¹' {f y})) : Measurable f := fun s _ => by
rw [← biUnion_preimage_singleton]
refine MeasurableSet.iUnion fun y => MeasurableSet.iUnion fun hy => ?_
by_cases hyf : y ∈ range f
· rcases hyf with ⟨y, rfl⟩
apply h
· simp only [preimage_singleton_eq_empty.2 hyf, MeasurableSet.empty]
#align measurable_to_countable measurable_to_countable
theorem measurable_to_countable' [MeasurableSpace α] [Countable α] [MeasurableSpace β] {f : β → α}
(h : ∀ x, MeasurableSet (f ⁻¹' {x})) : Measurable f :=
measurable_to_countable fun y => h (f y)
#align measurable_to_countable' measurable_to_countable'
@[measurability]
theorem measurable_unit [MeasurableSpace α] (f : Unit → α) : Measurable f :=
measurable_from_top
#align measurable_unit measurable_unit
section ULift
variable [MeasurableSpace α]
instance _root_.ULift.instMeasurableSpace : MeasurableSpace (ULift α) :=
‹MeasurableSpace α›.map ULift.up
lemma measurable_down : Measurable (ULift.down : ULift α → α) := fun _ ↦ id
lemma measurable_up : Measurable (ULift.up : α → ULift α) := fun _ ↦ id
@[simp] lemma measurableSet_preimage_down {s : Set α} :
MeasurableSet (ULift.down ⁻¹' s) ↔ MeasurableSet s := Iff.rfl
@[simp] lemma measurableSet_preimage_up {s : Set (ULift α)} :
MeasurableSet (ULift.up ⁻¹' s) ↔ MeasurableSet s := Iff.rfl
end ULift
section Nat
variable [MeasurableSpace α]
@[measurability]
theorem measurable_from_nat {f : ℕ → α} : Measurable f :=
measurable_from_top
#align measurable_from_nat measurable_from_nat
theorem measurable_to_nat {f : α → ℕ} : (∀ y, MeasurableSet (f ⁻¹' {f y})) → Measurable f :=
measurable_to_countable
#align measurable_to_nat measurable_to_nat
theorem measurable_to_bool {f : α → Bool} (h : MeasurableSet (f ⁻¹' {true})) : Measurable f := by
apply measurable_to_countable'
rintro (- | -)
· convert h.compl
rw [← preimage_compl, Bool.compl_singleton, Bool.not_true]
exact h
#align measurable_to_bool measurable_to_bool
theorem measurable_to_prop {f : α → Prop} (h : MeasurableSet (f ⁻¹' {True})) : Measurable f := by
refine measurable_to_countable' fun x => ?_
by_cases hx : x
· simpa [hx] using h
· simpa only [hx, ← preimage_compl, Prop.compl_singleton, not_true, preimage_singleton_false]
using h.compl
#align measurable_to_prop measurable_to_prop
theorem measurable_findGreatest' {p : α → ℕ → Prop} [∀ x, DecidablePred (p x)] {N : ℕ}
(hN : ∀ k ≤ N, MeasurableSet { x | Nat.findGreatest (p x) N = k }) :
Measurable fun x => Nat.findGreatest (p x) N :=
measurable_to_nat fun _ => hN _ N.findGreatest_le
#align measurable_find_greatest' measurable_findGreatest'
theorem measurable_findGreatest {p : α → ℕ → Prop} [∀ x, DecidablePred (p x)] {N}
(hN : ∀ k ≤ N, MeasurableSet { x | p x k }) : Measurable fun x => Nat.findGreatest (p x) N := by
refine measurable_findGreatest' fun k hk => ?_
simp only [Nat.findGreatest_eq_iff, setOf_and, setOf_forall, ← compl_setOf]
repeat' apply_rules [MeasurableSet.inter, MeasurableSet.const, MeasurableSet.iInter,
MeasurableSet.compl, hN] <;> try intros
#align measurable_find_greatest measurable_findGreatest
theorem measurable_find {p : α → ℕ → Prop} [∀ x, DecidablePred (p x)] (hp : ∀ x, ∃ N, p x N)
(hm : ∀ k, MeasurableSet { x | p x k }) : Measurable fun x => Nat.find (hp x) := by
refine measurable_to_nat fun x => ?_
rw [preimage_find_eq_disjointed (fun k => {x | p x k})]
exact MeasurableSet.disjointed hm _
#align measurable_find measurable_find
end Nat
section Quotient
variable [MeasurableSpace α] [MeasurableSpace β]
instance Quot.instMeasurableSpace {α} {r : α → α → Prop} [m : MeasurableSpace α] :
MeasurableSpace (Quot r) :=
m.map (Quot.mk r)
#align quot.measurable_space Quot.instMeasurableSpace
instance Quotient.instMeasurableSpace {α} {s : Setoid α} [m : MeasurableSpace α] :
MeasurableSpace (Quotient s) :=
m.map Quotient.mk''
#align quotient.measurable_space Quotient.instMeasurableSpace
@[to_additive]
instance QuotientGroup.measurableSpace {G} [Group G] [MeasurableSpace G] (S : Subgroup G) :
MeasurableSpace (G ⧸ S) :=
Quotient.instMeasurableSpace
#align quotient_group.measurable_space QuotientGroup.measurableSpace
#align quotient_add_group.measurable_space QuotientAddGroup.measurableSpace
theorem measurableSet_quotient {s : Setoid α} {t : Set (Quotient s)} :
MeasurableSet t ↔ MeasurableSet (Quotient.mk'' ⁻¹' t) :=
Iff.rfl
#align measurable_set_quotient measurableSet_quotient
theorem measurable_from_quotient {s : Setoid α} {f : Quotient s → β} :
Measurable f ↔ Measurable (f ∘ Quotient.mk'') :=
Iff.rfl
#align measurable_from_quotient measurable_from_quotient
@[measurability]
theorem measurable_quotient_mk' [s : Setoid α] : Measurable (Quotient.mk' : α → Quotient s) :=
fun _ => id
#align measurable_quotient_mk measurable_quotient_mk'
@[measurability]
theorem measurable_quotient_mk'' {s : Setoid α} : Measurable (Quotient.mk'' : α → Quotient s) :=
fun _ => id
#align measurable_quotient_mk' measurable_quotient_mk''
@[measurability]
theorem measurable_quot_mk {r : α → α → Prop} : Measurable (Quot.mk r) := fun _ => id
#align measurable_quot_mk measurable_quot_mk
@[to_additive (attr := measurability)]
theorem QuotientGroup.measurable_coe {G} [Group G] [MeasurableSpace G] {S : Subgroup G} :
Measurable ((↑) : G → G ⧸ S) :=
measurable_quotient_mk''
#align quotient_group.measurable_coe QuotientGroup.measurable_coe
#align quotient_add_group.measurable_coe QuotientAddGroup.measurable_coe
@[to_additive]
nonrec theorem QuotientGroup.measurable_from_quotient {G} [Group G] [MeasurableSpace G]
{S : Subgroup G} {f : G ⧸ S → α} : Measurable f ↔ Measurable (f ∘ ((↑) : G → G ⧸ S)) :=
measurable_from_quotient
#align quotient_group.measurable_from_quotient QuotientGroup.measurable_from_quotient
#align quotient_add_group.measurable_from_quotient QuotientAddGroup.measurable_from_quotient
end Quotient
section Subtype
instance Subtype.instMeasurableSpace {α} {p : α → Prop} [m : MeasurableSpace α] :
MeasurableSpace (Subtype p) :=
m.comap ((↑) : _ → α)
#align subtype.measurable_space Subtype.instMeasurableSpace
section
variable [MeasurableSpace α]
@[measurability]
theorem measurable_subtype_coe {p : α → Prop} : Measurable ((↑) : Subtype p → α) :=
MeasurableSpace.le_map_comap
#align measurable_subtype_coe measurable_subtype_coe
instance Subtype.instMeasurableSingletonClass {p : α → Prop} [MeasurableSingletonClass α] :
MeasurableSingletonClass (Subtype p) where
measurableSet_singleton x :=
⟨{(x : α)}, measurableSet_singleton (x : α), by
rw [← image_singleton, preimage_image_eq _ Subtype.val_injective]⟩
#align subtype.measurable_singleton_class Subtype.instMeasurableSingletonClass
end
variable {m : MeasurableSpace α} {mβ : MeasurableSpace β}
theorem MeasurableSet.of_subtype_image {s : Set α} {t : Set s}
(h : MeasurableSet (Subtype.val '' t)) : MeasurableSet t :=
⟨_, h, preimage_image_eq _ Subtype.val_injective⟩
theorem MeasurableSet.subtype_image {s : Set α} {t : Set s} (hs : MeasurableSet s) :
MeasurableSet t → MeasurableSet (((↑) : s → α) '' t) := by
rintro ⟨u, hu, rfl⟩
rw [Subtype.image_preimage_coe]
exact hs.inter hu
#align measurable_set.subtype_image MeasurableSet.subtype_image
@[measurability]
theorem Measurable.subtype_coe {p : β → Prop} {f : α → Subtype p} (hf : Measurable f) :
Measurable fun a : α => (f a : β) :=
measurable_subtype_coe.comp hf
#align measurable.subtype_coe Measurable.subtype_coe
alias Measurable.subtype_val := Measurable.subtype_coe
@[measurability]
theorem Measurable.subtype_mk {p : β → Prop} {f : α → β} (hf : Measurable f) {h : ∀ x, p (f x)} :
Measurable fun x => (⟨f x, h x⟩ : Subtype p) := fun t ⟨s, hs⟩ =>
hs.2 ▸ by simp only [← preimage_comp, (· ∘ ·), Subtype.coe_mk, hf hs.1]
#align measurable.subtype_mk Measurable.subtype_mk
@[measurability]
protected theorem Measurable.rangeFactorization {f : α → β} (hf : Measurable f) :
Measurable (rangeFactorization f) :=
hf.subtype_mk
theorem Measurable.subtype_map {f : α → β} {p : α → Prop} {q : β → Prop} (hf : Measurable f)
(hpq : ∀ x, p x → q (f x)) : Measurable (Subtype.map f hpq) :=
(hf.comp measurable_subtype_coe).subtype_mk
theorem measurable_inclusion {s t : Set α} (h : s ⊆ t) : Measurable (inclusion h) :=
measurable_id.subtype_map h
theorem MeasurableSet.image_inclusion' {s t : Set α} (h : s ⊆ t) {u : Set s}
(hs : MeasurableSet (Subtype.val ⁻¹' s : Set t)) (hu : MeasurableSet u) :
MeasurableSet (inclusion h '' u) := by
rcases hu with ⟨u, hu, rfl⟩
convert (measurable_subtype_coe hu).inter hs
ext ⟨x, hx⟩
simpa [@and_comm _ (_ = x)] using and_comm
theorem MeasurableSet.image_inclusion {s t : Set α} (h : s ⊆ t) {u : Set s}
(hs : MeasurableSet s) (hu : MeasurableSet u) :
MeasurableSet (inclusion h '' u) :=
(measurable_subtype_coe hs).image_inclusion' h hu
theorem MeasurableSet.of_union_cover {s t u : Set α} (hs : MeasurableSet s) (ht : MeasurableSet t)
(h : univ ⊆ s ∪ t) (hsu : MeasurableSet (((↑) : s → α) ⁻¹' u))
(htu : MeasurableSet (((↑) : t → α) ⁻¹' u)) : MeasurableSet u := by
convert (hs.subtype_image hsu).union (ht.subtype_image htu)
simp [image_preimage_eq_inter_range, ← inter_union_distrib_left, univ_subset_iff.1 h]
theorem measurable_of_measurable_union_cover {f : α → β} (s t : Set α) (hs : MeasurableSet s)
(ht : MeasurableSet t) (h : univ ⊆ s ∪ t) (hc : Measurable fun a : s => f a)
(hd : Measurable fun a : t => f a) : Measurable f := fun _u hu =>
.of_union_cover hs ht h (hc hu) (hd hu)
#align measurable_of_measurable_union_cover measurable_of_measurable_union_cover
theorem measurable_of_restrict_of_restrict_compl {f : α → β} {s : Set α} (hs : MeasurableSet s)
(h₁ : Measurable (s.restrict f)) (h₂ : Measurable (sᶜ.restrict f)) : Measurable f :=
measurable_of_measurable_union_cover s sᶜ hs hs.compl (union_compl_self s).ge h₁ h₂
#align measurable_of_restrict_of_restrict_compl measurable_of_restrict_of_restrict_compl
theorem Measurable.dite [∀ x, Decidable (x ∈ s)] {f : s → β} (hf : Measurable f)
{g : (sᶜ : Set α) → β} (hg : Measurable g) (hs : MeasurableSet s) :
Measurable fun x => if hx : x ∈ s then f ⟨x, hx⟩ else g ⟨x, hx⟩ :=
measurable_of_restrict_of_restrict_compl hs (by simpa) (by simpa)
#align measurable.dite Measurable.dite
theorem measurable_of_measurable_on_compl_finite [MeasurableSingletonClass α] {f : α → β}
(s : Set α) (hs : s.Finite) (hf : Measurable (sᶜ.restrict f)) : Measurable f :=
have := hs.to_subtype
measurable_of_restrict_of_restrict_compl hs.measurableSet (measurable_of_finite _) hf
#align measurable_of_measurable_on_compl_finite measurable_of_measurable_on_compl_finite
theorem measurable_of_measurable_on_compl_singleton [MeasurableSingletonClass α] {f : α → β} (a : α)
(hf : Measurable ({ x | x ≠ a }.restrict f)) : Measurable f :=
measurable_of_measurable_on_compl_finite {a} (finite_singleton a) hf
#align measurable_of_measurable_on_compl_singleton measurable_of_measurable_on_compl_singleton
end Subtype
section Atoms
variable [MeasurableSpace β]
/-- The *measurable atom* of `x` is the intersection of all the measurable sets countaining `x`.
It is measurable when the space is countable (or more generally when the measurable space is
countably generated). -/
def measurableAtom (x : β) : Set β :=
⋂ (s : Set β) (_h's : x ∈ s) (_hs : MeasurableSet s), s
@[simp] lemma mem_measurableAtom_self (x : β) : x ∈ measurableAtom x := by
simp (config := {contextual := true}) [measurableAtom]
lemma mem_of_mem_measurableAtom {x y : β} (h : y ∈ measurableAtom x) {s : Set β}
(hs : MeasurableSet s) (hxs : x ∈ s) : y ∈ s := by
simp only [measurableAtom, mem_iInter] at h
exact h s hxs hs
lemma measurableAtom_subset {s : Set β} {x : β} (hs : MeasurableSet s) (hx : x ∈ s) :
measurableAtom x ⊆ s :=
iInter₂_subset_of_subset s hx fun ⦃a⦄ ↦ (by simp [hs])
@[simp] lemma measurableAtom_of_measurableSingletonClass [MeasurableSingletonClass β] (x : β) :
measurableAtom x = {x} :=
Subset.antisymm (measurableAtom_subset (measurableSet_singleton x) rfl) (by simp)
lemma MeasurableSet.measurableAtom_of_countable [Countable β] (x : β) :
MeasurableSet (measurableAtom x) := by
have : ∀ (y : β), y ∉ measurableAtom x → ∃ s, x ∈ s ∧ MeasurableSet s ∧ y ∉ s :=
fun y hy ↦ by simpa [measurableAtom] using hy
choose! s hs using this
have : measurableAtom x = ⋂ (y ∈ (measurableAtom x)ᶜ), s y := by
apply Subset.antisymm
· intro z hz
simp only [mem_iInter, mem_compl_iff]
intro i hi
show z ∈ s i
exact mem_of_mem_measurableAtom hz (hs i hi).2.1 (hs i hi).1
· apply compl_subset_compl.1
intro z hz
simp only [compl_iInter, mem_iUnion, mem_compl_iff, exists_prop]
exact ⟨z, hz, (hs z hz).2.2⟩
rw [this]
exact MeasurableSet.biInter (to_countable (measurableAtom x)ᶜ) (fun i hi ↦ (hs i hi).2.1)
end Atoms
section Prod
/-- A `MeasurableSpace` structure on the product of two measurable spaces. -/
def MeasurableSpace.prod {α β} (m₁ : MeasurableSpace α) (m₂ : MeasurableSpace β) :
MeasurableSpace (α × β) :=
m₁.comap Prod.fst ⊔ m₂.comap Prod.snd
#align measurable_space.prod MeasurableSpace.prod
instance Prod.instMeasurableSpace {α β} [m₁ : MeasurableSpace α] [m₂ : MeasurableSpace β] :
MeasurableSpace (α × β) :=
m₁.prod m₂
#align prod.measurable_space Prod.instMeasurableSpace
@[measurability]
theorem measurable_fst {_ : MeasurableSpace α} {_ : MeasurableSpace β} :
Measurable (Prod.fst : α × β → α) :=
Measurable.of_comap_le le_sup_left
#align measurable_fst measurable_fst
@[measurability]
theorem measurable_snd {_ : MeasurableSpace α} {_ : MeasurableSpace β} :
Measurable (Prod.snd : α × β → β) :=
Measurable.of_comap_le le_sup_right
#align measurable_snd measurable_snd
variable {m : MeasurableSpace α} {mβ : MeasurableSpace β} {mγ : MeasurableSpace γ}
theorem Measurable.fst {f : α → β × γ} (hf : Measurable f) : Measurable fun a : α => (f a).1 :=
measurable_fst.comp hf
#align measurable.fst Measurable.fst
theorem Measurable.snd {f : α → β × γ} (hf : Measurable f) : Measurable fun a : α => (f a).2 :=
measurable_snd.comp hf
#align measurable.snd Measurable.snd
@[measurability]
theorem Measurable.prod {f : α → β × γ} (hf₁ : Measurable fun a => (f a).1)
(hf₂ : Measurable fun a => (f a).2) : Measurable f :=
Measurable.of_le_map <|
sup_le
(by
rw [MeasurableSpace.comap_le_iff_le_map, MeasurableSpace.map_comp]
exact hf₁)
(by
rw [MeasurableSpace.comap_le_iff_le_map, MeasurableSpace.map_comp]
exact hf₂)
#align measurable.prod Measurable.prod
theorem Measurable.prod_mk {β γ} {_ : MeasurableSpace β} {_ : MeasurableSpace γ} {f : α → β}
{g : α → γ} (hf : Measurable f) (hg : Measurable g) : Measurable fun a : α => (f a, g a) :=
Measurable.prod hf hg
#align measurable.prod_mk Measurable.prod_mk
theorem Measurable.prod_map [MeasurableSpace δ] {f : α → β} {g : γ → δ} (hf : Measurable f)
(hg : Measurable g) : Measurable (Prod.map f g) :=
(hf.comp measurable_fst).prod_mk (hg.comp measurable_snd)
#align measurable.prod_map Measurable.prod_map
theorem measurable_prod_mk_left {x : α} : Measurable (@Prod.mk _ β x) :=
measurable_const.prod_mk measurable_id
#align measurable_prod_mk_left measurable_prod_mk_left
theorem measurable_prod_mk_right {y : β} : Measurable fun x : α => (x, y) :=
measurable_id.prod_mk measurable_const
#align measurable_prod_mk_right measurable_prod_mk_right
theorem Measurable.of_uncurry_left {f : α → β → γ} (hf : Measurable (uncurry f)) {x : α} :
Measurable (f x) :=
hf.comp measurable_prod_mk_left
#align measurable.of_uncurry_left Measurable.of_uncurry_left
theorem Measurable.of_uncurry_right {f : α → β → γ} (hf : Measurable (uncurry f)) {y : β} :
Measurable fun x => f x y :=
hf.comp measurable_prod_mk_right
#align measurable.of_uncurry_right Measurable.of_uncurry_right
theorem measurable_prod {f : α → β × γ} :
Measurable f ↔ (Measurable fun a => (f a).1) ∧ Measurable fun a => (f a).2 :=
⟨fun hf => ⟨measurable_fst.comp hf, measurable_snd.comp hf⟩, fun h => Measurable.prod h.1 h.2⟩
#align measurable_prod measurable_prod
@[measurability]
theorem measurable_swap : Measurable (Prod.swap : α × β → β × α) :=
Measurable.prod measurable_snd measurable_fst
#align measurable_swap measurable_swap
theorem measurable_swap_iff {_ : MeasurableSpace γ} {f : α × β → γ} :
Measurable (f ∘ Prod.swap) ↔ Measurable f :=
⟨fun hf => hf.comp measurable_swap, fun hf => hf.comp measurable_swap⟩
#align measurable_swap_iff measurable_swap_iff
@[measurability]
protected theorem MeasurableSet.prod {s : Set α} {t : Set β} (hs : MeasurableSet s)
(ht : MeasurableSet t) : MeasurableSet (s ×ˢ t) :=
MeasurableSet.inter (measurable_fst hs) (measurable_snd ht)
#align measurable_set.prod MeasurableSet.prod
theorem measurableSet_prod_of_nonempty {s : Set α} {t : Set β} (h : (s ×ˢ t).Nonempty) :
MeasurableSet (s ×ˢ t) ↔ MeasurableSet s ∧ MeasurableSet t := by
rcases h with ⟨⟨x, y⟩, hx, hy⟩
refine ⟨fun hst => ?_, fun h => h.1.prod h.2⟩
have : MeasurableSet ((fun x => (x, y)) ⁻¹' s ×ˢ t) := measurable_prod_mk_right hst
have : MeasurableSet (Prod.mk x ⁻¹' s ×ˢ t) := measurable_prod_mk_left hst
simp_all
#align measurable_set_prod_of_nonempty measurableSet_prod_of_nonempty
theorem measurableSet_prod {s : Set α} {t : Set β} :
MeasurableSet (s ×ˢ t) ↔ MeasurableSet s ∧ MeasurableSet t ∨ s = ∅ ∨ t = ∅ := by
rcases (s ×ˢ t).eq_empty_or_nonempty with h | h
· simp [h, prod_eq_empty_iff.mp h]
· simp [← not_nonempty_iff_eq_empty, prod_nonempty_iff.mp h, measurableSet_prod_of_nonempty h]
#align measurable_set_prod measurableSet_prod
theorem measurableSet_swap_iff {s : Set (α × β)} :
MeasurableSet (Prod.swap ⁻¹' s) ↔ MeasurableSet s :=
⟨fun hs => measurable_swap hs, fun hs => measurable_swap hs⟩
#align measurable_set_swap_iff measurableSet_swap_iff
instance Prod.instMeasurableSingletonClass
[MeasurableSingletonClass α] [MeasurableSingletonClass β] :
MeasurableSingletonClass (α × β) :=
⟨fun ⟨a, b⟩ => @singleton_prod_singleton _ _ a b ▸ .prod (.singleton a) (.singleton b)⟩
#align prod.measurable_singleton_class Prod.instMeasurableSingletonClass
theorem measurable_from_prod_countable' [Countable β]
{_ : MeasurableSpace γ} {f : α × β → γ} (hf : ∀ y, Measurable fun x => f (x, y))
(h'f : ∀ y y' x, y' ∈ measurableAtom y → f (x, y') = f (x, y)) :
Measurable f := fun s hs => by
have : f ⁻¹' s = ⋃ y, ((fun x => f (x, y)) ⁻¹' s) ×ˢ (measurableAtom y : Set β) := by
ext1 ⟨x, y⟩
simp only [mem_preimage, mem_iUnion, mem_prod]
refine ⟨fun h ↦ ⟨y, h, mem_measurableAtom_self y⟩, ?_⟩
rintro ⟨y', hy's, hy'⟩
rwa [h'f y' y x hy']
rw [this]
exact .iUnion (fun y ↦ (hf y hs).prod (.measurableAtom_of_countable y))
theorem measurable_from_prod_countable [Countable β] [MeasurableSingletonClass β]
{_ : MeasurableSpace γ} {f : α × β → γ} (hf : ∀ y, Measurable fun x => f (x, y)) :
Measurable f :=
measurable_from_prod_countable' hf (by simp (config := {contextual := true}))
#align measurable_from_prod_countable measurable_from_prod_countable
/-- A piecewise function on countably many pieces is measurable if all the data is measurable. -/
@[measurability]
theorem Measurable.find {_ : MeasurableSpace α} {f : ℕ → α → β} {p : ℕ → α → Prop}
[∀ n, DecidablePred (p n)] (hf : ∀ n, Measurable (f n)) (hp : ∀ n, MeasurableSet { x | p n x })
(h : ∀ x, ∃ n, p n x) : Measurable fun x => f (Nat.find (h x)) x :=
have : Measurable fun p : α × ℕ => f p.2 p.1 := measurable_from_prod_countable fun n => hf n
this.comp (Measurable.prod_mk measurable_id (measurable_find h hp))
#align measurable.find Measurable.find
/-- Let `t i` be a countable covering of a set `T` by measurable sets. Let `f i : t i → β` be a
family of functions that agree on the intersections `t i ∩ t j`. Then the function
`Set.iUnionLift t f _ _ : T → β`, defined as `f i ⟨x, hx⟩` for `hx : x ∈ t i`, is measurable. -/
theorem measurable_iUnionLift [Countable ι] {t : ι → Set α} {f : ∀ i, t i → β}
(htf : ∀ (i j) (x : α) (hxi : x ∈ t i) (hxj : x ∈ t j), f i ⟨x, hxi⟩ = f j ⟨x, hxj⟩)
{T : Set α} (hT : T ⊆ ⋃ i, t i) (htm : ∀ i, MeasurableSet (t i)) (hfm : ∀ i, Measurable (f i)) :
Measurable (iUnionLift t f htf T hT) := fun s hs => by
rw [preimage_iUnionLift]
exact .preimage (.iUnion fun i => .image_inclusion _ (htm _) (hfm i hs)) (measurable_inclusion _)
/-- Let `t i` be a countable covering of `α` by measurable sets. Let `f i : t i → β` be a family of
functions that agree on the intersections `t i ∩ t j`. Then the function `Set.liftCover t f _ _`,
defined as `f i ⟨x, hx⟩` for `hx : x ∈ t i`, is measurable. -/
theorem measurable_liftCover [Countable ι] (t : ι → Set α) (htm : ∀ i, MeasurableSet (t i))
(f : ∀ i, t i → β) (hfm : ∀ i, Measurable (f i))
(hf : ∀ (i j) (x : α) (hxi : x ∈ t i) (hxj : x ∈ t j), f i ⟨x, hxi⟩ = f j ⟨x, hxj⟩)
(htU : ⋃ i, t i = univ) :
Measurable (liftCover t f hf htU) := fun s hs => by
rw [preimage_liftCover]
exact .iUnion fun i => .subtype_image (htm i) <| hfm i hs
/-- Let `t i` be a nonempty countable family of measurable sets in `α`. Let `g i : α → β` be a
family of measurable functions such that `g i` agrees with `g j` on `t i ∩ t j`. Then there exists
a measurable function `f : α → β` that agrees with each `g i` on `t i`.
We only need the assumption `[Nonempty ι]` to prove `[Nonempty (α → β)]`. -/
theorem exists_measurable_piecewise {ι} [Countable ι] [Nonempty ι] (t : ι → Set α)
(t_meas : ∀ n, MeasurableSet (t n)) (g : ι → α → β) (hg : ∀ n, Measurable (g n))
(ht : Pairwise fun i j => EqOn (g i) (g j) (t i ∩ t j)) :
∃ f : α → β, Measurable f ∧ ∀ n, EqOn f (g n) (t n) := by
inhabit ι
set g' : (i : ι) → t i → β := fun i => g i ∘ (↑)
-- see #2184
have ht' : ∀ (i j) (x : α) (hxi : x ∈ t i) (hxj : x ∈ t j), g' i ⟨x, hxi⟩ = g' j ⟨x, hxj⟩ := by
intro i j x hxi hxj
rcases eq_or_ne i j with rfl | hij
· rfl
· exact ht hij ⟨hxi, hxj⟩
set f : (⋃ i, t i) → β := iUnionLift t g' ht' _ Subset.rfl
have hfm : Measurable f := measurable_iUnionLift _ _ t_meas
(fun i => (hg i).comp measurable_subtype_coe)
classical
refine ⟨fun x => if hx : x ∈ ⋃ i, t i then f ⟨x, hx⟩ else g default x,
hfm.dite ((hg default).comp measurable_subtype_coe) (.iUnion t_meas), fun i x hx => ?_⟩
simp only [dif_pos (mem_iUnion.2 ⟨i, hx⟩)]
exact iUnionLift_of_mem ⟨x, mem_iUnion.2 ⟨i, hx⟩⟩ hx
/-- Given countably many disjoint measurable sets `t n` and countably many measurable
functions `g n`, one can construct a measurable function that coincides with `g n` on `t n`. -/
@[deprecated exists_measurable_piecewise (since := "2023-02-11")]
theorem exists_measurable_piecewise_nat {m : MeasurableSpace α} (t : ℕ → Set β)
(t_meas : ∀ n, MeasurableSet (t n)) (t_disj : Pairwise (Disjoint on t)) (g : ℕ → β → α)
(hg : ∀ n, Measurable (g n)) : ∃ f : β → α, Measurable f ∧ ∀ n x, x ∈ t n → f x = g n x :=
exists_measurable_piecewise t t_meas g hg <| t_disj.mono fun i j h => by
simp only [h.inter_eq, eqOn_empty]
#align exists_measurable_piecewise_nat exists_measurable_piecewise_nat
end Prod
section Pi
variable {π : δ → Type*} [MeasurableSpace α]
instance MeasurableSpace.pi [m : ∀ a, MeasurableSpace (π a)] : MeasurableSpace (∀ a, π a) :=
⨆ a, (m a).comap fun b => b a
#align measurable_space.pi MeasurableSpace.pi
variable [∀ a, MeasurableSpace (π a)] [MeasurableSpace γ]
theorem measurable_pi_iff {g : α → ∀ a, π a} : Measurable g ↔ ∀ a, Measurable fun x => g x a := by
simp_rw [measurable_iff_comap_le, MeasurableSpace.pi, MeasurableSpace.comap_iSup,
MeasurableSpace.comap_comp, Function.comp, iSup_le_iff]
#align measurable_pi_iff measurable_pi_iff
@[aesop safe 100 apply (rule_sets := [Measurable])]
theorem measurable_pi_apply (a : δ) : Measurable fun f : ∀ a, π a => f a :=
measurable_pi_iff.1 measurable_id a
#align measurable_pi_apply measurable_pi_apply
@[aesop safe 100 apply (rule_sets := [Measurable])]
theorem Measurable.eval {a : δ} {g : α → ∀ a, π a} (hg : Measurable g) :
Measurable fun x => g x a :=
(measurable_pi_apply a).comp hg
#align measurable.eval Measurable.eval
@[aesop safe 100 apply (rule_sets := [Measurable])]
theorem measurable_pi_lambda (f : α → ∀ a, π a) (hf : ∀ a, Measurable fun c => f c a) :
Measurable f :=
measurable_pi_iff.mpr hf
#align measurable_pi_lambda measurable_pi_lambda
/-- The function `(f, x) ↦ update f a x : (Π a, π a) × π a → Π a, π a` is measurable. -/
theorem measurable_update' {a : δ} [DecidableEq δ] :
Measurable (fun p : (∀ i, π i) × π a ↦ update p.1 a p.2) := by
rw [measurable_pi_iff]
intro j
dsimp [update]
split_ifs with h
· subst h
dsimp
exact measurable_snd
· exact measurable_pi_iff.1 measurable_fst _
theorem measurable_uniqueElim [Unique δ] [∀ i, MeasurableSpace (π i)] :
Measurable (uniqueElim : π (default : δ) → ∀ i, π i) := by
simp_rw [measurable_pi_iff, Unique.forall_iff, uniqueElim_default]; exact measurable_id
theorem measurable_updateFinset [DecidableEq δ] {s : Finset δ} {x : ∀ i, π i} :
Measurable (updateFinset x s) := by
simp (config := { unfoldPartialApp := true }) only [updateFinset, measurable_pi_iff]
intro i
by_cases h : i ∈ s <;> simp [h, measurable_pi_apply]
/-- The function `update f a : π a → Π a, π a` is always measurable.
This doesn't require `f` to be measurable.
This should not be confused with the statement that `update f a x` is measurable. -/
@[measurability]
theorem measurable_update (f : ∀ a : δ, π a) {a : δ} [DecidableEq δ] : Measurable (update f a) :=
measurable_update'.comp measurable_prod_mk_left
#align measurable_update measurable_update
theorem measurable_update_left {a : δ} [DecidableEq δ] {x : π a} :
Measurable (update · a x) :=
measurable_update'.comp measurable_prod_mk_right
variable (π) in
theorem measurable_eq_mp {i i' : δ} (h : i = i') : Measurable (congr_arg π h).mp := by
cases h
exact measurable_id
variable (π) in
theorem Measurable.eq_mp {β} [MeasurableSpace β] {i i' : δ} (h : i = i') {f : β → π i}
(hf : Measurable f) : Measurable fun x => (congr_arg π h).mp (f x) :=
(measurable_eq_mp π h).comp hf
theorem measurable_piCongrLeft (f : δ' ≃ δ) : Measurable (piCongrLeft π f) := by
rw [measurable_pi_iff]
intro i
simp_rw [piCongrLeft_apply_eq_cast]
exact Measurable.eq_mp π (f.apply_symm_apply i) <| measurable_pi_apply <| f.symm i
/- Even though we cannot use projection notation, we still keep a dot to be consistent with similar
lemmas, like `MeasurableSet.prod`. -/
@[measurability]
protected theorem MeasurableSet.pi {s : Set δ} {t : ∀ i : δ, Set (π i)} (hs : s.Countable)
(ht : ∀ i ∈ s, MeasurableSet (t i)) : MeasurableSet (s.pi t) := by
rw [pi_def]
exact MeasurableSet.biInter hs fun i hi => measurable_pi_apply _ (ht i hi)
#align measurable_set.pi MeasurableSet.pi
protected theorem MeasurableSet.univ_pi [Countable δ] {t : ∀ i : δ, Set (π i)}
(ht : ∀ i, MeasurableSet (t i)) : MeasurableSet (pi univ t) :=
MeasurableSet.pi (to_countable _) fun i _ => ht i
#align measurable_set.univ_pi MeasurableSet.univ_pi
theorem measurableSet_pi_of_nonempty {s : Set δ} {t : ∀ i, Set (π i)} (hs : s.Countable)
(h : (pi s t).Nonempty) : MeasurableSet (pi s t) ↔ ∀ i ∈ s, MeasurableSet (t i) := by
classical
rcases h with ⟨f, hf⟩
refine ⟨fun hst i hi => ?_, MeasurableSet.pi hs⟩
convert measurable_update f (a := i) hst
rw [update_preimage_pi hi]
exact fun j hj _ => hf j hj
#align measurable_set_pi_of_nonempty measurableSet_pi_of_nonempty
theorem measurableSet_pi {s : Set δ} {t : ∀ i, Set (π i)} (hs : s.Countable) :
MeasurableSet (pi s t) ↔ (∀ i ∈ s, MeasurableSet (t i)) ∨ pi s t = ∅ := by
rcases (pi s t).eq_empty_or_nonempty with h | h
· simp [h]
· simp [measurableSet_pi_of_nonempty hs, h, ← not_nonempty_iff_eq_empty]
#align measurable_set_pi measurableSet_pi
instance Pi.instMeasurableSingletonClass [Countable δ] [∀ a, MeasurableSingletonClass (π a)] :
MeasurableSingletonClass (∀ a, π a) :=
⟨fun f => univ_pi_singleton f ▸ MeasurableSet.univ_pi fun t => measurableSet_singleton (f t)⟩
#align pi.measurable_singleton_class Pi.instMeasurableSingletonClass
variable (π)
@[measurability]
theorem measurable_piEquivPiSubtypeProd_symm (p : δ → Prop) [DecidablePred p] :
Measurable (Equiv.piEquivPiSubtypeProd p π).symm := by
refine measurable_pi_iff.2 fun j => ?_
by_cases hj : p j
· simp only [hj, dif_pos, Equiv.piEquivPiSubtypeProd_symm_apply]
have : Measurable fun (f : ∀ i : { x // p x }, π i.1) => f ⟨j, hj⟩ :=
measurable_pi_apply (π := fun i : {x // p x} => π i.1) ⟨j, hj⟩
exact Measurable.comp this measurable_fst
· simp only [hj, Equiv.piEquivPiSubtypeProd_symm_apply, dif_neg, not_false_iff]
have : Measurable fun (f : ∀ i : { x // ¬p x }, π i.1) => f ⟨j, hj⟩ :=
measurable_pi_apply (π := fun i : {x // ¬p x} => π i.1) ⟨j, hj⟩
exact Measurable.comp this measurable_snd
#align measurable_pi_equiv_pi_subtype_prod_symm measurable_piEquivPiSubtypeProd_symm
@[measurability]
theorem measurable_piEquivPiSubtypeProd (p : δ → Prop) [DecidablePred p] :
Measurable (Equiv.piEquivPiSubtypeProd p π) :=
(measurable_pi_iff.2 fun _ => measurable_pi_apply _).prod_mk
(measurable_pi_iff.2 fun _ => measurable_pi_apply _)
#align measurable_pi_equiv_pi_subtype_prod measurable_piEquivPiSubtypeProd
end Pi
instance TProd.instMeasurableSpace (π : δ → Type*) [∀ x, MeasurableSpace (π x)] :
∀ l : List δ, MeasurableSpace (List.TProd π l)
| [] => PUnit.instMeasurableSpace
| _::is => @Prod.instMeasurableSpace _ _ _ (TProd.instMeasurableSpace π is)
#align tprod.measurable_space TProd.instMeasurableSpace
section TProd
open List
variable {π : δ → Type*} [∀ x, MeasurableSpace (π x)]
theorem measurable_tProd_mk (l : List δ) : Measurable (@TProd.mk δ π l) := by
induction' l with i l ih
· exact measurable_const
· exact (measurable_pi_apply i).prod_mk ih
#align measurable_tprod_mk measurable_tProd_mk
theorem measurable_tProd_elim [DecidableEq δ] :
∀ {l : List δ} {i : δ} (hi : i ∈ l), Measurable fun v : TProd π l => v.elim hi
| i::is, j, hj => by
by_cases hji : j = i
· subst hji
simpa using measurable_fst
· simp only [TProd.elim_of_ne _ hji]
rw [mem_cons] at hj
exact (measurable_tProd_elim (hj.resolve_left hji)).comp measurable_snd
#align measurable_tprod_elim measurable_tProd_elim
theorem measurable_tProd_elim' [DecidableEq δ] {l : List δ} (h : ∀ i, i ∈ l) :
Measurable (TProd.elim' h : TProd π l → ∀ i, π i) :=
measurable_pi_lambda _ fun i => measurable_tProd_elim (h i)
#align measurable_tprod_elim' measurable_tProd_elim'
theorem MeasurableSet.tProd (l : List δ) {s : ∀ i, Set (π i)} (hs : ∀ i, MeasurableSet (s i)) :
MeasurableSet (Set.tprod l s) := by
induction' l with i l ih
· exact MeasurableSet.univ
· exact (hs i).prod ih
#align measurable_set.tprod MeasurableSet.tProd
end TProd
instance Sum.instMeasurableSpace {α β} [m₁ : MeasurableSpace α] [m₂ : MeasurableSpace β] :
MeasurableSpace (α ⊕ β) :=
m₁.map Sum.inl ⊓ m₂.map Sum.inr
#align sum.measurable_space Sum.instMeasurableSpace
section Sum
@[measurability]
theorem measurable_inl [MeasurableSpace α] [MeasurableSpace β] : Measurable (@Sum.inl α β) :=
Measurable.of_le_map inf_le_left
#align measurable_inl measurable_inl
@[measurability]
theorem measurable_inr [MeasurableSpace α] [MeasurableSpace β] : Measurable (@Sum.inr α β) :=
Measurable.of_le_map inf_le_right
#align measurable_inr measurable_inr
variable {m : MeasurableSpace α} {mβ : MeasurableSpace β}
-- Porting note (#10756): new theorem
theorem measurableSet_sum_iff {s : Set (α ⊕ β)} :
MeasurableSet s ↔ MeasurableSet (Sum.inl ⁻¹' s) ∧ MeasurableSet (Sum.inr ⁻¹' s) :=
Iff.rfl
theorem measurable_sum {_ : MeasurableSpace γ} {f : α ⊕ β → γ} (hl : Measurable (f ∘ Sum.inl))
(hr : Measurable (f ∘ Sum.inr)) : Measurable f :=
Measurable.of_comap_le <|
le_inf (MeasurableSpace.comap_le_iff_le_map.2 <| hl)
(MeasurableSpace.comap_le_iff_le_map.2 <| hr)
#align measurable_sum measurable_sum
@[measurability]
theorem Measurable.sumElim {_ : MeasurableSpace γ} {f : α → γ} {g : β → γ} (hf : Measurable f)
(hg : Measurable g) : Measurable (Sum.elim f g) :=
measurable_sum hf hg
#align measurable.sum_elim Measurable.sumElim
theorem Measurable.sumMap {_ : MeasurableSpace γ} {_ : MeasurableSpace δ} {f : α → β} {g : γ → δ}
(hf : Measurable f) (hg : Measurable g) : Measurable (Sum.map f g) :=
(measurable_inl.comp hf).sumElim (measurable_inr.comp hg)
-- Porting note (#10756): new theorem
@[simp] theorem measurableSet_inl_image {s : Set α} :
MeasurableSet (Sum.inl '' s : Set (α ⊕ β)) ↔ MeasurableSet s := by
simp [measurableSet_sum_iff, Sum.inl_injective.preimage_image]
alias ⟨_, MeasurableSet.inl_image⟩ := measurableSet_inl_image
#align measurable_set.inl_image MeasurableSet.inl_image
-- Porting note (#10756): new theorem
@[simp] theorem measurableSet_inr_image {s : Set β} :
MeasurableSet (Sum.inr '' s : Set (α ⊕ β)) ↔ MeasurableSet s := by
simp [measurableSet_sum_iff, Sum.inr_injective.preimage_image]
alias ⟨_, MeasurableSet.inr_image⟩ := measurableSet_inr_image
#align measurable_set_inr_image measurableSet_inr_image
theorem measurableSet_range_inl [MeasurableSpace α] :
MeasurableSet (range Sum.inl : Set (α ⊕ β)) := by
rw [← image_univ]
exact MeasurableSet.univ.inl_image
#align measurable_set_range_inl measurableSet_range_inl
theorem measurableSet_range_inr [MeasurableSpace α] :
MeasurableSet (range Sum.inr : Set (α ⊕ β)) := by
rw [← image_univ]
exact MeasurableSet.univ.inr_image
#align measurable_set_range_inr measurableSet_range_inr
end Sum
instance Sigma.instMeasurableSpace {α} {β : α → Type*} [m : ∀ a, MeasurableSpace (β a)] :
MeasurableSpace (Sigma β) :=
⨅ a, (m a).map (Sigma.mk a)
#align sigma.measurable_space Sigma.instMeasurableSpace
section prop
variable [MeasurableSpace α] {p q : α → Prop}
@[simp] theorem measurableSet_setOf : MeasurableSet {a | p a} ↔ Measurable p :=
⟨fun h ↦ measurable_to_prop <| by simpa only [preimage_singleton_true], fun h => by
simpa using h (measurableSet_singleton True)⟩
#align measurable_set_set_of measurableSet_setOf
@[simp] theorem measurable_mem : Measurable (· ∈ s) ↔ MeasurableSet s := measurableSet_setOf.symm
#align measurable_mem measurable_mem
alias ⟨_, Measurable.setOf⟩ := measurableSet_setOf
#align measurable.set_of Measurable.setOf
alias ⟨_, MeasurableSet.mem⟩ := measurable_mem
#align measurable_set.mem MeasurableSet.mem
lemma Measurable.not (hp : Measurable p) : Measurable (¬ p ·) :=
measurableSet_setOf.1 hp.setOf.compl
lemma Measurable.and (hp : Measurable p) (hq : Measurable q) : Measurable fun a ↦ p a ∧ q a :=
measurableSet_setOf.1 <| hp.setOf.inter hq.setOf
lemma Measurable.or (hp : Measurable p) (hq : Measurable q) : Measurable fun a ↦ p a ∨ q a :=
measurableSet_setOf.1 <| hp.setOf.union hq.setOf
lemma Measurable.imp (hp : Measurable p) (hq : Measurable q) : Measurable fun a ↦ p a → q a :=
measurableSet_setOf.1 <| hp.setOf.himp hq.setOf
lemma Measurable.iff (hp : Measurable p) (hq : Measurable q) : Measurable fun a ↦ p a ↔ q a :=
measurableSet_setOf.1 <| by simp_rw [iff_iff_implies_and_implies]; exact hq.setOf.bihimp hp.setOf
lemma Measurable.forall [Countable ι] {p : ι → α → Prop} (hp : ∀ i, Measurable (p i)) :
Measurable fun a ↦ ∀ i, p i a :=
measurableSet_setOf.1 <| by rw [setOf_forall]; exact MeasurableSet.iInter fun i ↦ (hp i).setOf
lemma Measurable.exists [Countable ι] {p : ι → α → Prop} (hp : ∀ i, Measurable (p i)) :
Measurable fun a ↦ ∃ i, p i a :=
measurableSet_setOf.1 <| by rw [setOf_exists]; exact MeasurableSet.iUnion fun i ↦ (hp i).setOf
end prop
section Set
variable [MeasurableSpace β] {g : β → Set α}
/-- This instance is useful when talking about Bernoulli sequences of random variables or binomial
random graphs. -/
instance Set.instMeasurableSpace : MeasurableSpace (Set α) := by unfold Set; infer_instance
instance Set.instMeasurableSingletonClass [Countable α] : MeasurableSingletonClass (Set α) := by
unfold Set; infer_instance
lemma measurable_set_iff : Measurable g ↔ ∀ a, Measurable fun x ↦ a ∈ g x := measurable_pi_iff
@[aesop safe 100 apply (rule_sets := [Measurable])]
lemma measurable_set_mem (a : α) : Measurable fun s : Set α ↦ a ∈ s := measurable_pi_apply _
@[aesop safe 100 apply (rule_sets := [Measurable])]
lemma measurable_set_not_mem (a : α) : Measurable fun s : Set α ↦ a ∉ s :=
(measurable_discrete Not).comp <| measurable_set_mem a
@[aesop safe 100 apply (rule_sets := [Measurable])]
lemma measurableSet_mem (a : α) : MeasurableSet {s : Set α | a ∈ s} :=
measurableSet_setOf.2 <| measurable_set_mem _
@[aesop safe 100 apply (rule_sets := [Measurable])]
lemma measurableSet_not_mem (a : α) : MeasurableSet {s : Set α | a ∉ s} :=
measurableSet_setOf.2 <| measurable_set_not_mem _
lemma measurable_compl : Measurable ((·ᶜ) : Set α → Set α) :=
measurable_set_iff.2 fun _ ↦ measurable_set_not_mem _
end Set
end Constructions
namespace MeasurableSpace
/-- The sigma-algebra generated by a single set `s` is `{∅, s, sᶜ, univ}`. -/
@[simp] theorem generateFrom_singleton (s : Set α) :
generateFrom {s} = MeasurableSpace.comap (· ∈ s) ⊤ := by
classical
letI : MeasurableSpace α := generateFrom {s}
refine le_antisymm (generateFrom_le fun t ht => ⟨{True}, trivial, by simp [ht.symm]⟩) ?_
rintro _ ⟨u, -, rfl⟩
exact (show MeasurableSet s from GenerateMeasurable.basic _ <| mem_singleton s).mem trivial
#align measurable_space.generate_from_singleton MeasurableSpace.generateFrom_singleton
end MeasurableSpace
/-- A map `f : α → β` is called a *measurable embedding* if it is injective, measurable, and sends
measurable sets to measurable sets. The latter assumption can be replaced with “`f` has measurable
inverse `g : Set.range f → α`”, see `MeasurableEmbedding.measurable_rangeSplitting`,
`MeasurableEmbedding.of_measurable_inverse_range`, and
`MeasurableEmbedding.of_measurable_inverse`.
One more interpretation: `f` is a measurable embedding if it defines a measurable equivalence to its
range and the range is a measurable set. One implication is formalized as
`MeasurableEmbedding.equivRange`; the other one follows from
`MeasurableEquiv.measurableEmbedding`, `MeasurableEmbedding.subtype_coe`, and
`MeasurableEmbedding.comp`. -/
structure MeasurableEmbedding {α β : Type*} [MeasurableSpace α] [MeasurableSpace β]
(f : α → β) : Prop where
/-- A measurable embedding is injective. -/
protected injective : Injective f
/-- A measurable embedding is a measurable function. -/
protected measurable : Measurable f
/-- The image of a measurable set under a measurable embedding is a measurable set. -/
protected measurableSet_image' : ∀ ⦃s⦄, MeasurableSet s → MeasurableSet (f '' s)
#align measurable_embedding MeasurableEmbedding
namespace MeasurableEmbedding
variable {mα : MeasurableSpace α} [MeasurableSpace β] [MeasurableSpace γ] {f : α → β} {g : β → γ}
theorem measurableSet_image (hf : MeasurableEmbedding f) {s : Set α} :
MeasurableSet (f '' s) ↔ MeasurableSet s :=
⟨fun h => by simpa only [hf.injective.preimage_image] using hf.measurable h, fun h =>
hf.measurableSet_image' h⟩
#align measurable_embedding.measurable_set_image MeasurableEmbedding.measurableSet_image
theorem id : MeasurableEmbedding (id : α → α) :=
⟨injective_id, measurable_id, fun s hs => by rwa [image_id]⟩
#align measurable_embedding.id MeasurableEmbedding.id
theorem comp (hg : MeasurableEmbedding g) (hf : MeasurableEmbedding f) :
MeasurableEmbedding (g ∘ f) :=
⟨hg.injective.comp hf.injective, hg.measurable.comp hf.measurable, fun s hs => by
rwa [image_comp, hg.measurableSet_image, hf.measurableSet_image]⟩
#align measurable_embedding.comp MeasurableEmbedding.comp
theorem subtype_coe {s : Set α} (hs : MeasurableSet s) : MeasurableEmbedding ((↑) : s → α) where
injective := Subtype.coe_injective
measurable := measurable_subtype_coe
measurableSet_image' := fun _ => MeasurableSet.subtype_image hs
#align measurable_embedding.subtype_coe MeasurableEmbedding.subtype_coe
theorem measurableSet_range (hf : MeasurableEmbedding f) : MeasurableSet (range f) := by
rw [← image_univ]
exact hf.measurableSet_image' MeasurableSet.univ
#align measurable_embedding.measurable_set_range MeasurableEmbedding.measurableSet_range
| Mathlib/MeasureTheory/MeasurableSpace/Basic.lean | 1,354 | 1,356 | theorem measurableSet_preimage (hf : MeasurableEmbedding f) {s : Set β} :
MeasurableSet (f ⁻¹' s) ↔ MeasurableSet (s ∩ range f) := by |
rw [← image_preimage_eq_inter_range, hf.measurableSet_image]
|
/-
Copyright (c) 2021 Yourong Zang. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yourong Zang, Yury Kudryashov
-/
import Mathlib.Data.Fintype.Option
import Mathlib.Topology.Separation
import Mathlib.Topology.Sets.Opens
#align_import topology.alexandroff from "leanprover-community/mathlib"@"dc6c365e751e34d100e80fe6e314c3c3e0fd2988"
/-!
# The OnePoint Compactification
We construct the OnePoint compactification (the one-point compactification) of an arbitrary
topological space `X` and prove some properties inherited from `X`.
## Main definitions
* `OnePoint`: the OnePoint compactification, we use coercion for the canonical embedding
`X → OnePoint X`; when `X` is already compact, the compactification adds an isolated point
to the space.
* `OnePoint.infty`: the extra point
## Main results
* The topological structure of `OnePoint X`
* The connectedness of `OnePoint X` for a noncompact, preconnected `X`
* `OnePoint X` is `T₀` for a T₀ space `X`
* `OnePoint X` is `T₁` for a T₁ space `X`
* `OnePoint X` is normal if `X` is a locally compact Hausdorff space
## Tags
one-point compactification, compactness
-/
open Set Filter Topology
/-!
### Definition and basic properties
In this section we define `OnePoint X` to be the disjoint union of `X` and `∞`, implemented as
`Option X`. Then we restate some lemmas about `Option X` for `OnePoint X`.
-/
variable {X : Type*}
/-- The OnePoint extension of an arbitrary topological space `X` -/
def OnePoint (X : Type*) :=
Option X
#align alexandroff OnePoint
/-- The repr uses the notation from the `OnePoint` locale. -/
instance [Repr X] : Repr (OnePoint X) :=
⟨fun o _ =>
match o with
| none => "∞"
| some a => "↑" ++ repr a⟩
namespace OnePoint
/-- The point at infinity -/
@[match_pattern] def infty : OnePoint X := none
#align alexandroff.infty OnePoint.infty
@[inherit_doc]
scoped notation "∞" => OnePoint.infty
/-- Coercion from `X` to `OnePoint X`. -/
@[coe, match_pattern] def some : X → OnePoint X := Option.some
instance : CoeTC X (OnePoint X) := ⟨some⟩
instance : Inhabited (OnePoint X) := ⟨∞⟩
instance [Fintype X] : Fintype (OnePoint X) :=
inferInstanceAs (Fintype (Option X))
instance infinite [Infinite X] : Infinite (OnePoint X) :=
inferInstanceAs (Infinite (Option X))
#align alexandroff.infinite OnePoint.infinite
theorem coe_injective : Function.Injective ((↑) : X → OnePoint X) :=
Option.some_injective X
#align alexandroff.coe_injective OnePoint.coe_injective
@[norm_cast]
theorem coe_eq_coe {x y : X} : (x : OnePoint X) = y ↔ x = y :=
coe_injective.eq_iff
#align alexandroff.coe_eq_coe OnePoint.coe_eq_coe
@[simp]
theorem coe_ne_infty (x : X) : (x : OnePoint X) ≠ ∞ :=
nofun
#align alexandroff.coe_ne_infty OnePoint.coe_ne_infty
@[simp]
theorem infty_ne_coe (x : X) : ∞ ≠ (x : OnePoint X) :=
nofun
#align alexandroff.infty_ne_coe OnePoint.infty_ne_coe
/-- Recursor for `OnePoint` using the preferred forms `∞` and `↑x`. -/
@[elab_as_elim]
protected def rec {C : OnePoint X → Sort*} (h₁ : C ∞) (h₂ : ∀ x : X, C x) :
∀ z : OnePoint X, C z
| ∞ => h₁
| (x : X) => h₂ x
#align alexandroff.rec OnePoint.rec
theorem isCompl_range_coe_infty : IsCompl (range ((↑) : X → OnePoint X)) {∞} :=
isCompl_range_some_none X
#align alexandroff.is_compl_range_coe_infty OnePoint.isCompl_range_coe_infty
-- Porting note: moved @[simp] to a new lemma
theorem range_coe_union_infty : range ((↑) : X → OnePoint X) ∪ {∞} = univ :=
range_some_union_none X
#align alexandroff.range_coe_union_infty OnePoint.range_coe_union_infty
@[simp]
theorem insert_infty_range_coe : insert ∞ (range (@some X)) = univ :=
insert_none_range_some _
@[simp]
theorem range_coe_inter_infty : range ((↑) : X → OnePoint X) ∩ {∞} = ∅ :=
range_some_inter_none X
#align alexandroff.range_coe_inter_infty OnePoint.range_coe_inter_infty
@[simp]
theorem compl_range_coe : (range ((↑) : X → OnePoint X))ᶜ = {∞} :=
compl_range_some X
#align alexandroff.compl_range_coe OnePoint.compl_range_coe
theorem compl_infty : ({∞}ᶜ : Set (OnePoint X)) = range ((↑) : X → OnePoint X) :=
(@isCompl_range_coe_infty X).symm.compl_eq
#align alexandroff.compl_infty OnePoint.compl_infty
theorem compl_image_coe (s : Set X) : ((↑) '' s : Set (OnePoint X))ᶜ = (↑) '' sᶜ ∪ {∞} := by
rw [coe_injective.compl_image_eq, compl_range_coe]
#align alexandroff.compl_image_coe OnePoint.compl_image_coe
theorem ne_infty_iff_exists {x : OnePoint X} : x ≠ ∞ ↔ ∃ y : X, (y : OnePoint X) = x := by
induction x using OnePoint.rec <;> simp
#align alexandroff.ne_infty_iff_exists OnePoint.ne_infty_iff_exists
instance canLift : CanLift (OnePoint X) X (↑) fun x => x ≠ ∞ :=
WithTop.canLift
#align alexandroff.can_lift OnePoint.canLift
theorem not_mem_range_coe_iff {x : OnePoint X} : x ∉ range some ↔ x = ∞ := by
rw [← mem_compl_iff, compl_range_coe, mem_singleton_iff]
#align alexandroff.not_mem_range_coe_iff OnePoint.not_mem_range_coe_iff
theorem infty_not_mem_range_coe : ∞ ∉ range ((↑) : X → OnePoint X) :=
not_mem_range_coe_iff.2 rfl
#align alexandroff.infty_not_mem_range_coe OnePoint.infty_not_mem_range_coe
theorem infty_not_mem_image_coe {s : Set X} : ∞ ∉ ((↑) : X → OnePoint X) '' s :=
not_mem_subset (image_subset_range _ _) infty_not_mem_range_coe
#align alexandroff.infty_not_mem_image_coe OnePoint.infty_not_mem_image_coe
@[simp]
theorem coe_preimage_infty : ((↑) : X → OnePoint X) ⁻¹' {∞} = ∅ := by
ext
simp
#align alexandroff.coe_preimage_infty OnePoint.coe_preimage_infty
/-!
### Topological space structure on `OnePoint X`
We define a topological space structure on `OnePoint X` so that `s` is open if and only if
* `(↑) ⁻¹' s` is open in `X`;
* if `∞ ∈ s`, then `((↑) ⁻¹' s)ᶜ` is compact.
Then we reformulate this definition in a few different ways, and prove that
`(↑) : X → OnePoint X` is an open embedding. If `X` is not a compact space, then we also prove
that `(↑)` has dense range, so it is a dense embedding.
-/
variable [TopologicalSpace X]
instance : TopologicalSpace (OnePoint X) where
IsOpen s := (∞ ∈ s → IsCompact (((↑) : X → OnePoint X) ⁻¹' s)ᶜ) ∧
IsOpen (((↑) : X → OnePoint X) ⁻¹' s)
isOpen_univ := by simp
isOpen_inter s t := by
rintro ⟨hms, hs⟩ ⟨hmt, ht⟩
refine ⟨?_, hs.inter ht⟩
rintro ⟨hms', hmt'⟩
simpa [compl_inter] using (hms hms').union (hmt hmt')
isOpen_sUnion S ho := by
suffices IsOpen ((↑) ⁻¹' ⋃₀ S : Set X) by
refine ⟨?_, this⟩
rintro ⟨s, hsS : s ∈ S, hs : ∞ ∈ s⟩
refine IsCompact.of_isClosed_subset ((ho s hsS).1 hs) this.isClosed_compl ?_
exact compl_subset_compl.mpr (preimage_mono <| subset_sUnion_of_mem hsS)
rw [preimage_sUnion]
exact isOpen_biUnion fun s hs => (ho s hs).2
variable {s : Set (OnePoint X)} {t : Set X}
theorem isOpen_def :
IsOpen s ↔ (∞ ∈ s → IsCompact ((↑) ⁻¹' s : Set X)ᶜ) ∧ IsOpen ((↑) ⁻¹' s : Set X) :=
Iff.rfl
#align alexandroff.is_open_def OnePoint.isOpen_def
theorem isOpen_iff_of_mem' (h : ∞ ∈ s) :
IsOpen s ↔ IsCompact ((↑) ⁻¹' s : Set X)ᶜ ∧ IsOpen ((↑) ⁻¹' s : Set X) := by
simp [isOpen_def, h]
#align alexandroff.is_open_iff_of_mem' OnePoint.isOpen_iff_of_mem'
theorem isOpen_iff_of_mem (h : ∞ ∈ s) :
IsOpen s ↔ IsClosed ((↑) ⁻¹' s : Set X)ᶜ ∧ IsCompact ((↑) ⁻¹' s : Set X)ᶜ := by
simp only [isOpen_iff_of_mem' h, isClosed_compl_iff, and_comm]
#align alexandroff.is_open_iff_of_mem OnePoint.isOpen_iff_of_mem
theorem isOpen_iff_of_not_mem (h : ∞ ∉ s) : IsOpen s ↔ IsOpen ((↑) ⁻¹' s : Set X) := by
simp [isOpen_def, h]
#align alexandroff.is_open_iff_of_not_mem OnePoint.isOpen_iff_of_not_mem
theorem isClosed_iff_of_mem (h : ∞ ∈ s) : IsClosed s ↔ IsClosed ((↑) ⁻¹' s : Set X) := by
have : ∞ ∉ sᶜ := fun H => H h
rw [← isOpen_compl_iff, isOpen_iff_of_not_mem this, ← isOpen_compl_iff, preimage_compl]
#align alexandroff.is_closed_iff_of_mem OnePoint.isClosed_iff_of_mem
theorem isClosed_iff_of_not_mem (h : ∞ ∉ s) :
IsClosed s ↔ IsClosed ((↑) ⁻¹' s : Set X) ∧ IsCompact ((↑) ⁻¹' s : Set X) := by
rw [← isOpen_compl_iff, isOpen_iff_of_mem (mem_compl h), ← preimage_compl, compl_compl]
#align alexandroff.is_closed_iff_of_not_mem OnePoint.isClosed_iff_of_not_mem
@[simp]
theorem isOpen_image_coe {s : Set X} : IsOpen ((↑) '' s : Set (OnePoint X)) ↔ IsOpen s := by
rw [isOpen_iff_of_not_mem infty_not_mem_image_coe, preimage_image_eq _ coe_injective]
#align alexandroff.is_open_image_coe OnePoint.isOpen_image_coe
theorem isOpen_compl_image_coe {s : Set X} :
IsOpen ((↑) '' s : Set (OnePoint X))ᶜ ↔ IsClosed s ∧ IsCompact s := by
rw [isOpen_iff_of_mem, ← preimage_compl, compl_compl, preimage_image_eq _ coe_injective]
exact infty_not_mem_image_coe
#align alexandroff.is_open_compl_image_coe OnePoint.isOpen_compl_image_coe
@[simp]
theorem isClosed_image_coe {s : Set X} :
IsClosed ((↑) '' s : Set (OnePoint X)) ↔ IsClosed s ∧ IsCompact s := by
rw [← isOpen_compl_iff, isOpen_compl_image_coe]
#align alexandroff.is_closed_image_coe OnePoint.isClosed_image_coe
/-- An open set in `OnePoint X` constructed from a closed compact set in `X` -/
def opensOfCompl (s : Set X) (h₁ : IsClosed s) (h₂ : IsCompact s) :
TopologicalSpace.Opens (OnePoint X) :=
⟨((↑) '' s)ᶜ, isOpen_compl_image_coe.2 ⟨h₁, h₂⟩⟩
#align alexandroff.opens_of_compl OnePoint.opensOfCompl
theorem infty_mem_opensOfCompl {s : Set X} (h₁ : IsClosed s) (h₂ : IsCompact s) :
∞ ∈ opensOfCompl s h₁ h₂ :=
mem_compl infty_not_mem_image_coe
#align alexandroff.infty_mem_opens_of_compl OnePoint.infty_mem_opensOfCompl
@[continuity]
theorem continuous_coe : Continuous ((↑) : X → OnePoint X) :=
continuous_def.mpr fun _s hs => hs.right
#align alexandroff.continuous_coe OnePoint.continuous_coe
theorem isOpenMap_coe : IsOpenMap ((↑) : X → OnePoint X) := fun _ => isOpen_image_coe.2
#align alexandroff.is_open_map_coe OnePoint.isOpenMap_coe
theorem openEmbedding_coe : OpenEmbedding ((↑) : X → OnePoint X) :=
openEmbedding_of_continuous_injective_open continuous_coe coe_injective isOpenMap_coe
#align alexandroff.open_embedding_coe OnePoint.openEmbedding_coe
theorem isOpen_range_coe : IsOpen (range ((↑) : X → OnePoint X)) :=
openEmbedding_coe.isOpen_range
#align alexandroff.is_open_range_coe OnePoint.isOpen_range_coe
theorem isClosed_infty : IsClosed ({∞} : Set (OnePoint X)) := by
rw [← compl_range_coe, isClosed_compl_iff]
exact isOpen_range_coe
#align alexandroff.is_closed_infty OnePoint.isClosed_infty
theorem nhds_coe_eq (x : X) : 𝓝 ↑x = map ((↑) : X → OnePoint X) (𝓝 x) :=
(openEmbedding_coe.map_nhds_eq x).symm
#align alexandroff.nhds_coe_eq OnePoint.nhds_coe_eq
theorem nhdsWithin_coe_image (s : Set X) (x : X) :
𝓝[(↑) '' s] (x : OnePoint X) = map (↑) (𝓝[s] x) :=
(openEmbedding_coe.toEmbedding.map_nhdsWithin_eq _ _).symm
#align alexandroff.nhds_within_coe_image OnePoint.nhdsWithin_coe_image
theorem nhdsWithin_coe (s : Set (OnePoint X)) (x : X) : 𝓝[s] ↑x = map (↑) (𝓝[(↑) ⁻¹' s] x) :=
(openEmbedding_coe.map_nhdsWithin_preimage_eq _ _).symm
#align alexandroff.nhds_within_coe OnePoint.nhdsWithin_coe
theorem comap_coe_nhds (x : X) : comap ((↑) : X → OnePoint X) (𝓝 x) = 𝓝 x :=
(openEmbedding_coe.toInducing.nhds_eq_comap x).symm
#align alexandroff.comap_coe_nhds OnePoint.comap_coe_nhds
/-- If `x` is not an isolated point of `X`, then `x : OnePoint X` is not an isolated point
of `OnePoint X`. -/
instance nhdsWithin_compl_coe_neBot (x : X) [h : NeBot (𝓝[≠] x)] :
NeBot (𝓝[≠] (x : OnePoint X)) := by
simpa [nhdsWithin_coe, preimage, coe_eq_coe] using h.map some
#align alexandroff.nhds_within_compl_coe_ne_bot OnePoint.nhdsWithin_compl_coe_neBot
theorem nhdsWithin_compl_infty_eq : 𝓝[≠] (∞ : OnePoint X) = map (↑) (coclosedCompact X) := by
refine (nhdsWithin_basis_open ∞ _).ext (hasBasis_coclosedCompact.map _) ?_ ?_
· rintro s ⟨hs, hso⟩
refine ⟨_, (isOpen_iff_of_mem hs).mp hso, ?_⟩
simp [Subset.rfl]
· rintro s ⟨h₁, h₂⟩
refine ⟨_, ⟨mem_compl infty_not_mem_image_coe, isOpen_compl_image_coe.2 ⟨h₁, h₂⟩⟩, ?_⟩
simp [compl_image_coe, ← diff_eq, subset_preimage_image]
#align alexandroff.nhds_within_compl_infty_eq OnePoint.nhdsWithin_compl_infty_eq
/-- If `X` is a non-compact space, then `∞` is not an isolated point of `OnePoint X`. -/
instance nhdsWithin_compl_infty_neBot [NoncompactSpace X] : NeBot (𝓝[≠] (∞ : OnePoint X)) := by
rw [nhdsWithin_compl_infty_eq]
infer_instance
#align alexandroff.nhds_within_compl_infty_ne_bot OnePoint.nhdsWithin_compl_infty_neBot
instance (priority := 900) nhdsWithin_compl_neBot [∀ x : X, NeBot (𝓝[≠] x)] [NoncompactSpace X]
(x : OnePoint X) : NeBot (𝓝[≠] x) :=
OnePoint.rec OnePoint.nhdsWithin_compl_infty_neBot
(fun y => OnePoint.nhdsWithin_compl_coe_neBot y) x
#align alexandroff.nhds_within_compl_ne_bot OnePoint.nhdsWithin_compl_neBot
theorem nhds_infty_eq : 𝓝 (∞ : OnePoint X) = map (↑) (coclosedCompact X) ⊔ pure ∞ := by
rw [← nhdsWithin_compl_infty_eq, nhdsWithin_compl_singleton_sup_pure]
#align alexandroff.nhds_infty_eq OnePoint.nhds_infty_eq
theorem hasBasis_nhds_infty :
(𝓝 (∞ : OnePoint X)).HasBasis (fun s : Set X => IsClosed s ∧ IsCompact s) fun s =>
(↑) '' sᶜ ∪ {∞} := by
rw [nhds_infty_eq]
exact (hasBasis_coclosedCompact.map _).sup_pure _
#align alexandroff.has_basis_nhds_infty OnePoint.hasBasis_nhds_infty
@[simp]
theorem comap_coe_nhds_infty : comap ((↑) : X → OnePoint X) (𝓝 ∞) = coclosedCompact X := by
simp [nhds_infty_eq, comap_sup, comap_map coe_injective]
#align alexandroff.comap_coe_nhds_infty OnePoint.comap_coe_nhds_infty
theorem le_nhds_infty {f : Filter (OnePoint X)} :
f ≤ 𝓝 ∞ ↔ ∀ s : Set X, IsClosed s → IsCompact s → (↑) '' sᶜ ∪ {∞} ∈ f := by
simp only [hasBasis_nhds_infty.ge_iff, and_imp]
#align alexandroff.le_nhds_infty OnePoint.le_nhds_infty
theorem ultrafilter_le_nhds_infty {f : Ultrafilter (OnePoint X)} :
(f : Filter (OnePoint X)) ≤ 𝓝 ∞ ↔ ∀ s : Set X, IsClosed s → IsCompact s → (↑) '' s ∉ f := by
simp only [le_nhds_infty, ← compl_image_coe, Ultrafilter.mem_coe,
Ultrafilter.compl_mem_iff_not_mem]
#align alexandroff.ultrafilter_le_nhds_infty OnePoint.ultrafilter_le_nhds_infty
theorem tendsto_nhds_infty' {α : Type*} {f : OnePoint X → α} {l : Filter α} :
Tendsto f (𝓝 ∞) l ↔ Tendsto f (pure ∞) l ∧ Tendsto (f ∘ (↑)) (coclosedCompact X) l := by
simp [nhds_infty_eq, and_comm]
#align alexandroff.tendsto_nhds_infty' OnePoint.tendsto_nhds_infty'
theorem tendsto_nhds_infty {α : Type*} {f : OnePoint X → α} {l : Filter α} :
Tendsto f (𝓝 ∞) l ↔
∀ s ∈ l, f ∞ ∈ s ∧ ∃ t : Set X, IsClosed t ∧ IsCompact t ∧ MapsTo (f ∘ (↑)) tᶜ s :=
tendsto_nhds_infty'.trans <| by
simp only [tendsto_pure_left, hasBasis_coclosedCompact.tendsto_left_iff, forall_and,
and_assoc, exists_prop]
#align alexandroff.tendsto_nhds_infty OnePoint.tendsto_nhds_infty
theorem continuousAt_infty' {Y : Type*} [TopologicalSpace Y] {f : OnePoint X → Y} :
ContinuousAt f ∞ ↔ Tendsto (f ∘ (↑)) (coclosedCompact X) (𝓝 (f ∞)) :=
tendsto_nhds_infty'.trans <| and_iff_right (tendsto_pure_nhds _ _)
#align alexandroff.continuous_at_infty' OnePoint.continuousAt_infty'
theorem continuousAt_infty {Y : Type*} [TopologicalSpace Y] {f : OnePoint X → Y} :
ContinuousAt f ∞ ↔
∀ s ∈ 𝓝 (f ∞), ∃ t : Set X, IsClosed t ∧ IsCompact t ∧ MapsTo (f ∘ (↑)) tᶜ s :=
continuousAt_infty'.trans <| by simp only [hasBasis_coclosedCompact.tendsto_left_iff, and_assoc]
#align alexandroff.continuous_at_infty OnePoint.continuousAt_infty
theorem continuousAt_coe {Y : Type*} [TopologicalSpace Y] {f : OnePoint X → Y} {x : X} :
ContinuousAt f x ↔ ContinuousAt (f ∘ (↑)) x := by
rw [ContinuousAt, nhds_coe_eq, tendsto_map'_iff, ContinuousAt]; rfl
#align alexandroff.continuous_at_coe OnePoint.continuousAt_coe
/-- If `X` is not a compact space, then the natural embedding `X → OnePoint X` has dense range.
-/
theorem denseRange_coe [NoncompactSpace X] : DenseRange ((↑) : X → OnePoint X) := by
rw [DenseRange, ← compl_infty]
exact dense_compl_singleton _
#align alexandroff.dense_range_coe OnePoint.denseRange_coe
theorem denseEmbedding_coe [NoncompactSpace X] : DenseEmbedding ((↑) : X → OnePoint X) :=
{ openEmbedding_coe with dense := denseRange_coe }
#align alexandroff.dense_embedding_coe OnePoint.denseEmbedding_coe
@[simp, norm_cast]
theorem specializes_coe {x y : X} : (x : OnePoint X) ⤳ y ↔ x ⤳ y :=
openEmbedding_coe.toInducing.specializes_iff
#align alexandroff.specializes_coe OnePoint.specializes_coe
@[simp, norm_cast]
theorem inseparable_coe {x y : X} : Inseparable (x : OnePoint X) y ↔ Inseparable x y :=
openEmbedding_coe.toInducing.inseparable_iff
#align alexandroff.inseparable_coe OnePoint.inseparable_coe
theorem not_specializes_infty_coe {x : X} : ¬Specializes ∞ (x : OnePoint X) :=
isClosed_infty.not_specializes rfl (coe_ne_infty x)
#align alexandroff.not_specializes_infty_coe OnePoint.not_specializes_infty_coe
theorem not_inseparable_infty_coe {x : X} : ¬Inseparable ∞ (x : OnePoint X) := fun h =>
not_specializes_infty_coe h.specializes
#align alexandroff.not_inseparable_infty_coe OnePoint.not_inseparable_infty_coe
theorem not_inseparable_coe_infty {x : X} : ¬Inseparable (x : OnePoint X) ∞ := fun h =>
not_specializes_infty_coe h.specializes'
#align alexandroff.not_inseparable_coe_infty OnePoint.not_inseparable_coe_infty
theorem inseparable_iff {x y : OnePoint X} :
Inseparable x y ↔ x = ∞ ∧ y = ∞ ∨ ∃ x' : X, x = x' ∧ ∃ y' : X, y = y' ∧ Inseparable x' y' := by
induction x using OnePoint.rec <;> induction y using OnePoint.rec <;>
simp [not_inseparable_infty_coe, not_inseparable_coe_infty, coe_eq_coe, Inseparable.refl]
#align alexandroff.inseparable_iff OnePoint.inseparable_iff
/-!
### Compactness and separation properties
In this section we prove that `OnePoint X` is a compact space; it is a T₀ (resp., T₁) space if
the original space satisfies the same separation axiom. If the original space is a locally compact
Hausdorff space, then `OnePoint X` is a normal (hence, T₃ and Hausdorff) space.
Finally, if the original space `X` is *not* compact and is a preconnected space, then
`OnePoint X` is a connected space.
-/
/-- For any topological space `X`, its one point compactification is a compact space. -/
instance : CompactSpace (OnePoint X) where
isCompact_univ := by
have : Tendsto ((↑) : X → OnePoint X) (cocompact X) (𝓝 ∞) := by
rw [nhds_infty_eq]
exact (tendsto_map.mono_left cocompact_le_coclosedCompact).mono_right le_sup_left
rw [← insert_none_range_some X]
exact this.isCompact_insert_range_of_cocompact continuous_coe
/-- The one point compactification of a `T0Space` space is a `T0Space`. -/
instance [T0Space X] : T0Space (OnePoint X) := by
refine ⟨fun x y hxy => ?_⟩
rcases inseparable_iff.1 hxy with (⟨rfl, rfl⟩ | ⟨x, rfl, y, rfl, h⟩)
exacts [rfl, congr_arg some h.eq]
/-- The one point compactification of a `T1Space` space is a `T1Space`. -/
instance [T1Space X] : T1Space (OnePoint X) where
t1 z := by
induction z using OnePoint.rec
· exact isClosed_infty
· rw [← image_singleton, isClosed_image_coe]
exact ⟨isClosed_singleton, isCompact_singleton⟩
/-- The one point compactification of a locally compact R₁ space is a normal topological space. -/
instance [LocallyCompactSpace X] [R1Space X] : NormalSpace (OnePoint X) := by
suffices R1Space (OnePoint X) by infer_instance
have key : ∀ z : X, Disjoint (𝓝 (some z)) (𝓝 ∞) := fun z ↦ by
rw [nhds_infty_eq, disjoint_sup_right, nhds_coe_eq, coclosedCompact_eq_cocompact,
disjoint_map coe_injective, ← principal_singleton, disjoint_principal_right, compl_infty]
exact ⟨disjoint_nhds_cocompact z, range_mem_map⟩
refine ⟨fun x y ↦ ?_⟩
induction x using OnePoint.rec <;> induction y using OnePoint.rec
· exact .inl le_rfl
· exact .inr (key _).symm
· exact .inr (key _)
· rw [nhds_coe_eq, nhds_coe_eq, disjoint_map coe_injective, specializes_coe]
apply specializes_or_disjoint_nhds
/-- The one point compactification of a weakly locally compact Hausdorff space is a T₄
(hence, Hausdorff and regular) topological space. -/
example [WeaklyLocallyCompactSpace X] [T2Space X] : T4Space (OnePoint X) := inferInstance
/-- If `X` is not a compact space, then `OnePoint X` is a connected space. -/
instance [PreconnectedSpace X] [NoncompactSpace X] : ConnectedSpace (OnePoint X) where
toPreconnectedSpace := denseEmbedding_coe.toDenseInducing.preconnectedSpace
toNonempty := inferInstance
/-- If `X` is an infinite type with discrete topology (e.g., `ℕ`), then the identity map from
`CofiniteTopology (OnePoint X)` to `OnePoint X` is not continuous. -/
| Mathlib/Topology/Compactification/OnePoint.lean | 486 | 492 | theorem not_continuous_cofiniteTopology_of_symm [Infinite X] [DiscreteTopology X] :
¬Continuous (@CofiniteTopology.of (OnePoint X)).symm := by |
inhabit X
simp only [continuous_iff_continuousAt, ContinuousAt, not_forall]
use CofiniteTopology.of ↑(default : X)
simpa [nhds_coe_eq, nhds_discrete, CofiniteTopology.nhds_eq] using
(finite_singleton ((default : X) : OnePoint X)).infinite_compl
|
/-
Copyright (c) 2020 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Ken Lee, Chris Hughes
-/
import Mathlib.Algebra.BigOperators.Ring
import Mathlib.Data.Fintype.Basic
import Mathlib.Data.Int.GCD
import Mathlib.RingTheory.Coprime.Basic
#align_import ring_theory.coprime.lemmas from "leanprover-community/mathlib"@"509de852e1de55e1efa8eacfa11df0823f26f226"
/-!
# Additional lemmas about elements of a ring satisfying `IsCoprime`
and elements of a monoid satisfying `IsRelPrime`
These lemmas are in a separate file to the definition of `IsCoprime` or `IsRelPrime`
as they require more imports.
Notably, this includes lemmas about `Finset.prod` as this requires importing BigOperators, and
lemmas about `Pow` since these are easiest to prove via `Finset.prod`.
-/
universe u v
section IsCoprime
variable {R : Type u} {I : Type v} [CommSemiring R] {x y z : R} {s : I → R} {t : Finset I}
section
theorem Int.isCoprime_iff_gcd_eq_one {m n : ℤ} : IsCoprime m n ↔ Int.gcd m n = 1 := by
constructor
· rintro ⟨a, b, h⟩
have : 1 = m * a + n * b := by rwa [mul_comm m, mul_comm n, eq_comm]
exact Nat.dvd_one.mp (Int.gcd_dvd_iff.mpr ⟨a, b, this⟩)
· rw [← Int.ofNat_inj, IsCoprime, Int.gcd_eq_gcd_ab, mul_comm m, mul_comm n, Nat.cast_one]
intro h
exact ⟨_, _, h⟩
theorem Nat.isCoprime_iff_coprime {m n : ℕ} : IsCoprime (m : ℤ) n ↔ Nat.Coprime m n := by
rw [Int.isCoprime_iff_gcd_eq_one, Int.gcd_natCast_natCast]
#align nat.is_coprime_iff_coprime Nat.isCoprime_iff_coprime
alias ⟨IsCoprime.nat_coprime, Nat.Coprime.isCoprime⟩ := Nat.isCoprime_iff_coprime
#align is_coprime.nat_coprime IsCoprime.nat_coprime
#align nat.coprime.is_coprime Nat.Coprime.isCoprime
theorem Nat.Coprime.cast {R : Type*} [CommRing R] {a b : ℕ} (h : Nat.Coprime a b) :
IsCoprime (a : R) (b : R) := by
rw [← isCoprime_iff_coprime] at h
rw [← Int.cast_natCast a, ← Int.cast_natCast b]
exact IsCoprime.intCast h
theorem ne_zero_or_ne_zero_of_nat_coprime {A : Type u} [CommRing A] [Nontrivial A] {a b : ℕ}
(h : Nat.Coprime a b) : (a : A) ≠ 0 ∨ (b : A) ≠ 0 :=
IsCoprime.ne_zero_or_ne_zero (R := A) <| by
simpa only [map_natCast] using IsCoprime.map (Nat.Coprime.isCoprime h) (Int.castRingHom A)
theorem IsCoprime.prod_left : (∀ i ∈ t, IsCoprime (s i) x) → IsCoprime (∏ i ∈ t, s i) x := by
classical
refine Finset.induction_on t (fun _ ↦ isCoprime_one_left) fun b t hbt ih H ↦ ?_
rw [Finset.prod_insert hbt]
rw [Finset.forall_mem_insert] at H
exact H.1.mul_left (ih H.2)
#align is_coprime.prod_left IsCoprime.prod_left
theorem IsCoprime.prod_right : (∀ i ∈ t, IsCoprime x (s i)) → IsCoprime x (∏ i ∈ t, s i) := by
simpa only [isCoprime_comm] using IsCoprime.prod_left (R := R)
#align is_coprime.prod_right IsCoprime.prod_right
theorem IsCoprime.prod_left_iff : IsCoprime (∏ i ∈ t, s i) x ↔ ∀ i ∈ t, IsCoprime (s i) x := by
classical
refine Finset.induction_on t (iff_of_true isCoprime_one_left fun _ ↦ by simp) fun b t hbt ih ↦ ?_
rw [Finset.prod_insert hbt, IsCoprime.mul_left_iff, ih, Finset.forall_mem_insert]
#align is_coprime.prod_left_iff IsCoprime.prod_left_iff
theorem IsCoprime.prod_right_iff : IsCoprime x (∏ i ∈ t, s i) ↔ ∀ i ∈ t, IsCoprime x (s i) := by
simpa only [isCoprime_comm] using IsCoprime.prod_left_iff (R := R)
#align is_coprime.prod_right_iff IsCoprime.prod_right_iff
theorem IsCoprime.of_prod_left (H1 : IsCoprime (∏ i ∈ t, s i) x) (i : I) (hit : i ∈ t) :
IsCoprime (s i) x :=
IsCoprime.prod_left_iff.1 H1 i hit
#align is_coprime.of_prod_left IsCoprime.of_prod_left
theorem IsCoprime.of_prod_right (H1 : IsCoprime x (∏ i ∈ t, s i)) (i : I) (hit : i ∈ t) :
IsCoprime x (s i) :=
IsCoprime.prod_right_iff.1 H1 i hit
#align is_coprime.of_prod_right IsCoprime.of_prod_right
-- Porting note: removed names of things due to linter, but they seem helpful
theorem Finset.prod_dvd_of_coprime :
(t : Set I).Pairwise (IsCoprime on s) → (∀ i ∈ t, s i ∣ z) → (∏ x ∈ t, s x) ∣ z := by
classical
exact Finset.induction_on t (fun _ _ ↦ one_dvd z)
(by
intro a r har ih Hs Hs1
rw [Finset.prod_insert har]
have aux1 : a ∈ (↑(insert a r) : Set I) := Finset.mem_insert_self a r
refine
(IsCoprime.prod_right fun i hir ↦
Hs aux1 (Finset.mem_insert_of_mem hir) <| by
rintro rfl
exact har hir).mul_dvd
(Hs1 a aux1) (ih (Hs.mono ?_) fun i hi ↦ Hs1 i <| Finset.mem_insert_of_mem hi)
simp only [Finset.coe_insert, Set.subset_insert])
#align finset.prod_dvd_of_coprime Finset.prod_dvd_of_coprime
theorem Fintype.prod_dvd_of_coprime [Fintype I] (Hs : Pairwise (IsCoprime on s))
(Hs1 : ∀ i, s i ∣ z) : (∏ x, s x) ∣ z :=
Finset.prod_dvd_of_coprime (Hs.set_pairwise _) fun i _ ↦ Hs1 i
#align fintype.prod_dvd_of_coprime Fintype.prod_dvd_of_coprime
end
open Finset
theorem exists_sum_eq_one_iff_pairwise_coprime [DecidableEq I] (h : t.Nonempty) :
(∃ μ : I → R, (∑ i ∈ t, μ i * ∏ j ∈ t \ {i}, s j) = 1) ↔
Pairwise (IsCoprime on fun i : t ↦ s i) := by
induction h using Finset.Nonempty.cons_induction with
| singleton =>
simp [exists_apply_eq, Pairwise, Function.onFun]
| cons a t hat h ih =>
rw [pairwise_cons']
have mem : ∀ x ∈ t, a ∈ insert a t \ {x} := fun x hx ↦ by
rw [mem_sdiff, mem_singleton]
exact ⟨mem_insert_self _ _, fun ha ↦ hat (ha ▸ hx)⟩
constructor
· rintro ⟨μ, hμ⟩
rw [sum_cons, cons_eq_insert, sdiff_singleton_eq_erase, erase_insert hat] at hμ
refine ⟨ih.mp ⟨Pi.single h.choose (μ a * s h.choose) + μ * fun _ ↦ s a, ?_⟩, fun b hb ↦ ?_⟩
· rw [prod_eq_mul_prod_diff_singleton h.choose_spec, ← mul_assoc, ←
@if_pos _ _ h.choose_spec R (_ * _) 0, ← sum_pi_single', ← sum_add_distrib] at hμ
rw [← hμ, sum_congr rfl]
intro x hx
dsimp -- Porting note: terms were showing as sort of `HAdd.hadd` instead of `+`
-- this whole proof pretty much breaks and has to be rewritten from scratch
rw [add_mul]
congr 1
· by_cases hx : x = h.choose
· rw [hx, Pi.single_eq_same, Pi.single_eq_same]
· rw [Pi.single_eq_of_ne hx, Pi.single_eq_of_ne hx, zero_mul]
· rw [mul_assoc]
congr
rw [prod_eq_prod_diff_singleton_mul (mem x hx) _, mul_comm]
congr 2
rw [sdiff_sdiff_comm, sdiff_singleton_eq_erase a, erase_insert hat]
· have : IsCoprime (s b) (s a) :=
⟨μ a * ∏ i ∈ t \ {b}, s i, ∑ i ∈ t, μ i * ∏ j ∈ t \ {i}, s j, ?_⟩
· exact ⟨this.symm, this⟩
rw [mul_assoc, ← prod_eq_prod_diff_singleton_mul hb, sum_mul, ← hμ, sum_congr rfl]
intro x hx
rw [mul_assoc]
congr
rw [prod_eq_prod_diff_singleton_mul (mem x hx) _]
congr 2
rw [sdiff_sdiff_comm, sdiff_singleton_eq_erase a, erase_insert hat]
· rintro ⟨hs, Hb⟩
obtain ⟨μ, hμ⟩ := ih.mpr hs
obtain ⟨u, v, huv⟩ := IsCoprime.prod_left fun b hb ↦ (Hb b hb).right
use fun i ↦ if i = a then u else v * μ i
have hμ' : (∑ i ∈ t, v * ((μ i * ∏ j ∈ t \ {i}, s j) * s a)) = v * s a := by
rw [← mul_sum, ← sum_mul, hμ, one_mul]
rw [sum_cons, cons_eq_insert, sdiff_singleton_eq_erase, erase_insert hat, if_pos rfl,
← huv, ← hμ', sum_congr rfl]
intro x hx
rw [mul_assoc, if_neg fun ha : x = a ↦ hat (ha.casesOn hx)]
rw [mul_assoc]
congr
rw [prod_eq_prod_diff_singleton_mul (mem x hx) _]
congr 2
rw [sdiff_sdiff_comm, sdiff_singleton_eq_erase a, erase_insert hat]
#align exists_sum_eq_one_iff_pairwise_coprime exists_sum_eq_one_iff_pairwise_coprime
theorem exists_sum_eq_one_iff_pairwise_coprime' [Fintype I] [Nonempty I] [DecidableEq I] :
(∃ μ : I → R, (∑ i : I, μ i * ∏ j ∈ {i}ᶜ, s j) = 1) ↔ Pairwise (IsCoprime on s) := by
convert exists_sum_eq_one_iff_pairwise_coprime Finset.univ_nonempty (s := s) using 1
simp only [Function.onFun, pairwise_subtype_iff_pairwise_finset', coe_univ, Set.pairwise_univ]
#align exists_sum_eq_one_iff_pairwise_coprime' exists_sum_eq_one_iff_pairwise_coprime'
-- Porting note: a lot of the capitalization wasn't working
theorem pairwise_coprime_iff_coprime_prod [DecidableEq I] :
Pairwise (IsCoprime on fun i : t ↦ s i) ↔ ∀ i ∈ t, IsCoprime (s i) (∏ j ∈ t \ {i}, s j) := by
refine ⟨fun hp i hi ↦ IsCoprime.prod_right_iff.mpr fun j hj ↦ ?_, fun hp ↦ ?_⟩
· rw [Finset.mem_sdiff, Finset.mem_singleton] at hj
obtain ⟨hj, ji⟩ := hj
refine @hp ⟨i, hi⟩ ⟨j, hj⟩ fun h ↦ ji (congrArg Subtype.val h).symm
-- Porting note: is there a better way compared to the old `congr_arg coe h`?
· rintro ⟨i, hi⟩ ⟨j, hj⟩ h
apply IsCoprime.prod_right_iff.mp (hp i hi)
exact Finset.mem_sdiff.mpr ⟨hj, fun f ↦ h <| Subtype.ext (Finset.mem_singleton.mp f).symm⟩
#align pairwise_coprime_iff_coprime_prod pairwise_coprime_iff_coprime_prod
variable {m n : ℕ}
theorem IsCoprime.pow_left (H : IsCoprime x y) : IsCoprime (x ^ m) y := by
rw [← Finset.card_range m, ← Finset.prod_const]
exact IsCoprime.prod_left fun _ _ ↦ H
#align is_coprime.pow_left IsCoprime.pow_left
theorem IsCoprime.pow_right (H : IsCoprime x y) : IsCoprime x (y ^ n) := by
rw [← Finset.card_range n, ← Finset.prod_const]
exact IsCoprime.prod_right fun _ _ ↦ H
#align is_coprime.pow_right IsCoprime.pow_right
theorem IsCoprime.pow (H : IsCoprime x y) : IsCoprime (x ^ m) (y ^ n) :=
H.pow_left.pow_right
#align is_coprime.pow IsCoprime.pow
theorem IsCoprime.pow_left_iff (hm : 0 < m) : IsCoprime (x ^ m) y ↔ IsCoprime x y := by
refine ⟨fun h ↦ ?_, IsCoprime.pow_left⟩
rw [← Finset.card_range m, ← Finset.prod_const] at h
exact h.of_prod_left 0 (Finset.mem_range.mpr hm)
-- Porting note: I'm not sure why `finset` didn't get corrected automatically to `Finset`
-- by Mathport, nor whether this is an issue
#align is_coprime.pow_left_iff IsCoprime.pow_left_iff
theorem IsCoprime.pow_right_iff (hm : 0 < m) : IsCoprime x (y ^ m) ↔ IsCoprime x y :=
isCoprime_comm.trans <| (IsCoprime.pow_left_iff hm).trans <| isCoprime_comm
#align is_coprime.pow_right_iff IsCoprime.pow_right_iff
theorem IsCoprime.pow_iff (hm : 0 < m) (hn : 0 < n) : IsCoprime (x ^ m) (y ^ n) ↔ IsCoprime x y :=
(IsCoprime.pow_left_iff hm).trans <| IsCoprime.pow_right_iff hn
#align is_coprime.pow_iff IsCoprime.pow_iff
end IsCoprime
section RelPrime
variable {α I} [CommMonoid α] [DecompositionMonoid α] {x y z : α} {s : I → α} {t : Finset I}
theorem IsRelPrime.prod_left : (∀ i ∈ t, IsRelPrime (s i) x) → IsRelPrime (∏ i ∈ t, s i) x := by
classical
refine Finset.induction_on t (fun _ ↦ isRelPrime_one_left) fun b t hbt ih H ↦ ?_
rw [Finset.prod_insert hbt]
rw [Finset.forall_mem_insert] at H
exact H.1.mul_left (ih H.2)
| Mathlib/RingTheory/Coprime/Lemmas.lean | 242 | 243 | theorem IsRelPrime.prod_right : (∀ i ∈ t, IsRelPrime x (s i)) → IsRelPrime x (∏ i ∈ t, s i) := by |
simpa only [isRelPrime_comm] using IsRelPrime.prod_left (α := α)
|
/-
Copyright (c) 2019 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl
-/
import Mathlib.Data.Finsupp.Encodable
import Mathlib.LinearAlgebra.Pi
import Mathlib.LinearAlgebra.Span
import Mathlib.Data.Set.Countable
#align_import linear_algebra.finsupp from "leanprover-community/mathlib"@"9d684a893c52e1d6692a504a118bfccbae04feeb"
/-!
# Properties of the module `α →₀ M`
Given an `R`-module `M`, the `R`-module structure on `α →₀ M` is defined in
`Data.Finsupp.Basic`.
In this file we define `Finsupp.supported s` to be the set `{f : α →₀ M | f.support ⊆ s}`
interpreted as a submodule of `α →₀ M`. We also define `LinearMap` versions of various maps:
* `Finsupp.lsingle a : M →ₗ[R] ι →₀ M`: `Finsupp.single a` as a linear map;
* `Finsupp.lapply a : (ι →₀ M) →ₗ[R] M`: the map `fun f ↦ f a` as a linear map;
* `Finsupp.lsubtypeDomain (s : Set α) : (α →₀ M) →ₗ[R] (s →₀ M)`: restriction to a subtype as a
linear map;
* `Finsupp.restrictDom`: `Finsupp.filter` as a linear map to `Finsupp.supported s`;
* `Finsupp.lsum`: `Finsupp.sum` or `Finsupp.liftAddHom` as a `LinearMap`;
* `Finsupp.total α M R (v : ι → M)`: sends `l : ι → R` to the linear combination of `v i` with
coefficients `l i`;
* `Finsupp.totalOn`: a restricted version of `Finsupp.total` with domain `Finsupp.supported R R s`
and codomain `Submodule.span R (v '' s)`;
* `Finsupp.supportedEquivFinsupp`: a linear equivalence between the functions `α →₀ M` supported
on `s` and the functions `s →₀ M`;
* `Finsupp.lmapDomain`: a linear map version of `Finsupp.mapDomain`;
* `Finsupp.domLCongr`: a `LinearEquiv` version of `Finsupp.domCongr`;
* `Finsupp.congr`: if the sets `s` and `t` are equivalent, then `supported M R s` is equivalent to
`supported M R t`;
* `Finsupp.lcongr`: a `LinearEquiv`alence between `α →₀ M` and `β →₀ N` constructed using
`e : α ≃ β` and `e' : M ≃ₗ[R] N`.
## Tags
function with finite support, module, linear algebra
-/
noncomputable section
open Set LinearMap Submodule
namespace Finsupp
section SMul
variable {α : Type*} {β : Type*} {R : Type*} {M : Type*} {M₂ : Type*}
theorem smul_sum [Zero β] [AddCommMonoid M] [DistribSMul R M] {v : α →₀ β} {c : R} {h : α → β → M} :
c • v.sum h = v.sum fun a b => c • h a b :=
Finset.smul_sum
#align finsupp.smul_sum Finsupp.smul_sum
@[simp]
theorem sum_smul_index_linearMap' [Semiring R] [AddCommMonoid M] [Module R M] [AddCommMonoid M₂]
[Module R M₂] {v : α →₀ M} {c : R} {h : α → M →ₗ[R] M₂} :
((c • v).sum fun a => h a) = c • v.sum fun a => h a := by
rw [Finsupp.sum_smul_index', Finsupp.smul_sum]
· simp only [map_smul]
· intro i
exact (h i).map_zero
#align finsupp.sum_smul_index_linear_map' Finsupp.sum_smul_index_linearMap'
end SMul
section LinearEquivFunOnFinite
variable (R : Type*) {S : Type*} (M : Type*) (α : Type*)
variable [Finite α] [AddCommMonoid M] [Semiring R] [Module R M]
/-- Given `Finite α`, `linearEquivFunOnFinite R` is the natural `R`-linear equivalence between
`α →₀ β` and `α → β`. -/
@[simps apply]
noncomputable def linearEquivFunOnFinite : (α →₀ M) ≃ₗ[R] α → M :=
{ equivFunOnFinite with
toFun := (⇑)
map_add' := fun _ _ => rfl
map_smul' := fun _ _ => rfl }
#align finsupp.linear_equiv_fun_on_finite Finsupp.linearEquivFunOnFinite
@[simp]
theorem linearEquivFunOnFinite_single [DecidableEq α] (x : α) (m : M) :
(linearEquivFunOnFinite R M α) (single x m) = Pi.single x m :=
equivFunOnFinite_single x m
#align finsupp.linear_equiv_fun_on_finite_single Finsupp.linearEquivFunOnFinite_single
@[simp]
theorem linearEquivFunOnFinite_symm_single [DecidableEq α] (x : α) (m : M) :
(linearEquivFunOnFinite R M α).symm (Pi.single x m) = single x m :=
equivFunOnFinite_symm_single x m
#align finsupp.linear_equiv_fun_on_finite_symm_single Finsupp.linearEquivFunOnFinite_symm_single
@[simp]
theorem linearEquivFunOnFinite_symm_coe (f : α →₀ M) : (linearEquivFunOnFinite R M α).symm f = f :=
(linearEquivFunOnFinite R M α).symm_apply_apply f
#align finsupp.linear_equiv_fun_on_finite_symm_coe Finsupp.linearEquivFunOnFinite_symm_coe
end LinearEquivFunOnFinite
section LinearEquiv.finsuppUnique
variable (R : Type*) {S : Type*} (M : Type*)
variable [AddCommMonoid M] [Semiring R] [Module R M]
variable (α : Type*) [Unique α]
/-- If `α` has a unique term, then the type of finitely supported functions `α →₀ M` is
`R`-linearly equivalent to `M`. -/
noncomputable def LinearEquiv.finsuppUnique : (α →₀ M) ≃ₗ[R] M :=
{ Finsupp.equivFunOnFinite.trans (Equiv.funUnique α M) with
map_add' := fun _ _ => rfl
map_smul' := fun _ _ => rfl }
#align finsupp.linear_equiv.finsupp_unique Finsupp.LinearEquiv.finsuppUnique
variable {R M}
@[simp]
theorem LinearEquiv.finsuppUnique_apply (f : α →₀ M) :
LinearEquiv.finsuppUnique R M α f = f default :=
rfl
#align finsupp.linear_equiv.finsupp_unique_apply Finsupp.LinearEquiv.finsuppUnique_apply
variable {α}
@[simp]
theorem LinearEquiv.finsuppUnique_symm_apply [Unique α] (m : M) :
(LinearEquiv.finsuppUnique R M α).symm m = Finsupp.single default m := by
ext; simp [LinearEquiv.finsuppUnique, Equiv.funUnique, single, Pi.single,
equivFunOnFinite, Function.update]
#align finsupp.linear_equiv.finsupp_unique_symm_apply Finsupp.LinearEquiv.finsuppUnique_symm_apply
end LinearEquiv.finsuppUnique
variable {α : Type*} {M : Type*} {N : Type*} {P : Type*} {R : Type*} {S : Type*}
variable [Semiring R] [Semiring S] [AddCommMonoid M] [Module R M]
variable [AddCommMonoid N] [Module R N]
variable [AddCommMonoid P] [Module R P]
/-- Interpret `Finsupp.single a` as a linear map. -/
def lsingle (a : α) : M →ₗ[R] α →₀ M :=
{ Finsupp.singleAddHom a with map_smul' := fun _ _ => (smul_single _ _ _).symm }
#align finsupp.lsingle Finsupp.lsingle
/-- Two `R`-linear maps from `Finsupp X M` which agree on each `single x y` agree everywhere. -/
theorem lhom_ext ⦃φ ψ : (α →₀ M) →ₗ[R] N⦄ (h : ∀ a b, φ (single a b) = ψ (single a b)) : φ = ψ :=
LinearMap.toAddMonoidHom_injective <| addHom_ext h
#align finsupp.lhom_ext Finsupp.lhom_ext
/-- Two `R`-linear maps from `Finsupp X M` which agree on each `single x y` agree everywhere.
We formulate this fact using equality of linear maps `φ.comp (lsingle a)` and `ψ.comp (lsingle a)`
so that the `ext` tactic can apply a type-specific extensionality lemma to prove equality of these
maps. E.g., if `M = R`, then it suffices to verify `φ (single a 1) = ψ (single a 1)`. -/
-- Porting note: The priority should be higher than `LinearMap.ext`.
@[ext high]
theorem lhom_ext' ⦃φ ψ : (α →₀ M) →ₗ[R] N⦄ (h : ∀ a, φ.comp (lsingle a) = ψ.comp (lsingle a)) :
φ = ψ :=
lhom_ext fun a => LinearMap.congr_fun (h a)
#align finsupp.lhom_ext' Finsupp.lhom_ext'
/-- Interpret `fun f : α →₀ M ↦ f a` as a linear map. -/
def lapply (a : α) : (α →₀ M) →ₗ[R] M :=
{ Finsupp.applyAddHom a with map_smul' := fun _ _ => rfl }
#align finsupp.lapply Finsupp.lapply
section CompatibleSMul
variable (R S M N ι : Type*)
variable [Semiring S] [AddCommMonoid M] [AddCommMonoid N] [Module S M] [Module S N]
instance _root_.LinearMap.CompatibleSMul.finsupp_dom [SMulZeroClass R M] [DistribSMul R N]
[LinearMap.CompatibleSMul M N R S] : LinearMap.CompatibleSMul (ι →₀ M) N R S where
map_smul f r m := by
conv_rhs => rw [← sum_single m, map_finsupp_sum, smul_sum]
erw [← sum_single (r • m), sum_mapRange_index single_zero, map_finsupp_sum]
congr; ext i m; exact (f.comp <| lsingle i).map_smul_of_tower r m
instance _root_.LinearMap.CompatibleSMul.finsupp_cod [SMul R M] [SMulZeroClass R N]
[LinearMap.CompatibleSMul M N R S] : LinearMap.CompatibleSMul M (ι →₀ N) R S where
map_smul f r m := by ext i; apply ((lapply i).comp f).map_smul_of_tower
end CompatibleSMul
/-- Forget that a function is finitely supported.
This is the linear version of `Finsupp.toFun`. -/
@[simps]
def lcoeFun : (α →₀ M) →ₗ[R] α → M where
toFun := (⇑)
map_add' x y := by
ext
simp
map_smul' x y := by
ext
simp
#align finsupp.lcoe_fun Finsupp.lcoeFun
section LSubtypeDomain
variable (s : Set α)
/-- Interpret `Finsupp.subtypeDomain s` as a linear map. -/
def lsubtypeDomain : (α →₀ M) →ₗ[R] s →₀ M where
toFun := subtypeDomain fun x => x ∈ s
map_add' _ _ := subtypeDomain_add
map_smul' _ _ := ext fun _ => rfl
#align finsupp.lsubtype_domain Finsupp.lsubtypeDomain
theorem lsubtypeDomain_apply (f : α →₀ M) :
(lsubtypeDomain s : (α →₀ M) →ₗ[R] s →₀ M) f = subtypeDomain (fun x => x ∈ s) f :=
rfl
#align finsupp.lsubtype_domain_apply Finsupp.lsubtypeDomain_apply
end LSubtypeDomain
@[simp]
theorem lsingle_apply (a : α) (b : M) : (lsingle a : M →ₗ[R] α →₀ M) b = single a b :=
rfl
#align finsupp.lsingle_apply Finsupp.lsingle_apply
@[simp]
theorem lapply_apply (a : α) (f : α →₀ M) : (lapply a : (α →₀ M) →ₗ[R] M) f = f a :=
rfl
#align finsupp.lapply_apply Finsupp.lapply_apply
@[simp]
theorem lapply_comp_lsingle_same (a : α) : lapply a ∘ₗ lsingle a = (.id : M →ₗ[R] M) := by ext; simp
@[simp]
theorem lapply_comp_lsingle_of_ne (a a' : α) (h : a ≠ a') :
lapply a ∘ₗ lsingle a' = (0 : M →ₗ[R] M) := by ext; simp [h.symm]
@[simp]
theorem ker_lsingle (a : α) : ker (lsingle a : M →ₗ[R] α →₀ M) = ⊥ :=
ker_eq_bot_of_injective (single_injective a)
#align finsupp.ker_lsingle Finsupp.ker_lsingle
theorem lsingle_range_le_ker_lapply (s t : Set α) (h : Disjoint s t) :
⨆ a ∈ s, LinearMap.range (lsingle a : M →ₗ[R] α →₀ M) ≤
⨅ a ∈ t, ker (lapply a : (α →₀ M) →ₗ[R] M) := by
refine iSup_le fun a₁ => iSup_le fun h₁ => range_le_iff_comap.2 ?_
simp only [(ker_comp _ _).symm, eq_top_iff, SetLike.le_def, mem_ker, comap_iInf, mem_iInf]
intro b _ a₂ h₂
have : a₁ ≠ a₂ := fun eq => h.le_bot ⟨h₁, eq.symm ▸ h₂⟩
exact single_eq_of_ne this
#align finsupp.lsingle_range_le_ker_lapply Finsupp.lsingle_range_le_ker_lapply
theorem iInf_ker_lapply_le_bot : ⨅ a, ker (lapply a : (α →₀ M) →ₗ[R] M) ≤ ⊥ := by
simp only [SetLike.le_def, mem_iInf, mem_ker, mem_bot, lapply_apply]
exact fun a h => Finsupp.ext h
#align finsupp.infi_ker_lapply_le_bot Finsupp.iInf_ker_lapply_le_bot
theorem iSup_lsingle_range : ⨆ a, LinearMap.range (lsingle a : M →ₗ[R] α →₀ M) = ⊤ := by
refine eq_top_iff.2 <| SetLike.le_def.2 fun f _ => ?_
rw [← sum_single f]
exact sum_mem fun a _ => Submodule.mem_iSup_of_mem a ⟨_, rfl⟩
#align finsupp.supr_lsingle_range Finsupp.iSup_lsingle_range
theorem disjoint_lsingle_lsingle (s t : Set α) (hs : Disjoint s t) :
Disjoint (⨆ a ∈ s, LinearMap.range (lsingle a : M →ₗ[R] α →₀ M))
(⨆ a ∈ t, LinearMap.range (lsingle a : M →ₗ[R] α →₀ M)) := by
-- Porting note: 2 placeholders are added to prevent timeout.
refine
(Disjoint.mono
(lsingle_range_le_ker_lapply s sᶜ ?_)
(lsingle_range_le_ker_lapply t tᶜ ?_))
?_
· apply disjoint_compl_right
· apply disjoint_compl_right
rw [disjoint_iff_inf_le]
refine le_trans (le_iInf fun i => ?_) iInf_ker_lapply_le_bot
classical
by_cases his : i ∈ s
· by_cases hit : i ∈ t
· exact (hs.le_bot ⟨his, hit⟩).elim
exact inf_le_of_right_le (iInf_le_of_le i <| iInf_le _ hit)
exact inf_le_of_left_le (iInf_le_of_le i <| iInf_le _ his)
#align finsupp.disjoint_lsingle_lsingle Finsupp.disjoint_lsingle_lsingle
theorem span_single_image (s : Set M) (a : α) :
Submodule.span R (single a '' s) = (Submodule.span R s).map (lsingle a : M →ₗ[R] α →₀ M) := by
rw [← span_image]; rfl
#align finsupp.span_single_image Finsupp.span_single_image
variable (M R)
/-- `Finsupp.supported M R s` is the `R`-submodule of all `p : α →₀ M` such that `p.support ⊆ s`. -/
def supported (s : Set α) : Submodule R (α →₀ M) where
carrier := { p | ↑p.support ⊆ s }
add_mem' {p q} hp hq := by
classical
refine Subset.trans (Subset.trans (Finset.coe_subset.2 support_add) ?_) (union_subset hp hq)
rw [Finset.coe_union]
zero_mem' := by
simp only [subset_def, Finset.mem_coe, Set.mem_setOf_eq, mem_support_iff, zero_apply]
intro h ha
exact (ha rfl).elim
smul_mem' a p hp := Subset.trans (Finset.coe_subset.2 support_smul) hp
#align finsupp.supported Finsupp.supported
variable {M}
theorem mem_supported {s : Set α} (p : α →₀ M) : p ∈ supported M R s ↔ ↑p.support ⊆ s :=
Iff.rfl
#align finsupp.mem_supported Finsupp.mem_supported
theorem mem_supported' {s : Set α} (p : α →₀ M) :
p ∈ supported M R s ↔ ∀ x ∉ s, p x = 0 := by
haveI := Classical.decPred fun x : α => x ∈ s; simp [mem_supported, Set.subset_def, not_imp_comm]
#align finsupp.mem_supported' Finsupp.mem_supported'
theorem mem_supported_support (p : α →₀ M) : p ∈ Finsupp.supported M R (p.support : Set α) := by
rw [Finsupp.mem_supported]
#align finsupp.mem_supported_support Finsupp.mem_supported_support
theorem single_mem_supported {s : Set α} {a : α} (b : M) (h : a ∈ s) :
single a b ∈ supported M R s :=
Set.Subset.trans support_single_subset (Finset.singleton_subset_set_iff.2 h)
#align finsupp.single_mem_supported Finsupp.single_mem_supported
theorem supported_eq_span_single (s : Set α) :
supported R R s = span R ((fun i => single i 1) '' s) := by
refine (span_eq_of_le _ ?_ (SetLike.le_def.2 fun l hl => ?_)).symm
· rintro _ ⟨_, hp, rfl⟩
exact single_mem_supported R 1 hp
· rw [← l.sum_single]
refine sum_mem fun i il => ?_
-- Porting note: Needed to help this convert quite a bit replacing underscores
convert smul_mem (M := α →₀ R) (x := single i 1) (span R ((fun i => single i 1) '' s)) (l i) ?_
· simp [span]
· apply subset_span
apply Set.mem_image_of_mem _ (hl il)
#align finsupp.supported_eq_span_single Finsupp.supported_eq_span_single
variable (M)
/-- Interpret `Finsupp.filter s` as a linear map from `α →₀ M` to `supported M R s`. -/
def restrictDom (s : Set α) [DecidablePred (· ∈ s)] : (α →₀ M) →ₗ[R] supported M R s :=
LinearMap.codRestrict _
{ toFun := filter (· ∈ s)
map_add' := fun _ _ => filter_add
map_smul' := fun _ _ => filter_smul } fun l =>
(mem_supported' _ _).2 fun _ => filter_apply_neg (· ∈ s) l
#align finsupp.restrict_dom Finsupp.restrictDom
variable {M R}
section
@[simp]
theorem restrictDom_apply (s : Set α) (l : α →₀ M) [DecidablePred (· ∈ s)]:
(restrictDom M R s l : α →₀ M) = Finsupp.filter (· ∈ s) l := rfl
#align finsupp.restrict_dom_apply Finsupp.restrictDom_apply
end
theorem restrictDom_comp_subtype (s : Set α) [DecidablePred (· ∈ s)] :
(restrictDom M R s).comp (Submodule.subtype _) = LinearMap.id := by
ext l a
by_cases h : a ∈ s <;> simp [h]
exact ((mem_supported' R l.1).1 l.2 a h).symm
#align finsupp.restrict_dom_comp_subtype Finsupp.restrictDom_comp_subtype
theorem range_restrictDom (s : Set α) [DecidablePred (· ∈ s)] :
LinearMap.range (restrictDom M R s) = ⊤ :=
range_eq_top.2 <|
Function.RightInverse.surjective <| LinearMap.congr_fun (restrictDom_comp_subtype s)
#align finsupp.range_restrict_dom Finsupp.range_restrictDom
theorem supported_mono {s t : Set α} (st : s ⊆ t) : supported M R s ≤ supported M R t := fun _ h =>
Set.Subset.trans h st
#align finsupp.supported_mono Finsupp.supported_mono
@[simp]
theorem supported_empty : supported M R (∅ : Set α) = ⊥ :=
eq_bot_iff.2 fun l h => (Submodule.mem_bot R).2 <| by ext; simp_all [mem_supported']
#align finsupp.supported_empty Finsupp.supported_empty
@[simp]
theorem supported_univ : supported M R (Set.univ : Set α) = ⊤ :=
eq_top_iff.2 fun _ _ => Set.subset_univ _
#align finsupp.supported_univ Finsupp.supported_univ
theorem supported_iUnion {δ : Type*} (s : δ → Set α) :
supported M R (⋃ i, s i) = ⨆ i, supported M R (s i) := by
refine le_antisymm ?_ (iSup_le fun i => supported_mono <| Set.subset_iUnion _ _)
haveI := Classical.decPred fun x => x ∈ ⋃ i, s i
suffices
LinearMap.range ((Submodule.subtype _).comp (restrictDom M R (⋃ i, s i))) ≤
⨆ i, supported M R (s i) by
rwa [LinearMap.range_comp, range_restrictDom, Submodule.map_top, range_subtype] at this
rw [range_le_iff_comap, eq_top_iff]
rintro l ⟨⟩
-- Porting note: Was ported as `induction l using Finsupp.induction`
refine Finsupp.induction l ?_ ?_
· exact zero_mem _
· refine fun x a l _ _ => add_mem ?_
by_cases h : ∃ i, x ∈ s i <;> simp [h]
cases' h with i hi
exact le_iSup (fun i => supported M R (s i)) i (single_mem_supported R _ hi)
#align finsupp.supported_Union Finsupp.supported_iUnion
theorem supported_union (s t : Set α) :
supported M R (s ∪ t) = supported M R s ⊔ supported M R t := by
erw [Set.union_eq_iUnion, supported_iUnion, iSup_bool_eq]; rfl
#align finsupp.supported_union Finsupp.supported_union
theorem supported_iInter {ι : Type*} (s : ι → Set α) :
supported M R (⋂ i, s i) = ⨅ i, supported M R (s i) :=
Submodule.ext fun x => by simp [mem_supported, subset_iInter_iff]
#align finsupp.supported_Inter Finsupp.supported_iInter
theorem supported_inter (s t : Set α) :
supported M R (s ∩ t) = supported M R s ⊓ supported M R t := by
rw [Set.inter_eq_iInter, supported_iInter, iInf_bool_eq]; rfl
#align finsupp.supported_inter Finsupp.supported_inter
theorem disjoint_supported_supported {s t : Set α} (h : Disjoint s t) :
Disjoint (supported M R s) (supported M R t) :=
disjoint_iff.2 <| by rw [← supported_inter, disjoint_iff_inter_eq_empty.1 h, supported_empty]
#align finsupp.disjoint_supported_supported Finsupp.disjoint_supported_supported
theorem disjoint_supported_supported_iff [Nontrivial M] {s t : Set α} :
Disjoint (supported M R s) (supported M R t) ↔ Disjoint s t := by
refine ⟨fun h => Set.disjoint_left.mpr fun x hx1 hx2 => ?_, disjoint_supported_supported⟩
rcases exists_ne (0 : M) with ⟨y, hy⟩
have := h.le_bot ⟨single_mem_supported R y hx1, single_mem_supported R y hx2⟩
rw [mem_bot, single_eq_zero] at this
exact hy this
#align finsupp.disjoint_supported_supported_iff Finsupp.disjoint_supported_supported_iff
/-- Interpret `Finsupp.restrictSupportEquiv` as a linear equivalence between
`supported M R s` and `s →₀ M`. -/
def supportedEquivFinsupp (s : Set α) : supported M R s ≃ₗ[R] s →₀ M := by
let F : supported M R s ≃ (s →₀ M) := restrictSupportEquiv s M
refine F.toLinearEquiv ?_
have :
(F : supported M R s → ↥s →₀ M) =
(lsubtypeDomain s : (α →₀ M) →ₗ[R] s →₀ M).comp (Submodule.subtype (supported M R s)) :=
rfl
rw [this]
exact LinearMap.isLinear _
#align finsupp.supported_equiv_finsupp Finsupp.supportedEquivFinsupp
section LSum
variable (S)
variable [Module S N] [SMulCommClass R S N]
/-- Lift a family of linear maps `M →ₗ[R] N` indexed by `x : α` to a linear map from `α →₀ M` to
`N` using `Finsupp.sum`. This is an upgraded version of `Finsupp.liftAddHom`.
See note [bundled maps over different rings] for why separate `R` and `S` semirings are used.
-/
def lsum : (α → M →ₗ[R] N) ≃ₗ[S] (α →₀ M) →ₗ[R] N where
toFun F :=
{ toFun := fun d => d.sum fun i => F i
map_add' := (liftAddHom (α := α) (M := M) (N := N) fun x => (F x).toAddMonoidHom).map_add
map_smul' := fun c f => by simp [sum_smul_index', smul_sum] }
invFun F x := F.comp (lsingle x)
left_inv F := by
ext x y
simp
right_inv F := by
ext x y
simp
map_add' F G := by
ext x y
simp
map_smul' F G := by
ext x y
simp
#align finsupp.lsum Finsupp.lsum
@[simp]
theorem coe_lsum (f : α → M →ₗ[R] N) : (lsum S f : (α →₀ M) → N) = fun d => d.sum fun i => f i :=
rfl
#align finsupp.coe_lsum Finsupp.coe_lsum
theorem lsum_apply (f : α → M →ₗ[R] N) (l : α →₀ M) : Finsupp.lsum S f l = l.sum fun b => f b :=
rfl
#align finsupp.lsum_apply Finsupp.lsum_apply
theorem lsum_single (f : α → M →ₗ[R] N) (i : α) (m : M) :
Finsupp.lsum S f (Finsupp.single i m) = f i m :=
Finsupp.sum_single_index (f i).map_zero
#align finsupp.lsum_single Finsupp.lsum_single
@[simp] theorem lsum_comp_lsingle (f : α → M →ₗ[R] N) (i : α) :
Finsupp.lsum S f ∘ₗ lsingle i = f i := by ext; simp
theorem lsum_symm_apply (f : (α →₀ M) →ₗ[R] N) (x : α) : (lsum S).symm f x = f.comp (lsingle x) :=
rfl
#align finsupp.lsum_symm_apply Finsupp.lsum_symm_apply
end LSum
section
variable (M) (R) (X : Type*) (S)
variable [Module S M] [SMulCommClass R S M]
/-- A slight rearrangement from `lsum` gives us
the bijection underlying the free-forgetful adjunction for R-modules.
-/
noncomputable def lift : (X → M) ≃+ ((X →₀ R) →ₗ[R] M) :=
(AddEquiv.arrowCongr (Equiv.refl X) (ringLmapEquivSelf R ℕ M).toAddEquiv.symm).trans
(lsum _ : _ ≃ₗ[ℕ] _).toAddEquiv
#align finsupp.lift Finsupp.lift
@[simp]
theorem lift_symm_apply (f) (x) : ((lift M R X).symm f) x = f (single x 1) :=
rfl
#align finsupp.lift_symm_apply Finsupp.lift_symm_apply
@[simp]
theorem lift_apply (f) (g) : ((lift M R X) f) g = g.sum fun x r => r • f x :=
rfl
#align finsupp.lift_apply Finsupp.lift_apply
/-- Given compatible `S` and `R`-module structures on `M` and a type `X`, the set of functions
`X → M` is `S`-linearly equivalent to the `R`-linear maps from the free `R`-module
on `X` to `M`. -/
noncomputable def llift : (X → M) ≃ₗ[S] (X →₀ R) →ₗ[R] M :=
{ lift M R X with
map_smul' := by
intros
dsimp
ext
simp only [coe_comp, Function.comp_apply, lsingle_apply, lift_apply, Pi.smul_apply,
sum_single_index, zero_smul, one_smul, LinearMap.smul_apply] }
#align finsupp.llift Finsupp.llift
@[simp]
theorem llift_apply (f : X → M) (x : X →₀ R) : llift M R S X f x = lift M R X f x :=
rfl
#align finsupp.llift_apply Finsupp.llift_apply
@[simp]
theorem llift_symm_apply (f : (X →₀ R) →ₗ[R] M) (x : X) :
(llift M R S X).symm f x = f (single x 1) :=
rfl
#align finsupp.llift_symm_apply Finsupp.llift_symm_apply
end
section LMapDomain
variable {α' : Type*} {α'' : Type*} (M R)
/-- Interpret `Finsupp.mapDomain` as a linear map. -/
def lmapDomain (f : α → α') : (α →₀ M) →ₗ[R] α' →₀ M where
toFun := mapDomain f
map_add' _ _ := mapDomain_add
map_smul' := mapDomain_smul
#align finsupp.lmap_domain Finsupp.lmapDomain
@[simp]
theorem lmapDomain_apply (f : α → α') (l : α →₀ M) :
(lmapDomain M R f : (α →₀ M) →ₗ[R] α' →₀ M) l = mapDomain f l :=
rfl
#align finsupp.lmap_domain_apply Finsupp.lmapDomain_apply
@[simp]
theorem lmapDomain_id : (lmapDomain M R _root_.id : (α →₀ M) →ₗ[R] α →₀ M) = LinearMap.id :=
LinearMap.ext fun _ => mapDomain_id
#align finsupp.lmap_domain_id Finsupp.lmapDomain_id
theorem lmapDomain_comp (f : α → α') (g : α' → α'') :
lmapDomain M R (g ∘ f) = (lmapDomain M R g).comp (lmapDomain M R f) :=
LinearMap.ext fun _ => mapDomain_comp
#align finsupp.lmap_domain_comp Finsupp.lmapDomain_comp
theorem supported_comap_lmapDomain (f : α → α') (s : Set α') :
supported M R (f ⁻¹' s) ≤ (supported M R s).comap (lmapDomain M R f) := by
classical
intro l (hl : (l.support : Set α) ⊆ f ⁻¹' s)
show ↑(mapDomain f l).support ⊆ s
rw [← Set.image_subset_iff, ← Finset.coe_image] at hl
exact Set.Subset.trans mapDomain_support hl
#align finsupp.supported_comap_lmap_domain Finsupp.supported_comap_lmapDomain
theorem lmapDomain_supported (f : α → α') (s : Set α) :
(supported M R s).map (lmapDomain M R f) = supported M R (f '' s) := by
classical
cases isEmpty_or_nonempty α
· simp [s.eq_empty_of_isEmpty]
refine
le_antisymm
(map_le_iff_le_comap.2 <|
le_trans (supported_mono <| Set.subset_preimage_image _ _)
(supported_comap_lmapDomain M R _ _))
?_
intro l hl
refine ⟨(lmapDomain M R (Function.invFunOn f s) : (α' →₀ M) →ₗ[R] α →₀ M) l, fun x hx => ?_, ?_⟩
· rcases Finset.mem_image.1 (mapDomain_support hx) with ⟨c, hc, rfl⟩
exact Function.invFunOn_mem (by simpa using hl hc)
· rw [← LinearMap.comp_apply, ← lmapDomain_comp]
refine (mapDomain_congr fun c hc => ?_).trans mapDomain_id
exact Function.invFunOn_eq (by simpa using hl hc)
#align finsupp.lmap_domain_supported Finsupp.lmapDomain_supported
theorem lmapDomain_disjoint_ker (f : α → α') {s : Set α}
(H : ∀ a ∈ s, ∀ b ∈ s, f a = f b → a = b) :
Disjoint (supported M R s) (ker (lmapDomain M R f)) := by
rw [disjoint_iff_inf_le]
rintro l ⟨h₁, h₂⟩
rw [SetLike.mem_coe, mem_ker, lmapDomain_apply, mapDomain] at h₂
simp; ext x
haveI := Classical.decPred fun x => x ∈ s
by_cases xs : x ∈ s
· have : Finsupp.sum l (fun a => Finsupp.single (f a)) (f x) = 0 := by
rw [h₂]
rfl
rw [Finsupp.sum_apply, Finsupp.sum_eq_single x, single_eq_same] at this
· simpa
· intro y hy xy
simp only [SetLike.mem_coe, mem_supported, subset_def, Finset.mem_coe, mem_support_iff] at h₁
simp [mt (H _ (h₁ _ hy) _ xs) xy]
· simp (config := { contextual := true })
· by_contra h
exact xs (h₁ <| Finsupp.mem_support_iff.2 h)
#align finsupp.lmap_domain_disjoint_ker Finsupp.lmapDomain_disjoint_ker
end LMapDomain
section LComapDomain
variable {β : Type*}
/-- Given `f : α → β` and a proof `hf` that `f` is injective, `lcomapDomain f hf` is the linear map
sending `l : β →₀ M` to the finitely supported function from `α` to `M` given by composing
`l` with `f`.
This is the linear version of `Finsupp.comapDomain`. -/
def lcomapDomain (f : α → β) (hf : Function.Injective f) : (β →₀ M) →ₗ[R] α →₀ M where
toFun l := Finsupp.comapDomain f l hf.injOn
map_add' x y := by ext; simp
map_smul' c x := by ext; simp
#align finsupp.lcomap_domain Finsupp.lcomapDomain
end LComapDomain
section Total
variable (α) (M) (R)
variable {α' : Type*} {M' : Type*} [AddCommMonoid M'] [Module R M'] (v : α → M) {v' : α' → M'}
/-- Interprets (l : α →₀ R) as linear combination of the elements in the family (v : α → M) and
evaluates this linear combination. -/
protected def total : (α →₀ R) →ₗ[R] M :=
Finsupp.lsum ℕ fun i => LinearMap.id.smulRight (v i)
#align finsupp.total Finsupp.total
variable {α M v}
theorem total_apply (l : α →₀ R) : Finsupp.total α M R v l = l.sum fun i a => a • v i :=
rfl
#align finsupp.total_apply Finsupp.total_apply
theorem total_apply_of_mem_supported {l : α →₀ R} {s : Finset α}
(hs : l ∈ supported R R (↑s : Set α)) : Finsupp.total α M R v l = s.sum fun i => l i • v i :=
Finset.sum_subset hs fun x _ hxg =>
show l x • v x = 0 by rw [not_mem_support_iff.1 hxg, zero_smul]
#align finsupp.total_apply_of_mem_supported Finsupp.total_apply_of_mem_supported
@[simp]
theorem total_single (c : R) (a : α) : Finsupp.total α M R v (single a c) = c • v a := by
simp [total_apply, sum_single_index]
#align finsupp.total_single Finsupp.total_single
theorem total_zero_apply (x : α →₀ R) : (Finsupp.total α M R 0) x = 0 := by
simp [Finsupp.total_apply]
#align finsupp.total_zero_apply Finsupp.total_zero_apply
variable (α M)
@[simp]
theorem total_zero : Finsupp.total α M R 0 = 0 :=
LinearMap.ext (total_zero_apply R)
#align finsupp.total_zero Finsupp.total_zero
variable {α M}
theorem apply_total (f : M →ₗ[R] M') (v) (l : α →₀ R) :
f (Finsupp.total α M R v l) = Finsupp.total α M' R (f ∘ v) l := by
apply Finsupp.induction_linear l <;> simp (config := { contextual := true })
#align finsupp.apply_total Finsupp.apply_total
theorem apply_total_id (f : M →ₗ[R] M') (l : M →₀ R) :
f (Finsupp.total M M R _root_.id l) = Finsupp.total M M' R f l :=
apply_total ..
theorem total_unique [Unique α] (l : α →₀ R) (v) :
Finsupp.total α M R v l = l default • v default := by rw [← total_single, ← unique_single l]
#align finsupp.total_unique Finsupp.total_unique
theorem total_surjective (h : Function.Surjective v) :
Function.Surjective (Finsupp.total α M R v) := by
intro x
obtain ⟨y, hy⟩ := h x
exact ⟨Finsupp.single y 1, by simp [hy]⟩
#align finsupp.total_surjective Finsupp.total_surjective
theorem total_range (h : Function.Surjective v) : LinearMap.range (Finsupp.total α M R v) = ⊤ :=
range_eq_top.2 <| total_surjective R h
#align finsupp.total_range Finsupp.total_range
/-- Any module is a quotient of a free module. This is stated as surjectivity of
`Finsupp.total M M R id : (M →₀ R) →ₗ[R] M`. -/
theorem total_id_surjective (M) [AddCommMonoid M] [Module R M] :
Function.Surjective (Finsupp.total M M R _root_.id) :=
total_surjective R Function.surjective_id
#align finsupp.total_id_surjective Finsupp.total_id_surjective
theorem range_total : LinearMap.range (Finsupp.total α M R v) = span R (range v) := by
ext x
constructor
· intro hx
rw [LinearMap.mem_range] at hx
rcases hx with ⟨l, hl⟩
rw [← hl]
rw [Finsupp.total_apply]
exact sum_mem fun i _ => Submodule.smul_mem _ _ (subset_span (mem_range_self i))
· apply span_le.2
intro x hx
rcases hx with ⟨i, hi⟩
rw [SetLike.mem_coe, LinearMap.mem_range]
use Finsupp.single i 1
simp [hi]
#align finsupp.range_total Finsupp.range_total
theorem lmapDomain_total (f : α → α') (g : M →ₗ[R] M') (h : ∀ i, g (v i) = v' (f i)) :
(Finsupp.total α' M' R v').comp (lmapDomain R R f) = g.comp (Finsupp.total α M R v) := by
ext l
simp [total_apply, Finsupp.sum_mapDomain_index, add_smul, h]
#align finsupp.lmap_domain_total Finsupp.lmapDomain_total
| Mathlib/LinearAlgebra/Finsupp.lean | 746 | 749 | theorem total_comp_lmapDomain (f : α → α') :
(Finsupp.total α' M' R v').comp (Finsupp.lmapDomain R R f) = Finsupp.total α M' R (v' ∘ f) := by |
ext
simp
|
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Johannes Hölzl, Scott Morrison, Jens Wagemaker
-/
import Mathlib.Algebra.Polynomial.Inductions
import Mathlib.Algebra.Polynomial.Monic
import Mathlib.RingTheory.Multiplicity
import Mathlib.RingTheory.Ideal.Maps
#align_import data.polynomial.div from "leanprover-community/mathlib"@"e1e7190efdcefc925cb36f257a8362ef22944204"
/-!
# Division of univariate polynomials
The main defs are `divByMonic` and `modByMonic`.
The compatibility between these is given by `modByMonic_add_div`.
We also define `rootMultiplicity`.
-/
noncomputable section
open Polynomial
open Finset
namespace Polynomial
universe u v w z
variable {R : Type u} {S : Type v} {T : Type w} {A : Type z} {a b : R} {n : ℕ}
section Semiring
variable [Semiring R]
theorem X_dvd_iff {f : R[X]} : X ∣ f ↔ f.coeff 0 = 0 :=
⟨fun ⟨g, hfg⟩ => by rw [hfg, coeff_X_mul_zero], fun hf =>
⟨f.divX, by rw [← add_zero (X * f.divX), ← C_0, ← hf, X_mul_divX_add]⟩⟩
set_option linter.uppercaseLean3 false in
#align polynomial.X_dvd_iff Polynomial.X_dvd_iff
theorem X_pow_dvd_iff {f : R[X]} {n : ℕ} : X ^ n ∣ f ↔ ∀ d < n, f.coeff d = 0 :=
⟨fun ⟨g, hgf⟩ d hd => by
simp only [hgf, coeff_X_pow_mul', ite_eq_right_iff, not_le_of_lt hd, IsEmpty.forall_iff],
fun hd => by
induction' n with n hn
· simp [pow_zero, one_dvd]
· obtain ⟨g, hgf⟩ := hn fun d : ℕ => fun H : d < n => hd _ (Nat.lt_succ_of_lt H)
have := coeff_X_pow_mul g n 0
rw [zero_add, ← hgf, hd n (Nat.lt_succ_self n)] at this
obtain ⟨k, hgk⟩ := Polynomial.X_dvd_iff.mpr this.symm
use k
rwa [pow_succ, mul_assoc, ← hgk]⟩
set_option linter.uppercaseLean3 false in
#align polynomial.X_pow_dvd_iff Polynomial.X_pow_dvd_iff
variable {p q : R[X]}
theorem multiplicity_finite_of_degree_pos_of_monic (hp : (0 : WithBot ℕ) < degree p) (hmp : Monic p)
(hq : q ≠ 0) : multiplicity.Finite p q :=
have zn0 : (0 : R) ≠ 1 :=
haveI := Nontrivial.of_polynomial_ne hq
zero_ne_one
⟨natDegree q, fun ⟨r, hr⟩ => by
have hp0 : p ≠ 0 := fun hp0 => by simp [hp0] at hp
have hr0 : r ≠ 0 := fun hr0 => by subst hr0; simp [hq] at hr
have hpn1 : leadingCoeff p ^ (natDegree q + 1) = 1 := by simp [show _ = _ from hmp]
have hpn0' : leadingCoeff p ^ (natDegree q + 1) ≠ 0 := hpn1.symm ▸ zn0.symm
have hpnr0 : leadingCoeff (p ^ (natDegree q + 1)) * leadingCoeff r ≠ 0 := by
simp only [leadingCoeff_pow' hpn0', leadingCoeff_eq_zero, hpn1, one_pow, one_mul, Ne,
hr0, not_false_eq_true]
have hnp : 0 < natDegree p := Nat.cast_lt.1 <| by
rw [← degree_eq_natDegree hp0]; exact hp
have := congr_arg natDegree hr
rw [natDegree_mul' hpnr0, natDegree_pow' hpn0', add_mul, add_assoc] at this
exact
ne_of_lt
(lt_add_of_le_of_pos (le_mul_of_one_le_right (Nat.zero_le _) hnp)
(add_pos_of_pos_of_nonneg (by rwa [one_mul]) (Nat.zero_le _)))
this⟩
#align polynomial.multiplicity_finite_of_degree_pos_of_monic Polynomial.multiplicity_finite_of_degree_pos_of_monic
end Semiring
section Ring
variable [Ring R] {p q : R[X]}
theorem div_wf_lemma (h : degree q ≤ degree p ∧ p ≠ 0) (hq : Monic q) :
degree (p - q * (C (leadingCoeff p) * X ^ (natDegree p - natDegree q))) < degree p :=
have hp : leadingCoeff p ≠ 0 := mt leadingCoeff_eq_zero.1 h.2
have hq0 : q ≠ 0 := hq.ne_zero_of_polynomial_ne h.2
have hlt : natDegree q ≤ natDegree p :=
Nat.cast_le.1
(by rw [← degree_eq_natDegree h.2, ← degree_eq_natDegree hq0]; exact h.1)
degree_sub_lt
(by
rw [hq.degree_mul_comm, hq.degree_mul, degree_C_mul_X_pow _ hp, degree_eq_natDegree h.2,
degree_eq_natDegree hq0, ← Nat.cast_add, tsub_add_cancel_of_le hlt])
h.2 (by rw [leadingCoeff_monic_mul hq, leadingCoeff_mul_X_pow, leadingCoeff_C])
#align polynomial.div_wf_lemma Polynomial.div_wf_lemma
/-- See `divByMonic`. -/
noncomputable def divModByMonicAux : ∀ (_p : R[X]) {q : R[X]}, Monic q → R[X] × R[X]
| p, q, hq =>
letI := Classical.decEq R
if h : degree q ≤ degree p ∧ p ≠ 0 then
let z := C (leadingCoeff p) * X ^ (natDegree p - natDegree q)
have _wf := div_wf_lemma h hq
let dm := divModByMonicAux (p - q * z) hq
⟨z + dm.1, dm.2⟩
else ⟨0, p⟩
termination_by p => p
#align polynomial.div_mod_by_monic_aux Polynomial.divModByMonicAux
/-- `divByMonic` gives the quotient of `p` by a monic polynomial `q`. -/
def divByMonic (p q : R[X]) : R[X] :=
letI := Classical.decEq R
if hq : Monic q then (divModByMonicAux p hq).1 else 0
#align polynomial.div_by_monic Polynomial.divByMonic
/-- `modByMonic` gives the remainder of `p` by a monic polynomial `q`. -/
def modByMonic (p q : R[X]) : R[X] :=
letI := Classical.decEq R
if hq : Monic q then (divModByMonicAux p hq).2 else p
#align polynomial.mod_by_monic Polynomial.modByMonic
@[inherit_doc]
infixl:70 " /ₘ " => divByMonic
@[inherit_doc]
infixl:70 " %ₘ " => modByMonic
theorem degree_modByMonic_lt [Nontrivial R] :
∀ (p : R[X]) {q : R[X]} (_hq : Monic q), degree (p %ₘ q) < degree q
| p, q, hq =>
letI := Classical.decEq R
if h : degree q ≤ degree p ∧ p ≠ 0 then by
have _wf := div_wf_lemma ⟨h.1, h.2⟩ hq
have :=
degree_modByMonic_lt (p - q * (C (leadingCoeff p) * X ^ (natDegree p - natDegree q))) hq
unfold modByMonic at this ⊢
unfold divModByMonicAux
dsimp
rw [dif_pos hq] at this ⊢
rw [if_pos h]
exact this
else
Or.casesOn (not_and_or.1 h)
(by
unfold modByMonic divModByMonicAux
dsimp
rw [dif_pos hq, if_neg h]
exact lt_of_not_ge)
(by
intro hp
unfold modByMonic divModByMonicAux
dsimp
rw [dif_pos hq, if_neg h, Classical.not_not.1 hp]
exact lt_of_le_of_ne bot_le (Ne.symm (mt degree_eq_bot.1 hq.ne_zero)))
termination_by p => p
#align polynomial.degree_mod_by_monic_lt Polynomial.degree_modByMonic_lt
theorem natDegree_modByMonic_lt (p : R[X]) {q : R[X]} (hmq : Monic q) (hq : q ≠ 1) :
natDegree (p %ₘ q) < q.natDegree := by
by_cases hpq : p %ₘ q = 0
· rw [hpq, natDegree_zero, Nat.pos_iff_ne_zero]
contrapose! hq
exact eq_one_of_monic_natDegree_zero hmq hq
· haveI := Nontrivial.of_polynomial_ne hpq
exact natDegree_lt_natDegree hpq (degree_modByMonic_lt p hmq)
@[simp]
theorem zero_modByMonic (p : R[X]) : 0 %ₘ p = 0 := by
classical
unfold modByMonic divModByMonicAux
dsimp
by_cases hp : Monic p
· rw [dif_pos hp, if_neg (mt And.right (not_not_intro rfl))]
· rw [dif_neg hp]
#align polynomial.zero_mod_by_monic Polynomial.zero_modByMonic
@[simp]
theorem zero_divByMonic (p : R[X]) : 0 /ₘ p = 0 := by
classical
unfold divByMonic divModByMonicAux
dsimp
by_cases hp : Monic p
· rw [dif_pos hp, if_neg (mt And.right (not_not_intro rfl))]
· rw [dif_neg hp]
#align polynomial.zero_div_by_monic Polynomial.zero_divByMonic
@[simp]
theorem modByMonic_zero (p : R[X]) : p %ₘ 0 = p :=
letI := Classical.decEq R
if h : Monic (0 : R[X]) then by
haveI := monic_zero_iff_subsingleton.mp h
simp [eq_iff_true_of_subsingleton]
else by unfold modByMonic divModByMonicAux; rw [dif_neg h]
#align polynomial.mod_by_monic_zero Polynomial.modByMonic_zero
@[simp]
theorem divByMonic_zero (p : R[X]) : p /ₘ 0 = 0 :=
letI := Classical.decEq R
if h : Monic (0 : R[X]) then by
haveI := monic_zero_iff_subsingleton.mp h
simp [eq_iff_true_of_subsingleton]
else by unfold divByMonic divModByMonicAux; rw [dif_neg h]
#align polynomial.div_by_monic_zero Polynomial.divByMonic_zero
theorem divByMonic_eq_of_not_monic (p : R[X]) (hq : ¬Monic q) : p /ₘ q = 0 :=
dif_neg hq
#align polynomial.div_by_monic_eq_of_not_monic Polynomial.divByMonic_eq_of_not_monic
theorem modByMonic_eq_of_not_monic (p : R[X]) (hq : ¬Monic q) : p %ₘ q = p :=
dif_neg hq
#align polynomial.mod_by_monic_eq_of_not_monic Polynomial.modByMonic_eq_of_not_monic
theorem modByMonic_eq_self_iff [Nontrivial R] (hq : Monic q) : p %ₘ q = p ↔ degree p < degree q :=
⟨fun h => h ▸ degree_modByMonic_lt _ hq, fun h => by
classical
have : ¬degree q ≤ degree p := not_le_of_gt h
unfold modByMonic divModByMonicAux; dsimp; rw [dif_pos hq, if_neg (mt And.left this)]⟩
#align polynomial.mod_by_monic_eq_self_iff Polynomial.modByMonic_eq_self_iff
theorem degree_modByMonic_le (p : R[X]) {q : R[X]} (hq : Monic q) : degree (p %ₘ q) ≤ degree q := by
nontriviality R
exact (degree_modByMonic_lt _ hq).le
#align polynomial.degree_mod_by_monic_le Polynomial.degree_modByMonic_le
theorem natDegree_modByMonic_le (p : Polynomial R) {g : Polynomial R} (hg : g.Monic) :
natDegree (p %ₘ g) ≤ g.natDegree :=
natDegree_le_natDegree (degree_modByMonic_le p hg)
theorem X_dvd_sub_C : X ∣ p - C (p.coeff 0) := by
simp [X_dvd_iff, coeff_C]
theorem modByMonic_eq_sub_mul_div :
∀ (p : R[X]) {q : R[X]} (_hq : Monic q), p %ₘ q = p - q * (p /ₘ q)
| p, q, hq =>
letI := Classical.decEq R
if h : degree q ≤ degree p ∧ p ≠ 0 then by
have _wf := div_wf_lemma h hq
have ih := modByMonic_eq_sub_mul_div
(p - q * (C (leadingCoeff p) * X ^ (natDegree p - natDegree q))) hq
unfold modByMonic divByMonic divModByMonicAux
dsimp
rw [dif_pos hq, if_pos h]
rw [modByMonic, dif_pos hq] at ih
refine ih.trans ?_
unfold divByMonic
rw [dif_pos hq, dif_pos hq, if_pos h, mul_add, sub_add_eq_sub_sub]
else by
unfold modByMonic divByMonic divModByMonicAux
dsimp
rw [dif_pos hq, if_neg h, dif_pos hq, if_neg h, mul_zero, sub_zero]
termination_by p => p
#align polynomial.mod_by_monic_eq_sub_mul_div Polynomial.modByMonic_eq_sub_mul_div
theorem modByMonic_add_div (p : R[X]) {q : R[X]} (hq : Monic q) : p %ₘ q + q * (p /ₘ q) = p :=
eq_sub_iff_add_eq.1 (modByMonic_eq_sub_mul_div p hq)
#align polynomial.mod_by_monic_add_div Polynomial.modByMonic_add_div
theorem divByMonic_eq_zero_iff [Nontrivial R] (hq : Monic q) : p /ₘ q = 0 ↔ degree p < degree q :=
⟨fun h => by
have := modByMonic_add_div p hq;
rwa [h, mul_zero, add_zero, modByMonic_eq_self_iff hq] at this,
fun h => by
classical
have : ¬degree q ≤ degree p := not_le_of_gt h
unfold divByMonic divModByMonicAux; dsimp; rw [dif_pos hq, if_neg (mt And.left this)]⟩
#align polynomial.div_by_monic_eq_zero_iff Polynomial.divByMonic_eq_zero_iff
theorem degree_add_divByMonic (hq : Monic q) (h : degree q ≤ degree p) :
degree q + degree (p /ₘ q) = degree p := by
nontriviality R
have hdiv0 : p /ₘ q ≠ 0 := by rwa [Ne, divByMonic_eq_zero_iff hq, not_lt]
have hlc : leadingCoeff q * leadingCoeff (p /ₘ q) ≠ 0 := by
rwa [Monic.def.1 hq, one_mul, Ne, leadingCoeff_eq_zero]
have hmod : degree (p %ₘ q) < degree (q * (p /ₘ q)) :=
calc
degree (p %ₘ q) < degree q := degree_modByMonic_lt _ hq
_ ≤ _ := by
rw [degree_mul' hlc, degree_eq_natDegree hq.ne_zero, degree_eq_natDegree hdiv0, ←
Nat.cast_add, Nat.cast_le]
exact Nat.le_add_right _ _
calc
degree q + degree (p /ₘ q) = degree (q * (p /ₘ q)) := Eq.symm (degree_mul' hlc)
_ = degree (p %ₘ q + q * (p /ₘ q)) := (degree_add_eq_right_of_degree_lt hmod).symm
_ = _ := congr_arg _ (modByMonic_add_div _ hq)
#align polynomial.degree_add_div_by_monic Polynomial.degree_add_divByMonic
theorem degree_divByMonic_le (p q : R[X]) : degree (p /ₘ q) ≤ degree p :=
letI := Classical.decEq R
if hp0 : p = 0 then by simp only [hp0, zero_divByMonic, le_refl]
else
if hq : Monic q then
if h : degree q ≤ degree p then by
haveI := Nontrivial.of_polynomial_ne hp0;
rw [← degree_add_divByMonic hq h, degree_eq_natDegree hq.ne_zero,
degree_eq_natDegree (mt (divByMonic_eq_zero_iff hq).1 (not_lt.2 h))];
exact WithBot.coe_le_coe.2 (Nat.le_add_left _ _)
else by
unfold divByMonic divModByMonicAux;
simp [dif_pos hq, h, false_and_iff, if_false, degree_zero, bot_le]
else (divByMonic_eq_of_not_monic p hq).symm ▸ bot_le
#align polynomial.degree_div_by_monic_le Polynomial.degree_divByMonic_le
theorem degree_divByMonic_lt (p : R[X]) {q : R[X]} (hq : Monic q) (hp0 : p ≠ 0)
(h0q : 0 < degree q) : degree (p /ₘ q) < degree p :=
if hpq : degree p < degree q then by
haveI := Nontrivial.of_polynomial_ne hp0
rw [(divByMonic_eq_zero_iff hq).2 hpq, degree_eq_natDegree hp0]
exact WithBot.bot_lt_coe _
else by
haveI := Nontrivial.of_polynomial_ne hp0
rw [← degree_add_divByMonic hq (not_lt.1 hpq), degree_eq_natDegree hq.ne_zero,
degree_eq_natDegree (mt (divByMonic_eq_zero_iff hq).1 hpq)]
exact
Nat.cast_lt.2
(Nat.lt_add_of_pos_left (Nat.cast_lt.1 <|
by simpa [degree_eq_natDegree hq.ne_zero] using h0q))
#align polynomial.degree_div_by_monic_lt Polynomial.degree_divByMonic_lt
theorem natDegree_divByMonic (f : R[X]) {g : R[X]} (hg : g.Monic) :
natDegree (f /ₘ g) = natDegree f - natDegree g := by
nontriviality R
by_cases hfg : f /ₘ g = 0
· rw [hfg, natDegree_zero]
rw [divByMonic_eq_zero_iff hg] at hfg
rw [tsub_eq_zero_iff_le.mpr (natDegree_le_natDegree <| le_of_lt hfg)]
have hgf := hfg
rw [divByMonic_eq_zero_iff hg] at hgf
push_neg at hgf
have := degree_add_divByMonic hg hgf
have hf : f ≠ 0 := by
intro hf
apply hfg
rw [hf, zero_divByMonic]
rw [degree_eq_natDegree hf, degree_eq_natDegree hg.ne_zero, degree_eq_natDegree hfg,
← Nat.cast_add, Nat.cast_inj] at this
rw [← this, add_tsub_cancel_left]
#align polynomial.nat_degree_div_by_monic Polynomial.natDegree_divByMonic
theorem div_modByMonic_unique {f g} (q r : R[X]) (hg : Monic g)
(h : r + g * q = f ∧ degree r < degree g) : f /ₘ g = q ∧ f %ₘ g = r := by
nontriviality R
have h₁ : r - f %ₘ g = -g * (q - f /ₘ g) :=
eq_of_sub_eq_zero
(by
rw [← sub_eq_zero_of_eq (h.1.trans (modByMonic_add_div f hg).symm)]
simp [mul_add, mul_comm, sub_eq_add_neg, add_comm, add_left_comm, add_assoc])
have h₂ : degree (r - f %ₘ g) = degree (g * (q - f /ₘ g)) := by simp [h₁]
have h₄ : degree (r - f %ₘ g) < degree g :=
calc
degree (r - f %ₘ g) ≤ max (degree r) (degree (f %ₘ g)) := degree_sub_le _ _
_ < degree g := max_lt_iff.2 ⟨h.2, degree_modByMonic_lt _ hg⟩
have h₅ : q - f /ₘ g = 0 :=
_root_.by_contradiction fun hqf =>
not_le_of_gt h₄ <|
calc
degree g ≤ degree g + degree (q - f /ₘ g) := by
erw [degree_eq_natDegree hg.ne_zero, degree_eq_natDegree hqf, WithBot.coe_le_coe]
exact Nat.le_add_right _ _
_ = degree (r - f %ₘ g) := by rw [h₂, degree_mul']; simpa [Monic.def.1 hg]
exact ⟨Eq.symm <| eq_of_sub_eq_zero h₅, Eq.symm <| eq_of_sub_eq_zero <| by simpa [h₅] using h₁⟩
#align polynomial.div_mod_by_monic_unique Polynomial.div_modByMonic_unique
theorem map_mod_divByMonic [Ring S] (f : R →+* S) (hq : Monic q) :
(p /ₘ q).map f = p.map f /ₘ q.map f ∧ (p %ₘ q).map f = p.map f %ₘ q.map f := by
nontriviality S
haveI : Nontrivial R := f.domain_nontrivial
have : map f p /ₘ map f q = map f (p /ₘ q) ∧ map f p %ₘ map f q = map f (p %ₘ q) :=
div_modByMonic_unique ((p /ₘ q).map f) _ (hq.map f)
⟨Eq.symm <| by rw [← Polynomial.map_mul, ← Polynomial.map_add, modByMonic_add_div _ hq],
calc
_ ≤ degree (p %ₘ q) := degree_map_le _ _
_ < degree q := degree_modByMonic_lt _ hq
_ = _ :=
Eq.symm <|
degree_map_eq_of_leadingCoeff_ne_zero _
(by rw [Monic.def.1 hq, f.map_one]; exact one_ne_zero)⟩
exact ⟨this.1.symm, this.2.symm⟩
#align polynomial.map_mod_div_by_monic Polynomial.map_mod_divByMonic
theorem map_divByMonic [Ring S] (f : R →+* S) (hq : Monic q) :
(p /ₘ q).map f = p.map f /ₘ q.map f :=
(map_mod_divByMonic f hq).1
#align polynomial.map_div_by_monic Polynomial.map_divByMonic
theorem map_modByMonic [Ring S] (f : R →+* S) (hq : Monic q) :
(p %ₘ q).map f = p.map f %ₘ q.map f :=
(map_mod_divByMonic f hq).2
#align polynomial.map_mod_by_monic Polynomial.map_modByMonic
theorem modByMonic_eq_zero_iff_dvd (hq : Monic q) : p %ₘ q = 0 ↔ q ∣ p :=
⟨fun h => by rw [← modByMonic_add_div p hq, h, zero_add]; exact dvd_mul_right _ _, fun h => by
nontriviality R
obtain ⟨r, hr⟩ := exists_eq_mul_right_of_dvd h
by_contra hpq0
have hmod : p %ₘ q = q * (r - p /ₘ q) := by rw [modByMonic_eq_sub_mul_div _ hq, mul_sub, ← hr]
have : degree (q * (r - p /ₘ q)) < degree q := hmod ▸ degree_modByMonic_lt _ hq
have hrpq0 : leadingCoeff (r - p /ₘ q) ≠ 0 := fun h =>
hpq0 <|
leadingCoeff_eq_zero.1
(by rw [hmod, leadingCoeff_eq_zero.1 h, mul_zero, leadingCoeff_zero])
have hlc : leadingCoeff q * leadingCoeff (r - p /ₘ q) ≠ 0 := by rwa [Monic.def.1 hq, one_mul]
rw [degree_mul' hlc, degree_eq_natDegree hq.ne_zero,
degree_eq_natDegree (mt leadingCoeff_eq_zero.2 hrpq0)] at this
exact not_lt_of_ge (Nat.le_add_right _ _) (WithBot.coe_lt_coe.1 this)⟩
#align polynomial.dvd_iff_mod_by_monic_eq_zero Polynomial.modByMonic_eq_zero_iff_dvd
@[deprecated (since := "2024-03-23")] alias dvd_iff_modByMonic_eq_zero := modByMonic_eq_zero_iff_dvd
/-- See `Polynomial.mul_left_modByMonic` for the other multiplication order. That version, unlike
this one, requires commutativity. -/
@[simp]
lemma self_mul_modByMonic (hq : q.Monic) : (q * p) %ₘ q = 0 := by
rw [modByMonic_eq_zero_iff_dvd hq]
exact dvd_mul_right q p
theorem map_dvd_map [Ring S] (f : R →+* S) (hf : Function.Injective f) {x y : R[X]}
(hx : x.Monic) : x.map f ∣ y.map f ↔ x ∣ y := by
rw [← modByMonic_eq_zero_iff_dvd hx, ← modByMonic_eq_zero_iff_dvd (hx.map f), ←
map_modByMonic f hx]
exact
⟨fun H => map_injective f hf <| by rw [H, Polynomial.map_zero], fun H => by
rw [H, Polynomial.map_zero]⟩
#align polynomial.map_dvd_map Polynomial.map_dvd_map
@[simp]
theorem modByMonic_one (p : R[X]) : p %ₘ 1 = 0 :=
(modByMonic_eq_zero_iff_dvd (by convert monic_one (R := R))).2 (one_dvd _)
#align polynomial.mod_by_monic_one Polynomial.modByMonic_one
@[simp]
theorem divByMonic_one (p : R[X]) : p /ₘ 1 = p := by
conv_rhs => rw [← modByMonic_add_div p monic_one]; simp
#align polynomial.div_by_monic_one Polynomial.divByMonic_one
theorem sum_modByMonic_coeff (hq : q.Monic) {n : ℕ} (hn : q.degree ≤ n) :
(∑ i : Fin n, monomial i ((p %ₘ q).coeff i)) = p %ₘ q := by
nontriviality R
exact
(sum_fin (fun i c => monomial i c) (by simp) ((degree_modByMonic_lt _ hq).trans_le hn)).trans
(sum_monomial_eq _)
#align polynomial.sum_mod_by_monic_coeff Polynomial.sum_modByMonic_coeff
theorem mul_div_mod_by_monic_cancel_left (p : R[X]) {q : R[X]} (hmo : q.Monic) :
q * p /ₘ q = p := by
nontriviality R
refine (div_modByMonic_unique _ 0 hmo ⟨by rw [zero_add], ?_⟩).1
rw [degree_zero]
exact Ne.bot_lt fun h => hmo.ne_zero (degree_eq_bot.1 h)
#align polynomial.mul_div_mod_by_monic_cancel_left Polynomial.mul_div_mod_by_monic_cancel_left
lemma coeff_divByMonic_X_sub_C_rec (p : R[X]) (a : R) (n : ℕ) :
(p /ₘ (X - C a)).coeff n = coeff p (n + 1) + a * (p /ₘ (X - C a)).coeff (n + 1) := by
nontriviality R
have := monic_X_sub_C a
set q := p /ₘ (X - C a)
rw [← p.modByMonic_add_div this]
have : degree (p %ₘ (X - C a)) < ↑(n + 1) := degree_X_sub_C a ▸ p.degree_modByMonic_lt this
|>.trans_le <| WithBot.coe_le_coe.mpr le_add_self
simp [sub_mul, add_sub, coeff_eq_zero_of_degree_lt this]
theorem coeff_divByMonic_X_sub_C (p : R[X]) (a : R) (n : ℕ) :
(p /ₘ (X - C a)).coeff n = ∑ i ∈ Icc (n + 1) p.natDegree, a ^ (i - (n + 1)) * p.coeff i := by
wlog h : p.natDegree ≤ n generalizing n
· refine Nat.decreasingInduction' (fun n hn _ ih ↦ ?_) (le_of_not_le h) ?_
· rw [coeff_divByMonic_X_sub_C_rec, ih, eq_comm, Icc_eq_cons_Ioc (Nat.succ_le.mpr hn),
sum_cons, Nat.sub_self, pow_zero, one_mul, mul_sum]
congr 1; refine sum_congr ?_ fun i hi ↦ ?_
· ext; simp [Nat.succ_le]
rw [← mul_assoc, ← pow_succ', eq_comm, i.sub_succ', Nat.sub_add_cancel]
apply Nat.le_sub_of_add_le
rw [add_comm]; exact (mem_Icc.mp hi).1
· exact this _ le_rfl
rw [Icc_eq_empty (Nat.lt_succ.mpr h).not_le, sum_empty]
nontriviality R
by_cases hp : p.natDegree = 0
· rw [(divByMonic_eq_zero_iff <| monic_X_sub_C a).mpr, coeff_zero]
apply degree_lt_degree; rw [hp, natDegree_X_sub_C]; norm_num
· apply coeff_eq_zero_of_natDegree_lt
rw [natDegree_divByMonic p (monic_X_sub_C a), natDegree_X_sub_C]
exact (Nat.pred_lt hp).trans_le h
variable (R) in
theorem not_isField : ¬IsField R[X] := by
nontriviality R
intro h
letI := h.toField
simpa using congr_arg natDegree (monic_X.eq_one_of_isUnit <| monic_X (R := R).ne_zero.isUnit)
#align polynomial.not_is_field Polynomial.not_isField
section multiplicity
/-- An algorithm for deciding polynomial divisibility.
The algorithm is "compute `p %ₘ q` and compare to `0`".
See `polynomial.modByMonic` for the algorithm that computes `%ₘ`.
-/
def decidableDvdMonic [DecidableEq R] (p : R[X]) (hq : Monic q) : Decidable (q ∣ p) :=
decidable_of_iff (p %ₘ q = 0) (modByMonic_eq_zero_iff_dvd hq)
#align polynomial.decidable_dvd_monic Polynomial.decidableDvdMonic
theorem multiplicity_X_sub_C_finite (a : R) (h0 : p ≠ 0) : multiplicity.Finite (X - C a) p := by
haveI := Nontrivial.of_polynomial_ne h0
refine multiplicity_finite_of_degree_pos_of_monic ?_ (monic_X_sub_C _) h0
rw [degree_X_sub_C]
decide
set_option linter.uppercaseLean3 false in
#align polynomial.multiplicity_X_sub_C_finite Polynomial.multiplicity_X_sub_C_finite
/- Porting note: stripping out classical for decidability instance parameter might
make for better ergonomics -/
/-- The largest power of `X - C a` which divides `p`.
This *could be* computable via the divisibility algorithm `Polynomial.decidableDvdMonic`,
as shown by `Polynomial.rootMultiplicity_eq_nat_find_of_nonzero` which has a computable RHS. -/
def rootMultiplicity (a : R) (p : R[X]) : ℕ :=
letI := Classical.decEq R
if h0 : p = 0 then 0
else
let _ : DecidablePred fun n : ℕ => ¬(X - C a) ^ (n + 1) ∣ p := fun n =>
@Not.decidable _ (decidableDvdMonic p ((monic_X_sub_C a).pow (n + 1)))
Nat.find (multiplicity_X_sub_C_finite a h0)
#align polynomial.root_multiplicity Polynomial.rootMultiplicity
/- Porting note: added the following due to diamond with decidableProp and
decidableDvdMonic see also [Zulip]
(https://leanprover.zulipchat.com/#narrow/stream/287929-mathlib4/topic/non-defeq.20aliased.20instance) -/
theorem rootMultiplicity_eq_nat_find_of_nonzero [DecidableEq R] {p : R[X]} (p0 : p ≠ 0) {a : R} :
letI : DecidablePred fun n : ℕ => ¬(X - C a) ^ (n + 1) ∣ p := fun n =>
@Not.decidable _ (decidableDvdMonic p ((monic_X_sub_C a).pow (n + 1)))
rootMultiplicity a p = Nat.find (multiplicity_X_sub_C_finite a p0) := by
dsimp [rootMultiplicity]
cases Subsingleton.elim ‹DecidableEq R› (Classical.decEq R)
rw [dif_neg p0]
theorem rootMultiplicity_eq_multiplicity [DecidableEq R] [@DecidableRel R[X] (· ∣ ·)]
(p : R[X]) (a : R) :
rootMultiplicity a p =
if h0 : p = 0 then 0 else (multiplicity (X - C a) p).get (multiplicity_X_sub_C_finite a h0) :=
by simp [multiplicity, rootMultiplicity, Part.Dom]; congr; funext; congr
#align polynomial.root_multiplicity_eq_multiplicity Polynomial.rootMultiplicity_eq_multiplicity
@[simp]
theorem rootMultiplicity_zero {x : R} : rootMultiplicity x 0 = 0 :=
dif_pos rfl
#align polynomial.root_multiplicity_zero Polynomial.rootMultiplicity_zero
@[simp]
theorem rootMultiplicity_C (r a : R) : rootMultiplicity a (C r) = 0 := by
cases subsingleton_or_nontrivial R
· rw [Subsingleton.elim (C r) 0, rootMultiplicity_zero]
classical
rw [rootMultiplicity_eq_multiplicity]
split_ifs with hr
· rfl
have h : natDegree (C r) < natDegree (X - C a) := by simp
simp_rw [multiplicity.multiplicity_eq_zero.mpr ((monic_X_sub_C a).not_dvd_of_natDegree_lt hr h),
PartENat.get_zero]
set_option linter.uppercaseLean3 false in
#align polynomial.root_multiplicity_C Polynomial.rootMultiplicity_C
theorem pow_rootMultiplicity_dvd (p : R[X]) (a : R) : (X - C a) ^ rootMultiplicity a p ∣ p :=
letI := Classical.decEq R
if h : p = 0 then by simp [h]
else by
classical
rw [rootMultiplicity_eq_multiplicity, dif_neg h]; exact multiplicity.pow_multiplicity_dvd _
#align polynomial.pow_root_multiplicity_dvd Polynomial.pow_rootMultiplicity_dvd
theorem pow_mul_divByMonic_rootMultiplicity_eq (p : R[X]) (a : R) :
(X - C a) ^ rootMultiplicity a p * (p /ₘ (X - C a) ^ rootMultiplicity a p) = p := by
have : Monic ((X - C a) ^ rootMultiplicity a p) := (monic_X_sub_C _).pow _
conv_rhs =>
rw [← modByMonic_add_div p this,
(modByMonic_eq_zero_iff_dvd this).2 (pow_rootMultiplicity_dvd _ _)]
simp
#align polynomial.div_by_monic_mul_pow_root_multiplicity_eq Polynomial.pow_mul_divByMonic_rootMultiplicity_eq
theorem exists_eq_pow_rootMultiplicity_mul_and_not_dvd (p : R[X]) (hp : p ≠ 0) (a : R) :
∃ q : R[X], p = (X - C a) ^ p.rootMultiplicity a * q ∧ ¬ (X - C a) ∣ q := by
classical
rw [rootMultiplicity_eq_multiplicity, dif_neg hp]
apply multiplicity.exists_eq_pow_mul_and_not_dvd
end multiplicity
end Ring
section CommRing
variable [CommRing R] {p q : R[X]}
@[simp]
theorem modByMonic_X_sub_C_eq_C_eval (p : R[X]) (a : R) : p %ₘ (X - C a) = C (p.eval a) := by
nontriviality R
have h : (p %ₘ (X - C a)).eval a = p.eval a := by
rw [modByMonic_eq_sub_mul_div _ (monic_X_sub_C a), eval_sub, eval_mul, eval_sub, eval_X,
eval_C, sub_self, zero_mul, sub_zero]
have : degree (p %ₘ (X - C a)) < 1 :=
degree_X_sub_C a ▸ degree_modByMonic_lt p (monic_X_sub_C a)
have : degree (p %ₘ (X - C a)) ≤ 0 := by
revert this
cases degree (p %ₘ (X - C a))
· exact fun _ => bot_le
· exact fun h => WithBot.coe_le_coe.2 (Nat.le_of_lt_succ (WithBot.coe_lt_coe.1 h))
rw [eq_C_of_degree_le_zero this, eval_C] at h
rw [eq_C_of_degree_le_zero this, h]
set_option linter.uppercaseLean3 false in
#align polynomial.mod_by_monic_X_sub_C_eq_C_eval Polynomial.modByMonic_X_sub_C_eq_C_eval
theorem mul_divByMonic_eq_iff_isRoot : (X - C a) * (p /ₘ (X - C a)) = p ↔ IsRoot p a :=
.trans
⟨fun h => by rw [← h, eval_mul, eval_sub, eval_X, eval_C, sub_self, zero_mul],
fun h => by
conv_rhs =>
rw [← modByMonic_add_div p (monic_X_sub_C a)]
rw [modByMonic_X_sub_C_eq_C_eval, h, C_0, zero_add]⟩
IsRoot.def.symm
#align polynomial.mul_div_by_monic_eq_iff_is_root Polynomial.mul_divByMonic_eq_iff_isRoot
theorem dvd_iff_isRoot : X - C a ∣ p ↔ IsRoot p a :=
⟨fun h => by
rwa [← modByMonic_eq_zero_iff_dvd (monic_X_sub_C _), modByMonic_X_sub_C_eq_C_eval, ← C_0,
C_inj] at h,
fun h => ⟨p /ₘ (X - C a), by rw [mul_divByMonic_eq_iff_isRoot.2 h]⟩⟩
#align polynomial.dvd_iff_is_root Polynomial.dvd_iff_isRoot
theorem X_sub_C_dvd_sub_C_eval : X - C a ∣ p - C (p.eval a) := by
rw [dvd_iff_isRoot, IsRoot, eval_sub, eval_C, sub_self]
set_option linter.uppercaseLean3 false in
#align polynomial.X_sub_C_dvd_sub_C_eval Polynomial.X_sub_C_dvd_sub_C_eval
theorem mem_span_C_X_sub_C_X_sub_C_iff_eval_eval_eq_zero {b : R[X]} {P : R[X][X]} :
P ∈ Ideal.span {C (X - C a), X - C b} ↔ (P.eval b).eval a = 0 := by
rw [Ideal.mem_span_pair]
constructor <;> intro h
· rcases h with ⟨_, _, rfl⟩
simp only [eval_C, eval_X, eval_add, eval_sub, eval_mul, add_zero, mul_zero, sub_self]
· rcases dvd_iff_isRoot.mpr h with ⟨p, hp⟩
rcases @X_sub_C_dvd_sub_C_eval _ b _ P with ⟨q, hq⟩
exact ⟨C p, q, by rw [mul_comm, mul_comm q, eq_add_of_sub_eq' hq, hp, C_mul]⟩
set_option linter.uppercaseLean3 false in
#align polynomial.mem_span_C_X_sub_C_X_sub_C_iff_eval_eval_eq_zero Polynomial.mem_span_C_X_sub_C_X_sub_C_iff_eval_eval_eq_zero
-- TODO: generalize this to Ring. In general, 0 can be replaced by any element in the center of R.
theorem modByMonic_X (p : R[X]) : p %ₘ X = C (p.eval 0) := by
rw [← modByMonic_X_sub_C_eq_C_eval, C_0, sub_zero]
set_option linter.uppercaseLean3 false in
#align polynomial.mod_by_monic_X Polynomial.modByMonic_X
| Mathlib/Algebra/Polynomial/Div.lean | 656 | 658 | theorem eval₂_modByMonic_eq_self_of_root [CommRing S] {f : R →+* S} {p q : R[X]} (hq : q.Monic)
{x : S} (hx : q.eval₂ f x = 0) : (p %ₘ q).eval₂ f x = p.eval₂ f x := by |
rw [modByMonic_eq_sub_mul_div p hq, eval₂_sub, eval₂_mul, hx, zero_mul, sub_zero]
|
/-
Copyright (c) 2014 Jeremy Avigad. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jeremy Avigad, Leonardo de Moura, Floris van Doorn, Yury Kudryashov, Neil Strickland
-/
import Mathlib.Algebra.Ring.Semiconj
import Mathlib.Algebra.Ring.Units
import Mathlib.Algebra.Group.Commute.Defs
import Mathlib.Data.Bracket
#align_import algebra.ring.commute from "leanprover-community/mathlib"@"70d50ecfd4900dd6d328da39ab7ebd516abe4025"
/-!
# Semirings and rings
This file gives lemmas about semirings, rings and domains.
This is analogous to `Mathlib.Algebra.Group.Basic`,
the difference being that the former is about `+` and `*` separately, while
the present file is about their interaction.
For the definitions of semirings and rings see `Mathlib.Algebra.Ring.Defs`.
-/
universe u v w x
variable {α : Type u} {β : Type v} {γ : Type w} {R : Type x}
open Function
namespace Commute
@[simp]
theorem add_right [Distrib R] {a b c : R} : Commute a b → Commute a c → Commute a (b + c) :=
SemiconjBy.add_right
#align commute.add_right Commute.add_rightₓ
-- for some reason mathport expected `Semiring` instead of `Distrib`?
@[simp]
theorem add_left [Distrib R] {a b c : R} : Commute a c → Commute b c → Commute (a + b) c :=
SemiconjBy.add_left
#align commute.add_left Commute.add_leftₓ
-- for some reason mathport expected `Semiring` instead of `Distrib`?
section deprecated
set_option linter.deprecated false
@[deprecated]
theorem bit0_right [Distrib R] {x y : R} (h : Commute x y) : Commute x (bit0 y) :=
h.add_right h
#align commute.bit0_right Commute.bit0_right
@[deprecated]
theorem bit0_left [Distrib R] {x y : R} (h : Commute x y) : Commute (bit0 x) y :=
h.add_left h
#align commute.bit0_left Commute.bit0_left
@[deprecated]
theorem bit1_right [NonAssocSemiring R] {x y : R} (h : Commute x y) : Commute x (bit1 y) :=
h.bit0_right.add_right (Commute.one_right x)
#align commute.bit1_right Commute.bit1_right
@[deprecated]
theorem bit1_left [NonAssocSemiring R] {x y : R} (h : Commute x y) : Commute (bit1 x) y :=
h.bit0_left.add_left (Commute.one_left y)
#align commute.bit1_left Commute.bit1_left
end deprecated
/-- Representation of a difference of two squares of commuting elements as a product. -/
theorem mul_self_sub_mul_self_eq [NonUnitalNonAssocRing R] {a b : R} (h : Commute a b) :
a * a - b * b = (a + b) * (a - b) := by
rw [add_mul, mul_sub, mul_sub, h.eq, sub_add_sub_cancel]
#align commute.mul_self_sub_mul_self_eq Commute.mul_self_sub_mul_self_eq
| Mathlib/Algebra/Ring/Commute.lean | 77 | 79 | theorem mul_self_sub_mul_self_eq' [NonUnitalNonAssocRing R] {a b : R} (h : Commute a b) :
a * a - b * b = (a - b) * (a + b) := by |
rw [mul_add, sub_mul, sub_mul, h.eq, sub_add_sub_cancel]
|
/-
Copyright (c) 2022 Joseph Myers. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joseph Myers, Heather Macbeth
-/
import Mathlib.Analysis.SpecialFunctions.Complex.Circle
import Mathlib.Geometry.Euclidean.Angle.Oriented.Basic
#align_import geometry.euclidean.angle.oriented.rotation from "leanprover-community/mathlib"@"f0c8bf9245297a541f468be517f1bde6195105e9"
/-!
# Rotations by oriented angles.
This file defines rotations by oriented angles in real inner product spaces.
## Main definitions
* `Orientation.rotation` is the rotation by an oriented angle with respect to an orientation.
