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Diff for /OpenXM/src/asir-doc/parts/groebner.texi between version 1.12 and 1.13

version 1.12, 2003/12/27 11:52:07 version 1.13, 2004/09/13 09:23:30
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 @comment $OpenXM: OpenXM/src/asir-doc/parts/groebner.texi,v 1.11 2003/04/28 06:43:10 noro Exp $  @comment $OpenXM: OpenXM/src/asir-doc/parts/groebner.texi,v 1.12 2003/12/27 11:52:07 takayama Exp $
 \BJP  \BJP
 @node $B%0%l%V%J4pDl$N7W;;(B,,, Top  @node $B%0%l%V%J4pDl$N7W;;(B,,, Top
 @chapter $B%0%l%V%J4pDl$N7W;;(B  @chapter $B%0%l%V%J4pDl$N7W;;(B
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 * $B4pK\E*$JH!?t(B::  * $B4pK\E*$JH!?t(B::
 * $B7W;;$*$h$SI=<($N@)8f(B::  * $B7W;;$*$h$SI=<($N@)8f(B::
 * $B9`=g=x$N@_Dj(B::  * $B9`=g=x$N@_Dj(B::
   * Weight::
 * $BM-M}<0$r78?t$H$9$k%0%l%V%J4pDl7W;;(B::  * $BM-M}<0$r78?t$H$9$k%0%l%V%J4pDl7W;;(B::
 * $B4pDlJQ49(B::  * $B4pDlJQ49(B::
 * Weyl $BBe?t(B::  * Weyl $BBe?t(B::
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 * Fundamental functions::  * Fundamental functions::
 * Controlling Groebner basis computations::  * Controlling Groebner basis computations::
 * Setting term orderings::  * Setting term orderings::
   * Weight::
 * Groebner basis computation with rational function coefficients::  * Groebner basis computation with rational function coefficients::
 * Change of ordering::  * Change of ordering::
 * Weyl algebra::  * Weyl algebra::
Line 1052  expressed by variable @code{x}, and the above explanat
Line 1054  expressed by variable @code{x}, and the above explanat
 such a drastic experimental results.  such a drastic experimental results.
 In practice, however, optimum ordering for variables may not known  In practice, however, optimum ordering for variables may not known
 beforehand, and some heuristic trial may be inevitable.  beforehand, and some heuristic trial may be inevitable.
   \E
   
   \BJP
   @node Weight ,,, $B%0%l%V%J4pDl$N7W;;(B
   @section Weight
   \E
   \BEG
   @node Weight,,, Groebner basis computation
   @section Weight
   \E
   \BJP
   $BA0@a$G>R2p$7$?9`=g=x$O(B, $B3FJQ?t$K(B weight ($B=E$_(B) $B$r@_Dj$9$k$3$H$G(B
   $B$h$j0lHLE*$J$b$N$H$J$k(B.
   \E
   \BEG
   Term orders introduced in the previous section can be generalized
   by setting a weight for each variable.
   \E
   @example
   [0] dp_td(<<1,1,1>>);
   3
   [1] dp_set_weight([1,2,3])$
   [2] dp_td(<<1,1,1>>);
   6
   @end example
   \BJP
   $BC19`<0$NA4<!?t$r7W;;$9$k:](B, $B%G%U%)%k%H$G$O(B
   $B3FJQ?t$N;X?t$NOB$rA4<!?t$H$9$k(B. $B$3$l$O3FJQ?t$N(B weight $B$r(B 1 $B$H(B
   $B9M$($F$$$k$3$H$KAjEv$9$k(B. $B$3$NNc$G$O(B, $BBh0l(B, $BBhFs(B, $BBh;0JQ?t$N(B
   weight $B$r$=$l$>$l(B 1,2,3 $B$H;XDj$7$F$$$k(B. $B$3$N$?$a(B, @code{<<1,1,1>>}
   $B$NA4<!?t(B ($B0J2<$G$O$3$l$rC19`<0$N(B weight $B$H8F$V(B) $B$,(B @code{1*1+1*2+1*3=6} $B$H$J$k(B.
   weight $B$r@_Dj$9$k$3$H$G(B, $BF1$89`=g=x7?$N$b$H$G0[$J$k9`=g=x$,Dj5A$G$-$k(B.
   $BNc$($P(B, weight $B$r$&$^$/@_Dj$9$k$3$H$G(B, $BB?9`<0$r(B weighted homogeneous
   $B$K$9$k$3$H$,$G$-$k>l9g$,$"$k(B.
   \E
   \BEG
   By default, the total degree of a monomial is equal to
   the sum of all exponents. This means that the weight for each variable
   is set to 1.
   In this example, the weights for the first, the second and the third
   variable are set to 1, 2 and 3 respectively.
   Therefore the total degree of @code{<<1,1,1>>} under this weight,
   which is called the weight of the monomial, is @code{1*1+1*2+1*3=6}.
   By setting weights, different term orders can be set under a term
   order type. For example, a polynomial can be made weighted homogeneous
   by setting an appropriate weight.
   \E
   
   \BJP
   $B3FJQ?t$KBP$9$k(B weight $B$r$^$H$a$?$b$N$r(B weight vector $B$H8F$V(B.
   $B$9$Y$F$N@.J,$,@5$G$"$j(B, $B%0%l%V%J4pDl7W;;$K$*$$$F(B, $BA4<!?t$N(B
   $BBe$o$j$KMQ$$$i$l$k$b$N$rFC$K(B sugar weight $B$H8F$V$3$H$K$9$k(B.
   sugar strategy $B$K$*$$$F(B, $BA4<!?t$NBe$o$j$K;H$o$l$k$+$i$G$"$k(B.
   $B0lJ}$G(B, $B3F@.J,$,I,$:$7$b@5$H$O8B$i$J$$(B weight vector $B$O(B,
   sugar weight $B$H$7$F@_Dj$9$k$3$H$O$G$-$J$$$,(B, $B9`=g=x$N0lHL2=$K$O(B
   $BM-MQ$G$"$k(B. $B$3$l$i$O(B, $B9TNs$K$h$k9`=g=x$N@_Dj$K$9$G$K8=$l$F(B
   $B$$$k(B. $B$9$J$o$A(B, $B9`=g=x$rDj5A$9$k9TNs$N3F9T$,(B, $B0l$D$N(B weight vector
   $B$H8+$J$5$l$k(B. $B$^$?(B, $B%V%m%C%/=g=x$O(B, $B3F%V%m%C%/$N(B
   $BJQ?t$KBP1~$9$k@.J,$N$_(B 1 $B$GB>$O(B 0 $B$N(B weight vector $B$K$h$kHf3S$r(B
   $B:G=i$K9T$C$F$+$i(B, $B3F%V%m%C%/Kh$N(B tie breaking $B$r9T$&$3$H$KAjEv$9$k(B.
   \E
   
   \BEG
   A list of weights for all variables is called a weight vector.
   A weight vector is called a sugar weight vector if
   its elements are all positive and it is used for computing
   a weighted total degree of a monomial, because such a weight
   is used instead of total degree in sugar strategy.
   On the other hand, a weight vector whose elements are not necessarily
   positive cannot be set as a sugar weight, but it is useful for
   generalizing term order. In fact, such a weight vector already
   appeared in a matrix order. That is, each row of a matrix defining
   a term order is regarded as a weight vector. A block order
   is also considered as a refinement of comparison by weight vectors.
   It compares two terms by using a weight vector whose elements
   corresponding to variables in a block is 1 and 0 otherwise,
   then it applies a tie breaker.
   
 \E  \E
   
 \BJP  \BJP
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