open_bundle vec_syntax begin notation vec_nth (infixl‹$›90) and vec_lambda (binder‹χ›10) end
text‹
Concrete syntax for ‹('a, 'b) vec›: ▪‹'a^'b› becomes ‹('a, 'b::finite) vec› ▪‹'a^'b::_› becomes ‹('a, 'b) vec› without extra sort-constraint › syntax"_vec_type" :: "type → type → type" (infixl‹^›15)
syntax_types "_vec_type"⇌ vec parse_translation‹
let
fun vec t u = Syntax.const 🚫‹vec› $ t $ u;
fun finite_vec_tr [t, u] =
(case Term_Position.strip_positions u of
v as Free (x, _) =>
if Lexicon.is_tid x then
vec t (Syntax.const syntax_const‹_ofsort› $ v $
Syntax.const 🚫‹finite›)
else vec t u
| _ => vec t u)
in
[(syntax_const‹_vec_type›, K finite_vec_tr)]
end ›
lemma vec_lambda_beta [simp]: "vec_lambda g $ i = g i" by (simp add: vec_lambda_inverse)
lemma vec_lambda_unique: "(∀i. f$i = g i) ⟷ vec_lambda g = f" by (auto simp add: vec_eq_iff)
lemma vec_lambda_eta [simp]: "(χ i. (g$i)) = g" by (simp add: vec_eq_iff)
subsection‹Cardinality of vectors›
instance vec :: (finite, finite) finite proof show"finite (UNIV :: ('a, 'b) vec set)" proof (subst bij_betw_finite) show"bij_betw vec_nth UNIV (Pi (UNIV :: 'b set) (λ_. UNIV :: 'a set))" by (intro bij_betwI[of _ _ _ vec_lambda]) (auto simp: vec_eq_iff) have"finite (PiE (UNIV :: 'b set) (λ_. UNIV :: 'a set))" by (intro finite_PiE) auto alsohave"(PiE (UNIV :: 'b set) (λ_. UNIV :: 'a set)) = Pi UNIV (λ_. UNIV)" by auto finallyshow"finite …" . qed qed
lemma countable_PiE: "finite I ==> (∧i. i ∈ I ==> countable (F i)) ==> countable (PiE I F)" by (induct I arbitrary: F rule: finite_induct) (auto simp: PiE_insert_eq)
instance vec :: (countable, finite) countable proof have"countable (UNIV :: ('a, 'b) vec set)" proof (rule countableI_bij2) show"bij_betw vec_nth UNIV (Pi (UNIV :: 'b set) (λ_. UNIV :: 'a set))" by (intro bij_betwI[of _ _ _ vec_lambda]) (auto simp: vec_eq_iff) have"countable (PiE (UNIV :: 'b set) (λ_. UNIV :: 'a set))" by (intro countable_PiE) auto alsohave"(PiE (UNIV :: 'b set) (λ_. UNIV :: 'a set)) = Pi UNIV (λ_. UNIV)" by auto finallyshow"countable …" . qed thus"∃t::('a, 'b) vec → nat. inj t" by (auto elim!: countableE) qed
lemma infinite_UNIV_vec: assumes"infinite (UNIV :: 'a set)" shows"infinite (UNIV :: ('a^'b) set)" proof (subst bij_betw_finite) show"bij_betw vec_nth UNIV (Pi (UNIV :: 'b set) (λ_. UNIV :: 'a set))" by (intro bij_betwI[of _ _ _ vec_lambda]) (auto simp: vec_eq_iff) have"infinite (PiE (UNIV :: 'b set) (λ_. UNIV :: 'a set))" (is"infinite ?A") proof assume"finite ?A" hence"finite ((λf. f undefined) ` ?A)" by (rule finite_imageI) alsohave"(λf. f undefined) ` ?A = UNIV" by auto finallyshow False using‹infinite (UNIV :: 'a set)›by contradiction qed alsohave"?A = Pi UNIV (λ_. UNIV)" by auto finallyshow"infinite (Pi (UNIV :: 'b set) (λ_. UNIV :: 'a set))" . qed