-/
noncomputable section
open FiniteDimensional Complex
open scoped Real RealInnerProductSpace ComplexConjugate
namespace Orientation
attribute [local instance] Complex.finrank_real_complex_fact
variable {V V' : Type*}
variable [NormedAddCommGroup V] [NormedAddCommGroup V']
variable [InnerProductSpace ℝ V] [InnerProductSpace ℝ V']
variable [Fact (finrank ℝ V = 2)] [Fact (finrank ℝ V' = 2)] (o : Orientation ℝ V (Fin 2))
local notation "J" => o.rightAngleRotation
/-- Auxiliary construction to build a rotation by the oriented angle `θ`. -/
def rotationAux (θ : Real.Angle) : V →ₗᵢ[ℝ] V :=
LinearMap.isometryOfInner
(Real.Angle.cos θ • LinearMap.id +
Real.Angle.sin θ • (LinearIsometryEquiv.toLinearEquiv J).toLinearMap)
(by
intro x y
simp only [RCLike.conj_to_real, id, LinearMap.smul_apply, LinearMap.add_apply,
LinearMap.id_coe, LinearEquiv.coe_coe, LinearIsometryEquiv.coe_toLinearEquiv,
Orientation.areaForm_rightAngleRotation_left, Orientation.inner_rightAngleRotation_left,
Orientation.inner_rightAngleRotation_right, inner_add_left, inner_smul_left,
inner_add_right, inner_smul_right]
linear_combination inner (𝕜 := ℝ) x y * θ.cos_sq_add_sin_sq)
#align orientation.rotation_aux Orientation.rotationAux
@[simp]
theorem rotationAux_apply (θ : Real.Angle) (x : V) :
o.rotationAux θ x = Real.Angle.cos θ • x + Real.Angle.sin θ • J x :=
rfl
#align orientation.rotation_aux_apply Orientation.rotationAux_apply
/-- A rotation by the oriented angle `θ`. -/
def rotation (θ : Real.Angle) : V ≃ₗᵢ[ℝ] V :=
LinearIsometryEquiv.ofLinearIsometry (o.rotationAux θ)
(Real.Angle.cos θ • LinearMap.id -
Real.Angle.sin θ • (LinearIsometryEquiv.toLinearEquiv J).toLinearMap)
(by
ext x
convert congr_arg (fun t : ℝ => t • x) θ.cos_sq_add_sin_sq using 1
· simp only [o.rightAngleRotation_rightAngleRotation, o.rotationAux_apply,
Function.comp_apply, id, LinearEquiv.coe_coe, LinearIsometry.coe_toLinearMap,
LinearIsometryEquiv.coe_toLinearEquiv, map_smul, map_sub, LinearMap.coe_comp,
LinearMap.id_coe, LinearMap.smul_apply, LinearMap.sub_apply, ← mul_smul, add_smul,
smul_add, smul_neg, smul_sub, mul_comm, sq]
abel
· simp)
(by
ext x
convert congr_arg (fun t : ℝ => t • x) θ.cos_sq_add_sin_sq using 1
· simp only [o.rightAngleRotation_rightAngleRotation, o.rotationAux_apply,
Function.comp_apply, id, LinearEquiv.coe_coe, LinearIsometry.coe_toLinearMap,
LinearIsometryEquiv.coe_toLinearEquiv, map_add, map_smul, LinearMap.coe_comp,
LinearMap.id_coe, LinearMap.smul_apply, LinearMap.sub_apply,
add_smul, smul_neg, smul_sub, smul_smul]
ring_nf
abel
· simp)
#align orientation.rotation Orientation.rotation
theorem rotation_apply (θ : Real.Angle) (x : V) :
o.rotation θ x = Real.Angle.cos θ • x + Real.Angle.sin θ • J x :=
rfl
#align orientation.rotation_apply Orientation.rotation_apply
theorem rotation_symm_apply (θ : Real.Angle) (x : V) :
(o.rotation θ).symm x = Real.Angle.cos θ • x - Real.Angle.sin θ • J x :=
rfl
#align orientation.rotation_symm_apply Orientation.rotation_symm_apply
theorem rotation_eq_matrix_toLin (θ : Real.Angle) {x : V} (hx : x ≠ 0) :
(o.rotation θ).toLinearMap =
Matrix.toLin (o.basisRightAngleRotation x hx) (o.basisRightAngleRotation x hx)
!![θ.cos, -θ.sin; θ.sin, θ.cos] := by
apply (o.basisRightAngleRotation x hx).ext
intro i
fin_cases i
· rw [Matrix.toLin_self]
simp [rotation_apply, Fin.sum_univ_succ]
· rw [Matrix.toLin_self]
simp [rotation_apply, Fin.sum_univ_succ, add_comm]
#align orientation.rotation_eq_matrix_to_lin Orientation.rotation_eq_matrix_toLin
/-- The determinant of `rotation` (as a linear map) is equal to `1`. -/
@[simp]
theorem det_rotation (θ : Real.Angle) : LinearMap.det (o.rotation θ).toLinearMap = 1 := by
haveI : Nontrivial V :=
FiniteDimensional.nontrivial_of_finrank_eq_succ (@Fact.out (finrank ℝ V = 2) _)
obtain ⟨x, hx⟩ : ∃ x, x ≠ (0 : V) := exists_ne (0 : V)
rw [o.rotation_eq_matrix_toLin θ hx]
simpa [sq] using θ.cos_sq_add_sin_sq
#align orientation.det_rotation Orientation.det_rotation
/-- The determinant of `rotation` (as a linear equiv) is equal to `1`. -/
@[simp]
theorem linearEquiv_det_rotation (θ : Real.Angle) :
LinearEquiv.det (o.rotation θ).toLinearEquiv = 1 :=
Units.ext <| by
-- Porting note: Lean can't see through `LinearEquiv.coe_det` and needed the rewrite
-- in mathlib3 this was just `units.ext <| o.det_rotation θ`
simpa only [LinearEquiv.coe_det, Units.val_one] using o.det_rotation θ
#align orientation.linear_equiv_det_rotation Orientation.linearEquiv_det_rotation
/-- The inverse of `rotation` is rotation by the negation of the angle. -/
@[simp]
theorem rotation_symm (θ : Real.Angle) : (o.rotation θ).symm = o.rotation (-θ) := by
ext; simp [o.rotation_apply, o.rotation_symm_apply, sub_eq_add_neg]
#align orientation.rotation_symm Orientation.rotation_symm
/-- Rotation by 0 is the identity. -/
@[simp]
theorem rotation_zero : o.rotation 0 = LinearIsometryEquiv.refl ℝ V := by ext; simp [rotation]
#align orientation.rotation_zero Orientation.rotation_zero
/-- Rotation by π is negation. -/
@[simp]
theorem rotation_pi : o.rotation π = LinearIsometryEquiv.neg ℝ := by
ext x
simp [rotation]
#align orientation.rotation_pi Orientation.rotation_pi
/-- Rotation by π is negation. -/
theorem rotation_pi_apply (x : V) : o.rotation π x = -x := by simp
#align orientation.rotation_pi_apply Orientation.rotation_pi_apply
/-- Rotation by π / 2 is the "right-angle-rotation" map `J`. -/
theorem rotation_pi_div_two : o.rotation (π / 2 : ℝ) = J := by
ext x
simp [rotation]
#align orientation.rotation_pi_div_two Orientation.rotation_pi_div_two
/-- Rotating twice is equivalent to rotating by the sum of the angles. -/
@[simp]
theorem rotation_rotation (θ₁ θ₂ : Real.Angle) (x : V) :
o.rotation θ₁ (o.rotation θ₂ x) = o.rotation (θ₁ + θ₂) x := by
simp only [o.rotation_apply, ← mul_smul, Real.Angle.cos_add, Real.Angle.sin_add, add_smul,
sub_smul, LinearIsometryEquiv.trans_apply, smul_add, LinearIsometryEquiv.map_add,
LinearIsometryEquiv.map_smul, rightAngleRotation_rightAngleRotation, smul_neg]
ring_nf
abel
#align orientation.rotation_rotation Orientation.rotation_rotation
/-- Rotating twice is equivalent to rotating by the sum of the angles. -/
@[simp]
theorem rotation_trans (θ₁ θ₂ : Real.Angle) :
(o.rotation θ₁).trans (o.rotation θ₂) = o.rotation (θ₂ + θ₁) :=
LinearIsometryEquiv.ext fun _ => by rw [← rotation_rotation, LinearIsometryEquiv.trans_apply]
#align orientation.rotation_trans Orientation.rotation_trans
/-- Rotating the first of two vectors by `θ` scales their Kahler form by `cos θ - sin θ * I`. -/
@[simp]
| Mathlib/Geometry/Euclidean/Angle/Oriented/Rotation.lean | 180 | 188 | theorem kahler_rotation_left (x y : V) (θ : Real.Angle) :
o.kahler (o.rotation θ x) y = conj (θ.expMapCircle : ℂ) * o.kahler x y := by |
-- Porting note: this needed the `Complex.conj_ofReal` instead of `RCLike.conj_ofReal`;
-- I believe this is because the respective coercions are no longer defeq, and
-- `Real.Angle.coe_expMapCircle` uses the `Complex` version.
simp only [o.rotation_apply, map_add, map_mul, LinearMap.map_smulₛₗ, RingHom.id_apply,
LinearMap.add_apply, LinearMap.smul_apply, real_smul, kahler_rightAngleRotation_left,
Real.Angle.coe_expMapCircle, Complex.conj_ofReal, conj_I]
ring
|
/-
Copyright (c) 2023 Antoine Chambert-Loir and María Inés de Frutos-Fernández. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Antoine Chambert-Loir, María Inés de Frutos-Fernández, Bhavik Mehta, Eric Wieser
-/
import Mathlib.Algebra.Order.Sub.Defs
import Mathlib.Data.Finset.Basic
import Mathlib.Order.Interval.Finset.Defs
/-! # Antidiagonal with values in general types
We define a type class `Finset.HasAntidiagonal A` which contains a function
`antidiagonal : A → Finset (A × A)` such that `antidiagonal n`
is the finset of all pairs adding to `n`, as witnessed by `mem_antidiagonal`.
When `A` is a canonically ordered add monoid with locally finite order
this typeclass can be instantiated with `Finset.antidiagonalOfLocallyFinite`.
This applies in particular when `A` is `ℕ`, more generally or `σ →₀ ℕ`,
or even `ι →₀ A` under the additional assumption `OrderedSub A`
that make it a canonically ordered add monoid.
(In fact, we would just need an `AddMonoid` with a compatible order,
finite `Iic`, such that if `a + b = n`, then `a, b ≤ n`,
and any finiteness condition would be OK.)
For computational reasons it is better to manually provide instances for `ℕ`
and `σ →₀ ℕ`, to avoid quadratic runtime performance.
These instances are provided as `Finset.Nat.instHasAntidiagonal` and `Finsupp.instHasAntidiagonal`.
This is why `Finset.antidiagonalOfLocallyFinite` is an `abbrev` and not an `instance`.
This definition does not exactly match with that of `Multiset.antidiagonal`
defined in `Mathlib.Data.Multiset.Antidiagonal`, because of the multiplicities.
Indeed, by counting multiplicities, `Multiset α` is equivalent to `α →₀ ℕ`,
but `Finset.antidiagonal` and `Multiset.antidiagonal` will return different objects.
For example, for `s : Multiset ℕ := {0,0,0}`, `Multiset.antidiagonal s` has 8 elements
but `Finset.antidiagonal s` has only 4.
```lean
def s : Multiset ℕ := {0, 0, 0}
#eval (Finset.antidiagonal s).card -- 4
#eval Multiset.card (Multiset.antidiagonal s) -- 8
```
## TODO
* Define `HasMulAntidiagonal` (for monoids).
For `PNat`, we will recover the set of divisors of a strictly positive integer.
-/
open Function
namespace Finset
/-- The class of additive monoids with an antidiagonal -/
class HasAntidiagonal (A : Type*) [AddMonoid A] where
/-- The antidiagonal of an element `n` is the finset of pairs `(i, j)` such that `i + j = n`. -/
antidiagonal : A → Finset (A × A)
/-- A pair belongs to `antidiagonal n` iff the sum of its components is equal to `n`. -/
mem_antidiagonal {n} {a} : a ∈ antidiagonal n ↔ a.fst + a.snd = n
export HasAntidiagonal (antidiagonal mem_antidiagonal)
attribute [simp] mem_antidiagonal
variable {A : Type*}
/-- All `HasAntidiagonal` instances are equal -/
instance [AddMonoid A] : Subsingleton (HasAntidiagonal A) :=
⟨by
rintro ⟨a, ha⟩ ⟨b, hb⟩
congr with n xy
rw [ha, hb]⟩
-- The goal of this lemma is to allow to rewrite antidiagonal
-- when the decidability instances obsucate Lean
lemma hasAntidiagonal_congr (A : Type*) [AddMonoid A]
[H1 : HasAntidiagonal A] [H2 : HasAntidiagonal A] :
H1.antidiagonal = H2.antidiagonal := by congr!; apply Subsingleton.elim
theorem swap_mem_antidiagonal [AddCommMonoid A] [HasAntidiagonal A] {n : A} {xy : A × A}:
xy.swap ∈ antidiagonal n ↔ xy ∈ antidiagonal n := by
simp [add_comm]
@[simp] theorem map_prodComm_antidiagonal [AddCommMonoid A] [HasAntidiagonal A] {n : A} :
(antidiagonal n).map (Equiv.prodComm A A) = antidiagonal n :=
Finset.ext fun ⟨a, b⟩ => by simp [add_comm]
/-- See also `Finset.map_prodComm_antidiagonal`. -/
@[simp] theorem map_swap_antidiagonal [AddCommMonoid A] [HasAntidiagonal A] {n : A} :
(antidiagonal n).map ⟨Prod.swap, Prod.swap_injective⟩ = antidiagonal n :=
map_prodComm_antidiagonal
#align finset.nat.map_swap_antidiagonal Finset.map_swap_antidiagonal
section AddCancelMonoid
variable [AddCancelMonoid A] [HasAntidiagonal A] {p q : A × A} {n : A}
/-- A point in the antidiagonal is determined by its first coordinate.
See also `Finset.antidiagonal_congr'`. -/
theorem antidiagonal_congr (hp : p ∈ antidiagonal n) (hq : q ∈ antidiagonal n) :
p = q ↔ p.1 = q.1 := by
refine ⟨congr_arg Prod.fst, fun h ↦ Prod.ext h ((add_right_inj q.fst).mp ?_)⟩
rw [mem_antidiagonal] at hp hq
rw [hq, ← h, hp]
#align finset.nat.antidiagonal_congr Finset.antidiagonal_congr
/-- A point in the antidiagonal is determined by its first co-ordinate (subtype version of
`Finset.antidiagonal_congr`). This lemma is used by the `ext` tactic. -/
@[ext] theorem antidiagonal_subtype_ext {p q : antidiagonal n} (h : p.val.1 = q.val.1) : p = q :=
Subtype.ext ((antidiagonal_congr p.prop q.prop).mpr h)
end AddCancelMonoid
section AddCancelCommMonoid
variable [AddCancelCommMonoid A] [HasAntidiagonal A] {p q : A × A} {n : A}
/-- A point in the antidiagonal is determined by its second coordinate.
See also `Finset.antidiagonal_congr`. -/
lemma antidiagonal_congr' (hp : p ∈ antidiagonal n) (hq : q ∈ antidiagonal n) :
p = q ↔ p.2 = q.2 := by
rw [← Prod.swap_inj]
exact antidiagonal_congr (swap_mem_antidiagonal.2 hp) (swap_mem_antidiagonal.2 hq)
end AddCancelCommMonoid
section CanonicallyOrderedAddCommMonoid
variable [CanonicallyOrderedAddCommMonoid A] [HasAntidiagonal A]
@[simp]
theorem antidiagonal_zero : antidiagonal (0 : A) = {(0, 0)} := by
ext ⟨x, y⟩
simp
| Mathlib/Data/Finset/Antidiagonal.lean | 135 | 138 | theorem antidiagonal.fst_le {n : A} {kl : A × A} (hlk : kl ∈ antidiagonal n) : kl.1 ≤ n := by |
rw [le_iff_exists_add]
use kl.2
rwa [mem_antidiagonal, eq_comm] at hlk
|
/-
Copyright (c) 2024 Jz Pan. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jz Pan
-/
import Mathlib.LinearAlgebra.Dimension.Finite
import Mathlib.LinearAlgebra.Dimension.Constructions
/-!
# Some results on free modules over rings satisfying strong rank condition
This file contains some results on free modules over rings satisfying strong rank condition.
Most of them are generalized from the same result assuming the base ring being division ring,
and are moved from the files `Mathlib/LinearAlgebra/Dimension/DivisionRing.lean`
and `Mathlib/LinearAlgebra/FiniteDimensional.lean`.
-/
open Cardinal Submodule Set FiniteDimensional
universe u v
section Module
variable {K : Type u} {V : Type v} [Ring K] [StrongRankCondition K] [AddCommGroup V] [Module K V]
/-- The `ι` indexed basis on `V`, where `ι` is an empty type and `V` is zero-dimensional.
See also `FiniteDimensional.finBasis`.
-/
noncomputable def Basis.ofRankEqZero [Module.Free K V] {ι : Type*} [IsEmpty ι]
(hV : Module.rank K V = 0) : Basis ι K V :=
haveI : Subsingleton V := by
obtain ⟨_, b⟩ := Module.Free.exists_basis (R := K) (M := V)
haveI := mk_eq_zero_iff.1 (hV ▸ b.mk_eq_rank'')
exact b.repr.toEquiv.subsingleton
Basis.empty _
#align basis.of_rank_eq_zero Basis.ofRankEqZero
@[simp]
theorem Basis.ofRankEqZero_apply [Module.Free K V] {ι : Type*} [IsEmpty ι]
(hV : Module.rank K V = 0) (i : ι) : Basis.ofRankEqZero hV i = 0 := rfl
#align basis.of_rank_eq_zero_apply Basis.ofRankEqZero_apply
theorem le_rank_iff_exists_linearIndependent [Module.Free K V] {c : Cardinal} :
c ≤ Module.rank K V ↔ ∃ s : Set V, #s = c ∧ LinearIndependent K ((↑) : s → V) := by
haveI := nontrivial_of_invariantBasisNumber K
constructor
· intro h
obtain ⟨κ, t'⟩ := Module.Free.exists_basis (R := K) (M := V)
let t := t'.reindexRange
have : LinearIndependent K ((↑) : Set.range t' → V) := by
convert t.linearIndependent
ext; exact (Basis.reindexRange_apply _ _).symm
rw [← t.mk_eq_rank'', le_mk_iff_exists_subset] at h
rcases h with ⟨s, hst, hsc⟩
exact ⟨s, hsc, this.mono hst⟩
· rintro ⟨s, rfl, si⟩
exact si.cardinal_le_rank
#align le_rank_iff_exists_linear_independent le_rank_iff_exists_linearIndependent
theorem le_rank_iff_exists_linearIndependent_finset
[Module.Free K V] {n : ℕ} : ↑n ≤ Module.rank K V ↔
∃ s : Finset V, s.card = n ∧ LinearIndependent K ((↑) : ↥(s : Set V) → V) := by
simp only [le_rank_iff_exists_linearIndependent, mk_set_eq_nat_iff_finset]
constructor
· rintro ⟨s, ⟨t, rfl, rfl⟩, si⟩
exact ⟨t, rfl, si⟩
· rintro ⟨s, rfl, si⟩
exact ⟨s, ⟨s, rfl, rfl⟩, si⟩
#align le_rank_iff_exists_linear_independent_finset le_rank_iff_exists_linearIndependent_finset
/-- A vector space has dimension at most `1` if and only if there is a
single vector of which all vectors are multiples. -/
theorem rank_le_one_iff [Module.Free K V] :
Module.rank K V ≤ 1 ↔ ∃ v₀ : V, ∀ v, ∃ r : K, r • v₀ = v := by
obtain ⟨κ, b⟩ := Module.Free.exists_basis (R := K) (M := V)
constructor
· intro hd
rw [← b.mk_eq_rank'', le_one_iff_subsingleton] at hd
rcases isEmpty_or_nonempty κ with hb | ⟨⟨i⟩⟩
· use 0
have h' : ∀ v : V, v = 0 := by
simpa [range_eq_empty, Submodule.eq_bot_iff] using b.span_eq.symm
intro v
simp [h' v]
· use b i
have h' : (K ∙ b i) = ⊤ :=
(subsingleton_range b).eq_singleton_of_mem (mem_range_self i) ▸ b.span_eq
intro v
have hv : v ∈ (⊤ : Submodule K V) := mem_top
rwa [← h', mem_span_singleton] at hv
· rintro ⟨v₀, hv₀⟩
have h : (K ∙ v₀) = ⊤ := by
ext
simp [mem_span_singleton, hv₀]
rw [← rank_top, ← h]
refine (rank_span_le _).trans_eq ?_
simp
#align rank_le_one_iff rank_le_one_iff
/-- A vector space has dimension `1` if and only if there is a
single non-zero vector of which all vectors are multiples. -/
| Mathlib/LinearAlgebra/Dimension/FreeAndStrongRankCondition.lean | 105 | 119 | theorem rank_eq_one_iff [Module.Free K V] :
Module.rank K V = 1 ↔ ∃ v₀ : V, v₀ ≠ 0 ∧ ∀ v, ∃ r : K, r • v₀ = v := by |
haveI := nontrivial_of_invariantBasisNumber K
refine ⟨fun h ↦ ?_, fun ⟨v₀, h, hv⟩ ↦ (rank_le_one_iff.2 ⟨v₀, hv⟩).antisymm ?_⟩
· obtain ⟨v₀, hv⟩ := rank_le_one_iff.1 h.le
refine ⟨v₀, fun hzero ↦ ?_, hv⟩
simp_rw [hzero, smul_zero, exists_const] at hv
haveI : Subsingleton V := .intro fun _ _ ↦ by simp_rw [← hv]
exact one_ne_zero (h ▸ rank_subsingleton' K V)
· by_contra H
rw [not_le, lt_one_iff_zero] at H
obtain ⟨κ, b⟩ := Module.Free.exists_basis (R := K) (M := V)
haveI := mk_eq_zero_iff.1 (H ▸ b.mk_eq_rank'')
haveI := b.repr.toEquiv.subsingleton
exact h (Subsingleton.elim _ _)
|
/-
Copyright (c) 2022 Kyle Miller. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kyle Miller
-/
import Mathlib.Combinatorics.SimpleGraph.Connectivity
import Mathlib.Tactic.Linarith
#align_import combinatorics.simple_graph.acyclic from "leanprover-community/mathlib"@"b07688016d62f81d14508ff339ea3415558d6353"
/-!
# Acyclic graphs and trees
This module introduces *acyclic graphs* (a.k.a. *forests*) and *trees*.
## Main definitions
* `SimpleGraph.IsAcyclic` is a predicate for a graph having no cyclic walks
* `SimpleGraph.IsTree` is a predicate for a graph being a tree (a connected acyclic graph)
## Main statements
* `SimpleGraph.isAcyclic_iff_path_unique` characterizes acyclicity in terms of uniqueness of
paths between pairs of vertices.
* `SimpleGraph.isAcyclic_iff_forall_edge_isBridge` characterizes acyclicity in terms of every
edge being a bridge edge.
* `SimpleGraph.isTree_iff_existsUnique_path` characterizes trees in terms of existence and
uniqueness of paths between pairs of vertices from a nonempty vertex type.
## References
The structure of the proofs for `SimpleGraph.IsAcyclic` and `SimpleGraph.IsTree`, including
supporting lemmas about `SimpleGraph.IsBridge`, generally follows the high-level description
for these theorems for multigraphs from [Chou1994].
## Tags
acyclic graphs, trees
-/
universe u v
namespace SimpleGraph
open Walk
variable {V : Type u} (G : SimpleGraph V)
/-- A graph is *acyclic* (or a *forest*) if it has no cycles. -/
def IsAcyclic : Prop := ∀ ⦃v : V⦄ (c : G.Walk v v), ¬c.IsCycle
#align simple_graph.is_acyclic SimpleGraph.IsAcyclic
/-- A *tree* is a connected acyclic graph. -/
@[mk_iff]
structure IsTree : Prop where
/-- Graph is connected. -/
protected isConnected : G.Connected
/-- Graph is acyclic. -/
protected IsAcyclic : G.IsAcyclic
#align simple_graph.is_tree SimpleGraph.IsTree
variable {G}
@[simp] lemma isAcyclic_bot : IsAcyclic (⊥ : SimpleGraph V) := fun _a _w hw ↦ hw.ne_bot rfl
theorem isAcyclic_iff_forall_adj_isBridge :
G.IsAcyclic ↔ ∀ ⦃v w : V⦄, G.Adj v w → G.IsBridge s(v, w) := by
simp_rw [isBridge_iff_adj_and_forall_cycle_not_mem]
constructor
· intro ha v w hvw
apply And.intro hvw
intro u p hp
cases ha p hp
· rintro hb v (_ | ⟨ha, p⟩) hp
· exact hp.not_of_nil
· apply (hb ha).2 _ hp
rw [Walk.edges_cons]
apply List.mem_cons_self
#align simple_graph.is_acyclic_iff_forall_adj_is_bridge SimpleGraph.isAcyclic_iff_forall_adj_isBridge
theorem isAcyclic_iff_forall_edge_isBridge :
G.IsAcyclic ↔ ∀ ⦃e⦄, e ∈ (G.edgeSet) → G.IsBridge e := by
simp [isAcyclic_iff_forall_adj_isBridge, Sym2.forall]
#align simple_graph.is_acyclic_iff_forall_edge_is_bridge SimpleGraph.isAcyclic_iff_forall_edge_isBridge
| Mathlib/Combinatorics/SimpleGraph/Acyclic.lean | 88 | 115 | theorem IsAcyclic.path_unique {G : SimpleGraph V} (h : G.IsAcyclic) {v w : V} (p q : G.Path v w) :
p = q := by |
obtain ⟨p, hp⟩ := p
obtain ⟨q, hq⟩ := q
rw [Subtype.mk.injEq]
induction p with
| nil =>
cases (Walk.isPath_iff_eq_nil _).mp hq
rfl
| cons ph p ih =>
rw [isAcyclic_iff_forall_adj_isBridge] at h
specialize h ph
rw [isBridge_iff_adj_and_forall_walk_mem_edges] at h
replace h := h.2 (q.append p.reverse)
simp only [Walk.edges_append, Walk.edges_reverse, List.mem_append, List.mem_reverse] at h
cases' h with h h
· cases q with
| nil => simp [Walk.isPath_def] at hp
| cons _ q =>
rw [Walk.cons_isPath_iff] at hp hq
simp only [Walk.edges_cons, List.mem_cons, Sym2.eq_iff, true_and] at h
rcases h with (⟨h, rfl⟩ | ⟨rfl, rfl⟩) | h
· cases ih hp.1 q hq.1
rfl
· simp at hq
· exact absurd (Walk.fst_mem_support_of_mem_edges _ h) hq.2
· rw [Walk.cons_isPath_iff] at hp
exact absurd (Walk.fst_mem_support_of_mem_edges _ h) hp.2
|
/-
Copyright (c) 2020 Yury Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury Kudryashov, Frédéric Dupuis
-/
import Mathlib.Analysis.Convex.Hull
#align_import analysis.convex.cone.basic from "leanprover-community/mathlib"@"915591b2bb3ea303648db07284a161a7f2a9e3d4"
/-!
# Convex cones
In a `𝕜`-module `E`, we define a convex cone as a set `s` such that `a • x + b • y ∈ s` whenever
`x, y ∈ s` and `a, b > 0`. We prove that convex cones form a `CompleteLattice`, and define their
images (`ConvexCone.map`) and preimages (`ConvexCone.comap`) under linear maps.
We define pointed, blunt, flat and salient cones, and prove the correspondence between
convex cones and ordered modules.
We define `Convex.toCone` to be the minimal cone that includes a given convex set.
## Main statements
In `Mathlib/Analysis/Convex/Cone/Extension.lean` we prove
the M. Riesz extension theorem and a form of the Hahn-Banach theorem.
In `Mathlib/Analysis/Convex/Cone/Dual.lean` we prove
a variant of the hyperplane separation theorem.
## Implementation notes
While `Convex 𝕜` is a predicate on sets, `ConvexCone 𝕜 E` is a bundled convex cone.
## References
* https://en.wikipedia.org/wiki/Convex_cone
* [Stephen P. Boyd and Lieven Vandenberghe, *Convex Optimization*][boydVandenberghe2004]
* [Emo Welzl and Bernd Gärtner, *Cone Programming*][welzl_garter]
-/
assert_not_exists NormedSpace
assert_not_exists Real
open Set LinearMap
open scoped Classical
open Pointwise
variable {𝕜 E F G : Type*}
/-! ### Definition of `ConvexCone` and basic properties -/
section Definitions
variable (𝕜 E)
variable [OrderedSemiring 𝕜]
/-- A convex cone is a subset `s` of a `𝕜`-module such that `a • x + b • y ∈ s` whenever `a, b > 0`
and `x, y ∈ s`. -/
structure ConvexCone [AddCommMonoid E] [SMul 𝕜 E] where
/-- The **carrier set** underlying this cone: the set of points contained in it -/
carrier : Set E
smul_mem' : ∀ ⦃c : 𝕜⦄, 0 < c → ∀ ⦃x : E⦄, x ∈ carrier → c • x ∈ carrier
add_mem' : ∀ ⦃x⦄ (_ : x ∈ carrier) ⦃y⦄ (_ : y ∈ carrier), x + y ∈ carrier
#align convex_cone ConvexCone
end Definitions
namespace ConvexCone
section OrderedSemiring
variable [OrderedSemiring 𝕜] [AddCommMonoid E]
section SMul
variable [SMul 𝕜 E] (S T : ConvexCone 𝕜 E)
instance : SetLike (ConvexCone 𝕜 E) E where
coe := carrier
coe_injective' S T h := by cases S; cases T; congr
@[simp]
theorem coe_mk {s : Set E} {h₁ h₂} : ↑(@mk 𝕜 _ _ _ _ s h₁ h₂) = s :=
rfl
#align convex_cone.coe_mk ConvexCone.coe_mk
@[simp]
theorem mem_mk {s : Set E} {h₁ h₂ x} : x ∈ @mk 𝕜 _ _ _ _ s h₁ h₂ ↔ x ∈ s :=
Iff.rfl
#align convex_cone.mem_mk ConvexCone.mem_mk
/-- Two `ConvexCone`s are equal if they have the same elements. -/
@[ext]
theorem ext {S T : ConvexCone 𝕜 E} (h : ∀ x, x ∈ S ↔ x ∈ T) : S = T :=
SetLike.ext h
#align convex_cone.ext ConvexCone.ext
@[aesop safe apply (rule_sets := [SetLike])]
theorem smul_mem {c : 𝕜} {x : E} (hc : 0 < c) (hx : x ∈ S) : c • x ∈ S :=
S.smul_mem' hc hx
#align convex_cone.smul_mem ConvexCone.smul_mem
theorem add_mem ⦃x⦄ (hx : x ∈ S) ⦃y⦄ (hy : y ∈ S) : x + y ∈ S :=
S.add_mem' hx hy
#align convex_cone.add_mem ConvexCone.add_mem
instance : AddMemClass (ConvexCone 𝕜 E) E where add_mem ha hb := add_mem _ ha hb
instance : Inf (ConvexCone 𝕜 E) :=
⟨fun S T =>
⟨S ∩ T, fun _ hc _ hx => ⟨S.smul_mem hc hx.1, T.smul_mem hc hx.2⟩, fun _ hx _ hy =>
⟨S.add_mem hx.1 hy.1, T.add_mem hx.2 hy.2⟩⟩⟩
@[simp]
theorem coe_inf : ((S ⊓ T : ConvexCone 𝕜 E) : Set E) = ↑S ∩ ↑T :=
rfl
#align convex_cone.coe_inf ConvexCone.coe_inf
theorem mem_inf {x} : x ∈ S ⊓ T ↔ x ∈ S ∧ x ∈ T :=
Iff.rfl
#align convex_cone.mem_inf ConvexCone.mem_inf
instance : InfSet (ConvexCone 𝕜 E) :=
⟨fun S =>
⟨⋂ s ∈ S, ↑s, fun _ hc _ hx => mem_biInter fun s hs => s.smul_mem hc <| mem_iInter₂.1 hx s hs,
fun _ hx _ hy =>
mem_biInter fun s hs => s.add_mem (mem_iInter₂.1 hx s hs) (mem_iInter₂.1 hy s hs)⟩⟩
@[simp]
theorem coe_sInf (S : Set (ConvexCone 𝕜 E)) : ↑(sInf S) = ⋂ s ∈ S, (s : Set E) :=
rfl
#align convex_cone.coe_Inf ConvexCone.coe_sInf
theorem mem_sInf {x : E} {S : Set (ConvexCone 𝕜 E)} : x ∈ sInf S ↔ ∀ s ∈ S, x ∈ s :=
mem_iInter₂
#align convex_cone.mem_Inf ConvexCone.mem_sInf
@[simp]
theorem coe_iInf {ι : Sort*} (f : ι → ConvexCone 𝕜 E) : ↑(iInf f) = ⋂ i, (f i : Set E) := by
simp [iInf]
#align convex_cone.coe_infi ConvexCone.coe_iInf
theorem mem_iInf {ι : Sort*} {x : E} {f : ι → ConvexCone 𝕜 E} : x ∈ iInf f ↔ ∀ i, x ∈ f i :=
mem_iInter₂.trans <| by simp
#align convex_cone.mem_infi ConvexCone.mem_iInf
variable (𝕜)
instance : Bot (ConvexCone 𝕜 E) :=
⟨⟨∅, fun _ _ _ => False.elim, fun _ => False.elim⟩⟩
theorem mem_bot (x : E) : (x ∈ (⊥ : ConvexCone 𝕜 E)) = False :=
rfl
#align convex_cone.mem_bot ConvexCone.mem_bot
@[simp]
theorem coe_bot : ↑(⊥ : ConvexCone 𝕜 E) = (∅ : Set E) :=
rfl
#align convex_cone.coe_bot ConvexCone.coe_bot
instance : Top (ConvexCone 𝕜 E) :=
⟨⟨univ, fun _ _ _ _ => mem_univ _, fun _ _ _ _ => mem_univ _⟩⟩
theorem mem_top (x : E) : x ∈ (⊤ : ConvexCone 𝕜 E) :=
mem_univ x
#align convex_cone.mem_top ConvexCone.mem_top
@[simp]
theorem coe_top : ↑(⊤ : ConvexCone 𝕜 E) = (univ : Set E) :=
rfl
#align convex_cone.coe_top ConvexCone.coe_top
instance : CompleteLattice (ConvexCone 𝕜 E) :=
{ SetLike.instPartialOrder with
le := (· ≤ ·)
lt := (· < ·)
bot := ⊥
bot_le := fun _ _ => False.elim
top := ⊤
le_top := fun _ x _ => mem_top 𝕜 x
inf := (· ⊓ ·)
sInf := InfSet.sInf
sup := fun a b => sInf { x | a ≤ x ∧ b ≤ x }
sSup := fun s => sInf { T | ∀ S ∈ s, S ≤ T }
le_sup_left := fun _ _ => fun _ hx => mem_sInf.2 fun _ hs => hs.1 hx
le_sup_right := fun _ _ => fun _ hx => mem_sInf.2 fun _ hs => hs.2 hx
sup_le := fun _ _ c ha hb _ hx => mem_sInf.1 hx c ⟨ha, hb⟩
le_inf := fun _ _ _ ha hb _ hx => ⟨ha hx, hb hx⟩
inf_le_left := fun _ _ _ => And.left
inf_le_right := fun _ _ _ => And.right
le_sSup := fun _ p hs _ hx => mem_sInf.2 fun _ ht => ht p hs hx
sSup_le := fun _ p hs _ hx => mem_sInf.1 hx p hs
le_sInf := fun _ _ ha _ hx => mem_sInf.2 fun t ht => ha t ht hx
sInf_le := fun _ _ ha _ hx => mem_sInf.1 hx _ ha }
instance : Inhabited (ConvexCone 𝕜 E) :=
⟨⊥⟩
end SMul
section Module
variable [Module 𝕜 E] (S : ConvexCone 𝕜 E)
protected theorem convex : Convex 𝕜 (S : Set E) :=
convex_iff_forall_pos.2 fun _ hx _ hy _ _ ha hb _ =>
S.add_mem (S.smul_mem ha hx) (S.smul_mem hb hy)
#align convex_cone.convex ConvexCone.convex
end Module
section Maps
variable [AddCommMonoid E] [AddCommMonoid F] [AddCommMonoid G]
variable [Module 𝕜 E] [Module 𝕜 F] [Module 𝕜 G]
/-- The image of a convex cone under a `𝕜`-linear map is a convex cone. -/
def map (f : E →ₗ[𝕜] F) (S : ConvexCone 𝕜 E) : ConvexCone 𝕜 F where
carrier := f '' S
smul_mem' := fun c hc _ ⟨x, hx, hy⟩ => hy ▸ f.map_smul c x ▸ mem_image_of_mem f (S.smul_mem hc hx)
add_mem' := fun _ ⟨x₁, hx₁, hy₁⟩ _ ⟨x₂, hx₂, hy₂⟩ =>
hy₁ ▸ hy₂ ▸ f.map_add x₁ x₂ ▸ mem_image_of_mem f (S.add_mem hx₁ hx₂)
#align convex_cone.map ConvexCone.map
@[simp, norm_cast]
theorem coe_map (S : ConvexCone 𝕜 E) (f : E →ₗ[𝕜] F) : (S.map f : Set F) = f '' S :=
rfl
@[simp]
theorem mem_map {f : E →ₗ[𝕜] F} {S : ConvexCone 𝕜 E} {y : F} : y ∈ S.map f ↔ ∃ x ∈ S, f x = y :=
Set.mem_image f S y
#align convex_cone.mem_map ConvexCone.mem_map
theorem map_map (g : F →ₗ[𝕜] G) (f : E →ₗ[𝕜] F) (S : ConvexCone 𝕜 E) :
(S.map f).map g = S.map (g.comp f) :=
SetLike.coe_injective <| image_image g f S
#align convex_cone.map_map ConvexCone.map_map
@[simp]
theorem map_id (S : ConvexCone 𝕜 E) : S.map LinearMap.id = S :=
SetLike.coe_injective <| image_id _
#align convex_cone.map_id ConvexCone.map_id
/-- The preimage of a convex cone under a `𝕜`-linear map is a convex cone. -/
def comap (f : E →ₗ[𝕜] F) (S : ConvexCone 𝕜 F) : ConvexCone 𝕜 E where
carrier := f ⁻¹' S
smul_mem' c hc x hx := by
rw [mem_preimage, f.map_smul c]
exact S.smul_mem hc hx
add_mem' x hx y hy := by
rw [mem_preimage, f.map_add]
exact S.add_mem hx hy
#align convex_cone.comap ConvexCone.comap
@[simp]
theorem coe_comap (f : E →ₗ[𝕜] F) (S : ConvexCone 𝕜 F) : (S.comap f : Set E) = f ⁻¹' S :=
rfl
#align convex_cone.coe_comap ConvexCone.coe_comap
@[simp] -- Porting note: was not a `dsimp` lemma
theorem comap_id (S : ConvexCone 𝕜 E) : S.comap LinearMap.id = S :=
rfl
#align convex_cone.comap_id ConvexCone.comap_id
theorem comap_comap (g : F →ₗ[𝕜] G) (f : E →ₗ[𝕜] F) (S : ConvexCone 𝕜 G) :
(S.comap g).comap f = S.comap (g.comp f) :=
rfl
#align convex_cone.comap_comap ConvexCone.comap_comap
@[simp]
theorem mem_comap {f : E →ₗ[𝕜] F} {S : ConvexCone 𝕜 F} {x : E} : x ∈ S.comap f ↔ f x ∈ S :=
Iff.rfl
#align convex_cone.mem_comap ConvexCone.mem_comap
end Maps
end OrderedSemiring
section LinearOrderedField
variable [LinearOrderedField 𝕜]
section MulAction
variable [AddCommMonoid E]
variable [MulAction 𝕜 E] (S : ConvexCone 𝕜 E)
theorem smul_mem_iff {c : 𝕜} (hc : 0 < c) {x : E} : c • x ∈ S ↔ x ∈ S :=
⟨fun h => inv_smul_smul₀ hc.ne' x ▸ S.smul_mem (inv_pos.2 hc) h, S.smul_mem hc⟩
#align convex_cone.smul_mem_iff ConvexCone.smul_mem_iff
end MulAction
section OrderedAddCommGroup
variable [OrderedAddCommGroup E] [Module 𝕜 E]
/-- Constructs an ordered module given an `OrderedAddCommGroup`, a cone, and a proof that
the order relation is the one defined by the cone.
-/
theorem to_orderedSMul (S : ConvexCone 𝕜 E) (h : ∀ x y : E, x ≤ y ↔ y - x ∈ S) : OrderedSMul 𝕜 E :=
OrderedSMul.mk'
(by
intro x y z xy hz
rw [h (z • x) (z • y), ← smul_sub z y x]
exact smul_mem S hz ((h x y).mp xy.le))
#align convex_cone.to_ordered_smul ConvexCone.to_orderedSMul
end OrderedAddCommGroup
end LinearOrderedField
/-! ### Convex cones with extra properties -/
section OrderedSemiring
variable [OrderedSemiring 𝕜]
section AddCommMonoid
variable [AddCommMonoid E] [SMul 𝕜 E] (S : ConvexCone 𝕜 E)
/-- A convex cone is pointed if it includes `0`. -/
def Pointed (S : ConvexCone 𝕜 E) : Prop :=
(0 : E) ∈ S
#align convex_cone.pointed ConvexCone.Pointed
/-- A convex cone is blunt if it doesn't include `0`. -/
def Blunt (S : ConvexCone 𝕜 E) : Prop :=
(0 : E) ∉ S
#align convex_cone.blunt ConvexCone.Blunt
theorem pointed_iff_not_blunt (S : ConvexCone 𝕜 E) : S.Pointed ↔ ¬S.Blunt :=
⟨fun h₁ h₂ => h₂ h₁, Classical.not_not.mp⟩
#align convex_cone.pointed_iff_not_blunt ConvexCone.pointed_iff_not_blunt
theorem blunt_iff_not_pointed (S : ConvexCone 𝕜 E) : S.Blunt ↔ ¬S.Pointed := by
rw [pointed_iff_not_blunt, Classical.not_not]
#align convex_cone.blunt_iff_not_pointed ConvexCone.blunt_iff_not_pointed
theorem Pointed.mono {S T : ConvexCone 𝕜 E} (h : S ≤ T) : S.Pointed → T.Pointed :=
@h _
#align convex_cone.pointed.mono ConvexCone.Pointed.mono
theorem Blunt.anti {S T : ConvexCone 𝕜 E} (h : T ≤ S) : S.Blunt → T.Blunt :=
(· ∘ @h 0)
#align convex_cone.blunt.anti ConvexCone.Blunt.anti
end AddCommMonoid
section AddCommGroup
variable [AddCommGroup E] [SMul 𝕜 E] (S : ConvexCone 𝕜 E)
/-- A convex cone is flat if it contains some nonzero vector `x` and its opposite `-x`. -/
def Flat : Prop :=
∃ x ∈ S, x ≠ (0 : E) ∧ -x ∈ S
#align convex_cone.flat ConvexCone.Flat
/-- A convex cone is salient if it doesn't include `x` and `-x` for any nonzero `x`. -/
def Salient : Prop :=
∀ x ∈ S, x ≠ (0 : E) → -x ∉ S
#align convex_cone.salient ConvexCone.Salient
theorem salient_iff_not_flat (S : ConvexCone 𝕜 E) : S.Salient ↔ ¬S.Flat := by
simp [Salient, Flat]
#align convex_cone.salient_iff_not_flat ConvexCone.salient_iff_not_flat
theorem Flat.mono {S T : ConvexCone 𝕜 E} (h : S ≤ T) : S.Flat → T.Flat
| ⟨x, hxS, hx, hnxS⟩ => ⟨x, h hxS, hx, h hnxS⟩
#align convex_cone.flat.mono ConvexCone.Flat.mono
theorem Salient.anti {S T : ConvexCone 𝕜 E} (h : T ≤ S) : S.Salient → T.Salient :=
fun hS x hxT hx hnT => hS x (h hxT) hx (h hnT)
#align convex_cone.salient.anti ConvexCone.Salient.anti
/-- A flat cone is always pointed (contains `0`). -/
| Mathlib/Analysis/Convex/Cone/Basic.lean | 381 | 384 | theorem Flat.pointed {S : ConvexCone 𝕜 E} (hS : S.Flat) : S.Pointed := by |
obtain ⟨x, hx, _, hxneg⟩ := hS
rw [Pointed, ← add_neg_self x]
exact add_mem S hx hxneg
|
/-
Copyright (c) 2023 Josha Dekker. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Josha Dekker
-/
import Mathlib.Topology.Bases
import Mathlib.Order.Filter.CountableInter
import Mathlib.Topology.Compactness.SigmaCompact
/-!
# Lindelöf sets and Lindelöf spaces
## Main definitions
We define the following properties for sets in a topological space:
* `IsLindelof s`: Two definitions are possible here. The more standard definition is that
every open cover that contains `s` contains a countable subcover. We choose for the equivalent
definition where we require that every nontrivial filter on `s` with the countable intersection
property has a clusterpoint. Equivalence is established in `isLindelof_iff_countable_subcover`.
* `LindelofSpace X`: `X` is Lindelöf if it is Lindelöf as a set.
* `NonLindelofSpace`: a space that is not a Lindëlof space, e.g. the Long Line.
## Main results
* `isLindelof_iff_countable_subcover`: A set is Lindelöf iff every open cover has a
countable subcover.
## Implementation details
* This API is mainly based on the API for IsCompact and follows notation and style as much
as possible.
-/
open Set Filter Topology TopologicalSpace
universe u v
variable {X : Type u} {Y : Type v} {ι : Type*}
variable [TopologicalSpace X] [TopologicalSpace Y] {s t : Set X}
section Lindelof
/-- A set `s` is Lindelöf if every nontrivial filter `f` with the countable intersection
property that contains `s`, has a clusterpoint in `s`. The filter-free definition is given by
`isLindelof_iff_countable_subcover`. -/
def IsLindelof (s : Set X) :=
∀ ⦃f⦄ [NeBot f] [CountableInterFilter f], f ≤ 𝓟 s → ∃ x ∈ s, ClusterPt x f
/-- The complement to a Lindelöf set belongs to a filter `f` with the countable intersection
property if it belongs to each filter `𝓝 x ⊓ f`, `x ∈ s`. -/
theorem IsLindelof.compl_mem_sets (hs : IsLindelof s) {f : Filter X} [CountableInterFilter f]
(hf : ∀ x ∈ s, sᶜ ∈ 𝓝 x ⊓ f) : sᶜ ∈ f := by
contrapose! hf
simp only [not_mem_iff_inf_principal_compl, compl_compl, inf_assoc] at hf ⊢
exact hs inf_le_right
/-- The complement to a Lindelöf set belongs to a filter `f` with the countable intersection
property if each `x ∈ s` has a neighborhood `t` within `s` such that `tᶜ` belongs to `f`. -/
theorem IsLindelof.compl_mem_sets_of_nhdsWithin (hs : IsLindelof s) {f : Filter X}
[CountableInterFilter f] (hf : ∀ x ∈ s, ∃ t ∈ 𝓝[s] x, tᶜ ∈ f) : sᶜ ∈ f := by
refine hs.compl_mem_sets fun x hx ↦ ?_
rw [← disjoint_principal_right, disjoint_right_comm, (basis_sets _).disjoint_iff_left]
exact hf x hx
/-- If `p : Set X → Prop` is stable under restriction and union, and each point `x`
of a Lindelöf set `s` has a neighborhood `t` within `s` such that `p t`, then `p s` holds. -/
@[elab_as_elim]
theorem IsLindelof.induction_on (hs : IsLindelof s) {p : Set X → Prop}
(hmono : ∀ ⦃s t⦄, s ⊆ t → p t → p s)
(hcountable_union : ∀ (S : Set (Set X)), S.Countable → (∀ s ∈ S, p s) → p (⋃₀ S))
(hnhds : ∀ x ∈ s, ∃ t ∈ 𝓝[s] x, p t) : p s := by
let f : Filter X := ofCountableUnion p hcountable_union (fun t ht _ hsub ↦ hmono hsub ht)
have : sᶜ ∈ f := hs.compl_mem_sets_of_nhdsWithin (by simpa [f] using hnhds)
rwa [← compl_compl s]
/-- The intersection of a Lindelöf set and a closed set is a Lindelöf set. -/
theorem IsLindelof.inter_right (hs : IsLindelof s) (ht : IsClosed t) : IsLindelof (s ∩ t) := by
intro f hnf _ hstf
rw [← inf_principal, le_inf_iff] at hstf
obtain ⟨x, hsx, hx⟩ : ∃ x ∈ s, ClusterPt x f := hs hstf.1
have hxt : x ∈ t := ht.mem_of_nhdsWithin_neBot <| hx.mono hstf.2
exact ⟨x, ⟨hsx, hxt⟩, hx⟩
/-- The intersection of a closed set and a Lindelöf set is a Lindelöf set. -/
theorem IsLindelof.inter_left (ht : IsLindelof t) (hs : IsClosed s) : IsLindelof (s ∩ t) :=
inter_comm t s ▸ ht.inter_right hs
/-- The set difference of a Lindelöf set and an open set is a Lindelöf set. -/
theorem IsLindelof.diff (hs : IsLindelof s) (ht : IsOpen t) : IsLindelof (s \ t) :=
hs.inter_right (isClosed_compl_iff.mpr ht)
/-- A closed subset of a Lindelöf set is a Lindelöf set. -/
theorem IsLindelof.of_isClosed_subset (hs : IsLindelof s) (ht : IsClosed t) (h : t ⊆ s) :
IsLindelof t := inter_eq_self_of_subset_right h ▸ hs.inter_right ht
/-- A continuous image of a Lindelöf set is a Lindelöf set. -/
theorem IsLindelof.image_of_continuousOn {f : X → Y} (hs : IsLindelof s) (hf : ContinuousOn f s) :
IsLindelof (f '' s) := by
intro l lne _ ls
have : NeBot (l.comap f ⊓ 𝓟 s) :=
comap_inf_principal_neBot_of_image_mem lne (le_principal_iff.1 ls)
obtain ⟨x, hxs, hx⟩ : ∃ x ∈ s, ClusterPt x (l.comap f ⊓ 𝓟 s) := @hs _ this _ inf_le_right
haveI := hx.neBot
use f x, mem_image_of_mem f hxs
have : Tendsto f (𝓝 x ⊓ (comap f l ⊓ 𝓟 s)) (𝓝 (f x) ⊓ l) := by
convert (hf x hxs).inf (@tendsto_comap _ _ f l) using 1
rw [nhdsWithin]
ac_rfl
exact this.neBot
/-- A continuous image of a Lindelöf set is a Lindelöf set within the codomain. -/
theorem IsLindelof.image {f : X → Y} (hs : IsLindelof s) (hf : Continuous f) :
IsLindelof (f '' s) := hs.image_of_continuousOn hf.continuousOn
/-- A filter with the countable intersection property that is finer than the principal filter on
a Lindelöf set `s` contains any open set that contains all clusterpoints of `s`. -/
theorem IsLindelof.adherence_nhdset {f : Filter X} [CountableInterFilter f] (hs : IsLindelof s)
(hf₂ : f ≤ 𝓟 s) (ht₁ : IsOpen t) (ht₂ : ∀ x ∈ s, ClusterPt x f → x ∈ t) : t ∈ f :=
(eq_or_neBot _).casesOn mem_of_eq_bot fun _ ↦
let ⟨x, hx, hfx⟩ := @hs (f ⊓ 𝓟 tᶜ) _ _ <| inf_le_of_left_le hf₂
have : x ∈ t := ht₂ x hx hfx.of_inf_left
have : tᶜ ∩ t ∈ 𝓝[tᶜ] x := inter_mem_nhdsWithin _ (ht₁.mem_nhds this)
have A : 𝓝[tᶜ] x = ⊥ := empty_mem_iff_bot.1 <| compl_inter_self t ▸ this
have : 𝓝[tᶜ] x ≠ ⊥ := hfx.of_inf_right.ne
absurd A this
/-- For every open cover of a Lindelöf set, there exists a countable subcover. -/
theorem IsLindelof.elim_countable_subcover {ι : Type v} (hs : IsLindelof s) (U : ι → Set X)
(hUo : ∀ i, IsOpen (U i)) (hsU : s ⊆ ⋃ i, U i) :
∃ r : Set ι, r.Countable ∧ (s ⊆ ⋃ i ∈ r, U i) := by
have hmono : ∀ ⦃s t : Set X⦄, s ⊆ t → (∃ r : Set ι, r.Countable ∧ t ⊆ ⋃ i ∈ r, U i)
→ (∃ r : Set ι, r.Countable ∧ s ⊆ ⋃ i ∈ r, U i) := by
intro _ _ hst ⟨r, ⟨hrcountable, hsub⟩⟩
exact ⟨r, hrcountable, Subset.trans hst hsub⟩
have hcountable_union : ∀ (S : Set (Set X)), S.Countable
→ (∀ s ∈ S, ∃ r : Set ι, r.Countable ∧ (s ⊆ ⋃ i ∈ r, U i))
→ ∃ r : Set ι, r.Countable ∧ (⋃₀ S ⊆ ⋃ i ∈ r, U i) := by
intro S hS hsr
choose! r hr using hsr
refine ⟨⋃ s ∈ S, r s, hS.biUnion_iff.mpr (fun s hs ↦ (hr s hs).1), ?_⟩
refine sUnion_subset ?h.right.h
simp only [mem_iUnion, exists_prop, iUnion_exists, biUnion_and']
exact fun i is x hx ↦ mem_biUnion is ((hr i is).2 hx)
have h_nhds : ∀ x ∈ s, ∃ t ∈ 𝓝[s] x, ∃ r : Set ι, r.Countable ∧ (t ⊆ ⋃ i ∈ r, U i) := by
intro x hx
let ⟨i, hi⟩ := mem_iUnion.1 (hsU hx)
refine ⟨U i, mem_nhdsWithin_of_mem_nhds ((hUo i).mem_nhds hi), {i}, by simp, ?_⟩
simp only [mem_singleton_iff, iUnion_iUnion_eq_left]
exact Subset.refl _
exact hs.induction_on hmono hcountable_union h_nhds
theorem IsLindelof.elim_nhds_subcover' (hs : IsLindelof s) (U : ∀ x ∈ s, Set X)
(hU : ∀ x (hx : x ∈ s), U x ‹x ∈ s› ∈ 𝓝 x) :
∃ t : Set s, t.Countable ∧ s ⊆ ⋃ x ∈ t, U (x : s) x.2 := by
have := hs.elim_countable_subcover (fun x : s ↦ interior (U x x.2)) (fun _ ↦ isOpen_interior)
fun x hx ↦
mem_iUnion.2 ⟨⟨x, hx⟩, mem_interior_iff_mem_nhds.2 <| hU _ _⟩
rcases this with ⟨r, ⟨hr, hs⟩⟩
use r, hr
apply Subset.trans hs
apply iUnion₂_subset
intro i hi
apply Subset.trans interior_subset
exact subset_iUnion_of_subset i (subset_iUnion_of_subset hi (Subset.refl _))
theorem IsLindelof.elim_nhds_subcover (hs : IsLindelof s) (U : X → Set X)
(hU : ∀ x ∈ s, U x ∈ 𝓝 x) :
∃ t : Set X, t.Countable ∧ (∀ x ∈ t, x ∈ s) ∧ s ⊆ ⋃ x ∈ t, U x := by
let ⟨t, ⟨htc, htsub⟩⟩ := hs.elim_nhds_subcover' (fun x _ ↦ U x) hU
refine ⟨↑t, Countable.image htc Subtype.val, ?_⟩
constructor
· intro _
simp only [mem_image, Subtype.exists, exists_and_right, exists_eq_right, forall_exists_index]
tauto
· have : ⋃ x ∈ t, U ↑x = ⋃ x ∈ Subtype.val '' t, U x := biUnion_image.symm
rwa [← this]
/-- The neighborhood filter of a Lindelöf set is disjoint with a filter `l` with the countable
intersection property if and only if the neighborhood filter of each point of this set
is disjoint with `l`. -/
theorem IsLindelof.disjoint_nhdsSet_left {l : Filter X} [CountableInterFilter l]
(hs : IsLindelof s) :
Disjoint (𝓝ˢ s) l ↔ ∀ x ∈ s, Disjoint (𝓝 x) l := by
refine ⟨fun h x hx ↦ h.mono_left <| nhds_le_nhdsSet hx, fun H ↦ ?_⟩
choose! U hxU hUl using fun x hx ↦ (nhds_basis_opens x).disjoint_iff_left.1 (H x hx)
choose hxU hUo using hxU
rcases hs.elim_nhds_subcover U fun x hx ↦ (hUo x hx).mem_nhds (hxU x hx) with ⟨t, htc, hts, hst⟩
refine (hasBasis_nhdsSet _).disjoint_iff_left.2
⟨⋃ x ∈ t, U x, ⟨isOpen_biUnion fun x hx ↦ hUo x (hts x hx), hst⟩, ?_⟩
rw [compl_iUnion₂]
exact (countable_bInter_mem htc).mpr (fun i hi ↦ hUl _ (hts _ hi))
/-- A filter `l` with the countable intersection property is disjoint with the neighborhood
filter of a Lindelöf set if and only if it is disjoint with the neighborhood filter of each point
of this set. -/
theorem IsLindelof.disjoint_nhdsSet_right {l : Filter X} [CountableInterFilter l]
(hs : IsLindelof s) : Disjoint l (𝓝ˢ s) ↔ ∀ x ∈ s, Disjoint l (𝓝 x) := by
simpa only [disjoint_comm] using hs.disjoint_nhdsSet_left
/-- For every family of closed sets whose intersection avoids a Lindelö set,
there exists a countable subfamily whose intersection avoids this Lindelöf set. -/
theorem IsLindelof.elim_countable_subfamily_closed {ι : Type v} (hs : IsLindelof s)
(t : ι → Set X) (htc : ∀ i, IsClosed (t i)) (hst : (s ∩ ⋂ i, t i) = ∅) :
∃ u : Set ι, u.Countable ∧ (s ∩ ⋂ i ∈ u, t i) = ∅ := by
let U := tᶜ
have hUo : ∀ i, IsOpen (U i) := by simp only [U, Pi.compl_apply, isOpen_compl_iff]; exact htc
have hsU : s ⊆ ⋃ i, U i := by
simp only [U, Pi.compl_apply]
rw [← compl_iInter]
apply disjoint_compl_left_iff_subset.mp
simp only [compl_iInter, compl_iUnion, compl_compl]
apply Disjoint.symm
exact disjoint_iff_inter_eq_empty.mpr hst
rcases hs.elim_countable_subcover U hUo hsU with ⟨u, ⟨hucount, husub⟩⟩
use u, hucount
rw [← disjoint_compl_left_iff_subset] at husub
simp only [U, Pi.compl_apply, compl_iUnion, compl_compl] at husub
exact disjoint_iff_inter_eq_empty.mp (Disjoint.symm husub)
/-- To show that a Lindelöf set intersects the intersection of a family of closed sets,
it is sufficient to show that it intersects every countable subfamily. -/
theorem IsLindelof.inter_iInter_nonempty {ι : Type v} (hs : IsLindelof s) (t : ι → Set X)
(htc : ∀ i, IsClosed (t i)) (hst : ∀ u : Set ι, u.Countable ∧ (s ∩ ⋂ i ∈ u, t i).Nonempty) :
(s ∩ ⋂ i, t i).Nonempty := by
contrapose! hst
rcases hs.elim_countable_subfamily_closed t htc hst with ⟨u, ⟨_, husub⟩⟩
exact ⟨u, fun _ ↦ husub⟩
/-- For every open cover of a Lindelöf set, there exists a countable subcover. -/
theorem IsLindelof.elim_countable_subcover_image {b : Set ι} {c : ι → Set X} (hs : IsLindelof s)
(hc₁ : ∀ i ∈ b, IsOpen (c i)) (hc₂ : s ⊆ ⋃ i ∈ b, c i) :
∃ b', b' ⊆ b ∧ Set.Countable b' ∧ s ⊆ ⋃ i ∈ b', c i := by
simp only [Subtype.forall', biUnion_eq_iUnion] at hc₁ hc₂
rcases hs.elim_countable_subcover (fun i ↦ c i : b → Set X) hc₁ hc₂ with ⟨d, hd⟩
refine ⟨Subtype.val '' d, by simp, Countable.image hd.1 Subtype.val, ?_⟩
rw [biUnion_image]
exact hd.2
/-- A set `s` is Lindelöf if for every open cover of `s`, there exists a countable subcover. -/
theorem isLindelof_of_countable_subcover
(h : ∀ {ι : Type u} (U : ι → Set X), (∀ i, IsOpen (U i)) → (s ⊆ ⋃ i, U i) →
∃ t : Set ι, t.Countable ∧ s ⊆ ⋃ i ∈ t, U i) :
IsLindelof s := fun f hf hfs ↦ by
contrapose! h
simp only [ClusterPt, not_neBot, ← disjoint_iff, SetCoe.forall',
(nhds_basis_opens _).disjoint_iff_left] at h
choose fsub U hU hUf using h
refine ⟨s, U, fun x ↦ (hU x).2, fun x hx ↦ mem_iUnion.2 ⟨⟨x, hx⟩, (hU _).1 ⟩, ?_⟩
intro t ht h
have uinf := f.sets_of_superset (le_principal_iff.1 fsub) h
have uninf : ⋂ i ∈ t, (U i)ᶜ ∈ f := (countable_bInter_mem ht).mpr (fun _ _ ↦ hUf _)
rw [← compl_iUnion₂] at uninf
have uninf := compl_not_mem uninf
simp only [compl_compl] at uninf
contradiction
/-- A set `s` is Lindelöf if for every family of closed sets whose intersection avoids `s`,
there exists a countable subfamily whose intersection avoids `s`. -/
theorem isLindelof_of_countable_subfamily_closed
(h :
∀ {ι : Type u} (t : ι → Set X), (∀ i, IsClosed (t i)) → (s ∩ ⋂ i, t i) = ∅ →
∃ u : Set ι, u.Countable ∧ (s ∩ ⋂ i ∈ u, t i) = ∅) :
IsLindelof s :=
isLindelof_of_countable_subcover fun U hUo hsU ↦ by
rw [← disjoint_compl_right_iff_subset, compl_iUnion, disjoint_iff] at hsU
rcases h (fun i ↦ (U i)ᶜ) (fun i ↦ (hUo _).isClosed_compl) hsU with ⟨t, ht⟩
refine ⟨t, ?_⟩
rwa [← disjoint_compl_right_iff_subset, compl_iUnion₂, disjoint_iff]
/-- A set `s` is Lindelöf if and only if
for every open cover of `s`, there exists a countable subcover. -/
theorem isLindelof_iff_countable_subcover :
IsLindelof s ↔ ∀ {ι : Type u} (U : ι → Set X),
(∀ i, IsOpen (U i)) → (s ⊆ ⋃ i, U i) → ∃ t : Set ι, t.Countable ∧ s ⊆ ⋃ i ∈ t, U i :=
⟨fun hs ↦ hs.elim_countable_subcover, isLindelof_of_countable_subcover⟩
/-- A set `s` is Lindelöf if and only if
for every family of closed sets whose intersection avoids `s`,
there exists a countable subfamily whose intersection avoids `s`. -/
theorem isLindelof_iff_countable_subfamily_closed :
IsLindelof s ↔ ∀ {ι : Type u} (t : ι → Set X),
(∀ i, IsClosed (t i)) → (s ∩ ⋂ i, t i) = ∅
→ ∃ u : Set ι, u.Countable ∧ (s ∩ ⋂ i ∈ u, t i) = ∅ :=
⟨fun hs ↦ hs.elim_countable_subfamily_closed, isLindelof_of_countable_subfamily_closed⟩
/-- The empty set is a Lindelof set. -/
@[simp]
theorem isLindelof_empty : IsLindelof (∅ : Set X) := fun _f hnf _ hsf ↦
Not.elim hnf.ne <| empty_mem_iff_bot.1 <| le_principal_iff.1 hsf
/-- A singleton set is a Lindelof set. -/
@[simp]
theorem isLindelof_singleton {x : X} : IsLindelof ({x} : Set X) := fun f hf _ hfa ↦
⟨x, rfl, ClusterPt.of_le_nhds'
(hfa.trans <| by simpa only [principal_singleton] using pure_le_nhds x) hf⟩
theorem Set.Subsingleton.isLindelof (hs : s.Subsingleton) : IsLindelof s :=
Subsingleton.induction_on hs isLindelof_empty fun _ ↦ isLindelof_singleton
theorem Set.Countable.isLindelof_biUnion {s : Set ι} {f : ι → Set X} (hs : s.Countable)
(hf : ∀ i ∈ s, IsLindelof (f i)) : IsLindelof (⋃ i ∈ s, f i) := by
apply isLindelof_of_countable_subcover
intro i U hU hUcover
have hiU : ∀ i ∈ s, f i ⊆ ⋃ i, U i :=
fun _ is ↦ _root_.subset_trans (subset_biUnion_of_mem is) hUcover
have iSets := fun i is ↦ (hf i is).elim_countable_subcover U hU (hiU i is)
choose! r hr using iSets
use ⋃ i ∈ s, r i
constructor
· refine (Countable.biUnion_iff hs).mpr ?h.left.a
exact fun s hs ↦ (hr s hs).1
· refine iUnion₂_subset ?h.right.h
intro i is
simp only [mem_iUnion, exists_prop, iUnion_exists, biUnion_and']
intro x hx
exact mem_biUnion is ((hr i is).2 hx)
theorem Set.Finite.isLindelof_biUnion {s : Set ι} {f : ι → Set X} (hs : s.Finite)
(hf : ∀ i ∈ s, IsLindelof (f i)) : IsLindelof (⋃ i ∈ s, f i) :=
Set.Countable.isLindelof_biUnion (countable hs) hf
theorem Finset.isLindelof_biUnion (s : Finset ι) {f : ι → Set X} (hf : ∀ i ∈ s, IsLindelof (f i)) :
IsLindelof (⋃ i ∈ s, f i) :=
s.finite_toSet.isLindelof_biUnion hf
theorem isLindelof_accumulate {K : ℕ → Set X} (hK : ∀ n, IsLindelof (K n)) (n : ℕ) :
IsLindelof (Accumulate K n) :=
(finite_le_nat n).isLindelof_biUnion fun k _ => hK k
theorem Set.Countable.isLindelof_sUnion {S : Set (Set X)} (hf : S.Countable)
(hc : ∀ s ∈ S, IsLindelof s) : IsLindelof (⋃₀ S) := by
rw [sUnion_eq_biUnion]; exact hf.isLindelof_biUnion hc
theorem Set.Finite.isLindelof_sUnion {S : Set (Set X)} (hf : S.Finite)
(hc : ∀ s ∈ S, IsLindelof s) : IsLindelof (⋃₀ S) := by
rw [sUnion_eq_biUnion]; exact hf.isLindelof_biUnion hc
theorem isLindelof_iUnion {ι : Sort*} {f : ι → Set X} [Countable ι] (h : ∀ i, IsLindelof (f i)) :
IsLindelof (⋃ i, f i) := (countable_range f).isLindelof_sUnion <| forall_mem_range.2 h
theorem Set.Countable.isLindelof (hs : s.Countable) : IsLindelof s :=
biUnion_of_singleton s ▸ hs.isLindelof_biUnion fun _ _ => isLindelof_singleton
theorem Set.Finite.isLindelof (hs : s.Finite) : IsLindelof s :=
biUnion_of_singleton s ▸ hs.isLindelof_biUnion fun _ _ => isLindelof_singleton
theorem IsLindelof.countable_of_discrete [DiscreteTopology X] (hs : IsLindelof s) :
s.Countable := by
have : ∀ x : X, ({x} : Set X) ∈ 𝓝 x := by simp [nhds_discrete]
rcases hs.elim_nhds_subcover (fun x => {x}) fun x _ => this x with ⟨t, ht, _, hssubt⟩
rw [biUnion_of_singleton] at hssubt
exact ht.mono hssubt
theorem isLindelof_iff_countable [DiscreteTopology X] : IsLindelof s ↔ s.Countable :=
⟨fun h => h.countable_of_discrete, fun h => h.isLindelof⟩
theorem IsLindelof.union (hs : IsLindelof s) (ht : IsLindelof t) : IsLindelof (s ∪ t) := by
rw [union_eq_iUnion]; exact isLindelof_iUnion fun b => by cases b <;> assumption
protected theorem IsLindelof.insert (hs : IsLindelof s) (a) : IsLindelof (insert a s) :=
isLindelof_singleton.union hs
/-- If `X` has a basis consisting of compact opens, then an open set in `X` is compact open iff
it is a finite union of some elements in the basis -/
theorem isLindelof_open_iff_eq_countable_iUnion_of_isTopologicalBasis (b : ι → Set X)
(hb : IsTopologicalBasis (Set.range b)) (hb' : ∀ i, IsLindelof (b i)) (U : Set X) :
IsLindelof U ∧ IsOpen U ↔ ∃ s : Set ι, s.Countable ∧ U = ⋃ i ∈ s, b i := by
constructor
· rintro ⟨h₁, h₂⟩
obtain ⟨Y, f, rfl, hf⟩ := hb.open_eq_iUnion h₂
choose f' hf' using hf
have : b ∘ f' = f := funext hf'
subst this
obtain ⟨t, ht⟩ :=
h₁.elim_countable_subcover (b ∘ f') (fun i => hb.isOpen (Set.mem_range_self _)) Subset.rfl
refine ⟨t.image f', Countable.image (ht.1) f', le_antisymm ?_ ?_⟩
· refine Set.Subset.trans ht.2 ?_
simp only [Set.iUnion_subset_iff]
intro i hi
rw [← Set.iUnion_subtype (fun x : ι => x ∈ t.image f') fun i => b i.1]
exact Set.subset_iUnion (fun i : t.image f' => b i) ⟨_, mem_image_of_mem _ hi⟩
· apply Set.iUnion₂_subset
rintro i hi
obtain ⟨j, -, rfl⟩ := (mem_image ..).mp hi
exact Set.subset_iUnion (b ∘ f') j
· rintro ⟨s, hs, rfl⟩
constructor
· exact hs.isLindelof_biUnion fun i _ => hb' i
· exact isOpen_biUnion fun i _ => hb.isOpen (Set.mem_range_self _)
/-- `Filter.coLindelof` is the filter generated by complements to Lindelöf sets. -/
def Filter.coLindelof (X : Type*) [TopologicalSpace X] : Filter X :=
--`Filter.coLindelof` is the filter generated by complements to Lindelöf sets.
⨅ (s : Set X) (_ : IsLindelof s), 𝓟 sᶜ
theorem hasBasis_coLindelof : (coLindelof X).HasBasis IsLindelof compl :=
hasBasis_biInf_principal'
(fun s hs t ht =>
⟨s ∪ t, hs.union ht, compl_subset_compl.2 subset_union_left,
compl_subset_compl.2 subset_union_right⟩)
⟨∅, isLindelof_empty⟩
theorem mem_coLindelof : s ∈ coLindelof X ↔ ∃ t, IsLindelof t ∧ tᶜ ⊆ s :=
hasBasis_coLindelof.mem_iff
theorem mem_coLindelof' : s ∈ coLindelof X ↔ ∃ t, IsLindelof t ∧ sᶜ ⊆ t :=
mem_coLindelof.trans <| exists_congr fun _ => and_congr_right fun _ => compl_subset_comm
theorem _root_.IsLindelof.compl_mem_coLindelof (hs : IsLindelof s) : sᶜ ∈ coLindelof X :=
hasBasis_coLindelof.mem_of_mem hs
theorem coLindelof_le_cofinite : coLindelof X ≤ cofinite := fun s hs =>
compl_compl s ▸ hs.isLindelof.compl_mem_coLindelof
theorem Tendsto.isLindelof_insert_range_of_coLindelof {f : X → Y} {y}
(hf : Tendsto f (coLindelof X) (𝓝 y)) (hfc : Continuous f) :
IsLindelof (insert y (range f)) := by
intro l hne _ hle
by_cases hy : ClusterPt y l
· exact ⟨y, Or.inl rfl, hy⟩
simp only [clusterPt_iff, not_forall, ← not_disjoint_iff_nonempty_inter, not_not] at hy
rcases hy with ⟨s, hsy, t, htl, hd⟩
rcases mem_coLindelof.1 (hf hsy) with ⟨K, hKc, hKs⟩
have : f '' K ∈ l := by
filter_upwards [htl, le_principal_iff.1 hle] with y hyt hyf
rcases hyf with (rfl | ⟨x, rfl⟩)
exacts [(hd.le_bot ⟨mem_of_mem_nhds hsy, hyt⟩).elim,
mem_image_of_mem _ (not_not.1 fun hxK => hd.le_bot ⟨hKs hxK, hyt⟩)]
rcases hKc.image hfc (le_principal_iff.2 this) with ⟨y, hy, hyl⟩
exact ⟨y, Or.inr <| image_subset_range _ _ hy, hyl⟩
/-- `Filter.coclosedLindelof` is the filter generated by complements to closed Lindelof sets. -/
def Filter.coclosedLindelof (X : Type*) [TopologicalSpace X] : Filter X :=
-- `Filter.coclosedLindelof` is the filter generated by complements to closed Lindelof sets.
⨅ (s : Set X) (_ : IsClosed s) (_ : IsLindelof s), 𝓟 sᶜ
theorem hasBasis_coclosedLindelof :
(Filter.coclosedLindelof X).HasBasis (fun s => IsClosed s ∧ IsLindelof s) compl := by
simp only [Filter.coclosedLindelof, iInf_and']
refine hasBasis_biInf_principal' ?_ ⟨∅, isClosed_empty, isLindelof_empty⟩
rintro s ⟨hs₁, hs₂⟩ t ⟨ht₁, ht₂⟩
exact ⟨s ∪ t, ⟨⟨hs₁.union ht₁, hs₂.union ht₂⟩, compl_subset_compl.2 subset_union_left,
compl_subset_compl.2 subset_union_right⟩⟩
theorem mem_coclosedLindelof : s ∈ coclosedLindelof X ↔
∃ t, IsClosed t ∧ IsLindelof t ∧ tᶜ ⊆ s := by
simp only [hasBasis_coclosedLindelof.mem_iff, and_assoc]
theorem mem_coclosed_Lindelof' : s ∈ coclosedLindelof X ↔
∃ t, IsClosed t ∧ IsLindelof t ∧ sᶜ ⊆ t := by
simp only [mem_coclosedLindelof, compl_subset_comm]
theorem coLindelof_le_coclosedLindelof : coLindelof X ≤ coclosedLindelof X :=
iInf_mono fun _ => le_iInf fun _ => le_rfl
theorem IsLindeof.compl_mem_coclosedLindelof_of_isClosed (hs : IsLindelof s) (hs' : IsClosed s) :
sᶜ ∈ Filter.coclosedLindelof X :=
hasBasis_coclosedLindelof.mem_of_mem ⟨hs', hs⟩
/-- X is a Lindelöf space iff every open cover has a countable subcover. -/
class LindelofSpace (X : Type*) [TopologicalSpace X] : Prop where
/-- In a Lindelöf space, `Set.univ` is a Lindelöf set. -/
isLindelof_univ : IsLindelof (univ : Set X)
instance (priority := 10) Subsingleton.lindelofSpace [Subsingleton X] : LindelofSpace X :=
⟨subsingleton_univ.isLindelof⟩
theorem isLindelof_univ_iff : IsLindelof (univ : Set X) ↔ LindelofSpace X :=
⟨fun h => ⟨h⟩, fun h => h.1⟩
theorem isLindelof_univ [h : LindelofSpace X] : IsLindelof (univ : Set X) :=
h.isLindelof_univ
theorem cluster_point_of_Lindelof [LindelofSpace X] (f : Filter X) [NeBot f]
[CountableInterFilter f] : ∃ x, ClusterPt x f := by
simpa using isLindelof_univ (show f ≤ 𝓟 univ by simp)
| Mathlib/Topology/Compactness/Lindelof.lean | 481 | 485 | theorem LindelofSpace.elim_nhds_subcover [LindelofSpace X] (U : X → Set X) (hU : ∀ x, U x ∈ 𝓝 x) :
∃ t : Set X, t.Countable ∧ ⋃ x ∈ t, U x = univ := by |
obtain ⟨t, tc, -, s⟩ := IsLindelof.elim_nhds_subcover isLindelof_univ U fun x _ => hU x
use t, tc
apply top_unique s
|
/-
Copyright (c) 2020 Joseph Myers. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joseph Myers, Manuel Candales
-/
import Mathlib.Analysis.Convex.Between
import Mathlib.Analysis.Normed.Group.AddTorsor
import Mathlib.Geometry.Euclidean.Angle.Unoriented.Basic
import Mathlib.Analysis.NormedSpace.AffineIsometry
#align_import geometry.euclidean.angle.unoriented.affine from "leanprover-community/mathlib"@"46b633fd842bef9469441c0209906f6dddd2b4f5"
/-!
# Angles between points
This file defines unoriented angles in Euclidean affine spaces.
## Main definitions
* `EuclideanGeometry.angle`, with notation `∠`, is the undirected angle determined by three
points.
## TODO
Prove the triangle inequality for the angle.
-/
noncomputable section
open Real RealInnerProductSpace
namespace EuclideanGeometry
open InnerProductGeometry
variable {V P : Type*} [NormedAddCommGroup V] [InnerProductSpace ℝ V] [MetricSpace P]
[NormedAddTorsor V P] {p p₀ p₁ p₂ : P}
/-- The undirected angle at `p2` between the line segments to `p1` and
`p3`. If either of those points equals `p2`, this is π/2. Use
`open scoped EuclideanGeometry` to access the `∠ p1 p2 p3`
notation. -/
nonrec def angle (p1 p2 p3 : P) : ℝ :=
angle (p1 -ᵥ p2 : V) (p3 -ᵥ p2)
#align euclidean_geometry.angle EuclideanGeometry.angle
@[inherit_doc] scoped notation "∠" => EuclideanGeometry.angle
theorem continuousAt_angle {x : P × P × P} (hx12 : x.1 ≠ x.2.1) (hx32 : x.2.2 ≠ x.2.1) :
ContinuousAt (fun y : P × P × P => ∠ y.1 y.2.1 y.2.2) x := by
let f : P × P × P → V × V := fun y => (y.1 -ᵥ y.2.1, y.2.2 -ᵥ y.2.1)
have hf1 : (f x).1 ≠ 0 := by simp [hx12]
have hf2 : (f x).2 ≠ 0 := by simp [hx32]
exact (InnerProductGeometry.continuousAt_angle hf1 hf2).comp
((continuous_fst.vsub continuous_snd.fst).prod_mk
(continuous_snd.snd.vsub continuous_snd.fst)).continuousAt
#align euclidean_geometry.continuous_at_angle EuclideanGeometry.continuousAt_angle
@[simp]
theorem _root_.AffineIsometry.angle_map {V₂ P₂ : Type*} [NormedAddCommGroup V₂]
[InnerProductSpace ℝ V₂] [MetricSpace P₂] [NormedAddTorsor V₂ P₂]
(f : P →ᵃⁱ[ℝ] P₂) (p₁ p₂ p₃ : P) : ∠ (f p₁) (f p₂) (f p₃) = ∠ p₁ p₂ p₃ := by
simp_rw [angle, ← AffineIsometry.map_vsub, LinearIsometry.angle_map]
#align affine_isometry.angle_map AffineIsometry.angle_map
@[simp, norm_cast]
theorem _root_.AffineSubspace.angle_coe {s : AffineSubspace ℝ P} (p₁ p₂ p₃ : s) :
haveI : Nonempty s := ⟨p₁⟩
∠ (p₁ : P) (p₂ : P) (p₃ : P) = ∠ p₁ p₂ p₃ :=
haveI : Nonempty s := ⟨p₁⟩
s.subtypeₐᵢ.angle_map p₁ p₂ p₃
#align affine_subspace.angle_coe AffineSubspace.angle_coe
/-- Angles are translation invariant -/
@[simp]
theorem angle_const_vadd (v : V) (p₁ p₂ p₃ : P) : ∠ (v +ᵥ p₁) (v +ᵥ p₂) (v +ᵥ p₃) = ∠ p₁ p₂ p₃ :=
(AffineIsometryEquiv.constVAdd ℝ P v).toAffineIsometry.angle_map _ _ _
#align euclidean_geometry.angle_const_vadd EuclideanGeometry.angle_const_vadd
/-- Angles are translation invariant -/
@[simp]
theorem angle_vadd_const (v₁ v₂ v₃ : V) (p : P) : ∠ (v₁ +ᵥ p) (v₂ +ᵥ p) (v₃ +ᵥ p) = ∠ v₁ v₂ v₃ :=
(AffineIsometryEquiv.vaddConst ℝ p).toAffineIsometry.angle_map _ _ _
#align euclidean_geometry.angle_vadd_const EuclideanGeometry.angle_vadd_const
/-- Angles are translation invariant -/
@[simp]
theorem angle_const_vsub (p p₁ p₂ p₃ : P) : ∠ (p -ᵥ p₁) (p -ᵥ p₂) (p -ᵥ p₃) = ∠ p₁ p₂ p₃ :=
(AffineIsometryEquiv.constVSub ℝ p).toAffineIsometry.angle_map _ _ _
#align euclidean_geometry.angle_const_vsub EuclideanGeometry.angle_const_vsub
/-- Angles are translation invariant -/
@[simp]
theorem angle_vsub_const (p₁ p₂ p₃ p : P) : ∠ (p₁ -ᵥ p) (p₂ -ᵥ p) (p₃ -ᵥ p) = ∠ p₁ p₂ p₃ :=
(AffineIsometryEquiv.vaddConst ℝ p).symm.toAffineIsometry.angle_map _ _ _
#align euclidean_geometry.angle_vsub_const EuclideanGeometry.angle_vsub_const
/-- Angles in a vector space are translation invariant -/
@[simp]
theorem angle_add_const (v₁ v₂ v₃ : V) (v : V) : ∠ (v₁ + v) (v₂ + v) (v₃ + v) = ∠ v₁ v₂ v₃ :=
angle_vadd_const _ _ _ _
#align euclidean_geometry.angle_add_const EuclideanGeometry.angle_add_const
/-- Angles in a vector space are translation invariant -/
@[simp]
theorem angle_const_add (v : V) (v₁ v₂ v₃ : V) : ∠ (v + v₁) (v + v₂) (v + v₃) = ∠ v₁ v₂ v₃ :=
angle_const_vadd _ _ _ _
#align euclidean_geometry.angle_const_add EuclideanGeometry.angle_const_add
/-- Angles in a vector space are translation invariant -/
@[simp]
theorem angle_sub_const (v₁ v₂ v₃ : V) (v : V) : ∠ (v₁ - v) (v₂ - v) (v₃ - v) = ∠ v₁ v₂ v₃ := by
simpa only [vsub_eq_sub] using angle_vsub_const v₁ v₂ v₃ v
#align euclidean_geometry.angle_sub_const EuclideanGeometry.angle_sub_const
/-- Angles in a vector space are invariant to inversion -/
@[simp]
theorem angle_const_sub (v : V) (v₁ v₂ v₃ : V) : ∠ (v - v₁) (v - v₂) (v - v₃) = ∠ v₁ v₂ v₃ := by
simpa only [vsub_eq_sub] using angle_const_vsub v v₁ v₂ v₃
#align euclidean_geometry.angle_const_sub EuclideanGeometry.angle_const_sub
/-- Angles in a vector space are invariant to inversion -/
@[simp]
theorem angle_neg (v₁ v₂ v₃ : V) : ∠ (-v₁) (-v₂) (-v₃) = ∠ v₁ v₂ v₃ := by
simpa only [zero_sub] using angle_const_sub 0 v₁ v₂ v₃
#align euclidean_geometry.angle_neg EuclideanGeometry.angle_neg
/-- The angle at a point does not depend on the order of the other two
points. -/
nonrec theorem angle_comm (p1 p2 p3 : P) : ∠ p1 p2 p3 = ∠ p3 p2 p1 :=
angle_comm _ _
#align euclidean_geometry.angle_comm EuclideanGeometry.angle_comm
/-- The angle at a point is nonnegative. -/
nonrec theorem angle_nonneg (p1 p2 p3 : P) : 0 ≤ ∠ p1 p2 p3 :=
angle_nonneg _ _
#align euclidean_geometry.angle_nonneg EuclideanGeometry.angle_nonneg
/-- The angle at a point is at most π. -/
nonrec theorem angle_le_pi (p1 p2 p3 : P) : ∠ p1 p2 p3 ≤ π :=
angle_le_pi _ _
#align euclidean_geometry.angle_le_pi EuclideanGeometry.angle_le_pi
/-- The angle ∠AAB at a point is always `π / 2`. -/
@[simp] lemma angle_self_left (p₀ p : P) : ∠ p₀ p₀ p = π / 2 := by
unfold angle
rw [vsub_self]
exact angle_zero_left _
#align euclidean_geometry.angle_eq_left EuclideanGeometry.angle_self_left
/-- The angle ∠ABB at a point is always `π / 2`. -/
@[simp] lemma angle_self_right (p₀ p : P) : ∠ p p₀ p₀ = π / 2 := by rw [angle_comm, angle_self_left]
#align euclidean_geometry.angle_eq_right EuclideanGeometry.angle_self_right
/-- The angle ∠ABA at a point is `0`, unless `A = B`. -/
theorem angle_self_of_ne (h : p ≠ p₀) : ∠ p p₀ p = 0 := angle_self $ vsub_ne_zero.2 h
#align euclidean_geometry.angle_eq_of_ne EuclideanGeometry.angle_self_of_ne
@[deprecated (since := "2024-02-14")] alias angle_eq_left := angle_self_left
@[deprecated (since := "2024-02-14")] alias angle_eq_right := angle_self_right
@[deprecated (since := "2024-02-14")] alias angle_eq_of_ne := angle_self_of_ne
/-- If the angle ∠ABC at a point is π, the angle ∠BAC is 0. -/
theorem angle_eq_zero_of_angle_eq_pi_left {p1 p2 p3 : P} (h : ∠ p1 p2 p3 = π) : ∠ p2 p1 p3 = 0 := by
unfold angle at h
rw [angle_eq_pi_iff] at h
rcases h with ⟨hp1p2, ⟨r, ⟨hr, hpr⟩⟩⟩
unfold angle
rw [angle_eq_zero_iff]
rw [← neg_vsub_eq_vsub_rev, neg_ne_zero] at hp1p2
use hp1p2, -r + 1, add_pos (neg_pos_of_neg hr) zero_lt_one
rw [add_smul, ← neg_vsub_eq_vsub_rev p1 p2, smul_neg]
simp [← hpr]
#align euclidean_geometry.angle_eq_zero_of_angle_eq_pi_left EuclideanGeometry.angle_eq_zero_of_angle_eq_pi_left
/-- If the angle ∠ABC at a point is π, the angle ∠BCA is 0. -/
theorem angle_eq_zero_of_angle_eq_pi_right {p1 p2 p3 : P} (h : ∠ p1 p2 p3 = π) :
∠ p2 p3 p1 = 0 := by
rw [angle_comm] at h
exact angle_eq_zero_of_angle_eq_pi_left h
#align euclidean_geometry.angle_eq_zero_of_angle_eq_pi_right EuclideanGeometry.angle_eq_zero_of_angle_eq_pi_right
/-- If ∠BCD = π, then ∠ABC = ∠ABD. -/
theorem angle_eq_angle_of_angle_eq_pi (p1 : P) {p2 p3 p4 : P} (h : ∠ p2 p3 p4 = π) :
∠ p1 p2 p3 = ∠ p1 p2 p4 := by
unfold angle at *
rcases angle_eq_pi_iff.1 h with ⟨_, ⟨r, ⟨hr, hpr⟩⟩⟩
rw [eq_comm]
convert angle_smul_right_of_pos (p1 -ᵥ p2) (p3 -ᵥ p2) (add_pos (neg_pos_of_neg hr) zero_lt_one)
rw [add_smul, ← neg_vsub_eq_vsub_rev p2 p3, smul_neg, neg_smul, ← hpr]
simp
#align euclidean_geometry.angle_eq_angle_of_angle_eq_pi EuclideanGeometry.angle_eq_angle_of_angle_eq_pi
/-- If ∠BCD = π, then ∠ACB + ∠ACD = π. -/
nonrec theorem angle_add_angle_eq_pi_of_angle_eq_pi (p1 : P) {p2 p3 p4 : P} (h : ∠ p2 p3 p4 = π) :
∠ p1 p3 p2 + ∠ p1 p3 p4 = π := by
unfold angle at h
rw [angle_comm p1 p3 p2, angle_comm p1 p3 p4]
unfold angle
exact angle_add_angle_eq_pi_of_angle_eq_pi _ h
#align euclidean_geometry.angle_add_angle_eq_pi_of_angle_eq_pi EuclideanGeometry.angle_add_angle_eq_pi_of_angle_eq_pi
/-- **Vertical Angles Theorem**: angles opposite each other, formed by two intersecting straight
lines, are equal. -/
theorem angle_eq_angle_of_angle_eq_pi_of_angle_eq_pi {p1 p2 p3 p4 p5 : P} (hapc : ∠ p1 p5 p3 = π)
(hbpd : ∠ p2 p5 p4 = π) : ∠ p1 p5 p2 = ∠ p3 p5 p4 := by
linarith [angle_add_angle_eq_pi_of_angle_eq_pi p1 hbpd, angle_comm p4 p5 p1,
angle_add_angle_eq_pi_of_angle_eq_pi p4 hapc, angle_comm p4 p5 p3]
#align euclidean_geometry.angle_eq_angle_of_angle_eq_pi_of_angle_eq_pi EuclideanGeometry.angle_eq_angle_of_angle_eq_pi_of_angle_eq_pi
/-- If ∠ABC = π then dist A B ≠ 0. -/
theorem left_dist_ne_zero_of_angle_eq_pi {p1 p2 p3 : P} (h : ∠ p1 p2 p3 = π) : dist p1 p2 ≠ 0 := by
by_contra heq
rw [dist_eq_zero] at heq
rw [heq, angle_self_left] at h
exact Real.pi_ne_zero (by linarith)
#align euclidean_geometry.left_dist_ne_zero_of_angle_eq_pi EuclideanGeometry.left_dist_ne_zero_of_angle_eq_pi
/-- If ∠ABC = π then dist C B ≠ 0. -/
theorem right_dist_ne_zero_of_angle_eq_pi {p1 p2 p3 : P} (h : ∠ p1 p2 p3 = π) : dist p3 p2 ≠ 0 :=
left_dist_ne_zero_of_angle_eq_pi <| (angle_comm _ _ _).trans h
#align euclidean_geometry.right_dist_ne_zero_of_angle_eq_pi EuclideanGeometry.right_dist_ne_zero_of_angle_eq_pi
/-- If ∠ABC = π, then (dist A C) = (dist A B) + (dist B C). -/
theorem dist_eq_add_dist_of_angle_eq_pi {p1 p2 p3 : P} (h : ∠ p1 p2 p3 = π) :
dist p1 p3 = dist p1 p2 + dist p3 p2 := by
rw [dist_eq_norm_vsub V, dist_eq_norm_vsub V, dist_eq_norm_vsub V, ← vsub_sub_vsub_cancel_right]
exact norm_sub_eq_add_norm_of_angle_eq_pi h
#align euclidean_geometry.dist_eq_add_dist_of_angle_eq_pi EuclideanGeometry.dist_eq_add_dist_of_angle_eq_pi
/-- If A ≠ B and C ≠ B then ∠ABC = π if and only if (dist A C) = (dist A B) + (dist B C). -/
theorem dist_eq_add_dist_iff_angle_eq_pi {p1 p2 p3 : P} (hp1p2 : p1 ≠ p2) (hp3p2 : p3 ≠ p2) :
dist p1 p3 = dist p1 p2 + dist p3 p2 ↔ ∠ p1 p2 p3 = π := by
rw [dist_eq_norm_vsub V, dist_eq_norm_vsub V, dist_eq_norm_vsub V, ← vsub_sub_vsub_cancel_right]
exact
norm_sub_eq_add_norm_iff_angle_eq_pi (fun he => hp1p2 (vsub_eq_zero_iff_eq.1 he)) fun he =>
hp3p2 (vsub_eq_zero_iff_eq.1 he)
#align euclidean_geometry.dist_eq_add_dist_iff_angle_eq_pi EuclideanGeometry.dist_eq_add_dist_iff_angle_eq_pi
/-- If ∠ABC = 0, then (dist A C) = abs ((dist A B) - (dist B C)). -/
theorem dist_eq_abs_sub_dist_of_angle_eq_zero {p1 p2 p3 : P} (h : ∠ p1 p2 p3 = 0) :
dist p1 p3 = |dist p1 p2 - dist p3 p2| := by
rw [dist_eq_norm_vsub V, dist_eq_norm_vsub V, dist_eq_norm_vsub V, ← vsub_sub_vsub_cancel_right]
exact norm_sub_eq_abs_sub_norm_of_angle_eq_zero h
#align euclidean_geometry.dist_eq_abs_sub_dist_of_angle_eq_zero EuclideanGeometry.dist_eq_abs_sub_dist_of_angle_eq_zero
/-- If A ≠ B and C ≠ B then ∠ABC = 0 if and only if (dist A C) = abs ((dist A B) - (dist B C)). -/
theorem dist_eq_abs_sub_dist_iff_angle_eq_zero {p1 p2 p3 : P} (hp1p2 : p1 ≠ p2) (hp3p2 : p3 ≠ p2) :
dist p1 p3 = |dist p1 p2 - dist p3 p2| ↔ ∠ p1 p2 p3 = 0 := by
rw [dist_eq_norm_vsub V, dist_eq_norm_vsub V, dist_eq_norm_vsub V, ← vsub_sub_vsub_cancel_right]
exact
norm_sub_eq_abs_sub_norm_iff_angle_eq_zero (fun he => hp1p2 (vsub_eq_zero_iff_eq.1 he))
fun he => hp3p2 (vsub_eq_zero_iff_eq.1 he)
#align euclidean_geometry.dist_eq_abs_sub_dist_iff_angle_eq_zero EuclideanGeometry.dist_eq_abs_sub_dist_iff_angle_eq_zero
/-- If M is the midpoint of the segment AB, then ∠AMB = π. -/
theorem angle_midpoint_eq_pi (p1 p2 : P) (hp1p2 : p1 ≠ p2) : ∠ p1 (midpoint ℝ p1 p2) p2 = π := by
simp only [angle, left_vsub_midpoint, invOf_eq_inv, right_vsub_midpoint, inv_pos, zero_lt_two,
angle_smul_right_of_pos, angle_smul_left_of_pos]
rw [← neg_vsub_eq_vsub_rev p1 p2]
apply angle_self_neg_of_nonzero
simpa only [ne_eq, vsub_eq_zero_iff_eq]
#align euclidean_geometry.angle_midpoint_eq_pi EuclideanGeometry.angle_midpoint_eq_pi
/-- If M is the midpoint of the segment AB and C is the same distance from A as it is from B
then ∠CMA = π / 2. -/
theorem angle_left_midpoint_eq_pi_div_two_of_dist_eq {p1 p2 p3 : P} (h : dist p3 p1 = dist p3 p2) :
∠ p3 (midpoint ℝ p1 p2) p1 = π / 2 := by
let m : P := midpoint ℝ p1 p2
have h1 : p3 -ᵥ p1 = p3 -ᵥ m - (p1 -ᵥ m) := (vsub_sub_vsub_cancel_right p3 p1 m).symm
have h2 : p3 -ᵥ p2 = p3 -ᵥ m + (p1 -ᵥ m) := by
rw [left_vsub_midpoint, ← midpoint_vsub_right, vsub_add_vsub_cancel]
rw [dist_eq_norm_vsub V p3 p1, dist_eq_norm_vsub V p3 p2, h1, h2] at h
exact (norm_add_eq_norm_sub_iff_angle_eq_pi_div_two (p3 -ᵥ m) (p1 -ᵥ m)).mp h.symm
#align euclidean_geometry.angle_left_midpoint_eq_pi_div_two_of_dist_eq EuclideanGeometry.angle_left_midpoint_eq_pi_div_two_of_dist_eq
/-- If M is the midpoint of the segment AB and C is the same distance from A as it is from B
then ∠CMB = π / 2. -/
theorem angle_right_midpoint_eq_pi_div_two_of_dist_eq {p1 p2 p3 : P} (h : dist p3 p1 = dist p3 p2) :
∠ p3 (midpoint ℝ p1 p2) p2 = π / 2 := by
rw [midpoint_comm p1 p2, angle_left_midpoint_eq_pi_div_two_of_dist_eq h.symm]
#align euclidean_geometry.angle_right_midpoint_eq_pi_div_two_of_dist_eq EuclideanGeometry.angle_right_midpoint_eq_pi_div_two_of_dist_eq
/-- If the second of three points is strictly between the other two, the angle at that point
is π. -/
theorem _root_.Sbtw.angle₁₂₃_eq_pi {p₁ p₂ p₃ : P} (h : Sbtw ℝ p₁ p₂ p₃) : ∠ p₁ p₂ p₃ = π := by
rw [angle, angle_eq_pi_iff]
rcases h with ⟨⟨r, ⟨hr0, hr1⟩, hp₂⟩, hp₂p₁, hp₂p₃⟩
refine ⟨vsub_ne_zero.2 hp₂p₁.symm, -(1 - r) / r, ?_⟩
have hr0' : r ≠ 0 := by
rintro rfl
rw [← hp₂] at hp₂p₁
simp at hp₂p₁
have hr1' : r ≠ 1 := by
rintro rfl
rw [← hp₂] at hp₂p₃
simp at hp₂p₃
replace hr0 := hr0.lt_of_ne hr0'.symm
replace hr1 := hr1.lt_of_ne hr1'
refine ⟨div_neg_of_neg_of_pos (Left.neg_neg_iff.2 (sub_pos.2 hr1)) hr0, ?_⟩
rw [← hp₂, AffineMap.lineMap_apply, vsub_vadd_eq_vsub_sub, vsub_vadd_eq_vsub_sub, vsub_self,
zero_sub, smul_neg, smul_smul, div_mul_cancel₀ _ hr0', neg_smul, neg_neg, sub_eq_iff_eq_add, ←
add_smul, sub_add_cancel, one_smul]
#align sbtw.angle₁₂₃_eq_pi Sbtw.angle₁₂₃_eq_pi
/-- If the second of three points is strictly between the other two, the angle at that point
(reversed) is π. -/
| Mathlib/Geometry/Euclidean/Angle/Unoriented/Affine.lean | 309 | 310 | theorem _root_.Sbtw.angle₃₂₁_eq_pi {p₁ p₂ p₃ : P} (h : Sbtw ℝ p₁ p₂ p₃) : ∠ p₃ p₂ p₁ = π := by |
rw [← h.angle₁₂₃_eq_pi, angle_comm]
|
/-
Copyright (c) 2015 Microsoft Corporation. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Algebra.Group.Nat
import Mathlib.Algebra.Order.Sub.Canonical
import Mathlib.Data.List.Perm
import Mathlib.Data.Set.List
import Mathlib.Init.Quot
import Mathlib.Order.Hom.Basic
#align_import data.multiset.basic from "leanprover-community/mathlib"@"65a1391a0106c9204fe45bc73a039f056558cb83"
/-!
# Multisets
These are implemented as the quotient of a list by permutations.
## Notation
We define the global infix notation `::ₘ` for `Multiset.cons`.
-/
universe v
open List Subtype Nat Function
variable {α : Type*} {β : Type v} {γ : Type*}
/-- `Multiset α` is the quotient of `List α` by list permutation. The result
is a type of finite sets with duplicates allowed. -/
def Multiset.{u} (α : Type u) : Type u :=
Quotient (List.isSetoid α)
#align multiset Multiset
namespace Multiset
-- Porting note: new
/-- The quotient map from `List α` to `Multiset α`. -/
@[coe]
def ofList : List α → Multiset α :=
Quot.mk _
instance : Coe (List α) (Multiset α) :=
⟨ofList⟩
@[simp]
theorem quot_mk_to_coe (l : List α) : @Eq (Multiset α) ⟦l⟧ l :=
rfl
#align multiset.quot_mk_to_coe Multiset.quot_mk_to_coe
@[simp]
theorem quot_mk_to_coe' (l : List α) : @Eq (Multiset α) (Quot.mk (· ≈ ·) l) l :=
rfl
#align multiset.quot_mk_to_coe' Multiset.quot_mk_to_coe'
@[simp]
theorem quot_mk_to_coe'' (l : List α) : @Eq (Multiset α) (Quot.mk Setoid.r l) l :=
rfl
#align multiset.quot_mk_to_coe'' Multiset.quot_mk_to_coe''
@[simp]
theorem coe_eq_coe {l₁ l₂ : List α} : (l₁ : Multiset α) = l₂ ↔ l₁ ~ l₂ :=
Quotient.eq
#align multiset.coe_eq_coe Multiset.coe_eq_coe
-- Porting note: new instance;
-- Porting note (#11215): TODO: move to better place
instance [DecidableEq α] (l₁ l₂ : List α) : Decidable (l₁ ≈ l₂) :=
inferInstanceAs (Decidable (l₁ ~ l₂))
-- Porting note: `Quotient.recOnSubsingleton₂ s₁ s₂` was in parens which broke elaboration
instance decidableEq [DecidableEq α] : DecidableEq (Multiset α)
| s₁, s₂ => Quotient.recOnSubsingleton₂ s₁ s₂ fun _ _ => decidable_of_iff' _ Quotient.eq
#align multiset.has_decidable_eq Multiset.decidableEq
/-- defines a size for a multiset by referring to the size of the underlying list -/
protected
def sizeOf [SizeOf α] (s : Multiset α) : ℕ :=
(Quot.liftOn s SizeOf.sizeOf) fun _ _ => Perm.sizeOf_eq_sizeOf
#align multiset.sizeof Multiset.sizeOf
instance [SizeOf α] : SizeOf (Multiset α) :=
⟨Multiset.sizeOf⟩
/-! ### Empty multiset -/
/-- `0 : Multiset α` is the empty set -/
protected def zero : Multiset α :=
@nil α
#align multiset.zero Multiset.zero
instance : Zero (Multiset α) :=
⟨Multiset.zero⟩
instance : EmptyCollection (Multiset α) :=
⟨0⟩
instance inhabitedMultiset : Inhabited (Multiset α) :=
⟨0⟩
#align multiset.inhabited_multiset Multiset.inhabitedMultiset
instance [IsEmpty α] : Unique (Multiset α) where
default := 0
uniq := by rintro ⟨_ | ⟨a, l⟩⟩; exacts [rfl, isEmptyElim a]
@[simp]
theorem coe_nil : (@nil α : Multiset α) = 0 :=
rfl
#align multiset.coe_nil Multiset.coe_nil
@[simp]
theorem empty_eq_zero : (∅ : Multiset α) = 0 :=
rfl
#align multiset.empty_eq_zero Multiset.empty_eq_zero
@[simp]
theorem coe_eq_zero (l : List α) : (l : Multiset α) = 0 ↔ l = [] :=
Iff.trans coe_eq_coe perm_nil
#align multiset.coe_eq_zero Multiset.coe_eq_zero
theorem coe_eq_zero_iff_isEmpty (l : List α) : (l : Multiset α) = 0 ↔ l.isEmpty :=
Iff.trans (coe_eq_zero l) isEmpty_iff_eq_nil.symm
#align multiset.coe_eq_zero_iff_empty Multiset.coe_eq_zero_iff_isEmpty
/-! ### `Multiset.cons` -/
/-- `cons a s` is the multiset which contains `s` plus one more instance of `a`. -/
def cons (a : α) (s : Multiset α) : Multiset α :=
Quot.liftOn s (fun l => (a :: l : Multiset α)) fun _ _ p => Quot.sound (p.cons a)
#align multiset.cons Multiset.cons
@[inherit_doc Multiset.cons]
infixr:67 " ::ₘ " => Multiset.cons
instance : Insert α (Multiset α) :=
⟨cons⟩
@[simp]
theorem insert_eq_cons (a : α) (s : Multiset α) : insert a s = a ::ₘ s :=
rfl
#align multiset.insert_eq_cons Multiset.insert_eq_cons
@[simp]
theorem cons_coe (a : α) (l : List α) : (a ::ₘ l : Multiset α) = (a :: l : List α) :=
rfl
#align multiset.cons_coe Multiset.cons_coe
@[simp]
theorem cons_inj_left {a b : α} (s : Multiset α) : a ::ₘ s = b ::ₘ s ↔ a = b :=
⟨Quot.inductionOn s fun l e =>
have : [a] ++ l ~ [b] ++ l := Quotient.exact e
singleton_perm_singleton.1 <| (perm_append_right_iff _).1 this,
congr_arg (· ::ₘ _)⟩
#align multiset.cons_inj_left Multiset.cons_inj_left
@[simp]
theorem cons_inj_right (a : α) : ∀ {s t : Multiset α}, a ::ₘ s = a ::ₘ t ↔ s = t := by
rintro ⟨l₁⟩ ⟨l₂⟩; simp
#align multiset.cons_inj_right Multiset.cons_inj_right
@[elab_as_elim]
protected theorem induction {p : Multiset α → Prop} (empty : p 0)
(cons : ∀ (a : α) (s : Multiset α), p s → p (a ::ₘ s)) : ∀ s, p s := by
rintro ⟨l⟩; induction' l with _ _ ih <;> [exact empty; exact cons _ _ ih]
#align multiset.induction Multiset.induction
@[elab_as_elim]
protected theorem induction_on {p : Multiset α → Prop} (s : Multiset α) (empty : p 0)
(cons : ∀ (a : α) (s : Multiset α), p s → p (a ::ₘ s)) : p s :=
Multiset.induction empty cons s
#align multiset.induction_on Multiset.induction_on
theorem cons_swap (a b : α) (s : Multiset α) : a ::ₘ b ::ₘ s = b ::ₘ a ::ₘ s :=
Quot.inductionOn s fun _ => Quotient.sound <| Perm.swap _ _ _
#align multiset.cons_swap Multiset.cons_swap
section Rec
variable {C : Multiset α → Sort*}
/-- Dependent recursor on multisets.
TODO: should be @[recursor 6], but then the definition of `Multiset.pi` fails with a stack
overflow in `whnf`.
-/
protected
def rec (C_0 : C 0) (C_cons : ∀ a m, C m → C (a ::ₘ m))
(C_cons_heq :
∀ a a' m b, HEq (C_cons a (a' ::ₘ m) (C_cons a' m b)) (C_cons a' (a ::ₘ m) (C_cons a m b)))
(m : Multiset α) : C m :=
Quotient.hrecOn m (@List.rec α (fun l => C ⟦l⟧) C_0 fun a l b => C_cons a ⟦l⟧ b) fun l l' h =>
h.rec_heq
(fun hl _ ↦ by congr 1; exact Quot.sound hl)
(C_cons_heq _ _ ⟦_⟧ _)
#align multiset.rec Multiset.rec
/-- Companion to `Multiset.rec` with more convenient argument order. -/
@[elab_as_elim]
protected
def recOn (m : Multiset α) (C_0 : C 0) (C_cons : ∀ a m, C m → C (a ::ₘ m))
(C_cons_heq :
∀ a a' m b, HEq (C_cons a (a' ::ₘ m) (C_cons a' m b)) (C_cons a' (a ::ₘ m) (C_cons a m b))) :
C m :=
Multiset.rec C_0 C_cons C_cons_heq m
#align multiset.rec_on Multiset.recOn
variable {C_0 : C 0} {C_cons : ∀ a m, C m → C (a ::ₘ m)}
{C_cons_heq :
∀ a a' m b, HEq (C_cons a (a' ::ₘ m) (C_cons a' m b)) (C_cons a' (a ::ₘ m) (C_cons a m b))}
@[simp]
theorem recOn_0 : @Multiset.recOn α C (0 : Multiset α) C_0 C_cons C_cons_heq = C_0 :=
rfl
#align multiset.rec_on_0 Multiset.recOn_0
@[simp]
theorem recOn_cons (a : α) (m : Multiset α) :
(a ::ₘ m).recOn C_0 C_cons C_cons_heq = C_cons a m (m.recOn C_0 C_cons C_cons_heq) :=
Quotient.inductionOn m fun _ => rfl
#align multiset.rec_on_cons Multiset.recOn_cons
end Rec
section Mem
/-- `a ∈ s` means that `a` has nonzero multiplicity in `s`. -/
def Mem (a : α) (s : Multiset α) : Prop :=
Quot.liftOn s (fun l => a ∈ l) fun l₁ l₂ (e : l₁ ~ l₂) => propext <| e.mem_iff
#align multiset.mem Multiset.Mem
instance : Membership α (Multiset α) :=
⟨Mem⟩
@[simp]
theorem mem_coe {a : α} {l : List α} : a ∈ (l : Multiset α) ↔ a ∈ l :=
Iff.rfl
#align multiset.mem_coe Multiset.mem_coe
instance decidableMem [DecidableEq α] (a : α) (s : Multiset α) : Decidable (a ∈ s) :=
Quot.recOnSubsingleton' s fun l ↦ inferInstanceAs (Decidable (a ∈ l))
#align multiset.decidable_mem Multiset.decidableMem
@[simp]
theorem mem_cons {a b : α} {s : Multiset α} : a ∈ b ::ₘ s ↔ a = b ∨ a ∈ s :=
Quot.inductionOn s fun _ => List.mem_cons
#align multiset.mem_cons Multiset.mem_cons
theorem mem_cons_of_mem {a b : α} {s : Multiset α} (h : a ∈ s) : a ∈ b ::ₘ s :=
mem_cons.2 <| Or.inr h
#align multiset.mem_cons_of_mem Multiset.mem_cons_of_mem
-- @[simp] -- Porting note (#10618): simp can prove this
theorem mem_cons_self (a : α) (s : Multiset α) : a ∈ a ::ₘ s :=
mem_cons.2 (Or.inl rfl)
#align multiset.mem_cons_self Multiset.mem_cons_self
theorem forall_mem_cons {p : α → Prop} {a : α} {s : Multiset α} :
(∀ x ∈ a ::ₘ s, p x) ↔ p a ∧ ∀ x ∈ s, p x :=
Quotient.inductionOn' s fun _ => List.forall_mem_cons
#align multiset.forall_mem_cons Multiset.forall_mem_cons
theorem exists_cons_of_mem {s : Multiset α} {a : α} : a ∈ s → ∃ t, s = a ::ₘ t :=
Quot.inductionOn s fun l (h : a ∈ l) =>
let ⟨l₁, l₂, e⟩ := append_of_mem h
e.symm ▸ ⟨(l₁ ++ l₂ : List α), Quot.sound perm_middle⟩
#align multiset.exists_cons_of_mem Multiset.exists_cons_of_mem
@[simp]
theorem not_mem_zero (a : α) : a ∉ (0 : Multiset α) :=
List.not_mem_nil _
#align multiset.not_mem_zero Multiset.not_mem_zero
theorem eq_zero_of_forall_not_mem {s : Multiset α} : (∀ x, x ∉ s) → s = 0 :=
Quot.inductionOn s fun l H => by rw [eq_nil_iff_forall_not_mem.mpr H]; rfl
#align multiset.eq_zero_of_forall_not_mem Multiset.eq_zero_of_forall_not_mem
theorem eq_zero_iff_forall_not_mem {s : Multiset α} : s = 0 ↔ ∀ a, a ∉ s :=
⟨fun h => h.symm ▸ fun _ => not_mem_zero _, eq_zero_of_forall_not_mem⟩
#align multiset.eq_zero_iff_forall_not_mem Multiset.eq_zero_iff_forall_not_mem
theorem exists_mem_of_ne_zero {s : Multiset α} : s ≠ 0 → ∃ a : α, a ∈ s :=
Quot.inductionOn s fun l hl =>
match l, hl with
| [], h => False.elim <| h rfl
| a :: l, _ => ⟨a, by simp⟩
#align multiset.exists_mem_of_ne_zero Multiset.exists_mem_of_ne_zero
theorem empty_or_exists_mem (s : Multiset α) : s = 0 ∨ ∃ a, a ∈ s :=
or_iff_not_imp_left.mpr Multiset.exists_mem_of_ne_zero
#align multiset.empty_or_exists_mem Multiset.empty_or_exists_mem
@[simp]
theorem zero_ne_cons {a : α} {m : Multiset α} : 0 ≠ a ::ₘ m := fun h =>
have : a ∈ (0 : Multiset α) := h.symm ▸ mem_cons_self _ _
not_mem_zero _ this
#align multiset.zero_ne_cons Multiset.zero_ne_cons
@[simp]
theorem cons_ne_zero {a : α} {m : Multiset α} : a ::ₘ m ≠ 0 :=
zero_ne_cons.symm
#align multiset.cons_ne_zero Multiset.cons_ne_zero
theorem cons_eq_cons {a b : α} {as bs : Multiset α} :
a ::ₘ as = b ::ₘ bs ↔ a = b ∧ as = bs ∨ a ≠ b ∧ ∃ cs, as = b ::ₘ cs ∧ bs = a ::ₘ cs := by
haveI : DecidableEq α := Classical.decEq α
constructor
· intro eq
by_cases h : a = b
· subst h
simp_all
· have : a ∈ b ::ₘ bs := eq ▸ mem_cons_self _ _
have : a ∈ bs := by simpa [h]
rcases exists_cons_of_mem this with ⟨cs, hcs⟩
simp only [h, hcs, false_and, ne_eq, not_false_eq_true, cons_inj_right, exists_eq_right',
true_and, false_or]
have : a ::ₘ as = b ::ₘ a ::ₘ cs := by simp [eq, hcs]
have : a ::ₘ as = a ::ₘ b ::ₘ cs := by rwa [cons_swap]
simpa using this
· intro h
rcases h with (⟨eq₁, eq₂⟩ | ⟨_, cs, eq₁, eq₂⟩)
· simp [*]
· simp [*, cons_swap a b]
#align multiset.cons_eq_cons Multiset.cons_eq_cons
end Mem
/-! ### Singleton -/
instance : Singleton α (Multiset α) :=
⟨fun a => a ::ₘ 0⟩
instance : LawfulSingleton α (Multiset α) :=
⟨fun _ => rfl⟩
@[simp]
theorem cons_zero (a : α) : a ::ₘ 0 = {a} :=
rfl
#align multiset.cons_zero Multiset.cons_zero
@[simp, norm_cast]
theorem coe_singleton (a : α) : ([a] : Multiset α) = {a} :=
rfl
#align multiset.coe_singleton Multiset.coe_singleton
@[simp]
theorem mem_singleton {a b : α} : b ∈ ({a} : Multiset α) ↔ b = a := by
simp only [← cons_zero, mem_cons, iff_self_iff, or_false_iff, not_mem_zero]
#align multiset.mem_singleton Multiset.mem_singleton
theorem mem_singleton_self (a : α) : a ∈ ({a} : Multiset α) := by
rw [← cons_zero]
exact mem_cons_self _ _
#align multiset.mem_singleton_self Multiset.mem_singleton_self
@[simp]
theorem singleton_inj {a b : α} : ({a} : Multiset α) = {b} ↔ a = b := by
simp_rw [← cons_zero]
exact cons_inj_left _
#align multiset.singleton_inj Multiset.singleton_inj
@[simp, norm_cast]
theorem coe_eq_singleton {l : List α} {a : α} : (l : Multiset α) = {a} ↔ l = [a] := by
rw [← coe_singleton, coe_eq_coe, List.perm_singleton]
#align multiset.coe_eq_singleton Multiset.coe_eq_singleton
@[simp]
theorem singleton_eq_cons_iff {a b : α} (m : Multiset α) : {a} = b ::ₘ m ↔ a = b ∧ m = 0 := by
rw [← cons_zero, cons_eq_cons]
simp [eq_comm]
#align multiset.singleton_eq_cons_iff Multiset.singleton_eq_cons_iff
theorem pair_comm (x y : α) : ({x, y} : Multiset α) = {y, x} :=
cons_swap x y 0
#align multiset.pair_comm Multiset.pair_comm
/-! ### `Multiset.Subset` -/
section Subset
variable {s : Multiset α} {a : α}
/-- `s ⊆ t` is the lift of the list subset relation. It means that any
element with nonzero multiplicity in `s` has nonzero multiplicity in `t`,
but it does not imply that the multiplicity of `a` in `s` is less or equal than in `t`;
see `s ≤ t` for this relation. -/
protected def Subset (s t : Multiset α) : Prop :=
∀ ⦃a : α⦄, a ∈ s → a ∈ t
#align multiset.subset Multiset.Subset
instance : HasSubset (Multiset α) :=
⟨Multiset.Subset⟩
instance : HasSSubset (Multiset α) :=
⟨fun s t => s ⊆ t ∧ ¬t ⊆ s⟩
instance instIsNonstrictStrictOrder : IsNonstrictStrictOrder (Multiset α) (· ⊆ ·) (· ⊂ ·) where
right_iff_left_not_left _ _ := Iff.rfl
@[simp]
theorem coe_subset {l₁ l₂ : List α} : (l₁ : Multiset α) ⊆ l₂ ↔ l₁ ⊆ l₂ :=
Iff.rfl
#align multiset.coe_subset Multiset.coe_subset
@[simp]
theorem Subset.refl (s : Multiset α) : s ⊆ s := fun _ h => h
#align multiset.subset.refl Multiset.Subset.refl
theorem Subset.trans {s t u : Multiset α} : s ⊆ t → t ⊆ u → s ⊆ u := fun h₁ h₂ _ m => h₂ (h₁ m)
#align multiset.subset.trans Multiset.Subset.trans
theorem subset_iff {s t : Multiset α} : s ⊆ t ↔ ∀ ⦃x⦄, x ∈ s → x ∈ t :=
Iff.rfl
#align multiset.subset_iff Multiset.subset_iff
theorem mem_of_subset {s t : Multiset α} {a : α} (h : s ⊆ t) : a ∈ s → a ∈ t :=
@h _
#align multiset.mem_of_subset Multiset.mem_of_subset
@[simp]
theorem zero_subset (s : Multiset α) : 0 ⊆ s := fun a => (not_mem_nil a).elim
#align multiset.zero_subset Multiset.zero_subset
theorem subset_cons (s : Multiset α) (a : α) : s ⊆ a ::ₘ s := fun _ => mem_cons_of_mem
#align multiset.subset_cons Multiset.subset_cons
theorem ssubset_cons {s : Multiset α} {a : α} (ha : a ∉ s) : s ⊂ a ::ₘ s :=
⟨subset_cons _ _, fun h => ha <| h <| mem_cons_self _ _⟩
#align multiset.ssubset_cons Multiset.ssubset_cons
@[simp]
theorem cons_subset {a : α} {s t : Multiset α} : a ::ₘ s ⊆ t ↔ a ∈ t ∧ s ⊆ t := by
simp [subset_iff, or_imp, forall_and]
#align multiset.cons_subset Multiset.cons_subset
theorem cons_subset_cons {a : α} {s t : Multiset α} : s ⊆ t → a ::ₘ s ⊆ a ::ₘ t :=
Quotient.inductionOn₂ s t fun _ _ => List.cons_subset_cons _
#align multiset.cons_subset_cons Multiset.cons_subset_cons
theorem eq_zero_of_subset_zero {s : Multiset α} (h : s ⊆ 0) : s = 0 :=
eq_zero_of_forall_not_mem fun _ hx ↦ not_mem_zero _ (h hx)
#align multiset.eq_zero_of_subset_zero Multiset.eq_zero_of_subset_zero
@[simp] lemma subset_zero : s ⊆ 0 ↔ s = 0 :=
⟨eq_zero_of_subset_zero, fun xeq => xeq.symm ▸ Subset.refl 0⟩
#align multiset.subset_zero Multiset.subset_zero
@[simp] lemma zero_ssubset : 0 ⊂ s ↔ s ≠ 0 := by simp [ssubset_iff_subset_not_subset]
@[simp] lemma singleton_subset : {a} ⊆ s ↔ a ∈ s := by simp [subset_iff]
theorem induction_on' {p : Multiset α → Prop} (S : Multiset α) (h₁ : p 0)
(h₂ : ∀ {a s}, a ∈ S → s ⊆ S → p s → p (insert a s)) : p S :=
@Multiset.induction_on α (fun T => T ⊆ S → p T) S (fun _ => h₁)
(fun _ _ hps hs =>
let ⟨hS, sS⟩ := cons_subset.1 hs
h₂ hS sS (hps sS))
(Subset.refl S)
#align multiset.induction_on' Multiset.induction_on'
end Subset
/-! ### `Multiset.toList` -/
section ToList
/-- Produces a list of the elements in the multiset using choice. -/
noncomputable def toList (s : Multiset α) :=
s.out'
#align multiset.to_list Multiset.toList
@[simp, norm_cast]
theorem coe_toList (s : Multiset α) : (s.toList : Multiset α) = s :=
s.out_eq'
#align multiset.coe_to_list Multiset.coe_toList
@[simp]
theorem toList_eq_nil {s : Multiset α} : s.toList = [] ↔ s = 0 := by
rw [← coe_eq_zero, coe_toList]
#align multiset.to_list_eq_nil Multiset.toList_eq_nil
@[simp]
theorem empty_toList {s : Multiset α} : s.toList.isEmpty ↔ s = 0 :=
isEmpty_iff_eq_nil.trans toList_eq_nil
#align multiset.empty_to_list Multiset.empty_toList
@[simp]
theorem toList_zero : (Multiset.toList 0 : List α) = [] :=
toList_eq_nil.mpr rfl
#align multiset.to_list_zero Multiset.toList_zero
@[simp]
theorem mem_toList {a : α} {s : Multiset α} : a ∈ s.toList ↔ a ∈ s := by
rw [← mem_coe, coe_toList]
#align multiset.mem_to_list Multiset.mem_toList
@[simp]
theorem toList_eq_singleton_iff {a : α} {m : Multiset α} : m.toList = [a] ↔ m = {a} := by
rw [← perm_singleton, ← coe_eq_coe, coe_toList, coe_singleton]
#align multiset.to_list_eq_singleton_iff Multiset.toList_eq_singleton_iff
@[simp]
theorem toList_singleton (a : α) : ({a} : Multiset α).toList = [a] :=
Multiset.toList_eq_singleton_iff.2 rfl
#align multiset.to_list_singleton Multiset.toList_singleton
end ToList
/-! ### Partial order on `Multiset`s -/
/-- `s ≤ t` means that `s` is a sublist of `t` (up to permutation).
Equivalently, `s ≤ t` means that `count a s ≤ count a t` for all `a`. -/
protected def Le (s t : Multiset α) : Prop :=
(Quotient.liftOn₂ s t (· <+~ ·)) fun _ _ _ _ p₁ p₂ =>
propext (p₂.subperm_left.trans p₁.subperm_right)
#align multiset.le Multiset.Le
instance : PartialOrder (Multiset α) where
le := Multiset.Le
le_refl := by rintro ⟨l⟩; exact Subperm.refl _
le_trans := by rintro ⟨l₁⟩ ⟨l₂⟩ ⟨l₃⟩; exact @Subperm.trans _ _ _ _
le_antisymm := by rintro ⟨l₁⟩ ⟨l₂⟩ h₁ h₂; exact Quot.sound (Subperm.antisymm h₁ h₂)
instance decidableLE [DecidableEq α] : DecidableRel ((· ≤ ·) : Multiset α → Multiset α → Prop) :=
fun s t => Quotient.recOnSubsingleton₂ s t List.decidableSubperm
#align multiset.decidable_le Multiset.decidableLE
section
variable {s t : Multiset α} {a : α}
theorem subset_of_le : s ≤ t → s ⊆ t :=
Quotient.inductionOn₂ s t fun _ _ => Subperm.subset
#align multiset.subset_of_le Multiset.subset_of_le
alias Le.subset := subset_of_le
#align multiset.le.subset Multiset.Le.subset
theorem mem_of_le (h : s ≤ t) : a ∈ s → a ∈ t :=
mem_of_subset (subset_of_le h)
#align multiset.mem_of_le Multiset.mem_of_le
theorem not_mem_mono (h : s ⊆ t) : a ∉ t → a ∉ s :=
mt <| @h _
#align multiset.not_mem_mono Multiset.not_mem_mono
@[simp]
theorem coe_le {l₁ l₂ : List α} : (l₁ : Multiset α) ≤ l₂ ↔ l₁ <+~ l₂ :=
Iff.rfl
#align multiset.coe_le Multiset.coe_le
@[elab_as_elim]
theorem leInductionOn {C : Multiset α → Multiset α → Prop} {s t : Multiset α} (h : s ≤ t)
(H : ∀ {l₁ l₂ : List α}, l₁ <+ l₂ → C l₁ l₂) : C s t :=
Quotient.inductionOn₂ s t (fun l₁ _ ⟨l, p, s⟩ => (show ⟦l⟧ = ⟦l₁⟧ from Quot.sound p) ▸ H s) h
#align multiset.le_induction_on Multiset.leInductionOn
theorem zero_le (s : Multiset α) : 0 ≤ s :=
Quot.inductionOn s fun l => (nil_sublist l).subperm
#align multiset.zero_le Multiset.zero_le
instance : OrderBot (Multiset α) where
bot := 0
bot_le := zero_le
/-- This is a `rfl` and `simp` version of `bot_eq_zero`. -/
@[simp]
theorem bot_eq_zero : (⊥ : Multiset α) = 0 :=
rfl
#align multiset.bot_eq_zero Multiset.bot_eq_zero
theorem le_zero : s ≤ 0 ↔ s = 0 :=
le_bot_iff
#align multiset.le_zero Multiset.le_zero
theorem lt_cons_self (s : Multiset α) (a : α) : s < a ::ₘ s :=
Quot.inductionOn s fun l =>
suffices l <+~ a :: l ∧ ¬l ~ a :: l by simpa [lt_iff_le_and_ne]
⟨(sublist_cons _ _).subperm, fun p => _root_.ne_of_lt (lt_succ_self (length l)) p.length_eq⟩
#align multiset.lt_cons_self Multiset.lt_cons_self
theorem le_cons_self (s : Multiset α) (a : α) : s ≤ a ::ₘ s :=
le_of_lt <| lt_cons_self _ _
#align multiset.le_cons_self Multiset.le_cons_self
theorem cons_le_cons_iff (a : α) : a ::ₘ s ≤ a ::ₘ t ↔ s ≤ t :=
Quotient.inductionOn₂ s t fun _ _ => subperm_cons a
#align multiset.cons_le_cons_iff Multiset.cons_le_cons_iff
theorem cons_le_cons (a : α) : s ≤ t → a ::ₘ s ≤ a ::ₘ t :=
(cons_le_cons_iff a).2
#align multiset.cons_le_cons Multiset.cons_le_cons
@[simp] lemma cons_lt_cons_iff : a ::ₘ s < a ::ₘ t ↔ s < t :=
lt_iff_lt_of_le_iff_le' (cons_le_cons_iff _) (cons_le_cons_iff _)
lemma cons_lt_cons (a : α) (h : s < t) : a ::ₘ s < a ::ₘ t := cons_lt_cons_iff.2 h
theorem le_cons_of_not_mem (m : a ∉ s) : s ≤ a ::ₘ t ↔ s ≤ t := by
refine ⟨?_, fun h => le_trans h <| le_cons_self _ _⟩
suffices ∀ {t'}, s ≤ t' → a ∈ t' → a ::ₘ s ≤ t' by
exact fun h => (cons_le_cons_iff a).1 (this h (mem_cons_self _ _))
introv h
revert m
refine leInductionOn h ?_
introv s m₁ m₂
rcases append_of_mem m₂ with ⟨r₁, r₂, rfl⟩
exact
perm_middle.subperm_left.2
((subperm_cons _).2 <| ((sublist_or_mem_of_sublist s).resolve_right m₁).subperm)
#align multiset.le_cons_of_not_mem Multiset.le_cons_of_not_mem
@[simp]
theorem singleton_ne_zero (a : α) : ({a} : Multiset α) ≠ 0 :=
ne_of_gt (lt_cons_self _ _)
#align multiset.singleton_ne_zero Multiset.singleton_ne_zero
@[simp]
theorem singleton_le {a : α} {s : Multiset α} : {a} ≤ s ↔ a ∈ s :=
⟨fun h => mem_of_le h (mem_singleton_self _), fun h =>
let ⟨_t, e⟩ := exists_cons_of_mem h
e.symm ▸ cons_le_cons _ (zero_le _)⟩
#align multiset.singleton_le Multiset.singleton_le
@[simp] lemma le_singleton : s ≤ {a} ↔ s = 0 ∨ s = {a} :=
Quot.induction_on s fun l ↦ by simp only [cons_zero, ← coe_singleton, quot_mk_to_coe'', coe_le,
coe_eq_zero, coe_eq_coe, perm_singleton, subperm_singleton_iff]
@[simp] lemma lt_singleton : s < {a} ↔ s = 0 := by
simp only [lt_iff_le_and_ne, le_singleton, or_and_right, Ne, and_not_self, or_false,
and_iff_left_iff_imp]
rintro rfl
exact (singleton_ne_zero _).symm
@[simp] lemma ssubset_singleton_iff : s ⊂ {a} ↔ s = 0 := by
refine ⟨fun hs ↦ eq_zero_of_subset_zero fun b hb ↦ (hs.2 ?_).elim, ?_⟩
· obtain rfl := mem_singleton.1 (hs.1 hb)
rwa [singleton_subset]
· rintro rfl
simp
end
/-! ### Additive monoid -/
/-- The sum of two multisets is the lift of the list append operation.
This adds the multiplicities of each element,
i.e. `count a (s + t) = count a s + count a t`. -/
protected def add (s₁ s₂ : Multiset α) : Multiset α :=
(Quotient.liftOn₂ s₁ s₂ fun l₁ l₂ => ((l₁ ++ l₂ : List α) : Multiset α)) fun _ _ _ _ p₁ p₂ =>
Quot.sound <| p₁.append p₂
#align multiset.add Multiset.add
instance : Add (Multiset α) :=
⟨Multiset.add⟩
@[simp]
theorem coe_add (s t : List α) : (s + t : Multiset α) = (s ++ t : List α) :=
rfl
#align multiset.coe_add Multiset.coe_add
@[simp]
theorem singleton_add (a : α) (s : Multiset α) : {a} + s = a ::ₘ s :=
rfl
#align multiset.singleton_add Multiset.singleton_add
private theorem add_le_add_iff_left' {s t u : Multiset α} : s + t ≤ s + u ↔ t ≤ u :=
Quotient.inductionOn₃ s t u fun _ _ _ => subperm_append_left _
instance : CovariantClass (Multiset α) (Multiset α) (· + ·) (· ≤ ·) :=
⟨fun _s _t _u => add_le_add_iff_left'.2⟩
instance : ContravariantClass (Multiset α) (Multiset α) (· + ·) (· ≤ ·) :=
⟨fun _s _t _u => add_le_add_iff_left'.1⟩
instance : OrderedCancelAddCommMonoid (Multiset α) where
zero := 0
add := (· + ·)
add_comm := fun s t => Quotient.inductionOn₂ s t fun l₁ l₂ => Quot.sound perm_append_comm
add_assoc := fun s₁ s₂ s₃ =>
Quotient.inductionOn₃ s₁ s₂ s₃ fun l₁ l₂ l₃ => congr_arg _ <| append_assoc l₁ l₂ l₃
zero_add := fun s => Quot.inductionOn s fun l => rfl
add_zero := fun s => Quotient.inductionOn s fun l => congr_arg _ <| append_nil l
add_le_add_left := fun s₁ s₂ => add_le_add_left
le_of_add_le_add_left := fun s₁ s₂ s₃ => le_of_add_le_add_left
nsmul := nsmulRec
theorem le_add_right (s t : Multiset α) : s ≤ s + t := by simpa using add_le_add_left (zero_le t) s
#align multiset.le_add_right Multiset.le_add_right
theorem le_add_left (s t : Multiset α) : s ≤ t + s := by simpa using add_le_add_right (zero_le t) s
#align multiset.le_add_left Multiset.le_add_left
theorem le_iff_exists_add {s t : Multiset α} : s ≤ t ↔ ∃ u, t = s + u :=
⟨fun h =>
leInductionOn h fun s =>
let ⟨l, p⟩ := s.exists_perm_append
⟨l, Quot.sound p⟩,
fun ⟨_u, e⟩ => e.symm ▸ le_add_right _ _⟩
#align multiset.le_iff_exists_add Multiset.le_iff_exists_add
instance : CanonicallyOrderedAddCommMonoid (Multiset α) where
__ := inferInstanceAs (OrderBot (Multiset α))
le_self_add := le_add_right
exists_add_of_le h := leInductionOn h fun s =>
let ⟨l, p⟩ := s.exists_perm_append
⟨l, Quot.sound p⟩
@[simp]
theorem cons_add (a : α) (s t : Multiset α) : a ::ₘ s + t = a ::ₘ (s + t) := by
rw [← singleton_add, ← singleton_add, add_assoc]
#align multiset.cons_add Multiset.cons_add
@[simp]
theorem add_cons (a : α) (s t : Multiset α) : s + a ::ₘ t = a ::ₘ (s + t) := by
rw [add_comm, cons_add, add_comm]
#align multiset.add_cons Multiset.add_cons
@[simp]
theorem mem_add {a : α} {s t : Multiset α} : a ∈ s + t ↔ a ∈ s ∨ a ∈ t :=
Quotient.inductionOn₂ s t fun _l₁ _l₂ => mem_append
#align multiset.mem_add Multiset.mem_add
theorem mem_of_mem_nsmul {a : α} {s : Multiset α} {n : ℕ} (h : a ∈ n • s) : a ∈ s := by
induction' n with n ih
· rw [zero_nsmul] at h
exact absurd h (not_mem_zero _)
· rw [succ_nsmul, mem_add] at h
exact h.elim ih id
#align multiset.mem_of_mem_nsmul Multiset.mem_of_mem_nsmul
@[simp]
theorem mem_nsmul {a : α} {s : Multiset α} {n : ℕ} (h0 : n ≠ 0) : a ∈ n • s ↔ a ∈ s := by
refine ⟨mem_of_mem_nsmul, fun h => ?_⟩
obtain ⟨n, rfl⟩ := exists_eq_succ_of_ne_zero h0
rw [succ_nsmul, mem_add]
exact Or.inr h
#align multiset.mem_nsmul Multiset.mem_nsmul
theorem nsmul_cons {s : Multiset α} (n : ℕ) (a : α) :
n • (a ::ₘ s) = n • ({a} : Multiset α) + n • s := by
rw [← singleton_add, nsmul_add]
#align multiset.nsmul_cons Multiset.nsmul_cons
/-! ### Cardinality -/
/-- The cardinality of a multiset is the sum of the multiplicities
of all its elements, or simply the length of the underlying list. -/
def card : Multiset α →+ ℕ where
toFun s := (Quot.liftOn s length) fun _l₁ _l₂ => Perm.length_eq
map_zero' := rfl
map_add' s t := Quotient.inductionOn₂ s t length_append
#align multiset.card Multiset.card
@[simp]
theorem coe_card (l : List α) : card (l : Multiset α) = length l :=
rfl
#align multiset.coe_card Multiset.coe_card
@[simp]
theorem length_toList (s : Multiset α) : s.toList.length = card s := by
rw [← coe_card, coe_toList]
#align multiset.length_to_list Multiset.length_toList
@[simp, nolint simpNF] -- Porting note (#10675): `dsimp` can not prove this, yet linter complains
theorem card_zero : @card α 0 = 0 :=
rfl
#align multiset.card_zero Multiset.card_zero
theorem card_add (s t : Multiset α) : card (s + t) = card s + card t :=
card.map_add s t
#align multiset.card_add Multiset.card_add
theorem card_nsmul (s : Multiset α) (n : ℕ) : card (n • s) = n * card s := by
rw [card.map_nsmul s n, Nat.nsmul_eq_mul]
#align multiset.card_nsmul Multiset.card_nsmul
@[simp]
theorem card_cons (a : α) (s : Multiset α) : card (a ::ₘ s) = card s + 1 :=
Quot.inductionOn s fun _l => rfl
#align multiset.card_cons Multiset.card_cons
@[simp]
theorem card_singleton (a : α) : card ({a} : Multiset α) = 1 := by
simp only [← cons_zero, card_zero, eq_self_iff_true, zero_add, card_cons]
#align multiset.card_singleton Multiset.card_singleton
theorem card_pair (a b : α) : card {a, b} = 2 := by
rw [insert_eq_cons, card_cons, card_singleton]
#align multiset.card_pair Multiset.card_pair
theorem card_eq_one {s : Multiset α} : card s = 1 ↔ ∃ a, s = {a} :=
⟨Quot.inductionOn s fun _l h => (List.length_eq_one.1 h).imp fun _a => congr_arg _,
fun ⟨_a, e⟩ => e.symm ▸ rfl⟩
#align multiset.card_eq_one Multiset.card_eq_one
theorem card_le_card {s t : Multiset α} (h : s ≤ t) : card s ≤ card t :=
leInductionOn h Sublist.length_le
#align multiset.card_le_of_le Multiset.card_le_card
@[mono]
theorem card_mono : Monotone (@card α) := fun _a _b => card_le_card
#align multiset.card_mono Multiset.card_mono
theorem eq_of_le_of_card_le {s t : Multiset α} (h : s ≤ t) : card t ≤ card s → s = t :=
leInductionOn h fun s h₂ => congr_arg _ <| s.eq_of_length_le h₂
#align multiset.eq_of_le_of_card_le Multiset.eq_of_le_of_card_le
theorem card_lt_card {s t : Multiset α} (h : s < t) : card s < card t :=
lt_of_not_ge fun h₂ => _root_.ne_of_lt h <| eq_of_le_of_card_le (le_of_lt h) h₂
#align multiset.card_lt_card Multiset.card_lt_card
lemma card_strictMono : StrictMono (card : Multiset α → ℕ) := fun _ _ ↦ card_lt_card
theorem lt_iff_cons_le {s t : Multiset α} : s < t ↔ ∃ a, a ::ₘ s ≤ t :=
⟨Quotient.inductionOn₂ s t fun _l₁ _l₂ h =>
Subperm.exists_of_length_lt (le_of_lt h) (card_lt_card h),
fun ⟨_a, h⟩ => lt_of_lt_of_le (lt_cons_self _ _) h⟩
#align multiset.lt_iff_cons_le Multiset.lt_iff_cons_le
@[simp]
theorem card_eq_zero {s : Multiset α} : card s = 0 ↔ s = 0 :=
⟨fun h => (eq_of_le_of_card_le (zero_le _) (le_of_eq h)).symm, fun e => by simp [e]⟩
#align multiset.card_eq_zero Multiset.card_eq_zero
theorem card_pos {s : Multiset α} : 0 < card s ↔ s ≠ 0 :=
Nat.pos_iff_ne_zero.trans <| not_congr card_eq_zero
#align multiset.card_pos Multiset.card_pos
theorem card_pos_iff_exists_mem {s : Multiset α} : 0 < card s ↔ ∃ a, a ∈ s :=
Quot.inductionOn s fun _l => length_pos_iff_exists_mem
#align multiset.card_pos_iff_exists_mem Multiset.card_pos_iff_exists_mem
theorem card_eq_two {s : Multiset α} : card s = 2 ↔ ∃ x y, s = {x, y} :=
⟨Quot.inductionOn s fun _l h =>
(List.length_eq_two.mp h).imp fun _a => Exists.imp fun _b => congr_arg _,
fun ⟨_a, _b, e⟩ => e.symm ▸ rfl⟩
#align multiset.card_eq_two Multiset.card_eq_two
theorem card_eq_three {s : Multiset α} : card s = 3 ↔ ∃ x y z, s = {x, y, z} :=
⟨Quot.inductionOn s fun _l h =>
(List.length_eq_three.mp h).imp fun _a =>
Exists.imp fun _b => Exists.imp fun _c => congr_arg _,
fun ⟨_a, _b, _c, e⟩ => e.symm ▸ rfl⟩
#align multiset.card_eq_three Multiset.card_eq_three
/-! ### Induction principles -/
/-- The strong induction principle for multisets. -/
@[elab_as_elim]
def strongInductionOn {p : Multiset α → Sort*} (s : Multiset α) (ih : ∀ s, (∀ t < s, p t) → p s) :
p s :=
(ih s) fun t _h =>
strongInductionOn t ih
termination_by card s
decreasing_by exact card_lt_card _h
#align multiset.strong_induction_on Multiset.strongInductionOnₓ -- Porting note: reorderd universes
theorem strongInductionOn_eq {p : Multiset α → Sort*} (s : Multiset α) (H) :
@strongInductionOn _ p s H = H s fun t _h => @strongInductionOn _ p t H := by
rw [strongInductionOn]
#align multiset.strong_induction_eq Multiset.strongInductionOn_eq
@[elab_as_elim]
theorem case_strongInductionOn {p : Multiset α → Prop} (s : Multiset α) (h₀ : p 0)
(h₁ : ∀ a s, (∀ t ≤ s, p t) → p (a ::ₘ s)) : p s :=
Multiset.strongInductionOn s fun s =>
Multiset.induction_on s (fun _ => h₀) fun _a _s _ ih =>
(h₁ _ _) fun _t h => ih _ <| lt_of_le_of_lt h <| lt_cons_self _ _
#align multiset.case_strong_induction_on Multiset.case_strongInductionOn
/-- Suppose that, given that `p t` can be defined on all supersets of `s` of cardinality less than
`n`, one knows how to define `p s`. Then one can inductively define `p s` for all multisets `s` of
cardinality less than `n`, starting from multisets of card `n` and iterating. This
can be used either to define data, or to prove properties. -/
def strongDownwardInduction {p : Multiset α → Sort*} {n : ℕ}
(H : ∀ t₁, (∀ {t₂ : Multiset α}, card t₂ ≤ n → t₁ < t₂ → p t₂) → card t₁ ≤ n → p t₁)
(s : Multiset α) :
card s ≤ n → p s :=
H s fun {t} ht _h =>
strongDownwardInduction H t ht
termination_by n - card s
decreasing_by simp_wf; have := (card_lt_card _h); omega
-- Porting note: reorderd universes
#align multiset.strong_downward_induction Multiset.strongDownwardInductionₓ
theorem strongDownwardInduction_eq {p : Multiset α → Sort*} {n : ℕ}
(H : ∀ t₁, (∀ {t₂ : Multiset α}, card t₂ ≤ n → t₁ < t₂ → p t₂) → card t₁ ≤ n → p t₁)
(s : Multiset α) :
strongDownwardInduction H s = H s fun ht _hst => strongDownwardInduction H _ ht := by
rw [strongDownwardInduction]
#align multiset.strong_downward_induction_eq Multiset.strongDownwardInduction_eq
/-- Analogue of `strongDownwardInduction` with order of arguments swapped. -/
@[elab_as_elim]
def strongDownwardInductionOn {p : Multiset α → Sort*} {n : ℕ} :
∀ s : Multiset α,
(∀ t₁, (∀ {t₂ : Multiset α}, card t₂ ≤ n → t₁ < t₂ → p t₂) → card t₁ ≤ n → p t₁) →
card s ≤ n → p s :=
fun s H => strongDownwardInduction H s
#align multiset.strong_downward_induction_on Multiset.strongDownwardInductionOn
theorem strongDownwardInductionOn_eq {p : Multiset α → Sort*} (s : Multiset α) {n : ℕ}
(H : ∀ t₁, (∀ {t₂ : Multiset α}, card t₂ ≤ n → t₁ < t₂ → p t₂) → card t₁ ≤ n → p t₁) :
s.strongDownwardInductionOn H = H s fun {t} ht _h => t.strongDownwardInductionOn H ht := by
dsimp only [strongDownwardInductionOn]
rw [strongDownwardInduction]
#align multiset.strong_downward_induction_on_eq Multiset.strongDownwardInductionOn_eq
#align multiset.well_founded_lt wellFounded_lt
/-- Another way of expressing `strongInductionOn`: the `(<)` relation is well-founded. -/
instance instWellFoundedLT : WellFoundedLT (Multiset α) :=
⟨Subrelation.wf Multiset.card_lt_card (measure Multiset.card).2⟩
#align multiset.is_well_founded_lt Multiset.instWellFoundedLT
/-! ### `Multiset.replicate` -/
/-- `replicate n a` is the multiset containing only `a` with multiplicity `n`. -/
def replicate (n : ℕ) (a : α) : Multiset α :=
List.replicate n a
#align multiset.replicate Multiset.replicate
theorem coe_replicate (n : ℕ) (a : α) : (List.replicate n a : Multiset α) = replicate n a := rfl
#align multiset.coe_replicate Multiset.coe_replicate
@[simp] theorem replicate_zero (a : α) : replicate 0 a = 0 := rfl
#align multiset.replicate_zero Multiset.replicate_zero
@[simp] theorem replicate_succ (a : α) (n) : replicate (n + 1) a = a ::ₘ replicate n a := rfl
#align multiset.replicate_succ Multiset.replicate_succ
theorem replicate_add (m n : ℕ) (a : α) : replicate (m + n) a = replicate m a + replicate n a :=
congr_arg _ <| List.replicate_add ..
#align multiset.replicate_add Multiset.replicate_add
/-- `Multiset.replicate` as an `AddMonoidHom`. -/
@[simps]
def replicateAddMonoidHom (a : α) : ℕ →+ Multiset α where
toFun := fun n => replicate n a
map_zero' := replicate_zero a
map_add' := fun _ _ => replicate_add _ _ a
#align multiset.replicate_add_monoid_hom Multiset.replicateAddMonoidHom
#align multiset.replicate_add_monoid_hom_apply Multiset.replicateAddMonoidHom_apply
theorem replicate_one (a : α) : replicate 1 a = {a} := rfl
#align multiset.replicate_one Multiset.replicate_one
@[simp] theorem card_replicate (n) (a : α) : card (replicate n a) = n :=
length_replicate n a
#align multiset.card_replicate Multiset.card_replicate
theorem mem_replicate {a b : α} {n : ℕ} : b ∈ replicate n a ↔ n ≠ 0 ∧ b = a :=
List.mem_replicate
#align multiset.mem_replicate Multiset.mem_replicate
theorem eq_of_mem_replicate {a b : α} {n} : b ∈ replicate n a → b = a :=
List.eq_of_mem_replicate
#align multiset.eq_of_mem_replicate Multiset.eq_of_mem_replicate
theorem eq_replicate_card {a : α} {s : Multiset α} : s = replicate (card s) a ↔ ∀ b ∈ s, b = a :=
Quot.inductionOn s fun _l => coe_eq_coe.trans <| perm_replicate.trans eq_replicate_length
#align multiset.eq_replicate_card Multiset.eq_replicate_card
alias ⟨_, eq_replicate_of_mem⟩ := eq_replicate_card
#align multiset.eq_replicate_of_mem Multiset.eq_replicate_of_mem
theorem eq_replicate {a : α} {n} {s : Multiset α} :
s = replicate n a ↔ card s = n ∧ ∀ b ∈ s, b = a :=
⟨fun h => h.symm ▸ ⟨card_replicate _ _, fun _b => eq_of_mem_replicate⟩,
fun ⟨e, al⟩ => e ▸ eq_replicate_of_mem al⟩
#align multiset.eq_replicate Multiset.eq_replicate
theorem replicate_right_injective {n : ℕ} (hn : n ≠ 0) : Injective (@replicate α n) :=
fun _ _ h => (eq_replicate.1 h).2 _ <| mem_replicate.2 ⟨hn, rfl⟩
#align multiset.replicate_right_injective Multiset.replicate_right_injective
@[simp] theorem replicate_right_inj {a b : α} {n : ℕ} (h : n ≠ 0) :
replicate n a = replicate n b ↔ a = b :=
(replicate_right_injective h).eq_iff
#align multiset.replicate_right_inj Multiset.replicate_right_inj
theorem replicate_left_injective (a : α) : Injective (replicate · a) :=
-- Porting note: was `fun m n h => by rw [← (eq_replicate.1 h).1, card_replicate]`
LeftInverse.injective (card_replicate · a)
#align multiset.replicate_left_injective Multiset.replicate_left_injective
theorem replicate_subset_singleton (n : ℕ) (a : α) : replicate n a ⊆ {a} :=
List.replicate_subset_singleton n a
#align multiset.replicate_subset_singleton Multiset.replicate_subset_singleton
theorem replicate_le_coe {a : α} {n} {l : List α} : replicate n a ≤ l ↔ List.replicate n a <+ l :=
⟨fun ⟨_l', p, s⟩ => perm_replicate.1 p ▸ s, Sublist.subperm⟩
#align multiset.replicate_le_coe Multiset.replicate_le_coe
theorem nsmul_replicate {a : α} (n m : ℕ) : n • replicate m a = replicate (n * m) a :=
((replicateAddMonoidHom a).map_nsmul _ _).symm
#align multiset.nsmul_replicate Multiset.nsmul_replicate
theorem nsmul_singleton (a : α) (n) : n • ({a} : Multiset α) = replicate n a := by
rw [← replicate_one, nsmul_replicate, mul_one]
#align multiset.nsmul_singleton Multiset.nsmul_singleton
theorem replicate_le_replicate (a : α) {k n : ℕ} : replicate k a ≤ replicate n a ↔ k ≤ n :=
_root_.trans (by rw [← replicate_le_coe, coe_replicate]) (List.replicate_sublist_replicate a)
#align multiset.replicate_le_replicate Multiset.replicate_le_replicate
theorem le_replicate_iff {m : Multiset α} {a : α} {n : ℕ} :
m ≤ replicate n a ↔ ∃ k ≤ n, m = replicate k a :=
⟨fun h => ⟨card m, (card_mono h).trans_eq (card_replicate _ _),
eq_replicate_card.2 fun _ hb => eq_of_mem_replicate <| subset_of_le h hb⟩,
fun ⟨_, hkn, hm⟩ => hm.symm ▸ (replicate_le_replicate _).2 hkn⟩
#align multiset.le_replicate_iff Multiset.le_replicate_iff
theorem lt_replicate_succ {m : Multiset α} {x : α} {n : ℕ} :
m < replicate (n + 1) x ↔ m ≤ replicate n x := by
rw [lt_iff_cons_le]
constructor
· rintro ⟨x', hx'⟩
have := eq_of_mem_replicate (mem_of_le hx' (mem_cons_self _ _))
rwa [this, replicate_succ, cons_le_cons_iff] at hx'
· intro h
rw [replicate_succ]
exact ⟨x, cons_le_cons _ h⟩
#align multiset.lt_replicate_succ Multiset.lt_replicate_succ
/-! ### Erasing one copy of an element -/
section Erase
variable [DecidableEq α] {s t : Multiset α} {a b : α}
/-- `erase s a` is the multiset that subtracts 1 from the multiplicity of `a`. -/
def erase (s : Multiset α) (a : α) : Multiset α :=
Quot.liftOn s (fun l => (l.erase a : Multiset α)) fun _l₁ _l₂ p => Quot.sound (p.erase a)
#align multiset.erase Multiset.erase
@[simp]
theorem coe_erase (l : List α) (a : α) : erase (l : Multiset α) a = l.erase a :=
rfl
#align multiset.coe_erase Multiset.coe_erase
@[simp, nolint simpNF] -- Porting note (#10675): `dsimp` can not prove this, yet linter complains
theorem erase_zero (a : α) : (0 : Multiset α).erase a = 0 :=
rfl
#align multiset.erase_zero Multiset.erase_zero
@[simp]
theorem erase_cons_head (a : α) (s : Multiset α) : (a ::ₘ s).erase a = s :=
Quot.inductionOn s fun l => congr_arg _ <| List.erase_cons_head a l
#align multiset.erase_cons_head Multiset.erase_cons_head
@[simp]
theorem erase_cons_tail {a b : α} (s : Multiset α) (h : b ≠ a) :
(b ::ₘ s).erase a = b ::ₘ s.erase a :=
Quot.inductionOn s fun l => congr_arg _ <| List.erase_cons_tail l (not_beq_of_ne h)
#align multiset.erase_cons_tail Multiset.erase_cons_tail
@[simp]
theorem erase_singleton (a : α) : ({a} : Multiset α).erase a = 0 :=
erase_cons_head a 0
#align multiset.erase_singleton Multiset.erase_singleton
@[simp]
theorem erase_of_not_mem {a : α} {s : Multiset α} : a ∉ s → s.erase a = s :=
Quot.inductionOn s fun _l h => congr_arg _ <| List.erase_of_not_mem h
#align multiset.erase_of_not_mem Multiset.erase_of_not_mem
@[simp]
theorem cons_erase {s : Multiset α} {a : α} : a ∈ s → a ::ₘ s.erase a = s :=
Quot.inductionOn s fun _l h => Quot.sound (perm_cons_erase h).symm
#align multiset.cons_erase Multiset.cons_erase
theorem erase_cons_tail_of_mem (h : a ∈ s) :
(b ::ₘ s).erase a = b ::ₘ s.erase a := by
rcases eq_or_ne a b with rfl | hab
· simp [cons_erase h]
· exact s.erase_cons_tail hab.symm
theorem le_cons_erase (s : Multiset α) (a : α) : s ≤ a ::ₘ s.erase a :=
if h : a ∈ s then le_of_eq (cons_erase h).symm
else by rw [erase_of_not_mem h]; apply le_cons_self
#align multiset.le_cons_erase Multiset.le_cons_erase
theorem add_singleton_eq_iff {s t : Multiset α} {a : α} : s + {a} = t ↔ a ∈ t ∧ s = t.erase a := by
rw [add_comm, singleton_add]; constructor
· rintro rfl
exact ⟨s.mem_cons_self a, (s.erase_cons_head a).symm⟩
· rintro ⟨h, rfl⟩
exact cons_erase h
#align multiset.add_singleton_eq_iff Multiset.add_singleton_eq_iff
theorem erase_add_left_pos {a : α} {s : Multiset α} (t) : a ∈ s → (s + t).erase a = s.erase a + t :=
Quotient.inductionOn₂ s t fun _l₁ l₂ h => congr_arg _ <| erase_append_left l₂ h
#align multiset.erase_add_left_pos Multiset.erase_add_left_pos
theorem erase_add_right_pos {a : α} (s) {t : Multiset α} (h : a ∈ t) :
(s + t).erase a = s + t.erase a := by rw [add_comm, erase_add_left_pos s h, add_comm]
#align multiset.erase_add_right_pos Multiset.erase_add_right_pos
theorem erase_add_right_neg {a : α} {s : Multiset α} (t) :
a ∉ s → (s + t).erase a = s + t.erase a :=
Quotient.inductionOn₂ s t fun _l₁ l₂ h => congr_arg _ <| erase_append_right l₂ h
#align multiset.erase_add_right_neg Multiset.erase_add_right_neg
theorem erase_add_left_neg {a : α} (s) {t : Multiset α} (h : a ∉ t) :
(s + t).erase a = s.erase a + t := by rw [add_comm, erase_add_right_neg s h, add_comm]
#align multiset.erase_add_left_neg Multiset.erase_add_left_neg
theorem erase_le (a : α) (s : Multiset α) : s.erase a ≤ s :=
Quot.inductionOn s fun l => (erase_sublist a l).subperm
#align multiset.erase_le Multiset.erase_le
@[simp]
theorem erase_lt {a : α} {s : Multiset α} : s.erase a < s ↔ a ∈ s :=
⟨fun h => not_imp_comm.1 erase_of_not_mem (ne_of_lt h), fun h => by
simpa [h] using lt_cons_self (s.erase a) a⟩
#align multiset.erase_lt Multiset.erase_lt
theorem erase_subset (a : α) (s : Multiset α) : s.erase a ⊆ s :=
subset_of_le (erase_le a s)
#align multiset.erase_subset Multiset.erase_subset
theorem mem_erase_of_ne {a b : α} {s : Multiset α} (ab : a ≠ b) : a ∈ s.erase b ↔ a ∈ s :=
Quot.inductionOn s fun _l => List.mem_erase_of_ne ab
#align multiset.mem_erase_of_ne Multiset.mem_erase_of_ne
theorem mem_of_mem_erase {a b : α} {s : Multiset α} : a ∈ s.erase b → a ∈ s :=
mem_of_subset (erase_subset _ _)
#align multiset.mem_of_mem_erase Multiset.mem_of_mem_erase
theorem erase_comm (s : Multiset α) (a b : α) : (s.erase a).erase b = (s.erase b).erase a :=
Quot.inductionOn s fun l => congr_arg _ <| l.erase_comm a b
#align multiset.erase_comm Multiset.erase_comm
theorem erase_le_erase {s t : Multiset α} (a : α) (h : s ≤ t) : s.erase a ≤ t.erase a :=
leInductionOn h fun h => (h.erase _).subperm
#align multiset.erase_le_erase Multiset.erase_le_erase
theorem erase_le_iff_le_cons {s t : Multiset α} {a : α} : s.erase a ≤ t ↔ s ≤ a ::ₘ t :=
⟨fun h => le_trans (le_cons_erase _ _) (cons_le_cons _ h), fun h =>
if m : a ∈ s then by rw [← cons_erase m] at h; exact (cons_le_cons_iff _).1 h
else le_trans (erase_le _ _) ((le_cons_of_not_mem m).1 h)⟩
#align multiset.erase_le_iff_le_cons Multiset.erase_le_iff_le_cons
@[simp]
theorem card_erase_of_mem {a : α} {s : Multiset α} : a ∈ s → card (s.erase a) = pred (card s) :=
Quot.inductionOn s fun _l => length_erase_of_mem
#align multiset.card_erase_of_mem Multiset.card_erase_of_mem
@[simp]
theorem card_erase_add_one {a : α} {s : Multiset α} : a ∈ s → card (s.erase a) + 1 = card s :=
Quot.inductionOn s fun _l => length_erase_add_one
#align multiset.card_erase_add_one Multiset.card_erase_add_one
theorem card_erase_lt_of_mem {a : α} {s : Multiset α} : a ∈ s → card (s.erase a) < card s :=
fun h => card_lt_card (erase_lt.mpr h)
#align multiset.card_erase_lt_of_mem Multiset.card_erase_lt_of_mem
theorem card_erase_le {a : α} {s : Multiset α} : card (s.erase a) ≤ card s :=
card_le_card (erase_le a s)
#align multiset.card_erase_le Multiset.card_erase_le
theorem card_erase_eq_ite {a : α} {s : Multiset α} :
card (s.erase a) = if a ∈ s then pred (card s) else card s := by
by_cases h : a ∈ s
· rwa [card_erase_of_mem h, if_pos]
· rwa [erase_of_not_mem h, if_neg]
#align multiset.card_erase_eq_ite Multiset.card_erase_eq_ite
end Erase
@[simp]
theorem coe_reverse (l : List α) : (reverse l : Multiset α) = l :=
Quot.sound <| reverse_perm _
#align multiset.coe_reverse Multiset.coe_reverse
/-! ### `Multiset.map` -/
/-- `map f s` is the lift of the list `map` operation. The multiplicity
of `b` in `map f s` is the number of `a ∈ s` (counting multiplicity)
such that `f a = b`. -/
def map (f : α → β) (s : Multiset α) : Multiset β :=
Quot.liftOn s (fun l : List α => (l.map f : Multiset β)) fun _l₁ _l₂ p => Quot.sound (p.map f)
#align multiset.map Multiset.map
@[congr]
theorem map_congr {f g : α → β} {s t : Multiset α} :
s = t → (∀ x ∈ t, f x = g x) → map f s = map g t := by
rintro rfl h
induction s using Quot.inductionOn
exact congr_arg _ (List.map_congr h)
#align multiset.map_congr Multiset.map_congr
theorem map_hcongr {β' : Type v} {m : Multiset α} {f : α → β} {f' : α → β'} (h : β = β')
(hf : ∀ a ∈ m, HEq (f a) (f' a)) : HEq (map f m) (map f' m) := by
subst h; simp at hf
simp [map_congr rfl hf]
#align multiset.map_hcongr Multiset.map_hcongr
theorem forall_mem_map_iff {f : α → β} {p : β → Prop} {s : Multiset α} :
(∀ y ∈ s.map f, p y) ↔ ∀ x ∈ s, p (f x) :=
Quotient.inductionOn' s fun _L => List.forall_mem_map_iff
#align multiset.forall_mem_map_iff Multiset.forall_mem_map_iff
@[simp, norm_cast] lemma map_coe (f : α → β) (l : List α) : map f l = l.map f := rfl
#align multiset.coe_map Multiset.map_coe
@[simp]
theorem map_zero (f : α → β) : map f 0 = 0 :=
rfl
#align multiset.map_zero Multiset.map_zero
@[simp]
theorem map_cons (f : α → β) (a s) : map f (a ::ₘ s) = f a ::ₘ map f s :=
Quot.inductionOn s fun _l => rfl
#align multiset.map_cons Multiset.map_cons
theorem map_comp_cons (f : α → β) (t) : map f ∘ cons t = cons (f t) ∘ map f := by
ext
simp
#align multiset.map_comp_cons Multiset.map_comp_cons
@[simp]
theorem map_singleton (f : α → β) (a : α) : ({a} : Multiset α).map f = {f a} :=
rfl
#align multiset.map_singleton Multiset.map_singleton
@[simp]
theorem map_replicate (f : α → β) (k : ℕ) (a : α) : (replicate k a).map f = replicate k (f a) := by
simp only [← coe_replicate, map_coe, List.map_replicate]
#align multiset.map_replicate Multiset.map_replicate
@[simp]
theorem map_add (f : α → β) (s t) : map f (s + t) = map f s + map f t :=
Quotient.inductionOn₂ s t fun _l₁ _l₂ => congr_arg _ <| map_append _ _ _
#align multiset.map_add Multiset.map_add
/-- If each element of `s : Multiset α` can be lifted to `β`, then `s` can be lifted to
`Multiset β`. -/
instance canLift (c) (p) [CanLift α β c p] :
CanLift (Multiset α) (Multiset β) (map c) fun s => ∀ x ∈ s, p x where
prf := by
rintro ⟨l⟩ hl
lift l to List β using hl
exact ⟨l, map_coe _ _⟩
#align multiset.can_lift Multiset.canLift
/-- `Multiset.map` as an `AddMonoidHom`. -/
def mapAddMonoidHom (f : α → β) : Multiset α →+ Multiset β where
toFun := map f
map_zero' := map_zero _
map_add' := map_add _
#align multiset.map_add_monoid_hom Multiset.mapAddMonoidHom
@[simp]
theorem coe_mapAddMonoidHom (f : α → β) :
(mapAddMonoidHom f : Multiset α → Multiset β) = map f :=
rfl
#align multiset.coe_map_add_monoid_hom Multiset.coe_mapAddMonoidHom
theorem map_nsmul (f : α → β) (n : ℕ) (s) : map f (n • s) = n • map f s :=
(mapAddMonoidHom f).map_nsmul _ _
#align multiset.map_nsmul Multiset.map_nsmul
@[simp]
theorem mem_map {f : α → β} {b : β} {s : Multiset α} : b ∈ map f s ↔ ∃ a, a ∈ s ∧ f a = b :=
Quot.inductionOn s fun _l => List.mem_map
#align multiset.mem_map Multiset.mem_map
@[simp]
theorem card_map (f : α → β) (s) : card (map f s) = card s :=
Quot.inductionOn s fun _l => length_map _ _
#align multiset.card_map Multiset.card_map
@[simp]
theorem map_eq_zero {s : Multiset α} {f : α → β} : s.map f = 0 ↔ s = 0 := by
rw [← Multiset.card_eq_zero, Multiset.card_map, Multiset.card_eq_zero]
#align multiset.map_eq_zero Multiset.map_eq_zero
theorem mem_map_of_mem (f : α → β) {a : α} {s : Multiset α} (h : a ∈ s) : f a ∈ map f s :=
mem_map.2 ⟨_, h, rfl⟩
#align multiset.mem_map_of_mem Multiset.mem_map_of_mem
theorem map_eq_singleton {f : α → β} {s : Multiset α} {b : β} :
map f s = {b} ↔ ∃ a : α, s = {a} ∧ f a = b := by
constructor
· intro h
obtain ⟨a, ha⟩ : ∃ a, s = {a} := by rw [← card_eq_one, ← card_map, h, card_singleton]
refine ⟨a, ha, ?_⟩
rw [← mem_singleton, ← h, ha, map_singleton, mem_singleton]
· rintro ⟨a, rfl, rfl⟩
simp
#align multiset.map_eq_singleton Multiset.map_eq_singleton
theorem map_eq_cons [DecidableEq α] (f : α → β) (s : Multiset α) (t : Multiset β) (b : β) :
(∃ a ∈ s, f a = b ∧ (s.erase a).map f = t) ↔ s.map f = b ::ₘ t := by
constructor
· rintro ⟨a, ha, rfl, rfl⟩
rw [← map_cons, Multiset.cons_erase ha]
· intro h
have : b ∈ s.map f := by
rw [h]
exact mem_cons_self _ _
obtain ⟨a, h1, rfl⟩ := mem_map.mp this
obtain ⟨u, rfl⟩ := exists_cons_of_mem h1
rw [map_cons, cons_inj_right] at h
refine ⟨a, mem_cons_self _ _, rfl, ?_⟩
rw [Multiset.erase_cons_head, h]
#align multiset.map_eq_cons Multiset.map_eq_cons
-- The simpNF linter says that the LHS can be simplified via `Multiset.mem_map`.
-- However this is a higher priority lemma.
