In this manual we explain about a new b-function package `nn_ndbf.rr' in asir-contrib. To use this package one has to load `nn_ndbf.rr'.
[1518] load("nn_ndbf.rr");
A prefix ndbf. is necessary to call the functions in this package.
In this manual we also explain about some related built-in functions.
ndbf.bfunction[v1,w1,...,vn,wn]
weight=[v1,w1,...,vn,wn] is given,
the computation is done with a weight (w1,...,wn) for (v1,...,vn).
This option is useful when f is weighted homogeneous with respect to (w1,...,wn).
heuristic=1 is given
a change of ordering is done before entering elimination.
In some cases this improves the total efficiencty.
vord=v is given, a variable order v is used istead.
[1519] load("nn_ndbf.rr");
[1602] ndbf.bfunction(x^3-y^2*z^2);
-11664*s^7-93312*s^6-316872*s^5-592272*s^4-658233*s^3-435060*s^2
-158375*s-24500
[1603] F=256*u1^3-128*u3^2*u1^2+(144*u3*u2^2+16*u3^4)*u1-27*u2^4
-4*u3^3*u2^2$
[1604] ndbf.bfunction(F|weight=[u3,2,u2,3,u1,4]);
576*s^6+3456*s^5+8588*s^4+11312*s^3+8329*s^2+3250*s+525
ndbf.bf_local[v1,a1,...,vn,an]
[v1,w1,...,vn,wn]
op=1 is given,
a pair [b,P] of the local b-function and a differential operator satisfying
Pf^(s+1)=b(s)f^s. The operator P is represented as a commutative polynomial
of variables v1,...,vn,dv1,...,dvn. Although the d-variables
are treated as commutative indeterminates in this representation,
it should be regarded as a canonical representation with each polynomial coefficient
placed at the left of d-variables.
weight=[v1,w1,...,vn,wn] is given,
the computation is done with a weight (w1,...,wn) for (v1,...,vn).
This option is useful when f is weighted homogeneous with respect to
(w1,...,wn).
heuristic=1 is given
a change of ordering is done before entering elimination.
In some cases this improves the total efficiencty.
vord=v is given, a variable order v is used istead.
[1527] load("nn_ndbf.rr");
[1610] ndbf.bf_local(y*((x+1)*x^3-y^2),[x,-1,y,0]);
[[-s-1,2]]
[1611] ndbf.bf_local(y*((x+1)*x^3-y^2),[x,-1,y,0]|op=1);
[[[-s-1,2]],12*x^3+36*y^2*x-36*y^2,(32*y*x^2+56*y*x)*dx^2
+((-8*x^3-2*x^2+(128*y^2-6)*x+112*y^2)*dy+288*y*x+(-240*s-128)*y)*dx
+(32*y*x^2-6*y*x+128*y^3-9*y)*dy^2+(32*x^2+6*s*x+640*y^2+39*s+30)*dy
+(-1152*s^2-3840*s-2688)*y]
ndbf.bf_strat[v1,w1,...,vn,wn]
weight=[v1,w1,...,vn,wn] is given,
the computation is done with a weight (w1,...,wn) for (v1,...,vn).
This option is useful when f is weighted homogeneous with respect to
(w1,...,wn).
heuristic=1 is given
a change of ordering is done before entering elimination.
In some cases this improves the total efficiencty.
vord=v is given, a variable order v is used istead.
[1537] load("nn_ndbf.rr");
[1620] F=256*u1^3-128*u3^2*u1^2+(144*u3*u2^2+16*u3^4)*u1-27*u2^4
-4*u3^3*u2^2$
[1621] ndbf.bf_strat(F);
[[u3^2,-u1,-u2],[-1],[[-s-1,2],[16*s^2+32*s+15,1],[36*s^2+72*s+35,1]]]
[[-4*u1+u3^2,-u2],[96*u1^2+40*u3^2*u1-9*u3*u2^2,...],[[-s-1,2]]]
[[...],[-u3*u2,u2*u1,...],[[-s-1,1],...]]]
[[-256*u1^3+128*u3^2*u1^2+...],[...],[[-s-1,1]]]
[[],[-256*u1^3+128*u3^2*u1^2+...],[]]
ndbf.ann[v0,w1,...,vn,wn]
ndbf.bf_local.
weight=[v1,w1,...,vn,wn] is given,
the computation is done with a weight (w1,...,wn) for (v1,...,vn).
This option is useful when f is weighted homogeneous with respect to (w1,...,wn).
[1542] load("nn_ndbf.rr");
[1625] ndbf.ann(x*y*z*(x^3-y^2*z^2));
[(-x^4*dy^2+3*z^4*x*dz^2+12*z^3*x*dz+6*z^2*x)*dx+4*z*x^3*dz*dy^2
-z^5*dz^3-6*z^4*dz^2-6*z^3*dz,
(x^4*dy-3*z^3*y*x*dz-6*z^2*y*x)*dx-4*z*x^3*dz*dy+z^4*y*dz^2+3*z^3*y*dz,
(-x^4+3*z^2*y^2*x)*dx+(4*z*x^3-z^3*y^2)*dz,2*x*dx+3*z*dz-11*s,
-y*dy+z*dz]
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@vfill @eject
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