proposition CARD_vec [simp]: "CARD('a^'b) = CARD('a) ^ CARD('b)" proof (cases "finite (UNIV :: 'a set)") case True show ?thesis proof (subst bij_betw_same_card) show"bij_betw vec_nth UNIV (Pi (UNIV :: 'b set) (λ_. UNIV :: 'a set))" by (intro bij_betwI[of _ _ _ vec_lambda]) (auto simp: vec_eq_iff) have"CARD('a) ^ CARD('b) = card (PiE (UNIV :: 'b set) (λ_. UNIV :: 'a set))"
(is"_ = card ?A") by (subst card_PiE) (auto) alsohave"?A = Pi UNIV (λ_. UNIV)" by auto finallyshow"card … = CARD('a) ^ CARD('b)" .. qed qed (simp_all add: infinite_UNIV_vec)
lemma countable_vector: fixes B:: "'n::finite → 'a set" assumes"∧i. countable (B i)" shows"countable {V. ∀i::'n::finite. V $ i ∈ B i}" proof - have"f ∈ ($) ` {V. ∀i. V $ i ∈ B i}"if"f ∈ PiE UNIV B"for f proof - have"∃W. (∀i. W $ i ∈ B i) ∧ ($) W = f" by (metis that PiE_iff UNIV_I vec_lambda_inverse) thenshow"f ∈ ($) ` {v. ∀i. v $ i ∈ B i}" by blast qed thenhave"PiE UNIV B = vec_nth ` {V. ∀i::'n. V $ i ∈ B i}" by blast thenhave"countable (vec_nth ` {V. ∀i. V $ i ∈ B i})" by (metis finite_class.finite_UNIV countable_PiE assms) thenhave"countable (vec_lambda ` vec_nth ` {V. ∀i. V $ i ∈ B i})" by auto thenshow ?thesis by (simp add: image_comp o_def vec_nth_inverse) qed
subsection✐‹tag unimportant›‹Group operations and class instances›
instantiation vec :: (zero, finite) zero begin definition"0 ≡ (χ i. 0)" instance .. end
instantiation vec :: (plus, finite) plus begin definition"(+) ≡ (λ x y. (χ i. x$i + y$i))" instance .. end
instantiation vec :: (minus, finite) minus begin definition"(-) ≡ (λ x y. (χ i. x$i - y$i))" instance .. end
instantiation vec :: (uminus, finite) uminus begin definition"uminus ≡ (λ x. (χ i. - (x$i)))" instance .. end
lemma zero_index [simp]: "0 $ i = 0" unfolding zero_vec_def by simp
instance\<^marker>\<open>tagunimportant\<close>vec::(perfect_space,finite)perfect_space proof fixx::"'a^'b"show"\<not>open{x}" proof assume"open{x}" hence"\<forall>i.open((\<lambda>x.x$i)`{x})"by(fastintro:open_image_vec_nth) hence"\<forall>i.open{x$i}"bysimp thus"False"by(simpadd:not_open_singleton) qed qed
subsection\<open>Metricspace\<close>
(* TODO: Product of uniform spaces and compatibility with metric_spaces! *)
instantiation✐‹tag unimportant› vec :: (metric_space, finite) dist begin
definition✐‹tag important› "dist x y = L2_set (λi. dist (x$i) (y$i)) UNIV"
instance .. end
instantiation✐‹tag unimportant› vec :: (metric_space, finite) uniformity_dist begin
definition✐‹tag important› [code del]: "(uniformity :: (('a^'b::_) × ('a^'b::_)) filter) = (INF e∈{0 <..}. principal {(x, y). dist x y < e})"
instance✐‹tag unimportant› by standard (rule uniformity_vec_def) end
instantiation✐‹tag unimportant› vec :: (metric_space, finite) metric_space begin
proposition dist_vec_nth_le: "dist (x $ i) (y $ i) ≤ dist x y" unfolding dist_vec_def by (rule member_le_L2_set) simp_all