-- https://github.com/leanprover/std4/issues/207
@[simp 1100, nolint simpNF]
theorem mem_map_of_injective {f : α → β} (H : Function.Injective f) {a : α} {s : Multiset α} :
f a ∈ map f s ↔ a ∈ s :=
Quot.inductionOn s fun _l => List.mem_map_of_injective H
#align multiset.mem_map_of_injective Multiset.mem_map_of_injective
@[simp]
theorem map_map (g : β → γ) (f : α → β) (s : Multiset α) : map g (map f s) = map (g ∘ f) s :=
Quot.inductionOn s fun _l => congr_arg _ <| List.map_map _ _ _
#align multiset.map_map Multiset.map_map
theorem map_id (s : Multiset α) : map id s = s :=
Quot.inductionOn s fun _l => congr_arg _ <| List.map_id _
#align multiset.map_id Multiset.map_id
@[simp]
theorem map_id' (s : Multiset α) : map (fun x => x) s = s :=
map_id s
#align multiset.map_id' Multiset.map_id'
-- Porting note: was a `simp` lemma in mathlib3
theorem map_const (s : Multiset α) (b : β) : map (const α b) s = replicate (card s) b :=
Quot.inductionOn s fun _ => congr_arg _ <| List.map_const' _ _
#align multiset.map_const Multiset.map_const
-- Porting note: was not a `simp` lemma in mathlib3 because `Function.const` was reducible
@[simp] theorem map_const' (s : Multiset α) (b : β) : map (fun _ ↦ b) s = replicate (card s) b :=
map_const _ _
#align multiset.map_const' Multiset.map_const'
theorem eq_of_mem_map_const {b₁ b₂ : β} {l : List α} (h : b₁ ∈ map (Function.const α b₂) l) :
b₁ = b₂ :=
eq_of_mem_replicate <| by rwa [map_const] at h
#align multiset.eq_of_mem_map_const Multiset.eq_of_mem_map_const
@[simp]
theorem map_le_map {f : α → β} {s t : Multiset α} (h : s ≤ t) : map f s ≤ map f t :=
leInductionOn h fun h => (h.map f).subperm
#align multiset.map_le_map Multiset.map_le_map
@[simp]
theorem map_lt_map {f : α → β} {s t : Multiset α} (h : s < t) : s.map f < t.map f := by
refine (map_le_map h.le).lt_of_not_le fun H => h.ne <| eq_of_le_of_card_le h.le ?_
rw [← s.card_map f, ← t.card_map f]
exact card_le_card H
#align multiset.map_lt_map Multiset.map_lt_map
theorem map_mono (f : α → β) : Monotone (map f) := fun _ _ => map_le_map
#align multiset.map_mono Multiset.map_mono
theorem map_strictMono (f : α → β) : StrictMono (map f) := fun _ _ => map_lt_map
#align multiset.map_strict_mono Multiset.map_strictMono
@[simp]
theorem map_subset_map {f : α → β} {s t : Multiset α} (H : s ⊆ t) : map f s ⊆ map f t := fun _b m =>
let ⟨a, h, e⟩ := mem_map.1 m
mem_map.2 ⟨a, H h, e⟩
#align multiset.map_subset_map Multiset.map_subset_map
theorem map_erase [DecidableEq α] [DecidableEq β] (f : α → β) (hf : Function.Injective f) (x : α)
(s : Multiset α) : (s.erase x).map f = (s.map f).erase (f x) := by
induction' s using Multiset.induction_on with y s ih
· simp
by_cases hxy : y = x
· cases hxy
simp
· rw [s.erase_cons_tail hxy, map_cons, map_cons, (s.map f).erase_cons_tail (hf.ne hxy), ih]
#align multiset.map_erase Multiset.map_erase
theorem map_erase_of_mem [DecidableEq α] [DecidableEq β] (f : α → β)
(s : Multiset α) {x : α} (h : x ∈ s) : (s.erase x).map f = (s.map f).erase (f x) := by
induction' s using Multiset.induction_on with y s ih
· simp
rcases eq_or_ne y x with rfl | hxy
· simp
replace h : x ∈ s := by simpa [hxy.symm] using h
rw [s.erase_cons_tail hxy, map_cons, map_cons, ih h, erase_cons_tail_of_mem (mem_map_of_mem f h)]
theorem map_surjective_of_surjective {f : α → β} (hf : Function.Surjective f) :
Function.Surjective (map f) := by
intro s
induction' s using Multiset.induction_on with x s ih
· exact ⟨0, map_zero _⟩
· obtain ⟨y, rfl⟩ := hf x
obtain ⟨t, rfl⟩ := ih
exact ⟨y ::ₘ t, map_cons _ _ _⟩
#align multiset.map_surjective_of_surjective Multiset.map_surjective_of_surjective
/-! ### `Multiset.fold` -/
/-- `foldl f H b s` is the lift of the list operation `foldl f b l`,
which folds `f` over the multiset. It is well defined when `f` is right-commutative,
that is, `f (f b a₁) a₂ = f (f b a₂) a₁`. -/
def foldl (f : β → α → β) (H : RightCommutative f) (b : β) (s : Multiset α) : β :=
Quot.liftOn s (fun l => List.foldl f b l) fun _l₁ _l₂ p => p.foldl_eq H b
#align multiset.foldl Multiset.foldl
@[simp]
theorem foldl_zero (f : β → α → β) (H b) : foldl f H b 0 = b :=
rfl
#align multiset.foldl_zero Multiset.foldl_zero
@[simp]
theorem foldl_cons (f : β → α → β) (H b a s) : foldl f H b (a ::ₘ s) = foldl f H (f b a) s :=
Quot.inductionOn s fun _l => rfl
#align multiset.foldl_cons Multiset.foldl_cons
@[simp]
theorem foldl_add (f : β → α → β) (H b s t) : foldl f H b (s + t) = foldl f H (foldl f H b s) t :=
Quotient.inductionOn₂ s t fun _l₁ _l₂ => foldl_append _ _ _ _
#align multiset.foldl_add Multiset.foldl_add
/-- `foldr f H b s` is the lift of the list operation `foldr f b l`,
which folds `f` over the multiset. It is well defined when `f` is left-commutative,
that is, `f a₁ (f a₂ b) = f a₂ (f a₁ b)`. -/
def foldr (f : α → β → β) (H : LeftCommutative f) (b : β) (s : Multiset α) : β :=
Quot.liftOn s (fun l => List.foldr f b l) fun _l₁ _l₂ p => p.foldr_eq H b
#align multiset.foldr Multiset.foldr
@[simp]
theorem foldr_zero (f : α → β → β) (H b) : foldr f H b 0 = b :=
rfl
#align multiset.foldr_zero Multiset.foldr_zero
@[simp]
theorem foldr_cons (f : α → β → β) (H b a s) : foldr f H b (a ::ₘ s) = f a (foldr f H b s) :=
Quot.inductionOn s fun _l => rfl
#align multiset.foldr_cons Multiset.foldr_cons
@[simp]
theorem foldr_singleton (f : α → β → β) (H b a) : foldr f H b ({a} : Multiset α) = f a b :=
rfl
#align multiset.foldr_singleton Multiset.foldr_singleton
@[simp]
theorem foldr_add (f : α → β → β) (H b s t) : foldr f H b (s + t) = foldr f H (foldr f H b t) s :=
Quotient.inductionOn₂ s t fun _l₁ _l₂ => foldr_append _ _ _ _
#align multiset.foldr_add Multiset.foldr_add
@[simp]
theorem coe_foldr (f : α → β → β) (H : LeftCommutative f) (b : β) (l : List α) :
foldr f H b l = l.foldr f b :=
rfl
#align multiset.coe_foldr Multiset.coe_foldr
@[simp]
theorem coe_foldl (f : β → α → β) (H : RightCommutative f) (b : β) (l : List α) :
foldl f H b l = l.foldl f b :=
rfl
#align multiset.coe_foldl Multiset.coe_foldl
theorem coe_foldr_swap (f : α → β → β) (H : LeftCommutative f) (b : β) (l : List α) :
foldr f H b l = l.foldl (fun x y => f y x) b :=
(congr_arg (foldr f H b) (coe_reverse l)).symm.trans <| foldr_reverse _ _ _
#align multiset.coe_foldr_swap Multiset.coe_foldr_swap
theorem foldr_swap (f : α → β → β) (H : LeftCommutative f) (b : β) (s : Multiset α) :
foldr f H b s = foldl (fun x y => f y x) (fun _x _y _z => (H _ _ _).symm) b s :=
Quot.inductionOn s fun _l => coe_foldr_swap _ _ _ _
#align multiset.foldr_swap Multiset.foldr_swap
theorem foldl_swap (f : β → α → β) (H : RightCommutative f) (b : β) (s : Multiset α) :
foldl f H b s = foldr (fun x y => f y x) (fun _x _y _z => (H _ _ _).symm) b s :=
(foldr_swap _ _ _ _).symm
#align multiset.foldl_swap Multiset.foldl_swap
theorem foldr_induction' (f : α → β → β) (H : LeftCommutative f) (x : β) (q : α → Prop)
(p : β → Prop) (s : Multiset α) (hpqf : ∀ a b, q a → p b → p (f a b)) (px : p x)
(q_s : ∀ a ∈ s, q a) : p (foldr f H x s) := by
induction s using Multiset.induction with
| empty => simpa
| cons a s ihs =>
simp only [forall_mem_cons, foldr_cons] at q_s ⊢
exact hpqf _ _ q_s.1 (ihs q_s.2)
#align multiset.foldr_induction' Multiset.foldr_induction'
theorem foldr_induction (f : α → α → α) (H : LeftCommutative f) (x : α) (p : α → Prop)
(s : Multiset α) (p_f : ∀ a b, p a → p b → p (f a b)) (px : p x) (p_s : ∀ a ∈ s, p a) :
p (foldr f H x s) :=
foldr_induction' f H x p p s p_f px p_s
#align multiset.foldr_induction Multiset.foldr_induction
theorem foldl_induction' (f : β → α → β) (H : RightCommutative f) (x : β) (q : α → Prop)
(p : β → Prop) (s : Multiset α) (hpqf : ∀ a b, q a → p b → p (f b a)) (px : p x)
(q_s : ∀ a ∈ s, q a) : p (foldl f H x s) := by
rw [foldl_swap]
exact foldr_induction' (fun x y => f y x) (fun x y z => (H _ _ _).symm) x q p s hpqf px q_s
#align multiset.foldl_induction' Multiset.foldl_induction'
theorem foldl_induction (f : α → α → α) (H : RightCommutative f) (x : α) (p : α → Prop)
(s : Multiset α) (p_f : ∀ a b, p a → p b → p (f b a)) (px : p x) (p_s : ∀ a ∈ s, p a) :
p (foldl f H x s) :=
foldl_induction' f H x p p s p_f px p_s
#align multiset.foldl_induction Multiset.foldl_induction
/-! ### Map for partial functions -/
/-- Lift of the list `pmap` operation. Map a partial function `f` over a multiset
`s` whose elements are all in the domain of `f`. -/
nonrec def pmap {p : α → Prop} (f : ∀ a, p a → β) (s : Multiset α) : (∀ a ∈ s, p a) → Multiset β :=
Quot.recOn' s (fun l H => ↑(pmap f l H)) fun l₁ l₂ (pp : l₁ ~ l₂) =>
funext fun H₂ : ∀ a ∈ l₂, p a =>
have H₁ : ∀ a ∈ l₁, p a := fun a h => H₂ a (pp.subset h)
have : ∀ {s₂ e H}, @Eq.ndrec (Multiset α) l₁ (fun s => (∀ a ∈ s, p a) → Multiset β)
(fun _ => ↑(pmap f l₁ H₁)) s₂ e H = ↑(pmap f l₁ H₁) := by
intro s₂ e _; subst e; rfl
this.trans <| Quot.sound <| pp.pmap f
#align multiset.pmap Multiset.pmap
@[simp]
theorem coe_pmap {p : α → Prop} (f : ∀ a, p a → β) (l : List α) (H : ∀ a ∈ l, p a) :
pmap f l H = l.pmap f H :=
rfl
#align multiset.coe_pmap Multiset.coe_pmap
@[simp]
theorem pmap_zero {p : α → Prop} (f : ∀ a, p a → β) (h : ∀ a ∈ (0 : Multiset α), p a) :
pmap f 0 h = 0 :=
rfl
#align multiset.pmap_zero Multiset.pmap_zero
@[simp]
theorem pmap_cons {p : α → Prop} (f : ∀ a, p a → β) (a : α) (m : Multiset α) :
∀ h : ∀ b ∈ a ::ₘ m, p b,
pmap f (a ::ₘ m) h =
f a (h a (mem_cons_self a m)) ::ₘ pmap f m fun a ha => h a <| mem_cons_of_mem ha :=
Quotient.inductionOn m fun _l _h => rfl
#align multiset.pmap_cons Multiset.pmap_cons
/-- "Attach" a proof that `a ∈ s` to each element `a` in `s` to produce
a multiset on `{x // x ∈ s}`. -/
def attach (s : Multiset α) : Multiset { x // x ∈ s } :=
pmap Subtype.mk s fun _a => id
#align multiset.attach Multiset.attach
@[simp]
theorem coe_attach (l : List α) : @Eq (Multiset { x // x ∈ l }) (@attach α l) l.attach :=
rfl
#align multiset.coe_attach Multiset.coe_attach
theorem sizeOf_lt_sizeOf_of_mem [SizeOf α] {x : α} {s : Multiset α} (hx : x ∈ s) :
SizeOf.sizeOf x < SizeOf.sizeOf s := by
induction' s using Quot.inductionOn with l a b
exact List.sizeOf_lt_sizeOf_of_mem hx
#align multiset.sizeof_lt_sizeof_of_mem Multiset.sizeOf_lt_sizeOf_of_mem
theorem pmap_eq_map (p : α → Prop) (f : α → β) (s : Multiset α) :
∀ H, @pmap _ _ p (fun a _ => f a) s H = map f s :=
Quot.inductionOn s fun l H => congr_arg _ <| List.pmap_eq_map p f l H
#align multiset.pmap_eq_map Multiset.pmap_eq_map
theorem pmap_congr {p q : α → Prop} {f : ∀ a, p a → β} {g : ∀ a, q a → β} (s : Multiset α) :
∀ {H₁ H₂}, (∀ a ∈ s, ∀ (h₁ h₂), f a h₁ = g a h₂) → pmap f s H₁ = pmap g s H₂ :=
@(Quot.inductionOn s (fun l _H₁ _H₂ h => congr_arg _ <| List.pmap_congr l h))
#align multiset.pmap_congr Multiset.pmap_congr
theorem map_pmap {p : α → Prop} (g : β → γ) (f : ∀ a, p a → β) (s) :
∀ H, map g (pmap f s H) = pmap (fun a h => g (f a h)) s H :=
Quot.inductionOn s fun l H => congr_arg _ <| List.map_pmap g f l H
#align multiset.map_pmap Multiset.map_pmap
theorem pmap_eq_map_attach {p : α → Prop} (f : ∀ a, p a → β) (s) :
∀ H, pmap f s H = s.attach.map fun x => f x.1 (H _ x.2) :=
Quot.inductionOn s fun l H => congr_arg _ <| List.pmap_eq_map_attach f l H
#align multiset.pmap_eq_map_attach Multiset.pmap_eq_map_attach
-- @[simp] -- Porting note: Left hand does not simplify
theorem attach_map_val' (s : Multiset α) (f : α → β) : (s.attach.map fun i => f i.val) = s.map f :=
Quot.inductionOn s fun l => congr_arg _ <| List.attach_map_coe' l f
#align multiset.attach_map_coe' Multiset.attach_map_val'
#align multiset.attach_map_val' Multiset.attach_map_val'
@[simp]
theorem attach_map_val (s : Multiset α) : s.attach.map Subtype.val = s :=
(attach_map_val' _ _).trans s.map_id
#align multiset.attach_map_coe Multiset.attach_map_val
#align multiset.attach_map_val Multiset.attach_map_val
@[simp]
theorem mem_attach (s : Multiset α) : ∀ x, x ∈ s.attach :=
Quot.inductionOn s fun _l => List.mem_attach _
#align multiset.mem_attach Multiset.mem_attach
@[simp]
theorem mem_pmap {p : α → Prop} {f : ∀ a, p a → β} {s H b} :
b ∈ pmap f s H ↔ ∃ (a : _) (h : a ∈ s), f a (H a h) = b :=
Quot.inductionOn s (fun _l _H => List.mem_pmap) H
#align multiset.mem_pmap Multiset.mem_pmap
@[simp]
theorem card_pmap {p : α → Prop} (f : ∀ a, p a → β) (s H) : card (pmap f s H) = card s :=
Quot.inductionOn s (fun _l _H => length_pmap) H
#align multiset.card_pmap Multiset.card_pmap
@[simp]
theorem card_attach {m : Multiset α} : card (attach m) = card m :=
card_pmap _ _ _
#align multiset.card_attach Multiset.card_attach
@[simp]
theorem attach_zero : (0 : Multiset α).attach = 0 :=
rfl
#align multiset.attach_zero Multiset.attach_zero
theorem attach_cons (a : α) (m : Multiset α) :
(a ::ₘ m).attach =
⟨a, mem_cons_self a m⟩ ::ₘ m.attach.map fun p => ⟨p.1, mem_cons_of_mem p.2⟩ :=
Quotient.inductionOn m fun l =>
congr_arg _ <|
congr_arg (List.cons _) <| by
rw [List.map_pmap]; exact List.pmap_congr _ fun _ _ _ _ => Subtype.eq rfl
#align multiset.attach_cons Multiset.attach_cons
section DecidablePiExists
variable {m : Multiset α}
/-- If `p` is a decidable predicate,
so is the predicate that all elements of a multiset satisfy `p`. -/
protected def decidableForallMultiset {p : α → Prop} [hp : ∀ a, Decidable (p a)] :
Decidable (∀ a ∈ m, p a) :=
Quotient.recOnSubsingleton m fun l => decidable_of_iff (∀ a ∈ l, p a) <| by simp
#align multiset.decidable_forall_multiset Multiset.decidableForallMultiset
instance decidableDforallMultiset {p : ∀ a ∈ m, Prop} [_hp : ∀ (a) (h : a ∈ m), Decidable (p a h)] :
Decidable (∀ (a) (h : a ∈ m), p a h) :=
@decidable_of_iff _ _
(Iff.intro (fun h a ha => h ⟨a, ha⟩ (mem_attach _ _)) fun h ⟨_a, _ha⟩ _ => h _ _)
(@Multiset.decidableForallMultiset _ m.attach (fun a => p a.1 a.2) _)
#align multiset.decidable_dforall_multiset Multiset.decidableDforallMultiset
/-- decidable equality for functions whose domain is bounded by multisets -/
instance decidableEqPiMultiset {β : α → Type*} [h : ∀ a, DecidableEq (β a)] :
DecidableEq (∀ a ∈ m, β a) := fun f g =>
decidable_of_iff (∀ (a) (h : a ∈ m), f a h = g a h) (by simp [Function.funext_iff])
#align multiset.decidable_eq_pi_multiset Multiset.decidableEqPiMultiset
/-- If `p` is a decidable predicate,
so is the existence of an element in a multiset satisfying `p`. -/
protected def decidableExistsMultiset {p : α → Prop} [DecidablePred p] : Decidable (∃ x ∈ m, p x) :=
Quotient.recOnSubsingleton m fun l => decidable_of_iff (∃ a ∈ l, p a) <| by simp
#align multiset.decidable_exists_multiset Multiset.decidableExistsMultiset
instance decidableDexistsMultiset {p : ∀ a ∈ m, Prop} [_hp : ∀ (a) (h : a ∈ m), Decidable (p a h)] :
Decidable (∃ (a : _) (h : a ∈ m), p a h) :=
@decidable_of_iff _ _
(Iff.intro (fun ⟨⟨a, ha₁⟩, _, ha₂⟩ => ⟨a, ha₁, ha₂⟩) fun ⟨a, ha₁, ha₂⟩ =>
⟨⟨a, ha₁⟩, mem_attach _ _, ha₂⟩)
(@Multiset.decidableExistsMultiset { a // a ∈ m } m.attach (fun a => p a.1 a.2) _)
#align multiset.decidable_dexists_multiset Multiset.decidableDexistsMultiset
end DecidablePiExists
/-! ### Subtraction -/
section
variable [DecidableEq α] {s t u : Multiset α} {a b : α}
/-- `s - t` is the multiset such that `count a (s - t) = count a s - count a t` for all `a`
(note that it is truncated subtraction, so it is `0` if `count a t ≥ count a s`). -/
protected def sub (s t : Multiset α) : Multiset α :=
(Quotient.liftOn₂ s t fun l₁ l₂ => (l₁.diff l₂ : Multiset α)) fun _v₁ _v₂ _w₁ _w₂ p₁ p₂ =>
Quot.sound <| p₁.diff p₂
#align multiset.sub Multiset.sub
instance : Sub (Multiset α) :=
⟨Multiset.sub⟩
@[simp]
theorem coe_sub (s t : List α) : (s - t : Multiset α) = (s.diff t : List α) :=
rfl
#align multiset.coe_sub Multiset.coe_sub
/-- This is a special case of `tsub_zero`, which should be used instead of this.
This is needed to prove `OrderedSub (Multiset α)`. -/
protected theorem sub_zero (s : Multiset α) : s - 0 = s :=
Quot.inductionOn s fun _l => rfl
#align multiset.sub_zero Multiset.sub_zero
@[simp]
theorem sub_cons (a : α) (s t : Multiset α) : s - a ::ₘ t = s.erase a - t :=
Quotient.inductionOn₂ s t fun _l₁ _l₂ => congr_arg _ <| diff_cons _ _ _
#align multiset.sub_cons Multiset.sub_cons
/-- This is a special case of `tsub_le_iff_right`, which should be used instead of this.
This is needed to prove `OrderedSub (Multiset α)`. -/
protected theorem sub_le_iff_le_add : s - t ≤ u ↔ s ≤ u + t := by
revert s
exact @(Multiset.induction_on t (by simp [Multiset.sub_zero]) fun a t IH s => by
simp [IH, erase_le_iff_le_cons])
#align multiset.sub_le_iff_le_add Multiset.sub_le_iff_le_add
instance : OrderedSub (Multiset α) :=
⟨fun _n _m _k => Multiset.sub_le_iff_le_add⟩
theorem cons_sub_of_le (a : α) {s t : Multiset α} (h : t ≤ s) : a ::ₘ s - t = a ::ₘ (s - t) := by
rw [← singleton_add, ← singleton_add, add_tsub_assoc_of_le h]
#align multiset.cons_sub_of_le Multiset.cons_sub_of_le
theorem sub_eq_fold_erase (s t : Multiset α) : s - t = foldl erase erase_comm s t :=
Quotient.inductionOn₂ s t fun l₁ l₂ => by
show ofList (l₁.diff l₂) = foldl erase erase_comm l₁ l₂
rw [diff_eq_foldl l₁ l₂]
symm
exact foldl_hom _ _ _ _ _ fun x y => rfl
#align multiset.sub_eq_fold_erase Multiset.sub_eq_fold_erase
@[simp]
theorem card_sub {s t : Multiset α} (h : t ≤ s) : card (s - t) = card s - card t :=
Nat.eq_sub_of_add_eq $ by rw [← card_add, tsub_add_cancel_of_le h]
#align multiset.card_sub Multiset.card_sub
/-! ### Union -/
/-- `s ∪ t` is the lattice join operation with respect to the
multiset `≤`. The multiplicity of `a` in `s ∪ t` is the maximum
of the multiplicities in `s` and `t`. -/
def union (s t : Multiset α) : Multiset α :=
s - t + t
#align multiset.union Multiset.union
instance : Union (Multiset α) :=
⟨union⟩
theorem union_def (s t : Multiset α) : s ∪ t = s - t + t :=
rfl
#align multiset.union_def Multiset.union_def
theorem le_union_left (s t : Multiset α) : s ≤ s ∪ t :=
le_tsub_add
#align multiset.le_union_left Multiset.le_union_left
theorem le_union_right (s t : Multiset α) : t ≤ s ∪ t :=
le_add_left _ _
#align multiset.le_union_right Multiset.le_union_right
theorem eq_union_left : t ≤ s → s ∪ t = s :=
tsub_add_cancel_of_le
#align multiset.eq_union_left Multiset.eq_union_left
theorem union_le_union_right (h : s ≤ t) (u) : s ∪ u ≤ t ∪ u :=
add_le_add_right (tsub_le_tsub_right h _) u
#align multiset.union_le_union_right Multiset.union_le_union_right
theorem union_le (h₁ : s ≤ u) (h₂ : t ≤ u) : s ∪ t ≤ u := by
rw [← eq_union_left h₂]; exact union_le_union_right h₁ t
#align multiset.union_le Multiset.union_le
@[simp]
theorem mem_union : a ∈ s ∪ t ↔ a ∈ s ∨ a ∈ t :=
⟨fun h => (mem_add.1 h).imp_left (mem_of_le tsub_le_self),
(Or.elim · (mem_of_le <| le_union_left _ _) (mem_of_le <| le_union_right _ _))⟩
#align multiset.mem_union Multiset.mem_union
@[simp]
theorem map_union [DecidableEq β] {f : α → β} (finj : Function.Injective f) {s t : Multiset α} :
map f (s ∪ t) = map f s ∪ map f t :=
Quotient.inductionOn₂ s t fun l₁ l₂ =>
congr_arg ofList (by rw [List.map_append f, List.map_diff finj])
#align multiset.map_union Multiset.map_union
-- Porting note (#10756): new theorem
@[simp] theorem zero_union : 0 ∪ s = s := by
simp [union_def]
-- Porting note (#10756): new theorem
@[simp] theorem union_zero : s ∪ 0 = s := by
simp [union_def]
/-! ### Intersection -/
/-- `s ∩ t` is the lattice meet operation with respect to the
multiset `≤`. The multiplicity of `a` in `s ∩ t` is the minimum
of the multiplicities in `s` and `t`. -/
def inter (s t : Multiset α) : Multiset α :=
Quotient.liftOn₂ s t (fun l₁ l₂ => (l₁.bagInter l₂ : Multiset α)) fun _v₁ _v₂ _w₁ _w₂ p₁ p₂ =>
Quot.sound <| p₁.bagInter p₂
#align multiset.inter Multiset.inter
instance : Inter (Multiset α) :=
⟨inter⟩
@[simp]
theorem inter_zero (s : Multiset α) : s ∩ 0 = 0 :=
Quot.inductionOn s fun l => congr_arg ofList l.bagInter_nil
#align multiset.inter_zero Multiset.inter_zero
@[simp]
theorem zero_inter (s : Multiset α) : 0 ∩ s = 0 :=
Quot.inductionOn s fun l => congr_arg ofList l.nil_bagInter
#align multiset.zero_inter Multiset.zero_inter
@[simp]
theorem cons_inter_of_pos {a} (s : Multiset α) {t} : a ∈ t → (a ::ₘ s) ∩ t = a ::ₘ s ∩ t.erase a :=
Quotient.inductionOn₂ s t fun _l₁ _l₂ h => congr_arg ofList <| cons_bagInter_of_pos _ h
#align multiset.cons_inter_of_pos Multiset.cons_inter_of_pos
@[simp]
theorem cons_inter_of_neg {a} (s : Multiset α) {t} : a ∉ t → (a ::ₘ s) ∩ t = s ∩ t :=
Quotient.inductionOn₂ s t fun _l₁ _l₂ h => congr_arg ofList <| cons_bagInter_of_neg _ h
#align multiset.cons_inter_of_neg Multiset.cons_inter_of_neg
theorem inter_le_left (s t : Multiset α) : s ∩ t ≤ s :=
Quotient.inductionOn₂ s t fun _l₁ _l₂ => (bagInter_sublist_left _ _).subperm
#align multiset.inter_le_left Multiset.inter_le_left
theorem inter_le_right (s : Multiset α) : ∀ t, s ∩ t ≤ t :=
Multiset.induction_on s (fun t => (zero_inter t).symm ▸ zero_le _) fun a s IH t =>
if h : a ∈ t then by simpa [h] using cons_le_cons a (IH (t.erase a)) else by simp [h, IH]
#align multiset.inter_le_right Multiset.inter_le_right
theorem le_inter (h₁ : s ≤ t) (h₂ : s ≤ u) : s ≤ t ∩ u := by
revert s u; refine @(Multiset.induction_on t ?_ fun a t IH => ?_) <;> intros s u h₁ h₂
· simpa only [zero_inter, nonpos_iff_eq_zero] using h₁
by_cases h : a ∈ u
· rw [cons_inter_of_pos _ h, ← erase_le_iff_le_cons]
exact IH (erase_le_iff_le_cons.2 h₁) (erase_le_erase _ h₂)
· rw [cons_inter_of_neg _ h]
exact IH ((le_cons_of_not_mem <| mt (mem_of_le h₂) h).1 h₁) h₂
#align multiset.le_inter Multiset.le_inter
@[simp]
theorem mem_inter : a ∈ s ∩ t ↔ a ∈ s ∧ a ∈ t :=
⟨fun h => ⟨mem_of_le (inter_le_left _ _) h, mem_of_le (inter_le_right _ _) h⟩, fun ⟨h₁, h₂⟩ => by
rw [← cons_erase h₁, cons_inter_of_pos _ h₂]; apply mem_cons_self⟩
#align multiset.mem_inter Multiset.mem_inter
instance : Lattice (Multiset α) :=
{ sup := (· ∪ ·)
sup_le := @union_le _ _
le_sup_left := le_union_left
le_sup_right := le_union_right
inf := (· ∩ ·)
le_inf := @le_inter _ _
inf_le_left := inter_le_left
inf_le_right := inter_le_right }
@[simp]
theorem sup_eq_union (s t : Multiset α) : s ⊔ t = s ∪ t :=
rfl
#align multiset.sup_eq_union Multiset.sup_eq_union
@[simp]
theorem inf_eq_inter (s t : Multiset α) : s ⊓ t = s ∩ t :=
rfl
#align multiset.inf_eq_inter Multiset.inf_eq_inter
@[simp]
theorem le_inter_iff : s ≤ t ∩ u ↔ s ≤ t ∧ s ≤ u :=
le_inf_iff
#align multiset.le_inter_iff Multiset.le_inter_iff
@[simp]
theorem union_le_iff : s ∪ t ≤ u ↔ s ≤ u ∧ t ≤ u :=
sup_le_iff
#align multiset.union_le_iff Multiset.union_le_iff
theorem union_comm (s t : Multiset α) : s ∪ t = t ∪ s := sup_comm _ _
#align multiset.union_comm Multiset.union_comm
theorem inter_comm (s t : Multiset α) : s ∩ t = t ∩ s := inf_comm _ _
#align multiset.inter_comm Multiset.inter_comm
theorem eq_union_right (h : s ≤ t) : s ∪ t = t := by rw [union_comm, eq_union_left h]
#align multiset.eq_union_right Multiset.eq_union_right
theorem union_le_union_left (h : s ≤ t) (u) : u ∪ s ≤ u ∪ t :=
sup_le_sup_left h _
#align multiset.union_le_union_left Multiset.union_le_union_left
theorem union_le_add (s t : Multiset α) : s ∪ t ≤ s + t :=
union_le (le_add_right _ _) (le_add_left _ _)
#align multiset.union_le_add Multiset.union_le_add
theorem union_add_distrib (s t u : Multiset α) : s ∪ t + u = s + u ∪ (t + u) := by
simpa [(· ∪ ·), union, eq_comm, add_assoc] using
show s + u - (t + u) = s - t by rw [add_comm t, tsub_add_eq_tsub_tsub, add_tsub_cancel_right]
#align multiset.union_add_distrib Multiset.union_add_distrib
theorem add_union_distrib (s t u : Multiset α) : s + (t ∪ u) = s + t ∪ (s + u) := by
rw [add_comm, union_add_distrib, add_comm s, add_comm s]
#align multiset.add_union_distrib Multiset.add_union_distrib
theorem cons_union_distrib (a : α) (s t : Multiset α) : a ::ₘ (s ∪ t) = a ::ₘ s ∪ a ::ₘ t := by
simpa using add_union_distrib (a ::ₘ 0) s t
#align multiset.cons_union_distrib Multiset.cons_union_distrib
theorem inter_add_distrib (s t u : Multiset α) : s ∩ t + u = (s + u) ∩ (t + u) := by
by_contra h
cases'
lt_iff_cons_le.1
(lt_of_le_of_ne
(le_inter (add_le_add_right (inter_le_left s t) u)
(add_le_add_right (inter_le_right s t) u))
h) with
a hl
rw [← cons_add] at hl
exact
not_le_of_lt (lt_cons_self (s ∩ t) a)
(le_inter (le_of_add_le_add_right (le_trans hl (inter_le_left _ _)))
(le_of_add_le_add_right (le_trans hl (inter_le_right _ _))))
#align multiset.inter_add_distrib Multiset.inter_add_distrib
theorem add_inter_distrib (s t u : Multiset α) : s + t ∩ u = (s + t) ∩ (s + u) := by
rw [add_comm, inter_add_distrib, add_comm s, add_comm s]
#align multiset.add_inter_distrib Multiset.add_inter_distrib
theorem cons_inter_distrib (a : α) (s t : Multiset α) : a ::ₘ s ∩ t = (a ::ₘ s) ∩ (a ::ₘ t) := by
simp
#align multiset.cons_inter_distrib Multiset.cons_inter_distrib
theorem union_add_inter (s t : Multiset α) : s ∪ t + s ∩ t = s + t := by
apply _root_.le_antisymm
· rw [union_add_distrib]
refine union_le (add_le_add_left (inter_le_right _ _) _) ?_
rw [add_comm]
exact add_le_add_right (inter_le_left _ _) _
· rw [add_comm, add_inter_distrib]
refine le_inter (add_le_add_right (le_union_right _ _) _) ?_
rw [add_comm]
exact add_le_add_right (le_union_left _ _) _
#align multiset.union_add_inter Multiset.union_add_inter
theorem sub_add_inter (s t : Multiset α) : s - t + s ∩ t = s := by
rw [inter_comm]
revert s; refine Multiset.induction_on t (by simp) fun a t IH s => ?_
by_cases h : a ∈ s
· rw [cons_inter_of_pos _ h, sub_cons, add_cons, IH, cons_erase h]
· rw [cons_inter_of_neg _ h, sub_cons, erase_of_not_mem h, IH]
#align multiset.sub_add_inter Multiset.sub_add_inter
theorem sub_inter (s t : Multiset α) : s - s ∩ t = s - t :=
add_right_cancel <| by rw [sub_add_inter s t, tsub_add_cancel_of_le (inter_le_left s t)]
#align multiset.sub_inter Multiset.sub_inter
end
/-! ### `Multiset.filter` -/
section
variable (p : α → Prop) [DecidablePred p]
/-- `Filter p s` returns the elements in `s` (with the same multiplicities)
which satisfy `p`, and removes the rest. -/
def filter (s : Multiset α) : Multiset α :=
Quot.liftOn s (fun l => (List.filter p l : Multiset α)) fun _l₁ _l₂ h => Quot.sound <| h.filter p
#align multiset.filter Multiset.filter
@[simp, norm_cast] lemma filter_coe (l : List α) : filter p l = l.filter p := rfl
#align multiset.coe_filter Multiset.filter_coe
@[simp]
theorem filter_zero : filter p 0 = 0 :=
rfl
#align multiset.filter_zero Multiset.filter_zero
theorem filter_congr {p q : α → Prop} [DecidablePred p] [DecidablePred q] {s : Multiset α} :
(∀ x ∈ s, p x ↔ q x) → filter p s = filter q s :=
Quot.inductionOn s fun _l h => congr_arg ofList <| filter_congr' <| by simpa using h
#align multiset.filter_congr Multiset.filter_congr
@[simp]
theorem filter_add (s t : Multiset α) : filter p (s + t) = filter p s + filter p t :=
Quotient.inductionOn₂ s t fun _l₁ _l₂ => congr_arg ofList <| filter_append _ _
#align multiset.filter_add Multiset.filter_add
@[simp]
theorem filter_le (s : Multiset α) : filter p s ≤ s :=
Quot.inductionOn s fun _l => (filter_sublist _).subperm
#align multiset.filter_le Multiset.filter_le
@[simp]
theorem filter_subset (s : Multiset α) : filter p s ⊆ s :=
subset_of_le <| filter_le _ _
#align multiset.filter_subset Multiset.filter_subset
theorem filter_le_filter {s t} (h : s ≤ t) : filter p s ≤ filter p t :=
leInductionOn h fun h => (h.filter (p ·)).subperm
#align multiset.filter_le_filter Multiset.filter_le_filter
theorem monotone_filter_left : Monotone (filter p) := fun _s _t => filter_le_filter p
#align multiset.monotone_filter_left Multiset.monotone_filter_left
theorem monotone_filter_right (s : Multiset α) ⦃p q : α → Prop⦄ [DecidablePred p] [DecidablePred q]
(h : ∀ b, p b → q b) :
s.filter p ≤ s.filter q :=
Quotient.inductionOn s fun l => (l.monotone_filter_right <| by simpa using h).subperm
#align multiset.monotone_filter_right Multiset.monotone_filter_right
variable {p}
@[simp]
theorem filter_cons_of_pos {a : α} (s) : p a → filter p (a ::ₘ s) = a ::ₘ filter p s :=
Quot.inductionOn s fun l h => congr_arg ofList <| List.filter_cons_of_pos l <| by simpa using h
#align multiset.filter_cons_of_pos Multiset.filter_cons_of_pos
@[simp]
theorem filter_cons_of_neg {a : α} (s) : ¬p a → filter p (a ::ₘ s) = filter p s :=
Quot.inductionOn s fun l h => congr_arg ofList <| List.filter_cons_of_neg l <| by simpa using h
#align multiset.filter_cons_of_neg Multiset.filter_cons_of_neg
@[simp]
theorem mem_filter {a : α} {s} : a ∈ filter p s ↔ a ∈ s ∧ p a :=
Quot.inductionOn s fun _l => by simpa using List.mem_filter (p := (p ·))
#align multiset.mem_filter Multiset.mem_filter
theorem of_mem_filter {a : α} {s} (h : a ∈ filter p s) : p a :=
(mem_filter.1 h).2
#align multiset.of_mem_filter Multiset.of_mem_filter
theorem mem_of_mem_filter {a : α} {s} (h : a ∈ filter p s) : a ∈ s :=
(mem_filter.1 h).1
#align multiset.mem_of_mem_filter Multiset.mem_of_mem_filter
theorem mem_filter_of_mem {a : α} {l} (m : a ∈ l) (h : p a) : a ∈ filter p l :=
mem_filter.2 ⟨m, h⟩
#align multiset.mem_filter_of_mem Multiset.mem_filter_of_mem
theorem filter_eq_self {s} : filter p s = s ↔ ∀ a ∈ s, p a :=
Quot.inductionOn s fun _l =>
Iff.trans ⟨fun h => (filter_sublist _).eq_of_length (@congr_arg _ _ _ _ card h),
congr_arg ofList⟩ <| by simp
#align multiset.filter_eq_self Multiset.filter_eq_self
theorem filter_eq_nil {s} : filter p s = 0 ↔ ∀ a ∈ s, ¬p a :=
Quot.inductionOn s fun _l =>
Iff.trans ⟨fun h => eq_nil_of_length_eq_zero (@congr_arg _ _ _ _ card h), congr_arg ofList⟩ <|
by simpa using List.filter_eq_nil (p := (p ·))
#align multiset.filter_eq_nil Multiset.filter_eq_nil
theorem le_filter {s t} : s ≤ filter p t ↔ s ≤ t ∧ ∀ a ∈ s, p a :=
⟨fun h => ⟨le_trans h (filter_le _ _), fun _a m => of_mem_filter (mem_of_le h m)⟩, fun ⟨h, al⟩ =>
filter_eq_self.2 al ▸ filter_le_filter p h⟩
#align multiset.le_filter Multiset.le_filter
theorem filter_cons {a : α} (s : Multiset α) :
filter p (a ::ₘ s) = (if p a then {a} else 0) + filter p s := by
split_ifs with h
· rw [filter_cons_of_pos _ h, singleton_add]
· rw [filter_cons_of_neg _ h, zero_add]
#align multiset.filter_cons Multiset.filter_cons
theorem filter_singleton {a : α} (p : α → Prop) [DecidablePred p] :
filter p {a} = if p a then {a} else ∅ := by
simp only [singleton, filter_cons, filter_zero, add_zero, empty_eq_zero]
#align multiset.filter_singleton Multiset.filter_singleton
theorem filter_nsmul (s : Multiset α) (n : ℕ) : filter p (n • s) = n • filter p s := by
refine s.induction_on ?_ ?_
· simp only [filter_zero, nsmul_zero]
· intro a ha ih
rw [nsmul_cons, filter_add, ih, filter_cons, nsmul_add]
congr
split_ifs with hp <;>
· simp only [filter_eq_self, nsmul_zero, filter_eq_nil]
intro b hb
rwa [mem_singleton.mp (mem_of_mem_nsmul hb)]
#align multiset.filter_nsmul Multiset.filter_nsmul
variable (p)
@[simp]
theorem filter_sub [DecidableEq α] (s t : Multiset α) :
filter p (s - t) = filter p s - filter p t := by
revert s; refine Multiset.induction_on t (by simp) fun a t IH s => ?_
rw [sub_cons, IH]
by_cases h : p a
· rw [filter_cons_of_pos _ h, sub_cons]
congr
by_cases m : a ∈ s
· rw [← cons_inj_right a, ← filter_cons_of_pos _ h, cons_erase (mem_filter_of_mem m h),
cons_erase m]
· rw [erase_of_not_mem m, erase_of_not_mem (mt mem_of_mem_filter m)]
· rw [filter_cons_of_neg _ h]
by_cases m : a ∈ s
· rw [(by rw [filter_cons_of_neg _ h] : filter p (erase s a) = filter p (a ::ₘ erase s a)),
cons_erase m]
· rw [erase_of_not_mem m]
#align multiset.filter_sub Multiset.filter_sub
@[simp]
theorem filter_union [DecidableEq α] (s t : Multiset α) :
filter p (s ∪ t) = filter p s ∪ filter p t := by simp [(· ∪ ·), union]
#align multiset.filter_union Multiset.filter_union
@[simp]
theorem filter_inter [DecidableEq α] (s t : Multiset α) :
filter p (s ∩ t) = filter p s ∩ filter p t :=
le_antisymm
(le_inter (filter_le_filter _ <| inter_le_left _ _)
(filter_le_filter _ <| inter_le_right _ _)) <|
le_filter.2
⟨inf_le_inf (filter_le _ _) (filter_le _ _), fun _a h =>
of_mem_filter (mem_of_le (inter_le_left _ _) h)⟩
#align multiset.filter_inter Multiset.filter_inter
@[simp]
theorem filter_filter (q) [DecidablePred q] (s : Multiset α) :
filter p (filter q s) = filter (fun a => p a ∧ q a) s :=
Quot.inductionOn s fun l => by simp
#align multiset.filter_filter Multiset.filter_filter
lemma filter_comm (q) [DecidablePred q] (s : Multiset α) :
filter p (filter q s) = filter q (filter p s) := by simp [and_comm]
#align multiset.filter_comm Multiset.filter_comm
theorem filter_add_filter (q) [DecidablePred q] (s : Multiset α) :
filter p s + filter q s = filter (fun a => p a ∨ q a) s + filter (fun a => p a ∧ q a) s :=
Multiset.induction_on s rfl fun a s IH => by by_cases p a <;> by_cases q a <;> simp [*]
#align multiset.filter_add_filter Multiset.filter_add_filter
theorem filter_add_not (s : Multiset α) : filter p s + filter (fun a => ¬p a) s = s := by
rw [filter_add_filter, filter_eq_self.2, filter_eq_nil.2]
· simp only [add_zero]
· simp [Decidable.em, -Bool.not_eq_true, -not_and, not_and_or, or_comm]
· simp only [Bool.not_eq_true, decide_eq_true_eq, Bool.eq_false_or_eq_true,
decide_True, implies_true, Decidable.em]
#align multiset.filter_add_not Multiset.filter_add_not
theorem map_filter (f : β → α) (s : Multiset β) : filter p (map f s) = map f (filter (p ∘ f) s) :=
Quot.inductionOn s fun l => by simp [List.map_filter]; rfl
#align multiset.map_filter Multiset.map_filter
lemma map_filter' {f : α → β} (hf : Injective f) (s : Multiset α)
[DecidablePred fun b => ∃ a, p a ∧ f a = b] :
(s.filter p).map f = (s.map f).filter fun b => ∃ a, p a ∧ f a = b := by
simp [(· ∘ ·), map_filter, hf.eq_iff]
#align multiset.map_filter' Multiset.map_filter'
lemma card_filter_le_iff (s : Multiset α) (P : α → Prop) [DecidablePred P] (n : ℕ) :
card (s.filter P) ≤ n ↔ ∀ s' ≤ s, n < card s' → ∃ a ∈ s', ¬ P a := by
fconstructor
· intro H s' hs' s'_card
by_contra! rid
have card := card_le_card (monotone_filter_left P hs') |>.trans H
exact s'_card.not_le (filter_eq_self.mpr rid ▸ card)
· contrapose!
exact fun H ↦ ⟨s.filter P, filter_le _ _, H, fun a ha ↦ (mem_filter.mp ha).2⟩
/-! ### Simultaneously filter and map elements of a multiset -/
/-- `filterMap f s` is a combination filter/map operation on `s`.
The function `f : α → Option β` is applied to each element of `s`;
if `f a` is `some b` then `b` is added to the result, otherwise
`a` is removed from the resulting multiset. -/
def filterMap (f : α → Option β) (s : Multiset α) : Multiset β :=
Quot.liftOn s (fun l => (List.filterMap f l : Multiset β))
fun _l₁ _l₂ h => Quot.sound <| h.filterMap f
#align multiset.filter_map Multiset.filterMap
@[simp, norm_cast]
lemma filterMap_coe (f : α → Option β) (l : List α) : filterMap f l = l.filterMap f := rfl
#align multiset.coe_filter_map Multiset.filterMap_coe
@[simp]
theorem filterMap_zero (f : α → Option β) : filterMap f 0 = 0 :=
rfl
#align multiset.filter_map_zero Multiset.filterMap_zero
@[simp]
theorem filterMap_cons_none {f : α → Option β} (a : α) (s : Multiset α) (h : f a = none) :
filterMap f (a ::ₘ s) = filterMap f s :=
Quot.inductionOn s fun l => congr_arg ofList <| List.filterMap_cons_none a l h
#align multiset.filter_map_cons_none Multiset.filterMap_cons_none
@[simp]
theorem filterMap_cons_some (f : α → Option β) (a : α) (s : Multiset α) {b : β}
(h : f a = some b) : filterMap f (a ::ₘ s) = b ::ₘ filterMap f s :=
Quot.inductionOn s fun l => congr_arg ofList <| List.filterMap_cons_some f a l h
#align multiset.filter_map_cons_some Multiset.filterMap_cons_some
theorem filterMap_eq_map (f : α → β) : filterMap (some ∘ f) = map f :=
funext fun s =>
Quot.inductionOn s fun l => congr_arg ofList <| congr_fun (List.filterMap_eq_map f) l
#align multiset.filter_map_eq_map Multiset.filterMap_eq_map
theorem filterMap_eq_filter : filterMap (Option.guard p) = filter p :=
funext fun s =>
Quot.inductionOn s fun l => congr_arg ofList <| by
rw [← List.filterMap_eq_filter]
congr; funext a; simp
#align multiset.filter_map_eq_filter Multiset.filterMap_eq_filter
theorem filterMap_filterMap (f : α → Option β) (g : β → Option γ) (s : Multiset α) :
filterMap g (filterMap f s) = filterMap (fun x => (f x).bind g) s :=
Quot.inductionOn s fun l => congr_arg ofList <| List.filterMap_filterMap f g l
#align multiset.filter_map_filter_map Multiset.filterMap_filterMap
theorem map_filterMap (f : α → Option β) (g : β → γ) (s : Multiset α) :
map g (filterMap f s) = filterMap (fun x => (f x).map g) s :=
Quot.inductionOn s fun l => congr_arg ofList <| List.map_filterMap f g l
#align multiset.map_filter_map Multiset.map_filterMap
theorem filterMap_map (f : α → β) (g : β → Option γ) (s : Multiset α) :
filterMap g (map f s) = filterMap (g ∘ f) s :=
Quot.inductionOn s fun l => congr_arg ofList <| List.filterMap_map f g l
#align multiset.filter_map_map Multiset.filterMap_map
theorem filter_filterMap (f : α → Option β) (p : β → Prop) [DecidablePred p] (s : Multiset α) :
filter p (filterMap f s) = filterMap (fun x => (f x).filter p) s :=
Quot.inductionOn s fun l => congr_arg ofList <| List.filter_filterMap f p l
#align multiset.filter_filter_map Multiset.filter_filterMap
theorem filterMap_filter (f : α → Option β) (s : Multiset α) :
filterMap f (filter p s) = filterMap (fun x => if p x then f x else none) s :=
Quot.inductionOn s fun l => congr_arg ofList <| by simpa using List.filterMap_filter p f l
#align multiset.filter_map_filter Multiset.filterMap_filter
@[simp]
theorem filterMap_some (s : Multiset α) : filterMap some s = s :=
Quot.inductionOn s fun l => congr_arg ofList <| List.filterMap_some l
#align multiset.filter_map_some Multiset.filterMap_some
@[simp]
theorem mem_filterMap (f : α → Option β) (s : Multiset α) {b : β} :
b ∈ filterMap f s ↔ ∃ a, a ∈ s ∧ f a = some b :=
Quot.inductionOn s fun l => List.mem_filterMap f l
#align multiset.mem_filter_map Multiset.mem_filterMap
theorem map_filterMap_of_inv (f : α → Option β) (g : β → α) (H : ∀ x : α, (f x).map g = some x)
(s : Multiset α) : map g (filterMap f s) = s :=
Quot.inductionOn s fun l => congr_arg ofList <| List.map_filterMap_of_inv f g H l
#align multiset.map_filter_map_of_inv Multiset.map_filterMap_of_inv
theorem filterMap_le_filterMap (f : α → Option β) {s t : Multiset α} (h : s ≤ t) :
filterMap f s ≤ filterMap f t :=
leInductionOn h fun h => (h.filterMap _).subperm
#align multiset.filter_map_le_filter_map Multiset.filterMap_le_filterMap
/-! ### countP -/
/-- `countP p s` counts the number of elements of `s` (with multiplicity) that
satisfy `p`. -/
def countP (s : Multiset α) : ℕ :=
Quot.liftOn s (List.countP p) fun _l₁ _l₂ => Perm.countP_eq (p ·)
#align multiset.countp Multiset.countP
@[simp]
theorem coe_countP (l : List α) : countP p l = l.countP p :=
rfl
#align multiset.coe_countp Multiset.coe_countP
@[simp]
theorem countP_zero : countP p 0 = 0 :=
rfl
#align multiset.countp_zero Multiset.countP_zero
variable {p}
@[simp]
theorem countP_cons_of_pos {a : α} (s) : p a → countP p (a ::ₘ s) = countP p s + 1 :=
Quot.inductionOn s <| by simpa using List.countP_cons_of_pos (p ·)
#align multiset.countp_cons_of_pos Multiset.countP_cons_of_pos
@[simp]
theorem countP_cons_of_neg {a : α} (s) : ¬p a → countP p (a ::ₘ s) = countP p s :=
Quot.inductionOn s <| by simpa using List.countP_cons_of_neg (p ·)
#align multiset.countp_cons_of_neg Multiset.countP_cons_of_neg
variable (p)
theorem countP_cons (b : α) (s) : countP p (b ::ₘ s) = countP p s + if p b then 1 else 0 :=
Quot.inductionOn s <| by simp [List.countP_cons]
#align multiset.countp_cons Multiset.countP_cons
theorem countP_eq_card_filter (s) : countP p s = card (filter p s) :=
Quot.inductionOn s fun l => l.countP_eq_length_filter (p ·)
#align multiset.countp_eq_card_filter Multiset.countP_eq_card_filter
theorem countP_le_card (s) : countP p s ≤ card s :=
Quot.inductionOn s fun _l => countP_le_length (p ·)
#align multiset.countp_le_card Multiset.countP_le_card
@[simp]
theorem countP_add (s t) : countP p (s + t) = countP p s + countP p t := by
simp [countP_eq_card_filter]
#align multiset.countp_add Multiset.countP_add
@[simp]
theorem countP_nsmul (s) (n : ℕ) : countP p (n • s) = n * countP p s := by
induction n <;> simp [*, succ_nsmul, succ_mul, zero_nsmul]
#align multiset.countp_nsmul Multiset.countP_nsmul
theorem card_eq_countP_add_countP (s) : card s = countP p s + countP (fun x => ¬p x) s :=
Quot.inductionOn s fun l => by simp [l.length_eq_countP_add_countP p]
#align multiset.card_eq_countp_add_countp Multiset.card_eq_countP_add_countP
/-- `countP p`, the number of elements of a multiset satisfying `p`, promoted to an
`AddMonoidHom`. -/
def countPAddMonoidHom : Multiset α →+ ℕ where
toFun := countP p
map_zero' := countP_zero _
map_add' := countP_add _
#align multiset.countp_add_monoid_hom Multiset.countPAddMonoidHom
@[simp]
theorem coe_countPAddMonoidHom : (countPAddMonoidHom p : Multiset α → ℕ) = countP p :=
rfl
#align multiset.coe_countp_add_monoid_hom Multiset.coe_countPAddMonoidHom
@[simp]
theorem countP_sub [DecidableEq α] {s t : Multiset α} (h : t ≤ s) :
countP p (s - t) = countP p s - countP p t := by
simp [countP_eq_card_filter, h, filter_le_filter]
#align multiset.countp_sub Multiset.countP_sub
theorem countP_le_of_le {s t} (h : s ≤ t) : countP p s ≤ countP p t := by
simpa [countP_eq_card_filter] using card_le_card (filter_le_filter p h)
#align multiset.countp_le_of_le Multiset.countP_le_of_le
@[simp]
theorem countP_filter (q) [DecidablePred q] (s : Multiset α) :
countP p (filter q s) = countP (fun a => p a ∧ q a) s := by simp [countP_eq_card_filter]
#align multiset.countp_filter Multiset.countP_filter
theorem countP_eq_countP_filter_add (s) (p q : α → Prop) [DecidablePred p] [DecidablePred q] :
countP p s = (filter q s).countP p + (filter (fun a => ¬q a) s).countP p :=
Quot.inductionOn s fun l => by
convert l.countP_eq_countP_filter_add (p ·) (q ·)
simp [countP_filter]
#align multiset.countp_eq_countp_filter_add Multiset.countP_eq_countP_filter_add
@[simp]
theorem countP_True {s : Multiset α} : countP (fun _ => True) s = card s :=
Quot.inductionOn s fun _l => List.countP_true
#align multiset.countp_true Multiset.countP_True
@[simp]
theorem countP_False {s : Multiset α} : countP (fun _ => False) s = 0 :=
Quot.inductionOn s fun _l => List.countP_false
#align multiset.countp_false Multiset.countP_False
theorem countP_map (f : α → β) (s : Multiset α) (p : β → Prop) [DecidablePred p] :
countP p (map f s) = card (s.filter fun a => p (f a)) := by
refine Multiset.induction_on s ?_ fun a t IH => ?_
· rw [map_zero, countP_zero, filter_zero, card_zero]
· rw [map_cons, countP_cons, IH, filter_cons, card_add, apply_ite card, card_zero, card_singleton,
add_comm]
#align multiset.countp_map Multiset.countP_map
-- Porting note: `Lean.Internal.coeM` forces us to type-ascript `{a // a ∈ s}`
lemma countP_attach (s : Multiset α) : s.attach.countP (fun a : {a // a ∈ s} ↦ p a) = s.countP p :=
Quotient.inductionOn s fun l => by
simp only [quot_mk_to_coe, coe_countP]
-- Porting note: was
-- rw [quot_mk_to_coe, coe_attach, coe_countP]
-- exact List.countP_attach _ _
rw [coe_attach]
refine (coe_countP _ _).trans ?_
convert List.countP_attach _ _
rfl
#align multiset.countp_attach Multiset.countP_attach
lemma filter_attach (s : Multiset α) (p : α → Prop) [DecidablePred p] :
(s.attach.filter fun a : {a // a ∈ s} ↦ p ↑a) =
(s.filter p).attach.map (Subtype.map id fun _ ↦ Multiset.mem_of_mem_filter) :=
Quotient.inductionOn s fun l ↦ congr_arg _ (List.filter_attach l p)
#align multiset.filter_attach Multiset.filter_attach
variable {p}
theorem countP_pos {s} : 0 < countP p s ↔ ∃ a ∈ s, p a :=
Quot.inductionOn s fun _l => by simpa using List.countP_pos (p ·)
#align multiset.countp_pos Multiset.countP_pos
theorem countP_eq_zero {s} : countP p s = 0 ↔ ∀ a ∈ s, ¬p a :=
Quot.inductionOn s fun _l => by simp [List.countP_eq_zero]
#align multiset.countp_eq_zero Multiset.countP_eq_zero
theorem countP_eq_card {s} : countP p s = card s ↔ ∀ a ∈ s, p a :=
Quot.inductionOn s fun _l => by simp [List.countP_eq_length]
#align multiset.countp_eq_card Multiset.countP_eq_card
theorem countP_pos_of_mem {s a} (h : a ∈ s) (pa : p a) : 0 < countP p s :=
countP_pos.2 ⟨_, h, pa⟩
#align multiset.countp_pos_of_mem Multiset.countP_pos_of_mem
theorem countP_congr {s s' : Multiset α} (hs : s = s')
{p p' : α → Prop} [DecidablePred p] [DecidablePred p']
(hp : ∀ x ∈ s, p x = p' x) : s.countP p = s'.countP p' := by
revert hs hp
exact Quot.induction_on₂ s s'
(fun l l' hs hp => by
simp only [quot_mk_to_coe'', coe_eq_coe] at hs
apply hs.countP_congr
simpa using hp)
#align multiset.countp_congr Multiset.countP_congr
end
/-! ### Multiplicity of an element -/
section
variable [DecidableEq α] {s : Multiset α}
/-- `count a s` is the multiplicity of `a` in `s`. -/
def count (a : α) : Multiset α → ℕ :=
countP (a = ·)
#align multiset.count Multiset.count
@[simp]
theorem coe_count (a : α) (l : List α) : count a (ofList l) = l.count a := by
simp_rw [count, List.count, coe_countP (a = ·) l, @eq_comm _ a]
rfl
#align multiset.coe_count Multiset.coe_count
@[simp, nolint simpNF] -- Porting note (#10618): simp can prove this at EOF, but not right now
theorem count_zero (a : α) : count a 0 = 0 :=
rfl
#align multiset.count_zero Multiset.count_zero
@[simp]
theorem count_cons_self (a : α) (s : Multiset α) : count a (a ::ₘ s) = count a s + 1 :=
countP_cons_of_pos _ <| rfl
#align multiset.count_cons_self Multiset.count_cons_self
@[simp]
theorem count_cons_of_ne {a b : α} (h : a ≠ b) (s : Multiset α) : count a (b ::ₘ s) = count a s :=
countP_cons_of_neg _ <| h
#align multiset.count_cons_of_ne Multiset.count_cons_of_ne
theorem count_le_card (a : α) (s) : count a s ≤ card s :=
countP_le_card _ _
#align multiset.count_le_card Multiset.count_le_card
theorem count_le_of_le (a : α) {s t} : s ≤ t → count a s ≤ count a t :=
countP_le_of_le _
#align multiset.count_le_of_le Multiset.count_le_of_le
theorem count_le_count_cons (a b : α) (s : Multiset α) : count a s ≤ count a (b ::ₘ s) :=
count_le_of_le _ (le_cons_self _ _)
#align multiset.count_le_count_cons Multiset.count_le_count_cons
theorem count_cons (a b : α) (s : Multiset α) :
count a (b ::ₘ s) = count a s + if a = b then 1 else 0 :=
countP_cons (a = ·) _ _
#align multiset.count_cons Multiset.count_cons
theorem count_singleton_self (a : α) : count a ({a} : Multiset α) = 1 :=
count_eq_one_of_mem (nodup_singleton a) <| mem_singleton_self a
#align multiset.count_singleton_self Multiset.count_singleton_self
theorem count_singleton (a b : α) : count a ({b} : Multiset α) = if a = b then 1 else 0 := by
simp only [count_cons, ← cons_zero, count_zero, zero_add]
#align multiset.count_singleton Multiset.count_singleton
@[simp]
theorem count_add (a : α) : ∀ s t, count a (s + t) = count a s + count a t :=
countP_add _
#align multiset.count_add Multiset.count_add
/-- `count a`, the multiplicity of `a` in a multiset, promoted to an `AddMonoidHom`. -/
def countAddMonoidHom (a : α) : Multiset α →+ ℕ :=
countPAddMonoidHom (a = ·)
#align multiset.count_add_monoid_hom Multiset.countAddMonoidHom
@[simp]
theorem coe_countAddMonoidHom {a : α} : (countAddMonoidHom a : Multiset α → ℕ) = count a :=
rfl
#align multiset.coe_count_add_monoid_hom Multiset.coe_countAddMonoidHom
@[simp]
theorem count_nsmul (a : α) (n s) : count a (n • s) = n * count a s := by
induction n <;> simp [*, succ_nsmul, succ_mul, zero_nsmul]
#align multiset.count_nsmul Multiset.count_nsmul
@[simp]
lemma count_attach (a : {x // x ∈ s}) : s.attach.count a = s.count ↑a :=
Eq.trans (countP_congr rfl fun _ _ => by simp [Subtype.ext_iff]) <| countP_attach _ _
#align multiset.count_attach Multiset.count_attach
theorem count_pos {a : α} {s : Multiset α} : 0 < count a s ↔ a ∈ s := by simp [count, countP_pos]
#align multiset.count_pos Multiset.count_pos
theorem one_le_count_iff_mem {a : α} {s : Multiset α} : 1 ≤ count a s ↔ a ∈ s := by
rw [succ_le_iff, count_pos]
#align multiset.one_le_count_iff_mem Multiset.one_le_count_iff_mem
@[simp]
theorem count_eq_zero_of_not_mem {a : α} {s : Multiset α} (h : a ∉ s) : count a s = 0 :=
by_contradiction fun h' => h <| count_pos.1 (Nat.pos_of_ne_zero h')
#align multiset.count_eq_zero_of_not_mem Multiset.count_eq_zero_of_not_mem
lemma count_ne_zero {a : α} : count a s ≠ 0 ↔ a ∈ s := Nat.pos_iff_ne_zero.symm.trans count_pos
#align multiset.count_ne_zero Multiset.count_ne_zero
@[simp] lemma count_eq_zero {a : α} : count a s = 0 ↔ a ∉ s := count_ne_zero.not_right
#align multiset.count_eq_zero Multiset.count_eq_zero
theorem count_eq_card {a : α} {s} : count a s = card s ↔ ∀ x ∈ s, a = x := by
simp [countP_eq_card, count, @eq_comm _ a]
#align multiset.count_eq_card Multiset.count_eq_card
@[simp]
theorem count_replicate_self (a : α) (n : ℕ) : count a (replicate n a) = n := by
convert List.count_replicate_self a n
rw [← coe_count, coe_replicate]
#align multiset.count_replicate_self Multiset.count_replicate_self
theorem count_replicate (a b : α) (n : ℕ) : count a (replicate n b) = if a = b then n else 0 := by
convert List.count_replicate a b n
rw [← coe_count, coe_replicate]
#align multiset.count_replicate Multiset.count_replicate
@[simp]
theorem count_erase_self (a : α) (s : Multiset α) : count a (erase s a) = count a s - 1 :=
Quotient.inductionOn s fun l => by
convert List.count_erase_self a l <;> rw [← coe_count] <;> simp
#align multiset.count_erase_self Multiset.count_erase_self
@[simp]
theorem count_erase_of_ne {a b : α} (ab : a ≠ b) (s : Multiset α) :
count a (erase s b) = count a s :=
Quotient.inductionOn s fun l => by
convert List.count_erase_of_ne ab l <;> rw [← coe_count] <;> simp
#align multiset.count_erase_of_ne Multiset.count_erase_of_ne
@[simp]
theorem count_sub (a : α) (s t : Multiset α) : count a (s - t) = count a s - count a t := by
revert s; refine Multiset.induction_on t (by simp) fun b t IH s => ?_
rw [sub_cons, IH]
rcases Decidable.eq_or_ne a b with rfl | ab
· rw [count_erase_self, count_cons_self, Nat.sub_sub, add_comm]
· rw [count_erase_of_ne ab, count_cons_of_ne ab]
#align multiset.count_sub Multiset.count_sub
@[simp]
theorem count_union (a : α) (s t : Multiset α) : count a (s ∪ t) = max (count a s) (count a t) := by
simp [(· ∪ ·), union, Nat.sub_add_eq_max]
#align multiset.count_union Multiset.count_union
@[simp]
theorem count_inter (a : α) (s t : Multiset α) : count a (s ∩ t) = min (count a s) (count a t) := by
apply @Nat.add_left_cancel (count a (s - t))
rw [← count_add, sub_add_inter, count_sub, Nat.sub_add_min_cancel]
#align multiset.count_inter Multiset.count_inter
theorem le_count_iff_replicate_le {a : α} {s : Multiset α} {n : ℕ} :
n ≤ count a s ↔ replicate n a ≤ s :=
Quot.inductionOn s fun _l => by
simp only [quot_mk_to_coe'', mem_coe, coe_count]
exact le_count_iff_replicate_sublist.trans replicate_le_coe.symm
#align multiset.le_count_iff_replicate_le Multiset.le_count_iff_replicate_le
@[simp]
theorem count_filter_of_pos {p} [DecidablePred p] {a} {s : Multiset α} (h : p a) :
count a (filter p s) = count a s :=
Quot.inductionOn s fun _l => by
simp only [quot_mk_to_coe'', filter_coe, mem_coe, coe_count, decide_eq_true_eq]
apply count_filter
simpa using h
#align multiset.count_filter_of_pos Multiset.count_filter_of_pos
@[simp]
theorem count_filter_of_neg {p} [DecidablePred p] {a} {s : Multiset α} (h : ¬p a) :
count a (filter p s) = 0 :=
Multiset.count_eq_zero_of_not_mem fun t => h (of_mem_filter t)
#align multiset.count_filter_of_neg Multiset.count_filter_of_neg
theorem count_filter {p} [DecidablePred p] {a} {s : Multiset α} :
count a (filter p s) = if p a then count a s else 0 := by
split_ifs with h
· exact count_filter_of_pos h
· exact count_filter_of_neg h
#align multiset.count_filter Multiset.count_filter
theorem ext {s t : Multiset α} : s = t ↔ ∀ a, count a s = count a t :=
Quotient.inductionOn₂ s t fun _l₁ _l₂ => Quotient.eq.trans <| by
simp only [quot_mk_to_coe, filter_coe, mem_coe, coe_count, decide_eq_true_eq]
apply perm_iff_count
#align multiset.ext Multiset.ext
@[ext]
theorem ext' {s t : Multiset α} : (∀ a, count a s = count a t) → s = t :=
ext.2
#align multiset.ext' Multiset.ext'
@[simp]
theorem coe_inter (s t : List α) : (s ∩ t : Multiset α) = (s.bagInter t : List α) := by ext; simp
#align multiset.coe_inter Multiset.coe_inter
theorem le_iff_count {s t : Multiset α} : s ≤ t ↔ ∀ a, count a s ≤ count a t :=
⟨fun h a => count_le_of_le a h, fun al => by
rw [← (ext.2 fun a => by simp [max_eq_right (al a)] : s ∪ t = t)]; apply le_union_left⟩
#align multiset.le_iff_count Multiset.le_iff_count
instance : DistribLattice (Multiset α) :=
{ le_sup_inf := fun s t u =>
le_of_eq <|
Eq.symm <|
ext.2 fun a => by
simp only [max_min_distrib_left, Multiset.count_inter, Multiset.sup_eq_union,
Multiset.count_union, Multiset.inf_eq_inter] }
theorem count_map {α β : Type*} (f : α → β) (s : Multiset α) [DecidableEq β] (b : β) :
count b (map f s) = card (s.filter fun a => b = f a) := by
simp [Bool.beq_eq_decide_eq, eq_comm, count, countP_map]
#align multiset.count_map Multiset.count_map
/-- `Multiset.map f` preserves `count` if `f` is injective on the set of elements contained in
the multiset -/
theorem count_map_eq_count [DecidableEq β] (f : α → β) (s : Multiset α)
(hf : Set.InjOn f { x : α | x ∈ s }) (x) (H : x ∈ s) : (s.map f).count (f x) = s.count x := by
suffices (filter (fun a : α => f x = f a) s).count x = card (filter (fun a : α => f x = f a) s) by
rw [count, countP_map, ← this]
exact count_filter_of_pos <| rfl
· rw [eq_replicate_card.2 fun b hb => (hf H (mem_filter.1 hb).left _).symm]
· simp only [count_replicate, eq_self_iff_true, if_true, card_replicate]
· simp only [mem_filter, beq_iff_eq, and_imp, @eq_comm _ (f x), imp_self, implies_true]
#align multiset.count_map_eq_count Multiset.count_map_eq_count
/-- `Multiset.map f` preserves `count` if `f` is injective -/
theorem count_map_eq_count' [DecidableEq β] (f : α → β) (s : Multiset α) (hf : Function.Injective f)
(x : α) : (s.map f).count (f x) = s.count x := by
by_cases H : x ∈ s
· exact count_map_eq_count f _ hf.injOn _ H
· rw [count_eq_zero_of_not_mem H, count_eq_zero, mem_map]
rintro ⟨k, hks, hkx⟩
rw [hf hkx] at hks
contradiction
#align multiset.count_map_eq_count' Multiset.count_map_eq_count'
@[simp]
theorem sub_filter_eq_filter_not [DecidableEq α] (p) [DecidablePred p] (s : Multiset α) :
s - s.filter p = s.filter (fun a ↦ ¬ p a) := by
ext a; by_cases h : p a <;> simp [h]
theorem filter_eq' (s : Multiset α) (b : α) : s.filter (· = b) = replicate (count b s) b :=
Quotient.inductionOn s fun l => by
simp only [quot_mk_to_coe, filter_coe, mem_coe, coe_count]
rw [List.filter_eq l b, coe_replicate]
#align multiset.filter_eq' Multiset.filter_eq'
theorem filter_eq (s : Multiset α) (b : α) : s.filter (Eq b) = replicate (count b s) b := by
simp_rw [← filter_eq', eq_comm]
#align multiset.filter_eq Multiset.filter_eq
@[simp]
| Mathlib/Data/Multiset/Basic.lean | 2,669 | 2,675 | theorem replicate_inter (n : ℕ) (x : α) (s : Multiset α) :
replicate n x ∩ s = replicate (min n (s.count x)) x := by |
ext y
rw [count_inter, count_replicate, count_replicate]
by_cases h : y = x
· simp only [h, if_true]
· simp only [h, if_false, Nat.zero_min]
|
/-
Copyright (c) 2021 Anne Baanen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anne Baanen
-/
import Mathlib.FieldTheory.PrimitiveElement
import Mathlib.LinearAlgebra.Determinant
import Mathlib.LinearAlgebra.FiniteDimensional
import Mathlib.LinearAlgebra.Matrix.Charpoly.Minpoly
import Mathlib.LinearAlgebra.Matrix.ToLinearEquiv
import Mathlib.FieldTheory.IsAlgClosed.AlgebraicClosure
import Mathlib.FieldTheory.Galois
#align_import ring_theory.norm from "leanprover-community/mathlib"@"fecd3520d2a236856f254f27714b80dcfe28ea57"
/-!
# Norm for (finite) ring extensions
Suppose we have an `R`-algebra `S` with a finite basis. For each `s : S`,
the determinant of the linear map given by multiplying by `s` gives information
about the roots of the minimal polynomial of `s` over `R`.
## Implementation notes
Typically, the norm is defined specifically for finite field extensions.
The current definition is as general as possible and the assumption that we have
fields or that the extension is finite is added to the lemmas as needed.
We only define the norm for left multiplication (`Algebra.leftMulMatrix`,
i.e. `LinearMap.mulLeft`).
For now, the definitions assume `S` is commutative, so the choice doesn't
matter anyway.
See also `Algebra.trace`, which is defined similarly as the trace of
`Algebra.leftMulMatrix`.
## References
* https://en.wikipedia.org/wiki/Field_norm
-/
universe u v w
variable {R S T : Type*} [CommRing R] [Ring S]
variable [Algebra R S]
variable {K L F : Type*} [Field K] [Field L] [Field F]
variable [Algebra K L] [Algebra K F]
variable {ι : Type w}
open FiniteDimensional
open LinearMap
open Matrix Polynomial
open scoped Matrix
namespace Algebra
variable (R)
/-- The norm of an element `s` of an `R`-algebra is the determinant of `(*) s`. -/
noncomputable def norm : S →* R :=
LinearMap.det.comp (lmul R S).toRingHom.toMonoidHom
#align algebra.norm Algebra.norm
theorem norm_apply (x : S) : norm R x = LinearMap.det (lmul R S x) := rfl
#align algebra.norm_apply Algebra.norm_apply
theorem norm_eq_one_of_not_exists_basis (h : ¬∃ s : Finset S, Nonempty (Basis s R S)) (x : S) :
norm R x = 1 := by rw [norm_apply, LinearMap.det]; split_ifs <;> trivial
#align algebra.norm_eq_one_of_not_exists_basis Algebra.norm_eq_one_of_not_exists_basis
variable {R}
theorem norm_eq_one_of_not_module_finite (h : ¬Module.Finite R S) (x : S) : norm R x = 1 := by
refine norm_eq_one_of_not_exists_basis _ (mt ?_ h) _
rintro ⟨s, ⟨b⟩⟩
exact Module.Finite.of_basis b
#align algebra.norm_eq_one_of_not_module_finite Algebra.norm_eq_one_of_not_module_finite
-- Can't be a `simp` lemma because it depends on a choice of basis
theorem norm_eq_matrix_det [Fintype ι] [DecidableEq ι] (b : Basis ι R S) (s : S) :
norm R s = Matrix.det (Algebra.leftMulMatrix b s) := by
rw [norm_apply, ← LinearMap.det_toMatrix b, ← toMatrix_lmul_eq]; rfl
#align algebra.norm_eq_matrix_det Algebra.norm_eq_matrix_det
/-- If `x` is in the base ring `K`, then the norm is `x ^ [L : K]`. -/
theorem norm_algebraMap_of_basis [Fintype ι] (b : Basis ι R S) (x : R) :
norm R (algebraMap R S x) = x ^ Fintype.card ι := by
haveI := Classical.decEq ι
rw [norm_apply, ← det_toMatrix b, lmul_algebraMap]
convert @det_diagonal _ _ _ _ _ fun _ : ι => x
· ext (i j); rw [toMatrix_lsmul]
· rw [Finset.prod_const, Finset.card_univ]
#align algebra.norm_algebra_map_of_basis Algebra.norm_algebraMap_of_basis
/-- If `x` is in the base field `K`, then the norm is `x ^ [L : K]`.
(If `L` is not finite-dimensional over `K`, then `norm = 1 = x ^ 0 = x ^ (finrank L K)`.)
-/
@[simp]
protected theorem norm_algebraMap {L : Type*} [Ring L] [Algebra K L] (x : K) :
norm K (algebraMap K L x) = x ^ finrank K L := by
by_cases H : ∃ s : Finset L, Nonempty (Basis s K L)
· rw [norm_algebraMap_of_basis H.choose_spec.some, finrank_eq_card_basis H.choose_spec.some]
· rw [norm_eq_one_of_not_exists_basis K H, finrank_eq_zero_of_not_exists_basis, pow_zero]
rintro ⟨s, ⟨b⟩⟩
exact H ⟨s, ⟨b⟩⟩
#align algebra.norm_algebra_map Algebra.norm_algebraMap
section EqProdRoots
/-- Given `pb : PowerBasis K S`, then the norm of `pb.gen` is
`(-1) ^ pb.dim * coeff (minpoly K pb.gen) 0`. -/
theorem PowerBasis.norm_gen_eq_coeff_zero_minpoly (pb : PowerBasis R S) :
norm R pb.gen = (-1) ^ pb.dim * coeff (minpoly R pb.gen) 0 := by
rw [norm_eq_matrix_det pb.basis, det_eq_sign_charpoly_coeff, charpoly_leftMulMatrix,
Fintype.card_fin]
#align algebra.power_basis.norm_gen_eq_coeff_zero_minpoly Algebra.PowerBasis.norm_gen_eq_coeff_zero_minpoly
/-- Given `pb : PowerBasis R S`, then the norm of `pb.gen` is
`((minpoly R pb.gen).aroots F).prod`. -/
theorem PowerBasis.norm_gen_eq_prod_roots [Algebra R F] (pb : PowerBasis R S)
(hf : (minpoly R pb.gen).Splits (algebraMap R F)) :
algebraMap R F (norm R pb.gen) = ((minpoly R pb.gen).aroots F).prod := by
haveI := Module.nontrivial R F
have := minpoly.monic pb.isIntegral_gen
rw [PowerBasis.norm_gen_eq_coeff_zero_minpoly, ← pb.natDegree_minpoly, RingHom.map_mul,
← coeff_map,
prod_roots_eq_coeff_zero_of_monic_of_split (this.map _) ((splits_id_iff_splits _).2 hf),
this.natDegree_map, map_pow, ← mul_assoc, ← mul_pow]
simp only [map_neg, _root_.map_one, neg_mul, neg_neg, one_pow, one_mul]
#align algebra.power_basis.norm_gen_eq_prod_roots Algebra.PowerBasis.norm_gen_eq_prod_roots
end EqProdRoots
section EqZeroIff
variable [Finite ι]
@[simp]
theorem norm_zero [Nontrivial S] [Module.Free R S] [Module.Finite R S] : norm R (0 : S) = 0 := by
nontriviality
rw [norm_apply, coe_lmul_eq_mul, map_zero, LinearMap.det_zero' (Module.Free.chooseBasis R S)]
#align algebra.norm_zero Algebra.norm_zero
@[simp]
| Mathlib/RingTheory/Norm.lean | 151 | 166 | theorem norm_eq_zero_iff [IsDomain R] [IsDomain S] [Module.Free R S] [Module.Finite R S] {x : S} :
norm R x = 0 ↔ x = 0 := by |
constructor
on_goal 1 => let b := Module.Free.chooseBasis R S
swap
· rintro rfl; exact norm_zero
· letI := Classical.decEq (Module.Free.ChooseBasisIndex R S)
rw [norm_eq_matrix_det b, ← Matrix.exists_mulVec_eq_zero_iff]
rintro ⟨v, v_ne, hv⟩
rw [← b.equivFun.apply_symm_apply v, b.equivFun_symm_apply, b.equivFun_apply,
leftMulMatrix_mulVec_repr] at hv
refine (mul_eq_zero.mp (b.ext_elem fun i => ?_)).resolve_right (show ∑ i, v i • b i ≠ 0 from ?_)
· simpa only [LinearEquiv.map_zero, Pi.zero_apply] using congr_fun hv i
· contrapose! v_ne with sum_eq
apply b.equivFun.symm.injective
rw [b.equivFun_symm_apply, sum_eq, LinearEquiv.map_zero]
|
/-
Copyright (c) 2017 Scott Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Stephen Morgan, Scott Morrison, Floris van Doorn
-/
import Mathlib.CategoryTheory.Functor.Const
import Mathlib.CategoryTheory.DiscreteCategory
import Mathlib.CategoryTheory.Yoneda
import Mathlib.CategoryTheory.Functor.ReflectsIso
#align_import category_theory.limits.cones from "leanprover-community/mathlib"@"740acc0e6f9adf4423f92a485d0456fc271482da"
/-!
# Cones and cocones
We define `Cone F`, a cone over a functor `F`,
and `F.cones : Cᵒᵖ ⥤ Type`, the functor associating to `X` the cones over `F` with cone point `X`.
A cone `c` is defined by specifying its cone point `c.pt` and a natural transformation `c.π`
from the constant `c.pt` valued functor to `F`.
We provide `c.w f : c.π.app j ≫ F.map f = c.π.app j'` for any `f : j ⟶ j'`
as a wrapper for `c.π.naturality f` avoiding unneeded identity morphisms.
We define `c.extend f`, where `c : cone F` and `f : Y ⟶ c.pt` for some other `Y`,
which replaces the cone point by `Y` and inserts `f` into each of the components of the cone.
Similarly we have `c.whisker F` producing a `Cone (E ⋙ F)`
We define morphisms of cones, and the category of cones.
We define `Cone.postcompose α : cone F ⥤ cone G` for `α` a natural transformation `F ⟶ G`.
And, of course, we dualise all this to cocones as well.
For more results about the category of cones, see `cone_category.lean`.
-/
-- morphism levels before object levels. See note [CategoryTheory universes].
universe v₁ v₂ v₃ v₄ u₁ u₂ u₃ u₄
open CategoryTheory
variable {J : Type u₁} [Category.{v₁} J]
variable {K : Type u₂} [Category.{v₂} K]
variable {C : Type u₃} [Category.{v₃} C]
variable {D : Type u₄} [Category.{v₄} D]
open CategoryTheory
open CategoryTheory.Category
open CategoryTheory.Functor
open Opposite
namespace CategoryTheory
namespace Functor
variable (F : J ⥤ C)
/-- If `F : J ⥤ C` then `F.cones` is the functor assigning to an object `X : C` the
type of natural transformations from the constant functor with value `X` to `F`.
An object representing this functor is a limit of `F`.
-/
@[simps!]
def cones : Cᵒᵖ ⥤ Type max u₁ v₃ :=
(const J).op ⋙ yoneda.obj F
#align category_theory.functor.cones CategoryTheory.Functor.cones
/-- If `F : J ⥤ C` then `F.cocones` is the functor assigning to an object `(X : C)`
the type of natural transformations from `F` to the constant functor with value `X`.
An object corepresenting this functor is a colimit of `F`.
-/
@[simps!]
def cocones : C ⥤ Type max u₁ v₃ :=
const J ⋙ coyoneda.obj (op F)
#align category_theory.functor.cocones CategoryTheory.Functor.cocones
end Functor
section
variable (J C)
/-- Functorially associated to each functor `J ⥤ C`, we have the `C`-presheaf consisting of
cones with a given cone point.
-/
@[simps!]
def cones : (J ⥤ C) ⥤ Cᵒᵖ ⥤ Type max u₁ v₃ where
obj := Functor.cones
map f := whiskerLeft (const J).op (yoneda.map f)
#align category_theory.cones CategoryTheory.cones
/-- Contravariantly associated to each functor `J ⥤ C`, we have the `C`-copresheaf consisting of
cocones with a given cocone point.
-/
@[simps!]
def cocones : (J ⥤ C)ᵒᵖ ⥤ C ⥤ Type max u₁ v₃ where
obj F := Functor.cocones (unop F)
map f := whiskerLeft (const J) (coyoneda.map f)
#align category_theory.cocones CategoryTheory.cocones
end
namespace Limits
section
/-- A `c : Cone F` is:
* an object `c.pt` and
* a natural transformation `c.π : c.pt ⟶ F` from the constant `c.pt` functor to `F`.
Example: if `J` is a category coming from a poset then the data required to make
a term of type `Cone F` is morphisms `πⱼ : c.pt ⟶ F j` for all `j : J` and,
for all `i ≤ j` in `J`, morphisms `πᵢⱼ : F i ⟶ F j` such that `πᵢ ≫ πᵢⱼ = πᵢ`.
`Cone F` is equivalent, via `cone.equiv` below, to `Σ X, F.cones.obj X`.
-/
structure Cone (F : J ⥤ C) where
/-- An object of `C` -/
pt : C
/-- A natural transformation from the constant functor at `X` to `F` -/
π : (const J).obj pt ⟶ F
#align category_theory.limits.cone CategoryTheory.Limits.Cone
set_option linter.uppercaseLean3 false in
#align category_theory.limits.cone.X CategoryTheory.Limits.Cone.pt
instance inhabitedCone (F : Discrete PUnit ⥤ C) : Inhabited (Cone F) :=
⟨{ pt := F.obj ⟨⟨⟩⟩
π := { app := fun ⟨⟨⟩⟩ => 𝟙 _
naturality := by
intro X Y f
match X, Y, f with
| .mk A, .mk B, .up g =>
aesop_cat
}
}⟩
#align category_theory.limits.inhabited_cone CategoryTheory.Limits.inhabitedCone
@[reassoc (attr := simp)]
theorem Cone.w {F : J ⥤ C} (c : Cone F) {j j' : J} (f : j ⟶ j') :
c.π.app j ≫ F.map f = c.π.app j' := by
rw [← c.π.naturality f]
apply id_comp
#align category_theory.limits.cone.w CategoryTheory.Limits.Cone.w
/-- A `c : Cocone F` is
* an object `c.pt` and
* a natural transformation `c.ι : F ⟶ c.pt` from `F` to the constant `c.pt` functor.
For example, if the source `J` of `F` is a partially ordered set, then to give
`c : Cocone F` is to give a collection of morphisms `ιⱼ : F j ⟶ c.pt` and, for
all `j ≤ k` in `J`, morphisms `ιⱼₖ : F j ⟶ F k` such that `Fⱼₖ ≫ Fₖ = Fⱼ` for all `j ≤ k`.
`Cocone F` is equivalent, via `Cone.equiv` below, to `Σ X, F.cocones.obj X`.
-/
structure Cocone (F : J ⥤ C) where
/-- An object of `C` -/
pt : C
/-- A natural transformation from `F` to the constant functor at `pt` -/
ι : F ⟶ (const J).obj pt
#align category_theory.limits.cocone CategoryTheory.Limits.Cocone
set_option linter.uppercaseLean3 false in
#align category_theory.limits.cocone.X CategoryTheory.Limits.Cocone.pt
instance inhabitedCocone (F : Discrete PUnit ⥤ C) : Inhabited (Cocone F) :=
⟨{ pt := F.obj ⟨⟨⟩⟩
ι := { app := fun ⟨⟨⟩⟩ => 𝟙 _
naturality := by
intro X Y f
match X, Y, f with
| .mk A, .mk B, .up g =>
aesop_cat
}
}⟩
#align category_theory.limits.inhabited_cocone CategoryTheory.Limits.inhabitedCocone
@[reassoc] -- @[simp] -- Porting note (#10618): simp can prove this
theorem Cocone.w {F : J ⥤ C} (c : Cocone F) {j j' : J} (f : j ⟶ j') :
F.map f ≫ c.ι.app j' = c.ι.app j := by
rw [c.ι.naturality f]
apply comp_id
#align category_theory.limits.cocone.w CategoryTheory.Limits.Cocone.w
attribute [simp 1001] Cocone.w_assoc
end
variable {F : J ⥤ C}
namespace Cone
/-- The isomorphism between a cone on `F` and an element of the functor `F.cones`. -/
@[simps!]
def equiv (F : J ⥤ C) : Cone F ≅ ΣX, F.cones.obj X where
hom c := ⟨op c.pt, c.π⟩
inv c :=
{ pt := c.1.unop
π := c.2 }
hom_inv_id := by
funext X
cases X
rfl
inv_hom_id := by
funext X
cases X
rfl
#align category_theory.limits.cone.equiv CategoryTheory.Limits.Cone.equiv
/-- A map to the vertex of a cone naturally induces a cone by composition. -/
@[simps]
def extensions (c : Cone F) : yoneda.obj c.pt ⋙ uliftFunctor.{u₁} ⟶ F.cones where
app X f := (const J).map f.down ≫ c.π
#align category_theory.limits.cone.extensions CategoryTheory.Limits.Cone.extensions
/-- A map to the vertex of a cone induces a cone by composition. -/
@[simps]
def extend (c : Cone F) {X : C} (f : X ⟶ c.pt) : Cone F :=
{ pt := X
π := c.extensions.app (op X) ⟨f⟩ }
#align category_theory.limits.cone.extend CategoryTheory.Limits.Cone.extend
/-- Whisker a cone by precomposition of a functor. -/
@[simps]
def whisker (E : K ⥤ J) (c : Cone F) : Cone (E ⋙ F) where
pt := c.pt
π := whiskerLeft E c.π
#align category_theory.limits.cone.whisker CategoryTheory.Limits.Cone.whisker
end Cone
namespace Cocone
/-- The isomorphism between a cocone on `F` and an element of the functor `F.cocones`. -/
def equiv (F : J ⥤ C) : Cocone F ≅ ΣX, F.cocones.obj X where
hom c := ⟨c.pt, c.ι⟩
inv c :=
{ pt := c.1
ι := c.2 }
hom_inv_id := by
funext X
cases X
rfl
inv_hom_id := by
funext X
cases X
rfl
#align category_theory.limits.cocone.equiv CategoryTheory.Limits.Cocone.equiv
/-- A map from the vertex of a cocone naturally induces a cocone by composition. -/
@[simps]
def extensions (c : Cocone F) : coyoneda.obj (op c.pt) ⋙ uliftFunctor.{u₁} ⟶ F.cocones where
app X f := c.ι ≫ (const J).map f.down
#align category_theory.limits.cocone.extensions CategoryTheory.Limits.Cocone.extensions
/-- A map from the vertex of a cocone induces a cocone by composition. -/
@[simps]
def extend (c : Cocone F) {Y : C} (f : c.pt ⟶ Y) : Cocone F where
pt := Y
ι := c.extensions.app Y ⟨f⟩
#align category_theory.limits.cocone.extend CategoryTheory.Limits.Cocone.extend
/-- Whisker a cocone by precomposition of a functor. See `whiskering` for a functorial
version.
-/
@[simps]
def whisker (E : K ⥤ J) (c : Cocone F) : Cocone (E ⋙ F) where
pt := c.pt
ι := whiskerLeft E c.ι
#align category_theory.limits.cocone.whisker CategoryTheory.Limits.Cocone.whisker
end Cocone
/-- A cone morphism between two cones for the same diagram is a morphism of the cone points which
commutes with the cone legs. -/
structure ConeMorphism (A B : Cone F) where
/-- A morphism between the two vertex objects of the cones -/
hom : A.pt ⟶ B.pt
/-- The triangle consisting of the two natural transformations and `hom` commutes -/
w : ∀ j : J, hom ≫ B.π.app j = A.π.app j := by aesop_cat
#align category_theory.limits.cone_morphism CategoryTheory.Limits.ConeMorphism
#align category_theory.limits.cone_morphism.w' CategoryTheory.Limits.ConeMorphism.w
attribute [reassoc (attr := simp)] ConeMorphism.w
instance inhabitedConeMorphism (A : Cone F) : Inhabited (ConeMorphism A A) :=
⟨{ hom := 𝟙 _ }⟩
#align category_theory.limits.inhabited_cone_morphism CategoryTheory.Limits.inhabitedConeMorphism
/-- The category of cones on a given diagram. -/
@[simps]
instance Cone.category : Category (Cone F) where
Hom A B := ConeMorphism A B
comp f g := { hom := f.hom ≫ g.hom }
id B := { hom := 𝟙 B.pt }
#align category_theory.limits.cone.category CategoryTheory.Limits.Cone.category
-- Porting note: if we do not have `simps` automatically generate the lemma for simplifying
-- the hom field of a category, we need to write the `ext` lemma in terms of the categorical
-- morphism, rather than the underlying structure.
@[ext]
theorem ConeMorphism.ext {c c' : Cone F} (f g : c ⟶ c') (w : f.hom = g.hom) : f = g := by
cases f
cases g
congr
namespace Cones
/-- To give an isomorphism between cones, it suffices to give an
isomorphism between their vertices which commutes with the cone
maps. -/
-- Porting note: `@[ext]` used to accept lemmas like this. Now we add an aesop rule
@[aesop apply safe (rule_sets := [CategoryTheory]), simps]
def ext {c c' : Cone F} (φ : c.pt ≅ c'.pt)
(w : ∀ j, c.π.app j = φ.hom ≫ c'.π.app j := by aesop_cat) : c ≅ c' where
hom := { hom := φ.hom }
inv :=
{ hom := φ.inv
w := fun j => φ.inv_comp_eq.mpr (w j) }
#align category_theory.limits.cones.ext CategoryTheory.Limits.Cones.ext
/-- Eta rule for cones. -/
@[simps!]
def eta (c : Cone F) : c ≅ ⟨c.pt, c.π⟩ :=
Cones.ext (Iso.refl _)
#align category_theory.limits.cones.eta CategoryTheory.Limits.Cones.eta
/-- Given a cone morphism whose object part is an isomorphism, produce an
isomorphism of cones.
-/
theorem cone_iso_of_hom_iso {K : J ⥤ C} {c d : Cone K} (f : c ⟶ d) [i : IsIso f.hom] : IsIso f :=
⟨⟨{ hom := inv f.hom
w := fun j => (asIso f.hom).inv_comp_eq.2 (f.w j).symm }, by aesop_cat⟩⟩
#align category_theory.limits.cones.cone_iso_of_hom_iso CategoryTheory.Limits.Cones.cone_iso_of_hom_iso
/-- There is a morphism from an extended cone to the original cone. -/
@[simps]
def extend (s : Cone F) {X : C} (f : X ⟶ s.pt) : s.extend f ⟶ s where
hom := f
/-- Extending a cone by the identity does nothing. -/
@[simps!]
def extendId (s : Cone F) : s.extend (𝟙 s.pt) ≅ s :=
Cones.ext (Iso.refl _)
/-- Extending a cone by a composition is the same as extending the cone twice. -/
@[simps!]
def extendComp (s : Cone F) {X Y : C} (f : X ⟶ Y) (g : Y ⟶ s.pt) :
s.extend (f ≫ g) ≅ (s.extend g).extend f :=
Cones.ext (Iso.refl _)
/-- A cone extended by an isomorphism is isomorphic to the original cone. -/
@[simps]
def extendIso (s : Cone F) {X : C} (f : X ≅ s.pt) : s.extend f.hom ≅ s where
hom := { hom := f.hom }
inv := { hom := f.inv }
instance {s : Cone F} {X : C} (f : X ⟶ s.pt) [IsIso f] : IsIso (Cones.extend s f) :=
⟨(extendIso s (asIso f)).inv, by aesop_cat⟩
/--
Functorially postcompose a cone for `F` by a natural transformation `F ⟶ G` to give a cone for `G`.
-/
@[simps]
def postcompose {G : J ⥤ C} (α : F ⟶ G) : Cone F ⥤ Cone G where
obj c :=
{ pt := c.pt
π := c.π ≫ α }
map f := { hom := f.hom }
#align category_theory.limits.cones.postcompose CategoryTheory.Limits.Cones.postcompose
/-- Postcomposing a cone by the composite natural transformation `α ≫ β` is the same as
postcomposing by `α` and then by `β`. -/
@[simps!]
def postcomposeComp {G H : J ⥤ C} (α : F ⟶ G) (β : G ⟶ H) :
postcompose (α ≫ β) ≅ postcompose α ⋙ postcompose β :=
NatIso.ofComponents fun s => Cones.ext (Iso.refl _)
#align category_theory.limits.cones.postcompose_comp CategoryTheory.Limits.Cones.postcomposeComp
/-- Postcomposing by the identity does not change the cone up to isomorphism. -/
@[simps!]
def postcomposeId : postcompose (𝟙 F) ≅ 𝟭 (Cone F) :=
NatIso.ofComponents fun s => Cones.ext (Iso.refl _)
#align category_theory.limits.cones.postcompose_id CategoryTheory.Limits.Cones.postcomposeId
/-- If `F` and `G` are naturally isomorphic functors, then they have equivalent categories of
cones.
-/
@[simps]
def postcomposeEquivalence {G : J ⥤ C} (α : F ≅ G) : Cone F ≌ Cone G where
functor := postcompose α.hom
inverse := postcompose α.inv
unitIso := NatIso.ofComponents fun s => Cones.ext (Iso.refl _)
counitIso := NatIso.ofComponents fun s => Cones.ext (Iso.refl _)
#align category_theory.limits.cones.postcompose_equivalence CategoryTheory.Limits.Cones.postcomposeEquivalence
/-- Whiskering on the left by `E : K ⥤ J` gives a functor from `Cone F` to `Cone (E ⋙ F)`.
-/
@[simps]
def whiskering (E : K ⥤ J) : Cone F ⥤ Cone (E ⋙ F) where
obj c := c.whisker E
map f := { hom := f.hom }
#align category_theory.limits.cones.whiskering CategoryTheory.Limits.Cones.whiskering
/-- Whiskering by an equivalence gives an equivalence between categories of cones.
-/
@[simps]
def whiskeringEquivalence (e : K ≌ J) : Cone F ≌ Cone (e.functor ⋙ F) where
functor := whiskering e.functor
inverse := whiskering e.inverse ⋙ postcompose (e.invFunIdAssoc F).hom
unitIso := NatIso.ofComponents fun s => Cones.ext (Iso.refl _)
counitIso :=
NatIso.ofComponents
fun s =>
Cones.ext (Iso.refl _)
(by
intro k
simpa [e.counit_app_functor] using s.w (e.unitInv.app k))
#align category_theory.limits.cones.whiskering_equivalence CategoryTheory.Limits.Cones.whiskeringEquivalence
/-- The categories of cones over `F` and `G` are equivalent if `F` and `G` are naturally isomorphic
(possibly after changing the indexing category by an equivalence).
-/
@[simps! functor inverse unitIso counitIso]
def equivalenceOfReindexing {G : K ⥤ C} (e : K ≌ J) (α : e.functor ⋙ F ≅ G) : Cone F ≌ Cone G :=
(whiskeringEquivalence e).trans (postcomposeEquivalence α)
#align category_theory.limits.cones.equivalence_of_reindexing CategoryTheory.Limits.Cones.equivalenceOfReindexing
section
variable (F)
/-- Forget the cone structure and obtain just the cone point. -/
@[simps]
def forget : Cone F ⥤ C where
obj t := t.pt
map f := f.hom
#align category_theory.limits.cones.forget CategoryTheory.Limits.Cones.forget
variable (G : C ⥤ D)
/-- A functor `G : C ⥤ D` sends cones over `F` to cones over `F ⋙ G` functorially. -/
@[simps]
def functoriality : Cone F ⥤ Cone (F ⋙ G) where
obj A :=
{ pt := G.obj A.pt
π :=
{ app := fun j => G.map (A.π.app j)
naturality := by intros; erw [← G.map_comp]; aesop_cat } }
map f :=
{ hom := G.map f.hom
w := fun j => by simp [-ConeMorphism.w, ← f.w j] }
#align category_theory.limits.cones.functoriality CategoryTheory.Limits.Cones.functoriality
instance functoriality_full [G.Full] [G.Faithful] : (functoriality F G).Full where
map_surjective t :=
⟨{ hom := G.preimage t.hom
w := fun j => G.map_injective (by simpa using t.w j) }, by aesop_cat⟩
#align category_theory.limits.cones.functoriality_full CategoryTheory.Limits.Cones.functoriality_full
instance functoriality_faithful [G.Faithful] : (Cones.functoriality F G).Faithful where
map_injective {_X} {_Y} f g h :=
ConeMorphism.ext f g <| G.map_injective <| congr_arg ConeMorphism.hom h
#align category_theory.limits.cones.functoriality_faithful CategoryTheory.Limits.Cones.functoriality_faithful
/-- If `e : C ≌ D` is an equivalence of categories, then `functoriality F e.functor` induces an
equivalence between cones over `F` and cones over `F ⋙ e.functor`.
-/
@[simps]
def functorialityEquivalence (e : C ≌ D) : Cone F ≌ Cone (F ⋙ e.functor) :=
let f : (F ⋙ e.functor) ⋙ e.inverse ≅ F :=
Functor.associator _ _ _ ≪≫ isoWhiskerLeft _ e.unitIso.symm ≪≫ Functor.rightUnitor _
{ functor := functoriality F e.functor
inverse := functoriality (F ⋙ e.functor) e.inverse ⋙ (postcomposeEquivalence f).functor
unitIso := NatIso.ofComponents fun c => Cones.ext (e.unitIso.app _)
counitIso := NatIso.ofComponents fun c => Cones.ext (e.counitIso.app _) }
#align category_theory.limits.cones.functoriality_equivalence CategoryTheory.Limits.Cones.functorialityEquivalence
/-- If `F` reflects isomorphisms, then `Cones.functoriality F` reflects isomorphisms
as well.
-/
instance reflects_cone_isomorphism (F : C ⥤ D) [F.ReflectsIsomorphisms] (K : J ⥤ C) :
(Cones.functoriality K F).ReflectsIsomorphisms := by
constructor
intro A B f _
haveI : IsIso (F.map f.hom) :=
(Cones.forget (K ⋙ F)).map_isIso ((Cones.functoriality K F).map f)
haveI := ReflectsIsomorphisms.reflects F f.hom
apply cone_iso_of_hom_iso
#align category_theory.limits.cones.reflects_cone_isomorphism CategoryTheory.Limits.Cones.reflects_cone_isomorphism
end
end Cones
/-- A cocone morphism between two cocones for the same diagram is a morphism of the cocone points
which commutes with the cocone legs. -/
structure CoconeMorphism (A B : Cocone F) where
/-- A morphism between the (co)vertex objects in `C` -/
hom : A.pt ⟶ B.pt
/-- The triangle made from the two natural transformations and `hom` commutes -/
w : ∀ j : J, A.ι.app j ≫ hom = B.ι.app j := by aesop_cat
#align category_theory.limits.cocone_morphism CategoryTheory.Limits.CoconeMorphism
#align category_theory.limits.cocone_morphism.w' CategoryTheory.Limits.CoconeMorphism.w
instance inhabitedCoconeMorphism (A : Cocone F) : Inhabited (CoconeMorphism A A) :=
⟨{ hom := 𝟙 _ }⟩
#align category_theory.limits.inhabited_cocone_morphism CategoryTheory.Limits.inhabitedCoconeMorphism
attribute [reassoc (attr := simp)] CoconeMorphism.w
@[simps]
instance Cocone.category : Category (Cocone F) where
Hom A B := CoconeMorphism A B
comp f g := { hom := f.hom ≫ g.hom }
id B := { hom := 𝟙 B.pt }
#align category_theory.limits.cocone.category CategoryTheory.Limits.Cocone.category
-- Porting note: if we do not have `simps` automatically generate the lemma for simplifying
-- the hom field of a category, we need to write the `ext` lemma in terms of the categorical
-- morphism, rather than the underlying structure.
@[ext]
| Mathlib/CategoryTheory/Limits/Cones.lean | 525 | 528 | theorem CoconeMorphism.ext {c c' : Cocone F} (f g : c ⟶ c') (w : f.hom = g.hom) : f = g := by |
cases f
cases g
congr
|
/-
Copyright (c) 2020 Kenji Nakagawa. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenji Nakagawa, Anne Baanen, Filippo A. E. Nuccio
-/
import Mathlib.Algebra.Algebra.Subalgebra.Pointwise
import Mathlib.AlgebraicGeometry.PrimeSpectrum.Maximal
import Mathlib.AlgebraicGeometry.PrimeSpectrum.Noetherian
import Mathlib.RingTheory.ChainOfDivisors
import Mathlib.RingTheory.DedekindDomain.Basic
import Mathlib.RingTheory.FractionalIdeal.Operations
#align_import ring_theory.dedekind_domain.ideal from "leanprover-community/mathlib"@"2bbc7e3884ba234309d2a43b19144105a753292e"
/-!
# Dedekind domains and ideals
In this file, we show a ring is a Dedekind domain iff all fractional ideals are invertible.
Then we prove some results on the unique factorization monoid structure of the ideals.
## Main definitions
- `IsDedekindDomainInv` alternatively defines a Dedekind domain as an integral domain where
every nonzero fractional ideal is invertible.
- `isDedekindDomainInv_iff` shows that this does note depend on the choice of field of
fractions.
- `IsDedekindDomain.HeightOneSpectrum` defines the type of nonzero prime ideals of `R`.
## Main results:
- `isDedekindDomain_iff_isDedekindDomainInv`
- `Ideal.uniqueFactorizationMonoid`
## Implementation notes
The definitions that involve a field of fractions choose a canonical field of fractions,
but are independent of that choice. The `..._iff` lemmas express this independence.
Often, definitions assume that Dedekind domains are not fields. We found it more practical
to add a `(h : ¬ IsField A)` assumption whenever this is explicitly needed.
## References
* [D. Marcus, *Number Fields*][marcus1977number]
* [J.W.S. Cassels, A. Frölich, *Algebraic Number Theory*][cassels1967algebraic]
* [J. Neukirch, *Algebraic Number Theory*][Neukirch1992]
## Tags
dedekind domain, dedekind ring
-/
variable (R A K : Type*) [CommRing R] [CommRing A] [Field K]
open scoped nonZeroDivisors Polynomial
section Inverse
namespace FractionalIdeal
variable {R₁ : Type*} [CommRing R₁] [IsDomain R₁] [Algebra R₁ K] [IsFractionRing R₁ K]
variable {I J : FractionalIdeal R₁⁰ K}
noncomputable instance : Inv (FractionalIdeal R₁⁰ K) := ⟨fun I => 1 / I⟩
theorem inv_eq : I⁻¹ = 1 / I := rfl
#align fractional_ideal.inv_eq FractionalIdeal.inv_eq
theorem inv_zero' : (0 : FractionalIdeal R₁⁰ K)⁻¹ = 0 := div_zero
#align fractional_ideal.inv_zero' FractionalIdeal.inv_zero'
theorem inv_nonzero {J : FractionalIdeal R₁⁰ K} (h : J ≠ 0) :
J⁻¹ = ⟨(1 : FractionalIdeal R₁⁰ K) / J, fractional_div_of_nonzero h⟩ := div_nonzero h
#align fractional_ideal.inv_nonzero FractionalIdeal.inv_nonzero
theorem coe_inv_of_nonzero {J : FractionalIdeal R₁⁰ K} (h : J ≠ 0) :
(↑J⁻¹ : Submodule R₁ K) = IsLocalization.coeSubmodule K ⊤ / (J : Submodule R₁ K) := by
simp_rw [inv_nonzero _ h, coe_one, coe_mk, IsLocalization.coeSubmodule_top]
#align fractional_ideal.coe_inv_of_nonzero FractionalIdeal.coe_inv_of_nonzero
variable {K}
theorem mem_inv_iff (hI : I ≠ 0) {x : K} : x ∈ I⁻¹ ↔ ∀ y ∈ I, x * y ∈ (1 : FractionalIdeal R₁⁰ K) :=
mem_div_iff_of_nonzero hI
#align fractional_ideal.mem_inv_iff FractionalIdeal.mem_inv_iff
theorem inv_anti_mono (hI : I ≠ 0) (hJ : J ≠ 0) (hIJ : I ≤ J) : J⁻¹ ≤ I⁻¹ := by
-- Porting note: in Lean3, introducing `x` would just give `x ∈ J⁻¹ → x ∈ I⁻¹`, but
-- in Lean4, it goes all the way down to the subtypes
intro x
simp only [val_eq_coe, mem_coe, mem_inv_iff hJ, mem_inv_iff hI]
exact fun h y hy => h y (hIJ hy)
#align fractional_ideal.inv_anti_mono FractionalIdeal.inv_anti_mono
theorem le_self_mul_inv {I : FractionalIdeal R₁⁰ K} (hI : I ≤ (1 : FractionalIdeal R₁⁰ K)) :
I ≤ I * I⁻¹ :=
le_self_mul_one_div hI
#align fractional_ideal.le_self_mul_inv FractionalIdeal.le_self_mul_inv
variable (K)
theorem coe_ideal_le_self_mul_inv (I : Ideal R₁) :
(I : FractionalIdeal R₁⁰ K) ≤ I * (I : FractionalIdeal R₁⁰ K)⁻¹ :=
le_self_mul_inv coeIdeal_le_one
#align fractional_ideal.coe_ideal_le_self_mul_inv FractionalIdeal.coe_ideal_le_self_mul_inv
/-- `I⁻¹` is the inverse of `I` if `I` has an inverse. -/
theorem right_inverse_eq (I J : FractionalIdeal R₁⁰ K) (h : I * J = 1) : J = I⁻¹ := by
have hI : I ≠ 0 := ne_zero_of_mul_eq_one I J h
suffices h' : I * (1 / I) = 1 from
congr_arg Units.inv <| @Units.ext _ _ (Units.mkOfMulEqOne _ _ h) (Units.mkOfMulEqOne _ _ h') rfl
apply le_antisymm
· apply mul_le.mpr _
intro x hx y hy
rw [mul_comm]
exact (mem_div_iff_of_nonzero hI).mp hy x hx
rw [← h]
apply mul_left_mono I
apply (le_div_iff_of_nonzero hI).mpr _
intro y hy x hx
rw [mul_comm]
exact mul_mem_mul hx hy
#align fractional_ideal.right_inverse_eq FractionalIdeal.right_inverse_eq
theorem mul_inv_cancel_iff {I : FractionalIdeal R₁⁰ K} : I * I⁻¹ = 1 ↔ ∃ J, I * J = 1 :=
⟨fun h => ⟨I⁻¹, h⟩, fun ⟨J, hJ⟩ => by rwa [← right_inverse_eq K I J hJ]⟩
#align fractional_ideal.mul_inv_cancel_iff FractionalIdeal.mul_inv_cancel_iff
theorem mul_inv_cancel_iff_isUnit {I : FractionalIdeal R₁⁰ K} : I * I⁻¹ = 1 ↔ IsUnit I :=
(mul_inv_cancel_iff K).trans isUnit_iff_exists_inv.symm
#align fractional_ideal.mul_inv_cancel_iff_is_unit FractionalIdeal.mul_inv_cancel_iff_isUnit
variable {K' : Type*} [Field K'] [Algebra R₁ K'] [IsFractionRing R₁ K']
@[simp]
theorem map_inv (I : FractionalIdeal R₁⁰ K) (h : K ≃ₐ[R₁] K') :
I⁻¹.map (h : K →ₐ[R₁] K') = (I.map h)⁻¹ := by rw [inv_eq, map_div, map_one, inv_eq]
#align fractional_ideal.map_inv FractionalIdeal.map_inv
open Submodule Submodule.IsPrincipal
@[simp]
theorem spanSingleton_inv (x : K) : (spanSingleton R₁⁰ x)⁻¹ = spanSingleton _ x⁻¹ :=
one_div_spanSingleton x
#align fractional_ideal.span_singleton_inv FractionalIdeal.spanSingleton_inv
-- @[simp] -- Porting note: not in simpNF form
theorem spanSingleton_div_spanSingleton (x y : K) :
spanSingleton R₁⁰ x / spanSingleton R₁⁰ y = spanSingleton R₁⁰ (x / y) := by
rw [div_spanSingleton, mul_comm, spanSingleton_mul_spanSingleton, div_eq_mul_inv]
#align fractional_ideal.span_singleton_div_span_singleton FractionalIdeal.spanSingleton_div_spanSingleton
theorem spanSingleton_div_self {x : K} (hx : x ≠ 0) :
spanSingleton R₁⁰ x / spanSingleton R₁⁰ x = 1 := by
rw [spanSingleton_div_spanSingleton, div_self hx, spanSingleton_one]
#align fractional_ideal.span_singleton_div_self FractionalIdeal.spanSingleton_div_self
theorem coe_ideal_span_singleton_div_self {x : R₁} (hx : x ≠ 0) :
(Ideal.span ({x} : Set R₁) : FractionalIdeal R₁⁰ K) / Ideal.span ({x} : Set R₁) = 1 := by
rw [coeIdeal_span_singleton,
spanSingleton_div_self K <|
(map_ne_zero_iff _ <| NoZeroSMulDivisors.algebraMap_injective R₁ K).mpr hx]
#align fractional_ideal.coe_ideal_span_singleton_div_self FractionalIdeal.coe_ideal_span_singleton_div_self
theorem spanSingleton_mul_inv {x : K} (hx : x ≠ 0) :
spanSingleton R₁⁰ x * (spanSingleton R₁⁰ x)⁻¹ = 1 := by
rw [spanSingleton_inv, spanSingleton_mul_spanSingleton, mul_inv_cancel hx, spanSingleton_one]
#align fractional_ideal.span_singleton_mul_inv FractionalIdeal.spanSingleton_mul_inv
theorem coe_ideal_span_singleton_mul_inv {x : R₁} (hx : x ≠ 0) :
(Ideal.span ({x} : Set R₁) : FractionalIdeal R₁⁰ K) *
(Ideal.span ({x} : Set R₁) : FractionalIdeal R₁⁰ K)⁻¹ = 1 := by
rw [coeIdeal_span_singleton,
spanSingleton_mul_inv K <|
(map_ne_zero_iff _ <| NoZeroSMulDivisors.algebraMap_injective R₁ K).mpr hx]
#align fractional_ideal.coe_ideal_span_singleton_mul_inv FractionalIdeal.coe_ideal_span_singleton_mul_inv
theorem spanSingleton_inv_mul {x : K} (hx : x ≠ 0) :
(spanSingleton R₁⁰ x)⁻¹ * spanSingleton R₁⁰ x = 1 := by
rw [mul_comm, spanSingleton_mul_inv K hx]
#align fractional_ideal.span_singleton_inv_mul FractionalIdeal.spanSingleton_inv_mul
theorem coe_ideal_span_singleton_inv_mul {x : R₁} (hx : x ≠ 0) :
(Ideal.span ({x} : Set R₁) : FractionalIdeal R₁⁰ K)⁻¹ * Ideal.span ({x} : Set R₁) = 1 := by
rw [mul_comm, coe_ideal_span_singleton_mul_inv K hx]
#align fractional_ideal.coe_ideal_span_singleton_inv_mul FractionalIdeal.coe_ideal_span_singleton_inv_mul
theorem mul_generator_self_inv {R₁ : Type*} [CommRing R₁] [Algebra R₁ K] [IsLocalization R₁⁰ K]
(I : FractionalIdeal R₁⁰ K) [Submodule.IsPrincipal (I : Submodule R₁ K)] (h : I ≠ 0) :
I * spanSingleton _ (generator (I : Submodule R₁ K))⁻¹ = 1 := by
-- Rewrite only the `I` that appears alone.
conv_lhs => congr; rw [eq_spanSingleton_of_principal I]
rw [spanSingleton_mul_spanSingleton, mul_inv_cancel, spanSingleton_one]
intro generator_I_eq_zero
apply h
rw [eq_spanSingleton_of_principal I, generator_I_eq_zero, spanSingleton_zero]
#align fractional_ideal.mul_generator_self_inv FractionalIdeal.mul_generator_self_inv
theorem invertible_of_principal (I : FractionalIdeal R₁⁰ K)
[Submodule.IsPrincipal (I : Submodule R₁ K)] (h : I ≠ 0) : I * I⁻¹ = 1 :=
mul_div_self_cancel_iff.mpr
⟨spanSingleton _ (generator (I : Submodule R₁ K))⁻¹, mul_generator_self_inv _ I h⟩
#align fractional_ideal.invertible_of_principal FractionalIdeal.invertible_of_principal
theorem invertible_iff_generator_nonzero (I : FractionalIdeal R₁⁰ K)
[Submodule.IsPrincipal (I : Submodule R₁ K)] :
I * I⁻¹ = 1 ↔ generator (I : Submodule R₁ K) ≠ 0 := by
constructor
· intro hI hg
apply ne_zero_of_mul_eq_one _ _ hI
rw [eq_spanSingleton_of_principal I, hg, spanSingleton_zero]
· intro hg
apply invertible_of_principal
rw [eq_spanSingleton_of_principal I]
intro hI
have := mem_spanSingleton_self R₁⁰ (generator (I : Submodule R₁ K))
rw [hI, mem_zero_iff] at this
contradiction
#align fractional_ideal.invertible_iff_generator_nonzero FractionalIdeal.invertible_iff_generator_nonzero
theorem isPrincipal_inv (I : FractionalIdeal R₁⁰ K) [Submodule.IsPrincipal (I : Submodule R₁ K)]
(h : I ≠ 0) : Submodule.IsPrincipal I⁻¹.1 := by
rw [val_eq_coe, isPrincipal_iff]
use (generator (I : Submodule R₁ K))⁻¹
have hI : I * spanSingleton _ (generator (I : Submodule R₁ K))⁻¹ = 1 :=
mul_generator_self_inv _ I h
exact (right_inverse_eq _ I (spanSingleton _ (generator (I : Submodule R₁ K))⁻¹) hI).symm
#align fractional_ideal.is_principal_inv FractionalIdeal.isPrincipal_inv
noncomputable instance : InvOneClass (FractionalIdeal R₁⁰ K) := { inv_one := div_one }
end FractionalIdeal
section IsDedekindDomainInv
variable [IsDomain A]
/-- A Dedekind domain is an integral domain such that every fractional ideal has an inverse.
This is equivalent to `IsDedekindDomain`.
In particular we provide a `fractional_ideal.comm_group_with_zero` instance,
assuming `IsDedekindDomain A`, which implies `IsDedekindDomainInv`. For **integral** ideals,
`IsDedekindDomain`(`_inv`) implies only `Ideal.cancelCommMonoidWithZero`.
-/
def IsDedekindDomainInv : Prop :=
∀ I ≠ (⊥ : FractionalIdeal A⁰ (FractionRing A)), I * I⁻¹ = 1
#align is_dedekind_domain_inv IsDedekindDomainInv
open FractionalIdeal
variable {R A K}
theorem isDedekindDomainInv_iff [Algebra A K] [IsFractionRing A K] :
IsDedekindDomainInv A ↔ ∀ I ≠ (⊥ : FractionalIdeal A⁰ K), I * I⁻¹ = 1 := by
let h : FractionalIdeal A⁰ (FractionRing A) ≃+* FractionalIdeal A⁰ K :=
FractionalIdeal.mapEquiv (FractionRing.algEquiv A K)
refine h.toEquiv.forall_congr (fun {x} => ?_)
rw [← h.toEquiv.apply_eq_iff_eq]
simp [h, IsDedekindDomainInv]
#align is_dedekind_domain_inv_iff isDedekindDomainInv_iff
theorem FractionalIdeal.adjoinIntegral_eq_one_of_isUnit [Algebra A K] [IsFractionRing A K] (x : K)
(hx : IsIntegral A x) (hI : IsUnit (adjoinIntegral A⁰ x hx)) : adjoinIntegral A⁰ x hx = 1 := by
set I := adjoinIntegral A⁰ x hx
have mul_self : I * I = I := by apply coeToSubmodule_injective; simp [I]
convert congr_arg (· * I⁻¹) mul_self <;>
simp only [(mul_inv_cancel_iff_isUnit K).mpr hI, mul_assoc, mul_one]
#align fractional_ideal.adjoin_integral_eq_one_of_is_unit FractionalIdeal.adjoinIntegral_eq_one_of_isUnit
namespace IsDedekindDomainInv
variable [Algebra A K] [IsFractionRing A K] (h : IsDedekindDomainInv A)
theorem mul_inv_eq_one {I : FractionalIdeal A⁰ K} (hI : I ≠ 0) : I * I⁻¹ = 1 :=
isDedekindDomainInv_iff.mp h I hI
#align is_dedekind_domain_inv.mul_inv_eq_one IsDedekindDomainInv.mul_inv_eq_one
theorem inv_mul_eq_one {I : FractionalIdeal A⁰ K} (hI : I ≠ 0) : I⁻¹ * I = 1 :=
(mul_comm _ _).trans (h.mul_inv_eq_one hI)
#align is_dedekind_domain_inv.inv_mul_eq_one IsDedekindDomainInv.inv_mul_eq_one
protected theorem isUnit {I : FractionalIdeal A⁰ K} (hI : I ≠ 0) : IsUnit I :=
isUnit_of_mul_eq_one _ _ (h.mul_inv_eq_one hI)
#align is_dedekind_domain_inv.is_unit IsDedekindDomainInv.isUnit
theorem isNoetherianRing : IsNoetherianRing A := by
refine isNoetherianRing_iff.mpr ⟨fun I : Ideal A => ?_⟩
by_cases hI : I = ⊥
· rw [hI]; apply Submodule.fg_bot
have hI : (I : FractionalIdeal A⁰ (FractionRing A)) ≠ 0 := coeIdeal_ne_zero.mpr hI
exact I.fg_of_isUnit (IsFractionRing.injective A (FractionRing A)) (h.isUnit hI)
#align is_dedekind_domain_inv.is_noetherian_ring IsDedekindDomainInv.isNoetherianRing
theorem integrallyClosed : IsIntegrallyClosed A := by
-- It suffices to show that for integral `x`,
-- `A[x]` (which is a fractional ideal) is in fact equal to `A`.
refine (isIntegrallyClosed_iff (FractionRing A)).mpr (fun {x hx} => ?_)
rw [← Set.mem_range, ← Algebra.mem_bot, ← Subalgebra.mem_toSubmodule, Algebra.toSubmodule_bot,
Submodule.one_eq_span, ← coe_spanSingleton A⁰ (1 : FractionRing A), spanSingleton_one, ←
FractionalIdeal.adjoinIntegral_eq_one_of_isUnit x hx (h.isUnit _)]
· exact mem_adjoinIntegral_self A⁰ x hx
· exact fun h => one_ne_zero (eq_zero_iff.mp h 1 (Algebra.adjoin A {x}).one_mem)
#align is_dedekind_domain_inv.integrally_closed IsDedekindDomainInv.integrallyClosed
open Ring
theorem dimensionLEOne : DimensionLEOne A := ⟨by
-- We're going to show that `P` is maximal because any (maximal) ideal `M`
-- that is strictly larger would be `⊤`.
rintro P P_ne hP
refine Ideal.isMaximal_def.mpr ⟨hP.ne_top, fun M hM => ?_⟩
-- We may assume `P` and `M` (as fractional ideals) are nonzero.
have P'_ne : (P : FractionalIdeal A⁰ (FractionRing A)) ≠ 0 := coeIdeal_ne_zero.mpr P_ne
have M'_ne : (M : FractionalIdeal A⁰ (FractionRing A)) ≠ 0 := coeIdeal_ne_zero.mpr hM.ne_bot
-- In particular, we'll show `M⁻¹ * P ≤ P`
suffices (M⁻¹ : FractionalIdeal A⁰ (FractionRing A)) * P ≤ P by
rw [eq_top_iff, ← coeIdeal_le_coeIdeal (FractionRing A), coeIdeal_top]
calc
(1 : FractionalIdeal A⁰ (FractionRing A)) = _ * _ * _ := ?_
_ ≤ _ * _ := mul_right_mono
((P : FractionalIdeal A⁰ (FractionRing A))⁻¹ * M : FractionalIdeal A⁰ (FractionRing A)) this
_ = M := ?_
· rw [mul_assoc, ← mul_assoc (P : FractionalIdeal A⁰ (FractionRing A)), h.mul_inv_eq_one P'_ne,
one_mul, h.inv_mul_eq_one M'_ne]
· rw [← mul_assoc (P : FractionalIdeal A⁰ (FractionRing A)), h.mul_inv_eq_one P'_ne, one_mul]
-- Suppose we have `x ∈ M⁻¹ * P`, then in fact `x = algebraMap _ _ y` for some `y`.
intro x hx
have le_one : (M⁻¹ : FractionalIdeal A⁰ (FractionRing A)) * P ≤ 1 := by
rw [← h.inv_mul_eq_one M'_ne]
exact mul_left_mono _ ((coeIdeal_le_coeIdeal (FractionRing A)).mpr hM.le)
obtain ⟨y, _hy, rfl⟩ := (mem_coeIdeal _).mp (le_one hx)
-- Since `M` is strictly greater than `P`, let `z ∈ M \ P`.
obtain ⟨z, hzM, hzp⟩ := SetLike.exists_of_lt hM
-- We have `z * y ∈ M * (M⁻¹ * P) = P`.
have zy_mem := mul_mem_mul (mem_coeIdeal_of_mem A⁰ hzM) hx
rw [← RingHom.map_mul, ← mul_assoc, h.mul_inv_eq_one M'_ne, one_mul] at zy_mem
obtain ⟨zy, hzy, zy_eq⟩ := (mem_coeIdeal A⁰).mp zy_mem
rw [IsFractionRing.injective A (FractionRing A) zy_eq] at hzy
-- But `P` is a prime ideal, so `z ∉ P` implies `y ∈ P`, as desired.
exact mem_coeIdeal_of_mem A⁰ (Or.resolve_left (hP.mem_or_mem hzy) hzp)⟩
#align is_dedekind_domain_inv.dimension_le_one IsDedekindDomainInv.dimensionLEOne
/-- Showing one side of the equivalence between the definitions
`IsDedekindDomainInv` and `IsDedekindDomain` of Dedekind domains. -/
theorem isDedekindDomain : IsDedekindDomain A :=
{ h.isNoetherianRing, h.dimensionLEOne, h.integrallyClosed with }
#align is_dedekind_domain_inv.is_dedekind_domain IsDedekindDomainInv.isDedekindDomain
end IsDedekindDomainInv
end IsDedekindDomainInv
variable [Algebra A K] [IsFractionRing A K]
variable {A K}
theorem one_mem_inv_coe_ideal [IsDomain A] {I : Ideal A} (hI : I ≠ ⊥) :
(1 : K) ∈ (I : FractionalIdeal A⁰ K)⁻¹ := by
rw [FractionalIdeal.mem_inv_iff (FractionalIdeal.coeIdeal_ne_zero.mpr hI)]
intro y hy
rw [one_mul]
exact FractionalIdeal.coeIdeal_le_one hy
-- #align fractional_ideal.one_mem_inv_coe_ideal FractionalIdeal.one_mem_inv_coe_ideal
/-- Specialization of `exists_primeSpectrum_prod_le_and_ne_bot_of_domain` to Dedekind domains:
Let `I : Ideal A` be a nonzero ideal, where `A` is a Dedekind domain that is not a field.
Then `exists_primeSpectrum_prod_le_and_ne_bot_of_domain` states we can find a product of prime
ideals that is contained within `I`. This lemma extends that result by making the product minimal:
let `M` be a maximal ideal that contains `I`, then the product including `M` is contained within `I`
and the product excluding `M` is not contained within `I`. -/
theorem exists_multiset_prod_cons_le_and_prod_not_le [IsDedekindDomain A] (hNF : ¬IsField A)
{I M : Ideal A} (hI0 : I ≠ ⊥) (hIM : I ≤ M) [hM : M.IsMaximal] :
∃ Z : Multiset (PrimeSpectrum A),
(M ::ₘ Z.map PrimeSpectrum.asIdeal).prod ≤ I ∧
¬Multiset.prod (Z.map PrimeSpectrum.asIdeal) ≤ I := by
-- Let `Z` be a minimal set of prime ideals such that their product is contained in `J`.
obtain ⟨Z₀, hZ₀⟩ := PrimeSpectrum.exists_primeSpectrum_prod_le_and_ne_bot_of_domain hNF hI0
obtain ⟨Z, ⟨hZI, hprodZ⟩, h_eraseZ⟩ :=
wellFounded_lt.has_min
{Z | (Z.map PrimeSpectrum.asIdeal).prod ≤ I ∧ (Z.map PrimeSpectrum.asIdeal).prod ≠ ⊥}
⟨Z₀, hZ₀.1, hZ₀.2⟩
obtain ⟨_, hPZ', hPM⟩ := hM.isPrime.multiset_prod_le.mp (hZI.trans hIM)
-- Then in fact there is a `P ∈ Z` with `P ≤ M`.
obtain ⟨P, hPZ, rfl⟩ := Multiset.mem_map.mp hPZ'
classical
have := Multiset.map_erase PrimeSpectrum.asIdeal PrimeSpectrum.ext P Z
obtain ⟨hP0, hZP0⟩ : P.asIdeal ≠ ⊥ ∧ ((Z.erase P).map PrimeSpectrum.asIdeal).prod ≠ ⊥ := by
rwa [Ne, ← Multiset.cons_erase hPZ', Multiset.prod_cons, Ideal.mul_eq_bot, not_or, ←
this] at hprodZ
-- By maximality of `P` and `M`, we have that `P ≤ M` implies `P = M`.
have hPM' := (P.IsPrime.isMaximal hP0).eq_of_le hM.ne_top hPM
subst hPM'
-- By minimality of `Z`, erasing `P` from `Z` is exactly what we need.
refine ⟨Z.erase P, ?_, ?_⟩
· convert hZI
rw [this, Multiset.cons_erase hPZ']
· refine fun h => h_eraseZ (Z.erase P) ⟨h, ?_⟩ (Multiset.erase_lt.mpr hPZ)
exact hZP0
#align exists_multiset_prod_cons_le_and_prod_not_le exists_multiset_prod_cons_le_and_prod_not_le
namespace FractionalIdeal
open Ideal
lemma not_inv_le_one_of_ne_bot [IsDedekindDomain A] {I : Ideal A}
(hI0 : I ≠ ⊥) (hI1 : I ≠ ⊤) : ¬(I⁻¹ : FractionalIdeal A⁰ K) ≤ 1 := by
have hNF : ¬IsField A := fun h ↦ letI := h.toField; (eq_bot_or_eq_top I).elim hI0 hI1
wlog hM : I.IsMaximal generalizing I
· rcases I.exists_le_maximal hI1 with ⟨M, hmax, hIM⟩
have hMbot : M ≠ ⊥ := (M.bot_lt_of_maximal hNF).ne'
refine mt (le_trans <| inv_anti_mono ?_ ?_ ?_) (this hMbot hmax.ne_top hmax) <;>
simpa only [coeIdeal_ne_zero, coeIdeal_le_coeIdeal]
have hI0 : ⊥ < I := I.bot_lt_of_maximal hNF
obtain ⟨⟨a, haI⟩, ha0⟩ := Submodule.nonzero_mem_of_bot_lt hI0
replace ha0 : a ≠ 0 := Subtype.coe_injective.ne ha0
let J : Ideal A := Ideal.span {a}
have hJ0 : J ≠ ⊥ := mt Ideal.span_singleton_eq_bot.mp ha0
have hJI : J ≤ I := I.span_singleton_le_iff_mem.2 haI
-- Then we can find a product of prime (hence maximal) ideals contained in `J`,
-- such that removing element `M` from the product is not contained in `J`.
obtain ⟨Z, hle, hnle⟩ := exists_multiset_prod_cons_le_and_prod_not_le hNF hJ0 hJI
-- Choose an element `b` of the product that is not in `J`.
obtain ⟨b, hbZ, hbJ⟩ := SetLike.not_le_iff_exists.mp hnle
have hnz_fa : algebraMap A K a ≠ 0 :=
mt ((injective_iff_map_eq_zero _).mp (IsFractionRing.injective A K) a) ha0
-- Then `b a⁻¹ : K` is in `M⁻¹` but not in `1`.
refine Set.not_subset.2 ⟨algebraMap A K b * (algebraMap A K a)⁻¹, (mem_inv_iff ?_).mpr ?_, ?_⟩
· exact coeIdeal_ne_zero.mpr hI0.ne'
· rintro y₀ hy₀
obtain ⟨y, h_Iy, rfl⟩ := (mem_coeIdeal _).mp hy₀
rw [mul_comm, ← mul_assoc, ← RingHom.map_mul]
have h_yb : y * b ∈ J := by
apply hle
rw [Multiset.prod_cons]
exact Submodule.smul_mem_smul h_Iy hbZ
rw [Ideal.mem_span_singleton'] at h_yb
rcases h_yb with ⟨c, hc⟩
rw [← hc, RingHom.map_mul, mul_assoc, mul_inv_cancel hnz_fa, mul_one]
apply coe_mem_one
· refine mt (mem_one_iff _).mp ?_
rintro ⟨x', h₂_abs⟩
rw [← div_eq_mul_inv, eq_div_iff_mul_eq hnz_fa, ← RingHom.map_mul] at h₂_abs
have := Ideal.mem_span_singleton'.mpr ⟨x', IsFractionRing.injective A K h₂_abs⟩
contradiction
theorem exists_not_mem_one_of_ne_bot [IsDedekindDomain A] {I : Ideal A} (hI0 : I ≠ ⊥)
(hI1 : I ≠ ⊤) : ∃ x ∈ (I⁻¹ : FractionalIdeal A⁰ K), x ∉ (1 : FractionalIdeal A⁰ K) :=
Set.not_subset.1 <| not_inv_le_one_of_ne_bot hI0 hI1
#align fractional_ideal.exists_not_mem_one_of_ne_bot FractionalIdeal.exists_not_mem_one_of_ne_bot
theorem mul_inv_cancel_of_le_one [h : IsDedekindDomain A] {I : Ideal A} (hI0 : I ≠ ⊥)
(hI : (I * (I : FractionalIdeal A⁰ K)⁻¹)⁻¹ ≤ 1) : I * (I : FractionalIdeal A⁰ K)⁻¹ = 1 := by
-- We'll show a contradiction with `exists_not_mem_one_of_ne_bot`:
-- `J⁻¹ = (I * I⁻¹)⁻¹` cannot have an element `x ∉ 1`, so it must equal `1`.
obtain ⟨J, hJ⟩ : ∃ J : Ideal A, (J : FractionalIdeal A⁰ K) = I * (I : FractionalIdeal A⁰ K)⁻¹ :=
le_one_iff_exists_coeIdeal.mp mul_one_div_le_one
by_cases hJ0 : J = ⊥
· subst hJ0
refine absurd ?_ hI0
rw [eq_bot_iff, ← coeIdeal_le_coeIdeal K, hJ]
exact coe_ideal_le_self_mul_inv K I
by_cases hJ1 : J = ⊤
· rw [← hJ, hJ1, coeIdeal_top]
exact (not_inv_le_one_of_ne_bot (K := K) hJ0 hJ1 (hJ ▸ hI)).elim
#align fractional_ideal.mul_inv_cancel_of_le_one FractionalIdeal.mul_inv_cancel_of_le_one
/-- Nonzero integral ideals in a Dedekind domain are invertible.
We will use this to show that nonzero fractional ideals are invertible,
and finally conclude that fractional ideals in a Dedekind domain form a group with zero.
-/
theorem coe_ideal_mul_inv [h : IsDedekindDomain A] (I : Ideal A) (hI0 : I ≠ ⊥) :
I * (I : FractionalIdeal A⁰ K)⁻¹ = 1 := by
-- We'll show `1 ≤ J⁻¹ = (I * I⁻¹)⁻¹ ≤ 1`.
apply mul_inv_cancel_of_le_one hI0
by_cases hJ0 : I * (I : FractionalIdeal A⁰ K)⁻¹ = 0
· rw [hJ0, inv_zero']; exact zero_le _
intro x hx
-- In particular, we'll show all `x ∈ J⁻¹` are integral.
suffices x ∈ integralClosure A K by
rwa [IsIntegrallyClosed.integralClosure_eq_bot, Algebra.mem_bot, Set.mem_range,
← mem_one_iff] at this
-- For that, we'll find a subalgebra that is f.g. as a module and contains `x`.
-- `A` is a noetherian ring, so we just need to find a subalgebra between `{x}` and `I⁻¹`.
rw [mem_integralClosure_iff_mem_fg]
have x_mul_mem : ∀ b ∈ (I⁻¹ : FractionalIdeal A⁰ K), x * b ∈ (I⁻¹ : FractionalIdeal A⁰ K) := by
intro b hb
rw [mem_inv_iff (coeIdeal_ne_zero.mpr hI0)]
dsimp only at hx
rw [val_eq_coe, mem_coe, mem_inv_iff hJ0] at hx
simp only [mul_assoc, mul_comm b] at hx ⊢
intro y hy
exact hx _ (mul_mem_mul hy hb)
-- It turns out the subalgebra consisting of all `p(x)` for `p : A[X]` works.
refine ⟨AlgHom.range (Polynomial.aeval x : A[X] →ₐ[A] K),
isNoetherian_submodule.mp (isNoetherian (I : FractionalIdeal A⁰ K)⁻¹) _ fun y hy => ?_,
⟨Polynomial.X, Polynomial.aeval_X x⟩⟩
obtain ⟨p, rfl⟩ := (AlgHom.mem_range _).mp hy
rw [Polynomial.aeval_eq_sum_range]
refine Submodule.sum_mem _ fun i hi => Submodule.smul_mem _ _ ?_
clear hi
induction' i with i ih
· rw [pow_zero]; exact one_mem_inv_coe_ideal hI0
· show x ^ i.succ ∈ (I⁻¹ : FractionalIdeal A⁰ K)
rw [pow_succ']; exact x_mul_mem _ ih
#align fractional_ideal.coe_ideal_mul_inv FractionalIdeal.coe_ideal_mul_inv
/-- Nonzero fractional ideals in a Dedekind domain are units.
This is also available as `_root_.mul_inv_cancel`, using the
`Semifield` instance defined below.
-/
protected theorem mul_inv_cancel [IsDedekindDomain A] {I : FractionalIdeal A⁰ K} (hne : I ≠ 0) :
I * I⁻¹ = 1 := by
obtain ⟨a, J, ha, hJ⟩ :
∃ (a : A) (aI : Ideal A), a ≠ 0 ∧ I = spanSingleton A⁰ (algebraMap A K a)⁻¹ * aI :=
exists_eq_spanSingleton_mul I
suffices h₂ : I * (spanSingleton A⁰ (algebraMap _ _ a) * (J : FractionalIdeal A⁰ K)⁻¹) = 1 by
rw [mul_inv_cancel_iff]
exact ⟨spanSingleton A⁰ (algebraMap _ _ a) * (J : FractionalIdeal A⁰ K)⁻¹, h₂⟩
subst hJ
rw [mul_assoc, mul_left_comm (J : FractionalIdeal A⁰ K), coe_ideal_mul_inv, mul_one,
spanSingleton_mul_spanSingleton, inv_mul_cancel, spanSingleton_one]
· exact mt ((injective_iff_map_eq_zero (algebraMap A K)).mp (IsFractionRing.injective A K) _) ha
· exact coeIdeal_ne_zero.mp (right_ne_zero_of_mul hne)
#align fractional_ideal.mul_inv_cancel FractionalIdeal.mul_inv_cancel
theorem mul_right_le_iff [IsDedekindDomain A] {J : FractionalIdeal A⁰ K} (hJ : J ≠ 0) :
∀ {I I'}, I * J ≤ I' * J ↔ I ≤ I' := by
intro I I'
constructor
· intro h
convert mul_right_mono J⁻¹ h <;> dsimp only <;>
rw [mul_assoc, FractionalIdeal.mul_inv_cancel hJ, mul_one]
· exact fun h => mul_right_mono J h
#align fractional_ideal.mul_right_le_iff FractionalIdeal.mul_right_le_iff
theorem mul_left_le_iff [IsDedekindDomain A] {J : FractionalIdeal A⁰ K} (hJ : J ≠ 0) {I I'} :
J * I ≤ J * I' ↔ I ≤ I' := by convert mul_right_le_iff hJ using 1; simp only [mul_comm]
#align fractional_ideal.mul_left_le_iff FractionalIdeal.mul_left_le_iff
theorem mul_right_strictMono [IsDedekindDomain A] {I : FractionalIdeal A⁰ K} (hI : I ≠ 0) :
StrictMono (· * I) :=
strictMono_of_le_iff_le fun _ _ => (mul_right_le_iff hI).symm
#align fractional_ideal.mul_right_strict_mono FractionalIdeal.mul_right_strictMono
theorem mul_left_strictMono [IsDedekindDomain A] {I : FractionalIdeal A⁰ K} (hI : I ≠ 0) :
StrictMono (I * ·) :=
strictMono_of_le_iff_le fun _ _ => (mul_left_le_iff hI).symm
#align fractional_ideal.mul_left_strict_mono FractionalIdeal.mul_left_strictMono
/-- This is also available as `_root_.div_eq_mul_inv`, using the
`Semifield` instance defined below.
-/
protected theorem div_eq_mul_inv [IsDedekindDomain A] (I J : FractionalIdeal A⁰ K) :
I / J = I * J⁻¹ := by
by_cases hJ : J = 0
· rw [hJ, div_zero, inv_zero', mul_zero]
refine le_antisymm ((mul_right_le_iff hJ).mp ?_) ((le_div_iff_mul_le hJ).mpr ?_)
· rw [mul_assoc, mul_comm J⁻¹, FractionalIdeal.mul_inv_cancel hJ, mul_one, mul_le]
intro x hx y hy
rw [mem_div_iff_of_nonzero hJ] at hx
exact hx y hy
rw [mul_assoc, mul_comm J⁻¹, FractionalIdeal.mul_inv_cancel hJ, mul_one]
#align fractional_ideal.div_eq_mul_inv FractionalIdeal.div_eq_mul_inv
end FractionalIdeal
/-- `IsDedekindDomain` and `IsDedekindDomainInv` are equivalent ways
to express that an integral domain is a Dedekind domain. -/
theorem isDedekindDomain_iff_isDedekindDomainInv [IsDomain A] :
IsDedekindDomain A ↔ IsDedekindDomainInv A :=
⟨fun _h _I hI => FractionalIdeal.mul_inv_cancel hI, fun h => h.isDedekindDomain⟩
#align is_dedekind_domain_iff_is_dedekind_domain_inv isDedekindDomain_iff_isDedekindDomainInv
end Inverse
section IsDedekindDomain
variable {R A}
variable [IsDedekindDomain A] [Algebra A K] [IsFractionRing A K]
open FractionalIdeal
open Ideal
noncomputable instance FractionalIdeal.semifield : Semifield (FractionalIdeal A⁰ K) where
__ := coeIdeal_injective.nontrivial
inv_zero := inv_zero' _
div_eq_mul_inv := FractionalIdeal.div_eq_mul_inv
mul_inv_cancel _ := FractionalIdeal.mul_inv_cancel
nnqsmul := _
#align fractional_ideal.semifield FractionalIdeal.semifield
/-- Fractional ideals have cancellative multiplication in a Dedekind domain.
Although this instance is a direct consequence of the instance
`FractionalIdeal.semifield`, we define this instance to provide
a computable alternative.
-/
instance FractionalIdeal.cancelCommMonoidWithZero :
CancelCommMonoidWithZero (FractionalIdeal A⁰ K) where
__ : CommSemiring (FractionalIdeal A⁰ K) := inferInstance
#align fractional_ideal.cancel_comm_monoid_with_zero FractionalIdeal.cancelCommMonoidWithZero
instance Ideal.cancelCommMonoidWithZero : CancelCommMonoidWithZero (Ideal A) :=
{ Function.Injective.cancelCommMonoidWithZero (coeIdealHom A⁰ (FractionRing A)) coeIdeal_injective
(RingHom.map_zero _) (RingHom.map_one _) (RingHom.map_mul _) (RingHom.map_pow _) with }
#align ideal.cancel_comm_monoid_with_zero Ideal.cancelCommMonoidWithZero
-- Porting note: Lean can infer all it needs by itself
instance Ideal.isDomain : IsDomain (Ideal A) := { }
#align ideal.is_domain Ideal.isDomain
/-- For ideals in a Dedekind domain, to divide is to contain. -/
theorem Ideal.dvd_iff_le {I J : Ideal A} : I ∣ J ↔ J ≤ I :=
⟨Ideal.le_of_dvd, fun h => by
by_cases hI : I = ⊥
· have hJ : J = ⊥ := by rwa [hI, ← eq_bot_iff] at h
rw [hI, hJ]
have hI' : (I : FractionalIdeal A⁰ (FractionRing A)) ≠ 0 := coeIdeal_ne_zero.mpr hI
have : (I : FractionalIdeal A⁰ (FractionRing A))⁻¹ * J ≤ 1 :=
le_trans (mul_left_mono (↑I)⁻¹ ((coeIdeal_le_coeIdeal _).mpr h))
(le_of_eq (inv_mul_cancel hI'))
obtain ⟨H, hH⟩ := le_one_iff_exists_coeIdeal.mp this
use H
refine coeIdeal_injective (show (J : FractionalIdeal A⁰ (FractionRing A)) = ↑(I * H) from ?_)
rw [coeIdeal_mul, hH, ← mul_assoc, mul_inv_cancel hI', one_mul]⟩
#align ideal.dvd_iff_le Ideal.dvd_iff_le
theorem Ideal.dvdNotUnit_iff_lt {I J : Ideal A} : DvdNotUnit I J ↔ J < I :=
⟨fun ⟨hI, H, hunit, hmul⟩ =>
lt_of_le_of_ne (Ideal.dvd_iff_le.mp ⟨H, hmul⟩)
(mt
(fun h =>
have : H = 1 := mul_left_cancel₀ hI (by rw [← hmul, h, mul_one])
show IsUnit H from this.symm ▸ isUnit_one)
hunit),
fun h =>
dvdNotUnit_of_dvd_of_not_dvd (Ideal.dvd_iff_le.mpr (le_of_lt h))
(mt Ideal.dvd_iff_le.mp (not_le_of_lt h))⟩
#align ideal.dvd_not_unit_iff_lt Ideal.dvdNotUnit_iff_lt
instance : WfDvdMonoid (Ideal A) where
wellFounded_dvdNotUnit := by
have : WellFounded ((· > ·) : Ideal A → Ideal A → Prop) :=
isNoetherian_iff_wellFounded.mp (isNoetherianRing_iff.mp IsDedekindRing.toIsNoetherian)
convert this
ext
rw [Ideal.dvdNotUnit_iff_lt]
instance Ideal.uniqueFactorizationMonoid : UniqueFactorizationMonoid (Ideal A) :=
{ irreducible_iff_prime := by
intro P
exact ⟨fun hirr => ⟨hirr.ne_zero, hirr.not_unit, fun I J => by
have : P.IsMaximal := by
refine ⟨⟨mt Ideal.isUnit_iff.mpr hirr.not_unit, ?_⟩⟩
intro J hJ
obtain ⟨_J_ne, H, hunit, P_eq⟩ := Ideal.dvdNotUnit_iff_lt.mpr hJ
exact Ideal.isUnit_iff.mp ((hirr.isUnit_or_isUnit P_eq).resolve_right hunit)
rw [Ideal.dvd_iff_le, Ideal.dvd_iff_le, Ideal.dvd_iff_le, SetLike.le_def, SetLike.le_def,
SetLike.le_def]
contrapose!
rintro ⟨⟨x, x_mem, x_not_mem⟩, ⟨y, y_mem, y_not_mem⟩⟩
exact
⟨x * y, Ideal.mul_mem_mul x_mem y_mem,
mt this.isPrime.mem_or_mem (not_or_of_not x_not_mem y_not_mem)⟩⟩, Prime.irreducible⟩ }
#align ideal.unique_factorization_monoid Ideal.uniqueFactorizationMonoid
instance Ideal.normalizationMonoid : NormalizationMonoid (Ideal A) :=
normalizationMonoidOfUniqueUnits
#align ideal.normalization_monoid Ideal.normalizationMonoid
@[simp]
theorem Ideal.dvd_span_singleton {I : Ideal A} {x : A} : I ∣ Ideal.span {x} ↔ x ∈ I :=
Ideal.dvd_iff_le.trans (Ideal.span_le.trans Set.singleton_subset_iff)
#align ideal.dvd_span_singleton Ideal.dvd_span_singleton
theorem Ideal.isPrime_of_prime {P : Ideal A} (h : Prime P) : IsPrime P := by
refine ⟨?_, fun hxy => ?_⟩
· rintro rfl
rw [← Ideal.one_eq_top] at h
exact h.not_unit isUnit_one
· simp only [← Ideal.dvd_span_singleton, ← Ideal.span_singleton_mul_span_singleton] at hxy ⊢
exact h.dvd_or_dvd hxy
#align ideal.is_prime_of_prime Ideal.isPrime_of_prime
theorem Ideal.prime_of_isPrime {P : Ideal A} (hP : P ≠ ⊥) (h : IsPrime P) : Prime P := by
refine ⟨hP, mt Ideal.isUnit_iff.mp h.ne_top, fun I J hIJ => ?_⟩
simpa only [Ideal.dvd_iff_le] using h.mul_le.mp (Ideal.le_of_dvd hIJ)
#align ideal.prime_of_is_prime Ideal.prime_of_isPrime
/-- In a Dedekind domain, the (nonzero) prime elements of the monoid with zero `Ideal A`
are exactly the prime ideals. -/
theorem Ideal.prime_iff_isPrime {P : Ideal A} (hP : P ≠ ⊥) : Prime P ↔ IsPrime P :=
⟨Ideal.isPrime_of_prime, Ideal.prime_of_isPrime hP⟩
#align ideal.prime_iff_is_prime Ideal.prime_iff_isPrime
/-- In a Dedekind domain, the prime ideals are the zero ideal together with the prime elements
of the monoid with zero `Ideal A`. -/
theorem Ideal.isPrime_iff_bot_or_prime {P : Ideal A} : IsPrime P ↔ P = ⊥ ∨ Prime P :=
⟨fun hp => (eq_or_ne P ⊥).imp_right fun hp0 => Ideal.prime_of_isPrime hp0 hp, fun hp =>
hp.elim (fun h => h.symm ▸ Ideal.bot_prime) Ideal.isPrime_of_prime⟩
#align ideal.is_prime_iff_bot_or_prime Ideal.isPrime_iff_bot_or_prime
@[simp]
theorem Ideal.prime_span_singleton_iff {a : A} : Prime (Ideal.span {a}) ↔ Prime a := by
rcases eq_or_ne a 0 with rfl | ha
· rw [Set.singleton_zero, span_zero, ← Ideal.zero_eq_bot, ← not_iff_not]
simp only [not_prime_zero, not_false_eq_true]
· have ha' : span {a} ≠ ⊥ := by simpa only [ne_eq, span_singleton_eq_bot] using ha
rw [Ideal.prime_iff_isPrime ha', Ideal.span_singleton_prime ha]
open Submodule.IsPrincipal in
theorem Ideal.prime_generator_of_prime {P : Ideal A} (h : Prime P) [P.IsPrincipal] :
Prime (generator P) :=
have : Ideal.IsPrime P := Ideal.isPrime_of_prime h
prime_generator_of_isPrime _ h.ne_zero
open UniqueFactorizationMonoid in
nonrec theorem Ideal.mem_normalizedFactors_iff {p I : Ideal A} (hI : I ≠ ⊥) :
p ∈ normalizedFactors I ↔ p.IsPrime ∧ I ≤ p := by
rw [← Ideal.dvd_iff_le]
by_cases hp : p = 0
· rw [← zero_eq_bot] at hI
simp only [hp, zero_not_mem_normalizedFactors, zero_dvd_iff, hI, false_iff, not_and,
not_false_eq_true, implies_true]
· rwa [mem_normalizedFactors_iff hI, prime_iff_isPrime]
theorem Ideal.pow_right_strictAnti (I : Ideal A) (hI0 : I ≠ ⊥) (hI1 : I ≠ ⊤) :
StrictAnti (I ^ · : ℕ → Ideal A) :=
strictAnti_nat_of_succ_lt fun e =>
Ideal.dvdNotUnit_iff_lt.mp ⟨pow_ne_zero _ hI0, I, mt isUnit_iff.mp hI1, pow_succ I e⟩
#align ideal.strict_anti_pow Ideal.pow_right_strictAnti
theorem Ideal.pow_lt_self (I : Ideal A) (hI0 : I ≠ ⊥) (hI1 : I ≠ ⊤) (e : ℕ) (he : 2 ≤ e) :
I ^ e < I := by
convert I.pow_right_strictAnti hI0 hI1 he
dsimp only
rw [pow_one]
#align ideal.pow_lt_self Ideal.pow_lt_self
theorem Ideal.exists_mem_pow_not_mem_pow_succ (I : Ideal A) (hI0 : I ≠ ⊥) (hI1 : I ≠ ⊤) (e : ℕ) :
∃ x ∈ I ^ e, x ∉ I ^ (e + 1) :=
SetLike.exists_of_lt (I.pow_right_strictAnti hI0 hI1 e.lt_succ_self)
#align ideal.exists_mem_pow_not_mem_pow_succ Ideal.exists_mem_pow_not_mem_pow_succ
open UniqueFactorizationMonoid
theorem Ideal.eq_prime_pow_of_succ_lt_of_le {P I : Ideal A} [P_prime : P.IsPrime] (hP : P ≠ ⊥)
{i : ℕ} (hlt : P ^ (i + 1) < I) (hle : I ≤ P ^ i) : I = P ^ i := by
refine le_antisymm hle ?_
have P_prime' := Ideal.prime_of_isPrime hP P_prime
have h1 : I ≠ ⊥ := (lt_of_le_of_lt bot_le hlt).ne'
have := pow_ne_zero i hP
have h3 := pow_ne_zero (i + 1) hP
rw [← Ideal.dvdNotUnit_iff_lt, dvdNotUnit_iff_normalizedFactors_lt_normalizedFactors h1 h3,
normalizedFactors_pow, normalizedFactors_irreducible P_prime'.irreducible,
Multiset.nsmul_singleton, Multiset.lt_replicate_succ] at hlt
rw [← Ideal.dvd_iff_le, dvd_iff_normalizedFactors_le_normalizedFactors, normalizedFactors_pow,
normalizedFactors_irreducible P_prime'.irreducible, Multiset.nsmul_singleton]
all_goals assumption
#align ideal.eq_prime_pow_of_succ_lt_of_le Ideal.eq_prime_pow_of_succ_lt_of_le
theorem Ideal.pow_succ_lt_pow {P : Ideal A} [P_prime : P.IsPrime] (hP : P ≠ ⊥) (i : ℕ) :
P ^ (i + 1) < P ^ i :=
lt_of_le_of_ne (Ideal.pow_le_pow_right (Nat.le_succ _))
(mt (pow_eq_pow_iff hP (mt Ideal.isUnit_iff.mp P_prime.ne_top)).mp i.succ_ne_self)
#align ideal.pow_succ_lt_pow Ideal.pow_succ_lt_pow
theorem Associates.le_singleton_iff (x : A) (n : ℕ) (I : Ideal A) :
Associates.mk I ^ n ≤ Associates.mk (Ideal.span {x}) ↔ x ∈ I ^ n := by
simp_rw [← Associates.dvd_eq_le, ← Associates.mk_pow, Associates.mk_dvd_mk,
Ideal.dvd_span_singleton]
#align associates.le_singleton_iff Associates.le_singleton_iff
variable {K}
lemma FractionalIdeal.le_inv_comm {I J : FractionalIdeal A⁰ K} (hI : I ≠ 0) (hJ : J ≠ 0) :
I ≤ J⁻¹ ↔ J ≤ I⁻¹ := by
rw [inv_eq, inv_eq, le_div_iff_mul_le hI, le_div_iff_mul_le hJ, mul_comm]
lemma FractionalIdeal.inv_le_comm {I J : FractionalIdeal A⁰ K} (hI : I ≠ 0) (hJ : J ≠ 0) :
I⁻¹ ≤ J ↔ J⁻¹ ≤ I := by
simpa using le_inv_comm (A := A) (K := K) (inv_ne_zero hI) (inv_ne_zero hJ)
open FractionalIdeal
/-- Strengthening of `IsLocalization.exist_integer_multiples`:
Let `J ≠ ⊤` be an ideal in a Dedekind domain `A`, and `f ≠ 0` a finite collection
of elements of `K = Frac(A)`, then we can multiply the elements of `f` by some `a : K`
to find a collection of elements of `A` that is not completely contained in `J`. -/
theorem Ideal.exist_integer_multiples_not_mem {J : Ideal A} (hJ : J ≠ ⊤) {ι : Type*} (s : Finset ι)
(f : ι → K) {j} (hjs : j ∈ s) (hjf : f j ≠ 0) :
∃ a : K,
(∀ i ∈ s, IsLocalization.IsInteger A (a * f i)) ∧
∃ i ∈ s, a * f i ∉ (J : FractionalIdeal A⁰ K) := by
-- Consider the fractional ideal `I` spanned by the `f`s.
let I : FractionalIdeal A⁰ K := spanFinset A s f
have hI0 : I ≠ 0 := spanFinset_ne_zero.mpr ⟨j, hjs, hjf⟩
-- We claim the multiplier `a` we're looking for is in `I⁻¹ \ (J / I)`.
suffices ↑J / I < I⁻¹ by
obtain ⟨_, a, hI, hpI⟩ := SetLike.lt_iff_le_and_exists.mp this
rw [mem_inv_iff hI0] at hI
refine ⟨a, fun i hi => ?_, ?_⟩
-- By definition, `a ∈ I⁻¹` multiplies elements of `I` into elements of `1`,
-- in other words, `a * f i` is an integer.
· exact (mem_one_iff _).mp (hI (f i) (Submodule.subset_span (Set.mem_image_of_mem f hi)))
· contrapose! hpI
-- And if all `a`-multiples of `I` are an element of `J`,
-- then `a` is actually an element of `J / I`, contradiction.
refine (mem_div_iff_of_nonzero hI0).mpr fun y hy => Submodule.span_induction hy ?_ ?_ ?_ ?_
· rintro _ ⟨i, hi, rfl⟩; exact hpI i hi
· rw [mul_zero]; exact Submodule.zero_mem _
· intro x y hx hy; rw [mul_add]; exact Submodule.add_mem _ hx hy
· intro b x hx; rw [mul_smul_comm]; exact Submodule.smul_mem _ b hx
-- To show the inclusion of `J / I` into `I⁻¹ = 1 / I`, note that `J < I`.
calc
↑J / I = ↑J * I⁻¹ := div_eq_mul_inv (↑J) I
_ < 1 * I⁻¹ := mul_right_strictMono (inv_ne_zero hI0) ?_
_ = I⁻¹ := one_mul _
rw [← coeIdeal_top]
-- And multiplying by `I⁻¹` is indeed strictly monotone.
exact
strictMono_of_le_iff_le (fun _ _ => (coeIdeal_le_coeIdeal K).symm)
(lt_top_iff_ne_top.mpr hJ)
#align ideal.exist_integer_multiples_not_mem Ideal.exist_integer_multiples_not_mem
section Gcd
namespace Ideal
/-! ### GCD and LCM of ideals in a Dedekind domain
We show that the gcd of two ideals in a Dedekind domain is just their supremum,
and the lcm is their infimum, and use this to instantiate `NormalizedGCDMonoid (Ideal A)`.
-/
@[simp]
| Mathlib/RingTheory/DedekindDomain/Ideal.lean | 841 | 855 | theorem sup_mul_inf (I J : Ideal A) : (I ⊔ J) * (I ⊓ J) = I * J := by |
letI := UniqueFactorizationMonoid.toNormalizedGCDMonoid (Ideal A)
have hgcd : gcd I J = I ⊔ J := by
rw [gcd_eq_normalize _ _, normalize_eq]
· rw [dvd_iff_le, sup_le_iff, ← dvd_iff_le, ← dvd_iff_le]
exact ⟨gcd_dvd_left _ _, gcd_dvd_right _ _⟩
· rw [dvd_gcd_iff, dvd_iff_le, dvd_iff_le]
simp
have hlcm : lcm I J = I ⊓ J := by
rw [lcm_eq_normalize _ _, normalize_eq]
· rw [lcm_dvd_iff, dvd_iff_le, dvd_iff_le]
simp
· rw [dvd_iff_le, le_inf_iff, ← dvd_iff_le, ← dvd_iff_le]
exact ⟨dvd_lcm_left _ _, dvd_lcm_right _ _⟩
rw [← hgcd, ← hlcm, associated_iff_eq.mp (gcd_mul_lcm _ _)]
|
/-
Copyright (c) 2020 Scott Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Scott Morrison
-/
import Mathlib.CategoryTheory.Comma.StructuredArrow
import Mathlib.CategoryTheory.IsConnected
import Mathlib.CategoryTheory.Limits.Preserves.Shapes.Terminal
import Mathlib.CategoryTheory.Limits.Shapes.Types
import Mathlib.CategoryTheory.Filtered.Basic
import Mathlib.CategoryTheory.Limits.Yoneda
import Mathlib.CategoryTheory.PUnit
#align_import category_theory.limits.final from "leanprover-community/mathlib"@"8a318021995877a44630c898d0b2bc376fceef3b"
/-!
# Final and initial functors
A functor `F : C ⥤ D` is final if for every `d : D`,
the comma category of morphisms `d ⟶ F.obj c` is connected.
Dually, a functor `F : C ⥤ D` is initial if for every `d : D`,
the comma category of morphisms `F.obj c ⟶ d` is connected.
We show that right adjoints are examples of final functors, while
left adjoints are examples of initial functors.
For final functors, we prove that the following three statements are equivalent:
1. `F : C ⥤ D` is final.
2. Every functor `G : D ⥤ E` has a colimit if and only if `F ⋙ G` does,
and these colimits are isomorphic via `colimit.pre G F`.
3. `colimit (F ⋙ coyoneda.obj (op d)) ≅ PUnit`.
Starting at 1. we show (in `coconesEquiv`) that
the categories of cocones over `G : D ⥤ E` and over `F ⋙ G` are equivalent.
(In fact, via an equivalence which does not change the cocone point.)
This readily implies 2., as `comp_hasColimit`, `hasColimit_of_comp`, and `colimitIso`.
From 2. we can specialize to `G = coyoneda.obj (op d)` to obtain 3., as `colimitCompCoyonedaIso`.
From 3., we prove 1. directly in `cofinal_of_colimit_comp_coyoneda_iso_pUnit`.
Dually, we prove that if a functor `F : C ⥤ D` is initial, then any functor `G : D ⥤ E` has a
limit if and only if `F ⋙ G` does, and these limits are isomorphic via `limit.pre G F`.
## Naming
There is some discrepancy in the literature about naming; some say 'cofinal' instead of 'final'.
The explanation for this is that the 'co' prefix here is *not* the usual category-theoretic one
indicating duality, but rather indicating the sense of "along with".
## See also
In `CategoryTheory.Filtered.Final` we give additional equivalent conditions in the case that
`C` is filtered.
## Future work
Dualise condition 3 above and the implications 2 ⇒ 3 and 3 ⇒ 1 to initial functors.
## References
* https://stacks.math.columbia.edu/tag/09WN
* https://ncatlab.org/nlab/show/final+functor
* Borceux, Handbook of Categorical Algebra I, Section 2.11.
(Note he reverses the roles of definition and main result relative to here!)
-/
noncomputable section
universe v v₁ v₂ v₃ u₁ u₂ u₃
namespace CategoryTheory
namespace Functor
open Opposite
open CategoryTheory.Limits
section ArbitraryUniverse
variable {C : Type u₁} [Category.{v₁} C]
variable {D : Type u₂} [Category.{v₂} D]
/--
A functor `F : C ⥤ D` is final if for every `d : D`, the comma category of morphisms `d ⟶ F.obj c`
is connected.
See <https://stacks.math.columbia.edu/tag/04E6>
-/
class Final (F : C ⥤ D) : Prop where
out (d : D) : IsConnected (StructuredArrow d F)
#align category_theory.functor.final CategoryTheory.Functor.Final
attribute [instance] Final.out
/-- A functor `F : C ⥤ D` is initial if for every `d : D`, the comma category of morphisms
`F.obj c ⟶ d` is connected.
-/
class Initial (F : C ⥤ D) : Prop where
out (d : D) : IsConnected (CostructuredArrow F d)
#align category_theory.functor.initial CategoryTheory.Functor.Initial
attribute [instance] Initial.out
instance final_op_of_initial (F : C ⥤ D) [Initial F] : Final F.op where
out d := isConnected_of_equivalent (costructuredArrowOpEquivalence F (unop d))
#align category_theory.functor.final_op_of_initial CategoryTheory.Functor.final_op_of_initial
instance initial_op_of_final (F : C ⥤ D) [Final F] : Initial F.op where
out d := isConnected_of_equivalent (structuredArrowOpEquivalence F (unop d))
#align category_theory.functor.initial_op_of_final CategoryTheory.Functor.initial_op_of_final
theorem final_of_initial_op (F : C ⥤ D) [Initial F.op] : Final F :=
{
out := fun d =>
@isConnected_of_isConnected_op _ _
(isConnected_of_equivalent (structuredArrowOpEquivalence F d).symm) }
#align category_theory.functor.final_of_initial_op CategoryTheory.Functor.final_of_initial_op
theorem initial_of_final_op (F : C ⥤ D) [Final F.op] : Initial F :=
{
out := fun d =>
@isConnected_of_isConnected_op _ _
(isConnected_of_equivalent (costructuredArrowOpEquivalence F d).symm) }
#align category_theory.functor.initial_of_final_op CategoryTheory.Functor.initial_of_final_op
/-- If a functor `R : D ⥤ C` is a right adjoint, it is final. -/
theorem final_of_adjunction {L : C ⥤ D} {R : D ⥤ C} (adj : L ⊣ R) : Final R :=
{ out := fun c =>
let u : StructuredArrow c R := StructuredArrow.mk (adj.unit.app c)
@zigzag_isConnected _ _ ⟨u⟩ fun f g =>
Relation.ReflTransGen.trans
(Relation.ReflTransGen.single
(show Zag f u from
Or.inr ⟨StructuredArrow.homMk ((adj.homEquiv c f.right).symm f.hom) (by simp [u])⟩))
(Relation.ReflTransGen.single
(show Zag u g from
Or.inl ⟨StructuredArrow.homMk ((adj.homEquiv c g.right).symm g.hom) (by simp [u])⟩)) }
#align category_theory.functor.final_of_adjunction CategoryTheory.Functor.final_of_adjunction
/-- If a functor `L : C ⥤ D` is a left adjoint, it is initial. -/
theorem initial_of_adjunction {L : C ⥤ D} {R : D ⥤ C} (adj : L ⊣ R) : Initial L :=
{ out := fun d =>
let u : CostructuredArrow L d := CostructuredArrow.mk (adj.counit.app d)
@zigzag_isConnected _ _ ⟨u⟩ fun f g =>
Relation.ReflTransGen.trans
(Relation.ReflTransGen.single
(show Zag f u from
Or.inl ⟨CostructuredArrow.homMk (adj.homEquiv f.left d f.hom) (by simp [u])⟩))
(Relation.ReflTransGen.single
(show Zag u g from
Or.inr ⟨CostructuredArrow.homMk (adj.homEquiv g.left d g.hom) (by simp [u])⟩)) }
#align category_theory.functor.initial_of_adjunction CategoryTheory.Functor.initial_of_adjunction
instance (priority := 100) final_of_isRightAdjoint (F : C ⥤ D) [IsRightAdjoint F] : Final F :=
final_of_adjunction (Adjunction.ofIsRightAdjoint F)
#align category_theory.functor.final_of_is_right_adjoint CategoryTheory.Functor.final_of_isRightAdjoint
instance (priority := 100) initial_of_isLeftAdjoint (F : C ⥤ D) [IsLeftAdjoint F] : Initial F :=
initial_of_adjunction (Adjunction.ofIsLeftAdjoint F)
#align category_theory.functor.initial_of_is_left_adjoint CategoryTheory.Functor.initial_of_isLeftAdjoint
theorem final_of_natIso {F F' : C ⥤ D} [Final F] (i : F ≅ F') : Final F' where
out _ := isConnected_of_equivalent (StructuredArrow.mapNatIso i)
theorem final_natIso_iff {F F' : C ⥤ D} (i : F ≅ F') : Final F ↔ Final F' :=
⟨fun _ => final_of_natIso i, fun _ => final_of_natIso i.symm⟩
theorem initial_of_natIso {F F' : C ⥤ D} [Initial F] (i : F ≅ F') : Initial F' where
out _ := isConnected_of_equivalent (CostructuredArrow.mapNatIso i)
theorem initial_natIso_iff {F F' : C ⥤ D} (i : F ≅ F') : Initial F ↔ Initial F' :=
⟨fun _ => initial_of_natIso i, fun _ => initial_of_natIso i.symm⟩
namespace Final
variable (F : C ⥤ D) [Final F]
instance (d : D) : Nonempty (StructuredArrow d F) :=
IsConnected.is_nonempty
variable {E : Type u₃} [Category.{v₃} E] (G : D ⥤ E)
/--
When `F : C ⥤ D` is cofinal, we denote by `lift F d` an arbitrary choice of object in `C` such that
there exists a morphism `d ⟶ F.obj (lift F d)`.
-/
def lift (d : D) : C :=
(Classical.arbitrary (StructuredArrow d F)).right
#align category_theory.functor.final.lift CategoryTheory.Functor.Final.lift
/-- When `F : C ⥤ D` is cofinal, we denote by `homToLift` an arbitrary choice of morphism
`d ⟶ F.obj (lift F d)`.
-/
def homToLift (d : D) : d ⟶ F.obj (lift F d) :=
(Classical.arbitrary (StructuredArrow d F)).hom
#align category_theory.functor.final.hom_to_lift CategoryTheory.Functor.Final.homToLift
/-- We provide an induction principle for reasoning about `lift` and `homToLift`.
We want to perform some construction (usually just a proof) about
the particular choices `lift F d` and `homToLift F d`,
it suffices to perform that construction for some other pair of choices
(denoted `X₀ : C` and `k₀ : d ⟶ F.obj X₀` below),
and to show how to transport such a construction
*both* directions along a morphism between such choices.
-/
def induction {d : D} (Z : ∀ (X : C) (_ : d ⟶ F.obj X), Sort*)
(h₁ :
∀ (X₁ X₂) (k₁ : d ⟶ F.obj X₁) (k₂ : d ⟶ F.obj X₂) (f : X₁ ⟶ X₂),
k₁ ≫ F.map f = k₂ → Z X₁ k₁ → Z X₂ k₂)
(h₂ :
∀ (X₁ X₂) (k₁ : d ⟶ F.obj X₁) (k₂ : d ⟶ F.obj X₂) (f : X₁ ⟶ X₂),
k₁ ≫ F.map f = k₂ → Z X₂ k₂ → Z X₁ k₁)
{X₀ : C} {k₀ : d ⟶ F.obj X₀} (z : Z X₀ k₀) : Z (lift F d) (homToLift F d) := by
apply Nonempty.some
apply
@isPreconnected_induction _ _ _ (fun Y : StructuredArrow d F => Z Y.right Y.hom) _ _
(StructuredArrow.mk k₀) z
· intro j₁ j₂ f a
fapply h₁ _ _ _ _ f.right _ a
convert f.w.symm
dsimp
simp
· intro j₁ j₂ f a
fapply h₂ _ _ _ _ f.right _ a
convert f.w.symm
dsimp
simp
#align category_theory.functor.final.induction CategoryTheory.Functor.Final.induction
variable {F G}
/-- Given a cocone over `F ⋙ G`, we can construct a `Cocone G` with the same cocone point.
-/
@[simps]
def extendCocone : Cocone (F ⋙ G) ⥤ Cocone G where
obj c :=
{ pt := c.pt
ι :=
{ app := fun X => G.map (homToLift F X) ≫ c.ι.app (lift F X)
naturality := fun X Y f => by
dsimp; simp
-- This would be true if we'd chosen `lift F X` to be `lift F Y`
-- and `homToLift F X` to be `f ≫ homToLift F Y`.
apply
induction F fun Z k =>
G.map f ≫ G.map (homToLift F Y) ≫ c.ι.app (lift F Y) = G.map k ≫ c.ι.app Z
· intro Z₁ Z₂ k₁ k₂ g a z
rw [← a, Functor.map_comp, Category.assoc, ← Functor.comp_map, c.w, z]
· intro Z₁ Z₂ k₁ k₂ g a z
rw [← a, Functor.map_comp, Category.assoc, ← Functor.comp_map, c.w] at z
rw [z]
· rw [← Functor.map_comp_assoc] } }
map f := { hom := f.hom }
#align category_theory.functor.final.extend_cocone CategoryTheory.Functor.Final.extendCocone
@[simp]
theorem colimit_cocone_comp_aux (s : Cocone (F ⋙ G)) (j : C) :
G.map (homToLift F (F.obj j)) ≫ s.ι.app (lift F (F.obj j)) = s.ι.app j := by
-- This point is that this would be true if we took `lift (F.obj j)` to just be `j`
-- and `homToLift (F.obj j)` to be `𝟙 (F.obj j)`.
apply induction F fun X k => G.map k ≫ s.ι.app X = (s.ι.app j : _)
· intro j₁ j₂ k₁ k₂ f w h
rw [← w]
rw [← s.w f] at h
simpa using h
· intro j₁ j₂ k₁ k₂ f w h
rw [← w] at h
rw [← s.w f]
simpa using h
· exact s.w (𝟙 _)
#align category_theory.functor.final.colimit_cocone_comp_aux CategoryTheory.Functor.Final.colimit_cocone_comp_aux
variable (F G)
/-- If `F` is cofinal,
the category of cocones on `F ⋙ G` is equivalent to the category of cocones on `G`,
for any `G : D ⥤ E`.
-/
@[simps]
def coconesEquiv : Cocone (F ⋙ G) ≌ Cocone G where
functor := extendCocone
inverse := Cocones.whiskering F
unitIso := NatIso.ofComponents fun c => Cocones.ext (Iso.refl _)
counitIso := NatIso.ofComponents fun c => Cocones.ext (Iso.refl _)
#align category_theory.functor.final.cocones_equiv CategoryTheory.Functor.Final.coconesEquiv
variable {G}
/-- When `F : C ⥤ D` is cofinal, and `t : Cocone G` for some `G : D ⥤ E`,
`t.whisker F` is a colimit cocone exactly when `t` is.
-/
def isColimitWhiskerEquiv (t : Cocone G) : IsColimit (t.whisker F) ≃ IsColimit t :=
IsColimit.ofCoconeEquiv (coconesEquiv F G).symm
#align category_theory.functor.final.is_colimit_whisker_equiv CategoryTheory.Functor.Final.isColimitWhiskerEquiv
/-- When `F` is cofinal, and `t : Cocone (F ⋙ G)`,
`extendCocone.obj t` is a colimit cocone exactly when `t` is.
-/
def isColimitExtendCoconeEquiv (t : Cocone (F ⋙ G)) :
IsColimit (extendCocone.obj t) ≃ IsColimit t :=
IsColimit.ofCoconeEquiv (coconesEquiv F G)
#align category_theory.functor.final.is_colimit_extend_cocone_equiv CategoryTheory.Functor.Final.isColimitExtendCoconeEquiv
/-- Given a colimit cocone over `G : D ⥤ E` we can construct a colimit cocone over `F ⋙ G`. -/
@[simps]
def colimitCoconeComp (t : ColimitCocone G) : ColimitCocone (F ⋙ G) where
cocone := _
isColimit := (isColimitWhiskerEquiv F _).symm t.isColimit
#align category_theory.functor.final.colimit_cocone_comp CategoryTheory.Functor.Final.colimitCoconeComp
instance (priority := 100) comp_hasColimit [HasColimit G] : HasColimit (F ⋙ G) :=
HasColimit.mk (colimitCoconeComp F (getColimitCocone G))
#align category_theory.functor.final.comp_has_colimit CategoryTheory.Functor.Final.comp_hasColimit
instance colimit_pre_isIso [HasColimit G] : IsIso (colimit.pre G F) := by
rw [colimit.pre_eq (colimitCoconeComp F (getColimitCocone G)) (getColimitCocone G)]
erw [IsColimit.desc_self]
dsimp
infer_instance
#align category_theory.functor.final.colimit_pre_is_iso CategoryTheory.Functor.Final.colimit_pre_isIso
section
variable (G)
/-- When `F : C ⥤ D` is cofinal, and `G : D ⥤ E` has a colimit, then `F ⋙ G` has a colimit also and
`colimit (F ⋙ G) ≅ colimit G`
https://stacks.math.columbia.edu/tag/04E7
-/
def colimitIso [HasColimit G] : colimit (F ⋙ G) ≅ colimit G :=
asIso (colimit.pre G F)
#align category_theory.functor.final.colimit_iso CategoryTheory.Functor.Final.colimitIso
end
/-- Given a colimit cocone over `F ⋙ G` we can construct a colimit cocone over `G`. -/
@[simps]
def colimitCoconeOfComp (t : ColimitCocone (F ⋙ G)) : ColimitCocone G where
cocone := extendCocone.obj t.cocone
isColimit := (isColimitExtendCoconeEquiv F _).symm t.isColimit
#align category_theory.functor.final.colimit_cocone_of_comp CategoryTheory.Functor.Final.colimitCoconeOfComp
/-- When `F` is cofinal, and `F ⋙ G` has a colimit, then `G` has a colimit also.
We can't make this an instance, because `F` is not determined by the goal.
(Even if this weren't a problem, it would cause a loop with `comp_hasColimit`.)
-/
theorem hasColimit_of_comp [HasColimit (F ⋙ G)] : HasColimit G :=
HasColimit.mk (colimitCoconeOfComp F (getColimitCocone (F ⋙ G)))
#align category_theory.functor.final.has_colimit_of_comp CategoryTheory.Functor.Final.hasColimit_of_comp
theorem hasColimitsOfShape_of_final [HasColimitsOfShape C E] : HasColimitsOfShape D E where
has_colimit := fun _ => hasColimit_of_comp F
section
-- Porting note: this instance does not seem to be found automatically
--attribute [local instance] hasColimit_of_comp
/-- When `F` is cofinal, and `F ⋙ G` has a colimit, then `G` has a colimit also and
`colimit (F ⋙ G) ≅ colimit G`
https://stacks.math.columbia.edu/tag/04E7
-/
def colimitIso' [HasColimit (F ⋙ G)] :
haveI : HasColimit G := hasColimit_of_comp F;
colimit (F ⋙ G) ≅ colimit G :=
haveI : HasColimit G := hasColimit_of_comp F;
asIso (colimit.pre G F)
#align category_theory.functor.final.colimit_iso' CategoryTheory.Functor.Final.colimitIso'
end
end Final
end ArbitraryUniverse
section LocallySmall
variable {C : Type v} [Category.{v} C] {D : Type u₁} [Category.{v} D] (F : C ⥤ D)
namespace Final
theorem zigzag_of_eqvGen_quot_rel {F : C ⥤ D} {d : D} {f₁ f₂ : ΣX, d ⟶ F.obj X}
(t : EqvGen (Types.Quot.Rel.{v, v} (F ⋙ coyoneda.obj (op d))) f₁ f₂) :
Zigzag (StructuredArrow.mk f₁.2) (StructuredArrow.mk f₂.2) := by
induction t with
| rel x y r =>
obtain ⟨f, w⟩ := r
fconstructor
swap
· fconstructor
left; fconstructor
exact StructuredArrow.homMk f
| refl => fconstructor
| symm x y _ ih =>
apply zigzag_symmetric
exact ih
| trans x y z _ _ ih₁ ih₂ =>
apply Relation.ReflTransGen.trans
· exact ih₁
· exact ih₂
#align category_theory.functor.final.zigzag_of_eqv_gen_quot_rel CategoryTheory.Functor.Final.zigzag_of_eqvGen_quot_rel
end Final
/-- If `colimit (F ⋙ coyoneda.obj (op d)) ≅ PUnit` for all `d : D`, then `F` is cofinal.
-/
| Mathlib/CategoryTheory/Limits/Final.lean | 411 | 427 | theorem cofinal_of_colimit_comp_coyoneda_iso_pUnit
(I : ∀ d, colimit (F ⋙ coyoneda.obj (op d)) ≅ PUnit) : Final F :=
⟨fun d => by
have : Nonempty (StructuredArrow d F) := by |
have := (I d).inv PUnit.unit
obtain ⟨j, y, rfl⟩ := Limits.Types.jointly_surjective'.{v, v} this
exact ⟨StructuredArrow.mk y⟩
apply zigzag_isConnected
rintro ⟨⟨⟨⟩⟩, X₁, f₁⟩ ⟨⟨⟨⟩⟩, X₂, f₂⟩
let y₁ := colimit.ι (F ⋙ coyoneda.obj (op d)) X₁ f₁
let y₂ := colimit.ι (F ⋙ coyoneda.obj (op d)) X₂ f₂
have e : y₁ = y₂ := by
apply (I d).toEquiv.injective
ext
have t := Types.colimit_eq.{v, v} e
clear e y₁ y₂
exact Final.zigzag_of_eqvGen_quot_rel t⟩
|
/-
Copyright (c) 2018 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Data.Multiset.FinsetOps
import Mathlib.Data.Multiset.Fold
#align_import data.multiset.lattice from "leanprover-community/mathlib"@"65a1391a0106c9204fe45bc73a039f056558cb83"
/-!
# Lattice operations on multisets
-/
namespace Multiset
variable {α : Type*}
/-! ### sup -/
section Sup
-- can be defined with just `[Bot α]` where some lemmas hold without requiring `[OrderBot α]`
variable [SemilatticeSup α] [OrderBot α]
/-- Supremum of a multiset: `sup {a, b, c} = a ⊔ b ⊔ c` -/
def sup (s : Multiset α) : α :=
s.fold (· ⊔ ·) ⊥
#align multiset.sup Multiset.sup
@[simp]
theorem sup_coe (l : List α) : sup (l : Multiset α) = l.foldr (· ⊔ ·) ⊥ :=
rfl
#align multiset.sup_coe Multiset.sup_coe
@[simp]
theorem sup_zero : (0 : Multiset α).sup = ⊥ :=
fold_zero _ _
#align multiset.sup_zero Multiset.sup_zero
@[simp]
theorem sup_cons (a : α) (s : Multiset α) : (a ::ₘ s).sup = a ⊔ s.sup :=
fold_cons_left _ _ _ _
#align multiset.sup_cons Multiset.sup_cons
@[simp]
theorem sup_singleton {a : α} : ({a} : Multiset α).sup = a := sup_bot_eq _
#align multiset.sup_singleton Multiset.sup_singleton
@[simp]
theorem sup_add (s₁ s₂ : Multiset α) : (s₁ + s₂).sup = s₁.sup ⊔ s₂.sup :=
Eq.trans (by simp [sup]) (fold_add _ _ _ _ _)
#align multiset.sup_add Multiset.sup_add
@[simp]
theorem sup_le {s : Multiset α} {a : α} : s.sup ≤ a ↔ ∀ b ∈ s, b ≤ a :=
Multiset.induction_on s (by simp)
(by simp (config := { contextual := true }) [or_imp, forall_and])
#align multiset.sup_le Multiset.sup_le
theorem le_sup {s : Multiset α} {a : α} (h : a ∈ s) : a ≤ s.sup :=
sup_le.1 le_rfl _ h
#align multiset.le_sup Multiset.le_sup
theorem sup_mono {s₁ s₂ : Multiset α} (h : s₁ ⊆ s₂) : s₁.sup ≤ s₂.sup :=
sup_le.2 fun _ hb => le_sup (h hb)
#align multiset.sup_mono Multiset.sup_mono
variable [DecidableEq α]
@[simp]
theorem sup_dedup (s : Multiset α) : (dedup s).sup = s.sup :=
fold_dedup_idem _ _ _
#align multiset.sup_dedup Multiset.sup_dedup
@[simp]
| Mathlib/Data/Multiset/Lattice.lean | 79 | 80 | theorem sup_ndunion (s₁ s₂ : Multiset α) : (ndunion s₁ s₂).sup = s₁.sup ⊔ s₂.sup := by |
rw [← sup_dedup, dedup_ext.2, sup_dedup, sup_add]; simp
|
/-
Copyright (c) 2022 Yuyang Zhao. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yuyang Zhao
-/
import Batteries.Classes.Order
namespace Batteries.PairingHeapImp
/--
A `Heap` is the nodes of the pairing heap.
Each node have two pointers: `child` going to the first child of this node,
and `sibling` goes to the next sibling of this tree.
So it actually encodes a forest where each node has children
`node.child`, `node.child.sibling`, `node.child.sibling.sibling`, etc.
Each edge in this forest denotes a `le a b` relation that has been checked, so
the root is smaller than everything else under it.
