added Johannes' generalizations Modules.thy and Vector_Spaces.thy; adapted HOL and HOL-Analysis accordingly
section \<open>Instantiates the finite Cartesian product of Euclidean spaces as a Euclidean space\<close>
theory Cartesian_Euclidean_Space
imports Cartesian_Space Derivative
begin
lemma subspace_special_hyperplane: "subspace {x. x $ k = 0}"
by (simp add: subspace_def)
lemma sum_mult_product:
"sum h {..<A * B :: nat} = (\<Sum>i\<in>{..<A}. \<Sum>j\<in>{..<B}. h (j + i * B))"
unfolding sum_nat_group[of h B A, unfolded atLeast0LessThan, symmetric]
proof (rule sum.cong, simp, rule sum.reindex_cong)
fix i
show "inj_on (\<lambda>j. j + i * B) {..<B}" by (auto intro!: inj_onI)
show "{i * B..<i * B + B} = (\<lambda>j. j + i * B) ` {..<B}"
proof safe
fix j assume "j \<in> {i * B..<i * B + B}"
then show "j \<in> (\<lambda>j. j + i * B) ` {..<B}"
by (auto intro!: image_eqI[of _ _ "j - i * B"])
qed simp
qed simp
lemma interval_cbox_cart: "{a::real^'n..b} = cbox a b"
by (auto simp add: less_eq_vec_def mem_box Basis_vec_def inner_axis)
lemma differentiable_vec:
fixes S :: "'a::euclidean_space set"
shows "vec differentiable_on S"
by (simp add: linear_linear bounded_linear_imp_differentiable_on)
lemma continuous_vec [continuous_intros]:
fixes x :: "'a::euclidean_space"
shows "isCont vec x"
apply (clarsimp simp add: continuous_def LIM_def dist_vec_def L2_set_def)
apply (rule_tac x="r / sqrt (real CARD('b))" in exI)
by (simp add: mult.commute pos_less_divide_eq real_sqrt_mult)
lemma box_vec_eq_empty [simp]:
shows "cbox (vec a) (vec b) = {} \<longleftrightarrow> cbox a b = {}"
"box (vec a) (vec b) = {} \<longleftrightarrow> box a b = {}"
by (auto simp: Basis_vec_def mem_box box_eq_empty inner_axis)
subsection\<open>Closures and interiors of halfspaces\<close>
lemma interior_halfspace_le [simp]:
assumes "a \<noteq> 0"
shows "interior {x. a \<bullet> x \<le> b} = {x. a \<bullet> x < b}"
proof -
have *: "a \<bullet> x < b" if x: "x \<in> S" and S: "S \<subseteq> {x. a \<bullet> x \<le> b}" and "open S" for S x
proof -
obtain e where "e>0" and e: "cball x e \<subseteq> S"
using \<open>open S\<close> open_contains_cball x by blast
then have "x + (e / norm a) *\<^sub>R a \<in> cball x e"
by (simp add: dist_norm)
then have "x + (e / norm a) *\<^sub>R a \<in> S"
using e by blast
then have "x + (e / norm a) *\<^sub>R a \<in> {x. a \<bullet> x \<le> b}"
using S by blast
moreover have "e * (a \<bullet> a) / norm a > 0"
by (simp add: \<open>0 < e\<close> assms)
ultimately show ?thesis
by (simp add: algebra_simps)
qed
show ?thesis
by (rule interior_unique) (auto simp: open_halfspace_lt *)
qed
lemma interior_halfspace_ge [simp]:
"a \<noteq> 0 \<Longrightarrow> interior {x. a \<bullet> x \<ge> b} = {x. a \<bullet> x > b}"
using interior_halfspace_le [of "-a" "-b"] by simp
lemma interior_halfspace_component_le [simp]:
"interior {x. x$k \<le> a} = {x :: (real^'n). x$k < a}" (is "?LE")
and interior_halfspace_component_ge [simp]:
"interior {x. x$k \<ge> a} = {x :: (real^'n). x$k > a}" (is "?GE")
proof -
have "axis k (1::real) \<noteq> 0"
by (simp add: axis_def vec_eq_iff)
moreover have "axis k (1::real) \<bullet> x = x$k" for x
by (simp add: cart_eq_inner_axis inner_commute)
ultimately show ?LE ?GE
using interior_halfspace_le [of "axis k (1::real)" a]
interior_halfspace_ge [of "axis k (1::real)" a] by auto
qed
lemma closure_halfspace_lt [simp]:
assumes "a \<noteq> 0"
shows "closure {x. a \<bullet> x < b} = {x. a \<bullet> x \<le> b}"
proof -
have [simp]: "-{x. a \<bullet> x < b} = {x. a \<bullet> x \<ge> b}"
by (force simp:)
then show ?thesis
using interior_halfspace_ge [of a b] assms
by (force simp: closure_interior)
qed
lemma closure_halfspace_gt [simp]:
"a \<noteq> 0 \<Longrightarrow> closure {x. a \<bullet> x > b} = {x. a \<bullet> x \<ge> b}"
using closure_halfspace_lt [of "-a" "-b"] by simp
lemma closure_halfspace_component_lt [simp]:
"closure {x. x$k < a} = {x :: (real^'n). x$k \<le> a}" (is "?LE")
and closure_halfspace_component_gt [simp]:
"closure {x. x$k > a} = {x :: (real^'n). x$k \<ge> a}" (is "?GE")
proof -
have "axis k (1::real) \<noteq> 0"
by (simp add: axis_def vec_eq_iff)
moreover have "axis k (1::real) \<bullet> x = x$k" for x
by (simp add: cart_eq_inner_axis inner_commute)
ultimately show ?LE ?GE
using closure_halfspace_lt [of "axis k (1::real)" a]
closure_halfspace_gt [of "axis k (1::real)" a] by auto
qed
lemma interior_hyperplane [simp]:
assumes "a \<noteq> 0"
shows "interior {x. a \<bullet> x = b} = {}"
proof -
have [simp]: "{x. a \<bullet> x = b} = {x. a \<bullet> x \<le> b} \<inter> {x. a \<bullet> x \<ge> b}"
by (force simp:)
then show ?thesis
by (auto simp: assms)
qed
lemma frontier_halfspace_le:
assumes "a \<noteq> 0 \<or> b \<noteq> 0"
shows "frontier {x. a \<bullet> x \<le> b} = {x. a \<bullet> x = b}"
proof (cases "a = 0")
case True with assms show ?thesis by simp
next
case False then show ?thesis
by (force simp: frontier_def closed_halfspace_le)
qed
lemma frontier_halfspace_ge:
assumes "a \<noteq> 0 \<or> b \<noteq> 0"
shows "frontier {x. a \<bullet> x \<ge> b} = {x. a \<bullet> x = b}"
proof (cases "a = 0")
case True with assms show ?thesis by simp
next
case False then show ?thesis
by (force simp: frontier_def closed_halfspace_ge)
qed
lemma frontier_halfspace_lt:
assumes "a \<noteq> 0 \<or> b \<noteq> 0"
shows "frontier {x. a \<bullet> x < b} = {x. a \<bullet> x = b}"
proof (cases "a = 0")
case True with assms show ?thesis by simp
next
case False then show ?thesis
by (force simp: frontier_def interior_open open_halfspace_lt)
qed
lemma frontier_halfspace_gt:
assumes "a \<noteq> 0 \<or> b \<noteq> 0"
shows "frontier {x. a \<bullet> x > b} = {x. a \<bullet> x = b}"
proof (cases "a = 0")
case True with assms show ?thesis by simp
next
case False then show ?thesis
by (force simp: frontier_def interior_open open_halfspace_gt)
qed
lemma interior_standard_hyperplane:
"interior {x :: (real^'n). x$k = a} = {}"
proof -
have "axis k (1::real) \<noteq> 0"
by (simp add: axis_def vec_eq_iff)
moreover have "axis k (1::real) \<bullet> x = x$k" for x
by (simp add: cart_eq_inner_axis inner_commute)
ultimately show ?thesis
using interior_hyperplane [of "axis k (1::real)" a]
by force
qed
lemma matrix_mult_transpose_dot_column:
fixes A :: "real^'n^'n"
shows "transpose A ** A = (\<chi> 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:
fixes A :: "real^'n^'n"
shows "A ** transpose A = (\<chi> 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)
text\<open>Two sometimes fruitful ways of looking at matrix-vector multiplication.\<close>
lemma matrix_mult_dot: "A *v x = (\<chi> i. inner (A$i) x)"
by (simp add: matrix_vector_mult_def inner_vec_def)
lemma adjoint_matrix: "adjoint(\<lambda>x. (A::real^'n^'m) *v x) = (\<lambda>x. transpose A *v x)"
apply (rule adjoint_unique)
apply (simp add: transpose_def inner_vec_def matrix_vector_mult_def
sum_distrib_right sum_distrib_left)
apply (subst sum.swap)
apply (simp add: ac_simps)
done
lemma matrix_adjoint: assumes lf: "linear (f :: real^'n \<Rightarrow> real ^'m)"
shows "matrix(adjoint f) = transpose(matrix f)"
proof -
have "matrix(adjoint f) = matrix(adjoint (( *v) (matrix f)))"
by (simp add: lf)
also have "\<dots> = transpose(matrix f)"
unfolding adjoint_matrix matrix_of_matrix_vector_mul
apply rule
done
finally show ?thesis .
