Hi,

I have the following homogeneous Singular ideal defining a finite set
of points in projective space.  I would like to get numerical
approximations for these points.

sage: S.ring()

//   characteristic : 0
//   number of vars : 4
//        block   1 : ordering dp
//                  : names    x_3 x_2 x_1 x_0
//        block   2 : ordering C
sage: S.ideal()

x_1^3-x_3*x_2*x_0,
x_3*x_2*x_1-x_0^3,
x_2^3-x_3*x_1*x_0,
x_3^3-x_2*x_1*x_0,
x_2^2*x_1^2-x_3^2*x_0^2,
x_3^2*x_1^2-x_2^2*x_0^2,
x_3^2*x_2^2-x_1^2*x_0^2
sage: type(S.ideal())
<class 'sage.interfaces.singular.SingularElement'>

One way to go might be to map to a new ring, setting x_0 = 1, then use
the nice Singular algorithm for finding the solutions:

http://www.singular.uni-kl.de/Manual/3-0-4/sing_582.htm

I couldn't figure out how to get the Singular "map" function to work
with Sage, so I just converted equations using string commands (saved
in "y" in the following code) then tried:

sage: R = singular.ring(0,'(x_3,x_2,x_1)','lp')
sage: J = singular.ideal(y)
sage: J

-x_3*x_2+x_1^3,
x_3*x_2*x_1-1,
-x_3*x_1+x_2^3,
x_3^3-x_2*x_1,
-x_3^2+x_2^2*x_1^2,
x_3^2*x_1^2-x_2^2,
x_3^2*x_2^2-x_1^2
sage: K = J.groebner()
sage: M = K.solve(10,1)

I'm not sure where to go from there.  Of course, I might be taking the
wrong approach altogether.

Any advice would be appreciated.

Thanks,
Dave

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