-/
inductive Heap (α : Type u) where
/-- An empty forest, which has depth `0`. -/
| nil : Heap α
/-- A forest consists of a root `a`, a forest `child` elements greater than `a`,
and another forest `sibling`. -/
| node (a : α) (child sibling : Heap α) : Heap α
deriving Repr
/-- `O(n)`. The number of elements in the heap. -/
def Heap.size : Heap α → Nat
| .nil => 0
| .node _ c s => c.size + 1 + s.size
/-- A node containing a single element `a`. -/
def Heap.singleton (a : α) : Heap α := .node a .nil .nil
/-- `O(1)`. Is the heap empty? -/
def Heap.isEmpty : Heap α → Bool
| .nil => true
| _ => false
/-- `O(1)`. Merge two heaps. Ignore siblings. -/
@[specialize] def Heap.merge (le : α → α → Bool) : Heap α → Heap α → Heap α
| .nil, .nil => .nil
| .nil, .node a₂ c₂ _ => .node a₂ c₂ .nil
| .node a₁ c₁ _, .nil => .node a₁ c₁ .nil
| .node a₁ c₁ _, .node a₂ c₂ _ =>
if le a₁ a₂ then .node a₁ (.node a₂ c₂ c₁) .nil else .node a₂ (.node a₁ c₁ c₂) .nil
/-- Auxiliary for `Heap.deleteMin`: merge the forest in pairs. -/
@[specialize] def Heap.combine (le : α → α → Bool) : Heap α → Heap α
| h₁@(.node _ _ h₂@(.node _ _ s)) => merge le (merge le h₁ h₂) (s.combine le)
| h => h
/-- `O(1)`. Get the smallest element in the heap, including the passed in value `a`. -/
@[inline] def Heap.headD (a : α) : Heap α → α
| .nil => a
| .node a _ _ => a
/-- `O(1)`. Get the smallest element in the heap, if it has an element. -/
@[inline] def Heap.head? : Heap α → Option α
| .nil => none
| .node a _ _ => some a
/-- Amortized `O(log n)`. Find and remove the the minimum element from the heap. -/
@[inline] def Heap.deleteMin (le : α → α → Bool) : Heap α → Option (α × Heap α)
| .nil => none
| .node a c _ => (a, combine le c)
/-- Amortized `O(log n)`. Get the tail of the pairing heap after removing the minimum element. -/
@[inline] def Heap.tail? (le : α → α → Bool) (h : Heap α) : Option (Heap α) :=
deleteMin le h |>.map (·.snd)
/-- Amortized `O(log n)`. Remove the minimum element of the heap. -/
@[inline] def Heap.tail (le : α → α → Bool) (h : Heap α) : Heap α :=
tail? le h |>.getD .nil
/-- A predicate says there is no more than one tree. -/
inductive Heap.NoSibling : Heap α → Prop
/-- An empty heap is no more than one tree. -/
| nil : NoSibling .nil
/-- Or there is exactly one tree. -/
| node (a c) : NoSibling (.node a c .nil)
instance : Decidable (Heap.NoSibling s) :=
match s with
| .nil => isTrue .nil
| .node a c .nil => isTrue (.node a c)
| .node _ _ (.node _ _ _) => isFalse nofun
theorem Heap.noSibling_merge (le) (s₁ s₂ : Heap α) :
(s₁.merge le s₂).NoSibling := by
unfold merge
(split <;> try split) <;> constructor
theorem Heap.noSibling_combine (le) (s : Heap α) :
(s.combine le).NoSibling := by
unfold combine; split
· exact noSibling_merge _ _ _
· match s with
| nil | node _ _ nil => constructor
| node _ _ (node _ _ s) => rename_i h; exact (h _ _ _ _ _ rfl).elim
theorem Heap.noSibling_deleteMin {s : Heap α} (eq : s.deleteMin le = some (a, s')) :
s'.NoSibling := by
cases s with cases eq | node a c => exact noSibling_combine _ _
theorem Heap.noSibling_tail? {s : Heap α} : s.tail? le = some s' →
s'.NoSibling := by
simp only [Heap.tail?]; intro eq
match eq₂ : s.deleteMin le, eq with
| some (a, tl), rfl => exact noSibling_deleteMin eq₂
theorem Heap.noSibling_tail (le) (s : Heap α) : (s.tail le).NoSibling := by
simp only [Heap.tail]
match eq : s.tail? le with
| none => cases s with cases eq | nil => constructor
| some tl => exact Heap.noSibling_tail? eq
theorem Heap.size_merge_node (le) (a₁ : α) (c₁ s₁ : Heap α) (a₂ : α) (c₂ s₂ : Heap α) :
(merge le (.node a₁ c₁ s₁) (.node a₂ c₂ s₂)).size = c₁.size + c₂.size + 2 := by
unfold merge; dsimp; split <;> simp_arith [size]
theorem Heap.size_merge (le) {s₁ s₂ : Heap α} (h₁ : s₁.NoSibling) (h₂ : s₂.NoSibling) :
(merge le s₁ s₂).size = s₁.size + s₂.size := by
match h₁, h₂ with
| .nil, .nil | .nil, .node _ _ | .node _ _, .nil => simp [size]
| .node _ _, .node _ _ => unfold merge; dsimp; split <;> simp_arith [size]
theorem Heap.size_combine (le) (s : Heap α) :
(s.combine le).size = s.size := by
unfold combine; split
· rename_i a₁ c₁ a₂ c₂ s
rw [size_merge le (noSibling_merge _ _ _) (noSibling_combine _ _),
size_merge_node, size_combine le s]
simp_arith [size]
· rfl
theorem Heap.size_deleteMin {s : Heap α} (h : s.NoSibling) (eq : s.deleteMin le = some (a, s')) :
s.size = s'.size + 1 := by
cases h with cases eq | node a c => rw [size_combine, size, size]
| .lake/packages/batteries/Batteries/Data/PairingHeap.lean | 142 | 146 | theorem Heap.size_tail? {s : Heap α} (h : s.NoSibling) : s.tail? le = some s' →
s.size = s'.size + 1 := by |
simp only [Heap.tail?]; intro eq
match eq₂ : s.deleteMin le, eq with
| some (a, tl), rfl => exact size_deleteMin h eq₂
|
/-
Copyright (c) 2022 Floris van Doorn. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Floris van Doorn, Patrick Massot
-/
import Mathlib.Algebra.GroupWithZero.Indicator
import Mathlib.Algebra.Module.Basic
import Mathlib.Topology.Separation
#align_import topology.support from "leanprover-community/mathlib"@"d90e4e186f1d18e375dcd4e5b5f6364b01cb3e46"
/-!
# The topological support of a function
In this file we define the topological support of a function `f`, `tsupport f`, as the closure of
the support of `f`.
Furthermore, we say that `f` has compact support if the topological support of `f` is compact.
## Main definitions
* `mulTSupport` & `tsupport`
* `HasCompactMulSupport` & `HasCompactSupport`
## Implementation Notes
* We write all lemmas for multiplicative functions, and use `@[to_additive]` to get the more common
additive versions.
* We do not put the definitions in the `Function` namespace, following many other topological
definitions that are in the root namespace (compare `Embedding` vs `Function.Embedding`).
-/
open Function Set Filter Topology
variable {X α α' β γ δ M E R : Type*}
section One
variable [One α] [TopologicalSpace X]
/-- The topological support of a function is the closure of its support, i.e. the closure of the
set of all elements where the function is not equal to 1. -/
@[to_additive " The topological support of a function is the closure of its support. i.e. the
closure of the set of all elements where the function is nonzero. "]
def mulTSupport (f : X → α) : Set X := closure (mulSupport f)
#align mul_tsupport mulTSupport
#align tsupport tsupport
@[to_additive]
theorem subset_mulTSupport (f : X → α) : mulSupport f ⊆ mulTSupport f :=
subset_closure
#align subset_mul_tsupport subset_mulTSupport
#align subset_tsupport subset_tsupport
@[to_additive]
theorem isClosed_mulTSupport (f : X → α) : IsClosed (mulTSupport f) :=
isClosed_closure
#align is_closed_mul_tsupport isClosed_mulTSupport
#align is_closed_tsupport isClosed_tsupport
@[to_additive]
theorem mulTSupport_eq_empty_iff {f : X → α} : mulTSupport f = ∅ ↔ f = 1 := by
rw [mulTSupport, closure_empty_iff, mulSupport_eq_empty_iff]
#align mul_tsupport_eq_empty_iff mulTSupport_eq_empty_iff
#align tsupport_eq_empty_iff tsupport_eq_empty_iff
@[to_additive]
theorem image_eq_one_of_nmem_mulTSupport {f : X → α} {x : X} (hx : x ∉ mulTSupport f) : f x = 1 :=
mulSupport_subset_iff'.mp (subset_mulTSupport f) x hx
#align image_eq_one_of_nmem_mul_tsupport image_eq_one_of_nmem_mulTSupport
#align image_eq_zero_of_nmem_tsupport image_eq_zero_of_nmem_tsupport
@[to_additive]
theorem range_subset_insert_image_mulTSupport (f : X → α) :
range f ⊆ insert 1 (f '' mulTSupport f) :=
(range_subset_insert_image_mulSupport f).trans <|
insert_subset_insert <| image_subset _ subset_closure
#align range_subset_insert_image_mul_tsupport range_subset_insert_image_mulTSupport
#align range_subset_insert_image_tsupport range_subset_insert_image_tsupport
@[to_additive]
theorem range_eq_image_mulTSupport_or (f : X → α) :
range f = f '' mulTSupport f ∨ range f = insert 1 (f '' mulTSupport f) :=
(wcovBy_insert _ _).eq_or_eq (image_subset_range _ _) (range_subset_insert_image_mulTSupport f)
#align range_eq_image_mul_tsupport_or range_eq_image_mulTSupport_or
#align range_eq_image_tsupport_or range_eq_image_tsupport_or
theorem tsupport_mul_subset_left {α : Type*} [MulZeroClass α] {f g : X → α} :
(tsupport fun x => f x * g x) ⊆ tsupport f :=
closure_mono (support_mul_subset_left _ _)
#align tsupport_mul_subset_left tsupport_mul_subset_left
theorem tsupport_mul_subset_right {α : Type*} [MulZeroClass α] {f g : X → α} :
(tsupport fun x => f x * g x) ⊆ tsupport g :=
closure_mono (support_mul_subset_right _ _)
#align tsupport_mul_subset_right tsupport_mul_subset_right
end One
theorem tsupport_smul_subset_left {M α} [TopologicalSpace X] [Zero M] [Zero α] [SMulWithZero M α]
(f : X → M) (g : X → α) : (tsupport fun x => f x • g x) ⊆ tsupport f :=
closure_mono <| support_smul_subset_left f g
#align tsupport_smul_subset_left tsupport_smul_subset_left
theorem tsupport_smul_subset_right {M α} [TopologicalSpace X] [Zero α] [SMulZeroClass M α]
(f : X → M) (g : X → α) : (tsupport fun x => f x • g x) ⊆ tsupport g :=
closure_mono <| support_smul_subset_right f g
@[to_additive]
theorem mulTSupport_mul [TopologicalSpace X] [Monoid α] {f g : X → α} :
(mulTSupport fun x ↦ f x * g x) ⊆ mulTSupport f ∪ mulTSupport g :=
closure_minimal
((mulSupport_mul f g).trans (union_subset_union (subset_mulTSupport _) (subset_mulTSupport _)))
(isClosed_closure.union isClosed_closure)
section
variable [TopologicalSpace α] [TopologicalSpace α']
variable [One β] [One γ] [One δ]
variable {g : β → γ} {f : α → β} {f₂ : α → γ} {m : β → γ → δ} {x : α}
@[to_additive]
theorem not_mem_mulTSupport_iff_eventuallyEq : x ∉ mulTSupport f ↔ f =ᶠ[𝓝 x] 1 := by
simp_rw [mulTSupport, mem_closure_iff_nhds, not_forall, not_nonempty_iff_eq_empty, exists_prop,
← disjoint_iff_inter_eq_empty, disjoint_mulSupport_iff, eventuallyEq_iff_exists_mem]
#align not_mem_mul_tsupport_iff_eventually_eq not_mem_mulTSupport_iff_eventuallyEq
#align not_mem_tsupport_iff_eventually_eq not_mem_tsupport_iff_eventuallyEq
@[to_additive]
theorem continuous_of_mulTSupport [TopologicalSpace β] {f : α → β}
(hf : ∀ x ∈ mulTSupport f, ContinuousAt f x) : Continuous f :=
continuous_iff_continuousAt.2 fun x => (em _).elim (hf x) fun hx =>
(@continuousAt_const _ _ _ _ _ 1).congr (not_mem_mulTSupport_iff_eventuallyEq.mp hx).symm
#align continuous_of_mul_tsupport continuous_of_mulTSupport
#align continuous_of_tsupport continuous_of_tsupport
end
/-! ## Functions with compact support -/
section CompactSupport
variable [TopologicalSpace α] [TopologicalSpace α']
variable [One β] [One γ] [One δ]
variable {g : β → γ} {f : α → β} {f₂ : α → γ} {m : β → γ → δ} {x : α}
/-- A function `f` *has compact multiplicative support* or is *compactly supported* if the closure
of the multiplicative support of `f` is compact. In a T₂ space this is equivalent to `f` being equal
to `1` outside a compact set. -/
@[to_additive " A function `f` *has compact support* or is *compactly supported* if the closure of
the support of `f` is compact. In a T₂ space this is equivalent to `f` being equal to `0` outside a
compact set. "]
def HasCompactMulSupport (f : α → β) : Prop :=
IsCompact (mulTSupport f)
#align has_compact_mul_support HasCompactMulSupport
#align has_compact_support HasCompactSupport
@[to_additive]
theorem hasCompactMulSupport_def : HasCompactMulSupport f ↔ IsCompact (closure (mulSupport f)) := by
rfl
#align has_compact_mul_support_def hasCompactMulSupport_def
#align has_compact_support_def hasCompactSupport_def
@[to_additive]
theorem exists_compact_iff_hasCompactMulSupport [R1Space α] :
(∃ K : Set α, IsCompact K ∧ ∀ x, x ∉ K → f x = 1) ↔ HasCompactMulSupport f := by
simp_rw [← nmem_mulSupport, ← mem_compl_iff, ← subset_def, compl_subset_compl,
hasCompactMulSupport_def, exists_isCompact_superset_iff]
#align exists_compact_iff_has_compact_mul_support exists_compact_iff_hasCompactMulSupport
#align exists_compact_iff_has_compact_support exists_compact_iff_hasCompactSupport
namespace HasCompactMulSupport
@[to_additive]
theorem intro [R1Space α] {K : Set α} (hK : IsCompact K)
(hfK : ∀ x, x ∉ K → f x = 1) : HasCompactMulSupport f :=
exists_compact_iff_hasCompactMulSupport.mp ⟨K, hK, hfK⟩
#align has_compact_mul_support.intro HasCompactMulSupport.intro
#align has_compact_support.intro HasCompactSupport.intro
@[to_additive]
theorem intro' {K : Set α} (hK : IsCompact K) (h'K : IsClosed K)
(hfK : ∀ x, x ∉ K → f x = 1) : HasCompactMulSupport f := by
have : mulTSupport f ⊆ K := by
rw [← h'K.closure_eq]
apply closure_mono (mulSupport_subset_iff'.2 hfK)
exact IsCompact.of_isClosed_subset hK ( isClosed_mulTSupport f) this
@[to_additive]
theorem of_mulSupport_subset_isCompact [R1Space α] {K : Set α}
(hK : IsCompact K) (h : mulSupport f ⊆ K) : HasCompactMulSupport f :=
hK.closure_of_subset h
@[to_additive]
theorem isCompact (hf : HasCompactMulSupport f) : IsCompact (mulTSupport f) :=
hf
#align has_compact_mul_support.is_compact HasCompactMulSupport.isCompact
#align has_compact_support.is_compact HasCompactSupport.isCompact
@[to_additive]
theorem _root_.hasCompactMulSupport_iff_eventuallyEq :
HasCompactMulSupport f ↔ f =ᶠ[coclosedCompact α] 1 :=
mem_coclosedCompact_iff.symm
#align has_compact_mul_support_iff_eventually_eq hasCompactMulSupport_iff_eventuallyEq
#align has_compact_support_iff_eventually_eq hasCompactSupport_iff_eventuallyEq
@[to_additive]
theorem _root_.isCompact_range_of_mulSupport_subset_isCompact [TopologicalSpace β]
(hf : Continuous f) {k : Set α} (hk : IsCompact k) (h'f : mulSupport f ⊆ k) :
IsCompact (range f) := by
cases' range_eq_image_or_of_mulSupport_subset h'f with h2 h2 <;> rw [h2]
exacts [hk.image hf, (hk.image hf).insert 1]
@[to_additive]
theorem isCompact_range [TopologicalSpace β] (h : HasCompactMulSupport f)
(hf : Continuous f) : IsCompact (range f) :=
isCompact_range_of_mulSupport_subset_isCompact hf h (subset_mulTSupport f)
#align has_compact_mul_support.is_compact_range HasCompactMulSupport.isCompact_range
#align has_compact_support.is_compact_range HasCompactSupport.isCompact_range
@[to_additive]
theorem mono' {f' : α → γ} (hf : HasCompactMulSupport f)
(hff' : mulSupport f' ⊆ mulTSupport f) : HasCompactMulSupport f' :=
IsCompact.of_isClosed_subset hf isClosed_closure <| closure_minimal hff' isClosed_closure
#align has_compact_mul_support.mono' HasCompactMulSupport.mono'
#align has_compact_support.mono' HasCompactSupport.mono'
@[to_additive]
theorem mono {f' : α → γ} (hf : HasCompactMulSupport f)
(hff' : mulSupport f' ⊆ mulSupport f) : HasCompactMulSupport f' :=
hf.mono' <| hff'.trans subset_closure
#align has_compact_mul_support.mono HasCompactMulSupport.mono
#align has_compact_support.mono HasCompactSupport.mono
@[to_additive]
theorem comp_left (hf : HasCompactMulSupport f) (hg : g 1 = 1) :
HasCompactMulSupport (g ∘ f) :=
hf.mono <| mulSupport_comp_subset hg f
#align has_compact_mul_support.comp_left HasCompactMulSupport.comp_left
#align has_compact_support.comp_left HasCompactSupport.comp_left
@[to_additive]
theorem _root_.hasCompactMulSupport_comp_left (hg : ∀ {x}, g x = 1 ↔ x = 1) :
HasCompactMulSupport (g ∘ f) ↔ HasCompactMulSupport f := by
simp_rw [hasCompactMulSupport_def, mulSupport_comp_eq g (@hg) f]
#align has_compact_mul_support_comp_left hasCompactMulSupport_comp_left
#align has_compact_support_comp_left hasCompactSupport_comp_left
@[to_additive]
theorem comp_closedEmbedding (hf : HasCompactMulSupport f) {g : α' → α}
(hg : ClosedEmbedding g) : HasCompactMulSupport (f ∘ g) := by
rw [hasCompactMulSupport_def, Function.mulSupport_comp_eq_preimage]
refine IsCompact.of_isClosed_subset (hg.isCompact_preimage hf) isClosed_closure ?_
rw [hg.toEmbedding.closure_eq_preimage_closure_image]
exact preimage_mono (closure_mono <| image_preimage_subset _ _)
#align has_compact_mul_support.comp_closed_embedding HasCompactMulSupport.comp_closedEmbedding
#align has_compact_support.comp_closed_embedding HasCompactSupport.comp_closedEmbedding
@[to_additive]
theorem comp₂_left (hf : HasCompactMulSupport f)
(hf₂ : HasCompactMulSupport f₂) (hm : m 1 1 = 1) :
HasCompactMulSupport fun x => m (f x) (f₂ x) := by
rw [hasCompactMulSupport_iff_eventuallyEq] at hf hf₂ ⊢
#adaptation_note /-- `nightly-2024-03-11`
If we *either* (1) remove the type annotations on the
binders in the following `fun` or (2) revert `simp only` to `simp_rw`, `to_additive` fails
because an `OfNat.ofNat 1` is not replaced with `0`. Notably, as of this nightly, what used to
look like `OfNat.ofNat (nat_lit 1) x` in the proof term now looks like
`OfNat.ofNat (OfNat.ofNat (α := ℕ) (nat_lit 1)) x`, and this seems to trip up `to_additive`.
-/
filter_upwards [hf, hf₂] using fun x (hx : f x = (1 : α → β) x) (hx₂ : f₂ x = (1 : α → γ) x) => by
simp only [hx, hx₂, Pi.one_apply, hm]
#align has_compact_mul_support.comp₂_left HasCompactMulSupport.comp₂_left
#align has_compact_support.comp₂_left HasCompactSupport.comp₂_left
@[to_additive]
lemma isCompact_preimage [TopologicalSpace β]
(h'f : HasCompactMulSupport f) (hf : Continuous f) {k : Set β} (hk : IsClosed k)
(h'k : 1 ∉ k) : IsCompact (f ⁻¹' k) := by
apply IsCompact.of_isClosed_subset h'f (hk.preimage hf) (fun x hx ↦ ?_)
apply subset_mulTSupport
aesop
variable [T2Space α'] (hf : HasCompactMulSupport f) {g : α → α'} (cont : Continuous g)
@[to_additive]
theorem mulTSupport_extend_one_subset :
mulTSupport (g.extend f 1) ⊆ g '' mulTSupport f :=
(hf.image cont).isClosed.closure_subset_iff.mpr <|
mulSupport_extend_one_subset.trans (image_subset g subset_closure)
@[to_additive]
theorem extend_one : HasCompactMulSupport (g.extend f 1) :=
HasCompactMulSupport.of_mulSupport_subset_isCompact (hf.image cont)
(subset_closure.trans <| hf.mulTSupport_extend_one_subset cont)
@[to_additive]
theorem mulTSupport_extend_one (inj : g.Injective) :
mulTSupport (g.extend f 1) = g '' mulTSupport f :=
(hf.mulTSupport_extend_one_subset cont).antisymm <|
(image_closure_subset_closure_image cont).trans
(closure_mono (mulSupport_extend_one inj).superset)
@[to_additive]
theorem continuous_extend_one [TopologicalSpace β] {U : Set α'} (hU : IsOpen U) {f : U → β}
(cont : Continuous f) (supp : HasCompactMulSupport f) :
Continuous (Subtype.val.extend f 1) :=
continuous_of_mulTSupport fun x h ↦ by
rw [show x = ↑(⟨x, Subtype.coe_image_subset _ _
(supp.mulTSupport_extend_one_subset continuous_subtype_val h)⟩ : U) by rfl,
← (hU.openEmbedding_subtype_val).continuousAt_iff, extend_comp Subtype.val_injective]
exact cont.continuousAt
end HasCompactMulSupport
end CompactSupport
/-! ## Functions with compact support: algebraic operations -/
section CompactSupport2
section Monoid
variable [TopologicalSpace α] [Monoid β]
variable {f f' : α → β} {x : α}
@[to_additive]
theorem HasCompactMulSupport.mul (hf : HasCompactMulSupport f) (hf' : HasCompactMulSupport f') :
HasCompactMulSupport (f * f') := hf.comp₂_left hf' (mul_one 1)
#align has_compact_mul_support.mul HasCompactMulSupport.mul
#align has_compact_support.add HasCompactSupport.add
end Monoid
section DistribMulAction
variable [TopologicalSpace α] [MonoidWithZero R] [AddMonoid M] [DistribMulAction R M]
variable {f : α → R} {f' : α → M} {x : α}
theorem HasCompactSupport.smul_left (hf : HasCompactSupport f') : HasCompactSupport (f • f') := by
rw [hasCompactSupport_iff_eventuallyEq] at hf ⊢
exact hf.mono fun x hx => by simp_rw [Pi.smul_apply', hx, Pi.zero_apply, smul_zero]
#align has_compact_support.smul_left HasCompactSupport.smul_left
end DistribMulAction
section SMulWithZero
variable [TopologicalSpace α] [Zero R] [Zero M] [SMulWithZero R M]
variable {f : α → R} {f' : α → M} {x : α}
theorem HasCompactSupport.smul_right (hf : HasCompactSupport f) : HasCompactSupport (f • f') := by
rw [hasCompactSupport_iff_eventuallyEq] at hf ⊢
exact hf.mono fun x hx => by simp_rw [Pi.smul_apply', hx, Pi.zero_apply, zero_smul]
#align has_compact_support.smul_right HasCompactSupport.smul_right
theorem HasCompactSupport.smul_left' (hf : HasCompactSupport f') : HasCompactSupport (f • f') := by
rw [hasCompactSupport_iff_eventuallyEq] at hf ⊢
exact hf.mono fun x hx => by simp_rw [Pi.smul_apply', hx, Pi.zero_apply, smul_zero]
#align has_compact_support.smul_left' HasCompactSupport.smul_left'
end SMulWithZero
section MulZeroClass
variable [TopologicalSpace α] [MulZeroClass β]
variable {f f' : α → β} {x : α}
theorem HasCompactSupport.mul_right (hf : HasCompactSupport f) : HasCompactSupport (f * f') := by
rw [hasCompactSupport_iff_eventuallyEq] at hf ⊢
exact hf.mono fun x hx => by simp_rw [Pi.mul_apply, hx, Pi.zero_apply, zero_mul]
#align has_compact_support.mul_right HasCompactSupport.mul_right
| Mathlib/Topology/Support.lean | 370 | 372 | theorem HasCompactSupport.mul_left (hf : HasCompactSupport f') : HasCompactSupport (f * f') := by |
rw [hasCompactSupport_iff_eventuallyEq] at hf ⊢
exact hf.mono fun x hx => by simp_rw [Pi.mul_apply, hx, Pi.zero_apply, mul_zero]
|
/-
Copyright (c) 2015 Microsoft Corporation. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Leonardo de Moura, Jeremy Avigad
-/
import Mathlib.Data.Finset.Image
#align_import data.finset.card from "leanprover-community/mathlib"@"65a1391a0106c9204fe45bc73a039f056558cb83"
/-!
# Cardinality of a finite set
This defines the cardinality of a `Finset` and provides induction principles for finsets.
## Main declarations
* `Finset.card`: `s.card : ℕ` returns the cardinality of `s : Finset α`.
### Induction principles
* `Finset.strongInduction`: Strong induction
* `Finset.strongInductionOn`
* `Finset.strongDownwardInduction`
* `Finset.strongDownwardInductionOn`
* `Finset.case_strong_induction_on`
* `Finset.Nonempty.strong_induction`
-/
assert_not_exists MonoidWithZero
-- TODO: After a lot more work,
-- assert_not_exists OrderedCommMonoid
open Function Multiset Nat
variable {α β R : Type*}
namespace Finset
variable {s t : Finset α} {a b : α}
/-- `s.card` is the number of elements of `s`, aka its cardinality. -/
def card (s : Finset α) : ℕ :=
Multiset.card s.1
#align finset.card Finset.card
theorem card_def (s : Finset α) : s.card = Multiset.card s.1 :=
rfl
#align finset.card_def Finset.card_def
@[simp] lemma card_val (s : Finset α) : Multiset.card s.1 = s.card := rfl
#align finset.card_val Finset.card_val
@[simp]
theorem card_mk {m nodup} : (⟨m, nodup⟩ : Finset α).card = Multiset.card m :=
rfl
#align finset.card_mk Finset.card_mk
@[simp]
theorem card_empty : card (∅ : Finset α) = 0 :=
rfl
#align finset.card_empty Finset.card_empty
@[gcongr]
theorem card_le_card : s ⊆ t → s.card ≤ t.card :=
Multiset.card_le_card ∘ val_le_iff.mpr
#align finset.card_le_of_subset Finset.card_le_card
@[mono]
theorem card_mono : Monotone (@card α) := by apply card_le_card
#align finset.card_mono Finset.card_mono
@[simp] lemma card_eq_zero : s.card = 0 ↔ s = ∅ := card_eq_zero.trans val_eq_zero
lemma card_ne_zero : s.card ≠ 0 ↔ s.Nonempty := card_eq_zero.ne.trans nonempty_iff_ne_empty.symm
lemma card_pos : 0 < s.card ↔ s.Nonempty := Nat.pos_iff_ne_zero.trans card_ne_zero
#align finset.card_eq_zero Finset.card_eq_zero
#align finset.card_pos Finset.card_pos
alias ⟨_, Nonempty.card_pos⟩ := card_pos
alias ⟨_, Nonempty.card_ne_zero⟩ := card_ne_zero
#align finset.nonempty.card_pos Finset.Nonempty.card_pos
theorem card_ne_zero_of_mem (h : a ∈ s) : s.card ≠ 0 :=
(not_congr card_eq_zero).2 <| ne_empty_of_mem h
#align finset.card_ne_zero_of_mem Finset.card_ne_zero_of_mem
@[simp]
theorem card_singleton (a : α) : card ({a} : Finset α) = 1 :=
Multiset.card_singleton _
#align finset.card_singleton Finset.card_singleton
theorem card_singleton_inter [DecidableEq α] : ({a} ∩ s).card ≤ 1 := by
cases' Finset.decidableMem a s with h h
· simp [Finset.singleton_inter_of_not_mem h]
· simp [Finset.singleton_inter_of_mem h]
#align finset.card_singleton_inter Finset.card_singleton_inter
@[simp]
theorem card_cons (h : a ∉ s) : (s.cons a h).card = s.card + 1 :=
Multiset.card_cons _ _
#align finset.card_cons Finset.card_cons
section InsertErase
variable [DecidableEq α]
@[simp]
theorem card_insert_of_not_mem (h : a ∉ s) : (insert a s).card = s.card + 1 := by
rw [← cons_eq_insert _ _ h, card_cons]
#align finset.card_insert_of_not_mem Finset.card_insert_of_not_mem
theorem card_insert_of_mem (h : a ∈ s) : card (insert a s) = s.card := by rw [insert_eq_of_mem h]
#align finset.card_insert_of_mem Finset.card_insert_of_mem
theorem card_insert_le (a : α) (s : Finset α) : card (insert a s) ≤ s.card + 1 := by
by_cases h : a ∈ s
· rw [insert_eq_of_mem h]
exact Nat.le_succ _
· rw [card_insert_of_not_mem h]
#align finset.card_insert_le Finset.card_insert_le
section
variable {a b c d e f : α}
theorem card_le_two : card {a, b} ≤ 2 := card_insert_le _ _
theorem card_le_three : card {a, b, c} ≤ 3 :=
(card_insert_le _ _).trans (Nat.succ_le_succ card_le_two)
theorem card_le_four : card {a, b, c, d} ≤ 4 :=
(card_insert_le _ _).trans (Nat.succ_le_succ card_le_three)
theorem card_le_five : card {a, b, c, d, e} ≤ 5 :=
(card_insert_le _ _).trans (Nat.succ_le_succ card_le_four)
theorem card_le_six : card {a, b, c, d, e, f} ≤ 6 :=
(card_insert_le _ _).trans (Nat.succ_le_succ card_le_five)
end
/-- If `a ∈ s` is known, see also `Finset.card_insert_of_mem` and `Finset.card_insert_of_not_mem`.
-/
theorem card_insert_eq_ite : card (insert a s) = if a ∈ s then s.card else s.card + 1 := by
by_cases h : a ∈ s
· rw [card_insert_of_mem h, if_pos h]
· rw [card_insert_of_not_mem h, if_neg h]
#align finset.card_insert_eq_ite Finset.card_insert_eq_ite
@[simp]
theorem card_pair_eq_one_or_two : ({a,b} : Finset α).card = 1 ∨ ({a,b} : Finset α).card = 2 := by
simp [card_insert_eq_ite]
tauto
@[simp]
| Mathlib/Data/Finset/Card.lean | 155 | 156 | theorem card_pair (h : a ≠ b) : ({a, b} : Finset α).card = 2 := by |
rw [card_insert_of_not_mem (not_mem_singleton.2 h), card_singleton]
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro, Kyle Miller
-/
import Mathlib.Data.Finset.Basic
import Mathlib.Data.Finite.Basic
import Mathlib.Data.Set.Functor
import Mathlib.Data.Set.Lattice
#align_import data.set.finite from "leanprover-community/mathlib"@"65a1391a0106c9204fe45bc73a039f056558cb83"
/-!
# Finite sets
This file defines predicates for finite and infinite sets and provides
`Fintype` instances for many set constructions. It also proves basic facts
about finite sets and gives ways to manipulate `Set.Finite` expressions.
## Main definitions
* `Set.Finite : Set α → Prop`
* `Set.Infinite : Set α → Prop`
* `Set.toFinite` to prove `Set.Finite` for a `Set` from a `Finite` instance.
* `Set.Finite.toFinset` to noncomputably produce a `Finset` from a `Set.Finite` proof.
(See `Set.toFinset` for a computable version.)
## Implementation
A finite set is defined to be a set whose coercion to a type has a `Finite` instance.
There are two components to finiteness constructions. The first is `Fintype` instances for each
construction. This gives a way to actually compute a `Finset` that represents the set, and these
may be accessed using `set.toFinset`. This gets the `Finset` in the correct form, since otherwise
`Finset.univ : Finset s` is a `Finset` for the subtype for `s`. The second component is
"constructors" for `Set.Finite` that give proofs that `Fintype` instances exist classically given
other `Set.Finite` proofs. Unlike the `Fintype` instances, these *do not* use any decidability
instances since they do not compute anything.
## Tags
finite sets
-/
assert_not_exists OrderedRing
assert_not_exists MonoidWithZero
open Set Function
universe u v w x
variable {α : Type u} {β : Type v} {ι : Sort w} {γ : Type x}
namespace Set
/-- A set is finite if the corresponding `Subtype` is finite,
i.e., if there exists a natural `n : ℕ` and an equivalence `s ≃ Fin n`. -/
protected def Finite (s : Set α) : Prop := Finite s
#align set.finite Set.Finite
-- The `protected` attribute does not take effect within the same namespace block.
end Set
namespace Set
theorem finite_def {s : Set α} : s.Finite ↔ Nonempty (Fintype s) :=
finite_iff_nonempty_fintype s
#align set.finite_def Set.finite_def
protected alias ⟨Finite.nonempty_fintype, _⟩ := finite_def
#align set.finite.nonempty_fintype Set.Finite.nonempty_fintype
theorem finite_coe_iff {s : Set α} : Finite s ↔ s.Finite := .rfl
#align set.finite_coe_iff Set.finite_coe_iff
/-- Constructor for `Set.Finite` using a `Finite` instance. -/
theorem toFinite (s : Set α) [Finite s] : s.Finite := ‹_›
#align set.to_finite Set.toFinite
/-- Construct a `Finite` instance for a `Set` from a `Finset` with the same elements. -/
protected theorem Finite.ofFinset {p : Set α} (s : Finset α) (H : ∀ x, x ∈ s ↔ x ∈ p) : p.Finite :=
have := Fintype.ofFinset s H; p.toFinite
#align set.finite.of_finset Set.Finite.ofFinset
/-- Projection of `Set.Finite` to its `Finite` instance.
This is intended to be used with dot notation.
See also `Set.Finite.Fintype` and `Set.Finite.nonempty_fintype`. -/
protected theorem Finite.to_subtype {s : Set α} (h : s.Finite) : Finite s := h
#align set.finite.to_subtype Set.Finite.to_subtype
/-- A finite set coerced to a type is a `Fintype`.
This is the `Fintype` projection for a `Set.Finite`.
Note that because `Finite` isn't a typeclass, this definition will not fire if it
is made into an instance -/
protected noncomputable def Finite.fintype {s : Set α} (h : s.Finite) : Fintype s :=
h.nonempty_fintype.some
#align set.finite.fintype Set.Finite.fintype
/-- Using choice, get the `Finset` that represents this `Set`. -/
protected noncomputable def Finite.toFinset {s : Set α} (h : s.Finite) : Finset α :=
@Set.toFinset _ _ h.fintype
#align set.finite.to_finset Set.Finite.toFinset
theorem Finite.toFinset_eq_toFinset {s : Set α} [Fintype s] (h : s.Finite) :
h.toFinset = s.toFinset := by
-- Porting note: was `rw [Finite.toFinset]; congr`
-- in Lean 4, a goal is left after `congr`
have : h.fintype = ‹_› := Subsingleton.elim _ _
rw [Finite.toFinset, this]
#align set.finite.to_finset_eq_to_finset Set.Finite.toFinset_eq_toFinset
@[simp]
theorem toFinite_toFinset (s : Set α) [Fintype s] : s.toFinite.toFinset = s.toFinset :=
s.toFinite.toFinset_eq_toFinset
#align set.to_finite_to_finset Set.toFinite_toFinset
theorem Finite.exists_finset {s : Set α} (h : s.Finite) :
∃ s' : Finset α, ∀ a : α, a ∈ s' ↔ a ∈ s := by
cases h.nonempty_fintype
exact ⟨s.toFinset, fun _ => mem_toFinset⟩
#align set.finite.exists_finset Set.Finite.exists_finset
theorem Finite.exists_finset_coe {s : Set α} (h : s.Finite) : ∃ s' : Finset α, ↑s' = s := by
cases h.nonempty_fintype
exact ⟨s.toFinset, s.coe_toFinset⟩
#align set.finite.exists_finset_coe Set.Finite.exists_finset_coe
/-- Finite sets can be lifted to finsets. -/
instance : CanLift (Set α) (Finset α) (↑) Set.Finite where prf _ hs := hs.exists_finset_coe
/-- A set is infinite if it is not finite.
This is protected so that it does not conflict with global `Infinite`. -/
protected def Infinite (s : Set α) : Prop :=
¬s.Finite
#align set.infinite Set.Infinite
@[simp]
theorem not_infinite {s : Set α} : ¬s.Infinite ↔ s.Finite :=
not_not
#align set.not_infinite Set.not_infinite
alias ⟨_, Finite.not_infinite⟩ := not_infinite
#align set.finite.not_infinite Set.Finite.not_infinite
attribute [simp] Finite.not_infinite
/-- See also `finite_or_infinite`, `fintypeOrInfinite`. -/
protected theorem finite_or_infinite (s : Set α) : s.Finite ∨ s.Infinite :=
em _
#align set.finite_or_infinite Set.finite_or_infinite
protected theorem infinite_or_finite (s : Set α) : s.Infinite ∨ s.Finite :=
em' _
#align set.infinite_or_finite Set.infinite_or_finite
/-! ### Basic properties of `Set.Finite.toFinset` -/
namespace Finite
variable {s t : Set α} {a : α} (hs : s.Finite) {ht : t.Finite}
@[simp]
protected theorem mem_toFinset : a ∈ hs.toFinset ↔ a ∈ s :=
@mem_toFinset _ _ hs.fintype _
#align set.finite.mem_to_finset Set.Finite.mem_toFinset
@[simp]
protected theorem coe_toFinset : (hs.toFinset : Set α) = s :=
@coe_toFinset _ _ hs.fintype
#align set.finite.coe_to_finset Set.Finite.coe_toFinset
@[simp]
protected theorem toFinset_nonempty : hs.toFinset.Nonempty ↔ s.Nonempty := by
rw [← Finset.coe_nonempty, Finite.coe_toFinset]
#align set.finite.to_finset_nonempty Set.Finite.toFinset_nonempty
/-- Note that this is an equality of types not holding definitionally. Use wisely. -/
theorem coeSort_toFinset : ↥hs.toFinset = ↥s := by
rw [← Finset.coe_sort_coe _, hs.coe_toFinset]
#align set.finite.coe_sort_to_finset Set.Finite.coeSort_toFinset
/-- The identity map, bundled as an equivalence between the subtypes of `s : Set α` and of
`h.toFinset : Finset α`, where `h` is a proof of finiteness of `s`. -/
@[simps!] def subtypeEquivToFinset : {x // x ∈ s} ≃ {x // x ∈ hs.toFinset} :=
(Equiv.refl α).subtypeEquiv fun _ ↦ hs.mem_toFinset.symm
variable {hs}
@[simp]
protected theorem toFinset_inj : hs.toFinset = ht.toFinset ↔ s = t :=
@toFinset_inj _ _ _ hs.fintype ht.fintype
#align set.finite.to_finset_inj Set.Finite.toFinset_inj
@[simp]
theorem toFinset_subset {t : Finset α} : hs.toFinset ⊆ t ↔ s ⊆ t := by
rw [← Finset.coe_subset, Finite.coe_toFinset]
#align set.finite.to_finset_subset Set.Finite.toFinset_subset
@[simp]
theorem toFinset_ssubset {t : Finset α} : hs.toFinset ⊂ t ↔ s ⊂ t := by
rw [← Finset.coe_ssubset, Finite.coe_toFinset]
#align set.finite.to_finset_ssubset Set.Finite.toFinset_ssubset
@[simp]
theorem subset_toFinset {s : Finset α} : s ⊆ ht.toFinset ↔ ↑s ⊆ t := by
rw [← Finset.coe_subset, Finite.coe_toFinset]
#align set.finite.subset_to_finset Set.Finite.subset_toFinset
@[simp]
theorem ssubset_toFinset {s : Finset α} : s ⊂ ht.toFinset ↔ ↑s ⊂ t := by
rw [← Finset.coe_ssubset, Finite.coe_toFinset]
#align set.finite.ssubset_to_finset Set.Finite.ssubset_toFinset
@[mono]
protected theorem toFinset_subset_toFinset : hs.toFinset ⊆ ht.toFinset ↔ s ⊆ t := by
simp only [← Finset.coe_subset, Finite.coe_toFinset]
#align set.finite.to_finset_subset_to_finset Set.Finite.toFinset_subset_toFinset
@[mono]
protected theorem toFinset_ssubset_toFinset : hs.toFinset ⊂ ht.toFinset ↔ s ⊂ t := by
simp only [← Finset.coe_ssubset, Finite.coe_toFinset]
#align set.finite.to_finset_ssubset_to_finset Set.Finite.toFinset_ssubset_toFinset
alias ⟨_, toFinset_mono⟩ := Finite.toFinset_subset_toFinset
#align set.finite.to_finset_mono Set.Finite.toFinset_mono
alias ⟨_, toFinset_strictMono⟩ := Finite.toFinset_ssubset_toFinset
#align set.finite.to_finset_strict_mono Set.Finite.toFinset_strictMono
-- Porting note: attribute [protected] doesn't work
-- attribute [protected] toFinset_mono toFinset_strictMono
-- Porting note: `simp` can simplify LHS but then it simplifies something
-- in the generated `Fintype {x | p x}` instance and fails to apply `Set.toFinset_setOf`
@[simp high]
protected theorem toFinset_setOf [Fintype α] (p : α → Prop) [DecidablePred p]
(h : { x | p x }.Finite) : h.toFinset = Finset.univ.filter p := by
ext
-- Porting note: `simp` doesn't use the `simp` lemma `Set.toFinset_setOf` without the `_`
simp [Set.toFinset_setOf _]
#align set.finite.to_finset_set_of Set.Finite.toFinset_setOf
@[simp]
nonrec theorem disjoint_toFinset {hs : s.Finite} {ht : t.Finite} :
Disjoint hs.toFinset ht.toFinset ↔ Disjoint s t :=
@disjoint_toFinset _ _ _ hs.fintype ht.fintype
#align set.finite.disjoint_to_finset Set.Finite.disjoint_toFinset
protected theorem toFinset_inter [DecidableEq α] (hs : s.Finite) (ht : t.Finite)
(h : (s ∩ t).Finite) : h.toFinset = hs.toFinset ∩ ht.toFinset := by
ext
simp
#align set.finite.to_finset_inter Set.Finite.toFinset_inter
protected theorem toFinset_union [DecidableEq α] (hs : s.Finite) (ht : t.Finite)
(h : (s ∪ t).Finite) : h.toFinset = hs.toFinset ∪ ht.toFinset := by
ext
simp
#align set.finite.to_finset_union Set.Finite.toFinset_union
protected theorem toFinset_diff [DecidableEq α] (hs : s.Finite) (ht : t.Finite)
(h : (s \ t).Finite) : h.toFinset = hs.toFinset \ ht.toFinset := by
ext
simp
#align set.finite.to_finset_diff Set.Finite.toFinset_diff
open scoped symmDiff in
protected theorem toFinset_symmDiff [DecidableEq α] (hs : s.Finite) (ht : t.Finite)
(h : (s ∆ t).Finite) : h.toFinset = hs.toFinset ∆ ht.toFinset := by
ext
simp [mem_symmDiff, Finset.mem_symmDiff]
#align set.finite.to_finset_symm_diff Set.Finite.toFinset_symmDiff
protected theorem toFinset_compl [DecidableEq α] [Fintype α] (hs : s.Finite) (h : sᶜ.Finite) :
h.toFinset = hs.toFinsetᶜ := by
ext
simp
#align set.finite.to_finset_compl Set.Finite.toFinset_compl
protected theorem toFinset_univ [Fintype α] (h : (Set.univ : Set α).Finite) :
h.toFinset = Finset.univ := by
simp
#align set.finite.to_finset_univ Set.Finite.toFinset_univ
@[simp]
protected theorem toFinset_eq_empty {h : s.Finite} : h.toFinset = ∅ ↔ s = ∅ :=
@toFinset_eq_empty _ _ h.fintype
#align set.finite.to_finset_eq_empty Set.Finite.toFinset_eq_empty
protected theorem toFinset_empty (h : (∅ : Set α).Finite) : h.toFinset = ∅ := by
simp
#align set.finite.to_finset_empty Set.Finite.toFinset_empty
@[simp]
protected theorem toFinset_eq_univ [Fintype α] {h : s.Finite} :
h.toFinset = Finset.univ ↔ s = univ :=
@toFinset_eq_univ _ _ _ h.fintype
#align set.finite.to_finset_eq_univ Set.Finite.toFinset_eq_univ
protected theorem toFinset_image [DecidableEq β] (f : α → β) (hs : s.Finite) (h : (f '' s).Finite) :
h.toFinset = hs.toFinset.image f := by
ext
simp
#align set.finite.to_finset_image Set.Finite.toFinset_image
-- Porting note (#10618): now `simp` can prove it but it needs the `fintypeRange` instance
-- from the next section
protected theorem toFinset_range [DecidableEq α] [Fintype β] (f : β → α) (h : (range f).Finite) :
h.toFinset = Finset.univ.image f := by
ext
simp
#align set.finite.to_finset_range Set.Finite.toFinset_range
end Finite
/-! ### Fintype instances
Every instance here should have a corresponding `Set.Finite` constructor in the next section.
-/
section FintypeInstances
instance fintypeUniv [Fintype α] : Fintype (@univ α) :=
Fintype.ofEquiv α (Equiv.Set.univ α).symm
#align set.fintype_univ Set.fintypeUniv
/-- If `(Set.univ : Set α)` is finite then `α` is a finite type. -/
noncomputable def fintypeOfFiniteUniv (H : (univ (α := α)).Finite) : Fintype α :=
@Fintype.ofEquiv _ (univ : Set α) H.fintype (Equiv.Set.univ _)
#align set.fintype_of_finite_univ Set.fintypeOfFiniteUniv
instance fintypeUnion [DecidableEq α] (s t : Set α) [Fintype s] [Fintype t] :
Fintype (s ∪ t : Set α) :=
Fintype.ofFinset (s.toFinset ∪ t.toFinset) <| by simp
#align set.fintype_union Set.fintypeUnion
instance fintypeSep (s : Set α) (p : α → Prop) [Fintype s] [DecidablePred p] :
Fintype ({ a ∈ s | p a } : Set α) :=
Fintype.ofFinset (s.toFinset.filter p) <| by simp
#align set.fintype_sep Set.fintypeSep
instance fintypeInter (s t : Set α) [DecidableEq α] [Fintype s] [Fintype t] :
Fintype (s ∩ t : Set α) :=
Fintype.ofFinset (s.toFinset ∩ t.toFinset) <| by simp
#align set.fintype_inter Set.fintypeInter
/-- A `Fintype` instance for set intersection where the left set has a `Fintype` instance. -/
instance fintypeInterOfLeft (s t : Set α) [Fintype s] [DecidablePred (· ∈ t)] :
Fintype (s ∩ t : Set α) :=
Fintype.ofFinset (s.toFinset.filter (· ∈ t)) <| by simp
#align set.fintype_inter_of_left Set.fintypeInterOfLeft
/-- A `Fintype` instance for set intersection where the right set has a `Fintype` instance. -/
instance fintypeInterOfRight (s t : Set α) [Fintype t] [DecidablePred (· ∈ s)] :
Fintype (s ∩ t : Set α) :=
Fintype.ofFinset (t.toFinset.filter (· ∈ s)) <| by simp [and_comm]
#align set.fintype_inter_of_right Set.fintypeInterOfRight
/-- A `Fintype` structure on a set defines a `Fintype` structure on its subset. -/
def fintypeSubset (s : Set α) {t : Set α} [Fintype s] [DecidablePred (· ∈ t)] (h : t ⊆ s) :
Fintype t := by
rw [← inter_eq_self_of_subset_right h]
apply Set.fintypeInterOfLeft
#align set.fintype_subset Set.fintypeSubset
instance fintypeDiff [DecidableEq α] (s t : Set α) [Fintype s] [Fintype t] :
Fintype (s \ t : Set α) :=
Fintype.ofFinset (s.toFinset \ t.toFinset) <| by simp
#align set.fintype_diff Set.fintypeDiff
instance fintypeDiffLeft (s t : Set α) [Fintype s] [DecidablePred (· ∈ t)] :
Fintype (s \ t : Set α) :=
Set.fintypeSep s (· ∈ tᶜ)
#align set.fintype_diff_left Set.fintypeDiffLeft
instance fintypeiUnion [DecidableEq α] [Fintype (PLift ι)] (f : ι → Set α) [∀ i, Fintype (f i)] :
Fintype (⋃ i, f i) :=
Fintype.ofFinset (Finset.univ.biUnion fun i : PLift ι => (f i.down).toFinset) <| by simp
#align set.fintype_Union Set.fintypeiUnion
instance fintypesUnion [DecidableEq α] {s : Set (Set α)} [Fintype s]
[H : ∀ t : s, Fintype (t : Set α)] : Fintype (⋃₀ s) := by
rw [sUnion_eq_iUnion]
exact @Set.fintypeiUnion _ _ _ _ _ H
#align set.fintype_sUnion Set.fintypesUnion
/-- A union of sets with `Fintype` structure over a set with `Fintype` structure has a `Fintype`
structure. -/
def fintypeBiUnion [DecidableEq α] {ι : Type*} (s : Set ι) [Fintype s] (t : ι → Set α)
(H : ∀ i ∈ s, Fintype (t i)) : Fintype (⋃ x ∈ s, t x) :=
haveI : ∀ i : toFinset s, Fintype (t i) := fun i => H i (mem_toFinset.1 i.2)
Fintype.ofFinset (s.toFinset.attach.biUnion fun x => (t x).toFinset) fun x => by simp
#align set.fintype_bUnion Set.fintypeBiUnion
instance fintypeBiUnion' [DecidableEq α] {ι : Type*} (s : Set ι) [Fintype s] (t : ι → Set α)
[∀ i, Fintype (t i)] : Fintype (⋃ x ∈ s, t x) :=
Fintype.ofFinset (s.toFinset.biUnion fun x => (t x).toFinset) <| by simp
#align set.fintype_bUnion' Set.fintypeBiUnion'
section monad
attribute [local instance] Set.monad
/-- If `s : Set α` is a set with `Fintype` instance and `f : α → Set β` is a function such that
each `f a`, `a ∈ s`, has a `Fintype` structure, then `s >>= f` has a `Fintype` structure. -/
def fintypeBind {α β} [DecidableEq β] (s : Set α) [Fintype s] (f : α → Set β)
(H : ∀ a ∈ s, Fintype (f a)) : Fintype (s >>= f) :=
Set.fintypeBiUnion s f H
#align set.fintype_bind Set.fintypeBind
instance fintypeBind' {α β} [DecidableEq β] (s : Set α) [Fintype s] (f : α → Set β)
[∀ a, Fintype (f a)] : Fintype (s >>= f) :=
Set.fintypeBiUnion' s f
#align set.fintype_bind' Set.fintypeBind'
end monad
instance fintypeEmpty : Fintype (∅ : Set α) :=
Fintype.ofFinset ∅ <| by simp
#align set.fintype_empty Set.fintypeEmpty
instance fintypeSingleton (a : α) : Fintype ({a} : Set α) :=
Fintype.ofFinset {a} <| by simp
#align set.fintype_singleton Set.fintypeSingleton
instance fintypePure : ∀ a : α, Fintype (pure a : Set α) :=
Set.fintypeSingleton
#align set.fintype_pure Set.fintypePure
/-- A `Fintype` instance for inserting an element into a `Set` using the
corresponding `insert` function on `Finset`. This requires `DecidableEq α`.
There is also `Set.fintypeInsert'` when `a ∈ s` is decidable. -/
instance fintypeInsert (a : α) (s : Set α) [DecidableEq α] [Fintype s] :
Fintype (insert a s : Set α) :=
Fintype.ofFinset (insert a s.toFinset) <| by simp
#align set.fintype_insert Set.fintypeInsert
/-- A `Fintype` structure on `insert a s` when inserting a new element. -/
def fintypeInsertOfNotMem {a : α} (s : Set α) [Fintype s] (h : a ∉ s) :
Fintype (insert a s : Set α) :=
Fintype.ofFinset ⟨a ::ₘ s.toFinset.1, s.toFinset.nodup.cons (by simp [h])⟩ <| by simp
#align set.fintype_insert_of_not_mem Set.fintypeInsertOfNotMem
/-- A `Fintype` structure on `insert a s` when inserting a pre-existing element. -/
def fintypeInsertOfMem {a : α} (s : Set α) [Fintype s] (h : a ∈ s) : Fintype (insert a s : Set α) :=
Fintype.ofFinset s.toFinset <| by simp [h]
#align set.fintype_insert_of_mem Set.fintypeInsertOfMem
/-- The `Set.fintypeInsert` instance requires decidable equality, but when `a ∈ s`
is decidable for this particular `a` we can still get a `Fintype` instance by using
`Set.fintypeInsertOfNotMem` or `Set.fintypeInsertOfMem`.
This instance pre-dates `Set.fintypeInsert`, and it is less efficient.
When `Set.decidableMemOfFintype` is made a local instance, then this instance would
override `Set.fintypeInsert` if not for the fact that its priority has been
adjusted. See Note [lower instance priority]. -/
instance (priority := 100) fintypeInsert' (a : α) (s : Set α) [Decidable <| a ∈ s] [Fintype s] :
Fintype (insert a s : Set α) :=
if h : a ∈ s then fintypeInsertOfMem s h else fintypeInsertOfNotMem s h
#align set.fintype_insert' Set.fintypeInsert'
instance fintypeImage [DecidableEq β] (s : Set α) (f : α → β) [Fintype s] : Fintype (f '' s) :=
Fintype.ofFinset (s.toFinset.image f) <| by simp
#align set.fintype_image Set.fintypeImage
/-- If a function `f` has a partial inverse and sends a set `s` to a set with `[Fintype]` instance,
then `s` has a `Fintype` structure as well. -/
def fintypeOfFintypeImage (s : Set α) {f : α → β} {g} (I : IsPartialInv f g) [Fintype (f '' s)] :
Fintype s :=
Fintype.ofFinset ⟨_, (f '' s).toFinset.2.filterMap g <| injective_of_isPartialInv_right I⟩
fun a => by
suffices (∃ b x, f x = b ∧ g b = some a ∧ x ∈ s) ↔ a ∈ s by
simpa [exists_and_left.symm, and_comm, and_left_comm, and_assoc]
rw [exists_swap]
suffices (∃ x, x ∈ s ∧ g (f x) = some a) ↔ a ∈ s by simpa [and_comm, and_left_comm, and_assoc]
simp [I _, (injective_of_isPartialInv I).eq_iff]
#align set.fintype_of_fintype_image Set.fintypeOfFintypeImage
instance fintypeRange [DecidableEq α] (f : ι → α) [Fintype (PLift ι)] : Fintype (range f) :=
Fintype.ofFinset (Finset.univ.image <| f ∘ PLift.down) <| by simp
#align set.fintype_range Set.fintypeRange
instance fintypeMap {α β} [DecidableEq β] :
∀ (s : Set α) (f : α → β) [Fintype s], Fintype (f <$> s) :=
Set.fintypeImage
#align set.fintype_map Set.fintypeMap
instance fintypeLTNat (n : ℕ) : Fintype { i | i < n } :=
Fintype.ofFinset (Finset.range n) <| by simp
#align set.fintype_lt_nat Set.fintypeLTNat
instance fintypeLENat (n : ℕ) : Fintype { i | i ≤ n } := by
simpa [Nat.lt_succ_iff] using Set.fintypeLTNat (n + 1)
#align set.fintype_le_nat Set.fintypeLENat
/-- This is not an instance so that it does not conflict with the one
in `Mathlib/Order/LocallyFinite.lean`. -/
def Nat.fintypeIio (n : ℕ) : Fintype (Iio n) :=
Set.fintypeLTNat n
#align set.nat.fintype_Iio Set.Nat.fintypeIio
instance fintypeProd (s : Set α) (t : Set β) [Fintype s] [Fintype t] :
Fintype (s ×ˢ t : Set (α × β)) :=
Fintype.ofFinset (s.toFinset ×ˢ t.toFinset) <| by simp
#align set.fintype_prod Set.fintypeProd
instance fintypeOffDiag [DecidableEq α] (s : Set α) [Fintype s] : Fintype s.offDiag :=
Fintype.ofFinset s.toFinset.offDiag <| by simp
#align set.fintype_off_diag Set.fintypeOffDiag
/-- `image2 f s t` is `Fintype` if `s` and `t` are. -/
instance fintypeImage2 [DecidableEq γ] (f : α → β → γ) (s : Set α) (t : Set β) [hs : Fintype s]
[ht : Fintype t] : Fintype (image2 f s t : Set γ) := by
rw [← image_prod]
apply Set.fintypeImage
#align set.fintype_image2 Set.fintypeImage2
instance fintypeSeq [DecidableEq β] (f : Set (α → β)) (s : Set α) [Fintype f] [Fintype s] :
Fintype (f.seq s) := by
rw [seq_def]
apply Set.fintypeBiUnion'
#align set.fintype_seq Set.fintypeSeq
instance fintypeSeq' {α β : Type u} [DecidableEq β] (f : Set (α → β)) (s : Set α) [Fintype f]
[Fintype s] : Fintype (f <*> s) :=
Set.fintypeSeq f s
#align set.fintype_seq' Set.fintypeSeq'
instance fintypeMemFinset (s : Finset α) : Fintype { a | a ∈ s } :=
Finset.fintypeCoeSort s
#align set.fintype_mem_finset Set.fintypeMemFinset
end FintypeInstances
end Set
theorem Equiv.set_finite_iff {s : Set α} {t : Set β} (hst : s ≃ t) : s.Finite ↔ t.Finite := by
simp_rw [← Set.finite_coe_iff, hst.finite_iff]
#align equiv.set_finite_iff Equiv.set_finite_iff
/-! ### Finset -/
namespace Finset
/-- Gives a `Set.Finite` for the `Finset` coerced to a `Set`.
This is a wrapper around `Set.toFinite`. -/
@[simp]
theorem finite_toSet (s : Finset α) : (s : Set α).Finite :=
Set.toFinite _
#align finset.finite_to_set Finset.finite_toSet
-- Porting note (#10618): was @[simp], now `simp` can prove it
theorem finite_toSet_toFinset (s : Finset α) : s.finite_toSet.toFinset = s := by
rw [toFinite_toFinset, toFinset_coe]
#align finset.finite_to_set_to_finset Finset.finite_toSet_toFinset
end Finset
namespace Multiset
@[simp]
theorem finite_toSet (s : Multiset α) : { x | x ∈ s }.Finite := by
classical simpa only [← Multiset.mem_toFinset] using s.toFinset.finite_toSet
#align multiset.finite_to_set Multiset.finite_toSet
@[simp]
theorem finite_toSet_toFinset [DecidableEq α] (s : Multiset α) :
s.finite_toSet.toFinset = s.toFinset := by
ext x
simp
#align multiset.finite_to_set_to_finset Multiset.finite_toSet_toFinset
end Multiset
@[simp]
theorem List.finite_toSet (l : List α) : { x | x ∈ l }.Finite :=
(show Multiset α from ⟦l⟧).finite_toSet
#align list.finite_to_set List.finite_toSet
/-! ### Finite instances
There is seemingly some overlap between the following instances and the `Fintype` instances
in `Data.Set.Finite`. While every `Fintype` instance gives a `Finite` instance, those
instances that depend on `Fintype` or `Decidable` instances need an additional `Finite` instance
to be able to generally apply.
Some set instances do not appear here since they are consequences of others, for example
`Subtype.Finite` for subsets of a finite type.
-/
namespace Finite.Set
open scoped Classical
example {s : Set α} [Finite α] : Finite s :=
inferInstance
example : Finite (∅ : Set α) :=
inferInstance
example (a : α) : Finite ({a} : Set α) :=
inferInstance
instance finite_union (s t : Set α) [Finite s] [Finite t] : Finite (s ∪ t : Set α) := by
cases nonempty_fintype s
cases nonempty_fintype t
infer_instance
#align finite.set.finite_union Finite.Set.finite_union
instance finite_sep (s : Set α) (p : α → Prop) [Finite s] : Finite ({ a ∈ s | p a } : Set α) := by
cases nonempty_fintype s
infer_instance
#align finite.set.finite_sep Finite.Set.finite_sep
protected theorem subset (s : Set α) {t : Set α} [Finite s] (h : t ⊆ s) : Finite t := by
rw [← sep_eq_of_subset h]
infer_instance
#align finite.set.subset Finite.Set.subset
instance finite_inter_of_right (s t : Set α) [Finite t] : Finite (s ∩ t : Set α) :=
Finite.Set.subset t inter_subset_right
#align finite.set.finite_inter_of_right Finite.Set.finite_inter_of_right
instance finite_inter_of_left (s t : Set α) [Finite s] : Finite (s ∩ t : Set α) :=
Finite.Set.subset s inter_subset_left
#align finite.set.finite_inter_of_left Finite.Set.finite_inter_of_left
instance finite_diff (s t : Set α) [Finite s] : Finite (s \ t : Set α) :=
Finite.Set.subset s diff_subset
#align finite.set.finite_diff Finite.Set.finite_diff
instance finite_range (f : ι → α) [Finite ι] : Finite (range f) := by
haveI := Fintype.ofFinite (PLift ι)
infer_instance
#align finite.set.finite_range Finite.Set.finite_range
instance finite_iUnion [Finite ι] (f : ι → Set α) [∀ i, Finite (f i)] : Finite (⋃ i, f i) := by
rw [iUnion_eq_range_psigma]
apply Set.finite_range
#align finite.set.finite_Union Finite.Set.finite_iUnion
instance finite_sUnion {s : Set (Set α)} [Finite s] [H : ∀ t : s, Finite (t : Set α)] :
Finite (⋃₀ s) := by
rw [sUnion_eq_iUnion]
exact @Finite.Set.finite_iUnion _ _ _ _ H
#align finite.set.finite_sUnion Finite.Set.finite_sUnion
theorem finite_biUnion {ι : Type*} (s : Set ι) [Finite s] (t : ι → Set α)
(H : ∀ i ∈ s, Finite (t i)) : Finite (⋃ x ∈ s, t x) := by
rw [biUnion_eq_iUnion]
haveI : ∀ i : s, Finite (t i) := fun i => H i i.property
infer_instance
#align finite.set.finite_bUnion Finite.Set.finite_biUnion
instance finite_biUnion' {ι : Type*} (s : Set ι) [Finite s] (t : ι → Set α) [∀ i, Finite (t i)] :
Finite (⋃ x ∈ s, t x) :=
finite_biUnion s t fun _ _ => inferInstance
#align finite.set.finite_bUnion' Finite.Set.finite_biUnion'
/-- Example: `Finite (⋃ (i < n), f i)` where `f : ℕ → Set α` and `[∀ i, Finite (f i)]`
(when given instances from `Order.Interval.Finset.Nat`).
-/
instance finite_biUnion'' {ι : Type*} (p : ι → Prop) [h : Finite { x | p x }] (t : ι → Set α)
[∀ i, Finite (t i)] : Finite (⋃ (x) (_ : p x), t x) :=
@Finite.Set.finite_biUnion' _ _ (setOf p) h t _
#align finite.set.finite_bUnion'' Finite.Set.finite_biUnion''
instance finite_iInter {ι : Sort*} [Nonempty ι] (t : ι → Set α) [∀ i, Finite (t i)] :
Finite (⋂ i, t i) :=
Finite.Set.subset (t <| Classical.arbitrary ι) (iInter_subset _ _)
#align finite.set.finite_Inter Finite.Set.finite_iInter
instance finite_insert (a : α) (s : Set α) [Finite s] : Finite (insert a s : Set α) :=
Finite.Set.finite_union {a} s
#align finite.set.finite_insert Finite.Set.finite_insert
instance finite_image (s : Set α) (f : α → β) [Finite s] : Finite (f '' s) := by
cases nonempty_fintype s
infer_instance
#align finite.set.finite_image Finite.Set.finite_image
instance finite_replacement [Finite α] (f : α → β) :
Finite {f x | x : α} :=
Finite.Set.finite_range f
#align finite.set.finite_replacement Finite.Set.finite_replacement
instance finite_prod (s : Set α) (t : Set β) [Finite s] [Finite t] :
Finite (s ×ˢ t : Set (α × β)) :=
Finite.of_equiv _ (Equiv.Set.prod s t).symm
#align finite.set.finite_prod Finite.Set.finite_prod
instance finite_image2 (f : α → β → γ) (s : Set α) (t : Set β) [Finite s] [Finite t] :
Finite (image2 f s t : Set γ) := by
rw [← image_prod]
infer_instance
#align finite.set.finite_image2 Finite.Set.finite_image2
instance finite_seq (f : Set (α → β)) (s : Set α) [Finite f] [Finite s] : Finite (f.seq s) := by
rw [seq_def]
infer_instance
#align finite.set.finite_seq Finite.Set.finite_seq
end Finite.Set
namespace Set
/-! ### Constructors for `Set.Finite`
Every constructor here should have a corresponding `Fintype` instance in the previous section
(or in the `Fintype` module).
The implementation of these constructors ideally should be no more than `Set.toFinite`,
after possibly setting up some `Fintype` and classical `Decidable` instances.
-/
section SetFiniteConstructors
@[nontriviality]
theorem Finite.of_subsingleton [Subsingleton α] (s : Set α) : s.Finite :=
s.toFinite
#align set.finite.of_subsingleton Set.Finite.of_subsingleton
theorem finite_univ [Finite α] : (@univ α).Finite :=
Set.toFinite _
#align set.finite_univ Set.finite_univ
theorem finite_univ_iff : (@univ α).Finite ↔ Finite α := (Equiv.Set.univ α).finite_iff
#align set.finite_univ_iff Set.finite_univ_iff
alias ⟨_root_.Finite.of_finite_univ, _⟩ := finite_univ_iff
#align finite.of_finite_univ Finite.of_finite_univ
theorem Finite.subset {s : Set α} (hs : s.Finite) {t : Set α} (ht : t ⊆ s) : t.Finite := by
have := hs.to_subtype
exact Finite.Set.subset _ ht
#align set.finite.subset Set.Finite.subset
theorem Finite.union {s t : Set α} (hs : s.Finite) (ht : t.Finite) : (s ∪ t).Finite := by
rw [Set.Finite] at hs ht
apply toFinite
#align set.finite.union Set.Finite.union
theorem Finite.finite_of_compl {s : Set α} (hs : s.Finite) (hsc : sᶜ.Finite) : Finite α := by
rw [← finite_univ_iff, ← union_compl_self s]
exact hs.union hsc
#align set.finite.finite_of_compl Set.Finite.finite_of_compl
theorem Finite.sup {s t : Set α} : s.Finite → t.Finite → (s ⊔ t).Finite :=
Finite.union
#align set.finite.sup Set.Finite.sup
theorem Finite.sep {s : Set α} (hs : s.Finite) (p : α → Prop) : { a ∈ s | p a }.Finite :=
hs.subset <| sep_subset _ _
#align set.finite.sep Set.Finite.sep
theorem Finite.inter_of_left {s : Set α} (hs : s.Finite) (t : Set α) : (s ∩ t).Finite :=
hs.subset inter_subset_left
#align set.finite.inter_of_left Set.Finite.inter_of_left
theorem Finite.inter_of_right {s : Set α} (hs : s.Finite) (t : Set α) : (t ∩ s).Finite :=
hs.subset inter_subset_right
#align set.finite.inter_of_right Set.Finite.inter_of_right
theorem Finite.inf_of_left {s : Set α} (h : s.Finite) (t : Set α) : (s ⊓ t).Finite :=
h.inter_of_left t
#align set.finite.inf_of_left Set.Finite.inf_of_left
theorem Finite.inf_of_right {s : Set α} (h : s.Finite) (t : Set α) : (t ⊓ s).Finite :=
h.inter_of_right t
#align set.finite.inf_of_right Set.Finite.inf_of_right
protected lemma Infinite.mono {s t : Set α} (h : s ⊆ t) : s.Infinite → t.Infinite :=
mt fun ht ↦ ht.subset h
#align set.infinite.mono Set.Infinite.mono
theorem Finite.diff {s : Set α} (hs : s.Finite) (t : Set α) : (s \ t).Finite :=
hs.subset diff_subset
#align set.finite.diff Set.Finite.diff
theorem Finite.of_diff {s t : Set α} (hd : (s \ t).Finite) (ht : t.Finite) : s.Finite :=
(hd.union ht).subset <| subset_diff_union _ _
#align set.finite.of_diff Set.Finite.of_diff
theorem finite_iUnion [Finite ι] {f : ι → Set α} (H : ∀ i, (f i).Finite) : (⋃ i, f i).Finite :=
haveI := fun i => (H i).to_subtype
toFinite _
#align set.finite_Union Set.finite_iUnion
/-- Dependent version of `Finite.biUnion`. -/
theorem Finite.biUnion' {ι} {s : Set ι} (hs : s.Finite) {t : ∀ i ∈ s, Set α}
(ht : ∀ i (hi : i ∈ s), (t i hi).Finite) : (⋃ i ∈ s, t i ‹_›).Finite := by
have := hs.to_subtype
rw [biUnion_eq_iUnion]
apply finite_iUnion fun i : s => ht i.1 i.2
#align set.finite.bUnion' Set.Finite.biUnion'
theorem Finite.biUnion {ι} {s : Set ι} (hs : s.Finite) {t : ι → Set α}
(ht : ∀ i ∈ s, (t i).Finite) : (⋃ i ∈ s, t i).Finite :=
hs.biUnion' ht
#align set.finite.bUnion Set.Finite.biUnion
theorem Finite.sUnion {s : Set (Set α)} (hs : s.Finite) (H : ∀ t ∈ s, Set.Finite t) :
(⋃₀ s).Finite := by
simpa only [sUnion_eq_biUnion] using hs.biUnion H
#align set.finite.sUnion Set.Finite.sUnion
theorem Finite.sInter {α : Type*} {s : Set (Set α)} {t : Set α} (ht : t ∈ s) (hf : t.Finite) :
(⋂₀ s).Finite :=
hf.subset (sInter_subset_of_mem ht)
#align set.finite.sInter Set.Finite.sInter
/-- If sets `s i` are finite for all `i` from a finite set `t` and are empty for `i ∉ t`, then the
union `⋃ i, s i` is a finite set. -/
theorem Finite.iUnion {ι : Type*} {s : ι → Set α} {t : Set ι} (ht : t.Finite)
(hs : ∀ i ∈ t, (s i).Finite) (he : ∀ i, i ∉ t → s i = ∅) : (⋃ i, s i).Finite := by
suffices ⋃ i, s i ⊆ ⋃ i ∈ t, s i by exact (ht.biUnion hs).subset this
refine iUnion_subset fun i x hx => ?_
by_cases hi : i ∈ t
· exact mem_biUnion hi hx
· rw [he i hi, mem_empty_iff_false] at hx
contradiction
#align set.finite.Union Set.Finite.iUnion
section monad
attribute [local instance] Set.monad
theorem Finite.bind {α β} {s : Set α} {f : α → Set β} (h : s.Finite) (hf : ∀ a ∈ s, (f a).Finite) :
(s >>= f).Finite :=
h.biUnion hf
#align set.finite.bind Set.Finite.bind
end monad
@[simp]
theorem finite_empty : (∅ : Set α).Finite :=
toFinite _
#align set.finite_empty Set.finite_empty
protected theorem Infinite.nonempty {s : Set α} (h : s.Infinite) : s.Nonempty :=
nonempty_iff_ne_empty.2 <| by
rintro rfl
exact h finite_empty
#align set.infinite.nonempty Set.Infinite.nonempty
@[simp]
theorem finite_singleton (a : α) : ({a} : Set α).Finite :=
toFinite _
#align set.finite_singleton Set.finite_singleton
theorem finite_pure (a : α) : (pure a : Set α).Finite :=
toFinite _
#align set.finite_pure Set.finite_pure
@[simp]
protected theorem Finite.insert (a : α) {s : Set α} (hs : s.Finite) : (insert a s).Finite :=
(finite_singleton a).union hs
#align set.finite.insert Set.Finite.insert
theorem Finite.image {s : Set α} (f : α → β) (hs : s.Finite) : (f '' s).Finite := by
have := hs.to_subtype
apply toFinite
#align set.finite.image Set.Finite.image
theorem finite_range (f : ι → α) [Finite ι] : (range f).Finite :=
toFinite _
#align set.finite_range Set.finite_range
lemma Finite.of_surjOn {s : Set α} {t : Set β} (f : α → β) (hf : SurjOn f s t) (hs : s.Finite) :
t.Finite := (hs.image _).subset hf
theorem Finite.dependent_image {s : Set α} (hs : s.Finite) (F : ∀ i ∈ s, β) :
{y : β | ∃ x hx, F x hx = y}.Finite := by
have := hs.to_subtype
simpa [range] using finite_range fun x : s => F x x.2
#align set.finite.dependent_image Set.Finite.dependent_image
theorem Finite.map {α β} {s : Set α} : ∀ f : α → β, s.Finite → (f <$> s).Finite :=
Finite.image
#align set.finite.map Set.Finite.map
theorem Finite.of_finite_image {s : Set α} {f : α → β} (h : (f '' s).Finite) (hi : Set.InjOn f s) :
s.Finite :=
have := h.to_subtype
.of_injective _ hi.bijOn_image.bijective.injective
#align set.finite.of_finite_image Set.Finite.of_finite_image
section preimage
variable {f : α → β} {s : Set β}
theorem finite_of_finite_preimage (h : (f ⁻¹' s).Finite) (hs : s ⊆ range f) : s.Finite := by
rw [← image_preimage_eq_of_subset hs]
exact Finite.image f h
#align set.finite_of_finite_preimage Set.finite_of_finite_preimage
theorem Finite.of_preimage (h : (f ⁻¹' s).Finite) (hf : Surjective f) : s.Finite :=
hf.image_preimage s ▸ h.image _
#align set.finite.of_preimage Set.Finite.of_preimage
theorem Finite.preimage (I : Set.InjOn f (f ⁻¹' s)) (h : s.Finite) : (f ⁻¹' s).Finite :=
(h.subset (image_preimage_subset f s)).of_finite_image I
#align set.finite.preimage Set.Finite.preimage
protected lemma Infinite.preimage (hs : s.Infinite) (hf : s ⊆ range f) : (f ⁻¹' s).Infinite :=
fun h ↦ hs <| finite_of_finite_preimage h hf
lemma Infinite.preimage' (hs : (s ∩ range f).Infinite) : (f ⁻¹' s).Infinite :=
(hs.preimage inter_subset_right).mono <| preimage_mono inter_subset_left
theorem Finite.preimage_embedding {s : Set β} (f : α ↪ β) (h : s.Finite) : (f ⁻¹' s).Finite :=
h.preimage fun _ _ _ _ h' => f.injective h'
#align set.finite.preimage_embedding Set.Finite.preimage_embedding
end preimage
theorem finite_lt_nat (n : ℕ) : Set.Finite { i | i < n } :=
toFinite _
#align set.finite_lt_nat Set.finite_lt_nat
theorem finite_le_nat (n : ℕ) : Set.Finite { i | i ≤ n } :=
toFinite _
#align set.finite_le_nat Set.finite_le_nat
section MapsTo
variable {s : Set α} {f : α → α} (hs : s.Finite) (hm : MapsTo f s s)
theorem Finite.surjOn_iff_bijOn_of_mapsTo : SurjOn f s s ↔ BijOn f s s := by
refine ⟨fun h ↦ ⟨hm, ?_, h⟩, BijOn.surjOn⟩
have : Finite s := finite_coe_iff.mpr hs
exact hm.restrict_inj.mp (Finite.injective_iff_surjective.mpr <| hm.restrict_surjective_iff.mpr h)
theorem Finite.injOn_iff_bijOn_of_mapsTo : InjOn f s ↔ BijOn f s s := by
refine ⟨fun h ↦ ⟨hm, h, ?_⟩, BijOn.injOn⟩
have : Finite s := finite_coe_iff.mpr hs
exact hm.restrict_surjective_iff.mp (Finite.injective_iff_surjective.mp <| hm.restrict_inj.mpr h)
end MapsTo
section Prod
variable {s : Set α} {t : Set β}
protected theorem Finite.prod (hs : s.Finite) (ht : t.Finite) : (s ×ˢ t : Set (α × β)).Finite := by
have := hs.to_subtype
have := ht.to_subtype
apply toFinite
#align set.finite.prod Set.Finite.prod
theorem Finite.of_prod_left (h : (s ×ˢ t : Set (α × β)).Finite) : t.Nonempty → s.Finite :=
fun ⟨b, hb⟩ => (h.image Prod.fst).subset fun a ha => ⟨(a, b), ⟨ha, hb⟩, rfl⟩
#align set.finite.of_prod_left Set.Finite.of_prod_left
theorem Finite.of_prod_right (h : (s ×ˢ t : Set (α × β)).Finite) : s.Nonempty → t.Finite :=
fun ⟨a, ha⟩ => (h.image Prod.snd).subset fun b hb => ⟨(a, b), ⟨ha, hb⟩, rfl⟩
#align set.finite.of_prod_right Set.Finite.of_prod_right
protected theorem Infinite.prod_left (hs : s.Infinite) (ht : t.Nonempty) : (s ×ˢ t).Infinite :=
fun h => hs <| h.of_prod_left ht
#align set.infinite.prod_left Set.Infinite.prod_left
protected theorem Infinite.prod_right (ht : t.Infinite) (hs : s.Nonempty) : (s ×ˢ t).Infinite :=
fun h => ht <| h.of_prod_right hs
#align set.infinite.prod_right Set.Infinite.prod_right
protected theorem infinite_prod :
(s ×ˢ t).Infinite ↔ s.Infinite ∧ t.Nonempty ∨ t.Infinite ∧ s.Nonempty := by
refine ⟨fun h => ?_, ?_⟩
· simp_rw [Set.Infinite, @and_comm ¬_, ← Classical.not_imp]
by_contra!
exact h ((this.1 h.nonempty.snd).prod <| this.2 h.nonempty.fst)
· rintro (h | h)
· exact h.1.prod_left h.2
· exact h.1.prod_right h.2
#align set.infinite_prod Set.infinite_prod
theorem finite_prod : (s ×ˢ t).Finite ↔ (s.Finite ∨ t = ∅) ∧ (t.Finite ∨ s = ∅) := by
simp only [← not_infinite, Set.infinite_prod, not_or, not_and_or, not_nonempty_iff_eq_empty]
#align set.finite_prod Set.finite_prod
protected theorem Finite.offDiag {s : Set α} (hs : s.Finite) : s.offDiag.Finite :=
(hs.prod hs).subset s.offDiag_subset_prod
#align set.finite.off_diag Set.Finite.offDiag
protected theorem Finite.image2 (f : α → β → γ) (hs : s.Finite) (ht : t.Finite) :
(image2 f s t).Finite := by
have := hs.to_subtype
have := ht.to_subtype
apply toFinite
#align set.finite.image2 Set.Finite.image2
end Prod
theorem Finite.seq {f : Set (α → β)} {s : Set α} (hf : f.Finite) (hs : s.Finite) :
(f.seq s).Finite :=
hf.image2 _ hs
#align set.finite.seq Set.Finite.seq
theorem Finite.seq' {α β : Type u} {f : Set (α → β)} {s : Set α} (hf : f.Finite) (hs : s.Finite) :
(f <*> s).Finite :=
hf.seq hs
#align set.finite.seq' Set.Finite.seq'
theorem finite_mem_finset (s : Finset α) : { a | a ∈ s }.Finite :=
toFinite _
#align set.finite_mem_finset Set.finite_mem_finset
theorem Subsingleton.finite {s : Set α} (h : s.Subsingleton) : s.Finite :=
h.induction_on finite_empty finite_singleton
#align set.subsingleton.finite Set.Subsingleton.finite
theorem Infinite.nontrivial {s : Set α} (hs : s.Infinite) : s.Nontrivial :=
not_subsingleton_iff.1 <| mt Subsingleton.finite hs
theorem finite_preimage_inl_and_inr {s : Set (Sum α β)} :
(Sum.inl ⁻¹' s).Finite ∧ (Sum.inr ⁻¹' s).Finite ↔ s.Finite :=
⟨fun h => image_preimage_inl_union_image_preimage_inr s ▸ (h.1.image _).union (h.2.image _),
fun h => ⟨h.preimage Sum.inl_injective.injOn, h.preimage Sum.inr_injective.injOn⟩⟩
#align set.finite_preimage_inl_and_inr Set.finite_preimage_inl_and_inr
theorem exists_finite_iff_finset {p : Set α → Prop} :
(∃ s : Set α, s.Finite ∧ p s) ↔ ∃ s : Finset α, p ↑s :=
⟨fun ⟨_, hs, hps⟩ => ⟨hs.toFinset, hs.coe_toFinset.symm ▸ hps⟩, fun ⟨s, hs⟩ =>
⟨s, s.finite_toSet, hs⟩⟩
#align set.exists_finite_iff_finset Set.exists_finite_iff_finset
/-- There are finitely many subsets of a given finite set -/
theorem Finite.finite_subsets {α : Type u} {a : Set α} (h : a.Finite) : { b | b ⊆ a }.Finite := by
convert ((Finset.powerset h.toFinset).map Finset.coeEmb.1).finite_toSet
ext s
simpa [← @exists_finite_iff_finset α fun t => t ⊆ a ∧ t = s, Finite.subset_toFinset,
← and_assoc, Finset.coeEmb] using h.subset
#align set.finite.finite_subsets Set.Finite.finite_subsets
section Pi
variable {ι : Type*} [Finite ι] {κ : ι → Type*} {t : ∀ i, Set (κ i)}
/-- Finite product of finite sets is finite -/
theorem Finite.pi (ht : ∀ i, (t i).Finite) : (pi univ t).Finite := by
cases nonempty_fintype ι
lift t to ∀ d, Finset (κ d) using ht
classical
rw [← Fintype.coe_piFinset]
apply Finset.finite_toSet
#align set.finite.pi Set.Finite.pi
/-- Finite product of finite sets is finite. Note this is a variant of `Set.Finite.pi` without the
extra `i ∈ univ` binder. -/
lemma Finite.pi' (ht : ∀ i, (t i).Finite) : {f : ∀ i, κ i | ∀ i, f i ∈ t i}.Finite := by
simpa [Set.pi] using Finite.pi ht
end Pi
/-- A finite union of finsets is finite. -/
theorem union_finset_finite_of_range_finite (f : α → Finset β) (h : (range f).Finite) :
(⋃ a, (f a : Set β)).Finite := by
rw [← biUnion_range]
exact h.biUnion fun y _ => y.finite_toSet
#align set.union_finset_finite_of_range_finite Set.union_finset_finite_of_range_finite
theorem finite_range_ite {p : α → Prop} [DecidablePred p] {f g : α → β} (hf : (range f).Finite)
(hg : (range g).Finite) : (range fun x => if p x then f x else g x).Finite :=
(hf.union hg).subset range_ite_subset
#align set.finite_range_ite Set.finite_range_ite
theorem finite_range_const {c : β} : (range fun _ : α => c).Finite :=
(finite_singleton c).subset range_const_subset
#align set.finite_range_const Set.finite_range_const
end SetFiniteConstructors
/-! ### Properties -/
instance Finite.inhabited : Inhabited { s : Set α // s.Finite } :=
⟨⟨∅, finite_empty⟩⟩
#align set.finite.inhabited Set.Finite.inhabited
@[simp]
theorem finite_union {s t : Set α} : (s ∪ t).Finite ↔ s.Finite ∧ t.Finite :=
⟨fun h => ⟨h.subset subset_union_left, h.subset subset_union_right⟩, fun ⟨hs, ht⟩ =>
hs.union ht⟩
#align set.finite_union Set.finite_union
theorem finite_image_iff {s : Set α} {f : α → β} (hi : InjOn f s) : (f '' s).Finite ↔ s.Finite :=
⟨fun h => h.of_finite_image hi, Finite.image _⟩
#align set.finite_image_iff Set.finite_image_iff
theorem univ_finite_iff_nonempty_fintype : (univ : Set α).Finite ↔ Nonempty (Fintype α) :=
⟨fun h => ⟨fintypeOfFiniteUniv h⟩, fun ⟨_i⟩ => finite_univ⟩
#align set.univ_finite_iff_nonempty_fintype Set.univ_finite_iff_nonempty_fintype
-- Porting note: moved `@[simp]` to `Set.toFinset_singleton` because `simp` can now simplify LHS
theorem Finite.toFinset_singleton {a : α} (ha : ({a} : Set α).Finite := finite_singleton _) :
ha.toFinset = {a} :=
Set.toFinite_toFinset _
#align set.finite.to_finset_singleton Set.Finite.toFinset_singleton
@[simp]
theorem Finite.toFinset_insert [DecidableEq α] {s : Set α} {a : α} (hs : (insert a s).Finite) :
hs.toFinset = insert a (hs.subset <| subset_insert _ _).toFinset :=
Finset.ext <| by simp
#align set.finite.to_finset_insert Set.Finite.toFinset_insert
theorem Finite.toFinset_insert' [DecidableEq α] {a : α} {s : Set α} (hs : s.Finite) :
(hs.insert a).toFinset = insert a hs.toFinset :=
Finite.toFinset_insert _
#align set.finite.to_finset_insert' Set.Finite.toFinset_insert'
theorem Finite.toFinset_prod {s : Set α} {t : Set β} (hs : s.Finite) (ht : t.Finite) :
hs.toFinset ×ˢ ht.toFinset = (hs.prod ht).toFinset :=
Finset.ext <| by simp
#align set.finite.to_finset_prod Set.Finite.toFinset_prod
theorem Finite.toFinset_offDiag {s : Set α} [DecidableEq α] (hs : s.Finite) :
hs.offDiag.toFinset = hs.toFinset.offDiag :=
Finset.ext <| by simp
#align set.finite.to_finset_off_diag Set.Finite.toFinset_offDiag
theorem Finite.fin_embedding {s : Set α} (h : s.Finite) :
∃ (n : ℕ) (f : Fin n ↪ α), range f = s :=
⟨_, (Fintype.equivFin (h.toFinset : Set α)).symm.asEmbedding, by
simp only [Finset.coe_sort_coe, Equiv.asEmbedding_range, Finite.coe_toFinset, setOf_mem_eq]⟩
#align set.finite.fin_embedding Set.Finite.fin_embedding
theorem Finite.fin_param {s : Set α} (h : s.Finite) :
∃ (n : ℕ) (f : Fin n → α), Injective f ∧ range f = s :=
let ⟨n, f, hf⟩ := h.fin_embedding
⟨n, f, f.injective, hf⟩
#align set.finite.fin_param Set.Finite.fin_param
theorem finite_option {s : Set (Option α)} : s.Finite ↔ { x : α | some x ∈ s }.Finite :=
⟨fun h => h.preimage_embedding Embedding.some, fun h =>
((h.image some).insert none).subset fun x =>
x.casesOn (fun _ => Or.inl rfl) fun _ hx => Or.inr <| mem_image_of_mem _ hx⟩
#align set.finite_option Set.finite_option
theorem finite_image_fst_and_snd_iff {s : Set (α × β)} :
(Prod.fst '' s).Finite ∧ (Prod.snd '' s).Finite ↔ s.Finite :=
⟨fun h => (h.1.prod h.2).subset fun _ h => ⟨mem_image_of_mem _ h, mem_image_of_mem _ h⟩,
fun h => ⟨h.image _, h.image _⟩⟩
#align set.finite_image_fst_and_snd_iff Set.finite_image_fst_and_snd_iff
theorem forall_finite_image_eval_iff {δ : Type*} [Finite δ] {κ : δ → Type*} {s : Set (∀ d, κ d)} :
(∀ d, (eval d '' s).Finite) ↔ s.Finite :=
⟨fun h => (Finite.pi h).subset <| subset_pi_eval_image _ _, fun h _ => h.image _⟩
#align set.forall_finite_image_eval_iff Set.forall_finite_image_eval_iff
theorem finite_subset_iUnion {s : Set α} (hs : s.Finite) {ι} {t : ι → Set α} (h : s ⊆ ⋃ i, t i) :
∃ I : Set ι, I.Finite ∧ s ⊆ ⋃ i ∈ I, t i := by
have := hs.to_subtype
choose f hf using show ∀ x : s, ∃ i, x.1 ∈ t i by simpa [subset_def] using h
refine ⟨range f, finite_range f, fun x hx => ?_⟩
rw [biUnion_range, mem_iUnion]
exact ⟨⟨x, hx⟩, hf _⟩
#align set.finite_subset_Union Set.finite_subset_iUnion
theorem eq_finite_iUnion_of_finite_subset_iUnion {ι} {s : ι → Set α} {t : Set α} (tfin : t.Finite)
(h : t ⊆ ⋃ i, s i) :
∃ I : Set ι,
I.Finite ∧
∃ σ : { i | i ∈ I } → Set α, (∀ i, (σ i).Finite) ∧ (∀ i, σ i ⊆ s i) ∧ t = ⋃ i, σ i :=
let ⟨I, Ifin, hI⟩ := finite_subset_iUnion tfin h
⟨I, Ifin, fun x => s x ∩ t, fun i => tfin.subset inter_subset_right, fun i =>
inter_subset_left, by
ext x
rw [mem_iUnion]
constructor
· intro x_in
rcases mem_iUnion.mp (hI x_in) with ⟨i, _, ⟨hi, rfl⟩, H⟩
exact ⟨⟨i, hi⟩, ⟨H, x_in⟩⟩
· rintro ⟨i, -, H⟩
exact H⟩
#align set.eq_finite_Union_of_finite_subset_Union Set.eq_finite_iUnion_of_finite_subset_iUnion
@[elab_as_elim]
theorem Finite.induction_on {C : Set α → Prop} {s : Set α} (h : s.Finite) (H0 : C ∅)
(H1 : ∀ {a s}, a ∉ s → Set.Finite s → C s → C (insert a s)) : C s := by
lift s to Finset α using h
induction' s using Finset.cons_induction_on with a s ha hs
· rwa [Finset.coe_empty]
· rw [Finset.coe_cons]
exact @H1 a s ha (Set.toFinite _) hs
#align set.finite.induction_on Set.Finite.induction_on
/-- Analogous to `Finset.induction_on'`. -/
@[elab_as_elim]
theorem Finite.induction_on' {C : Set α → Prop} {S : Set α} (h : S.Finite) (H0 : C ∅)
(H1 : ∀ {a s}, a ∈ S → s ⊆ S → a ∉ s → C s → C (insert a s)) : C S := by
refine @Set.Finite.induction_on α (fun s => s ⊆ S → C s) S h (fun _ => H0) ?_ Subset.rfl
intro a s has _ hCs haS
rw [insert_subset_iff] at haS
exact H1 haS.1 haS.2 has (hCs haS.2)
#align set.finite.induction_on' Set.Finite.induction_on'
@[elab_as_elim]
theorem Finite.dinduction_on {C : ∀ s : Set α, s.Finite → Prop} (s : Set α) (h : s.Finite)
(H0 : C ∅ finite_empty)
(H1 : ∀ {a s}, a ∉ s → ∀ h : Set.Finite s, C s h → C (insert a s) (h.insert a)) : C s h :=
have : ∀ h : s.Finite, C s h :=
Finite.induction_on h (fun _ => H0) fun has hs ih _ => H1 has hs (ih _)
this h
#align set.finite.dinduction_on Set.Finite.dinduction_on
/-- Induction up to a finite set `S`. -/
theorem Finite.induction_to {C : Set α → Prop} {S : Set α} (h : S.Finite)
(S0 : Set α) (hS0 : S0 ⊆ S) (H0 : C S0) (H1 : ∀ s ⊂ S, C s → ∃ a ∈ S \ s, C (insert a s)) :
C S := by
have : Finite S := Finite.to_subtype h
have : Finite {T : Set α // T ⊆ S} := Finite.of_equiv (Set S) (Equiv.Set.powerset S).symm
rw [← Subtype.coe_mk (p := (· ⊆ S)) _ le_rfl]
rw [← Subtype.coe_mk (p := (· ⊆ S)) _ hS0] at H0
refine Finite.to_wellFoundedGT.wf.induction_bot' (fun s hs hs' ↦ ?_) H0
obtain ⟨a, ⟨ha1, ha2⟩, ha'⟩ := H1 s (ssubset_of_ne_of_subset hs s.2) hs'
exact ⟨⟨insert a s.1, insert_subset ha1 s.2⟩, Set.ssubset_insert ha2, ha'⟩
/-- Induction up to `univ`. -/
theorem Finite.induction_to_univ [Finite α] {C : Set α → Prop} (S0 : Set α)
(H0 : C S0) (H1 : ∀ S ≠ univ, C S → ∃ a ∉ S, C (insert a S)) : C univ :=
finite_univ.induction_to S0 (subset_univ S0) H0 (by simpa [ssubset_univ_iff])
section
attribute [local instance] Nat.fintypeIio
/-- If `P` is some relation between terms of `γ` and sets in `γ`, such that every finite set
`t : Set γ` has some `c : γ` related to it, then there is a recursively defined sequence `u` in `γ`
so `u n` is related to the image of `{0, 1, ..., n-1}` under `u`.
(We use this later to show sequentially compact sets are totally bounded.)
-/
theorem seq_of_forall_finite_exists {γ : Type*} {P : γ → Set γ → Prop}
(h : ∀ t : Set γ, t.Finite → ∃ c, P c t) : ∃ u : ℕ → γ, ∀ n, P (u n) (u '' Iio n) := by
haveI : Nonempty γ := (h ∅ finite_empty).nonempty
choose! c hc using h
set f : (n : ℕ) → (g : (m : ℕ) → m < n → γ) → γ := fun n g => c (range fun k : Iio n => g k.1 k.2)
set u : ℕ → γ := fun n => Nat.strongRecOn' n f
refine ⟨u, fun n => ?_⟩
convert hc (u '' Iio n) ((finite_lt_nat _).image _)
rw [image_eq_range]
exact Nat.strongRecOn'_beta
#align set.seq_of_forall_finite_exists Set.seq_of_forall_finite_exists
end
/-! ### Cardinality -/
theorem empty_card : Fintype.card (∅ : Set α) = 0 :=
rfl
#align set.empty_card Set.empty_card
theorem empty_card' {h : Fintype.{u} (∅ : Set α)} : @Fintype.card (∅ : Set α) h = 0 := by
simp
#align set.empty_card' Set.empty_card'
theorem card_fintypeInsertOfNotMem {a : α} (s : Set α) [Fintype s] (h : a ∉ s) :
@Fintype.card _ (fintypeInsertOfNotMem s h) = Fintype.card s + 1 := by
simp [fintypeInsertOfNotMem, Fintype.card_ofFinset]
#align set.card_fintype_insert_of_not_mem Set.card_fintypeInsertOfNotMem
@[simp]
theorem card_insert {a : α} (s : Set α) [Fintype s] (h : a ∉ s)
{d : Fintype.{u} (insert a s : Set α)} : @Fintype.card _ d = Fintype.card s + 1 := by
rw [← card_fintypeInsertOfNotMem s h]; congr; exact Subsingleton.elim _ _
#align set.card_insert Set.card_insert
theorem card_image_of_inj_on {s : Set α} [Fintype s] {f : α → β} [Fintype (f '' s)]
(H : ∀ x ∈ s, ∀ y ∈ s, f x = f y → x = y) : Fintype.card (f '' s) = Fintype.card s :=
haveI := Classical.propDecidable
calc
Fintype.card (f '' s) = (s.toFinset.image f).card := Fintype.card_of_finset' _ (by simp)
_ = s.toFinset.card :=
Finset.card_image_of_injOn fun x hx y hy hxy =>
H x (mem_toFinset.1 hx) y (mem_toFinset.1 hy) hxy
_ = Fintype.card s := (Fintype.card_of_finset' _ fun a => mem_toFinset).symm
#align set.card_image_of_inj_on Set.card_image_of_inj_on
theorem card_image_of_injective (s : Set α) [Fintype s] {f : α → β} [Fintype (f '' s)]
(H : Function.Injective f) : Fintype.card (f '' s) = Fintype.card s :=
card_image_of_inj_on fun _ _ _ _ h => H h
#align set.card_image_of_injective Set.card_image_of_injective
@[simp]
theorem card_singleton (a : α) : Fintype.card ({a} : Set α) = 1 :=
Fintype.card_ofSubsingleton _
#align set.card_singleton Set.card_singleton
theorem card_lt_card {s t : Set α} [Fintype s] [Fintype t] (h : s ⊂ t) :
Fintype.card s < Fintype.card t :=
Fintype.card_lt_of_injective_not_surjective (Set.inclusion h.1) (Set.inclusion_injective h.1)
fun hst => (ssubset_iff_subset_ne.1 h).2 (eq_of_inclusion_surjective hst)
#align set.card_lt_card Set.card_lt_card
theorem card_le_card {s t : Set α} [Fintype s] [Fintype t] (hsub : s ⊆ t) :
Fintype.card s ≤ Fintype.card t :=
Fintype.card_le_of_injective (Set.inclusion hsub) (Set.inclusion_injective hsub)
#align set.card_le_card Set.card_le_card
theorem eq_of_subset_of_card_le {s t : Set α} [Fintype s] [Fintype t] (hsub : s ⊆ t)
(hcard : Fintype.card t ≤ Fintype.card s) : s = t :=
(eq_or_ssubset_of_subset hsub).elim id fun h => absurd hcard <| not_le_of_lt <| card_lt_card h
#align set.eq_of_subset_of_card_le Set.eq_of_subset_of_card_le
theorem card_range_of_injective [Fintype α] {f : α → β} (hf : Injective f) [Fintype (range f)] :
Fintype.card (range f) = Fintype.card α :=
Eq.symm <| Fintype.card_congr <| Equiv.ofInjective f hf
#align set.card_range_of_injective Set.card_range_of_injective
theorem Finite.card_toFinset {s : Set α} [Fintype s] (h : s.Finite) :
h.toFinset.card = Fintype.card s :=
Eq.symm <| Fintype.card_of_finset' _ fun _ ↦ h.mem_toFinset
#align set.finite.card_to_finset Set.Finite.card_toFinset
theorem card_ne_eq [Fintype α] (a : α) [Fintype { x : α | x ≠ a }] :
Fintype.card { x : α | x ≠ a } = Fintype.card α - 1 := by
haveI := Classical.decEq α
rw [← toFinset_card, toFinset_setOf, Finset.filter_ne',
Finset.card_erase_of_mem (Finset.mem_univ _), Finset.card_univ]
#align set.card_ne_eq Set.card_ne_eq
/-! ### Infinite sets -/
variable {s t : Set α}
theorem infinite_univ_iff : (@univ α).Infinite ↔ Infinite α := by
rw [Set.Infinite, finite_univ_iff, not_finite_iff_infinite]
#align set.infinite_univ_iff Set.infinite_univ_iff
theorem infinite_univ [h : Infinite α] : (@univ α).Infinite :=
infinite_univ_iff.2 h
#align set.infinite_univ Set.infinite_univ
theorem infinite_coe_iff {s : Set α} : Infinite s ↔ s.Infinite :=
not_finite_iff_infinite.symm.trans finite_coe_iff.not
#align set.infinite_coe_iff Set.infinite_coe_iff
-- Porting note: something weird happened here
alias ⟨_, Infinite.to_subtype⟩ := infinite_coe_iff
#align set.infinite.to_subtype Set.Infinite.to_subtype
lemma Infinite.exists_not_mem_finite (hs : s.Infinite) (ht : t.Finite) : ∃ a, a ∈ s ∧ a ∉ t := by
by_contra! h; exact hs <| ht.subset h
lemma Infinite.exists_not_mem_finset (hs : s.Infinite) (t : Finset α) : ∃ a ∈ s, a ∉ t :=
hs.exists_not_mem_finite t.finite_toSet
#align set.infinite.exists_not_mem_finset Set.Infinite.exists_not_mem_finset
section Infinite
variable [Infinite α]
lemma Finite.exists_not_mem (hs : s.Finite) : ∃ a, a ∉ s := by
by_contra! h; exact infinite_univ (hs.subset fun a _ ↦ h _)
lemma _root_.Finset.exists_not_mem (s : Finset α) : ∃ a, a ∉ s := s.finite_toSet.exists_not_mem
end Infinite
/-- Embedding of `ℕ` into an infinite set. -/
noncomputable def Infinite.natEmbedding (s : Set α) (h : s.Infinite) : ℕ ↪ s :=
h.to_subtype.natEmbedding
#align set.infinite.nat_embedding Set.Infinite.natEmbedding
theorem Infinite.exists_subset_card_eq {s : Set α} (hs : s.Infinite) (n : ℕ) :
∃ t : Finset α, ↑t ⊆ s ∧ t.card = n :=
⟨((Finset.range n).map (hs.natEmbedding _)).map (Embedding.subtype _), by simp⟩
#align set.infinite.exists_subset_card_eq Set.Infinite.exists_subset_card_eq
theorem infinite_of_finite_compl [Infinite α] {s : Set α} (hs : sᶜ.Finite) : s.Infinite := fun h =>
Set.infinite_univ (by simpa using hs.union h)
#align set.infinite_of_finite_compl Set.infinite_of_finite_compl
theorem Finite.infinite_compl [Infinite α] {s : Set α} (hs : s.Finite) : sᶜ.Infinite := fun h =>
Set.infinite_univ (by simpa using hs.union h)
#align set.finite.infinite_compl Set.Finite.infinite_compl
theorem Infinite.diff {s t : Set α} (hs : s.Infinite) (ht : t.Finite) : (s \ t).Infinite := fun h =>
hs <| h.of_diff ht
#align set.infinite.diff Set.Infinite.diff
@[simp]
theorem infinite_union {s t : Set α} : (s ∪ t).Infinite ↔ s.Infinite ∨ t.Infinite := by
simp only [Set.Infinite, finite_union, not_and_or]
#align set.infinite_union Set.infinite_union
theorem Infinite.of_image (f : α → β) {s : Set α} (hs : (f '' s).Infinite) : s.Infinite :=
mt (Finite.image f) hs
#align set.infinite.of_image Set.Infinite.of_image
theorem infinite_image_iff {s : Set α} {f : α → β} (hi : InjOn f s) :
(f '' s).Infinite ↔ s.Infinite :=
not_congr <| finite_image_iff hi
#align set.infinite_image_iff Set.infinite_image_iff
theorem infinite_range_iff {f : α → β} (hi : Injective f) :
(range f).Infinite ↔ Infinite α := by
rw [← image_univ, infinite_image_iff hi.injOn, infinite_univ_iff]
alias ⟨_, Infinite.image⟩ := infinite_image_iff
#align set.infinite.image Set.Infinite.image
-- Porting note: attribute [protected] doesn't work
-- attribute [protected] infinite.image
section Image2
variable {f : α → β → γ} {s : Set α} {t : Set β} {a : α} {b : β}
protected theorem Infinite.image2_left (hs : s.Infinite) (hb : b ∈ t)
(hf : InjOn (fun a => f a b) s) : (image2 f s t).Infinite :=
(hs.image hf).mono <| image_subset_image2_left hb
#align set.infinite.image2_left Set.Infinite.image2_left
protected theorem Infinite.image2_right (ht : t.Infinite) (ha : a ∈ s) (hf : InjOn (f a) t) :
(image2 f s t).Infinite :=
(ht.image hf).mono <| image_subset_image2_right ha
#align set.infinite.image2_right Set.Infinite.image2_right
theorem infinite_image2 (hfs : ∀ b ∈ t, InjOn (fun a => f a b) s) (hft : ∀ a ∈ s, InjOn (f a) t) :
(image2 f s t).Infinite ↔ s.Infinite ∧ t.Nonempty ∨ t.Infinite ∧ s.Nonempty := by
refine ⟨fun h => Set.infinite_prod.1 ?_, ?_⟩
· rw [← image_uncurry_prod] at h
exact h.of_image _
· rintro (⟨hs, b, hb⟩ | ⟨ht, a, ha⟩)
· exact hs.image2_left hb (hfs _ hb)
· exact ht.image2_right ha (hft _ ha)
#align set.infinite_image2 Set.infinite_image2
lemma finite_image2 (hfs : ∀ b ∈ t, InjOn (f · b) s) (hft : ∀ a ∈ s, InjOn (f a) t) :
(image2 f s t).Finite ↔ s.Finite ∧ t.Finite ∨ s = ∅ ∨ t = ∅ := by
rw [← not_infinite, infinite_image2 hfs hft]
simp [not_or, -not_and, not_and_or, not_nonempty_iff_eq_empty]
aesop
end Image2
theorem infinite_of_injOn_mapsTo {s : Set α} {t : Set β} {f : α → β} (hi : InjOn f s)
(hm : MapsTo f s t) (hs : s.Infinite) : t.Infinite :=
((infinite_image_iff hi).2 hs).mono (mapsTo'.mp hm)
#align set.infinite_of_inj_on_maps_to Set.infinite_of_injOn_mapsTo
theorem Infinite.exists_ne_map_eq_of_mapsTo {s : Set α} {t : Set β} {f : α → β} (hs : s.Infinite)
(hf : MapsTo f s t) (ht : t.Finite) : ∃ x ∈ s, ∃ y ∈ s, x ≠ y ∧ f x = f y := by
contrapose! ht
exact infinite_of_injOn_mapsTo (fun x hx y hy => not_imp_not.1 (ht x hx y hy)) hf hs
#align set.infinite.exists_ne_map_eq_of_maps_to Set.Infinite.exists_ne_map_eq_of_mapsTo
theorem infinite_range_of_injective [Infinite α] {f : α → β} (hi : Injective f) :
(range f).Infinite := by
rw [← image_univ, infinite_image_iff hi.injOn]
exact infinite_univ
#align set.infinite_range_of_injective Set.infinite_range_of_injective
theorem infinite_of_injective_forall_mem [Infinite α] {s : Set β} {f : α → β} (hi : Injective f)
(hf : ∀ x : α, f x ∈ s) : s.Infinite := by
rw [← range_subset_iff] at hf
exact (infinite_range_of_injective hi).mono hf
#align set.infinite_of_injective_forall_mem Set.infinite_of_injective_forall_mem
theorem not_injOn_infinite_finite_image {f : α → β} {s : Set α} (h_inf : s.Infinite)
(h_fin : (f '' s).Finite) : ¬InjOn f s := by
have : Finite (f '' s) := finite_coe_iff.mpr h_fin
have : Infinite s := infinite_coe_iff.mpr h_inf
have h := not_injective_infinite_finite
((f '' s).codRestrict (s.restrict f) fun x => ⟨x, x.property, rfl⟩)
contrapose! h
rwa [injective_codRestrict, ← injOn_iff_injective]
#align set.not_inj_on_infinite_finite_image Set.not_injOn_infinite_finite_image
/-! ### Order properties -/
section Preorder
variable [Preorder α] [Nonempty α] {s : Set α}
theorem infinite_of_forall_exists_gt (h : ∀ a, ∃ b ∈ s, a < b) : s.Infinite := by
inhabit α
set f : ℕ → α := fun n => Nat.recOn n (h default).choose fun _ a => (h a).choose
have hf : ∀ n, f n ∈ s := by rintro (_ | _) <;> exact (h _).choose_spec.1
exact infinite_of_injective_forall_mem
(strictMono_nat_of_lt_succ fun n => (h _).choose_spec.2).injective hf
#align set.infinite_of_forall_exists_gt Set.infinite_of_forall_exists_gt
theorem infinite_of_forall_exists_lt (h : ∀ a, ∃ b ∈ s, b < a) : s.Infinite :=
@infinite_of_forall_exists_gt αᵒᵈ _ _ _ h
#align set.infinite_of_forall_exists_lt Set.infinite_of_forall_exists_lt
end Preorder
theorem finite_isTop (α : Type*) [PartialOrder α] : { x : α | IsTop x }.Finite :=
(subsingleton_isTop α).finite
#align set.finite_is_top Set.finite_isTop
theorem finite_isBot (α : Type*) [PartialOrder α] : { x : α | IsBot x }.Finite :=
(subsingleton_isBot α).finite
#align set.finite_is_bot Set.finite_isBot
theorem Infinite.exists_lt_map_eq_of_mapsTo [LinearOrder α] {s : Set α} {t : Set β} {f : α → β}
(hs : s.Infinite) (hf : MapsTo f s t) (ht : t.Finite) : ∃ x ∈ s, ∃ y ∈ s, x < y ∧ f x = f y :=
let ⟨x, hx, y, hy, hxy, hf⟩ := hs.exists_ne_map_eq_of_mapsTo hf ht
hxy.lt_or_lt.elim (fun hxy => ⟨x, hx, y, hy, hxy, hf⟩) fun hyx => ⟨y, hy, x, hx, hyx, hf.symm⟩
#align set.infinite.exists_lt_map_eq_of_maps_to Set.Infinite.exists_lt_map_eq_of_mapsTo
| Mathlib/Data/Set/Finite.lean | 1,505 | 1,509 | theorem Finite.exists_lt_map_eq_of_forall_mem [LinearOrder α] [Infinite α] {t : Set β} {f : α → β}
(hf : ∀ a, f a ∈ t) (ht : t.Finite) : ∃ a b, a < b ∧ f a = f b := by |
rw [← mapsTo_univ_iff] at hf
obtain ⟨a, -, b, -, h⟩ := infinite_univ.exists_lt_map_eq_of_mapsTo hf ht
exact ⟨a, b, h⟩
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro
-/
import Mathlib.MeasureTheory.Measure.NullMeasurable
import Mathlib.MeasureTheory.MeasurableSpace.Basic
import Mathlib.Topology.Algebra.Order.LiminfLimsup
#align_import measure_theory.measure.measure_space from "leanprover-community/mathlib"@"343e80208d29d2d15f8050b929aa50fe4ce71b55"
/-!
# Measure spaces
The definition of a measure and a measure space are in `MeasureTheory.MeasureSpaceDef`, with
only a few basic properties. This file provides many more properties of these objects.
This separation allows the measurability tactic to import only the file `MeasureSpaceDef`, and to
be available in `MeasureSpace` (through `MeasurableSpace`).
Given a measurable space `α`, a measure on `α` is a function that sends measurable sets to the
extended nonnegative reals that satisfies the following conditions:
1. `μ ∅ = 0`;
2. `μ` is countably additive. This means that the measure of a countable union of pairwise disjoint
sets is equal to the measure of the individual sets.
Every measure can be canonically extended to an outer measure, so that it assigns values to
all subsets, not just the measurable subsets. On the other hand, a measure that is countably
additive on measurable sets can be restricted to measurable sets to obtain a measure.
In this file a measure is defined to be an outer measure that is countably additive on
measurable sets, with the additional assumption that the outer measure is the canonical
extension of the restricted measure.
Measures on `α` form a complete lattice, and are closed under scalar multiplication with `ℝ≥0∞`.
Given a measure, the null sets are the sets where `μ s = 0`, where `μ` denotes the corresponding
outer measure (so `s` might not be measurable). We can then define the completion of `μ` as the
measure on the least `σ`-algebra that also contains all null sets, by defining the measure to be `0`
on the null sets.
## Main statements
* `completion` is the completion of a measure to all null measurable sets.
* `Measure.ofMeasurable` and `OuterMeasure.toMeasure` are two important ways to define a measure.
## Implementation notes
Given `μ : Measure α`, `μ s` is the value of the *outer measure* applied to `s`.
This conveniently allows us to apply the measure to sets without proving that they are measurable.
We get countable subadditivity for all sets, but only countable additivity for measurable sets.
You often don't want to define a measure via its constructor.
Two ways that are sometimes more convenient:
* `Measure.ofMeasurable` is a way to define a measure by only giving its value on measurable sets
and proving the properties (1) and (2) mentioned above.
* `OuterMeasure.toMeasure` is a way of obtaining a measure from an outer measure by showing that
all measurable sets in the measurable space are Carathéodory measurable.
To prove that two measures are equal, there are multiple options:
* `ext`: two measures are equal if they are equal on all measurable sets.
* `ext_of_generateFrom_of_iUnion`: two measures are equal if they are equal on a π-system generating
the measurable sets, if the π-system contains a spanning increasing sequence of sets where the
measures take finite value (in particular the measures are σ-finite). This is a special case of
the more general `ext_of_generateFrom_of_cover`
* `ext_of_generate_finite`: two finite measures are equal if they are equal on a π-system
generating the measurable sets. This is a special case of `ext_of_generateFrom_of_iUnion` using
`C ∪ {univ}`, but is easier to work with.
A `MeasureSpace` is a class that is a measurable space with a canonical measure.
The measure is denoted `volume`.
## References
* <https://en.wikipedia.org/wiki/Measure_(mathematics)>
* <https://en.wikipedia.org/wiki/Complete_measure>
* <https://en.wikipedia.org/wiki/Almost_everywhere>
## Tags
measure, almost everywhere, measure space, completion, null set, null measurable set
-/
noncomputable section
open Set
open Filter hiding map
open Function MeasurableSpace
open scoped Classical symmDiff
open Topology Filter ENNReal NNReal Interval MeasureTheory
variable {α β γ δ ι R R' : Type*}
namespace MeasureTheory
section
variable {m : MeasurableSpace α} {μ μ₁ μ₂ : Measure α} {s s₁ s₂ t : Set α}
instance ae_isMeasurablyGenerated : IsMeasurablyGenerated (ae μ) :=
⟨fun _s hs =>
let ⟨t, hst, htm, htμ⟩ := exists_measurable_superset_of_null hs
⟨tᶜ, compl_mem_ae_iff.2 htμ, htm.compl, compl_subset_comm.1 hst⟩⟩
#align measure_theory.ae_is_measurably_generated MeasureTheory.ae_isMeasurablyGenerated
/-- See also `MeasureTheory.ae_restrict_uIoc_iff`. -/
theorem ae_uIoc_iff [LinearOrder α] {a b : α} {P : α → Prop} :
(∀ᵐ x ∂μ, x ∈ Ι a b → P x) ↔ (∀ᵐ x ∂μ, x ∈ Ioc a b → P x) ∧ ∀ᵐ x ∂μ, x ∈ Ioc b a → P x := by
simp only [uIoc_eq_union, mem_union, or_imp, eventually_and]
#align measure_theory.ae_uIoc_iff MeasureTheory.ae_uIoc_iff
theorem measure_union (hd : Disjoint s₁ s₂) (h : MeasurableSet s₂) : μ (s₁ ∪ s₂) = μ s₁ + μ s₂ :=
measure_union₀ h.nullMeasurableSet hd.aedisjoint
#align measure_theory.measure_union MeasureTheory.measure_union
theorem measure_union' (hd : Disjoint s₁ s₂) (h : MeasurableSet s₁) : μ (s₁ ∪ s₂) = μ s₁ + μ s₂ :=
measure_union₀' h.nullMeasurableSet hd.aedisjoint
#align measure_theory.measure_union' MeasureTheory.measure_union'
theorem measure_inter_add_diff (s : Set α) (ht : MeasurableSet t) : μ (s ∩ t) + μ (s \ t) = μ s :=
measure_inter_add_diff₀ _ ht.nullMeasurableSet
#align measure_theory.measure_inter_add_diff MeasureTheory.measure_inter_add_diff
theorem measure_diff_add_inter (s : Set α) (ht : MeasurableSet t) : μ (s \ t) + μ (s ∩ t) = μ s :=
(add_comm _ _).trans (measure_inter_add_diff s ht)
#align measure_theory.measure_diff_add_inter MeasureTheory.measure_diff_add_inter
theorem measure_union_add_inter (s : Set α) (ht : MeasurableSet t) :
μ (s ∪ t) + μ (s ∩ t) = μ s + μ t := by
rw [← measure_inter_add_diff (s ∪ t) ht, Set.union_inter_cancel_right, union_diff_right, ←
measure_inter_add_diff s ht]
ac_rfl
#align measure_theory.measure_union_add_inter MeasureTheory.measure_union_add_inter
theorem measure_union_add_inter' (hs : MeasurableSet s) (t : Set α) :
μ (s ∪ t) + μ (s ∩ t) = μ s + μ t := by
rw [union_comm, inter_comm, measure_union_add_inter t hs, add_comm]
#align measure_theory.measure_union_add_inter' MeasureTheory.measure_union_add_inter'
lemma measure_symmDiff_eq (hs : MeasurableSet s) (ht : MeasurableSet t) :
μ (s ∆ t) = μ (s \ t) + μ (t \ s) := by
simpa only [symmDiff_def, sup_eq_union] using measure_union disjoint_sdiff_sdiff (ht.diff hs)
lemma measure_symmDiff_le (s t u : Set α) :
μ (s ∆ u) ≤ μ (s ∆ t) + μ (t ∆ u) :=
le_trans (μ.mono <| symmDiff_triangle s t u) (measure_union_le (s ∆ t) (t ∆ u))
theorem measure_add_measure_compl (h : MeasurableSet s) : μ s + μ sᶜ = μ univ :=
measure_add_measure_compl₀ h.nullMeasurableSet
#align measure_theory.measure_add_measure_compl MeasureTheory.measure_add_measure_compl
theorem measure_biUnion₀ {s : Set β} {f : β → Set α} (hs : s.Countable)
(hd : s.Pairwise (AEDisjoint μ on f)) (h : ∀ b ∈ s, NullMeasurableSet (f b) μ) :
μ (⋃ b ∈ s, f b) = ∑' p : s, μ (f p) := by
haveI := hs.toEncodable
rw [biUnion_eq_iUnion]
exact measure_iUnion₀ (hd.on_injective Subtype.coe_injective fun x => x.2) fun x => h x x.2
#align measure_theory.measure_bUnion₀ MeasureTheory.measure_biUnion₀
theorem measure_biUnion {s : Set β} {f : β → Set α} (hs : s.Countable) (hd : s.PairwiseDisjoint f)
(h : ∀ b ∈ s, MeasurableSet (f b)) : μ (⋃ b ∈ s, f b) = ∑' p : s, μ (f p) :=
measure_biUnion₀ hs hd.aedisjoint fun b hb => (h b hb).nullMeasurableSet
#align measure_theory.measure_bUnion MeasureTheory.measure_biUnion
theorem measure_sUnion₀ {S : Set (Set α)} (hs : S.Countable) (hd : S.Pairwise (AEDisjoint μ))
(h : ∀ s ∈ S, NullMeasurableSet s μ) : μ (⋃₀ S) = ∑' s : S, μ s := by
rw [sUnion_eq_biUnion, measure_biUnion₀ hs hd h]
#align measure_theory.measure_sUnion₀ MeasureTheory.measure_sUnion₀
theorem measure_sUnion {S : Set (Set α)} (hs : S.Countable) (hd : S.Pairwise Disjoint)
(h : ∀ s ∈ S, MeasurableSet s) : μ (⋃₀ S) = ∑' s : S, μ s := by
rw [sUnion_eq_biUnion, measure_biUnion hs hd h]
#align measure_theory.measure_sUnion MeasureTheory.measure_sUnion
theorem measure_biUnion_finset₀ {s : Finset ι} {f : ι → Set α}
(hd : Set.Pairwise (↑s) (AEDisjoint μ on f)) (hm : ∀ b ∈ s, NullMeasurableSet (f b) μ) :
μ (⋃ b ∈ s, f b) = ∑ p ∈ s, μ (f p) := by
rw [← Finset.sum_attach, Finset.attach_eq_univ, ← tsum_fintype]
exact measure_biUnion₀ s.countable_toSet hd hm
#align measure_theory.measure_bUnion_finset₀ MeasureTheory.measure_biUnion_finset₀
theorem measure_biUnion_finset {s : Finset ι} {f : ι → Set α} (hd : PairwiseDisjoint (↑s) f)
(hm : ∀ b ∈ s, MeasurableSet (f b)) : μ (⋃ b ∈ s, f b) = ∑ p ∈ s, μ (f p) :=
measure_biUnion_finset₀ hd.aedisjoint fun b hb => (hm b hb).nullMeasurableSet
#align measure_theory.measure_bUnion_finset MeasureTheory.measure_biUnion_finset
/-- The measure of an a.e. disjoint union (even uncountable) of null-measurable sets is at least
the sum of the measures of the sets. -/
theorem tsum_meas_le_meas_iUnion_of_disjoint₀ {ι : Type*} [MeasurableSpace α] (μ : Measure α)
{As : ι → Set α} (As_mble : ∀ i : ι, NullMeasurableSet (As i) μ)
(As_disj : Pairwise (AEDisjoint μ on As)) : (∑' i, μ (As i)) ≤ μ (⋃ i, As i) := by
rw [ENNReal.tsum_eq_iSup_sum, iSup_le_iff]
intro s
simp only [← measure_biUnion_finset₀ (fun _i _hi _j _hj hij => As_disj hij) fun i _ => As_mble i]
gcongr
exact iUnion_subset fun _ ↦ Subset.rfl
/-- The measure of a disjoint union (even uncountable) of measurable sets is at least the sum of
the measures of the sets. -/
theorem tsum_meas_le_meas_iUnion_of_disjoint {ι : Type*} [MeasurableSpace α] (μ : Measure α)
{As : ι → Set α} (As_mble : ∀ i : ι, MeasurableSet (As i))
(As_disj : Pairwise (Disjoint on As)) : (∑' i, μ (As i)) ≤ μ (⋃ i, As i) :=
tsum_meas_le_meas_iUnion_of_disjoint₀ μ (fun i ↦ (As_mble i).nullMeasurableSet)
(fun _ _ h ↦ Disjoint.aedisjoint (As_disj h))
#align measure_theory.tsum_meas_le_meas_Union_of_disjoint MeasureTheory.tsum_meas_le_meas_iUnion_of_disjoint
/-- If `s` is a countable set, then the measure of its preimage can be found as the sum of measures
of the fibers `f ⁻¹' {y}`. -/
theorem tsum_measure_preimage_singleton {s : Set β} (hs : s.Countable) {f : α → β}
(hf : ∀ y ∈ s, MeasurableSet (f ⁻¹' {y})) : (∑' b : s, μ (f ⁻¹' {↑b})) = μ (f ⁻¹' s) := by
rw [← Set.biUnion_preimage_singleton, measure_biUnion hs (pairwiseDisjoint_fiber f s) hf]
#align measure_theory.tsum_measure_preimage_singleton MeasureTheory.tsum_measure_preimage_singleton
lemma measure_preimage_eq_zero_iff_of_countable {s : Set β} {f : α → β} (hs : s.Countable) :
μ (f ⁻¹' s) = 0 ↔ ∀ x ∈ s, μ (f ⁻¹' {x}) = 0 := by
rw [← biUnion_preimage_singleton, measure_biUnion_null_iff hs]
/-- If `s` is a `Finset`, then the measure of its preimage can be found as the sum of measures
of the fibers `f ⁻¹' {y}`. -/
theorem sum_measure_preimage_singleton (s : Finset β) {f : α → β}
(hf : ∀ y ∈ s, MeasurableSet (f ⁻¹' {y})) : (∑ b ∈ s, μ (f ⁻¹' {b})) = μ (f ⁻¹' ↑s) := by
simp only [← measure_biUnion_finset (pairwiseDisjoint_fiber f s) hf,
Finset.set_biUnion_preimage_singleton]
#align measure_theory.sum_measure_preimage_singleton MeasureTheory.sum_measure_preimage_singleton
theorem measure_diff_null' (h : μ (s₁ ∩ s₂) = 0) : μ (s₁ \ s₂) = μ s₁ :=
measure_congr <| diff_ae_eq_self.2 h
#align measure_theory.measure_diff_null' MeasureTheory.measure_diff_null'
theorem measure_add_diff (hs : MeasurableSet s) (t : Set α) : μ s + μ (t \ s) = μ (s ∪ t) := by
rw [← measure_union' disjoint_sdiff_right hs, union_diff_self]
#align measure_theory.measure_add_diff MeasureTheory.measure_add_diff
theorem measure_diff' (s : Set α) (hm : MeasurableSet t) (h_fin : μ t ≠ ∞) :
μ (s \ t) = μ (s ∪ t) - μ t :=
Eq.symm <| ENNReal.sub_eq_of_add_eq h_fin <| by rw [add_comm, measure_add_diff hm, union_comm]
#align measure_theory.measure_diff' MeasureTheory.measure_diff'
theorem measure_diff (h : s₂ ⊆ s₁) (h₂ : MeasurableSet s₂) (h_fin : μ s₂ ≠ ∞) :
μ (s₁ \ s₂) = μ s₁ - μ s₂ := by rw [measure_diff' _ h₂ h_fin, union_eq_self_of_subset_right h]
#align measure_theory.measure_diff MeasureTheory.measure_diff
theorem le_measure_diff : μ s₁ - μ s₂ ≤ μ (s₁ \ s₂) :=
tsub_le_iff_left.2 <| (measure_le_inter_add_diff μ s₁ s₂).trans <| by
gcongr; apply inter_subset_right
#align measure_theory.le_measure_diff MeasureTheory.le_measure_diff
/-- If the measure of the symmetric difference of two sets is finite,
then one has infinite measure if and only if the other one does. -/
theorem measure_eq_top_iff_of_symmDiff (hμst : μ (s ∆ t) ≠ ∞) : μ s = ∞ ↔ μ t = ∞ := by
suffices h : ∀ u v, μ (u ∆ v) ≠ ∞ → μ u = ∞ → μ v = ∞
from ⟨h s t hμst, h t s (symmDiff_comm s t ▸ hμst)⟩
intro u v hμuv hμu
by_contra! hμv
apply hμuv
rw [Set.symmDiff_def, eq_top_iff]
calc
∞ = μ u - μ v := (WithTop.sub_eq_top_iff.2 ⟨hμu, hμv⟩).symm
_ ≤ μ (u \ v) := le_measure_diff
_ ≤ μ (u \ v ∪ v \ u) := measure_mono subset_union_left
/-- If the measure of the symmetric difference of two sets is finite,
then one has finite measure if and only if the other one does. -/
theorem measure_ne_top_iff_of_symmDiff (hμst : μ (s ∆ t) ≠ ∞) : μ s ≠ ∞ ↔ μ t ≠ ∞ :=
(measure_eq_top_iff_of_symmDiff hμst).ne
theorem measure_diff_lt_of_lt_add (hs : MeasurableSet s) (hst : s ⊆ t) (hs' : μ s ≠ ∞) {ε : ℝ≥0∞}
(h : μ t < μ s + ε) : μ (t \ s) < ε := by
rw [measure_diff hst hs hs']; rw [add_comm] at h
exact ENNReal.sub_lt_of_lt_add (measure_mono hst) h
#align measure_theory.measure_diff_lt_of_lt_add MeasureTheory.measure_diff_lt_of_lt_add
theorem measure_diff_le_iff_le_add (hs : MeasurableSet s) (hst : s ⊆ t) (hs' : μ s ≠ ∞) {ε : ℝ≥0∞} :
μ (t \ s) ≤ ε ↔ μ t ≤ μ s + ε := by rw [measure_diff hst hs hs', tsub_le_iff_left]
#align measure_theory.measure_diff_le_iff_le_add MeasureTheory.measure_diff_le_iff_le_add
theorem measure_eq_measure_of_null_diff {s t : Set α} (hst : s ⊆ t) (h_nulldiff : μ (t \ s) = 0) :
μ s = μ t := measure_congr <|
EventuallyLE.antisymm (HasSubset.Subset.eventuallyLE hst) (ae_le_set.mpr h_nulldiff)
#align measure_theory.measure_eq_measure_of_null_diff MeasureTheory.measure_eq_measure_of_null_diff
theorem measure_eq_measure_of_between_null_diff {s₁ s₂ s₃ : Set α} (h12 : s₁ ⊆ s₂) (h23 : s₂ ⊆ s₃)
(h_nulldiff : μ (s₃ \ s₁) = 0) : μ s₁ = μ s₂ ∧ μ s₂ = μ s₃ := by
have le12 : μ s₁ ≤ μ s₂ := measure_mono h12
have le23 : μ s₂ ≤ μ s₃ := measure_mono h23
have key : μ s₃ ≤ μ s₁ :=
calc
μ s₃ = μ (s₃ \ s₁ ∪ s₁) := by rw [diff_union_of_subset (h12.trans h23)]
_ ≤ μ (s₃ \ s₁) + μ s₁ := measure_union_le _ _
_ = μ s₁ := by simp only [h_nulldiff, zero_add]
exact ⟨le12.antisymm (le23.trans key), le23.antisymm (key.trans le12)⟩
#align measure_theory.measure_eq_measure_of_between_null_diff MeasureTheory.measure_eq_measure_of_between_null_diff
theorem measure_eq_measure_smaller_of_between_null_diff {s₁ s₂ s₃ : Set α} (h12 : s₁ ⊆ s₂)
(h23 : s₂ ⊆ s₃) (h_nulldiff : μ (s₃ \ s₁) = 0) : μ s₁ = μ s₂ :=
(measure_eq_measure_of_between_null_diff h12 h23 h_nulldiff).1
#align measure_theory.measure_eq_measure_smaller_of_between_null_diff MeasureTheory.measure_eq_measure_smaller_of_between_null_diff
theorem measure_eq_measure_larger_of_between_null_diff {s₁ s₂ s₃ : Set α} (h12 : s₁ ⊆ s₂)
(h23 : s₂ ⊆ s₃) (h_nulldiff : μ (s₃ \ s₁) = 0) : μ s₂ = μ s₃ :=
(measure_eq_measure_of_between_null_diff h12 h23 h_nulldiff).2
#align measure_theory.measure_eq_measure_larger_of_between_null_diff MeasureTheory.measure_eq_measure_larger_of_between_null_diff
lemma measure_compl₀ (h : NullMeasurableSet s μ) (hs : μ s ≠ ∞) :
μ sᶜ = μ Set.univ - μ s := by
rw [← measure_add_measure_compl₀ h, ENNReal.add_sub_cancel_left hs]
theorem measure_compl (h₁ : MeasurableSet s) (h_fin : μ s ≠ ∞) : μ sᶜ = μ univ - μ s :=
measure_compl₀ h₁.nullMeasurableSet h_fin
#align measure_theory.measure_compl MeasureTheory.measure_compl
lemma measure_inter_conull' (ht : μ (s \ t) = 0) : μ (s ∩ t) = μ s := by
rw [← diff_compl, measure_diff_null']; rwa [← diff_eq]
lemma measure_inter_conull (ht : μ tᶜ = 0) : μ (s ∩ t) = μ s := by
rw [← diff_compl, measure_diff_null ht]
@[simp]
theorem union_ae_eq_left_iff_ae_subset : (s ∪ t : Set α) =ᵐ[μ] s ↔ t ≤ᵐ[μ] s := by
rw [ae_le_set]
refine
⟨fun h => by simpa only [union_diff_left] using (ae_eq_set.mp h).1, fun h =>
eventuallyLE_antisymm_iff.mpr
⟨by rwa [ae_le_set, union_diff_left],
HasSubset.Subset.eventuallyLE subset_union_left⟩⟩
#align measure_theory.union_ae_eq_left_iff_ae_subset MeasureTheory.union_ae_eq_left_iff_ae_subset
@[simp]
theorem union_ae_eq_right_iff_ae_subset : (s ∪ t : Set α) =ᵐ[μ] t ↔ s ≤ᵐ[μ] t := by
rw [union_comm, union_ae_eq_left_iff_ae_subset]
#align measure_theory.union_ae_eq_right_iff_ae_subset MeasureTheory.union_ae_eq_right_iff_ae_subset
theorem ae_eq_of_ae_subset_of_measure_ge (h₁ : s ≤ᵐ[μ] t) (h₂ : μ t ≤ μ s) (hsm : MeasurableSet s)
(ht : μ t ≠ ∞) : s =ᵐ[μ] t := by
refine eventuallyLE_antisymm_iff.mpr ⟨h₁, ae_le_set.mpr ?_⟩
replace h₂ : μ t = μ s := h₂.antisymm (measure_mono_ae h₁)
replace ht : μ s ≠ ∞ := h₂ ▸ ht
rw [measure_diff' t hsm ht, measure_congr (union_ae_eq_left_iff_ae_subset.mpr h₁), h₂, tsub_self]
#align measure_theory.ae_eq_of_ae_subset_of_measure_ge MeasureTheory.ae_eq_of_ae_subset_of_measure_ge
/-- If `s ⊆ t`, `μ t ≤ μ s`, `μ t ≠ ∞`, and `s` is measurable, then `s =ᵐ[μ] t`. -/
theorem ae_eq_of_subset_of_measure_ge (h₁ : s ⊆ t) (h₂ : μ t ≤ μ s) (hsm : MeasurableSet s)
(ht : μ t ≠ ∞) : s =ᵐ[μ] t :=
ae_eq_of_ae_subset_of_measure_ge (HasSubset.Subset.eventuallyLE h₁) h₂ hsm ht
#align measure_theory.ae_eq_of_subset_of_measure_ge MeasureTheory.ae_eq_of_subset_of_measure_ge
theorem measure_iUnion_congr_of_subset [Countable β] {s : β → Set α} {t : β → Set α}
(hsub : ∀ b, s b ⊆ t b) (h_le : ∀ b, μ (t b) ≤ μ (s b)) : μ (⋃ b, s b) = μ (⋃ b, t b) := by
rcases Classical.em (∃ b, μ (t b) = ∞) with (⟨b, hb⟩ | htop)
· calc
μ (⋃ b, s b) = ∞ := top_unique (hb ▸ (h_le b).trans <| measure_mono <| subset_iUnion _ _)
_ = μ (⋃ b, t b) := Eq.symm <| top_unique <| hb ▸ measure_mono (subset_iUnion _ _)
push_neg at htop
refine le_antisymm (measure_mono (iUnion_mono hsub)) ?_
set M := toMeasurable μ
have H : ∀ b, (M (t b) ∩ M (⋃ b, s b) : Set α) =ᵐ[μ] M (t b) := by
refine fun b => ae_eq_of_subset_of_measure_ge inter_subset_left ?_ ?_ ?_
· calc
μ (M (t b)) = μ (t b) := measure_toMeasurable _
_ ≤ μ (s b) := h_le b
_ ≤ μ (M (t b) ∩ M (⋃ b, s b)) :=
measure_mono <|
subset_inter ((hsub b).trans <| subset_toMeasurable _ _)
((subset_iUnion _ _).trans <| subset_toMeasurable _ _)
· exact (measurableSet_toMeasurable _ _).inter (measurableSet_toMeasurable _ _)
· rw [measure_toMeasurable]
exact htop b
calc
μ (⋃ b, t b) ≤ μ (⋃ b, M (t b)) := measure_mono (iUnion_mono fun b => subset_toMeasurable _ _)
_ = μ (⋃ b, M (t b) ∩ M (⋃ b, s b)) := measure_congr (EventuallyEq.countable_iUnion H).symm
_ ≤ μ (M (⋃ b, s b)) := measure_mono (iUnion_subset fun b => inter_subset_right)
_ = μ (⋃ b, s b) := measure_toMeasurable _
#align measure_theory.measure_Union_congr_of_subset MeasureTheory.measure_iUnion_congr_of_subset
theorem measure_union_congr_of_subset {t₁ t₂ : Set α} (hs : s₁ ⊆ s₂) (hsμ : μ s₂ ≤ μ s₁)
(ht : t₁ ⊆ t₂) (htμ : μ t₂ ≤ μ t₁) : μ (s₁ ∪ t₁) = μ (s₂ ∪ t₂) := by
rw [union_eq_iUnion, union_eq_iUnion]
exact measure_iUnion_congr_of_subset (Bool.forall_bool.2 ⟨ht, hs⟩) (Bool.forall_bool.2 ⟨htμ, hsμ⟩)
#align measure_theory.measure_union_congr_of_subset MeasureTheory.measure_union_congr_of_subset
@[simp]
theorem measure_iUnion_toMeasurable [Countable β] (s : β → Set α) :
μ (⋃ b, toMeasurable μ (s b)) = μ (⋃ b, s b) :=
Eq.symm <|
measure_iUnion_congr_of_subset (fun _b => subset_toMeasurable _ _) fun _b =>
(measure_toMeasurable _).le
#align measure_theory.measure_Union_to_measurable MeasureTheory.measure_iUnion_toMeasurable
theorem measure_biUnion_toMeasurable {I : Set β} (hc : I.Countable) (s : β → Set α) :
μ (⋃ b ∈ I, toMeasurable μ (s b)) = μ (⋃ b ∈ I, s b) := by
haveI := hc.toEncodable
simp only [biUnion_eq_iUnion, measure_iUnion_toMeasurable]
#align measure_theory.measure_bUnion_to_measurable MeasureTheory.measure_biUnion_toMeasurable
@[simp]
theorem measure_toMeasurable_union : μ (toMeasurable μ s ∪ t) = μ (s ∪ t) :=
Eq.symm <|
measure_union_congr_of_subset (subset_toMeasurable _ _) (measure_toMeasurable _).le Subset.rfl
le_rfl
#align measure_theory.measure_to_measurable_union MeasureTheory.measure_toMeasurable_union
@[simp]
theorem measure_union_toMeasurable : μ (s ∪ toMeasurable μ t) = μ (s ∪ t) :=
Eq.symm <|
measure_union_congr_of_subset Subset.rfl le_rfl (subset_toMeasurable _ _)
(measure_toMeasurable _).le
#align measure_theory.measure_union_to_measurable MeasureTheory.measure_union_toMeasurable
theorem sum_measure_le_measure_univ {s : Finset ι} {t : ι → Set α}
(h : ∀ i ∈ s, MeasurableSet (t i)) (H : Set.PairwiseDisjoint (↑s) t) :
(∑ i ∈ s, μ (t i)) ≤ μ (univ : Set α) := by
rw [← measure_biUnion_finset H h]
exact measure_mono (subset_univ _)
#align measure_theory.sum_measure_le_measure_univ MeasureTheory.sum_measure_le_measure_univ
theorem tsum_measure_le_measure_univ {s : ι → Set α} (hs : ∀ i, MeasurableSet (s i))
(H : Pairwise (Disjoint on s)) : (∑' i, μ (s i)) ≤ μ (univ : Set α) := by
rw [ENNReal.tsum_eq_iSup_sum]
exact iSup_le fun s =>
sum_measure_le_measure_univ (fun i _hi => hs i) fun i _hi j _hj hij => H hij
#align measure_theory.tsum_measure_le_measure_univ MeasureTheory.tsum_measure_le_measure_univ
/-- Pigeonhole principle for measure spaces: if `∑' i, μ (s i) > μ univ`, then
one of the intersections `s i ∩ s j` is not empty. -/
theorem exists_nonempty_inter_of_measure_univ_lt_tsum_measure {m : MeasurableSpace α}
(μ : Measure α) {s : ι → Set α} (hs : ∀ i, MeasurableSet (s i))
(H : μ (univ : Set α) < ∑' i, μ (s i)) : ∃ i j, i ≠ j ∧ (s i ∩ s j).Nonempty := by
contrapose! H
apply tsum_measure_le_measure_univ hs
intro i j hij
exact disjoint_iff_inter_eq_empty.mpr (H i j hij)
#align measure_theory.exists_nonempty_inter_of_measure_univ_lt_tsum_measure MeasureTheory.exists_nonempty_inter_of_measure_univ_lt_tsum_measure
/-- Pigeonhole principle for measure spaces: if `s` is a `Finset` and
`∑ i ∈ s, μ (t i) > μ univ`, then one of the intersections `t i ∩ t j` is not empty. -/
theorem exists_nonempty_inter_of_measure_univ_lt_sum_measure {m : MeasurableSpace α} (μ : Measure α)
{s : Finset ι} {t : ι → Set α} (h : ∀ i ∈ s, MeasurableSet (t i))
(H : μ (univ : Set α) < ∑ i ∈ s, μ (t i)) :
∃ i ∈ s, ∃ j ∈ s, ∃ _h : i ≠ j, (t i ∩ t j).Nonempty := by
contrapose! H
apply sum_measure_le_measure_univ h
intro i hi j hj hij
exact disjoint_iff_inter_eq_empty.mpr (H i hi j hj hij)
#align measure_theory.exists_nonempty_inter_of_measure_univ_lt_sum_measure MeasureTheory.exists_nonempty_inter_of_measure_univ_lt_sum_measure
/-- If two sets `s` and `t` are included in a set `u`, and `μ s + μ t > μ u`,
then `s` intersects `t`. Version assuming that `t` is measurable. -/
theorem nonempty_inter_of_measure_lt_add {m : MeasurableSpace α} (μ : Measure α) {s t u : Set α}
(ht : MeasurableSet t) (h's : s ⊆ u) (h't : t ⊆ u) (h : μ u < μ s + μ t) :
(s ∩ t).Nonempty := by
rw [← Set.not_disjoint_iff_nonempty_inter]
contrapose! h
calc
μ s + μ t = μ (s ∪ t) := (measure_union h ht).symm
_ ≤ μ u := measure_mono (union_subset h's h't)
#align measure_theory.nonempty_inter_of_measure_lt_add MeasureTheory.nonempty_inter_of_measure_lt_add
/-- If two sets `s` and `t` are included in a set `u`, and `μ s + μ t > μ u`,
then `s` intersects `t`. Version assuming that `s` is measurable. -/
theorem nonempty_inter_of_measure_lt_add' {m : MeasurableSpace α} (μ : Measure α) {s t u : Set α}
(hs : MeasurableSet s) (h's : s ⊆ u) (h't : t ⊆ u) (h : μ u < μ s + μ t) :
(s ∩ t).Nonempty := by
rw [add_comm] at h
rw [inter_comm]
exact nonempty_inter_of_measure_lt_add μ hs h't h's h
#align measure_theory.nonempty_inter_of_measure_lt_add' MeasureTheory.nonempty_inter_of_measure_lt_add'
/-- Continuity from below: the measure of the union of a directed sequence of (not necessarily
-measurable) sets is the supremum of the measures. -/
theorem measure_iUnion_eq_iSup [Countable ι] {s : ι → Set α} (hd : Directed (· ⊆ ·) s) :
μ (⋃ i, s i) = ⨆ i, μ (s i) := by
cases nonempty_encodable ι
-- WLOG, `ι = ℕ`
generalize ht : Function.extend Encodable.encode s ⊥ = t
replace hd : Directed (· ⊆ ·) t := ht ▸ hd.extend_bot Encodable.encode_injective
suffices μ (⋃ n, t n) = ⨆ n, μ (t n) by
simp only [← ht, Function.apply_extend μ, ← iSup_eq_iUnion,
iSup_extend_bot Encodable.encode_injective, (· ∘ ·), Pi.bot_apply, bot_eq_empty,
measure_empty] at this
exact this.trans (iSup_extend_bot Encodable.encode_injective _)
clear! ι
-- The `≥` inequality is trivial
refine le_antisymm ?_ (iSup_le fun i => measure_mono <| subset_iUnion _ _)
-- Choose `T n ⊇ t n` of the same measure, put `Td n = disjointed T`
set T : ℕ → Set α := fun n => toMeasurable μ (t n)
set Td : ℕ → Set α := disjointed T
have hm : ∀ n, MeasurableSet (Td n) :=
MeasurableSet.disjointed fun n => measurableSet_toMeasurable _ _
calc
μ (⋃ n, t n) ≤ μ (⋃ n, T n) := measure_mono (iUnion_mono fun i => subset_toMeasurable _ _)
_ = μ (⋃ n, Td n) := by rw [iUnion_disjointed]
_ ≤ ∑' n, μ (Td n) := measure_iUnion_le _
_ = ⨆ I : Finset ℕ, ∑ n ∈ I, μ (Td n) := ENNReal.tsum_eq_iSup_sum
_ ≤ ⨆ n, μ (t n) := iSup_le fun I => by
rcases hd.finset_le I with ⟨N, hN⟩
calc
(∑ n ∈ I, μ (Td n)) = μ (⋃ n ∈ I, Td n) :=
(measure_biUnion_finset ((disjoint_disjointed T).set_pairwise I) fun n _ => hm n).symm
_ ≤ μ (⋃ n ∈ I, T n) := measure_mono (iUnion₂_mono fun n _hn => disjointed_subset _ _)
_ = μ (⋃ n ∈ I, t n) := measure_biUnion_toMeasurable I.countable_toSet _
_ ≤ μ (t N) := measure_mono (iUnion₂_subset hN)
_ ≤ ⨆ n, μ (t n) := le_iSup (μ ∘ t) N
#align measure_theory.measure_Union_eq_supr MeasureTheory.measure_iUnion_eq_iSup
/-- Continuity from below: the measure of the union of a sequence of
(not necessarily measurable) sets is the supremum of the measures of the partial unions. -/
theorem measure_iUnion_eq_iSup' {α ι : Type*} [MeasurableSpace α] {μ : Measure α}
[Countable ι] [Preorder ι] [IsDirected ι (· ≤ ·)]
{f : ι → Set α} : μ (⋃ i, f i) = ⨆ i, μ (Accumulate f i) := by
have hd : Directed (· ⊆ ·) (Accumulate f) := by
intro i j
rcases directed_of (· ≤ ·) i j with ⟨k, rik, rjk⟩
exact ⟨k, biUnion_subset_biUnion_left fun l rli ↦ le_trans rli rik,
biUnion_subset_biUnion_left fun l rlj ↦ le_trans rlj rjk⟩
rw [← iUnion_accumulate]
exact measure_iUnion_eq_iSup hd
theorem measure_biUnion_eq_iSup {s : ι → Set α} {t : Set ι} (ht : t.Countable)
(hd : DirectedOn ((· ⊆ ·) on s) t) : μ (⋃ i ∈ t, s i) = ⨆ i ∈ t, μ (s i) := by
haveI := ht.toEncodable
rw [biUnion_eq_iUnion, measure_iUnion_eq_iSup hd.directed_val, ← iSup_subtype'']
#align measure_theory.measure_bUnion_eq_supr MeasureTheory.measure_biUnion_eq_iSup
/-- Continuity from above: the measure of the intersection of a decreasing sequence of measurable
sets is the infimum of the measures. -/
theorem measure_iInter_eq_iInf [Countable ι] {s : ι → Set α} (h : ∀ i, MeasurableSet (s i))
(hd : Directed (· ⊇ ·) s) (hfin : ∃ i, μ (s i) ≠ ∞) : μ (⋂ i, s i) = ⨅ i, μ (s i) := by
rcases hfin with ⟨k, hk⟩
have : ∀ t ⊆ s k, μ t ≠ ∞ := fun t ht => ne_top_of_le_ne_top hk (measure_mono ht)
rw [← ENNReal.sub_sub_cancel hk (iInf_le _ k), ENNReal.sub_iInf, ←
ENNReal.sub_sub_cancel hk (measure_mono (iInter_subset _ k)), ←
measure_diff (iInter_subset _ k) (MeasurableSet.iInter h) (this _ (iInter_subset _ k)),
diff_iInter, measure_iUnion_eq_iSup]
· congr 1
refine le_antisymm (iSup_mono' fun i => ?_) (iSup_mono fun i => ?_)
· rcases hd i k with ⟨j, hji, hjk⟩
use j
rw [← measure_diff hjk (h _) (this _ hjk)]
gcongr
· rw [tsub_le_iff_right, ← measure_union, Set.union_comm]
· exact measure_mono (diff_subset_iff.1 Subset.rfl)
· apply disjoint_sdiff_left
· apply h i
· exact hd.mono_comp _ fun _ _ => diff_subset_diff_right
#align measure_theory.measure_Inter_eq_infi MeasureTheory.measure_iInter_eq_iInf
/-- Continuity from above: the measure of the intersection of a sequence of
measurable sets is the infimum of the measures of the partial intersections. -/
theorem measure_iInter_eq_iInf' {α ι : Type*} [MeasurableSpace α] {μ : Measure α}
[Countable ι] [Preorder ι] [IsDirected ι (· ≤ ·)]
{f : ι → Set α} (h : ∀ i, MeasurableSet (f i)) (hfin : ∃ i, μ (f i) ≠ ∞) :
μ (⋂ i, f i) = ⨅ i, μ (⋂ j ≤ i, f j) := by
let s := fun i ↦ ⋂ j ≤ i, f j
have iInter_eq : ⋂ i, f i = ⋂ i, s i := by
ext x; simp [s]; constructor
· exact fun h _ j _ ↦ h j
· intro h i
rcases directed_of (· ≤ ·) i i with ⟨j, rij, -⟩
exact h j i rij
have ms : ∀ i, MeasurableSet (s i) :=
fun i ↦ MeasurableSet.biInter (countable_univ.mono <| subset_univ _) fun i _ ↦ h i
have hd : Directed (· ⊇ ·) s := by
intro i j
rcases directed_of (· ≤ ·) i j with ⟨k, rik, rjk⟩
exact ⟨k, biInter_subset_biInter_left fun j rji ↦ le_trans rji rik,
biInter_subset_biInter_left fun i rij ↦ le_trans rij rjk⟩
have hfin' : ∃ i, μ (s i) ≠ ∞ := by
rcases hfin with ⟨i, hi⟩
rcases directed_of (· ≤ ·) i i with ⟨j, rij, -⟩
exact ⟨j, ne_top_of_le_ne_top hi <| measure_mono <| biInter_subset_of_mem rij⟩
exact iInter_eq ▸ measure_iInter_eq_iInf ms hd hfin'
/-- Continuity from below: the measure of the union of an increasing sequence of (not necessarily
measurable) sets is the limit of the measures. -/
theorem tendsto_measure_iUnion [Preorder ι] [IsDirected ι (· ≤ ·)] [Countable ι]
{s : ι → Set α} (hm : Monotone s) : Tendsto (μ ∘ s) atTop (𝓝 (μ (⋃ n, s n))) := by
rw [measure_iUnion_eq_iSup hm.directed_le]
exact tendsto_atTop_iSup fun n m hnm => measure_mono <| hm hnm
#align measure_theory.tendsto_measure_Union MeasureTheory.tendsto_measure_iUnion
/-- Continuity from below: the measure of the union of a sequence of (not necessarily measurable)
sets is the limit of the measures of the partial unions. -/
theorem tendsto_measure_iUnion' {α ι : Type*} [MeasurableSpace α] {μ : Measure α} [Countable ι]
[Preorder ι] [IsDirected ι (· ≤ ·)] {f : ι → Set α} :
Tendsto (fun i ↦ μ (Accumulate f i)) atTop (𝓝 (μ (⋃ i, f i))) := by
rw [measure_iUnion_eq_iSup']
exact tendsto_atTop_iSup fun i j hij ↦ by gcongr
/-- Continuity from above: the measure of the intersection of a decreasing sequence of measurable
sets is the limit of the measures. -/
theorem tendsto_measure_iInter [Countable ι] [Preorder ι] [IsDirected ι (· ≤ ·)] {s : ι → Set α}
(hs : ∀ n, MeasurableSet (s n)) (hm : Antitone s) (hf : ∃ i, μ (s i) ≠ ∞) :
Tendsto (μ ∘ s) atTop (𝓝 (μ (⋂ n, s n))) := by
rw [measure_iInter_eq_iInf hs hm.directed_ge hf]
exact tendsto_atTop_iInf fun n m hnm => measure_mono <| hm hnm
#align measure_theory.tendsto_measure_Inter MeasureTheory.tendsto_measure_iInter
/-- Continuity from above: the measure of the intersection of a sequence of measurable
sets such that one has finite measure is the limit of the measures of the partial intersections. -/
theorem tendsto_measure_iInter' {α ι : Type*} [MeasurableSpace α] {μ : Measure α} [Countable ι]
[Preorder ι] [IsDirected ι (· ≤ ·)] {f : ι → Set α} (hm : ∀ i, MeasurableSet (f i))
(hf : ∃ i, μ (f i) ≠ ∞) :
Tendsto (fun i ↦ μ (⋂ j ∈ {j | j ≤ i}, f j)) atTop (𝓝 (μ (⋂ i, f i))) := by
rw [measure_iInter_eq_iInf' hm hf]
exact tendsto_atTop_iInf
fun i j hij ↦ measure_mono <| biInter_subset_biInter_left fun k hki ↦ le_trans hki hij
/-- The measure of the intersection of a decreasing sequence of measurable
sets indexed by a linear order with first countable topology is the limit of the measures. -/
theorem tendsto_measure_biInter_gt {ι : Type*} [LinearOrder ι] [TopologicalSpace ι]
[OrderTopology ι] [DenselyOrdered ι] [FirstCountableTopology ι] {s : ι → Set α}
{a : ι} (hs : ∀ r > a, MeasurableSet (s r)) (hm : ∀ i j, a < i → i ≤ j → s i ⊆ s j)
(hf : ∃ r > a, μ (s r) ≠ ∞) : Tendsto (μ ∘ s) (𝓝[Ioi a] a) (𝓝 (μ (⋂ r > a, s r))) := by
refine tendsto_order.2 ⟨fun l hl => ?_, fun L hL => ?_⟩
· filter_upwards [self_mem_nhdsWithin (s := Ioi a)] with r hr using hl.trans_le
(measure_mono (biInter_subset_of_mem hr))
obtain ⟨u, u_anti, u_pos, u_lim⟩ :
∃ u : ℕ → ι, StrictAnti u ∧ (∀ n : ℕ, a < u n) ∧ Tendsto u atTop (𝓝 a) := by
rcases hf with ⟨r, ar, _⟩
rcases exists_seq_strictAnti_tendsto' ar with ⟨w, w_anti, w_mem, w_lim⟩
exact ⟨w, w_anti, fun n => (w_mem n).1, w_lim⟩
have A : Tendsto (μ ∘ s ∘ u) atTop (𝓝 (μ (⋂ n, s (u n)))) := by
refine tendsto_measure_iInter (fun n => hs _ (u_pos n)) ?_ ?_
· intro m n hmn
exact hm _ _ (u_pos n) (u_anti.antitone hmn)
· rcases hf with ⟨r, rpos, hr⟩
obtain ⟨n, hn⟩ : ∃ n : ℕ, u n < r := ((tendsto_order.1 u_lim).2 r rpos).exists
refine ⟨n, ne_of_lt (lt_of_le_of_lt ?_ hr.lt_top)⟩
exact measure_mono (hm _ _ (u_pos n) hn.le)
have B : ⋂ n, s (u n) = ⋂ r > a, s r := by
apply Subset.antisymm
· simp only [subset_iInter_iff, gt_iff_lt]
intro r rpos
obtain ⟨n, hn⟩ : ∃ n, u n < r := ((tendsto_order.1 u_lim).2 _ rpos).exists
exact Subset.trans (iInter_subset _ n) (hm (u n) r (u_pos n) hn.le)
· simp only [subset_iInter_iff, gt_iff_lt]
intro n
apply biInter_subset_of_mem
exact u_pos n
rw [B] at A
obtain ⟨n, hn⟩ : ∃ n, μ (s (u n)) < L := ((tendsto_order.1 A).2 _ hL).exists
have : Ioc a (u n) ∈ 𝓝[>] a := Ioc_mem_nhdsWithin_Ioi ⟨le_rfl, u_pos n⟩
filter_upwards [this] with r hr using lt_of_le_of_lt (measure_mono (hm _ _ hr.1 hr.2)) hn
#align measure_theory.tendsto_measure_bInter_gt MeasureTheory.tendsto_measure_biInter_gt
/-- One direction of the **Borel-Cantelli lemma** (sometimes called the "*first* Borel-Cantelli
lemma"): if (sᵢ) is a sequence of sets such that `∑ μ sᵢ` is finite, then the limit superior of the
`sᵢ` is a null set.
Note: for the *second* Borel-Cantelli lemma (applying to independent sets in a probability space),
see `ProbabilityTheory.measure_limsup_eq_one`. -/
theorem measure_limsup_eq_zero {s : ℕ → Set α} (hs : (∑' i, μ (s i)) ≠ ∞) :
μ (limsup s atTop) = 0 := by
-- First we replace the sequence `sₙ` with a sequence of measurable sets `tₙ ⊇ sₙ` of the same
-- measure.
set t : ℕ → Set α := fun n => toMeasurable μ (s n)
have ht : (∑' i, μ (t i)) ≠ ∞ := by simpa only [t, measure_toMeasurable] using hs
suffices μ (limsup t atTop) = 0 by
have A : s ≤ t := fun n => subset_toMeasurable μ (s n)
-- TODO default args fail
exact measure_mono_null (limsup_le_limsup (eventually_of_forall (Pi.le_def.mp A))) this
-- Next we unfold `limsup` for sets and replace equality with an inequality
simp only [limsup_eq_iInf_iSup_of_nat', Set.iInf_eq_iInter, Set.iSup_eq_iUnion, ←
nonpos_iff_eq_zero]
-- Finally, we estimate `μ (⋃ i, t (i + n))` by `∑ i', μ (t (i + n))`
refine
le_of_tendsto_of_tendsto'
(tendsto_measure_iInter
(fun i => MeasurableSet.iUnion fun b => measurableSet_toMeasurable _ _) ?_
⟨0, ne_top_of_le_ne_top ht (measure_iUnion_le t)⟩)
(ENNReal.tendsto_sum_nat_add (μ ∘ t) ht) fun n => measure_iUnion_le _
intro n m hnm x
simp only [Set.mem_iUnion]
exact fun ⟨i, hi⟩ => ⟨i + (m - n), by simpa only [add_assoc, tsub_add_cancel_of_le hnm] using hi⟩
#align measure_theory.measure_limsup_eq_zero MeasureTheory.measure_limsup_eq_zero
theorem measure_liminf_eq_zero {s : ℕ → Set α} (h : (∑' i, μ (s i)) ≠ ∞) :
μ (liminf s atTop) = 0 := by
rw [← le_zero_iff]
have : liminf s atTop ≤ limsup s atTop := liminf_le_limsup
exact (μ.mono this).trans (by simp [measure_limsup_eq_zero h])
#align measure_theory.measure_liminf_eq_zero MeasureTheory.measure_liminf_eq_zero
-- Need to specify `α := Set α` below because of diamond; see #19041
theorem limsup_ae_eq_of_forall_ae_eq (s : ℕ → Set α) {t : Set α}
(h : ∀ n, s n =ᵐ[μ] t) : limsup (α := Set α) s atTop =ᵐ[μ] t := by
simp_rw [ae_eq_set] at h ⊢
constructor
· rw [atTop.limsup_sdiff s t]
apply measure_limsup_eq_zero
simp [h]
· rw [atTop.sdiff_limsup s t]
apply measure_liminf_eq_zero
simp [h]
#align measure_theory.limsup_ae_eq_of_forall_ae_eq MeasureTheory.limsup_ae_eq_of_forall_ae_eq
-- Need to specify `α := Set α` above because of diamond; see #19041
theorem liminf_ae_eq_of_forall_ae_eq (s : ℕ → Set α) {t : Set α}
(h : ∀ n, s n =ᵐ[μ] t) : liminf (α := Set α) s atTop =ᵐ[μ] t := by
simp_rw [ae_eq_set] at h ⊢
constructor
· rw [atTop.liminf_sdiff s t]
apply measure_liminf_eq_zero
simp [h]
· rw [atTop.sdiff_liminf s t]
apply measure_limsup_eq_zero
simp [h]
#align measure_theory.liminf_ae_eq_of_forall_ae_eq MeasureTheory.liminf_ae_eq_of_forall_ae_eq
theorem measure_if {x : β} {t : Set β} {s : Set α} :
μ (if x ∈ t then s else ∅) = indicator t (fun _ => μ s) x := by split_ifs with h <;> simp [h]
#align measure_theory.measure_if MeasureTheory.measure_if
end
section OuterMeasure
variable [ms : MeasurableSpace α] {s t : Set α}
/-- Obtain a measure by giving an outer measure where all sets in the σ-algebra are
Carathéodory measurable. -/
def OuterMeasure.toMeasure (m : OuterMeasure α) (h : ms ≤ m.caratheodory) : Measure α :=
Measure.ofMeasurable (fun s _ => m s) m.empty fun _f hf hd =>
m.iUnion_eq_of_caratheodory (fun i => h _ (hf i)) hd
#align measure_theory.outer_measure.to_measure MeasureTheory.OuterMeasure.toMeasure
theorem le_toOuterMeasure_caratheodory (μ : Measure α) : ms ≤ μ.toOuterMeasure.caratheodory :=
fun _s hs _t => (measure_inter_add_diff _ hs).symm
#align measure_theory.le_to_outer_measure_caratheodory MeasureTheory.le_toOuterMeasure_caratheodory
@[simp]
theorem toMeasure_toOuterMeasure (m : OuterMeasure α) (h : ms ≤ m.caratheodory) :
(m.toMeasure h).toOuterMeasure = m.trim :=
rfl
#align measure_theory.to_measure_to_outer_measure MeasureTheory.toMeasure_toOuterMeasure
@[simp]
theorem toMeasure_apply (m : OuterMeasure α) (h : ms ≤ m.caratheodory) {s : Set α}
(hs : MeasurableSet s) : m.toMeasure h s = m s :=
m.trim_eq hs
#align measure_theory.to_measure_apply MeasureTheory.toMeasure_apply
theorem le_toMeasure_apply (m : OuterMeasure α) (h : ms ≤ m.caratheodory) (s : Set α) :
m s ≤ m.toMeasure h s :=
m.le_trim s
#align measure_theory.le_to_measure_apply MeasureTheory.le_toMeasure_apply
theorem toMeasure_apply₀ (m : OuterMeasure α) (h : ms ≤ m.caratheodory) {s : Set α}
(hs : NullMeasurableSet s (m.toMeasure h)) : m.toMeasure h s = m s := by
refine le_antisymm ?_ (le_toMeasure_apply _ _ _)
rcases hs.exists_measurable_subset_ae_eq with ⟨t, hts, htm, heq⟩
calc
m.toMeasure h s = m.toMeasure h t := measure_congr heq.symm
_ = m t := toMeasure_apply m h htm
_ ≤ m s := m.mono hts
#align measure_theory.to_measure_apply₀ MeasureTheory.toMeasure_apply₀
@[simp]
theorem toOuterMeasure_toMeasure {μ : Measure α} :
μ.toOuterMeasure.toMeasure (le_toOuterMeasure_caratheodory _) = μ :=
Measure.ext fun _s => μ.toOuterMeasure.trim_eq
#align measure_theory.to_outer_measure_to_measure MeasureTheory.toOuterMeasure_toMeasure
@[simp]
theorem boundedBy_measure (μ : Measure α) : OuterMeasure.boundedBy μ = μ.toOuterMeasure :=
μ.toOuterMeasure.boundedBy_eq_self
#align measure_theory.bounded_by_measure MeasureTheory.boundedBy_measure
end OuterMeasure
section
/- Porting note: These variables are wrapped by an anonymous section because they interrupt
synthesizing instances in `MeasureSpace` section. -/
variable {m0 : MeasurableSpace α} [MeasurableSpace β] [MeasurableSpace γ]
variable {μ μ₁ μ₂ μ₃ ν ν' ν₁ ν₂ : Measure α} {s s' t : Set α}
namespace Measure
/-- If `u` is a superset of `t` with the same (finite) measure (both sets possibly non-measurable),
then for any measurable set `s` one also has `μ (t ∩ s) = μ (u ∩ s)`. -/
| Mathlib/MeasureTheory/Measure/MeasureSpace.lean | 782 | 793 | theorem measure_inter_eq_of_measure_eq {s t u : Set α} (hs : MeasurableSet s) (h : μ t = μ u)
(htu : t ⊆ u) (ht_ne_top : μ t ≠ ∞) : μ (t ∩ s) = μ (u ∩ s) := by |
rw [h] at ht_ne_top
refine le_antisymm (by gcongr) ?_
have A : μ (u ∩ s) + μ (u \ s) ≤ μ (t ∩ s) + μ (u \ s) :=
calc
μ (u ∩ s) + μ (u \ s) = μ u := measure_inter_add_diff _ hs
_ = μ t := h.symm
_ = μ (t ∩ s) + μ (t \ s) := (measure_inter_add_diff _ hs).symm
_ ≤ μ (t ∩ s) + μ (u \ s) := by gcongr
have B : μ (u \ s) ≠ ∞ := (lt_of_le_of_lt (measure_mono diff_subset) ht_ne_top.lt_top).ne
exact ENNReal.le_of_add_le_add_right B A
|
/-
Copyright (c) 2020 Zhouhang Zhou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Zhouhang Zhou
-/
import Mathlib.Algebra.Group.Pi.Lemmas
import Mathlib.Algebra.Group.Support
#align_import algebra.indicator_function from "leanprover-community/mathlib"@"2445c98ae4b87eabebdde552593519b9b6dc350c"
/-!
# Indicator function
- `Set.indicator (s : Set α) (f : α → β) (a : α)` is `f a` if `a ∈ s` and is `0` otherwise.
- `Set.mulIndicator (s : Set α) (f : α → β) (a : α)` is `f a` if `a ∈ s` and is `1` otherwise.
## Implementation note
In mathematics, an indicator function or a characteristic function is a function
used to indicate membership of an element in a set `s`,
having the value `1` for all elements of `s` and the value `0` otherwise.
But since it is usually used to restrict a function to a certain set `s`,
we let the indicator function take the value `f x` for some function `f`, instead of `1`.
If the usual indicator function is needed, just set `f` to be the constant function `fun _ ↦ 1`.
The indicator function is implemented non-computably, to avoid having to pass around `Decidable`
arguments. This is in contrast with the design of `Pi.single` or `Set.piecewise`.
## Tags
indicator, characteristic
-/
assert_not_exists MonoidWithZero
open Function
variable {α β ι M N : Type*}
namespace Set
section One
variable [One M] [One N] {s t : Set α} {f g : α → M} {a : α}
/-- `Set.mulIndicator s f a` is `f a` if `a ∈ s`, `1` otherwise. -/
@[to_additive "`Set.indicator s f a` is `f a` if `a ∈ s`, `0` otherwise."]
noncomputable def mulIndicator (s : Set α) (f : α → M) (x : α) : M :=
haveI := Classical.decPred (· ∈ s)
if x ∈ s then f x else 1
#align set.mul_indicator Set.mulIndicator
@[to_additive (attr := simp)]
theorem piecewise_eq_mulIndicator [DecidablePred (· ∈ s)] : s.piecewise f 1 = s.mulIndicator f :=
funext fun _ => @if_congr _ _ _ _ (id _) _ _ _ _ Iff.rfl rfl rfl
#align set.piecewise_eq_mul_indicator Set.piecewise_eq_mulIndicator
#align set.piecewise_eq_indicator Set.piecewise_eq_indicator
-- Porting note: needed unfold for mulIndicator
@[to_additive]
theorem mulIndicator_apply (s : Set α) (f : α → M) (a : α) [Decidable (a ∈ s)] :
mulIndicator s f a = if a ∈ s then f a else 1 := by
unfold mulIndicator
congr
#align set.mul_indicator_apply Set.mulIndicator_apply
#align set.indicator_apply Set.indicator_apply
@[to_additive (attr := simp)]
theorem mulIndicator_of_mem (h : a ∈ s) (f : α → M) : mulIndicator s f a = f a :=
if_pos h
#align set.mul_indicator_of_mem Set.mulIndicator_of_mem
#align set.indicator_of_mem Set.indicator_of_mem
@[to_additive (attr := simp)]
theorem mulIndicator_of_not_mem (h : a ∉ s) (f : α → M) : mulIndicator s f a = 1 :=
if_neg h
#align set.mul_indicator_of_not_mem Set.mulIndicator_of_not_mem
#align set.indicator_of_not_mem Set.indicator_of_not_mem
@[to_additive]
theorem mulIndicator_eq_one_or_self (s : Set α) (f : α → M) (a : α) :
mulIndicator s f a = 1 ∨ mulIndicator s f a = f a := by
by_cases h : a ∈ s
· exact Or.inr (mulIndicator_of_mem h f)
· exact Or.inl (mulIndicator_of_not_mem h f)
#align set.mul_indicator_eq_one_or_self Set.mulIndicator_eq_one_or_self
#align set.indicator_eq_zero_or_self Set.indicator_eq_zero_or_self
@[to_additive (attr := simp)]
theorem mulIndicator_apply_eq_self : s.mulIndicator f a = f a ↔ a ∉ s → f a = 1 :=
letI := Classical.dec (a ∈ s)
ite_eq_left_iff.trans (by rw [@eq_comm _ (f a)])
#align set.mul_indicator_apply_eq_self Set.mulIndicator_apply_eq_self
#align set.indicator_apply_eq_self Set.indicator_apply_eq_self
@[to_additive (attr := simp)]
theorem mulIndicator_eq_self : s.mulIndicator f = f ↔ mulSupport f ⊆ s := by
simp only [funext_iff, subset_def, mem_mulSupport, mulIndicator_apply_eq_self, not_imp_comm]
#align set.mul_indicator_eq_self Set.mulIndicator_eq_self
#align set.indicator_eq_self Set.indicator_eq_self
@[to_additive]
theorem mulIndicator_eq_self_of_superset (h1 : s.mulIndicator f = f) (h2 : s ⊆ t) :
t.mulIndicator f = f := by
rw [mulIndicator_eq_self] at h1 ⊢
exact Subset.trans h1 h2
#align set.mul_indicator_eq_self_of_superset Set.mulIndicator_eq_self_of_superset
#align set.indicator_eq_self_of_superset Set.indicator_eq_self_of_superset
@[to_additive (attr := simp)]
theorem mulIndicator_apply_eq_one : mulIndicator s f a = 1 ↔ a ∈ s → f a = 1 :=
letI := Classical.dec (a ∈ s)
ite_eq_right_iff
#align set.mul_indicator_apply_eq_one Set.mulIndicator_apply_eq_one
#align set.indicator_apply_eq_zero Set.indicator_apply_eq_zero
@[to_additive (attr := simp)]
theorem mulIndicator_eq_one : (mulIndicator s f = fun x => 1) ↔ Disjoint (mulSupport f) s := by
simp only [funext_iff, mulIndicator_apply_eq_one, Set.disjoint_left, mem_mulSupport,
not_imp_not]
#align set.mul_indicator_eq_one Set.mulIndicator_eq_one
#align set.indicator_eq_zero Set.indicator_eq_zero
@[to_additive (attr := simp)]
theorem mulIndicator_eq_one' : mulIndicator s f = 1 ↔ Disjoint (mulSupport f) s :=
mulIndicator_eq_one
#align set.mul_indicator_eq_one' Set.mulIndicator_eq_one'
#align set.indicator_eq_zero' Set.indicator_eq_zero'
@[to_additive]
theorem mulIndicator_apply_ne_one {a : α} : s.mulIndicator f a ≠ 1 ↔ a ∈ s ∩ mulSupport f := by
simp only [Ne, mulIndicator_apply_eq_one, Classical.not_imp, mem_inter_iff, mem_mulSupport]
#align set.mul_indicator_apply_ne_one Set.mulIndicator_apply_ne_one
#align set.indicator_apply_ne_zero Set.indicator_apply_ne_zero
@[to_additive (attr := simp)]
theorem mulSupport_mulIndicator :
Function.mulSupport (s.mulIndicator f) = s ∩ Function.mulSupport f :=
ext fun x => by simp [Function.mem_mulSupport, mulIndicator_apply_eq_one]
#align set.mul_support_mul_indicator Set.mulSupport_mulIndicator
#align set.support_indicator Set.support_indicator
/-- If a multiplicative indicator function is not equal to `1` at a point, then that point is in the
set. -/
@[to_additive
"If an additive indicator function is not equal to `0` at a point, then that point is
in the set."]
theorem mem_of_mulIndicator_ne_one (h : mulIndicator s f a ≠ 1) : a ∈ s :=
not_imp_comm.1 (fun hn => mulIndicator_of_not_mem hn f) h
#align set.mem_of_mul_indicator_ne_one Set.mem_of_mulIndicator_ne_one
#align set.mem_of_indicator_ne_zero Set.mem_of_indicator_ne_zero
@[to_additive]
theorem eqOn_mulIndicator : EqOn (mulIndicator s f) f s := fun _ hx => mulIndicator_of_mem hx f
#align set.eq_on_mul_indicator Set.eqOn_mulIndicator
#align set.eq_on_indicator Set.eqOn_indicator
@[to_additive]
theorem mulSupport_mulIndicator_subset : mulSupport (s.mulIndicator f) ⊆ s := fun _ hx =>
hx.imp_symm fun h => mulIndicator_of_not_mem h f
#align set.mul_support_mul_indicator_subset Set.mulSupport_mulIndicator_subset
#align set.support_indicator_subset Set.support_indicator_subset
@[to_additive (attr := simp)]
theorem mulIndicator_mulSupport : mulIndicator (mulSupport f) f = f :=
mulIndicator_eq_self.2 Subset.rfl
#align set.mul_indicator_mul_support Set.mulIndicator_mulSupport
#align set.indicator_support Set.indicator_support
@[to_additive (attr := simp)]
theorem mulIndicator_range_comp {ι : Sort*} (f : ι → α) (g : α → M) :
mulIndicator (range f) g ∘ f = g ∘ f :=
letI := Classical.decPred (· ∈ range f)
piecewise_range_comp _ _ _
#align set.mul_indicator_range_comp Set.mulIndicator_range_comp
#align set.indicator_range_comp Set.indicator_range_comp
@[to_additive]
theorem mulIndicator_congr (h : EqOn f g s) : mulIndicator s f = mulIndicator s g :=
funext fun x => by
simp only [mulIndicator]
split_ifs with h_1
· exact h h_1
rfl
#align set.mul_indicator_congr Set.mulIndicator_congr
#align set.indicator_congr Set.indicator_congr
@[to_additive (attr := simp)]
theorem mulIndicator_univ (f : α → M) : mulIndicator (univ : Set α) f = f :=
mulIndicator_eq_self.2 <| subset_univ _
#align set.mul_indicator_univ Set.mulIndicator_univ
#align set.indicator_univ Set.indicator_univ
@[to_additive (attr := simp)]
theorem mulIndicator_empty (f : α → M) : mulIndicator (∅ : Set α) f = fun _ => 1 :=
mulIndicator_eq_one.2 <| disjoint_empty _
#align set.mul_indicator_empty Set.mulIndicator_empty
#align set.indicator_empty Set.indicator_empty
@[to_additive]
theorem mulIndicator_empty' (f : α → M) : mulIndicator (∅ : Set α) f = 1 :=
mulIndicator_empty f
#align set.mul_indicator_empty' Set.mulIndicator_empty'
#align set.indicator_empty' Set.indicator_empty'
variable (M)
@[to_additive (attr := simp)]
theorem mulIndicator_one (s : Set α) : (mulIndicator s fun _ => (1 : M)) = fun _ => (1 : M) :=
mulIndicator_eq_one.2 <| by simp only [mulSupport_one, empty_disjoint]
#align set.mul_indicator_one Set.mulIndicator_one
#align set.indicator_zero Set.indicator_zero
@[to_additive (attr := simp)]
theorem mulIndicator_one' {s : Set α} : s.mulIndicator (1 : α → M) = 1 :=
mulIndicator_one M s
#align set.mul_indicator_one' Set.mulIndicator_one'
#align set.indicator_zero' Set.indicator_zero'
variable {M}
@[to_additive]
theorem mulIndicator_mulIndicator (s t : Set α) (f : α → M) :
mulIndicator s (mulIndicator t f) = mulIndicator (s ∩ t) f :=
funext fun x => by
simp only [mulIndicator]
split_ifs <;> simp_all (config := { contextual := true })
#align set.mul_indicator_mul_indicator Set.mulIndicator_mulIndicator
#align set.indicator_indicator Set.indicator_indicator
@[to_additive (attr := simp)]
theorem mulIndicator_inter_mulSupport (s : Set α) (f : α → M) :
mulIndicator (s ∩ mulSupport f) f = mulIndicator s f := by
rw [← mulIndicator_mulIndicator, mulIndicator_mulSupport]
#align set.mul_indicator_inter_mul_support Set.mulIndicator_inter_mulSupport
#align set.indicator_inter_support Set.indicator_inter_support
@[to_additive]
theorem comp_mulIndicator (h : M → β) (f : α → M) {s : Set α} {x : α} [DecidablePred (· ∈ s)] :
h (s.mulIndicator f x) = s.piecewise (h ∘ f) (const α (h 1)) x := by
letI := Classical.decPred (· ∈ s)
convert s.apply_piecewise f (const α 1) (fun _ => h) (x := x) using 2
#align set.comp_mul_indicator Set.comp_mulIndicator
#align set.comp_indicator Set.comp_indicator
@[to_additive]
theorem mulIndicator_comp_right {s : Set α} (f : β → α) {g : α → M} {x : β} :
mulIndicator (f ⁻¹' s) (g ∘ f) x = mulIndicator s g (f x) := by
simp only [mulIndicator, Function.comp]
split_ifs with h h' h'' <;> first | rfl | contradiction
#align set.mul_indicator_comp_right Set.mulIndicator_comp_right
#align set.indicator_comp_right Set.indicator_comp_right
@[to_additive]
theorem mulIndicator_image {s : Set α} {f : β → M} {g : α → β} (hg : Injective g) {x : α} :
mulIndicator (g '' s) f (g x) = mulIndicator s (f ∘ g) x := by
rw [← mulIndicator_comp_right, preimage_image_eq _ hg]
#align set.mul_indicator_image Set.mulIndicator_image
#align set.indicator_image Set.indicator_image
@[to_additive]
theorem mulIndicator_comp_of_one {g : M → N} (hg : g 1 = 1) :
mulIndicator s (g ∘ f) = g ∘ mulIndicator s f := by
funext
simp only [mulIndicator]
split_ifs <;> simp [*]
#align set.mul_indicator_comp_of_one Set.mulIndicator_comp_of_one
#align set.indicator_comp_of_zero Set.indicator_comp_of_zero
@[to_additive]
theorem comp_mulIndicator_const (c : M) (f : M → N) (hf : f 1 = 1) :
(fun x => f (s.mulIndicator (fun _ => c) x)) = s.mulIndicator fun _ => f c :=
(mulIndicator_comp_of_one hf).symm
#align set.comp_mul_indicator_const Set.comp_mulIndicator_const
#align set.comp_indicator_const Set.comp_indicator_const
@[to_additive]
theorem mulIndicator_preimage (s : Set α) (f : α → M) (B : Set M) :
mulIndicator s f ⁻¹' B = s.ite (f ⁻¹' B) (1 ⁻¹' B) :=
letI := Classical.decPred (· ∈ s)
piecewise_preimage s f 1 B
#align set.mul_indicator_preimage Set.mulIndicator_preimage
#align set.indicator_preimage Set.indicator_preimage
@[to_additive]
theorem mulIndicator_one_preimage (s : Set M) :
t.mulIndicator 1 ⁻¹' s ∈ ({Set.univ, ∅} : Set (Set α)) := by
classical
rw [mulIndicator_one', preimage_one]
split_ifs <;> simp
#align set.mul_indicator_one_preimage Set.mulIndicator_one_preimage
#align set.indicator_zero_preimage Set.indicator_zero_preimage
@[to_additive]
theorem mulIndicator_const_preimage_eq_union (U : Set α) (s : Set M) (a : M) [Decidable (a ∈ s)]
[Decidable ((1 : M) ∈ s)] : (U.mulIndicator fun _ => a) ⁻¹' s =
(if a ∈ s then U else ∅) ∪ if (1 : M) ∈ s then Uᶜ else ∅ := by
rw [mulIndicator_preimage, preimage_one, preimage_const]
split_ifs <;> simp [← compl_eq_univ_diff]
#align set.mul_indicator_const_preimage_eq_union Set.mulIndicator_const_preimage_eq_union
#align set.indicator_const_preimage_eq_union Set.indicator_const_preimage_eq_union
@[to_additive]
| Mathlib/Algebra/Group/Indicator.lean | 304 | 308 | theorem mulIndicator_const_preimage (U : Set α) (s : Set M) (a : M) :
(U.mulIndicator fun _ => a) ⁻¹' s ∈ ({Set.univ, U, Uᶜ, ∅} : Set (Set α)) := by |
classical
rw [mulIndicator_const_preimage_eq_union]
split_ifs <;> simp
|
/-
Copyright (c) 2015 Microsoft Corporation. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Leonardo de Moura, Jeremy Avigad, Minchao Wu, Mario Carneiro
-/
import Mathlib.Data.Finset.Attr
import Mathlib.Data.Multiset.FinsetOps
import Mathlib.Logic.Equiv.Set
import Mathlib.Order.Directed
import Mathlib.Order.Interval.Set.Basic
#align_import data.finset.basic from "leanprover-community/mathlib"@"442a83d738cb208d3600056c489be16900ba701d"
/-!
