> Is there any way around it ? I could scale down points by 10, > and again scale back the results. But I want to get a generic > solution as I use this program in a library and I would have > no way of telling automatically when to scale and when not to scale. Yes, of course, I see the problem. A "generic" way would be to compare the first and last nonzero coefficient, and scale by a factor which makes them approximately equal (i.e., scale by the n-the root of that factor), then scale back the result. I was thinking of adding a method "solve_robust()" to the vnl_rnpoly_solve class which does something like this, but I'm not feeling comfortable enough to do this right away for the general m-dimensional case. But for your particular (generic) use, it should not be too difficult: something like: double factor = coeffs[4]/coeffs[0]; // take 4th root: factor = sqrt(factor); factor = sqrt(factor); double mfactor = 1.0; for (int i=0; i<=4; ++i) coeffs[i]/=mfactor, mfactor*=factor; ... vnl_rnpoly_solve solver(l); vcl_vector<vnl_vector<double>*> re = solver.real(); vcl_vector<vnl_vector<double>*> im = solver.imag(); ... (*(*rp)) *= factor; // globally scale the vnl_vector back I've put a working implementation of exactly this in the last SVN version of core/vnl/algo/tests/test_rnpoly_roots.cxx -- Peter. |