instanceproof fix x y :: "'a ^ 'b" show"dist x y = 0 ⟷ x = y" unfolding dist_vec_def by (simp add: L2_set_eq_0_iff vec_eq_iff) next fix x y z :: "'a ^ 'b" show"dist x y ≤ dist x z + dist y z" unfolding dist_vec_def apply (rule order_trans [OF _ L2_set_triangle_ineq]) apply (simp add: L2_set_mono dist_triangle2) done next fix S :: "('a ^ 'b) set" have *: "open S ⟷ (∀x∈S. ∃e>0. ∀y. dist y x < e ⟶ y ∈ S)" proof assume"open S"show"∀x∈S. ∃e>0. ∀y. dist y x < e ⟶ y ∈ S" proof fix x assume"x ∈ S" obtain A where A: "∀i. open (A i)""∀i. x $ i ∈ A i" and S: "∀y. (∀i. y $ i ∈ A i) ⟶ y ∈ S" using‹open S›and‹x ∈ S›unfolding open_vec_def by metis have"∀i∈UNIV. ∃r>0. ∀y. dist y (x $ i) < r ⟶ y ∈ A i" using A unfolding open_dist by simp hence"∃r. ∀i∈UNIV. 0 < r i ∧ (∀y. dist y (x $ i) < r i ⟶ y ∈ A i)" by (rule finite_set_choice [OF finite]) thenobtain r where r1: "∀i. 0 < r i" and r2: "∀i y. dist y (x $ i) < r i ⟶ y ∈ A i"by fast have"0 < Min (range r) ∧ (∀y. dist y x < Min (range r) ⟶ y ∈ S)" by (simp add: r1 r2 S le_less_trans [OF dist_vec_nth_le]) thus"∃e>0. ∀y. dist y x < e ⟶ y ∈ S" .. qed next assume *: "∀x∈S. ∃e>0. ∀y. dist y x < e ⟶ y ∈ S"show"open S" proof (unfold open_vec_def, rule) fix x assume"x ∈ S" thenobtain e where"0 < e"and S: "∀y. dist y x < e ⟶ y ∈ S" using * by fast define r where [abs_def]: "r i = e / sqrt (of_nat CARD('b))"for i :: 'b from‹0 < e›have r: "∀i. 0 < r i" unfolding r_def by simp_all from‹0 < e›have e: "e = L2_set r UNIV" unfolding r_def by (simp add: L2_set_constant) define A where"A i = {y. dist (x $ i) y < r i}"for i have"∀i. open (A i) ∧ x $ i ∈ A i" unfolding A_def by (simp add: open_ball r) moreoverhave"∀y. (∀i. y $ i ∈ A i) ⟶ y ∈ S" by (simp add: A_def S dist_vec_def e L2_set_strict_mono dist_commute) ultimatelyshow"∃A. (∀i. open (A i) ∧ x $ i ∈ A i) ∧ (∀y. (∀i. y $ i ∈ A i) ⟶ y ∈ S)"by metis qed qed show"open S = (∀x∈S. ∀F (x', y) in uniformity. x' = x ⟶ y ∈ S)" unfolding * eventually_uniformity_metric by (simp del: split_paired_All add: dist_vec_def dist_commute) qed
end
lemma Cauchy_vec_nth: "Cauchy (λn. X n) ==> Cauchy (λn. X n $ i)" unfolding Cauchy_def by (fast intro: le_less_trans [OF dist_vec_nth_le])
lemma vec_CauchyI: fixes X :: "nat → 'a::metric_space ^ 'n" assumes X: "∧i. Cauchy (λn. X n $ i)" shows"Cauchy (λn. X n)" proof (rule metric_CauchyI) fix r :: real assume"0 < r" hence"0 < r / of_nat CARD('n)" (is"0 < ?s") by simp define N where"N i = (LEAST N. ∀m≥N. ∀n≥N. dist (X m $ i) (X n $ i) < ?s)"for i define M where"M = Max (range N)" have"∧i. ∃N. ∀m≥N. ∀n≥N. dist (X m $ i) (X n $ i) < ?s" using X ‹0 < ?s›by (rule metric_CauchyD) hence"∧i. ∀m≥N i. ∀n≥N i. dist (X m $ i) (X n $ i) < ?s" unfolding N_def by (rule LeastI_ex) hence M: "∧i. ∀m≥M. ∀n≥M. dist (X m $ i) (X n $ i) < ?s" unfolding M_def by simp
{ fix m n :: nat assume"M ≤ m""M ≤ n" have"dist (X m) (X n) = L2_set (λi. dist (X m $ i) (X n $ i)) UNIV" unfolding dist_vec_def .. alsohave"…≤ sum (λi. dist (X m $ i) (X n $ i)) UNIV" by (rule L2_set_le_sum [OF zero_le_dist]) alsohave"… < sum (λi::'n. ?s) UNIV" by (rule sum_strict_mono, simp_all add: M ‹M ≤ m›‹M ≤ n›) alsohave"… = r" by simp finallyhave"dist (X m) (X n) < r" .
