Theory Determinant_Impl

(*  
    Author:      René Thiemann 
                 Akihisa Yamada
    License:     BSD
*)
section ‹Code Equations for Determinants›

text ‹We compute determinants on arbitrary rings by applying elementary row-operations
  to bring a matrix on upper-triangular form. Then the determinant can be determined
  by multiplying all entries on the diagonal. Moreover the final result has to be divided
  by a factor which is determined by the row-operations that we performed. To this end,
  we require a division operation on the element type.

  The algorithm is parametric in a selection function for the pivot-element, e.g., for 
  matrices over polynomials it turned out that selecting a polynomial of minimal degree
  is beneficial.›

theory Determinant_Impl
imports
  Polynomial_Interpolation.Missing_Polynomial
  "HOL-Computational_Algebra.Polynomial_Factorial"
  Determinant
begin

type_synonym 'a det_selection_fun = "(nat × 'a)list ⇒ nat"

definition det_selection_fun :: "'a det_selection_fun ⇒ bool" where 
  "det_selection_fun f = (∀ xs. xs ≠ [] ⟶ f xs ∈ fst ` set xs)"


lemma det_selection_funD: "det_selection_fun f ⟹ xs ≠ [] ⟹ f xs ∈ fst ` set xs"
  unfolding det_selection_fun_def by auto

definition mute_fun :: "('a :: comm_ring_1 ⇒ 'a ⇒ 'a × 'a × 'a) ⇒ bool" where
  "mute_fun f = (∀ x y x' y' g. f x y = (x',y',g) ⟶ y ≠ 0 
   ⟶ x = x' * g ∧ y * x' = x * y')"

context
  fixes sel_fun :: "'a ::idom_divide det_selection_fun"
begin

subsection ‹Properties of triangular matrices›

text ‹
  Each column of a triangular matrix should satisfy the following property.
›

definition triangular_column::"nat ⇒ 'a mat ⇒ bool"
  where "triangular_column j A ≡ ∀i. j < i ⟶ i < dim_row A ⟶ A $$ (i,j) = 0"

lemma triangular_columnD [dest]:
  "triangular_column j A ⟹ j < i ⟹ i < dim_row A ⟹ A $$ (i,j) = 0"
  unfolding triangular_column_def by auto

lemma triangular_columnI [intro]:
  "(⋀i. j < i ⟹ i < dim_row A ⟹ A $$ (i,j) = 0) ⟹ triangular_column j A"
  unfolding triangular_column_def by auto

text ‹
  The following predicate states that the first $k$ columns satisfy
  triangularity.
›

definition triangular_to:: "nat ⇒ 'a mat ⇒ bool"
  where "triangular_to k A == ∀j. j<k ⟶ triangular_column j A"

lemma triangular_to_triangular: "upper_triangular A = triangular_to (dim_row A) A"
  unfolding triangular_to_def triangular_column_def upper_triangular_def
  by auto

lemma triangular_toD [dest]:
  "triangular_to k A ⟹ j < k ⟹ j < i ⟹ i < dim_row A ⟹ A $$ (i,j) = 0"
  unfolding triangular_to_def triangular_column_def by auto

lemma triangular_toI [intro]:
  "(⋀i j. j < k ⟹ j < i ⟹ i < dim_row A ⟹ A $$ (i,j) = 0) ⟹ triangular_to k A"
  unfolding triangular_to_def triangular_column_def by auto

lemma triangle_growth:
  assumes tri:"triangular_to k A"
  and col:"triangular_column k A"
  shows "triangular_to (Suc k) A"
  unfolding triangular_to_def
proof (intro allI impI)
  fix i assume iSk:"i < Suc k"
  show "triangular_column i A"
  proof (cases "i = k")
    case True
      then show ?thesis using col by auto next
    case False
      then have "i < k" using iSk by auto
      thus ?thesis using tri unfolding triangular_to_def by auto
  qed
qed

lemma triangle_trans: "triangular_to k A ⟹ k > k' ⟹ triangular_to k' A"
  by (intro triangular_toI, elim triangular_toD, auto)


subsection ‹Algorithms for Triangulization›

context 
  fixes mf :: "'a ⇒ 'a ⇒ 'a × 'a × 'a"
begin

private fun mute :: "'a ⇒ nat ⇒ nat ⇒ 'a × 'a mat ⇒ 'a × 'a mat" where
  "mute A_ll k l (r,A) = (let p = A $$ (k,l) in if p = 0 then (r,A) else 
    case mf A_ll p of (q',p',g) ⇒ 
      (r * q', addrow (-p') k l (multrow k q' A)))" 

lemma mute_preserves_dimensions:
  assumes "mute q k l (r,A) = (r',A')"
  shows [simp]: "dim_row A' = dim_row A" and [simp]: "dim_col A' = dim_col A"
using assms by (auto simp: Let_def split: if_splits prod.splits)

text ‹
  Algorithm @{term "mute k l"} makes $k$-th row $l$-th column element to 0.
›

lemma mute_makes_0 :
 assumes mute_fun: "mute_fun mf"
 assumes "mute (A $$ (l,l)) k l (r,A) = (r',A')"
 "l < dim_row A"
 "l < dim_col A"
 "k < dim_row A"
 "k ≠ l"
 shows "A' $$ (k,l) = 0"
proof -
  define a where "a = A $$ (l, l)"
  define b where "b = A $$ (k, l)"
  let ?mf = "mf (A $$ (l, l)) (A $$ (k, l))"
  obtain q' p' g where id: "?mf = (q',p',g)" by (cases ?mf, auto)
  note mf = mute_fun[unfolded mute_fun_def, rule_format, OF id]
  from assms show ?thesis
  unfolding mat_addrow_def using mf id by (auto simp: ac_simps Let_def split: if_splits)
qed