qed
lemma matrix_vector_mul_bounded_linear[intro, simp]: "bounded_linear (( *v) A)" for A :: "real^'n^'m"
using matrix_vector_mul_linear[of A]
by (simp add: linear_conv_bounded_linear linear_matrix_vector_mul_eq)
lemma
fixes A :: "real^'n^'m"
shows matrix_vector_mult_linear_continuous_at [continuous_intros]: "isCont (( *v) A) z"
and matrix_vector_mult_linear_continuous_on [continuous_intros]: "continuous_on S (( *v) A)"
by (simp_all add: linear_continuous_at linear_continuous_on)
subsection\<open>Some bounds on components etc. relative to operator norm\<close>
lemma norm_column_le_onorm:
fixes A :: "real^'n^'m"
shows "norm(column i A) \<le> onorm(( *v) A)"
proof -
have "norm (\<chi> j. A $ j $ i) \<le> norm (A *v axis i 1)"
by (simp add: matrix_mult_dot cart_eq_inner_axis)
also have "\<dots> \<le> onorm (( *v) A)"
using onorm [OF matrix_vector_mul_bounded_linear, of A "axis i 1"] by auto
finally have "norm (\<chi> j. A $ j $ i) \<le> onorm (( *v) A)" .
then show ?thesis
unfolding column_def .
qed
lemma matrix_component_le_onorm:
fixes A :: "real^'n^'m"
shows "\<bar>A $ i $ j\<bar> \<le> onorm(( *v) A)"
proof -
have "\<bar>A $ i $ j\<bar> \<le> norm (\<chi> n. (A $ n $ j))"
by (metis (full_types, lifting) component_le_norm_cart vec_lambda_beta)
also have "\<dots> \<le> onorm (( *v) A)"
by (metis (no_types) column_def norm_column_le_onorm)
finally show ?thesis .
qed
lemma component_le_onorm:
fixes f :: "real^'m \<Rightarrow> real^'n"
shows "linear f \<Longrightarrow> \<bar>matrix f $ i $ j\<bar> \<le> onorm f"
by (metis linear_matrix_vector_mul_eq matrix_component_le_onorm matrix_vector_mul)
lemma onorm_le_matrix_component_sum:
fixes A :: "real^'n^'m"
shows "onorm(( *v) A) \<le> (\<Sum>i\<in>UNIV. \<Sum>j\<in>UNIV. \<bar>A $ i $ j\<bar>)"
proof (rule onorm_le)
fix x
have "norm (A *v x) \<le> (\<Sum>i\<in>UNIV. \<bar>(A *v x) $ i\<bar>)"
by (rule norm_le_l1_cart)
also have "\<dots> \<le> (\<Sum>i\<in>UNIV. \<Sum>j\<in>UNIV. \<bar>A $ i $ j\<bar> * norm x)"
proof (rule sum_mono)
fix i
have "\<bar>(A *v x) $ i\<bar> \<le> \<bar>\<Sum>j\<in>UNIV. A $ i $ j * x $ j\<bar>"
by (simp add: matrix_vector_mult_def)
also have "\<dots> \<le> (\<Sum>j\<in>UNIV. \<bar>A $ i $ j * x $ j\<bar>)"
by (rule sum_abs)
also have "\<dots> \<le> (\<Sum>j\<in>UNIV. \<bar>A $ i $ j\<bar> * norm x)"
by (rule sum_mono) (simp add: abs_mult component_le_norm_cart mult_left_mono)
finally show "\<bar>(A *v x) $ i\<bar> \<le> (\<Sum>j\<in>UNIV. \<bar>A $ i $ j\<bar> * norm x)" .
qed
finally show "norm (A *v x) \<le> (\<Sum>i\<in>UNIV. \<Sum>j\<in>UNIV. \<bar>A $ i $ j\<bar>) * norm x"
by (simp add: sum_distrib_right)
qed
lemma onorm_le_matrix_component:
fixes A :: "real^'n^'m"
assumes "\<And>i j. abs(A$i$j) \<le> B"
shows "onorm(( *v) A) \<le> real (CARD('m)) * real (CARD('n)) * B"
proof (rule onorm_le)
fix x :: "real^'n::_"
have "norm (A *v x) \<le> (\<Sum>i\<in>UNIV. \<bar>(A *v x) $ i\<bar>)"
by (rule norm_le_l1_cart)
also have "\<dots> \<le> (\<Sum>i::'m \<in>UNIV. real (CARD('n)) * B * norm x)"
proof (rule sum_mono)
fix i
have "\<bar>(A *v x) $ i\<bar> \<le> norm(A $ i) * norm x"
by (simp add: matrix_mult_dot Cauchy_Schwarz_ineq2)
also have "\<dots> \<le> (\<Sum>j\<in>UNIV. \<bar>A $ i $ j\<bar>) * norm x"
by (simp add: mult_right_mono norm_le_l1_cart)
also have "\<dots> \<le> real (CARD('n)) * B * norm x"
by (simp add: assms sum_bounded_above mult_right_mono)
finally show "\<bar>(A *v x) $ i\<bar> \<le> real (CARD('n)) * B * norm x" .
qed
also have "\<dots> \<le> CARD('m) * real (CARD('n)) * B * norm x"
by simp
finally show "norm (A *v x) \<le> CARD('m) * real (CARD('n)) * B * norm x" .
qed
subsection \<open>lambda skolemization on cartesian products\<close>
lemma lambda_skolem: "(\<forall>i. \<exists>x. P i x) \<longleftrightarrow>
(\<exists>x::'a ^ 'n. \<forall>i. P i (x $ i))" (is "?lhs \<longleftrightarrow> ?rhs")
proof -
let ?S = "(UNIV :: 'n set)"
{ assume H: "?rhs"
then have ?lhs by auto }
moreover
{ assume H: "?lhs"
then obtain f where f:"\<forall>i. P i (f i)" unfolding choice_iff by metis
let ?x = "(\<chi> i. (f i)) :: 'a ^ 'n"
{ fix i
from f have "P i (f i)" by metis
then have "P i (?x $ i)" by auto
}
hence "\<forall>i. P i (?x$i)" by metis
hence ?rhs by metis }
ultimately show ?thesis by metis
qed
lemma rational_approximation:
assumes "e > 0"
obtains r::real where "r \<in> \<rat>" "\<bar>r - x\<bar> < e"
using Rats_dense_in_real [of "x - e/2" "x + e/2"] assms by auto
lemma matrix_rational_approximation:
fixes A :: "real^'n^'m"
assumes "e > 0"
obtains B where "\<And>i j. B$i$j \<in> \<rat>" "onorm(\<lambda>x. (A - B) *v x) < e"
proof -
have "\<forall>i j. \<exists>q \<in> \<rat>. \<bar>q - A $ i $ j\<bar> < e / (2 * CARD('m) * CARD('n))"
using assms by (force intro: rational_approximation [of "e / (2 * CARD('m) * CARD('n))"])
then obtain B where B: "\<And>i j. B$i$j \<in> \<rat>" and Bclo: "\<And>i j. \<bar>B$i$j - A $ i $ j\<bar> < e / (2 * CARD('m) * CARD('n))"
by (auto simp: lambda_skolem Bex_def)
show ?thesis
proof
have "onorm (( *v) (A - B)) \<le> real CARD('m) * real CARD('n) *
(e / (2 * real CARD('m) * real CARD('n)))"
apply (rule onorm_le_matrix_component)
using Bclo by (simp add: abs_minus_commute less_imp_le)
also have "\<dots> < e"
using \<open>0 < e\<close> by (simp add: divide_simps)
finally show "onorm (( *v) (A - B)) < e" .