} hence"∀m≥M. ∀n≥M. dist (X m) (X n) < r" by simp thenshow"∃M. ∀m≥M. ∀n≥M. dist (X m) (X n) < r" .. qed
instance✐‹tag unimportant› vec :: (complete_space, finite) complete_space proof fix X :: "nat → 'a ^ 'b"assume"Cauchy X" have"∧i. (λn. X n $ i) <---- lim (λn. X n $ i)" using Cauchy_vec_nth [OF ‹Cauchy X›] by (simp add: Cauchy_convergent_iff convergent_LIMSEQ_iff) hence"X <---- vec_lambda (λi. lim (λn. X n $ i))" by (simp add: vec_tendstoI) thenshow"convergent X" by (rule convergentI) qed
subsection‹Normed vector space›
instantiation✐‹tag unimportant› vec :: (real_normed_vector, finite) real_normed_vector begin
definition✐‹tag important›"norm x = L2_set (λi. norm (x$i)) UNIV"
lemma norm_le_componentwise_cart: fixes x :: "'a::real_normed_vector^'n" assumes"∧i. norm(x$i) ≤ norm(y$i)" shows"norm x ≤ norm y" unfolding norm_vec_def by (rule L2_set_mono) (auto simp: assms)
lemma component_le_norm_cart: "∣x$i∣≤ norm x" by (metis norm_nth_le real_norm_def)
lemma norm_bound_component_le_cart: "norm x ≤ e ==> ∣x$i∣≤ e" by (metis component_le_norm_cart order_trans)
lemma norm_bound_component_lt_cart: "norm x < e ==> ∣x$i∣ < e" by (metis component_le_norm_cart le_less_trans)
lemma norm_le_l1_cart: "norm x ≤ sum(λi. ∣x$i∣) UNIV" by (simp add: norm_vec_def L2_set_le_sum)
lemma bounded_linear_vec_nth[intro]: "bounded_linear (λx. x $ i)" proof show"∃K. ∀x. norm (x $ i) ≤ norm x * K" by (metis mult.commute mult.left_neutral norm_nth_le) qed auto
instance vec :: (banach, finite) banach ..
subsection‹Inner product space›
instantiation✐‹tag unimportant› vec :: (real_inner, finite) real_inner begin
definition✐‹tag important›"inner x y = sum (λi. inner (x$i) (y$i)) UNIV"
instance✐‹tag unimportant›proof fix r :: real and x y z :: "'a ^ 'b" show"inner x y = inner y x" unfolding inner_vec_def by (simp add: inner_commute) show"inner (x + y) z = inner x z + inner y z" unfolding inner_vec_def by (simp add: inner_add_left sum.distrib) show"inner (scaleR r x) y = r * inner x y" unfolding inner_vec_def by (simp add: sum_distrib_left) show"0 ≤ inner x x" unfolding inner_vec_def by (simp add: sum_nonneg) show"inner x x = 0 ⟷ x = 0" unfolding inner_vec_def by (simp add: vec_eq_iff sum_nonneg_eq_0_iff) show"norm x = sqrt (inner x x)" unfolding inner_vec_def norm_vec_def L2_set_def by (simp add: power2_norm_eq_inner) qed
end
subsection‹Euclidean space›
text‹Vectors pointing along a single axis.›
definition✐‹tag important›"axis k x = (χ i. if i = k then x else 0)"
lemma axis_nth [simp]: "axis i x $ i = x" unfolding axis_def by simp
lemma axis_eq_axis: "axis i x = axis j y ⟷ x = y ∧ i = j ∨ x = 0 ∧ y = 0" unfolding axis_def vec_eq_iff by auto
lemma inner_axis_axis: "inner (axis i x) (axis j y) = (if i = j then inner x y else 0)" by (simp add: inner_vec_def axis_def sum.neutral sum.remove [of _ j])
lemma inner_axis: "inner x (axis i y) = inner (x $ i) y" by (simp add: inner_vec_def axis_def sum.remove [where x=i])
lemma inner_axis': "inner(axis i y) x = inner y (x $ i)" by (simp add: inner_axis inner_commute)