text ‹It will not touch unexpected rows.›
lemma mute_preserves:
  "mute q k l (r,A) = (r',A') ⟹
   i < dim_row A ⟹
   j < dim_col A ⟹
   l < dim_row A ⟹
   k < dim_row A ⟹
   i ≠ k ⟹
   A' $$ (i,j) = A $$ (i,j)"
   by (auto simp: Let_def split: if_splits prod.splits)

text ‹It preserves $0$s in the touched row.›
lemma mute_preserves_0:
  "mute q k l (r,A) = (r',A') ⟹
   i < dim_row A ⟹
   j < dim_col A ⟹
   l < dim_row A ⟹
   k < dim_row A ⟹
   A $$ (i,j) = 0 ⟹
   A $$ (l,j) = 0 ⟹
   A' $$ (i,j) = 0"
   by (auto simp: Let_def split: if_splits prod.splits)

text ‹Hence, it will respect partially triangular matrix.›
lemma mute_preserves_triangle:
 assumes rA' : "mute q k l (r,A) = (r',A')"
 and triA: "triangular_to l A"
 and lk: "l < k"
 and kr: "k < dim_row A"
 and lr: "l < dim_row A"
 and lc: "l < dim_col A"
 shows "triangular_to l A'"
proof (rule triangular_toI)
  fix i j
  assume jl: "j < l" and ji: "j < i" and ir': "i < dim_row A'"
  then have A0: "A $$ (i,j) = 0" using triA rA' by auto
  moreover have "A $$ (l,j) = 0" using triA jl jl lr by auto
  moreover have jc:"j < dim_col A" using jl lc by auto
  moreover have ir: "i < dim_row A" using ir' rA' by auto
  ultimately show "A' $$ (i,j) = 0"
    using mute_preserves_0[OF rA'] lr kr by auto
qed


text ‹Recursive application of @{const mute}›

private fun sub1 :: "'a ⇒ nat ⇒ nat ⇒ 'a × 'a mat ⇒ 'a × 'a mat"
where "sub1 q 0 l rA = rA"
  | "sub1 q (Suc k) l rA = mute q (l + Suc k) l (sub1 q k l rA)"

lemma sub1_preserves_dimensions[simp]:
  "sub1 q k l (r,A) = (r',A') ⟹ dim_row A' = dim_row A"
  "sub1 q k l (r,A) = (r',A') ⟹ dim_col A' = dim_col A"
proof (induction k arbitrary: r' A')
  case (Suc k)
    moreover obtain r' A' where rA': "sub1 q k l (r, A) = (r', A')" by force
    moreover fix r'' A'' assume "sub1 q (Suc k) l (r, A) = (r'', A'')" 
    ultimately show "dim_row A'' = dim_row A" "dim_col A'' = dim_col A" by auto
qed auto

lemma sub1_closed [simp]:
  "sub1 q k l (r,A) = (r',A') ⟹ A ∈ carrier_mat m n ⟹ A' ∈ carrier_mat m n"
  unfolding carrier_mat_def by auto

lemma sub1_preserves_diagnal:
  assumes "sub1 q k l (r,A) = (r',A')"
  and "l < dim_col A"
  and "k + l < dim_row A"
  shows "A' $$ (l,l) = A $$ (l,l)"
using assms
proof -
  show "k + l < dim_row A ⟹ sub1 q k l (r,A) = (r',A') ⟹
    A' $$ (l,l) = A $$ (l,l)"
  proof (induction k arbitrary: r' A')
    case (Suc k)
      obtain r'' A'' where rA''[simp]: "sub1 q k l (r,A) = (r'',A'')" by force
      have [simp]:"dim_row A'' = dim_row A" and [simp]:"dim_col A'' = dim_col A"
        using snd_conv sub1_preserves_dimensions[OF rA''] by auto
      have "A'' $$ (l,l) = A $$ (l,l)" using assms Suc by auto
      have rA': "mute q (l + Suc k) l (r'', A'') = (r',A')"
        using Suc by auto
      show ?case using subst mute_preserves[OF rA'] Suc assms by auto
  qed auto
qed

text ‹Triangularity is respected by @{const sub1}.›
lemma sub1_preserves_triangle:
  assumes "sub1 q k l (r,A) = (r',A')"
  and tri: "triangular_to l A"
  and lr: "l < dim_row A"
  and lc: "l < dim_col A"
  and lkr: "l + k < dim_row A"
  shows "triangular_to l A'"
using assms
proof -
  show "sub1 q k l (r,A) = (r',A') ⟹ l + k < dim_row A ⟹
    triangular_to l A'"
  proof (induction k arbitrary: r' A')
  case (Suc k)
    then have "sub1 q (Suc k) l (r,A) = (r',A')" by auto
    moreover obtain r'' A''
      where rA'': "sub1 q k l (r, A) = (r'',A'')" by force
    ultimately
      have rA': "mute q (Suc (l + k)) l (r'',A'') = (r',A')" by auto
    have "triangular_to l A''" using rA'' Suc by auto
    thus ?case
      using Suc assms mute_preserves_triangle[OF rA'] rA'' by auto
  qed (insert assms,auto)
qed