# Finite sets
Terms of type `Finset α` are one way of talking about finite subsets of `α` in mathlib.
Below, `Finset α` is defined as a structure with 2 fields:
1. `val` is a `Multiset α` of elements;
2. `nodup` is a proof that `val` has no duplicates.
Finsets in Lean are constructive in that they have an underlying `List` that enumerates their
elements. In particular, any function that uses the data of the underlying list cannot depend on its
ordering. This is handled on the `Multiset` level by multiset API, so in most cases one needn't
worry about it explicitly.
Finsets give a basic foundation for defining finite sums and products over types:
1. `∑ i ∈ (s : Finset α), f i`;
2. `∏ i ∈ (s : Finset α), f i`.
Lean refers to these operations as big operators.
More information can be found in `Mathlib.Algebra.BigOperators.Group.Finset`.
Finsets are directly used to define fintypes in Lean.
A `Fintype α` instance for a type `α` consists of a universal `Finset α` containing every term of
`α`, called `univ`. See `Mathlib.Data.Fintype.Basic`.
There is also `univ'`, the noncomputable partner to `univ`,
which is defined to be `α` as a finset if `α` is finite,
and the empty finset otherwise. See `Mathlib.Data.Fintype.Basic`.
`Finset.card`, the size of a finset is defined in `Mathlib.Data.Finset.Card`.
This is then used to define `Fintype.card`, the size of a type.
## Main declarations
### Main definitions
* `Finset`: Defines a type for the finite subsets of `α`.
Constructing a `Finset` requires two pieces of data: `val`, a `Multiset α` of elements,
and `nodup`, a proof that `val` has no duplicates.
* `Finset.instMembershipFinset`: Defines membership `a ∈ (s : Finset α)`.
* `Finset.instCoeTCFinsetSet`: Provides a coercion `s : Finset α` to `s : Set α`.
* `Finset.instCoeSortFinsetType`: Coerce `s : Finset α` to the type of all `x ∈ s`.
* `Finset.induction_on`: Induction on finsets. To prove a proposition about an arbitrary `Finset α`,
it suffices to prove it for the empty finset, and to show that if it holds for some `Finset α`,
then it holds for the finset obtained by inserting a new element.
* `Finset.choose`: Given a proof `h` of existence and uniqueness of a certain element
satisfying a predicate, `choose s h` returns the element of `s` satisfying that predicate.
### Finset constructions
* `Finset.instSingletonFinset`: Denoted by `{a}`; the finset consisting of one element.
* `Finset.empty`: Denoted by `∅`. The finset associated to any type consisting of no elements.
* `Finset.range`: For any `n : ℕ`, `range n` is equal to `{0, 1, ... , n - 1} ⊆ ℕ`.
This convention is consistent with other languages and normalizes `card (range n) = n`.
Beware, `n` is not in `range n`.
* `Finset.attach`: Given `s : Finset α`, `attach s` forms a finset of elements of the subtype
`{a // a ∈ s}`; in other words, it attaches elements to a proof of membership in the set.
### Finsets from functions
* `Finset.filter`: Given a decidable predicate `p : α → Prop`, `s.filter p` is
the finset consisting of those elements in `s` satisfying the predicate `p`.
### The lattice structure on subsets of finsets
There is a natural lattice structure on the subsets of a set.
In Lean, we use lattice notation to talk about things involving unions and intersections. See
`Mathlib.Order.Lattice`. For the lattice structure on finsets, `⊥` is called `bot` with `⊥ = ∅` and
`⊤` is called `top` with `⊤ = univ`.
* `Finset.instHasSubsetFinset`: Lots of API about lattices, otherwise behaves as one would expect.
* `Finset.instUnionFinset`: Defines `s ∪ t` (or `s ⊔ t`) as the union of `s` and `t`.
See `Finset.sup`/`Finset.biUnion` for finite unions.
* `Finset.instInterFinset`: Defines `s ∩ t` (or `s ⊓ t`) as the intersection of `s` and `t`.
See `Finset.inf` for finite intersections.
### Operations on two or more finsets
* `insert` and `Finset.cons`: For any `a : α`, `insert s a` returns `s ∪ {a}`. `cons s a h`
returns the same except that it requires a hypothesis stating that `a` is not already in `s`.
This does not require decidable equality on the type `α`.
* `Finset.instUnionFinset`: see "The lattice structure on subsets of finsets"
* `Finset.instInterFinset`: see "The lattice structure on subsets of finsets"
* `Finset.erase`: For any `a : α`, `erase s a` returns `s` with the element `a` removed.
* `Finset.instSDiffFinset`: Defines the set difference `s \ t` for finsets `s` and `t`.
* `Finset.product`: Given finsets of `α` and `β`, defines finsets of `α × β`.
For arbitrary dependent products, see `Mathlib.Data.Finset.Pi`.
### Predicates on finsets
* `Disjoint`: defined via the lattice structure on finsets; two sets are disjoint if their
intersection is empty.
* `Finset.Nonempty`: A finset is nonempty if it has elements. This is equivalent to saying `s ≠ ∅`.
### Equivalences between finsets
* The `Mathlib.Data.Equiv` files describe a general type of equivalence, so look in there for any
lemmas. There is some API for rewriting sums and products from `s` to `t` given that `s ≃ t`.
TODO: examples
## Tags
finite sets, finset
-/
-- Assert that we define `Finset` without the material on `List.sublists`.
-- Note that we cannot use `List.sublists` itself as that is defined very early.
assert_not_exists List.sublistsLen
assert_not_exists Multiset.Powerset
assert_not_exists CompleteLattice
open Multiset Subtype Nat Function
universe u
variable {α : Type*} {β : Type*} {γ : Type*}
/-- `Finset α` is the type of finite sets of elements of `α`. It is implemented
as a multiset (a list up to permutation) which has no duplicate elements. -/
structure Finset (α : Type*) where
/-- The underlying multiset -/
val : Multiset α
/-- `val` contains no duplicates -/
nodup : Nodup val
#align finset Finset
instance Multiset.canLiftFinset {α} : CanLift (Multiset α) (Finset α) Finset.val Multiset.Nodup :=
⟨fun m hm => ⟨⟨m, hm⟩, rfl⟩⟩
#align multiset.can_lift_finset Multiset.canLiftFinset
namespace Finset
theorem eq_of_veq : ∀ {s t : Finset α}, s.1 = t.1 → s = t
| ⟨s, _⟩, ⟨t, _⟩, h => by cases h; rfl
#align finset.eq_of_veq Finset.eq_of_veq
theorem val_injective : Injective (val : Finset α → Multiset α) := fun _ _ => eq_of_veq
#align finset.val_injective Finset.val_injective
@[simp]
theorem val_inj {s t : Finset α} : s.1 = t.1 ↔ s = t :=
val_injective.eq_iff
#align finset.val_inj Finset.val_inj
@[simp]
theorem dedup_eq_self [DecidableEq α] (s : Finset α) : dedup s.1 = s.1 :=
s.2.dedup
#align finset.dedup_eq_self Finset.dedup_eq_self
instance decidableEq [DecidableEq α] : DecidableEq (Finset α)
| _, _ => decidable_of_iff _ val_inj
#align finset.has_decidable_eq Finset.decidableEq
/-! ### membership -/
instance : Membership α (Finset α) :=
⟨fun a s => a ∈ s.1⟩
theorem mem_def {a : α} {s : Finset α} : a ∈ s ↔ a ∈ s.1 :=
Iff.rfl
#align finset.mem_def Finset.mem_def
@[simp]
theorem mem_val {a : α} {s : Finset α} : a ∈ s.1 ↔ a ∈ s :=
Iff.rfl
#align finset.mem_val Finset.mem_val
@[simp]
theorem mem_mk {a : α} {s nd} : a ∈ @Finset.mk α s nd ↔ a ∈ s :=
Iff.rfl
#align finset.mem_mk Finset.mem_mk
instance decidableMem [_h : DecidableEq α] (a : α) (s : Finset α) : Decidable (a ∈ s) :=
Multiset.decidableMem _ _
#align finset.decidable_mem Finset.decidableMem
@[simp] lemma forall_mem_not_eq {s : Finset α} {a : α} : (∀ b ∈ s, ¬ a = b) ↔ a ∉ s := by aesop
@[simp] lemma forall_mem_not_eq' {s : Finset α} {a : α} : (∀ b ∈ s, ¬ b = a) ↔ a ∉ s := by aesop
/-! ### set coercion -/
-- Porting note (#11445): new definition
/-- Convert a finset to a set in the natural way. -/
@[coe] def toSet (s : Finset α) : Set α :=
{ a | a ∈ s }
/-- Convert a finset to a set in the natural way. -/
instance : CoeTC (Finset α) (Set α) :=
⟨toSet⟩
@[simp, norm_cast]
theorem mem_coe {a : α} {s : Finset α} : a ∈ (s : Set α) ↔ a ∈ (s : Finset α) :=
Iff.rfl
#align finset.mem_coe Finset.mem_coe
@[simp]
theorem setOf_mem {α} {s : Finset α} : { a | a ∈ s } = s :=
rfl
#align finset.set_of_mem Finset.setOf_mem
@[simp]
theorem coe_mem {s : Finset α} (x : (s : Set α)) : ↑x ∈ s :=
x.2
#align finset.coe_mem Finset.coe_mem
-- Porting note (#10618): @[simp] can prove this
theorem mk_coe {s : Finset α} (x : (s : Set α)) {h} : (⟨x, h⟩ : (s : Set α)) = x :=
Subtype.coe_eta _ _
#align finset.mk_coe Finset.mk_coe
instance decidableMem' [DecidableEq α] (a : α) (s : Finset α) : Decidable (a ∈ (s : Set α)) :=
s.decidableMem _
#align finset.decidable_mem' Finset.decidableMem'
/-! ### extensionality -/
theorem ext_iff {s₁ s₂ : Finset α} : s₁ = s₂ ↔ ∀ a, a ∈ s₁ ↔ a ∈ s₂ :=
val_inj.symm.trans <| s₁.nodup.ext s₂.nodup
#align finset.ext_iff Finset.ext_iff
@[ext]
theorem ext {s₁ s₂ : Finset α} : (∀ a, a ∈ s₁ ↔ a ∈ s₂) → s₁ = s₂ :=
ext_iff.2
#align finset.ext Finset.ext
@[simp, norm_cast]
theorem coe_inj {s₁ s₂ : Finset α} : (s₁ : Set α) = s₂ ↔ s₁ = s₂ :=
Set.ext_iff.trans ext_iff.symm
#align finset.coe_inj Finset.coe_inj
theorem coe_injective {α} : Injective ((↑) : Finset α → Set α) := fun _s _t => coe_inj.1
#align finset.coe_injective Finset.coe_injective
/-! ### type coercion -/
/-- Coercion from a finset to the corresponding subtype. -/
instance {α : Type u} : CoeSort (Finset α) (Type u) :=
⟨fun s => { x // x ∈ s }⟩
-- Porting note (#10618): @[simp] can prove this
protected theorem forall_coe {α : Type*} (s : Finset α) (p : s → Prop) :
(∀ x : s, p x) ↔ ∀ (x : α) (h : x ∈ s), p ⟨x, h⟩ :=
Subtype.forall
#align finset.forall_coe Finset.forall_coe
-- Porting note (#10618): @[simp] can prove this
protected theorem exists_coe {α : Type*} (s : Finset α) (p : s → Prop) :
(∃ x : s, p x) ↔ ∃ (x : α) (h : x ∈ s), p ⟨x, h⟩ :=
Subtype.exists
#align finset.exists_coe Finset.exists_coe
instance PiFinsetCoe.canLift (ι : Type*) (α : ι → Type*) [_ne : ∀ i, Nonempty (α i)]
(s : Finset ι) : CanLift (∀ i : s, α i) (∀ i, α i) (fun f i => f i) fun _ => True :=
PiSubtype.canLift ι α (· ∈ s)
#align finset.pi_finset_coe.can_lift Finset.PiFinsetCoe.canLift
instance PiFinsetCoe.canLift' (ι α : Type*) [_ne : Nonempty α] (s : Finset ι) :
CanLift (s → α) (ι → α) (fun f i => f i) fun _ => True :=
PiFinsetCoe.canLift ι (fun _ => α) s
#align finset.pi_finset_coe.can_lift' Finset.PiFinsetCoe.canLift'
instance FinsetCoe.canLift (s : Finset α) : CanLift α s (↑) fun a => a ∈ s where
prf a ha := ⟨⟨a, ha⟩, rfl⟩
#align finset.finset_coe.can_lift Finset.FinsetCoe.canLift
@[simp, norm_cast]
theorem coe_sort_coe (s : Finset α) : ((s : Set α) : Sort _) = s :=
rfl
#align finset.coe_sort_coe Finset.coe_sort_coe
/-! ### Subset and strict subset relations -/
section Subset
variable {s t : Finset α}
instance : HasSubset (Finset α) :=
⟨fun s t => ∀ ⦃a⦄, a ∈ s → a ∈ t⟩
instance : HasSSubset (Finset α) :=
⟨fun s t => s ⊆ t ∧ ¬t ⊆ s⟩
instance partialOrder : PartialOrder (Finset α) where
le := (· ⊆ ·)
lt := (· ⊂ ·)
le_refl s a := id
le_trans s t u hst htu a ha := htu <| hst ha
le_antisymm s t hst hts := ext fun a => ⟨@hst _, @hts _⟩
instance : IsRefl (Finset α) (· ⊆ ·) :=
show IsRefl (Finset α) (· ≤ ·) by infer_instance
instance : IsTrans (Finset α) (· ⊆ ·) :=
show IsTrans (Finset α) (· ≤ ·) by infer_instance
instance : IsAntisymm (Finset α) (· ⊆ ·) :=
show IsAntisymm (Finset α) (· ≤ ·) by infer_instance
instance : IsIrrefl (Finset α) (· ⊂ ·) :=
show IsIrrefl (Finset α) (· < ·) by infer_instance
instance : IsTrans (Finset α) (· ⊂ ·) :=
show IsTrans (Finset α) (· < ·) by infer_instance
instance : IsAsymm (Finset α) (· ⊂ ·) :=
show IsAsymm (Finset α) (· < ·) by infer_instance
instance : IsNonstrictStrictOrder (Finset α) (· ⊆ ·) (· ⊂ ·) :=
⟨fun _ _ => Iff.rfl⟩
theorem subset_def : s ⊆ t ↔ s.1 ⊆ t.1 :=
Iff.rfl
#align finset.subset_def Finset.subset_def
theorem ssubset_def : s ⊂ t ↔ s ⊆ t ∧ ¬t ⊆ s :=
Iff.rfl
#align finset.ssubset_def Finset.ssubset_def
@[simp]
theorem Subset.refl (s : Finset α) : s ⊆ s :=
Multiset.Subset.refl _
#align finset.subset.refl Finset.Subset.refl
protected theorem Subset.rfl {s : Finset α} : s ⊆ s :=
Subset.refl _
#align finset.subset.rfl Finset.Subset.rfl
protected theorem subset_of_eq {s t : Finset α} (h : s = t) : s ⊆ t :=
h ▸ Subset.refl _
#align finset.subset_of_eq Finset.subset_of_eq
theorem Subset.trans {s₁ s₂ s₃ : Finset α} : s₁ ⊆ s₂ → s₂ ⊆ s₃ → s₁ ⊆ s₃ :=
Multiset.Subset.trans
#align finset.subset.trans Finset.Subset.trans
theorem Superset.trans {s₁ s₂ s₃ : Finset α} : s₁ ⊇ s₂ → s₂ ⊇ s₃ → s₁ ⊇ s₃ := fun h' h =>
Subset.trans h h'
#align finset.superset.trans Finset.Superset.trans
theorem mem_of_subset {s₁ s₂ : Finset α} {a : α} : s₁ ⊆ s₂ → a ∈ s₁ → a ∈ s₂ :=
Multiset.mem_of_subset
#align finset.mem_of_subset Finset.mem_of_subset
theorem not_mem_mono {s t : Finset α} (h : s ⊆ t) {a : α} : a ∉ t → a ∉ s :=
mt <| @h _
#align finset.not_mem_mono Finset.not_mem_mono
theorem Subset.antisymm {s₁ s₂ : Finset α} (H₁ : s₁ ⊆ s₂) (H₂ : s₂ ⊆ s₁) : s₁ = s₂ :=
ext fun a => ⟨@H₁ a, @H₂ a⟩
#align finset.subset.antisymm Finset.Subset.antisymm
theorem subset_iff {s₁ s₂ : Finset α} : s₁ ⊆ s₂ ↔ ∀ ⦃x⦄, x ∈ s₁ → x ∈ s₂ :=
Iff.rfl
#align finset.subset_iff Finset.subset_iff
@[simp, norm_cast]
theorem coe_subset {s₁ s₂ : Finset α} : (s₁ : Set α) ⊆ s₂ ↔ s₁ ⊆ s₂ :=
Iff.rfl
#align finset.coe_subset Finset.coe_subset
@[simp]
theorem val_le_iff {s₁ s₂ : Finset α} : s₁.1 ≤ s₂.1 ↔ s₁ ⊆ s₂ :=
le_iff_subset s₁.2
#align finset.val_le_iff Finset.val_le_iff
theorem Subset.antisymm_iff {s₁ s₂ : Finset α} : s₁ = s₂ ↔ s₁ ⊆ s₂ ∧ s₂ ⊆ s₁ :=
le_antisymm_iff
#align finset.subset.antisymm_iff Finset.Subset.antisymm_iff
theorem not_subset : ¬s ⊆ t ↔ ∃ x ∈ s, x ∉ t := by simp only [← coe_subset, Set.not_subset, mem_coe]
#align finset.not_subset Finset.not_subset
@[simp]
theorem le_eq_subset : ((· ≤ ·) : Finset α → Finset α → Prop) = (· ⊆ ·) :=
rfl
#align finset.le_eq_subset Finset.le_eq_subset
@[simp]
theorem lt_eq_subset : ((· < ·) : Finset α → Finset α → Prop) = (· ⊂ ·) :=
rfl
#align finset.lt_eq_subset Finset.lt_eq_subset
theorem le_iff_subset {s₁ s₂ : Finset α} : s₁ ≤ s₂ ↔ s₁ ⊆ s₂ :=
Iff.rfl
#align finset.le_iff_subset Finset.le_iff_subset
theorem lt_iff_ssubset {s₁ s₂ : Finset α} : s₁ < s₂ ↔ s₁ ⊂ s₂ :=
Iff.rfl
#align finset.lt_iff_ssubset Finset.lt_iff_ssubset
@[simp, norm_cast]
theorem coe_ssubset {s₁ s₂ : Finset α} : (s₁ : Set α) ⊂ s₂ ↔ s₁ ⊂ s₂ :=
show (s₁ : Set α) ⊂ s₂ ↔ s₁ ⊆ s₂ ∧ ¬s₂ ⊆ s₁ by simp only [Set.ssubset_def, Finset.coe_subset]
#align finset.coe_ssubset Finset.coe_ssubset
@[simp]
theorem val_lt_iff {s₁ s₂ : Finset α} : s₁.1 < s₂.1 ↔ s₁ ⊂ s₂ :=
and_congr val_le_iff <| not_congr val_le_iff
#align finset.val_lt_iff Finset.val_lt_iff
lemma val_strictMono : StrictMono (val : Finset α → Multiset α) := fun _ _ ↦ val_lt_iff.2
theorem ssubset_iff_subset_ne {s t : Finset α} : s ⊂ t ↔ s ⊆ t ∧ s ≠ t :=
@lt_iff_le_and_ne _ _ s t
#align finset.ssubset_iff_subset_ne Finset.ssubset_iff_subset_ne
theorem ssubset_iff_of_subset {s₁ s₂ : Finset α} (h : s₁ ⊆ s₂) : s₁ ⊂ s₂ ↔ ∃ x ∈ s₂, x ∉ s₁ :=
Set.ssubset_iff_of_subset h
#align finset.ssubset_iff_of_subset Finset.ssubset_iff_of_subset
theorem ssubset_of_ssubset_of_subset {s₁ s₂ s₃ : Finset α} (hs₁s₂ : s₁ ⊂ s₂) (hs₂s₃ : s₂ ⊆ s₃) :
s₁ ⊂ s₃ :=
Set.ssubset_of_ssubset_of_subset hs₁s₂ hs₂s₃
#align finset.ssubset_of_ssubset_of_subset Finset.ssubset_of_ssubset_of_subset
theorem ssubset_of_subset_of_ssubset {s₁ s₂ s₃ : Finset α} (hs₁s₂ : s₁ ⊆ s₂) (hs₂s₃ : s₂ ⊂ s₃) :
s₁ ⊂ s₃ :=
Set.ssubset_of_subset_of_ssubset hs₁s₂ hs₂s₃
#align finset.ssubset_of_subset_of_ssubset Finset.ssubset_of_subset_of_ssubset
theorem exists_of_ssubset {s₁ s₂ : Finset α} (h : s₁ ⊂ s₂) : ∃ x ∈ s₂, x ∉ s₁ :=
Set.exists_of_ssubset h
#align finset.exists_of_ssubset Finset.exists_of_ssubset
instance isWellFounded_ssubset : IsWellFounded (Finset α) (· ⊂ ·) :=
Subrelation.isWellFounded (InvImage _ _) val_lt_iff.2
#align finset.is_well_founded_ssubset Finset.isWellFounded_ssubset
instance wellFoundedLT : WellFoundedLT (Finset α) :=
Finset.isWellFounded_ssubset
#align finset.is_well_founded_lt Finset.wellFoundedLT
end Subset
-- TODO: these should be global attributes, but this will require fixing other files
attribute [local trans] Subset.trans Superset.trans
/-! ### Order embedding from `Finset α` to `Set α` -/
/-- Coercion to `Set α` as an `OrderEmbedding`. -/
def coeEmb : Finset α ↪o Set α :=
⟨⟨(↑), coe_injective⟩, coe_subset⟩
#align finset.coe_emb Finset.coeEmb
@[simp]
theorem coe_coeEmb : ⇑(coeEmb : Finset α ↪o Set α) = ((↑) : Finset α → Set α) :=
rfl
#align finset.coe_coe_emb Finset.coe_coeEmb
/-! ### Nonempty -/
/-- The property `s.Nonempty` expresses the fact that the finset `s` is not empty. It should be used
in theorem assumptions instead of `∃ x, x ∈ s` or `s ≠ ∅` as it gives access to a nice API thanks
to the dot notation. -/
protected def Nonempty (s : Finset α) : Prop := ∃ x : α, x ∈ s
#align finset.nonempty Finset.Nonempty
-- Porting note: Much longer than in Lean3
instance decidableNonempty {s : Finset α} : Decidable s.Nonempty :=
Quotient.recOnSubsingleton (motive := fun s : Multiset α => Decidable (∃ a, a ∈ s)) s.1
(fun l : List α =>
match l with
| [] => isFalse <| by simp
| a::l => isTrue ⟨a, by simp⟩)
#align finset.decidable_nonempty Finset.decidableNonempty
@[simp, norm_cast]
theorem coe_nonempty {s : Finset α} : (s : Set α).Nonempty ↔ s.Nonempty :=
Iff.rfl
#align finset.coe_nonempty Finset.coe_nonempty
-- Porting note: Left-hand side simplifies @[simp]
theorem nonempty_coe_sort {s : Finset α} : Nonempty (s : Type _) ↔ s.Nonempty :=
nonempty_subtype
#align finset.nonempty_coe_sort Finset.nonempty_coe_sort
alias ⟨_, Nonempty.to_set⟩ := coe_nonempty
#align finset.nonempty.to_set Finset.Nonempty.to_set
alias ⟨_, Nonempty.coe_sort⟩ := nonempty_coe_sort
#align finset.nonempty.coe_sort Finset.Nonempty.coe_sort
theorem Nonempty.exists_mem {s : Finset α} (h : s.Nonempty) : ∃ x : α, x ∈ s :=
h
#align finset.nonempty.bex Finset.Nonempty.exists_mem
@[deprecated (since := "2024-03-23")] alias Nonempty.bex := Nonempty.exists_mem
theorem Nonempty.mono {s t : Finset α} (hst : s ⊆ t) (hs : s.Nonempty) : t.Nonempty :=
Set.Nonempty.mono hst hs
#align finset.nonempty.mono Finset.Nonempty.mono
theorem Nonempty.forall_const {s : Finset α} (h : s.Nonempty) {p : Prop} : (∀ x ∈ s, p) ↔ p :=
let ⟨x, hx⟩ := h
⟨fun h => h x hx, fun h _ _ => h⟩
#align finset.nonempty.forall_const Finset.Nonempty.forall_const
theorem Nonempty.to_subtype {s : Finset α} : s.Nonempty → Nonempty s :=
nonempty_coe_sort.2
#align finset.nonempty.to_subtype Finset.Nonempty.to_subtype
theorem Nonempty.to_type {s : Finset α} : s.Nonempty → Nonempty α := fun ⟨x, _hx⟩ => ⟨x⟩
#align finset.nonempty.to_type Finset.Nonempty.to_type
/-! ### empty -/
section Empty
variable {s : Finset α}
/-- The empty finset -/
protected def empty : Finset α :=
⟨0, nodup_zero⟩
#align finset.empty Finset.empty
instance : EmptyCollection (Finset α) :=
⟨Finset.empty⟩
instance inhabitedFinset : Inhabited (Finset α) :=
⟨∅⟩
#align finset.inhabited_finset Finset.inhabitedFinset
@[simp]
theorem empty_val : (∅ : Finset α).1 = 0 :=
rfl
#align finset.empty_val Finset.empty_val
@[simp]
theorem not_mem_empty (a : α) : a ∉ (∅ : Finset α) := by
-- Porting note: was `id`. `a ∈ List.nil` is no longer definitionally equal to `False`
simp only [mem_def, empty_val, not_mem_zero, not_false_iff]
#align finset.not_mem_empty Finset.not_mem_empty
@[simp]
theorem not_nonempty_empty : ¬(∅ : Finset α).Nonempty := fun ⟨x, hx⟩ => not_mem_empty x hx
#align finset.not_nonempty_empty Finset.not_nonempty_empty
@[simp]
theorem mk_zero : (⟨0, nodup_zero⟩ : Finset α) = ∅ :=
rfl
#align finset.mk_zero Finset.mk_zero
theorem ne_empty_of_mem {a : α} {s : Finset α} (h : a ∈ s) : s ≠ ∅ := fun e =>
not_mem_empty a <| e ▸ h
#align finset.ne_empty_of_mem Finset.ne_empty_of_mem
theorem Nonempty.ne_empty {s : Finset α} (h : s.Nonempty) : s ≠ ∅ :=
(Exists.elim h) fun _a => ne_empty_of_mem
#align finset.nonempty.ne_empty Finset.Nonempty.ne_empty
@[simp]
theorem empty_subset (s : Finset α) : ∅ ⊆ s :=
zero_subset _
#align finset.empty_subset Finset.empty_subset
theorem eq_empty_of_forall_not_mem {s : Finset α} (H : ∀ x, x ∉ s) : s = ∅ :=
eq_of_veq (eq_zero_of_forall_not_mem H)
#align finset.eq_empty_of_forall_not_mem Finset.eq_empty_of_forall_not_mem
theorem eq_empty_iff_forall_not_mem {s : Finset α} : s = ∅ ↔ ∀ x, x ∉ s :=
-- Porting note: used `id`
⟨by rintro rfl x; apply not_mem_empty, fun h => eq_empty_of_forall_not_mem h⟩
#align finset.eq_empty_iff_forall_not_mem Finset.eq_empty_iff_forall_not_mem
@[simp]
theorem val_eq_zero {s : Finset α} : s.1 = 0 ↔ s = ∅ :=
@val_inj _ s ∅
#align finset.val_eq_zero Finset.val_eq_zero
theorem subset_empty {s : Finset α} : s ⊆ ∅ ↔ s = ∅ :=
subset_zero.trans val_eq_zero
#align finset.subset_empty Finset.subset_empty
@[simp]
theorem not_ssubset_empty (s : Finset α) : ¬s ⊂ ∅ := fun h =>
let ⟨_, he, _⟩ := exists_of_ssubset h
-- Porting note: was `he`
not_mem_empty _ he
#align finset.not_ssubset_empty Finset.not_ssubset_empty
theorem nonempty_of_ne_empty {s : Finset α} (h : s ≠ ∅) : s.Nonempty :=
exists_mem_of_ne_zero (mt val_eq_zero.1 h)
#align finset.nonempty_of_ne_empty Finset.nonempty_of_ne_empty
theorem nonempty_iff_ne_empty {s : Finset α} : s.Nonempty ↔ s ≠ ∅ :=
⟨Nonempty.ne_empty, nonempty_of_ne_empty⟩
#align finset.nonempty_iff_ne_empty Finset.nonempty_iff_ne_empty
@[simp]
theorem not_nonempty_iff_eq_empty {s : Finset α} : ¬s.Nonempty ↔ s = ∅ :=
nonempty_iff_ne_empty.not.trans not_not
#align finset.not_nonempty_iff_eq_empty Finset.not_nonempty_iff_eq_empty
theorem eq_empty_or_nonempty (s : Finset α) : s = ∅ ∨ s.Nonempty :=
by_cases Or.inl fun h => Or.inr (nonempty_of_ne_empty h)
#align finset.eq_empty_or_nonempty Finset.eq_empty_or_nonempty
@[simp, norm_cast]
theorem coe_empty : ((∅ : Finset α) : Set α) = ∅ :=
Set.ext <| by simp
#align finset.coe_empty Finset.coe_empty
@[simp, norm_cast]
theorem coe_eq_empty {s : Finset α} : (s : Set α) = ∅ ↔ s = ∅ := by rw [← coe_empty, coe_inj]
#align finset.coe_eq_empty Finset.coe_eq_empty
-- Porting note: Left-hand side simplifies @[simp]
theorem isEmpty_coe_sort {s : Finset α} : IsEmpty (s : Type _) ↔ s = ∅ := by
simpa using @Set.isEmpty_coe_sort α s
#align finset.is_empty_coe_sort Finset.isEmpty_coe_sort
instance instIsEmpty : IsEmpty (∅ : Finset α) :=
isEmpty_coe_sort.2 rfl
/-- A `Finset` for an empty type is empty. -/
theorem eq_empty_of_isEmpty [IsEmpty α] (s : Finset α) : s = ∅ :=
Finset.eq_empty_of_forall_not_mem isEmptyElim
#align finset.eq_empty_of_is_empty Finset.eq_empty_of_isEmpty
instance : OrderBot (Finset α) where
bot := ∅
bot_le := empty_subset
@[simp]
theorem bot_eq_empty : (⊥ : Finset α) = ∅ :=
rfl
#align finset.bot_eq_empty Finset.bot_eq_empty
@[simp]
theorem empty_ssubset : ∅ ⊂ s ↔ s.Nonempty :=
(@bot_lt_iff_ne_bot (Finset α) _ _ _).trans nonempty_iff_ne_empty.symm
#align finset.empty_ssubset Finset.empty_ssubset
alias ⟨_, Nonempty.empty_ssubset⟩ := empty_ssubset
#align finset.nonempty.empty_ssubset Finset.Nonempty.empty_ssubset
end Empty
/-! ### singleton -/
section Singleton
variable {s : Finset α} {a b : α}
/-- `{a} : Finset a` is the set `{a}` containing `a` and nothing else.
This differs from `insert a ∅` in that it does not require a `DecidableEq` instance for `α`.
-/
instance : Singleton α (Finset α) :=
⟨fun a => ⟨{a}, nodup_singleton a⟩⟩
@[simp]
theorem singleton_val (a : α) : ({a} : Finset α).1 = {a} :=
rfl
#align finset.singleton_val Finset.singleton_val
@[simp]
theorem mem_singleton {a b : α} : b ∈ ({a} : Finset α) ↔ b = a :=
Multiset.mem_singleton
#align finset.mem_singleton Finset.mem_singleton
theorem eq_of_mem_singleton {x y : α} (h : x ∈ ({y} : Finset α)) : x = y :=
mem_singleton.1 h
#align finset.eq_of_mem_singleton Finset.eq_of_mem_singleton
theorem not_mem_singleton {a b : α} : a ∉ ({b} : Finset α) ↔ a ≠ b :=
not_congr mem_singleton
#align finset.not_mem_singleton Finset.not_mem_singleton
theorem mem_singleton_self (a : α) : a ∈ ({a} : Finset α) :=
-- Porting note: was `Or.inl rfl`
mem_singleton.mpr rfl
#align finset.mem_singleton_self Finset.mem_singleton_self
@[simp]
theorem val_eq_singleton_iff {a : α} {s : Finset α} : s.val = {a} ↔ s = {a} := by
rw [← val_inj]
rfl
#align finset.val_eq_singleton_iff Finset.val_eq_singleton_iff
theorem singleton_injective : Injective (singleton : α → Finset α) := fun _a _b h =>
mem_singleton.1 (h ▸ mem_singleton_self _)
#align finset.singleton_injective Finset.singleton_injective
@[simp]
theorem singleton_inj : ({a} : Finset α) = {b} ↔ a = b :=
singleton_injective.eq_iff
#align finset.singleton_inj Finset.singleton_inj
@[simp, aesop safe apply (rule_sets := [finsetNonempty])]
theorem singleton_nonempty (a : α) : ({a} : Finset α).Nonempty :=
⟨a, mem_singleton_self a⟩
#align finset.singleton_nonempty Finset.singleton_nonempty
@[simp]
theorem singleton_ne_empty (a : α) : ({a} : Finset α) ≠ ∅ :=
(singleton_nonempty a).ne_empty
#align finset.singleton_ne_empty Finset.singleton_ne_empty
theorem empty_ssubset_singleton : (∅ : Finset α) ⊂ {a} :=
(singleton_nonempty _).empty_ssubset
#align finset.empty_ssubset_singleton Finset.empty_ssubset_singleton
@[simp, norm_cast]
theorem coe_singleton (a : α) : (({a} : Finset α) : Set α) = {a} := by
ext
simp
#align finset.coe_singleton Finset.coe_singleton
@[simp, norm_cast]
theorem coe_eq_singleton {s : Finset α} {a : α} : (s : Set α) = {a} ↔ s = {a} := by
rw [← coe_singleton, coe_inj]
#align finset.coe_eq_singleton Finset.coe_eq_singleton
@[norm_cast]
lemma coe_subset_singleton : (s : Set α) ⊆ {a} ↔ s ⊆ {a} := by rw [← coe_subset, coe_singleton]
@[norm_cast]
lemma singleton_subset_coe : {a} ⊆ (s : Set α) ↔ {a} ⊆ s := by rw [← coe_subset, coe_singleton]
theorem eq_singleton_iff_unique_mem {s : Finset α} {a : α} : s = {a} ↔ a ∈ s ∧ ∀ x ∈ s, x = a := by
constructor <;> intro t
· rw [t]
exact ⟨Finset.mem_singleton_self _, fun _ => Finset.mem_singleton.1⟩
· ext
rw [Finset.mem_singleton]
exact ⟨t.right _, fun r => r.symm ▸ t.left⟩
#align finset.eq_singleton_iff_unique_mem Finset.eq_singleton_iff_unique_mem
theorem eq_singleton_iff_nonempty_unique_mem {s : Finset α} {a : α} :
s = {a} ↔ s.Nonempty ∧ ∀ x ∈ s, x = a := by
constructor
· rintro rfl
simp
· rintro ⟨hne, h_uniq⟩
rw [eq_singleton_iff_unique_mem]
refine ⟨?_, h_uniq⟩
rw [← h_uniq hne.choose hne.choose_spec]
exact hne.choose_spec
#align finset.eq_singleton_iff_nonempty_unique_mem Finset.eq_singleton_iff_nonempty_unique_mem
theorem nonempty_iff_eq_singleton_default [Unique α] {s : Finset α} :
s.Nonempty ↔ s = {default} := by
simp [eq_singleton_iff_nonempty_unique_mem, eq_iff_true_of_subsingleton]
#align finset.nonempty_iff_eq_singleton_default Finset.nonempty_iff_eq_singleton_default
alias ⟨Nonempty.eq_singleton_default, _⟩ := nonempty_iff_eq_singleton_default
#align finset.nonempty.eq_singleton_default Finset.Nonempty.eq_singleton_default
theorem singleton_iff_unique_mem (s : Finset α) : (∃ a, s = {a}) ↔ ∃! a, a ∈ s := by
simp only [eq_singleton_iff_unique_mem, ExistsUnique]
#align finset.singleton_iff_unique_mem Finset.singleton_iff_unique_mem
theorem singleton_subset_set_iff {s : Set α} {a : α} : ↑({a} : Finset α) ⊆ s ↔ a ∈ s := by
rw [coe_singleton, Set.singleton_subset_iff]
#align finset.singleton_subset_set_iff Finset.singleton_subset_set_iff
@[simp]
theorem singleton_subset_iff {s : Finset α} {a : α} : {a} ⊆ s ↔ a ∈ s :=
singleton_subset_set_iff
#align finset.singleton_subset_iff Finset.singleton_subset_iff
@[simp]
theorem subset_singleton_iff {s : Finset α} {a : α} : s ⊆ {a} ↔ s = ∅ ∨ s = {a} := by
rw [← coe_subset, coe_singleton, Set.subset_singleton_iff_eq, coe_eq_empty, coe_eq_singleton]
#align finset.subset_singleton_iff Finset.subset_singleton_iff
theorem singleton_subset_singleton : ({a} : Finset α) ⊆ {b} ↔ a = b := by simp
#align finset.singleton_subset_singleton Finset.singleton_subset_singleton
protected theorem Nonempty.subset_singleton_iff {s : Finset α} {a : α} (h : s.Nonempty) :
s ⊆ {a} ↔ s = {a} :=
subset_singleton_iff.trans <| or_iff_right h.ne_empty
#align finset.nonempty.subset_singleton_iff Finset.Nonempty.subset_singleton_iff
theorem subset_singleton_iff' {s : Finset α} {a : α} : s ⊆ {a} ↔ ∀ b ∈ s, b = a :=
forall₂_congr fun _ _ => mem_singleton
#align finset.subset_singleton_iff' Finset.subset_singleton_iff'
@[simp]
theorem ssubset_singleton_iff {s : Finset α} {a : α} : s ⊂ {a} ↔ s = ∅ := by
rw [← coe_ssubset, coe_singleton, Set.ssubset_singleton_iff, coe_eq_empty]
#align finset.ssubset_singleton_iff Finset.ssubset_singleton_iff
theorem eq_empty_of_ssubset_singleton {s : Finset α} {x : α} (hs : s ⊂ {x}) : s = ∅ :=
ssubset_singleton_iff.1 hs
#align finset.eq_empty_of_ssubset_singleton Finset.eq_empty_of_ssubset_singleton
/-- A finset is nontrivial if it has at least two elements. -/
protected abbrev Nontrivial (s : Finset α) : Prop := (s : Set α).Nontrivial
#align finset.nontrivial Finset.Nontrivial
@[simp]
theorem not_nontrivial_empty : ¬ (∅ : Finset α).Nontrivial := by simp [Finset.Nontrivial]
#align finset.not_nontrivial_empty Finset.not_nontrivial_empty
@[simp]
theorem not_nontrivial_singleton : ¬ ({a} : Finset α).Nontrivial := by simp [Finset.Nontrivial]
#align finset.not_nontrivial_singleton Finset.not_nontrivial_singleton
theorem Nontrivial.ne_singleton (hs : s.Nontrivial) : s ≠ {a} := by
rintro rfl; exact not_nontrivial_singleton hs
#align finset.nontrivial.ne_singleton Finset.Nontrivial.ne_singleton
nonrec lemma Nontrivial.exists_ne (hs : s.Nontrivial) (a : α) : ∃ b ∈ s, b ≠ a := hs.exists_ne _
theorem eq_singleton_or_nontrivial (ha : a ∈ s) : s = {a} ∨ s.Nontrivial := by
rw [← coe_eq_singleton]; exact Set.eq_singleton_or_nontrivial ha
#align finset.eq_singleton_or_nontrivial Finset.eq_singleton_or_nontrivial
theorem nontrivial_iff_ne_singleton (ha : a ∈ s) : s.Nontrivial ↔ s ≠ {a} :=
⟨Nontrivial.ne_singleton, (eq_singleton_or_nontrivial ha).resolve_left⟩
#align finset.nontrivial_iff_ne_singleton Finset.nontrivial_iff_ne_singleton
theorem Nonempty.exists_eq_singleton_or_nontrivial : s.Nonempty → (∃ a, s = {a}) ∨ s.Nontrivial :=
fun ⟨a, ha⟩ => (eq_singleton_or_nontrivial ha).imp_left <| Exists.intro a
#align finset.nonempty.exists_eq_singleton_or_nontrivial Finset.Nonempty.exists_eq_singleton_or_nontrivial
instance instNontrivial [Nonempty α] : Nontrivial (Finset α) :=
‹Nonempty α›.elim fun a => ⟨⟨{a}, ∅, singleton_ne_empty _⟩⟩
#align finset.nontrivial' Finset.instNontrivial
instance [IsEmpty α] : Unique (Finset α) where
default := ∅
uniq _ := eq_empty_of_forall_not_mem isEmptyElim
instance (i : α) : Unique ({i} : Finset α) where
default := ⟨i, mem_singleton_self i⟩
uniq j := Subtype.ext <| mem_singleton.mp j.2
@[simp]
lemma default_singleton (i : α) : ((default : ({i} : Finset α)) : α) = i := rfl
end Singleton
/-! ### cons -/
section Cons
variable {s t : Finset α} {a b : α}
/-- `cons a s h` is the set `{a} ∪ s` containing `a` and the elements of `s`. It is the same as
`insert a s` when it is defined, but unlike `insert a s` it does not require `DecidableEq α`,
and the union is guaranteed to be disjoint. -/
def cons (a : α) (s : Finset α) (h : a ∉ s) : Finset α :=
⟨a ::ₘ s.1, nodup_cons.2 ⟨h, s.2⟩⟩
#align finset.cons Finset.cons
@[simp]
theorem mem_cons {h} : b ∈ s.cons a h ↔ b = a ∨ b ∈ s :=
Multiset.mem_cons
#align finset.mem_cons Finset.mem_cons
theorem mem_cons_of_mem {a b : α} {s : Finset α} {hb : b ∉ s} (ha : a ∈ s) : a ∈ cons b s hb :=
Multiset.mem_cons_of_mem ha
-- Porting note (#10618): @[simp] can prove this
theorem mem_cons_self (a : α) (s : Finset α) {h} : a ∈ cons a s h :=
Multiset.mem_cons_self _ _
#align finset.mem_cons_self Finset.mem_cons_self
@[simp]
theorem cons_val (h : a ∉ s) : (cons a s h).1 = a ::ₘ s.1 :=
rfl
#align finset.cons_val Finset.cons_val
theorem forall_mem_cons (h : a ∉ s) (p : α → Prop) :
(∀ x, x ∈ cons a s h → p x) ↔ p a ∧ ∀ x, x ∈ s → p x := by
simp only [mem_cons, or_imp, forall_and, forall_eq]
#align finset.forall_mem_cons Finset.forall_mem_cons
/-- Useful in proofs by induction. -/
theorem forall_of_forall_cons {p : α → Prop} {h : a ∉ s} (H : ∀ x, x ∈ cons a s h → p x) (x)
(h : x ∈ s) : p x :=
H _ <| mem_cons.2 <| Or.inr h
#align finset.forall_of_forall_cons Finset.forall_of_forall_cons
@[simp]
theorem mk_cons {s : Multiset α} (h : (a ::ₘ s).Nodup) :
(⟨a ::ₘ s, h⟩ : Finset α) = cons a ⟨s, (nodup_cons.1 h).2⟩ (nodup_cons.1 h).1 :=
rfl
#align finset.mk_cons Finset.mk_cons
@[simp]
theorem cons_empty (a : α) : cons a ∅ (not_mem_empty _) = {a} := rfl
#align finset.cons_empty Finset.cons_empty
@[simp, aesop safe apply (rule_sets := [finsetNonempty])]
theorem nonempty_cons (h : a ∉ s) : (cons a s h).Nonempty :=
⟨a, mem_cons.2 <| Or.inl rfl⟩
#align finset.nonempty_cons Finset.nonempty_cons
@[simp]
theorem nonempty_mk {m : Multiset α} {hm} : (⟨m, hm⟩ : Finset α).Nonempty ↔ m ≠ 0 := by
induction m using Multiset.induction_on <;> simp
#align finset.nonempty_mk Finset.nonempty_mk
@[simp]
theorem coe_cons {a s h} : (@cons α a s h : Set α) = insert a (s : Set α) := by
ext
simp
#align finset.coe_cons Finset.coe_cons
theorem subset_cons (h : a ∉ s) : s ⊆ s.cons a h :=
Multiset.subset_cons _ _
#align finset.subset_cons Finset.subset_cons
theorem ssubset_cons (h : a ∉ s) : s ⊂ s.cons a h :=
Multiset.ssubset_cons h
#align finset.ssubset_cons Finset.ssubset_cons
theorem cons_subset {h : a ∉ s} : s.cons a h ⊆ t ↔ a ∈ t ∧ s ⊆ t :=
Multiset.cons_subset
#align finset.cons_subset Finset.cons_subset
@[simp]
theorem cons_subset_cons {hs ht} : s.cons a hs ⊆ t.cons a ht ↔ s ⊆ t := by
rwa [← coe_subset, coe_cons, coe_cons, Set.insert_subset_insert_iff, coe_subset]
#align finset.cons_subset_cons Finset.cons_subset_cons
theorem ssubset_iff_exists_cons_subset : s ⊂ t ↔ ∃ (a : _) (h : a ∉ s), s.cons a h ⊆ t := by
refine ⟨fun h => ?_, fun ⟨a, ha, h⟩ => ssubset_of_ssubset_of_subset (ssubset_cons _) h⟩
obtain ⟨a, hs, ht⟩ := not_subset.1 h.2
exact ⟨a, ht, cons_subset.2 ⟨hs, h.subset⟩⟩
#align finset.ssubset_iff_exists_cons_subset Finset.ssubset_iff_exists_cons_subset
end Cons
/-! ### disjoint -/
section Disjoint
variable {f : α → β} {s t u : Finset α} {a b : α}
theorem disjoint_left : Disjoint s t ↔ ∀ ⦃a⦄, a ∈ s → a ∉ t :=
⟨fun h a hs ht => not_mem_empty a <|
singleton_subset_iff.mp (h (singleton_subset_iff.mpr hs) (singleton_subset_iff.mpr ht)),
fun h _ hs ht _ ha => (h (hs ha) (ht ha)).elim⟩
#align finset.disjoint_left Finset.disjoint_left
theorem disjoint_right : Disjoint s t ↔ ∀ ⦃a⦄, a ∈ t → a ∉ s := by
rw [_root_.disjoint_comm, disjoint_left]
#align finset.disjoint_right Finset.disjoint_right
theorem disjoint_iff_ne : Disjoint s t ↔ ∀ a ∈ s, ∀ b ∈ t, a ≠ b := by
simp only [disjoint_left, imp_not_comm, forall_eq']
#align finset.disjoint_iff_ne Finset.disjoint_iff_ne
@[simp]
theorem disjoint_val : s.1.Disjoint t.1 ↔ Disjoint s t :=
disjoint_left.symm
#align finset.disjoint_val Finset.disjoint_val
theorem _root_.Disjoint.forall_ne_finset (h : Disjoint s t) (ha : a ∈ s) (hb : b ∈ t) : a ≠ b :=
disjoint_iff_ne.1 h _ ha _ hb
#align disjoint.forall_ne_finset Disjoint.forall_ne_finset
theorem not_disjoint_iff : ¬Disjoint s t ↔ ∃ a, a ∈ s ∧ a ∈ t :=
disjoint_left.not.trans <| not_forall.trans <| exists_congr fun _ => by
rw [Classical.not_imp, not_not]
#align finset.not_disjoint_iff Finset.not_disjoint_iff
theorem disjoint_of_subset_left (h : s ⊆ u) (d : Disjoint u t) : Disjoint s t :=
disjoint_left.2 fun _x m₁ => (disjoint_left.1 d) (h m₁)
#align finset.disjoint_of_subset_left Finset.disjoint_of_subset_left
theorem disjoint_of_subset_right (h : t ⊆ u) (d : Disjoint s u) : Disjoint s t :=
disjoint_right.2 fun _x m₁ => (disjoint_right.1 d) (h m₁)
#align finset.disjoint_of_subset_right Finset.disjoint_of_subset_right
@[simp]
theorem disjoint_empty_left (s : Finset α) : Disjoint ∅ s :=
disjoint_bot_left
#align finset.disjoint_empty_left Finset.disjoint_empty_left
@[simp]
theorem disjoint_empty_right (s : Finset α) : Disjoint s ∅ :=
disjoint_bot_right
#align finset.disjoint_empty_right Finset.disjoint_empty_right
@[simp]
theorem disjoint_singleton_left : Disjoint (singleton a) s ↔ a ∉ s := by
simp only [disjoint_left, mem_singleton, forall_eq]
#align finset.disjoint_singleton_left Finset.disjoint_singleton_left
@[simp]
theorem disjoint_singleton_right : Disjoint s (singleton a) ↔ a ∉ s :=
disjoint_comm.trans disjoint_singleton_left
#align finset.disjoint_singleton_right Finset.disjoint_singleton_right
-- Porting note: Left-hand side simplifies @[simp]
theorem disjoint_singleton : Disjoint ({a} : Finset α) {b} ↔ a ≠ b := by
rw [disjoint_singleton_left, mem_singleton]
#align finset.disjoint_singleton Finset.disjoint_singleton
theorem disjoint_self_iff_empty (s : Finset α) : Disjoint s s ↔ s = ∅ :=
disjoint_self
#align finset.disjoint_self_iff_empty Finset.disjoint_self_iff_empty
@[simp, norm_cast]
theorem disjoint_coe : Disjoint (s : Set α) t ↔ Disjoint s t := by
simp only [Finset.disjoint_left, Set.disjoint_left, mem_coe]
#align finset.disjoint_coe Finset.disjoint_coe
@[simp, norm_cast]
theorem pairwiseDisjoint_coe {ι : Type*} {s : Set ι} {f : ι → Finset α} :
s.PairwiseDisjoint (fun i => f i : ι → Set α) ↔ s.PairwiseDisjoint f :=
forall₅_congr fun _ _ _ _ _ => disjoint_coe
#align finset.pairwise_disjoint_coe Finset.pairwiseDisjoint_coe
end Disjoint
/-! ### disjoint union -/
/-- `disjUnion s t h` is the set such that `a ∈ disjUnion s t h` iff `a ∈ s` or `a ∈ t`.
It is the same as `s ∪ t`, but it does not require decidable equality on the type. The hypothesis
ensures that the sets are disjoint. -/
def disjUnion (s t : Finset α) (h : Disjoint s t) : Finset α :=
⟨s.1 + t.1, Multiset.nodup_add.2 ⟨s.2, t.2, disjoint_val.2 h⟩⟩
#align finset.disj_union Finset.disjUnion
@[simp]
theorem mem_disjUnion {α s t h a} : a ∈ @disjUnion α s t h ↔ a ∈ s ∨ a ∈ t := by
rcases s with ⟨⟨s⟩⟩; rcases t with ⟨⟨t⟩⟩; apply List.mem_append
#align finset.mem_disj_union Finset.mem_disjUnion
@[simp, norm_cast]
theorem coe_disjUnion {s t : Finset α} (h : Disjoint s t) :
(disjUnion s t h : Set α) = (s : Set α) ∪ t :=
Set.ext <| by simp
theorem disjUnion_comm (s t : Finset α) (h : Disjoint s t) :
disjUnion s t h = disjUnion t s h.symm :=
eq_of_veq <| add_comm _ _
#align finset.disj_union_comm Finset.disjUnion_comm
@[simp]
theorem empty_disjUnion (t : Finset α) (h : Disjoint ∅ t := disjoint_bot_left) :
disjUnion ∅ t h = t :=
eq_of_veq <| zero_add _
#align finset.empty_disj_union Finset.empty_disjUnion
@[simp]
theorem disjUnion_empty (s : Finset α) (h : Disjoint s ∅ := disjoint_bot_right) :
disjUnion s ∅ h = s :=
eq_of_veq <| add_zero _
#align finset.disj_union_empty Finset.disjUnion_empty
theorem singleton_disjUnion (a : α) (t : Finset α) (h : Disjoint {a} t) :
disjUnion {a} t h = cons a t (disjoint_singleton_left.mp h) :=
eq_of_veq <| Multiset.singleton_add _ _
#align finset.singleton_disj_union Finset.singleton_disjUnion
theorem disjUnion_singleton (s : Finset α) (a : α) (h : Disjoint s {a}) :
disjUnion s {a} h = cons a s (disjoint_singleton_right.mp h) := by
rw [disjUnion_comm, singleton_disjUnion]
#align finset.disj_union_singleton Finset.disjUnion_singleton
/-! ### insert -/
section Insert
variable [DecidableEq α] {s t u v : Finset α} {a b : α}
/-- `insert a s` is the set `{a} ∪ s` containing `a` and the elements of `s`. -/
instance : Insert α (Finset α) :=
⟨fun a s => ⟨_, s.2.ndinsert a⟩⟩
theorem insert_def (a : α) (s : Finset α) : insert a s = ⟨_, s.2.ndinsert a⟩ :=
rfl
#align finset.insert_def Finset.insert_def
@[simp]
theorem insert_val (a : α) (s : Finset α) : (insert a s).1 = ndinsert a s.1 :=
rfl
#align finset.insert_val Finset.insert_val
theorem insert_val' (a : α) (s : Finset α) : (insert a s).1 = dedup (a ::ₘ s.1) := by
rw [dedup_cons, dedup_eq_self]; rfl
#align finset.insert_val' Finset.insert_val'
theorem insert_val_of_not_mem {a : α} {s : Finset α} (h : a ∉ s) : (insert a s).1 = a ::ₘ s.1 := by
rw [insert_val, ndinsert_of_not_mem h]
#align finset.insert_val_of_not_mem Finset.insert_val_of_not_mem
@[simp]
theorem mem_insert : a ∈ insert b s ↔ a = b ∨ a ∈ s :=
mem_ndinsert
#align finset.mem_insert Finset.mem_insert
theorem mem_insert_self (a : α) (s : Finset α) : a ∈ insert a s :=
mem_ndinsert_self a s.1
#align finset.mem_insert_self Finset.mem_insert_self
theorem mem_insert_of_mem (h : a ∈ s) : a ∈ insert b s :=
mem_ndinsert_of_mem h
#align finset.mem_insert_of_mem Finset.mem_insert_of_mem
theorem mem_of_mem_insert_of_ne (h : b ∈ insert a s) : b ≠ a → b ∈ s :=
(mem_insert.1 h).resolve_left
#align finset.mem_of_mem_insert_of_ne Finset.mem_of_mem_insert_of_ne
theorem eq_of_not_mem_of_mem_insert (ha : b ∈ insert a s) (hb : b ∉ s) : b = a :=
(mem_insert.1 ha).resolve_right hb
#align finset.eq_of_not_mem_of_mem_insert Finset.eq_of_not_mem_of_mem_insert
/-- A version of `LawfulSingleton.insert_emptyc_eq` that works with `dsimp`. -/
@[simp, nolint simpNF] lemma insert_empty : insert a (∅ : Finset α) = {a} := rfl
@[simp]
theorem cons_eq_insert (a s h) : @cons α a s h = insert a s :=
ext fun a => by simp
#align finset.cons_eq_insert Finset.cons_eq_insert
@[simp, norm_cast]
theorem coe_insert (a : α) (s : Finset α) : ↑(insert a s) = (insert a s : Set α) :=
Set.ext fun x => by simp only [mem_coe, mem_insert, Set.mem_insert_iff]
#align finset.coe_insert Finset.coe_insert
theorem mem_insert_coe {s : Finset α} {x y : α} : x ∈ insert y s ↔ x ∈ insert y (s : Set α) := by
simp
#align finset.mem_insert_coe Finset.mem_insert_coe
instance : LawfulSingleton α (Finset α) :=
⟨fun a => by ext; simp⟩
@[simp]
theorem insert_eq_of_mem (h : a ∈ s) : insert a s = s :=
eq_of_veq <| ndinsert_of_mem h
#align finset.insert_eq_of_mem Finset.insert_eq_of_mem
@[simp]
theorem insert_eq_self : insert a s = s ↔ a ∈ s :=
⟨fun h => h ▸ mem_insert_self _ _, insert_eq_of_mem⟩
#align finset.insert_eq_self Finset.insert_eq_self
theorem insert_ne_self : insert a s ≠ s ↔ a ∉ s :=
insert_eq_self.not
#align finset.insert_ne_self Finset.insert_ne_self
-- Porting note (#10618): @[simp] can prove this
theorem pair_eq_singleton (a : α) : ({a, a} : Finset α) = {a} :=
insert_eq_of_mem <| mem_singleton_self _
#align finset.pair_eq_singleton Finset.pair_eq_singleton
theorem Insert.comm (a b : α) (s : Finset α) : insert a (insert b s) = insert b (insert a s) :=
ext fun x => by simp only [mem_insert, or_left_comm]
#align finset.insert.comm Finset.Insert.comm
-- Porting note (#10618): @[simp] can prove this
@[norm_cast]
theorem coe_pair {a b : α} : (({a, b} : Finset α) : Set α) = {a, b} := by
ext
simp
#align finset.coe_pair Finset.coe_pair
@[simp, norm_cast]
theorem coe_eq_pair {s : Finset α} {a b : α} : (s : Set α) = {a, b} ↔ s = {a, b} := by
rw [← coe_pair, coe_inj]
#align finset.coe_eq_pair Finset.coe_eq_pair
theorem pair_comm (a b : α) : ({a, b} : Finset α) = {b, a} :=
Insert.comm a b ∅
#align finset.pair_comm Finset.pair_comm
-- Porting note (#10618): @[simp] can prove this
theorem insert_idem (a : α) (s : Finset α) : insert a (insert a s) = insert a s :=
ext fun x => by simp only [mem_insert, ← or_assoc, or_self_iff]
#align finset.insert_idem Finset.insert_idem
@[simp, aesop safe apply (rule_sets := [finsetNonempty])]
theorem insert_nonempty (a : α) (s : Finset α) : (insert a s).Nonempty :=
⟨a, mem_insert_self a s⟩
#align finset.insert_nonempty Finset.insert_nonempty
@[simp]
theorem insert_ne_empty (a : α) (s : Finset α) : insert a s ≠ ∅ :=
(insert_nonempty a s).ne_empty
#align finset.insert_ne_empty Finset.insert_ne_empty
-- Porting note: explicit universe annotation is no longer required.
instance (i : α) (s : Finset α) : Nonempty ((insert i s : Finset α) : Set α) :=
(Finset.coe_nonempty.mpr (s.insert_nonempty i)).to_subtype
theorem ne_insert_of_not_mem (s t : Finset α) {a : α} (h : a ∉ s) : s ≠ insert a t := by
contrapose! h
simp [h]
#align finset.ne_insert_of_not_mem Finset.ne_insert_of_not_mem
theorem insert_subset_iff : insert a s ⊆ t ↔ a ∈ t ∧ s ⊆ t := by
simp only [subset_iff, mem_insert, forall_eq, or_imp, forall_and]
#align finset.insert_subset Finset.insert_subset_iff
theorem insert_subset (ha : a ∈ t) (hs : s ⊆ t) : insert a s ⊆ t :=
insert_subset_iff.mpr ⟨ha,hs⟩
@[simp] theorem subset_insert (a : α) (s : Finset α) : s ⊆ insert a s := fun _b => mem_insert_of_mem
#align finset.subset_insert Finset.subset_insert
@[gcongr]
theorem insert_subset_insert (a : α) {s t : Finset α} (h : s ⊆ t) : insert a s ⊆ insert a t :=
insert_subset_iff.2 ⟨mem_insert_self _ _, Subset.trans h (subset_insert _ _)⟩
#align finset.insert_subset_insert Finset.insert_subset_insert
@[simp] lemma insert_subset_insert_iff (ha : a ∉ s) : insert a s ⊆ insert a t ↔ s ⊆ t := by
simp_rw [← coe_subset]; simp [-coe_subset, ha]
theorem insert_inj (ha : a ∉ s) : insert a s = insert b s ↔ a = b :=
⟨fun h => eq_of_not_mem_of_mem_insert (h.subst <| mem_insert_self _ _) ha, congr_arg (insert · s)⟩
#align finset.insert_inj Finset.insert_inj
theorem insert_inj_on (s : Finset α) : Set.InjOn (fun a => insert a s) sᶜ := fun _ h _ _ =>
(insert_inj h).1
#align finset.insert_inj_on Finset.insert_inj_on
theorem ssubset_iff : s ⊂ t ↔ ∃ a ∉ s, insert a s ⊆ t := mod_cast @Set.ssubset_iff_insert α s t
#align finset.ssubset_iff Finset.ssubset_iff
theorem ssubset_insert (h : a ∉ s) : s ⊂ insert a s :=
ssubset_iff.mpr ⟨a, h, Subset.rfl⟩
#align finset.ssubset_insert Finset.ssubset_insert
@[elab_as_elim]
theorem cons_induction {α : Type*} {p : Finset α → Prop} (empty : p ∅)
(cons : ∀ (a : α) (s : Finset α) (h : a ∉ s), p s → p (cons a s h)) : ∀ s, p s
| ⟨s, nd⟩ => by
induction s using Multiset.induction with
| empty => exact empty
| cons a s IH =>
rw [mk_cons nd]
exact cons a _ _ (IH _)
#align finset.cons_induction Finset.cons_induction
@[elab_as_elim]
theorem cons_induction_on {α : Type*} {p : Finset α → Prop} (s : Finset α) (h₁ : p ∅)
(h₂ : ∀ ⦃a : α⦄ {s : Finset α} (h : a ∉ s), p s → p (cons a s h)) : p s :=
cons_induction h₁ h₂ s
#align finset.cons_induction_on Finset.cons_induction_on
@[elab_as_elim]
protected theorem induction {α : Type*} {p : Finset α → Prop} [DecidableEq α] (empty : p ∅)
(insert : ∀ ⦃a : α⦄ {s : Finset α}, a ∉ s → p s → p (insert a s)) : ∀ s, p s :=
cons_induction empty fun a s ha => (s.cons_eq_insert a ha).symm ▸ insert ha
#align finset.induction Finset.induction
/-- To prove a proposition about an arbitrary `Finset α`,
it suffices to prove it for the empty `Finset`,
and to show that if it holds for some `Finset α`,
then it holds for the `Finset` obtained by inserting a new element.
-/
@[elab_as_elim]
protected theorem induction_on {α : Type*} {p : Finset α → Prop} [DecidableEq α] (s : Finset α)
(empty : p ∅) (insert : ∀ ⦃a : α⦄ {s : Finset α}, a ∉ s → p s → p (insert a s)) : p s :=
Finset.induction empty insert s
#align finset.induction_on Finset.induction_on
/-- To prove a proposition about `S : Finset α`,
it suffices to prove it for the empty `Finset`,
and to show that if it holds for some `Finset α ⊆ S`,
then it holds for the `Finset` obtained by inserting a new element of `S`.
-/
@[elab_as_elim]
theorem induction_on' {α : Type*} {p : Finset α → Prop} [DecidableEq α] (S : Finset α) (h₁ : p ∅)
(h₂ : ∀ {a s}, a ∈ S → s ⊆ S → a ∉ s → p s → p (insert a s)) : p S :=
@Finset.induction_on α (fun T => T ⊆ S → p T) _ S (fun _ => h₁)
(fun _ _ has hqs hs =>
let ⟨hS, sS⟩ := Finset.insert_subset_iff.1 hs
h₂ hS sS has (hqs sS))
(Finset.Subset.refl S)
#align finset.induction_on' Finset.induction_on'
/-- To prove a proposition about a nonempty `s : Finset α`, it suffices to show it holds for all
singletons and that if it holds for nonempty `t : Finset α`, then it also holds for the `Finset`
obtained by inserting an element in `t`. -/
@[elab_as_elim]
theorem Nonempty.cons_induction {α : Type*} {p : ∀ s : Finset α, s.Nonempty → Prop}
(singleton : ∀ a, p {a} (singleton_nonempty _))
(cons : ∀ a s (h : a ∉ s) (hs), p s hs → p (Finset.cons a s h) (nonempty_cons h))
{s : Finset α} (hs : s.Nonempty) : p s hs := by
induction s using Finset.cons_induction with
| empty => exact (not_nonempty_empty hs).elim
| cons a t ha h =>
obtain rfl | ht := t.eq_empty_or_nonempty
· exact singleton a
· exact cons a t ha ht (h ht)
#align finset.nonempty.cons_induction Finset.Nonempty.cons_induction
lemma Nonempty.exists_cons_eq (hs : s.Nonempty) : ∃ t a ha, cons a t ha = s :=
hs.cons_induction (fun a ↦ ⟨∅, a, _, cons_empty _⟩) fun _ _ _ _ _ ↦ ⟨_, _, _, rfl⟩
/-- Inserting an element to a finite set is equivalent to the option type. -/
def subtypeInsertEquivOption {t : Finset α} {x : α} (h : x ∉ t) :
{ i // i ∈ insert x t } ≃ Option { i // i ∈ t } where
toFun y := if h : ↑y = x then none else some ⟨y, (mem_insert.mp y.2).resolve_left h⟩
invFun y := (y.elim ⟨x, mem_insert_self _ _⟩) fun z => ⟨z, mem_insert_of_mem z.2⟩
left_inv y := by
by_cases h : ↑y = x
· simp only [Subtype.ext_iff, h, Option.elim, dif_pos, Subtype.coe_mk]
· simp only [h, Option.elim, dif_neg, not_false_iff, Subtype.coe_eta, Subtype.coe_mk]
right_inv := by
rintro (_ | y)
· simp only [Option.elim, dif_pos]
· have : ↑y ≠ x := by
rintro ⟨⟩
exact h y.2
simp only [this, Option.elim, Subtype.eta, dif_neg, not_false_iff, Subtype.coe_mk]
#align finset.subtype_insert_equiv_option Finset.subtypeInsertEquivOption
@[simp]
theorem disjoint_insert_left : Disjoint (insert a s) t ↔ a ∉ t ∧ Disjoint s t := by
simp only [disjoint_left, mem_insert, or_imp, forall_and, forall_eq]
#align finset.disjoint_insert_left Finset.disjoint_insert_left
@[simp]
theorem disjoint_insert_right : Disjoint s (insert a t) ↔ a ∉ s ∧ Disjoint s t :=
disjoint_comm.trans <| by rw [disjoint_insert_left, _root_.disjoint_comm]
#align finset.disjoint_insert_right Finset.disjoint_insert_right
end Insert
/-! ### Lattice structure -/
section Lattice
variable [DecidableEq α] {s s₁ s₂ t t₁ t₂ u v : Finset α} {a b : α}
/-- `s ∪ t` is the set such that `a ∈ s ∪ t` iff `a ∈ s` or `a ∈ t`. -/
instance : Union (Finset α) :=
⟨fun s t => ⟨_, t.2.ndunion s.1⟩⟩
/-- `s ∩ t` is the set such that `a ∈ s ∩ t` iff `a ∈ s` and `a ∈ t`. -/
instance : Inter (Finset α) :=
⟨fun s t => ⟨_, s.2.ndinter t.1⟩⟩
instance : Lattice (Finset α) :=
{ Finset.partialOrder with
sup := (· ∪ ·)
sup_le := fun _ _ _ hs ht _ ha => (mem_ndunion.1 ha).elim (fun h => hs h) fun h => ht h
le_sup_left := fun _ _ _ h => mem_ndunion.2 <| Or.inl h
le_sup_right := fun _ _ _ h => mem_ndunion.2 <| Or.inr h
inf := (· ∩ ·)
le_inf := fun _ _ _ ht hu _ h => mem_ndinter.2 ⟨ht h, hu h⟩
inf_le_left := fun _ _ _ h => (mem_ndinter.1 h).1
inf_le_right := fun _ _ _ h => (mem_ndinter.1 h).2 }
@[simp]
theorem sup_eq_union : (Sup.sup : Finset α → Finset α → Finset α) = Union.union :=
rfl
#align finset.sup_eq_union Finset.sup_eq_union
@[simp]
theorem inf_eq_inter : (Inf.inf : Finset α → Finset α → Finset α) = Inter.inter :=
rfl
#align finset.inf_eq_inter Finset.inf_eq_inter
theorem disjoint_iff_inter_eq_empty : Disjoint s t ↔ s ∩ t = ∅ :=
disjoint_iff
#align finset.disjoint_iff_inter_eq_empty Finset.disjoint_iff_inter_eq_empty
instance decidableDisjoint (U V : Finset α) : Decidable (Disjoint U V) :=
decidable_of_iff _ disjoint_left.symm
#align finset.decidable_disjoint Finset.decidableDisjoint
/-! #### union -/
theorem union_val_nd (s t : Finset α) : (s ∪ t).1 = ndunion s.1 t.1 :=
rfl
#align finset.union_val_nd Finset.union_val_nd
@[simp]
theorem union_val (s t : Finset α) : (s ∪ t).1 = s.1 ∪ t.1 :=
ndunion_eq_union s.2
#align finset.union_val Finset.union_val
@[simp]
theorem mem_union : a ∈ s ∪ t ↔ a ∈ s ∨ a ∈ t :=
mem_ndunion
#align finset.mem_union Finset.mem_union
@[simp]
theorem disjUnion_eq_union (s t h) : @disjUnion α s t h = s ∪ t :=
ext fun a => by simp
#align finset.disj_union_eq_union Finset.disjUnion_eq_union
theorem mem_union_left (t : Finset α) (h : a ∈ s) : a ∈ s ∪ t :=
mem_union.2 <| Or.inl h
#align finset.mem_union_left Finset.mem_union_left
theorem mem_union_right (s : Finset α) (h : a ∈ t) : a ∈ s ∪ t :=
mem_union.2 <| Or.inr h
#align finset.mem_union_right Finset.mem_union_right
theorem forall_mem_union {p : α → Prop} : (∀ a ∈ s ∪ t, p a) ↔ (∀ a ∈ s, p a) ∧ ∀ a ∈ t, p a :=
⟨fun h => ⟨fun a => h a ∘ mem_union_left _, fun b => h b ∘ mem_union_right _⟩,
fun h _ab hab => (mem_union.mp hab).elim (h.1 _) (h.2 _)⟩
#align finset.forall_mem_union Finset.forall_mem_union
theorem not_mem_union : a ∉ s ∪ t ↔ a ∉ s ∧ a ∉ t := by rw [mem_union, not_or]
#align finset.not_mem_union Finset.not_mem_union
@[simp, norm_cast]
theorem coe_union (s₁ s₂ : Finset α) : ↑(s₁ ∪ s₂) = (s₁ ∪ s₂ : Set α) :=
Set.ext fun _ => mem_union
#align finset.coe_union Finset.coe_union
theorem union_subset (hs : s ⊆ u) : t ⊆ u → s ∪ t ⊆ u :=
sup_le <| le_iff_subset.2 hs
#align finset.union_subset Finset.union_subset
theorem subset_union_left {s₁ s₂ : Finset α} : s₁ ⊆ s₁ ∪ s₂ := fun _x => mem_union_left _
#align finset.subset_union_left Finset.subset_union_left
theorem subset_union_right {s₁ s₂ : Finset α} : s₂ ⊆ s₁ ∪ s₂ := fun _x => mem_union_right _
#align finset.subset_union_right Finset.subset_union_right
@[gcongr]
theorem union_subset_union (hsu : s ⊆ u) (htv : t ⊆ v) : s ∪ t ⊆ u ∪ v :=
sup_le_sup (le_iff_subset.2 hsu) htv
#align finset.union_subset_union Finset.union_subset_union
@[gcongr]
theorem union_subset_union_left (h : s₁ ⊆ s₂) : s₁ ∪ t ⊆ s₂ ∪ t :=
union_subset_union h Subset.rfl
#align finset.union_subset_union_left Finset.union_subset_union_left
@[gcongr]
theorem union_subset_union_right (h : t₁ ⊆ t₂) : s ∪ t₁ ⊆ s ∪ t₂ :=
union_subset_union Subset.rfl h
#align finset.union_subset_union_right Finset.union_subset_union_right
theorem union_comm (s₁ s₂ : Finset α) : s₁ ∪ s₂ = s₂ ∪ s₁ := sup_comm _ _
#align finset.union_comm Finset.union_comm
instance : Std.Commutative (α := Finset α) (· ∪ ·) :=
⟨union_comm⟩
@[simp]
theorem union_assoc (s₁ s₂ s₃ : Finset α) : s₁ ∪ s₂ ∪ s₃ = s₁ ∪ (s₂ ∪ s₃) := sup_assoc _ _ _
#align finset.union_assoc Finset.union_assoc
instance : Std.Associative (α := Finset α) (· ∪ ·) :=
⟨union_assoc⟩
@[simp]
theorem union_idempotent (s : Finset α) : s ∪ s = s := sup_idem _
#align finset.union_idempotent Finset.union_idempotent
instance : Std.IdempotentOp (α := Finset α) (· ∪ ·) :=
⟨union_idempotent⟩
theorem union_subset_left (h : s ∪ t ⊆ u) : s ⊆ u :=
subset_union_left.trans h
#align finset.union_subset_left Finset.union_subset_left
theorem union_subset_right {s t u : Finset α} (h : s ∪ t ⊆ u) : t ⊆ u :=
Subset.trans subset_union_right h
#align finset.union_subset_right Finset.union_subset_right
theorem union_left_comm (s t u : Finset α) : s ∪ (t ∪ u) = t ∪ (s ∪ u) :=
ext fun _ => by simp only [mem_union, or_left_comm]
#align finset.union_left_comm Finset.union_left_comm
theorem union_right_comm (s t u : Finset α) : s ∪ t ∪ u = s ∪ u ∪ t :=
ext fun x => by simp only [mem_union, or_assoc, @or_comm (x ∈ t)]
#align finset.union_right_comm Finset.union_right_comm
theorem union_self (s : Finset α) : s ∪ s = s :=
union_idempotent s
#align finset.union_self Finset.union_self
@[simp]
theorem union_empty (s : Finset α) : s ∪ ∅ = s :=
ext fun x => mem_union.trans <| by simp
#align finset.union_empty Finset.union_empty
@[simp]
theorem empty_union (s : Finset α) : ∅ ∪ s = s :=
ext fun x => mem_union.trans <| by simp
#align finset.empty_union Finset.empty_union
@[aesop unsafe apply (rule_sets := [finsetNonempty])]
theorem Nonempty.inl {s t : Finset α} (h : s.Nonempty) : (s ∪ t).Nonempty :=
h.mono subset_union_left
@[aesop unsafe apply (rule_sets := [finsetNonempty])]
theorem Nonempty.inr {s t : Finset α} (h : t.Nonempty) : (s ∪ t).Nonempty :=
h.mono subset_union_right
theorem insert_eq (a : α) (s : Finset α) : insert a s = {a} ∪ s :=
rfl
#align finset.insert_eq Finset.insert_eq
@[simp]
theorem insert_union (a : α) (s t : Finset α) : insert a s ∪ t = insert a (s ∪ t) := by
simp only [insert_eq, union_assoc]
#align finset.insert_union Finset.insert_union
@[simp]
theorem union_insert (a : α) (s t : Finset α) : s ∪ insert a t = insert a (s ∪ t) := by
simp only [insert_eq, union_left_comm]
#align finset.union_insert Finset.union_insert
theorem insert_union_distrib (a : α) (s t : Finset α) :
insert a (s ∪ t) = insert a s ∪ insert a t := by
simp only [insert_union, union_insert, insert_idem]
#align finset.insert_union_distrib Finset.insert_union_distrib
@[simp] lemma union_eq_left : s ∪ t = s ↔ t ⊆ s := sup_eq_left
#align finset.union_eq_left_iff_subset Finset.union_eq_left
@[simp] lemma left_eq_union : s = s ∪ t ↔ t ⊆ s := by rw [eq_comm, union_eq_left]
#align finset.left_eq_union_iff_subset Finset.left_eq_union
@[simp] lemma union_eq_right : s ∪ t = t ↔ s ⊆ t := sup_eq_right
#align finset.union_eq_right_iff_subset Finset.union_eq_right
@[simp] lemma right_eq_union : s = t ∪ s ↔ t ⊆ s := by rw [eq_comm, union_eq_right]
#align finset.right_eq_union_iff_subset Finset.right_eq_union
-- Porting note: replaced `⊔` in RHS
theorem union_congr_left (ht : t ⊆ s ∪ u) (hu : u ⊆ s ∪ t) : s ∪ t = s ∪ u :=
sup_congr_left ht hu
#align finset.union_congr_left Finset.union_congr_left
theorem union_congr_right (hs : s ⊆ t ∪ u) (ht : t ⊆ s ∪ u) : s ∪ u = t ∪ u :=
sup_congr_right hs ht
#align finset.union_congr_right Finset.union_congr_right
theorem union_eq_union_iff_left : s ∪ t = s ∪ u ↔ t ⊆ s ∪ u ∧ u ⊆ s ∪ t :=
sup_eq_sup_iff_left
#align finset.union_eq_union_iff_left Finset.union_eq_union_iff_left
theorem union_eq_union_iff_right : s ∪ u = t ∪ u ↔ s ⊆ t ∪ u ∧ t ⊆ s ∪ u :=
sup_eq_sup_iff_right
#align finset.union_eq_union_iff_right Finset.union_eq_union_iff_right
@[simp]
theorem disjoint_union_left : Disjoint (s ∪ t) u ↔ Disjoint s u ∧ Disjoint t u := by
simp only [disjoint_left, mem_union, or_imp, forall_and]
#align finset.disjoint_union_left Finset.disjoint_union_left
@[simp]
theorem disjoint_union_right : Disjoint s (t ∪ u) ↔ Disjoint s t ∧ Disjoint s u := by
simp only [disjoint_right, mem_union, or_imp, forall_and]
#align finset.disjoint_union_right Finset.disjoint_union_right
/-- To prove a relation on pairs of `Finset X`, it suffices to show that it is
* symmetric,
* it holds when one of the `Finset`s is empty,
* it holds for pairs of singletons,
* if it holds for `[a, c]` and for `[b, c]`, then it holds for `[a ∪ b, c]`.
-/
theorem induction_on_union (P : Finset α → Finset α → Prop) (symm : ∀ {a b}, P a b → P b a)
(empty_right : ∀ {a}, P a ∅) (singletons : ∀ {a b}, P {a} {b})
(union_of : ∀ {a b c}, P a c → P b c → P (a ∪ b) c) : ∀ a b, P a b := by
intro a b
refine Finset.induction_on b empty_right fun x s _xs hi => symm ?_
rw [Finset.insert_eq]
apply union_of _ (symm hi)
refine Finset.induction_on a empty_right fun a t _ta hi => symm ?_
rw [Finset.insert_eq]
exact union_of singletons (symm hi)
#align finset.induction_on_union Finset.induction_on_union
/-! #### inter -/
theorem inter_val_nd (s₁ s₂ : Finset α) : (s₁ ∩ s₂).1 = ndinter s₁.1 s₂.1 :=
rfl
#align finset.inter_val_nd Finset.inter_val_nd
@[simp]
theorem inter_val (s₁ s₂ : Finset α) : (s₁ ∩ s₂).1 = s₁.1 ∩ s₂.1 :=
ndinter_eq_inter s₁.2
#align finset.inter_val Finset.inter_val
@[simp]
theorem mem_inter {a : α} {s₁ s₂ : Finset α} : a ∈ s₁ ∩ s₂ ↔ a ∈ s₁ ∧ a ∈ s₂ :=
mem_ndinter
#align finset.mem_inter Finset.mem_inter
theorem mem_of_mem_inter_left {a : α} {s₁ s₂ : Finset α} (h : a ∈ s₁ ∩ s₂) : a ∈ s₁ :=
(mem_inter.1 h).1
#align finset.mem_of_mem_inter_left Finset.mem_of_mem_inter_left
theorem mem_of_mem_inter_right {a : α} {s₁ s₂ : Finset α} (h : a ∈ s₁ ∩ s₂) : a ∈ s₂ :=
(mem_inter.1 h).2
#align finset.mem_of_mem_inter_right Finset.mem_of_mem_inter_right
theorem mem_inter_of_mem {a : α} {s₁ s₂ : Finset α} : a ∈ s₁ → a ∈ s₂ → a ∈ s₁ ∩ s₂ :=
and_imp.1 mem_inter.2
#align finset.mem_inter_of_mem Finset.mem_inter_of_mem
theorem inter_subset_left {s₁ s₂ : Finset α} : s₁ ∩ s₂ ⊆ s₁ := fun _a => mem_of_mem_inter_left
#align finset.inter_subset_left Finset.inter_subset_left
theorem inter_subset_right {s₁ s₂ : Finset α} : s₁ ∩ s₂ ⊆ s₂ := fun _a => mem_of_mem_inter_right
#align finset.inter_subset_right Finset.inter_subset_right
theorem subset_inter {s₁ s₂ u : Finset α} : s₁ ⊆ s₂ → s₁ ⊆ u → s₁ ⊆ s₂ ∩ u := by
simp (config := { contextual := true }) [subset_iff, mem_inter]
#align finset.subset_inter Finset.subset_inter
@[simp, norm_cast]
theorem coe_inter (s₁ s₂ : Finset α) : ↑(s₁ ∩ s₂) = (s₁ ∩ s₂ : Set α) :=
Set.ext fun _ => mem_inter
#align finset.coe_inter Finset.coe_inter
@[simp]
theorem union_inter_cancel_left {s t : Finset α} : (s ∪ t) ∩ s = s := by
rw [← coe_inj, coe_inter, coe_union, Set.union_inter_cancel_left]
#align finset.union_inter_cancel_left Finset.union_inter_cancel_left
@[simp]
theorem union_inter_cancel_right {s t : Finset α} : (s ∪ t) ∩ t = t := by
rw [← coe_inj, coe_inter, coe_union, Set.union_inter_cancel_right]
#align finset.union_inter_cancel_right Finset.union_inter_cancel_right
theorem inter_comm (s₁ s₂ : Finset α) : s₁ ∩ s₂ = s₂ ∩ s₁ :=
ext fun _ => by simp only [mem_inter, and_comm]
#align finset.inter_comm Finset.inter_comm
@[simp]
theorem inter_assoc (s₁ s₂ s₃ : Finset α) : s₁ ∩ s₂ ∩ s₃ = s₁ ∩ (s₂ ∩ s₃) :=
ext fun _ => by simp only [mem_inter, and_assoc]
#align finset.inter_assoc Finset.inter_assoc
theorem inter_left_comm (s₁ s₂ s₃ : Finset α) : s₁ ∩ (s₂ ∩ s₃) = s₂ ∩ (s₁ ∩ s₃) :=
ext fun _ => by simp only [mem_inter, and_left_comm]
#align finset.inter_left_comm Finset.inter_left_comm
theorem inter_right_comm (s₁ s₂ s₃ : Finset α) : s₁ ∩ s₂ ∩ s₃ = s₁ ∩ s₃ ∩ s₂ :=
ext fun _ => by simp only [mem_inter, and_right_comm]
#align finset.inter_right_comm Finset.inter_right_comm
@[simp]
theorem inter_self (s : Finset α) : s ∩ s = s :=
ext fun _ => mem_inter.trans <| and_self_iff
#align finset.inter_self Finset.inter_self
@[simp]
theorem inter_empty (s : Finset α) : s ∩ ∅ = ∅ :=
ext fun _ => mem_inter.trans <| by simp
#align finset.inter_empty Finset.inter_empty
@[simp]
theorem empty_inter (s : Finset α) : ∅ ∩ s = ∅ :=
ext fun _ => mem_inter.trans <| by simp
#align finset.empty_inter Finset.empty_inter
@[simp]
theorem inter_union_self (s t : Finset α) : s ∩ (t ∪ s) = s := by
rw [inter_comm, union_inter_cancel_right]
#align finset.inter_union_self Finset.inter_union_self
@[simp]
theorem insert_inter_of_mem {s₁ s₂ : Finset α} {a : α} (h : a ∈ s₂) :
insert a s₁ ∩ s₂ = insert a (s₁ ∩ s₂) :=
ext fun x => by
have : x = a ∨ x ∈ s₂ ↔ x ∈ s₂ := or_iff_right_of_imp <| by rintro rfl; exact h
simp only [mem_inter, mem_insert, or_and_left, this]
#align finset.insert_inter_of_mem Finset.insert_inter_of_mem
@[simp]
theorem inter_insert_of_mem {s₁ s₂ : Finset α} {a : α} (h : a ∈ s₁) :
s₁ ∩ insert a s₂ = insert a (s₁ ∩ s₂) := by rw [inter_comm, insert_inter_of_mem h, inter_comm]
#align finset.inter_insert_of_mem Finset.inter_insert_of_mem
@[simp]
theorem insert_inter_of_not_mem {s₁ s₂ : Finset α} {a : α} (h : a ∉ s₂) :
insert a s₁ ∩ s₂ = s₁ ∩ s₂ :=
ext fun x => by
have : ¬(x = a ∧ x ∈ s₂) := by rintro ⟨rfl, H⟩; exact h H
simp only [mem_inter, mem_insert, or_and_right, this, false_or_iff]
#align finset.insert_inter_of_not_mem Finset.insert_inter_of_not_mem
@[simp]
theorem inter_insert_of_not_mem {s₁ s₂ : Finset α} {a : α} (h : a ∉ s₁) :
s₁ ∩ insert a s₂ = s₁ ∩ s₂ := by rw [inter_comm, insert_inter_of_not_mem h, inter_comm]
#align finset.inter_insert_of_not_mem Finset.inter_insert_of_not_mem
@[simp]
theorem singleton_inter_of_mem {a : α} {s : Finset α} (H : a ∈ s) : {a} ∩ s = {a} :=
show insert a ∅ ∩ s = insert a ∅ by rw [insert_inter_of_mem H, empty_inter]
#align finset.singleton_inter_of_mem Finset.singleton_inter_of_mem
@[simp]
theorem singleton_inter_of_not_mem {a : α} {s : Finset α} (H : a ∉ s) : {a} ∩ s = ∅ :=
eq_empty_of_forall_not_mem <| by
simp only [mem_inter, mem_singleton]; rintro x ⟨rfl, h⟩; exact H h
#align finset.singleton_inter_of_not_mem Finset.singleton_inter_of_not_mem
@[simp]
theorem inter_singleton_of_mem {a : α} {s : Finset α} (h : a ∈ s) : s ∩ {a} = {a} := by
rw [inter_comm, singleton_inter_of_mem h]
#align finset.inter_singleton_of_mem Finset.inter_singleton_of_mem
@[simp]
theorem inter_singleton_of_not_mem {a : α} {s : Finset α} (h : a ∉ s) : s ∩ {a} = ∅ := by
rw [inter_comm, singleton_inter_of_not_mem h]
#align finset.inter_singleton_of_not_mem Finset.inter_singleton_of_not_mem
@[mono, gcongr]
theorem inter_subset_inter {x y s t : Finset α} (h : x ⊆ y) (h' : s ⊆ t) : x ∩ s ⊆ y ∩ t := by
intro a a_in
rw [Finset.mem_inter] at a_in ⊢
exact ⟨h a_in.1, h' a_in.2⟩
#align finset.inter_subset_inter Finset.inter_subset_inter
@[gcongr]
theorem inter_subset_inter_left (h : t ⊆ u) : s ∩ t ⊆ s ∩ u :=
inter_subset_inter Subset.rfl h
#align finset.inter_subset_inter_left Finset.inter_subset_inter_left
@[gcongr]
theorem inter_subset_inter_right (h : s ⊆ t) : s ∩ u ⊆ t ∩ u :=
inter_subset_inter h Subset.rfl
#align finset.inter_subset_inter_right Finset.inter_subset_inter_right
theorem inter_subset_union : s ∩ t ⊆ s ∪ t :=
le_iff_subset.1 inf_le_sup
#align finset.inter_subset_union Finset.inter_subset_union
instance : DistribLattice (Finset α) :=
{ le_sup_inf := fun a b c => by
simp (config := { contextual := true }) only
[sup_eq_union, inf_eq_inter, le_eq_subset, subset_iff, mem_inter, mem_union, and_imp,
or_imp, true_or_iff, imp_true_iff, true_and_iff, or_true_iff] }
@[simp]
theorem union_left_idem (s t : Finset α) : s ∪ (s ∪ t) = s ∪ t := sup_left_idem _ _
#align finset.union_left_idem Finset.union_left_idem
-- Porting note (#10618): @[simp] can prove this
theorem union_right_idem (s t : Finset α) : s ∪ t ∪ t = s ∪ t := sup_right_idem _ _
#align finset.union_right_idem Finset.union_right_idem
@[simp]
theorem inter_left_idem (s t : Finset α) : s ∩ (s ∩ t) = s ∩ t := inf_left_idem _ _
#align finset.inter_left_idem Finset.inter_left_idem
-- Porting note (#10618): @[simp] can prove this
theorem inter_right_idem (s t : Finset α) : s ∩ t ∩ t = s ∩ t := inf_right_idem _ _
#align finset.inter_right_idem Finset.inter_right_idem
theorem inter_union_distrib_left (s t u : Finset α) : s ∩ (t ∪ u) = s ∩ t ∪ s ∩ u :=
inf_sup_left _ _ _
#align finset.inter_distrib_left Finset.inter_union_distrib_left
theorem union_inter_distrib_right (s t u : Finset α) : (s ∪ t) ∩ u = s ∩ u ∪ t ∩ u :=
inf_sup_right _ _ _
#align finset.inter_distrib_right Finset.union_inter_distrib_right
theorem union_inter_distrib_left (s t u : Finset α) : s ∪ t ∩ u = (s ∪ t) ∩ (s ∪ u) :=
sup_inf_left _ _ _
#align finset.union_distrib_left Finset.union_inter_distrib_left
theorem inter_union_distrib_right (s t u : Finset α) : s ∩ t ∪ u = (s ∪ u) ∩ (t ∪ u) :=
sup_inf_right _ _ _
#align finset.union_distrib_right Finset.inter_union_distrib_right
-- 2024-03-22
@[deprecated] alias inter_distrib_left := inter_union_distrib_left
@[deprecated] alias inter_distrib_right := union_inter_distrib_right
@[deprecated] alias union_distrib_left := union_inter_distrib_left
@[deprecated] alias union_distrib_right := inter_union_distrib_right
theorem union_union_distrib_left (s t u : Finset α) : s ∪ (t ∪ u) = s ∪ t ∪ (s ∪ u) :=
sup_sup_distrib_left _ _ _
#align finset.union_union_distrib_left Finset.union_union_distrib_left
theorem union_union_distrib_right (s t u : Finset α) : s ∪ t ∪ u = s ∪ u ∪ (t ∪ u) :=
sup_sup_distrib_right _ _ _
#align finset.union_union_distrib_right Finset.union_union_distrib_right
theorem inter_inter_distrib_left (s t u : Finset α) : s ∩ (t ∩ u) = s ∩ t ∩ (s ∩ u) :=
inf_inf_distrib_left _ _ _
#align finset.inter_inter_distrib_left Finset.inter_inter_distrib_left
theorem inter_inter_distrib_right (s t u : Finset α) : s ∩ t ∩ u = s ∩ u ∩ (t ∩ u) :=
inf_inf_distrib_right _ _ _
#align finset.inter_inter_distrib_right Finset.inter_inter_distrib_right
theorem union_union_union_comm (s t u v : Finset α) : s ∪ t ∪ (u ∪ v) = s ∪ u ∪ (t ∪ v) :=
sup_sup_sup_comm _ _ _ _
#align finset.union_union_union_comm Finset.union_union_union_comm
theorem inter_inter_inter_comm (s t u v : Finset α) : s ∩ t ∩ (u ∩ v) = s ∩ u ∩ (t ∩ v) :=
inf_inf_inf_comm _ _ _ _
#align finset.inter_inter_inter_comm Finset.inter_inter_inter_comm
lemma union_eq_empty : s ∪ t = ∅ ↔ s = ∅ ∧ t = ∅ := sup_eq_bot_iff
#align finset.union_eq_empty_iff Finset.union_eq_empty
theorem union_subset_iff : s ∪ t ⊆ u ↔ s ⊆ u ∧ t ⊆ u :=
(sup_le_iff : s ⊔ t ≤ u ↔ s ≤ u ∧ t ≤ u)
#align finset.union_subset_iff Finset.union_subset_iff
theorem subset_inter_iff : s ⊆ t ∩ u ↔ s ⊆ t ∧ s ⊆ u :=
(le_inf_iff : s ≤ t ⊓ u ↔ s ≤ t ∧ s ≤ u)
#align finset.subset_inter_iff Finset.subset_inter_iff
@[simp] lemma inter_eq_left : s ∩ t = s ↔ s ⊆ t := inf_eq_left
#align finset.inter_eq_left_iff_subset_iff_subset Finset.inter_eq_left
@[simp] lemma inter_eq_right : t ∩ s = s ↔ s ⊆ t := inf_eq_right
#align finset.inter_eq_right_iff_subset Finset.inter_eq_right
theorem inter_congr_left (ht : s ∩ u ⊆ t) (hu : s ∩ t ⊆ u) : s ∩ t = s ∩ u :=
inf_congr_left ht hu
#align finset.inter_congr_left Finset.inter_congr_left
theorem inter_congr_right (hs : t ∩ u ⊆ s) (ht : s ∩ u ⊆ t) : s ∩ u = t ∩ u :=
inf_congr_right hs ht
#align finset.inter_congr_right Finset.inter_congr_right
theorem inter_eq_inter_iff_left : s ∩ t = s ∩ u ↔ s ∩ u ⊆ t ∧ s ∩ t ⊆ u :=
inf_eq_inf_iff_left
#align finset.inter_eq_inter_iff_left Finset.inter_eq_inter_iff_left
theorem inter_eq_inter_iff_right : s ∩ u = t ∩ u ↔ t ∩ u ⊆ s ∧ s ∩ u ⊆ t :=
inf_eq_inf_iff_right
#align finset.inter_eq_inter_iff_right Finset.inter_eq_inter_iff_right
theorem ite_subset_union (s s' : Finset α) (P : Prop) [Decidable P] : ite P s s' ⊆ s ∪ s' :=
ite_le_sup s s' P
#align finset.ite_subset_union Finset.ite_subset_union
theorem inter_subset_ite (s s' : Finset α) (P : Prop) [Decidable P] : s ∩ s' ⊆ ite P s s' :=
inf_le_ite s s' P
#align finset.inter_subset_ite Finset.inter_subset_ite
theorem not_disjoint_iff_nonempty_inter : ¬Disjoint s t ↔ (s ∩ t).Nonempty :=
not_disjoint_iff.trans <| by simp [Finset.Nonempty]
#align finset.not_disjoint_iff_nonempty_inter Finset.not_disjoint_iff_nonempty_inter
alias ⟨_, Nonempty.not_disjoint⟩ := not_disjoint_iff_nonempty_inter
#align finset.nonempty.not_disjoint Finset.Nonempty.not_disjoint
theorem disjoint_or_nonempty_inter (s t : Finset α) : Disjoint s t ∨ (s ∩ t).Nonempty := by
rw [← not_disjoint_iff_nonempty_inter]
exact em _
#align finset.disjoint_or_nonempty_inter Finset.disjoint_or_nonempty_inter
end Lattice
instance isDirected_le : IsDirected (Finset α) (· ≤ ·) := by classical infer_instance
instance isDirected_subset : IsDirected (Finset α) (· ⊆ ·) := isDirected_le
/-! ### erase -/
section Erase
variable [DecidableEq α] {s t u v : Finset α} {a b : α}
/-- `erase s a` is the set `s - {a}`, that is, the elements of `s` which are
not equal to `a`. -/
def erase (s : Finset α) (a : α) : Finset α :=
⟨_, s.2.erase a⟩
#align finset.erase Finset.erase
@[simp]
theorem erase_val (s : Finset α) (a : α) : (erase s a).1 = s.1.erase a :=
rfl
#align finset.erase_val Finset.erase_val
@[simp]
theorem mem_erase {a b : α} {s : Finset α} : a ∈ erase s b ↔ a ≠ b ∧ a ∈ s :=
s.2.mem_erase_iff
#align finset.mem_erase Finset.mem_erase
theorem not_mem_erase (a : α) (s : Finset α) : a ∉ erase s a :=
s.2.not_mem_erase
#align finset.not_mem_erase Finset.not_mem_erase
-- While this can be solved by `simp`, this lemma is eligible for `dsimp`
@[nolint simpNF, simp]
theorem erase_empty (a : α) : erase ∅ a = ∅ :=
rfl
#align finset.erase_empty Finset.erase_empty
protected lemma Nontrivial.erase_nonempty (hs : s.Nontrivial) : (s.erase a).Nonempty :=
(hs.exists_ne a).imp $ by aesop
@[simp] lemma erase_nonempty (ha : a ∈ s) : (s.erase a).Nonempty ↔ s.Nontrivial := by
simp only [Finset.Nonempty, mem_erase, and_comm (b := _ ∈ _)]
refine ⟨?_, fun hs ↦ hs.exists_ne a⟩
rintro ⟨b, hb, hba⟩
exact ⟨_, hb, _, ha, hba⟩
@[simp]
theorem erase_singleton (a : α) : ({a} : Finset α).erase a = ∅ := by
ext x
simp
#align finset.erase_singleton Finset.erase_singleton
theorem ne_of_mem_erase : b ∈ erase s a → b ≠ a := fun h => (mem_erase.1 h).1
#align finset.ne_of_mem_erase Finset.ne_of_mem_erase
theorem mem_of_mem_erase : b ∈ erase s a → b ∈ s :=
Multiset.mem_of_mem_erase
#align finset.mem_of_mem_erase Finset.mem_of_mem_erase
theorem mem_erase_of_ne_of_mem : a ≠ b → a ∈ s → a ∈ erase s b := by
simp only [mem_erase]; exact And.intro
#align finset.mem_erase_of_ne_of_mem Finset.mem_erase_of_ne_of_mem
/-- An element of `s` that is not an element of `erase s a` must be`a`. -/
theorem eq_of_mem_of_not_mem_erase (hs : b ∈ s) (hsa : b ∉ s.erase a) : b = a := by
rw [mem_erase, not_and] at hsa
exact not_imp_not.mp hsa hs
#align finset.eq_of_mem_of_not_mem_erase Finset.eq_of_mem_of_not_mem_erase
@[simp]
theorem erase_eq_of_not_mem {a : α} {s : Finset α} (h : a ∉ s) : erase s a = s :=
eq_of_veq <| erase_of_not_mem h
#align finset.erase_eq_of_not_mem Finset.erase_eq_of_not_mem
@[simp]
theorem erase_eq_self : s.erase a = s ↔ a ∉ s :=
⟨fun h => h ▸ not_mem_erase _ _, erase_eq_of_not_mem⟩
#align finset.erase_eq_self Finset.erase_eq_self
@[simp]
theorem erase_insert_eq_erase (s : Finset α) (a : α) : (insert a s).erase a = s.erase a :=
ext fun x => by
simp (config := { contextual := true }) only [mem_erase, mem_insert, and_congr_right_iff,
false_or_iff, iff_self_iff, imp_true_iff]
#align finset.erase_insert_eq_erase Finset.erase_insert_eq_erase
theorem erase_insert {a : α} {s : Finset α} (h : a ∉ s) : erase (insert a s) a = s := by
rw [erase_insert_eq_erase, erase_eq_of_not_mem h]
#align finset.erase_insert Finset.erase_insert
theorem erase_insert_of_ne {a b : α} {s : Finset α} (h : a ≠ b) :
erase (insert a s) b = insert a (erase s b) :=
ext fun x => by
have : x ≠ b ∧ x = a ↔ x = a := and_iff_right_of_imp fun hx => hx.symm ▸ h
simp only [mem_erase, mem_insert, and_or_left, this]
#align finset.erase_insert_of_ne Finset.erase_insert_of_ne
theorem erase_cons_of_ne {a b : α} {s : Finset α} (ha : a ∉ s) (hb : a ≠ b) :
erase (cons a s ha) b = cons a (erase s b) fun h => ha <| erase_subset _ _ h := by
simp only [cons_eq_insert, erase_insert_of_ne hb]
#align finset.erase_cons_of_ne Finset.erase_cons_of_ne
@[simp] theorem insert_erase (h : a ∈ s) : insert a (erase s a) = s :=
ext fun x => by
simp only [mem_insert, mem_erase, or_and_left, dec_em, true_and_iff]
apply or_iff_right_of_imp
rintro rfl
exact h
#align finset.insert_erase Finset.insert_erase
lemma erase_eq_iff_eq_insert (hs : a ∈ s) (ht : a ∉ t) : erase s a = t ↔ s = insert a t := by
aesop
lemma insert_erase_invOn :
Set.InvOn (insert a) (fun s ↦ erase s a) {s : Finset α | a ∈ s} {s : Finset α | a ∉ s} :=
⟨fun _s ↦ insert_erase, fun _s ↦ erase_insert⟩
theorem erase_subset_erase (a : α) {s t : Finset α} (h : s ⊆ t) : erase s a ⊆ erase t a :=
val_le_iff.1 <| erase_le_erase _ <| val_le_iff.2 h
#align finset.erase_subset_erase Finset.erase_subset_erase
theorem erase_subset (a : α) (s : Finset α) : erase s a ⊆ s :=
Multiset.erase_subset _ _
#align finset.erase_subset Finset.erase_subset
theorem subset_erase {a : α} {s t : Finset α} : s ⊆ t.erase a ↔ s ⊆ t ∧ a ∉ s :=
⟨fun h => ⟨h.trans (erase_subset _ _), fun ha => not_mem_erase _ _ (h ha)⟩,
fun h _b hb => mem_erase.2 ⟨ne_of_mem_of_not_mem hb h.2, h.1 hb⟩⟩
#align finset.subset_erase Finset.subset_erase
@[simp, norm_cast]
theorem coe_erase (a : α) (s : Finset α) : ↑(erase s a) = (s \ {a} : Set α) :=
Set.ext fun _ => mem_erase.trans <| by rw [and_comm, Set.mem_diff, Set.mem_singleton_iff, mem_coe]
#align finset.coe_erase Finset.coe_erase
theorem erase_ssubset {a : α} {s : Finset α} (h : a ∈ s) : s.erase a ⊂ s :=
calc
s.erase a ⊂ insert a (s.erase a) := ssubset_insert <| not_mem_erase _ _
_ = _ := insert_erase h
#align finset.erase_ssubset Finset.erase_ssubset
theorem ssubset_iff_exists_subset_erase {s t : Finset α} : s ⊂ t ↔ ∃ a ∈ t, s ⊆ t.erase a := by
refine ⟨fun h => ?_, fun ⟨a, ha, h⟩ => ssubset_of_subset_of_ssubset h <| erase_ssubset ha⟩
obtain ⟨a, ht, hs⟩ := not_subset.1 h.2
exact ⟨a, ht, subset_erase.2 ⟨h.1, hs⟩⟩
#align finset.ssubset_iff_exists_subset_erase Finset.ssubset_iff_exists_subset_erase
theorem erase_ssubset_insert (s : Finset α) (a : α) : s.erase a ⊂ insert a s :=
ssubset_iff_exists_subset_erase.2
⟨a, mem_insert_self _ _, erase_subset_erase _ <| subset_insert _ _⟩
#align finset.erase_ssubset_insert Finset.erase_ssubset_insert
theorem erase_ne_self : s.erase a ≠ s ↔ a ∈ s :=
erase_eq_self.not_left
#align finset.erase_ne_self Finset.erase_ne_self
theorem erase_cons {s : Finset α} {a : α} (h : a ∉ s) : (s.cons a h).erase a = s := by
rw [cons_eq_insert, erase_insert_eq_erase, erase_eq_of_not_mem h]
#align finset.erase_cons Finset.erase_cons
theorem erase_idem {a : α} {s : Finset α} : erase (erase s a) a = erase s a := by simp
#align finset.erase_idem Finset.erase_idem
theorem erase_right_comm {a b : α} {s : Finset α} : erase (erase s a) b = erase (erase s b) a := by
ext x
simp only [mem_erase, ← and_assoc]
rw [@and_comm (x ≠ a)]
#align finset.erase_right_comm Finset.erase_right_comm
theorem subset_insert_iff {a : α} {s t : Finset α} : s ⊆ insert a t ↔ erase s a ⊆ t := by
simp only [subset_iff, or_iff_not_imp_left, mem_erase, mem_insert, and_imp]
exact forall_congr' fun x => forall_swap
#align finset.subset_insert_iff Finset.subset_insert_iff
theorem erase_insert_subset (a : α) (s : Finset α) : erase (insert a s) a ⊆ s :=
subset_insert_iff.1 <| Subset.rfl
#align finset.erase_insert_subset Finset.erase_insert_subset
theorem insert_erase_subset (a : α) (s : Finset α) : s ⊆ insert a (erase s a) :=
subset_insert_iff.2 <| Subset.rfl
#align finset.insert_erase_subset Finset.insert_erase_subset
theorem subset_insert_iff_of_not_mem (h : a ∉ s) : s ⊆ insert a t ↔ s ⊆ t := by
rw [subset_insert_iff, erase_eq_of_not_mem h]
#align finset.subset_insert_iff_of_not_mem Finset.subset_insert_iff_of_not_mem
theorem erase_subset_iff_of_mem (h : a ∈ t) : s.erase a ⊆ t ↔ s ⊆ t := by
rw [← subset_insert_iff, insert_eq_of_mem h]
#align finset.erase_subset_iff_of_mem Finset.erase_subset_iff_of_mem
theorem erase_inj {x y : α} (s : Finset α) (hx : x ∈ s) : s.erase x = s.erase y ↔ x = y := by
refine ⟨fun h => eq_of_mem_of_not_mem_erase hx ?_, congr_arg _⟩
rw [← h]
simp
#align finset.erase_inj Finset.erase_inj
theorem erase_injOn (s : Finset α) : Set.InjOn s.erase s := fun _ _ _ _ => (erase_inj s ‹_›).mp
#align finset.erase_inj_on Finset.erase_injOn
theorem erase_injOn' (a : α) : { s : Finset α | a ∈ s }.InjOn fun s => erase s a :=
fun s hs t ht (h : s.erase a = _) => by rw [← insert_erase hs, ← insert_erase ht, h]
#align finset.erase_inj_on' Finset.erase_injOn'
end Erase
lemma Nontrivial.exists_cons_eq {s : Finset α} (hs : s.Nontrivial) :
∃ t a ha b hb hab, (cons b t hb).cons a (mem_cons.not.2 <| not_or_intro hab ha) = s := by
classical
obtain ⟨a, ha, b, hb, hab⟩ := hs
have : b ∈ s.erase a := mem_erase.2 ⟨hab.symm, hb⟩
refine ⟨(s.erase a).erase b, a, ?_, b, ?_, ?_, ?_⟩ <;>
simp [insert_erase this, insert_erase ha, *]
/-! ### sdiff -/
section Sdiff
variable [DecidableEq α] {s t u v : Finset α} {a b : α}
/-- `s \ t` is the set consisting of the elements of `s` that are not in `t`. -/
instance : SDiff (Finset α) :=
⟨fun s₁ s₂ => ⟨s₁.1 - s₂.1, nodup_of_le tsub_le_self s₁.2⟩⟩
@[simp]
theorem sdiff_val (s₁ s₂ : Finset α) : (s₁ \ s₂).val = s₁.val - s₂.val :=
rfl
#align finset.sdiff_val Finset.sdiff_val
@[simp]
theorem mem_sdiff : a ∈ s \ t ↔ a ∈ s ∧ a ∉ t :=
mem_sub_of_nodup s.2
#align finset.mem_sdiff Finset.mem_sdiff
@[simp]
theorem inter_sdiff_self (s₁ s₂ : Finset α) : s₁ ∩ (s₂ \ s₁) = ∅ :=
eq_empty_of_forall_not_mem <| by
simp only [mem_inter, mem_sdiff]; rintro x ⟨h, _, hn⟩; exact hn h
#align finset.inter_sdiff_self Finset.inter_sdiff_self
instance : GeneralizedBooleanAlgebra (Finset α) :=
{ sup_inf_sdiff := fun x y => by
simp only [ext_iff, mem_union, mem_sdiff, inf_eq_inter, sup_eq_union, mem_inter,
← and_or_left, em, and_true, implies_true]
inf_inf_sdiff := fun x y => by
simp only [ext_iff, inter_sdiff_self, inter_empty, inter_assoc, false_iff_iff, inf_eq_inter,
not_mem_empty, bot_eq_empty, not_false_iff, implies_true] }
theorem not_mem_sdiff_of_mem_right (h : a ∈ t) : a ∉ s \ t := by
simp only [mem_sdiff, h, not_true, not_false_iff, and_false_iff]
#align finset.not_mem_sdiff_of_mem_right Finset.not_mem_sdiff_of_mem_right
theorem not_mem_sdiff_of_not_mem_left (h : a ∉ s) : a ∉ s \ t := by simp [h]
#align finset.not_mem_sdiff_of_not_mem_left Finset.not_mem_sdiff_of_not_mem_left
theorem union_sdiff_of_subset (h : s ⊆ t) : s ∪ t \ s = t :=
sup_sdiff_cancel_right h
#align finset.union_sdiff_of_subset Finset.union_sdiff_of_subset
theorem sdiff_union_of_subset {s₁ s₂ : Finset α} (h : s₁ ⊆ s₂) : s₂ \ s₁ ∪ s₁ = s₂ :=
(union_comm _ _).trans (union_sdiff_of_subset h)
#align finset.sdiff_union_of_subset Finset.sdiff_union_of_subset
lemma inter_sdiff_assoc (s t u : Finset α) : (s ∩ t) \ u = s ∩ (t \ u) := by
ext x; simp [and_assoc]
@[deprecated inter_sdiff_assoc (since := "2024-05-01")]
theorem inter_sdiff (s t u : Finset α) : s ∩ (t \ u) = (s ∩ t) \ u := (inter_sdiff_assoc _ _ _).symm
#align finset.inter_sdiff Finset.inter_sdiff
@[simp]
theorem sdiff_inter_self (s₁ s₂ : Finset α) : s₂ \ s₁ ∩ s₁ = ∅ :=
inf_sdiff_self_left
#align finset.sdiff_inter_self Finset.sdiff_inter_self
-- Porting note (#10618): @[simp] can prove this
protected theorem sdiff_self (s₁ : Finset α) : s₁ \ s₁ = ∅ :=
_root_.sdiff_self
#align finset.sdiff_self Finset.sdiff_self
theorem sdiff_inter_distrib_right (s t u : Finset α) : s \ (t ∩ u) = s \ t ∪ s \ u :=
sdiff_inf
#align finset.sdiff_inter_distrib_right Finset.sdiff_inter_distrib_right
@[simp]
theorem sdiff_inter_self_left (s t : Finset α) : s \ (s ∩ t) = s \ t :=
sdiff_inf_self_left _ _
#align finset.sdiff_inter_self_left Finset.sdiff_inter_self_left
@[simp]
theorem sdiff_inter_self_right (s t : Finset α) : s \ (t ∩ s) = s \ t :=
sdiff_inf_self_right _ _
#align finset.sdiff_inter_self_right Finset.sdiff_inter_self_right
@[simp]
theorem sdiff_empty : s \ ∅ = s :=
sdiff_bot
#align finset.sdiff_empty Finset.sdiff_empty
@[mono, gcongr]
theorem sdiff_subset_sdiff (hst : s ⊆ t) (hvu : v ⊆ u) : s \ u ⊆ t \ v :=
sdiff_le_sdiff hst hvu
#align finset.sdiff_subset_sdiff Finset.sdiff_subset_sdiff
@[simp, norm_cast]
theorem coe_sdiff (s₁ s₂ : Finset α) : ↑(s₁ \ s₂) = (s₁ \ s₂ : Set α) :=
Set.ext fun _ => mem_sdiff
#align finset.coe_sdiff Finset.coe_sdiff
@[simp]
theorem union_sdiff_self_eq_union : s ∪ t \ s = s ∪ t :=
sup_sdiff_self_right _ _
#align finset.union_sdiff_self_eq_union Finset.union_sdiff_self_eq_union
@[simp]
theorem sdiff_union_self_eq_union : s \ t ∪ t = s ∪ t :=
sup_sdiff_self_left _ _
#align finset.sdiff_union_self_eq_union Finset.sdiff_union_self_eq_union
theorem union_sdiff_left (s t : Finset α) : (s ∪ t) \ s = t \ s :=
sup_sdiff_left_self
#align finset.union_sdiff_left Finset.union_sdiff_left
theorem union_sdiff_right (s t : Finset α) : (s ∪ t) \ t = s \ t :=
sup_sdiff_right_self
#align finset.union_sdiff_right Finset.union_sdiff_right
theorem union_sdiff_cancel_left (h : Disjoint s t) : (s ∪ t) \ s = t :=
h.sup_sdiff_cancel_left
#align finset.union_sdiff_cancel_left Finset.union_sdiff_cancel_left
theorem union_sdiff_cancel_right (h : Disjoint s t) : (s ∪ t) \ t = s :=
h.sup_sdiff_cancel_right
#align finset.union_sdiff_cancel_right Finset.union_sdiff_cancel_right
theorem union_sdiff_symm : s ∪ t \ s = t ∪ s \ t := by simp [union_comm]
#align finset.union_sdiff_symm Finset.union_sdiff_symm
theorem sdiff_union_inter (s t : Finset α) : s \ t ∪ s ∩ t = s :=
sup_sdiff_inf _ _
#align finset.sdiff_union_inter Finset.sdiff_union_inter
-- Porting note (#10618): @[simp] can prove this
theorem sdiff_idem (s t : Finset α) : (s \ t) \ t = s \ t :=
_root_.sdiff_idem
#align finset.sdiff_idem Finset.sdiff_idem
theorem subset_sdiff : s ⊆ t \ u ↔ s ⊆ t ∧ Disjoint s u :=
le_iff_subset.symm.trans le_sdiff
#align finset.subset_sdiff Finset.subset_sdiff
@[simp]
theorem sdiff_eq_empty_iff_subset : s \ t = ∅ ↔ s ⊆ t :=
sdiff_eq_bot_iff
#align finset.sdiff_eq_empty_iff_subset Finset.sdiff_eq_empty_iff_subset
theorem sdiff_nonempty : (s \ t).Nonempty ↔ ¬s ⊆ t :=
nonempty_iff_ne_empty.trans sdiff_eq_empty_iff_subset.not
#align finset.sdiff_nonempty Finset.sdiff_nonempty
@[simp]
theorem empty_sdiff (s : Finset α) : ∅ \ s = ∅ :=
bot_sdiff
#align finset.empty_sdiff Finset.empty_sdiff
theorem insert_sdiff_of_not_mem (s : Finset α) {t : Finset α} {x : α} (h : x ∉ t) :
insert x s \ t = insert x (s \ t) := by
rw [← coe_inj, coe_insert, coe_sdiff, coe_sdiff, coe_insert]
exact Set.insert_diff_of_not_mem _ h
#align finset.insert_sdiff_of_not_mem Finset.insert_sdiff_of_not_mem
theorem insert_sdiff_of_mem (s : Finset α) {x : α} (h : x ∈ t) : insert x s \ t = s \ t := by
rw [← coe_inj, coe_sdiff, coe_sdiff, coe_insert]
exact Set.insert_diff_of_mem _ h
#align finset.insert_sdiff_of_mem Finset.insert_sdiff_of_mem
@[simp] lemma insert_sdiff_cancel (ha : a ∉ s) : insert a s \ s = {a} := by
rw [insert_sdiff_of_not_mem _ ha, Finset.sdiff_self, insert_emptyc_eq]
@[simp]
theorem insert_sdiff_insert (s t : Finset α) (x : α) : insert x s \ insert x t = s \ insert x t :=
insert_sdiff_of_mem _ (mem_insert_self _ _)
#align finset.insert_sdiff_insert Finset.insert_sdiff_insert
lemma insert_sdiff_insert' (hab : a ≠ b) (ha : a ∉ s) : insert a s \ insert b s = {a} := by
ext; aesop
lemma erase_sdiff_erase (hab : a ≠ b) (hb : b ∈ s) : s.erase a \ s.erase b = {b} := by
ext; aesop
lemma cons_sdiff_cons (hab : a ≠ b) (ha hb) : s.cons a ha \ s.cons b hb = {a} := by
rw [cons_eq_insert, cons_eq_insert, insert_sdiff_insert' hab ha]
| Mathlib/Data/Finset/Basic.lean | 2,266 | 2,269 | theorem sdiff_insert_of_not_mem {x : α} (h : x ∉ s) (t : Finset α) : s \ insert x t = s \ t := by |
refine Subset.antisymm (sdiff_subset_sdiff (Subset.refl _) (subset_insert _ _)) fun y hy => ?_
simp only [mem_sdiff, mem_insert, not_or] at hy ⊢
exact ⟨hy.1, fun hxy => h <| hxy ▸ hy.1, hy.2⟩
|
/-
Copyright (c) 2022 Floris van Doorn. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Floris van Doorn
-/
import Mathlib.Analysis.Calculus.BumpFunction.Basic
import Mathlib.MeasureTheory.Integral.SetIntegral
import Mathlib.MeasureTheory.Measure.Lebesgue.EqHaar
#align_import analysis.calculus.bump_function_inner from "leanprover-community/mathlib"@"3bce8d800a6f2b8f63fe1e588fd76a9ff4adcebe"
/-!
# Normed bump function
In this file we define `ContDiffBump.normed f μ` to be the bump function `f` normalized so that
`∫ x, f.normed μ x ∂μ = 1` and prove some properties of this function.
-/
noncomputable section
open Function Filter Set Metric MeasureTheory FiniteDimensional Measure
open scoped Topology
namespace ContDiffBump
variable {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E] [HasContDiffBump E]
[MeasurableSpace E] {c : E} (f : ContDiffBump c) {x : E} {n : ℕ∞} {μ : Measure E}
/-- A bump function normed so that `∫ x, f.normed μ x ∂μ = 1`. -/
protected def normed (μ : Measure E) : E → ℝ := fun x => f x / ∫ x, f x ∂μ
#align cont_diff_bump.normed ContDiffBump.normed
theorem normed_def {μ : Measure E} (x : E) : f.normed μ x = f x / ∫ x, f x ∂μ :=
rfl
#align cont_diff_bump.normed_def ContDiffBump.normed_def
theorem nonneg_normed (x : E) : 0 ≤ f.normed μ x :=
div_nonneg f.nonneg <| integral_nonneg f.nonneg'
#align cont_diff_bump.nonneg_normed ContDiffBump.nonneg_normed
theorem contDiff_normed {n : ℕ∞} : ContDiff ℝ n (f.normed μ) :=
f.contDiff.div_const _
#align cont_diff_bump.cont_diff_normed ContDiffBump.contDiff_normed
theorem continuous_normed : Continuous (f.normed μ) :=
f.continuous.div_const _
#align cont_diff_bump.continuous_normed ContDiffBump.continuous_normed
theorem normed_sub (x : E) : f.normed μ (c - x) = f.normed μ (c + x) := by
simp_rw [f.normed_def, f.sub]
#align cont_diff_bump.normed_sub ContDiffBump.normed_sub
theorem normed_neg (f : ContDiffBump (0 : E)) (x : E) : f.normed μ (-x) = f.normed μ x := by
simp_rw [f.normed_def, f.neg]
#align cont_diff_bump.normed_neg ContDiffBump.normed_neg
variable [BorelSpace E] [FiniteDimensional ℝ E] [IsLocallyFiniteMeasure μ]
protected theorem integrable : Integrable f μ :=
f.continuous.integrable_of_hasCompactSupport f.hasCompactSupport
#align cont_diff_bump.integrable ContDiffBump.integrable
protected theorem integrable_normed : Integrable (f.normed μ) μ :=
f.integrable.div_const _
#align cont_diff_bump.integrable_normed ContDiffBump.integrable_normed
variable [μ.IsOpenPosMeasure]
theorem integral_pos : 0 < ∫ x, f x ∂μ := by
refine (integral_pos_iff_support_of_nonneg f.nonneg' f.integrable).mpr ?_
rw [f.support_eq]
exact measure_ball_pos μ c f.rOut_pos
#align cont_diff_bump.integral_pos ContDiffBump.integral_pos
theorem integral_normed : ∫ x, f.normed μ x ∂μ = 1 := by
simp_rw [ContDiffBump.normed, div_eq_mul_inv, mul_comm (f _), ← smul_eq_mul, integral_smul]
exact inv_mul_cancel f.integral_pos.ne'
#align cont_diff_bump.integral_normed ContDiffBump.integral_normed
theorem support_normed_eq : Function.support (f.normed μ) = Metric.ball c f.rOut := by
unfold ContDiffBump.normed
rw [support_div, f.support_eq, support_const f.integral_pos.ne', inter_univ]
#align cont_diff_bump.support_normed_eq ContDiffBump.support_normed_eq
| Mathlib/Analysis/Calculus/BumpFunction/Normed.lean | 85 | 86 | theorem tsupport_normed_eq : tsupport (f.normed μ) = Metric.closedBall c f.rOut := by |
rw [tsupport, f.support_normed_eq, closure_ball _ f.rOut_pos.ne']
|
/-
Copyright (c) 2019 Zhouhang Zhou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Zhouhang Zhou, Sébastien Gouëzel, Frédéric Dupuis
-/
import Mathlib.Algebra.DirectSum.Module
import Mathlib.Analysis.Complex.Basic
import Mathlib.Analysis.Convex.Uniform
import Mathlib.Analysis.NormedSpace.Completion
import Mathlib.Analysis.NormedSpace.BoundedLinearMaps
#align_import analysis.inner_product_space.basic from "leanprover-community/mathlib"@"3f655f5297b030a87d641ad4e825af8d9679eb0b"
/-!
# Inner product space
This file defines inner product spaces and proves the basic properties. We do not formally
define Hilbert spaces, but they can be obtained using the set of assumptions
`[NormedAddCommGroup E] [InnerProductSpace 𝕜 E] [CompleteSpace E]`.
An inner product space is a vector space endowed with an inner product. It generalizes the notion of
dot product in `ℝ^n` and provides the means of defining the length of a vector and the angle between
two vectors. In particular vectors `x` and `y` are orthogonal if their inner product equals zero.
We define both the real and complex cases at the same time using the `RCLike` typeclass.
This file proves general results on inner product spaces. For the specific construction of an inner
product structure on `n → 𝕜` for `𝕜 = ℝ` or `ℂ`, see `EuclideanSpace` in
`Analysis.InnerProductSpace.PiL2`.
## Main results
- We define the class `InnerProductSpace 𝕜 E` extending `NormedSpace 𝕜 E` with a number of basic
properties, most notably the Cauchy-Schwarz inequality. Here `𝕜` is understood to be either `ℝ`
or `ℂ`, through the `RCLike` typeclass.
- We show that the inner product is continuous, `continuous_inner`, and bundle it as the
continuous sesquilinear map `innerSL` (see also `innerₛₗ` for the non-continuous version).
- We define `Orthonormal`, a predicate on a function `v : ι → E`, and prove the existence of a
maximal orthonormal set, `exists_maximal_orthonormal`. Bessel's inequality,
`Orthonormal.tsum_inner_products_le`, states that given an orthonormal set `v` and a vector `x`,
the sum of the norm-squares of the inner products `⟪v i, x⟫` is no more than the norm-square of
`x`. For the existence of orthonormal bases, Hilbert bases, etc., see the file
`Analysis.InnerProductSpace.projection`.
## Notation
We globally denote the real and complex inner products by `⟪·, ·⟫_ℝ` and `⟪·, ·⟫_ℂ` respectively.
We also provide two notation namespaces: `RealInnerProductSpace`, `ComplexInnerProductSpace`,
which respectively introduce the plain notation `⟪·, ·⟫` for the real and complex inner product.
## Implementation notes
We choose the convention that inner products are conjugate linear in the first argument and linear
in the second.
## Tags
inner product space, Hilbert space, norm
## References
* [Clément & Martin, *The Lax-Milgram Theorem. A detailed proof to be formalized in Coq*]
* [Clément & Martin, *A Coq formal proof of the Lax–Milgram theorem*]
The Coq code is available at the following address: <http://www.lri.fr/~sboldo/elfic/index.html>
-/
noncomputable section
open RCLike Real Filter
open Topology ComplexConjugate
open LinearMap (BilinForm)
variable {𝕜 E F : Type*} [RCLike 𝕜]
/-- Syntactic typeclass for types endowed with an inner product -/
class Inner (𝕜 E : Type*) where
/-- The inner product function. -/
inner : E → E → 𝕜
#align has_inner Inner
export Inner (inner)
/-- The inner product with values in `𝕜`. -/
notation3:max "⟪" x ", " y "⟫_" 𝕜:max => @inner 𝕜 _ _ x y
section Notations
/-- The inner product with values in `ℝ`. -/
scoped[RealInnerProductSpace] notation "⟪" x ", " y "⟫" => @inner ℝ _ _ x y
/-- The inner product with values in `ℂ`. -/
scoped[ComplexInnerProductSpace] notation "⟪" x ", " y "⟫" => @inner ℂ _ _ x y
end Notations
/-- An inner product space is a vector space with an additional operation called inner product.
The norm could be derived from the inner product, instead we require the existence of a norm and
the fact that `‖x‖^2 = re ⟪x, x⟫` to be able to put instances on `𝕂` or product
spaces.
To construct a norm from an inner product, see `InnerProductSpace.ofCore`.
-/
class InnerProductSpace (𝕜 : Type*) (E : Type*) [RCLike 𝕜] [NormedAddCommGroup E] extends
NormedSpace 𝕜 E, Inner 𝕜 E where
/-- The inner product induces the norm. -/
norm_sq_eq_inner : ∀ x : E, ‖x‖ ^ 2 = re (inner x x)
/-- The inner product is *hermitian*, taking the `conj` swaps the arguments. -/
conj_symm : ∀ x y, conj (inner y x) = inner x y
/-- The inner product is additive in the first coordinate. -/
add_left : ∀ x y z, inner (x + y) z = inner x z + inner y z
/-- The inner product is conjugate linear in the first coordinate. -/
smul_left : ∀ x y r, inner (r • x) y = conj r * inner x y
#align inner_product_space InnerProductSpace
/-!
### Constructing a normed space structure from an inner product
In the definition of an inner product space, we require the existence of a norm, which is equal
(but maybe not defeq) to the square root of the scalar product. This makes it possible to put
an inner product space structure on spaces with a preexisting norm (for instance `ℝ`), with good
properties. However, sometimes, one would like to define the norm starting only from a well-behaved
scalar product. This is what we implement in this paragraph, starting from a structure
`InnerProductSpace.Core` stating that we have a nice scalar product.
Our goal here is not to develop a whole theory with all the supporting API, as this will be done
below for `InnerProductSpace`. Instead, we implement the bare minimum to go as directly as
possible to the construction of the norm and the proof of the triangular inequality.
Warning: Do not use this `Core` structure if the space you are interested in already has a norm
instance defined on it, otherwise this will create a second non-defeq norm instance!
-/
/-- A structure requiring that a scalar product is positive definite and symmetric, from which one
can construct an `InnerProductSpace` instance in `InnerProductSpace.ofCore`. -/
-- @[nolint HasNonemptyInstance] porting note: I don't think we have this linter anymore
structure InnerProductSpace.Core (𝕜 : Type*) (F : Type*) [RCLike 𝕜] [AddCommGroup F]
[Module 𝕜 F] extends Inner 𝕜 F where
/-- The inner product is *hermitian*, taking the `conj` swaps the arguments. -/
conj_symm : ∀ x y, conj (inner y x) = inner x y
/-- The inner product is positive (semi)definite. -/
nonneg_re : ∀ x, 0 ≤ re (inner x x)
/-- The inner product is positive definite. -/
definite : ∀ x, inner x x = 0 → x = 0
/-- The inner product is additive in the first coordinate. -/
add_left : ∀ x y z, inner (x + y) z = inner x z + inner y z
/-- The inner product is conjugate linear in the first coordinate. -/
smul_left : ∀ x y r, inner (r • x) y = conj r * inner x y
#align inner_product_space.core InnerProductSpace.Core
/- We set `InnerProductSpace.Core` to be a class as we will use it as such in the construction
of the normed space structure that it produces. However, all the instances we will use will be
local to this proof. -/
attribute [class] InnerProductSpace.Core
/-- Define `InnerProductSpace.Core` from `InnerProductSpace`. Defined to reuse lemmas about
`InnerProductSpace.Core` for `InnerProductSpace`s. Note that the `Norm` instance provided by
`InnerProductSpace.Core.norm` is propositionally but not definitionally equal to the original
norm. -/
def InnerProductSpace.toCore [NormedAddCommGroup E] [c : InnerProductSpace 𝕜 E] :
InnerProductSpace.Core 𝕜 E :=
{ c with
nonneg_re := fun x => by
rw [← InnerProductSpace.norm_sq_eq_inner]
apply sq_nonneg
definite := fun x hx =>
norm_eq_zero.1 <| pow_eq_zero (n := 2) <| by
rw [InnerProductSpace.norm_sq_eq_inner (𝕜 := 𝕜) x, hx, map_zero] }
#align inner_product_space.to_core InnerProductSpace.toCore
namespace InnerProductSpace.Core
variable [AddCommGroup F] [Module 𝕜 F] [c : InnerProductSpace.Core 𝕜 F]
local notation "⟪" x ", " y "⟫" => @inner 𝕜 F _ x y
local notation "normSqK" => @RCLike.normSq 𝕜 _
local notation "reK" => @RCLike.re 𝕜 _
local notation "ext_iff" => @RCLike.ext_iff 𝕜 _
local postfix:90 "†" => starRingEnd _
/-- Inner product defined by the `InnerProductSpace.Core` structure. We can't reuse
`InnerProductSpace.Core.toInner` because it takes `InnerProductSpace.Core` as an explicit
argument. -/
def toInner' : Inner 𝕜 F :=
c.toInner
#align inner_product_space.core.to_has_inner' InnerProductSpace.Core.toInner'
attribute [local instance] toInner'
/-- The norm squared function for `InnerProductSpace.Core` structure. -/
def normSq (x : F) :=
reK ⟪x, x⟫
#align inner_product_space.core.norm_sq InnerProductSpace.Core.normSq
local notation "normSqF" => @normSq 𝕜 F _ _ _ _
theorem inner_conj_symm (x y : F) : ⟪y, x⟫† = ⟪x, y⟫ :=
c.conj_symm x y
#align inner_product_space.core.inner_conj_symm InnerProductSpace.Core.inner_conj_symm
theorem inner_self_nonneg {x : F} : 0 ≤ re ⟪x, x⟫ :=
c.nonneg_re _
#align inner_product_space.core.inner_self_nonneg InnerProductSpace.Core.inner_self_nonneg
theorem inner_self_im (x : F) : im ⟪x, x⟫ = 0 := by
rw [← @ofReal_inj 𝕜, im_eq_conj_sub]
simp [inner_conj_symm]
#align inner_product_space.core.inner_self_im InnerProductSpace.Core.inner_self_im
theorem inner_add_left (x y z : F) : ⟪x + y, z⟫ = ⟪x, z⟫ + ⟪y, z⟫ :=
c.add_left _ _ _
#align inner_product_space.core.inner_add_left InnerProductSpace.Core.inner_add_left
theorem inner_add_right (x y z : F) : ⟪x, y + z⟫ = ⟪x, y⟫ + ⟪x, z⟫ := by
rw [← inner_conj_symm, inner_add_left, RingHom.map_add]; simp only [inner_conj_symm]
#align inner_product_space.core.inner_add_right InnerProductSpace.Core.inner_add_right
theorem ofReal_normSq_eq_inner_self (x : F) : (normSqF x : 𝕜) = ⟪x, x⟫ := by
rw [ext_iff]
exact ⟨by simp only [ofReal_re]; rfl, by simp only [inner_self_im, ofReal_im]⟩
#align inner_product_space.core.coe_norm_sq_eq_inner_self InnerProductSpace.Core.ofReal_normSq_eq_inner_self
theorem inner_re_symm (x y : F) : re ⟪x, y⟫ = re ⟪y, x⟫ := by rw [← inner_conj_symm, conj_re]
#align inner_product_space.core.inner_re_symm InnerProductSpace.Core.inner_re_symm
theorem inner_im_symm (x y : F) : im ⟪x, y⟫ = -im ⟪y, x⟫ := by rw [← inner_conj_symm, conj_im]
#align inner_product_space.core.inner_im_symm InnerProductSpace.Core.inner_im_symm
theorem inner_smul_left (x y : F) {r : 𝕜} : ⟪r • x, y⟫ = r† * ⟪x, y⟫ :=
c.smul_left _ _ _
#align inner_product_space.core.inner_smul_left InnerProductSpace.Core.inner_smul_left
theorem inner_smul_right (x y : F) {r : 𝕜} : ⟪x, r • y⟫ = r * ⟪x, y⟫ := by
rw [← inner_conj_symm, inner_smul_left];
simp only [conj_conj, inner_conj_symm, RingHom.map_mul]
#align inner_product_space.core.inner_smul_right InnerProductSpace.Core.inner_smul_right
theorem inner_zero_left (x : F) : ⟪0, x⟫ = 0 := by
rw [← zero_smul 𝕜 (0 : F), inner_smul_left];
simp only [zero_mul, RingHom.map_zero]
#align inner_product_space.core.inner_zero_left InnerProductSpace.Core.inner_zero_left
theorem inner_zero_right (x : F) : ⟪x, 0⟫ = 0 := by
rw [← inner_conj_symm, inner_zero_left]; simp only [RingHom.map_zero]
#align inner_product_space.core.inner_zero_right InnerProductSpace.Core.inner_zero_right
theorem inner_self_eq_zero {x : F} : ⟪x, x⟫ = 0 ↔ x = 0 :=
⟨c.definite _, by
rintro rfl
exact inner_zero_left _⟩
#align inner_product_space.core.inner_self_eq_zero InnerProductSpace.Core.inner_self_eq_zero
theorem normSq_eq_zero {x : F} : normSqF x = 0 ↔ x = 0 :=
Iff.trans
(by simp only [normSq, ext_iff, map_zero, inner_self_im, eq_self_iff_true, and_true_iff])
(@inner_self_eq_zero 𝕜 _ _ _ _ _ x)
#align inner_product_space.core.norm_sq_eq_zero InnerProductSpace.Core.normSq_eq_zero
theorem inner_self_ne_zero {x : F} : ⟪x, x⟫ ≠ 0 ↔ x ≠ 0 :=
inner_self_eq_zero.not
#align inner_product_space.core.inner_self_ne_zero InnerProductSpace.Core.inner_self_ne_zero
theorem inner_self_ofReal_re (x : F) : (re ⟪x, x⟫ : 𝕜) = ⟪x, x⟫ := by
norm_num [ext_iff, inner_self_im]
set_option linter.uppercaseLean3 false in
#align inner_product_space.core.inner_self_re_to_K InnerProductSpace.Core.inner_self_ofReal_re
theorem norm_inner_symm (x y : F) : ‖⟪x, y⟫‖ = ‖⟪y, x⟫‖ := by rw [← inner_conj_symm, norm_conj]
#align inner_product_space.core.norm_inner_symm InnerProductSpace.Core.norm_inner_symm
theorem inner_neg_left (x y : F) : ⟪-x, y⟫ = -⟪x, y⟫ := by
rw [← neg_one_smul 𝕜 x, inner_smul_left]
simp
#align inner_product_space.core.inner_neg_left InnerProductSpace.Core.inner_neg_left
theorem inner_neg_right (x y : F) : ⟪x, -y⟫ = -⟪x, y⟫ := by
rw [← inner_conj_symm, inner_neg_left]; simp only [RingHom.map_neg, inner_conj_symm]
#align inner_product_space.core.inner_neg_right InnerProductSpace.Core.inner_neg_right
theorem inner_sub_left (x y z : F) : ⟪x - y, z⟫ = ⟪x, z⟫ - ⟪y, z⟫ := by
simp [sub_eq_add_neg, inner_add_left, inner_neg_left]
#align inner_product_space.core.inner_sub_left InnerProductSpace.Core.inner_sub_left
theorem inner_sub_right (x y z : F) : ⟪x, y - z⟫ = ⟪x, y⟫ - ⟪x, z⟫ := by
simp [sub_eq_add_neg, inner_add_right, inner_neg_right]
#align inner_product_space.core.inner_sub_right InnerProductSpace.Core.inner_sub_right
theorem inner_mul_symm_re_eq_norm (x y : F) : re (⟪x, y⟫ * ⟪y, x⟫) = ‖⟪x, y⟫ * ⟪y, x⟫‖ := by
rw [← inner_conj_symm, mul_comm]
exact re_eq_norm_of_mul_conj (inner y x)
#align inner_product_space.core.inner_mul_symm_re_eq_norm InnerProductSpace.Core.inner_mul_symm_re_eq_norm
/-- Expand `inner (x + y) (x + y)` -/
theorem inner_add_add_self (x y : F) : ⟪x + y, x + y⟫ = ⟪x, x⟫ + ⟪x, y⟫ + ⟪y, x⟫ + ⟪y, y⟫ := by
simp only [inner_add_left, inner_add_right]; ring
#align inner_product_space.core.inner_add_add_self InnerProductSpace.Core.inner_add_add_self
-- Expand `inner (x - y) (x - y)`
theorem inner_sub_sub_self (x y : F) : ⟪x - y, x - y⟫ = ⟪x, x⟫ - ⟪x, y⟫ - ⟪y, x⟫ + ⟪y, y⟫ := by
simp only [inner_sub_left, inner_sub_right]; ring
#align inner_product_space.core.inner_sub_sub_self InnerProductSpace.Core.inner_sub_sub_self
/-- An auxiliary equality useful to prove the **Cauchy–Schwarz inequality**: the square of the norm
of `⟪x, y⟫ • x - ⟪x, x⟫ • y` is equal to `‖x‖ ^ 2 * (‖x‖ ^ 2 * ‖y‖ ^ 2 - ‖⟪x, y⟫‖ ^ 2)`. We use
`InnerProductSpace.ofCore.normSq x` etc (defeq to `is_R_or_C.re ⟪x, x⟫`) instead of `‖x‖ ^ 2`
etc to avoid extra rewrites when applying it to an `InnerProductSpace`. -/
theorem cauchy_schwarz_aux (x y : F) :
normSqF (⟪x, y⟫ • x - ⟪x, x⟫ • y) = normSqF x * (normSqF x * normSqF y - ‖⟪x, y⟫‖ ^ 2) := by
rw [← @ofReal_inj 𝕜, ofReal_normSq_eq_inner_self]
simp only [inner_sub_sub_self, inner_smul_left, inner_smul_right, conj_ofReal, mul_sub, ←
ofReal_normSq_eq_inner_self x, ← ofReal_normSq_eq_inner_self y]
rw [← mul_assoc, mul_conj, RCLike.conj_mul, mul_left_comm, ← inner_conj_symm y, mul_conj]
push_cast
ring
#align inner_product_space.core.cauchy_schwarz_aux InnerProductSpace.Core.cauchy_schwarz_aux
/-- **Cauchy–Schwarz inequality**.
We need this for the `Core` structure to prove the triangle inequality below when
showing the core is a normed group.
-/
theorem inner_mul_inner_self_le (x y : F) : ‖⟪x, y⟫‖ * ‖⟪y, x⟫‖ ≤ re ⟪x, x⟫ * re ⟪y, y⟫ := by
rcases eq_or_ne x 0 with (rfl | hx)
· simpa only [inner_zero_left, map_zero, zero_mul, norm_zero] using le_rfl
· have hx' : 0 < normSqF x := inner_self_nonneg.lt_of_ne' (mt normSq_eq_zero.1 hx)
rw [← sub_nonneg, ← mul_nonneg_iff_right_nonneg_of_pos hx', ← normSq, ← normSq,
norm_inner_symm y, ← sq, ← cauchy_schwarz_aux]
exact inner_self_nonneg
#align inner_product_space.core.inner_mul_inner_self_le InnerProductSpace.Core.inner_mul_inner_self_le
/-- Norm constructed from an `InnerProductSpace.Core` structure, defined to be the square root
of the scalar product. -/
def toNorm : Norm F where norm x := √(re ⟪x, x⟫)
#align inner_product_space.core.to_has_norm InnerProductSpace.Core.toNorm
attribute [local instance] toNorm
theorem norm_eq_sqrt_inner (x : F) : ‖x‖ = √(re ⟪x, x⟫) := rfl
#align inner_product_space.core.norm_eq_sqrt_inner InnerProductSpace.Core.norm_eq_sqrt_inner
theorem inner_self_eq_norm_mul_norm (x : F) : re ⟪x, x⟫ = ‖x‖ * ‖x‖ := by
rw [norm_eq_sqrt_inner, ← sqrt_mul inner_self_nonneg (re ⟪x, x⟫), sqrt_mul_self inner_self_nonneg]
#align inner_product_space.core.inner_self_eq_norm_mul_norm InnerProductSpace.Core.inner_self_eq_norm_mul_norm
theorem sqrt_normSq_eq_norm (x : F) : √(normSqF x) = ‖x‖ := rfl
#align inner_product_space.core.sqrt_norm_sq_eq_norm InnerProductSpace.Core.sqrt_normSq_eq_norm
/-- Cauchy–Schwarz inequality with norm -/
theorem norm_inner_le_norm (x y : F) : ‖⟪x, y⟫‖ ≤ ‖x‖ * ‖y‖ :=
nonneg_le_nonneg_of_sq_le_sq (mul_nonneg (sqrt_nonneg _) (sqrt_nonneg _)) <|
calc
‖⟪x, y⟫‖ * ‖⟪x, y⟫‖ = ‖⟪x, y⟫‖ * ‖⟪y, x⟫‖ := by rw [norm_inner_symm]
_ ≤ re ⟪x, x⟫ * re ⟪y, y⟫ := inner_mul_inner_self_le x y
_ = ‖x‖ * ‖y‖ * (‖x‖ * ‖y‖) := by simp only [inner_self_eq_norm_mul_norm]; ring
#align inner_product_space.core.norm_inner_le_norm InnerProductSpace.Core.norm_inner_le_norm
/-- Normed group structure constructed from an `InnerProductSpace.Core` structure -/
def toNormedAddCommGroup : NormedAddCommGroup F :=
AddGroupNorm.toNormedAddCommGroup
{ toFun := fun x => √(re ⟪x, x⟫)
map_zero' := by simp only [sqrt_zero, inner_zero_right, map_zero]
neg' := fun x => by simp only [inner_neg_left, neg_neg, inner_neg_right]
add_le' := fun x y => by
have h₁ : ‖⟪x, y⟫‖ ≤ ‖x‖ * ‖y‖ := norm_inner_le_norm _ _
have h₂ : re ⟪x, y⟫ ≤ ‖⟪x, y⟫‖ := re_le_norm _
have h₃ : re ⟪x, y⟫ ≤ ‖x‖ * ‖y‖ := h₂.trans h₁
have h₄ : re ⟪y, x⟫ ≤ ‖x‖ * ‖y‖ := by rwa [← inner_conj_symm, conj_re]
have : ‖x + y‖ * ‖x + y‖ ≤ (‖x‖ + ‖y‖) * (‖x‖ + ‖y‖) := by
simp only [← inner_self_eq_norm_mul_norm, inner_add_add_self, mul_add, mul_comm, map_add]
linarith
exact nonneg_le_nonneg_of_sq_le_sq (add_nonneg (sqrt_nonneg _) (sqrt_nonneg _)) this
eq_zero_of_map_eq_zero' := fun x hx =>
normSq_eq_zero.1 <| (sqrt_eq_zero inner_self_nonneg).1 hx }
#align inner_product_space.core.to_normed_add_comm_group InnerProductSpace.Core.toNormedAddCommGroup
attribute [local instance] toNormedAddCommGroup
/-- Normed space structure constructed from an `InnerProductSpace.Core` structure -/
def toNormedSpace : NormedSpace 𝕜 F where
norm_smul_le r x := by
rw [norm_eq_sqrt_inner, inner_smul_left, inner_smul_right, ← mul_assoc]
rw [RCLike.conj_mul, ← ofReal_pow, re_ofReal_mul, sqrt_mul, ← ofReal_normSq_eq_inner_self,
ofReal_re]
· simp [sqrt_normSq_eq_norm, RCLike.sqrt_normSq_eq_norm]
· positivity
#align inner_product_space.core.to_normed_space InnerProductSpace.Core.toNormedSpace
end InnerProductSpace.Core
section
attribute [local instance] InnerProductSpace.Core.toNormedAddCommGroup
/-- Given an `InnerProductSpace.Core` structure on a space, one can use it to turn
the space into an inner product space. The `NormedAddCommGroup` structure is expected
to already be defined with `InnerProductSpace.ofCore.toNormedAddCommGroup`. -/
def InnerProductSpace.ofCore [AddCommGroup F] [Module 𝕜 F] (c : InnerProductSpace.Core 𝕜 F) :
InnerProductSpace 𝕜 F :=
letI : NormedSpace 𝕜 F := @InnerProductSpace.Core.toNormedSpace 𝕜 F _ _ _ c
{ c with
norm_sq_eq_inner := fun x => by
have h₁ : ‖x‖ ^ 2 = √(re (c.inner x x)) ^ 2 := rfl
have h₂ : 0 ≤ re (c.inner x x) := InnerProductSpace.Core.inner_self_nonneg
simp [h₁, sq_sqrt, h₂] }
#align inner_product_space.of_core InnerProductSpace.ofCore
end
/-! ### Properties of inner product spaces -/
variable [NormedAddCommGroup E] [InnerProductSpace 𝕜 E]
variable [NormedAddCommGroup F] [InnerProductSpace ℝ F]
local notation "⟪" x ", " y "⟫" => @inner 𝕜 _ _ x y
local notation "IK" => @RCLike.I 𝕜 _
local postfix:90 "†" => starRingEnd _
export InnerProductSpace (norm_sq_eq_inner)
section BasicProperties
@[simp]
theorem inner_conj_symm (x y : E) : ⟪y, x⟫† = ⟪x, y⟫ :=
InnerProductSpace.conj_symm _ _
#align inner_conj_symm inner_conj_symm
theorem real_inner_comm (x y : F) : ⟪y, x⟫_ℝ = ⟪x, y⟫_ℝ :=
@inner_conj_symm ℝ _ _ _ _ x y
#align real_inner_comm real_inner_comm
theorem inner_eq_zero_symm {x y : E} : ⟪x, y⟫ = 0 ↔ ⟪y, x⟫ = 0 := by
rw [← inner_conj_symm]
exact star_eq_zero
#align inner_eq_zero_symm inner_eq_zero_symm
@[simp]
theorem inner_self_im (x : E) : im ⟪x, x⟫ = 0 := by rw [← @ofReal_inj 𝕜, im_eq_conj_sub]; simp
#align inner_self_im inner_self_im
theorem inner_add_left (x y z : E) : ⟪x + y, z⟫ = ⟪x, z⟫ + ⟪y, z⟫ :=
InnerProductSpace.add_left _ _ _
#align inner_add_left inner_add_left
theorem inner_add_right (x y z : E) : ⟪x, y + z⟫ = ⟪x, y⟫ + ⟪x, z⟫ := by
rw [← inner_conj_symm, inner_add_left, RingHom.map_add]
simp only [inner_conj_symm]
#align inner_add_right inner_add_right
theorem inner_re_symm (x y : E) : re ⟪x, y⟫ = re ⟪y, x⟫ := by rw [← inner_conj_symm, conj_re]
#align inner_re_symm inner_re_symm
theorem inner_im_symm (x y : E) : im ⟪x, y⟫ = -im ⟪y, x⟫ := by rw [← inner_conj_symm, conj_im]
#align inner_im_symm inner_im_symm
theorem inner_smul_left (x y : E) (r : 𝕜) : ⟪r • x, y⟫ = r† * ⟪x, y⟫ :=
InnerProductSpace.smul_left _ _ _
#align inner_smul_left inner_smul_left
theorem real_inner_smul_left (x y : F) (r : ℝ) : ⟪r • x, y⟫_ℝ = r * ⟪x, y⟫_ℝ :=
inner_smul_left _ _ _
#align real_inner_smul_left real_inner_smul_left
theorem inner_smul_real_left (x y : E) (r : ℝ) : ⟪(r : 𝕜) • x, y⟫ = r • ⟪x, y⟫ := by
rw [inner_smul_left, conj_ofReal, Algebra.smul_def]
rfl
#align inner_smul_real_left inner_smul_real_left
theorem inner_smul_right (x y : E) (r : 𝕜) : ⟪x, r • y⟫ = r * ⟪x, y⟫ := by
rw [← inner_conj_symm, inner_smul_left, RingHom.map_mul, conj_conj, inner_conj_symm]
#align inner_smul_right inner_smul_right
theorem real_inner_smul_right (x y : F) (r : ℝ) : ⟪x, r • y⟫_ℝ = r * ⟪x, y⟫_ℝ :=
inner_smul_right _ _ _
#align real_inner_smul_right real_inner_smul_right
theorem inner_smul_real_right (x y : E) (r : ℝ) : ⟪x, (r : 𝕜) • y⟫ = r • ⟪x, y⟫ := by
rw [inner_smul_right, Algebra.smul_def]
rfl
#align inner_smul_real_right inner_smul_real_right
/-- The inner product as a sesquilinear form.
Note that in the case `𝕜 = ℝ` this is a bilinear form. -/
@[simps!]
def sesqFormOfInner : E →ₗ[𝕜] E →ₗ⋆[𝕜] 𝕜 :=
LinearMap.mk₂'ₛₗ (RingHom.id 𝕜) (starRingEnd _) (fun x y => ⟪y, x⟫)
(fun _x _y _z => inner_add_right _ _ _) (fun _r _x _y => inner_smul_right _ _ _)
(fun _x _y _z => inner_add_left _ _ _) fun _r _x _y => inner_smul_left _ _ _
#align sesq_form_of_inner sesqFormOfInner
/-- The real inner product as a bilinear form.
Note that unlike `sesqFormOfInner`, this does not reverse the order of the arguments. -/
@[simps!]
def bilinFormOfRealInner : BilinForm ℝ F := sesqFormOfInner.flip
#align bilin_form_of_real_inner bilinFormOfRealInner
/-- An inner product with a sum on the left. -/
theorem sum_inner {ι : Type*} (s : Finset ι) (f : ι → E) (x : E) :
⟪∑ i ∈ s, f i, x⟫ = ∑ i ∈ s, ⟪f i, x⟫ :=
map_sum (sesqFormOfInner (𝕜 := 𝕜) (E := E) x) _ _
#align sum_inner sum_inner
/-- An inner product with a sum on the right. -/
theorem inner_sum {ι : Type*} (s : Finset ι) (f : ι → E) (x : E) :
⟪x, ∑ i ∈ s, f i⟫ = ∑ i ∈ s, ⟪x, f i⟫ :=
map_sum (LinearMap.flip sesqFormOfInner x) _ _
#align inner_sum inner_sum
/-- An inner product with a sum on the left, `Finsupp` version. -/
theorem Finsupp.sum_inner {ι : Type*} (l : ι →₀ 𝕜) (v : ι → E) (x : E) :
⟪l.sum fun (i : ι) (a : 𝕜) => a • v i, x⟫ = l.sum fun (i : ι) (a : 𝕜) => conj a • ⟪v i, x⟫ := by
convert _root_.sum_inner (𝕜 := 𝕜) l.support (fun a => l a • v a) x
simp only [inner_smul_left, Finsupp.sum, smul_eq_mul]
#align finsupp.sum_inner Finsupp.sum_inner
/-- An inner product with a sum on the right, `Finsupp` version. -/
theorem Finsupp.inner_sum {ι : Type*} (l : ι →₀ 𝕜) (v : ι → E) (x : E) :
⟪x, l.sum fun (i : ι) (a : 𝕜) => a • v i⟫ = l.sum fun (i : ι) (a : 𝕜) => a • ⟪x, v i⟫ := by
convert _root_.inner_sum (𝕜 := 𝕜) l.support (fun a => l a • v a) x
simp only [inner_smul_right, Finsupp.sum, smul_eq_mul]
#align finsupp.inner_sum Finsupp.inner_sum
theorem DFinsupp.sum_inner {ι : Type*} [DecidableEq ι] {α : ι → Type*}
[∀ i, AddZeroClass (α i)] [∀ (i) (x : α i), Decidable (x ≠ 0)] (f : ∀ i, α i → E)
(l : Π₀ i, α i) (x : E) : ⟪l.sum f, x⟫ = l.sum fun i a => ⟪f i a, x⟫ := by
simp (config := { contextual := true }) only [DFinsupp.sum, _root_.sum_inner, smul_eq_mul]
#align dfinsupp.sum_inner DFinsupp.sum_inner
theorem DFinsupp.inner_sum {ι : Type*} [DecidableEq ι] {α : ι → Type*}
[∀ i, AddZeroClass (α i)] [∀ (i) (x : α i), Decidable (x ≠ 0)] (f : ∀ i, α i → E)
(l : Π₀ i, α i) (x : E) : ⟪x, l.sum f⟫ = l.sum fun i a => ⟪x, f i a⟫ := by
simp (config := { contextual := true }) only [DFinsupp.sum, _root_.inner_sum, smul_eq_mul]
#align dfinsupp.inner_sum DFinsupp.inner_sum
@[simp]
theorem inner_zero_left (x : E) : ⟪0, x⟫ = 0 := by
rw [← zero_smul 𝕜 (0 : E), inner_smul_left, RingHom.map_zero, zero_mul]
#align inner_zero_left inner_zero_left
theorem inner_re_zero_left (x : E) : re ⟪0, x⟫ = 0 := by
simp only [inner_zero_left, AddMonoidHom.map_zero]
#align inner_re_zero_left inner_re_zero_left
@[simp]
theorem inner_zero_right (x : E) : ⟪x, 0⟫ = 0 := by
rw [← inner_conj_symm, inner_zero_left, RingHom.map_zero]
#align inner_zero_right inner_zero_right
theorem inner_re_zero_right (x : E) : re ⟪x, 0⟫ = 0 := by
simp only [inner_zero_right, AddMonoidHom.map_zero]
#align inner_re_zero_right inner_re_zero_right
theorem inner_self_nonneg {x : E} : 0 ≤ re ⟪x, x⟫ :=
InnerProductSpace.toCore.nonneg_re x
#align inner_self_nonneg inner_self_nonneg
theorem real_inner_self_nonneg {x : F} : 0 ≤ ⟪x, x⟫_ℝ :=
@inner_self_nonneg ℝ F _ _ _ x
#align real_inner_self_nonneg real_inner_self_nonneg
@[simp]
theorem inner_self_ofReal_re (x : E) : (re ⟪x, x⟫ : 𝕜) = ⟪x, x⟫ :=
((RCLike.is_real_TFAE (⟪x, x⟫ : 𝕜)).out 2 3).2 (inner_self_im _)
set_option linter.uppercaseLean3 false in
#align inner_self_re_to_K inner_self_ofReal_re
theorem inner_self_eq_norm_sq_to_K (x : E) : ⟪x, x⟫ = (‖x‖ : 𝕜) ^ 2 := by
rw [← inner_self_ofReal_re, ← norm_sq_eq_inner, ofReal_pow]
set_option linter.uppercaseLean3 false in
#align inner_self_eq_norm_sq_to_K inner_self_eq_norm_sq_to_K
theorem inner_self_re_eq_norm (x : E) : re ⟪x, x⟫ = ‖⟪x, x⟫‖ := by
conv_rhs => rw [← inner_self_ofReal_re]
symm
exact norm_of_nonneg inner_self_nonneg
#align inner_self_re_eq_norm inner_self_re_eq_norm
theorem inner_self_ofReal_norm (x : E) : (‖⟪x, x⟫‖ : 𝕜) = ⟪x, x⟫ := by
rw [← inner_self_re_eq_norm]
exact inner_self_ofReal_re _
set_option linter.uppercaseLean3 false in
#align inner_self_norm_to_K inner_self_ofReal_norm
theorem real_inner_self_abs (x : F) : |⟪x, x⟫_ℝ| = ⟪x, x⟫_ℝ :=
@inner_self_ofReal_norm ℝ F _ _ _ x
#align real_inner_self_abs real_inner_self_abs
@[simp]
theorem inner_self_eq_zero {x : E} : ⟪x, x⟫ = 0 ↔ x = 0 := by
rw [inner_self_eq_norm_sq_to_K, sq_eq_zero_iff, ofReal_eq_zero, norm_eq_zero]
#align inner_self_eq_zero inner_self_eq_zero
theorem inner_self_ne_zero {x : E} : ⟪x, x⟫ ≠ 0 ↔ x ≠ 0 :=
inner_self_eq_zero.not
#align inner_self_ne_zero inner_self_ne_zero
@[simp]
theorem inner_self_nonpos {x : E} : re ⟪x, x⟫ ≤ 0 ↔ x = 0 := by
rw [← norm_sq_eq_inner, (sq_nonneg _).le_iff_eq, sq_eq_zero_iff, norm_eq_zero]
#align inner_self_nonpos inner_self_nonpos
theorem real_inner_self_nonpos {x : F} : ⟪x, x⟫_ℝ ≤ 0 ↔ x = 0 :=
@inner_self_nonpos ℝ F _ _ _ x
#align real_inner_self_nonpos real_inner_self_nonpos
theorem norm_inner_symm (x y : E) : ‖⟪x, y⟫‖ = ‖⟪y, x⟫‖ := by rw [← inner_conj_symm, norm_conj]
#align norm_inner_symm norm_inner_symm
@[simp]
theorem inner_neg_left (x y : E) : ⟪-x, y⟫ = -⟪x, y⟫ := by
rw [← neg_one_smul 𝕜 x, inner_smul_left]
simp
#align inner_neg_left inner_neg_left
@[simp]
theorem inner_neg_right (x y : E) : ⟪x, -y⟫ = -⟪x, y⟫ := by
rw [← inner_conj_symm, inner_neg_left]; simp only [RingHom.map_neg, inner_conj_symm]
#align inner_neg_right inner_neg_right
theorem inner_neg_neg (x y : E) : ⟪-x, -y⟫ = ⟪x, y⟫ := by simp
#align inner_neg_neg inner_neg_neg
-- Porting note: removed `simp` because it can prove it using `inner_conj_symm`
theorem inner_self_conj (x : E) : ⟪x, x⟫† = ⟪x, x⟫ := inner_conj_symm _ _
#align inner_self_conj inner_self_conj
theorem inner_sub_left (x y z : E) : ⟪x - y, z⟫ = ⟪x, z⟫ - ⟪y, z⟫ := by
simp [sub_eq_add_neg, inner_add_left]
#align inner_sub_left inner_sub_left
theorem inner_sub_right (x y z : E) : ⟪x, y - z⟫ = ⟪x, y⟫ - ⟪x, z⟫ := by
simp [sub_eq_add_neg, inner_add_right]
#align inner_sub_right inner_sub_right
theorem inner_mul_symm_re_eq_norm (x y : E) : re (⟪x, y⟫ * ⟪y, x⟫) = ‖⟪x, y⟫ * ⟪y, x⟫‖ := by
rw [← inner_conj_symm, mul_comm]
exact re_eq_norm_of_mul_conj (inner y x)
#align inner_mul_symm_re_eq_norm inner_mul_symm_re_eq_norm
/-- Expand `⟪x + y, x + y⟫` -/
theorem inner_add_add_self (x y : E) : ⟪x + y, x + y⟫ = ⟪x, x⟫ + ⟪x, y⟫ + ⟪y, x⟫ + ⟪y, y⟫ := by
simp only [inner_add_left, inner_add_right]; ring
#align inner_add_add_self inner_add_add_self
/-- Expand `⟪x + y, x + y⟫_ℝ` -/
theorem real_inner_add_add_self (x y : F) :
⟪x + y, x + y⟫_ℝ = ⟪x, x⟫_ℝ + 2 * ⟪x, y⟫_ℝ + ⟪y, y⟫_ℝ := by
have : ⟪y, x⟫_ℝ = ⟪x, y⟫_ℝ := by rw [← inner_conj_symm]; rfl
simp only [inner_add_add_self, this, add_left_inj]
ring
#align real_inner_add_add_self real_inner_add_add_self
-- Expand `⟪x - y, x - y⟫`
theorem inner_sub_sub_self (x y : E) : ⟪x - y, x - y⟫ = ⟪x, x⟫ - ⟪x, y⟫ - ⟪y, x⟫ + ⟪y, y⟫ := by
simp only [inner_sub_left, inner_sub_right]; ring
#align inner_sub_sub_self inner_sub_sub_self
/-- Expand `⟪x - y, x - y⟫_ℝ` -/
theorem real_inner_sub_sub_self (x y : F) :
⟪x - y, x - y⟫_ℝ = ⟪x, x⟫_ℝ - 2 * ⟪x, y⟫_ℝ + ⟪y, y⟫_ℝ := by
have : ⟪y, x⟫_ℝ = ⟪x, y⟫_ℝ := by rw [← inner_conj_symm]; rfl
simp only [inner_sub_sub_self, this, add_left_inj]
ring
#align real_inner_sub_sub_self real_inner_sub_sub_self
variable (𝕜)
theorem ext_inner_left {x y : E} (h : ∀ v, ⟪v, x⟫ = ⟪v, y⟫) : x = y := by
rw [← sub_eq_zero, ← @inner_self_eq_zero 𝕜, inner_sub_right, sub_eq_zero, h (x - y)]
#align ext_inner_left ext_inner_left
theorem ext_inner_right {x y : E} (h : ∀ v, ⟪x, v⟫ = ⟪y, v⟫) : x = y := by
rw [← sub_eq_zero, ← @inner_self_eq_zero 𝕜, inner_sub_left, sub_eq_zero, h (x - y)]
#align ext_inner_right ext_inner_right
variable {𝕜}
/-- Parallelogram law -/
theorem parallelogram_law {x y : E} : ⟪x + y, x + y⟫ + ⟪x - y, x - y⟫ = 2 * (⟪x, x⟫ + ⟪y, y⟫) := by
simp only [inner_add_add_self, inner_sub_sub_self]
ring
#align parallelogram_law parallelogram_law
/-- **Cauchy–Schwarz inequality**. -/
theorem inner_mul_inner_self_le (x y : E) : ‖⟪x, y⟫‖ * ‖⟪y, x⟫‖ ≤ re ⟪x, x⟫ * re ⟪y, y⟫ :=
letI c : InnerProductSpace.Core 𝕜 E := InnerProductSpace.toCore
InnerProductSpace.Core.inner_mul_inner_self_le x y
#align inner_mul_inner_self_le inner_mul_inner_self_le
/-- Cauchy–Schwarz inequality for real inner products. -/
theorem real_inner_mul_inner_self_le (x y : F) : ⟪x, y⟫_ℝ * ⟪x, y⟫_ℝ ≤ ⟪x, x⟫_ℝ * ⟪y, y⟫_ℝ :=
calc
⟪x, y⟫_ℝ * ⟪x, y⟫_ℝ ≤ ‖⟪x, y⟫_ℝ‖ * ‖⟪y, x⟫_ℝ‖ := by
rw [real_inner_comm y, ← norm_mul]
exact le_abs_self _
_ ≤ ⟪x, x⟫_ℝ * ⟪y, y⟫_ℝ := @inner_mul_inner_self_le ℝ _ _ _ _ x y
#align real_inner_mul_inner_self_le real_inner_mul_inner_self_le
/-- A family of vectors is linearly independent if they are nonzero
and orthogonal. -/
theorem linearIndependent_of_ne_zero_of_inner_eq_zero {ι : Type*} {v : ι → E} (hz : ∀ i, v i ≠ 0)
(ho : Pairwise fun i j => ⟪v i, v j⟫ = 0) : LinearIndependent 𝕜 v := by
rw [linearIndependent_iff']
intro s g hg i hi
have h' : g i * inner (v i) (v i) = inner (v i) (∑ j ∈ s, g j • v j) := by
rw [inner_sum]
symm
convert Finset.sum_eq_single (β := 𝕜) i ?_ ?_
· rw [inner_smul_right]
· intro j _hj hji
rw [inner_smul_right, ho hji.symm, mul_zero]
· exact fun h => False.elim (h hi)
simpa [hg, hz] using h'
#align linear_independent_of_ne_zero_of_inner_eq_zero linearIndependent_of_ne_zero_of_inner_eq_zero
end BasicProperties
section OrthonormalSets
variable {ι : Type*} (𝕜)
/-- An orthonormal set of vectors in an `InnerProductSpace` -/
def Orthonormal (v : ι → E) : Prop :=
(∀ i, ‖v i‖ = 1) ∧ Pairwise fun i j => ⟪v i, v j⟫ = 0
#align orthonormal Orthonormal
variable {𝕜}
/-- `if ... then ... else` characterization of an indexed set of vectors being orthonormal. (Inner
product equals Kronecker delta.) -/
theorem orthonormal_iff_ite [DecidableEq ι] {v : ι → E} :
Orthonormal 𝕜 v ↔ ∀ i j, ⟪v i, v j⟫ = if i = j then (1 : 𝕜) else (0 : 𝕜) := by
constructor
· intro hv i j
split_ifs with h
· simp [h, inner_self_eq_norm_sq_to_K, hv.1]
· exact hv.2 h
· intro h
constructor
· intro i
have h' : ‖v i‖ ^ 2 = 1 ^ 2 := by simp [@norm_sq_eq_inner 𝕜, h i i]
have h₁ : 0 ≤ ‖v i‖ := norm_nonneg _
have h₂ : (0 : ℝ) ≤ 1 := zero_le_one
rwa [sq_eq_sq h₁ h₂] at h'
· intro i j hij
simpa [hij] using h i j
#align orthonormal_iff_ite orthonormal_iff_ite
/-- `if ... then ... else` characterization of a set of vectors being orthonormal. (Inner product
equals Kronecker delta.) -/
theorem orthonormal_subtype_iff_ite [DecidableEq E] {s : Set E} :
Orthonormal 𝕜 (Subtype.val : s → E) ↔ ∀ v ∈ s, ∀ w ∈ s, ⟪v, w⟫ = if v = w then 1 else 0 := by
rw [orthonormal_iff_ite]
constructor
· intro h v hv w hw
convert h ⟨v, hv⟩ ⟨w, hw⟩ using 1
simp
· rintro h ⟨v, hv⟩ ⟨w, hw⟩
convert h v hv w hw using 1
simp
#align orthonormal_subtype_iff_ite orthonormal_subtype_iff_ite
/-- The inner product of a linear combination of a set of orthonormal vectors with one of those
vectors picks out the coefficient of that vector. -/
theorem Orthonormal.inner_right_finsupp {v : ι → E} (hv : Orthonormal 𝕜 v) (l : ι →₀ 𝕜) (i : ι) :
⟪v i, Finsupp.total ι E 𝕜 v l⟫ = l i := by
classical
simpa [Finsupp.total_apply, Finsupp.inner_sum, orthonormal_iff_ite.mp hv] using Eq.symm
#align orthonormal.inner_right_finsupp Orthonormal.inner_right_finsupp
/-- The inner product of a linear combination of a set of orthonormal vectors with one of those
vectors picks out the coefficient of that vector. -/
theorem Orthonormal.inner_right_sum {v : ι → E} (hv : Orthonormal 𝕜 v) (l : ι → 𝕜) {s : Finset ι}
{i : ι} (hi : i ∈ s) : ⟪v i, ∑ i ∈ s, l i • v i⟫ = l i := by
classical
simp [inner_sum, inner_smul_right, orthonormal_iff_ite.mp hv, hi]
#align orthonormal.inner_right_sum Orthonormal.inner_right_sum
/-- The inner product of a linear combination of a set of orthonormal vectors with one of those
vectors picks out the coefficient of that vector. -/
theorem Orthonormal.inner_right_fintype [Fintype ι] {v : ι → E} (hv : Orthonormal 𝕜 v) (l : ι → 𝕜)
(i : ι) : ⟪v i, ∑ i : ι, l i • v i⟫ = l i :=
hv.inner_right_sum l (Finset.mem_univ _)
#align orthonormal.inner_right_fintype Orthonormal.inner_right_fintype
/-- The inner product of a linear combination of a set of orthonormal vectors with one of those
vectors picks out the coefficient of that vector. -/
theorem Orthonormal.inner_left_finsupp {v : ι → E} (hv : Orthonormal 𝕜 v) (l : ι →₀ 𝕜) (i : ι) :
⟪Finsupp.total ι E 𝕜 v l, v i⟫ = conj (l i) := by rw [← inner_conj_symm, hv.inner_right_finsupp]
#align orthonormal.inner_left_finsupp Orthonormal.inner_left_finsupp
/-- The inner product of a linear combination of a set of orthonormal vectors with one of those
vectors picks out the coefficient of that vector. -/
theorem Orthonormal.inner_left_sum {v : ι → E} (hv : Orthonormal 𝕜 v) (l : ι → 𝕜) {s : Finset ι}
{i : ι} (hi : i ∈ s) : ⟪∑ i ∈ s, l i • v i, v i⟫ = conj (l i) := by
classical
simp only [sum_inner, inner_smul_left, orthonormal_iff_ite.mp hv, hi, mul_boole,
Finset.sum_ite_eq', if_true]
#align orthonormal.inner_left_sum Orthonormal.inner_left_sum
/-- The inner product of a linear combination of a set of orthonormal vectors with one of those
vectors picks out the coefficient of that vector. -/
theorem Orthonormal.inner_left_fintype [Fintype ι] {v : ι → E} (hv : Orthonormal 𝕜 v) (l : ι → 𝕜)
(i : ι) : ⟪∑ i : ι, l i • v i, v i⟫ = conj (l i) :=
hv.inner_left_sum l (Finset.mem_univ _)
#align orthonormal.inner_left_fintype Orthonormal.inner_left_fintype
/-- The inner product of two linear combinations of a set of orthonormal vectors, expressed as
a sum over the first `Finsupp`. -/
theorem Orthonormal.inner_finsupp_eq_sum_left {v : ι → E} (hv : Orthonormal 𝕜 v) (l₁ l₂ : ι →₀ 𝕜) :
⟪Finsupp.total ι E 𝕜 v l₁, Finsupp.total ι E 𝕜 v l₂⟫ = l₁.sum fun i y => conj y * l₂ i := by
simp only [l₁.total_apply _, Finsupp.sum_inner, hv.inner_right_finsupp, smul_eq_mul]
#align orthonormal.inner_finsupp_eq_sum_left Orthonormal.inner_finsupp_eq_sum_left
/-- The inner product of two linear combinations of a set of orthonormal vectors, expressed as
a sum over the second `Finsupp`. -/
theorem Orthonormal.inner_finsupp_eq_sum_right {v : ι → E} (hv : Orthonormal 𝕜 v) (l₁ l₂ : ι →₀ 𝕜) :
⟪Finsupp.total ι E 𝕜 v l₁, Finsupp.total ι E 𝕜 v l₂⟫ = l₂.sum fun i y => conj (l₁ i) * y := by
simp only [l₂.total_apply _, Finsupp.inner_sum, hv.inner_left_finsupp, mul_comm, smul_eq_mul]
#align orthonormal.inner_finsupp_eq_sum_right Orthonormal.inner_finsupp_eq_sum_right
/-- The inner product of two linear combinations of a set of orthonormal vectors, expressed as
a sum. -/
theorem Orthonormal.inner_sum {v : ι → E} (hv : Orthonormal 𝕜 v) (l₁ l₂ : ι → 𝕜) (s : Finset ι) :
⟪∑ i ∈ s, l₁ i • v i, ∑ i ∈ s, l₂ i • v i⟫ = ∑ i ∈ s, conj (l₁ i) * l₂ i := by
simp_rw [sum_inner, inner_smul_left]
refine Finset.sum_congr rfl fun i hi => ?_
rw [hv.inner_right_sum l₂ hi]
#align orthonormal.inner_sum Orthonormal.inner_sum
/--
The double sum of weighted inner products of pairs of vectors from an orthonormal sequence is the
sum of the weights.