qed (use B in auto)
qed
lemma vector_sub_project_orthogonal_cart: "(b::real^'n) \<bullet> (x - ((b \<bullet> x) / (b \<bullet> b)) *s b) = 0"
unfolding inner_simps scalar_mult_eq_scaleR by auto
lemma matrix_left_invertible_injective:
fixes A :: "'a::field^'n^'m"
shows "(\<exists>B. B ** A = mat 1) \<longleftrightarrow> inj (( *v) A)"
proof safe
fix B
assume B: "B ** A = mat 1"
show "inj (( *v) A)"
unfolding inj_on_def
by (metis B matrix_vector_mul_assoc matrix_vector_mul_lid)
next
assume "inj (( *v) A)"
from vec.linear_injective_left_inverse[OF matrix_vector_mul_linear_gen this]
obtain g where "Vector_Spaces.linear ( *s) ( *s) g" and g: "g \<circ> ( *v) A = id"
by blast
have "matrix g ** A = mat 1"
by (metis matrix_vector_mul_linear_gen \<open>Vector_Spaces.linear ( *s) ( *s) g\<close> g matrix_compose_gen
matrix_eq matrix_id_mat_1 matrix_vector_mul(1))
then show "\<exists>B. B ** A = mat 1"
by metis
qed
lemma matrix_right_invertible_surjective:
"(\<exists>B. (A::'a::field^'n^'m) ** (B::'a::field^'m^'n) = mat 1) \<longleftrightarrow> surj (\<lambda>x. A *v x)"
proof -
{ fix B :: "'a ^'m^'n"
assume AB: "A ** B = mat 1"
{ fix x :: "'a ^ 'm"
have "A *v (B *v x) = x"
by (simp add: matrix_vector_mul_assoc AB) }
hence "surj (( *v) A)" unfolding surj_def by metis }
moreover
{ assume sf: "surj (( *v) A)"
from vec.linear_surjective_right_inverse[OF _ this]
obtain g:: "'a ^'m \<Rightarrow> 'a ^'n" where g: "Vector_Spaces.linear ( *s) ( *s) g" "( *v) A \<circ> g = id"
by blast
have "A ** (matrix g) = mat 1"
unfolding matrix_eq matrix_vector_mul_lid
matrix_vector_mul_assoc[symmetric] matrix_works[OF g(1)]
using g(2) unfolding o_def fun_eq_iff id_def
.
hence "\<exists>B. A ** (B::'a^'m^'n) = mat 1" by blast
}
ultimately show ?thesis unfolding surj_def by blast
qed
lemma matrix_right_invertible_span_columns:
"(\<exists>(B::'a::field ^'n^'m). (A::'a ^'m^'n) ** B = mat 1) \<longleftrightarrow>
vec.span (columns A) = UNIV" (is "?lhs = ?rhs")
proof -
let ?U = "UNIV :: 'm set"
have fU: "finite ?U" by simp
have lhseq: "?lhs \<longleftrightarrow> (\<forall>y. \<exists>(x::'a^'m). sum (\<lambda>i. (x$i) *s column i A) ?U = y)"
unfolding matrix_right_invertible_surjective matrix_mult_sum surj_def
apply (subst eq_commute)
apply rule
done
have rhseq: "?rhs \<longleftrightarrow> (\<forall>x. x \<in> vec.span (columns A))" by blast
{ assume h: ?lhs
{ fix x:: "'a ^'n"
from h[unfolded lhseq, rule_format, of x] obtain y :: "'a ^'m"
where y: "sum (\<lambda>i. (y$i) *s column i A) ?U = x" by blast
have "x \<in> vec.span (columns A)"
unfolding y[symmetric]
apply (rule vec.span_sum)
apply (rule vec.span_scale)
apply (rule vec.span_base)
unfolding columns_def
apply blast
done
}
then have ?rhs unfolding rhseq by blast }
moreover
{ assume h:?rhs
let ?P = "\<lambda>(y::'a ^'n). \<exists>(x::'a^'m). sum (\<lambda>i. (x$i) *s column i A) ?U = y"
{ fix y
have "y \<in> vec.span (columns A)"
unfolding h by blast
then have "?P y"
proof (induction rule: vec.span_induct_alt)
show "\<exists>x::'a ^ 'm. sum (\<lambda>i. (x$i) *s column i A) ?U = 0"
by (rule exI[where x=0], simp)
next
fix c y1 y2
assume y1: "y1 \<in> columns A" and y2: "?P y2"
from y1 obtain i where i: "i \<in> ?U" "y1 = column i A"
unfolding columns_def by blast
from y2 obtain x:: "'a ^'m" where
x: "sum (\<lambda>i. (x$i) *s column i A) ?U = y2" by blast
let ?x = "(\<chi> j. if j = i then c + (x$i) else (x$j))::'a^'m"
show "?P (c*s y1 + y2)"
proof (rule exI[where x= "?x"], vector, auto simp add: i x[symmetric] if_distrib distrib_left if_distribR cong del: if_weak_cong)
fix j
have th: "\<forall>xa \<in> ?U. (if xa = i then (c + (x$i)) * ((column xa A)$j)
else (x$xa) * ((column xa A$j))) = (if xa = i then c * ((column i A)$j) else 0) + ((x$xa) * ((column xa A)$j))"
using i(1) by (simp add: field_simps)
have "sum (\<lambda>xa. if xa = i then (c + (x$i)) * ((column xa A)$j)
else (x$xa) * ((column xa A$j))) ?U = sum (\<lambda>xa. (if xa = i then c * ((column i A)$j) else 0) + ((x$xa) * ((column xa A)$j))) ?U"
apply (rule sum.cong[OF refl])
using th apply blast
done
also have "\<dots> = sum (\<lambda>xa. if xa = i then c * ((column i A)$j) else 0) ?U + sum (\<lambda>xa. ((x$xa) * ((column xa A)$j))) ?U"
by (simp add: sum.distrib)
also have "\<dots> = c * ((column i A)$j) + sum (\<lambda>xa. ((x$xa) * ((column xa A)$j))) ?U"
unfolding sum.delta[OF fU]
using i(1) by simp
finally show "sum (\<lambda>xa. if xa = i then (c + (x$i)) * ((column xa A)$j)
else (x$xa) * ((column xa A$j))) ?U = c * ((column i A)$j) + sum (\<lambda>xa. ((x$xa) * ((column xa A)$j))) ?U" .
qed
qed
}
then have ?lhs unfolding lhseq ..
}
ultimately show ?thesis by blast
qed
lemma matrix_left_invertible_span_rows_gen:
"(\<exists>(B::'a^'m^'n). B ** (A::'a::field^'n^'m) = mat 1) \<longleftrightarrow> vec.span (rows A) = UNIV"
unfolding right_invertible_transpose[symmetric]
unfolding columns_transpose[symmetric]
unfolding matrix_right_invertible_span_columns
..
