[Numpy-discussion] Unpleasant behavior with poly1d and numpy scalar multiplication
Fernando Perez
fperez.net@gmail....
Sat Feb 13 11:04:04 CST 2010
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:
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,
f
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