-/
theorem Orthonormal.inner_left_right_finset {s : Finset ι} {v : ι → E} (hv : Orthonormal 𝕜 v)
{a : ι → ι → 𝕜} : (∑ i ∈ s, ∑ j ∈ s, a i j • ⟪v j, v i⟫) = ∑ k ∈ s, a k k := by
classical
simp [orthonormal_iff_ite.mp hv, Finset.sum_ite_of_true]
#align orthonormal.inner_left_right_finset Orthonormal.inner_left_right_finset
/-- An orthonormal set is linearly independent. -/
theorem Orthonormal.linearIndependent {v : ι → E} (hv : Orthonormal 𝕜 v) :
LinearIndependent 𝕜 v := by
rw [linearIndependent_iff]
intro l hl
ext i
have key : ⟪v i, Finsupp.total ι E 𝕜 v l⟫ = ⟪v i, 0⟫ := by rw [hl]
simpa only [hv.inner_right_finsupp, inner_zero_right] using key
#align orthonormal.linear_independent Orthonormal.linearIndependent
/-- A subfamily of an orthonormal family (i.e., a composition with an injective map) is an
orthonormal family. -/
theorem Orthonormal.comp {ι' : Type*} {v : ι → E} (hv : Orthonormal 𝕜 v) (f : ι' → ι)
(hf : Function.Injective f) : Orthonormal 𝕜 (v ∘ f) := by
classical
rw [orthonormal_iff_ite] at hv ⊢
intro i j
convert hv (f i) (f j) using 1
simp [hf.eq_iff]
#align orthonormal.comp Orthonormal.comp
/-- An injective family `v : ι → E` is orthonormal if and only if `Subtype.val : (range v) → E` is
orthonormal. -/
theorem orthonormal_subtype_range {v : ι → E} (hv : Function.Injective v) :
Orthonormal 𝕜 (Subtype.val : Set.range v → E) ↔ Orthonormal 𝕜 v := by
let f : ι ≃ Set.range v := Equiv.ofInjective v hv
refine ⟨fun h => h.comp f f.injective, fun h => ?_⟩
rw [← Equiv.self_comp_ofInjective_symm hv]
exact h.comp f.symm f.symm.injective
#align orthonormal_subtype_range orthonormal_subtype_range
/-- If `v : ι → E` is an orthonormal family, then `Subtype.val : (range v) → E` is an orthonormal
family. -/
theorem Orthonormal.toSubtypeRange {v : ι → E} (hv : Orthonormal 𝕜 v) :
Orthonormal 𝕜 (Subtype.val : Set.range v → E) :=
(orthonormal_subtype_range hv.linearIndependent.injective).2 hv
#align orthonormal.to_subtype_range Orthonormal.toSubtypeRange
/-- A linear combination of some subset of an orthonormal set is orthogonal to other members of the
set. -/
theorem Orthonormal.inner_finsupp_eq_zero {v : ι → E} (hv : Orthonormal 𝕜 v) {s : Set ι} {i : ι}
(hi : i ∉ s) {l : ι →₀ 𝕜} (hl : l ∈ Finsupp.supported 𝕜 𝕜 s) :
⟪Finsupp.total ι E 𝕜 v l, v i⟫ = 0 := by
rw [Finsupp.mem_supported'] at hl
simp only [hv.inner_left_finsupp, hl i hi, map_zero]
#align orthonormal.inner_finsupp_eq_zero Orthonormal.inner_finsupp_eq_zero
/-- Given an orthonormal family, a second family of vectors is orthonormal if every vector equals
the corresponding vector in the original family or its negation. -/
theorem Orthonormal.orthonormal_of_forall_eq_or_eq_neg {v w : ι → E} (hv : Orthonormal 𝕜 v)
(hw : ∀ i, w i = v i ∨ w i = -v i) : Orthonormal 𝕜 w := by
classical
rw [orthonormal_iff_ite] at *
intro i j
cases' hw i with hi hi <;> cases' hw j with hj hj <;>
replace hv := hv i j <;> split_ifs at hv ⊢ with h <;>
simpa only [hi, hj, h, inner_neg_right, inner_neg_left, neg_neg, eq_self_iff_true,
neg_eq_zero] using hv
#align orthonormal.orthonormal_of_forall_eq_or_eq_neg Orthonormal.orthonormal_of_forall_eq_or_eq_neg
/- The material that follows, culminating in the existence of a maximal orthonormal subset, is
adapted from the corresponding development of the theory of linearly independents sets. See
`exists_linearIndependent` in particular. -/
variable (𝕜 E)
theorem orthonormal_empty : Orthonormal 𝕜 (fun x => x : (∅ : Set E) → E) := by
classical
simp [orthonormal_subtype_iff_ite]
#align orthonormal_empty orthonormal_empty
variable {𝕜 E}
theorem orthonormal_iUnion_of_directed {η : Type*} {s : η → Set E} (hs : Directed (· ⊆ ·) s)
(h : ∀ i, Orthonormal 𝕜 (fun x => x : s i → E)) :
Orthonormal 𝕜 (fun x => x : (⋃ i, s i) → E) := by
classical
rw [orthonormal_subtype_iff_ite]
rintro x ⟨_, ⟨i, rfl⟩, hxi⟩ y ⟨_, ⟨j, rfl⟩, hyj⟩
obtain ⟨k, hik, hjk⟩ := hs i j
have h_orth : Orthonormal 𝕜 (fun x => x : s k → E) := h k
rw [orthonormal_subtype_iff_ite] at h_orth
exact h_orth x (hik hxi) y (hjk hyj)
#align orthonormal_Union_of_directed orthonormal_iUnion_of_directed
theorem orthonormal_sUnion_of_directed {s : Set (Set E)} (hs : DirectedOn (· ⊆ ·) s)
(h : ∀ a ∈ s, Orthonormal 𝕜 (fun x => ((x : a) : E))) :
Orthonormal 𝕜 (fun x => x : ⋃₀ s → E) := by
rw [Set.sUnion_eq_iUnion]; exact orthonormal_iUnion_of_directed hs.directed_val (by simpa using h)
#align orthonormal_sUnion_of_directed orthonormal_sUnion_of_directed
/-- Given an orthonormal set `v` of vectors in `E`, there exists a maximal orthonormal set
containing it. -/
theorem exists_maximal_orthonormal {s : Set E} (hs : Orthonormal 𝕜 (Subtype.val : s → E)) :
∃ w ⊇ s, Orthonormal 𝕜 (Subtype.val : w → E) ∧
∀ u ⊇ w, Orthonormal 𝕜 (Subtype.val : u → E) → u = w := by
have := zorn_subset_nonempty { b | Orthonormal 𝕜 (Subtype.val : b → E) } ?_ _ hs
· obtain ⟨b, bi, sb, h⟩ := this
refine ⟨b, sb, bi, ?_⟩
exact fun u hus hu => h u hu hus
· refine fun c hc cc _c0 => ⟨⋃₀ c, ?_, ?_⟩
· exact orthonormal_sUnion_of_directed cc.directedOn fun x xc => hc xc
· exact fun _ => Set.subset_sUnion_of_mem
#align exists_maximal_orthonormal exists_maximal_orthonormal
theorem Orthonormal.ne_zero {v : ι → E} (hv : Orthonormal 𝕜 v) (i : ι) : v i ≠ 0 := by
have : ‖v i‖ ≠ 0 := by
rw [hv.1 i]
norm_num
simpa using this
#align orthonormal.ne_zero Orthonormal.ne_zero
open FiniteDimensional
/-- A family of orthonormal vectors with the correct cardinality forms a basis. -/
def basisOfOrthonormalOfCardEqFinrank [Fintype ι] [Nonempty ι] {v : ι → E} (hv : Orthonormal 𝕜 v)
(card_eq : Fintype.card ι = finrank 𝕜 E) : Basis ι 𝕜 E :=
basisOfLinearIndependentOfCardEqFinrank hv.linearIndependent card_eq
#align basis_of_orthonormal_of_card_eq_finrank basisOfOrthonormalOfCardEqFinrank
@[simp]
theorem coe_basisOfOrthonormalOfCardEqFinrank [Fintype ι] [Nonempty ι] {v : ι → E}
(hv : Orthonormal 𝕜 v) (card_eq : Fintype.card ι = finrank 𝕜 E) :
(basisOfOrthonormalOfCardEqFinrank hv card_eq : ι → E) = v :=
coe_basisOfLinearIndependentOfCardEqFinrank _ _
#align coe_basis_of_orthonormal_of_card_eq_finrank coe_basisOfOrthonormalOfCardEqFinrank
end OrthonormalSets
section Norm
theorem norm_eq_sqrt_inner (x : E) : ‖x‖ = √(re ⟪x, x⟫) :=
calc
‖x‖ = √(‖x‖ ^ 2) := (sqrt_sq (norm_nonneg _)).symm
_ = √(re ⟪x, x⟫) := congr_arg _ (norm_sq_eq_inner _)
#align norm_eq_sqrt_inner norm_eq_sqrt_inner
theorem norm_eq_sqrt_real_inner (x : F) : ‖x‖ = √⟪x, x⟫_ℝ :=
@norm_eq_sqrt_inner ℝ _ _ _ _ x
#align norm_eq_sqrt_real_inner norm_eq_sqrt_real_inner
theorem inner_self_eq_norm_mul_norm (x : E) : re ⟪x, x⟫ = ‖x‖ * ‖x‖ := by
rw [@norm_eq_sqrt_inner 𝕜, ← sqrt_mul inner_self_nonneg (re ⟪x, x⟫),
sqrt_mul_self inner_self_nonneg]
#align inner_self_eq_norm_mul_norm inner_self_eq_norm_mul_norm
| Mathlib/Analysis/InnerProductSpace/Basic.lean | 997 | 998 | theorem inner_self_eq_norm_sq (x : E) : re ⟪x, x⟫ = ‖x‖ ^ 2 := by |
rw [pow_two, inner_self_eq_norm_mul_norm]
|
/-
Copyright (c) 2021 Kevin Kappelmann. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kevin Kappelmann
-/
import Mathlib.Algebra.ContinuedFractions.Computation.Approximations
import Mathlib.Algebra.ContinuedFractions.ConvergentsEquiv
import Mathlib.Algebra.Order.Archimedean
import Mathlib.Tactic.GCongr
import Mathlib.Topology.Order.LeftRightNhds
#align_import algebra.continued_fractions.computation.approximation_corollaries from "leanprover-community/mathlib"@"f0c8bf9245297a541f468be517f1bde6195105e9"
/-!
# Corollaries From Approximation Lemmas (`Algebra.ContinuedFractions.Computation.Approximations`)
## Summary
We show that the generalized_continued_fraction given by `GeneralizedContinuedFraction.of` in fact
is a (regular) continued fraction. Using the equivalence of the convergents computations
(`GeneralizedContinuedFraction.convergents` and `GeneralizedContinuedFraction.convergents'`) for
continued fractions (see `Algebra.ContinuedFractions.ConvergentsEquiv`), it follows that the
convergents computations for `GeneralizedContinuedFraction.of` are equivalent.
Moreover, we show the convergence of the continued fractions computations, that is
`(GeneralizedContinuedFraction.of v).convergents` indeed computes `v` in the limit.
## Main Definitions
- `ContinuedFraction.of` returns the (regular) continued fraction of a value.
## Main Theorems
- `GeneralizedContinuedFraction.of_convergents_eq_convergents'` shows that the convergents
computations for `GeneralizedContinuedFraction.of` are equivalent.
- `GeneralizedContinuedFraction.of_convergence` shows that
`(GeneralizedContinuedFraction.of v).convergents` converges to `v`.
## Tags
convergence, fractions
-/
variable {K : Type*} (v : K) [LinearOrderedField K] [FloorRing K]
open GeneralizedContinuedFraction (of)
open GeneralizedContinuedFraction
open scoped Topology
theorem GeneralizedContinuedFraction.of_isSimpleContinuedFraction :
(of v).IsSimpleContinuedFraction := fun _ _ nth_part_num_eq =>
of_part_num_eq_one nth_part_num_eq
#align generalized_continued_fraction.of_is_simple_continued_fraction GeneralizedContinuedFraction.of_isSimpleContinuedFraction
/-- Creates the simple continued fraction of a value. -/
nonrec def SimpleContinuedFraction.of : SimpleContinuedFraction K :=
⟨of v, GeneralizedContinuedFraction.of_isSimpleContinuedFraction v⟩
#align simple_continued_fraction.of SimpleContinuedFraction.of
theorem SimpleContinuedFraction.of_isContinuedFraction :
(SimpleContinuedFraction.of v).IsContinuedFraction := fun _ _ nth_part_denom_eq =>
lt_of_lt_of_le zero_lt_one (of_one_le_get?_part_denom nth_part_denom_eq)
#align simple_continued_fraction.of_is_continued_fraction SimpleContinuedFraction.of_isContinuedFraction
/-- Creates the continued fraction of a value. -/
def ContinuedFraction.of : ContinuedFraction K :=
⟨SimpleContinuedFraction.of v, SimpleContinuedFraction.of_isContinuedFraction v⟩
#align continued_fraction.of ContinuedFraction.of
namespace GeneralizedContinuedFraction
theorem of_convergents_eq_convergents' : (of v).convergents = (of v).convergents' :=
@ContinuedFraction.convergents_eq_convergents' _ _ (ContinuedFraction.of v)
#align generalized_continued_fraction.of_convergents_eq_convergents' GeneralizedContinuedFraction.of_convergents_eq_convergents'
/-- The recurrence relation for the `convergents` of the continued fraction expansion
of an element `v` of `K` in terms of the convergents of the inverse of its fractional part.
-/
theorem convergents_succ (n : ℕ) :
(of v).convergents (n + 1) = ⌊v⌋ + 1 / (of (Int.fract v)⁻¹).convergents n := by
rw [of_convergents_eq_convergents', convergents'_succ, of_convergents_eq_convergents']
#align generalized_continued_fraction.convergents_succ GeneralizedContinuedFraction.convergents_succ
section Convergence
/-!
### Convergence
We next show that `(GeneralizedContinuedFraction.of v).convergents v` converges to `v`.
-/
variable [Archimedean K]
open Nat
theorem of_convergence_epsilon :
∀ ε > (0 : K), ∃ N : ℕ, ∀ n ≥ N, |v - (of v).convergents n| < ε := by
intro ε ε_pos
-- use the archimedean property to obtain a suitable N
rcases (exists_nat_gt (1 / ε) : ∃ N' : ℕ, 1 / ε < N') with ⟨N', one_div_ε_lt_N'⟩
let N := max N' 5
-- set minimum to 5 to have N ≤ fib N work
exists N
intro n n_ge_N
let g := of v
cases' Decidable.em (g.TerminatedAt n) with terminated_at_n not_terminated_at_n
· have : v = g.convergents n := of_correctness_of_terminatedAt terminated_at_n
have : v - g.convergents n = 0 := sub_eq_zero.mpr this
rw [this]
exact mod_cast ε_pos
· let B := g.denominators n
let nB := g.denominators (n + 1)
have abs_v_sub_conv_le : |v - g.convergents n| ≤ 1 / (B * nB) :=
abs_sub_convergents_le not_terminated_at_n
suffices 1 / (B * nB) < ε from lt_of_le_of_lt abs_v_sub_conv_le this
-- show that `0 < (B * nB)` and then multiply by `B * nB` to get rid of the division
have nB_ineq : (fib (n + 2) : K) ≤ nB :=
haveI : ¬g.TerminatedAt (n + 1 - 1) := not_terminated_at_n
succ_nth_fib_le_of_nth_denom (Or.inr this)
have B_ineq : (fib (n + 1) : K) ≤ B :=
haveI : ¬g.TerminatedAt (n - 1) := mt (terminated_stable n.pred_le) not_terminated_at_n
succ_nth_fib_le_of_nth_denom (Or.inr this)
have zero_lt_B : 0 < B := B_ineq.trans_lt' <| mod_cast fib_pos.2 n.succ_pos
have nB_pos : 0 < nB := nB_ineq.trans_lt' <| mod_cast fib_pos.2 <| succ_pos _
have zero_lt_mul_conts : 0 < B * nB := by positivity
suffices 1 < ε * (B * nB) from (div_lt_iff zero_lt_mul_conts).mpr this
-- use that `N' ≥ n` was obtained from the archimedean property to show the following
calc 1 < ε * (N' : K) := (div_lt_iff' ε_pos).mp one_div_ε_lt_N'
_ ≤ ε * (B * nB) := ?_
-- cancel `ε`
gcongr
calc
(N' : K) ≤ (N : K) := by exact_mod_cast le_max_left _ _
_ ≤ n := by exact_mod_cast n_ge_N
_ ≤ fib n := by exact_mod_cast le_fib_self <| le_trans (le_max_right N' 5) n_ge_N
_ ≤ fib (n + 1) := by exact_mod_cast fib_le_fib_succ
_ ≤ fib (n + 1) * fib (n + 1) := by exact_mod_cast (fib (n + 1)).le_mul_self
_ ≤ fib (n + 1) * fib (n + 2) := by gcongr; exact_mod_cast fib_le_fib_succ
_ ≤ B * nB := by gcongr
#align generalized_continued_fraction.of_convergence_epsilon GeneralizedContinuedFraction.of_convergence_epsilon
| Mathlib/Algebra/ContinuedFractions/Computation/ApproximationCorollaries.lean | 144 | 146 | theorem of_convergence [TopologicalSpace K] [OrderTopology K] :
Filter.Tendsto (of v).convergents Filter.atTop <| 𝓝 v := by |
simpa [LinearOrderedAddCommGroup.tendsto_nhds, abs_sub_comm] using of_convergence_epsilon v
|
/-
Copyright (c) 2018 Ellen Arlt. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Ellen Arlt, Blair Shi, Sean Leather, Mario Carneiro, Johan Commelin
-/
import Mathlib.Data.Matrix.Basic
#align_import data.matrix.block from "leanprover-community/mathlib"@"c060baa79af5ca092c54b8bf04f0f10592f59489"
/-!
# Block Matrices
## Main definitions
* `Matrix.fromBlocks`: build a block matrix out of 4 blocks
* `Matrix.toBlocks₁₁`, `Matrix.toBlocks₁₂`, `Matrix.toBlocks₂₁`, `Matrix.toBlocks₂₂`:
extract each of the four blocks from `Matrix.fromBlocks`.
* `Matrix.blockDiagonal`: block diagonal of equally sized blocks. On square blocks, this is a
ring homomorphisms, `Matrix.blockDiagonalRingHom`.
* `Matrix.blockDiag`: extract the blocks from the diagonal of a block diagonal matrix.
* `Matrix.blockDiagonal'`: block diagonal of unequally sized blocks. On square blocks, this is a
ring homomorphisms, `Matrix.blockDiagonal'RingHom`.
* `Matrix.blockDiag'`: extract the blocks from the diagonal of a block diagonal matrix.
-/
variable {l m n o p q : Type*} {m' n' p' : o → Type*}
variable {R : Type*} {S : Type*} {α : Type*} {β : Type*}
open Matrix
namespace Matrix
theorem dotProduct_block [Fintype m] [Fintype n] [Mul α] [AddCommMonoid α] (v w : Sum m n → α) :
v ⬝ᵥ w = v ∘ Sum.inl ⬝ᵥ w ∘ Sum.inl + v ∘ Sum.inr ⬝ᵥ w ∘ Sum.inr :=
Fintype.sum_sum_type _
#align matrix.dot_product_block Matrix.dotProduct_block
section BlockMatrices
/-- We can form a single large matrix by flattening smaller 'block' matrices of compatible
dimensions. -/
-- @[pp_nodot] -- Porting note: removed
def fromBlocks (A : Matrix n l α) (B : Matrix n m α) (C : Matrix o l α) (D : Matrix o m α) :
Matrix (Sum n o) (Sum l m) α :=
of <| Sum.elim (fun i => Sum.elim (A i) (B i)) fun i => Sum.elim (C i) (D i)
#align matrix.from_blocks Matrix.fromBlocks
@[simp]
theorem fromBlocks_apply₁₁ (A : Matrix n l α) (B : Matrix n m α) (C : Matrix o l α)
(D : Matrix o m α) (i : n) (j : l) : fromBlocks A B C D (Sum.inl i) (Sum.inl j) = A i j :=
rfl
#align matrix.from_blocks_apply₁₁ Matrix.fromBlocks_apply₁₁
@[simp]
theorem fromBlocks_apply₁₂ (A : Matrix n l α) (B : Matrix n m α) (C : Matrix o l α)
(D : Matrix o m α) (i : n) (j : m) : fromBlocks A B C D (Sum.inl i) (Sum.inr j) = B i j :=
rfl
#align matrix.from_blocks_apply₁₂ Matrix.fromBlocks_apply₁₂
@[simp]
theorem fromBlocks_apply₂₁ (A : Matrix n l α) (B : Matrix n m α) (C : Matrix o l α)
(D : Matrix o m α) (i : o) (j : l) : fromBlocks A B C D (Sum.inr i) (Sum.inl j) = C i j :=
rfl
#align matrix.from_blocks_apply₂₁ Matrix.fromBlocks_apply₂₁
@[simp]
theorem fromBlocks_apply₂₂ (A : Matrix n l α) (B : Matrix n m α) (C : Matrix o l α)
(D : Matrix o m α) (i : o) (j : m) : fromBlocks A B C D (Sum.inr i) (Sum.inr j) = D i j :=
rfl
#align matrix.from_blocks_apply₂₂ Matrix.fromBlocks_apply₂₂
/-- Given a matrix whose row and column indexes are sum types, we can extract the corresponding
"top left" submatrix. -/
def toBlocks₁₁ (M : Matrix (Sum n o) (Sum l m) α) : Matrix n l α :=
of fun i j => M (Sum.inl i) (Sum.inl j)
#align matrix.to_blocks₁₁ Matrix.toBlocks₁₁
/-- Given a matrix whose row and column indexes are sum types, we can extract the corresponding
"top right" submatrix. -/
def toBlocks₁₂ (M : Matrix (Sum n o) (Sum l m) α) : Matrix n m α :=
of fun i j => M (Sum.inl i) (Sum.inr j)
#align matrix.to_blocks₁₂ Matrix.toBlocks₁₂
/-- Given a matrix whose row and column indexes are sum types, we can extract the corresponding
"bottom left" submatrix. -/
def toBlocks₂₁ (M : Matrix (Sum n o) (Sum l m) α) : Matrix o l α :=
of fun i j => M (Sum.inr i) (Sum.inl j)
#align matrix.to_blocks₂₁ Matrix.toBlocks₂₁
/-- Given a matrix whose row and column indexes are sum types, we can extract the corresponding
"bottom right" submatrix. -/
def toBlocks₂₂ (M : Matrix (Sum n o) (Sum l m) α) : Matrix o m α :=
of fun i j => M (Sum.inr i) (Sum.inr j)
#align matrix.to_blocks₂₂ Matrix.toBlocks₂₂
theorem fromBlocks_toBlocks (M : Matrix (Sum n o) (Sum l m) α) :
fromBlocks M.toBlocks₁₁ M.toBlocks₁₂ M.toBlocks₂₁ M.toBlocks₂₂ = M := by
ext i j
rcases i with ⟨⟩ <;> rcases j with ⟨⟩ <;> rfl
#align matrix.from_blocks_to_blocks Matrix.fromBlocks_toBlocks
@[simp]
theorem toBlocks_fromBlocks₁₁ (A : Matrix n l α) (B : Matrix n m α) (C : Matrix o l α)
(D : Matrix o m α) : (fromBlocks A B C D).toBlocks₁₁ = A :=
rfl
#align matrix.to_blocks_from_blocks₁₁ Matrix.toBlocks_fromBlocks₁₁
@[simp]
theorem toBlocks_fromBlocks₁₂ (A : Matrix n l α) (B : Matrix n m α) (C : Matrix o l α)
(D : Matrix o m α) : (fromBlocks A B C D).toBlocks₁₂ = B :=
rfl
#align matrix.to_blocks_from_blocks₁₂ Matrix.toBlocks_fromBlocks₁₂
@[simp]
theorem toBlocks_fromBlocks₂₁ (A : Matrix n l α) (B : Matrix n m α) (C : Matrix o l α)
(D : Matrix o m α) : (fromBlocks A B C D).toBlocks₂₁ = C :=
rfl
#align matrix.to_blocks_from_blocks₂₁ Matrix.toBlocks_fromBlocks₂₁
@[simp]
theorem toBlocks_fromBlocks₂₂ (A : Matrix n l α) (B : Matrix n m α) (C : Matrix o l α)
(D : Matrix o m α) : (fromBlocks A B C D).toBlocks₂₂ = D :=
rfl
#align matrix.to_blocks_from_blocks₂₂ Matrix.toBlocks_fromBlocks₂₂
/-- Two block matrices are equal if their blocks are equal. -/
theorem ext_iff_blocks {A B : Matrix (Sum n o) (Sum l m) α} :
A = B ↔
A.toBlocks₁₁ = B.toBlocks₁₁ ∧
A.toBlocks₁₂ = B.toBlocks₁₂ ∧ A.toBlocks₂₁ = B.toBlocks₂₁ ∧ A.toBlocks₂₂ = B.toBlocks₂₂ :=
⟨fun h => h ▸ ⟨rfl, rfl, rfl, rfl⟩, fun ⟨h₁₁, h₁₂, h₂₁, h₂₂⟩ => by
rw [← fromBlocks_toBlocks A, ← fromBlocks_toBlocks B, h₁₁, h₁₂, h₂₁, h₂₂]⟩
#align matrix.ext_iff_blocks Matrix.ext_iff_blocks
@[simp]
theorem fromBlocks_inj {A : Matrix n l α} {B : Matrix n m α} {C : Matrix o l α} {D : Matrix o m α}
{A' : Matrix n l α} {B' : Matrix n m α} {C' : Matrix o l α} {D' : Matrix o m α} :
fromBlocks A B C D = fromBlocks A' B' C' D' ↔ A = A' ∧ B = B' ∧ C = C' ∧ D = D' :=
ext_iff_blocks
#align matrix.from_blocks_inj Matrix.fromBlocks_inj
theorem fromBlocks_map (A : Matrix n l α) (B : Matrix n m α) (C : Matrix o l α) (D : Matrix o m α)
(f : α → β) : (fromBlocks A B C D).map f =
fromBlocks (A.map f) (B.map f) (C.map f) (D.map f) := by
ext i j; rcases i with ⟨⟩ <;> rcases j with ⟨⟩ <;> simp [fromBlocks]
#align matrix.from_blocks_map Matrix.fromBlocks_map
theorem fromBlocks_transpose (A : Matrix n l α) (B : Matrix n m α) (C : Matrix o l α)
(D : Matrix o m α) : (fromBlocks A B C D)ᵀ = fromBlocks Aᵀ Cᵀ Bᵀ Dᵀ := by
ext i j
rcases i with ⟨⟩ <;> rcases j with ⟨⟩ <;> simp [fromBlocks]
#align matrix.from_blocks_transpose Matrix.fromBlocks_transpose
theorem fromBlocks_conjTranspose [Star α] (A : Matrix n l α) (B : Matrix n m α) (C : Matrix o l α)
(D : Matrix o m α) : (fromBlocks A B C D)ᴴ = fromBlocks Aᴴ Cᴴ Bᴴ Dᴴ := by
simp only [conjTranspose, fromBlocks_transpose, fromBlocks_map]
#align matrix.from_blocks_conj_transpose Matrix.fromBlocks_conjTranspose
@[simp]
theorem fromBlocks_submatrix_sum_swap_left (A : Matrix n l α) (B : Matrix n m α) (C : Matrix o l α)
(D : Matrix o m α) (f : p → Sum l m) :
(fromBlocks A B C D).submatrix Sum.swap f = (fromBlocks C D A B).submatrix id f := by
ext i j
cases i <;> dsimp <;> cases f j <;> rfl
#align matrix.from_blocks_submatrix_sum_swap_left Matrix.fromBlocks_submatrix_sum_swap_left
@[simp]
theorem fromBlocks_submatrix_sum_swap_right (A : Matrix n l α) (B : Matrix n m α) (C : Matrix o l α)
(D : Matrix o m α) (f : p → Sum n o) :
(fromBlocks A B C D).submatrix f Sum.swap = (fromBlocks B A D C).submatrix f id := by
ext i j
cases j <;> dsimp <;> cases f i <;> rfl
#align matrix.from_blocks_submatrix_sum_swap_right Matrix.fromBlocks_submatrix_sum_swap_right
theorem fromBlocks_submatrix_sum_swap_sum_swap {l m n o α : Type*} (A : Matrix n l α)
(B : Matrix n m α) (C : Matrix o l α) (D : Matrix o m α) :
(fromBlocks A B C D).submatrix Sum.swap Sum.swap = fromBlocks D C B A := by simp
#align matrix.from_blocks_submatrix_sum_swap_sum_swap Matrix.fromBlocks_submatrix_sum_swap_sum_swap
/-- A 2x2 block matrix is block diagonal if the blocks outside of the diagonal vanish -/
def IsTwoBlockDiagonal [Zero α] (A : Matrix (Sum n o) (Sum l m) α) : Prop :=
toBlocks₁₂ A = 0 ∧ toBlocks₂₁ A = 0
#align matrix.is_two_block_diagonal Matrix.IsTwoBlockDiagonal
/-- Let `p` pick out certain rows and `q` pick out certain columns of a matrix `M`. Then
`toBlock M p q` is the corresponding block matrix. -/
def toBlock (M : Matrix m n α) (p : m → Prop) (q : n → Prop) : Matrix { a // p a } { a // q a } α :=
M.submatrix (↑) (↑)
#align matrix.to_block Matrix.toBlock
@[simp]
theorem toBlock_apply (M : Matrix m n α) (p : m → Prop) (q : n → Prop) (i : { a // p a })
(j : { a // q a }) : toBlock M p q i j = M ↑i ↑j :=
rfl
#align matrix.to_block_apply Matrix.toBlock_apply
/-- Let `p` pick out certain rows and columns of a square matrix `M`. Then
`toSquareBlockProp M p` is the corresponding block matrix. -/
def toSquareBlockProp (M : Matrix m m α) (p : m → Prop) : Matrix { a // p a } { a // p a } α :=
toBlock M _ _
#align matrix.to_square_block_prop Matrix.toSquareBlockProp
theorem toSquareBlockProp_def (M : Matrix m m α) (p : m → Prop) :
-- Porting note: added missing `of`
toSquareBlockProp M p = of (fun i j : { a // p a } => M ↑i ↑j) :=
rfl
#align matrix.to_square_block_prop_def Matrix.toSquareBlockProp_def
/-- Let `b` map rows and columns of a square matrix `M` to blocks. Then
`toSquareBlock M b k` is the block `k` matrix. -/
def toSquareBlock (M : Matrix m m α) (b : m → β) (k : β) :
Matrix { a // b a = k } { a // b a = k } α :=
toSquareBlockProp M _
#align matrix.to_square_block Matrix.toSquareBlock
theorem toSquareBlock_def (M : Matrix m m α) (b : m → β) (k : β) :
-- Porting note: added missing `of`
toSquareBlock M b k = of (fun i j : { a // b a = k } => M ↑i ↑j) :=
rfl
#align matrix.to_square_block_def Matrix.toSquareBlock_def
theorem fromBlocks_smul [SMul R α] (x : R) (A : Matrix n l α) (B : Matrix n m α) (C : Matrix o l α)
(D : Matrix o m α) : x • fromBlocks A B C D = fromBlocks (x • A) (x • B) (x • C) (x • D) := by
ext i j; rcases i with ⟨⟩ <;> rcases j with ⟨⟩ <;> simp [fromBlocks]
#align matrix.from_blocks_smul Matrix.fromBlocks_smul
theorem fromBlocks_neg [Neg R] (A : Matrix n l R) (B : Matrix n m R) (C : Matrix o l R)
(D : Matrix o m R) : -fromBlocks A B C D = fromBlocks (-A) (-B) (-C) (-D) := by
ext i j
cases i <;> cases j <;> simp [fromBlocks]
#align matrix.from_blocks_neg Matrix.fromBlocks_neg
@[simp]
theorem fromBlocks_zero [Zero α] : fromBlocks (0 : Matrix n l α) 0 0 (0 : Matrix o m α) = 0 := by
ext i j
rcases i with ⟨⟩ <;> rcases j with ⟨⟩ <;> rfl
#align matrix.from_blocks_zero Matrix.fromBlocks_zero
theorem fromBlocks_add [Add α] (A : Matrix n l α) (B : Matrix n m α) (C : Matrix o l α)
(D : Matrix o m α) (A' : Matrix n l α) (B' : Matrix n m α) (C' : Matrix o l α)
(D' : Matrix o m α) : fromBlocks A B C D + fromBlocks A' B' C' D' =
fromBlocks (A + A') (B + B') (C + C') (D + D') := by
ext i j; rcases i with ⟨⟩ <;> rcases j with ⟨⟩ <;> rfl
#align matrix.from_blocks_add Matrix.fromBlocks_add
theorem fromBlocks_multiply [Fintype l] [Fintype m] [NonUnitalNonAssocSemiring α] (A : Matrix n l α)
(B : Matrix n m α) (C : Matrix o l α) (D : Matrix o m α) (A' : Matrix l p α) (B' : Matrix l q α)
(C' : Matrix m p α) (D' : Matrix m q α) :
fromBlocks A B C D * fromBlocks A' B' C' D' =
fromBlocks (A * A' + B * C') (A * B' + B * D') (C * A' + D * C') (C * B' + D * D') := by
ext i j
rcases i with ⟨⟩ <;> rcases j with ⟨⟩ <;> simp only [fromBlocks, mul_apply, of_apply,
Sum.elim_inr, Fintype.sum_sum_type, Sum.elim_inl, add_apply]
#align matrix.from_blocks_multiply Matrix.fromBlocks_multiply
theorem fromBlocks_mulVec [Fintype l] [Fintype m] [NonUnitalNonAssocSemiring α] (A : Matrix n l α)
(B : Matrix n m α) (C : Matrix o l α) (D : Matrix o m α) (x : Sum l m → α) :
(fromBlocks A B C D) *ᵥ x =
Sum.elim (A *ᵥ (x ∘ Sum.inl) + B *ᵥ (x ∘ Sum.inr))
(C *ᵥ (x ∘ Sum.inl) + D *ᵥ (x ∘ Sum.inr)) := by
ext i
cases i <;> simp [mulVec, dotProduct]
#align matrix.from_blocks_mul_vec Matrix.fromBlocks_mulVec
theorem vecMul_fromBlocks [Fintype n] [Fintype o] [NonUnitalNonAssocSemiring α] (A : Matrix n l α)
(B : Matrix n m α) (C : Matrix o l α) (D : Matrix o m α) (x : Sum n o → α) :
x ᵥ* fromBlocks A B C D =
Sum.elim ((x ∘ Sum.inl) ᵥ* A + (x ∘ Sum.inr) ᵥ* C)
((x ∘ Sum.inl) ᵥ* B + (x ∘ Sum.inr) ᵥ* D) := by
ext i
cases i <;> simp [vecMul, dotProduct]
#align matrix.vec_mul_from_blocks Matrix.vecMul_fromBlocks
variable [DecidableEq l] [DecidableEq m]
section Zero
variable [Zero α]
theorem toBlock_diagonal_self (d : m → α) (p : m → Prop) :
Matrix.toBlock (diagonal d) p p = diagonal fun i : Subtype p => d ↑i := by
ext i j
by_cases h : i = j
· simp [h]
· simp [One.one, h, Subtype.val_injective.ne h]
#align matrix.to_block_diagonal_self Matrix.toBlock_diagonal_self
theorem toBlock_diagonal_disjoint (d : m → α) {p q : m → Prop} (hpq : Disjoint p q) :
Matrix.toBlock (diagonal d) p q = 0 := by
ext ⟨i, hi⟩ ⟨j, hj⟩
have : i ≠ j := fun heq => hpq.le_bot i ⟨hi, heq.symm ▸ hj⟩
simp [diagonal_apply_ne d this]
#align matrix.to_block_diagonal_disjoint Matrix.toBlock_diagonal_disjoint
@[simp]
theorem fromBlocks_diagonal (d₁ : l → α) (d₂ : m → α) :
fromBlocks (diagonal d₁) 0 0 (diagonal d₂) = diagonal (Sum.elim d₁ d₂) := by
ext i j
rcases i with ⟨⟩ <;> rcases j with ⟨⟩ <;> simp [diagonal]
#align matrix.from_blocks_diagonal Matrix.fromBlocks_diagonal
@[simp]
lemma toBlocks₁₁_diagonal (v : l ⊕ m → α) :
toBlocks₁₁ (diagonal v) = diagonal (fun i => v (Sum.inl i)) := by
unfold toBlocks₁₁
funext i j
simp only [ne_eq, Sum.inl.injEq, of_apply, diagonal_apply]
@[simp]
lemma toBlocks₂₂_diagonal (v : l ⊕ m → α) :
toBlocks₂₂ (diagonal v) = diagonal (fun i => v (Sum.inr i)) := by
unfold toBlocks₂₂
funext i j
simp only [ne_eq, Sum.inr.injEq, of_apply, diagonal_apply]
@[simp]
lemma toBlocks₁₂_diagonal (v : l ⊕ m → α) : toBlocks₁₂ (diagonal v) = 0 := rfl
@[simp]
lemma toBlocks₂₁_diagonal (v : l ⊕ m → α) : toBlocks₂₁ (diagonal v) = 0 := rfl
end Zero
section HasZeroHasOne
variable [Zero α] [One α]
@[simp]
theorem fromBlocks_one : fromBlocks (1 : Matrix l l α) 0 0 (1 : Matrix m m α) = 1 := by
ext i j
rcases i with ⟨⟩ <;> rcases j with ⟨⟩ <;> simp [one_apply]
#align matrix.from_blocks_one Matrix.fromBlocks_one
@[simp]
theorem toBlock_one_self (p : m → Prop) : Matrix.toBlock (1 : Matrix m m α) p p = 1 :=
toBlock_diagonal_self _ p
#align matrix.to_block_one_self Matrix.toBlock_one_self
theorem toBlock_one_disjoint {p q : m → Prop} (hpq : Disjoint p q) :
Matrix.toBlock (1 : Matrix m m α) p q = 0 :=
toBlock_diagonal_disjoint _ hpq
#align matrix.to_block_one_disjoint Matrix.toBlock_one_disjoint
end HasZeroHasOne
end BlockMatrices
section BlockDiagonal
variable [DecidableEq o]
section Zero
variable [Zero α] [Zero β]
/-- `Matrix.blockDiagonal M` turns a homogenously-indexed collection of matrices
`M : o → Matrix m n α'` into an `m × o`-by-`n × o` block matrix which has the entries of `M` along
the diagonal and zero elsewhere.
See also `Matrix.blockDiagonal'` if the matrices may not have the same size everywhere.
-/
def blockDiagonal (M : o → Matrix m n α) : Matrix (m × o) (n × o) α :=
of <| (fun ⟨i, k⟩ ⟨j, k'⟩ => if k = k' then M k i j else 0 : m × o → n × o → α)
#align matrix.block_diagonal Matrix.blockDiagonal
-- TODO: set as an equation lemma for `blockDiagonal`, see mathlib4#3024
theorem blockDiagonal_apply' (M : o → Matrix m n α) (i k j k') :
blockDiagonal M ⟨i, k⟩ ⟨j, k'⟩ = if k = k' then M k i j else 0 :=
rfl
#align matrix.block_diagonal_apply' Matrix.blockDiagonal_apply'
theorem blockDiagonal_apply (M : o → Matrix m n α) (ik jk) :
blockDiagonal M ik jk = if ik.2 = jk.2 then M ik.2 ik.1 jk.1 else 0 := by
cases ik
cases jk
rfl
#align matrix.block_diagonal_apply Matrix.blockDiagonal_apply
@[simp]
theorem blockDiagonal_apply_eq (M : o → Matrix m n α) (i j k) :
blockDiagonal M (i, k) (j, k) = M k i j :=
if_pos rfl
#align matrix.block_diagonal_apply_eq Matrix.blockDiagonal_apply_eq
theorem blockDiagonal_apply_ne (M : o → Matrix m n α) (i j) {k k'} (h : k ≠ k') :
blockDiagonal M (i, k) (j, k') = 0 :=
if_neg h
#align matrix.block_diagonal_apply_ne Matrix.blockDiagonal_apply_ne
theorem blockDiagonal_map (M : o → Matrix m n α) (f : α → β) (hf : f 0 = 0) :
(blockDiagonal M).map f = blockDiagonal fun k => (M k).map f := by
ext
simp only [map_apply, blockDiagonal_apply, eq_comm]
rw [apply_ite f, hf]
#align matrix.block_diagonal_map Matrix.blockDiagonal_map
@[simp]
theorem blockDiagonal_transpose (M : o → Matrix m n α) :
(blockDiagonal M)ᵀ = blockDiagonal fun k => (M k)ᵀ := by
ext
simp only [transpose_apply, blockDiagonal_apply, eq_comm]
split_ifs with h
· rw [h]
· rfl
#align matrix.block_diagonal_transpose Matrix.blockDiagonal_transpose
@[simp]
theorem blockDiagonal_conjTranspose {α : Type*} [AddMonoid α] [StarAddMonoid α]
(M : o → Matrix m n α) : (blockDiagonal M)ᴴ = blockDiagonal fun k => (M k)ᴴ := by
simp only [conjTranspose, blockDiagonal_transpose]
rw [blockDiagonal_map _ star (star_zero α)]
#align matrix.block_diagonal_conj_transpose Matrix.blockDiagonal_conjTranspose
@[simp]
theorem blockDiagonal_zero : blockDiagonal (0 : o → Matrix m n α) = 0 := by
ext
simp [blockDiagonal_apply]
#align matrix.block_diagonal_zero Matrix.blockDiagonal_zero
@[simp]
theorem blockDiagonal_diagonal [DecidableEq m] (d : o → m → α) :
(blockDiagonal fun k => diagonal (d k)) = diagonal fun ik => d ik.2 ik.1 := by
ext ⟨i, k⟩ ⟨j, k'⟩
simp only [blockDiagonal_apply, diagonal_apply, Prod.mk.inj_iff, ← ite_and]
congr 1
rw [and_comm]
#align matrix.block_diagonal_diagonal Matrix.blockDiagonal_diagonal
@[simp]
theorem blockDiagonal_one [DecidableEq m] [One α] : blockDiagonal (1 : o → Matrix m m α) = 1 :=
show (blockDiagonal fun _ : o => diagonal fun _ : m => (1 : α)) = diagonal fun _ => 1 by
rw [blockDiagonal_diagonal]
#align matrix.block_diagonal_one Matrix.blockDiagonal_one
end Zero
@[simp]
theorem blockDiagonal_add [AddZeroClass α] (M N : o → Matrix m n α) :
blockDiagonal (M + N) = blockDiagonal M + blockDiagonal N := by
ext
simp only [blockDiagonal_apply, Pi.add_apply, add_apply]
split_ifs <;> simp
#align matrix.block_diagonal_add Matrix.blockDiagonal_add
section
variable (o m n α)
/-- `Matrix.blockDiagonal` as an `AddMonoidHom`. -/
@[simps]
def blockDiagonalAddMonoidHom [AddZeroClass α] :
(o → Matrix m n α) →+ Matrix (m × o) (n × o) α where
toFun := blockDiagonal
map_zero' := blockDiagonal_zero
map_add' := blockDiagonal_add
#align matrix.block_diagonal_add_monoid_hom Matrix.blockDiagonalAddMonoidHom
end
@[simp]
theorem blockDiagonal_neg [AddGroup α] (M : o → Matrix m n α) :
blockDiagonal (-M) = -blockDiagonal M :=
map_neg (blockDiagonalAddMonoidHom m n o α) M
#align matrix.block_diagonal_neg Matrix.blockDiagonal_neg
@[simp]
theorem blockDiagonal_sub [AddGroup α] (M N : o → Matrix m n α) :
blockDiagonal (M - N) = blockDiagonal M - blockDiagonal N :=
map_sub (blockDiagonalAddMonoidHom m n o α) M N
#align matrix.block_diagonal_sub Matrix.blockDiagonal_sub
@[simp]
theorem blockDiagonal_mul [Fintype n] [Fintype o] [NonUnitalNonAssocSemiring α]
(M : o → Matrix m n α) (N : o → Matrix n p α) :
(blockDiagonal fun k => M k * N k) = blockDiagonal M * blockDiagonal N := by
ext ⟨i, k⟩ ⟨j, k'⟩
simp only [blockDiagonal_apply, mul_apply, ← Finset.univ_product_univ, Finset.sum_product]
split_ifs with h <;> simp [h]
#align matrix.block_diagonal_mul Matrix.blockDiagonal_mul
section
variable (α m o)
/-- `Matrix.blockDiagonal` as a `RingHom`. -/
@[simps]
def blockDiagonalRingHom [DecidableEq m] [Fintype o] [Fintype m] [NonAssocSemiring α] :
(o → Matrix m m α) →+* Matrix (m × o) (m × o) α :=
{ blockDiagonalAddMonoidHom m m o α with
toFun := blockDiagonal
map_one' := blockDiagonal_one
map_mul' := blockDiagonal_mul }
#align matrix.block_diagonal_ring_hom Matrix.blockDiagonalRingHom
end
@[simp]
theorem blockDiagonal_pow [DecidableEq m] [Fintype o] [Fintype m] [Semiring α]
(M : o → Matrix m m α) (n : ℕ) : blockDiagonal (M ^ n) = blockDiagonal M ^ n :=
map_pow (blockDiagonalRingHom m o α) M n
#align matrix.block_diagonal_pow Matrix.blockDiagonal_pow
@[simp]
theorem blockDiagonal_smul {R : Type*} [Monoid R] [AddMonoid α] [DistribMulAction R α] (x : R)
(M : o → Matrix m n α) : blockDiagonal (x • M) = x • blockDiagonal M := by
ext
simp only [blockDiagonal_apply, Pi.smul_apply, smul_apply]
split_ifs <;> simp
#align matrix.block_diagonal_smul Matrix.blockDiagonal_smul
end BlockDiagonal
section BlockDiag
/-- Extract a block from the diagonal of a block diagonal matrix.
This is the block form of `Matrix.diag`, and the left-inverse of `Matrix.blockDiagonal`. -/
def blockDiag (M : Matrix (m × o) (n × o) α) (k : o) : Matrix m n α :=
of fun i j => M (i, k) (j, k)
#align matrix.block_diag Matrix.blockDiag
-- TODO: set as an equation lemma for `blockDiag`, see mathlib4#3024
theorem blockDiag_apply (M : Matrix (m × o) (n × o) α) (k : o) (i j) :
blockDiag M k i j = M (i, k) (j, k) :=
rfl
#align matrix.block_diag_apply Matrix.blockDiag_apply
theorem blockDiag_map (M : Matrix (m × o) (n × o) α) (f : α → β) :
blockDiag (M.map f) = fun k => (blockDiag M k).map f :=
rfl
#align matrix.block_diag_map Matrix.blockDiag_map
@[simp]
theorem blockDiag_transpose (M : Matrix (m × o) (n × o) α) (k : o) :
blockDiag Mᵀ k = (blockDiag M k)ᵀ :=
ext fun _ _ => rfl
#align matrix.block_diag_transpose Matrix.blockDiag_transpose
@[simp]
theorem blockDiag_conjTranspose {α : Type*} [AddMonoid α] [StarAddMonoid α]
(M : Matrix (m × o) (n × o) α) (k : o) : blockDiag Mᴴ k = (blockDiag M k)ᴴ :=
ext fun _ _ => rfl
#align matrix.block_diag_conj_transpose Matrix.blockDiag_conjTranspose
section Zero
variable [Zero α] [Zero β]
@[simp]
theorem blockDiag_zero : blockDiag (0 : Matrix (m × o) (n × o) α) = 0 :=
rfl
#align matrix.block_diag_zero Matrix.blockDiag_zero
@[simp]
theorem blockDiag_diagonal [DecidableEq o] [DecidableEq m] (d : m × o → α) (k : o) :
blockDiag (diagonal d) k = diagonal fun i => d (i, k) :=
ext fun i j => by
obtain rfl | hij := Decidable.eq_or_ne i j
· rw [blockDiag_apply, diagonal_apply_eq, diagonal_apply_eq]
· rw [blockDiag_apply, diagonal_apply_ne _ hij, diagonal_apply_ne _ (mt _ hij)]
exact Prod.fst_eq_iff.mpr
#align matrix.block_diag_diagonal Matrix.blockDiag_diagonal
@[simp]
theorem blockDiag_blockDiagonal [DecidableEq o] (M : o → Matrix m n α) :
blockDiag (blockDiagonal M) = M :=
funext fun _ => ext fun i j => blockDiagonal_apply_eq M i j _
#align matrix.block_diag_block_diagonal Matrix.blockDiag_blockDiagonal
theorem blockDiagonal_injective [DecidableEq o] :
Function.Injective (blockDiagonal : (o → Matrix m n α) → Matrix _ _ α) :=
Function.LeftInverse.injective blockDiag_blockDiagonal
#align matrix.block_diagonal_injective Matrix.blockDiagonal_injective
@[simp]
theorem blockDiagonal_inj [DecidableEq o] {M N : o → Matrix m n α} :
blockDiagonal M = blockDiagonal N ↔ M = N :=
blockDiagonal_injective.eq_iff
#align matrix.block_diagonal_inj Matrix.blockDiagonal_inj
@[simp]
theorem blockDiag_one [DecidableEq o] [DecidableEq m] [One α] :
blockDiag (1 : Matrix (m × o) (m × o) α) = 1 :=
funext <| blockDiag_diagonal _
#align matrix.block_diag_one Matrix.blockDiag_one
end Zero
@[simp]
theorem blockDiag_add [AddZeroClass α] (M N : Matrix (m × o) (n × o) α) :
blockDiag (M + N) = blockDiag M + blockDiag N :=
rfl
#align matrix.block_diag_add Matrix.blockDiag_add
section
variable (o m n α)
/-- `Matrix.blockDiag` as an `AddMonoidHom`. -/
@[simps]
def blockDiagAddMonoidHom [AddZeroClass α] : Matrix (m × o) (n × o) α →+ o → Matrix m n α where
toFun := blockDiag
map_zero' := blockDiag_zero
map_add' := blockDiag_add
#align matrix.block_diag_add_monoid_hom Matrix.blockDiagAddMonoidHom
end
@[simp]
theorem blockDiag_neg [AddGroup α] (M : Matrix (m × o) (n × o) α) : blockDiag (-M) = -blockDiag M :=
map_neg (blockDiagAddMonoidHom m n o α) M
#align matrix.block_diag_neg Matrix.blockDiag_neg
@[simp]
theorem blockDiag_sub [AddGroup α] (M N : Matrix (m × o) (n × o) α) :
blockDiag (M - N) = blockDiag M - blockDiag N :=
map_sub (blockDiagAddMonoidHom m n o α) M N
#align matrix.block_diag_sub Matrix.blockDiag_sub
@[simp]
theorem blockDiag_smul {R : Type*} [Monoid R] [AddMonoid α] [DistribMulAction R α] (x : R)
(M : Matrix (m × o) (n × o) α) : blockDiag (x • M) = x • blockDiag M :=
rfl
#align matrix.block_diag_smul Matrix.blockDiag_smul
end BlockDiag
section BlockDiagonal'
variable [DecidableEq o]
section Zero
variable [Zero α] [Zero β]
/-- `Matrix.blockDiagonal' M` turns `M : Π i, Matrix (m i) (n i) α` into a
`Σ i, m i`-by-`Σ i, n i` block matrix which has the entries of `M` along the diagonal
and zero elsewhere.
This is the dependently-typed version of `Matrix.blockDiagonal`. -/
def blockDiagonal' (M : ∀ i, Matrix (m' i) (n' i) α) : Matrix (Σi, m' i) (Σi, n' i) α :=
of <|
(fun ⟨k, i⟩ ⟨k', j⟩ => if h : k = k' then M k i (cast (congr_arg n' h.symm) j) else 0 :
(Σi, m' i) → (Σi, n' i) → α)
#align matrix.block_diagonal' Matrix.blockDiagonal'
-- TODO: set as an equation lemma for `blockDiagonal'`, see mathlib4#3024
theorem blockDiagonal'_apply' (M : ∀ i, Matrix (m' i) (n' i) α) (k i k' j) :
blockDiagonal' M ⟨k, i⟩ ⟨k', j⟩ =
if h : k = k' then M k i (cast (congr_arg n' h.symm) j) else 0 :=
rfl
#align matrix.block_diagonal'_apply' Matrix.blockDiagonal'_apply'
theorem blockDiagonal'_eq_blockDiagonal (M : o → Matrix m n α) {k k'} (i j) :
blockDiagonal M (i, k) (j, k') = blockDiagonal' M ⟨k, i⟩ ⟨k', j⟩ :=
rfl
#align matrix.block_diagonal'_eq_block_diagonal Matrix.blockDiagonal'_eq_blockDiagonal
theorem blockDiagonal'_submatrix_eq_blockDiagonal (M : o → Matrix m n α) :
(blockDiagonal' M).submatrix (Prod.toSigma ∘ Prod.swap) (Prod.toSigma ∘ Prod.swap) =
blockDiagonal M :=
Matrix.ext fun ⟨_, _⟩ ⟨_, _⟩ => rfl
#align matrix.block_diagonal'_submatrix_eq_block_diagonal Matrix.blockDiagonal'_submatrix_eq_blockDiagonal
theorem blockDiagonal'_apply (M : ∀ i, Matrix (m' i) (n' i) α) (ik jk) :
blockDiagonal' M ik jk =
if h : ik.1 = jk.1 then M ik.1 ik.2 (cast (congr_arg n' h.symm) jk.2) else 0 := by
cases ik
cases jk
rfl
#align matrix.block_diagonal'_apply Matrix.blockDiagonal'_apply
@[simp]
theorem blockDiagonal'_apply_eq (M : ∀ i, Matrix (m' i) (n' i) α) (k i j) :
blockDiagonal' M ⟨k, i⟩ ⟨k, j⟩ = M k i j :=
dif_pos rfl
#align matrix.block_diagonal'_apply_eq Matrix.blockDiagonal'_apply_eq
theorem blockDiagonal'_apply_ne (M : ∀ i, Matrix (m' i) (n' i) α) {k k'} (i j) (h : k ≠ k') :
blockDiagonal' M ⟨k, i⟩ ⟨k', j⟩ = 0 :=
dif_neg h
#align matrix.block_diagonal'_apply_ne Matrix.blockDiagonal'_apply_ne
theorem blockDiagonal'_map (M : ∀ i, Matrix (m' i) (n' i) α) (f : α → β) (hf : f 0 = 0) :
(blockDiagonal' M).map f = blockDiagonal' fun k => (M k).map f := by
ext
simp only [map_apply, blockDiagonal'_apply, eq_comm]
rw [apply_dite f, hf]
#align matrix.block_diagonal'_map Matrix.blockDiagonal'_map
@[simp]
| Mathlib/Data/Matrix/Block.lean | 693 | 701 | theorem blockDiagonal'_transpose (M : ∀ i, Matrix (m' i) (n' i) α) :
(blockDiagonal' M)ᵀ = blockDiagonal' fun k => (M k)ᵀ := by |
ext ⟨ii, ix⟩ ⟨ji, jx⟩
simp only [transpose_apply, blockDiagonal'_apply]
split_ifs with h -- Porting note: was split_ifs <;> cc
· subst h; rfl
· simp_all only [not_true]
· simp_all only [not_true]
· rfl
|
/-
Copyright (c) 2022 Kexing Ying. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kexing Ying, Rémy Degenne
-/
import Mathlib.Probability.Process.Stopping
import Mathlib.Tactic.AdaptationNote
#align_import probability.process.hitting_time from "leanprover-community/mathlib"@"f2ce6086713c78a7f880485f7917ea547a215982"
/-!
# Hitting time
Given a stochastic process, the hitting time provides the first time the process "hits" some
subset of the state space. The hitting time is a stopping time in the case that the time index is
discrete and the process is adapted (this is true in a far more general setting however we have
only proved it for the discrete case so far).
## Main definition
* `MeasureTheory.hitting`: the hitting time of a stochastic process
## Main results
* `MeasureTheory.hitting_isStoppingTime`: a discrete hitting time of an adapted process is a
stopping time
## Implementation notes
In the definition of the hitting time, we bound the hitting time by an upper and lower bound.
This is to ensure that our result is meaningful in the case we are taking the infimum of an
empty set or the infimum of a set which is unbounded from below. With this, we can talk about
hitting times indexed by the natural numbers or the reals. By taking the bounds to be
`⊤` and `⊥`, we obtain the standard definition in the case that the index is `ℕ∞` or `ℝ≥0∞`.
-/
open Filter Order TopologicalSpace
open scoped Classical MeasureTheory NNReal ENNReal Topology
namespace MeasureTheory
variable {Ω β ι : Type*} {m : MeasurableSpace Ω}
/-- Hitting time: given a stochastic process `u` and a set `s`, `hitting u s n m` is the first time
`u` is in `s` after time `n` and before time `m` (if `u` does not hit `s` after time `n` and
before `m` then the hitting time is simply `m`).
The hitting time is a stopping time if the process is adapted and discrete. -/
noncomputable def hitting [Preorder ι] [InfSet ι] (u : ι → Ω → β) (s : Set β) (n m : ι) : Ω → ι :=
fun x => if ∃ j ∈ Set.Icc n m, u j x ∈ s then sInf (Set.Icc n m ∩ {i : ι | u i x ∈ s}) else m
#align measure_theory.hitting MeasureTheory.hitting
#adaptation_note /-- nightly-2024-03-16: added to replace simp [hitting] -/
theorem hitting_def [Preorder ι] [InfSet ι] (u : ι → Ω → β) (s : Set β) (n m : ι) :
hitting u s n m =
fun x => if ∃ j ∈ Set.Icc n m, u j x ∈ s then sInf (Set.Icc n m ∩ {i : ι | u i x ∈ s}) else m :=
rfl
section Inequalities
variable [ConditionallyCompleteLinearOrder ι] {u : ι → Ω → β} {s : Set β} {n i : ι} {ω : Ω}
/-- This lemma is strictly weaker than `hitting_of_le`. -/
theorem hitting_of_lt {m : ι} (h : m < n) : hitting u s n m ω = m := by
simp_rw [hitting]
have h_not : ¬∃ (j : ι) (_ : j ∈ Set.Icc n m), u j ω ∈ s := by
push_neg
intro j
rw [Set.Icc_eq_empty_of_lt h]
simp only [Set.mem_empty_iff_false, IsEmpty.forall_iff]
simp only [exists_prop] at h_not
simp only [h_not, if_false]
#align measure_theory.hitting_of_lt MeasureTheory.hitting_of_lt
theorem hitting_le {m : ι} (ω : Ω) : hitting u s n m ω ≤ m := by
simp only [hitting]
split_ifs with h
· obtain ⟨j, hj₁, hj₂⟩ := h
change j ∈ {i | u i ω ∈ s} at hj₂
exact (csInf_le (BddBelow.inter_of_left bddBelow_Icc) (Set.mem_inter hj₁ hj₂)).trans hj₁.2
· exact le_rfl
#align measure_theory.hitting_le MeasureTheory.hitting_le
theorem not_mem_of_lt_hitting {m k : ι} (hk₁ : k < hitting u s n m ω) (hk₂ : n ≤ k) :
u k ω ∉ s := by
classical
intro h
have hexists : ∃ j ∈ Set.Icc n m, u j ω ∈ s := ⟨k, ⟨hk₂, le_trans hk₁.le <| hitting_le _⟩, h⟩
refine not_le.2 hk₁ ?_
simp_rw [hitting, if_pos hexists]
exact csInf_le bddBelow_Icc.inter_of_left ⟨⟨hk₂, le_trans hk₁.le <| hitting_le _⟩, h⟩
#align measure_theory.not_mem_of_lt_hitting MeasureTheory.not_mem_of_lt_hitting
theorem hitting_eq_end_iff {m : ι} : hitting u s n m ω = m ↔
(∃ j ∈ Set.Icc n m, u j ω ∈ s) → sInf (Set.Icc n m ∩ {i : ι | u i ω ∈ s}) = m := by
rw [hitting, ite_eq_right_iff]
#align measure_theory.hitting_eq_end_iff MeasureTheory.hitting_eq_end_iff
theorem hitting_of_le {m : ι} (hmn : m ≤ n) : hitting u s n m ω = m := by
obtain rfl | h := le_iff_eq_or_lt.1 hmn
· rw [hitting, ite_eq_right_iff, forall_exists_index]
conv => intro; rw [Set.mem_Icc, Set.Icc_self, and_imp, and_imp]
intro i hi₁ hi₂ hi
rw [Set.inter_eq_left.2, csInf_singleton]
exact Set.singleton_subset_iff.2 (le_antisymm hi₂ hi₁ ▸ hi)
· exact hitting_of_lt h
#align measure_theory.hitting_of_le MeasureTheory.hitting_of_le
theorem le_hitting {m : ι} (hnm : n ≤ m) (ω : Ω) : n ≤ hitting u s n m ω := by
simp only [hitting]
split_ifs with h
· refine le_csInf ?_ fun b hb => ?_
· obtain ⟨k, hk_Icc, hk_s⟩ := h
exact ⟨k, hk_Icc, hk_s⟩
· rw [Set.mem_inter_iff] at hb
exact hb.1.1
· exact hnm
#align measure_theory.le_hitting MeasureTheory.le_hitting
theorem le_hitting_of_exists {m : ι} (h_exists : ∃ j ∈ Set.Icc n m, u j ω ∈ s) :
n ≤ hitting u s n m ω := by
refine le_hitting ?_ ω
by_contra h
rw [Set.Icc_eq_empty_of_lt (not_le.mp h)] at h_exists
simp at h_exists
#align measure_theory.le_hitting_of_exists MeasureTheory.le_hitting_of_exists
theorem hitting_mem_Icc {m : ι} (hnm : n ≤ m) (ω : Ω) : hitting u s n m ω ∈ Set.Icc n m :=
⟨le_hitting hnm ω, hitting_le ω⟩
#align measure_theory.hitting_mem_Icc MeasureTheory.hitting_mem_Icc
theorem hitting_mem_set [IsWellOrder ι (· < ·)] {m : ι} (h_exists : ∃ j ∈ Set.Icc n m, u j ω ∈ s) :
u (hitting u s n m ω) ω ∈ s := by
simp_rw [hitting, if_pos h_exists]
have h_nonempty : (Set.Icc n m ∩ {i : ι | u i ω ∈ s}).Nonempty := by
obtain ⟨k, hk₁, hk₂⟩ := h_exists
exact ⟨k, Set.mem_inter hk₁ hk₂⟩
have h_mem := csInf_mem h_nonempty
rw [Set.mem_inter_iff] at h_mem
exact h_mem.2
#align measure_theory.hitting_mem_set MeasureTheory.hitting_mem_set
theorem hitting_mem_set_of_hitting_lt [IsWellOrder ι (· < ·)] {m : ι} (hl : hitting u s n m ω < m) :
u (hitting u s n m ω) ω ∈ s := by
by_cases h : ∃ j ∈ Set.Icc n m, u j ω ∈ s
· exact hitting_mem_set h
· simp_rw [hitting, if_neg h] at hl
exact False.elim (hl.ne rfl)
#align measure_theory.hitting_mem_set_of_hitting_lt MeasureTheory.hitting_mem_set_of_hitting_lt
theorem hitting_le_of_mem {m : ι} (hin : n ≤ i) (him : i ≤ m) (his : u i ω ∈ s) :
hitting u s n m ω ≤ i := by
have h_exists : ∃ k ∈ Set.Icc n m, u k ω ∈ s := ⟨i, ⟨hin, him⟩, his⟩
simp_rw [hitting, if_pos h_exists]
exact csInf_le (BddBelow.inter_of_left bddBelow_Icc) (Set.mem_inter ⟨hin, him⟩ his)
#align measure_theory.hitting_le_of_mem MeasureTheory.hitting_le_of_mem
theorem hitting_le_iff_of_exists [IsWellOrder ι (· < ·)] {m : ι}
(h_exists : ∃ j ∈ Set.Icc n m, u j ω ∈ s) :
hitting u s n m ω ≤ i ↔ ∃ j ∈ Set.Icc n i, u j ω ∈ s := by
constructor <;> intro h'
· exact ⟨hitting u s n m ω, ⟨le_hitting_of_exists h_exists, h'⟩, hitting_mem_set h_exists⟩
· have h'' : ∃ k ∈ Set.Icc n (min m i), u k ω ∈ s := by
obtain ⟨k₁, hk₁_mem, hk₁_s⟩ := h_exists
obtain ⟨k₂, hk₂_mem, hk₂_s⟩ := h'
refine ⟨min k₁ k₂, ⟨le_min hk₁_mem.1 hk₂_mem.1, min_le_min hk₁_mem.2 hk₂_mem.2⟩, ?_⟩
exact min_rec' (fun j => u j ω ∈ s) hk₁_s hk₂_s
obtain ⟨k, hk₁, hk₂⟩ := h''
refine le_trans ?_ (hk₁.2.trans (min_le_right _ _))
exact hitting_le_of_mem hk₁.1 (hk₁.2.trans (min_le_left _ _)) hk₂
#align measure_theory.hitting_le_iff_of_exists MeasureTheory.hitting_le_iff_of_exists
theorem hitting_le_iff_of_lt [IsWellOrder ι (· < ·)] {m : ι} (i : ι) (hi : i < m) :
hitting u s n m ω ≤ i ↔ ∃ j ∈ Set.Icc n i, u j ω ∈ s := by
by_cases h_exists : ∃ j ∈ Set.Icc n m, u j ω ∈ s
· rw [hitting_le_iff_of_exists h_exists]
· simp_rw [hitting, if_neg h_exists]
push_neg at h_exists
simp only [not_le.mpr hi, Set.mem_Icc, false_iff_iff, not_exists, not_and, and_imp]
exact fun k hkn hki => h_exists k ⟨hkn, hki.trans hi.le⟩
#align measure_theory.hitting_le_iff_of_lt MeasureTheory.hitting_le_iff_of_lt
theorem hitting_lt_iff [IsWellOrder ι (· < ·)] {m : ι} (i : ι) (hi : i ≤ m) :
hitting u s n m ω < i ↔ ∃ j ∈ Set.Ico n i, u j ω ∈ s := by
constructor <;> intro h'
· have h : ∃ j ∈ Set.Icc n m, u j ω ∈ s := by
by_contra h
simp_rw [hitting, if_neg h, ← not_le] at h'
exact h' hi
exact ⟨hitting u s n m ω, ⟨le_hitting_of_exists h, h'⟩, hitting_mem_set h⟩
· obtain ⟨k, hk₁, hk₂⟩ := h'
refine lt_of_le_of_lt ?_ hk₁.2
exact hitting_le_of_mem hk₁.1 (hk₁.2.le.trans hi) hk₂
#align measure_theory.hitting_lt_iff MeasureTheory.hitting_lt_iff
theorem hitting_eq_hitting_of_exists {m₁ m₂ : ι} (h : m₁ ≤ m₂)
(h' : ∃ j ∈ Set.Icc n m₁, u j ω ∈ s) : hitting u s n m₁ ω = hitting u s n m₂ ω := by
simp only [hitting, if_pos h']
obtain ⟨j, hj₁, hj₂⟩ := h'
rw [if_pos]
· refine le_antisymm ?_ (csInf_le_csInf bddBelow_Icc.inter_of_left ⟨j, hj₁, hj₂⟩
(Set.inter_subset_inter_left _ (Set.Icc_subset_Icc_right h)))
refine le_csInf ⟨j, Set.Icc_subset_Icc_right h hj₁, hj₂⟩ fun i hi => ?_
by_cases hi' : i ≤ m₁
· exact csInf_le bddBelow_Icc.inter_of_left ⟨⟨hi.1.1, hi'⟩, hi.2⟩
· change j ∈ {i | u i ω ∈ s} at hj₂
exact ((csInf_le bddBelow_Icc.inter_of_left ⟨hj₁, hj₂⟩).trans (hj₁.2.trans le_rfl)).trans
(le_of_lt (not_le.1 hi'))
exact ⟨j, ⟨hj₁.1, hj₁.2.trans h⟩, hj₂⟩
#align measure_theory.hitting_eq_hitting_of_exists MeasureTheory.hitting_eq_hitting_of_exists
| Mathlib/Probability/Process/HittingTime.lean | 215 | 225 | theorem hitting_mono {m₁ m₂ : ι} (hm : m₁ ≤ m₂) : hitting u s n m₁ ω ≤ hitting u s n m₂ ω := by |
by_cases h : ∃ j ∈ Set.Icc n m₁, u j ω ∈ s
· exact (hitting_eq_hitting_of_exists hm h).le
· simp_rw [hitting, if_neg h]
split_ifs with h'
· obtain ⟨j, hj₁, hj₂⟩ := h'
refine le_csInf ⟨j, hj₁, hj₂⟩ ?_
by_contra hneg; push_neg at hneg
obtain ⟨i, hi₁, hi₂⟩ := hneg
exact h ⟨i, ⟨hi₁.1.1, hi₂.le⟩, hi₁.2⟩
· exact hm
|
/-
Copyright (c) 2022 Joseph Myers. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joseph Myers
-/
import Mathlib.Analysis.Convex.Between
import Mathlib.Analysis.Convex.Normed
import Mathlib.Analysis.Normed.Group.AddTorsor
#align_import analysis.convex.side from "leanprover-community/mathlib"@"a63928c34ec358b5edcda2bf7513c50052a5230f"
/-!
# Sides of affine subspaces
This file defines notions of two points being on the same or opposite sides of an affine subspace.
## Main definitions
* `s.WSameSide x y`: The points `x` and `y` are weakly on the same side of the affine
subspace `s`.
* `s.SSameSide x y`: The points `x` and `y` are strictly on the same side of the affine
subspace `s`.
* `s.WOppSide x y`: The points `x` and `y` are weakly on opposite sides of the affine
subspace `s`.
* `s.SOppSide x y`: The points `x` and `y` are strictly on opposite sides of the affine
subspace `s`.
-/
variable {R V V' P P' : Type*}
open AffineEquiv AffineMap
namespace AffineSubspace
section StrictOrderedCommRing
variable [StrictOrderedCommRing R] [AddCommGroup V] [Module R V] [AddTorsor V P]
variable [AddCommGroup V'] [Module R V'] [AddTorsor V' P']
/-- The points `x` and `y` are weakly on the same side of `s`. -/
def WSameSide (s : AffineSubspace R P) (x y : P) : Prop :=
∃ᵉ (p₁ ∈ s) (p₂ ∈ s), SameRay R (x -ᵥ p₁) (y -ᵥ p₂)
#align affine_subspace.w_same_side AffineSubspace.WSameSide
/-- The points `x` and `y` are strictly on the same side of `s`. -/
def SSameSide (s : AffineSubspace R P) (x y : P) : Prop :=
s.WSameSide x y ∧ x ∉ s ∧ y ∉ s
#align affine_subspace.s_same_side AffineSubspace.SSameSide
/-- The points `x` and `y` are weakly on opposite sides of `s`. -/
def WOppSide (s : AffineSubspace R P) (x y : P) : Prop :=
∃ᵉ (p₁ ∈ s) (p₂ ∈ s), SameRay R (x -ᵥ p₁) (p₂ -ᵥ y)
#align affine_subspace.w_opp_side AffineSubspace.WOppSide
/-- The points `x` and `y` are strictly on opposite sides of `s`. -/
def SOppSide (s : AffineSubspace R P) (x y : P) : Prop :=
s.WOppSide x y ∧ x ∉ s ∧ y ∉ s
#align affine_subspace.s_opp_side AffineSubspace.SOppSide
theorem WSameSide.map {s : AffineSubspace R P} {x y : P} (h : s.WSameSide x y) (f : P →ᵃ[R] P') :
(s.map f).WSameSide (f x) (f y) := by
rcases h with ⟨p₁, hp₁, p₂, hp₂, h⟩
refine ⟨f p₁, mem_map_of_mem f hp₁, f p₂, mem_map_of_mem f hp₂, ?_⟩
simp_rw [← linearMap_vsub]
exact h.map f.linear
#align affine_subspace.w_same_side.map AffineSubspace.WSameSide.map
theorem _root_.Function.Injective.wSameSide_map_iff {s : AffineSubspace R P} {x y : P}
{f : P →ᵃ[R] P'} (hf : Function.Injective f) :
(s.map f).WSameSide (f x) (f y) ↔ s.WSameSide x y := by
refine ⟨fun h => ?_, fun h => h.map _⟩
rcases h with ⟨fp₁, hfp₁, fp₂, hfp₂, h⟩
rw [mem_map] at hfp₁ hfp₂
rcases hfp₁ with ⟨p₁, hp₁, rfl⟩
rcases hfp₂ with ⟨p₂, hp₂, rfl⟩
refine ⟨p₁, hp₁, p₂, hp₂, ?_⟩
simp_rw [← linearMap_vsub, (f.linear_injective_iff.2 hf).sameRay_map_iff] at h
exact h
#align function.injective.w_same_side_map_iff Function.Injective.wSameSide_map_iff
theorem _root_.Function.Injective.sSameSide_map_iff {s : AffineSubspace R P} {x y : P}
{f : P →ᵃ[R] P'} (hf : Function.Injective f) :
(s.map f).SSameSide (f x) (f y) ↔ s.SSameSide x y := by
simp_rw [SSameSide, hf.wSameSide_map_iff, mem_map_iff_mem_of_injective hf]
#align function.injective.s_same_side_map_iff Function.Injective.sSameSide_map_iff
@[simp]
theorem _root_.AffineEquiv.wSameSide_map_iff {s : AffineSubspace R P} {x y : P} (f : P ≃ᵃ[R] P') :
(s.map ↑f).WSameSide (f x) (f y) ↔ s.WSameSide x y :=
(show Function.Injective f.toAffineMap from f.injective).wSameSide_map_iff
#align affine_equiv.w_same_side_map_iff AffineEquiv.wSameSide_map_iff
@[simp]
theorem _root_.AffineEquiv.sSameSide_map_iff {s : AffineSubspace R P} {x y : P} (f : P ≃ᵃ[R] P') :
(s.map ↑f).SSameSide (f x) (f y) ↔ s.SSameSide x y :=
(show Function.Injective f.toAffineMap from f.injective).sSameSide_map_iff
#align affine_equiv.s_same_side_map_iff AffineEquiv.sSameSide_map_iff
theorem WOppSide.map {s : AffineSubspace R P} {x y : P} (h : s.WOppSide x y) (f : P →ᵃ[R] P') :
(s.map f).WOppSide (f x) (f y) := by
rcases h with ⟨p₁, hp₁, p₂, hp₂, h⟩
refine ⟨f p₁, mem_map_of_mem f hp₁, f p₂, mem_map_of_mem f hp₂, ?_⟩
simp_rw [← linearMap_vsub]
exact h.map f.linear
#align affine_subspace.w_opp_side.map AffineSubspace.WOppSide.map
theorem _root_.Function.Injective.wOppSide_map_iff {s : AffineSubspace R P} {x y : P}
{f : P →ᵃ[R] P'} (hf : Function.Injective f) :
(s.map f).WOppSide (f x) (f y) ↔ s.WOppSide x y := by
refine ⟨fun h => ?_, fun h => h.map _⟩
rcases h with ⟨fp₁, hfp₁, fp₂, hfp₂, h⟩
rw [mem_map] at hfp₁ hfp₂
rcases hfp₁ with ⟨p₁, hp₁, rfl⟩
rcases hfp₂ with ⟨p₂, hp₂, rfl⟩
refine ⟨p₁, hp₁, p₂, hp₂, ?_⟩
simp_rw [← linearMap_vsub, (f.linear_injective_iff.2 hf).sameRay_map_iff] at h
exact h
#align function.injective.w_opp_side_map_iff Function.Injective.wOppSide_map_iff
theorem _root_.Function.Injective.sOppSide_map_iff {s : AffineSubspace R P} {x y : P}
{f : P →ᵃ[R] P'} (hf : Function.Injective f) :
(s.map f).SOppSide (f x) (f y) ↔ s.SOppSide x y := by
simp_rw [SOppSide, hf.wOppSide_map_iff, mem_map_iff_mem_of_injective hf]
#align function.injective.s_opp_side_map_iff Function.Injective.sOppSide_map_iff
@[simp]
theorem _root_.AffineEquiv.wOppSide_map_iff {s : AffineSubspace R P} {x y : P} (f : P ≃ᵃ[R] P') :
(s.map ↑f).WOppSide (f x) (f y) ↔ s.WOppSide x y :=
(show Function.Injective f.toAffineMap from f.injective).wOppSide_map_iff
#align affine_equiv.w_opp_side_map_iff AffineEquiv.wOppSide_map_iff
@[simp]
theorem _root_.AffineEquiv.sOppSide_map_iff {s : AffineSubspace R P} {x y : P} (f : P ≃ᵃ[R] P') :
(s.map ↑f).SOppSide (f x) (f y) ↔ s.SOppSide x y :=
(show Function.Injective f.toAffineMap from f.injective).sOppSide_map_iff
#align affine_equiv.s_opp_side_map_iff AffineEquiv.sOppSide_map_iff
theorem WSameSide.nonempty {s : AffineSubspace R P} {x y : P} (h : s.WSameSide x y) :
(s : Set P).Nonempty :=
⟨h.choose, h.choose_spec.left⟩
#align affine_subspace.w_same_side.nonempty AffineSubspace.WSameSide.nonempty
theorem SSameSide.nonempty {s : AffineSubspace R P} {x y : P} (h : s.SSameSide x y) :
(s : Set P).Nonempty :=
⟨h.1.choose, h.1.choose_spec.left⟩
#align affine_subspace.s_same_side.nonempty AffineSubspace.SSameSide.nonempty
theorem WOppSide.nonempty {s : AffineSubspace R P} {x y : P} (h : s.WOppSide x y) :
(s : Set P).Nonempty :=
⟨h.choose, h.choose_spec.left⟩
#align affine_subspace.w_opp_side.nonempty AffineSubspace.WOppSide.nonempty
theorem SOppSide.nonempty {s : AffineSubspace R P} {x y : P} (h : s.SOppSide x y) :
(s : Set P).Nonempty :=
⟨h.1.choose, h.1.choose_spec.left⟩
#align affine_subspace.s_opp_side.nonempty AffineSubspace.SOppSide.nonempty
theorem SSameSide.wSameSide {s : AffineSubspace R P} {x y : P} (h : s.SSameSide x y) :
s.WSameSide x y :=
h.1
#align affine_subspace.s_same_side.w_same_side AffineSubspace.SSameSide.wSameSide
theorem SSameSide.left_not_mem {s : AffineSubspace R P} {x y : P} (h : s.SSameSide x y) : x ∉ s :=
h.2.1
#align affine_subspace.s_same_side.left_not_mem AffineSubspace.SSameSide.left_not_mem
theorem SSameSide.right_not_mem {s : AffineSubspace R P} {x y : P} (h : s.SSameSide x y) : y ∉ s :=
h.2.2
#align affine_subspace.s_same_side.right_not_mem AffineSubspace.SSameSide.right_not_mem
theorem SOppSide.wOppSide {s : AffineSubspace R P} {x y : P} (h : s.SOppSide x y) :
s.WOppSide x y :=
h.1
#align affine_subspace.s_opp_side.w_opp_side AffineSubspace.SOppSide.wOppSide
theorem SOppSide.left_not_mem {s : AffineSubspace R P} {x y : P} (h : s.SOppSide x y) : x ∉ s :=
h.2.1
#align affine_subspace.s_opp_side.left_not_mem AffineSubspace.SOppSide.left_not_mem
theorem SOppSide.right_not_mem {s : AffineSubspace R P} {x y : P} (h : s.SOppSide x y) : y ∉ s :=
h.2.2
#align affine_subspace.s_opp_side.right_not_mem AffineSubspace.SOppSide.right_not_mem
theorem wSameSide_comm {s : AffineSubspace R P} {x y : P} : s.WSameSide x y ↔ s.WSameSide y x :=
⟨fun ⟨p₁, hp₁, p₂, hp₂, h⟩ => ⟨p₂, hp₂, p₁, hp₁, h.symm⟩,
fun ⟨p₁, hp₁, p₂, hp₂, h⟩ => ⟨p₂, hp₂, p₁, hp₁, h.symm⟩⟩
#align affine_subspace.w_same_side_comm AffineSubspace.wSameSide_comm
alias ⟨WSameSide.symm, _⟩ := wSameSide_comm
#align affine_subspace.w_same_side.symm AffineSubspace.WSameSide.symm
theorem sSameSide_comm {s : AffineSubspace R P} {x y : P} : s.SSameSide x y ↔ s.SSameSide y x := by
rw [SSameSide, SSameSide, wSameSide_comm, and_comm (b := x ∉ s)]
#align affine_subspace.s_same_side_comm AffineSubspace.sSameSide_comm
alias ⟨SSameSide.symm, _⟩ := sSameSide_comm
#align affine_subspace.s_same_side.symm AffineSubspace.SSameSide.symm
theorem wOppSide_comm {s : AffineSubspace R P} {x y : P} : s.WOppSide x y ↔ s.WOppSide y x := by
constructor
· rintro ⟨p₁, hp₁, p₂, hp₂, h⟩
refine ⟨p₂, hp₂, p₁, hp₁, ?_⟩
rwa [SameRay.sameRay_comm, ← sameRay_neg_iff, neg_vsub_eq_vsub_rev, neg_vsub_eq_vsub_rev]
· rintro ⟨p₁, hp₁, p₂, hp₂, h⟩
refine ⟨p₂, hp₂, p₁, hp₁, ?_⟩
rwa [SameRay.sameRay_comm, ← sameRay_neg_iff, neg_vsub_eq_vsub_rev, neg_vsub_eq_vsub_rev]
#align affine_subspace.w_opp_side_comm AffineSubspace.wOppSide_comm
alias ⟨WOppSide.symm, _⟩ := wOppSide_comm
#align affine_subspace.w_opp_side.symm AffineSubspace.WOppSide.symm
theorem sOppSide_comm {s : AffineSubspace R P} {x y : P} : s.SOppSide x y ↔ s.SOppSide y x := by
rw [SOppSide, SOppSide, wOppSide_comm, and_comm (b := x ∉ s)]
#align affine_subspace.s_opp_side_comm AffineSubspace.sOppSide_comm
alias ⟨SOppSide.symm, _⟩ := sOppSide_comm
#align affine_subspace.s_opp_side.symm AffineSubspace.SOppSide.symm
theorem not_wSameSide_bot (x y : P) : ¬(⊥ : AffineSubspace R P).WSameSide x y :=
fun ⟨_, h, _⟩ => h.elim
#align affine_subspace.not_w_same_side_bot AffineSubspace.not_wSameSide_bot
theorem not_sSameSide_bot (x y : P) : ¬(⊥ : AffineSubspace R P).SSameSide x y :=
fun h => not_wSameSide_bot x y h.wSameSide
#align affine_subspace.not_s_same_side_bot AffineSubspace.not_sSameSide_bot
theorem not_wOppSide_bot (x y : P) : ¬(⊥ : AffineSubspace R P).WOppSide x y :=
fun ⟨_, h, _⟩ => h.elim
#align affine_subspace.not_w_opp_side_bot AffineSubspace.not_wOppSide_bot
theorem not_sOppSide_bot (x y : P) : ¬(⊥ : AffineSubspace R P).SOppSide x y :=
fun h => not_wOppSide_bot x y h.wOppSide
#align affine_subspace.not_s_opp_side_bot AffineSubspace.not_sOppSide_bot
@[simp]
theorem wSameSide_self_iff {s : AffineSubspace R P} {x : P} :
s.WSameSide x x ↔ (s : Set P).Nonempty :=
⟨fun h => h.nonempty, fun ⟨p, hp⟩ => ⟨p, hp, p, hp, SameRay.rfl⟩⟩
#align affine_subspace.w_same_side_self_iff AffineSubspace.wSameSide_self_iff
theorem sSameSide_self_iff {s : AffineSubspace R P} {x : P} :
s.SSameSide x x ↔ (s : Set P).Nonempty ∧ x ∉ s :=
⟨fun ⟨h, hx, _⟩ => ⟨wSameSide_self_iff.1 h, hx⟩, fun ⟨h, hx⟩ => ⟨wSameSide_self_iff.2 h, hx, hx⟩⟩
#align affine_subspace.s_same_side_self_iff AffineSubspace.sSameSide_self_iff
theorem wSameSide_of_left_mem {s : AffineSubspace R P} {x : P} (y : P) (hx : x ∈ s) :
s.WSameSide x y := by
refine ⟨x, hx, x, hx, ?_⟩
rw [vsub_self]
apply SameRay.zero_left
#align affine_subspace.w_same_side_of_left_mem AffineSubspace.wSameSide_of_left_mem
theorem wSameSide_of_right_mem {s : AffineSubspace R P} (x : P) {y : P} (hy : y ∈ s) :
s.WSameSide x y :=
(wSameSide_of_left_mem x hy).symm
#align affine_subspace.w_same_side_of_right_mem AffineSubspace.wSameSide_of_right_mem
theorem wOppSide_of_left_mem {s : AffineSubspace R P} {x : P} (y : P) (hx : x ∈ s) :
s.WOppSide x y := by
refine ⟨x, hx, x, hx, ?_⟩
rw [vsub_self]
apply SameRay.zero_left
#align affine_subspace.w_opp_side_of_left_mem AffineSubspace.wOppSide_of_left_mem
theorem wOppSide_of_right_mem {s : AffineSubspace R P} (x : P) {y : P} (hy : y ∈ s) :
s.WOppSide x y :=
(wOppSide_of_left_mem x hy).symm
#align affine_subspace.w_opp_side_of_right_mem AffineSubspace.wOppSide_of_right_mem
theorem wSameSide_vadd_left_iff {s : AffineSubspace R P} {x y : P} {v : V} (hv : v ∈ s.direction) :
s.WSameSide (v +ᵥ x) y ↔ s.WSameSide x y := by
constructor
· rintro ⟨p₁, hp₁, p₂, hp₂, h⟩
refine
⟨-v +ᵥ p₁, AffineSubspace.vadd_mem_of_mem_direction (Submodule.neg_mem _ hv) hp₁, p₂, hp₂, ?_⟩
rwa [vsub_vadd_eq_vsub_sub, sub_neg_eq_add, add_comm, ← vadd_vsub_assoc]
· rintro ⟨p₁, hp₁, p₂, hp₂, h⟩
refine ⟨v +ᵥ p₁, AffineSubspace.vadd_mem_of_mem_direction hv hp₁, p₂, hp₂, ?_⟩
rwa [vadd_vsub_vadd_cancel_left]
#align affine_subspace.w_same_side_vadd_left_iff AffineSubspace.wSameSide_vadd_left_iff
theorem wSameSide_vadd_right_iff {s : AffineSubspace R P} {x y : P} {v : V} (hv : v ∈ s.direction) :
s.WSameSide x (v +ᵥ y) ↔ s.WSameSide x y := by
rw [wSameSide_comm, wSameSide_vadd_left_iff hv, wSameSide_comm]
#align affine_subspace.w_same_side_vadd_right_iff AffineSubspace.wSameSide_vadd_right_iff
theorem sSameSide_vadd_left_iff {s : AffineSubspace R P} {x y : P} {v : V} (hv : v ∈ s.direction) :
s.SSameSide (v +ᵥ x) y ↔ s.SSameSide x y := by
rw [SSameSide, SSameSide, wSameSide_vadd_left_iff hv, vadd_mem_iff_mem_of_mem_direction hv]
#align affine_subspace.s_same_side_vadd_left_iff AffineSubspace.sSameSide_vadd_left_iff
theorem sSameSide_vadd_right_iff {s : AffineSubspace R P} {x y : P} {v : V} (hv : v ∈ s.direction) :
s.SSameSide x (v +ᵥ y) ↔ s.SSameSide x y := by
rw [sSameSide_comm, sSameSide_vadd_left_iff hv, sSameSide_comm]
#align affine_subspace.s_same_side_vadd_right_iff AffineSubspace.sSameSide_vadd_right_iff
theorem wOppSide_vadd_left_iff {s : AffineSubspace R P} {x y : P} {v : V} (hv : v ∈ s.direction) :
s.WOppSide (v +ᵥ x) y ↔ s.WOppSide x y := by
constructor
· rintro ⟨p₁, hp₁, p₂, hp₂, h⟩
refine
⟨-v +ᵥ p₁, AffineSubspace.vadd_mem_of_mem_direction (Submodule.neg_mem _ hv) hp₁, p₂, hp₂, ?_⟩
rwa [vsub_vadd_eq_vsub_sub, sub_neg_eq_add, add_comm, ← vadd_vsub_assoc]
· rintro ⟨p₁, hp₁, p₂, hp₂, h⟩
refine ⟨v +ᵥ p₁, AffineSubspace.vadd_mem_of_mem_direction hv hp₁, p₂, hp₂, ?_⟩
rwa [vadd_vsub_vadd_cancel_left]
#align affine_subspace.w_opp_side_vadd_left_iff AffineSubspace.wOppSide_vadd_left_iff
theorem wOppSide_vadd_right_iff {s : AffineSubspace R P} {x y : P} {v : V} (hv : v ∈ s.direction) :
s.WOppSide x (v +ᵥ y) ↔ s.WOppSide x y := by
rw [wOppSide_comm, wOppSide_vadd_left_iff hv, wOppSide_comm]
#align affine_subspace.w_opp_side_vadd_right_iff AffineSubspace.wOppSide_vadd_right_iff
theorem sOppSide_vadd_left_iff {s : AffineSubspace R P} {x y : P} {v : V} (hv : v ∈ s.direction) :
s.SOppSide (v +ᵥ x) y ↔ s.SOppSide x y := by
rw [SOppSide, SOppSide, wOppSide_vadd_left_iff hv, vadd_mem_iff_mem_of_mem_direction hv]
#align affine_subspace.s_opp_side_vadd_left_iff AffineSubspace.sOppSide_vadd_left_iff
theorem sOppSide_vadd_right_iff {s : AffineSubspace R P} {x y : P} {v : V} (hv : v ∈ s.direction) :
s.SOppSide x (v +ᵥ y) ↔ s.SOppSide x y := by
rw [sOppSide_comm, sOppSide_vadd_left_iff hv, sOppSide_comm]
#align affine_subspace.s_opp_side_vadd_right_iff AffineSubspace.sOppSide_vadd_right_iff
theorem wSameSide_smul_vsub_vadd_left {s : AffineSubspace R P} {p₁ p₂ : P} (x : P) (hp₁ : p₁ ∈ s)
(hp₂ : p₂ ∈ s) {t : R} (ht : 0 ≤ t) : s.WSameSide (t • (x -ᵥ p₁) +ᵥ p₂) x := by
refine ⟨p₂, hp₂, p₁, hp₁, ?_⟩
rw [vadd_vsub]
exact SameRay.sameRay_nonneg_smul_left _ ht
#align affine_subspace.w_same_side_smul_vsub_vadd_left AffineSubspace.wSameSide_smul_vsub_vadd_left
theorem wSameSide_smul_vsub_vadd_right {s : AffineSubspace R P} {p₁ p₂ : P} (x : P) (hp₁ : p₁ ∈ s)
(hp₂ : p₂ ∈ s) {t : R} (ht : 0 ≤ t) : s.WSameSide x (t • (x -ᵥ p₁) +ᵥ p₂) :=
(wSameSide_smul_vsub_vadd_left x hp₁ hp₂ ht).symm
#align affine_subspace.w_same_side_smul_vsub_vadd_right AffineSubspace.wSameSide_smul_vsub_vadd_right
theorem wSameSide_lineMap_left {s : AffineSubspace R P} {x : P} (y : P) (h : x ∈ s) {t : R}
(ht : 0 ≤ t) : s.WSameSide (lineMap x y t) y :=
wSameSide_smul_vsub_vadd_left y h h ht
#align affine_subspace.w_same_side_line_map_left AffineSubspace.wSameSide_lineMap_left
theorem wSameSide_lineMap_right {s : AffineSubspace R P} {x : P} (y : P) (h : x ∈ s) {t : R}
(ht : 0 ≤ t) : s.WSameSide y (lineMap x y t) :=
(wSameSide_lineMap_left y h ht).symm
#align affine_subspace.w_same_side_line_map_right AffineSubspace.wSameSide_lineMap_right
theorem wOppSide_smul_vsub_vadd_left {s : AffineSubspace R P} {p₁ p₂ : P} (x : P) (hp₁ : p₁ ∈ s)
(hp₂ : p₂ ∈ s) {t : R} (ht : t ≤ 0) : s.WOppSide (t • (x -ᵥ p₁) +ᵥ p₂) x := by
refine ⟨p₂, hp₂, p₁, hp₁, ?_⟩
rw [vadd_vsub, ← neg_neg t, neg_smul, ← smul_neg, neg_vsub_eq_vsub_rev]
exact SameRay.sameRay_nonneg_smul_left _ (neg_nonneg.2 ht)
#align affine_subspace.w_opp_side_smul_vsub_vadd_left AffineSubspace.wOppSide_smul_vsub_vadd_left
theorem wOppSide_smul_vsub_vadd_right {s : AffineSubspace R P} {p₁ p₂ : P} (x : P) (hp₁ : p₁ ∈ s)
(hp₂ : p₂ ∈ s) {t : R} (ht : t ≤ 0) : s.WOppSide x (t • (x -ᵥ p₁) +ᵥ p₂) :=
(wOppSide_smul_vsub_vadd_left x hp₁ hp₂ ht).symm
#align affine_subspace.w_opp_side_smul_vsub_vadd_right AffineSubspace.wOppSide_smul_vsub_vadd_right
theorem wOppSide_lineMap_left {s : AffineSubspace R P} {x : P} (y : P) (h : x ∈ s) {t : R}
(ht : t ≤ 0) : s.WOppSide (lineMap x y t) y :=
wOppSide_smul_vsub_vadd_left y h h ht
#align affine_subspace.w_opp_side_line_map_left AffineSubspace.wOppSide_lineMap_left
theorem wOppSide_lineMap_right {s : AffineSubspace R P} {x : P} (y : P) (h : x ∈ s) {t : R}
(ht : t ≤ 0) : s.WOppSide y (lineMap x y t) :=
(wOppSide_lineMap_left y h ht).symm
#align affine_subspace.w_opp_side_line_map_right AffineSubspace.wOppSide_lineMap_right
theorem _root_.Wbtw.wSameSide₂₃ {s : AffineSubspace R P} {x y z : P} (h : Wbtw R x y z)
(hx : x ∈ s) : s.WSameSide y z := by
rcases h with ⟨t, ⟨ht0, -⟩, rfl⟩
exact wSameSide_lineMap_left z hx ht0
#align wbtw.w_same_side₂₃ Wbtw.wSameSide₂₃
theorem _root_.Wbtw.wSameSide₃₂ {s : AffineSubspace R P} {x y z : P} (h : Wbtw R x y z)
(hx : x ∈ s) : s.WSameSide z y :=
(h.wSameSide₂₃ hx).symm
#align wbtw.w_same_side₃₂ Wbtw.wSameSide₃₂
theorem _root_.Wbtw.wSameSide₁₂ {s : AffineSubspace R P} {x y z : P} (h : Wbtw R x y z)
(hz : z ∈ s) : s.WSameSide x y :=
h.symm.wSameSide₃₂ hz
#align wbtw.w_same_side₁₂ Wbtw.wSameSide₁₂
theorem _root_.Wbtw.wSameSide₂₁ {s : AffineSubspace R P} {x y z : P} (h : Wbtw R x y z)
(hz : z ∈ s) : s.WSameSide y x :=
h.symm.wSameSide₂₃ hz
#align wbtw.w_same_side₂₁ Wbtw.wSameSide₂₁
theorem _root_.Wbtw.wOppSide₁₃ {s : AffineSubspace R P} {x y z : P} (h : Wbtw R x y z)
(hy : y ∈ s) : s.WOppSide x z := by
rcases h with ⟨t, ⟨ht0, ht1⟩, rfl⟩
refine ⟨_, hy, _, hy, ?_⟩
rcases ht1.lt_or_eq with (ht1' | rfl); swap
· rw [lineMap_apply_one]; simp
rcases ht0.lt_or_eq with (ht0' | rfl); swap
· rw [lineMap_apply_zero]; simp
refine Or.inr (Or.inr ⟨1 - t, t, sub_pos.2 ht1', ht0', ?_⟩)
-- TODO: after lean4#2336 "simp made no progress feature"
-- had to add `_` to several lemmas here. Not sure why!
simp_rw [lineMap_apply _, vadd_vsub_assoc _, vsub_vadd_eq_vsub_sub _,
← neg_vsub_eq_vsub_rev z x, vsub_self _, zero_sub, ← neg_one_smul R (z -ᵥ x),
← add_smul, smul_neg, ← neg_smul, smul_smul]
ring_nf
#align wbtw.w_opp_side₁₃ Wbtw.wOppSide₁₃
theorem _root_.Wbtw.wOppSide₃₁ {s : AffineSubspace R P} {x y z : P} (h : Wbtw R x y z)
(hy : y ∈ s) : s.WOppSide z x :=
h.symm.wOppSide₁₃ hy
#align wbtw.w_opp_side₃₁ Wbtw.wOppSide₃₁
end StrictOrderedCommRing
section LinearOrderedField
variable [LinearOrderedField R] [AddCommGroup V] [Module R V] [AddTorsor V P]
variable [AddCommGroup V'] [Module R V'] [AddTorsor V' P']
@[simp]
theorem wOppSide_self_iff {s : AffineSubspace R P} {x : P} : s.WOppSide x x ↔ x ∈ s := by
constructor
· rintro ⟨p₁, hp₁, p₂, hp₂, h⟩
obtain ⟨a, -, -, -, -, h₁, -⟩ := h.exists_eq_smul_add
rw [add_comm, vsub_add_vsub_cancel, ← eq_vadd_iff_vsub_eq] at h₁
rw [h₁]
exact s.smul_vsub_vadd_mem a hp₂ hp₁ hp₁
· exact fun h => ⟨x, h, x, h, SameRay.rfl⟩
#align affine_subspace.w_opp_side_self_iff AffineSubspace.wOppSide_self_iff
theorem not_sOppSide_self (s : AffineSubspace R P) (x : P) : ¬s.SOppSide x x := by
rw [SOppSide]
simp
#align affine_subspace.not_s_opp_side_self AffineSubspace.not_sOppSide_self
theorem wSameSide_iff_exists_left {s : AffineSubspace R P} {x y p₁ : P} (h : p₁ ∈ s) :
s.WSameSide x y ↔ x ∈ s ∨ ∃ p₂ ∈ s, SameRay R (x -ᵥ p₁) (y -ᵥ p₂) := by
constructor
· rintro ⟨p₁', hp₁', p₂', hp₂', h0 | h0 | ⟨r₁, r₂, hr₁, hr₂, hr⟩⟩
· rw [vsub_eq_zero_iff_eq] at h0
rw [h0]
exact Or.inl hp₁'
· refine Or.inr ⟨p₂', hp₂', ?_⟩
rw [h0]
exact SameRay.zero_right _
· refine Or.inr ⟨(r₁ / r₂) • (p₁ -ᵥ p₁') +ᵥ p₂', s.smul_vsub_vadd_mem _ h hp₁' hp₂',
Or.inr (Or.inr ⟨r₁, r₂, hr₁, hr₂, ?_⟩)⟩
rw [vsub_vadd_eq_vsub_sub, smul_sub, ← hr, smul_smul, mul_div_cancel₀ _ hr₂.ne.symm,
← smul_sub, vsub_sub_vsub_cancel_right]
· rintro (h' | ⟨h₁, h₂, h₃⟩)
· exact wSameSide_of_left_mem y h'
· exact ⟨p₁, h, h₁, h₂, h₃⟩
#align affine_subspace.w_same_side_iff_exists_left AffineSubspace.wSameSide_iff_exists_left
theorem wSameSide_iff_exists_right {s : AffineSubspace R P} {x y p₂ : P} (h : p₂ ∈ s) :
s.WSameSide x y ↔ y ∈ s ∨ ∃ p₁ ∈ s, SameRay R (x -ᵥ p₁) (y -ᵥ p₂) := by
rw [wSameSide_comm, wSameSide_iff_exists_left h]
simp_rw [SameRay.sameRay_comm]
#align affine_subspace.w_same_side_iff_exists_right AffineSubspace.wSameSide_iff_exists_right
theorem sSameSide_iff_exists_left {s : AffineSubspace R P} {x y p₁ : P} (h : p₁ ∈ s) :
s.SSameSide x y ↔ x ∉ s ∧ y ∉ s ∧ ∃ p₂ ∈ s, SameRay R (x -ᵥ p₁) (y -ᵥ p₂) := by
rw [SSameSide, and_comm, wSameSide_iff_exists_left h, and_assoc, and_congr_right_iff]
intro hx
rw [or_iff_right hx]
#align affine_subspace.s_same_side_iff_exists_left AffineSubspace.sSameSide_iff_exists_left
theorem sSameSide_iff_exists_right {s : AffineSubspace R P} {x y p₂ : P} (h : p₂ ∈ s) :
s.SSameSide x y ↔ x ∉ s ∧ y ∉ s ∧ ∃ p₁ ∈ s, SameRay R (x -ᵥ p₁) (y -ᵥ p₂) := by
rw [sSameSide_comm, sSameSide_iff_exists_left h, ← and_assoc, and_comm (a := y ∉ s), and_assoc]
simp_rw [SameRay.sameRay_comm]
#align affine_subspace.s_same_side_iff_exists_right AffineSubspace.sSameSide_iff_exists_right
| Mathlib/Analysis/Convex/Side.lean | 474 | 491 | theorem wOppSide_iff_exists_left {s : AffineSubspace R P} {x y p₁ : P} (h : p₁ ∈ s) :
s.WOppSide x y ↔ x ∈ s ∨ ∃ p₂ ∈ s, SameRay R (x -ᵥ p₁) (p₂ -ᵥ y) := by |
constructor
· rintro ⟨p₁', hp₁', p₂', hp₂', h0 | h0 | ⟨r₁, r₂, hr₁, hr₂, hr⟩⟩
· rw [vsub_eq_zero_iff_eq] at h0
rw [h0]
exact Or.inl hp₁'
· refine Or.inr ⟨p₂', hp₂', ?_⟩
rw [h0]
exact SameRay.zero_right _
· refine Or.inr ⟨(-r₁ / r₂) • (p₁ -ᵥ p₁') +ᵥ p₂', s.smul_vsub_vadd_mem _ h hp₁' hp₂',
Or.inr (Or.inr ⟨r₁, r₂, hr₁, hr₂, ?_⟩)⟩
rw [vadd_vsub_assoc, smul_add, ← hr, smul_smul, neg_div, mul_neg,
mul_div_cancel₀ _ hr₂.ne.symm, neg_smul, neg_add_eq_sub, ← smul_sub,
vsub_sub_vsub_cancel_right]
· rintro (h' | ⟨h₁, h₂, h₃⟩)
· exact wOppSide_of_left_mem y h'
· exact ⟨p₁, h, h₁, h₂, h₃⟩
|
/-
Copyright (c) 2020 Rémy Degenne. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Rémy Degenne, Eric Wieser
-/
import Mathlib.MeasureTheory.Function.LpSeminorm.Basic
import Mathlib.MeasureTheory.Integral.MeanInequalities
#align_import measure_theory.function.lp_seminorm from "leanprover-community/mathlib"@"c4015acc0a223449d44061e27ddac1835a3852b9"
/-!
# Compare Lp seminorms for different values of `p`
In this file we compare `MeasureTheory.snorm'` and `MeasureTheory.snorm` for different exponents.
-/
open Filter
open scoped ENNReal Topology
namespace MeasureTheory
section SameSpace
variable {α E : Type*} {m : MeasurableSpace α} [NormedAddCommGroup E] {μ : Measure α} {f : α → E}
theorem snorm'_le_snorm'_mul_rpow_measure_univ {p q : ℝ} (hp0_lt : 0 < p) (hpq : p ≤ q)
(hf : AEStronglyMeasurable f μ) :
snorm' f p μ ≤ snorm' f q μ * μ Set.univ ^ (1 / p - 1 / q) := by
have hq0_lt : 0 < q := lt_of_lt_of_le hp0_lt hpq
by_cases hpq_eq : p = q
· rw [hpq_eq, sub_self, ENNReal.rpow_zero, mul_one]
have hpq : p < q := lt_of_le_of_ne hpq hpq_eq
let g := fun _ : α => (1 : ℝ≥0∞)
have h_rw : (∫⁻ a, (‖f a‖₊ : ℝ≥0∞) ^ p ∂μ) = ∫⁻ a, ((‖f a‖₊ : ℝ≥0∞) * g a) ^ p ∂μ :=
lintegral_congr fun a => by simp [g]
repeat' rw [snorm']
rw [h_rw]
let r := p * q / (q - p)
have hpqr : 1 / p = 1 / q + 1 / r := by field_simp [r, hp0_lt.ne', hq0_lt.ne']
calc
(∫⁻ a : α, (↑‖f a‖₊ * g a) ^ p ∂μ) ^ (1 / p) ≤
(∫⁻ a : α, ↑‖f a‖₊ ^ q ∂μ) ^ (1 / q) * (∫⁻ a : α, g a ^ r ∂μ) ^ (1 / r) :=
ENNReal.lintegral_Lp_mul_le_Lq_mul_Lr hp0_lt hpq hpqr μ hf.ennnorm aemeasurable_const
_ = (∫⁻ a : α, ↑‖f a‖₊ ^ q ∂μ) ^ (1 / q) * μ Set.univ ^ (1 / p - 1 / q) := by
rw [hpqr]; simp [r, g]
#align measure_theory.snorm'_le_snorm'_mul_rpow_measure_univ MeasureTheory.snorm'_le_snorm'_mul_rpow_measure_univ
theorem snorm'_le_snormEssSup_mul_rpow_measure_univ {q : ℝ} (hq_pos : 0 < q) :
snorm' f q μ ≤ snormEssSup f μ * μ Set.univ ^ (1 / q) := by
have h_le : (∫⁻ a : α, (‖f a‖₊ : ℝ≥0∞) ^ q ∂μ) ≤ ∫⁻ _ : α, snormEssSup f μ ^ q ∂μ := by
refine lintegral_mono_ae ?_
have h_nnnorm_le_snorm_ess_sup := coe_nnnorm_ae_le_snormEssSup f μ
exact h_nnnorm_le_snorm_ess_sup.mono fun x hx => by gcongr
rw [snorm', ← ENNReal.rpow_one (snormEssSup f μ)]
nth_rw 2 [← mul_inv_cancel (ne_of_lt hq_pos).symm]
rw [ENNReal.rpow_mul, one_div, ← ENNReal.mul_rpow_of_nonneg _ _ (by simp [hq_pos.le] : 0 ≤ q⁻¹)]
gcongr
rwa [lintegral_const] at h_le
#align measure_theory.snorm'_le_snorm_ess_sup_mul_rpow_measure_univ MeasureTheory.snorm'_le_snormEssSup_mul_rpow_measure_univ
theorem snorm_le_snorm_mul_rpow_measure_univ {p q : ℝ≥0∞} (hpq : p ≤ q)
(hf : AEStronglyMeasurable f μ) :
snorm f p μ ≤ snorm f q μ * μ Set.univ ^ (1 / p.toReal - 1 / q.toReal) := by
by_cases hp0 : p = 0
· simp [hp0, zero_le]
rw [← Ne] at hp0
have hp0_lt : 0 < p := lt_of_le_of_ne (zero_le _) hp0.symm
have hq0_lt : 0 < q := lt_of_lt_of_le hp0_lt hpq
by_cases hq_top : q = ∞
· simp only [hq_top, _root_.div_zero, one_div, ENNReal.top_toReal, sub_zero, snorm_exponent_top,
GroupWithZero.inv_zero]
by_cases hp_top : p = ∞
· simp only [hp_top, ENNReal.rpow_zero, mul_one, ENNReal.top_toReal, sub_zero,
GroupWithZero.inv_zero, snorm_exponent_top]
exact le_rfl
rw [snorm_eq_snorm' hp0 hp_top]
have hp_pos : 0 < p.toReal := ENNReal.toReal_pos hp0_lt.ne' hp_top
refine (snorm'_le_snormEssSup_mul_rpow_measure_univ hp_pos).trans (le_of_eq ?_)
congr
exact one_div _
have hp_lt_top : p < ∞ := hpq.trans_lt (lt_top_iff_ne_top.mpr hq_top)
have hp_pos : 0 < p.toReal := ENNReal.toReal_pos hp0_lt.ne' hp_lt_top.ne
rw [snorm_eq_snorm' hp0_lt.ne.symm hp_lt_top.ne, snorm_eq_snorm' hq0_lt.ne.symm hq_top]
have hpq_real : p.toReal ≤ q.toReal := by rwa [ENNReal.toReal_le_toReal hp_lt_top.ne hq_top]
exact snorm'_le_snorm'_mul_rpow_measure_univ hp_pos hpq_real hf
#align measure_theory.snorm_le_snorm_mul_rpow_measure_univ MeasureTheory.snorm_le_snorm_mul_rpow_measure_univ
theorem snorm'_le_snorm'_of_exponent_le {p q : ℝ} (hp0_lt : 0 < p)
(hpq : p ≤ q) (μ : Measure α) [IsProbabilityMeasure μ] (hf : AEStronglyMeasurable f μ) :
snorm' f p μ ≤ snorm' f q μ := by
have h_le_μ := snorm'_le_snorm'_mul_rpow_measure_univ hp0_lt hpq hf
rwa [measure_univ, ENNReal.one_rpow, mul_one] at h_le_μ
#align measure_theory.snorm'_le_snorm'_of_exponent_le MeasureTheory.snorm'_le_snorm'_of_exponent_le
theorem snorm'_le_snormEssSup {q : ℝ} (hq_pos : 0 < q) [IsProbabilityMeasure μ] :
snorm' f q μ ≤ snormEssSup f μ :=
le_trans (snorm'_le_snormEssSup_mul_rpow_measure_univ hq_pos) (le_of_eq (by simp [measure_univ]))
#align measure_theory.snorm'_le_snorm_ess_sup MeasureTheory.snorm'_le_snormEssSup
theorem snorm_le_snorm_of_exponent_le {p q : ℝ≥0∞} (hpq : p ≤ q) [IsProbabilityMeasure μ]
(hf : AEStronglyMeasurable f μ) : snorm f p μ ≤ snorm f q μ :=
(snorm_le_snorm_mul_rpow_measure_univ hpq hf).trans (le_of_eq (by simp [measure_univ]))
#align measure_theory.snorm_le_snorm_of_exponent_le MeasureTheory.snorm_le_snorm_of_exponent_le
theorem snorm'_lt_top_of_snorm'_lt_top_of_exponent_le {p q : ℝ} [IsFiniteMeasure μ]
(hf : AEStronglyMeasurable f μ) (hfq_lt_top : snorm' f q μ < ∞) (hp_nonneg : 0 ≤ p)
(hpq : p ≤ q) : snorm' f p μ < ∞ := by
rcases le_or_lt p 0 with hp_nonpos | hp_pos
· rw [le_antisymm hp_nonpos hp_nonneg]
simp
have hq_pos : 0 < q := lt_of_lt_of_le hp_pos hpq
calc
snorm' f p μ ≤ snorm' f q μ * μ Set.univ ^ (1 / p - 1 / q) :=
snorm'_le_snorm'_mul_rpow_measure_univ hp_pos hpq hf
_ < ∞ := by
rw [ENNReal.mul_lt_top_iff]
refine Or.inl ⟨hfq_lt_top, ENNReal.rpow_lt_top_of_nonneg ?_ (measure_ne_top μ Set.univ)⟩
rwa [le_sub_comm, sub_zero, one_div, one_div, inv_le_inv hq_pos hp_pos]
#align measure_theory.snorm'_lt_top_of_snorm'_lt_top_of_exponent_le MeasureTheory.snorm'_lt_top_of_snorm'_lt_top_of_exponent_le
| Mathlib/MeasureTheory/Function/LpSeminorm/CompareExp.lean | 121 | 147 | theorem Memℒp.memℒp_of_exponent_le {p q : ℝ≥0∞} [IsFiniteMeasure μ] {f : α → E} (hfq : Memℒp f q μ)
(hpq : p ≤ q) : Memℒp f p μ := by |
cases' hfq with hfq_m hfq_lt_top
by_cases hp0 : p = 0
· rwa [hp0, memℒp_zero_iff_aestronglyMeasurable]
rw [← Ne] at hp0
refine ⟨hfq_m, ?_⟩
by_cases hp_top : p = ∞
· have hq_top : q = ∞ := by rwa [hp_top, top_le_iff] at hpq
rw [hp_top]
rwa [hq_top] at hfq_lt_top
have hp_pos : 0 < p.toReal := ENNReal.toReal_pos hp0 hp_top
by_cases hq_top : q = ∞
· rw [snorm_eq_snorm' hp0 hp_top]
rw [hq_top, snorm_exponent_top] at hfq_lt_top
refine lt_of_le_of_lt (snorm'_le_snormEssSup_mul_rpow_measure_univ hp_pos) ?_
refine ENNReal.mul_lt_top hfq_lt_top.ne ?_
exact (ENNReal.rpow_lt_top_of_nonneg (by simp [hp_pos.le]) (measure_ne_top μ Set.univ)).ne
have hq0 : q ≠ 0 := by
by_contra hq_eq_zero
have hp_eq_zero : p = 0 := le_antisymm (by rwa [hq_eq_zero] at hpq) (zero_le _)
rw [hp_eq_zero, ENNReal.zero_toReal] at hp_pos
exact (lt_irrefl _) hp_pos
have hpq_real : p.toReal ≤ q.toReal := by rwa [ENNReal.toReal_le_toReal hp_top hq_top]
rw [snorm_eq_snorm' hp0 hp_top]
rw [snorm_eq_snorm' hq0 hq_top] at hfq_lt_top
exact snorm'_lt_top_of_snorm'_lt_top_of_exponent_le hfq_m hfq_lt_top (le_of_lt hp_pos) hpq_real
|
/-
Copyright (c) 2018 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl
-/
import Mathlib.MeasureTheory.Measure.Typeclasses
import Mathlib.MeasureTheory.Measure.MutuallySingular
import Mathlib.MeasureTheory.MeasurableSpace.CountablyGenerated
/-!
# Dirac measure
In this file we define the Dirac measure `MeasureTheory.Measure.dirac a`
and prove some basic facts about it.
-/
open Function Set
open scoped ENNReal Classical
noncomputable section
variable {α β δ : Type*} [MeasurableSpace α] [MeasurableSpace β] {s : Set α} {a : α}
namespace MeasureTheory
namespace Measure
/-- The dirac measure. -/
def dirac (a : α) : Measure α := (OuterMeasure.dirac a).toMeasure (by simp)
#align measure_theory.measure.dirac MeasureTheory.Measure.dirac
instance : MeasureSpace PUnit :=
⟨dirac PUnit.unit⟩
theorem le_dirac_apply {a} : s.indicator 1 a ≤ dirac a s :=
OuterMeasure.dirac_apply a s ▸ le_toMeasure_apply _ _ _
#align measure_theory.measure.le_dirac_apply MeasureTheory.Measure.le_dirac_apply
@[simp]
theorem dirac_apply' (a : α) (hs : MeasurableSet s) : dirac a s = s.indicator 1 a :=
toMeasure_apply _ _ hs
#align measure_theory.measure.dirac_apply' MeasureTheory.Measure.dirac_apply'
@[simp]
theorem dirac_apply_of_mem {a : α} (h : a ∈ s) : dirac a s = 1 := by
have : ∀ t : Set α, a ∈ t → t.indicator (1 : α → ℝ≥0∞) a = 1 := fun t ht => indicator_of_mem ht 1
refine le_antisymm (this univ trivial ▸ ?_) (this s h ▸ le_dirac_apply)
rw [← dirac_apply' a MeasurableSet.univ]
exact measure_mono (subset_univ s)
#align measure_theory.measure.dirac_apply_of_mem MeasureTheory.Measure.dirac_apply_of_mem
@[simp]
theorem dirac_apply [MeasurableSingletonClass α] (a : α) (s : Set α) :
dirac a s = s.indicator 1 a := by
by_cases h : a ∈ s; · rw [dirac_apply_of_mem h, indicator_of_mem h, Pi.one_apply]
rw [indicator_of_not_mem h, ← nonpos_iff_eq_zero]
calc
dirac a s ≤ dirac a {a}ᶜ := measure_mono (subset_compl_comm.1 <| singleton_subset_iff.2 h)
_ = 0 := by simp [dirac_apply' _ (measurableSet_singleton _).compl]
#align measure_theory.measure.dirac_apply MeasureTheory.Measure.dirac_apply
theorem map_dirac {f : α → β} (hf : Measurable f) (a : α) : (dirac a).map f = dirac (f a) :=
ext fun s hs => by simp [hs, map_apply hf hs, hf hs, indicator_apply]
#align measure_theory.measure.map_dirac MeasureTheory.Measure.map_dirac
lemma map_const (μ : Measure α) (c : β) : μ.map (fun _ ↦ c) = (μ Set.univ) • dirac c := by
ext s hs
simp only [aemeasurable_const, measurable_const, Measure.coe_smul, Pi.smul_apply,
dirac_apply' _ hs, smul_eq_mul]
classical
rw [Measure.map_apply measurable_const hs, Set.preimage_const]
by_cases hsc : c ∈ s
· rw [(Set.indicator_eq_one_iff_mem _).mpr hsc, mul_one, if_pos hsc]
· rw [if_neg hsc, (Set.indicator_eq_zero_iff_not_mem _).mpr hsc, measure_empty, mul_zero]
@[simp]
theorem restrict_singleton (μ : Measure α) (a : α) : μ.restrict {a} = μ {a} • dirac a := by
ext1 s hs
by_cases ha : a ∈ s
· have : s ∩ {a} = {a} := by simpa
simp [*]
· have : s ∩ {a} = ∅ := inter_singleton_eq_empty.2 ha
simp [*]
#align measure_theory.measure.restrict_singleton MeasureTheory.Measure.restrict_singleton
/-- If `f` is a map with countable codomain, then `μ.map f` is a sum of Dirac measures. -/
theorem map_eq_sum [Countable β] [MeasurableSingletonClass β] (μ : Measure α) (f : α → β)
(hf : Measurable f) : μ.map f = sum fun b : β => μ (f ⁻¹' {b}) • dirac b := by
ext s
have : ∀ y ∈ s, MeasurableSet (f ⁻¹' {y}) := fun y _ => hf (measurableSet_singleton _)
simp [← tsum_measure_preimage_singleton (to_countable s) this, *,
tsum_subtype s fun b => μ (f ⁻¹' {b}), ← indicator_mul_right s fun b => μ (f ⁻¹' {b})]
#align measure_theory.measure.map_eq_sum MeasureTheory.Measure.map_eq_sum
/-- A measure on a countable type is a sum of Dirac measures. -/
@[simp]
theorem sum_smul_dirac [Countable α] [MeasurableSingletonClass α] (μ : Measure α) :
(sum fun a => μ {a} • dirac a) = μ := by simpa using (map_eq_sum μ id measurable_id).symm
#align measure_theory.measure.sum_smul_dirac MeasureTheory.Measure.sum_smul_dirac
/-- Given that `α` is a countable, measurable space with all singleton sets measurable,
write the measure of a set `s` as the sum of the measure of `{x}` for all `x ∈ s`. -/
| Mathlib/MeasureTheory/Measure/Dirac.lean | 103 | 110 | theorem tsum_indicator_apply_singleton [Countable α] [MeasurableSingletonClass α] (μ : Measure α)
(s : Set α) (hs : MeasurableSet s) : (∑' x : α, s.indicator (fun x => μ {x}) x) = μ s :=
calc
(∑' x : α, s.indicator (fun x => μ {x}) x) =
Measure.sum (fun a => μ {a} • Measure.dirac a) s := by |
simp only [Measure.sum_apply _ hs, Measure.smul_apply, smul_eq_mul, Measure.dirac_apply,
Set.indicator_apply, mul_ite, Pi.one_apply, mul_one, mul_zero]
_ = μ s := by rw [μ.sum_smul_dirac]
|
/-
Copyright (c) 2021 Andrew Yang. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Andrew Yang, Yury G. Kudryashov
-/
import Mathlib.Tactic.TFAE
import Mathlib.Topology.ContinuousOn
#align_import topology.inseparable from "leanprover-community/mathlib"@"bcfa726826abd57587355b4b5b7e78ad6527b7e4"
/-!
# Inseparable points in a topological space
In this file we prove basic properties of the following notions defined elsewhere.
* `Specializes` (notation: `x ⤳ y`) : a relation saying that `𝓝 x ≤ 𝓝 y`;
* `Inseparable`: a relation saying that two points in a topological space have the same
neighbourhoods; equivalently, they can't be separated by an open set;
* `InseparableSetoid X`: same relation, as a `Setoid`;
* `SeparationQuotient X`: the quotient of `X` by its `InseparableSetoid`.
We also prove various basic properties of the relation `Inseparable`.
## Notations
- `x ⤳ y`: notation for `Specializes x y`;
- `x ~ᵢ y` is used as a local notation for `Inseparable x y`;
- `𝓝 x` is the neighbourhoods filter `nhds x` of a point `x`, defined elsewhere.
## Tags
topological space, separation setoid
-/
open Set Filter Function Topology List
variable {X Y Z α ι : Type*} {π : ι → Type*} [TopologicalSpace X] [TopologicalSpace Y]
[TopologicalSpace Z] [∀ i, TopologicalSpace (π i)] {x y z : X} {s : Set X} {f g : X → Y}
/-!
### `Specializes` relation
-/
/-- A collection of equivalent definitions of `x ⤳ y`. The public API is given by `iff` lemmas
below. -/
theorem specializes_TFAE (x y : X) :
TFAE [x ⤳ y,
pure x ≤ 𝓝 y,
∀ s : Set X , IsOpen s → y ∈ s → x ∈ s,
∀ s : Set X , IsClosed s → x ∈ s → y ∈ s,
y ∈ closure ({ x } : Set X),
closure ({ y } : Set X) ⊆ closure { x },
ClusterPt y (pure x)] := by
tfae_have 1 → 2
· exact (pure_le_nhds _).trans
tfae_have 2 → 3
· exact fun h s hso hy => h (hso.mem_nhds hy)
tfae_have 3 → 4
· exact fun h s hsc hx => of_not_not fun hy => h sᶜ hsc.isOpen_compl hy hx
tfae_have 4 → 5
· exact fun h => h _ isClosed_closure (subset_closure <| mem_singleton _)
tfae_have 6 ↔ 5
· exact isClosed_closure.closure_subset_iff.trans singleton_subset_iff
tfae_have 5 ↔ 7
· rw [mem_closure_iff_clusterPt, principal_singleton]
tfae_have 5 → 1
· refine fun h => (nhds_basis_opens _).ge_iff.2 ?_
rintro s ⟨hy, ho⟩
rcases mem_closure_iff.1 h s ho hy with ⟨z, hxs, rfl : z = x⟩
exact ho.mem_nhds hxs
tfae_finish
#align specializes_tfae specializes_TFAE
theorem specializes_iff_nhds : x ⤳ y ↔ 𝓝 x ≤ 𝓝 y :=
Iff.rfl
#align specializes_iff_nhds specializes_iff_nhds
theorem Specializes.not_disjoint (h : x ⤳ y) : ¬Disjoint (𝓝 x) (𝓝 y) := fun hd ↦
absurd (hd.mono_right h) <| by simp [NeBot.ne']
theorem specializes_iff_pure : x ⤳ y ↔ pure x ≤ 𝓝 y :=
(specializes_TFAE x y).out 0 1
#align specializes_iff_pure specializes_iff_pure
alias ⟨Specializes.nhds_le_nhds, _⟩ := specializes_iff_nhds
#align specializes.nhds_le_nhds Specializes.nhds_le_nhds
alias ⟨Specializes.pure_le_nhds, _⟩ := specializes_iff_pure
#align specializes.pure_le_nhds Specializes.pure_le_nhds
theorem ker_nhds_eq_specializes : (𝓝 x).ker = {y | y ⤳ x} := by
ext; simp [specializes_iff_pure, le_def]
theorem specializes_iff_forall_open : x ⤳ y ↔ ∀ s : Set X, IsOpen s → y ∈ s → x ∈ s :=
(specializes_TFAE x y).out 0 2
#align specializes_iff_forall_open specializes_iff_forall_open
theorem Specializes.mem_open (h : x ⤳ y) (hs : IsOpen s) (hy : y ∈ s) : x ∈ s :=
specializes_iff_forall_open.1 h s hs hy
#align specializes.mem_open Specializes.mem_open
theorem IsOpen.not_specializes (hs : IsOpen s) (hx : x ∉ s) (hy : y ∈ s) : ¬x ⤳ y := fun h =>
hx <| h.mem_open hs hy
#align is_open.not_specializes IsOpen.not_specializes
theorem specializes_iff_forall_closed : x ⤳ y ↔ ∀ s : Set X, IsClosed s → x ∈ s → y ∈ s :=
(specializes_TFAE x y).out 0 3
#align specializes_iff_forall_closed specializes_iff_forall_closed
theorem Specializes.mem_closed (h : x ⤳ y) (hs : IsClosed s) (hx : x ∈ s) : y ∈ s :=
specializes_iff_forall_closed.1 h s hs hx
#align specializes.mem_closed Specializes.mem_closed
theorem IsClosed.not_specializes (hs : IsClosed s) (hx : x ∈ s) (hy : y ∉ s) : ¬x ⤳ y := fun h =>
hy <| h.mem_closed hs hx
#align is_closed.not_specializes IsClosed.not_specializes
theorem specializes_iff_mem_closure : x ⤳ y ↔ y ∈ closure ({x} : Set X) :=
(specializes_TFAE x y).out 0 4
#align specializes_iff_mem_closure specializes_iff_mem_closure
alias ⟨Specializes.mem_closure, _⟩ := specializes_iff_mem_closure
#align specializes.mem_closure Specializes.mem_closure
theorem specializes_iff_closure_subset : x ⤳ y ↔ closure ({y} : Set X) ⊆ closure {x} :=
(specializes_TFAE x y).out 0 5
#align specializes_iff_closure_subset specializes_iff_closure_subset
alias ⟨Specializes.closure_subset, _⟩ := specializes_iff_closure_subset
#align specializes.closure_subset Specializes.closure_subset
-- Porting note (#10756): new lemma
theorem specializes_iff_clusterPt : x ⤳ y ↔ ClusterPt y (pure x) :=
(specializes_TFAE x y).out 0 6
theorem Filter.HasBasis.specializes_iff {ι} {p : ι → Prop} {s : ι → Set X}
(h : (𝓝 y).HasBasis p s) : x ⤳ y ↔ ∀ i, p i → x ∈ s i :=
specializes_iff_pure.trans h.ge_iff
#align filter.has_basis.specializes_iff Filter.HasBasis.specializes_iff
theorem specializes_rfl : x ⤳ x := le_rfl
#align specializes_rfl specializes_rfl
@[refl]
theorem specializes_refl (x : X) : x ⤳ x :=
specializes_rfl
#align specializes_refl specializes_refl
@[trans]
theorem Specializes.trans : x ⤳ y → y ⤳ z → x ⤳ z :=
le_trans
#align specializes.trans Specializes.trans
theorem specializes_of_eq (e : x = y) : x ⤳ y :=
e ▸ specializes_refl x
#align specializes_of_eq specializes_of_eq
theorem specializes_of_nhdsWithin (h₁ : 𝓝[s] x ≤ 𝓝[s] y) (h₂ : x ∈ s) : x ⤳ y :=
specializes_iff_pure.2 <|
calc
pure x ≤ 𝓝[s] x := le_inf (pure_le_nhds _) (le_principal_iff.2 h₂)
_ ≤ 𝓝[s] y := h₁
_ ≤ 𝓝 y := inf_le_left
#align specializes_of_nhds_within specializes_of_nhdsWithin
theorem Specializes.map_of_continuousAt (h : x ⤳ y) (hy : ContinuousAt f y) : f x ⤳ f y :=
specializes_iff_pure.2 fun _s hs =>
mem_pure.2 <| mem_preimage.1 <| mem_of_mem_nhds <| hy.mono_left h hs
#align specializes.map_of_continuous_at Specializes.map_of_continuousAt
theorem Specializes.map (h : x ⤳ y) (hf : Continuous f) : f x ⤳ f y :=
h.map_of_continuousAt hf.continuousAt
#align specializes.map Specializes.map
theorem Inducing.specializes_iff (hf : Inducing f) : f x ⤳ f y ↔ x ⤳ y := by
simp only [specializes_iff_mem_closure, hf.closure_eq_preimage_closure_image, image_singleton,
mem_preimage]
#align inducing.specializes_iff Inducing.specializes_iff
theorem subtype_specializes_iff {p : X → Prop} (x y : Subtype p) : x ⤳ y ↔ (x : X) ⤳ y :=
inducing_subtype_val.specializes_iff.symm
#align subtype_specializes_iff subtype_specializes_iff
@[simp]
theorem specializes_prod {x₁ x₂ : X} {y₁ y₂ : Y} : (x₁, y₁) ⤳ (x₂, y₂) ↔ x₁ ⤳ x₂ ∧ y₁ ⤳ y₂ := by
simp only [Specializes, nhds_prod_eq, prod_le_prod]
#align specializes_prod specializes_prod
theorem Specializes.prod {x₁ x₂ : X} {y₁ y₂ : Y} (hx : x₁ ⤳ x₂) (hy : y₁ ⤳ y₂) :
(x₁, y₁) ⤳ (x₂, y₂) :=
specializes_prod.2 ⟨hx, hy⟩
#align specializes.prod Specializes.prod
theorem Specializes.fst {a b : X × Y} (h : a ⤳ b) : a.1 ⤳ b.1 := (specializes_prod.1 h).1
theorem Specializes.snd {a b : X × Y} (h : a ⤳ b) : a.2 ⤳ b.2 := (specializes_prod.1 h).2
@[simp]
theorem specializes_pi {f g : ∀ i, π i} : f ⤳ g ↔ ∀ i, f i ⤳ g i := by
simp only [Specializes, nhds_pi, pi_le_pi]
#align specializes_pi specializes_pi
theorem not_specializes_iff_exists_open : ¬x ⤳ y ↔ ∃ S : Set X, IsOpen S ∧ y ∈ S ∧ x ∉ S := by
rw [specializes_iff_forall_open]
push_neg
rfl
#align not_specializes_iff_exists_open not_specializes_iff_exists_open
theorem not_specializes_iff_exists_closed : ¬x ⤳ y ↔ ∃ S : Set X, IsClosed S ∧ x ∈ S ∧ y ∉ S := by
rw [specializes_iff_forall_closed]
push_neg
rfl
#align not_specializes_iff_exists_closed not_specializes_iff_exists_closed
theorem IsOpen.continuous_piecewise_of_specializes [DecidablePred (· ∈ s)] (hs : IsOpen s)
(hf : Continuous f) (hg : Continuous g) (hspec : ∀ x, f x ⤳ g x) :
Continuous (s.piecewise f g) := by
have : ∀ U, IsOpen U → g ⁻¹' U ⊆ f ⁻¹' U := fun U hU x hx ↦ (hspec x).mem_open hU hx
rw [continuous_def]
intro U hU
rw [piecewise_preimage, ite_eq_of_subset_right _ (this U hU)]
exact hU.preimage hf |>.inter hs |>.union (hU.preimage hg)
theorem IsClosed.continuous_piecewise_of_specializes [DecidablePred (· ∈ s)] (hs : IsClosed s)
(hf : Continuous f) (hg : Continuous g) (hspec : ∀ x, g x ⤳ f x) :
Continuous (s.piecewise f g) := by
simpa only [piecewise_compl] using hs.isOpen_compl.continuous_piecewise_of_specializes hg hf hspec
/-- A continuous function is monotone with respect to the specialization preorders on the domain and
the codomain. -/
theorem Continuous.specialization_monotone (hf : Continuous f) :
@Monotone _ _ (specializationPreorder X) (specializationPreorder Y) f := fun _ _ h => h.map hf
#align continuous.specialization_monotone Continuous.specialization_monotone
/-!
### `Inseparable` relation
-/
local infixl:0 " ~ᵢ " => Inseparable
theorem inseparable_def : (x ~ᵢ y) ↔ 𝓝 x = 𝓝 y :=
Iff.rfl
#align inseparable_def inseparable_def
theorem inseparable_iff_specializes_and : (x ~ᵢ y) ↔ x ⤳ y ∧ y ⤳ x :=
le_antisymm_iff
#align inseparable_iff_specializes_and inseparable_iff_specializes_and
theorem Inseparable.specializes (h : x ~ᵢ y) : x ⤳ y := h.le
#align inseparable.specializes Inseparable.specializes
theorem Inseparable.specializes' (h : x ~ᵢ y) : y ⤳ x := h.ge
#align inseparable.specializes' Inseparable.specializes'
theorem Specializes.antisymm (h₁ : x ⤳ y) (h₂ : y ⤳ x) : x ~ᵢ y :=
le_antisymm h₁ h₂
#align specializes.antisymm Specializes.antisymm
theorem inseparable_iff_forall_open : (x ~ᵢ y) ↔ ∀ s : Set X, IsOpen s → (x ∈ s ↔ y ∈ s) := by
simp only [inseparable_iff_specializes_and, specializes_iff_forall_open, ← forall_and, ← iff_def,
Iff.comm]
#align inseparable_iff_forall_open inseparable_iff_forall_open
theorem not_inseparable_iff_exists_open :
¬(x ~ᵢ y) ↔ ∃ s : Set X, IsOpen s ∧ Xor' (x ∈ s) (y ∈ s) := by
simp [inseparable_iff_forall_open, ← xor_iff_not_iff]
#align not_inseparable_iff_exists_open not_inseparable_iff_exists_open
theorem inseparable_iff_forall_closed : (x ~ᵢ y) ↔ ∀ s : Set X, IsClosed s → (x ∈ s ↔ y ∈ s) := by
simp only [inseparable_iff_specializes_and, specializes_iff_forall_closed, ← forall_and, ←
iff_def]
#align inseparable_iff_forall_closed inseparable_iff_forall_closed
theorem inseparable_iff_mem_closure :
(x ~ᵢ y) ↔ x ∈ closure ({y} : Set X) ∧ y ∈ closure ({x} : Set X) :=
inseparable_iff_specializes_and.trans <| by simp only [specializes_iff_mem_closure, and_comm]
#align inseparable_iff_mem_closure inseparable_iff_mem_closure
theorem inseparable_iff_closure_eq : (x ~ᵢ y) ↔ closure ({x} : Set X) = closure {y} := by
simp only [inseparable_iff_specializes_and, specializes_iff_closure_subset, ← subset_antisymm_iff,
eq_comm]
#align inseparable_iff_closure_eq inseparable_iff_closure_eq
theorem inseparable_of_nhdsWithin_eq (hx : x ∈ s) (hy : y ∈ s) (h : 𝓝[s] x = 𝓝[s] y) : x ~ᵢ y :=
(specializes_of_nhdsWithin h.le hx).antisymm (specializes_of_nhdsWithin h.ge hy)
#align inseparable_of_nhds_within_eq inseparable_of_nhdsWithin_eq
theorem Inducing.inseparable_iff (hf : Inducing f) : (f x ~ᵢ f y) ↔ (x ~ᵢ y) := by
simp only [inseparable_iff_specializes_and, hf.specializes_iff]
#align inducing.inseparable_iff Inducing.inseparable_iff
theorem subtype_inseparable_iff {p : X → Prop} (x y : Subtype p) : (x ~ᵢ y) ↔ ((x : X) ~ᵢ y) :=
inducing_subtype_val.inseparable_iff.symm
#align subtype_inseparable_iff subtype_inseparable_iff
@[simp] theorem inseparable_prod {x₁ x₂ : X} {y₁ y₂ : Y} :
((x₁, y₁) ~ᵢ (x₂, y₂)) ↔ (x₁ ~ᵢ x₂) ∧ (y₁ ~ᵢ y₂) := by
simp only [Inseparable, nhds_prod_eq, prod_inj]
#align inseparable_prod inseparable_prod
theorem Inseparable.prod {x₁ x₂ : X} {y₁ y₂ : Y} (hx : x₁ ~ᵢ x₂) (hy : y₁ ~ᵢ y₂) :
(x₁, y₁) ~ᵢ (x₂, y₂) :=
inseparable_prod.2 ⟨hx, hy⟩
#align inseparable.prod Inseparable.prod
@[simp]
theorem inseparable_pi {f g : ∀ i, π i} : (f ~ᵢ g) ↔ ∀ i, f i ~ᵢ g i := by
simp only [Inseparable, nhds_pi, funext_iff, pi_inj]
#align inseparable_pi inseparable_pi
namespace Inseparable
@[refl]
theorem refl (x : X) : x ~ᵢ x :=
Eq.refl (𝓝 x)
#align inseparable.refl Inseparable.refl
theorem rfl : x ~ᵢ x :=
refl x
#align inseparable.rfl Inseparable.rfl
theorem of_eq (e : x = y) : Inseparable x y :=
e ▸ refl x
#align inseparable.of_eq Inseparable.of_eq
@[symm]
nonrec theorem symm (h : x ~ᵢ y) : y ~ᵢ x := h.symm
#align inseparable.symm Inseparable.symm
@[trans]
nonrec theorem trans (h₁ : x ~ᵢ y) (h₂ : y ~ᵢ z) : x ~ᵢ z := h₁.trans h₂
#align inseparable.trans Inseparable.trans
theorem nhds_eq (h : x ~ᵢ y) : 𝓝 x = 𝓝 y := h
#align inseparable.nhds_eq Inseparable.nhds_eq
theorem mem_open_iff (h : x ~ᵢ y) (hs : IsOpen s) : x ∈ s ↔ y ∈ s :=
inseparable_iff_forall_open.1 h s hs
#align inseparable.mem_open_iff Inseparable.mem_open_iff
theorem mem_closed_iff (h : x ~ᵢ y) (hs : IsClosed s) : x ∈ s ↔ y ∈ s :=
inseparable_iff_forall_closed.1 h s hs
#align inseparable.mem_closed_iff Inseparable.mem_closed_iff
theorem map_of_continuousAt (h : x ~ᵢ y) (hx : ContinuousAt f x) (hy : ContinuousAt f y) :
f x ~ᵢ f y :=
(h.specializes.map_of_continuousAt hy).antisymm (h.specializes'.map_of_continuousAt hx)
#align inseparable.map_of_continuous_at Inseparable.map_of_continuousAt
theorem map (h : x ~ᵢ y) (hf : Continuous f) : f x ~ᵢ f y :=
h.map_of_continuousAt hf.continuousAt hf.continuousAt
#align inseparable.map Inseparable.map
end Inseparable
theorem IsClosed.not_inseparable (hs : IsClosed s) (hx : x ∈ s) (hy : y ∉ s) : ¬(x ~ᵢ y) := fun h =>
hy <| (h.mem_closed_iff hs).1 hx
#align is_closed.not_inseparable IsClosed.not_inseparable
theorem IsOpen.not_inseparable (hs : IsOpen s) (hx : x ∈ s) (hy : y ∉ s) : ¬(x ~ᵢ y) := fun h =>
hy <| (h.mem_open_iff hs).1 hx
#align is_open.not_inseparable IsOpen.not_inseparable
/-!
### Separation quotient
In this section we define the quotient of a topological space by the `Inseparable` relation.
-/
variable (X)
instance : TopologicalSpace (SeparationQuotient X) := instTopologicalSpaceQuotient
variable {X}
variable {t : Set (SeparationQuotient X)}
namespace SeparationQuotient
/-- The natural map from a topological space to its separation quotient. -/
def mk : X → SeparationQuotient X := Quotient.mk''
#align separation_quotient.mk SeparationQuotient.mk
theorem quotientMap_mk : QuotientMap (mk : X → SeparationQuotient X) :=
quotientMap_quot_mk
#align separation_quotient.quotient_map_mk SeparationQuotient.quotientMap_mk
theorem continuous_mk : Continuous (mk : X → SeparationQuotient X) :=
continuous_quot_mk
#align separation_quotient.continuous_mk SeparationQuotient.continuous_mk
@[simp]
theorem mk_eq_mk : mk x = mk y ↔ (x ~ᵢ y) :=
Quotient.eq''
#align separation_quotient.mk_eq_mk SeparationQuotient.mk_eq_mk
theorem surjective_mk : Surjective (mk : X → SeparationQuotient X) :=
surjective_quot_mk _
#align separation_quotient.surjective_mk SeparationQuotient.surjective_mk
@[simp]
theorem range_mk : range (mk : X → SeparationQuotient X) = univ :=
surjective_mk.range_eq
#align separation_quotient.range_mk SeparationQuotient.range_mk
instance [Nonempty X] : Nonempty (SeparationQuotient X) :=
Nonempty.map mk ‹_›
instance [Inhabited X] : Inhabited (SeparationQuotient X) :=
⟨mk default⟩
instance [Subsingleton X] : Subsingleton (SeparationQuotient X) :=
surjective_mk.subsingleton
theorem preimage_image_mk_open (hs : IsOpen s) : mk ⁻¹' (mk '' s) = s := by
refine Subset.antisymm ?_ (subset_preimage_image _ _)
rintro x ⟨y, hys, hxy⟩
exact ((mk_eq_mk.1 hxy).mem_open_iff hs).1 hys
#align separation_quotient.preimage_image_mk_open SeparationQuotient.preimage_image_mk_open
theorem isOpenMap_mk : IsOpenMap (mk : X → SeparationQuotient X) := fun s hs =>
quotientMap_mk.isOpen_preimage.1 <| by rwa [preimage_image_mk_open hs]
#align separation_quotient.is_open_map_mk SeparationQuotient.isOpenMap_mk
theorem preimage_image_mk_closed (hs : IsClosed s) : mk ⁻¹' (mk '' s) = s := by
refine Subset.antisymm ?_ (subset_preimage_image _ _)
rintro x ⟨y, hys, hxy⟩
exact ((mk_eq_mk.1 hxy).mem_closed_iff hs).1 hys
#align separation_quotient.preimage_image_mk_closed SeparationQuotient.preimage_image_mk_closed
theorem inducing_mk : Inducing (mk : X → SeparationQuotient X) :=
⟨le_antisymm (continuous_iff_le_induced.1 continuous_mk) fun s hs =>
⟨mk '' s, isOpenMap_mk s hs, preimage_image_mk_open hs⟩⟩
#align separation_quotient.inducing_mk SeparationQuotient.inducing_mk
theorem isClosedMap_mk : IsClosedMap (mk : X → SeparationQuotient X) :=
inducing_mk.isClosedMap <| by rw [range_mk]; exact isClosed_univ
#align separation_quotient.is_closed_map_mk SeparationQuotient.isClosedMap_mk
@[simp]
theorem comap_mk_nhds_mk : comap mk (𝓝 (mk x)) = 𝓝 x :=
(inducing_mk.nhds_eq_comap _).symm
#align separation_quotient.comap_mk_nhds_mk SeparationQuotient.comap_mk_nhds_mk
@[simp]
theorem comap_mk_nhdsSet_image : comap mk (𝓝ˢ (mk '' s)) = 𝓝ˢ s :=
(inducing_mk.nhdsSet_eq_comap _).symm
#align separation_quotient.comap_mk_nhds_set_image SeparationQuotient.comap_mk_nhdsSet_image
theorem map_mk_nhds : map mk (𝓝 x) = 𝓝 (mk x) := by
rw [← comap_mk_nhds_mk, map_comap_of_surjective surjective_mk]
#align separation_quotient.map_mk_nhds SeparationQuotient.map_mk_nhds
theorem map_mk_nhdsSet : map mk (𝓝ˢ s) = 𝓝ˢ (mk '' s) := by
rw [← comap_mk_nhdsSet_image, map_comap_of_surjective surjective_mk]
#align separation_quotient.map_mk_nhds_set SeparationQuotient.map_mk_nhdsSet
theorem comap_mk_nhdsSet : comap mk (𝓝ˢ t) = 𝓝ˢ (mk ⁻¹' t) := by
conv_lhs => rw [← image_preimage_eq t surjective_mk, comap_mk_nhdsSet_image]
#align separation_quotient.comap_mk_nhds_set SeparationQuotient.comap_mk_nhdsSet
theorem preimage_mk_closure : mk ⁻¹' closure t = closure (mk ⁻¹' t) :=
isOpenMap_mk.preimage_closure_eq_closure_preimage continuous_mk t
#align separation_quotient.preimage_mk_closure SeparationQuotient.preimage_mk_closure
theorem preimage_mk_interior : mk ⁻¹' interior t = interior (mk ⁻¹' t) :=
isOpenMap_mk.preimage_interior_eq_interior_preimage continuous_mk t
#align separation_quotient.preimage_mk_interior SeparationQuotient.preimage_mk_interior
theorem preimage_mk_frontier : mk ⁻¹' frontier t = frontier (mk ⁻¹' t) :=
isOpenMap_mk.preimage_frontier_eq_frontier_preimage continuous_mk t
#align separation_quotient.preimage_mk_frontier SeparationQuotient.preimage_mk_frontier
theorem image_mk_closure : mk '' closure s = closure (mk '' s) :=
(image_closure_subset_closure_image continuous_mk).antisymm <|
isClosedMap_mk.closure_image_subset _
#align separation_quotient.image_mk_closure SeparationQuotient.image_mk_closure
| Mathlib/Topology/Inseparable.lean | 482 | 484 | theorem map_prod_map_mk_nhds (x : X) (y : Y) :
map (Prod.map mk mk) (𝓝 (x, y)) = 𝓝 (mk x, mk y) := by |
rw [nhds_prod_eq, ← prod_map_map_eq', map_mk_nhds, map_mk_nhds, nhds_prod_eq]
|
/-
Copyright (c) 2020 Yury Kudryashov, Anne Baanen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury Kudryashov, Anne Baanen
-/
import Mathlib.Algebra.BigOperators.Ring
import Mathlib.Data.Fintype.BigOperators
import Mathlib.Data.Fintype.Fin
import Mathlib.GroupTheory.GroupAction.Pi
import Mathlib.Logic.Equiv.Fin
#align_import algebra.big_operators.fin from "leanprover-community/mathlib"@"cc5dd6244981976cc9da7afc4eee5682b037a013"
/-!
# Big operators and `Fin`
Some results about products and sums over the type `Fin`.
The most important results are the induction formulas `Fin.prod_univ_castSucc`
and `Fin.prod_univ_succ`, and the formula `Fin.prod_const` for the product of a
constant function. These results have variants for sums instead of products.
## Main declarations
* `finFunctionFinEquiv`: An explicit equivalence between `Fin n → Fin m` and `Fin (m ^ n)`.
-/
open Finset
variable {α : Type*} {β : Type*}
namespace Finset
@[to_additive]
theorem prod_range [CommMonoid β] {n : ℕ} (f : ℕ → β) :
∏ i ∈ Finset.range n, f i = ∏ i : Fin n, f i :=
(Fin.prod_univ_eq_prod_range _ _).symm
#align finset.prod_range Finset.prod_range
#align finset.sum_range Finset.sum_range
end Finset
namespace Fin
@[to_additive]
theorem prod_ofFn [CommMonoid β] {n : ℕ} (f : Fin n → β) : (List.ofFn f).prod = ∏ i, f i := by
simp [prod_eq_multiset_prod]
#align fin.prod_of_fn Fin.prod_ofFn
#align fin.sum_of_fn Fin.sum_ofFn
@[to_additive]
theorem prod_univ_def [CommMonoid β] {n : ℕ} (f : Fin n → β) :
∏ i, f i = ((List.finRange n).map f).prod := by
rw [← List.ofFn_eq_map, prod_ofFn]
#align fin.prod_univ_def Fin.prod_univ_def
#align fin.sum_univ_def Fin.sum_univ_def
/-- A product of a function `f : Fin 0 → β` is `1` because `Fin 0` is empty -/
@[to_additive "A sum of a function `f : Fin 0 → β` is `0` because `Fin 0` is empty"]
theorem prod_univ_zero [CommMonoid β] (f : Fin 0 → β) : ∏ i, f i = 1 :=
rfl
#align fin.prod_univ_zero Fin.prod_univ_zero
#align fin.sum_univ_zero Fin.sum_univ_zero
/-- A product of a function `f : Fin (n + 1) → β` over all `Fin (n + 1)`
is the product of `f x`, for some `x : Fin (n + 1)` times the remaining product -/
@[to_additive "A sum of a function `f : Fin (n + 1) → β` over all `Fin (n + 1)` is the sum of
`f x`, for some `x : Fin (n + 1)` plus the remaining product"]
theorem prod_univ_succAbove [CommMonoid β] {n : ℕ} (f : Fin (n + 1) → β) (x : Fin (n + 1)) :
∏ i, f i = f x * ∏ i : Fin n, f (x.succAbove i) := by
rw [univ_succAbove, prod_cons, Finset.prod_map _ x.succAboveEmb]
rfl
#align fin.prod_univ_succ_above Fin.prod_univ_succAbove
#align fin.sum_univ_succ_above Fin.sum_univ_succAbove
/-- A product of a function `f : Fin (n + 1) → β` over all `Fin (n + 1)`
is the product of `f 0` plus the remaining product -/
@[to_additive "A sum of a function `f : Fin (n + 1) → β` over all `Fin (n + 1)` is the sum of
`f 0` plus the remaining product"]
theorem prod_univ_succ [CommMonoid β] {n : ℕ} (f : Fin (n + 1) → β) :
∏ i, f i = f 0 * ∏ i : Fin n, f i.succ :=
prod_univ_succAbove f 0
#align fin.prod_univ_succ Fin.prod_univ_succ
#align fin.sum_univ_succ Fin.sum_univ_succ
/-- A product of a function `f : Fin (n + 1) → β` over all `Fin (n + 1)`
is the product of `f (Fin.last n)` plus the remaining product -/
@[to_additive "A sum of a function `f : Fin (n + 1) → β` over all `Fin (n + 1)` is the sum of
`f (Fin.last n)` plus the remaining sum"]
theorem prod_univ_castSucc [CommMonoid β] {n : ℕ} (f : Fin (n + 1) → β) :
∏ i, f i = (∏ i : Fin n, f (Fin.castSucc i)) * f (last n) := by
simpa [mul_comm] using prod_univ_succAbove f (last n)
#align fin.prod_univ_cast_succ Fin.prod_univ_castSucc
#align fin.sum_univ_cast_succ Fin.sum_univ_castSucc
@[to_additive (attr := simp)]
theorem prod_univ_get [CommMonoid α] (l : List α) : ∏ i, l.get i = l.prod := by
simp [Finset.prod_eq_multiset_prod]
@[to_additive (attr := simp)]
theorem prod_univ_get' [CommMonoid β] (l : List α) (f : α → β) :
∏ i, f (l.get i) = (l.map f).prod := by
simp [Finset.prod_eq_multiset_prod]
@[to_additive]
theorem prod_cons [CommMonoid β] {n : ℕ} (x : β) (f : Fin n → β) :
(∏ i : Fin n.succ, (cons x f : Fin n.succ → β) i) = x * ∏ i : Fin n, f i := by
simp_rw [prod_univ_succ, cons_zero, cons_succ]
#align fin.prod_cons Fin.prod_cons
#align fin.sum_cons Fin.sum_cons
@[to_additive sum_univ_one]
theorem prod_univ_one [CommMonoid β] (f : Fin 1 → β) : ∏ i, f i = f 0 := by simp
#align fin.prod_univ_one Fin.prod_univ_one
#align fin.sum_univ_one Fin.sum_univ_one
@[to_additive (attr := simp)]
theorem prod_univ_two [CommMonoid β] (f : Fin 2 → β) : ∏ i, f i = f 0 * f 1 := by
simp [prod_univ_succ]
#align fin.prod_univ_two Fin.prod_univ_two
#align fin.sum_univ_two Fin.sum_univ_two
@[to_additive]
theorem prod_univ_two' [CommMonoid β] (f : α → β) (a b : α) :
∏ i, f (![a, b] i) = f a * f b :=
prod_univ_two _
@[to_additive]
theorem prod_univ_three [CommMonoid β] (f : Fin 3 → β) : ∏ i, f i = f 0 * f 1 * f 2 := by
rw [prod_univ_castSucc, prod_univ_two]
rfl
#align fin.prod_univ_three Fin.prod_univ_three
#align fin.sum_univ_three Fin.sum_univ_three
@[to_additive]
theorem prod_univ_four [CommMonoid β] (f : Fin 4 → β) : ∏ i, f i = f 0 * f 1 * f 2 * f 3 := by
rw [prod_univ_castSucc, prod_univ_three]
rfl
#align fin.prod_univ_four Fin.prod_univ_four
#align fin.sum_univ_four Fin.sum_univ_four
@[to_additive]
theorem prod_univ_five [CommMonoid β] (f : Fin 5 → β) :
∏ i, f i = f 0 * f 1 * f 2 * f 3 * f 4 := by
rw [prod_univ_castSucc, prod_univ_four]
rfl
#align fin.prod_univ_five Fin.prod_univ_five
#align fin.sum_univ_five Fin.sum_univ_five
@[to_additive]
theorem prod_univ_six [CommMonoid β] (f : Fin 6 → β) :
∏ i, f i = f 0 * f 1 * f 2 * f 3 * f 4 * f 5 := by
rw [prod_univ_castSucc, prod_univ_five]
rfl
#align fin.prod_univ_six Fin.prod_univ_six
#align fin.sum_univ_six Fin.sum_univ_six
@[to_additive]
theorem prod_univ_seven [CommMonoid β] (f : Fin 7 → β) :
∏ i, f i = f 0 * f 1 * f 2 * f 3 * f 4 * f 5 * f 6 := by
rw [prod_univ_castSucc, prod_univ_six]
rfl
#align fin.prod_univ_seven Fin.prod_univ_seven
#align fin.sum_univ_seven Fin.sum_univ_seven
@[to_additive]
theorem prod_univ_eight [CommMonoid β] (f : Fin 8 → β) :
∏ i, f i = f 0 * f 1 * f 2 * f 3 * f 4 * f 5 * f 6 * f 7 := by
rw [prod_univ_castSucc, prod_univ_seven]
rfl
#align fin.prod_univ_eight Fin.prod_univ_eight
#align fin.sum_univ_eight Fin.sum_univ_eight
theorem sum_pow_mul_eq_add_pow {n : ℕ} {R : Type*} [CommSemiring R] (a b : R) :
(∑ s : Finset (Fin n), a ^ s.card * b ^ (n - s.card)) = (a + b) ^ n := by
simpa using Fintype.sum_pow_mul_eq_add_pow (Fin n) a b
#align fin.sum_pow_mul_eq_add_pow Fin.sum_pow_mul_eq_add_pow
theorem prod_const [CommMonoid α] (n : ℕ) (x : α) : ∏ _i : Fin n, x = x ^ n := by simp
#align fin.prod_const Fin.prod_const
theorem sum_const [AddCommMonoid α] (n : ℕ) (x : α) : ∑ _i : Fin n, x = n • x := by simp
#align fin.sum_const Fin.sum_const
@[to_additive]
theorem prod_Ioi_zero {M : Type*} [CommMonoid M] {n : ℕ} {v : Fin n.succ → M} :
∏ i ∈ Ioi 0, v i = ∏ j : Fin n, v j.succ := by
rw [Ioi_zero_eq_map, Finset.prod_map, val_succEmb]
#align fin.prod_Ioi_zero Fin.prod_Ioi_zero
#align fin.sum_Ioi_zero Fin.sum_Ioi_zero
@[to_additive]
theorem prod_Ioi_succ {M : Type*} [CommMonoid M] {n : ℕ} (i : Fin n) (v : Fin n.succ → M) :
∏ j ∈ Ioi i.succ, v j = ∏ j ∈ Ioi i, v j.succ := by
rw [Ioi_succ, Finset.prod_map, val_succEmb]
#align fin.prod_Ioi_succ Fin.prod_Ioi_succ
#align fin.sum_Ioi_succ Fin.sum_Ioi_succ
@[to_additive]
theorem prod_congr' {M : Type*} [CommMonoid M] {a b : ℕ} (f : Fin b → M) (h : a = b) :
(∏ i : Fin a, f (cast h i)) = ∏ i : Fin b, f i := by
subst h
congr
#align fin.prod_congr' Fin.prod_congr'
#align fin.sum_congr' Fin.sum_congr'
@[to_additive]
theorem prod_univ_add {M : Type*} [CommMonoid M] {a b : ℕ} (f : Fin (a + b) → M) :
(∏ i : Fin (a + b), f i) = (∏ i : Fin a, f (castAdd b i)) * ∏ i : Fin b, f (natAdd a i) := by
rw [Fintype.prod_equiv finSumFinEquiv.symm f fun i => f (finSumFinEquiv.toFun i)]
· apply Fintype.prod_sum_type
· intro x
simp only [Equiv.toFun_as_coe, Equiv.apply_symm_apply]
#align fin.prod_univ_add Fin.prod_univ_add
#align fin.sum_univ_add Fin.sum_univ_add
@[to_additive]
theorem prod_trunc {M : Type*} [CommMonoid M] {a b : ℕ} (f : Fin (a + b) → M)
(hf : ∀ j : Fin b, f (natAdd a j) = 1) :
(∏ i : Fin (a + b), f i) = ∏ i : Fin a, f (castLE (Nat.le.intro rfl) i) := by
rw [prod_univ_add, Fintype.prod_eq_one _ hf, mul_one]
rfl
#align fin.prod_trunc Fin.prod_trunc
#align fin.sum_trunc Fin.sum_trunc
section PartialProd
variable [Monoid α] {n : ℕ}
/-- For `f = (a₁, ..., aₙ)` in `αⁿ`, `partialProd f` is `(1, a₁, a₁a₂, ..., a₁...aₙ)` in `αⁿ⁺¹`. -/
@[to_additive "For `f = (a₁, ..., aₙ)` in `αⁿ`, `partialSum f` is\n
`(0, a₁, a₁ + a₂, ..., a₁ + ... + aₙ)` in `αⁿ⁺¹`."]
def partialProd (f : Fin n → α) (i : Fin (n + 1)) : α :=
((List.ofFn f).take i).prod
#align fin.partial_prod Fin.partialProd
#align fin.partial_sum Fin.partialSum
@[to_additive (attr := simp)]
theorem partialProd_zero (f : Fin n → α) : partialProd f 0 = 1 := by simp [partialProd]
#align fin.partial_prod_zero Fin.partialProd_zero
#align fin.partial_sum_zero Fin.partialSum_zero
@[to_additive]
theorem partialProd_succ (f : Fin n → α) (j : Fin n) :
partialProd f j.succ = partialProd f (Fin.castSucc j) * f j := by
simp [partialProd, List.take_succ, List.ofFnNthVal, dif_pos j.is_lt]
#align fin.partial_prod_succ Fin.partialProd_succ
#align fin.partial_sum_succ Fin.partialSum_succ
@[to_additive]
theorem partialProd_succ' (f : Fin (n + 1) → α) (j : Fin (n + 1)) :
partialProd f j.succ = f 0 * partialProd (Fin.tail f) j := by
simp [partialProd]
rfl
#align fin.partial_prod_succ' Fin.partialProd_succ'
#align fin.partial_sum_succ' Fin.partialSum_succ'
@[to_additive]
theorem partialProd_left_inv {G : Type*} [Group G] (f : Fin (n + 1) → G) :
(f 0 • partialProd fun i : Fin n => (f i)⁻¹ * f i.succ) = f :=
funext fun x => Fin.inductionOn x (by simp) fun x hx => by
simp only [coe_eq_castSucc, Pi.smul_apply, smul_eq_mul] at hx ⊢
rw [partialProd_succ, ← mul_assoc, hx, mul_inv_cancel_left]
#align fin.partial_prod_left_inv Fin.partialProd_left_inv
#align fin.partial_sum_left_neg Fin.partialSum_left_neg
@[to_additive]
theorem partialProd_right_inv {G : Type*} [Group G] (f : Fin n → G) (i : Fin n) :
(partialProd f (Fin.castSucc i))⁻¹ * partialProd f i.succ = f i := by
cases' i with i hn
induction i with
| zero => simp [-Fin.succ_mk, partialProd_succ]
| succ i hi =>
specialize hi (lt_trans (Nat.lt_succ_self i) hn)
simp only [Fin.coe_eq_castSucc, Fin.succ_mk, Fin.castSucc_mk] at hi ⊢
rw [← Fin.succ_mk _ _ (lt_trans (Nat.lt_succ_self _) hn), ← Fin.succ_mk _ _ hn]
simp only [partialProd_succ, mul_inv_rev, Fin.castSucc_mk]
-- Porting note: was
-- assoc_rw [hi, inv_mul_cancel_left]
rw [← mul_assoc, mul_left_eq_self, mul_assoc, hi, mul_left_inv]
#align fin.partial_prod_right_inv Fin.partialProd_right_inv
#align fin.partial_sum_right_neg Fin.partialSum_right_neg
/-- Let `(g₀, g₁, ..., gₙ)` be a tuple of elements in `Gⁿ⁺¹`.
Then if `k < j`, this says `(g₀g₁...gₖ₋₁)⁻¹ * g₀g₁...gₖ = gₖ`.
If `k = j`, it says `(g₀g₁...gₖ₋₁)⁻¹ * g₀g₁...gₖ₊₁ = gₖgₖ₊₁`.
If `k > j`, it says `(g₀g₁...gₖ)⁻¹ * g₀g₁...gₖ₊₁ = gₖ₊₁.`
Useful for defining group cohomology. -/
@[to_additive
"Let `(g₀, g₁, ..., gₙ)` be a tuple of elements in `Gⁿ⁺¹`.
Then if `k < j`, this says `-(g₀ + g₁ + ... + gₖ₋₁) + (g₀ + g₁ + ... + gₖ) = gₖ`.
If `k = j`, it says `-(g₀ + g₁ + ... + gₖ₋₁) + (g₀ + g₁ + ... + gₖ₊₁) = gₖ + gₖ₊₁`.
If `k > j`, it says `-(g₀ + g₁ + ... + gₖ) + (g₀ + g₁ + ... + gₖ₊₁) = gₖ₊₁.`
Useful for defining group cohomology."]
theorem inv_partialProd_mul_eq_contractNth {G : Type*} [Group G] (g : Fin (n + 1) → G)
(j : Fin (n + 1)) (k : Fin n) :
(partialProd g (j.succ.succAbove (Fin.castSucc k)))⁻¹ * partialProd g (j.succAbove k).succ =
j.contractNth (· * ·) g k := by
rcases lt_trichotomy (k : ℕ) j with (h | h | h)
· rwa [succAbove_of_castSucc_lt, succAbove_of_castSucc_lt, partialProd_right_inv,
contractNth_apply_of_lt]
· assumption
· rw [castSucc_lt_iff_succ_le, succ_le_succ_iff, le_iff_val_le_val]
exact le_of_lt h
· rwa [succAbove_of_castSucc_lt, succAbove_of_le_castSucc, partialProd_succ,
castSucc_fin_succ, ← mul_assoc,
partialProd_right_inv, contractNth_apply_of_eq]
· simp [le_iff_val_le_val, ← h]
· rw [castSucc_lt_iff_succ_le, succ_le_succ_iff, le_iff_val_le_val]
exact le_of_eq h
· rwa [succAbove_of_le_castSucc, succAbove_of_le_castSucc, partialProd_succ, partialProd_succ,
castSucc_fin_succ, partialProd_succ, inv_mul_cancel_left, contractNth_apply_of_gt]
· exact le_iff_val_le_val.2 (le_of_lt h)
· rw [le_iff_val_le_val, val_succ]
exact Nat.succ_le_of_lt h
#align fin.inv_partial_prod_mul_eq_contract_nth Fin.inv_partialProd_mul_eq_contractNth
#align fin.neg_partial_sum_add_eq_contract_nth Fin.neg_partialSum_add_eq_contractNth
end PartialProd
end Fin
/-- Equivalence between `Fin n → Fin m` and `Fin (m ^ n)`. -/
@[simps!]
def finFunctionFinEquiv {m n : ℕ} : (Fin n → Fin m) ≃ Fin (m ^ n) :=
Equiv.ofRightInverseOfCardLE (le_of_eq <| by simp_rw [Fintype.card_fun, Fintype.card_fin])
(fun f => ⟨∑ i, f i * m ^ (i : ℕ), by
induction' n with n ih
· simp
cases m
· exact isEmptyElim (f <| Fin.last _)
simp_rw [Fin.sum_univ_castSucc, Fin.coe_castSucc, Fin.val_last]
refine (Nat.add_lt_add_of_lt_of_le (ih _) <| Nat.mul_le_mul_right _ (Fin.is_le _)).trans_eq ?_
rw [← one_add_mul (_ : ℕ), add_comm, pow_succ']⟩)
(fun a b => ⟨a / m ^ (b : ℕ) % m, by
cases' n with n
· exact b.elim0
cases' m with m
· rw [zero_pow n.succ_ne_zero] at a
exact a.elim0
· exact Nat.mod_lt _ m.succ_pos⟩)
fun a => by
dsimp
induction' n with n ih
· haveI : Subsingleton (Fin (m ^ 0)) := (finCongr <| pow_zero _).subsingleton
exact Subsingleton.elim _ _
simp_rw [Fin.forall_iff, Fin.ext_iff] at ih
ext
simp_rw [Fin.sum_univ_succ, Fin.val_zero, Fin.val_succ, pow_zero, Nat.div_one,
mul_one, pow_succ', ← Nat.div_div_eq_div_mul, mul_left_comm _ m, ← mul_sum]
rw [ih _ (Nat.div_lt_of_lt_mul ?_), Nat.mod_add_div]
-- Porting note: replaces `a.is_lt` in the wildcard above. Caused by a refactor of the `npow`
-- instance for `Fin`.
exact a.is_lt.trans_eq (pow_succ' _ _)
#align fin_function_fin_equiv finFunctionFinEquiv
theorem finFunctionFinEquiv_apply {m n : ℕ} (f : Fin n → Fin m) :
(finFunctionFinEquiv f : ℕ) = ∑ i : Fin n, ↑(f i) * m ^ (i : ℕ) :=
rfl
#align fin_function_fin_equiv_apply finFunctionFinEquiv_apply
theorem finFunctionFinEquiv_single {m n : ℕ} [NeZero m] (i : Fin n) (j : Fin m) :
(finFunctionFinEquiv (Pi.single i j) : ℕ) = j * m ^ (i : ℕ) := by
rw [finFunctionFinEquiv_apply, Fintype.sum_eq_single i, Pi.single_eq_same]
rintro x hx
rw [Pi.single_eq_of_ne hx, Fin.val_zero', zero_mul]
#align fin_function_fin_equiv_single finFunctionFinEquiv_single
/-- Equivalence between `∀ i : Fin m, Fin (n i)` and `Fin (∏ i : Fin m, n i)`. -/
def finPiFinEquiv {m : ℕ} {n : Fin m → ℕ} : (∀ i : Fin m, Fin (n i)) ≃ Fin (∏ i : Fin m, n i) :=
Equiv.ofRightInverseOfCardLE (le_of_eq <| by simp_rw [Fintype.card_pi, Fintype.card_fin])
(fun f => ⟨∑ i, f i * ∏ j, n (Fin.castLE i.is_lt.le j), by
induction' m with m ih
· simp
rw [Fin.prod_univ_castSucc, Fin.sum_univ_castSucc]
suffices
∀ (n : Fin m → ℕ) (nn : ℕ) (f : ∀ i : Fin m, Fin (n i)) (fn : Fin nn),
((∑ i : Fin m, ↑(f i) * ∏ j : Fin i, n (Fin.castLE i.prop.le j)) + ↑fn * ∏ j, n j) <
(∏ i : Fin m, n i) * nn by
replace := this (Fin.init n) (n (Fin.last _)) (Fin.init f) (f (Fin.last _))
rw [← Fin.snoc_init_self f]
simp (config := { singlePass := true }) only [← Fin.snoc_init_self n]
simp_rw [Fin.snoc_castSucc, Fin.snoc_last, Fin.snoc_init_self n]
exact this
intro n nn f fn
cases nn
· exact isEmptyElim fn
refine (Nat.add_lt_add_of_lt_of_le (ih _) <| Nat.mul_le_mul_right _ (Fin.is_le _)).trans_eq ?_
rw [← one_add_mul (_ : ℕ), mul_comm, add_comm]⟩)
(fun a b => ⟨(a / ∏ j : Fin b, n (Fin.castLE b.is_lt.le j)) % n b, by
cases m
· exact b.elim0
cases' h : n b with nb
· rw [prod_eq_zero (Finset.mem_univ _) h] at a
exact isEmptyElim a
exact Nat.mod_lt _ nb.succ_pos⟩)
(by
intro a; revert a; dsimp only [Fin.val_mk]
refine Fin.consInduction ?_ ?_ n
· intro a
haveI : Subsingleton (Fin (∏ i : Fin 0, i.elim0)) :=
(finCongr <| prod_empty).subsingleton
exact Subsingleton.elim _ _
· intro n x xs ih a
simp_rw [Fin.forall_iff, Fin.ext_iff] at ih
ext
simp_rw [Fin.sum_univ_succ, Fin.cons_succ]
have := fun i : Fin n =>
Fintype.prod_equiv (finCongr <| Fin.val_succ i)
(fun j => (Fin.cons x xs : _ → ℕ) (Fin.castLE (Fin.is_lt _).le j))
(fun j => (Fin.cons x xs : _ → ℕ) (Fin.castLE (Nat.succ_le_succ (Fin.is_lt _).le) j))
fun j => rfl
simp_rw [this]
clear this
dsimp only [Fin.val_zero]
simp_rw [Fintype.prod_empty, Nat.div_one, mul_one, Fin.cons_zero, Fin.prod_univ_succ]
change (_ + ∑ y : _, _ / (x * _) % _ * (x * _)) = _
simp_rw [← Nat.div_div_eq_div_mul, mul_left_comm (_ % _ : ℕ), ← mul_sum]
convert Nat.mod_add_div _ _
-- Porting note: new
refine (ih (a / x) (Nat.div_lt_of_lt_mul <| a.is_lt.trans_eq ?_))
exact Fin.prod_univ_succ _
-- Porting note: was:
/-
refine' Eq.trans _ (ih (a / x) (Nat.div_lt_of_lt_mul <| a.is_lt.trans_eq _))
swap
· convert Fin.prod_univ_succ (Fin.cons x xs : _ → ℕ)
simp_rw [Fin.cons_succ]
congr with i
congr with j
· cases j
rfl
· cases j
rfl-/)
#align fin_pi_fin_equiv finPiFinEquiv
theorem finPiFinEquiv_apply {m : ℕ} {n : Fin m → ℕ} (f : ∀ i : Fin m, Fin (n i)) :
(finPiFinEquiv f : ℕ) = ∑ i, f i * ∏ j, n (Fin.castLE i.is_lt.le j) := rfl
#align fin_pi_fin_equiv_apply finPiFinEquiv_apply
| Mathlib/Algebra/BigOperators/Fin.lean | 441 | 447 | theorem finPiFinEquiv_single {m : ℕ} {n : Fin m → ℕ} [∀ i, NeZero (n i)] (i : Fin m)
(j : Fin (n i)) :
(finPiFinEquiv (Pi.single i j : ∀ i : Fin m, Fin (n i)) : ℕ) =
j * ∏ j, n (Fin.castLE i.is_lt.le j) := by |
rw [finPiFinEquiv_apply, Fintype.sum_eq_single i, Pi.single_eq_same]
rintro x hx
rw [Pi.single_eq_of_ne hx, Fin.val_zero', zero_mul]
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro
-/
import Mathlib.Topology.Constructions
import Mathlib.Topology.ContinuousOn
#align_import topology.bases from "leanprover-community/mathlib"@"bcfa726826abd57587355b4b5b7e78ad6527b7e4"
/-!