lemma matrix_left_invertible_span_rows:
"(\<exists>(B::real^'m^'n). B ** (A::real^'n^'m) = mat 1) \<longleftrightarrow> span (rows A) = UNIV"
using matrix_left_invertible_span_rows_gen[of A] by (simp add: span_vec_eq)
text \<open>The same result in terms of square matrices.\<close>
text \<open>Considering an n-element vector as an n-by-1 or 1-by-n matrix.\<close>
definition "rowvector v = (\<chi> i j. (v$j))"
definition "columnvector v = (\<chi> i j. (v$i))"
lemma transpose_columnvector: "transpose(columnvector v) = rowvector v"
by (simp add: transpose_def rowvector_def columnvector_def vec_eq_iff)
lemma transpose_rowvector: "transpose(rowvector v) = columnvector v"
by (simp add: transpose_def columnvector_def rowvector_def vec_eq_iff)
lemma dot_rowvector_columnvector: "columnvector (A *v v) = A ** columnvector v"
by (vector columnvector_def matrix_matrix_mult_def matrix_vector_mult_def)
lemma dot_matrix_product:
"(x::real^'n) \<bullet> y = (((rowvector x ::real^'n^1) ** (columnvector y :: real^1^'n))$1)$1"
by (vector matrix_matrix_mult_def rowvector_def columnvector_def inner_vec_def)
lemma dot_matrix_vector_mul:
fixes A B :: "real ^'n ^'n" and x y :: "real ^'n"
shows "(A *v x) \<bullet> (B *v y) =
(((rowvector x :: real^'n^1) ** ((transpose A ** B) ** (columnvector y :: real ^1^'n)))$1)$1"
unfolding dot_matrix_product transpose_columnvector[symmetric]
dot_rowvector_columnvector matrix_transpose_mul matrix_mul_assoc ..
lemma infnorm_cart:"infnorm (x::real^'n) = Sup {\<bar>x$i\<bar> |i. i\<in>UNIV}"
by (simp add: infnorm_def inner_axis Basis_vec_def) (metis (lifting) inner_axis real_inner_1_right)
lemma component_le_infnorm_cart: "\<bar>x$i\<bar> \<le> infnorm (x::real^'n)"
using Basis_le_infnorm[of "axis i 1" x]
by (simp add: Basis_vec_def axis_eq_axis inner_axis)
lemma continuous_component[continuous_intros]: "continuous F f \<Longrightarrow> continuous F (\<lambda>x. f x $ i)"
unfolding continuous_def by (rule tendsto_vec_nth)
lemma continuous_on_component[continuous_intros]: "continuous_on s f \<Longrightarrow> continuous_on s (\<lambda>x. f x $ i)"
unfolding continuous_on_def by (fast intro: tendsto_vec_nth)
lemma continuous_on_vec_lambda[continuous_intros]:
"(\<And>i. continuous_on S (f i)) \<Longrightarrow> continuous_on S (\<lambda>x. \<chi> i. f i x)"
unfolding continuous_on_def by (auto intro: tendsto_vec_lambda)
lemma closed_positive_orthant: "closed {x::real^'n. \<forall>i. 0 \<le>x$i}"
by (simp add: Collect_all_eq closed_INT closed_Collect_le continuous_on_const continuous_on_id continuous_on_component)
lemma bounded_component_cart: "bounded s \<Longrightarrow> bounded ((\<lambda>x. x $ i) ` s)"
unfolding bounded_def
apply clarify
apply (rule_tac x="x $ i" in exI)
apply (rule_tac x="e" in exI)
apply clarify
apply (rule order_trans [OF dist_vec_nth_le], simp)
done
lemma compact_lemma_cart:
fixes f :: "nat \<Rightarrow> 'a::heine_borel ^ 'n"
assumes f: "bounded (range f)"
shows "\<exists>l r. strict_mono r \<and>
(\<forall>e>0. eventually (\<lambda>n. \<forall>i\<in>d. dist (f (r n) $ i) (l $ i) < e) sequentially)"
(is "?th d")
proof -
have "\<forall>d' \<subseteq> d. ?th d'"
by (rule compact_lemma_general[where unproj=vec_lambda])
(auto intro!: f bounded_component_cart simp: vec_lambda_eta)
then show "?th d" by simp
qed
instance vec :: (heine_borel, finite) heine_borel
proof
fix f :: "nat \<Rightarrow> 'a ^ 'b"
assume f: "bounded (range f)"
then obtain l r where r: "strict_mono r"
and l: "\<forall>e>0. eventually (\<lambda>n. \<forall>i\<in>UNIV. dist (f (r n) $ i) (l $ i) < e) sequentially"
using compact_lemma_cart [OF f] by blast
let ?d = "UNIV::'b set"
{ fix e::real assume "e>0"
hence "0 < e / (real_of_nat (card ?d))"
using zero_less_card_finite divide_pos_pos[of e, of "real_of_nat (card ?d)"] by auto
with l have "eventually (\<lambda>n. \<forall>i. dist (f (r n) $ i) (l $ i) < e / (real_of_nat (card ?d))) sequentially"
by simp
moreover
{ fix n
assume n: "\<forall>i. dist (f (r n) $ i) (l $ i) < e / (real_of_nat (card ?d))"
have "dist (f (r n)) l \<le> (\<Sum>i\<in>?d. dist (f (r n) $ i) (l $ i))"
unfolding dist_vec_def using zero_le_dist by (rule L2_set_le_sum)
also have "\<dots> < (\<Sum>i\<in>?d. e / (real_of_nat (card ?d)))"
by (rule sum_strict_mono) (simp_all add: n)
finally have "dist (f (r n)) l < e" by simp
}
ultimately have "eventually (\<lambda>n. dist (f (r n)) l < e) sequentially"
by (rule eventually_mono)
}
hence "((f \<circ> r) \<longlongrightarrow> l) sequentially" unfolding o_def tendsto_iff by simp
with r show "\<exists>l r. strict_mono r \<and> ((f \<circ> r) \<longlongrightarrow> l) sequentially" by auto
qed
lemma interval_cart:
fixes a :: "real^'n"
shows "box a b = {x::real^'n. \<forall>i. a$i < x$i \<and> x$i < b$i}"
and "cbox a b = {x::real^'n. \<forall>i. a$i \<le> x$i \<and> x$i \<le> b$i}"
by (auto simp add: set_eq_iff less_vec_def less_eq_vec_def mem_box Basis_vec_def inner_axis)
lemma mem_box_cart:
fixes a :: "real^'n"
shows "x \<in> box a b \<longleftrightarrow> (\<forall>i. a$i < x$i \<and> x$i < b$i)"
and "x \<in> cbox a b \<longleftrightarrow> (\<forall>i. a$i \<le> x$i \<and> x$i \<le> b$i)"
using interval_cart[of a b] by (auto simp add: set_eq_iff less_vec_def less_eq_vec_def)
lemma interval_eq_empty_cart:
fixes a :: "real^'n"
shows "(box a b = {} \<longleftrightarrow> (\<exists>i. b$i \<le> a$i))" (is ?th1)
and "(cbox a b = {} \<longleftrightarrow> (\<exists>i. b$i < a$i))" (is ?th2)
proof -
{ fix i x assume as:"b$i \<le> a$i" and x:"x\<in>box a b"
hence "a $ i < x $ i \<and> x $ i < b $ i" unfolding mem_box_cart by auto
hence "a$i < b$i" by auto
hence False using as by auto }
moreover
{ assume as:"\<forall>i. \<not> (b$i \<le> a$i)"
let ?x = "(1/2) *\<^sub>R (a + b)"
{ fix i
have "a$i < b$i" using as[THEN spec[where x=i]] by auto
hence "a$i < ((1/2) *\<^sub>R (a+b)) $ i" "((1/2) *\<^sub>R (a+b)) $ i < b$i"
unfolding vector_smult_component and vector_add_component
by auto }
hence "box a b \<noteq> {}" using mem_box_cart(1)[of "?x" a b] by auto }
ultimately show ?th1 by blast
{ fix i x assume as:"b$i < a$i" and x:"x\<in>cbox a b"
hence "a $ i \<le> x $ i \<and> x $ i \<le> b $ i" unfolding mem_box_cart by auto
hence "a$i \<le> b$i" by auto
hence False using as by auto }
moreover
{ assume as:"\<forall>i. \<not> (b$i < a$i)"
let ?x = "(1/2) *\<^sub>R (a + b)"
{ fix i
have "a$i \<le> b$i" using as[THEN spec[where x=i]] by auto
hence "a$i \<le> ((1/2) *\<^sub>R (a+b)) $ i" "((1/2) *\<^sub>R (a+b)) $ i \<le> b$i"
unfolding vector_smult_component and vector_add_component
by auto }
hence "cbox a b \<noteq> {}" using mem_box_cart(2)[of "?x" a b] by auto }
ultimately show ?th2 by blast
qed
lemma interval_ne_empty_cart:
fixes a :: "real^'n"
shows "cbox a b \<noteq> {} \<longleftrightarrow> (\<forall>i. a$i \<le> b$i)"
and "box a b \<noteq> {} \<longleftrightarrow> (\<forall>i. a$i < b$i)"
