On Sat, Feb 13, 2010 at 10:04 AM, Fernando Perez <fperez.net@gmail.com>wrote:
On Sat, Feb 13, 2010 at 10:34 AM, Charles R Harris <charlesr.harris@gmail.com> wrote:
The new polynomials don't have that problem.
In [1]: from numpy.polynomial import Polynomial as Poly
In [2]: p = Poly([1,2])
Aha, great! Many thanks, I can tell my students this, and just show them the caveat of calling float(x) on any scalar they want to use with the 'old' ones for now.
I remember being excited about your work on the new Polys, but since I'm teaching with stock 1.3, I hadn't found them recently and just forgot about them. Excellent.
One minor suggestion: I think it would be useful to have the new polys have some form of pretty-printing like the old ones. It is actually useful when working, to verify what one has at hand, to see an expanded printout like the old ones do:
I thought about that, but decided it was best left to a derived class, say PrettyPoly ;) Overriding __repr__ and __str__ is an example where inheritance makes sense.
In [26]: p_old = numpy.poly1d([3, 2, 1])
In [27]: p_old Out[27]: poly1d([3, 2, 1])
In [28]: print(p_old) 2 3 x + 2 x + 1
Just yesterday I was validating some code against a symbolic construction with sympy, and it was handy to pretty-print them; I also think it makes them much easier to grasp for students new to the tools.
In any case, thanks both for the tip and especially the code contribution!
Cheers,
Chuck