Hi there,
I have a question regarding the definitions surrounding FFTs. The help
to numpy.fft.fft says:
help(N.fft.fft)
Help on function fft in module numpy.fft.fftpack:
fft(a, n=None, axis=-1)
fft(a, n=None, axis=-1)
Will return the n point discrete Fourier transform of a. n
The frequencies produced by the two recipies are not the same. But the
DFT is periodic in both frequency and time. So whether you think that the
number in bin in n/2 should correspond to frequency n/2 or -n/2, it's the
same number.
w
On Mon, 5 Feb 2007, Hanno Klemm wrote:
Hi there,
I have
On 2/4/07, Pierre GM [EMAIL PROTECTED] wrote:
On Sunday 04 February 2007 20:22:44 Jeremy Conlin wrote:
I have subclassed the numpy.ndarray object, but need some help setting
some attributes. I have read http://scipy.org/Subclasses but it
doesn't provide the answer I am looking for.
This eats up memory quickly on my system.
import numpy.matlib as M
def memleak():
a = M.randn(500, 1)
while True:
a = a.argsort(0)
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El dl 05 de 02 del 2007 a les 08:45 -0800, en/na Keith Goodman va
escriure:
This eats up memory quickly on my system.
import numpy.matlib as M
def memleak():
a = M.randn(500, 1)
while True:
a = a.argsort(0)
Yeah, the guilty in this case is argsort():
On 2/5/07, Francesc Altet [EMAIL PROTECTED] wrote:
El dl 05 de 02 del 2007 a les 08:45 -0800, en/na Keith Goodman va
escriure:
This eats up memory quickly on my system.
import numpy.matlib as M
def memleak():
a = M.randn(500, 1)
while True:
a = a.argsort(0)
On Mon, 5 Feb 2007, Timothy Hochberg wrote:
On 2/5/07, Hanno Klemm [EMAIL PROTECTED] wrote:
[numpy.fft[
The packing of the result is standard: If A = fft(a, n), then A[0]
contains the zero-frequency term, A[1:n/2+1] contains the
positive-frequency terms, and A[n/2+1:]
On 2/5/07, Warren Focke [EMAIL PROTECTED] wrote:
On Mon, 5 Feb 2007, Timothy Hochberg wrote:
On 2/5/07, Hanno Klemm [EMAIL PROTECTED] wrote:
[numpy.fft[
The packing of the result is standard: If A = fft(a, n), then A[0]
contains the zero-frequency term, A[1:n/2+1] contains the
On 2/5/07, Pierre GM [EMAIL PROTECTED] wrote:
On Monday 05 February 2007 11:32:22 Jeremy Conlin wrote:
Thanks for clarifying that. I didn't understand what the
__array_finalize__ did.
That means I should clarify some points on the wiki, then.
A good exercise is to put some temporary
Hey,
After reading Travis' email about getting more projects ported to
Numpy, I sent an email to the RPy developer's asking when they would
commit Travis' patch. Anyway, George Warnes replied that he would
apply it this week (see the forwarded email below).
I would encourage anyone who is using
The current development release of ScientificPython (2.7.3) supports
NumPy. The release notes are here:
http://sourcesup.cru.fr/frs/shownotes.php?release_id=634
I updated the Porting to NumPy wiki page:
http://www.scipy.org/Porting_to_NumPy
--
Jarrod Millman
Computational Infrastructure for
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