Holger wrote:

What does it mean to me? How do I get to the wanted frequenca spectrum???

It's packed in the conventional FFT format. Here is a function in numpy (the

successor to Numeric, which I assume that you are using) that generates the

corresponding frequencies in the same packed format:

In [324]: import numpy

In [325]: numpy.fft.fftfreq?

Type: function

Base Class: <type 'function'>

Namespace: Interactive

File:

/Library/Frameworks/Python.framework/Versions/2.5/lib/python2.5/site-packages/numpy-1.0.2.dev3507-py2.5-macosx-10.4-i386.egg/numpy/fft/helper.py

Definition: numpy.fft.fftfreq(n, d=1.0)

Docstring:

fftfreq(n, d=1.0) -f

DFT sample frequencies

The returned float array contains the frequency bins in

cycles/unit (with zero at the start) given a window length n and a

sample spacing d:

f = [0,1,...,n/2-1,-n/2,...,-1]/(d*n) if n is even

f = [0,1,...,(n-1)/2,-(n-1)/2,...,-1]/(d*n) if n is odd

--

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