context
  assumes mf: "mute_fun mf"
begin
lemma sub1_makes_0s:
  assumes "sub1 (A $$ (l,l)) k l (r,A) = (r',A')"
  and lr: "l < dim_row A"
  and lc: "l < dim_col A"
  and li: "l < i"
  and "i ≤ k + l"
  and "k + l < dim_row A"
  shows "A' $$ (i,l) = 0"
using assms
proof -
  show "sub1 (A $$ (l,l)) k l (r,A) = (r',A') ⟹ i ≤ k + l ⟹ k + l < dim_row A ⟹
    A' $$ (i,l) = 0"
  using lr lc li
  proof (induction k arbitrary: r' A')
  case (Suc k)
    obtain r' A' where rA': "sub1 (A $$ (l,l)) k l (r, A) = (r',A')" by force
    fix r'' A''
    from sub1_preserves_diagnal[OF rA'] have AA': "A $$ (l, l) = A' $$ (l, l)" using Suc(2-) by auto
    assume "sub1 (A $$ (l,l)) (Suc k) l (r, A) = (r'',A'')"
    then have rA'': "mute (A $$ (l,l)) (Suc (l + k)) l (r', A') = (r'', A'')"
      using rA' by simp
    have ir: "i < dim_row A" using Suc by auto
    have il: "i ≠ l" using li by auto
    have lr': "l < dim_row A'" using lr rA' by auto
    have lc': "l < dim_col A'" using lc rA' by auto
    have Slkr': "Suc (l+k) < dim_row A'" using Suc rA' by auto
    show "A'' $$ (i,l) = 0"
    proof (cases "Suc(l + k) = i")
      case True {
        have l: "Suc (l + k) ≠ l" by auto
        show ?thesis
          using mute_makes_0[OF mf rA''[unfolded AA'] lr' lc' Slkr' l] ir il rA'
          by (simp add:True)
      } next
      case False {
        then have ikl: "i ≤ k+l" using Suc by auto
        have ir': "i < dim_row A'" using ir rA' by auto
        have lc': "l < dim_col A'" using lc rA' by auto
        have IH: "A' $$ (i,l) = 0" using rA' Suc False by auto
        thus ?thesis using mute_preserves[OF rA'' ir' lc'] rA' False Suc
          by simp
      }
    qed
  qed auto
qed

lemma sub1_triangulizes_column:
  assumes rA': "sub1 (A $$ (l,l)) (dim_row A - Suc l) l (r,A) = (r',A')"
  and tri:"triangular_to l A"
  and r: "dim_row A > 0"
  and lr: "l < dim_row A"
  and lc: "l < dim_col A"
  shows "triangular_column l A'"
proof (intro triangular_columnI)
  fix i
  assume li: "l < i"
  assume ir: "i < dim_row A'"
    also have "... = dim_row A" using sub1_preserves_dimensions[OF rA'] by auto
    also have "... = dim_row A - l + l" using lr li by auto
    finally have ir2: "i ≤ dim_row A - l + l" by auto
  show "A' $$ (i,l) = 0"
    apply (subst sub1_makes_0s[OF rA' lr lc])
    using li ir assms
    by auto
qed

text ‹
  The algorithm @{const sub1} increases the number of columns that form triangle.
›
lemma sub1_grows_triangle:
  assumes rA': "sub1 (A $$ (l,l)) (dim_row A - Suc l) l (r,A) = (r',A')"
  and r: "dim_row A > 0"
  and tri:"triangular_to l A"
  and lr: "l < dim_row A"
  and lc: "l < dim_col A"
  shows "triangular_to (Suc l) A'"
proof -
  have "triangular_to l A'"
    using sub1_preserves_triangle[OF rA'] assms by auto
  moreover have "triangular_column l A'"
    using sub1_triangulizes_column[OF rA'] assms by auto
  ultimately show ?thesis by (rule triangle_growth)
qed
end

subsection ‹Finding Non-Zero Elements›

private definition find_non0 :: "nat ⇒ 'a mat ⇒ nat option" where
  "find_non0 l A = (let is = [Suc l ..< dim_row A];
    Ais = filter (λ (i,Ail). Ail ≠ 0) (map (λ i. (i, A $$ (i,l))) is)
    in case Ais of [] ⇒ None | _ ⇒ Some (sel_fun Ais))"

lemma find_non0: assumes sel_fun: "det_selection_fun sel_fun"
  and res: "find_non0 l A = Some m"
  shows "A $$ (m,l) ≠ 0" "l < m" "m < dim_row A"
proof -
  let ?xs = "filter (λ (i,Ail). Ail ≠ 0) (map (λ i. (i, A $$ (i,l))) [Suc l..<dim_row A])"
  from res[unfolded find_non0_def Let_def]
  have xs: "?xs ≠ []" and m: "m = sel_fun ?xs"
    by (cases ?xs, auto)+
  from det_selection_funD[OF sel_fun xs, folded m] show "A $$ (m, l) ≠ 0" "l < m" "m < dim_row A" by auto
qed

text ‹
  If @{term "find_non0 l A"} fails,
  then $A$ is already triangular to $l$-th column.
›

