===================================================================
RCS file: /home/cvs/OpenXM/src/asir-doc/parts/builtin/array.texi,v
retrieving revision 1.4
retrieving revision 1.5
diff -u -p -r1.4 -r1.5
--- OpenXM/src/asir-doc/parts/builtin/array.texi	2000/11/13 00:16:36	1.4
+++ OpenXM/src/asir-doc/parts/builtin/array.texi	2002/08/08 05:24:37	1.5
@@ -1,4 +1,4 @@
-@comment $OpenXM: OpenXM/src/asir-doc/parts/builtin/array.texi,v 1.3 2000/02/05 12:01:09 takayama Exp $
+@comment $OpenXM: OpenXM/src/asir-doc/parts/builtin/array.texi,v 1.4 2000/11/13 00:16:36 noro Exp $
 \BJP
 @node 配列,,, 組み込み函数
 @section 配列
@@ -14,7 +14,7 @@
 * vtol::
 * newmat::
 * size::
-* det::
+* det invmat::
 * qsort::
 @end menu
 
@@ -337,7 +337,7 @@ return to toplevel
 @table @t
 \JP @item 参照
 \EG @item References
-@fref{newvect}, @fref{size}, @fref{det}.
+@fref{newvect}, @fref{size}, @fref{det invmat}.
 @end table
 
 \JP @node size,,, 配列
@@ -405,21 +405,25 @@ in a rational expression.
 @fref{car cdr cons append reverse length}, @fref{nmono}.
 @end table
 
-\JP @node det,,, 配列
-\EG @node det,,, Arrays
-@subsection @code{det}
+\JP @node det invmat,,, 配列
+\EG @node det invmat,,, Arrays
+@subsection @code{det},@code{invmat}
 @findex det
+@findex invmat
 
 @table @t
 @item det(@var{mat}[,@var{mod}])
 \JP :: @var{mat} の行列式を求める. 
 \EG :: Determinant of @var{mat}.
+@item invmat(@var{mat})
+\JP :: @var{mat} の行列式を求める. 
+\EG :: Inverse matrix of @var{mat}.
 @end table
 
 @table @var
 @item return
-\JP 式
-\EG expression
+\JP @code{det}: 式, @code{invmat}: リスト
+\EG @code{det}: expression, @code{invmat}: list
 @item mat
 \JP 行列
 \EG matrix
@@ -431,7 +435,9 @@ in a rational expression.
 @itemize @bullet
 \BJP
 @item
-行列 @var{mat} の行列式を求める. 
+@code{det} は行列 @var{mat} の行列式を求める. 
+@code{invmat} は行列 @var{mat} の逆行列を求める. 逆行列は @code{[分母, 分子]}
+の形で返され, @code{分母}が行列, @code{分母/分子} が逆行列となる. 
 @item
 引数 @var{mod} がある時, GF(@var{mod}) 上での行列式を求める. 
 @item
@@ -440,7 +446,10 @@ in a rational expression.
 \E
 \BEG
 @item 
-Determinant of matrix @var{mat}.
+@code{det} computes the determinant of matrix @var{mat}.
+@code{invmat} computes the inverse matrix of matrix @var{mat}.
+@code{invmat} returns a list @code{[num,den]}, where @code{num}
+is a matrix and @code{num/den} represents the inverse matrix.
 @item 
 The computation is done over GF(@var{mod}) if @var{mod} is specitied.
 @item 
@@ -464,6 +473,24 @@ is more efficient than the fraction free Gaussian algo
 [95] fctr(det(A));
 [[1,1],[u-v,1],[-z+v,1],[-z+u,1],[-y+u,1],[y-v,1],[-y+z,1],[-x+u,1],[-x+z,1],
 [-x+v,1],[-x+y,1]]
+[96] A = newmat(3,3)$
+[97] for(I=0;I<3;I++)for(J=0,B=A[I],W=V[I];J<3;J++)B[J]=W^J;
+[98] A;
+[ 1 x x^2 ]
+[ 1 y y^2 ]
+[ 1 z z^2 ]
+[99] invmat(A);
+[[ -z*y^2+z^2*y z*x^2-z^2*x -y*x^2+y^2*x ]
+[ y^2-z^2 -x^2+z^2 x^2-y^2 ]
+[ -y+z x-z -x+y ],(-y+z)*x^2+(y^2-z^2)*x-z*y^2+z^2*y]
+[100] A*B[0];
+[ (-y+z)*x^2+(y^2-z^2)*x-z*y^2+z^2*y 0 0 ]
+[ 0 (-y+z)*x^2+(y^2-z^2)*x-z*y^2+z^2*y 0 ]
+[ 0 0 (-y+z)*x^2+(y^2-z^2)*x-z*y^2+z^2*y ]
+[101] map(red,A*B[0]/B[1]);
+[ 1 0 0 ]
+[ 0 1 0 ]
+[ 0 0 1 ]
 @end example
 
 @table @t