# Bases of topologies. Countability axioms.
A topological basis on a topological space `t` is a collection of sets,
such that all open sets can be generated as unions of these sets, without the need to take
finite intersections of them. This file introduces a framework for dealing with these collections,
and also what more we can say under certain countability conditions on bases,
which are referred to as first- and second-countable.
We also briefly cover the theory of separable spaces, which are those with a countable, dense
subset. If a space is second-countable, and also has a countably generated uniformity filter
(for example, if `t` is a metric space), it will automatically be separable (and indeed, these
conditions are equivalent in this case).
## Main definitions
* `TopologicalSpace.IsTopologicalBasis s`: The topological space `t` has basis `s`.
* `TopologicalSpace.SeparableSpace α`: The topological space `t` has a countable, dense subset.
* `TopologicalSpace.IsSeparable s`: The set `s` is contained in the closure of a countable set.
* `FirstCountableTopology α`: A topology in which `𝓝 x` is countably generated for
every `x`.
* `SecondCountableTopology α`: A topology which has a topological basis which is
countable.
## Main results
* `TopologicalSpace.FirstCountableTopology.tendsto_subseq`: In a first-countable space,
cluster points are limits of subsequences.
* `TopologicalSpace.SecondCountableTopology.isOpen_iUnion_countable`: In a second-countable space,
the union of arbitrarily-many open sets is equal to a sub-union of only countably many of these
sets.
* `TopologicalSpace.SecondCountableTopology.countable_cover_nhds`: Consider `f : α → Set α` with the
property that `f x ∈ 𝓝 x` for all `x`. Then there is some countable set `s` whose image covers
the space.
## Implementation Notes
For our applications we are interested that there exists a countable basis, but we do not need the
concrete basis itself. This allows us to declare these type classes as `Prop` to use them as mixins.
### TODO:
More fine grained instances for `FirstCountableTopology`,
`TopologicalSpace.SeparableSpace`, and more.
-/
open Set Filter Function Topology
noncomputable section
namespace TopologicalSpace
universe u
variable {α : Type u} {β : Type*} [t : TopologicalSpace α] {B : Set (Set α)} {s : Set α}
/-- A topological basis is one that satisfies the necessary conditions so that
it suffices to take unions of the basis sets to get a topology (without taking
finite intersections as well). -/
structure IsTopologicalBasis (s : Set (Set α)) : Prop where
/-- For every point `x`, the set of `t ∈ s` such that `x ∈ t` is directed downwards. -/
exists_subset_inter : ∀ t₁ ∈ s, ∀ t₂ ∈ s, ∀ x ∈ t₁ ∩ t₂, ∃ t₃ ∈ s, x ∈ t₃ ∧ t₃ ⊆ t₁ ∩ t₂
/-- The sets from `s` cover the whole space. -/
sUnion_eq : ⋃₀ s = univ
/-- The topology is generated by sets from `s`. -/
eq_generateFrom : t = generateFrom s
#align topological_space.is_topological_basis TopologicalSpace.IsTopologicalBasis
theorem IsTopologicalBasis.insert_empty {s : Set (Set α)} (h : IsTopologicalBasis s) :
IsTopologicalBasis (insert ∅ s) := by
refine ⟨?_, by rw [sUnion_insert, empty_union, h.sUnion_eq], ?_⟩
· rintro t₁ (rfl | h₁) t₂ (rfl | h₂) x ⟨hx₁, hx₂⟩
· cases hx₁
· cases hx₁
· cases hx₂
· obtain ⟨t₃, h₃, hs⟩ := h.exists_subset_inter _ h₁ _ h₂ x ⟨hx₁, hx₂⟩
exact ⟨t₃, .inr h₃, hs⟩
· rw [h.eq_generateFrom]
refine le_antisymm (le_generateFrom fun t => ?_) (generateFrom_anti <| subset_insert ∅ s)
rintro (rfl | ht)
· exact @isOpen_empty _ (generateFrom s)
· exact .basic t ht
#align topological_space.is_topological_basis.insert_empty TopologicalSpace.IsTopologicalBasis.insert_empty
| Mathlib/Topology/Bases.lean | 93 | 103 | theorem IsTopologicalBasis.diff_empty {s : Set (Set α)} (h : IsTopologicalBasis s) :
IsTopologicalBasis (s \ {∅}) := by |
refine ⟨?_, by rw [sUnion_diff_singleton_empty, h.sUnion_eq], ?_⟩
· rintro t₁ ⟨h₁, -⟩ t₂ ⟨h₂, -⟩ x hx
obtain ⟨t₃, h₃, hs⟩ := h.exists_subset_inter _ h₁ _ h₂ x hx
exact ⟨t₃, ⟨h₃, Nonempty.ne_empty ⟨x, hs.1⟩⟩, hs⟩
· rw [h.eq_generateFrom]
refine le_antisymm (generateFrom_anti diff_subset) (le_generateFrom fun t ht => ?_)
obtain rfl | he := eq_or_ne t ∅
· exact @isOpen_empty _ (generateFrom _)
· exact .basic t ⟨ht, he⟩
|
/-
Copyright (c) 2021 Yury G. Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury G. Kudryashov
-/
import Mathlib.Analysis.NormedSpace.AddTorsor
import Mathlib.LinearAlgebra.AffineSpace.Ordered
import Mathlib.Topology.ContinuousFunction.Basic
import Mathlib.Topology.GDelta
import Mathlib.Analysis.NormedSpace.FunctionSeries
import Mathlib.Analysis.SpecificLimits.Basic
#align_import topology.urysohns_lemma from "leanprover-community/mathlib"@"f2ce6086713c78a7f880485f7917ea547a215982"
/-!
# Urysohn's lemma
In this file we prove Urysohn's lemma `exists_continuous_zero_one_of_isClosed`: for any two disjoint
closed sets `s` and `t` in a normal topological space `X` there exists a continuous function
`f : X → ℝ` such that
* `f` equals zero on `s`;
* `f` equals one on `t`;
* `0 ≤ f x ≤ 1` for all `x`.
We also give versions in a regular locally compact space where one assumes that `s` is compact
and `t` is closed, in `exists_continuous_zero_one_of_isCompact`
and `exists_continuous_one_zero_of_isCompact` (the latter providing additionally a function with
compact support).
We write a generic proof so that it applies both to normal spaces and to regular locally
compact spaces.
## Implementation notes
Most paper sources prove Urysohn's lemma using a family of open sets indexed by dyadic rational
numbers on `[0, 1]`. There are many technical difficulties with formalizing this proof (e.g., one
needs to formalize the "dyadic induction", then prove that the resulting family of open sets is
monotone). So, we formalize a slightly different proof.
Let `Urysohns.CU` be the type of pairs `(C, U)` of a closed set `C` and an open set `U` such that
`C ⊆ U`. Since `X` is a normal topological space, for each `c : CU` there exists an open set `u`
such that `c.C ⊆ u ∧ closure u ⊆ c.U`. We define `c.left` and `c.right` to be `(c.C, u)` and
`(closure u, c.U)`, respectively. Then we define a family of functions
`Urysohns.CU.approx (c : Urysohns.CU) (n : ℕ) : X → ℝ` by recursion on `n`:
* `c.approx 0` is the indicator of `c.Uᶜ`;
* `c.approx (n + 1) x = (c.left.approx n x + c.right.approx n x) / 2`.
For each `x` this is a monotone family of functions that are equal to zero on `c.C` and are equal to
one outside of `c.U`. We also have `c.approx n x ∈ [0, 1]` for all `c`, `n`, and `x`.
Let `Urysohns.CU.lim c` be the supremum (or equivalently, the limit) of `c.approx n`. Then
properties of `Urysohns.CU.approx` immediately imply that
* `c.lim x ∈ [0, 1]` for all `x`;
* `c.lim` equals zero on `c.C` and equals one outside of `c.U`;
* `c.lim x = (c.left.lim x + c.right.lim x) / 2`.
In order to prove that `c.lim` is continuous at `x`, we prove by induction on `n : ℕ` that for `y`
in a small neighborhood of `x` we have `|c.lim y - c.lim x| ≤ (3 / 4) ^ n`. Induction base follows
from `c.lim x ∈ [0, 1]`, `c.lim y ∈ [0, 1]`. For the induction step, consider two cases:
* `x ∈ c.left.U`; then for `y` in a small neighborhood of `x` we have `y ∈ c.left.U ⊆ c.right.C`
(hence `c.right.lim x = c.right.lim y = 0`) and `|c.left.lim y - c.left.lim x| ≤ (3 / 4) ^ n`.
Then
`|c.lim y - c.lim x| = |c.left.lim y - c.left.lim x| / 2 ≤ (3 / 4) ^ n / 2 < (3 / 4) ^ (n + 1)`.
* otherwise, `x ∉ c.left.right.C`; then for `y` in a small neighborhood of `x` we have
`y ∉ c.left.right.C ⊇ c.left.left.U` (hence `c.left.left.lim x = c.left.left.lim y = 1`),
`|c.left.right.lim y - c.left.right.lim x| ≤ (3 / 4) ^ n`, and
`|c.right.lim y - c.right.lim x| ≤ (3 / 4) ^ n`. Combining these inequalities, the triangle
inequality, and the recurrence formula for `c.lim`, we get
`|c.lim x - c.lim y| ≤ (3 / 4) ^ (n + 1)`.
The actual formalization uses `midpoint ℝ x y` instead of `(x + y) / 2` because we have more API
lemmas about `midpoint`.
## Tags
Urysohn's lemma, normal topological space, locally compact topological space
-/
variable {X : Type*} [TopologicalSpace X]
open Set Filter TopologicalSpace Topology Filter
open scoped Pointwise
namespace Urysohns
set_option linter.uppercaseLean3 false
/-- An auxiliary type for the proof of Urysohn's lemma: a pair of a closed set `C` and its
open neighborhood `U`, together with the assumption that `C` satisfies the property `P C`. The
latter assumption will make it possible to prove simultaneously both versions of Urysohn's lemma,
in normal spaces (with `P` always true) and in locally compact spaces (with `P = IsCompact`).
We put also in the structure the assumption that, for any such pair, one may find an intermediate
pair inbetween satisfying `P`, to avoid carrying it around in the argument. -/
structure CU {X : Type*} [TopologicalSpace X] (P : Set X → Prop) where
/-- The inner set in the inductive construction towards Urysohn's lemma -/
protected C : Set X
/-- The outer set in the inductive construction towards Urysohn's lemma -/
protected U : Set X
protected P_C : P C
protected closed_C : IsClosed C
protected open_U : IsOpen U
protected subset : C ⊆ U
protected hP : ∀ {c u : Set X}, IsClosed c → P c → IsOpen u → c ⊆ u →
∃ v, IsOpen v ∧ c ⊆ v ∧ closure v ⊆ u ∧ P (closure v)
#align urysohns.CU Urysohns.CU
namespace CU
variable {P : Set X → Prop}
/-- By assumption, for each `c : CU P` there exists an open set `u`
such that `c.C ⊆ u` and `closure u ⊆ c.U`. `c.left` is the pair `(c.C, u)`. -/
@[simps C]
def left (c : CU P) : CU P where
C := c.C
U := (c.hP c.closed_C c.P_C c.open_U c.subset).choose
closed_C := c.closed_C
P_C := c.P_C
open_U := (c.hP c.closed_C c.P_C c.open_U c.subset).choose_spec.1
subset := (c.hP c.closed_C c.P_C c.open_U c.subset).choose_spec.2.1
hP := c.hP
#align urysohns.CU.left Urysohns.CU.left
/-- By assumption, for each `c : CU P` there exists an open set `u`
such that `c.C ⊆ u` and `closure u ⊆ c.U`. `c.right` is the pair `(closure u, c.U)`. -/
@[simps U]
def right (c : CU P) : CU P where
C := closure (c.hP c.closed_C c.P_C c.open_U c.subset).choose
U := c.U
closed_C := isClosed_closure
P_C := (c.hP c.closed_C c.P_C c.open_U c.subset).choose_spec.2.2.2
open_U := c.open_U
subset := (c.hP c.closed_C c.P_C c.open_U c.subset).choose_spec.2.2.1
hP := c.hP
#align urysohns.CU.right Urysohns.CU.right
theorem left_U_subset_right_C (c : CU P) : c.left.U ⊆ c.right.C :=
subset_closure
#align urysohns.CU.left_U_subset_right_C Urysohns.CU.left_U_subset_right_C
theorem left_U_subset (c : CU P) : c.left.U ⊆ c.U :=
Subset.trans c.left_U_subset_right_C c.right.subset
#align urysohns.CU.left_U_subset Urysohns.CU.left_U_subset
theorem subset_right_C (c : CU P) : c.C ⊆ c.right.C :=
Subset.trans c.left.subset c.left_U_subset_right_C
#align urysohns.CU.subset_right_C Urysohns.CU.subset_right_C
/-- `n`-th approximation to a continuous function `f : X → ℝ` such that `f = 0` on `c.C` and `f = 1`
outside of `c.U`. -/
noncomputable def approx : ℕ → CU P → X → ℝ
| 0, c, x => indicator c.Uᶜ 1 x
| n + 1, c, x => midpoint ℝ (approx n c.left x) (approx n c.right x)
#align urysohns.CU.approx Urysohns.CU.approx
theorem approx_of_mem_C (c : CU P) (n : ℕ) {x : X} (hx : x ∈ c.C) : c.approx n x = 0 := by
induction' n with n ihn generalizing c
· exact indicator_of_not_mem (fun (hU : x ∈ c.Uᶜ) => hU <| c.subset hx) _
· simp only [approx]
rw [ihn, ihn, midpoint_self]
exacts [c.subset_right_C hx, hx]
#align urysohns.CU.approx_of_mem_C Urysohns.CU.approx_of_mem_C
theorem approx_of_nmem_U (c : CU P) (n : ℕ) {x : X} (hx : x ∉ c.U) : c.approx n x = 1 := by
induction' n with n ihn generalizing c
· rw [← mem_compl_iff] at hx
exact indicator_of_mem hx _
· simp only [approx]
rw [ihn, ihn, midpoint_self]
exacts [hx, fun hU => hx <| c.left_U_subset hU]
#align urysohns.CU.approx_of_nmem_U Urysohns.CU.approx_of_nmem_U
theorem approx_nonneg (c : CU P) (n : ℕ) (x : X) : 0 ≤ c.approx n x := by
induction' n with n ihn generalizing c
· exact indicator_nonneg (fun _ _ => zero_le_one) _
· simp only [approx, midpoint_eq_smul_add, invOf_eq_inv]
refine mul_nonneg (inv_nonneg.2 zero_le_two) (add_nonneg ?_ ?_) <;> apply ihn
#align urysohns.CU.approx_nonneg Urysohns.CU.approx_nonneg
theorem approx_le_one (c : CU P) (n : ℕ) (x : X) : c.approx n x ≤ 1 := by
induction' n with n ihn generalizing c
· exact indicator_apply_le' (fun _ => le_rfl) fun _ => zero_le_one
· simp only [approx, midpoint_eq_smul_add, invOf_eq_inv, smul_eq_mul, ← div_eq_inv_mul]
have := add_le_add (ihn (left c)) (ihn (right c))
set_option tactic.skipAssignedInstances false in
norm_num at this
exact Iff.mpr (div_le_one zero_lt_two) this
#align urysohns.CU.approx_le_one Urysohns.CU.approx_le_one
theorem bddAbove_range_approx (c : CU P) (x : X) : BddAbove (range fun n => c.approx n x) :=
⟨1, fun _ ⟨n, hn⟩ => hn ▸ c.approx_le_one n x⟩
#align urysohns.CU.bdd_above_range_approx Urysohns.CU.bddAbove_range_approx
theorem approx_le_approx_of_U_sub_C {c₁ c₂ : CU P} (h : c₁.U ⊆ c₂.C) (n₁ n₂ : ℕ) (x : X) :
c₂.approx n₂ x ≤ c₁.approx n₁ x := by
by_cases hx : x ∈ c₁.U
· calc
approx n₂ c₂ x = 0 := approx_of_mem_C _ _ (h hx)
_ ≤ approx n₁ c₁ x := approx_nonneg _ _ _
· calc
approx n₂ c₂ x ≤ 1 := approx_le_one _ _ _
_ = approx n₁ c₁ x := (approx_of_nmem_U _ _ hx).symm
#align urysohns.CU.approx_le_approx_of_U_sub_C Urysohns.CU.approx_le_approx_of_U_sub_C
theorem approx_mem_Icc_right_left (c : CU P) (n : ℕ) (x : X) :
c.approx n x ∈ Icc (c.right.approx n x) (c.left.approx n x) := by
induction' n with n ihn generalizing c
· exact ⟨le_rfl, indicator_le_indicator_of_subset (compl_subset_compl.2 c.left_U_subset)
(fun _ => zero_le_one) _⟩
· simp only [approx, mem_Icc]
refine ⟨midpoint_le_midpoint ?_ (ihn _).1, midpoint_le_midpoint (ihn _).2 ?_⟩ <;>
apply approx_le_approx_of_U_sub_C
exacts [subset_closure, subset_closure]
#align urysohns.CU.approx_mem_Icc_right_left Urysohns.CU.approx_mem_Icc_right_left
theorem approx_le_succ (c : CU P) (n : ℕ) (x : X) : c.approx n x ≤ c.approx (n + 1) x := by
induction' n with n ihn generalizing c
· simp only [approx, right_U, right_le_midpoint]
exact (approx_mem_Icc_right_left c 0 x).2
· rw [approx, approx]
exact midpoint_le_midpoint (ihn _) (ihn _)
#align urysohns.CU.approx_le_succ Urysohns.CU.approx_le_succ
theorem approx_mono (c : CU P) (x : X) : Monotone fun n => c.approx n x :=
monotone_nat_of_le_succ fun n => c.approx_le_succ n x
#align urysohns.CU.approx_mono Urysohns.CU.approx_mono
/-- A continuous function `f : X → ℝ` such that
* `0 ≤ f x ≤ 1` for all `x`;
* `f` equals zero on `c.C` and equals one outside of `c.U`;
-/
protected noncomputable def lim (c : CU P) (x : X) : ℝ :=
⨆ n, c.approx n x
#align urysohns.CU.lim Urysohns.CU.lim
theorem tendsto_approx_atTop (c : CU P) (x : X) :
Tendsto (fun n => c.approx n x) atTop (𝓝 <| c.lim x) :=
tendsto_atTop_ciSup (c.approx_mono x) ⟨1, fun _ ⟨_, hn⟩ => hn ▸ c.approx_le_one _ _⟩
#align urysohns.CU.tendsto_approx_at_top Urysohns.CU.tendsto_approx_atTop
theorem lim_of_mem_C (c : CU P) (x : X) (h : x ∈ c.C) : c.lim x = 0 := by
simp only [CU.lim, approx_of_mem_C, h, ciSup_const]
#align urysohns.CU.lim_of_mem_C Urysohns.CU.lim_of_mem_C
theorem lim_of_nmem_U (c : CU P) (x : X) (h : x ∉ c.U) : c.lim x = 1 := by
simp only [CU.lim, approx_of_nmem_U c _ h, ciSup_const]
#align urysohns.CU.lim_of_nmem_U Urysohns.CU.lim_of_nmem_U
theorem lim_eq_midpoint (c : CU P) (x : X) :
c.lim x = midpoint ℝ (c.left.lim x) (c.right.lim x) := by
refine tendsto_nhds_unique (c.tendsto_approx_atTop x) ((tendsto_add_atTop_iff_nat 1).1 ?_)
simp only [approx]
exact (c.left.tendsto_approx_atTop x).midpoint (c.right.tendsto_approx_atTop x)
#align urysohns.CU.lim_eq_midpoint Urysohns.CU.lim_eq_midpoint
theorem approx_le_lim (c : CU P) (x : X) (n : ℕ) : c.approx n x ≤ c.lim x :=
le_ciSup (c.bddAbove_range_approx x) _
#align urysohns.CU.approx_le_lim Urysohns.CU.approx_le_lim
theorem lim_nonneg (c : CU P) (x : X) : 0 ≤ c.lim x :=
(c.approx_nonneg 0 x).trans (c.approx_le_lim x 0)
#align urysohns.CU.lim_nonneg Urysohns.CU.lim_nonneg
theorem lim_le_one (c : CU P) (x : X) : c.lim x ≤ 1 :=
ciSup_le fun _ => c.approx_le_one _ _
#align urysohns.CU.lim_le_one Urysohns.CU.lim_le_one
theorem lim_mem_Icc (c : CU P) (x : X) : c.lim x ∈ Icc (0 : ℝ) 1 :=
⟨c.lim_nonneg x, c.lim_le_one x⟩
#align urysohns.CU.lim_mem_Icc Urysohns.CU.lim_mem_Icc
/-- Continuity of `Urysohns.CU.lim`. See module docstring for a sketch of the proofs. -/
theorem continuous_lim (c : CU P) : Continuous c.lim := by
obtain ⟨h0, h1234, h1⟩ : 0 < (2⁻¹ : ℝ) ∧ (2⁻¹ : ℝ) < 3 / 4 ∧ (3 / 4 : ℝ) < 1 := by norm_num
refine
continuous_iff_continuousAt.2 fun x =>
(Metric.nhds_basis_closedBall_pow (h0.trans h1234) h1).tendsto_right_iff.2 fun n _ => ?_
simp only [Metric.mem_closedBall]
induction' n with n ihn generalizing c
· filter_upwards with y
rw [pow_zero]
exact Real.dist_le_of_mem_Icc_01 (c.lim_mem_Icc _) (c.lim_mem_Icc _)
· by_cases hxl : x ∈ c.left.U
· filter_upwards [IsOpen.mem_nhds c.left.open_U hxl, ihn c.left] with _ hyl hyd
rw [pow_succ', c.lim_eq_midpoint, c.lim_eq_midpoint,
c.right.lim_of_mem_C _ (c.left_U_subset_right_C hyl),
c.right.lim_of_mem_C _ (c.left_U_subset_right_C hxl)]
refine (dist_midpoint_midpoint_le _ _ _ _).trans ?_
rw [dist_self, add_zero, div_eq_inv_mul]
gcongr
· replace hxl : x ∈ c.left.right.Cᶜ :=
compl_subset_compl.2 c.left.right.subset hxl
filter_upwards [IsOpen.mem_nhds (isOpen_compl_iff.2 c.left.right.closed_C) hxl,
ihn c.left.right, ihn c.right] with y hyl hydl hydr
replace hxl : x ∉ c.left.left.U :=
compl_subset_compl.2 c.left.left_U_subset_right_C hxl
replace hyl : y ∉ c.left.left.U :=
compl_subset_compl.2 c.left.left_U_subset_right_C hyl
simp only [pow_succ, c.lim_eq_midpoint, c.left.lim_eq_midpoint,
c.left.left.lim_of_nmem_U _ hxl, c.left.left.lim_of_nmem_U _ hyl]
refine (dist_midpoint_midpoint_le _ _ _ _).trans ?_
refine (div_le_div_of_nonneg_right (add_le_add_right (dist_midpoint_midpoint_le _ _ _ _) _)
zero_le_two).trans ?_
rw [dist_self, zero_add]
set r := (3 / 4 : ℝ) ^ n
calc _ ≤ (r / 2 + r) / 2 := by gcongr
_ = _ := by field_simp; ring
#align urysohns.CU.continuous_lim Urysohns.CU.continuous_lim
end CU
end Urysohns
/-- Urysohn's lemma: if `s` and `t` are two disjoint closed sets in a normal topological space `X`,
then there exists a continuous function `f : X → ℝ` such that
* `f` equals zero on `s`;
* `f` equals one on `t`;
* `0 ≤ f x ≤ 1` for all `x`.
-/
theorem exists_continuous_zero_one_of_isClosed [NormalSpace X]
{s t : Set X} (hs : IsClosed s) (ht : IsClosed t)
(hd : Disjoint s t) : ∃ f : C(X, ℝ), EqOn f 0 s ∧ EqOn f 1 t ∧ ∀ x, f x ∈ Icc (0 : ℝ) 1 := by
-- The actual proof is in the code above. Here we just repack it into the expected format.
let P : Set X → Prop := fun _ ↦ True
set c : Urysohns.CU P :=
{ C := s
U := tᶜ
P_C := trivial
closed_C := hs
open_U := ht.isOpen_compl
subset := disjoint_left.1 hd
hP := by
rintro c u c_closed - u_open cu
rcases normal_exists_closure_subset c_closed u_open cu with ⟨v, v_open, cv, hv⟩
exact ⟨v, v_open, cv, hv, trivial⟩ }
exact ⟨⟨c.lim, c.continuous_lim⟩, c.lim_of_mem_C, fun x hx => c.lim_of_nmem_U _ fun h => h hx,
c.lim_mem_Icc⟩
#align exists_continuous_zero_one_of_closed exists_continuous_zero_one_of_isClosed
/-- Urysohn's lemma: if `s` and `t` are two disjoint sets in a regular locally compact topological
space `X`, with `s` compact and `t` closed, then there exists a continuous
function `f : X → ℝ` such that
* `f` equals zero on `s`;
* `f` equals one on `t`;
* `0 ≤ f x ≤ 1` for all `x`.
-/
theorem exists_continuous_zero_one_of_isCompact [RegularSpace X] [LocallyCompactSpace X]
{s t : Set X} (hs : IsCompact s) (ht : IsClosed t) (hd : Disjoint s t) :
∃ f : C(X, ℝ), EqOn f 0 s ∧ EqOn f 1 t ∧ ∀ x, f x ∈ Icc (0 : ℝ) 1 := by
obtain ⟨k, k_comp, k_closed, sk, kt⟩ : ∃ k, IsCompact k ∧ IsClosed k ∧ s ⊆ interior k ∧ k ⊆ tᶜ :=
exists_compact_closed_between hs ht.isOpen_compl hd.symm.subset_compl_left
let P : Set X → Prop := IsCompact
set c : Urysohns.CU P :=
{ C := k
U := tᶜ
P_C := k_comp
closed_C := k_closed
open_U := ht.isOpen_compl
subset := kt
hP := by
rintro c u - c_comp u_open cu
rcases exists_compact_closed_between c_comp u_open cu with ⟨k, k_comp, k_closed, ck, ku⟩
have A : closure (interior k) ⊆ k :=
(IsClosed.closure_subset_iff k_closed).2 interior_subset
refine ⟨interior k, isOpen_interior, ck, A.trans ku,
k_comp.of_isClosed_subset isClosed_closure A⟩ }
exact ⟨⟨c.lim, c.continuous_lim⟩, fun x hx ↦ c.lim_of_mem_C _ (sk.trans interior_subset hx),
fun x hx => c.lim_of_nmem_U _ fun h => h hx, c.lim_mem_Icc⟩
/-- Urysohn's lemma: if `s` and `t` are two disjoint sets in a regular locally compact topological
space `X`, with `s` compact and `t` closed, then there exists a continuous compactly supported
function `f : X → ℝ` such that
* `f` equals one on `s`;
* `f` equals zero on `t`;
* `0 ≤ f x ≤ 1` for all `x`.
-/
theorem exists_continuous_one_zero_of_isCompact [RegularSpace X] [LocallyCompactSpace X]
{s t : Set X} (hs : IsCompact s) (ht : IsClosed t) (hd : Disjoint s t) :
∃ f : C(X, ℝ), EqOn f 1 s ∧ EqOn f 0 t ∧ HasCompactSupport f ∧ ∀ x, f x ∈ Icc (0 : ℝ) 1 := by
obtain ⟨k, k_comp, k_closed, sk, kt⟩ : ∃ k, IsCompact k ∧ IsClosed k ∧ s ⊆ interior k ∧ k ⊆ tᶜ :=
exists_compact_closed_between hs ht.isOpen_compl hd.symm.subset_compl_left
rcases exists_continuous_zero_one_of_isCompact hs isOpen_interior.isClosed_compl
(disjoint_compl_right_iff_subset.mpr sk) with ⟨⟨f, hf⟩, hfs, hft, h'f⟩
have A : t ⊆ (interior k)ᶜ := subset_compl_comm.mpr (interior_subset.trans kt)
refine ⟨⟨fun x ↦ 1 - f x, continuous_const.sub hf⟩, fun x hx ↦ by simpa using hfs hx,
fun x hx ↦ by simpa [sub_eq_zero] using (hft (A hx)).symm, ?_, fun x ↦ ?_⟩
· apply HasCompactSupport.intro' k_comp k_closed (fun x hx ↦ ?_)
simp only [ContinuousMap.coe_mk, sub_eq_zero]
apply (hft _).symm
contrapose! hx
simp only [mem_compl_iff, not_not] at hx
exact interior_subset hx
· have : 0 ≤ f x ∧ f x ≤ 1 := by simpa using h'f x
simp [this]
/-- Urysohn's lemma: if `s` and `t` are two disjoint sets in a regular locally compact topological
space `X`, with `s` compact and `t` closed, then there exists a continuous compactly supported
function `f : X → ℝ` such that
* `f` equals one on `s`;
* `f` equals zero on `t`;
* `0 ≤ f x ≤ 1` for all `x`.
Moreover, if `s` is Gδ, one can ensure that `f ⁻¹ {1}` is exactly `s`.
-/
| Mathlib/Topology/UrysohnsLemma.lean | 415 | 458 | theorem exists_continuous_one_zero_of_isCompact_of_isGδ [RegularSpace X] [LocallyCompactSpace X]
{s t : Set X} (hs : IsCompact s) (h's : IsGδ s) (ht : IsClosed t) (hd : Disjoint s t) :
∃ f : C(X, ℝ), s = f ⁻¹' {1} ∧ EqOn f 0 t ∧ HasCompactSupport f
∧ ∀ x, f x ∈ Icc (0 : ℝ) 1 := by |
rcases h's.eq_iInter_nat with ⟨U, U_open, hU⟩
obtain ⟨m, m_comp, -, sm, mt⟩ : ∃ m, IsCompact m ∧ IsClosed m ∧ s ⊆ interior m ∧ m ⊆ tᶜ :=
exists_compact_closed_between hs ht.isOpen_compl hd.symm.subset_compl_left
have A n : ∃ f : C(X, ℝ), EqOn f 1 s ∧ EqOn f 0 (U n ∩ interior m)ᶜ ∧ HasCompactSupport f
∧ ∀ x, f x ∈ Icc (0 : ℝ) 1 := by
apply exists_continuous_one_zero_of_isCompact hs
((U_open n).inter isOpen_interior).isClosed_compl
rw [disjoint_compl_right_iff_subset]
exact subset_inter ((hU.subset.trans (iInter_subset U n))) sm
choose f fs fm _hf f_range using A
obtain ⟨u, u_pos, u_sum, hu⟩ : ∃ (u : ℕ → ℝ), (∀ i, 0 < u i) ∧ Summable u ∧ ∑' i, u i = 1 :=
⟨fun n ↦ 1/2/2^n, fun n ↦ by positivity, summable_geometric_two' 1, tsum_geometric_two' 1⟩
let g : X → ℝ := fun x ↦ ∑' n, u n * f n x
have hgmc : EqOn g 0 mᶜ := by
intro x hx
have B n : f n x = 0 := by
have : mᶜ ⊆ (U n ∩ interior m)ᶜ := by
simpa using inter_subset_right.trans interior_subset
exact fm n (this hx)
simp [g, B]
have I n x : u n * f n x ≤ u n := mul_le_of_le_one_right (u_pos n).le (f_range n x).2
have S x : Summable (fun n ↦ u n * f n x) := Summable.of_nonneg_of_le
(fun n ↦ mul_nonneg (u_pos n).le (f_range n x).1) (fun n ↦ I n x) u_sum
refine ⟨⟨g, ?_⟩, ?_, hgmc.mono (subset_compl_comm.mp mt), ?_, fun x ↦ ⟨?_, ?_⟩⟩
· apply continuous_tsum (fun n ↦ continuous_const.mul (f n).continuous) u_sum (fun n x ↦ ?_)
simpa [abs_of_nonneg, (u_pos n).le, (f_range n x).1] using I n x
· apply Subset.antisymm (fun x hx ↦ by simp [g, fs _ hx, hu]) ?_
apply compl_subset_compl.1
intro x hx
obtain ⟨n, hn⟩ : ∃ n, x ∉ U n := by simpa [hU] using hx
have fnx : f n x = 0 := fm _ (by simp [hn])
have : g x < 1 := by
apply lt_of_lt_of_le ?_ hu.le
exact tsum_lt_tsum (i := n) (fun i ↦ I i x) (by simp [fnx, u_pos n]) (S x) u_sum
simpa using this.ne
· exact HasCompactSupport.of_support_subset_isCompact m_comp
(Function.support_subset_iff'.mpr hgmc)
· exact tsum_nonneg (fun n ↦ mul_nonneg (u_pos n).le (f_range n x).1)
· apply le_trans _ hu.le
exact tsum_le_tsum (fun n ↦ I n x) (S x) u_sum
|
/-
Copyright (c) 2017 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Data.List.Basic
#align_import data.list.infix from "leanprover-community/mathlib"@"26f081a2fb920140ed5bc5cc5344e84bcc7cb2b2"
/-!
# Prefixes, suffixes, infixes
This file proves properties about
* `List.isPrefix`: `l₁` is a prefix of `l₂` if `l₂` starts with `l₁`.
* `List.isSuffix`: `l₁` is a suffix of `l₂` if `l₂` ends with `l₁`.
* `List.isInfix`: `l₁` is an infix of `l₂` if `l₁` is a prefix of some suffix of `l₂`.
* `List.inits`: The list of prefixes of a list.
* `List.tails`: The list of prefixes of a list.
* `insert` on lists
All those (except `insert`) are defined in `Mathlib.Data.List.Defs`.
## Notation
* `l₁ <+: l₂`: `l₁` is a prefix of `l₂`.
* `l₁ <:+ l₂`: `l₁` is a suffix of `l₂`.
* `l₁ <:+: l₂`: `l₁` is an infix of `l₂`.
-/
open Nat
variable {α β : Type*}
namespace List
variable {l l₁ l₂ l₃ : List α} {a b : α} {m n : ℕ}
/-! ### prefix, suffix, infix -/
section Fix
#align list.prefix_append List.prefix_append
#align list.suffix_append List.suffix_append
#align list.infix_append List.infix_append
#align list.infix_append' List.infix_append'
#align list.is_prefix.is_infix List.IsPrefix.isInfix
#align list.is_suffix.is_infix List.IsSuffix.isInfix
#align list.nil_prefix List.nil_prefix
#align list.nil_suffix List.nil_suffix
#align list.nil_infix List.nil_infix
#align list.prefix_refl List.prefix_refl
#align list.suffix_refl List.suffix_refl
#align list.infix_refl List.infix_refl
theorem prefix_rfl : l <+: l :=
prefix_refl _
#align list.prefix_rfl List.prefix_rfl
theorem suffix_rfl : l <:+ l :=
suffix_refl _
#align list.suffix_rfl List.suffix_rfl
theorem infix_rfl : l <:+: l :=
infix_refl _
#align list.infix_rfl List.infix_rfl
#align list.suffix_cons List.suffix_cons
theorem prefix_concat (a : α) (l) : l <+: concat l a := by simp
#align list.prefix_concat List.prefix_concat
theorem prefix_concat_iff {l₁ l₂ : List α} {a : α} :
l₁ <+: l₂ ++ [a] ↔ l₁ = l₂ ++ [a] ∨ l₁ <+: l₂ := by
simpa only [← reverse_concat', reverse_inj, reverse_suffix] using
suffix_cons_iff (l₁ := l₁.reverse) (l₂ := l₂.reverse)
#align list.infix_cons List.infix_cons
#align list.infix_concat List.infix_concat
#align list.is_prefix.trans List.IsPrefix.trans
#align list.is_suffix.trans List.IsSuffix.trans
#align list.is_infix.trans List.IsInfix.trans
#align list.is_infix.sublist List.IsInfix.sublist
#align list.is_infix.subset List.IsInfix.subset
#align list.is_prefix.sublist List.IsPrefix.sublist
#align list.is_prefix.subset List.IsPrefix.subset
#align list.is_suffix.sublist List.IsSuffix.sublist
#align list.is_suffix.subset List.IsSuffix.subset
#align list.reverse_suffix List.reverse_suffix
#align list.reverse_prefix List.reverse_prefix
#align list.reverse_infix List.reverse_infix
protected alias ⟨_, isSuffix.reverse⟩ := reverse_prefix
#align list.is_suffix.reverse List.isSuffix.reverse
protected alias ⟨_, isPrefix.reverse⟩ := reverse_suffix
#align list.is_prefix.reverse List.isPrefix.reverse
protected alias ⟨_, isInfix.reverse⟩ := reverse_infix
#align list.is_infix.reverse List.isInfix.reverse
#align list.is_infix.length_le List.IsInfix.length_le
#align list.is_prefix.length_le List.IsPrefix.length_le
#align list.is_suffix.length_le List.IsSuffix.length_le
#align list.infix_nil_iff List.infix_nil
#align list.prefix_nil_iff List.prefix_nil
#align list.suffix_nil_iff List.suffix_nil
alias ⟨eq_nil_of_infix_nil, _⟩ := infix_nil
#align list.eq_nil_of_infix_nil List.eq_nil_of_infix_nil
alias ⟨eq_nil_of_prefix_nil, _⟩ := prefix_nil
#align list.eq_nil_of_prefix_nil List.eq_nil_of_prefix_nil
alias ⟨eq_nil_of_suffix_nil, _⟩ := suffix_nil
#align list.eq_nil_of_suffix_nil List.eq_nil_of_suffix_nil
#align list.infix_iff_prefix_suffix List.infix_iff_prefix_suffix
theorem eq_of_infix_of_length_eq (h : l₁ <:+: l₂) : l₁.length = l₂.length → l₁ = l₂ :=
h.sublist.eq_of_length
#align list.eq_of_infix_of_length_eq List.eq_of_infix_of_length_eq
theorem eq_of_prefix_of_length_eq (h : l₁ <+: l₂) : l₁.length = l₂.length → l₁ = l₂ :=
h.sublist.eq_of_length
#align list.eq_of_prefix_of_length_eq List.eq_of_prefix_of_length_eq
theorem eq_of_suffix_of_length_eq (h : l₁ <:+ l₂) : l₁.length = l₂.length → l₁ = l₂ :=
h.sublist.eq_of_length
#align list.eq_of_suffix_of_length_eq List.eq_of_suffix_of_length_eq
#align list.prefix_of_prefix_length_le List.prefix_of_prefix_length_le
#align list.prefix_or_prefix_of_prefix List.prefix_or_prefix_of_prefix
#align list.suffix_of_suffix_length_le List.suffix_of_suffix_length_le
#align list.suffix_or_suffix_of_suffix List.suffix_or_suffix_of_suffix
#align list.suffix_cons_iff List.suffix_cons_iff
#align list.infix_cons_iff List.infix_cons_iff
#align list.infix_of_mem_join List.infix_of_mem_join
#align list.prefix_append_right_inj List.prefix_append_right_inj
#align list.prefix_cons_inj List.prefix_cons_inj
#align list.take_prefix List.take_prefix
#align list.drop_suffix List.drop_suffix
#align list.take_sublist List.take_sublist
#align list.drop_sublist List.drop_sublist
#align list.take_subset List.take_subset
#align list.drop_subset List.drop_subset
#align list.mem_of_mem_take List.mem_of_mem_take
#align list.mem_of_mem_drop List.mem_of_mem_drop
lemma dropSlice_sublist (n m : ℕ) (l : List α) : l.dropSlice n m <+ l :=
calc
l.dropSlice n m = take n l ++ drop m (drop n l) := by rw [dropSlice_eq, drop_drop, Nat.add_comm]
_ <+ take n l ++ drop n l := (Sublist.refl _).append (drop_sublist _ _)
_ = _ := take_append_drop _ _
#align list.slice_sublist List.dropSlice_sublist
lemma dropSlice_subset (n m : ℕ) (l : List α) : l.dropSlice n m ⊆ l :=
(dropSlice_sublist n m l).subset
#align list.slice_subset List.dropSlice_subset
lemma mem_of_mem_dropSlice {n m : ℕ} {l : List α} {a : α} (h : a ∈ l.dropSlice n m) : a ∈ l :=
dropSlice_subset n m l h
#align list.mem_of_mem_slice List.mem_of_mem_dropSlice
theorem takeWhile_prefix (p : α → Bool) : l.takeWhile p <+: l :=
⟨l.dropWhile p, takeWhile_append_dropWhile p l⟩
#align list.take_while_prefix List.takeWhile_prefix
theorem dropWhile_suffix (p : α → Bool) : l.dropWhile p <:+ l :=
⟨l.takeWhile p, takeWhile_append_dropWhile p l⟩
#align list.drop_while_suffix List.dropWhile_suffix
theorem dropLast_prefix : ∀ l : List α, l.dropLast <+: l
| [] => ⟨nil, by rw [dropLast, List.append_nil]⟩
| a :: l => ⟨_, dropLast_append_getLast (cons_ne_nil a l)⟩
#align list.init_prefix List.dropLast_prefix
theorem tail_suffix (l : List α) : tail l <:+ l := by rw [← drop_one]; apply drop_suffix
#align list.tail_suffix List.tail_suffix
theorem dropLast_sublist (l : List α) : l.dropLast <+ l :=
(dropLast_prefix l).sublist
#align list.init_sublist List.dropLast_sublist
@[gcongr]
theorem drop_sublist_drop_left (l : List α) {m n : ℕ} (h : m ≤ n) : drop n l <+ drop m l := by
rw [← Nat.sub_add_cancel h, drop_add]
apply drop_sublist
theorem dropLast_subset (l : List α) : l.dropLast ⊆ l :=
(dropLast_sublist l).subset
#align list.init_subset List.dropLast_subset
theorem tail_subset (l : List α) : tail l ⊆ l :=
(tail_sublist l).subset
#align list.tail_subset List.tail_subset
theorem mem_of_mem_dropLast (h : a ∈ l.dropLast) : a ∈ l :=
dropLast_subset l h
#align list.mem_of_mem_init List.mem_of_mem_dropLast
theorem mem_of_mem_tail (h : a ∈ l.tail) : a ∈ l :=
tail_subset l h
#align list.mem_of_mem_tail List.mem_of_mem_tail
@[gcongr]
protected theorem Sublist.drop : ∀ {l₁ l₂ : List α}, l₁ <+ l₂ → ∀ n, l₁.drop n <+ l₂.drop n
| _, _, h, 0 => h
| _, _, h, n + 1 => by rw [← drop_tail, ← drop_tail]; exact h.tail.drop n
theorem prefix_iff_eq_append : l₁ <+: l₂ ↔ l₁ ++ drop (length l₁) l₂ = l₂ :=
⟨by rintro ⟨r, rfl⟩; rw [drop_left], fun e => ⟨_, e⟩⟩
#align list.prefix_iff_eq_append List.prefix_iff_eq_append
theorem suffix_iff_eq_append : l₁ <:+ l₂ ↔ take (length l₂ - length l₁) l₂ ++ l₁ = l₂ :=
⟨by rintro ⟨r, rfl⟩; simp only [length_append, Nat.add_sub_cancel_right, take_left], fun e =>
⟨_, e⟩⟩
#align list.suffix_iff_eq_append List.suffix_iff_eq_append
theorem prefix_iff_eq_take : l₁ <+: l₂ ↔ l₁ = take (length l₁) l₂ :=
⟨fun h => append_cancel_right <| (prefix_iff_eq_append.1 h).trans (take_append_drop _ _).symm,
fun e => e.symm ▸ take_prefix _ _⟩
#align list.prefix_iff_eq_take List.prefix_iff_eq_take
theorem prefix_take_iff {x y : List α} {n : ℕ} : x <+: y.take n ↔ x <+: y ∧ x.length ≤ n := by
constructor
· intro h
constructor
· exact List.IsPrefix.trans h <| List.take_prefix n y
· replace h := h.length_le
rw [length_take, Nat.le_min] at h
exact h.left
· intro ⟨hp, hl⟩
have hl' := hp.length_le
rw [List.prefix_iff_eq_take] at *
rw [hp, List.take_take]
simp [min_eq_left, hl, hl']
theorem concat_get_prefix {x y : List α} (h : x <+: y) (hl : x.length < y.length) :
x ++ [y.get ⟨x.length, hl⟩] <+: y := by
use y.drop (x.length + 1)
nth_rw 1 [List.prefix_iff_eq_take.mp h]
convert List.take_append_drop (x.length + 1) y using 2
rw [← List.take_concat_get, List.concat_eq_append]; rfl
theorem suffix_iff_eq_drop : l₁ <:+ l₂ ↔ l₁ = drop (length l₂ - length l₁) l₂ :=
⟨fun h => append_cancel_left <| (suffix_iff_eq_append.1 h).trans (take_append_drop _ _).symm,
fun e => e.symm ▸ drop_suffix _ _⟩
#align list.suffix_iff_eq_drop List.suffix_iff_eq_drop
instance decidablePrefix [DecidableEq α] : ∀ l₁ l₂ : List α, Decidable (l₁ <+: l₂)
| [], l₂ => isTrue ⟨l₂, rfl⟩
| a :: l₁, [] => isFalse fun ⟨t, te⟩ => List.noConfusion te
| a :: l₁, b :: l₂ =>
if h : a = b then
@decidable_of_decidable_of_iff _ _ (decidablePrefix l₁ l₂) (by rw [← h, prefix_cons_inj])
else
isFalse fun ⟨t, te⟩ => h <| by injection te
#align list.decidable_prefix List.decidablePrefix
-- Alternatively, use mem_tails
instance decidableSuffix [DecidableEq α] : ∀ l₁ l₂ : List α, Decidable (l₁ <:+ l₂)
| [], l₂ => isTrue ⟨l₂, append_nil _⟩
| a :: l₁, [] => isFalse <| mt (Sublist.length_le ∘ IsSuffix.sublist) (by simp)
| l₁, b :: l₂ =>
@decidable_of_decidable_of_iff _ _
(@instDecidableOr _ _ _ (l₁.decidableSuffix l₂))
suffix_cons_iff.symm
#align list.decidable_suffix List.decidableSuffix
instance decidableInfix [DecidableEq α] : ∀ l₁ l₂ : List α, Decidable (l₁ <:+: l₂)
| [], l₂ => isTrue ⟨[], l₂, rfl⟩
| a :: l₁, [] => isFalse fun ⟨s, t, te⟩ => by simp at te
| l₁, b :: l₂ =>
@decidable_of_decidable_of_iff _ _
(@instDecidableOr _ _ (l₁.decidablePrefix (b :: l₂)) (l₁.decidableInfix l₂))
infix_cons_iff.symm
#align list.decidable_infix List.decidableInfix
theorem prefix_take_le_iff {L : List (List (Option α))} (hm : m < L.length) :
L.take m <+: L.take n ↔ m ≤ n := by
simp only [prefix_iff_eq_take, length_take]
induction m generalizing L n with
| zero => simp [min_eq_left, eq_self_iff_true, Nat.zero_le, take]
| succ m IH =>
cases L with
| nil => simp_all
| cons l ls =>
cases n with
| zero =>
simp
| succ n =>
simp only [length_cons, succ_eq_add_one, Nat.add_lt_add_iff_right] at hm
simp [← @IH n ls hm, Nat.min_eq_left, Nat.le_of_lt hm]
#align list.prefix_take_le_iff List.prefix_take_le_iff
theorem cons_prefix_iff : a :: l₁ <+: b :: l₂ ↔ a = b ∧ l₁ <+: l₂ := by
constructor
· rintro ⟨L, hL⟩
simp only [cons_append] at hL
injection hL with hLLeft hLRight
exact ⟨hLLeft, ⟨L, hLRight⟩⟩
· rintro ⟨rfl, h⟩
rwa [prefix_cons_inj]
#align list.cons_prefix_iff List.cons_prefix_iff
protected theorem IsPrefix.map (h : l₁ <+: l₂) (f : α → β) : l₁.map f <+: l₂.map f := by
induction' l₁ with hd tl hl generalizing l₂
· simp only [nil_prefix, map_nil]
· cases' l₂ with hd₂ tl₂
· simpa only using eq_nil_of_prefix_nil h
· rw [cons_prefix_iff] at h
simp only [List.map_cons, h, prefix_cons_inj, hl, map]
#align list.is_prefix.map List.IsPrefix.map
protected theorem IsPrefix.filterMap (h : l₁ <+: l₂) (f : α → Option β) :
l₁.filterMap f <+: l₂.filterMap f := by
induction' l₁ with hd₁ tl₁ hl generalizing l₂
· simp only [nil_prefix, filterMap_nil]
· cases' l₂ with hd₂ tl₂
· simpa only using eq_nil_of_prefix_nil h
· rw [cons_prefix_iff] at h
rw [← @singleton_append _ hd₁ _, ← @singleton_append _ hd₂ _, filterMap_append,
filterMap_append, h.left, prefix_append_right_inj]
exact hl h.right
#align list.is_prefix.filter_map List.IsPrefix.filterMap
@[deprecated (since := "2024-03-26")] alias IsPrefix.filter_map := IsPrefix.filterMap
protected theorem IsPrefix.reduceOption {l₁ l₂ : List (Option α)} (h : l₁ <+: l₂) :
l₁.reduceOption <+: l₂.reduceOption :=
h.filterMap id
#align list.is_prefix.reduce_option List.IsPrefix.reduceOption
#align list.is_prefix.filter List.IsPrefix.filter
#align list.is_suffix.filter List.IsSuffix.filter
#align list.is_infix.filter List.IsInfix.filter
instance : IsPartialOrder (List α) (· <+: ·) where
refl := prefix_refl
trans _ _ _ := IsPrefix.trans
antisymm _ _ h₁ h₂ := eq_of_prefix_of_length_eq h₁ <| h₁.length_le.antisymm h₂.length_le
instance : IsPartialOrder (List α) (· <:+ ·) where
refl := suffix_refl
trans _ _ _ := IsSuffix.trans
antisymm _ _ h₁ h₂ := eq_of_suffix_of_length_eq h₁ <| h₁.length_le.antisymm h₂.length_le
instance : IsPartialOrder (List α) (· <:+: ·) where
refl := infix_refl
trans _ _ _ := IsInfix.trans
antisymm _ _ h₁ h₂ := eq_of_infix_of_length_eq h₁ <| h₁.length_le.antisymm h₂.length_le
end Fix
section InitsTails
@[simp]
theorem mem_inits : ∀ s t : List α, s ∈ inits t ↔ s <+: t
| s, [] =>
suffices s = nil ↔ s <+: nil by simpa only [inits, mem_singleton]
⟨fun h => h.symm ▸ prefix_refl [], eq_nil_of_prefix_nil⟩
| s, a :: t =>
suffices (s = nil ∨ ∃ l ∈ inits t, a :: l = s) ↔ s <+: a :: t by simpa
⟨fun o =>
match s, o with
| _, Or.inl rfl => ⟨_, rfl⟩
| s, Or.inr ⟨r, hr, hs⟩ => by
let ⟨s, ht⟩ := (mem_inits _ _).1 hr
rw [← hs, ← ht]; exact ⟨s, rfl⟩,
fun mi =>
match s, mi with
| [], ⟨_, rfl⟩ => Or.inl rfl
| b :: s, ⟨r, hr⟩ =>
(List.noConfusion hr) fun ba (st : s ++ r = t) =>
Or.inr <| by rw [ba]; exact ⟨_, (mem_inits _ _).2 ⟨_, st⟩, rfl⟩⟩
#align list.mem_inits List.mem_inits
@[simp]
theorem mem_tails : ∀ s t : List α, s ∈ tails t ↔ s <:+ t
| s, [] => by
simp only [tails, mem_singleton, suffix_nil]
| s, a :: t => by
simp only [tails, mem_cons, mem_tails s t];
exact
show s = a :: t ∨ s <:+ t ↔ s <:+ a :: t from
⟨fun o =>
match s, t, o with
| _, t, Or.inl rfl => suffix_rfl
| s, _, Or.inr ⟨l, rfl⟩ => ⟨a :: l, rfl⟩,
fun e =>
match s, t, e with
| _, t, ⟨[], rfl⟩ => Or.inl rfl
| s, t, ⟨b :: l, he⟩ => List.noConfusion he fun _ lt => Or.inr ⟨l, lt⟩⟩
#align list.mem_tails List.mem_tails
theorem inits_cons (a : α) (l : List α) : inits (a :: l) = [] :: l.inits.map fun t => a :: t := by
simp
#align list.inits_cons List.inits_cons
theorem tails_cons (a : α) (l : List α) : tails (a :: l) = (a :: l) :: l.tails := by simp
#align list.tails_cons List.tails_cons
@[simp]
theorem inits_append : ∀ s t : List α, inits (s ++ t) = s.inits ++ t.inits.tail.map fun l => s ++ l
| [], [] => by simp
| [], a :: t => by simp [· ∘ ·]
| a :: s, t => by simp [inits_append s t, · ∘ ·]
#align list.inits_append List.inits_append
@[simp]
theorem tails_append :
∀ s t : List α, tails (s ++ t) = (s.tails.map fun l => l ++ t) ++ t.tails.tail
| [], [] => by simp
| [], a :: t => by simp
| a :: s, t => by simp [tails_append s t]
#align list.tails_append List.tails_append
-- the lemma names `inits_eq_tails` and `tails_eq_inits` are like `sublists_eq_sublists'`
theorem inits_eq_tails : ∀ l : List α, l.inits = (reverse <| map reverse <| tails <| reverse l)
| [] => by simp
| a :: l => by simp [inits_eq_tails l, map_eq_map_iff, reverse_map]
#align list.inits_eq_tails List.inits_eq_tails
theorem tails_eq_inits : ∀ l : List α, l.tails = (reverse <| map reverse <| inits <| reverse l)
| [] => by simp
| a :: l => by simp [tails_eq_inits l, append_left_inj]
#align list.tails_eq_inits List.tails_eq_inits
theorem inits_reverse (l : List α) : inits (reverse l) = reverse (map reverse l.tails) := by
rw [tails_eq_inits l]
simp [reverse_involutive.comp_self, reverse_map]
#align list.inits_reverse List.inits_reverse
| Mathlib/Data/List/Infix.lean | 435 | 437 | theorem tails_reverse (l : List α) : tails (reverse l) = reverse (map reverse l.inits) := by |
rw [inits_eq_tails l]
simp [reverse_involutive.comp_self, reverse_map]
|
/-
Copyright (c) 2018 Scott Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Reid Barton, Mario Carneiro, Scott Morrison, Floris van Doorn
-/
import Mathlib.CategoryTheory.Adjunction.Basic
import Mathlib.CategoryTheory.Limits.Cones
#align_import category_theory.limits.is_limit from "leanprover-community/mathlib"@"740acc0e6f9adf4423f92a485d0456fc271482da"
/-!
# Limits and colimits
We set up the general theory of limits and colimits in a category.
In this introduction we only describe the setup for limits;
it is repeated, with slightly different names, for colimits.
The main structures defined in this file is
* `IsLimit c`, for `c : Cone F`, `F : J ⥤ C`, expressing that `c` is a limit cone,
See also `CategoryTheory.Limits.HasLimits` which further builds:
* `LimitCone F`, which consists of a choice of cone for `F` and the fact it is a limit cone, and
* `HasLimit F`, asserting the mere existence of some limit cone for `F`.
## Implementation
At present we simply say everything twice, in order to handle both limits and colimits.
It would be highly desirable to have some automation support,
e.g. a `@[dualize]` attribute that behaves similarly to `@[to_additive]`.
## References
* [Stacks: Limits and colimits](https://stacks.math.columbia.edu/tag/002D)
-/
noncomputable section
open CategoryTheory CategoryTheory.Category CategoryTheory.Functor Opposite
namespace CategoryTheory.Limits
-- declare the `v`'s first; see `CategoryTheory.Category` for an explanation
universe v₁ v₂ v₃ v₄ u₁ u₂ u₃ u₄
variable {J : Type u₁} [Category.{v₁} J] {K : Type u₂} [Category.{v₂} K]
variable {C : Type u₃} [Category.{v₃} C]
variable {F : J ⥤ C}
/-- A cone `t` on `F` is a limit cone if each cone on `F` admits a unique
cone morphism to `t`.
See <https://stacks.math.columbia.edu/tag/002E>.
-/
-- porting note (#5171): removed @[nolint has_nonempty_instance]
structure IsLimit (t : Cone F) where
/-- There is a morphism from any cone point to `t.pt` -/
lift : ∀ s : Cone F, s.pt ⟶ t.pt
/-- The map makes the triangle with the two natural transformations commute -/
fac : ∀ (s : Cone F) (j : J), lift s ≫ t.π.app j = s.π.app j := by aesop_cat
/-- It is the unique such map to do this -/
uniq : ∀ (s : Cone F) (m : s.pt ⟶ t.pt) (_ : ∀ j : J, m ≫ t.π.app j = s.π.app j), m = lift s := by
aesop_cat
#align category_theory.limits.is_limit CategoryTheory.Limits.IsLimit
#align category_theory.limits.is_limit.fac' CategoryTheory.Limits.IsLimit.fac
#align category_theory.limits.is_limit.uniq' CategoryTheory.Limits.IsLimit.uniq
-- Porting note (#10618): simp can prove this. Linter complains it still exists
attribute [-simp, nolint simpNF] IsLimit.mk.injEq
attribute [reassoc (attr := simp)] IsLimit.fac
namespace IsLimit
instance subsingleton {t : Cone F} : Subsingleton (IsLimit t) :=
⟨by intro P Q; cases P; cases Q; congr; aesop_cat⟩
#align category_theory.limits.is_limit.subsingleton CategoryTheory.Limits.IsLimit.subsingleton
/-- Given a natural transformation `α : F ⟶ G`, we give a morphism from the cone point
of any cone over `F` to the cone point of a limit cone over `G`. -/
def map {F G : J ⥤ C} (s : Cone F) {t : Cone G} (P : IsLimit t) (α : F ⟶ G) : s.pt ⟶ t.pt :=
P.lift ((Cones.postcompose α).obj s)
#align category_theory.limits.is_limit.map CategoryTheory.Limits.IsLimit.map
@[reassoc (attr := simp)]
theorem map_π {F G : J ⥤ C} (c : Cone F) {d : Cone G} (hd : IsLimit d) (α : F ⟶ G) (j : J) :
hd.map c α ≫ d.π.app j = c.π.app j ≫ α.app j :=
fac _ _ _
#align category_theory.limits.is_limit.map_π CategoryTheory.Limits.IsLimit.map_π
@[simp]
theorem lift_self {c : Cone F} (t : IsLimit c) : t.lift c = 𝟙 c.pt :=
(t.uniq _ _ fun _ => id_comp _).symm
#align category_theory.limits.is_limit.lift_self CategoryTheory.Limits.IsLimit.lift_self
-- Repackaging the definition in terms of cone morphisms.
/-- The universal morphism from any other cone to a limit cone. -/
@[simps]
def liftConeMorphism {t : Cone F} (h : IsLimit t) (s : Cone F) : s ⟶ t where hom := h.lift s
#align category_theory.limits.is_limit.lift_cone_morphism CategoryTheory.Limits.IsLimit.liftConeMorphism
theorem uniq_cone_morphism {s t : Cone F} (h : IsLimit t) {f f' : s ⟶ t} : f = f' :=
have : ∀ {g : s ⟶ t}, g = h.liftConeMorphism s := by
intro g; apply ConeMorphism.ext; exact h.uniq _ _ g.w
this.trans this.symm
#align category_theory.limits.is_limit.uniq_cone_morphism CategoryTheory.Limits.IsLimit.uniq_cone_morphism
/-- Restating the definition of a limit cone in terms of the ∃! operator. -/
theorem existsUnique {t : Cone F} (h : IsLimit t) (s : Cone F) :
∃! l : s.pt ⟶ t.pt, ∀ j, l ≫ t.π.app j = s.π.app j :=
⟨h.lift s, h.fac s, h.uniq s⟩
#align category_theory.limits.is_limit.exists_unique CategoryTheory.Limits.IsLimit.existsUnique
/-- Noncomputably make a limit cone from the existence of unique factorizations. -/
def ofExistsUnique {t : Cone F}
(ht : ∀ s : Cone F, ∃! l : s.pt ⟶ t.pt, ∀ j, l ≫ t.π.app j = s.π.app j) : IsLimit t := by
choose s hs hs' using ht
exact ⟨s, hs, hs'⟩
#align category_theory.limits.is_limit.of_exists_unique CategoryTheory.Limits.IsLimit.ofExistsUnique
/-- Alternative constructor for `isLimit`,
providing a morphism of cones rather than a morphism between the cone points
and separately the factorisation condition.
-/
@[simps]
def mkConeMorphism {t : Cone F} (lift : ∀ s : Cone F, s ⟶ t)
(uniq : ∀ (s : Cone F) (m : s ⟶ t), m = lift s) : IsLimit t where
lift s := (lift s).hom
uniq s m w :=
have : ConeMorphism.mk m w = lift s := by apply uniq
congrArg ConeMorphism.hom this
#align category_theory.limits.is_limit.mk_cone_morphism CategoryTheory.Limits.IsLimit.mkConeMorphism
/-- Limit cones on `F` are unique up to isomorphism. -/
@[simps]
def uniqueUpToIso {s t : Cone F} (P : IsLimit s) (Q : IsLimit t) : s ≅ t where
hom := Q.liftConeMorphism s
inv := P.liftConeMorphism t
hom_inv_id := P.uniq_cone_morphism
inv_hom_id := Q.uniq_cone_morphism
#align category_theory.limits.is_limit.unique_up_to_iso CategoryTheory.Limits.IsLimit.uniqueUpToIso
/-- Any cone morphism between limit cones is an isomorphism. -/
theorem hom_isIso {s t : Cone F} (P : IsLimit s) (Q : IsLimit t) (f : s ⟶ t) : IsIso f :=
⟨⟨P.liftConeMorphism t, ⟨P.uniq_cone_morphism, Q.uniq_cone_morphism⟩⟩⟩
#align category_theory.limits.is_limit.hom_is_iso CategoryTheory.Limits.IsLimit.hom_isIso
/-- Limits of `F` are unique up to isomorphism. -/
def conePointUniqueUpToIso {s t : Cone F} (P : IsLimit s) (Q : IsLimit t) : s.pt ≅ t.pt :=
(Cones.forget F).mapIso (uniqueUpToIso P Q)
#align category_theory.limits.is_limit.cone_point_unique_up_to_iso CategoryTheory.Limits.IsLimit.conePointUniqueUpToIso
@[reassoc (attr := simp)]
theorem conePointUniqueUpToIso_hom_comp {s t : Cone F} (P : IsLimit s) (Q : IsLimit t) (j : J) :
(conePointUniqueUpToIso P Q).hom ≫ t.π.app j = s.π.app j :=
(uniqueUpToIso P Q).hom.w _
#align category_theory.limits.is_limit.cone_point_unique_up_to_iso_hom_comp CategoryTheory.Limits.IsLimit.conePointUniqueUpToIso_hom_comp
@[reassoc (attr := simp)]
theorem conePointUniqueUpToIso_inv_comp {s t : Cone F} (P : IsLimit s) (Q : IsLimit t) (j : J) :
(conePointUniqueUpToIso P Q).inv ≫ s.π.app j = t.π.app j :=
(uniqueUpToIso P Q).inv.w _
#align category_theory.limits.is_limit.cone_point_unique_up_to_iso_inv_comp CategoryTheory.Limits.IsLimit.conePointUniqueUpToIso_inv_comp
@[reassoc (attr := simp)]
theorem lift_comp_conePointUniqueUpToIso_hom {r s t : Cone F} (P : IsLimit s) (Q : IsLimit t) :
P.lift r ≫ (conePointUniqueUpToIso P Q).hom = Q.lift r :=
Q.uniq _ _ (by simp)
#align category_theory.limits.is_limit.lift_comp_cone_point_unique_up_to_iso_hom CategoryTheory.Limits.IsLimit.lift_comp_conePointUniqueUpToIso_hom
@[reassoc (attr := simp)]
theorem lift_comp_conePointUniqueUpToIso_inv {r s t : Cone F} (P : IsLimit s) (Q : IsLimit t) :
Q.lift r ≫ (conePointUniqueUpToIso P Q).inv = P.lift r :=
P.uniq _ _ (by simp)
#align category_theory.limits.is_limit.lift_comp_cone_point_unique_up_to_iso_inv CategoryTheory.Limits.IsLimit.lift_comp_conePointUniqueUpToIso_inv
/-- Transport evidence that a cone is a limit cone across an isomorphism of cones. -/
def ofIsoLimit {r t : Cone F} (P : IsLimit r) (i : r ≅ t) : IsLimit t :=
IsLimit.mkConeMorphism (fun s => P.liftConeMorphism s ≫ i.hom) fun s m => by
rw [← i.comp_inv_eq]; apply P.uniq_cone_morphism
#align category_theory.limits.is_limit.of_iso_limit CategoryTheory.Limits.IsLimit.ofIsoLimit
@[simp]
theorem ofIsoLimit_lift {r t : Cone F} (P : IsLimit r) (i : r ≅ t) (s) :
(P.ofIsoLimit i).lift s = P.lift s ≫ i.hom.hom :=
rfl
#align category_theory.limits.is_limit.of_iso_limit_lift CategoryTheory.Limits.IsLimit.ofIsoLimit_lift
/-- Isomorphism of cones preserves whether or not they are limiting cones. -/
def equivIsoLimit {r t : Cone F} (i : r ≅ t) : IsLimit r ≃ IsLimit t where
toFun h := h.ofIsoLimit i
invFun h := h.ofIsoLimit i.symm
left_inv := by aesop_cat
right_inv := by aesop_cat
#align category_theory.limits.is_limit.equiv_iso_limit CategoryTheory.Limits.IsLimit.equivIsoLimit
@[simp]
theorem equivIsoLimit_apply {r t : Cone F} (i : r ≅ t) (P : IsLimit r) :
equivIsoLimit i P = P.ofIsoLimit i :=
rfl
#align category_theory.limits.is_limit.equiv_iso_limit_apply CategoryTheory.Limits.IsLimit.equivIsoLimit_apply
@[simp]
theorem equivIsoLimit_symm_apply {r t : Cone F} (i : r ≅ t) (P : IsLimit t) :
(equivIsoLimit i).symm P = P.ofIsoLimit i.symm :=
rfl
#align category_theory.limits.is_limit.equiv_iso_limit_symm_apply CategoryTheory.Limits.IsLimit.equivIsoLimit_symm_apply
/-- If the canonical morphism from a cone point to a limiting cone point is an iso, then the
first cone was limiting also.
-/
def ofPointIso {r t : Cone F} (P : IsLimit r) [i : IsIso (P.lift t)] : IsLimit t :=
ofIsoLimit P (by
haveI : IsIso (P.liftConeMorphism t).hom := i
haveI : IsIso (P.liftConeMorphism t) := Cones.cone_iso_of_hom_iso _
symm
apply asIso (P.liftConeMorphism t))
#align category_theory.limits.is_limit.of_point_iso CategoryTheory.Limits.IsLimit.ofPointIso
variable {t : Cone F}
theorem hom_lift (h : IsLimit t) {W : C} (m : W ⟶ t.pt) :
m = h.lift { pt := W, π := { app := fun b => m ≫ t.π.app b } } :=
h.uniq { pt := W, π := { app := fun b => m ≫ t.π.app b } } m fun b => rfl
#align category_theory.limits.is_limit.hom_lift CategoryTheory.Limits.IsLimit.hom_lift
/-- Two morphisms into a limit are equal if their compositions with
each cone morphism are equal. -/
theorem hom_ext (h : IsLimit t) {W : C} {f f' : W ⟶ t.pt}
(w : ∀ j, f ≫ t.π.app j = f' ≫ t.π.app j) :
f = f' := by
rw [h.hom_lift f, h.hom_lift f']; congr; exact funext w
#align category_theory.limits.is_limit.hom_ext CategoryTheory.Limits.IsLimit.hom_ext
/-- Given a right adjoint functor between categories of cones,
the image of a limit cone is a limit cone.
-/
def ofRightAdjoint {D : Type u₄} [Category.{v₄} D] {G : K ⥤ D} {left : Cone F ⥤ Cone G}
{right : Cone G ⥤ Cone F}
(adj : left ⊣ right) {c : Cone G} (t : IsLimit c) : IsLimit (right.obj c) :=
mkConeMorphism (fun s => adj.homEquiv s c (t.liftConeMorphism _))
fun _ _ => (Adjunction.eq_homEquiv_apply _ _ _).2 t.uniq_cone_morphism
#align category_theory.limits.is_limit.of_right_adjoint CategoryTheory.Limits.IsLimit.ofRightAdjoint
/-- Given two functors which have equivalent categories of cones, we can transport a limiting cone
across the equivalence.
-/
def ofConeEquiv {D : Type u₄} [Category.{v₄} D] {G : K ⥤ D} (h : Cone G ≌ Cone F) {c : Cone G} :
IsLimit (h.functor.obj c) ≃ IsLimit c where
toFun P := ofIsoLimit (ofRightAdjoint h.toAdjunction P) (h.unitIso.symm.app c)
invFun := ofRightAdjoint h.symm.toAdjunction
left_inv := by aesop_cat
right_inv := by aesop_cat
#align category_theory.limits.is_limit.of_cone_equiv CategoryTheory.Limits.IsLimit.ofConeEquiv
@[simp]
theorem ofConeEquiv_apply_desc {D : Type u₄} [Category.{v₄} D] {G : K ⥤ D} (h : Cone G ≌ Cone F)
{c : Cone G} (P : IsLimit (h.functor.obj c)) (s) :
(ofConeEquiv h P).lift s =
((h.unitIso.hom.app s).hom ≫ (h.inverse.map (P.liftConeMorphism (h.functor.obj s))).hom) ≫
(h.unitIso.inv.app c).hom :=
rfl
#align category_theory.limits.is_limit.of_cone_equiv_apply_desc CategoryTheory.Limits.IsLimit.ofConeEquiv_apply_desc
@[simp]
theorem ofConeEquiv_symm_apply_desc {D : Type u₄} [Category.{v₄} D] {G : K ⥤ D}
(h : Cone G ≌ Cone F) {c : Cone G} (P : IsLimit c) (s) :
((ofConeEquiv h).symm P).lift s =
(h.counitIso.inv.app s).hom ≫ (h.functor.map (P.liftConeMorphism (h.inverse.obj s))).hom :=
rfl
#align category_theory.limits.is_limit.of_cone_equiv_symm_apply_desc CategoryTheory.Limits.IsLimit.ofConeEquiv_symm_apply_desc
/--
A cone postcomposed with a natural isomorphism is a limit cone if and only if the original cone is.
-/
def postcomposeHomEquiv {F G : J ⥤ C} (α : F ≅ G) (c : Cone F) :
IsLimit ((Cones.postcompose α.hom).obj c) ≃ IsLimit c :=
ofConeEquiv (Cones.postcomposeEquivalence α)
#align category_theory.limits.is_limit.postcompose_hom_equiv CategoryTheory.Limits.IsLimit.postcomposeHomEquiv
/-- A cone postcomposed with the inverse of a natural isomorphism is a limit cone if and only if
the original cone is.
-/
def postcomposeInvEquiv {F G : J ⥤ C} (α : F ≅ G) (c : Cone G) :
IsLimit ((Cones.postcompose α.inv).obj c) ≃ IsLimit c :=
postcomposeHomEquiv α.symm c
#align category_theory.limits.is_limit.postcompose_inv_equiv CategoryTheory.Limits.IsLimit.postcomposeInvEquiv
/-- Constructing an equivalence `IsLimit c ≃ IsLimit d` from a natural isomorphism
between the underlying functors, and then an isomorphism between `c` transported along this and `d`.
-/
def equivOfNatIsoOfIso {F G : J ⥤ C} (α : F ≅ G) (c : Cone F) (d : Cone G)
(w : (Cones.postcompose α.hom).obj c ≅ d) : IsLimit c ≃ IsLimit d :=
(postcomposeHomEquiv α _).symm.trans (equivIsoLimit w)
#align category_theory.limits.is_limit.equiv_of_nat_iso_of_iso CategoryTheory.Limits.IsLimit.equivOfNatIsoOfIso
/-- The cone points of two limit cones for naturally isomorphic functors
are themselves isomorphic.
-/
@[simps]
def conePointsIsoOfNatIso {F G : J ⥤ C} {s : Cone F} {t : Cone G} (P : IsLimit s) (Q : IsLimit t)
(w : F ≅ G) : s.pt ≅ t.pt where
hom := Q.map s w.hom
inv := P.map t w.inv
hom_inv_id := P.hom_ext (by aesop_cat)
inv_hom_id := Q.hom_ext (by aesop_cat)
#align category_theory.limits.is_limit.cone_points_iso_of_nat_iso CategoryTheory.Limits.IsLimit.conePointsIsoOfNatIso
@[reassoc]
theorem conePointsIsoOfNatIso_hom_comp {F G : J ⥤ C} {s : Cone F} {t : Cone G} (P : IsLimit s)
(Q : IsLimit t) (w : F ≅ G) (j : J) :
(conePointsIsoOfNatIso P Q w).hom ≫ t.π.app j = s.π.app j ≫ w.hom.app j := by simp
#align category_theory.limits.is_limit.cone_points_iso_of_nat_iso_hom_comp CategoryTheory.Limits.IsLimit.conePointsIsoOfNatIso_hom_comp
@[reassoc]
theorem conePointsIsoOfNatIso_inv_comp {F G : J ⥤ C} {s : Cone F} {t : Cone G} (P : IsLimit s)
(Q : IsLimit t) (w : F ≅ G) (j : J) :
(conePointsIsoOfNatIso P Q w).inv ≫ s.π.app j = t.π.app j ≫ w.inv.app j := by simp
#align category_theory.limits.is_limit.cone_points_iso_of_nat_iso_inv_comp CategoryTheory.Limits.IsLimit.conePointsIsoOfNatIso_inv_comp
@[reassoc]
theorem lift_comp_conePointsIsoOfNatIso_hom {F G : J ⥤ C} {r s : Cone F} {t : Cone G}
(P : IsLimit s) (Q : IsLimit t) (w : F ≅ G) :
P.lift r ≫ (conePointsIsoOfNatIso P Q w).hom = Q.map r w.hom :=
Q.hom_ext (by simp)
#align category_theory.limits.is_limit.lift_comp_cone_points_iso_of_nat_iso_hom CategoryTheory.Limits.IsLimit.lift_comp_conePointsIsoOfNatIso_hom
@[reassoc]
theorem lift_comp_conePointsIsoOfNatIso_inv {F G : J ⥤ C} {r s : Cone G} {t : Cone F}
(P : IsLimit t) (Q : IsLimit s) (w : F ≅ G) :
Q.lift r ≫ (conePointsIsoOfNatIso P Q w).inv = P.map r w.inv :=
P.hom_ext (by simp)
#align category_theory.limits.is_limit.lift_comp_cone_points_iso_of_nat_iso_inv CategoryTheory.Limits.IsLimit.lift_comp_conePointsIsoOfNatIso_inv
section Equivalence
open CategoryTheory.Equivalence
/-- If `s : Cone F` is a limit cone, so is `s` whiskered by an equivalence `e`.
-/
def whiskerEquivalence {s : Cone F} (P : IsLimit s) (e : K ≌ J) : IsLimit (s.whisker e.functor) :=
ofRightAdjoint (Cones.whiskeringEquivalence e).symm.toAdjunction P
#align category_theory.limits.is_limit.whisker_equivalence CategoryTheory.Limits.IsLimit.whiskerEquivalence
/-- If `s : Cone F` whiskered by an equivalence `e` is a limit cone, so is `s`.
-/
def ofWhiskerEquivalence {s : Cone F} (e : K ≌ J) (P : IsLimit (s.whisker e.functor)) : IsLimit s :=
equivIsoLimit ((Cones.whiskeringEquivalence e).unitIso.app s).symm
(ofRightAdjoint (Cones.whiskeringEquivalence e).toAdjunction P)
#align category_theory.limits.is_limit.of_whisker_equivalence CategoryTheory.Limits.IsLimit.ofWhiskerEquivalence
/-- Given an equivalence of diagrams `e`, `s` is a limit cone iff `s.whisker e.functor` is.
-/
def whiskerEquivalenceEquiv {s : Cone F} (e : K ≌ J) : IsLimit s ≃ IsLimit (s.whisker e.functor) :=
⟨fun h => h.whiskerEquivalence e, ofWhiskerEquivalence e, by aesop_cat, by aesop_cat⟩
#align category_theory.limits.is_limit.whisker_equivalence_equiv CategoryTheory.Limits.IsLimit.whiskerEquivalenceEquiv
/-- A limit cone extended by an isomorphism is a limit cone. -/
def extendIso {s : Cone F} {X : C} (i : X ⟶ s.pt) [IsIso i] (hs : IsLimit s) :
IsLimit (s.extend i) :=
IsLimit.ofIsoLimit hs (Cones.extendIso s (asIso i)).symm
/-- A cone is a limit cone if its extension by an isomorphism is. -/
def ofExtendIso {s : Cone F} {X : C} (i : X ⟶ s.pt) [IsIso i] (hs : IsLimit (s.extend i)) :
IsLimit s :=
IsLimit.ofIsoLimit hs (Cones.extendIso s (asIso i))
/-- A cone is a limit cone iff its extension by an isomorphism is. -/
def extendIsoEquiv {s : Cone F} {X : C} (i : X ⟶ s.pt) [IsIso i] :
IsLimit s ≃ IsLimit (s.extend i) :=
equivOfSubsingletonOfSubsingleton (extendIso i) (ofExtendIso i)
/-- We can prove two cone points `(s : Cone F).pt` and `(t : Cone G).pt` are isomorphic if
* both cones are limit cones
* their indexing categories are equivalent via some `e : J ≌ K`,
* the triangle of functors commutes up to a natural isomorphism: `e.functor ⋙ G ≅ F`.
This is the most general form of uniqueness of cone points,
allowing relabelling of both the indexing category (up to equivalence)
and the functor (up to natural isomorphism).
-/
@[simps]
def conePointsIsoOfEquivalence {F : J ⥤ C} {s : Cone F} {G : K ⥤ C} {t : Cone G} (P : IsLimit s)
(Q : IsLimit t) (e : J ≌ K) (w : e.functor ⋙ G ≅ F) : s.pt ≅ t.pt :=
let w' : e.inverse ⋙ F ≅ G := (isoWhiskerLeft e.inverse w).symm ≪≫ invFunIdAssoc e G
{ hom := Q.lift ((Cones.equivalenceOfReindexing e.symm w').functor.obj s)
inv := P.lift ((Cones.equivalenceOfReindexing e w).functor.obj t)
hom_inv_id := by
apply hom_ext P; intro j
dsimp [w']
simp only [Limits.Cone.whisker_π, Limits.Cones.postcompose_obj_π, fac, whiskerLeft_app,
assoc, id_comp, invFunIdAssoc_hom_app, fac_assoc, NatTrans.comp_app]
rw [counit_app_functor, ← Functor.comp_map]
have l :
NatTrans.app w.hom j = NatTrans.app w.hom (Prefunctor.obj (𝟭 J).toPrefunctor j) := by dsimp
rw [l,w.hom.naturality]
simp
inv_hom_id := by
apply hom_ext Q
aesop_cat }
#align category_theory.limits.is_limit.cone_points_iso_of_equivalence CategoryTheory.Limits.IsLimit.conePointsIsoOfEquivalence
end Equivalence
/-- The universal property of a limit cone: a map `W ⟶ X` is the same as
a cone on `F` with cone point `W`. -/
def homIso (h : IsLimit t) (W : C) : ULift.{u₁} (W ⟶ t.pt : Type v₃) ≅ (const J).obj W ⟶ F where
hom f := (t.extend f.down).π
inv π := ⟨h.lift { pt := W, π }⟩
hom_inv_id := by
funext f; apply ULift.ext
apply h.hom_ext; intro j; simp
#align category_theory.limits.is_limit.hom_iso CategoryTheory.Limits.IsLimit.homIso
@[simp]
theorem homIso_hom (h : IsLimit t) {W : C} (f : ULift.{u₁} (W ⟶ t.pt)) :
(IsLimit.homIso h W).hom f = (t.extend f.down).π :=
rfl
#align category_theory.limits.is_limit.hom_iso_hom CategoryTheory.Limits.IsLimit.homIso_hom
/-- The limit of `F` represents the functor taking `W` to
the set of cones on `F` with cone point `W`. -/
def natIso (h : IsLimit t) : yoneda.obj t.pt ⋙ uliftFunctor.{u₁} ≅ F.cones :=
NatIso.ofComponents fun W => IsLimit.homIso h (unop W)
#align category_theory.limits.is_limit.nat_iso CategoryTheory.Limits.IsLimit.natIso
/-- Another, more explicit, formulation of the universal property of a limit cone.
See also `homIso`. -/
def homIso' (h : IsLimit t) (W : C) :
ULift.{u₁} (W ⟶ t.pt : Type v₃) ≅
{ p : ∀ j, W ⟶ F.obj j // ∀ {j j'} (f : j ⟶ j'), p j ≫ F.map f = p j' } :=
h.homIso W ≪≫
{ hom := fun π =>
⟨fun j => π.app j, fun f => by convert ← (π.naturality f).symm; apply id_comp⟩
inv := fun p =>
{ app := fun j => p.1 j
naturality := fun j j' f => by dsimp; rw [id_comp]; exact (p.2 f).symm } }
#align category_theory.limits.is_limit.hom_iso' CategoryTheory.Limits.IsLimit.homIso'
/-- If G : C → D is a faithful functor which sends t to a limit cone,
then it suffices to check that the induced maps for the image of t
can be lifted to maps of C. -/
def ofFaithful {t : Cone F} {D : Type u₄} [Category.{v₄} D] (G : C ⥤ D) [G.Faithful]
(ht : IsLimit (mapCone G t)) (lift : ∀ s : Cone F, s.pt ⟶ t.pt)
(h : ∀ s, G.map (lift s) = ht.lift (mapCone G s)) : IsLimit t :=
{ lift
fac := fun s j => by apply G.map_injective; rw [G.map_comp, h]; apply ht.fac
uniq := fun s m w => by
apply G.map_injective; rw [h]
refine ht.uniq (mapCone G s) _ fun j => ?_
convert ← congrArg (fun f => G.map f) (w j)
apply G.map_comp }
#align category_theory.limits.is_limit.of_faithful CategoryTheory.Limits.IsLimit.ofFaithful
/-- If `F` and `G` are naturally isomorphic, then `F.mapCone c` being a limit implies
`G.mapCone c` is also a limit.
-/
def mapConeEquiv {D : Type u₄} [Category.{v₄} D] {K : J ⥤ C} {F G : C ⥤ D} (h : F ≅ G) {c : Cone K}
(t : IsLimit (mapCone F c)) : IsLimit (mapCone G c) := by
apply postcomposeInvEquiv (isoWhiskerLeft K h : _) (mapCone G c) _
apply t.ofIsoLimit (postcomposeWhiskerLeftMapCone h.symm c).symm
#align category_theory.limits.is_limit.map_cone_equiv CategoryTheory.Limits.IsLimit.mapConeEquiv
/-- A cone is a limit cone exactly if
there is a unique cone morphism from any other cone.
-/
def isoUniqueConeMorphism {t : Cone F} : IsLimit t ≅ ∀ s, Unique (s ⟶ t) where
hom h s :=
{ default := h.liftConeMorphism s
uniq := fun _ => h.uniq_cone_morphism }
inv h :=
{ lift := fun s => (h s).default.hom
uniq := fun s f w => congrArg ConeMorphism.hom ((h s).uniq ⟨f, w⟩) }
#align category_theory.limits.is_limit.iso_unique_cone_morphism CategoryTheory.Limits.IsLimit.isoUniqueConeMorphism
namespace OfNatIso
variable {X : C} (h : yoneda.obj X ⋙ uliftFunctor.{u₁} ≅ F.cones)
/-- If `F.cones` is represented by `X`, each morphism `f : Y ⟶ X` gives a cone with cone point
`Y`. -/
def coneOfHom {Y : C} (f : Y ⟶ X) : Cone F where
pt := Y
π := h.hom.app (op Y) ⟨f⟩
#align category_theory.limits.is_limit.of_nat_iso.cone_of_hom CategoryTheory.Limits.IsLimit.OfNatIso.coneOfHom
/-- If `F.cones` is represented by `X`, each cone `s` gives a morphism `s.pt ⟶ X`. -/
def homOfCone (s : Cone F) : s.pt ⟶ X :=
(h.inv.app (op s.pt) s.π).down
#align category_theory.limits.is_limit.of_nat_iso.hom_of_cone CategoryTheory.Limits.IsLimit.OfNatIso.homOfCone
@[simp]
theorem coneOfHom_homOfCone (s : Cone F) : coneOfHom h (homOfCone h s) = s := by
dsimp [coneOfHom, homOfCone]
match s with
| .mk s_pt s_π =>
congr; dsimp
convert congrFun (congrFun (congrArg NatTrans.app h.inv_hom_id) (op s_pt)) s_π using 1
#align category_theory.limits.is_limit.of_nat_iso.cone_of_hom_of_cone CategoryTheory.Limits.IsLimit.OfNatIso.coneOfHom_homOfCone
@[simp]
theorem homOfCone_coneOfHom {Y : C} (f : Y ⟶ X) : homOfCone h (coneOfHom h f) = f :=
congrArg ULift.down (congrFun (congrFun (congrArg NatTrans.app h.hom_inv_id) (op Y)) ⟨f⟩ : _)
#align category_theory.limits.is_limit.of_nat_iso.hom_of_cone_of_hom CategoryTheory.Limits.IsLimit.OfNatIso.homOfCone_coneOfHom
/-- If `F.cones` is represented by `X`, the cone corresponding to the identity morphism on `X`
will be a limit cone. -/
def limitCone : Cone F :=
coneOfHom h (𝟙 X)
#align category_theory.limits.is_limit.of_nat_iso.limit_cone CategoryTheory.Limits.IsLimit.OfNatIso.limitCone
/-- If `F.cones` is represented by `X`, the cone corresponding to a morphism `f : Y ⟶ X` is
the limit cone extended by `f`. -/
| Mathlib/CategoryTheory/Limits/IsLimit.lean | 513 | 520 | theorem coneOfHom_fac {Y : C} (f : Y ⟶ X) : coneOfHom h f = (limitCone h).extend f := by |
dsimp [coneOfHom, limitCone, Cone.extend]
congr with j
have t := congrFun (h.hom.naturality f.op) ⟨𝟙 X⟩
dsimp at t
simp only [comp_id] at t
rw [congrFun (congrArg NatTrans.app t) j]
rfl
|
/-
Copyright (c) 2019 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Yaël Dillies
-/
import Mathlib.Algebra.Module.BigOperators
import Mathlib.Data.Fintype.Perm
import Mathlib.GroupTheory.Perm.Finite
import Mathlib.GroupTheory.Perm.List
#align_import group_theory.perm.cycle.basic from "leanprover-community/mathlib"@"e8638a0fcaf73e4500469f368ef9494e495099b3"
/-!
# Cycles of a permutation
This file starts the theory of cycles in permutations.
## Main definitions
In the following, `f : Equiv.Perm β`.
* `Equiv.Perm.SameCycle`: `f.SameCycle x y` when `x` and `y` are in the same cycle of `f`.
* `Equiv.Perm.IsCycle`: `f` is a cycle if any two nonfixed points of `f` are related by repeated
applications of `f`, and `f` is not the identity.
* `Equiv.Perm.IsCycleOn`: `f` is a cycle on a set `s` when any two points of `s` are related by
repeated applications of `f`.
## Notes
`Equiv.Perm.IsCycle` and `Equiv.Perm.IsCycleOn` are different in three ways:
* `IsCycle` is about the entire type while `IsCycleOn` is restricted to a set.
* `IsCycle` forbids the identity while `IsCycleOn` allows it (if `s` is a subsingleton).
* `IsCycleOn` forbids fixed points on `s` (if `s` is nontrivial), while `IsCycle` allows them.
-/
open Equiv Function Finset
variable {ι α β : Type*}
namespace Equiv.Perm
/-! ### `SameCycle` -/
section SameCycle
variable {f g : Perm α} {p : α → Prop} {x y z : α}
/-- The equivalence relation indicating that two points are in the same cycle of a permutation. -/
def SameCycle (f : Perm α) (x y : α) : Prop :=
∃ i : ℤ, (f ^ i) x = y
#align equiv.perm.same_cycle Equiv.Perm.SameCycle
@[refl]
theorem SameCycle.refl (f : Perm α) (x : α) : SameCycle f x x :=
⟨0, rfl⟩
#align equiv.perm.same_cycle.refl Equiv.Perm.SameCycle.refl
theorem SameCycle.rfl : SameCycle f x x :=
SameCycle.refl _ _
#align equiv.perm.same_cycle.rfl Equiv.Perm.SameCycle.rfl
protected theorem _root_.Eq.sameCycle (h : x = y) (f : Perm α) : f.SameCycle x y := by rw [h]
#align eq.same_cycle Eq.sameCycle
@[symm]
theorem SameCycle.symm : SameCycle f x y → SameCycle f y x := fun ⟨i, hi⟩ =>
⟨-i, by rw [zpow_neg, ← hi, inv_apply_self]⟩
#align equiv.perm.same_cycle.symm Equiv.Perm.SameCycle.symm
theorem sameCycle_comm : SameCycle f x y ↔ SameCycle f y x :=
⟨SameCycle.symm, SameCycle.symm⟩
#align equiv.perm.same_cycle_comm Equiv.Perm.sameCycle_comm
@[trans]
theorem SameCycle.trans : SameCycle f x y → SameCycle f y z → SameCycle f x z :=
fun ⟨i, hi⟩ ⟨j, hj⟩ => ⟨j + i, by rw [zpow_add, mul_apply, hi, hj]⟩
#align equiv.perm.same_cycle.trans Equiv.Perm.SameCycle.trans
variable (f) in
theorem SameCycle.equivalence : Equivalence (SameCycle f) :=
⟨SameCycle.refl f, SameCycle.symm, SameCycle.trans⟩
/-- The setoid defined by the `SameCycle` relation. -/
def SameCycle.setoid (f : Perm α) : Setoid α where
iseqv := SameCycle.equivalence f
@[simp]
theorem sameCycle_one : SameCycle 1 x y ↔ x = y := by simp [SameCycle]
#align equiv.perm.same_cycle_one Equiv.Perm.sameCycle_one
@[simp]
theorem sameCycle_inv : SameCycle f⁻¹ x y ↔ SameCycle f x y :=
(Equiv.neg _).exists_congr_left.trans <| by simp [SameCycle]
#align equiv.perm.same_cycle_inv Equiv.Perm.sameCycle_inv
alias ⟨SameCycle.of_inv, SameCycle.inv⟩ := sameCycle_inv
#align equiv.perm.same_cycle.of_inv Equiv.Perm.SameCycle.of_inv
#align equiv.perm.same_cycle.inv Equiv.Perm.SameCycle.inv
@[simp]
theorem sameCycle_conj : SameCycle (g * f * g⁻¹) x y ↔ SameCycle f (g⁻¹ x) (g⁻¹ y) :=
exists_congr fun i => by simp [conj_zpow, eq_inv_iff_eq]
#align equiv.perm.same_cycle_conj Equiv.Perm.sameCycle_conj
theorem SameCycle.conj : SameCycle f x y → SameCycle (g * f * g⁻¹) (g x) (g y) := by
simp [sameCycle_conj]
#align equiv.perm.same_cycle.conj Equiv.Perm.SameCycle.conj
theorem SameCycle.apply_eq_self_iff : SameCycle f x y → (f x = x ↔ f y = y) := fun ⟨i, hi⟩ => by
rw [← hi, ← mul_apply, ← zpow_one_add, add_comm, zpow_add_one, mul_apply,
(f ^ i).injective.eq_iff]
#align equiv.perm.same_cycle.apply_eq_self_iff Equiv.Perm.SameCycle.apply_eq_self_iff
theorem SameCycle.eq_of_left (h : SameCycle f x y) (hx : IsFixedPt f x) : x = y :=
let ⟨_, hn⟩ := h
(hx.perm_zpow _).eq.symm.trans hn
#align equiv.perm.same_cycle.eq_of_left Equiv.Perm.SameCycle.eq_of_left
theorem SameCycle.eq_of_right (h : SameCycle f x y) (hy : IsFixedPt f y) : x = y :=
h.eq_of_left <| h.apply_eq_self_iff.2 hy
#align equiv.perm.same_cycle.eq_of_right Equiv.Perm.SameCycle.eq_of_right
@[simp]
theorem sameCycle_apply_left : SameCycle f (f x) y ↔ SameCycle f x y :=
(Equiv.addRight 1).exists_congr_left.trans <| by
simp [zpow_sub, SameCycle, Int.add_neg_one, Function.comp]
#align equiv.perm.same_cycle_apply_left Equiv.Perm.sameCycle_apply_left
@[simp]
theorem sameCycle_apply_right : SameCycle f x (f y) ↔ SameCycle f x y := by
rw [sameCycle_comm, sameCycle_apply_left, sameCycle_comm]
#align equiv.perm.same_cycle_apply_right Equiv.Perm.sameCycle_apply_right
@[simp]
theorem sameCycle_inv_apply_left : SameCycle f (f⁻¹ x) y ↔ SameCycle f x y := by
rw [← sameCycle_apply_left, apply_inv_self]
#align equiv.perm.same_cycle_inv_apply_left Equiv.Perm.sameCycle_inv_apply_left
@[simp]
theorem sameCycle_inv_apply_right : SameCycle f x (f⁻¹ y) ↔ SameCycle f x y := by
rw [← sameCycle_apply_right, apply_inv_self]
#align equiv.perm.same_cycle_inv_apply_right Equiv.Perm.sameCycle_inv_apply_right
@[simp]
theorem sameCycle_zpow_left {n : ℤ} : SameCycle f ((f ^ n) x) y ↔ SameCycle f x y :=
(Equiv.addRight (n : ℤ)).exists_congr_left.trans <| by simp [SameCycle, zpow_add]
#align equiv.perm.same_cycle_zpow_left Equiv.Perm.sameCycle_zpow_left
@[simp]
theorem sameCycle_zpow_right {n : ℤ} : SameCycle f x ((f ^ n) y) ↔ SameCycle f x y := by
rw [sameCycle_comm, sameCycle_zpow_left, sameCycle_comm]
#align equiv.perm.same_cycle_zpow_right Equiv.Perm.sameCycle_zpow_right
@[simp]
theorem sameCycle_pow_left {n : ℕ} : SameCycle f ((f ^ n) x) y ↔ SameCycle f x y := by
rw [← zpow_natCast, sameCycle_zpow_left]
#align equiv.perm.same_cycle_pow_left Equiv.Perm.sameCycle_pow_left
@[simp]
theorem sameCycle_pow_right {n : ℕ} : SameCycle f x ((f ^ n) y) ↔ SameCycle f x y := by
rw [← zpow_natCast, sameCycle_zpow_right]
#align equiv.perm.same_cycle_pow_right Equiv.Perm.sameCycle_pow_right
alias ⟨SameCycle.of_apply_left, SameCycle.apply_left⟩ := sameCycle_apply_left
#align equiv.perm.same_cycle.of_apply_left Equiv.Perm.SameCycle.of_apply_left
#align equiv.perm.same_cycle.apply_left Equiv.Perm.SameCycle.apply_left
alias ⟨SameCycle.of_apply_right, SameCycle.apply_right⟩ := sameCycle_apply_right
#align equiv.perm.same_cycle.of_apply_right Equiv.Perm.SameCycle.of_apply_right
#align equiv.perm.same_cycle.apply_right Equiv.Perm.SameCycle.apply_right
alias ⟨SameCycle.of_inv_apply_left, SameCycle.inv_apply_left⟩ := sameCycle_inv_apply_left
#align equiv.perm.same_cycle.of_inv_apply_left Equiv.Perm.SameCycle.of_inv_apply_left
#align equiv.perm.same_cycle.inv_apply_left Equiv.Perm.SameCycle.inv_apply_left
alias ⟨SameCycle.of_inv_apply_right, SameCycle.inv_apply_right⟩ := sameCycle_inv_apply_right
#align equiv.perm.same_cycle.of_inv_apply_right Equiv.Perm.SameCycle.of_inv_apply_right
#align equiv.perm.same_cycle.inv_apply_right Equiv.Perm.SameCycle.inv_apply_right
alias ⟨SameCycle.of_pow_left, SameCycle.pow_left⟩ := sameCycle_pow_left
#align equiv.perm.same_cycle.of_pow_left Equiv.Perm.SameCycle.of_pow_left
#align equiv.perm.same_cycle.pow_left Equiv.Perm.SameCycle.pow_left
alias ⟨SameCycle.of_pow_right, SameCycle.pow_right⟩ := sameCycle_pow_right
#align equiv.perm.same_cycle.of_pow_right Equiv.Perm.SameCycle.of_pow_right
#align equiv.perm.same_cycle.pow_right Equiv.Perm.SameCycle.pow_right
alias ⟨SameCycle.of_zpow_left, SameCycle.zpow_left⟩ := sameCycle_zpow_left
#align equiv.perm.same_cycle.of_zpow_left Equiv.Perm.SameCycle.of_zpow_left
#align equiv.perm.same_cycle.zpow_left Equiv.Perm.SameCycle.zpow_left
alias ⟨SameCycle.of_zpow_right, SameCycle.zpow_right⟩ := sameCycle_zpow_right
#align equiv.perm.same_cycle.of_zpow_right Equiv.Perm.SameCycle.of_zpow_right
#align equiv.perm.same_cycle.zpow_right Equiv.Perm.SameCycle.zpow_right
theorem SameCycle.of_pow {n : ℕ} : SameCycle (f ^ n) x y → SameCycle f x y := fun ⟨m, h⟩ =>
⟨n * m, by simp [zpow_mul, h]⟩
#align equiv.perm.same_cycle.of_pow Equiv.Perm.SameCycle.of_pow
theorem SameCycle.of_zpow {n : ℤ} : SameCycle (f ^ n) x y → SameCycle f x y := fun ⟨m, h⟩ =>
⟨n * m, by simp [zpow_mul, h]⟩
#align equiv.perm.same_cycle.of_zpow Equiv.Perm.SameCycle.of_zpow
@[simp]
theorem sameCycle_subtypePerm {h} {x y : { x // p x }} :
(f.subtypePerm h).SameCycle x y ↔ f.SameCycle x y :=
exists_congr fun n => by simp [Subtype.ext_iff]
#align equiv.perm.same_cycle_subtype_perm Equiv.Perm.sameCycle_subtypePerm
alias ⟨_, SameCycle.subtypePerm⟩ := sameCycle_subtypePerm
#align equiv.perm.same_cycle.subtype_perm Equiv.Perm.SameCycle.subtypePerm
@[simp]
theorem sameCycle_extendDomain {p : β → Prop} [DecidablePred p] {f : α ≃ Subtype p} :
SameCycle (g.extendDomain f) (f x) (f y) ↔ g.SameCycle x y :=
exists_congr fun n => by
rw [← extendDomain_zpow, extendDomain_apply_image, Subtype.coe_inj, f.injective.eq_iff]
#align equiv.perm.same_cycle_extend_domain Equiv.Perm.sameCycle_extendDomain
alias ⟨_, SameCycle.extendDomain⟩ := sameCycle_extendDomain
#align equiv.perm.same_cycle.extend_domain Equiv.Perm.SameCycle.extendDomain
theorem SameCycle.exists_pow_eq' [Finite α] : SameCycle f x y → ∃ i < orderOf f, (f ^ i) x = y := by
classical
rintro ⟨k, rfl⟩
use (k % orderOf f).natAbs
have h₀ := Int.natCast_pos.mpr (orderOf_pos f)
have h₁ := Int.emod_nonneg k h₀.ne'
rw [← zpow_natCast, Int.natAbs_of_nonneg h₁, zpow_mod_orderOf]
refine ⟨?_, by rfl⟩
rw [← Int.ofNat_lt, Int.natAbs_of_nonneg h₁]
exact Int.emod_lt_of_pos _ h₀
#align equiv.perm.same_cycle.exists_pow_eq' Equiv.Perm.SameCycle.exists_pow_eq'
theorem SameCycle.exists_pow_eq'' [Finite α] (h : SameCycle f x y) :
∃ i : ℕ, 0 < i ∧ i ≤ orderOf f ∧ (f ^ i) x = y := by
classical
obtain ⟨_ | i, hi, rfl⟩ := h.exists_pow_eq'
· refine ⟨orderOf f, orderOf_pos f, le_rfl, ?_⟩
rw [pow_orderOf_eq_one, pow_zero]
· exact ⟨i.succ, i.zero_lt_succ, hi.le, by rfl⟩
#align equiv.perm.same_cycle.exists_pow_eq'' Equiv.Perm.SameCycle.exists_pow_eq''
instance [Fintype α] [DecidableEq α] (f : Perm α) : DecidableRel (SameCycle f) := fun x y =>
decidable_of_iff (∃ n ∈ List.range (Fintype.card (Perm α)), (f ^ n) x = y)
⟨fun ⟨n, _, hn⟩ => ⟨n, hn⟩, fun ⟨i, hi⟩ => ⟨(i % orderOf f).natAbs,
List.mem_range.2 (Int.ofNat_lt.1 <| by
rw [Int.natAbs_of_nonneg (Int.emod_nonneg _ <| Int.natCast_ne_zero.2 (orderOf_pos _).ne')]
refine (Int.emod_lt _ <| Int.natCast_ne_zero_iff_pos.2 <| orderOf_pos _).trans_le ?_
simp [orderOf_le_card_univ]),
by
rw [← zpow_natCast, Int.natAbs_of_nonneg (Int.emod_nonneg _ <|
Int.natCast_ne_zero_iff_pos.2 <| orderOf_pos _), zpow_mod_orderOf, hi]⟩⟩
end SameCycle
/-!
### `IsCycle`
-/
section IsCycle
variable {f g : Perm α} {x y : α}
/-- A cycle is a non identity permutation where any two nonfixed points of the permutation are
related by repeated application of the permutation. -/
def IsCycle (f : Perm α) : Prop :=
∃ x, f x ≠ x ∧ ∀ ⦃y⦄, f y ≠ y → SameCycle f x y
#align equiv.perm.is_cycle Equiv.Perm.IsCycle
theorem IsCycle.ne_one (h : IsCycle f) : f ≠ 1 := fun hf => by simp [hf, IsCycle] at h
#align equiv.perm.is_cycle.ne_one Equiv.Perm.IsCycle.ne_one
@[simp]
theorem not_isCycle_one : ¬(1 : Perm α).IsCycle := fun H => H.ne_one rfl
#align equiv.perm.not_is_cycle_one Equiv.Perm.not_isCycle_one
protected theorem IsCycle.sameCycle (hf : IsCycle f) (hx : f x ≠ x) (hy : f y ≠ y) :
SameCycle f x y :=
let ⟨g, hg⟩ := hf
let ⟨a, ha⟩ := hg.2 hx
let ⟨b, hb⟩ := hg.2 hy
⟨b - a, by rw [← ha, ← mul_apply, ← zpow_add, sub_add_cancel, hb]⟩
#align equiv.perm.is_cycle.same_cycle Equiv.Perm.IsCycle.sameCycle
theorem IsCycle.exists_zpow_eq : IsCycle f → f x ≠ x → f y ≠ y → ∃ i : ℤ, (f ^ i) x = y :=
IsCycle.sameCycle
#align equiv.perm.is_cycle.exists_zpow_eq Equiv.Perm.IsCycle.exists_zpow_eq
theorem IsCycle.inv (hf : IsCycle f) : IsCycle f⁻¹ :=
hf.imp fun _ ⟨hx, h⟩ =>
⟨inv_eq_iff_eq.not.2 hx.symm, fun _ hy => (h <| inv_eq_iff_eq.not.2 hy.symm).inv⟩
#align equiv.perm.is_cycle.inv Equiv.Perm.IsCycle.inv
@[simp]
theorem isCycle_inv : IsCycle f⁻¹ ↔ IsCycle f :=
⟨fun h => h.inv, IsCycle.inv⟩
#align equiv.perm.is_cycle_inv Equiv.Perm.isCycle_inv
theorem IsCycle.conj : IsCycle f → IsCycle (g * f * g⁻¹) := by
rintro ⟨x, hx, h⟩
refine ⟨g x, by simp [coe_mul, inv_apply_self, hx], fun y hy => ?_⟩
rw [← apply_inv_self g y]
exact (h <| eq_inv_iff_eq.not.2 hy).conj
#align equiv.perm.is_cycle.conj Equiv.Perm.IsCycle.conj
protected theorem IsCycle.extendDomain {p : β → Prop} [DecidablePred p] (f : α ≃ Subtype p) :
IsCycle g → IsCycle (g.extendDomain f) := by
rintro ⟨a, ha, ha'⟩
refine ⟨f a, ?_, fun b hb => ?_⟩
· rw [extendDomain_apply_image]
exact Subtype.coe_injective.ne (f.injective.ne ha)
have h : b = f (f.symm ⟨b, of_not_not <| hb ∘ extendDomain_apply_not_subtype _ _⟩) := by
rw [apply_symm_apply, Subtype.coe_mk]
rw [h] at hb ⊢
simp only [extendDomain_apply_image, Subtype.coe_injective.ne_iff, f.injective.ne_iff] at hb
exact (ha' hb).extendDomain
#align equiv.perm.is_cycle.extend_domain Equiv.Perm.IsCycle.extendDomain
theorem isCycle_iff_sameCycle (hx : f x ≠ x) : IsCycle f ↔ ∀ {y}, SameCycle f x y ↔ f y ≠ y :=
⟨fun hf y =>
⟨fun ⟨i, hi⟩ hy =>
hx <| by
rw [← zpow_apply_eq_self_of_apply_eq_self hy i, (f ^ i).injective.eq_iff] at hi
rw [hi, hy],
hf.exists_zpow_eq hx⟩,
fun h => ⟨x, hx, fun y hy => h.2 hy⟩⟩
#align equiv.perm.is_cycle_iff_same_cycle Equiv.Perm.isCycle_iff_sameCycle
section Finite
variable [Finite α]
theorem IsCycle.exists_pow_eq (hf : IsCycle f) (hx : f x ≠ x) (hy : f y ≠ y) :
∃ i : ℕ, (f ^ i) x = y := by
let ⟨n, hn⟩ := hf.exists_zpow_eq hx hy
classical exact
⟨(n % orderOf f).toNat, by
{have := n.emod_nonneg (Int.natCast_ne_zero.mpr (ne_of_gt (orderOf_pos f)))
rwa [← zpow_natCast, Int.toNat_of_nonneg this, zpow_mod_orderOf]}⟩
#align equiv.perm.is_cycle.exists_pow_eq Equiv.Perm.IsCycle.exists_pow_eq
end Finite
variable [DecidableEq α]
theorem isCycle_swap (hxy : x ≠ y) : IsCycle (swap x y) :=
⟨y, by rwa [swap_apply_right], fun a (ha : ite (a = x) y (ite (a = y) x a) ≠ a) =>
if hya : y = a then ⟨0, hya⟩
else
⟨1, by
rw [zpow_one, swap_apply_def]
split_ifs at * <;> tauto⟩⟩
#align equiv.perm.is_cycle_swap Equiv.Perm.isCycle_swap
protected theorem IsSwap.isCycle : IsSwap f → IsCycle f := by
rintro ⟨x, y, hxy, rfl⟩
exact isCycle_swap hxy
#align equiv.perm.is_swap.is_cycle Equiv.Perm.IsSwap.isCycle
variable [Fintype α]
theorem IsCycle.two_le_card_support (h : IsCycle f) : 2 ≤ f.support.card :=
two_le_card_support_of_ne_one h.ne_one
#align equiv.perm.is_cycle.two_le_card_support Equiv.Perm.IsCycle.two_le_card_support
#noalign equiv.perm.is_cycle.exists_pow_eq_one
/-- The subgroup generated by a cycle is in bijection with its support -/
noncomputable def IsCycle.zpowersEquivSupport {σ : Perm α} (hσ : IsCycle σ) :
(Subgroup.zpowers σ) ≃ σ.support :=
Equiv.ofBijective
(fun (τ : ↥ ((Subgroup.zpowers σ) : Set (Perm α))) =>
⟨(τ : Perm α) (Classical.choose hσ), by
obtain ⟨τ, n, rfl⟩ := τ
erw [Finset.mem_coe, Subtype.coe_mk, zpow_apply_mem_support, mem_support]
exact (Classical.choose_spec hσ).1⟩)
(by
constructor
· rintro ⟨a, m, rfl⟩ ⟨b, n, rfl⟩ h
ext y
by_cases hy : σ y = y
· simp_rw [zpow_apply_eq_self_of_apply_eq_self hy]
· obtain ⟨i, rfl⟩ := (Classical.choose_spec hσ).2 hy
rw [Subtype.coe_mk, Subtype.coe_mk, zpow_apply_comm σ m i, zpow_apply_comm σ n i]
exact congr_arg _ (Subtype.ext_iff.mp h)
· rintro ⟨y, hy⟩
erw [Finset.mem_coe, mem_support] at hy
obtain ⟨n, rfl⟩ := (Classical.choose_spec hσ).2 hy
exact ⟨⟨σ ^ n, n, rfl⟩, rfl⟩)
#align equiv.perm.is_cycle.zpowers_equiv_support Equiv.Perm.IsCycle.zpowersEquivSupport
@[simp]
theorem IsCycle.zpowersEquivSupport_apply {σ : Perm α} (hσ : IsCycle σ) {n : ℕ} :
hσ.zpowersEquivSupport ⟨σ ^ n, n, rfl⟩ =
⟨(σ ^ n) (Classical.choose hσ),
pow_apply_mem_support.2 (mem_support.2 (Classical.choose_spec hσ).1)⟩ :=
rfl
#align equiv.perm.is_cycle.zpowers_equiv_support_apply Equiv.Perm.IsCycle.zpowersEquivSupport_apply
@[simp]
theorem IsCycle.zpowersEquivSupport_symm_apply {σ : Perm α} (hσ : IsCycle σ) (n : ℕ) :
hσ.zpowersEquivSupport.symm
⟨(σ ^ n) (Classical.choose hσ),
pow_apply_mem_support.2 (mem_support.2 (Classical.choose_spec hσ).1)⟩ =
⟨σ ^ n, n, rfl⟩ :=
(Equiv.symm_apply_eq _).2 hσ.zpowersEquivSupport_apply
#align equiv.perm.is_cycle.zpowers_equiv_support_symm_apply Equiv.Perm.IsCycle.zpowersEquivSupport_symm_apply
protected theorem IsCycle.orderOf (hf : IsCycle f) : orderOf f = f.support.card := by
rw [← Fintype.card_zpowers, ← Fintype.card_coe]
convert Fintype.card_congr (IsCycle.zpowersEquivSupport hf)
#align equiv.perm.is_cycle.order_of Equiv.Perm.IsCycle.orderOf
theorem isCycle_swap_mul_aux₁ {α : Type*} [DecidableEq α] :
∀ (n : ℕ) {b x : α} {f : Perm α} (_ : (swap x (f x) * f) b ≠ b) (_ : (f ^ n) (f x) = b),
∃ i : ℤ, ((swap x (f x) * f) ^ i) (f x) = b := by
intro n
induction' n with n hn
· exact fun _ h => ⟨0, h⟩
· intro b x f hb h
exact if hfbx : f x = b then ⟨0, hfbx⟩
else
have : f b ≠ b ∧ b ≠ x := ne_and_ne_of_swap_mul_apply_ne_self hb
have hb' : (swap x (f x) * f) (f⁻¹ b) ≠ f⁻¹ b := by
rw [mul_apply, apply_inv_self, swap_apply_of_ne_of_ne this.2 (Ne.symm hfbx), Ne, ←
f.injective.eq_iff, apply_inv_self]
exact this.1
let ⟨i, hi⟩ := hn hb' (f.injective <| by
rw [apply_inv_self]; rwa [pow_succ', mul_apply] at h)
⟨i + 1, by
rw [add_comm, zpow_add, mul_apply, hi, zpow_one, mul_apply, apply_inv_self,
swap_apply_of_ne_of_ne (ne_and_ne_of_swap_mul_apply_ne_self hb).2 (Ne.symm hfbx)]⟩
#align equiv.perm.is_cycle_swap_mul_aux₁ Equiv.Perm.isCycle_swap_mul_aux₁
theorem isCycle_swap_mul_aux₂ {α : Type*} [DecidableEq α] :
∀ (n : ℤ) {b x : α} {f : Perm α} (_ : (swap x (f x) * f) b ≠ b) (_ : (f ^ n) (f x) = b),
∃ i : ℤ, ((swap x (f x) * f) ^ i) (f x) = b := by
intro n
induction' n with n n
· exact isCycle_swap_mul_aux₁ n
· intro b x f hb h
exact if hfbx' : f x = b then ⟨0, hfbx'⟩
else
have : f b ≠ b ∧ b ≠ x := ne_and_ne_of_swap_mul_apply_ne_self hb
have hb : (swap x (f⁻¹ x) * f⁻¹) (f⁻¹ b) ≠ f⁻¹ b := by
rw [mul_apply, swap_apply_def]
split_ifs <;>
simp only [inv_eq_iff_eq, Perm.mul_apply, zpow_negSucc, Ne, Perm.apply_inv_self] at *
<;> tauto
let ⟨i, hi⟩ :=
isCycle_swap_mul_aux₁ n hb
(show (f⁻¹ ^ n) (f⁻¹ x) = f⁻¹ b by
rw [← zpow_natCast, ← h, ← mul_apply, ← mul_apply, ← mul_apply, zpow_negSucc,
← inv_pow, pow_succ, mul_assoc, mul_assoc, inv_mul_self, mul_one, zpow_natCast,
← pow_succ', ← pow_succ])
have h : (swap x (f⁻¹ x) * f⁻¹) (f x) = f⁻¹ x := by
rw [mul_apply, inv_apply_self, swap_apply_left]
⟨-i, by
rw [← add_sub_cancel_right i 1, neg_sub, sub_eq_add_neg, zpow_add, zpow_one, zpow_neg,
← inv_zpow, mul_inv_rev, swap_inv, mul_swap_eq_swap_mul, inv_apply_self, swap_comm _ x,
zpow_add, zpow_one, mul_apply, mul_apply (_ ^ i), h, hi, mul_apply, apply_inv_self,
swap_apply_of_ne_of_ne this.2 (Ne.symm hfbx')]⟩
#align equiv.perm.is_cycle_swap_mul_aux₂ Equiv.Perm.isCycle_swap_mul_aux₂
theorem IsCycle.eq_swap_of_apply_apply_eq_self {α : Type*} [DecidableEq α] {f : Perm α}
(hf : IsCycle f) {x : α} (hfx : f x ≠ x) (hffx : f (f x) = x) : f = swap x (f x) :=
Equiv.ext fun y =>
let ⟨z, hz⟩ := hf
let ⟨i, hi⟩ := hz.2 hfx
if hyx : y = x then by simp [hyx]
else
if hfyx : y = f x then by simp [hfyx, hffx]
else by
rw [swap_apply_of_ne_of_ne hyx hfyx]
refine by_contradiction fun hy => ?_
cases' hz.2 hy with j hj
rw [← sub_add_cancel j i, zpow_add, mul_apply, hi] at hj
cases' zpow_apply_eq_of_apply_apply_eq_self hffx (j - i) with hji hji
· rw [← hj, hji] at hyx
tauto
· rw [← hj, hji] at hfyx
tauto
#align equiv.perm.is_cycle.eq_swap_of_apply_apply_eq_self Equiv.Perm.IsCycle.eq_swap_of_apply_apply_eq_self
theorem IsCycle.swap_mul {α : Type*} [DecidableEq α] {f : Perm α} (hf : IsCycle f) {x : α}
(hx : f x ≠ x) (hffx : f (f x) ≠ x) : IsCycle (swap x (f x) * f) :=
⟨f x, by simp [swap_apply_def, mul_apply, if_neg hffx, f.injective.eq_iff, if_neg hx, hx],
fun y hy =>
let ⟨i, hi⟩ := hf.exists_zpow_eq hx (ne_and_ne_of_swap_mul_apply_ne_self hy).1
-- Porting note: Needed to add Perm α typehint, otherwise does not know how to coerce to fun
have hi : (f ^ (i - 1) : Perm α) (f x) = y :=
calc
(f ^ (i - 1) : Perm α) (f x) = (f ^ (i - 1) * f ^ (1 : ℤ) : Perm α) x := by simp
_ = y := by rwa [← zpow_add, sub_add_cancel]
isCycle_swap_mul_aux₂ (i - 1) hy hi⟩
#align equiv.perm.is_cycle.swap_mul Equiv.Perm.IsCycle.swap_mul
theorem IsCycle.sign {f : Perm α} (hf : IsCycle f) : sign f = -(-1) ^ f.support.card :=
let ⟨x, hx⟩ := hf
calc
Perm.sign f = Perm.sign (swap x (f x) * (swap x (f x) * f)) := by
{rw [← mul_assoc, mul_def, mul_def, swap_swap, trans_refl]}
_ = -(-1) ^ f.support.card :=
if h1 : f (f x) = x then by
have h : swap x (f x) * f = 1 := by
simp only [mul_def, one_def]
rw [hf.eq_swap_of_apply_apply_eq_self hx.1 h1, swap_apply_left, swap_swap]
rw [sign_mul, sign_swap hx.1.symm, h, sign_one,
hf.eq_swap_of_apply_apply_eq_self hx.1 h1, card_support_swap hx.1.symm]
rfl
else by
have h : card (support (swap x (f x) * f)) + 1 = card (support f) := by
rw [← insert_erase (mem_support.2 hx.1), support_swap_mul_eq _ _ h1,
card_insert_of_not_mem (not_mem_erase _ _), sdiff_singleton_eq_erase]
have : card (support (swap x (f x) * f)) < card (support f) :=
card_support_swap_mul hx.1
rw [sign_mul, sign_swap hx.1.symm, (hf.swap_mul hx.1 h1).sign, ← h]
simp only [mul_neg, neg_mul, one_mul, neg_neg, pow_add, pow_one, mul_one]
termination_by f.support.card
#align equiv.perm.is_cycle.sign Equiv.Perm.IsCycle.sign
theorem IsCycle.of_pow {n : ℕ} (h1 : IsCycle (f ^ n)) (h2 : f.support ⊆ (f ^ n).support) :
IsCycle f := by
have key : ∀ x : α, (f ^ n) x ≠ x ↔ f x ≠ x := by
simp_rw [← mem_support, ← Finset.ext_iff]
exact (support_pow_le _ n).antisymm h2
obtain ⟨x, hx1, hx2⟩ := h1
refine ⟨x, (key x).mp hx1, fun y hy => ?_⟩
cases' hx2 ((key y).mpr hy) with i _
exact ⟨n * i, by rwa [zpow_mul]⟩
#align equiv.perm.is_cycle.of_pow Equiv.Perm.IsCycle.of_pow
-- The lemma `support_zpow_le` is relevant. It means that `h2` is equivalent to
-- `σ.support = (σ ^ n).support`, as well as to `σ.support.card ≤ (σ ^ n).support.card`.
theorem IsCycle.of_zpow {n : ℤ} (h1 : IsCycle (f ^ n)) (h2 : f.support ⊆ (f ^ n).support) :
IsCycle f := by
cases n
· exact h1.of_pow h2
· simp only [le_eq_subset, zpow_negSucc, Perm.support_inv] at h1 h2
exact (inv_inv (f ^ _) ▸ h1.inv).of_pow h2
#align equiv.perm.is_cycle.of_zpow Equiv.Perm.IsCycle.of_zpow
theorem nodup_of_pairwise_disjoint_cycles {l : List (Perm β)} (h1 : ∀ f ∈ l, IsCycle f)
(h2 : l.Pairwise Disjoint) : l.Nodup :=
nodup_of_pairwise_disjoint (fun h => (h1 1 h).ne_one rfl) h2
#align equiv.perm.nodup_of_pairwise_disjoint_cycles Equiv.Perm.nodup_of_pairwise_disjoint_cycles
/-- Unlike `support_congr`, which assumes that `∀ (x ∈ g.support), f x = g x)`, here
we have the weaker assumption that `∀ (x ∈ f.support), f x = g x`. -/
theorem IsCycle.support_congr (hf : IsCycle f) (hg : IsCycle g) (h : f.support ⊆ g.support)
(h' : ∀ x ∈ f.support, f x = g x) : f = g := by
have : f.support = g.support := by
refine le_antisymm h ?_
intro z hz
obtain ⟨x, hx, _⟩ := id hf
have hx' : g x ≠ x := by rwa [← h' x (mem_support.mpr hx)]
obtain ⟨m, hm⟩ := hg.exists_pow_eq hx' (mem_support.mp hz)
have h'' : ∀ x ∈ f.support ∩ g.support, f x = g x := by
intro x hx
exact h' x (mem_of_mem_inter_left hx)
rwa [← hm, ←
pow_eq_on_of_mem_support h'' _ x
(mem_inter_of_mem (mem_support.mpr hx) (mem_support.mpr hx')),
pow_apply_mem_support, mem_support]
refine Equiv.Perm.support_congr h ?_
simpa [← this] using h'
#align equiv.perm.is_cycle.support_congr Equiv.Perm.IsCycle.support_congr
/-- If two cyclic permutations agree on all terms in their intersection,
and that intersection is not empty, then the two cyclic permutations must be equal. -/
theorem IsCycle.eq_on_support_inter_nonempty_congr (hf : IsCycle f) (hg : IsCycle g)
(h : ∀ x ∈ f.support ∩ g.support, f x = g x)
(hx : f x = g x) (hx' : x ∈ f.support) : f = g := by
have hx'' : x ∈ g.support := by rwa [mem_support, ← hx, ← mem_support]
have : f.support ⊆ g.support := by
intro y hy
obtain ⟨k, rfl⟩ := hf.exists_pow_eq (mem_support.mp hx') (mem_support.mp hy)
rwa [pow_eq_on_of_mem_support h _ _ (mem_inter_of_mem hx' hx''), pow_apply_mem_support]
rw [inter_eq_left.mpr this] at h
exact hf.support_congr hg this h
#align equiv.perm.is_cycle.eq_on_support_inter_nonempty_congr Equiv.Perm.IsCycle.eq_on_support_inter_nonempty_congr
theorem IsCycle.support_pow_eq_iff (hf : IsCycle f) {n : ℕ} :
support (f ^ n) = support f ↔ ¬orderOf f ∣ n := by
rw [orderOf_dvd_iff_pow_eq_one]
constructor
· intro h H
refine hf.ne_one ?_
rw [← support_eq_empty_iff, ← h, H, support_one]
· intro H
apply le_antisymm (support_pow_le _ n) _
intro x hx
contrapose! H
ext z
by_cases hz : f z = z
· rw [pow_apply_eq_self_of_apply_eq_self hz, one_apply]
· obtain ⟨k, rfl⟩ := hf.exists_pow_eq hz (mem_support.mp hx)
apply (f ^ k).injective
rw [← mul_apply, (Commute.pow_pow_self _ _ _).eq, mul_apply]
simpa using H
#align equiv.perm.is_cycle.support_pow_eq_iff Equiv.Perm.IsCycle.support_pow_eq_iff
theorem IsCycle.support_pow_of_pos_of_lt_orderOf (hf : IsCycle f) {n : ℕ} (npos : 0 < n)
(hn : n < orderOf f) : (f ^ n).support = f.support :=
hf.support_pow_eq_iff.2 <| Nat.not_dvd_of_pos_of_lt npos hn
#align equiv.perm.is_cycle.support_pow_of_pos_of_lt_order_of Equiv.Perm.IsCycle.support_pow_of_pos_of_lt_orderOf
theorem IsCycle.pow_iff [Finite β] {f : Perm β} (hf : IsCycle f) {n : ℕ} :
IsCycle (f ^ n) ↔ n.Coprime (orderOf f) := by
classical
cases nonempty_fintype β
constructor
· intro h
have hr : support (f ^ n) = support f := by
rw [hf.support_pow_eq_iff]
rintro ⟨k, rfl⟩
refine h.ne_one ?_
simp [pow_mul, pow_orderOf_eq_one]
have : orderOf (f ^ n) = orderOf f := by rw [h.orderOf, hr, hf.orderOf]
rw [orderOf_pow, Nat.div_eq_self] at this
cases' this with h
· exact absurd h (orderOf_pos _).ne'
· rwa [Nat.coprime_iff_gcd_eq_one, Nat.gcd_comm]
· intro h
obtain ⟨m, hm⟩ := exists_pow_eq_self_of_coprime h
have hf' : IsCycle ((f ^ n) ^ m) := by rwa [hm]
refine hf'.of_pow fun x hx => ?_
rw [hm]
exact support_pow_le _ n hx
#align equiv.perm.is_cycle.pow_iff Equiv.Perm.IsCycle.pow_iff
-- TODO: Define a `Set`-valued support to get rid of the `Finite β` assumption
theorem IsCycle.pow_eq_one_iff [Finite β] {f : Perm β} (hf : IsCycle f) {n : ℕ} :
f ^ n = 1 ↔ ∃ x, f x ≠ x ∧ (f ^ n) x = x := by
classical
cases nonempty_fintype β
constructor
· intro h
obtain ⟨x, hx, -⟩ := id hf
exact ⟨x, hx, by simp [h]⟩
· rintro ⟨x, hx, hx'⟩
by_cases h : support (f ^ n) = support f
· rw [← mem_support, ← h, mem_support] at hx
contradiction
· rw [hf.support_pow_eq_iff, Classical.not_not] at h
obtain ⟨k, rfl⟩ := h
rw [pow_mul, pow_orderOf_eq_one, one_pow]
#align equiv.perm.is_cycle.pow_eq_one_iff Equiv.Perm.IsCycle.pow_eq_one_iff
-- TODO: Define a `Set`-valued support to get rid of the `Finite β` assumption
theorem IsCycle.pow_eq_one_iff' [Finite β] {f : Perm β} (hf : IsCycle f) {n : ℕ} {x : β}
(hx : f x ≠ x) : f ^ n = 1 ↔ (f ^ n) x = x :=
⟨fun h => DFunLike.congr_fun h x, fun h => hf.pow_eq_one_iff.2 ⟨x, hx, h⟩⟩
#align equiv.perm.is_cycle.pow_eq_one_iff' Equiv.Perm.IsCycle.pow_eq_one_iff'
-- TODO: Define a `Set`-valued support to get rid of the `Finite β` assumption
theorem IsCycle.pow_eq_one_iff'' [Finite β] {f : Perm β} (hf : IsCycle f) {n : ℕ} :
f ^ n = 1 ↔ ∀ x, f x ≠ x → (f ^ n) x = x :=
⟨fun h _ hx => (hf.pow_eq_one_iff' hx).1 h, fun h =>
let ⟨_, hx, _⟩ := id hf
(hf.pow_eq_one_iff' hx).2 (h _ hx)⟩
#align equiv.perm.is_cycle.pow_eq_one_iff'' Equiv.Perm.IsCycle.pow_eq_one_iff''
-- TODO: Define a `Set`-valued support to get rid of the `Finite β` assumption
theorem IsCycle.pow_eq_pow_iff [Finite β] {f : Perm β} (hf : IsCycle f) {a b : ℕ} :
f ^ a = f ^ b ↔ ∃ x, f x ≠ x ∧ (f ^ a) x = (f ^ b) x := by
classical
cases nonempty_fintype β
constructor
· intro h
obtain ⟨x, hx, -⟩ := id hf
exact ⟨x, hx, by simp [h]⟩
· rintro ⟨x, hx, hx'⟩
wlog hab : a ≤ b generalizing a b
· exact (this hx'.symm (le_of_not_le hab)).symm
suffices f ^ (b - a) = 1 by
rw [pow_sub _ hab, mul_inv_eq_one] at this
rw [this]
rw [hf.pow_eq_one_iff]
by_cases hfa : (f ^ a) x ∈ f.support
· refine ⟨(f ^ a) x, mem_support.mp hfa, ?_⟩
simp only [pow_sub _ hab, Equiv.Perm.coe_mul, Function.comp_apply, inv_apply_self, ← hx']
· have h := @Equiv.Perm.zpow_apply_comm _ f 1 a x
simp only [zpow_one, zpow_natCast] at h
rw [not_mem_support, h, Function.Injective.eq_iff (f ^ a).injective] at hfa
contradiction
#align equiv.perm.is_cycle.pow_eq_pow_iff Equiv.Perm.IsCycle.pow_eq_pow_iff
theorem IsCycle.isCycle_pow_pos_of_lt_prime_order [Finite β] {f : Perm β} (hf : IsCycle f)
(hf' : (orderOf f).Prime) (n : ℕ) (hn : 0 < n) (hn' : n < orderOf f) : IsCycle (f ^ n) := by
classical
cases nonempty_fintype β
have : n.Coprime (orderOf f) := by
refine Nat.Coprime.symm ?_
rw [Nat.Prime.coprime_iff_not_dvd hf']
exact Nat.not_dvd_of_pos_of_lt hn hn'
obtain ⟨m, hm⟩ := exists_pow_eq_self_of_coprime this
have hf'' := hf
rw [← hm] at hf''
refine hf''.of_pow ?_
rw [hm]
exact support_pow_le f n
#align equiv.perm.is_cycle.is_cycle_pow_pos_of_lt_prime_order Equiv.Perm.IsCycle.isCycle_pow_pos_of_lt_prime_order
end IsCycle
open Equiv
theorem _root_.Int.addLeft_one_isCycle : (Equiv.addLeft 1 : Perm ℤ).IsCycle :=
⟨0, one_ne_zero, fun n _ => ⟨n, by simp⟩⟩
#align int.add_left_one_is_cycle Int.addLeft_one_isCycle
theorem _root_.Int.addRight_one_isCycle : (Equiv.addRight 1 : Perm ℤ).IsCycle :=
⟨0, one_ne_zero, fun n _ => ⟨n, by simp⟩⟩
#align int.add_right_one_is_cycle Int.addRight_one_isCycle
section Conjugation
variable [Fintype α] [DecidableEq α] {σ τ : Perm α}
theorem IsCycle.isConj (hσ : IsCycle σ) (hτ : IsCycle τ) (h : σ.support.card = τ.support.card) :
IsConj σ τ := by
refine
isConj_of_support_equiv
(hσ.zpowersEquivSupport.symm.trans <|
(zpowersEquivZPowers <| by rw [hσ.orderOf, h, hτ.orderOf]).trans hτ.zpowersEquivSupport)
?_
intro x hx
simp only [Perm.mul_apply, Equiv.trans_apply, Equiv.sumCongr_apply]
obtain ⟨n, rfl⟩ := hσ.exists_pow_eq (Classical.choose_spec hσ).1 (mem_support.1 hx)
erw [hσ.zpowersEquivSupport_symm_apply n]
simp only [← Perm.mul_apply, ← pow_succ']
erw [hσ.zpowersEquivSupport_symm_apply (n + 1)]
-- This used to be a `simp only` before leanprover/lean4#2644
erw [zpowersEquivZPowers_apply, zpowersEquivZPowers_apply, zpowersEquivSupport_apply]
-- This used to be `rw`, but we need `erw` after leanprover/lean4#2644
simp_rw [pow_succ', Perm.mul_apply]
rfl
#align equiv.perm.is_cycle.is_conj Equiv.Perm.IsCycle.isConj
| Mathlib/GroupTheory/Perm/Cycle/Basic.lean | 745 | 755 | theorem IsCycle.isConj_iff (hσ : IsCycle σ) (hτ : IsCycle τ) :
IsConj σ τ ↔ σ.support.card = τ.support.card where
mp h := by |
obtain ⟨π, rfl⟩ := (_root_.isConj_iff).1 h
refine Finset.card_bij (fun a _ => π a) (fun _ ha => ?_) (fun _ _ _ _ ab => π.injective ab)
fun b hb ↦ ⟨π⁻¹ b, ?_, π.apply_inv_self b⟩
· simp [mem_support.1 ha]
contrapose! hb
rw [mem_support, Classical.not_not] at hb
rw [mem_support, Classical.not_not, Perm.mul_apply, Perm.mul_apply, hb, Perm.apply_inv_self]
mpr := hσ.isConj hτ
|
/-
Copyright (c) 2020 Yury Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Alexander Bentkamp, Yury Kudryashov
-/
import Mathlib.Analysis.Convex.Combination
import Mathlib.Analysis.Convex.Strict
import Mathlib.Topology.Connected.PathConnected
import Mathlib.Topology.Algebra.Affine
import Mathlib.Topology.Algebra.Module.Basic
#align_import analysis.convex.topology from "leanprover-community/mathlib"@"0e3aacdc98d25e0afe035c452d876d28cbffaa7e"
/-!
# Topological properties of convex sets
We prove the following facts:
* `Convex.interior` : interior of a convex set is convex;
* `Convex.closure` : closure of a convex set is convex;
* `Set.Finite.isCompact_convexHull` : convex hull of a finite set is compact;
* `Set.Finite.isClosed_convexHull` : convex hull of a finite set is closed.
-/
assert_not_exists Norm
open Metric Bornology Set Pointwise Convex
variable {ι 𝕜 E : Type*}
theorem Real.convex_iff_isPreconnected {s : Set ℝ} : Convex ℝ s ↔ IsPreconnected s :=
convex_iff_ordConnected.trans isPreconnected_iff_ordConnected.symm
#align real.convex_iff_is_preconnected Real.convex_iff_isPreconnected
alias ⟨_, IsPreconnected.convex⟩ := Real.convex_iff_isPreconnected
#align is_preconnected.convex IsPreconnected.convex
/-! ### Standard simplex -/
section stdSimplex
variable [Fintype ι]
/-- Every vector in `stdSimplex 𝕜 ι` has `max`-norm at most `1`. -/
theorem stdSimplex_subset_closedBall : stdSimplex ℝ ι ⊆ Metric.closedBall 0 1 := fun f hf ↦ by
rw [Metric.mem_closedBall, dist_pi_le_iff zero_le_one]
intro x
rw [Pi.zero_apply, Real.dist_0_eq_abs, abs_of_nonneg <| hf.1 x]
exact (mem_Icc_of_mem_stdSimplex hf x).2
#align std_simplex_subset_closed_ball stdSimplex_subset_closedBall
variable (ι)
/-- `stdSimplex ℝ ι` is bounded. -/
theorem bounded_stdSimplex : IsBounded (stdSimplex ℝ ι) :=
(Metric.isBounded_iff_subset_closedBall 0).2 ⟨1, stdSimplex_subset_closedBall⟩
#align bounded_std_simplex bounded_stdSimplex
/-- `stdSimplex ℝ ι` is closed. -/
theorem isClosed_stdSimplex : IsClosed (stdSimplex ℝ ι) :=
(stdSimplex_eq_inter ℝ ι).symm ▸
IsClosed.inter (isClosed_iInter fun i => isClosed_le continuous_const (continuous_apply i))
(isClosed_eq (continuous_finset_sum _ fun x _ => continuous_apply x) continuous_const)
#align is_closed_std_simplex isClosed_stdSimplex
/-- `stdSimplex ℝ ι` is compact. -/
theorem isCompact_stdSimplex : IsCompact (stdSimplex ℝ ι) :=
Metric.isCompact_iff_isClosed_bounded.2 ⟨isClosed_stdSimplex ι, bounded_stdSimplex ι⟩
#align is_compact_std_simplex isCompact_stdSimplex
instance stdSimplex.instCompactSpace_coe : CompactSpace ↥(stdSimplex ℝ ι) :=
isCompact_iff_compactSpace.mp <| isCompact_stdSimplex _
/-- The standard one-dimensional simplex in `ℝ² = Fin 2 → ℝ`
is homeomorphic to the unit interval. -/
@[simps! (config := .asFn)]
def stdSimplexHomeomorphUnitInterval : stdSimplex ℝ (Fin 2) ≃ₜ unitInterval where
toEquiv := stdSimplexEquivIcc ℝ
continuous_toFun := .subtype_mk ((continuous_apply 0).comp continuous_subtype_val) _
continuous_invFun := by
apply Continuous.subtype_mk
exact (continuous_pi <| Fin.forall_fin_two.2
⟨continuous_subtype_val, continuous_const.sub continuous_subtype_val⟩)
end stdSimplex
/-! ### Topological vector spaces -/
section TopologicalSpace
variable [LinearOrderedRing 𝕜] [DenselyOrdered 𝕜] [TopologicalSpace 𝕜] [OrderTopology 𝕜]
[AddCommGroup E] [TopologicalSpace E] [ContinuousAdd E] [Module 𝕜 E] [ContinuousSMul 𝕜 E]
{x y : E}
theorem segment_subset_closure_openSegment : [x -[𝕜] y] ⊆ closure (openSegment 𝕜 x y) := by
rw [segment_eq_image, openSegment_eq_image, ← closure_Ioo (zero_ne_one' 𝕜)]
exact image_closure_subset_closure_image (by continuity)
#align segment_subset_closure_open_segment segment_subset_closure_openSegment
end TopologicalSpace
section PseudoMetricSpace
variable [LinearOrderedRing 𝕜] [DenselyOrdered 𝕜] [PseudoMetricSpace 𝕜] [OrderTopology 𝕜]
[ProperSpace 𝕜] [CompactIccSpace 𝕜] [AddCommGroup E] [TopologicalSpace E] [T2Space E]
[ContinuousAdd E] [Module 𝕜 E] [ContinuousSMul 𝕜 E]
@[simp]
theorem closure_openSegment (x y : E) : closure (openSegment 𝕜 x y) = [x -[𝕜] y] := by
rw [segment_eq_image, openSegment_eq_image, ← closure_Ioo (zero_ne_one' 𝕜)]
exact (image_closure_of_isCompact (isBounded_Ioo _ _).isCompact_closure <|
Continuous.continuousOn <| by continuity).symm
#align closure_open_segment closure_openSegment
end PseudoMetricSpace
section ContinuousConstSMul
variable [LinearOrderedField 𝕜] [AddCommGroup E] [Module 𝕜 E] [TopologicalSpace E]
[TopologicalAddGroup E] [ContinuousConstSMul 𝕜 E]
/-- If `s` is a convex set, then `a • interior s + b • closure s ⊆ interior s` for all `0 < a`,
`0 ≤ b`, `a + b = 1`. See also `Convex.combo_interior_self_subset_interior` for a weaker version. -/
theorem Convex.combo_interior_closure_subset_interior {s : Set E} (hs : Convex 𝕜 s) {a b : 𝕜}
(ha : 0 < a) (hb : 0 ≤ b) (hab : a + b = 1) : a • interior s + b • closure s ⊆ interior s :=
interior_smul₀ ha.ne' s ▸
calc
interior (a • s) + b • closure s ⊆ interior (a • s) + closure (b • s) :=
add_subset_add Subset.rfl (smul_closure_subset b s)
_ = interior (a • s) + b • s := by rw [isOpen_interior.add_closure (b • s)]
_ ⊆ interior (a • s + b • s) := subset_interior_add_left
_ ⊆ interior s := interior_mono <| hs.set_combo_subset ha.le hb hab
#align convex.combo_interior_closure_subset_interior Convex.combo_interior_closure_subset_interior
/-- If `s` is a convex set, then `a • interior s + b • s ⊆ interior s` for all `0 < a`, `0 ≤ b`,
`a + b = 1`. See also `Convex.combo_interior_closure_subset_interior` for a stronger version. -/
theorem Convex.combo_interior_self_subset_interior {s : Set E} (hs : Convex 𝕜 s) {a b : 𝕜}
(ha : 0 < a) (hb : 0 ≤ b) (hab : a + b = 1) : a • interior s + b • s ⊆ interior s :=
calc
a • interior s + b • s ⊆ a • interior s + b • closure s :=
add_subset_add Subset.rfl <| image_subset _ subset_closure
_ ⊆ interior s := hs.combo_interior_closure_subset_interior ha hb hab
#align convex.combo_interior_self_subset_interior Convex.combo_interior_self_subset_interior
/-- If `s` is a convex set, then `a • closure s + b • interior s ⊆ interior s` for all `0 ≤ a`,
`0 < b`, `a + b = 1`. See also `Convex.combo_self_interior_subset_interior` for a weaker version. -/
theorem Convex.combo_closure_interior_subset_interior {s : Set E} (hs : Convex 𝕜 s) {a b : 𝕜}
(ha : 0 ≤ a) (hb : 0 < b) (hab : a + b = 1) : a • closure s + b • interior s ⊆ interior s := by
rw [add_comm]
exact hs.combo_interior_closure_subset_interior hb ha (add_comm a b ▸ hab)
#align convex.combo_closure_interior_subset_interior Convex.combo_closure_interior_subset_interior
/-- If `s` is a convex set, then `a • s + b • interior s ⊆ interior s` for all `0 ≤ a`, `0 < b`,
`a + b = 1`. See also `Convex.combo_closure_interior_subset_interior` for a stronger version. -/
theorem Convex.combo_self_interior_subset_interior {s : Set E} (hs : Convex 𝕜 s) {a b : 𝕜}
(ha : 0 ≤ a) (hb : 0 < b) (hab : a + b = 1) : a • s + b • interior s ⊆ interior s := by
rw [add_comm]
exact hs.combo_interior_self_subset_interior hb ha (add_comm a b ▸ hab)
#align convex.combo_self_interior_subset_interior Convex.combo_self_interior_subset_interior
theorem Convex.combo_interior_closure_mem_interior {s : Set E} (hs : Convex 𝕜 s) {x y : E}
(hx : x ∈ interior s) (hy : y ∈ closure s) {a b : 𝕜} (ha : 0 < a) (hb : 0 ≤ b)
(hab : a + b = 1) : a • x + b • y ∈ interior s :=
hs.combo_interior_closure_subset_interior ha hb hab <|
add_mem_add (smul_mem_smul_set hx) (smul_mem_smul_set hy)
#align convex.combo_interior_closure_mem_interior Convex.combo_interior_closure_mem_interior
theorem Convex.combo_interior_self_mem_interior {s : Set E} (hs : Convex 𝕜 s) {x y : E}
(hx : x ∈ interior s) (hy : y ∈ s) {a b : 𝕜} (ha : 0 < a) (hb : 0 ≤ b) (hab : a + b = 1) :
a • x + b • y ∈ interior s :=
hs.combo_interior_closure_mem_interior hx (subset_closure hy) ha hb hab
#align convex.combo_interior_self_mem_interior Convex.combo_interior_self_mem_interior
theorem Convex.combo_closure_interior_mem_interior {s : Set E} (hs : Convex 𝕜 s) {x y : E}
(hx : x ∈ closure s) (hy : y ∈ interior s) {a b : 𝕜} (ha : 0 ≤ a) (hb : 0 < b)
(hab : a + b = 1) : a • x + b • y ∈ interior s :=
hs.combo_closure_interior_subset_interior ha hb hab <|
add_mem_add (smul_mem_smul_set hx) (smul_mem_smul_set hy)
#align convex.combo_closure_interior_mem_interior Convex.combo_closure_interior_mem_interior
theorem Convex.combo_self_interior_mem_interior {s : Set E} (hs : Convex 𝕜 s) {x y : E} (hx : x ∈ s)
(hy : y ∈ interior s) {a b : 𝕜} (ha : 0 ≤ a) (hb : 0 < b) (hab : a + b = 1) :
a • x + b • y ∈ interior s :=
hs.combo_closure_interior_mem_interior (subset_closure hx) hy ha hb hab
#align convex.combo_self_interior_mem_interior Convex.combo_self_interior_mem_interior
theorem Convex.openSegment_interior_closure_subset_interior {s : Set E} (hs : Convex 𝕜 s) {x y : E}
(hx : x ∈ interior s) (hy : y ∈ closure s) : openSegment 𝕜 x y ⊆ interior s := by
rintro _ ⟨a, b, ha, hb, hab, rfl⟩
exact hs.combo_interior_closure_mem_interior hx hy ha hb.le hab
#align convex.open_segment_interior_closure_subset_interior Convex.openSegment_interior_closure_subset_interior
theorem Convex.openSegment_interior_self_subset_interior {s : Set E} (hs : Convex 𝕜 s) {x y : E}
(hx : x ∈ interior s) (hy : y ∈ s) : openSegment 𝕜 x y ⊆ interior s :=
hs.openSegment_interior_closure_subset_interior hx (subset_closure hy)
#align convex.open_segment_interior_self_subset_interior Convex.openSegment_interior_self_subset_interior
| Mathlib/Analysis/Convex/Topology.lean | 200 | 203 | theorem Convex.openSegment_closure_interior_subset_interior {s : Set E} (hs : Convex 𝕜 s) {x y : E}
(hx : x ∈ closure s) (hy : y ∈ interior s) : openSegment 𝕜 x y ⊆ interior s := by |
rintro _ ⟨a, b, ha, hb, hab, rfl⟩
exact hs.combo_closure_interior_mem_interior hx hy ha.le hb hab
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Jeremy Avigad
-/
import Mathlib.Algebra.Order.Ring.Defs
import Mathlib.Data.Set.Finite
#align_import order.filter.basic from "leanprover-community/mathlib"@"d4f691b9e5f94cfc64639973f3544c95f8d5d494"
/-!
# Theory of filters on sets
## Main definitions
* `Filter` : filters on a set;
* `Filter.principal` : filter of all sets containing a given set;
* `Filter.map`, `Filter.comap` : operations on filters;
* `Filter.Tendsto` : limit with respect to filters;
* `Filter.Eventually` : `f.eventually p` means `{x | p x} ∈ f`;
* `Filter.Frequently` : `f.frequently p` means `{x | ¬p x} ∉ f`;
* `filter_upwards [h₁, ..., hₙ]` :
a tactic that takes a list of proofs `hᵢ : sᵢ ∈ f`,
and replaces a goal `s ∈ f` with `∀ x, x ∈ s₁ → ... → x ∈ sₙ → x ∈ s`;
* `Filter.NeBot f` : a utility class stating that `f` is a non-trivial filter.
Filters on a type `X` are sets of sets of `X` satisfying three conditions. They are mostly used to
abstract two related kinds of ideas:
* *limits*, including finite or infinite limits of sequences, finite or infinite limits of functions
at a point or at infinity, etc...
* *things happening eventually*, including things happening for large enough `n : ℕ`, or near enough
a point `x`, or for close enough pairs of points, or things happening almost everywhere in the
sense of measure theory. Dually, filters can also express the idea of *things happening often*:
for arbitrarily large `n`, or at a point in any neighborhood of given a point etc...
In this file, we define the type `Filter X` of filters on `X`, and endow it with a complete lattice
structure. This structure is lifted from the lattice structure on `Set (Set X)` using the Galois
insertion which maps a filter to its elements in one direction, and an arbitrary set of sets to
the smallest filter containing it in the other direction.
We also prove `Filter` is a monadic functor, with a push-forward operation
`Filter.map` and a pull-back operation `Filter.comap` that form a Galois connections for the
order on filters.
The examples of filters appearing in the description of the two motivating ideas are:
* `(Filter.atTop : Filter ℕ)` : made of sets of `ℕ` containing `{n | n ≥ N}` for some `N`
* `𝓝 x` : made of neighborhoods of `x` in a topological space (defined in topology.basic)
* `𝓤 X` : made of entourages of a uniform space (those space are generalizations of metric spaces
defined in `Mathlib/Topology/UniformSpace/Basic.lean`)
* `MeasureTheory.ae` : made of sets whose complement has zero measure with respect to `μ`
(defined in `Mathlib/MeasureTheory/OuterMeasure/AE`)
The general notion of limit of a map with respect to filters on the source and target types
is `Filter.Tendsto`. It is defined in terms of the order and the push-forward operation.
The predicate "happening eventually" is `Filter.Eventually`, and "happening often" is
`Filter.Frequently`, whose definitions are immediate after `Filter` is defined (but they come
rather late in this file in order to immediately relate them to the lattice structure).
For instance, anticipating on Topology.Basic, the statement: "if a sequence `u` converges to
some `x` and `u n` belongs to a set `M` for `n` large enough then `x` is in the closure of
`M`" is formalized as: `Tendsto u atTop (𝓝 x) → (∀ᶠ n in atTop, u n ∈ M) → x ∈ closure M`,
which is a special case of `mem_closure_of_tendsto` from Topology.Basic.
## Notations
* `∀ᶠ x in f, p x` : `f.Eventually p`;
* `∃ᶠ x in f, p x` : `f.Frequently p`;
* `f =ᶠ[l] g` : `∀ᶠ x in l, f x = g x`;
* `f ≤ᶠ[l] g` : `∀ᶠ x in l, f x ≤ g x`;
* `𝓟 s` : `Filter.Principal s`, localized in `Filter`.
## References
* [N. Bourbaki, *General Topology*][bourbaki1966]
Important note: Bourbaki requires that a filter on `X` cannot contain all sets of `X`, which
we do *not* require. This gives `Filter X` better formal properties, in particular a bottom element
`⊥` for its lattice structure, at the cost of including the assumption
`[NeBot f]` in a number of lemmas and definitions.
-/
set_option autoImplicit true
open Function Set Order
open scoped Classical
universe u v w x y
/-- A filter `F` on a type `α` is a collection of sets of `α` which contains the whole `α`,
is upwards-closed, and is stable under intersection. We do not forbid this collection to be
all sets of `α`. -/
structure Filter (α : Type*) where
/-- The set of sets that belong to the filter. -/
sets : Set (Set α)
/-- The set `Set.univ` belongs to any filter. -/
univ_sets : Set.univ ∈ sets
/-- If a set belongs to a filter, then its superset belongs to the filter as well. -/
sets_of_superset {x y} : x ∈ sets → x ⊆ y → y ∈ sets
/-- If two sets belong to a filter, then their intersection belongs to the filter as well. -/
inter_sets {x y} : x ∈ sets → y ∈ sets → x ∩ y ∈ sets
#align filter Filter
/-- If `F` is a filter on `α`, and `U` a subset of `α` then we can write `U ∈ F` as on paper. -/
instance {α : Type*} : Membership (Set α) (Filter α) :=
⟨fun U F => U ∈ F.sets⟩
namespace Filter
variable {α : Type u} {f g : Filter α} {s t : Set α}
@[simp]
protected theorem mem_mk {t : Set (Set α)} {h₁ h₂ h₃} : s ∈ mk t h₁ h₂ h₃ ↔ s ∈ t :=
Iff.rfl
#align filter.mem_mk Filter.mem_mk
@[simp]
protected theorem mem_sets : s ∈ f.sets ↔ s ∈ f :=
Iff.rfl
#align filter.mem_sets Filter.mem_sets
instance inhabitedMem : Inhabited { s : Set α // s ∈ f } :=
⟨⟨univ, f.univ_sets⟩⟩
#align filter.inhabited_mem Filter.inhabitedMem
theorem filter_eq : ∀ {f g : Filter α}, f.sets = g.sets → f = g
| ⟨_, _, _, _⟩, ⟨_, _, _, _⟩, rfl => rfl
#align filter.filter_eq Filter.filter_eq
theorem filter_eq_iff : f = g ↔ f.sets = g.sets :=
⟨congr_arg _, filter_eq⟩
#align filter.filter_eq_iff Filter.filter_eq_iff
protected theorem ext_iff : f = g ↔ ∀ s, s ∈ f ↔ s ∈ g := by
simp only [filter_eq_iff, ext_iff, Filter.mem_sets]
#align filter.ext_iff Filter.ext_iff
@[ext]
protected theorem ext : (∀ s, s ∈ f ↔ s ∈ g) → f = g :=
Filter.ext_iff.2
#align filter.ext Filter.ext
/-- An extensionality lemma that is useful for filters with good lemmas about `sᶜ ∈ f` (e.g.,
`Filter.comap`, `Filter.coprod`, `Filter.Coprod`, `Filter.cofinite`). -/
protected theorem coext (h : ∀ s, sᶜ ∈ f ↔ sᶜ ∈ g) : f = g :=
Filter.ext <| compl_surjective.forall.2 h
#align filter.coext Filter.coext
@[simp]
theorem univ_mem : univ ∈ f :=
f.univ_sets
#align filter.univ_mem Filter.univ_mem
theorem mem_of_superset {x y : Set α} (hx : x ∈ f) (hxy : x ⊆ y) : y ∈ f :=
f.sets_of_superset hx hxy
#align filter.mem_of_superset Filter.mem_of_superset
instance : Trans (· ⊇ ·) ((· ∈ ·) : Set α → Filter α → Prop) (· ∈ ·) where
trans h₁ h₂ := mem_of_superset h₂ h₁
theorem inter_mem {s t : Set α} (hs : s ∈ f) (ht : t ∈ f) : s ∩ t ∈ f :=
f.inter_sets hs ht
#align filter.inter_mem Filter.inter_mem
@[simp]
theorem inter_mem_iff {s t : Set α} : s ∩ t ∈ f ↔ s ∈ f ∧ t ∈ f :=
⟨fun h => ⟨mem_of_superset h inter_subset_left, mem_of_superset h inter_subset_right⟩,
and_imp.2 inter_mem⟩
#align filter.inter_mem_iff Filter.inter_mem_iff
theorem diff_mem {s t : Set α} (hs : s ∈ f) (ht : tᶜ ∈ f) : s \ t ∈ f :=
inter_mem hs ht
#align filter.diff_mem Filter.diff_mem
theorem univ_mem' (h : ∀ a, a ∈ s) : s ∈ f :=
mem_of_superset univ_mem fun x _ => h x
#align filter.univ_mem' Filter.univ_mem'
theorem mp_mem (hs : s ∈ f) (h : { x | x ∈ s → x ∈ t } ∈ f) : t ∈ f :=
mem_of_superset (inter_mem hs h) fun _ ⟨h₁, h₂⟩ => h₂ h₁
#align filter.mp_mem Filter.mp_mem
theorem congr_sets (h : { x | x ∈ s ↔ x ∈ t } ∈ f) : s ∈ f ↔ t ∈ f :=
⟨fun hs => mp_mem hs (mem_of_superset h fun _ => Iff.mp), fun hs =>
mp_mem hs (mem_of_superset h fun _ => Iff.mpr)⟩
#align filter.congr_sets Filter.congr_sets
/-- Override `sets` field of a filter to provide better definitional equality. -/
protected def copy (f : Filter α) (S : Set (Set α)) (hmem : ∀ s, s ∈ S ↔ s ∈ f) : Filter α where
sets := S
univ_sets := (hmem _).2 univ_mem
sets_of_superset h hsub := (hmem _).2 <| mem_of_superset ((hmem _).1 h) hsub
inter_sets h₁ h₂ := (hmem _).2 <| inter_mem ((hmem _).1 h₁) ((hmem _).1 h₂)
lemma copy_eq {S} (hmem : ∀ s, s ∈ S ↔ s ∈ f) : f.copy S hmem = f := Filter.ext hmem
@[simp] lemma mem_copy {S hmem} : s ∈ f.copy S hmem ↔ s ∈ S := Iff.rfl
@[simp]
theorem biInter_mem {β : Type v} {s : β → Set α} {is : Set β} (hf : is.Finite) :
(⋂ i ∈ is, s i) ∈ f ↔ ∀ i ∈ is, s i ∈ f :=
Finite.induction_on hf (by simp) fun _ _ hs => by simp [hs]
#align filter.bInter_mem Filter.biInter_mem
@[simp]
theorem biInter_finset_mem {β : Type v} {s : β → Set α} (is : Finset β) :
(⋂ i ∈ is, s i) ∈ f ↔ ∀ i ∈ is, s i ∈ f :=
biInter_mem is.finite_toSet
#align filter.bInter_finset_mem Filter.biInter_finset_mem
alias _root_.Finset.iInter_mem_sets := biInter_finset_mem
#align finset.Inter_mem_sets Finset.iInter_mem_sets
-- attribute [protected] Finset.iInter_mem_sets porting note: doesn't work
@[simp]
theorem sInter_mem {s : Set (Set α)} (hfin : s.Finite) : ⋂₀ s ∈ f ↔ ∀ U ∈ s, U ∈ f := by
rw [sInter_eq_biInter, biInter_mem hfin]
#align filter.sInter_mem Filter.sInter_mem
@[simp]
theorem iInter_mem {β : Sort v} {s : β → Set α} [Finite β] : (⋂ i, s i) ∈ f ↔ ∀ i, s i ∈ f :=
(sInter_mem (finite_range _)).trans forall_mem_range
#align filter.Inter_mem Filter.iInter_mem
theorem exists_mem_subset_iff : (∃ t ∈ f, t ⊆ s) ↔ s ∈ f :=
⟨fun ⟨_, ht, ts⟩ => mem_of_superset ht ts, fun hs => ⟨s, hs, Subset.rfl⟩⟩
#align filter.exists_mem_subset_iff Filter.exists_mem_subset_iff
theorem monotone_mem {f : Filter α} : Monotone fun s => s ∈ f := fun _ _ hst h =>
mem_of_superset h hst
#align filter.monotone_mem Filter.monotone_mem
theorem exists_mem_and_iff {P : Set α → Prop} {Q : Set α → Prop} (hP : Antitone P)
(hQ : Antitone Q) : ((∃ u ∈ f, P u) ∧ ∃ u ∈ f, Q u) ↔ ∃ u ∈ f, P u ∧ Q u := by
constructor
· rintro ⟨⟨u, huf, hPu⟩, v, hvf, hQv⟩
exact
⟨u ∩ v, inter_mem huf hvf, hP inter_subset_left hPu, hQ inter_subset_right hQv⟩
· rintro ⟨u, huf, hPu, hQu⟩
exact ⟨⟨u, huf, hPu⟩, u, huf, hQu⟩
#align filter.exists_mem_and_iff Filter.exists_mem_and_iff
theorem forall_in_swap {β : Type*} {p : Set α → β → Prop} :
(∀ a ∈ f, ∀ (b), p a b) ↔ ∀ (b), ∀ a ∈ f, p a b :=
Set.forall_in_swap
#align filter.forall_in_swap Filter.forall_in_swap
end Filter
namespace Mathlib.Tactic
open Lean Meta Elab Tactic
/--
`filter_upwards [h₁, ⋯, hₙ]` replaces a goal of the form `s ∈ f` and terms
`h₁ : t₁ ∈ f, ⋯, hₙ : tₙ ∈ f` with `∀ x, x ∈ t₁ → ⋯ → x ∈ tₙ → x ∈ s`.
The list is an optional parameter, `[]` being its default value.
`filter_upwards [h₁, ⋯, hₙ] with a₁ a₂ ⋯ aₖ` is a short form for
`{ filter_upwards [h₁, ⋯, hₙ], intros a₁ a₂ ⋯ aₖ }`.
`filter_upwards [h₁, ⋯, hₙ] using e` is a short form for
`{ filter_upwards [h1, ⋯, hn], exact e }`.
Combining both shortcuts is done by writing `filter_upwards [h₁, ⋯, hₙ] with a₁ a₂ ⋯ aₖ using e`.
Note that in this case, the `aᵢ` terms can be used in `e`.
-/
syntax (name := filterUpwards) "filter_upwards" (" [" term,* "]")?