lemma find_non0_all0:
  "find_non0 l A = None ⟹ triangular_column l A"
proof (intro triangular_columnI) 
  fix i
  let ?xs = "filter (λ (i,Ail). Ail ≠ 0) (map (λ i. (i, A $$ (i,l))) [Suc l..<dim_row A])"
  assume none: "find_non0 l A = None" and li: "l < i" "i < dim_row A"
  from none have xs: "?xs = []"
    unfolding find_non0_def Let_def by (cases ?xs, auto)
  from li have "(i, A $$ (i,l)) ∈ set (map (λ i. (i, A $$ (i,l))) [Suc l..<dim_row A])" by auto
  with xs show "A $$ (i,l) = 0"
    by (metis (mono_tags) xs case_prodI filter_empty_conv)
qed

subsection ‹Determinant Preserving Growth of Triangle›

text ‹
  The algorithm @{const sub1} does not preserve determinants when it hits
  a $0$-valued diagonal element. To avoid this case, we introduce the following
  operation:
›

private fun sub2 :: "nat ⇒ nat ⇒ 'a × 'a mat ⇒ 'a × 'a mat"
  where "sub2 d l (r,A) = (
    case find_non0 l A of None ⇒ (r,A)
    | Some m ⇒ let A' = swaprows m l A in sub1 (A' $$ (l,l)) (d - Suc l) l (-r, A'))"

lemma sub2_preserves_dimensions[simp]:
  assumes rA': "sub2 d l (r,A) = (r',A')"
  shows "dim_row A' = dim_row A ∧ dim_col A' = dim_col A"
proof (cases "find_non0 l A")
  case None then show ?thesis using rA' by auto next
  case (Some m) then show ?thesis using rA' by (cases "m = l", auto simp: Let_def)
qed

lemma sub2_closed [simp]:
  "sub2 d l (r,A) = (r',A') ⟹ A ∈ carrier_mat m n ⟹ A' ∈ carrier_mat m n"
  unfolding carrier_mat_def by auto

context 
  assumes sel_fun: "det_selection_fun sel_fun"
begin

lemma sub2_preserves_triangle:
  assumes rA': "sub2 d l (r,A) = (r',A')"
  and tri: "triangular_to l A"
  and lc: "l < dim_col A"
  and ld: "l < d"
  and dr: "d ≤ dim_row A"
  shows "triangular_to l A'"
proof -
  have lr: "l < dim_row A" using ld dr by auto
  show ?thesis
  proof (cases "find_non0 l A")
    case None then show ?thesis using rA' tri by simp next
    case (Some m) {
      have lm : "l < m" and mr : "m < dim_row A"
        using find_non0[OF sel_fun Some] by auto
      let ?A1 = "swaprows m l A"
  
      have tri'': "triangular_to l ?A1"
      proof (intro triangular_toI)
        fix i j
        assume jl:"j < l" and ji:"j < i" and ir1: "i < dim_row ?A1"
        have jm: "j < m" using jl lm by auto
        have ir: "i < dim_row A" using ir1 by auto
        have jc: "j < dim_col A" using jl lc by auto
        show "?A1 $$ (i, j) = 0"
        proof (cases "m=i")
          case True {
            then have li: "l ≠ i" using lm by auto
            hence "?A1 $$ (i,j) = A $$ (l,j)" using ir jc ‹m=i› by auto
            also have "... = 0" using tri jl lr by auto
            finally show ?thesis.
           }  next
          case False show ?thesis
            proof (cases "l=i")
              case True {
                then have "?A1 $$ (i,j) = A $$ (m,j)"
                  using ir jc ‹m≠i› by auto
                thus "?A1 $$ (i,j) = 0" using tri jl jm mr by auto
              } next
              case False {
                then have "?A1 $$ (i,j) = A $$ (i,j)"
                  using ir jc ‹m≠i› by auto
                thus "?A1 $$ (i,j) = 0" using tri jl ji ir by auto
              }
           qed
        qed
      qed
  
      let ?rA3 = "sub1 (?A1 $$ (l,l)) (d - Suc l) l (-r,?A1)"
      have [simp]: "dim_row ?A1 = dim_row A ∧ dim_col ?A1 = dim_col A" by auto
      have rA'2: "?rA3 = (r',A')" using rA' Some by (simp add: Let_def)
      have "l + (d - Suc l) < dim_row A" using ld dr by auto
      thus ?thesis
        using sub1_preserves_triangle[OF rA'2 tri''] lr lc rA' by auto
    }
  qed
qed

lemma sub2_grows_triangle:
  assumes mf: "mute_fun mf"
  and rA': "sub2 (dim_row A) l (r,A) = (r',A')"
  and tri: "triangular_to l A"
  and lc: "l < dim_col A"
  and lr: "l < dim_row A"
  shows "triangular_to (Suc l) A'"
proof (rule triangle_growth)
  show "triangular_to l A'"
    using sub2_preserves_triangle[OF rA' tri lc lr] by auto
    next
  have r0: "0 < dim_row A" using lr by auto
  show "triangular_column l A'"
    proof (cases "find_non0 l A")
      case None {
        then have "A' = A" using rA' by simp
        moreover have "triangular_column l A"  using find_non0_all0[OF None].
        ultimately show ?thesis by auto
      } next
      case (Some m) {
        have lm: "l < m" and mr: "m < dim_row A"
          using find_non0[OF sel_fun Some] by auto
        let ?A = "swaprows m l A"
        have tri2: "triangular_to l ?A"
          proof
            fix i j assume jl: "j < l" and ji:"j < i" and ir: "i < dim_row ?A"
            show "?A $$ (i,j) = 0"
            proof (cases "i = m")
              case True {
                then have "?A $$ (i,j) = A $$ (l,j)"
                  using jl lc ir by simp
                also have "... = 0"
                  using triangular_toD[OF tri jl jl] lr by auto
                finally show ?thesis by auto
              } next
              case False show ?thesis
                proof (cases "i = l")
                  case True {
                    then have "?A $$ (i,j) = A $$ (m,j)"
                      using jl lc ir by auto
                    also have "... = 0"
                      using triangular_toD[OF tri jl] jl lm mr by auto
                    finally show ?thesis by auto
                  } next
                  case False {
                    then have "?A $$ (i,j) = A $$ (i,j)"
                      using ‹i ≠ m› jl lc ir by auto
                    thus ?thesis using tri jl ji ir by auto
                  }
                qed
            qed
          qed
        have rA'2: "sub1 (?A $$ (l,l)) (dim_row ?A - Suc l) l (-r, ?A) = (r',A')"
          using lm Some rA' by (simp add: Let_def)
        show ?thesis
          using sub1_triangulizes_column[OF mf rA'2 tri2] r0 lr lc by auto
      }
    qed
qed
end