unfolding interval_eq_empty_cart[of a b] by (auto simp add: not_less not_le)
(* BH: Why doesn't just "auto" work here? *)
lemma subset_interval_imp_cart:
fixes a :: "real^'n"
shows "(\<forall>i. a$i \<le> c$i \<and> d$i \<le> b$i) \<Longrightarrow> cbox c d \<subseteq> cbox a b"
and "(\<forall>i. a$i < c$i \<and> d$i < b$i) \<Longrightarrow> cbox c d \<subseteq> box a b"
and "(\<forall>i. a$i \<le> c$i \<and> d$i \<le> b$i) \<Longrightarrow> box c d \<subseteq> cbox a b"
and "(\<forall>i. a$i \<le> c$i \<and> d$i \<le> b$i) \<Longrightarrow> box c d \<subseteq> box a b"
unfolding subset_eq[unfolded Ball_def] unfolding mem_box_cart
by (auto intro: order_trans less_le_trans le_less_trans less_imp_le) (* BH: Why doesn't just "auto" work here? *)
lemma interval_sing:
fixes a :: "'a::linorder^'n"
shows "{a .. a} = {a} \<and> {a<..<a} = {}"
apply (auto simp add: set_eq_iff less_vec_def less_eq_vec_def vec_eq_iff)
done
lemma subset_interval_cart:
fixes a :: "real^'n"
shows "cbox c d \<subseteq> cbox a b \<longleftrightarrow> (\<forall>i. c$i \<le> d$i) --> (\<forall>i. a$i \<le> c$i \<and> d$i \<le> b$i)" (is ?th1)
and "cbox c d \<subseteq> box a b \<longleftrightarrow> (\<forall>i. c$i \<le> d$i) --> (\<forall>i. a$i < c$i \<and> d$i < b$i)" (is ?th2)
and "box c d \<subseteq> cbox a b \<longleftrightarrow> (\<forall>i. c$i < d$i) --> (\<forall>i. a$i \<le> c$i \<and> d$i \<le> b$i)" (is ?th3)
and "box c d \<subseteq> box a b \<longleftrightarrow> (\<forall>i. c$i < d$i) --> (\<forall>i. a$i \<le> c$i \<and> d$i \<le> b$i)" (is ?th4)
using subset_box[of c d a b] by (simp_all add: Basis_vec_def inner_axis)
lemma disjoint_interval_cart:
fixes a::"real^'n"
shows "cbox a b \<inter> cbox c d = {} \<longleftrightarrow> (\<exists>i. (b$i < a$i \<or> d$i < c$i \<or> b$i < c$i \<or> d$i < a$i))" (is ?th1)
and "cbox a b \<inter> box c d = {} \<longleftrightarrow> (\<exists>i. (b$i < a$i \<or> d$i \<le> c$i \<or> b$i \<le> c$i \<or> d$i \<le> a$i))" (is ?th2)
and "box a b \<inter> cbox c d = {} \<longleftrightarrow> (\<exists>i. (b$i \<le> a$i \<or> d$i < c$i \<or> b$i \<le> c$i \<or> d$i \<le> a$i))" (is ?th3)
and "box a b \<inter> box c d = {} \<longleftrightarrow> (\<exists>i. (b$i \<le> a$i \<or> d$i \<le> c$i \<or> b$i \<le> c$i \<or> d$i \<le> a$i))" (is ?th4)
using disjoint_interval[of a b c d] by (simp_all add: Basis_vec_def inner_axis)
lemma Int_interval_cart:
fixes a :: "real^'n"
shows "cbox a b \<inter> cbox c d = {(\<chi> i. max (a$i) (c$i)) .. (\<chi> i. min (b$i) (d$i))}"
unfolding Int_interval
by (auto simp: mem_box less_eq_vec_def)
(auto simp: Basis_vec_def inner_axis)
lemma closed_interval_left_cart:
fixes b :: "real^'n"
shows "closed {x::real^'n. \<forall>i. x$i \<le> b$i}"
by (simp add: Collect_all_eq closed_INT closed_Collect_le continuous_on_const continuous_on_id continuous_on_component)
lemma closed_interval_right_cart:
fixes a::"real^'n"
shows "closed {x::real^'n. \<forall>i. a$i \<le> x$i}"
by (simp add: Collect_all_eq closed_INT closed_Collect_le continuous_on_const continuous_on_id continuous_on_component)
lemma is_interval_cart:
"is_interval (s::(real^'n) set) \<longleftrightarrow>
(\<forall>a\<in>s. \<forall>b\<in>s. \<forall>x. (\<forall>i. ((a$i \<le> x$i \<and> x$i \<le> b$i) \<or> (b$i \<le> x$i \<and> x$i \<le> a$i))) \<longrightarrow> x \<in> s)"
by (simp add: is_interval_def Ball_def Basis_vec_def inner_axis imp_ex)
lemma closed_halfspace_component_le_cart: "closed {x::real^'n. x$i \<le> a}"
by (simp add: closed_Collect_le continuous_on_const continuous_on_id continuous_on_component)
lemma closed_halfspace_component_ge_cart: "closed {x::real^'n. x$i \<ge> a}"
by (simp add: closed_Collect_le continuous_on_const continuous_on_id continuous_on_component)
lemma open_halfspace_component_lt_cart: "open {x::real^'n. x$i < a}"
by (simp add: open_Collect_less continuous_on_const continuous_on_id continuous_on_component)
lemma open_halfspace_component_gt_cart: "open {x::real^'n. x$i > a}"
by (simp add: open_Collect_less continuous_on_const continuous_on_id continuous_on_component)
lemma Lim_component_le_cart:
fixes f :: "'a \<Rightarrow> real^'n"
assumes "(f \<longlongrightarrow> l) net" "\<not> (trivial_limit net)" "eventually (\<lambda>x. f x $i \<le> b) net"
shows "l$i \<le> b"
by (rule tendsto_le[OF assms(2) tendsto_const tendsto_vec_nth, OF assms(1, 3)])
lemma Lim_component_ge_cart:
fixes f :: "'a \<Rightarrow> real^'n"
assumes "(f \<longlongrightarrow> l) net" "\<not> (trivial_limit net)" "eventually (\<lambda>x. b \<le> (f x)$i) net"
shows "b \<le> l$i"
by (rule tendsto_le[OF assms(2) tendsto_vec_nth tendsto_const, OF assms(1, 3)])
lemma Lim_component_eq_cart:
fixes f :: "'a \<Rightarrow> real^'n"
assumes net: "(f \<longlongrightarrow> l) net" "~(trivial_limit net)" and ev:"eventually (\<lambda>x. f(x)$i = b) net"
shows "l$i = b"
using ev[unfolded order_eq_iff eventually_conj_iff] and
Lim_component_ge_cart[OF net, of b i] and
Lim_component_le_cart[OF net, of i b] by auto
lemma connected_ivt_component_cart:
fixes x :: "real^'n"
shows "connected s \<Longrightarrow> x \<in> s \<Longrightarrow> y \<in> s \<Longrightarrow> x$k \<le> a \<Longrightarrow> a \<le> y$k \<Longrightarrow> (\<exists>z\<in>s. z$k = a)"
using connected_ivt_hyperplane[of s x y "axis k 1" a]
by (auto simp add: inner_axis inner_commute)
lemma subspace_substandard_cart: "vec.subspace {x. (\<forall>i. P i \<longrightarrow> x$i = 0)}"
unfolding vec.subspace_def by auto
lemma closed_substandard_cart:
"closed {x::'a::real_normed_vector ^ 'n. \<forall>i. P i \<longrightarrow> x$i = 0}"
proof -
{ fix i::'n
have "closed {x::'a ^ 'n. P i \<longrightarrow> x$i = 0}"
by (cases "P i") (simp_all add: closed_Collect_eq continuous_on_const continuous_on_id continuous_on_component) }
thus ?thesis
unfolding Collect_all_eq by (simp add: closed_INT)
qed
lemma dim_substandard_cart: "vec.dim {x::'a::field^'n. \<forall>i. i \<notin> d \<longrightarrow> x$i = 0} = card d"
(is "vec.dim ?A = _")
proof (rule vec.dim_unique)
let ?B = "((\<lambda>x. axis x 1) ` d)"
have subset_basis: "?B \<subseteq> cart_basis"
by (auto simp: cart_basis_def)
show "?B \<subseteq> ?A"
by (auto simp: axis_def)
show "vec.independent ((\<lambda>x. axis x 1) ` d)"
using subset_basis
by (rule vec.independent_mono[OF vec.independent_Basis])
have "x \<in> vec.span ?B" if "\<forall>i. i \<notin> d \<longrightarrow> x $ i = 0" for x::"'a^'n"
proof -
have "finite ?B"
using subset_basis finite_cart_basis
by (rule finite_subset)
have "x = (\<Sum>i\<in>UNIV. x $ i *s axis i 1)"
by (rule basis_expansion[symmetric])
also have "\<dots> = (\<Sum>i\<in>d. (x $ i) *s axis i 1)"
by (rule sum.mono_neutral_cong_right) (auto simp: that)
also have "\<dots> \<in> vec.span ?B"
by (simp add: vec.span_sum vec.span_clauses)
finally show "x \<in> vec.span ?B" .
