# [Numpy-discussion] [ANN]: Taylorpoly, an implementation of vectorized Taylor polynomial operations and request for opinions

Friedrich Romstedt friedrichromstedt@gmail....
Sat Feb 27 17:36:09 CST 2010

```2010/2/27 Sebastian Walter <sebastian.walter@gmail.com>:
> On Sat, Feb 27, 2010 at 11:11 PM, Friedrich Romstedt
> <friedrichromstedt@gmail.com> wrote:
>> Ok, it took me about one hour, but here they are: Fourier-accelerated
>> polynomials.
>
> that's the spirit! ;)

Yes! I like it! :-)

>>> python
>> Python 2.4.1 (#65, Mar 30 2005, 09:13:57) [MSC v.1310 32 bit (Intel)] on win32
>>>>> import gdft_polynomial
>>>>> p1 = gdft_polynomial.Polynomial([1])
>>>>> p2 = gdft_polynomial.Polynomial([2])
>>>>> p1 * p2
>> <gdft_polynomial.polynomial.Polynomial instance at 0x00E78A08>
>>>>> print p1 * p2
>> [ 2.+0.j]
>>>>> p1 = gdft_polynomial.Polynomial([1, 1])
>>>>> p2 = gdft_polynomial.Polynomial([1])
>>>>> print p1 * p2
>> [ 1. +6.12303177e-17j  1. -6.12303177e-17j]
>>>>> p2 = gdft_polynomial.Polynomial([1, 2])
>>>>> print p1 * p2
>> [ 1. +8.51170986e-16j  3. +3.70074342e-17j  2. -4.44089210e-16j]
>>>>> p1 = gdft_polynomial.Polynomial([1, 2, 3, 4, 3, 2, 1])
>>>>> p2 = gdft_polynomial.Polynomial([4, 3, 2, 1, 2, 3, 4])
>>>>> print (p1 * p2).coefficients.real
>> [  4.  11.  20.  30.  34.  35.  36.  35.  34.  30.  20.  11.   4.]
>>>>>
>>
>> github.com/friedrichromstedt/gdft_polynomials
>>
>> It's open for bug hunting :-)
>>
>> Haven't checked the last result.
> looks correct

We should check, simply using numpy.polynomial

>> I used my own gdft module.  Maybe one could incorporate numpy.fft
>> easily.  But that's your job, Sebastian, isn't it?  Feel free to push
>> to the repo, and don't forget to add your name to the copyright
>> notice, hope you are happy with MIT.
> i'll have a look at it.

I will be obliged.

>> Anyway, I don't know whether numpy.fft supports transforming only one
>> coordinate and using the others for "parallelisation"?

I will check tomorrow.