subsection ‹Recursive Triangulization of Columns›

text ‹
  Now we recursively apply @{const sub2} to make the entire matrix to be triangular.
›

private fun sub3 :: "nat ⇒ nat ⇒ 'a × 'a mat ⇒ 'a × 'a mat"
  where "sub3 d 0 rA = rA"
  | "sub3 d (Suc l) rA = sub2 d l (sub3 d l rA)"

lemma sub3_preserves_dimensions[simp]:
  "sub3 d l (r,A) = (r',A') ⟹ dim_row A' = dim_row A"
  "sub3 d l (r,A) = (r',A') ⟹ dim_col A' = dim_col A"
proof (induction l arbitrary: r' A')
  case (Suc l)
    obtain r' A' where rA': "sub3 d l (r, A) = (r', A')" by force
    fix r'' A'' assume rA'': "sub3 d (Suc l) (r, A) = (r'', A'')" 
    then show "dim_row A'' = dim_row A" "dim_col A'' = dim_col A"
    using Suc rA' by auto
qed auto

lemma sub3_closed[simp]:
  "sub3 k l (r,A) = (r',A') ⟹ A ∈ carrier_mat m n ⟹ A' ∈ carrier_mat m n"
  unfolding carrier_mat_def by auto

lemma sub3_makes_triangle:
  assumes mf: "mute_fun mf"
  and sel_fun: "det_selection_fun sel_fun"
  and "sub3 (dim_row A) l (r,A) = (r',A')"
  and "l ≤ dim_row A"
  and "l ≤ dim_col A"
  shows "triangular_to l A'"
  using assms
proof -
  show "sub3 (dim_row A) l (r,A) = (r',A') ⟹ l ≤ dim_row A ⟹ l ≤ dim_col A ⟹
    triangular_to l A'"
  proof (induction l arbitrary:r' A')
    case (Suc l)
      then have Slr: "Suc l ≤ dim_row A" and Slc: "Suc l ≤ dim_col A" by auto
      hence lr: "l < dim_row A" and lc: "l < dim_col A" by auto
      moreover obtain r'' A''
        where rA'': "sub3 (dim_row A) l (r,A) = (r'',A'')" by force
      ultimately have IH: "triangular_to l A''" using Suc by auto
      have [simp]:"dim_row A'' = dim_row A" and [simp]:"dim_col A'' = dim_col A"
        using Slr Slc rA'' by auto
      fix r' A'
      assume "sub3 (dim_row A) (Suc l) (r, A) = (r', A')"
      then have rA': "sub2 (dim_row A'') l (r'',A'') = (r',A')"
        using rA'' by auto
      show "triangular_to (Suc l) A'"
        using sub2_grows_triangle[OF sel_fun mf rA'] lr lc rA'' IH by auto
  qed auto
qed

subsection ‹Triangulization›

definition triangulize :: "'a mat ⇒ 'a × 'a mat"
where "triangulize A = sub3 (dim_row A) (dim_row A) (1,A)"

lemma triangulize_preserves_dimensions[simp]:
  "triangulize A = (r',A') ⟹ dim_row A' = dim_row A"
  "triangulize A = (r',A') ⟹ dim_col A' = dim_col A"
  unfolding triangulize_def by auto

lemma triangulize_closed[simp]:
  "triangulize A = (r',A') ⟹ A ∈ carrier_mat m n ⟹ A' ∈ carrier_mat m n"
  unfolding carrier_mat_def by auto

context
  assumes mf: "mute_fun mf"
  and sel_fun: "det_selection_fun sel_fun"
begin

theorem triangulized:
  assumes "A ∈ carrier_mat n n"
  and "triangulize A = (r',A')"
  shows "upper_triangular A'"
proof (cases "0<n")
  case True
    have rA': "sub3 (dim_row A) (dim_row A) (1,A) = (r',A')"
      using assms unfolding triangulize_def by auto
    have nr:"n = dim_row A" and nc:"n = dim_col A" and nr':"n = dim_row A'"
    using assms by auto
    thus ?thesis
      unfolding triangular_to_triangular
      using sub3_makes_triangle[OF mf sel_fun rA'] True by auto
    next
  case False
    then have nr':"dim_row A' = 0" using assms by auto
    thus ?thesis unfolding upper_triangular_def by auto
qed