(" with" (ppSpace colGt term:max)*)? (" using " term)? : tactic
elab_rules : tactic
| `(tactic| filter_upwards $[[$[$args],*]]? $[with $wth*]? $[using $usingArg]?) => do
let config : ApplyConfig := {newGoals := ApplyNewGoals.nonDependentOnly}
for e in args.getD #[] |>.reverse do
let goal ← getMainGoal
replaceMainGoal <| ← goal.withContext <| runTermElab do
let m ← mkFreshExprMVar none
let lem ← Term.elabTermEnsuringType
(← ``(Filter.mp_mem $e $(← Term.exprToSyntax m))) (← goal.getType)
goal.assign lem
return [m.mvarId!]
liftMetaTactic fun goal => do
goal.apply (← mkConstWithFreshMVarLevels ``Filter.univ_mem') config
evalTactic <|← `(tactic| dsimp (config := {zeta := false}) only [Set.mem_setOf_eq])
if let some l := wth then
evalTactic <|← `(tactic| intro $[$l]*)
if let some e := usingArg then
evalTactic <|← `(tactic| exact $e)
end Mathlib.Tactic
namespace Filter
variable {α : Type u} {β : Type v} {γ : Type w} {δ : Type*} {ι : Sort x}
section Principal
/-- The principal filter of `s` is the collection of all supersets of `s`. -/
def principal (s : Set α) : Filter α where
sets := { t | s ⊆ t }
univ_sets := subset_univ s
sets_of_superset hx := Subset.trans hx
inter_sets := subset_inter
#align filter.principal Filter.principal
@[inherit_doc]
scoped notation "𝓟" => Filter.principal
@[simp] theorem mem_principal {s t : Set α} : s ∈ 𝓟 t ↔ t ⊆ s := Iff.rfl
#align filter.mem_principal Filter.mem_principal
theorem mem_principal_self (s : Set α) : s ∈ 𝓟 s := Subset.rfl
#align filter.mem_principal_self Filter.mem_principal_self
end Principal
open Filter
section Join
/-- The join of a filter of filters is defined by the relation `s ∈ join f ↔ {t | s ∈ t} ∈ f`. -/
def join (f : Filter (Filter α)) : Filter α where
sets := { s | { t : Filter α | s ∈ t } ∈ f }
univ_sets := by simp only [mem_setOf_eq, univ_sets, ← Filter.mem_sets, setOf_true]
sets_of_superset hx xy := mem_of_superset hx fun f h => mem_of_superset h xy
inter_sets hx hy := mem_of_superset (inter_mem hx hy) fun f ⟨h₁, h₂⟩ => inter_mem h₁ h₂
#align filter.join Filter.join
@[simp]
theorem mem_join {s : Set α} {f : Filter (Filter α)} : s ∈ join f ↔ { t | s ∈ t } ∈ f :=
Iff.rfl
#align filter.mem_join Filter.mem_join
end Join
section Lattice
variable {f g : Filter α} {s t : Set α}
instance : PartialOrder (Filter α) where
le f g := ∀ ⦃U : Set α⦄, U ∈ g → U ∈ f
le_antisymm a b h₁ h₂ := filter_eq <| Subset.antisymm h₂ h₁
le_refl a := Subset.rfl
le_trans a b c h₁ h₂ := Subset.trans h₂ h₁
theorem le_def : f ≤ g ↔ ∀ x ∈ g, x ∈ f :=
Iff.rfl
#align filter.le_def Filter.le_def
protected theorem not_le : ¬f ≤ g ↔ ∃ s ∈ g, s ∉ f := by simp_rw [le_def, not_forall, exists_prop]
#align filter.not_le Filter.not_le
/-- `GenerateSets g s`: `s` is in the filter closure of `g`. -/
inductive GenerateSets (g : Set (Set α)) : Set α → Prop
| basic {s : Set α} : s ∈ g → GenerateSets g s
| univ : GenerateSets g univ
| superset {s t : Set α} : GenerateSets g s → s ⊆ t → GenerateSets g t
| inter {s t : Set α} : GenerateSets g s → GenerateSets g t → GenerateSets g (s ∩ t)
#align filter.generate_sets Filter.GenerateSets
/-- `generate g` is the largest filter containing the sets `g`. -/
def generate (g : Set (Set α)) : Filter α where
sets := {s | GenerateSets g s}
univ_sets := GenerateSets.univ
sets_of_superset := GenerateSets.superset
inter_sets := GenerateSets.inter
#align filter.generate Filter.generate
lemma mem_generate_of_mem {s : Set <| Set α} {U : Set α} (h : U ∈ s) :
U ∈ generate s := GenerateSets.basic h
theorem le_generate_iff {s : Set (Set α)} {f : Filter α} : f ≤ generate s ↔ s ⊆ f.sets :=
Iff.intro (fun h _ hu => h <| GenerateSets.basic <| hu) fun h _ hu =>
hu.recOn (fun h' => h h') univ_mem (fun _ hxy hx => mem_of_superset hx hxy) fun _ _ hx hy =>
inter_mem hx hy
#align filter.sets_iff_generate Filter.le_generate_iff
theorem mem_generate_iff {s : Set <| Set α} {U : Set α} :
U ∈ generate s ↔ ∃ t ⊆ s, Set.Finite t ∧ ⋂₀ t ⊆ U := by
constructor <;> intro h
· induction h with
| @basic V V_in =>
exact ⟨{V}, singleton_subset_iff.2 V_in, finite_singleton _, (sInter_singleton _).subset⟩
| univ => exact ⟨∅, empty_subset _, finite_empty, subset_univ _⟩
| superset _ hVW hV =>
rcases hV with ⟨t, hts, ht, htV⟩
exact ⟨t, hts, ht, htV.trans hVW⟩
| inter _ _ hV hW =>
rcases hV, hW with ⟨⟨t, hts, ht, htV⟩, u, hus, hu, huW⟩
exact
⟨t ∪ u, union_subset hts hus, ht.union hu,
(sInter_union _ _).subset.trans <| inter_subset_inter htV huW⟩
· rcases h with ⟨t, hts, tfin, h⟩
exact mem_of_superset ((sInter_mem tfin).2 fun V hV => GenerateSets.basic <| hts hV) h
#align filter.mem_generate_iff Filter.mem_generate_iff
@[simp] lemma generate_singleton (s : Set α) : generate {s} = 𝓟 s :=
le_antisymm (fun _t ht ↦ mem_of_superset (mem_generate_of_mem <| mem_singleton _) ht) <|
le_generate_iff.2 <| singleton_subset_iff.2 Subset.rfl
/-- `mkOfClosure s hs` constructs a filter on `α` whose elements set is exactly
`s : Set (Set α)`, provided one gives the assumption `hs : (generate s).sets = s`. -/
protected def mkOfClosure (s : Set (Set α)) (hs : (generate s).sets = s) : Filter α where
sets := s
univ_sets := hs ▸ univ_mem
sets_of_superset := hs ▸ mem_of_superset
inter_sets := hs ▸ inter_mem
#align filter.mk_of_closure Filter.mkOfClosure
theorem mkOfClosure_sets {s : Set (Set α)} {hs : (generate s).sets = s} :
Filter.mkOfClosure s hs = generate s :=
Filter.ext fun u =>
show u ∈ (Filter.mkOfClosure s hs).sets ↔ u ∈ (generate s).sets from hs.symm ▸ Iff.rfl
#align filter.mk_of_closure_sets Filter.mkOfClosure_sets
/-- Galois insertion from sets of sets into filters. -/
def giGenerate (α : Type*) :
@GaloisInsertion (Set (Set α)) (Filter α)ᵒᵈ _ _ Filter.generate Filter.sets where
gc _ _ := le_generate_iff
le_l_u _ _ h := GenerateSets.basic h
choice s hs := Filter.mkOfClosure s (le_antisymm hs <| le_generate_iff.1 <| le_rfl)
choice_eq _ _ := mkOfClosure_sets
#align filter.gi_generate Filter.giGenerate
/-- The infimum of filters is the filter generated by intersections
of elements of the two filters. -/
instance : Inf (Filter α) :=
⟨fun f g : Filter α =>
{ sets := { s | ∃ a ∈ f, ∃ b ∈ g, s = a ∩ b }
univ_sets := ⟨_, univ_mem, _, univ_mem, by simp⟩
sets_of_superset := by
rintro x y ⟨a, ha, b, hb, rfl⟩ xy
refine
⟨a ∪ y, mem_of_superset ha subset_union_left, b ∪ y,
mem_of_superset hb subset_union_left, ?_⟩
rw [← inter_union_distrib_right, union_eq_self_of_subset_left xy]
inter_sets := by
rintro x y ⟨a, ha, b, hb, rfl⟩ ⟨c, hc, d, hd, rfl⟩
refine ⟨a ∩ c, inter_mem ha hc, b ∩ d, inter_mem hb hd, ?_⟩
ac_rfl }⟩
theorem mem_inf_iff {f g : Filter α} {s : Set α} : s ∈ f ⊓ g ↔ ∃ t₁ ∈ f, ∃ t₂ ∈ g, s = t₁ ∩ t₂ :=
Iff.rfl
#align filter.mem_inf_iff Filter.mem_inf_iff
theorem mem_inf_of_left {f g : Filter α} {s : Set α} (h : s ∈ f) : s ∈ f ⊓ g :=
⟨s, h, univ, univ_mem, (inter_univ s).symm⟩
#align filter.mem_inf_of_left Filter.mem_inf_of_left
theorem mem_inf_of_right {f g : Filter α} {s : Set α} (h : s ∈ g) : s ∈ f ⊓ g :=
⟨univ, univ_mem, s, h, (univ_inter s).symm⟩
#align filter.mem_inf_of_right Filter.mem_inf_of_right
theorem inter_mem_inf {α : Type u} {f g : Filter α} {s t : Set α} (hs : s ∈ f) (ht : t ∈ g) :
s ∩ t ∈ f ⊓ g :=
⟨s, hs, t, ht, rfl⟩
#align filter.inter_mem_inf Filter.inter_mem_inf
theorem mem_inf_of_inter {f g : Filter α} {s t u : Set α} (hs : s ∈ f) (ht : t ∈ g)
(h : s ∩ t ⊆ u) : u ∈ f ⊓ g :=
mem_of_superset (inter_mem_inf hs ht) h
#align filter.mem_inf_of_inter Filter.mem_inf_of_inter
theorem mem_inf_iff_superset {f g : Filter α} {s : Set α} :
s ∈ f ⊓ g ↔ ∃ t₁ ∈ f, ∃ t₂ ∈ g, t₁ ∩ t₂ ⊆ s :=
⟨fun ⟨t₁, h₁, t₂, h₂, Eq⟩ => ⟨t₁, h₁, t₂, h₂, Eq ▸ Subset.rfl⟩, fun ⟨_, h₁, _, h₂, sub⟩ =>
mem_inf_of_inter h₁ h₂ sub⟩
#align filter.mem_inf_iff_superset Filter.mem_inf_iff_superset
instance : Top (Filter α) :=
⟨{ sets := { s | ∀ x, x ∈ s }
univ_sets := fun x => mem_univ x
sets_of_superset := fun hx hxy a => hxy (hx a)
inter_sets := fun hx hy _ => mem_inter (hx _) (hy _) }⟩
theorem mem_top_iff_forall {s : Set α} : s ∈ (⊤ : Filter α) ↔ ∀ x, x ∈ s :=
Iff.rfl
#align filter.mem_top_iff_forall Filter.mem_top_iff_forall
@[simp]
theorem mem_top {s : Set α} : s ∈ (⊤ : Filter α) ↔ s = univ := by
rw [mem_top_iff_forall, eq_univ_iff_forall]
#align filter.mem_top Filter.mem_top
section CompleteLattice
/- We lift the complete lattice along the Galois connection `generate` / `sets`. Unfortunately,
we want to have different definitional equalities for some lattice operations. So we define them
upfront and change the lattice operations for the complete lattice instance. -/
instance instCompleteLatticeFilter : CompleteLattice (Filter α) :=
{ @OrderDual.instCompleteLattice _ (giGenerate α).liftCompleteLattice with
le := (· ≤ ·)
top := ⊤
le_top := fun _ _s hs => (mem_top.1 hs).symm ▸ univ_mem
inf := (· ⊓ ·)
inf_le_left := fun _ _ _ => mem_inf_of_left
inf_le_right := fun _ _ _ => mem_inf_of_right
le_inf := fun _ _ _ h₁ h₂ _s ⟨_a, ha, _b, hb, hs⟩ => hs.symm ▸ inter_mem (h₁ ha) (h₂ hb)
sSup := join ∘ 𝓟
le_sSup := fun _ _f hf _s hs => hs hf
sSup_le := fun _ _f hf _s hs _g hg => hf _ hg hs }
instance : Inhabited (Filter α) := ⟨⊥⟩
end CompleteLattice
/-- A filter is `NeBot` if it is not equal to `⊥`, or equivalently the empty set does not belong to
the filter. Bourbaki include this assumption in the definition of a filter but we prefer to have a
`CompleteLattice` structure on `Filter _`, so we use a typeclass argument in lemmas instead. -/
class NeBot (f : Filter α) : Prop where
/-- The filter is nontrivial: `f ≠ ⊥` or equivalently, `∅ ∉ f`. -/
ne' : f ≠ ⊥
#align filter.ne_bot Filter.NeBot
theorem neBot_iff {f : Filter α} : NeBot f ↔ f ≠ ⊥ :=
⟨fun h => h.1, fun h => ⟨h⟩⟩
#align filter.ne_bot_iff Filter.neBot_iff
theorem NeBot.ne {f : Filter α} (hf : NeBot f) : f ≠ ⊥ := hf.ne'
#align filter.ne_bot.ne Filter.NeBot.ne
@[simp] theorem not_neBot {f : Filter α} : ¬f.NeBot ↔ f = ⊥ := neBot_iff.not_left
#align filter.not_ne_bot Filter.not_neBot
theorem NeBot.mono {f g : Filter α} (hf : NeBot f) (hg : f ≤ g) : NeBot g :=
⟨ne_bot_of_le_ne_bot hf.1 hg⟩
#align filter.ne_bot.mono Filter.NeBot.mono
theorem neBot_of_le {f g : Filter α} [hf : NeBot f] (hg : f ≤ g) : NeBot g :=
hf.mono hg
#align filter.ne_bot_of_le Filter.neBot_of_le
@[simp] theorem sup_neBot {f g : Filter α} : NeBot (f ⊔ g) ↔ NeBot f ∨ NeBot g := by
simp only [neBot_iff, not_and_or, Ne, sup_eq_bot_iff]
#align filter.sup_ne_bot Filter.sup_neBot
theorem not_disjoint_self_iff : ¬Disjoint f f ↔ f.NeBot := by rw [disjoint_self, neBot_iff]
#align filter.not_disjoint_self_iff Filter.not_disjoint_self_iff
theorem bot_sets_eq : (⊥ : Filter α).sets = univ := rfl
#align filter.bot_sets_eq Filter.bot_sets_eq
/-- Either `f = ⊥` or `Filter.NeBot f`. This is a version of `eq_or_ne` that uses `Filter.NeBot`
as the second alternative, to be used as an instance. -/
theorem eq_or_neBot (f : Filter α) : f = ⊥ ∨ NeBot f := (eq_or_ne f ⊥).imp_right NeBot.mk
theorem sup_sets_eq {f g : Filter α} : (f ⊔ g).sets = f.sets ∩ g.sets :=
(giGenerate α).gc.u_inf
#align filter.sup_sets_eq Filter.sup_sets_eq
theorem sSup_sets_eq {s : Set (Filter α)} : (sSup s).sets = ⋂ f ∈ s, (f : Filter α).sets :=
(giGenerate α).gc.u_sInf
#align filter.Sup_sets_eq Filter.sSup_sets_eq
theorem iSup_sets_eq {f : ι → Filter α} : (iSup f).sets = ⋂ i, (f i).sets :=
(giGenerate α).gc.u_iInf
#align filter.supr_sets_eq Filter.iSup_sets_eq
theorem generate_empty : Filter.generate ∅ = (⊤ : Filter α) :=
(giGenerate α).gc.l_bot
#align filter.generate_empty Filter.generate_empty
theorem generate_univ : Filter.generate univ = (⊥ : Filter α) :=
bot_unique fun _ _ => GenerateSets.basic (mem_univ _)
#align filter.generate_univ Filter.generate_univ
theorem generate_union {s t : Set (Set α)} :
Filter.generate (s ∪ t) = Filter.generate s ⊓ Filter.generate t :=
(giGenerate α).gc.l_sup
#align filter.generate_union Filter.generate_union
theorem generate_iUnion {s : ι → Set (Set α)} :
Filter.generate (⋃ i, s i) = ⨅ i, Filter.generate (s i) :=
(giGenerate α).gc.l_iSup
#align filter.generate_Union Filter.generate_iUnion
@[simp]
theorem mem_bot {s : Set α} : s ∈ (⊥ : Filter α) :=
trivial
#align filter.mem_bot Filter.mem_bot
@[simp]
theorem mem_sup {f g : Filter α} {s : Set α} : s ∈ f ⊔ g ↔ s ∈ f ∧ s ∈ g :=
Iff.rfl
#align filter.mem_sup Filter.mem_sup
theorem union_mem_sup {f g : Filter α} {s t : Set α} (hs : s ∈ f) (ht : t ∈ g) : s ∪ t ∈ f ⊔ g :=
⟨mem_of_superset hs subset_union_left, mem_of_superset ht subset_union_right⟩
#align filter.union_mem_sup Filter.union_mem_sup
@[simp]
theorem mem_sSup {x : Set α} {s : Set (Filter α)} : x ∈ sSup s ↔ ∀ f ∈ s, x ∈ (f : Filter α) :=
Iff.rfl
#align filter.mem_Sup Filter.mem_sSup
@[simp]
theorem mem_iSup {x : Set α} {f : ι → Filter α} : x ∈ iSup f ↔ ∀ i, x ∈ f i := by
simp only [← Filter.mem_sets, iSup_sets_eq, iff_self_iff, mem_iInter]
#align filter.mem_supr Filter.mem_iSup
@[simp]
theorem iSup_neBot {f : ι → Filter α} : (⨆ i, f i).NeBot ↔ ∃ i, (f i).NeBot := by
simp [neBot_iff]
#align filter.supr_ne_bot Filter.iSup_neBot
theorem iInf_eq_generate (s : ι → Filter α) : iInf s = generate (⋃ i, (s i).sets) :=
show generate _ = generate _ from congr_arg _ <| congr_arg sSup <| (range_comp _ _).symm
#align filter.infi_eq_generate Filter.iInf_eq_generate
theorem mem_iInf_of_mem {f : ι → Filter α} (i : ι) {s} (hs : s ∈ f i) : s ∈ ⨅ i, f i :=
iInf_le f i hs
#align filter.mem_infi_of_mem Filter.mem_iInf_of_mem
theorem mem_iInf_of_iInter {ι} {s : ι → Filter α} {U : Set α} {I : Set ι} (I_fin : I.Finite)
{V : I → Set α} (hV : ∀ i, V i ∈ s i) (hU : ⋂ i, V i ⊆ U) : U ∈ ⨅ i, s i := by
haveI := I_fin.fintype
refine mem_of_superset (iInter_mem.2 fun i => ?_) hU
exact mem_iInf_of_mem (i : ι) (hV _)
#align filter.mem_infi_of_Inter Filter.mem_iInf_of_iInter
theorem mem_iInf {ι} {s : ι → Filter α} {U : Set α} :
(U ∈ ⨅ i, s i) ↔ ∃ I : Set ι, I.Finite ∧ ∃ V : I → Set α, (∀ i, V i ∈ s i) ∧ U = ⋂ i, V i := by
constructor
· rw [iInf_eq_generate, mem_generate_iff]
rintro ⟨t, tsub, tfin, tinter⟩
rcases eq_finite_iUnion_of_finite_subset_iUnion tfin tsub with ⟨I, Ifin, σ, σfin, σsub, rfl⟩
rw [sInter_iUnion] at tinter
set V := fun i => U ∪ ⋂₀ σ i with hV
have V_in : ∀ i, V i ∈ s i := by
rintro i
have : ⋂₀ σ i ∈ s i := by
rw [sInter_mem (σfin _)]
apply σsub
exact mem_of_superset this subset_union_right
refine ⟨I, Ifin, V, V_in, ?_⟩
rwa [hV, ← union_iInter, union_eq_self_of_subset_right]
· rintro ⟨I, Ifin, V, V_in, rfl⟩
exact mem_iInf_of_iInter Ifin V_in Subset.rfl
#align filter.mem_infi Filter.mem_iInf
theorem mem_iInf' {ι} {s : ι → Filter α} {U : Set α} :
(U ∈ ⨅ i, s i) ↔
∃ I : Set ι, I.Finite ∧ ∃ V : ι → Set α, (∀ i, V i ∈ s i) ∧
(∀ i ∉ I, V i = univ) ∧ (U = ⋂ i ∈ I, V i) ∧ U = ⋂ i, V i := by
simp only [mem_iInf, SetCoe.forall', biInter_eq_iInter]
refine ⟨?_, fun ⟨I, If, V, hVs, _, hVU, _⟩ => ⟨I, If, fun i => V i, fun i => hVs i, hVU⟩⟩
rintro ⟨I, If, V, hV, rfl⟩
refine ⟨I, If, fun i => if hi : i ∈ I then V ⟨i, hi⟩ else univ, fun i => ?_, fun i hi => ?_, ?_⟩
· dsimp only
split_ifs
exacts [hV _, univ_mem]
· exact dif_neg hi
· simp only [iInter_dite, biInter_eq_iInter, dif_pos (Subtype.coe_prop _), Subtype.coe_eta,
iInter_univ, inter_univ, eq_self_iff_true, true_and_iff]
#align filter.mem_infi' Filter.mem_iInf'
theorem exists_iInter_of_mem_iInf {ι : Type*} {α : Type*} {f : ι → Filter α} {s}
(hs : s ∈ ⨅ i, f i) : ∃ t : ι → Set α, (∀ i, t i ∈ f i) ∧ s = ⋂ i, t i :=
let ⟨_, _, V, hVs, _, _, hVU'⟩ := mem_iInf'.1 hs; ⟨V, hVs, hVU'⟩
#align filter.exists_Inter_of_mem_infi Filter.exists_iInter_of_mem_iInf
theorem mem_iInf_of_finite {ι : Type*} [Finite ι] {α : Type*} {f : ι → Filter α} (s) :
(s ∈ ⨅ i, f i) ↔ ∃ t : ι → Set α, (∀ i, t i ∈ f i) ∧ s = ⋂ i, t i := by
refine ⟨exists_iInter_of_mem_iInf, ?_⟩
rintro ⟨t, ht, rfl⟩
exact iInter_mem.2 fun i => mem_iInf_of_mem i (ht i)
#align filter.mem_infi_of_finite Filter.mem_iInf_of_finite
@[simp]
theorem le_principal_iff {s : Set α} {f : Filter α} : f ≤ 𝓟 s ↔ s ∈ f :=
⟨fun h => h Subset.rfl, fun hs _ ht => mem_of_superset hs ht⟩
#align filter.le_principal_iff Filter.le_principal_iff
theorem Iic_principal (s : Set α) : Iic (𝓟 s) = { l | s ∈ l } :=
Set.ext fun _ => le_principal_iff
#align filter.Iic_principal Filter.Iic_principal
theorem principal_mono {s t : Set α} : 𝓟 s ≤ 𝓟 t ↔ s ⊆ t := by
simp only [le_principal_iff, iff_self_iff, mem_principal]
#align filter.principal_mono Filter.principal_mono
@[gcongr] alias ⟨_, _root_.GCongr.filter_principal_mono⟩ := principal_mono
@[mono]
theorem monotone_principal : Monotone (𝓟 : Set α → Filter α) := fun _ _ => principal_mono.2
#align filter.monotone_principal Filter.monotone_principal
@[simp] theorem principal_eq_iff_eq {s t : Set α} : 𝓟 s = 𝓟 t ↔ s = t := by
simp only [le_antisymm_iff, le_principal_iff, mem_principal]; rfl
#align filter.principal_eq_iff_eq Filter.principal_eq_iff_eq
@[simp] theorem join_principal_eq_sSup {s : Set (Filter α)} : join (𝓟 s) = sSup s := rfl
#align filter.join_principal_eq_Sup Filter.join_principal_eq_sSup
@[simp] theorem principal_univ : 𝓟 (univ : Set α) = ⊤ :=
top_unique <| by simp only [le_principal_iff, mem_top, eq_self_iff_true]
#align filter.principal_univ Filter.principal_univ
@[simp]
theorem principal_empty : 𝓟 (∅ : Set α) = ⊥ :=
bot_unique fun _ _ => empty_subset _
#align filter.principal_empty Filter.principal_empty
theorem generate_eq_biInf (S : Set (Set α)) : generate S = ⨅ s ∈ S, 𝓟 s :=
eq_of_forall_le_iff fun f => by simp [le_generate_iff, le_principal_iff, subset_def]
#align filter.generate_eq_binfi Filter.generate_eq_biInf
/-! ### Lattice equations -/
theorem empty_mem_iff_bot {f : Filter α} : ∅ ∈ f ↔ f = ⊥ :=
⟨fun h => bot_unique fun s _ => mem_of_superset h (empty_subset s), fun h => h.symm ▸ mem_bot⟩
#align filter.empty_mem_iff_bot Filter.empty_mem_iff_bot
theorem nonempty_of_mem {f : Filter α} [hf : NeBot f] {s : Set α} (hs : s ∈ f) : s.Nonempty :=
s.eq_empty_or_nonempty.elim (fun h => absurd hs (h.symm ▸ mt empty_mem_iff_bot.mp hf.1)) id
#align filter.nonempty_of_mem Filter.nonempty_of_mem
theorem NeBot.nonempty_of_mem {f : Filter α} (hf : NeBot f) {s : Set α} (hs : s ∈ f) : s.Nonempty :=
@Filter.nonempty_of_mem α f hf s hs
#align filter.ne_bot.nonempty_of_mem Filter.NeBot.nonempty_of_mem
@[simp]
theorem empty_not_mem (f : Filter α) [NeBot f] : ¬∅ ∈ f := fun h => (nonempty_of_mem h).ne_empty rfl
#align filter.empty_not_mem Filter.empty_not_mem
theorem nonempty_of_neBot (f : Filter α) [NeBot f] : Nonempty α :=
nonempty_of_exists <| nonempty_of_mem (univ_mem : univ ∈ f)
#align filter.nonempty_of_ne_bot Filter.nonempty_of_neBot
theorem compl_not_mem {f : Filter α} {s : Set α} [NeBot f] (h : s ∈ f) : sᶜ ∉ f := fun hsc =>
(nonempty_of_mem (inter_mem h hsc)).ne_empty <| inter_compl_self s
#align filter.compl_not_mem Filter.compl_not_mem
theorem filter_eq_bot_of_isEmpty [IsEmpty α] (f : Filter α) : f = ⊥ :=
empty_mem_iff_bot.mp <| univ_mem' isEmptyElim
#align filter.filter_eq_bot_of_is_empty Filter.filter_eq_bot_of_isEmpty
protected lemma disjoint_iff {f g : Filter α} : Disjoint f g ↔ ∃ s ∈ f, ∃ t ∈ g, Disjoint s t := by
simp only [disjoint_iff, ← empty_mem_iff_bot, mem_inf_iff, inf_eq_inter, bot_eq_empty,
@eq_comm _ ∅]
#align filter.disjoint_iff Filter.disjoint_iff
theorem disjoint_of_disjoint_of_mem {f g : Filter α} {s t : Set α} (h : Disjoint s t) (hs : s ∈ f)
(ht : t ∈ g) : Disjoint f g :=
Filter.disjoint_iff.mpr ⟨s, hs, t, ht, h⟩
#align filter.disjoint_of_disjoint_of_mem Filter.disjoint_of_disjoint_of_mem
theorem NeBot.not_disjoint (hf : f.NeBot) (hs : s ∈ f) (ht : t ∈ f) : ¬Disjoint s t := fun h =>
not_disjoint_self_iff.2 hf <| Filter.disjoint_iff.2 ⟨s, hs, t, ht, h⟩
#align filter.ne_bot.not_disjoint Filter.NeBot.not_disjoint
theorem inf_eq_bot_iff {f g : Filter α} : f ⊓ g = ⊥ ↔ ∃ U ∈ f, ∃ V ∈ g, U ∩ V = ∅ := by
simp only [← disjoint_iff, Filter.disjoint_iff, Set.disjoint_iff_inter_eq_empty]
#align filter.inf_eq_bot_iff Filter.inf_eq_bot_iff
theorem _root_.Pairwise.exists_mem_filter_of_disjoint {ι : Type*} [Finite ι] {l : ι → Filter α}
(hd : Pairwise (Disjoint on l)) :
∃ s : ι → Set α, (∀ i, s i ∈ l i) ∧ Pairwise (Disjoint on s) := by
have : Pairwise fun i j => ∃ (s : {s // s ∈ l i}) (t : {t // t ∈ l j}), Disjoint s.1 t.1 := by
simpa only [Pairwise, Function.onFun, Filter.disjoint_iff, exists_prop, Subtype.exists] using hd
choose! s t hst using this
refine ⟨fun i => ⋂ j, @s i j ∩ @t j i, fun i => ?_, fun i j hij => ?_⟩
exacts [iInter_mem.2 fun j => inter_mem (@s i j).2 (@t j i).2,
(hst hij).mono ((iInter_subset _ j).trans inter_subset_left)
((iInter_subset _ i).trans inter_subset_right)]
#align pairwise.exists_mem_filter_of_disjoint Pairwise.exists_mem_filter_of_disjoint
theorem _root_.Set.PairwiseDisjoint.exists_mem_filter {ι : Type*} {l : ι → Filter α} {t : Set ι}
(hd : t.PairwiseDisjoint l) (ht : t.Finite) :
∃ s : ι → Set α, (∀ i, s i ∈ l i) ∧ t.PairwiseDisjoint s := by
haveI := ht.to_subtype
rcases (hd.subtype _ _).exists_mem_filter_of_disjoint with ⟨s, hsl, hsd⟩
lift s to (i : t) → {s // s ∈ l i} using hsl
rcases @Subtype.exists_pi_extension ι (fun i => { s // s ∈ l i }) _ _ s with ⟨s, rfl⟩
exact ⟨fun i => s i, fun i => (s i).2, hsd.set_of_subtype _ _⟩
#align set.pairwise_disjoint.exists_mem_filter Set.PairwiseDisjoint.exists_mem_filter
/-- There is exactly one filter on an empty type. -/
instance unique [IsEmpty α] : Unique (Filter α) where
default := ⊥
uniq := filter_eq_bot_of_isEmpty
#align filter.unique Filter.unique
theorem NeBot.nonempty (f : Filter α) [hf : f.NeBot] : Nonempty α :=
not_isEmpty_iff.mp fun _ ↦ hf.ne (Subsingleton.elim _ _)
/-- There are only two filters on a `Subsingleton`: `⊥` and `⊤`. If the type is empty, then they are
equal. -/
theorem eq_top_of_neBot [Subsingleton α] (l : Filter α) [NeBot l] : l = ⊤ := by
refine top_unique fun s hs => ?_
obtain rfl : s = univ := Subsingleton.eq_univ_of_nonempty (nonempty_of_mem hs)
exact univ_mem
#align filter.eq_top_of_ne_bot Filter.eq_top_of_neBot
theorem forall_mem_nonempty_iff_neBot {f : Filter α} :
(∀ s : Set α, s ∈ f → s.Nonempty) ↔ NeBot f :=
⟨fun h => ⟨fun hf => not_nonempty_empty (h ∅ <| hf.symm ▸ mem_bot)⟩, @nonempty_of_mem _ _⟩
#align filter.forall_mem_nonempty_iff_ne_bot Filter.forall_mem_nonempty_iff_neBot
instance instNontrivialFilter [Nonempty α] : Nontrivial (Filter α) :=
⟨⟨⊤, ⊥, NeBot.ne <| forall_mem_nonempty_iff_neBot.1
fun s hs => by rwa [mem_top.1 hs, ← nonempty_iff_univ_nonempty]⟩⟩
theorem nontrivial_iff_nonempty : Nontrivial (Filter α) ↔ Nonempty α :=
⟨fun _ =>
by_contra fun h' =>
haveI := not_nonempty_iff.1 h'
not_subsingleton (Filter α) inferInstance,
@Filter.instNontrivialFilter α⟩
#align filter.nontrivial_iff_nonempty Filter.nontrivial_iff_nonempty
theorem eq_sInf_of_mem_iff_exists_mem {S : Set (Filter α)} {l : Filter α}
(h : ∀ {s}, s ∈ l ↔ ∃ f ∈ S, s ∈ f) : l = sInf S :=
le_antisymm (le_sInf fun f hf _ hs => h.2 ⟨f, hf, hs⟩)
fun _ hs => let ⟨_, hf, hs⟩ := h.1 hs; (sInf_le hf) hs
#align filter.eq_Inf_of_mem_iff_exists_mem Filter.eq_sInf_of_mem_iff_exists_mem
theorem eq_iInf_of_mem_iff_exists_mem {f : ι → Filter α} {l : Filter α}
(h : ∀ {s}, s ∈ l ↔ ∃ i, s ∈ f i) : l = iInf f :=
eq_sInf_of_mem_iff_exists_mem <| h.trans exists_range_iff.symm
#align filter.eq_infi_of_mem_iff_exists_mem Filter.eq_iInf_of_mem_iff_exists_mem
theorem eq_biInf_of_mem_iff_exists_mem {f : ι → Filter α} {p : ι → Prop} {l : Filter α}
(h : ∀ {s}, s ∈ l ↔ ∃ i, p i ∧ s ∈ f i) : l = ⨅ (i) (_ : p i), f i := by
rw [iInf_subtype']
exact eq_iInf_of_mem_iff_exists_mem fun {_} => by simp only [Subtype.exists, h, exists_prop]
#align filter.eq_binfi_of_mem_iff_exists_mem Filter.eq_biInf_of_mem_iff_exists_memₓ
theorem iInf_sets_eq {f : ι → Filter α} (h : Directed (· ≥ ·) f) [ne : Nonempty ι] :
(iInf f).sets = ⋃ i, (f i).sets :=
let ⟨i⟩ := ne
let u :=
{ sets := ⋃ i, (f i).sets
univ_sets := mem_iUnion.2 ⟨i, univ_mem⟩
sets_of_superset := by
simp only [mem_iUnion, exists_imp]
exact fun i hx hxy => ⟨i, mem_of_superset hx hxy⟩
inter_sets := by
simp only [mem_iUnion, exists_imp]
intro x y a hx b hy
rcases h a b with ⟨c, ha, hb⟩
exact ⟨c, inter_mem (ha hx) (hb hy)⟩ }
have : u = iInf f := eq_iInf_of_mem_iff_exists_mem mem_iUnion
-- Porting note: it was just `congr_arg filter.sets this.symm`
(congr_arg Filter.sets this.symm).trans <| by simp only
#align filter.infi_sets_eq Filter.iInf_sets_eq
theorem mem_iInf_of_directed {f : ι → Filter α} (h : Directed (· ≥ ·) f) [Nonempty ι] (s) :
s ∈ iInf f ↔ ∃ i, s ∈ f i := by
simp only [← Filter.mem_sets, iInf_sets_eq h, mem_iUnion]
#align filter.mem_infi_of_directed Filter.mem_iInf_of_directed
theorem mem_biInf_of_directed {f : β → Filter α} {s : Set β} (h : DirectedOn (f ⁻¹'o (· ≥ ·)) s)
(ne : s.Nonempty) {t : Set α} : (t ∈ ⨅ i ∈ s, f i) ↔ ∃ i ∈ s, t ∈ f i := by
haveI := ne.to_subtype
simp_rw [iInf_subtype', mem_iInf_of_directed h.directed_val, Subtype.exists, exists_prop]
#align filter.mem_binfi_of_directed Filter.mem_biInf_of_directed
theorem biInf_sets_eq {f : β → Filter α} {s : Set β} (h : DirectedOn (f ⁻¹'o (· ≥ ·)) s)
(ne : s.Nonempty) : (⨅ i ∈ s, f i).sets = ⋃ i ∈ s, (f i).sets :=
ext fun t => by simp [mem_biInf_of_directed h ne]
#align filter.binfi_sets_eq Filter.biInf_sets_eq
theorem iInf_sets_eq_finite {ι : Type*} (f : ι → Filter α) :
(⨅ i, f i).sets = ⋃ t : Finset ι, (⨅ i ∈ t, f i).sets := by
rw [iInf_eq_iInf_finset, iInf_sets_eq]
exact directed_of_isDirected_le fun _ _ => biInf_mono
#align filter.infi_sets_eq_finite Filter.iInf_sets_eq_finite
theorem iInf_sets_eq_finite' (f : ι → Filter α) :
(⨅ i, f i).sets = ⋃ t : Finset (PLift ι), (⨅ i ∈ t, f (PLift.down i)).sets := by
rw [← iInf_sets_eq_finite, ← Equiv.plift.surjective.iInf_comp, Equiv.plift_apply]
#align filter.infi_sets_eq_finite' Filter.iInf_sets_eq_finite'
theorem mem_iInf_finite {ι : Type*} {f : ι → Filter α} (s) :
s ∈ iInf f ↔ ∃ t : Finset ι, s ∈ ⨅ i ∈ t, f i :=
(Set.ext_iff.1 (iInf_sets_eq_finite f) s).trans mem_iUnion
#align filter.mem_infi_finite Filter.mem_iInf_finite
theorem mem_iInf_finite' {f : ι → Filter α} (s) :
s ∈ iInf f ↔ ∃ t : Finset (PLift ι), s ∈ ⨅ i ∈ t, f (PLift.down i) :=
(Set.ext_iff.1 (iInf_sets_eq_finite' f) s).trans mem_iUnion
#align filter.mem_infi_finite' Filter.mem_iInf_finite'
@[simp]
theorem sup_join {f₁ f₂ : Filter (Filter α)} : join f₁ ⊔ join f₂ = join (f₁ ⊔ f₂) :=
Filter.ext fun x => by simp only [mem_sup, mem_join]
#align filter.sup_join Filter.sup_join
@[simp]
theorem iSup_join {ι : Sort w} {f : ι → Filter (Filter α)} : ⨆ x, join (f x) = join (⨆ x, f x) :=
Filter.ext fun x => by simp only [mem_iSup, mem_join]
#align filter.supr_join Filter.iSup_join
instance : DistribLattice (Filter α) :=
{ Filter.instCompleteLatticeFilter with
le_sup_inf := by
intro x y z s
simp only [and_assoc, mem_inf_iff, mem_sup, exists_prop, exists_imp, and_imp]
rintro hs t₁ ht₁ t₂ ht₂ rfl
exact
⟨t₁, x.sets_of_superset hs inter_subset_left, ht₁, t₂,
x.sets_of_superset hs inter_subset_right, ht₂, rfl⟩ }
-- The dual version does not hold! `Filter α` is not a `CompleteDistribLattice`. -/
instance : Coframe (Filter α) :=
{ Filter.instCompleteLatticeFilter with
iInf_sup_le_sup_sInf := fun f s t ⟨h₁, h₂⟩ => by
rw [iInf_subtype']
rw [sInf_eq_iInf', iInf_sets_eq_finite, mem_iUnion] at h₂
obtain ⟨u, hu⟩ := h₂
rw [← Finset.inf_eq_iInf] at hu
suffices ⨅ i : s, f ⊔ ↑i ≤ f ⊔ u.inf fun i => ↑i from this ⟨h₁, hu⟩
refine Finset.induction_on u (le_sup_of_le_right le_top) ?_
rintro ⟨i⟩ u _ ih
rw [Finset.inf_insert, sup_inf_left]
exact le_inf (iInf_le _ _) ih }
theorem mem_iInf_finset {s : Finset α} {f : α → Filter β} {t : Set β} :
(t ∈ ⨅ a ∈ s, f a) ↔ ∃ p : α → Set β, (∀ a ∈ s, p a ∈ f a) ∧ t = ⋂ a ∈ s, p a := by
simp only [← Finset.set_biInter_coe, biInter_eq_iInter, iInf_subtype']
refine ⟨fun h => ?_, ?_⟩
· rcases (mem_iInf_of_finite _).1 h with ⟨p, hp, rfl⟩
refine ⟨fun a => if h : a ∈ s then p ⟨a, h⟩ else univ,
fun a ha => by simpa [ha] using hp ⟨a, ha⟩, ?_⟩
refine iInter_congr_of_surjective id surjective_id ?_
rintro ⟨a, ha⟩
simp [ha]
· rintro ⟨p, hpf, rfl⟩
exact iInter_mem.2 fun a => mem_iInf_of_mem a (hpf a a.2)
#align filter.mem_infi_finset Filter.mem_iInf_finset
/-- If `f : ι → Filter α` is directed, `ι` is not empty, and `∀ i, f i ≠ ⊥`, then `iInf f ≠ ⊥`.
See also `iInf_neBot_of_directed` for a version assuming `Nonempty α` instead of `Nonempty ι`. -/
theorem iInf_neBot_of_directed' {f : ι → Filter α} [Nonempty ι] (hd : Directed (· ≥ ·) f) :
(∀ i, NeBot (f i)) → NeBot (iInf f) :=
not_imp_not.1 <| by simpa only [not_forall, not_neBot, ← empty_mem_iff_bot,
mem_iInf_of_directed hd] using id
#align filter.infi_ne_bot_of_directed' Filter.iInf_neBot_of_directed'
/-- If `f : ι → Filter α` is directed, `α` is not empty, and `∀ i, f i ≠ ⊥`, then `iInf f ≠ ⊥`.
See also `iInf_neBot_of_directed'` for a version assuming `Nonempty ι` instead of `Nonempty α`. -/
theorem iInf_neBot_of_directed {f : ι → Filter α} [hn : Nonempty α] (hd : Directed (· ≥ ·) f)
(hb : ∀ i, NeBot (f i)) : NeBot (iInf f) := by
cases isEmpty_or_nonempty ι
· constructor
simp [iInf_of_empty f, top_ne_bot]
· exact iInf_neBot_of_directed' hd hb
#align filter.infi_ne_bot_of_directed Filter.iInf_neBot_of_directed
theorem sInf_neBot_of_directed' {s : Set (Filter α)} (hne : s.Nonempty) (hd : DirectedOn (· ≥ ·) s)
(hbot : ⊥ ∉ s) : NeBot (sInf s) :=
(sInf_eq_iInf' s).symm ▸
@iInf_neBot_of_directed' _ _ _ hne.to_subtype hd.directed_val fun ⟨_, hf⟩ =>
⟨ne_of_mem_of_not_mem hf hbot⟩
#align filter.Inf_ne_bot_of_directed' Filter.sInf_neBot_of_directed'
theorem sInf_neBot_of_directed [Nonempty α] {s : Set (Filter α)} (hd : DirectedOn (· ≥ ·) s)
(hbot : ⊥ ∉ s) : NeBot (sInf s) :=
(sInf_eq_iInf' s).symm ▸
iInf_neBot_of_directed hd.directed_val fun ⟨_, hf⟩ => ⟨ne_of_mem_of_not_mem hf hbot⟩
#align filter.Inf_ne_bot_of_directed Filter.sInf_neBot_of_directed
theorem iInf_neBot_iff_of_directed' {f : ι → Filter α} [Nonempty ι] (hd : Directed (· ≥ ·) f) :
NeBot (iInf f) ↔ ∀ i, NeBot (f i) :=
⟨fun H i => H.mono (iInf_le _ i), iInf_neBot_of_directed' hd⟩
#align filter.infi_ne_bot_iff_of_directed' Filter.iInf_neBot_iff_of_directed'
theorem iInf_neBot_iff_of_directed {f : ι → Filter α} [Nonempty α] (hd : Directed (· ≥ ·) f) :
NeBot (iInf f) ↔ ∀ i, NeBot (f i) :=
⟨fun H i => H.mono (iInf_le _ i), iInf_neBot_of_directed hd⟩
#align filter.infi_ne_bot_iff_of_directed Filter.iInf_neBot_iff_of_directed
@[elab_as_elim]
theorem iInf_sets_induct {f : ι → Filter α} {s : Set α} (hs : s ∈ iInf f) {p : Set α → Prop}
(uni : p univ) (ins : ∀ {i s₁ s₂}, s₁ ∈ f i → p s₂ → p (s₁ ∩ s₂)) : p s := by
rw [mem_iInf_finite'] at hs
simp only [← Finset.inf_eq_iInf] at hs
rcases hs with ⟨is, his⟩
induction is using Finset.induction_on generalizing s with
| empty => rwa [mem_top.1 his]
| insert _ ih =>
rw [Finset.inf_insert, mem_inf_iff] at his
rcases his with ⟨s₁, hs₁, s₂, hs₂, rfl⟩
exact ins hs₁ (ih hs₂)
#align filter.infi_sets_induct Filter.iInf_sets_induct
/-! #### `principal` equations -/
@[simp]
theorem inf_principal {s t : Set α} : 𝓟 s ⊓ 𝓟 t = 𝓟 (s ∩ t) :=
le_antisymm
(by simp only [le_principal_iff, mem_inf_iff]; exact ⟨s, Subset.rfl, t, Subset.rfl, rfl⟩)
(by simp [le_inf_iff, inter_subset_left, inter_subset_right])
#align filter.inf_principal Filter.inf_principal
@[simp]
theorem sup_principal {s t : Set α} : 𝓟 s ⊔ 𝓟 t = 𝓟 (s ∪ t) :=
Filter.ext fun u => by simp only [union_subset_iff, mem_sup, mem_principal]
#align filter.sup_principal Filter.sup_principal
@[simp]
theorem iSup_principal {ι : Sort w} {s : ι → Set α} : ⨆ x, 𝓟 (s x) = 𝓟 (⋃ i, s i) :=
Filter.ext fun x => by simp only [mem_iSup, mem_principal, iUnion_subset_iff]
#align filter.supr_principal Filter.iSup_principal
@[simp]
theorem principal_eq_bot_iff {s : Set α} : 𝓟 s = ⊥ ↔ s = ∅ :=
empty_mem_iff_bot.symm.trans <| mem_principal.trans subset_empty_iff
#align filter.principal_eq_bot_iff Filter.principal_eq_bot_iff
@[simp]
theorem principal_neBot_iff {s : Set α} : NeBot (𝓟 s) ↔ s.Nonempty :=
neBot_iff.trans <| (not_congr principal_eq_bot_iff).trans nonempty_iff_ne_empty.symm
#align filter.principal_ne_bot_iff Filter.principal_neBot_iff
alias ⟨_, _root_.Set.Nonempty.principal_neBot⟩ := principal_neBot_iff
#align set.nonempty.principal_ne_bot Set.Nonempty.principal_neBot
theorem isCompl_principal (s : Set α) : IsCompl (𝓟 s) (𝓟 sᶜ) :=
IsCompl.of_eq (by rw [inf_principal, inter_compl_self, principal_empty]) <| by
rw [sup_principal, union_compl_self, principal_univ]
#align filter.is_compl_principal Filter.isCompl_principal
theorem mem_inf_principal' {f : Filter α} {s t : Set α} : s ∈ f ⊓ 𝓟 t ↔ tᶜ ∪ s ∈ f := by
simp only [← le_principal_iff, (isCompl_principal s).le_left_iff, disjoint_assoc, inf_principal,
← (isCompl_principal (t ∩ sᶜ)).le_right_iff, compl_inter, compl_compl]
#align filter.mem_inf_principal' Filter.mem_inf_principal'
lemma mem_inf_principal {f : Filter α} {s t : Set α} : s ∈ f ⊓ 𝓟 t ↔ { x | x ∈ t → x ∈ s } ∈ f := by
simp only [mem_inf_principal', imp_iff_not_or, setOf_or, compl_def, setOf_mem_eq]
#align filter.mem_inf_principal Filter.mem_inf_principal
lemma iSup_inf_principal (f : ι → Filter α) (s : Set α) : ⨆ i, f i ⊓ 𝓟 s = (⨆ i, f i) ⊓ 𝓟 s := by
ext
simp only [mem_iSup, mem_inf_principal]
#align filter.supr_inf_principal Filter.iSup_inf_principal
theorem inf_principal_eq_bot {f : Filter α} {s : Set α} : f ⊓ 𝓟 s = ⊥ ↔ sᶜ ∈ f := by
rw [← empty_mem_iff_bot, mem_inf_principal]
simp only [mem_empty_iff_false, imp_false, compl_def]
#align filter.inf_principal_eq_bot Filter.inf_principal_eq_bot
theorem mem_of_eq_bot {f : Filter α} {s : Set α} (h : f ⊓ 𝓟 sᶜ = ⊥) : s ∈ f := by
rwa [inf_principal_eq_bot, compl_compl] at h
#align filter.mem_of_eq_bot Filter.mem_of_eq_bot
theorem diff_mem_inf_principal_compl {f : Filter α} {s : Set α} (hs : s ∈ f) (t : Set α) :
s \ t ∈ f ⊓ 𝓟 tᶜ :=
inter_mem_inf hs <| mem_principal_self tᶜ
#align filter.diff_mem_inf_principal_compl Filter.diff_mem_inf_principal_compl
theorem principal_le_iff {s : Set α} {f : Filter α} : 𝓟 s ≤ f ↔ ∀ V ∈ f, s ⊆ V := by
simp_rw [le_def, mem_principal]
#align filter.principal_le_iff Filter.principal_le_iff
@[simp]
theorem iInf_principal_finset {ι : Type w} (s : Finset ι) (f : ι → Set α) :
⨅ i ∈ s, 𝓟 (f i) = 𝓟 (⋂ i ∈ s, f i) := by
induction' s using Finset.induction_on with i s _ hs
· simp
· rw [Finset.iInf_insert, Finset.set_biInter_insert, hs, inf_principal]
#align filter.infi_principal_finset Filter.iInf_principal_finset
theorem iInf_principal {ι : Sort w} [Finite ι] (f : ι → Set α) : ⨅ i, 𝓟 (f i) = 𝓟 (⋂ i, f i) := by
cases nonempty_fintype (PLift ι)
rw [← iInf_plift_down, ← iInter_plift_down]
simpa using iInf_principal_finset Finset.univ (f <| PLift.down ·)
/-- A special case of `iInf_principal` that is safe to mark `simp`. -/
@[simp]
theorem iInf_principal' {ι : Type w} [Finite ι] (f : ι → Set α) : ⨅ i, 𝓟 (f i) = 𝓟 (⋂ i, f i) :=
iInf_principal _
#align filter.infi_principal Filter.iInf_principal
theorem iInf_principal_finite {ι : Type w} {s : Set ι} (hs : s.Finite) (f : ι → Set α) :
⨅ i ∈ s, 𝓟 (f i) = 𝓟 (⋂ i ∈ s, f i) := by
lift s to Finset ι using hs
exact mod_cast iInf_principal_finset s f
#align filter.infi_principal_finite Filter.iInf_principal_finite
end Lattice
@[mono, gcongr]
theorem join_mono {f₁ f₂ : Filter (Filter α)} (h : f₁ ≤ f₂) : join f₁ ≤ join f₂ := fun _ hs => h hs
#align filter.join_mono Filter.join_mono
/-! ### Eventually -/
/-- `f.Eventually p` or `∀ᶠ x in f, p x` mean that `{x | p x} ∈ f`. E.g., `∀ᶠ x in atTop, p x`
means that `p` holds true for sufficiently large `x`. -/
protected def Eventually (p : α → Prop) (f : Filter α) : Prop :=
{ x | p x } ∈ f
#align filter.eventually Filter.Eventually
@[inherit_doc Filter.Eventually]
notation3 "∀ᶠ "(...)" in "f", "r:(scoped p => Filter.Eventually p f) => r
theorem eventually_iff {f : Filter α} {P : α → Prop} : (∀ᶠ x in f, P x) ↔ { x | P x } ∈ f :=
Iff.rfl
#align filter.eventually_iff Filter.eventually_iff
@[simp]
theorem eventually_mem_set {s : Set α} {l : Filter α} : (∀ᶠ x in l, x ∈ s) ↔ s ∈ l :=
Iff.rfl
#align filter.eventually_mem_set Filter.eventually_mem_set
protected theorem ext' {f₁ f₂ : Filter α}
(h : ∀ p : α → Prop, (∀ᶠ x in f₁, p x) ↔ ∀ᶠ x in f₂, p x) : f₁ = f₂ :=
Filter.ext h
#align filter.ext' Filter.ext'
theorem Eventually.filter_mono {f₁ f₂ : Filter α} (h : f₁ ≤ f₂) {p : α → Prop}
(hp : ∀ᶠ x in f₂, p x) : ∀ᶠ x in f₁, p x :=
h hp
#align filter.eventually.filter_mono Filter.Eventually.filter_mono
theorem eventually_of_mem {f : Filter α} {P : α → Prop} {U : Set α} (hU : U ∈ f)
(h : ∀ x ∈ U, P x) : ∀ᶠ x in f, P x :=
mem_of_superset hU h
#align filter.eventually_of_mem Filter.eventually_of_mem
protected theorem Eventually.and {p q : α → Prop} {f : Filter α} :
f.Eventually p → f.Eventually q → ∀ᶠ x in f, p x ∧ q x :=
inter_mem
#align filter.eventually.and Filter.Eventually.and
@[simp] theorem eventually_true (f : Filter α) : ∀ᶠ _ in f, True := univ_mem
#align filter.eventually_true Filter.eventually_true
theorem eventually_of_forall {p : α → Prop} {f : Filter α} (hp : ∀ x, p x) : ∀ᶠ x in f, p x :=
univ_mem' hp
#align filter.eventually_of_forall Filter.eventually_of_forall
@[simp]
theorem eventually_false_iff_eq_bot {f : Filter α} : (∀ᶠ _ in f, False) ↔ f = ⊥ :=
empty_mem_iff_bot
#align filter.eventually_false_iff_eq_bot Filter.eventually_false_iff_eq_bot
@[simp]
theorem eventually_const {f : Filter α} [t : NeBot f] {p : Prop} : (∀ᶠ _ in f, p) ↔ p := by
by_cases h : p <;> simp [h, t.ne]
#align filter.eventually_const Filter.eventually_const
theorem eventually_iff_exists_mem {p : α → Prop} {f : Filter α} :
(∀ᶠ x in f, p x) ↔ ∃ v ∈ f, ∀ y ∈ v, p y :=
exists_mem_subset_iff.symm
#align filter.eventually_iff_exists_mem Filter.eventually_iff_exists_mem
theorem Eventually.exists_mem {p : α → Prop} {f : Filter α} (hp : ∀ᶠ x in f, p x) :
∃ v ∈ f, ∀ y ∈ v, p y :=
eventually_iff_exists_mem.1 hp
#align filter.eventually.exists_mem Filter.Eventually.exists_mem
theorem Eventually.mp {p q : α → Prop} {f : Filter α} (hp : ∀ᶠ x in f, p x)
(hq : ∀ᶠ x in f, p x → q x) : ∀ᶠ x in f, q x :=
mp_mem hp hq
#align filter.eventually.mp Filter.Eventually.mp
theorem Eventually.mono {p q : α → Prop} {f : Filter α} (hp : ∀ᶠ x in f, p x)
(hq : ∀ x, p x → q x) : ∀ᶠ x in f, q x :=
hp.mp (eventually_of_forall hq)
#align filter.eventually.mono Filter.Eventually.mono
theorem forall_eventually_of_eventually_forall {f : Filter α} {p : α → β → Prop}
(h : ∀ᶠ x in f, ∀ y, p x y) : ∀ y, ∀ᶠ x in f, p x y :=
fun y => h.mono fun _ h => h y
#align filter.forall_eventually_of_eventually_forall Filter.forall_eventually_of_eventually_forall
@[simp]
theorem eventually_and {p q : α → Prop} {f : Filter α} :
(∀ᶠ x in f, p x ∧ q x) ↔ (∀ᶠ x in f, p x) ∧ ∀ᶠ x in f, q x :=
inter_mem_iff
#align filter.eventually_and Filter.eventually_and
theorem Eventually.congr {f : Filter α} {p q : α → Prop} (h' : ∀ᶠ x in f, p x)
(h : ∀ᶠ x in f, p x ↔ q x) : ∀ᶠ x in f, q x :=
h'.mp (h.mono fun _ hx => hx.mp)
#align filter.eventually.congr Filter.Eventually.congr
theorem eventually_congr {f : Filter α} {p q : α → Prop} (h : ∀ᶠ x in f, p x ↔ q x) :
(∀ᶠ x in f, p x) ↔ ∀ᶠ x in f, q x :=
⟨fun hp => hp.congr h, fun hq => hq.congr <| by simpa only [Iff.comm] using h⟩
#align filter.eventually_congr Filter.eventually_congr
@[simp]
theorem eventually_all {ι : Sort*} [Finite ι] {l} {p : ι → α → Prop} :
(∀ᶠ x in l, ∀ i, p i x) ↔ ∀ i, ∀ᶠ x in l, p i x := by
simpa only [Filter.Eventually, setOf_forall] using iInter_mem
#align filter.eventually_all Filter.eventually_all
@[simp]
theorem eventually_all_finite {ι} {I : Set ι} (hI : I.Finite) {l} {p : ι → α → Prop} :
(∀ᶠ x in l, ∀ i ∈ I, p i x) ↔ ∀ i ∈ I, ∀ᶠ x in l, p i x := by
simpa only [Filter.Eventually, setOf_forall] using biInter_mem hI
#align filter.eventually_all_finite Filter.eventually_all_finite
alias _root_.Set.Finite.eventually_all := eventually_all_finite
#align set.finite.eventually_all Set.Finite.eventually_all
-- attribute [protected] Set.Finite.eventually_all
@[simp] theorem eventually_all_finset {ι} (I : Finset ι) {l} {p : ι → α → Prop} :
(∀ᶠ x in l, ∀ i ∈ I, p i x) ↔ ∀ i ∈ I, ∀ᶠ x in l, p i x :=
I.finite_toSet.eventually_all
#align filter.eventually_all_finset Filter.eventually_all_finset
alias _root_.Finset.eventually_all := eventually_all_finset
#align finset.eventually_all Finset.eventually_all
-- attribute [protected] Finset.eventually_all
@[simp]
theorem eventually_or_distrib_left {f : Filter α} {p : Prop} {q : α → Prop} :
(∀ᶠ x in f, p ∨ q x) ↔ p ∨ ∀ᶠ x in f, q x :=
by_cases (fun h : p => by simp [h]) fun h => by simp [h]
#align filter.eventually_or_distrib_left Filter.eventually_or_distrib_left
@[simp]
theorem eventually_or_distrib_right {f : Filter α} {p : α → Prop} {q : Prop} :
(∀ᶠ x in f, p x ∨ q) ↔ (∀ᶠ x in f, p x) ∨ q := by
simp only [@or_comm _ q, eventually_or_distrib_left]
#align filter.eventually_or_distrib_right Filter.eventually_or_distrib_right
theorem eventually_imp_distrib_left {f : Filter α} {p : Prop} {q : α → Prop} :
(∀ᶠ x in f, p → q x) ↔ p → ∀ᶠ x in f, q x :=
eventually_all
#align filter.eventually_imp_distrib_left Filter.eventually_imp_distrib_left
@[simp]
theorem eventually_bot {p : α → Prop} : ∀ᶠ x in ⊥, p x :=
⟨⟩
#align filter.eventually_bot Filter.eventually_bot
@[simp]
theorem eventually_top {p : α → Prop} : (∀ᶠ x in ⊤, p x) ↔ ∀ x, p x :=
Iff.rfl
#align filter.eventually_top Filter.eventually_top
@[simp]
theorem eventually_sup {p : α → Prop} {f g : Filter α} :
(∀ᶠ x in f ⊔ g, p x) ↔ (∀ᶠ x in f, p x) ∧ ∀ᶠ x in g, p x :=
Iff.rfl
#align filter.eventually_sup Filter.eventually_sup
@[simp]
theorem eventually_sSup {p : α → Prop} {fs : Set (Filter α)} :
(∀ᶠ x in sSup fs, p x) ↔ ∀ f ∈ fs, ∀ᶠ x in f, p x :=
Iff.rfl
#align filter.eventually_Sup Filter.eventually_sSup
@[simp]
theorem eventually_iSup {p : α → Prop} {fs : ι → Filter α} :
(∀ᶠ x in ⨆ b, fs b, p x) ↔ ∀ b, ∀ᶠ x in fs b, p x :=
mem_iSup
#align filter.eventually_supr Filter.eventually_iSup
@[simp]
theorem eventually_principal {a : Set α} {p : α → Prop} : (∀ᶠ x in 𝓟 a, p x) ↔ ∀ x ∈ a, p x :=
Iff.rfl
#align filter.eventually_principal Filter.eventually_principal
theorem Eventually.forall_mem {α : Type*} {f : Filter α} {s : Set α} {P : α → Prop}
(hP : ∀ᶠ x in f, P x) (hf : 𝓟 s ≤ f) : ∀ x ∈ s, P x :=
Filter.eventually_principal.mp (hP.filter_mono hf)
theorem eventually_inf {f g : Filter α} {p : α → Prop} :
(∀ᶠ x in f ⊓ g, p x) ↔ ∃ s ∈ f, ∃ t ∈ g, ∀ x ∈ s ∩ t, p x :=
mem_inf_iff_superset
#align filter.eventually_inf Filter.eventually_inf
theorem eventually_inf_principal {f : Filter α} {p : α → Prop} {s : Set α} :
(∀ᶠ x in f ⊓ 𝓟 s, p x) ↔ ∀ᶠ x in f, x ∈ s → p x :=
mem_inf_principal
#align filter.eventually_inf_principal Filter.eventually_inf_principal
/-! ### Frequently -/
/-- `f.Frequently p` or `∃ᶠ x in f, p x` mean that `{x | ¬p x} ∉ f`. E.g., `∃ᶠ x in atTop, p x`
means that there exist arbitrarily large `x` for which `p` holds true. -/
protected def Frequently (p : α → Prop) (f : Filter α) : Prop :=
¬∀ᶠ x in f, ¬p x
#align filter.frequently Filter.Frequently
@[inherit_doc Filter.Frequently]
notation3 "∃ᶠ "(...)" in "f", "r:(scoped p => Filter.Frequently p f) => r
theorem Eventually.frequently {f : Filter α} [NeBot f] {p : α → Prop} (h : ∀ᶠ x in f, p x) :
∃ᶠ x in f, p x :=
compl_not_mem h
#align filter.eventually.frequently Filter.Eventually.frequently
theorem frequently_of_forall {f : Filter α} [NeBot f] {p : α → Prop} (h : ∀ x, p x) :
∃ᶠ x in f, p x :=
Eventually.frequently (eventually_of_forall h)
#align filter.frequently_of_forall Filter.frequently_of_forall
theorem Frequently.mp {p q : α → Prop} {f : Filter α} (h : ∃ᶠ x in f, p x)
(hpq : ∀ᶠ x in f, p x → q x) : ∃ᶠ x in f, q x :=
mt (fun hq => hq.mp <| hpq.mono fun _ => mt) h
#align filter.frequently.mp Filter.Frequently.mp
theorem Frequently.filter_mono {p : α → Prop} {f g : Filter α} (h : ∃ᶠ x in f, p x) (hle : f ≤ g) :
∃ᶠ x in g, p x :=
mt (fun h' => h'.filter_mono hle) h
#align filter.frequently.filter_mono Filter.Frequently.filter_mono
theorem Frequently.mono {p q : α → Prop} {f : Filter α} (h : ∃ᶠ x in f, p x)
(hpq : ∀ x, p x → q x) : ∃ᶠ x in f, q x :=
h.mp (eventually_of_forall hpq)
#align filter.frequently.mono Filter.Frequently.mono
theorem Frequently.and_eventually {p q : α → Prop} {f : Filter α} (hp : ∃ᶠ x in f, p x)
(hq : ∀ᶠ x in f, q x) : ∃ᶠ x in f, p x ∧ q x := by
refine mt (fun h => hq.mp <| h.mono ?_) hp
exact fun x hpq hq hp => hpq ⟨hp, hq⟩
#align filter.frequently.and_eventually Filter.Frequently.and_eventually
theorem Eventually.and_frequently {p q : α → Prop} {f : Filter α} (hp : ∀ᶠ x in f, p x)
(hq : ∃ᶠ x in f, q x) : ∃ᶠ x in f, p x ∧ q x := by
simpa only [and_comm] using hq.and_eventually hp
#align filter.eventually.and_frequently Filter.Eventually.and_frequently
theorem Frequently.exists {p : α → Prop} {f : Filter α} (hp : ∃ᶠ x in f, p x) : ∃ x, p x := by
by_contra H
replace H : ∀ᶠ x in f, ¬p x := eventually_of_forall (not_exists.1 H)
exact hp H
#align filter.frequently.exists Filter.Frequently.exists
theorem Eventually.exists {p : α → Prop} {f : Filter α} [NeBot f] (hp : ∀ᶠ x in f, p x) :
∃ x, p x :=
hp.frequently.exists
#align filter.eventually.exists Filter.Eventually.exists
lemma frequently_iff_neBot {p : α → Prop} : (∃ᶠ x in l, p x) ↔ NeBot (l ⊓ 𝓟 {x | p x}) := by
rw [neBot_iff, Ne, inf_principal_eq_bot]; rfl
lemma frequently_mem_iff_neBot {s : Set α} : (∃ᶠ x in l, x ∈ s) ↔ NeBot (l ⊓ 𝓟 s) :=
frequently_iff_neBot
theorem frequently_iff_forall_eventually_exists_and {p : α → Prop} {f : Filter α} :
(∃ᶠ x in f, p x) ↔ ∀ {q : α → Prop}, (∀ᶠ x in f, q x) → ∃ x, p x ∧ q x :=
⟨fun hp q hq => (hp.and_eventually hq).exists, fun H hp => by
simpa only [and_not_self_iff, exists_false] using H hp⟩
#align filter.frequently_iff_forall_eventually_exists_and Filter.frequently_iff_forall_eventually_exists_and
theorem frequently_iff {f : Filter α} {P : α → Prop} :
(∃ᶠ x in f, P x) ↔ ∀ {U}, U ∈ f → ∃ x ∈ U, P x := by
simp only [frequently_iff_forall_eventually_exists_and, @and_comm (P _)]
rfl
#align filter.frequently_iff Filter.frequently_iff
@[simp]
theorem not_eventually {p : α → Prop} {f : Filter α} : (¬∀ᶠ x in f, p x) ↔ ∃ᶠ x in f, ¬p x := by
simp [Filter.Frequently]
#align filter.not_eventually Filter.not_eventually
@[simp]
theorem not_frequently {p : α → Prop} {f : Filter α} : (¬∃ᶠ x in f, p x) ↔ ∀ᶠ x in f, ¬p x := by
simp only [Filter.Frequently, not_not]
#align filter.not_frequently Filter.not_frequently
@[simp]
theorem frequently_true_iff_neBot (f : Filter α) : (∃ᶠ _ in f, True) ↔ NeBot f := by
simp [frequently_iff_neBot]
#align filter.frequently_true_iff_ne_bot Filter.frequently_true_iff_neBot
@[simp]
theorem frequently_false (f : Filter α) : ¬∃ᶠ _ in f, False := by simp
#align filter.frequently_false Filter.frequently_false
@[simp]
theorem frequently_const {f : Filter α} [NeBot f] {p : Prop} : (∃ᶠ _ in f, p) ↔ p := by
by_cases p <;> simp [*]
#align filter.frequently_const Filter.frequently_const
@[simp]
theorem frequently_or_distrib {f : Filter α} {p q : α → Prop} :
(∃ᶠ x in f, p x ∨ q x) ↔ (∃ᶠ x in f, p x) ∨ ∃ᶠ x in f, q x := by
simp only [Filter.Frequently, ← not_and_or, not_or, eventually_and]
#align filter.frequently_or_distrib Filter.frequently_or_distrib
theorem frequently_or_distrib_left {f : Filter α} [NeBot f] {p : Prop} {q : α → Prop} :
(∃ᶠ x in f, p ∨ q x) ↔ p ∨ ∃ᶠ x in f, q x := by simp
#align filter.frequently_or_distrib_left Filter.frequently_or_distrib_left
theorem frequently_or_distrib_right {f : Filter α} [NeBot f] {p : α → Prop} {q : Prop} :
(∃ᶠ x in f, p x ∨ q) ↔ (∃ᶠ x in f, p x) ∨ q := by simp
#align filter.frequently_or_distrib_right Filter.frequently_or_distrib_right
theorem frequently_imp_distrib {f : Filter α} {p q : α → Prop} :
(∃ᶠ x in f, p x → q x) ↔ (∀ᶠ x in f, p x) → ∃ᶠ x in f, q x := by
simp [imp_iff_not_or]
#align filter.frequently_imp_distrib Filter.frequently_imp_distrib
theorem frequently_imp_distrib_left {f : Filter α} [NeBot f] {p : Prop} {q : α → Prop} :
(∃ᶠ x in f, p → q x) ↔ p → ∃ᶠ x in f, q x := by simp [frequently_imp_distrib]
#align filter.frequently_imp_distrib_left Filter.frequently_imp_distrib_left
theorem frequently_imp_distrib_right {f : Filter α} [NeBot f] {p : α → Prop} {q : Prop} :
(∃ᶠ x in f, p x → q) ↔ (∀ᶠ x in f, p x) → q := by
set_option tactic.skipAssignedInstances false in simp [frequently_imp_distrib]
#align filter.frequently_imp_distrib_right Filter.frequently_imp_distrib_right
theorem eventually_imp_distrib_right {f : Filter α} {p : α → Prop} {q : Prop} :
(∀ᶠ x in f, p x → q) ↔ (∃ᶠ x in f, p x) → q := by
simp only [imp_iff_not_or, eventually_or_distrib_right, not_frequently]
#align filter.eventually_imp_distrib_right Filter.eventually_imp_distrib_right
@[simp]
theorem frequently_and_distrib_left {f : Filter α} {p : Prop} {q : α → Prop} :
(∃ᶠ x in f, p ∧ q x) ↔ p ∧ ∃ᶠ x in f, q x := by
simp only [Filter.Frequently, not_and, eventually_imp_distrib_left, Classical.not_imp]
#align filter.frequently_and_distrib_left Filter.frequently_and_distrib_left
@[simp]
theorem frequently_and_distrib_right {f : Filter α} {p : α → Prop} {q : Prop} :
(∃ᶠ x in f, p x ∧ q) ↔ (∃ᶠ x in f, p x) ∧ q := by
simp only [@and_comm _ q, frequently_and_distrib_left]
#align filter.frequently_and_distrib_right Filter.frequently_and_distrib_right
@[simp]
theorem frequently_bot {p : α → Prop} : ¬∃ᶠ x in ⊥, p x := by simp
#align filter.frequently_bot Filter.frequently_bot
@[simp]
theorem frequently_top {p : α → Prop} : (∃ᶠ x in ⊤, p x) ↔ ∃ x, p x := by simp [Filter.Frequently]
#align filter.frequently_top Filter.frequently_top
@[simp]
theorem frequently_principal {a : Set α} {p : α → Prop} : (∃ᶠ x in 𝓟 a, p x) ↔ ∃ x ∈ a, p x := by
simp [Filter.Frequently, not_forall]
#align filter.frequently_principal Filter.frequently_principal
theorem frequently_inf_principal {f : Filter α} {s : Set α} {p : α → Prop} :
(∃ᶠ x in f ⊓ 𝓟 s, p x) ↔ ∃ᶠ x in f, x ∈ s ∧ p x := by
simp only [Filter.Frequently, eventually_inf_principal, not_and]
alias ⟨Frequently.of_inf_principal, Frequently.inf_principal⟩ := frequently_inf_principal
theorem frequently_sup {p : α → Prop} {f g : Filter α} :
(∃ᶠ x in f ⊔ g, p x) ↔ (∃ᶠ x in f, p x) ∨ ∃ᶠ x in g, p x := by
simp only [Filter.Frequently, eventually_sup, not_and_or]
#align filter.frequently_sup Filter.frequently_sup
@[simp]
theorem frequently_sSup {p : α → Prop} {fs : Set (Filter α)} :
(∃ᶠ x in sSup fs, p x) ↔ ∃ f ∈ fs, ∃ᶠ x in f, p x := by
simp only [Filter.Frequently, not_forall, eventually_sSup, exists_prop]
#align filter.frequently_Sup Filter.frequently_sSup
@[simp]
theorem frequently_iSup {p : α → Prop} {fs : β → Filter α} :
(∃ᶠ x in ⨆ b, fs b, p x) ↔ ∃ b, ∃ᶠ x in fs b, p x := by
simp only [Filter.Frequently, eventually_iSup, not_forall]
#align filter.frequently_supr Filter.frequently_iSup
theorem Eventually.choice {r : α → β → Prop} {l : Filter α} [l.NeBot] (h : ∀ᶠ x in l, ∃ y, r x y) :
∃ f : α → β, ∀ᶠ x in l, r x (f x) := by
haveI : Nonempty β := let ⟨_, hx⟩ := h.exists; hx.nonempty
choose! f hf using fun x (hx : ∃ y, r x y) => hx
exact ⟨f, h.mono hf⟩
#align filter.eventually.choice Filter.Eventually.choice
/-!
### Relation “eventually equal”
-/
/-- Two functions `f` and `g` are *eventually equal* along a filter `l` if the set of `x` such that
`f x = g x` belongs to `l`. -/
def EventuallyEq (l : Filter α) (f g : α → β) : Prop :=
∀ᶠ x in l, f x = g x
#align filter.eventually_eq Filter.EventuallyEq
@[inherit_doc]
notation:50 f " =ᶠ[" l:50 "] " g:50 => EventuallyEq l f g
theorem EventuallyEq.eventually {l : Filter α} {f g : α → β} (h : f =ᶠ[l] g) :
∀ᶠ x in l, f x = g x :=
h
#align filter.eventually_eq.eventually Filter.EventuallyEq.eventually
theorem EventuallyEq.rw {l : Filter α} {f g : α → β} (h : f =ᶠ[l] g) (p : α → β → Prop)
(hf : ∀ᶠ x in l, p x (f x)) : ∀ᶠ x in l, p x (g x) :=
hf.congr <| h.mono fun _ hx => hx ▸ Iff.rfl
#align filter.eventually_eq.rw Filter.EventuallyEq.rw
theorem eventuallyEq_set {s t : Set α} {l : Filter α} : s =ᶠ[l] t ↔ ∀ᶠ x in l, x ∈ s ↔ x ∈ t :=
eventually_congr <| eventually_of_forall fun _ ↦ eq_iff_iff
#align filter.eventually_eq_set Filter.eventuallyEq_set
alias ⟨EventuallyEq.mem_iff, Eventually.set_eq⟩ := eventuallyEq_set
#align filter.eventually_eq.mem_iff Filter.EventuallyEq.mem_iff
#align filter.eventually.set_eq Filter.Eventually.set_eq
@[simp]
theorem eventuallyEq_univ {s : Set α} {l : Filter α} : s =ᶠ[l] univ ↔ s ∈ l := by
simp [eventuallyEq_set]
#align filter.eventually_eq_univ Filter.eventuallyEq_univ
theorem EventuallyEq.exists_mem {l : Filter α} {f g : α → β} (h : f =ᶠ[l] g) :
∃ s ∈ l, EqOn f g s :=
Eventually.exists_mem h
#align filter.eventually_eq.exists_mem Filter.EventuallyEq.exists_mem
theorem eventuallyEq_of_mem {l : Filter α} {f g : α → β} {s : Set α} (hs : s ∈ l) (h : EqOn f g s) :
f =ᶠ[l] g :=
eventually_of_mem hs h
#align filter.eventually_eq_of_mem Filter.eventuallyEq_of_mem
theorem eventuallyEq_iff_exists_mem {l : Filter α} {f g : α → β} :
f =ᶠ[l] g ↔ ∃ s ∈ l, EqOn f g s :=
eventually_iff_exists_mem
#align filter.eventually_eq_iff_exists_mem Filter.eventuallyEq_iff_exists_mem
theorem EventuallyEq.filter_mono {l l' : Filter α} {f g : α → β} (h₁ : f =ᶠ[l] g) (h₂ : l' ≤ l) :
f =ᶠ[l'] g :=
h₂ h₁
#align filter.eventually_eq.filter_mono Filter.EventuallyEq.filter_mono
@[refl, simp]
theorem EventuallyEq.refl (l : Filter α) (f : α → β) : f =ᶠ[l] f :=
eventually_of_forall fun _ => rfl
#align filter.eventually_eq.refl Filter.EventuallyEq.refl
protected theorem EventuallyEq.rfl {l : Filter α} {f : α → β} : f =ᶠ[l] f :=
EventuallyEq.refl l f
#align filter.eventually_eq.rfl Filter.EventuallyEq.rfl
@[symm]
theorem EventuallyEq.symm {f g : α → β} {l : Filter α} (H : f =ᶠ[l] g) : g =ᶠ[l] f :=
H.mono fun _ => Eq.symm
#align filter.eventually_eq.symm Filter.EventuallyEq.symm
@[trans]
theorem EventuallyEq.trans {l : Filter α} {f g h : α → β} (H₁ : f =ᶠ[l] g) (H₂ : g =ᶠ[l] h) :
f =ᶠ[l] h :=
H₂.rw (fun x y => f x = y) H₁
#align filter.eventually_eq.trans Filter.EventuallyEq.trans
instance : Trans ((· =ᶠ[l] ·) : (α → β) → (α → β) → Prop) (· =ᶠ[l] ·) (· =ᶠ[l] ·) where
trans := EventuallyEq.trans
theorem EventuallyEq.prod_mk {l} {f f' : α → β} (hf : f =ᶠ[l] f') {g g' : α → γ} (hg : g =ᶠ[l] g') :
(fun x => (f x, g x)) =ᶠ[l] fun x => (f' x, g' x) :=
hf.mp <|
hg.mono <| by
intros
simp only [*]
#align filter.eventually_eq.prod_mk Filter.EventuallyEq.prod_mk
-- See `EventuallyEq.comp_tendsto` further below for a similar statement w.r.t.
-- composition on the right.
theorem EventuallyEq.fun_comp {f g : α → β} {l : Filter α} (H : f =ᶠ[l] g) (h : β → γ) :
h ∘ f =ᶠ[l] h ∘ g :=
H.mono fun _ hx => congr_arg h hx
#align filter.eventually_eq.fun_comp Filter.EventuallyEq.fun_comp
theorem EventuallyEq.comp₂ {δ} {f f' : α → β} {g g' : α → γ} {l} (Hf : f =ᶠ[l] f') (h : β → γ → δ)
(Hg : g =ᶠ[l] g') : (fun x => h (f x) (g x)) =ᶠ[l] fun x => h (f' x) (g' x) :=
(Hf.prod_mk Hg).fun_comp (uncurry h)
#align filter.eventually_eq.comp₂ Filter.EventuallyEq.comp₂
@[to_additive]
theorem EventuallyEq.mul [Mul β] {f f' g g' : α → β} {l : Filter α} (h : f =ᶠ[l] g)
(h' : f' =ᶠ[l] g') : (fun x => f x * f' x) =ᶠ[l] fun x => g x * g' x :=
h.comp₂ (· * ·) h'
#align filter.eventually_eq.mul Filter.EventuallyEq.mul
#align filter.eventually_eq.add Filter.EventuallyEq.add
@[to_additive const_smul]
theorem EventuallyEq.pow_const {γ} [Pow β γ] {f g : α → β} {l : Filter α} (h : f =ᶠ[l] g) (c : γ):
(fun x => f x ^ c) =ᶠ[l] fun x => g x ^ c :=
h.fun_comp (· ^ c)
#align filter.eventually_eq.const_smul Filter.EventuallyEq.const_smul
@[to_additive]
theorem EventuallyEq.inv [Inv β] {f g : α → β} {l : Filter α} (h : f =ᶠ[l] g) :
(fun x => (f x)⁻¹) =ᶠ[l] fun x => (g x)⁻¹ :=
h.fun_comp Inv.inv
#align filter.eventually_eq.inv Filter.EventuallyEq.inv
#align filter.eventually_eq.neg Filter.EventuallyEq.neg
@[to_additive]
theorem EventuallyEq.div [Div β] {f f' g g' : α → β} {l : Filter α} (h : f =ᶠ[l] g)
(h' : f' =ᶠ[l] g') : (fun x => f x / f' x) =ᶠ[l] fun x => g x / g' x :=
h.comp₂ (· / ·) h'
#align filter.eventually_eq.div Filter.EventuallyEq.div
#align filter.eventually_eq.sub Filter.EventuallyEq.sub
attribute [to_additive] EventuallyEq.const_smul
#align filter.eventually_eq.const_vadd Filter.EventuallyEq.const_vadd
@[to_additive]
theorem EventuallyEq.smul {𝕜} [SMul 𝕜 β] {l : Filter α} {f f' : α → 𝕜} {g g' : α → β}
(hf : f =ᶠ[l] f') (hg : g =ᶠ[l] g') : (fun x => f x • g x) =ᶠ[l] fun x => f' x • g' x :=
hf.comp₂ (· • ·) hg
#align filter.eventually_eq.smul Filter.EventuallyEq.smul
#align filter.eventually_eq.vadd Filter.EventuallyEq.vadd
theorem EventuallyEq.sup [Sup β] {l : Filter α} {f f' g g' : α → β} (hf : f =ᶠ[l] f')
(hg : g =ᶠ[l] g') : (fun x => f x ⊔ g x) =ᶠ[l] fun x => f' x ⊔ g' x :=
hf.comp₂ (· ⊔ ·) hg
#align filter.eventually_eq.sup Filter.EventuallyEq.sup
theorem EventuallyEq.inf [Inf β] {l : Filter α} {f f' g g' : α → β} (hf : f =ᶠ[l] f')
(hg : g =ᶠ[l] g') : (fun x => f x ⊓ g x) =ᶠ[l] fun x => f' x ⊓ g' x :=
hf.comp₂ (· ⊓ ·) hg
#align filter.eventually_eq.inf Filter.EventuallyEq.inf
theorem EventuallyEq.preimage {l : Filter α} {f g : α → β} (h : f =ᶠ[l] g) (s : Set β) :
f ⁻¹' s =ᶠ[l] g ⁻¹' s :=
h.fun_comp s
#align filter.eventually_eq.preimage Filter.EventuallyEq.preimage
theorem EventuallyEq.inter {s t s' t' : Set α} {l : Filter α} (h : s =ᶠ[l] t) (h' : s' =ᶠ[l] t') :
(s ∩ s' : Set α) =ᶠ[l] (t ∩ t' : Set α) :=
h.comp₂ (· ∧ ·) h'
#align filter.eventually_eq.inter Filter.EventuallyEq.inter
theorem EventuallyEq.union {s t s' t' : Set α} {l : Filter α} (h : s =ᶠ[l] t) (h' : s' =ᶠ[l] t') :
(s ∪ s' : Set α) =ᶠ[l] (t ∪ t' : Set α) :=
h.comp₂ (· ∨ ·) h'
#align filter.eventually_eq.union Filter.EventuallyEq.union
theorem EventuallyEq.compl {s t : Set α} {l : Filter α} (h : s =ᶠ[l] t) :
(sᶜ : Set α) =ᶠ[l] (tᶜ : Set α) :=
h.fun_comp Not
#align filter.eventually_eq.compl Filter.EventuallyEq.compl
theorem EventuallyEq.diff {s t s' t' : Set α} {l : Filter α} (h : s =ᶠ[l] t) (h' : s' =ᶠ[l] t') :
(s \ s' : Set α) =ᶠ[l] (t \ t' : Set α) :=
h.inter h'.compl
#align filter.eventually_eq.diff Filter.EventuallyEq.diff
theorem eventuallyEq_empty {s : Set α} {l : Filter α} : s =ᶠ[l] (∅ : Set α) ↔ ∀ᶠ x in l, x ∉ s :=
eventuallyEq_set.trans <| by simp
#align filter.eventually_eq_empty Filter.eventuallyEq_empty
theorem inter_eventuallyEq_left {s t : Set α} {l : Filter α} :
(s ∩ t : Set α) =ᶠ[l] s ↔ ∀ᶠ x in l, x ∈ s → x ∈ t := by
simp only [eventuallyEq_set, mem_inter_iff, and_iff_left_iff_imp]
#align filter.inter_eventually_eq_left Filter.inter_eventuallyEq_left
theorem inter_eventuallyEq_right {s t : Set α} {l : Filter α} :
(s ∩ t : Set α) =ᶠ[l] t ↔ ∀ᶠ x in l, x ∈ t → x ∈ s := by
rw [inter_comm, inter_eventuallyEq_left]
#align filter.inter_eventually_eq_right Filter.inter_eventuallyEq_right
@[simp]
theorem eventuallyEq_principal {s : Set α} {f g : α → β} : f =ᶠ[𝓟 s] g ↔ EqOn f g s :=
Iff.rfl
#align filter.eventually_eq_principal Filter.eventuallyEq_principal
theorem eventuallyEq_inf_principal_iff {F : Filter α} {s : Set α} {f g : α → β} :
f =ᶠ[F ⊓ 𝓟 s] g ↔ ∀ᶠ x in F, x ∈ s → f x = g x :=
eventually_inf_principal
#align filter.eventually_eq_inf_principal_iff Filter.eventuallyEq_inf_principal_iff
theorem EventuallyEq.sub_eq [AddGroup β] {f g : α → β} {l : Filter α} (h : f =ᶠ[l] g) :
f - g =ᶠ[l] 0 := by simpa using ((EventuallyEq.refl l f).sub h).symm
#align filter.eventually_eq.sub_eq Filter.EventuallyEq.sub_eq
theorem eventuallyEq_iff_sub [AddGroup β] {f g : α → β} {l : Filter α} :
f =ᶠ[l] g ↔ f - g =ᶠ[l] 0 :=
⟨fun h => h.sub_eq, fun h => by simpa using h.add (EventuallyEq.refl l g)⟩
#align filter.eventually_eq_iff_sub Filter.eventuallyEq_iff_sub
section LE
variable [LE β] {l : Filter α}
/-- A function `f` is eventually less than or equal to a function `g` at a filter `l`. -/
def EventuallyLE (l : Filter α) (f g : α → β) : Prop :=
∀ᶠ x in l, f x ≤ g x
#align filter.eventually_le Filter.EventuallyLE
@[inherit_doc]
notation:50 f " ≤ᶠ[" l:50 "] " g:50 => EventuallyLE l f g
theorem EventuallyLE.congr {f f' g g' : α → β} (H : f ≤ᶠ[l] g) (hf : f =ᶠ[l] f') (hg : g =ᶠ[l] g') :
f' ≤ᶠ[l] g' :=
H.mp <| hg.mp <| hf.mono fun x hf hg H => by rwa [hf, hg] at H
#align filter.eventually_le.congr Filter.EventuallyLE.congr
theorem eventuallyLE_congr {f f' g g' : α → β} (hf : f =ᶠ[l] f') (hg : g =ᶠ[l] g') :
f ≤ᶠ[l] g ↔ f' ≤ᶠ[l] g' :=
⟨fun H => H.congr hf hg, fun H => H.congr hf.symm hg.symm⟩
#align filter.eventually_le_congr Filter.eventuallyLE_congr
end LE
section Preorder
variable [Preorder β] {l : Filter α} {f g h : α → β}
theorem EventuallyEq.le (h : f =ᶠ[l] g) : f ≤ᶠ[l] g :=
h.mono fun _ => le_of_eq
#align filter.eventually_eq.le Filter.EventuallyEq.le
@[refl]
theorem EventuallyLE.refl (l : Filter α) (f : α → β) : f ≤ᶠ[l] f :=
EventuallyEq.rfl.le
#align filter.eventually_le.refl Filter.EventuallyLE.refl
theorem EventuallyLE.rfl : f ≤ᶠ[l] f :=
EventuallyLE.refl l f
#align filter.eventually_le.rfl Filter.EventuallyLE.rfl
@[trans]
theorem EventuallyLE.trans (H₁ : f ≤ᶠ[l] g) (H₂ : g ≤ᶠ[l] h) : f ≤ᶠ[l] h :=
H₂.mp <| H₁.mono fun _ => le_trans
#align filter.eventually_le.trans Filter.EventuallyLE.trans
instance : Trans ((· ≤ᶠ[l] ·) : (α → β) → (α → β) → Prop) (· ≤ᶠ[l] ·) (· ≤ᶠ[l] ·) where
trans := EventuallyLE.trans
@[trans]
theorem EventuallyEq.trans_le (H₁ : f =ᶠ[l] g) (H₂ : g ≤ᶠ[l] h) : f ≤ᶠ[l] h :=
H₁.le.trans H₂
#align filter.eventually_eq.trans_le Filter.EventuallyEq.trans_le
instance : Trans ((· =ᶠ[l] ·) : (α → β) → (α → β) → Prop) (· ≤ᶠ[l] ·) (· ≤ᶠ[l] ·) where
trans := EventuallyEq.trans_le
@[trans]
theorem EventuallyLE.trans_eq (H₁ : f ≤ᶠ[l] g) (H₂ : g =ᶠ[l] h) : f ≤ᶠ[l] h :=
H₁.trans H₂.le
#align filter.eventually_le.trans_eq Filter.EventuallyLE.trans_eq
instance : Trans ((· ≤ᶠ[l] ·) : (α → β) → (α → β) → Prop) (· =ᶠ[l] ·) (· ≤ᶠ[l] ·) where
trans := EventuallyLE.trans_eq
end Preorder
theorem EventuallyLE.antisymm [PartialOrder β] {l : Filter α} {f g : α → β} (h₁ : f ≤ᶠ[l] g)
(h₂ : g ≤ᶠ[l] f) : f =ᶠ[l] g :=
h₂.mp <| h₁.mono fun _ => le_antisymm
#align filter.eventually_le.antisymm Filter.EventuallyLE.antisymm
theorem eventuallyLE_antisymm_iff [PartialOrder β] {l : Filter α} {f g : α → β} :
f =ᶠ[l] g ↔ f ≤ᶠ[l] g ∧ g ≤ᶠ[l] f := by
simp only [EventuallyEq, EventuallyLE, le_antisymm_iff, eventually_and]
#align filter.eventually_le_antisymm_iff Filter.eventuallyLE_antisymm_iff
theorem EventuallyLE.le_iff_eq [PartialOrder β] {l : Filter α} {f g : α → β} (h : f ≤ᶠ[l] g) :
g ≤ᶠ[l] f ↔ g =ᶠ[l] f :=
⟨fun h' => h'.antisymm h, EventuallyEq.le⟩
#align filter.eventually_le.le_iff_eq Filter.EventuallyLE.le_iff_eq
theorem Eventually.ne_of_lt [Preorder β] {l : Filter α} {f g : α → β} (h : ∀ᶠ x in l, f x < g x) :
∀ᶠ x in l, f x ≠ g x :=
h.mono fun _ hx => hx.ne
#align filter.eventually.ne_of_lt Filter.Eventually.ne_of_lt
theorem Eventually.ne_top_of_lt [PartialOrder β] [OrderTop β] {l : Filter α} {f g : α → β}
(h : ∀ᶠ x in l, f x < g x) : ∀ᶠ x in l, f x ≠ ⊤ :=
h.mono fun _ hx => hx.ne_top
#align filter.eventually.ne_top_of_lt Filter.Eventually.ne_top_of_lt
theorem Eventually.lt_top_of_ne [PartialOrder β] [OrderTop β] {l : Filter α} {f : α → β}
(h : ∀ᶠ x in l, f x ≠ ⊤) : ∀ᶠ x in l, f x < ⊤ :=
h.mono fun _ hx => hx.lt_top
#align filter.eventually.lt_top_of_ne Filter.Eventually.lt_top_of_ne
theorem Eventually.lt_top_iff_ne_top [PartialOrder β] [OrderTop β] {l : Filter α} {f : α → β} :
(∀ᶠ x in l, f x < ⊤) ↔ ∀ᶠ x in l, f x ≠ ⊤ :=
⟨Eventually.ne_of_lt, Eventually.lt_top_of_ne⟩
#align filter.eventually.lt_top_iff_ne_top Filter.Eventually.lt_top_iff_ne_top
@[mono]
theorem EventuallyLE.inter {s t s' t' : Set α} {l : Filter α} (h : s ≤ᶠ[l] t) (h' : s' ≤ᶠ[l] t') :
(s ∩ s' : Set α) ≤ᶠ[l] (t ∩ t' : Set α) :=
h'.mp <| h.mono fun _ => And.imp
#align filter.eventually_le.inter Filter.EventuallyLE.inter
@[mono]
theorem EventuallyLE.union {s t s' t' : Set α} {l : Filter α} (h : s ≤ᶠ[l] t) (h' : s' ≤ᶠ[l] t') :
(s ∪ s' : Set α) ≤ᶠ[l] (t ∪ t' : Set α) :=
h'.mp <| h.mono fun _ => Or.imp
#align filter.eventually_le.union Filter.EventuallyLE.union
protected lemma EventuallyLE.iUnion [Finite ι] {s t : ι → Set α}
(h : ∀ i, s i ≤ᶠ[l] t i) : (⋃ i, s i) ≤ᶠ[l] ⋃ i, t i :=
(eventually_all.2 h).mono fun _x hx hx' ↦
let ⟨i, hi⟩ := mem_iUnion.1 hx'; mem_iUnion.2 ⟨i, hx i hi⟩
protected lemma EventuallyEq.iUnion [Finite ι] {s t : ι → Set α}
(h : ∀ i, s i =ᶠ[l] t i) : (⋃ i, s i) =ᶠ[l] ⋃ i, t i :=
(EventuallyLE.iUnion fun i ↦ (h i).le).antisymm <| .iUnion fun i ↦ (h i).symm.le
protected lemma EventuallyLE.iInter [Finite ι] {s t : ι → Set α}
(h : ∀ i, s i ≤ᶠ[l] t i) : (⋂ i, s i) ≤ᶠ[l] ⋂ i, t i :=
(eventually_all.2 h).mono fun _x hx hx' ↦ mem_iInter.2 fun i ↦ hx i (mem_iInter.1 hx' i)
protected lemma EventuallyEq.iInter [Finite ι] {s t : ι → Set α}
(h : ∀ i, s i =ᶠ[l] t i) : (⋂ i, s i) =ᶠ[l] ⋂ i, t i :=
(EventuallyLE.iInter fun i ↦ (h i).le).antisymm <| .iInter fun i ↦ (h i).symm.le
lemma _root_.Set.Finite.eventuallyLE_iUnion {ι : Type*} {s : Set ι} (hs : s.Finite)
{f g : ι → Set α} (hle : ∀ i ∈ s, f i ≤ᶠ[l] g i) : (⋃ i ∈ s, f i) ≤ᶠ[l] (⋃ i ∈ s, g i) := by
have := hs.to_subtype
rw [biUnion_eq_iUnion, biUnion_eq_iUnion]
exact .iUnion fun i ↦ hle i.1 i.2
alias EventuallyLE.biUnion := Set.Finite.eventuallyLE_iUnion
lemma _root_.Set.Finite.eventuallyEq_iUnion {ι : Type*} {s : Set ι} (hs : s.Finite)
{f g : ι → Set α} (heq : ∀ i ∈ s, f i =ᶠ[l] g i) : (⋃ i ∈ s, f i) =ᶠ[l] (⋃ i ∈ s, g i) :=
(EventuallyLE.biUnion hs fun i hi ↦ (heq i hi).le).antisymm <|
.biUnion hs fun i hi ↦ (heq i hi).symm.le
alias EventuallyEq.biUnion := Set.Finite.eventuallyEq_iUnion
lemma _root_.Set.Finite.eventuallyLE_iInter {ι : Type*} {s : Set ι} (hs : s.Finite)
{f g : ι → Set α} (hle : ∀ i ∈ s, f i ≤ᶠ[l] g i) : (⋂ i ∈ s, f i) ≤ᶠ[l] (⋂ i ∈ s, g i) := by
have := hs.to_subtype
rw [biInter_eq_iInter, biInter_eq_iInter]
exact .iInter fun i ↦ hle i.1 i.2
alias EventuallyLE.biInter := Set.Finite.eventuallyLE_iInter
lemma _root_.Set.Finite.eventuallyEq_iInter {ι : Type*} {s : Set ι} (hs : s.Finite)
{f g : ι → Set α} (heq : ∀ i ∈ s, f i =ᶠ[l] g i) : (⋂ i ∈ s, f i) =ᶠ[l] (⋂ i ∈ s, g i) :=
(EventuallyLE.biInter hs fun i hi ↦ (heq i hi).le).antisymm <|
.biInter hs fun i hi ↦ (heq i hi).symm.le
alias EventuallyEq.biInter := Set.Finite.eventuallyEq_iInter
lemma _root_.Finset.eventuallyLE_iUnion {ι : Type*} (s : Finset ι) {f g : ι → Set α}
(hle : ∀ i ∈ s, f i ≤ᶠ[l] g i) : (⋃ i ∈ s, f i) ≤ᶠ[l] (⋃ i ∈ s, g i) :=
.biUnion s.finite_toSet hle
lemma _root_.Finset.eventuallyEq_iUnion {ι : Type*} (s : Finset ι) {f g : ι → Set α}
(heq : ∀ i ∈ s, f i =ᶠ[l] g i) : (⋃ i ∈ s, f i) =ᶠ[l] (⋃ i ∈ s, g i) :=
.biUnion s.finite_toSet heq
lemma _root_.Finset.eventuallyLE_iInter {ι : Type*} (s : Finset ι) {f g : ι → Set α}
(hle : ∀ i ∈ s, f i ≤ᶠ[l] g i) : (⋂ i ∈ s, f i) ≤ᶠ[l] (⋂ i ∈ s, g i) :=
.biInter s.finite_toSet hle
lemma _root_.Finset.eventuallyEq_iInter {ι : Type*} (s : Finset ι) {f g : ι → Set α}
(heq : ∀ i ∈ s, f i =ᶠ[l] g i) : (⋂ i ∈ s, f i) =ᶠ[l] (⋂ i ∈ s, g i) :=
.biInter s.finite_toSet heq
@[mono]
theorem EventuallyLE.compl {s t : Set α} {l : Filter α} (h : s ≤ᶠ[l] t) :
(tᶜ : Set α) ≤ᶠ[l] (sᶜ : Set α) :=
h.mono fun _ => mt
#align filter.eventually_le.compl Filter.EventuallyLE.compl
@[mono]
theorem EventuallyLE.diff {s t s' t' : Set α} {l : Filter α} (h : s ≤ᶠ[l] t) (h' : t' ≤ᶠ[l] s') :
(s \ s' : Set α) ≤ᶠ[l] (t \ t' : Set α) :=
h.inter h'.compl
#align filter.eventually_le.diff Filter.EventuallyLE.diff
theorem set_eventuallyLE_iff_mem_inf_principal {s t : Set α} {l : Filter α} :
s ≤ᶠ[l] t ↔ t ∈ l ⊓ 𝓟 s :=
eventually_inf_principal.symm
#align filter.set_eventually_le_iff_mem_inf_principal Filter.set_eventuallyLE_iff_mem_inf_principal
theorem set_eventuallyLE_iff_inf_principal_le {s t : Set α} {l : Filter α} :
s ≤ᶠ[l] t ↔ l ⊓ 𝓟 s ≤ l ⊓ 𝓟 t :=
set_eventuallyLE_iff_mem_inf_principal.trans <| by
simp only [le_inf_iff, inf_le_left, true_and_iff, le_principal_iff]
#align filter.set_eventually_le_iff_inf_principal_le Filter.set_eventuallyLE_iff_inf_principal_le
theorem set_eventuallyEq_iff_inf_principal {s t : Set α} {l : Filter α} :
s =ᶠ[l] t ↔ l ⊓ 𝓟 s = l ⊓ 𝓟 t := by
simp only [eventuallyLE_antisymm_iff, le_antisymm_iff, set_eventuallyLE_iff_inf_principal_le]
#align filter.set_eventually_eq_iff_inf_principal Filter.set_eventuallyEq_iff_inf_principal
theorem EventuallyLE.mul_le_mul [MulZeroClass β] [PartialOrder β] [PosMulMono β] [MulPosMono β]
{l : Filter α} {f₁ f₂ g₁ g₂ : α → β} (hf : f₁ ≤ᶠ[l] f₂) (hg : g₁ ≤ᶠ[l] g₂) (hg₀ : 0 ≤ᶠ[l] g₁)
(hf₀ : 0 ≤ᶠ[l] f₂) : f₁ * g₁ ≤ᶠ[l] f₂ * g₂ := by
filter_upwards [hf, hg, hg₀, hf₀] with x using _root_.mul_le_mul
#align filter.eventually_le.mul_le_mul Filter.EventuallyLE.mul_le_mul
@[to_additive EventuallyLE.add_le_add]
theorem EventuallyLE.mul_le_mul' [Mul β] [Preorder β] [CovariantClass β β (· * ·) (· ≤ ·)]
[CovariantClass β β (swap (· * ·)) (· ≤ ·)] {l : Filter α} {f₁ f₂ g₁ g₂ : α → β}
(hf : f₁ ≤ᶠ[l] f₂) (hg : g₁ ≤ᶠ[l] g₂) : f₁ * g₁ ≤ᶠ[l] f₂ * g₂ := by
filter_upwards [hf, hg] with x hfx hgx using _root_.mul_le_mul' hfx hgx
#align filter.eventually_le.mul_le_mul' Filter.EventuallyLE.mul_le_mul'
#align filter.eventually_le.add_le_add Filter.EventuallyLE.add_le_add
theorem EventuallyLE.mul_nonneg [OrderedSemiring β] {l : Filter α} {f g : α → β} (hf : 0 ≤ᶠ[l] f)
(hg : 0 ≤ᶠ[l] g) : 0 ≤ᶠ[l] f * g := by filter_upwards [hf, hg] with x using _root_.mul_nonneg
#align filter.eventually_le.mul_nonneg Filter.EventuallyLE.mul_nonneg
theorem eventually_sub_nonneg [OrderedRing β] {l : Filter α} {f g : α → β} :
0 ≤ᶠ[l] g - f ↔ f ≤ᶠ[l] g :=
eventually_congr <| eventually_of_forall fun _ => sub_nonneg
#align filter.eventually_sub_nonneg Filter.eventually_sub_nonneg
theorem EventuallyLE.sup [SemilatticeSup β] {l : Filter α} {f₁ f₂ g₁ g₂ : α → β} (hf : f₁ ≤ᶠ[l] f₂)
(hg : g₁ ≤ᶠ[l] g₂) : f₁ ⊔ g₁ ≤ᶠ[l] f₂ ⊔ g₂ := by
filter_upwards [hf, hg] with x hfx hgx using sup_le_sup hfx hgx
#align filter.eventually_le.sup Filter.EventuallyLE.sup
theorem EventuallyLE.sup_le [SemilatticeSup β] {l : Filter α} {f g h : α → β} (hf : f ≤ᶠ[l] h)
(hg : g ≤ᶠ[l] h) : f ⊔ g ≤ᶠ[l] h := by
filter_upwards [hf, hg] with x hfx hgx using _root_.sup_le hfx hgx
#align filter.eventually_le.sup_le Filter.EventuallyLE.sup_le
theorem EventuallyLE.le_sup_of_le_left [SemilatticeSup β] {l : Filter α} {f g h : α → β}
(hf : h ≤ᶠ[l] f) : h ≤ᶠ[l] f ⊔ g :=
hf.mono fun _ => _root_.le_sup_of_le_left
#align filter.eventually_le.le_sup_of_le_left Filter.EventuallyLE.le_sup_of_le_left
theorem EventuallyLE.le_sup_of_le_right [SemilatticeSup β] {l : Filter α} {f g h : α → β}
(hg : h ≤ᶠ[l] g) : h ≤ᶠ[l] f ⊔ g :=
hg.mono fun _ => _root_.le_sup_of_le_right
#align filter.eventually_le.le_sup_of_le_right Filter.EventuallyLE.le_sup_of_le_right
theorem join_le {f : Filter (Filter α)} {l : Filter α} (h : ∀ᶠ m in f, m ≤ l) : join f ≤ l :=
fun _ hs => h.mono fun _ hm => hm hs
#align filter.join_le Filter.join_le
/-! ### Push-forwards, pull-backs, and the monad structure -/
section Map
/-- The forward map of a filter -/
def map (m : α → β) (f : Filter α) : Filter β where
sets := preimage m ⁻¹' f.sets
univ_sets := univ_mem
sets_of_superset hs st := mem_of_superset hs <| preimage_mono st
inter_sets hs ht := inter_mem hs ht
#align filter.map Filter.map
@[simp]
theorem map_principal {s : Set α} {f : α → β} : map f (𝓟 s) = 𝓟 (Set.image f s) :=
Filter.ext fun _ => image_subset_iff.symm
#align filter.map_principal Filter.map_principal
variable {f : Filter α} {m : α → β} {m' : β → γ} {s : Set α} {t : Set β}
@[simp]
theorem eventually_map {P : β → Prop} : (∀ᶠ b in map m f, P b) ↔ ∀ᶠ a in f, P (m a) :=
Iff.rfl
#align filter.eventually_map Filter.eventually_map
@[simp]
theorem frequently_map {P : β → Prop} : (∃ᶠ b in map m f, P b) ↔ ∃ᶠ a in f, P (m a) :=
Iff.rfl
#align filter.frequently_map Filter.frequently_map
@[simp]
theorem mem_map : t ∈ map m f ↔ m ⁻¹' t ∈ f :=
Iff.rfl
#align filter.mem_map Filter.mem_map
theorem mem_map' : t ∈ map m f ↔ { x | m x ∈ t } ∈ f :=
Iff.rfl
#align filter.mem_map' Filter.mem_map'
theorem image_mem_map (hs : s ∈ f) : m '' s ∈ map m f :=
f.sets_of_superset hs <| subset_preimage_image m s
#align filter.image_mem_map Filter.image_mem_map
-- The simpNF linter says that the LHS can be simplified via `Filter.mem_map`.
-- However this is a higher priority lemma.
-- https://github.com/leanprover/std4/issues/207
@[simp 1100, nolint simpNF]
theorem image_mem_map_iff (hf : Injective m) : m '' s ∈ map m f ↔ s ∈ f :=
⟨fun h => by rwa [← preimage_image_eq s hf], image_mem_map⟩
#align filter.image_mem_map_iff Filter.image_mem_map_iff
theorem range_mem_map : range m ∈ map m f := by
rw [← image_univ]
exact image_mem_map univ_mem
#align filter.range_mem_map Filter.range_mem_map
theorem mem_map_iff_exists_image : t ∈ map m f ↔ ∃ s ∈ f, m '' s ⊆ t :=
⟨fun ht => ⟨m ⁻¹' t, ht, image_preimage_subset _ _⟩, fun ⟨_, hs, ht⟩ =>
mem_of_superset (image_mem_map hs) ht⟩
#align filter.mem_map_iff_exists_image Filter.mem_map_iff_exists_image
@[simp]
theorem map_id : Filter.map id f = f :=
filter_eq <| rfl
#align filter.map_id Filter.map_id
@[simp]
theorem map_id' : Filter.map (fun x => x) f = f :=
map_id
#align filter.map_id' Filter.map_id'
@[simp]
theorem map_compose : Filter.map m' ∘ Filter.map m = Filter.map (m' ∘ m) :=
funext fun _ => filter_eq <| rfl
#align filter.map_compose Filter.map_compose
@[simp]
theorem map_map : Filter.map m' (Filter.map m f) = Filter.map (m' ∘ m) f :=
congr_fun Filter.map_compose f
#align filter.map_map Filter.map_map
/-- If functions `m₁` and `m₂` are eventually equal at a filter `f`, then
they map this filter to the same filter. -/
theorem map_congr {m₁ m₂ : α → β} {f : Filter α} (h : m₁ =ᶠ[f] m₂) : map m₁ f = map m₂ f :=
Filter.ext' fun _ => eventually_congr (h.mono fun _ hx => hx ▸ Iff.rfl)
#align filter.map_congr Filter.map_congr
end Map
section Comap
/-- The inverse map of a filter. A set `s` belongs to `Filter.comap m f` if either of the following
equivalent conditions hold.
1. There exists a set `t ∈ f` such that `m ⁻¹' t ⊆ s`. This is used as a definition.
2. The set `kernImage m s = {y | ∀ x, m x = y → x ∈ s}` belongs to `f`, see `Filter.mem_comap'`.
3. The set `(m '' sᶜ)ᶜ` belongs to `f`, see `Filter.mem_comap_iff_compl` and
`Filter.compl_mem_comap`. -/
def comap (m : α → β) (f : Filter β) : Filter α where
sets := { s | ∃ t ∈ f, m ⁻¹' t ⊆ s }
univ_sets := ⟨univ, univ_mem, by simp only [subset_univ, preimage_univ]⟩
sets_of_superset := fun ⟨a', ha', ma'a⟩ ab => ⟨a', ha', ma'a.trans ab⟩
inter_sets := fun ⟨a', ha₁, ha₂⟩ ⟨b', hb₁, hb₂⟩ =>
⟨a' ∩ b', inter_mem ha₁ hb₁, inter_subset_inter ha₂ hb₂⟩
#align filter.comap Filter.comap
variable {f : α → β} {l : Filter β} {p : α → Prop} {s : Set α}
theorem mem_comap' : s ∈ comap f l ↔ { y | ∀ ⦃x⦄, f x = y → x ∈ s } ∈ l :=
⟨fun ⟨t, ht, hts⟩ => mem_of_superset ht fun y hy x hx => hts <| mem_preimage.2 <| by rwa [hx],
fun h => ⟨_, h, fun x hx => hx rfl⟩⟩
#align filter.mem_comap' Filter.mem_comap'
-- TODO: it would be nice to use `kernImage` much more to take advantage of common name and API,
-- and then this would become `mem_comap'`
theorem mem_comap'' : s ∈ comap f l ↔ kernImage f s ∈ l :=
mem_comap'
/-- RHS form is used, e.g., in the definition of `UniformSpace`. -/
lemma mem_comap_prod_mk {x : α} {s : Set β} {F : Filter (α × β)} :
s ∈ comap (Prod.mk x) F ↔ {p : α × β | p.fst = x → p.snd ∈ s} ∈ F := by
simp_rw [mem_comap', Prod.ext_iff, and_imp, @forall_swap β (_ = _), forall_eq, eq_comm]
#align filter.mem_comap_prod_mk Filter.mem_comap_prod_mk
@[simp]
theorem eventually_comap : (∀ᶠ a in comap f l, p a) ↔ ∀ᶠ b in l, ∀ a, f a = b → p a :=
mem_comap'
#align filter.eventually_comap Filter.eventually_comap
@[simp]
theorem frequently_comap : (∃ᶠ a in comap f l, p a) ↔ ∃ᶠ b in l, ∃ a, f a = b ∧ p a := by
simp only [Filter.Frequently, eventually_comap, not_exists, _root_.not_and]
#align filter.frequently_comap Filter.frequently_comap
theorem mem_comap_iff_compl : s ∈ comap f l ↔ (f '' sᶜ)ᶜ ∈ l := by
simp only [mem_comap'', kernImage_eq_compl]
#align filter.mem_comap_iff_compl Filter.mem_comap_iff_compl
theorem compl_mem_comap : sᶜ ∈ comap f l ↔ (f '' s)ᶜ ∈ l := by rw [mem_comap_iff_compl, compl_compl]
#align filter.compl_mem_comap Filter.compl_mem_comap
end Comap
section KernMap
/-- The analog of `kernImage` for filters. A set `s` belongs to `Filter.kernMap m f` if either of
the following equivalent conditions hold.
1. There exists a set `t ∈ f` such that `s = kernImage m t`. This is used as a definition.
2. There exists a set `t` such that `tᶜ ∈ f` and `sᶜ = m '' t`, see `Filter.mem_kernMap_iff_compl`
and `Filter.compl_mem_kernMap`.
This definition because it gives a right adjoint to `Filter.comap`, and because it has a nice
interpretation when working with `co-` filters (`Filter.cocompact`, `Filter.cofinite`, ...).
For example, `kernMap m (cocompact α)` is the filter generated by the complements of the sets
`m '' K` where `K` is a compact subset of `α`. -/
def kernMap (m : α → β) (f : Filter α) : Filter β where
sets := (kernImage m) '' f.sets
univ_sets := ⟨univ, f.univ_sets, by simp [kernImage_eq_compl]⟩
sets_of_superset := by
rintro _ t ⟨s, hs, rfl⟩ hst
refine ⟨s ∪ m ⁻¹' t, mem_of_superset hs subset_union_left, ?_⟩
rw [kernImage_union_preimage, union_eq_right.mpr hst]
inter_sets := by
rintro _ _ ⟨s₁, h₁, rfl⟩ ⟨s₂, h₂, rfl⟩
exact ⟨s₁ ∩ s₂, f.inter_sets h₁ h₂, Set.preimage_kernImage.u_inf⟩
variable {m : α → β} {f : Filter α}
theorem mem_kernMap {s : Set β} : s ∈ kernMap m f ↔ ∃ t ∈ f, kernImage m t = s :=
Iff.rfl
theorem mem_kernMap_iff_compl {s : Set β} : s ∈ kernMap m f ↔ ∃ t, tᶜ ∈ f ∧ m '' t = sᶜ := by
rw [mem_kernMap, compl_surjective.exists]
refine exists_congr (fun x ↦ and_congr_right fun _ ↦ ?_)
rw [kernImage_compl, compl_eq_comm, eq_comm]
theorem compl_mem_kernMap {s : Set β} : sᶜ ∈ kernMap m f ↔ ∃ t, tᶜ ∈ f ∧ m '' t = s := by
simp_rw [mem_kernMap_iff_compl, compl_compl]
end KernMap
/-- The monadic bind operation on filter is defined the usual way in terms of `map` and `join`.
Unfortunately, this `bind` does not result in the expected applicative. See `Filter.seq` for the
applicative instance. -/
def bind (f : Filter α) (m : α → Filter β) : Filter β :=
join (map m f)
#align filter.bind Filter.bind
/-- The applicative sequentiation operation. This is not induced by the bind operation. -/
def seq (f : Filter (α → β)) (g : Filter α) : Filter β where
sets := { s | ∃ u ∈ f, ∃ t ∈ g, ∀ m ∈ u, ∀ x ∈ t, (m : α → β) x ∈ s }
univ_sets := ⟨univ, univ_mem, univ, univ_mem, fun _ _ _ _ => trivial⟩
sets_of_superset := fun ⟨t₀, t₁, h₀, h₁, h⟩ hst =>
⟨t₀, t₁, h₀, h₁, fun _ hx _ hy => hst <| h _ hx _ hy⟩
inter_sets := fun ⟨t₀, ht₀, t₁, ht₁, ht⟩ ⟨u₀, hu₀, u₁, hu₁, hu⟩ =>
⟨t₀ ∩ u₀, inter_mem ht₀ hu₀, t₁ ∩ u₁, inter_mem ht₁ hu₁, fun _ ⟨hx₀, hx₁⟩ _ ⟨hy₀, hy₁⟩ =>
⟨ht _ hx₀ _ hy₀, hu _ hx₁ _ hy₁⟩⟩
#align filter.seq Filter.seq
/-- `pure x` is the set of sets that contain `x`. It is equal to `𝓟 {x}` but
with this definition we have `s ∈ pure a` defeq `a ∈ s`. -/
instance : Pure Filter :=
⟨fun x =>
{ sets := { s | x ∈ s }
inter_sets := And.intro
sets_of_superset := fun hs hst => hst hs
univ_sets := trivial }⟩
instance : Bind Filter :=
⟨@Filter.bind⟩
instance : Functor Filter where map := @Filter.map
instance : LawfulFunctor (Filter : Type u → Type u) where
id_map _ := map_id
comp_map _ _ _ := map_map.symm
map_const := rfl
theorem pure_sets (a : α) : (pure a : Filter α).sets = { s | a ∈ s } :=
rfl
#align filter.pure_sets Filter.pure_sets
@[simp]
theorem mem_pure {a : α} {s : Set α} : s ∈ (pure a : Filter α) ↔ a ∈ s :=
Iff.rfl
#align filter.mem_pure Filter.mem_pure
@[simp]
theorem eventually_pure {a : α} {p : α → Prop} : (∀ᶠ x in pure a, p x) ↔ p a :=
Iff.rfl
#align filter.eventually_pure Filter.eventually_pure
@[simp]
theorem principal_singleton (a : α) : 𝓟 {a} = pure a :=
Filter.ext fun s => by simp only [mem_pure, mem_principal, singleton_subset_iff]
#align filter.principal_singleton Filter.principal_singleton
@[simp]
theorem map_pure (f : α → β) (a : α) : map f (pure a) = pure (f a) :=
rfl
#align filter.map_pure Filter.map_pure
theorem pure_le_principal (a : α) : pure a ≤ 𝓟 s ↔ a ∈ s := by
simp
@[simp] theorem join_pure (f : Filter α) : join (pure f) = f := rfl
#align filter.join_pure Filter.join_pure
@[simp]
theorem pure_bind (a : α) (m : α → Filter β) : bind (pure a) m = m a := by
simp only [Bind.bind, bind, map_pure, join_pure]
#align filter.pure_bind Filter.pure_bind
theorem map_bind {α β} (m : β → γ) (f : Filter α) (g : α → Filter β) :
map m (bind f g) = bind f (map m ∘ g) :=
rfl
theorem bind_map {α β} (m : α → β) (f : Filter α) (g : β → Filter γ) :
(bind (map m f) g) = bind f (g ∘ m) :=
rfl
/-!
### `Filter` as a `Monad`
In this section we define `Filter.monad`, a `Monad` structure on `Filter`s. This definition is not
an instance because its `Seq` projection is not equal to the `Filter.seq` function we use in the
`Applicative` instance on `Filter`.
-/
section
/-- The monad structure on filters. -/
protected def monad : Monad Filter where map := @Filter.map
#align filter.monad Filter.monad
attribute [local instance] Filter.monad
protected theorem lawfulMonad : LawfulMonad Filter where
map_const := rfl
id_map _ := rfl
seqLeft_eq _ _ := rfl
seqRight_eq _ _ := rfl
pure_seq _ _ := rfl
bind_pure_comp _ _ := rfl
bind_map _ _ := rfl
pure_bind _ _ := rfl
bind_assoc _ _ _ := rfl
#align filter.is_lawful_monad Filter.lawfulMonad
end
instance : Alternative Filter where
seq := fun x y => x.seq (y ())
failure := ⊥
orElse x y := x ⊔ y ()
@[simp]
theorem map_def {α β} (m : α → β) (f : Filter α) : m <$> f = map m f :=
rfl
#align filter.map_def Filter.map_def
@[simp]
theorem bind_def {α β} (f : Filter α) (m : α → Filter β) : f >>= m = bind f m :=
rfl
#align filter.bind_def Filter.bind_def
/-! #### `map` and `comap` equations -/
section Map
variable {f f₁ f₂ : Filter α} {g g₁ g₂ : Filter β} {m : α → β} {m' : β → γ} {s : Set α} {t : Set β}
@[simp] theorem mem_comap : s ∈ comap m g ↔ ∃ t ∈ g, m ⁻¹' t ⊆ s := Iff.rfl
#align filter.mem_comap Filter.mem_comap
theorem preimage_mem_comap (ht : t ∈ g) : m ⁻¹' t ∈ comap m g :=
⟨t, ht, Subset.rfl⟩
#align filter.preimage_mem_comap Filter.preimage_mem_comap
theorem Eventually.comap {p : β → Prop} (hf : ∀ᶠ b in g, p b) (f : α → β) :
∀ᶠ a in comap f g, p (f a) :=
preimage_mem_comap hf
#align filter.eventually.comap Filter.Eventually.comap
theorem comap_id : comap id f = f :=
le_antisymm (fun _ => preimage_mem_comap) fun _ ⟨_, ht, hst⟩ => mem_of_superset ht hst
#align filter.comap_id Filter.comap_id
theorem comap_id' : comap (fun x => x) f = f := comap_id
#align filter.comap_id' Filter.comap_id'
theorem comap_const_of_not_mem {x : β} (ht : t ∈ g) (hx : x ∉ t) : comap (fun _ : α => x) g = ⊥ :=
empty_mem_iff_bot.1 <| mem_comap'.2 <| mem_of_superset ht fun _ hx' _ h => hx <| h.symm ▸ hx'
#align filter.comap_const_of_not_mem Filter.comap_const_of_not_mem
theorem comap_const_of_mem {x : β} (h : ∀ t ∈ g, x ∈ t) : comap (fun _ : α => x) g = ⊤ :=
top_unique fun _ hs => univ_mem' fun _ => h _ (mem_comap'.1 hs) rfl
#align filter.comap_const_of_mem Filter.comap_const_of_mem
theorem map_const [NeBot f] {c : β} : (f.map fun _ => c) = pure c := by
ext s
by_cases h : c ∈ s <;> simp [h]
#align filter.map_const Filter.map_const
theorem comap_comap {m : γ → β} {n : β → α} : comap m (comap n f) = comap (n ∘ m) f :=
Filter.coext fun s => by simp only [compl_mem_comap, image_image, (· ∘ ·)]
#align filter.comap_comap Filter.comap_comap
section comm
/-!
The variables in the following lemmas are used as in this diagram:
```
φ
α → β
θ ↓ ↓ ψ
γ → δ
ρ
```
-/
variable {φ : α → β} {θ : α → γ} {ψ : β → δ} {ρ : γ → δ} (H : ψ ∘ φ = ρ ∘ θ)
theorem map_comm (F : Filter α) : map ψ (map φ F) = map ρ (map θ F) := by
rw [Filter.map_map, H, ← Filter.map_map]
#align filter.map_comm Filter.map_comm
theorem comap_comm (G : Filter δ) : comap φ (comap ψ G) = comap θ (comap ρ G) := by
rw [Filter.comap_comap, H, ← Filter.comap_comap]
#align filter.comap_comm Filter.comap_comm
end comm
theorem _root_.Function.Semiconj.filter_map {f : α → β} {ga : α → α} {gb : β → β}
(h : Function.Semiconj f ga gb) : Function.Semiconj (map f) (map ga) (map gb) :=
map_comm h.comp_eq
#align function.semiconj.filter_map Function.Semiconj.filter_map
theorem _root_.Function.Commute.filter_map {f g : α → α} (h : Function.Commute f g) :
Function.Commute (map f) (map g) :=
h.semiconj.filter_map
#align function.commute.filter_map Function.Commute.filter_map
theorem _root_.Function.Semiconj.filter_comap {f : α → β} {ga : α → α} {gb : β → β}
(h : Function.Semiconj f ga gb) : Function.Semiconj (comap f) (comap gb) (comap ga) :=
comap_comm h.comp_eq.symm
#align function.semiconj.filter_comap Function.Semiconj.filter_comap
theorem _root_.Function.Commute.filter_comap {f g : α → α} (h : Function.Commute f g) :
Function.Commute (comap f) (comap g) :=
h.semiconj.filter_comap
#align function.commute.filter_comap Function.Commute.filter_comap
section
open Filter
theorem _root_.Function.LeftInverse.filter_map {f : α → β} {g : β → α} (hfg : LeftInverse g f) :
LeftInverse (map g) (map f) := fun F ↦ by
rw [map_map, hfg.comp_eq_id, map_id]
theorem _root_.Function.LeftInverse.filter_comap {f : α → β} {g : β → α} (hfg : LeftInverse g f) :
RightInverse (comap g) (comap f) := fun F ↦ by
rw [comap_comap, hfg.comp_eq_id, comap_id]
nonrec theorem _root_.Function.RightInverse.filter_map {f : α → β} {g : β → α}
(hfg : RightInverse g f) : RightInverse (map g) (map f) :=
hfg.filter_map
nonrec theorem _root_.Function.RightInverse.filter_comap {f : α → β} {g : β → α}
(hfg : RightInverse g f) : LeftInverse (comap g) (comap f) :=
hfg.filter_comap
theorem _root_.Set.LeftInvOn.filter_map_Iic {f : α → β} {g : β → α} (hfg : LeftInvOn g f s) :
LeftInvOn (map g) (map f) (Iic <| 𝓟 s) := fun F (hF : F ≤ 𝓟 s) ↦ by
have : (g ∘ f) =ᶠ[𝓟 s] id := by simpa only [eventuallyEq_principal] using hfg
rw [map_map, map_congr (this.filter_mono hF), map_id]
nonrec theorem _root_.Set.RightInvOn.filter_map_Iic {f : α → β} {g : β → α}
(hfg : RightInvOn g f t) : RightInvOn (map g) (map f) (Iic <| 𝓟 t) :=
hfg.filter_map_Iic
end
@[simp]
theorem comap_principal {t : Set β} : comap m (𝓟 t) = 𝓟 (m ⁻¹' t) :=
Filter.ext fun _ => ⟨fun ⟨_u, hu, b⟩ => (preimage_mono hu).trans b,
fun h => ⟨t, Subset.rfl, h⟩⟩
#align filter.comap_principal Filter.comap_principal
theorem principal_subtype {α : Type*} (s : Set α) (t : Set s) :
𝓟 t = comap (↑) (𝓟 (((↑) : s → α) '' t)) := by
rw [comap_principal, preimage_image_eq _ Subtype.coe_injective]
#align principal_subtype Filter.principal_subtype
@[simp]
theorem comap_pure {b : β} : comap m (pure b) = 𝓟 (m ⁻¹' {b}) := by
rw [← principal_singleton, comap_principal]
#align filter.comap_pure Filter.comap_pure
theorem map_le_iff_le_comap : map m f ≤ g ↔ f ≤ comap m g :=
⟨fun h _ ⟨_, ht, hts⟩ => mem_of_superset (h ht) hts, fun h _ ht => h ⟨_, ht, Subset.rfl⟩⟩
#align filter.map_le_iff_le_comap Filter.map_le_iff_le_comap
theorem gc_map_comap (m : α → β) : GaloisConnection (map m) (comap m) :=
fun _ _ => map_le_iff_le_comap
#align filter.gc_map_comap Filter.gc_map_comap
theorem comap_le_iff_le_kernMap : comap m g ≤ f ↔ g ≤ kernMap m f := by
simp [Filter.le_def, mem_comap'', mem_kernMap, -mem_comap]
theorem gc_comap_kernMap (m : α → β) : GaloisConnection (comap m) (kernMap m) :=
fun _ _ ↦ comap_le_iff_le_kernMap
theorem kernMap_principal {s : Set α} : kernMap m (𝓟 s) = 𝓟 (kernImage m s) := by
refine eq_of_forall_le_iff (fun g ↦ ?_)
rw [← comap_le_iff_le_kernMap, le_principal_iff, le_principal_iff, mem_comap'']
@[mono]
theorem map_mono : Monotone (map m) :=
(gc_map_comap m).monotone_l
#align filter.map_mono Filter.map_mono
@[mono]
theorem comap_mono : Monotone (comap m) :=
(gc_map_comap m).monotone_u
#align filter.comap_mono Filter.comap_mono
/-- Temporary lemma that we can tag with `gcongr` -/
@[gcongr, deprecated] theorem map_le_map (h : F ≤ G) : map m F ≤ map m G := map_mono h
/-- Temporary lemma that we can tag with `gcongr` -/
@[gcongr, deprecated] theorem comap_le_comap (h : F ≤ G) : comap m F ≤ comap m G := comap_mono h
@[simp] theorem map_bot : map m ⊥ = ⊥ := (gc_map_comap m).l_bot
#align filter.map_bot Filter.map_bot
@[simp] theorem map_sup : map m (f₁ ⊔ f₂) = map m f₁ ⊔ map m f₂ := (gc_map_comap m).l_sup
#align filter.map_sup Filter.map_sup
@[simp]
theorem map_iSup {f : ι → Filter α} : map m (⨆ i, f i) = ⨆ i, map m (f i) :=
(gc_map_comap m).l_iSup
#align filter.map_supr Filter.map_iSup
@[simp]
theorem map_top (f : α → β) : map f ⊤ = 𝓟 (range f) := by
rw [← principal_univ, map_principal, image_univ]
#align filter.map_top Filter.map_top
@[simp] theorem comap_top : comap m ⊤ = ⊤ := (gc_map_comap m).u_top
#align filter.comap_top Filter.comap_top
@[simp] theorem comap_inf : comap m (g₁ ⊓ g₂) = comap m g₁ ⊓ comap m g₂ := (gc_map_comap m).u_inf
#align filter.comap_inf Filter.comap_inf
@[simp]
theorem comap_iInf {f : ι → Filter β} : comap m (⨅ i, f i) = ⨅ i, comap m (f i) :=
(gc_map_comap m).u_iInf
#align filter.comap_infi Filter.comap_iInf
theorem le_comap_top (f : α → β) (l : Filter α) : l ≤ comap f ⊤ := by
rw [comap_top]
exact le_top
#align filter.le_comap_top Filter.le_comap_top
theorem map_comap_le : map m (comap m g) ≤ g :=
(gc_map_comap m).l_u_le _
#align filter.map_comap_le Filter.map_comap_le
theorem le_comap_map : f ≤ comap m (map m f) :=
(gc_map_comap m).le_u_l _
#align filter.le_comap_map Filter.le_comap_map
@[simp]
theorem comap_bot : comap m ⊥ = ⊥ :=
bot_unique fun s _ => ⟨∅, mem_bot, by simp only [empty_subset, preimage_empty]⟩
#align filter.comap_bot Filter.comap_bot
theorem neBot_of_comap (h : (comap m g).NeBot) : g.NeBot := by
rw [neBot_iff] at *
contrapose! h
rw [h]
exact comap_bot
#align filter.ne_bot_of_comap Filter.neBot_of_comap
theorem comap_inf_principal_range : comap m (g ⊓ 𝓟 (range m)) = comap m g := by
simp
#align filter.comap_inf_principal_range Filter.comap_inf_principal_range
theorem disjoint_comap (h : Disjoint g₁ g₂) : Disjoint (comap m g₁) (comap m g₂) := by
simp only [disjoint_iff, ← comap_inf, h.eq_bot, comap_bot]
#align filter.disjoint_comap Filter.disjoint_comap
theorem comap_iSup {ι} {f : ι → Filter β} {m : α → β} : comap m (iSup f) = ⨆ i, comap m (f i) :=
(gc_comap_kernMap m).l_iSup
#align filter.comap_supr Filter.comap_iSup
theorem comap_sSup {s : Set (Filter β)} {m : α → β} : comap m (sSup s) = ⨆ f ∈ s, comap m f := by
simp only [sSup_eq_iSup, comap_iSup, eq_self_iff_true]
#align filter.comap_Sup Filter.comap_sSup
theorem comap_sup : comap m (g₁ ⊔ g₂) = comap m g₁ ⊔ comap m g₂ := by
rw [sup_eq_iSup, comap_iSup, iSup_bool_eq, Bool.cond_true, Bool.cond_false]
#align filter.comap_sup Filter.comap_sup
theorem map_comap (f : Filter β) (m : α → β) : (f.comap m).map m = f ⊓ 𝓟 (range m) := by
refine le_antisymm (le_inf map_comap_le <| le_principal_iff.2 range_mem_map) ?_
rintro t' ⟨t, ht, sub⟩
refine mem_inf_principal.2 (mem_of_superset ht ?_)
rintro _ hxt ⟨x, rfl⟩
exact sub hxt
#align filter.map_comap Filter.map_comap
theorem map_comap_setCoe_val (f : Filter β) (s : Set β) :
(f.comap ((↑) : s → β)).map (↑) = f ⊓ 𝓟 s := by
rw [map_comap, Subtype.range_val]
theorem map_comap_of_mem {f : Filter β} {m : α → β} (hf : range m ∈ f) : (f.comap m).map m = f := by
rw [map_comap, inf_eq_left.2 (le_principal_iff.2 hf)]
#align filter.map_comap_of_mem Filter.map_comap_of_mem
instance canLift (c) (p) [CanLift α β c p] :
CanLift (Filter α) (Filter β) (map c) fun f => ∀ᶠ x : α in f, p x where
prf f hf := ⟨comap c f, map_comap_of_mem <| hf.mono CanLift.prf⟩
#align filter.can_lift Filter.canLift
theorem comap_le_comap_iff {f g : Filter β} {m : α → β} (hf : range m ∈ f) :
comap m f ≤ comap m g ↔ f ≤ g :=
⟨fun h => map_comap_of_mem hf ▸ (map_mono h).trans map_comap_le, fun h => comap_mono h⟩
#align filter.comap_le_comap_iff Filter.comap_le_comap_iff
theorem map_comap_of_surjective {f : α → β} (hf : Surjective f) (l : Filter β) :
map f (comap f l) = l :=
map_comap_of_mem <| by simp only [hf.range_eq, univ_mem]
#align filter.map_comap_of_surjective Filter.map_comap_of_surjective
theorem comap_injective {f : α → β} (hf : Surjective f) : Injective (comap f) :=
LeftInverse.injective <| map_comap_of_surjective hf
theorem _root_.Function.Surjective.filter_map_top {f : α → β} (hf : Surjective f) : map f ⊤ = ⊤ :=
(congr_arg _ comap_top).symm.trans <| map_comap_of_surjective hf ⊤
#align function.surjective.filter_map_top Function.Surjective.filter_map_top
theorem subtype_coe_map_comap (s : Set α) (f : Filter α) :
map ((↑) : s → α) (comap ((↑) : s → α) f) = f ⊓ 𝓟 s := by rw [map_comap, Subtype.range_coe]
#align filter.subtype_coe_map_comap Filter.subtype_coe_map_comap
theorem image_mem_of_mem_comap {f : Filter α} {c : β → α} (h : range c ∈ f) {W : Set β}
(W_in : W ∈ comap c f) : c '' W ∈ f := by
rw [← map_comap_of_mem h]
exact image_mem_map W_in
#align filter.image_mem_of_mem_comap Filter.image_mem_of_mem_comap
theorem image_coe_mem_of_mem_comap {f : Filter α} {U : Set α} (h : U ∈ f) {W : Set U}
(W_in : W ∈ comap ((↑) : U → α) f) : (↑) '' W ∈ f :=
image_mem_of_mem_comap (by simp [h]) W_in
#align filter.image_coe_mem_of_mem_comap Filter.image_coe_mem_of_mem_comap
theorem comap_map {f : Filter α} {m : α → β} (h : Injective m) : comap m (map m f) = f :=
le_antisymm
(fun s hs =>
mem_of_superset (preimage_mem_comap <| image_mem_map hs) <| by
simp only [preimage_image_eq s h, Subset.rfl])
le_comap_map
#align filter.comap_map Filter.comap_map
theorem mem_comap_iff {f : Filter β} {m : α → β} (inj : Injective m) (large : Set.range m ∈ f)
{S : Set α} : S ∈ comap m f ↔ m '' S ∈ f := by
rw [← image_mem_map_iff inj, map_comap_of_mem large]
#align filter.mem_comap_iff Filter.mem_comap_iff
theorem map_le_map_iff_of_injOn {l₁ l₂ : Filter α} {f : α → β} {s : Set α} (h₁ : s ∈ l₁)
(h₂ : s ∈ l₂) (hinj : InjOn f s) : map f l₁ ≤ map f l₂ ↔ l₁ ≤ l₂ :=
⟨fun h _t ht =>
mp_mem h₁ <|
mem_of_superset (h <| image_mem_map (inter_mem h₂ ht)) fun _y ⟨_x, ⟨hxs, hxt⟩, hxy⟩ hys =>
hinj hxs hys hxy ▸ hxt,
fun h => map_mono h⟩
#align filter.map_le_map_iff_of_inj_on Filter.map_le_map_iff_of_injOn
theorem map_le_map_iff {f g : Filter α} {m : α → β} (hm : Injective m) :
map m f ≤ map m g ↔ f ≤ g := by rw [map_le_iff_le_comap, comap_map hm]
#align filter.map_le_map_iff Filter.map_le_map_iff
theorem map_eq_map_iff_of_injOn {f g : Filter α} {m : α → β} {s : Set α} (hsf : s ∈ f) (hsg : s ∈ g)
(hm : InjOn m s) : map m f = map m g ↔ f = g := by
simp only [le_antisymm_iff, map_le_map_iff_of_injOn hsf hsg hm,
map_le_map_iff_of_injOn hsg hsf hm]
#align filter.map_eq_map_iff_of_inj_on Filter.map_eq_map_iff_of_injOn
theorem map_inj {f g : Filter α} {m : α → β} (hm : Injective m) : map m f = map m g ↔ f = g :=
map_eq_map_iff_of_injOn univ_mem univ_mem hm.injOn
#align filter.map_inj Filter.map_inj
theorem map_injective {m : α → β} (hm : Injective m) : Injective (map m) := fun _ _ =>
(map_inj hm).1
#align filter.map_injective Filter.map_injective
theorem comap_neBot_iff {f : Filter β} {m : α → β} : NeBot (comap m f) ↔ ∀ t ∈ f, ∃ a, m a ∈ t := by
simp only [← forall_mem_nonempty_iff_neBot, mem_comap, forall_exists_index, and_imp]
exact ⟨fun h t t_in => h (m ⁻¹' t) t t_in Subset.rfl, fun h s t ht hst => (h t ht).imp hst⟩
#align filter.comap_ne_bot_iff Filter.comap_neBot_iff
theorem comap_neBot {f : Filter β} {m : α → β} (hm : ∀ t ∈ f, ∃ a, m a ∈ t) : NeBot (comap m f) :=
comap_neBot_iff.mpr hm
#align filter.comap_ne_bot Filter.comap_neBot
theorem comap_neBot_iff_frequently {f : Filter β} {m : α → β} :
NeBot (comap m f) ↔ ∃ᶠ y in f, y ∈ range m := by
simp only [comap_neBot_iff, frequently_iff, mem_range, @and_comm (_ ∈ _), exists_exists_eq_and]
#align filter.comap_ne_bot_iff_frequently Filter.comap_neBot_iff_frequently
theorem comap_neBot_iff_compl_range {f : Filter β} {m : α → β} :
NeBot (comap m f) ↔ (range m)ᶜ ∉ f :=
comap_neBot_iff_frequently
#align filter.comap_ne_bot_iff_compl_range Filter.comap_neBot_iff_compl_range
theorem comap_eq_bot_iff_compl_range {f : Filter β} {m : α → β} : comap m f = ⊥ ↔ (range m)ᶜ ∈ f :=
not_iff_not.mp <| neBot_iff.symm.trans comap_neBot_iff_compl_range
#align filter.comap_eq_bot_iff_compl_range Filter.comap_eq_bot_iff_compl_range
theorem comap_surjective_eq_bot {f : Filter β} {m : α → β} (hm : Surjective m) :
comap m f = ⊥ ↔ f = ⊥ := by
rw [comap_eq_bot_iff_compl_range, hm.range_eq, compl_univ, empty_mem_iff_bot]
#align filter.comap_surjective_eq_bot Filter.comap_surjective_eq_bot
theorem disjoint_comap_iff (h : Surjective m) :
Disjoint (comap m g₁) (comap m g₂) ↔ Disjoint g₁ g₂ := by
rw [disjoint_iff, disjoint_iff, ← comap_inf, comap_surjective_eq_bot h]
#align filter.disjoint_comap_iff Filter.disjoint_comap_iff
theorem NeBot.comap_of_range_mem {f : Filter β} {m : α → β} (_ : NeBot f) (hm : range m ∈ f) :
NeBot (comap m f) :=
comap_neBot_iff_frequently.2 <| Eventually.frequently hm
#align filter.ne_bot.comap_of_range_mem Filter.NeBot.comap_of_range_mem
@[simp]
theorem comap_fst_neBot_iff {f : Filter α} :
(f.comap (Prod.fst : α × β → α)).NeBot ↔ f.NeBot ∧ Nonempty β := by
cases isEmpty_or_nonempty β
· rw [filter_eq_bot_of_isEmpty (f.comap _), ← not_iff_not]; simp [*]
· simp [comap_neBot_iff_frequently, *]
#align filter.comap_fst_ne_bot_iff Filter.comap_fst_neBot_iff
@[instance]
theorem comap_fst_neBot [Nonempty β] {f : Filter α} [NeBot f] :
(f.comap (Prod.fst : α × β → α)).NeBot :=
comap_fst_neBot_iff.2 ⟨‹_›, ‹_›⟩
#align filter.comap_fst_ne_bot Filter.comap_fst_neBot
@[simp]
theorem comap_snd_neBot_iff {f : Filter β} :
(f.comap (Prod.snd : α × β → β)).NeBot ↔ Nonempty α ∧ f.NeBot := by
cases' isEmpty_or_nonempty α with hα hα
· rw [filter_eq_bot_of_isEmpty (f.comap _), ← not_iff_not]; simp
· simp [comap_neBot_iff_frequently, hα]
#align filter.comap_snd_ne_bot_iff Filter.comap_snd_neBot_iff
@[instance]
theorem comap_snd_neBot [Nonempty α] {f : Filter β} [NeBot f] :
(f.comap (Prod.snd : α × β → β)).NeBot :=
comap_snd_neBot_iff.2 ⟨‹_›, ‹_›⟩
#align filter.comap_snd_ne_bot Filter.comap_snd_neBot
theorem comap_eval_neBot_iff' {ι : Type*} {α : ι → Type*} {i : ι} {f : Filter (α i)} :
(comap (eval i) f).NeBot ↔ (∀ j, Nonempty (α j)) ∧ NeBot f := by
cases' isEmpty_or_nonempty (∀ j, α j) with H H
· rw [filter_eq_bot_of_isEmpty (f.comap _), ← not_iff_not]
simp [← Classical.nonempty_pi]
· have : ∀ j, Nonempty (α j) := Classical.nonempty_pi.1 H
simp [comap_neBot_iff_frequently, *]
#align filter.comap_eval_ne_bot_iff' Filter.comap_eval_neBot_iff'
@[simp]
theorem comap_eval_neBot_iff {ι : Type*} {α : ι → Type*} [∀ j, Nonempty (α j)] {i : ι}
{f : Filter (α i)} : (comap (eval i) f).NeBot ↔ NeBot f := by simp [comap_eval_neBot_iff', *]
#align filter.comap_eval_ne_bot_iff Filter.comap_eval_neBot_iff
@[instance]
theorem comap_eval_neBot {ι : Type*} {α : ι → Type*} [∀ j, Nonempty (α j)] (i : ι)
(f : Filter (α i)) [NeBot f] : (comap (eval i) f).NeBot :=
comap_eval_neBot_iff.2 ‹_›
#align filter.comap_eval_ne_bot Filter.comap_eval_neBot
theorem comap_inf_principal_neBot_of_image_mem {f : Filter β} {m : α → β} (hf : NeBot f) {s : Set α}
(hs : m '' s ∈ f) : NeBot (comap m f ⊓ 𝓟 s) := by
refine ⟨compl_compl s ▸ mt mem_of_eq_bot ?_⟩
rintro ⟨t, ht, hts⟩
rcases hf.nonempty_of_mem (inter_mem hs ht) with ⟨_, ⟨x, hxs, rfl⟩, hxt⟩
exact absurd hxs (hts hxt)
#align filter.comap_inf_principal_ne_bot_of_image_mem Filter.comap_inf_principal_neBot_of_image_mem
theorem comap_coe_neBot_of_le_principal {s : Set γ} {l : Filter γ} [h : NeBot l] (h' : l ≤ 𝓟 s) :
NeBot (comap ((↑) : s → γ) l) :=
h.comap_of_range_mem <| (@Subtype.range_coe γ s).symm ▸ h' (mem_principal_self s)
#align filter.comap_coe_ne_bot_of_le_principal Filter.comap_coe_neBot_of_le_principal
theorem NeBot.comap_of_surj {f : Filter β} {m : α → β} (hf : NeBot f) (hm : Surjective m) :
NeBot (comap m f) :=
hf.comap_of_range_mem <| univ_mem' hm
#align filter.ne_bot.comap_of_surj Filter.NeBot.comap_of_surj
theorem NeBot.comap_of_image_mem {f : Filter β} {m : α → β} (hf : NeBot f) {s : Set α}
(hs : m '' s ∈ f) : NeBot (comap m f) :=
hf.comap_of_range_mem <| mem_of_superset hs (image_subset_range _ _)
#align filter.ne_bot.comap_of_image_mem Filter.NeBot.comap_of_image_mem
@[simp]
theorem map_eq_bot_iff : map m f = ⊥ ↔ f = ⊥ :=
⟨by
rw [← empty_mem_iff_bot, ← empty_mem_iff_bot]
exact id, fun h => by simp only [h, map_bot]⟩
#align filter.map_eq_bot_iff Filter.map_eq_bot_iff
theorem map_neBot_iff (f : α → β) {F : Filter α} : NeBot (map f F) ↔ NeBot F := by
simp only [neBot_iff, Ne, map_eq_bot_iff]
#align filter.map_ne_bot_iff Filter.map_neBot_iff
theorem NeBot.map (hf : NeBot f) (m : α → β) : NeBot (map m f) :=
(map_neBot_iff m).2 hf
#align filter.ne_bot.map Filter.NeBot.map
theorem NeBot.of_map : NeBot (f.map m) → NeBot f :=
(map_neBot_iff m).1
#align filter.ne_bot.of_map Filter.NeBot.of_map
instance map_neBot [hf : NeBot f] : NeBot (f.map m) :=
hf.map m
#align filter.map_ne_bot Filter.map_neBot
theorem sInter_comap_sets (f : α → β) (F : Filter β) : ⋂₀ (comap f F).sets = ⋂ U ∈ F, f ⁻¹' U := by
ext x
suffices (∀ (A : Set α) (B : Set β), B ∈ F → f ⁻¹' B ⊆ A → x ∈ A) ↔
∀ B : Set β, B ∈ F → f x ∈ B by
simp only [mem_sInter, mem_iInter, Filter.mem_sets, mem_comap, this, and_imp, exists_prop,
mem_preimage, exists_imp]
constructor
· intro h U U_in
simpa only [Subset.rfl, forall_prop_of_true, mem_preimage] using h (f ⁻¹' U) U U_in
· intro h V U U_in f_U_V
exact f_U_V (h U U_in)
#align filter.sInter_comap_sets Filter.sInter_comap_sets
end Map
-- this is a generic rule for monotone functions:
theorem map_iInf_le {f : ι → Filter α} {m : α → β} : map m (iInf f) ≤ ⨅ i, map m (f i) :=
le_iInf fun _ => map_mono <| iInf_le _ _
#align filter.map_infi_le Filter.map_iInf_le
theorem map_iInf_eq {f : ι → Filter α} {m : α → β} (hf : Directed (· ≥ ·) f) [Nonempty ι] :
map m (iInf f) = ⨅ i, map m (f i) :=
map_iInf_le.antisymm fun s (hs : m ⁻¹' s ∈ iInf f) =>
let ⟨i, hi⟩ := (mem_iInf_of_directed hf _).1 hs
have : ⨅ i, map m (f i) ≤ 𝓟 s :=
iInf_le_of_le i <| by simpa only [le_principal_iff, mem_map]
Filter.le_principal_iff.1 this
#align filter.map_infi_eq Filter.map_iInf_eq
theorem map_biInf_eq {ι : Type w} {f : ι → Filter α} {m : α → β} {p : ι → Prop}
(h : DirectedOn (f ⁻¹'o (· ≥ ·)) { x | p x }) (ne : ∃ i, p i) :
map m (⨅ (i) (_ : p i), f i) = ⨅ (i) (_ : p i), map m (f i) := by
haveI := nonempty_subtype.2 ne
simp only [iInf_subtype']
exact map_iInf_eq h.directed_val
#align filter.map_binfi_eq Filter.map_biInf_eq
theorem map_inf_le {f g : Filter α} {m : α → β} : map m (f ⊓ g) ≤ map m f ⊓ map m g :=
(@map_mono _ _ m).map_inf_le f g
#align filter.map_inf_le Filter.map_inf_le
theorem map_inf {f g : Filter α} {m : α → β} (h : Injective m) :
map m (f ⊓ g) = map m f ⊓ map m g := by
refine map_inf_le.antisymm ?_
rintro t ⟨s₁, hs₁, s₂, hs₂, ht : m ⁻¹' t = s₁ ∩ s₂⟩
refine mem_inf_of_inter (image_mem_map hs₁) (image_mem_map hs₂) ?_
rw [← image_inter h, image_subset_iff, ht]
#align filter.map_inf Filter.map_inf
theorem map_inf' {f g : Filter α} {m : α → β} {t : Set α} (htf : t ∈ f) (htg : t ∈ g)
(h : InjOn m t) : map m (f ⊓ g) = map m f ⊓ map m g := by
lift f to Filter t using htf; lift g to Filter t using htg
replace h : Injective (m ∘ ((↑) : t → α)) := h.injective
simp only [map_map, ← map_inf Subtype.coe_injective, map_inf h]
#align filter.map_inf' Filter.map_inf'
lemma disjoint_of_map {α β : Type*} {F G : Filter α} {f : α → β}
(h : Disjoint (map f F) (map f G)) : Disjoint F G :=
disjoint_iff.mpr <| map_eq_bot_iff.mp <| le_bot_iff.mp <| trans map_inf_le (disjoint_iff.mp h)
theorem disjoint_map {m : α → β} (hm : Injective m) {f₁ f₂ : Filter α} :
Disjoint (map m f₁) (map m f₂) ↔ Disjoint f₁ f₂ := by
simp only [disjoint_iff, ← map_inf hm, map_eq_bot_iff]
#align filter.disjoint_map Filter.disjoint_map
theorem map_equiv_symm (e : α ≃ β) (f : Filter β) : map e.symm f = comap e f :=
map_injective e.injective <| by
rw [map_map, e.self_comp_symm, map_id, map_comap_of_surjective e.surjective]
#align filter.map_equiv_symm Filter.map_equiv_symm
theorem map_eq_comap_of_inverse {f : Filter α} {m : α → β} {n : β → α} (h₁ : m ∘ n = id)
(h₂ : n ∘ m = id) : map m f = comap n f :=
map_equiv_symm ⟨n, m, congr_fun h₁, congr_fun h₂⟩ f
#align filter.map_eq_comap_of_inverse Filter.map_eq_comap_of_inverse
theorem comap_equiv_symm (e : α ≃ β) (f : Filter α) : comap e.symm f = map e f :=
(map_eq_comap_of_inverse e.self_comp_symm e.symm_comp_self).symm
#align filter.comap_equiv_symm Filter.comap_equiv_symm
theorem map_swap_eq_comap_swap {f : Filter (α × β)} : Prod.swap <$> f = comap Prod.swap f :=
map_eq_comap_of_inverse Prod.swap_swap_eq Prod.swap_swap_eq
#align filter.map_swap_eq_comap_swap Filter.map_swap_eq_comap_swap
/-- A useful lemma when dealing with uniformities. -/
theorem map_swap4_eq_comap {f : Filter ((α × β) × γ × δ)} :
map (fun p : (α × β) × γ × δ => ((p.1.1, p.2.1), (p.1.2, p.2.2))) f =
comap (fun p : (α × γ) × β × δ => ((p.1.1, p.2.1), (p.1.2, p.2.2))) f :=
map_eq_comap_of_inverse (funext fun ⟨⟨_, _⟩, ⟨_, _⟩⟩ => rfl) (funext fun ⟨⟨_, _⟩, ⟨_, _⟩⟩ => rfl)
#align filter.map_swap4_eq_comap Filter.map_swap4_eq_comap
theorem le_map {f : Filter α} {m : α → β} {g : Filter β} (h : ∀ s ∈ f, m '' s ∈ g) : g ≤ f.map m :=
fun _ hs => mem_of_superset (h _ hs) <| image_preimage_subset _ _
#align filter.le_map Filter.le_map
theorem le_map_iff {f : Filter α} {m : α → β} {g : Filter β} : g ≤ f.map m ↔ ∀ s ∈ f, m '' s ∈ g :=
⟨fun h _ hs => h (image_mem_map hs), le_map⟩
#align filter.le_map_iff Filter.le_map_iff
protected theorem push_pull (f : α → β) (F : Filter α) (G : Filter β) :
map f (F ⊓ comap f G) = map f F ⊓ G := by
apply le_antisymm
· calc
map f (F ⊓ comap f G) ≤ map f F ⊓ (map f <| comap f G) := map_inf_le
_ ≤ map f F ⊓ G := inf_le_inf_left (map f F) map_comap_le
· rintro U ⟨V, V_in, W, ⟨Z, Z_in, hZ⟩, h⟩
apply mem_inf_of_inter (image_mem_map V_in) Z_in
calc
f '' V ∩ Z = f '' (V ∩ f ⁻¹' Z) := by rw [image_inter_preimage]
_ ⊆ f '' (V ∩ W) := image_subset _ (inter_subset_inter_right _ ‹_›)
_ = f '' (f ⁻¹' U) := by rw [h]
_ ⊆ U := image_preimage_subset f U
#align filter.push_pull Filter.push_pull
protected theorem push_pull' (f : α → β) (F : Filter α) (G : Filter β) :
map f (comap f G ⊓ F) = G ⊓ map f F := by simp only [Filter.push_pull, inf_comm]
#align filter.push_pull' Filter.push_pull'
theorem principal_eq_map_coe_top (s : Set α) : 𝓟 s = map ((↑) : s → α) ⊤ := by simp
#align filter.principal_eq_map_coe_top Filter.principal_eq_map_coe_top
theorem inf_principal_eq_bot_iff_comap {F : Filter α} {s : Set α} :
F ⊓ 𝓟 s = ⊥ ↔ comap ((↑) : s → α) F = ⊥ := by
rw [principal_eq_map_coe_top s, ← Filter.push_pull', inf_top_eq, map_eq_bot_iff]
#align filter.inf_principal_eq_bot_iff_comap Filter.inf_principal_eq_bot_iff_comap
section Applicative
theorem singleton_mem_pure {a : α} : {a} ∈ (pure a : Filter α) :=
mem_singleton a
#align filter.singleton_mem_pure Filter.singleton_mem_pure
theorem pure_injective : Injective (pure : α → Filter α) := fun a _ hab =>
(Filter.ext_iff.1 hab { x | a = x }).1 rfl
#align filter.pure_injective Filter.pure_injective
instance pure_neBot {α : Type u} {a : α} : NeBot (pure a) :=
⟨mt empty_mem_iff_bot.2 <| not_mem_empty a⟩
#align filter.pure_ne_bot Filter.pure_neBot
@[simp]
theorem le_pure_iff {f : Filter α} {a : α} : f ≤ pure a ↔ {a} ∈ f := by
rw [← principal_singleton, le_principal_iff]
#align filter.le_pure_iff Filter.le_pure_iff
theorem mem_seq_def {f : Filter (α → β)} {g : Filter α} {s : Set β} :
s ∈ f.seq g ↔ ∃ u ∈ f, ∃ t ∈ g, ∀ x ∈ u, ∀ y ∈ t, (x : α → β) y ∈ s :=
Iff.rfl
#align filter.mem_seq_def Filter.mem_seq_def
theorem mem_seq_iff {f : Filter (α → β)} {g : Filter α} {s : Set β} :
s ∈ f.seq g ↔ ∃ u ∈ f, ∃ t ∈ g, Set.seq u t ⊆ s := by
simp only [mem_seq_def, seq_subset, exists_prop, iff_self_iff]
#align filter.mem_seq_iff Filter.mem_seq_iff
theorem mem_map_seq_iff {f : Filter α} {g : Filter β} {m : α → β → γ} {s : Set γ} :
s ∈ (f.map m).seq g ↔ ∃ t u, t ∈ g ∧ u ∈ f ∧ ∀ x ∈ u, ∀ y ∈ t, m x y ∈ s :=
Iff.intro (fun ⟨t, ht, s, hs, hts⟩ => ⟨s, m ⁻¹' t, hs, ht, fun _ => hts _⟩)
fun ⟨t, s, ht, hs, hts⟩ =>
⟨m '' s, image_mem_map hs, t, ht, fun _ ⟨_, has, Eq⟩ => Eq ▸ hts _ has⟩
#align filter.mem_map_seq_iff Filter.mem_map_seq_iff
theorem seq_mem_seq {f : Filter (α → β)} {g : Filter α} {s : Set (α → β)} {t : Set α} (hs : s ∈ f)
(ht : t ∈ g) : s.seq t ∈ f.seq g :=
⟨s, hs, t, ht, fun f hf a ha => ⟨f, hf, a, ha, rfl⟩⟩
#align filter.seq_mem_seq Filter.seq_mem_seq
theorem le_seq {f : Filter (α → β)} {g : Filter α} {h : Filter β}
(hh : ∀ t ∈ f, ∀ u ∈ g, Set.seq t u ∈ h) : h ≤ seq f g := fun _ ⟨_, ht, _, hu, hs⟩ =>
mem_of_superset (hh _ ht _ hu) fun _ ⟨_, hm, _, ha, eq⟩ => eq ▸ hs _ hm _ ha
#align filter.le_seq Filter.le_seq
@[mono]
theorem seq_mono {f₁ f₂ : Filter (α → β)} {g₁ g₂ : Filter α} (hf : f₁ ≤ f₂) (hg : g₁ ≤ g₂) :
f₁.seq g₁ ≤ f₂.seq g₂ :=
le_seq fun _ hs _ ht => seq_mem_seq (hf hs) (hg ht)
#align filter.seq_mono Filter.seq_mono
@[simp]
theorem pure_seq_eq_map (g : α → β) (f : Filter α) : seq (pure g) f = f.map g := by
refine le_antisymm (le_map fun s hs => ?_) (le_seq fun s hs t ht => ?_)
· rw [← singleton_seq]
apply seq_mem_seq _ hs
exact singleton_mem_pure
· refine sets_of_superset (map g f) (image_mem_map ht) ?_
rintro b ⟨a, ha, rfl⟩
exact ⟨g, hs, a, ha, rfl⟩
#align filter.pure_seq_eq_map Filter.pure_seq_eq_map
@[simp]
theorem seq_pure (f : Filter (α → β)) (a : α) : seq f (pure a) = map (fun g : α → β => g a) f := by
refine le_antisymm (le_map fun s hs => ?_) (le_seq fun s hs t ht => ?_)
· rw [← seq_singleton]
exact seq_mem_seq hs singleton_mem_pure
· refine sets_of_superset (map (fun g : α → β => g a) f) (image_mem_map hs) ?_
rintro b ⟨g, hg, rfl⟩
exact ⟨g, hg, a, ht, rfl⟩
#align filter.seq_pure Filter.seq_pure
@[simp]
theorem seq_assoc (x : Filter α) (g : Filter (α → β)) (h : Filter (β → γ)) :
seq h (seq g x) = seq (seq (map (· ∘ ·) h) g) x := by
refine le_antisymm (le_seq fun s hs t ht => ?_) (le_seq fun s hs t ht => ?_)
· rcases mem_seq_iff.1 hs with ⟨u, hu, v, hv, hs⟩
rcases mem_map_iff_exists_image.1 hu with ⟨w, hw, hu⟩
refine mem_of_superset ?_ (Set.seq_mono ((Set.seq_mono hu Subset.rfl).trans hs) Subset.rfl)
rw [← Set.seq_seq]
exact seq_mem_seq hw (seq_mem_seq hv ht)
· rcases mem_seq_iff.1 ht with ⟨u, hu, v, hv, ht⟩
refine mem_of_superset ?_ (Set.seq_mono Subset.rfl ht)
rw [Set.seq_seq]
exact seq_mem_seq (seq_mem_seq (image_mem_map hs) hu) hv
#align filter.seq_assoc Filter.seq_assoc
theorem prod_map_seq_comm (f : Filter α) (g : Filter β) :
(map Prod.mk f).seq g = seq (map (fun b a => (a, b)) g) f := by
refine le_antisymm (le_seq fun s hs t ht => ?_) (le_seq fun s hs t ht => ?_)
· rcases mem_map_iff_exists_image.1 hs with ⟨u, hu, hs⟩
refine mem_of_superset ?_ (Set.seq_mono hs Subset.rfl)
rw [← Set.prod_image_seq_comm]
exact seq_mem_seq (image_mem_map ht) hu
· rcases mem_map_iff_exists_image.1 hs with ⟨u, hu, hs⟩
refine mem_of_superset ?_ (Set.seq_mono hs Subset.rfl)
rw [Set.prod_image_seq_comm]
exact seq_mem_seq (image_mem_map ht) hu
#align filter.prod_map_seq_comm Filter.prod_map_seq_comm
theorem seq_eq_filter_seq {α β : Type u} (f : Filter (α → β)) (g : Filter α) :
f <*> g = seq f g :=
rfl
#align filter.seq_eq_filter_seq Filter.seq_eq_filter_seq
instance : LawfulApplicative (Filter : Type u → Type u) where
map_pure := map_pure
seqLeft_eq _ _ := rfl
seqRight_eq _ _ := rfl
seq_pure := seq_pure
pure_seq := pure_seq_eq_map
seq_assoc := seq_assoc
instance : CommApplicative (Filter : Type u → Type u) :=
⟨fun f g => prod_map_seq_comm f g⟩
end Applicative
/-! #### `bind` equations -/
section Bind
@[simp]
theorem eventually_bind {f : Filter α} {m : α → Filter β} {p : β → Prop} :
(∀ᶠ y in bind f m, p y) ↔ ∀ᶠ x in f, ∀ᶠ y in m x, p y :=
Iff.rfl
#align filter.eventually_bind Filter.eventually_bind
@[simp]
theorem eventuallyEq_bind {f : Filter α} {m : α → Filter β} {g₁ g₂ : β → γ} :
g₁ =ᶠ[bind f m] g₂ ↔ ∀ᶠ x in f, g₁ =ᶠ[m x] g₂ :=
Iff.rfl
#align filter.eventually_eq_bind Filter.eventuallyEq_bind
@[simp]
theorem eventuallyLE_bind [LE γ] {f : Filter α} {m : α → Filter β} {g₁ g₂ : β → γ} :
g₁ ≤ᶠ[bind f m] g₂ ↔ ∀ᶠ x in f, g₁ ≤ᶠ[m x] g₂ :=
Iff.rfl
#align filter.eventually_le_bind Filter.eventuallyLE_bind
theorem mem_bind' {s : Set β} {f : Filter α} {m : α → Filter β} :
s ∈ bind f m ↔ { a | s ∈ m a } ∈ f :=
Iff.rfl
#align filter.mem_bind' Filter.mem_bind'
@[simp]
theorem mem_bind {s : Set β} {f : Filter α} {m : α → Filter β} :
s ∈ bind f m ↔ ∃ t ∈ f, ∀ x ∈ t, s ∈ m x :=
calc
s ∈ bind f m ↔ { a | s ∈ m a } ∈ f := Iff.rfl
_ ↔ ∃ t ∈ f, t ⊆ { a | s ∈ m a } := exists_mem_subset_iff.symm
_ ↔ ∃ t ∈ f, ∀ x ∈ t, s ∈ m x := Iff.rfl
#align filter.mem_bind Filter.mem_bind
theorem bind_le {f : Filter α} {g : α → Filter β} {l : Filter β} (h : ∀ᶠ x in f, g x ≤ l) :
f.bind g ≤ l :=
join_le <| eventually_map.2 h
#align filter.bind_le Filter.bind_le
@[mono]
theorem bind_mono {f₁ f₂ : Filter α} {g₁ g₂ : α → Filter β} (hf : f₁ ≤ f₂) (hg : g₁ ≤ᶠ[f₁] g₂) :
bind f₁ g₁ ≤ bind f₂ g₂ := by
refine le_trans (fun s hs => ?_) (join_mono <| map_mono hf)
simp only [mem_join, mem_bind', mem_map] at hs ⊢
filter_upwards [hg, hs] with _ hx hs using hx hs
#align filter.bind_mono Filter.bind_mono
theorem bind_inf_principal {f : Filter α} {g : α → Filter β} {s : Set β} :
(f.bind fun x => g x ⊓ 𝓟 s) = f.bind g ⊓ 𝓟 s :=
Filter.ext fun s => by simp only [mem_bind, mem_inf_principal]
#align filter.bind_inf_principal Filter.bind_inf_principal
theorem sup_bind {f g : Filter α} {h : α → Filter β} : bind (f ⊔ g) h = bind f h ⊔ bind g h := rfl
#align filter.sup_bind Filter.sup_bind
theorem principal_bind {s : Set α} {f : α → Filter β} : bind (𝓟 s) f = ⨆ x ∈ s, f x :=
show join (map f (𝓟 s)) = ⨆ x ∈ s, f x by
simp only [sSup_image, join_principal_eq_sSup, map_principal, eq_self_iff_true]
#align filter.principal_bind Filter.principal_bind
end Bind
/-! ### Limits -/
/-- `Filter.Tendsto` is the generic "limit of a function" predicate.
`Tendsto f l₁ l₂` asserts that for every `l₂` neighborhood `a`,
the `f`-preimage of `a` is an `l₁` neighborhood. -/
def Tendsto (f : α → β) (l₁ : Filter α) (l₂ : Filter β) :=
l₁.map f ≤ l₂
#align filter.tendsto Filter.Tendsto
theorem tendsto_def {f : α → β} {l₁ : Filter α} {l₂ : Filter β} :
Tendsto f l₁ l₂ ↔ ∀ s ∈ l₂, f ⁻¹' s ∈ l₁ :=
Iff.rfl
#align filter.tendsto_def Filter.tendsto_def
theorem tendsto_iff_eventually {f : α → β} {l₁ : Filter α} {l₂ : Filter β} :
Tendsto f l₁ l₂ ↔ ∀ ⦃p : β → Prop⦄, (∀ᶠ y in l₂, p y) → ∀ᶠ x in l₁, p (f x) :=
Iff.rfl
#align filter.tendsto_iff_eventually Filter.tendsto_iff_eventually
theorem tendsto_iff_forall_eventually_mem {f : α → β} {l₁ : Filter α} {l₂ : Filter β} :
Tendsto f l₁ l₂ ↔ ∀ s ∈ l₂, ∀ᶠ x in l₁, f x ∈ s :=
Iff.rfl
#align filter.tendsto_iff_forall_eventually_mem Filter.tendsto_iff_forall_eventually_mem
lemma Tendsto.eventually_mem {f : α → β} {l₁ : Filter α} {l₂ : Filter β} {s : Set β}
(hf : Tendsto f l₁ l₂) (h : s ∈ l₂) : ∀ᶠ x in l₁, f x ∈ s :=
hf h
theorem Tendsto.eventually {f : α → β} {l₁ : Filter α} {l₂ : Filter β} {p : β → Prop}
(hf : Tendsto f l₁ l₂) (h : ∀ᶠ y in l₂, p y) : ∀ᶠ x in l₁, p (f x) :=
hf h
#align filter.tendsto.eventually Filter.Tendsto.eventually
theorem not_tendsto_iff_exists_frequently_nmem {f : α → β} {l₁ : Filter α} {l₂ : Filter β} :
¬Tendsto f l₁ l₂ ↔ ∃ s ∈ l₂, ∃ᶠ x in l₁, f x ∉ s := by
simp only [tendsto_iff_forall_eventually_mem, not_forall, exists_prop, not_eventually]
#align filter.not_tendsto_iff_exists_frequently_nmem Filter.not_tendsto_iff_exists_frequently_nmem
theorem Tendsto.frequently {f : α → β} {l₁ : Filter α} {l₂ : Filter β} {p : β → Prop}
(hf : Tendsto f l₁ l₂) (h : ∃ᶠ x in l₁, p (f x)) : ∃ᶠ y in l₂, p y :=
mt hf.eventually h
#align filter.tendsto.frequently Filter.Tendsto.frequently
theorem Tendsto.frequently_map {l₁ : Filter α} {l₂ : Filter β} {p : α → Prop} {q : β → Prop}
(f : α → β) (c : Filter.Tendsto f l₁ l₂) (w : ∀ x, p x → q (f x)) (h : ∃ᶠ x in l₁, p x) :
∃ᶠ y in l₂, q y :=
c.frequently (h.mono w)
#align filter.tendsto.frequently_map Filter.Tendsto.frequently_map
@[simp]
theorem tendsto_bot {f : α → β} {l : Filter β} : Tendsto f ⊥ l := by simp [Tendsto]
#align filter.tendsto_bot Filter.tendsto_bot
@[simp] theorem tendsto_top {f : α → β} {l : Filter α} : Tendsto f l ⊤ := le_top
#align filter.tendsto_top Filter.tendsto_top
theorem le_map_of_right_inverse {mab : α → β} {mba : β → α} {f : Filter α} {g : Filter β}
(h₁ : mab ∘ mba =ᶠ[g] id) (h₂ : Tendsto mba g f) : g ≤ map mab f := by
rw [← @map_id _ g, ← map_congr h₁, ← map_map]
exact map_mono h₂
#align filter.le_map_of_right_inverse Filter.le_map_of_right_inverse
theorem tendsto_of_isEmpty [IsEmpty α] {f : α → β} {la : Filter α} {lb : Filter β} :
Tendsto f la lb := by simp only [filter_eq_bot_of_isEmpty la, tendsto_bot]
#align filter.tendsto_of_is_empty Filter.tendsto_of_isEmpty
theorem eventuallyEq_of_left_inv_of_right_inv {f : α → β} {g₁ g₂ : β → α} {fa : Filter α}
{fb : Filter β} (hleft : ∀ᶠ x in fa, g₁ (f x) = x) (hright : ∀ᶠ y in fb, f (g₂ y) = y)
(htendsto : Tendsto g₂ fb fa) : g₁ =ᶠ[fb] g₂ :=
(htendsto.eventually hleft).mp <| hright.mono fun _ hr hl => (congr_arg g₁ hr.symm).trans hl
#align filter.eventually_eq_of_left_inv_of_right_inv Filter.eventuallyEq_of_left_inv_of_right_inv
theorem tendsto_iff_comap {f : α → β} {l₁ : Filter α} {l₂ : Filter β} :
Tendsto f l₁ l₂ ↔ l₁ ≤ l₂.comap f :=
map_le_iff_le_comap
#align filter.tendsto_iff_comap Filter.tendsto_iff_comap
alias ⟨Tendsto.le_comap, _⟩ := tendsto_iff_comap
#align filter.tendsto.le_comap Filter.Tendsto.le_comap
protected theorem Tendsto.disjoint {f : α → β} {la₁ la₂ : Filter α} {lb₁ lb₂ : Filter β}
(h₁ : Tendsto f la₁ lb₁) (hd : Disjoint lb₁ lb₂) (h₂ : Tendsto f la₂ lb₂) : Disjoint la₁ la₂ :=
(disjoint_comap hd).mono h₁.le_comap h₂.le_comap
#align filter.tendsto.disjoint Filter.Tendsto.disjoint
theorem tendsto_congr' {f₁ f₂ : α → β} {l₁ : Filter α} {l₂ : Filter β} (hl : f₁ =ᶠ[l₁] f₂) :
Tendsto f₁ l₁ l₂ ↔ Tendsto f₂ l₁ l₂ := by rw [Tendsto, Tendsto, map_congr hl]
#align filter.tendsto_congr' Filter.tendsto_congr'
theorem Tendsto.congr' {f₁ f₂ : α → β} {l₁ : Filter α} {l₂ : Filter β} (hl : f₁ =ᶠ[l₁] f₂)
(h : Tendsto f₁ l₁ l₂) : Tendsto f₂ l₁ l₂ :=
(tendsto_congr' hl).1 h
#align filter.tendsto.congr' Filter.Tendsto.congr'
theorem tendsto_congr {f₁ f₂ : α → β} {l₁ : Filter α} {l₂ : Filter β} (h : ∀ x, f₁ x = f₂ x) :
Tendsto f₁ l₁ l₂ ↔ Tendsto f₂ l₁ l₂ :=
tendsto_congr' (univ_mem' h)
#align filter.tendsto_congr Filter.tendsto_congr
theorem Tendsto.congr {f₁ f₂ : α → β} {l₁ : Filter α} {l₂ : Filter β} (h : ∀ x, f₁ x = f₂ x) :
Tendsto f₁ l₁ l₂ → Tendsto f₂ l₁ l₂ :=
(tendsto_congr h).1
#align filter.tendsto.congr Filter.Tendsto.congr
theorem tendsto_id' {x y : Filter α} : Tendsto id x y ↔ x ≤ y :=
Iff.rfl
#align filter.tendsto_id' Filter.tendsto_id'
theorem tendsto_id {x : Filter α} : Tendsto id x x :=
le_refl x
#align filter.tendsto_id Filter.tendsto_id
theorem Tendsto.comp {f : α → β} {g : β → γ} {x : Filter α} {y : Filter β} {z : Filter γ}
(hg : Tendsto g y z) (hf : Tendsto f x y) : Tendsto (g ∘ f) x z := fun _ hs => hf (hg hs)
#align filter.tendsto.comp Filter.Tendsto.comp
protected theorem Tendsto.iterate {f : α → α} {l : Filter α} (h : Tendsto f l l) :
∀ n, Tendsto (f^[n]) l l
| 0 => tendsto_id
| (n + 1) => (h.iterate n).comp h
theorem Tendsto.mono_left {f : α → β} {x y : Filter α} {z : Filter β} (hx : Tendsto f x z)
(h : y ≤ x) : Tendsto f y z :=
(map_mono h).trans hx
#align filter.tendsto.mono_left Filter.Tendsto.mono_left
theorem Tendsto.mono_right {f : α → β} {x : Filter α} {y z : Filter β} (hy : Tendsto f x y)
(hz : y ≤ z) : Tendsto f x z :=
le_trans hy hz
#align filter.tendsto.mono_right Filter.Tendsto.mono_right
theorem Tendsto.neBot {f : α → β} {x : Filter α} {y : Filter β} (h : Tendsto f x y) [hx : NeBot x] :
NeBot y :=
(hx.map _).mono h
#align filter.tendsto.ne_bot Filter.Tendsto.neBot
theorem tendsto_map {f : α → β} {x : Filter α} : Tendsto f x (map f x) :=
le_refl (map f x)
#align filter.tendsto_map Filter.tendsto_map
@[simp]
theorem tendsto_map'_iff {f : β → γ} {g : α → β} {x : Filter α} {y : Filter γ} :
Tendsto f (map g x) y ↔ Tendsto (f ∘ g) x y := by
rw [Tendsto, Tendsto, map_map]
#align filter.tendsto_map'_iff Filter.tendsto_map'_iff
alias ⟨_, tendsto_map'⟩ := tendsto_map'_iff
#align filter.tendsto_map' Filter.tendsto_map'
theorem tendsto_comap {f : α → β} {x : Filter β} : Tendsto f (comap f x) x :=
map_comap_le
#align filter.tendsto_comap Filter.tendsto_comap
@[simp]
theorem tendsto_comap_iff {f : α → β} {g : β → γ} {a : Filter α} {c : Filter γ} :
Tendsto f a (c.comap g) ↔ Tendsto (g ∘ f) a c :=
⟨fun h => tendsto_comap.comp h, fun h => map_le_iff_le_comap.mp <| by rwa [map_map]⟩
#align filter.tendsto_comap_iff Filter.tendsto_comap_iff
theorem tendsto_comap'_iff {m : α → β} {f : Filter α} {g : Filter β} {i : γ → α} (h : range i ∈ f) :
Tendsto (m ∘ i) (comap i f) g ↔ Tendsto m f g := by
rw [Tendsto, ← map_compose]
simp only [(· ∘ ·), map_comap_of_mem h, Tendsto]
#align filter.tendsto_comap'_iff Filter.tendsto_comap'_iff
theorem Tendsto.of_tendsto_comp {f : α → β} {g : β → γ} {a : Filter α} {b : Filter β} {c : Filter γ}
(hfg : Tendsto (g ∘ f) a c) (hg : comap g c ≤ b) : Tendsto f a b := by
rw [tendsto_iff_comap] at hfg ⊢
calc
a ≤ comap (g ∘ f) c := hfg
_ ≤ comap f b := by simpa [comap_comap] using comap_mono hg
#align filter.tendsto.of_tendsto_comp Filter.Tendsto.of_tendsto_comp
theorem comap_eq_of_inverse {f : Filter α} {g : Filter β} {φ : α → β} (ψ : β → α) (eq : ψ ∘ φ = id)
(hφ : Tendsto φ f g) (hψ : Tendsto ψ g f) : comap φ g = f := by
refine ((comap_mono <| map_le_iff_le_comap.1 hψ).trans ?_).antisymm (map_le_iff_le_comap.1 hφ)
rw [comap_comap, eq, comap_id]
#align filter.comap_eq_of_inverse Filter.comap_eq_of_inverse
theorem map_eq_of_inverse {f : Filter α} {g : Filter β} {φ : α → β} (ψ : β → α) (eq : φ ∘ ψ = id)
(hφ : Tendsto φ f g) (hψ : Tendsto ψ g f) : map φ f = g := by
refine le_antisymm hφ (le_trans ?_ (map_mono hψ))
rw [map_map, eq, map_id]
#align filter.map_eq_of_inverse Filter.map_eq_of_inverse
theorem tendsto_inf {f : α → β} {x : Filter α} {y₁ y₂ : Filter β} :
Tendsto f x (y₁ ⊓ y₂) ↔ Tendsto f x y₁ ∧ Tendsto f x y₂ := by
simp only [Tendsto, le_inf_iff, iff_self_iff]
#align filter.tendsto_inf Filter.tendsto_inf
theorem tendsto_inf_left {f : α → β} {x₁ x₂ : Filter α} {y : Filter β} (h : Tendsto f x₁ y) :
Tendsto f (x₁ ⊓ x₂) y :=
le_trans (map_mono inf_le_left) h
#align filter.tendsto_inf_left Filter.tendsto_inf_left
theorem tendsto_inf_right {f : α → β} {x₁ x₂ : Filter α} {y : Filter β} (h : Tendsto f x₂ y) :
Tendsto f (x₁ ⊓ x₂) y :=
le_trans (map_mono inf_le_right) h
#align filter.tendsto_inf_right Filter.tendsto_inf_right
theorem Tendsto.inf {f : α → β} {x₁ x₂ : Filter α} {y₁ y₂ : Filter β} (h₁ : Tendsto f x₁ y₁)
(h₂ : Tendsto f x₂ y₂) : Tendsto f (x₁ ⊓ x₂) (y₁ ⊓ y₂) :=
tendsto_inf.2 ⟨tendsto_inf_left h₁, tendsto_inf_right h₂⟩
#align filter.tendsto.inf Filter.Tendsto.inf
@[simp]
theorem tendsto_iInf {f : α → β} {x : Filter α} {y : ι → Filter β} :
Tendsto f x (⨅ i, y i) ↔ ∀ i, Tendsto f x (y i) := by
simp only [Tendsto, iff_self_iff, le_iInf_iff]
#align filter.tendsto_infi Filter.tendsto_iInf
theorem tendsto_iInf' {f : α → β} {x : ι → Filter α} {y : Filter β} (i : ι)
(hi : Tendsto f (x i) y) : Tendsto f (⨅ i, x i) y :=
hi.mono_left <| iInf_le _ _
#align filter.tendsto_infi' Filter.tendsto_iInf'
theorem tendsto_iInf_iInf {f : α → β} {x : ι → Filter α} {y : ι → Filter β}
(h : ∀ i, Tendsto f (x i) (y i)) : Tendsto f (iInf x) (iInf y) :=
tendsto_iInf.2 fun i => tendsto_iInf' i (h i)
#align filter.tendsto_infi_infi Filter.tendsto_iInf_iInf
@[simp]
theorem tendsto_sup {f : α → β} {x₁ x₂ : Filter α} {y : Filter β} :
Tendsto f (x₁ ⊔ x₂) y ↔ Tendsto f x₁ y ∧ Tendsto f x₂ y := by
simp only [Tendsto, map_sup, sup_le_iff]
#align filter.tendsto_sup Filter.tendsto_sup
theorem Tendsto.sup {f : α → β} {x₁ x₂ : Filter α} {y : Filter β} :
Tendsto f x₁ y → Tendsto f x₂ y → Tendsto f (x₁ ⊔ x₂) y := fun h₁ h₂ => tendsto_sup.mpr ⟨h₁, h₂⟩
#align filter.tendsto.sup Filter.Tendsto.sup
theorem Tendsto.sup_sup {f : α → β} {x₁ x₂ : Filter α} {y₁ y₂ : Filter β}
(h₁ : Tendsto f x₁ y₁) (h₂ : Tendsto f x₂ y₂) : Tendsto f (x₁ ⊔ x₂) (y₁ ⊔ y₂) :=
tendsto_sup.mpr ⟨h₁.mono_right le_sup_left, h₂.mono_right le_sup_right⟩
@[simp]
theorem tendsto_iSup {f : α → β} {x : ι → Filter α} {y : Filter β} :
Tendsto f (⨆ i, x i) y ↔ ∀ i, Tendsto f (x i) y := by simp only [Tendsto, map_iSup, iSup_le_iff]
#align filter.tendsto_supr Filter.tendsto_iSup
theorem tendsto_iSup_iSup {f : α → β} {x : ι → Filter α} {y : ι → Filter β}
(h : ∀ i, Tendsto f (x i) (y i)) : Tendsto f (iSup x) (iSup y) :=
tendsto_iSup.2 fun i => (h i).mono_right <| le_iSup _ _
#align filter.tendsto_supr_supr Filter.tendsto_iSup_iSup
@[simp] theorem tendsto_principal {f : α → β} {l : Filter α} {s : Set β} :
Tendsto f l (𝓟 s) ↔ ∀ᶠ a in l, f a ∈ s := by
simp only [Tendsto, le_principal_iff, mem_map', Filter.Eventually]
#align filter.tendsto_principal Filter.tendsto_principal
-- Porting note: was a `simp` lemma
theorem tendsto_principal_principal {f : α → β} {s : Set α} {t : Set β} :
Tendsto f (𝓟 s) (𝓟 t) ↔ ∀ a ∈ s, f a ∈ t := by
simp only [tendsto_principal, eventually_principal]
#align filter.tendsto_principal_principal Filter.tendsto_principal_principal
@[simp] theorem tendsto_pure {f : α → β} {a : Filter α} {b : β} :
Tendsto f a (pure b) ↔ ∀ᶠ x in a, f x = b := by
simp only [Tendsto, le_pure_iff, mem_map', mem_singleton_iff, Filter.Eventually]
#align filter.tendsto_pure Filter.tendsto_pure
theorem tendsto_pure_pure (f : α → β) (a : α) : Tendsto f (pure a) (pure (f a)) :=
tendsto_pure.2 rfl
#align filter.tendsto_pure_pure Filter.tendsto_pure_pure
theorem tendsto_const_pure {a : Filter α} {b : β} : Tendsto (fun _ => b) a (pure b) :=
tendsto_pure.2 <| univ_mem' fun _ => rfl
#align filter.tendsto_const_pure Filter.tendsto_const_pure
theorem pure_le_iff {a : α} {l : Filter α} : pure a ≤ l ↔ ∀ s ∈ l, a ∈ s :=
Iff.rfl
#align filter.pure_le_iff Filter.pure_le_iff
theorem tendsto_pure_left {f : α → β} {a : α} {l : Filter β} :
Tendsto f (pure a) l ↔ ∀ s ∈ l, f a ∈ s :=
Iff.rfl
#align filter.tendsto_pure_left Filter.tendsto_pure_left
@[simp]
theorem map_inf_principal_preimage {f : α → β} {s : Set β} {l : Filter α} :
map f (l ⊓ 𝓟 (f ⁻¹' s)) = map f l ⊓ 𝓟 s :=
Filter.ext fun t => by simp only [mem_map', mem_inf_principal, mem_setOf_eq, mem_preimage]
#align filter.map_inf_principal_preimage Filter.map_inf_principal_preimage
/-- If two filters are disjoint, then a function cannot tend to both of them along a non-trivial
filter. -/
theorem Tendsto.not_tendsto {f : α → β} {a : Filter α} {b₁ b₂ : Filter β} (hf : Tendsto f a b₁)
[NeBot a] (hb : Disjoint b₁ b₂) : ¬Tendsto f a b₂ := fun hf' =>
(tendsto_inf.2 ⟨hf, hf'⟩).neBot.ne hb.eq_bot
#align filter.tendsto.not_tendsto Filter.Tendsto.not_tendsto
protected theorem Tendsto.if {l₁ : Filter α} {l₂ : Filter β} {f g : α → β} {p : α → Prop}
[∀ x, Decidable (p x)] (h₀ : Tendsto f (l₁ ⊓ 𝓟 { x | p x }) l₂)
(h₁ : Tendsto g (l₁ ⊓ 𝓟 { x | ¬p x }) l₂) :
Tendsto (fun x => if p x then f x else g x) l₁ l₂ := by
simp only [tendsto_def, mem_inf_principal] at *
intro s hs
filter_upwards [h₀ s hs, h₁ s hs] with x hp₀ hp₁
rw [mem_preimage]
split_ifs with h
exacts [hp₀ h, hp₁ h]
#align filter.tendsto.if Filter.Tendsto.if
protected theorem Tendsto.if' {α β : Type*} {l₁ : Filter α} {l₂ : Filter β} {f g : α → β}
{p : α → Prop} [DecidablePred p] (hf : Tendsto f l₁ l₂) (hg : Tendsto g l₁ l₂) :
Tendsto (fun a => if p a then f a else g a) l₁ l₂ :=
(tendsto_inf_left hf).if (tendsto_inf_left hg)
#align filter.tendsto.if' Filter.Tendsto.if'
protected theorem Tendsto.piecewise {l₁ : Filter α} {l₂ : Filter β} {f g : α → β} {s : Set α}
[∀ x, Decidable (x ∈ s)] (h₀ : Tendsto f (l₁ ⊓ 𝓟 s) l₂) (h₁ : Tendsto g (l₁ ⊓ 𝓟 sᶜ) l₂) :
Tendsto (piecewise s f g) l₁ l₂ :=
Tendsto.if h₀ h₁
#align filter.tendsto.piecewise Filter.Tendsto.piecewise
end Filter
open Filter
theorem Set.EqOn.eventuallyEq {α β} {s : Set α} {f g : α → β} (h : EqOn f g s) : f =ᶠ[𝓟 s] g :=
h
#align set.eq_on.eventually_eq Set.EqOn.eventuallyEq
theorem Set.EqOn.eventuallyEq_of_mem {α β} {s : Set α} {l : Filter α} {f g : α → β} (h : EqOn f g s)
(hl : s ∈ l) : f =ᶠ[l] g :=
h.eventuallyEq.filter_mono <| Filter.le_principal_iff.2 hl
#align set.eq_on.eventually_eq_of_mem Set.EqOn.eventuallyEq_of_mem
theorem HasSubset.Subset.eventuallyLE {α} {l : Filter α} {s t : Set α} (h : s ⊆ t) : s ≤ᶠ[l] t :=
Filter.eventually_of_forall h
#align has_subset.subset.eventually_le HasSubset.Subset.eventuallyLE
theorem Set.MapsTo.tendsto {α β} {s : Set α} {t : Set β} {f : α → β} (h : MapsTo f s t) :
Filter.Tendsto f (𝓟 s) (𝓟 t) :=
Filter.tendsto_principal_principal.2 h
#align set.maps_to.tendsto Set.MapsTo.tendsto
theorem Filter.EventuallyEq.comp_tendsto {f' : α → β} (H : f =ᶠ[l] f') {g : γ → α} {lc : Filter γ}
(hg : Tendsto g lc l) : f ∘ g =ᶠ[lc] f' ∘ g :=
hg.eventually H
#align filter.eventually_eq.comp_tendsto Filter.EventuallyEq.comp_tendsto
theorem Filter.map_mapsTo_Iic_iff_tendsto {m : α → β} :
MapsTo (map m) (Iic F) (Iic G) ↔ Tendsto m F G :=
⟨fun hm ↦ hm right_mem_Iic, fun hm _ ↦ hm.mono_left⟩
alias ⟨_, Filter.Tendsto.map_mapsTo_Iic⟩ := Filter.map_mapsTo_Iic_iff_tendsto
theorem Filter.map_mapsTo_Iic_iff_mapsTo {m : α → β} :
MapsTo (map m) (Iic <| 𝓟 s) (Iic <| 𝓟 t) ↔ MapsTo m s t := by
rw [map_mapsTo_Iic_iff_tendsto, tendsto_principal_principal, MapsTo]
alias ⟨_, Set.MapsTo.filter_map_Iic⟩ := Filter.map_mapsTo_Iic_iff_mapsTo
-- TODO(Anatole): unify with the global case
| Mathlib/Order/Filter/Basic.lean | 3,360 | 3,367 | theorem Filter.map_surjOn_Iic_iff_le_map {m : α → β} :
SurjOn (map m) (Iic F) (Iic G) ↔ G ≤ map m F := by |
refine ⟨fun hm ↦ ?_, fun hm ↦ ?_⟩
· rcases hm right_mem_Iic with ⟨H, (hHF : H ≤ F), rfl⟩
exact map_mono hHF
· have : RightInvOn (F ⊓ comap m ·) (map m) (Iic G) :=
fun H (hHG : H ≤ G) ↦ by simpa [Filter.push_pull] using hHG.trans hm
exact this.surjOn fun H _ ↦ mem_Iic.mpr inf_le_left
|
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