instantiation✐‹tag unimportant› vec :: (euclidean_space, finite) euclidean_space begin
definition✐‹tag important›"Basis = (∪i. ∪u∈Basis. {axis i u})"
instance✐‹tag unimportant›proof show"(Basis :: ('a ^ 'b) set) ≠ {}" unfolding Basis_vec_def by simp next show"finite (Basis :: ('a ^ 'b) set)" unfolding Basis_vec_def by simp next fix u v :: "'a ^ 'b" assume"u ∈ Basis"and"v ∈ Basis" thus"inner u v = (if u = v then 1 else 0)" unfolding Basis_vec_def by (auto simp add: inner_axis_axis axis_eq_axis inner_Basis) next fix x :: "'a ^ 'b" show"(∀u∈Basis. inner x u = 0) ⟷ x = 0" unfolding Basis_vec_def by (simp add: inner_axis euclidean_all_zero_iff vec_eq_iff) qed
proposition DIM_cart [simp]: "DIM('a^'b) = CARD('b) * DIM('a)" proof - have"card (∪i::'b. ∪u::'a∈Basis. {axis i u}) = (∑i::'b∈UNIV. card (∪u::'a∈Basis. {axis i u}))" by (rule card_UN_disjoint) (auto simp: axis_eq_axis) alsohave"... = CARD('b) * DIM('a)" by (subst card_UN_disjoint) (auto simp: axis_eq_axis) finallyshow ?thesis by (simp add: Basis_vec_def) qed
end
lemma norm_axis_1 [simp]: "norm (axis m (1::real)) = 1" by (simp add: inner_axis' norm_eq_1)
lemma sum_norm_allsubsets_bound_cart: fixes f:: "'a → real ^'n" assumes fP: "finite P"and fPs: "∧Q. Q ⊆ P ==> norm (sum f Q) ≤ e" shows"sum (λx. norm (f x)) P ≤ 2 * real CARD('n) * e" using sum_norm_allsubsets_bound[OF assms] by simp
lemma cart_eq_inner_axis: "a $ i = inner a (axis i 1)" by (simp add: inner_axis)
lemma axis_eq_0_iff [simp]: shows"axis m x = 0 ⟷ x = 0" by (simp add: axis_def vec_eq_iff)
lemma axis_in_Basis_iff [simp]: "axis i a ∈ Basis ⟷ a ∈ Basis" by (auto simp: Basis_vec_def axis_eq_axis)
text‹Mapping each basis element to the corresponding finite index› definition axis_index :: "('a::comm_ring_1)^'n → 'n"where"axis_index v ≡ SOME i. v = axis i 1"
lemma axis_inverse: fixes v :: "real^'n" assumes"v ∈ Basis" shows"∃i. v = axis i 1" proof - have"v ∈ (∪n. ∪r∈Basis. {axis n r})" using assms Basis_vec_def by blast thenshow ?thesis by (force simp add: vec_eq_iff) qed
lemma vec_inj[simp]: "vec x = vec y ⟷ x = y"by vector
lemma vec_in_image_vec: "vec x ∈ (vec ` S) ⟷ x ∈ S"by auto
lemma vec_add: "vec(x + y) = vec x + vec y"by vector lemma vec_sub: "vec(x - y) = vec x - vec y"by vector lemma vec_cmul: "vec(c * x) = c *s vec x "by vector lemma vec_neg: "vec(- x) = - vec x "by vector
lemma vec_scaleR: "vec(c * x) = c *R vec x" by vector
lemma vec_sum: assumes"finite S" shows"vec(sum f S) = sum (vec ∘ f) S" using assms proof induct case empty thenshow ?caseby simp next case insert thenshow ?caseby (auto simp add: vec_add) qed
lemma sum_component [simp]: fixes f:: " 'a → ('b::comm_monoid_add) ^'n" shows "(sum f S)$i = sum (λx. (f x)$i) S" proof (cases "finite S") case True then show ?thesis by induct simp_all next case False then show ?thesis by simp qed
lemma sum_eq: "sum f S = (χ i. sum (λx. (f x)$i ) S)" by (simp add: vec_eq_iff)