subsection‹Divisor will not be 0›

text ‹
  Here we show that each sub-algorithm will not make $r$
  of the input/output pair $(r,A)$ to 0.
  The algorithm @{term "sub1 A_ll k l (r,A)"} requires $A_{l,l} \neq 0$.
›

lemma sub1_divisor [simp]:
  assumes rA': "sub1 q k l (r, A) = (r',A')"
  and r0: "r ≠ 0"
  and All: "q ≠ 0"
  and "k + l < dim_row A "
  and lc: "l < dim_col A"
  shows "r' ≠ 0"
using assms
proof -
  show "sub1 q k l (r,A) = (r',A') ⟹ k + l < dim_row A ⟹ r' ≠ 0"
  proof (induction k arbitrary: r' A')
    case (Suc k)
      obtain r'' A'' where rA'': "sub1 q k l (r, A) = (r'', A'')" by force
      then have IH: "r'' ≠ 0" using Suc by auto
      obtain q' l' g where mf_id: "mf q (A'' $$ (Suc (l + k), l)) = (q',l',g)" by (rule prod_cases3)      
      define fact where "fact = (if A'' $$ (Suc (l+k),l) = 0 then 1 else q')"
      note mf = mf[unfolded mute_fun_def, rule_format, OF mf_id]
      have All: "q ≠ 0"
        using sub1_preserves_diagnal[OF rA'' lc] All Suc by auto
      moreover have "fact ≠ 0" unfolding fact_def using All mf by auto
      moreover assume "sub1 q (Suc k) l (r,A) = (r',A')"
        then have "mute q (Suc (l + k)) l (r'',A'') = (r',A')"
          using rA'' by auto
        hence "r'' * fact = r'"
          unfolding mute.simps fact_def Let_def mf_id using IH by (auto split: if_splits)
      ultimately show "r' ≠ 0" using IH by auto
  qed (insert r0, simp)
qed

text ‹The algorithm @{term "sub2"} will not require such a condition.›
lemma sub2_divisor [simp]:
  assumes rA': "sub2 k l (r, A) = (r',A')"
  and lk: "l < k"
  and kr: "k ≤ dim_row A"
  and lc: "l < dim_col A"
  and r0: "r ≠ 0"
  shows "r' ≠ 0"
using assms
proof (cases "find_non0 l A") {
  case (Some m)
    then have Aml0: "A $$ (m,l) ≠ 0" using find_non0[OF sel_fun] by auto
    have md: "m < dim_row A" using find_non0[OF sel_fun Some] lk kr by auto
    let ?A'' = "swaprows m l A"
    have rA'2: "sub1 (?A'' $$ (l,l)) (k - Suc l) l (-r, ?A'') = (r',A')"
      using rA' Some by (simp add: Let_def)
    have All0: "?A'' $$ (l,l) ≠ 0" using Aml0 md lk kr lc by auto
    show ?thesis using sub1_divisor[OF rA'2 _ All0] r0 lk kr lc by simp
} qed auto

lemma sub3_divisor [simp]:
  assumes "sub3 d l (r,A) = (r'',A'')"
  and "l ≤ d"
  and "d ≤ dim_row A"
  and "l ≤ dim_col A"
  and r0: "r ≠ 0"
  shows "r'' ≠ 0"
  using assms
proof -
  show
    "sub3 d l (r,A) = (r'',A'') ⟹
     l ≤ d ⟹ d ≤ dim_row A ⟹ l ≤ dim_col A ⟹ ?thesis"
  proof (induction l arbitrary: r'' A'')
    case 0
      then show ?case using r0 by simp
      next
    case (Suc l)
      obtain r' A' where rA': "sub3 d l (r,A) = (r',A')" by force
      then have [simp]:"dim_row A' = dim_row A" and [simp]:"dim_col A' = dim_col A"
        by auto
      from rA' have "r' ≠ 0" using Suc r0 by auto
      moreover have "sub2 d l (r',A') = (r'',A'')"
        using rA' Suc by simp
      ultimately show ?case using sub2_divisor using Suc by simp
  qed
qed

theorem triangulize_divisor:
  assumes A: "A ∈ carrier_mat d d"
  shows "triangulize A = (r',A') ⟹ r' ≠ 0"
unfolding triangulize_def
proof -
  assume rA': "sub3 (dim_row A) (dim_row A) (1, A) = (r', A')"
  show ?thesis using sub3_divisor[OF rA'] A by auto 
qed

subsection ‹Determinant Preservation Results›

text ‹
  For each sub-algorithm $f$,
  we show $f(r,A) = (r',A')$ implies @{term "r * det A' = r' * det A"}.
›

lemma mute_det:
  assumes "A ∈ carrier_mat n n"
  and rA': "mute q k l (r,A) = (r',A')"
  and "k < n"
  and "l < n"
  and "k ≠ l"
  shows "r * det A' = r' * det A"
proof (cases "A $$ (k,l) = 0")
  case True
  thus ?thesis using assms by auto
next
  case False
  obtain p' q' g where mf_id: "mf q (A $$ (k,l)) = (q',p',g)" by (rule prod_cases3)
  let ?All = "q'"
  let ?Akl = "- p'"
  let ?B = "multrow k ?All A"
  let ?C = "addrow ?Akl k l ?B"
  have "r * det A' = r * det ?C"  using assms by (simp add: Let_def mf_id False)
  also have "det ?C = det ?B" using assms by (auto simp: det_addrow)
  also have "… = ?All * det A" using assms det_multrow by auto
  also have "r * … = (r * ?All) * det A" by simp
  also have r: "r * ?All = r'" using assms by (simp add: Let_def mf_id False)
  finally show ?thesis.
qed

