best way(s) to fit a polynomial to points?

[Natsu Mizutani]

Hi,

How about using `scipy.optimize` at http://www.scipy.org .

 From scipy_tutorial.pdf, it says
 >A collection of general-purpose optimization routines.
 > fmin -- Nelder-Mead Simplex algorithm
 > (uses only function calls)
 > fmin_powell -- Powell’s (modified) level set method (uses onlyfunction
 > calls)
 > fmin_bfgs -- Quasi-Newton method (can use function and gradient)
 > fmin_ncg -- Line-search Newton Conjugate Gradient (can usefunction,
 > gradient and hessian).
 > leastsq -- Minimize the sum of squares of M equations in N unknowns
 > given a starting estimate.

Note that if you want Win binary, you'll find them under
http://www.scipy.org/site_content/downloads
where you cannot reach by clicking links, I suppose.

-----
Natsu