lemma sum_cmul: fixes f:: "'c → ('a::semiring_1)^'n" shows "sum (λx. c *s f x) S = c *s sum f S" by (simp add: vec_eq_iff sum_distrib_left)
lemma linear_vec [simp]: "linear vec" using Vector_Spaces_linear_vec by unfold_locales (vector algebra_simps)+
subsection ‹Matrix operations›
text‹Matrix notation. NB: an MxN matrix is of type typ‹'a^'n^'m›, not typ‹'a^'m^'n››
definition✐‹tag important› map_matrix::"('a → 'b) → (('a, 'i::finite)vec, 'j::finite) vec →(('b, 'i)vec, 'j) vec" where "map_matrix f x = (χ i j. f (x $ i $ j))"
lemma nth_map_matrix[simp]: "map_matrix f x $ i $ j = f (x $ i $ j)" by (simp add: map_matrix_def)
definition✐‹tag important› matrix_matrix_mult :: "('a::semiring_1) ^'n^'m → 'a ^'p^'n →'a ^ 'p ^'m" (infixl ‹**› 70) where "m ** m' == (χ i j. sum (λk. ((m$i)$k) * ((m'$k)$j)) (UNIV :: 'n set)) ::'a ^ 'p ^'m"
definition✐‹tag important› matrix_vector_mult :: "('a::semiring_1) ^'n^'m → 'a ^'n → 'a ^ 'm" (infixl ‹*v› 70) where "m *v x ≡ (χ i. sum (λj. ((m$i)$j) * (x$j)) (UNIV ::'n set)) :: 'a^'m"
definition✐‹tag important› vector_matrix_mult :: "'a ^ 'm → ('a::semiring_1) ^'n^'m → 'a ^'n " (infixl ‹v*› 70) where "v v* m == (χ j. sum (λi. ((v$i) * (m$i)$j)) (UNIV :: 'm set)) :: 'a^'n"
definition✐‹tag unimportant› "(mat::'a::zero => 'a ^'n^'n) k = (χ i j. if i = j then k else 0)" definition✐‹tag unimportant› transpose where "(transpose::'a^'n^'m → 'a^'m^'n) A = (χ i j. ((A$j)$i))" definition✐‹tag unimportant› "(row::'m => 'a ^'n^'m → 'a ^'n) i A = (χ j. ((A$i)$j))" definition✐‹tag unimportant› "(column::'n =>'a^'n^'m =>'a^'m) j A = (χ i. ((A$i)$j))" definition✐‹tag unimportant› "rows(A::'a^'n^'m) = { row i A | i. i ∈ (UNIV :: 'm set)}" definition✐‹tag unimportant› "columns(A::'a^'n^'m) = { column i A | i. i ∈ (UNIV :: 'n set)}"
lemma mat_0[simp]: "mat 0 = 0" by (vector mat_def) lemma matrix_add_ldistrib: "(A ** (B + C)) = (A ** B) + (A ** C)" by (vector matrix_matrix_mult_def sum.distrib[symmetric] field_simps)
lemma matrix_mul_lid [simp]: fixes A :: "'a::semiring_1 ^ 'm ^ 'n" shows "mat 1 ** A = A" unfolding matrix_matrix_mult_def mat_def by (auto simp: if_distrib if_distribR sum.delta'[OF finite] cong: if_cong)
lemma matrix_mul_rid [simp]: fixes A :: "'a::semiring_1 ^ 'm ^ 'n" shows "A ** mat 1 = A" unfolding matrix_matrix_mult_def mat_def by (auto simp: if_distrib if_distribR sum.delta'[OF finite] cong: if_cong)
lemma matrix_mul_assoc: "A ** (B ** C) = (A ** B) ** C" apply (vector matrix_matrix_mult_def sum_distrib_left sum_distrib_right mult.assoc) using sum.swap by fastforce
lemma matrix_vector_mul_assoc: "A *v (B *v x) = (A ** B) *v x" apply (vector matrix_matrix_mult_def matrix_vector_mult_def sum_distrib_left sum_distrib_right mult.assoc) using sum.swap by fastforce
lemma vector_matrix_mul_assoc: "(x v* A) v* B = x v* (A**B)" apply (vector matrix_matrix_mult_def vector_matrix_mult_def sum_distrib_left sum_distrib_right mult.assoc) using sum.swap by fastforce
lemma scalar_matrix_assoc: fixes A :: "('a::real_algebra_1)^'m^'n" shows "k *R (A ** B) = (k *R A) ** B" by (simp add: matrix_matrix_mult_def sum_distrib_left mult_ac vec_eq_iff scaleR_sum_right)