lemma sub1_det:
  assumes A: "A ∈ carrier_mat n n"
  and sub1: "sub1 q k l (r,A) = (r'',A'')"
  and r0: "r ≠ 0"
  and All0: "q ≠ 0"
  and l: "l + k < n"
  shows "r * det A'' = r'' * det A"
  using sub1 l
proof (induction k arbitrary: A'' r'')
  case 0
  then show ?case by auto
next
  case (Suc k)
  let ?rA' = "sub1 q k l (r,A)"
  obtain r' A' where rA':"?rA' = (r',A')" by force
  have A':"A' ∈ carrier_mat n n" using sub1_closed[OF rA'] A by auto
  have IH: "r * det A' = r' * det A" using Suc assms rA' by auto
  assume "sub1 q (Suc k) l (r,A) = (r'',A'')"
  then have rA'':"mute q (Suc (l+k)) l (r',A') = (r'',A'')" using rA' by auto
  hence lem: "r' * det A'' = r'' * det A'"
    using assms Suc A' mute_det[OF A' rA''] by auto
  hence "r * r' * det A'' = r * r'' * det A'" by auto
  also from IH have "... = r'' * r' * det A" by auto
  finally have *: "r * r' * det A'' = r'' * r' * det A" .
  then have "r * r' * det A'' div r' = r'' * r' * det A div r'" by presburger
  moreover have "r' ≠ 0"
    using r0 sub1_divisor[OF rA'] All0 Suc A by auto
  ultimately show ?case using * by auto
qed

lemma sub2_det:
  assumes A: "A ∈ carrier_mat d d"
  and rA': "sub2 d l (r,A) = (r',A')"
  and r0: "r ≠ 0"
  and ld: "l < d"
  shows "r * det A' = r' * det A"
proof (cases "find_non0 l A")
  case None then show ?thesis using assms by auto next
  case (Some m) {
    then have lm: "l < m" and md: "m < d"
      using A find_non0[OF sel_fun Some] ld by auto
    hence "m ≠ l" by auto
    let ?A'' = "swaprows m l A"
    have rA'2: "sub1 (?A'' $$ (l,l)) (d - Suc l) l (-r, ?A'') = (r',A')"
      using rA' Some by (simp add: Let_def)
    have A'': "?A'' ∈ carrier_mat d d" using A by auto
    hence A''ll0: "?A'' $$ (l,l) ≠ 0"
      using find_non0[OF sel_fun Some] ld by auto
    hence "-r * det A' = r' * det ?A''"
      using sub1_det[OF A'' rA'2] ld A r0 by auto
    also have "r * ... = -r * r' * det A"
      using det_swaprows[OF md ld ‹m≠l› A] by auto
    finally have "r * -r * det A' = -r * r' * det A" by auto
    thus ?thesis using r0 by auto
  }
qed

lemma sub3_det:
  assumes A:"A ∈ carrier_mat d d"
  and "sub3 d l (r,A) = (r'',A'')"
  and r0: "r ≠ 0"
  and "l ≤ d"
  shows "r * det A'' = r'' * det A"
  using assms
proof -
  have d: "d = dim_row A" using A by auto
  show "sub3 d l (r,A) = (r'',A'') ⟹ l ≤ d ⟹ r * det A'' = r'' * det A"
  proof (induction l arbitrary: r'' A'')
    case (Suc l)
      let ?rA' = "sub3 d l (r,A)"
      obtain r' A' where rA':"?rA' = (r',A')" by force
      then have rA'': "sub2 d l (r',A') = (r'',A'')"
        using Suc by auto
      have A': "A' ∈ carrier_mat d d" using A rA' rA'' by auto
      have r'0: "r' ≠ 0" using r0 sub3_divisor[OF rA'] A Suc by auto
      have "r' * det A'' = r'' * det A'"
        using Suc r'0 A by(subst sub2_det[OF A' rA''],auto)
      also have "r * ... = r'' * (r * det A')" by auto
      also have "r * det A' = r' * det A" using Suc rA' by auto
      also have "r'' * ... div r' = r'' * r' * det A div r'" by (simp add: ac_simps)
      finally show "r * det A'' = r'' * det A" using r'0 
        by (metis ‹r * det A' = r' * det A› ‹r' * det A'' = r'' * det A'› 
          mult.left_commute mult_cancel_left)
  qed simp
qed

theorem triangulize_det:
  assumes A: "A ∈ carrier_mat d d"
  and rA': "triangulize A = (r',A')"
  shows "det A * r' = det A'"
proof -
  have rA'2: "sub3 d d (1,A) = (r',A')"
    using A rA' unfolding triangulize_def by auto
  show ?thesis
  proof (cases "d = 0")
    case True
      then have A': "A' ∈ carrier_mat 0 0" using A rA'2 by auto
      have rA'3: "(r',A') = (1,A)" using True rA'2 by simp
      thus ?thesis by auto
      next
    case False
      then show ?thesis using sub3_det[OF A rA'2] assms by auto
  qed
qed
end

subsection ‹Determinant Computation›

definition det_code :: "'a mat ⇒ 'a" where
  "det_code A = (if dim_row A = dim_col A then
     case triangulize A of (m,A') ⇒
       prod_list (diag_mat A') div m
   else 0)"

