Mike Duffy wrote:

I've been debugging a simulation I wrote a while ago, and it seems that

the problem is in the fft module itself. I'm trying a simple test by

just feeding the function a basic real gaussian. Obviously, I should

get back the same real gaussian, but what I get is not even close. Can

anyone help me? Thanks in advance.

You will probably want to ask scipy questions on scipy-user. There aren't many

scipy people here.

http://www.scipy.org/Mailing_Lists
I haven't run your code, yet, but one of the things you are running into is the

FFT packing convention for FFTs on real functions. Please read the docstring:

Type: function

Base Class: <type 'function'>

String Form: <function rfft at 0x204fbf0>

Namespace: Interactive

File:

/Library/Frameworks/Python.framework/Versions/2.4/lib/python2.4/site-packages/scipy-0.5.0.1980-py2.4-mac

osx-10.4-ppc.egg/scipy/fftpack/basic.py

Definition: rfft(x, n=None, axis=-1, overwrite_x=0)

Docstring:

rfft(x, n=None, axis=-1, overwrite_x=0) -> y

Return discrete Fourier transform of real sequence x.

The returned real arrays contains

[y(0),Re(y(1)),Im(y(1)),...,Re(y(n/2))] if n is even

[y(0),Re(y(1)),Im(y(1)),...,Re(y(n/2)),Im(y(n/2))] if n is odd

where

y(j) = sum[k=0..n-1] x[k] * exp(-sqrt(-1)*j*k* 2*pi/n)

j = 0..n-1

Note that y(-j) = y(n-j).

Optional input:

n

Defines the length of the Fourier transform. If n is not

specified then n=x.shape[axis] is set. If n<x.shape[axis],

x is truncated. If n>x.shape[axis], x is zero-padded.

axis

The transform is applied along the given axis of the input

array (or the newly constructed array if n argument was used).

overwrite_x

If set to true, the contents of x can be destroyed.

Notes:

y == rfft(irfft(y)) within numerical accuracy.

--

Robert Kern

"I have come to believe that the whole world is an enigma, a harmless enigma

that is made terrible by our own mad attempt to interpret it as though it had

an underlying truth."

-- Umberto Eco