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 -- http://mail.python.org/mailman/listinfo/python-list