lemma det_code[simp]: assumes sel_fun: "det_selection_fun sel_fun"
  and mf: "mute_fun mf"
  shows "det_code A = det A"
  using det_code_def[simp]
proof (cases "dim_row A = dim_col A")
  case True
  then have A: "A ∈ carrier_mat (dim_row A) (dim_row A)" unfolding carrier_mat_def by auto
  obtain r' A' where rA': "triangulize A = (r',A')" by force
  from triangulize_divisor[OF mf sel_fun A] rA' have r'0: "r' ≠ 0" by auto
  from triangulize_det[OF mf sel_fun A rA'] have det': "det A * r' = det A'" by auto
  from triangulized[OF mf sel_fun A, unfolded rA'] have tri': "upper_triangular A'" by simp
  have A': "A' ∈ carrier_mat (dim_row A') (dim_row A')"
    using triangulize_closed[OF rA' A] by auto
  from tri' have tr: "triangular_to (dim_row A') A'" by auto
  have "det_code A = prod_list (diag_mat A') div r'" using rA' True by simp
  also have "prod_list (diag_mat A') = det A'"
    unfolding det_upper_triangular[OF tri' A'] ..
  also have "… = det A * r'" by (simp add: det')
  also have "… div r' = det A" using r'0 by auto
  finally show ?thesis .
qed (simp add: det_def)

end
end

text ‹Now we can select an arbitrary selection and mute function. This will be important for computing
  resultants over polynomials, where usually a polynomial with small degree is preferable.

  The default however is to use the first element.›

definition trivial_mute_fun :: "'a :: comm_ring_1 ⇒ 'a ⇒ 'a × 'a × 'a" where
  "trivial_mute_fun x y = (x,y,1)"

lemma trivial_mute_fun[simp,intro]: "mute_fun trivial_mute_fun"
  unfolding mute_fun_def trivial_mute_fun_def by auto

definition fst_sel_fun :: "'a det_selection_fun" where
  "fst_sel_fun x = fst (hd x)" 

lemma fst_sel_fun[simp]: "det_selection_fun fst_sel_fun"
  unfolding det_selection_fun_def fst_sel_fun_def by auto

context
  fixes measure :: "'a ⇒ nat" 
begin
private fun select_min_main where 
  "select_min_main m i ((j,p) # xs) = (let n = measure p in if n < m then select_min_main n j xs
    else select_min_main m i xs)"
| "select_min_main m i [] = i"

definition select_min :: "(nat × 'a) list ⇒ nat" where
  "select_min xs = (case xs of ((i,p) # ys) ⇒ (select_min_main (measure p) i ys))"

lemma select_min[simp]: "det_selection_fun select_min"
  unfolding det_selection_fun_def 
proof (intro allI impI)
  fix xs :: "(nat × 'a)list"
  assume "xs ≠ []"
  then obtain i p ys where xs: "xs = ((i,p) # ys)" by (cases xs, auto)
  then obtain m where id: "select_min xs = select_min_main m i ys" unfolding select_min_def by auto
  have "i ∈ fst ` set xs" "set ys ⊆ set xs" unfolding xs by auto
  thus "select_min xs ∈ fst ` set xs" unfolding id
  proof (induct ys arbitrary: m i )
    case (Cons jp ys m i)
    obtain j p where jp: "jp = (j,p)" by force
    obtain k n where res: "select_min_main m i (jp # ys) = select_min_main n k ys" 
      and k: "k ∈ fst ` set xs"
      using Cons(2-) unfolding jp by (cases "measure p < m"; force simp: Let_def)
    from Cons(1)[OF k, of n] Cons(3) 
    show ?case unfolding res by auto
  qed simp
qed
end

text ‹For the code equation we use the trivial mute and selection function as this does
  not impose any further class restrictions.›

lemma det_code_fst_sel_fun[code]: "det A = det_code fst_sel_fun trivial_mute_fun A" by simp

text ‹But we also provide specialiced functions for more specific carriers.›

definition field_mute_fun :: "'a :: field ⇒ 'a ⇒ 'a × 'a × 'a" where
  "field_mute_fun x y = (x/y,1,y)"

lemma field_mute_fun[simp,intro]: "mute_fun field_mute_fun"
  unfolding mute_fun_def field_mute_fun_def by auto

definition det_field :: "'a :: field mat ⇒ 'a" where 
  "det_field A = det_code fst_sel_fun field_mute_fun A"

lemma det_field[simp]: "det_field = det"
  by (intro ext, auto simp: det_field_def)

definition gcd_mute_fun :: "'a :: ring_gcd ⇒ 'a ⇒ 'a × 'a × 'a" where
  "gcd_mute_fun x y = (let g = gcd x y in (x div g, y div g,g))"

lemma gcd_mute_fun[simp,intro]: "mute_fun gcd_mute_fun"
  unfolding mute_fun_def gcd_mute_fun_def by (auto simp: Let_def div_mult_swap mult.commute)

definition det_int :: "int mat ⇒ int" where 
  "det_int A = det_code (select_min (λ x. nat (abs x))) gcd_mute_fun A"

lemma det_int[simp]: "det_int = det"
  by (intro ext, auto simp: det_int_def)

definition det_field_poly :: "'a :: {field,field_gcd} poly mat ⇒ 'a poly" where
  "det_field_poly A = det_code (select_min degree) gcd_mute_fun A"

lemma det_field_poly[simp]: "det_field_poly = det"
  by (intro ext, auto simp: det_field_poly_def)

end