On Sun, Feb 28, 2010 at 9:06 PM, Friedrich Romstedt
wrote:
> 2010/2/28 Sebastian Walter :
>>> I think I can use that to make my upy accept arbitrary functions, but
>>> how do you apply sin() to a TTP?
>>
>> perform truncated Taylor expansion of [y]_D = sin([x]_D), i.e.
>> y_d = d^d/dt^d sin( \su
2010/2/28 Sebastian Walter :
>> I think I can use that to make my upy accept arbitrary functions, but
>> how do you apply sin() to a TTP?
>
> perform truncated Taylor expansion of [y]_D = sin([x]_D), i.e.
> y_d = d^d/dt^d sin( \sum_{k=0}^{D-1} x_k t^k) |_{t=0}
> to obtain an explicit algorithm.
>
On Sun, Feb 28, 2010 at 12:47 AM, Friedrich Romstedt
wrote:
> Sebastian, and, please, be not offended by what I wrote. I regret a
> bit my jokes ... It's simply too late at night.
no offense taken
>
> Friedrich
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On Sun, Feb 28, 2010 at 12:30 AM, Friedrich Romstedt
wrote:
> 2010/2/27 Sebastian Walter :
>> I'm sorry this comment turns out to be confusing.
>
> Maybe it's not important.
>
>> It has apparently quite the contrary effect of what I wanted to achieve:
>> Since there is already a polynomial module
Sebastian, and, please, be not offended by what I wrote. I regret a
bit my jokes ... It's simply too late at night.
Friedrich
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2010/2/27 Sebastian Walter :
> On Sat, Feb 27, 2010 at 11:11 PM, Friedrich Romstedt
> 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
2010/2/27 Sebastian Walter :
> I'm sorry this comment turns out to be confusing.
Maybe it's not important.
> It has apparently quite the contrary effect of what I wanted to achieve:
> Since there is already a polynomial module in numpy I wanted to
> highlight their difference
> and stress that t
On Sat, Feb 27, 2010 at 11:11 PM, Friedrich Romstedt
wrote:
> Ok, it took me about one hour, but here they are: Fourier-accelerated
> polynomials.
that's the spirit! ;)
>
>> python
> Python 2.4.1 (#65, Mar 30 2005, 09:13:57) [MSC v.1310 32 bit (Intel)] on win32
> Type "help", "copyright", "credi
On Sat, Feb 27, 2010 at 10:02 PM, Friedrich Romstedt
wrote:
> To the core developers (of numpy.polynomial e.g.): Skip the mess and
> read the last paragraph.
>
> The other things I will post back to the list, where they belong to.
> I just didn't want to have off-topic discussion there.
>
>> I wan
Ok, it took me about one hour, but here they are: Fourier-accelerated
polynomials.
> python
Python 2.4.1 (#65, Mar 30 2005, 09:13:57) [MSC v.1310 32 bit (Intel)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import gdft_polynomial
>>> p1 = gdft_polynomial.Poly
2010/2/27 Sebastian Walter :
> IMO this kind of discussion is not offtopic since it is directly
> related to the original question.
Ok, but I say it's not my responsibility now if the numpy-discussion
namespace is polluted now.
>> 2010/2/27 Sebastian Walter :
>>> On Sat, Feb 27, 2010 at 3:59 PM,
To the core developers (of numpy.polynomial e.g.): Skip the mess and
read the last paragraph.
The other things I will post back to the list, where they belong to.
I just didn't want to have off-topic discussion there.
> I wanted to stress that one can do arithmetic on Taylor polynomials in
> a ve
Announcement:
---
I have started to implement vectorized univariate truncated Taylor
polynomial operations (add,sub,mul,div,sin,exp,...) in ANSI-C.
The interface to python is implemented by using numpy.ndarray's ctypes
functionality. Unit tests are implement using nose.
It is B
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