lemma matrix_scalar_ac: fixes A :: "('a::real_algebra_1)^'m^'n" shows "A ** (k *R B) = k *R A ** B" by (simp add: matrix_matrix_mult_def sum_distrib_left mult_ac vec_eq_iff)
lemma matrix_transpose_mul: "transpose(A ** B) = transpose B ** transpose (A::'a::comm_semiring_1^_^_)" by (simp add: matrix_matrix_mult_def transpose_def vec_eq_iff mult.commute)
lemma matrix_mult_transpose_dot_column: shows "transpose A ** A = (χ i j. inner (column i A) (column j A))" by (simp add: matrix_matrix_mult_def vec_eq_iff transpose_def column_def inner_vec_def)
lemma matrix_mult_transpose_dot_row: shows "A ** transpose A = (χ i j. inner (row i A) (row j A))" by (simp add: matrix_matrix_mult_def vec_eq_iff transpose_def row_def inner_vec_def)
lemma matrix_eq: fixes A B :: "'a::semiring_1 ^ 'n ^ 'm" shows "A = B ⟷ (∀x. A *v x = B *v x)" (is "?lhs ⟷ ?rhs") proof assume ?rhs then show ?lhs apply (subst vec_eq_iff) apply (clarsimp simp add: matrix_vector_mult_def if_distrib if_distribR vec_eq_iff cong: if_cong) apply (erule_tac x="axis ia 1" in allE) apply (erule_tac x="i" in allE) apply (auto simp add: if_distrib if_distribR axis_def sum.delta[OF finite] cong del: if_weak_cong) done qed auto
lemma dot_lmul_matrix: "inner ((x::real ^_) v* A) y = inner x (A *v y)" apply (simp add: inner_vec_def matrix_vector_mult_def vector_matrix_mult_def sum_distrib_right sum_distrib_left ac_simps) apply (subst sum.swap) apply simp done
lemma transpose_mat [simp]: "transpose (mat n) = mat n" by (vector transpose_def mat_def)
lemma transpose_transpose [simp]: "transpose(transpose A) = A" by (vector transpose_def)
lemma row_transpose [simp]: "row i (transpose A) = column i A" by (simp add: row_def column_def transpose_def vec_eq_iff)
lemma column_transpose [simp]: "column i (transpose A) = row i A" by (simp add: row_def column_def transpose_def vec_eq_iff)
lemma rows_transpose [simp]: "rows(transpose A) = columns A" by (auto simp add: rows_def columns_def intro: set_eqI)
lemma columns_transpose [simp]: "columns(transpose A) = rows A" by (metis transpose_transpose rows_transpose)
lemma transpose_scalar: "transpose (k *R A) = k *R transpose A" unfolding transpose_def by (simp add: vec_eq_iff)
lemma transpose_iff [iff]: "transpose A = transpose B ⟷ A = B" by (metis transpose_transpose)
lemma matrix_mult_sum: "(A::'a::comm_semiring_1^'n^'m) *v x = sum (λi. (x$i) *s column i A) (UNIV:: 'n set)" by (simp add: matrix_vector_mult_def vec_eq_iff column_def mult.commute)
lemma vector_componentwise: "(x::'a::ring_1^'n) = (χ j. ∑i∈UNIV. (x$i) * (axis i 1 :: 'a^'n) $ j)" by (simp add: axis_def if_distrib sum.If_cases vec_eq_iff)
Die Informationen auf dieser Webseite wurden
nach bestem Wissen sorgfältig zusammengestellt. Es wird jedoch weder Vollständigkeit, noch Richtigkeit,
noch Qualität der bereit gestellten Informationen zugesichert.
Bemerkung:
Die farbliche Syntaxdarstellung und die Messung sind noch experimentell.