qed
then show "?A \<subseteq> vec.span ?B" by auto
qed (simp add: card_image inj_on_def axis_eq_axis)
lemma dim_subset_UNIV_cart_gen:
fixes S :: "('a::field^'n) set"
shows "vec.dim S \<le> CARD('n)"
by (metis vec.dim_eq_full vec.dim_subset_UNIV vec.span_UNIV vec_dim_card)
lemma dim_subset_UNIV_cart:
fixes S :: "(real^'n) set"
shows "dim S \<le> CARD('n)"
using dim_subset_UNIV_cart_gen[of S] by (simp add: dim_vec_eq)
lemma affinity_inverses:
assumes m0: "m \<noteq> (0::'a::field)"
shows "(\<lambda>x. m *s x + c) \<circ> (\<lambda>x. inverse(m) *s x + (-(inverse(m) *s c))) = id"
"(\<lambda>x. inverse(m) *s x + (-(inverse(m) *s c))) \<circ> (\<lambda>x. m *s x + c) = id"
using m0
by (auto simp add: fun_eq_iff vector_add_ldistrib diff_conv_add_uminus simp del: add_uminus_conv_diff)
lemma vector_affinity_eq:
assumes m0: "(m::'a::field) \<noteq> 0"
shows "m *s x + c = y \<longleftrightarrow> x = inverse m *s y + -(inverse m *s c)"
proof
assume h: "m *s x + c = y"
hence "m *s x = y - c" by (simp add: field_simps)
hence "inverse m *s (m *s x) = inverse m *s (y - c)" by simp
then show "x = inverse m *s y + - (inverse m *s c)"
using m0 by (simp add: vector_smult_assoc vector_ssub_ldistrib)
next
assume h: "x = inverse m *s y + - (inverse m *s c)"
show "m *s x + c = y" unfolding h
using m0 by (simp add: vector_smult_assoc vector_ssub_ldistrib)
qed
lemma vector_eq_affinity:
"(m::'a::field) \<noteq> 0 ==> (y = m *s x + c \<longleftrightarrow> inverse(m) *s y + -(inverse(m) *s c) = x)"
using vector_affinity_eq[where m=m and x=x and y=y and c=c]
by metis
lemma vector_cart:
fixes f :: "real^'n \<Rightarrow> real"
shows "(\<chi> i. f (axis i 1)) = (\<Sum>i\<in>Basis. f i *\<^sub>R i)"
unfolding euclidean_eq_iff[where 'a="real^'n"]
by simp (simp add: Basis_vec_def inner_axis)
lemma const_vector_cart:"((\<chi> i. d)::real^'n) = (\<Sum>i\<in>Basis. d *\<^sub>R i)"
by (rule vector_cart)
subsection "Convex Euclidean Space"
lemma Cart_1:"(1::real^'n) = \<Sum>Basis"
using const_vector_cart[of 1] by (simp add: one_vec_def)
declare vector_add_ldistrib[simp] vector_ssub_ldistrib[simp] vector_smult_assoc[simp] vector_smult_rneg[simp]
declare vector_sadd_rdistrib[simp] vector_sub_rdistrib[simp]
lemmas vector_component_simps = vector_minus_component vector_smult_component vector_add_component less_eq_vec_def vec_lambda_beta vector_uminus_component
lemma convex_box_cart:
assumes "\<And>i. convex {x. P i x}"
shows "convex {x. \<forall>i. P i (x$i)}"
using assms unfolding convex_def by auto
lemma convex_positive_orthant_cart: "convex {x::real^'n. (\<forall>i. 0 \<le> x$i)}"
by (rule convex_box_cart) (simp add: atLeast_def[symmetric])
lemma unit_interval_convex_hull_cart:
"cbox (0::real^'n) 1 = convex hull {x. \<forall>i. (x$i = 0) \<or> (x$i = 1)}"
unfolding Cart_1 unit_interval_convex_hull[where 'a="real^'n"] box_real[symmetric]
by (rule arg_cong[where f="\<lambda>x. convex hull x"]) (simp add: Basis_vec_def inner_axis)
lemma cube_convex_hull_cart:
assumes "0 < d"
obtains s::"(real^'n) set"
where "finite s" "cbox (x - (\<chi> i. d)) (x + (\<chi> i. d)) = convex hull s"
proof -
from assms obtain s where "finite s"
and "cbox (x - sum (( *\<^sub>R) d) Basis) (x + sum (( *\<^sub>R) d) Basis) = convex hull s"
by (rule cube_convex_hull)
with that[of s] show thesis
by (simp add: const_vector_cart)
qed
subsection "Derivative"
definition "jacobian f net = matrix(frechet_derivative f net)"
lemma jacobian_works:
"(f::(real^'a) \<Rightarrow> (real^'b)) differentiable net \<longleftrightarrow>
(f has_derivative (\<lambda>h. (jacobian f net) *v h)) net" (is "?lhs = ?rhs")
proof
assume ?lhs then show ?rhs
by (simp add: frechet_derivative_works has_derivative_linear jacobian_def)
next
assume ?rhs then show ?lhs
by (rule differentiableI)
qed
subsection \<open>Component of the differential must be zero if it exists at a local
maximum or minimum for that corresponding component\<close>
lemma differential_zero_maxmin_cart:
fixes f::"real^'a \<Rightarrow> real^'b"
assumes "0 < e" "((\<forall>y \<in> ball x e. (f y)$k \<le> (f x)$k) \<or> (\<forall>y\<in>ball x e. (f x)$k \<le> (f y)$k))"
"f differentiable (at x)"
shows "jacobian f (at x) $ k = 0"
using differential_zero_maxmin_component[of "axis k 1" e x f] assms
vector_cart[of "\<lambda>j. frechet_derivative f (at x) j $ k"]
by (simp add: Basis_vec_def axis_eq_axis inner_axis jacobian_def matrix_def)
subsection \<open>Lemmas for working on @{typ "real^1"}\<close>
lemma forall_1[simp]: "(\<forall>i::1. P i) \<longleftrightarrow> P 1"
by (metis (full_types) num1_eq_iff)
lemma ex_1[simp]: "(\<exists>x::1. P x) \<longleftrightarrow> P 1"
by auto (metis (full_types) num1_eq_iff)
lemma exhaust_2:
fixes x :: 2
shows "x = 1 \<or> x = 2"
proof (induct x)
case (of_int z)
then have "0 \<le> z" and "z < 2" by simp_all
then have "z = 0 | z = 1" by arith
then show ?case by auto
qed
lemma forall_2: "(\<forall>i::2. P i) \<longleftrightarrow> P 1 \<and> P 2"
by (metis exhaust_2)
lemma exhaust_3:
fixes x :: 3
shows "x = 1 \<or> x = 2 \<or> x = 3"
proof (induct x)
case (of_int z)
then have "0 \<le> z" and "z < 3" by simp_all
then have "z = 0 \<or> z = 1 \<or> z = 2" by arith
then show ?case by auto
qed
lemma forall_3: "(\<forall>i::3. P i) \<longleftrightarrow> P 1 \<and> P 2 \<and> P 3"
by (metis exhaust_3)
lemma UNIV_1 [simp]: "UNIV = {1::1}"
by (auto simp add: num1_eq_iff)
lemma UNIV_2: "UNIV = {1::2, 2::2}"
using exhaust_2 by auto
lemma UNIV_3: "UNIV = {1::3, 2::3, 3::3}"
using exhaust_3 by auto
lemma sum_1: "sum f (UNIV::1 set) = f 1"
unfolding UNIV_1 by simp
lemma sum_2: "sum f (UNIV::2 set) = f 1 + f 2"
unfolding UNIV_2 by simp
lemma sum_3: "sum f (UNIV::3 set) = f 1 + f 2 + f 3"
unfolding UNIV_3 by (simp add: ac_simps)
lemma num1_eqI:
fixes a::num1 shows "a = b"
by (metis (full_types) UNIV_1 UNIV_I empty_iff insert_iff)
lemma num1_eq1 [simp]:
fixes a::num1 shows "a = 1"
by (rule num1_eqI)
instantiation num1 :: cart_one
begin
instance
proof
show "CARD(1) = Suc 0" by auto
qed
end
instantiation num1 :: linorder begin
definition "a < b \<longleftrightarrow> Rep_num1 a < Rep_num1 b"
definition "a \<le> b \<longleftrightarrow> Rep_num1 a \<le> Rep_num1 b"
instance
by intro_classes (auto simp: less_eq_num1_def less_num1_def intro: num1_eqI)
end
instance num1 :: wellorder
by intro_classes (auto simp: less_eq_num1_def less_num1_def)
subsection\<open>The collapse of the general concepts to dimension one\<close>
lemma vector_one: "(x::'a ^1) = (\<chi> i. (x$1))"
by (simp add: vec_eq_iff)
lemma forall_one: "(\<forall>(x::'a ^1). P x) \<longleftrightarrow> (\<forall>x. P(\<chi> i. x))"
apply auto
apply (erule_tac x= "x$1" in allE)
apply (simp only: vector_one[symmetric])
done
lemma norm_vector_1: "norm (x :: _^1) = norm (x$1)"
by (simp add: norm_vec_def)
lemma dist_vector_1:
fixes x :: "'a::real_normed_vector^1"
shows "dist x y = dist (x$1) (y$1)"
by (simp add: dist_norm norm_vector_1)
lemma norm_real: "norm(x::real ^ 1) = \<bar>x$1\<bar>"
by (simp add: norm_vector_1)
lemma dist_real: "dist(x::real ^ 1) y = \<bar>(x$1) - (y$1)\<bar>"
by (auto simp add: norm_real dist_norm)
subsection\<open> Rank of a matrix\<close>
text\<open>Equivalence of row and column rank is taken from George Mackiw's paper, Mathematics Magazine 1995, p. 285.\<close>
lemma matrix_vector_mult_in_columnspace_gen:
fixes A :: "'a::field^'n^'m"
shows "(A *v x) \<in> vec.span(columns A)"
apply (simp add: matrix_vector_column columns_def transpose_def column_def)
apply (intro vec.span_sum vec.span_scale)
apply (force intro: vec.span_base)
done
lemma matrix_vector_mult_in_columnspace:
fixes A :: "real^'n^'m"
shows "(A *v x) \<in> span(columns A)"
using matrix_vector_mult_in_columnspace_gen[of A x] by (simp add: span_vec_eq)
lemma orthogonal_nullspace_rowspace:
fixes A :: "real^'n^'m"
assumes 0: "A *v x = 0" and y: "y \<in> span(rows A)"
shows "orthogonal x y"
proof (rule span_induct [OF y])
show "subspace {a. orthogonal x a}"
by (simp add: subspace_orthogonal_to_vector)
next
fix v
assume "v \<in> rows A"
then obtain i where "v = row i A"
by (auto simp: rows_def)
with 0 show "orthogonal x v"
unfolding orthogonal_def inner_vec_def matrix_vector_mult_def row_def
by (simp add: mult.commute) (metis (no_types) vec_lambda_beta zero_index)
qed
lemma nullspace_inter_rowspace:
fixes A :: "real^'n^'m"
shows "A *v x = 0 \<and> x \<in> span(rows A) \<longleftrightarrow> x = 0"
using orthogonal_nullspace_rowspace orthogonal_self span_zero matrix_vector_mult_0_right
by blast
lemma matrix_vector_mul_injective_on_rowspace:
fixes A :: "real^'n^'m"
shows "\<lbrakk>A *v x = A *v y; x \<in> span(rows A); y \<in> span(rows A)\<rbrakk> \<Longrightarrow> x = y"
using nullspace_inter_rowspace [of A "x-y"]
by (metis diff_eq_diff_eq diff_self matrix_vector_mult_diff_distrib span_diff)
definition rank :: "'a::field^'n^'m=>nat"
where row_rank_def_gen: "rank A \<equiv> vec.dim(rows A)"
lemma row_rank_def: "rank A = dim (rows A)" for A::"real^'n^'m"
by (auto simp: row_rank_def_gen dim_vec_eq)
lemma dim_rows_le_dim_columns:
fixes A :: "real^'n^'m"
shows "dim(rows A) \<le> dim(columns A)"
proof -
have "dim (span (rows A)) \<le> dim (span (columns A))"
proof -
obtain B where "independent B" "span(rows A) \<subseteq> span B"
and B: "B \<subseteq> span(rows A)""card B = dim (span(rows A))"
using basis_exists [of "span(rows A)"] by blast
then have eq: "span B = span(rows A)"
using span_subspace subspace_span by blast
then have inj: "inj_on (( *v) A) (span B)"
by (simp add: inj_on_def matrix_vector_mul_injective_on_rowspace)
then have ind: "independent (( *v) A ` B)"
by (rule linear_independent_injective_image [OF Finite_Cartesian_Product.matrix_vector_mul_linear \<open>independent B\<close>])
have "dim (span (rows A)) \<le> card (( *v) A ` B)"
unfolding B(2)[symmetric]
using inj
by (auto simp: card_image inj_on_subset span_superset)
also have "\<dots> \<le> dim (span (columns A))"
using _ ind
by (rule independent_card_le_dim) (auto intro!: matrix_vector_mult_in_columnspace)
finally show ?thesis .
qed
then show ?thesis
by (simp add: dim_span)
qed
lemma column_rank_def:
fixes A :: "real^'n^'m"
shows "rank A = dim(columns A)"
unfolding row_rank_def
by (metis columns_transpose dim_rows_le_dim_columns le_antisym rows_transpose)
lemma rank_transpose:
fixes A :: "real^'n^'m"
shows "rank(transpose A) = rank A"
by (metis column_rank_def row_rank_def rows_transpose)
lemma matrix_vector_mult_basis:
fixes A :: "real^'n^'m"
shows "A *v (axis k 1) = column k A"
by (simp add: cart_eq_inner_axis column_def matrix_mult_dot)
lemma columns_image_basis:
fixes A :: "real^'n^'m"
shows "columns A = ( *v) A ` (range (\<lambda>i. axis i 1))"
by (force simp: columns_def matrix_vector_mult_basis [symmetric])
lemma rank_dim_range:
fixes A :: "real^'n^'m"
shows "rank A = dim(range (\<lambda>x. A *v x))"
unfolding column_rank_def
proof (rule span_eq_dim)
have "span (columns A) \<subseteq> span (range (( *v) A))" (is "?l \<subseteq> ?r")
by (simp add: columns_image_basis image_subsetI span_mono)
then show "?l = ?r"
by (metis (no_types, lifting) image_subset_iff matrix_vector_mult_in_columnspace
span_eq span_span)
qed
lemma rank_bound:
fixes A :: "real^'n^'m"
shows "rank A \<le> min CARD('m) (CARD('n))"
by (metis (mono_tags, lifting) dim_subset_UNIV_cart min.bounded_iff
column_rank_def row_rank_def)
lemma full_rank_injective:
fixes A :: "real^'n^'m"
shows "rank A = CARD('n) \<longleftrightarrow> inj (( *v) A)"
by (simp add: matrix_left_invertible_injective [symmetric] matrix_left_invertible_span_rows row_rank_def
dim_eq_full [symmetric] card_cart_basis vec.dimension_def)
lemma full_rank_surjective:
fixes A :: "real^'n^'m"
shows "rank A = CARD('m) \<longleftrightarrow> surj (( *v) A)"
by (simp add: matrix_right_invertible_surjective [symmetric] left_invertible_transpose [symmetric]
matrix_left_invertible_injective full_rank_injective [symmetric] rank_transpose)
lemma rank_I: "rank(mat 1::real^'n^'n) = CARD('n)"
by (simp add: full_rank_injective inj_on_def)
lemma less_rank_noninjective:
fixes A :: "real^'n^'m"
shows "rank A < CARD('n) \<longleftrightarrow> \<not> inj (( *v) A)"
using less_le rank_bound by (auto simp: full_rank_injective [symmetric])
lemma matrix_nonfull_linear_equations_eq:
fixes A :: "real^'n^'m"
shows "(\<exists>x. (x \<noteq> 0) \<and> A *v x = 0) \<longleftrightarrow> ~(rank A = CARD('n))"
by (meson matrix_left_invertible_injective full_rank_injective matrix_left_invertible_ker)
lemma rank_eq_0: "rank A = 0 \<longleftrightarrow> A = 0" and rank_0 [simp]: "rank (0::real^'n^'m) = 0"
for A :: "real^'n^'m"
by (auto simp: rank_dim_range matrix_eq)
lemma rank_mul_le_right:
fixes A :: "real^'n^'m" and B :: "real^'p^'n"
shows "rank(A ** B) \<le> rank B"
proof -
have "rank(A ** B) \<le> dim (( *v) A ` range (( *v) B))"
by (auto simp: rank_dim_range image_comp o_def matrix_vector_mul_assoc)
also have "\<dots> \<le> rank B"
by (simp add: rank_dim_range dim_image_le)
finally show ?thesis .
qed
lemma rank_mul_le_left:
fixes A :: "real^'n^'m" and B :: "real^'p^'n"
shows "rank(A ** B) \<le> rank A"
by (metis matrix_transpose_mul rank_mul_le_right rank_transpose)
subsection\<open>Routine results connecting the types @{typ "real^1"} and @{typ real}\<close>
lemma vector_one_nth [simp]:
fixes x :: "'a^1" shows "vec (x $ 1) = x"
by (metis vec_def vector_one)
lemma vec_cbox_1_eq [simp]:
shows "vec ` cbox u v = cbox (vec u) (vec v ::real^1)"
by (force simp: Basis_vec_def cart_eq_inner_axis [symmetric] mem_box)
lemma vec_nth_cbox_1_eq [simp]:
fixes u v :: "'a::euclidean_space^1"
shows "(\<lambda>x. x $ 1) ` cbox u v = cbox (u$1) (v$1)"
by (auto simp: Basis_vec_def cart_eq_inner_axis [symmetric] mem_box image_iff Bex_def inner_axis) (metis vec_component)
lemma vec_nth_1_iff_cbox [simp]:
fixes a b :: "'a::euclidean_space"
shows "(\<lambda>x::'a^1. x $ 1) ` S = cbox a b \<longleftrightarrow> S = cbox (vec a) (vec b)"
(is "?lhs = ?rhs")
proof
assume L: ?lhs show ?rhs
proof (intro equalityI subsetI)
fix x
assume "x \<in> S"
then have "x $ 1 \<in> (\<lambda>v. v $ (1::1)) ` cbox (vec a) (vec b)"
using L by auto
then show "x \<in> cbox (vec a) (vec b)"
by (metis (no_types, lifting) imageE vector_one_nth)
next
fix x :: "'a^1"
assume "x \<in> cbox (vec a) (vec b)"
then show "x \<in> S"
by (metis (no_types, lifting) L imageE imageI vec_component vec_nth_cbox_1_eq vector_one_nth)
qed
qed simp
lemma tendsto_at_within_vector_1:
fixes S :: "'a :: metric_space set"
assumes "(f \<longlongrightarrow> fx) (at x within S)"
shows "((\<lambda>y::'a^1. \<chi> i. f (y $ 1)) \<longlongrightarrow> (vec fx::'a^1)) (at (vec x) within vec ` S)"
proof (rule topological_tendstoI)
fix T :: "('a^1) set"
assume "open T" "vec fx \<in> T"
have "\<forall>\<^sub>F x in at x within S. f x \<in> (\<lambda>x. x $ 1) ` T"
using \<open>open T\<close> \<open>vec fx \<in> T\<close> assms open_image_vec_nth tendsto_def by fastforce
then show "\<forall>\<^sub>F x::'a^1 in at (vec x) within vec ` S. (\<chi> i. f (x $ 1)) \<in> T"
unfolding eventually_at dist_norm [symmetric]
by (rule ex_forward)
(use \<open>open T\<close> in
\<open>fastforce simp: dist_norm dist_vec_def L2_set_def image_iff vector_one open_vec_def\<close>)
qed
lemma has_derivative_vector_1:
assumes der_g: "(g has_derivative (\<lambda>x. x * g' a)) (at a within S)"
shows "((\<lambda>x. vec (g (x $ 1))) has_derivative ( *\<^sub>R) (g' a))
(at ((vec a)::real^1) within vec ` S)"
using der_g
apply (auto simp: Deriv.has_derivative_within bounded_linear_scaleR_right norm_vector_1)
apply (drule tendsto_at_within_vector_1, vector)
apply (auto simp: algebra_simps eventually_at tendsto_def)
done
subsection\<open>Explicit vector construction from lists\<close>
definition "vector l = (\<chi> i. foldr (\<lambda>x f n. fun_upd (f (n+1)) n x) l (\<lambda>n x. 0) 1 i)"
lemma vector_1: "(vector[x]) $1 = x"
unfolding vector_def by simp
lemma vector_2:
"(vector[x,y]) $1 = x"
"(vector[x,y] :: 'a^2)$2 = (y::'a::zero)"
unfolding vector_def by simp_all
lemma vector_3:
"(vector [x,y,z] ::('a::zero)^3)$1 = x"
"(vector [x,y,z] ::('a::zero)^3)$2 = y"
"(vector [x,y,z] ::('a::zero)^3)$3 = z"
unfolding vector_def by simp_all
lemma forall_vector_1: "(\<forall>v::'a::zero^1. P v) \<longleftrightarrow> (\<forall>x. P(vector[x]))"
by (metis vector_1 vector_one)
lemma forall_vector_2: "(\<forall>v::'a::zero^2. P v) \<longleftrightarrow> (\<forall>x y. P(vector[x, y]))"
apply auto
apply (erule_tac x="v$1" in allE)
apply (erule_tac x="v$2" in allE)
apply (subgoal_tac "vector [v$1, v$2] = v")
apply simp
apply (vector vector_def)
apply (simp add: forall_2)
done
lemma forall_vector_3: "(\<forall>v::'a::zero^3. P v) \<longleftrightarrow> (\<forall>x y z. P(vector[x, y, z]))"
apply auto
apply (erule_tac x="v$1" in allE)
apply (erule_tac x="v$2" in allE)
apply (erule_tac x="v$3" in allE)
apply (subgoal_tac "vector [v$1, v$2, v$3] = v")
apply simp
apply (vector vector_def)
apply (simp add: forall_3)
done
lemma bounded_linear_component_cart[intro]: "bounded_linear (\<lambda>x::real^'n. x $ k)"
apply (rule bounded_linearI[where K=1])
using component_le_norm_cart[of _ k] unfolding real_norm_def by auto
lemma interval_split_cart:
"{a..b::real^'n} \<inter> {x. x$k \<le> c} = {a .. (\<chi> i. if i = k then min (b$k) c else b$i)}"
"cbox a b \<inter> {x. x$k \<ge> c} = {(\<chi> i. if i = k then max (a$k) c else a$i) .. b}"
apply (rule_tac[!] set_eqI)
unfolding Int_iff mem_box_cart mem_Collect_eq interval_cbox_cart
unfolding vec_lambda_beta
by auto
lemmas cartesian_euclidean_space_uniform_limit_intros[uniform_limit_intros] =
bounded_linear.uniform_limit[OF blinfun.bounded_linear_right]
bounded_linear.uniform_limit[OF bounded_linear_vec_nth]
bounded_linear.uniform_limit[OF bounded_linear_component_cart]
end