[Numpy-discussion] numpy.correlate with phase offset 1D data series
Ray Schumacher
subscriber100@rjs....
Mon Mar 3 13:57:12 CST 2008
I'm trying to figure out what numpy.correlate does, and, what are
people using to calculate the phase shift of 1D signals?
(I coded on routine that uses rfft, conjugate, ratio, irfft, and
argmax based on a paper by Hongjie Xie "An IDL/ENVI implementation
of the FFT Based Algorithm for Automatic Image Registration" - but
that seems more intensive than it could be.)
In numpy, an identity
import numpy
from pylab import *
l=[1,5,3,8,15,6,7,7,9,10,4]
c=numpy.correlate(l,l, mode='same')
plot(c) peaks at the center, x=5, and is symmetric
when the data is rotated by 2
c=numpy.correlate(l, l[-2:]+l[:-2], mode='same')
it peaks at x=3
I was expecting, I guess, that the peak should reflect the x axis shift, as in
http://en.wikipedia.org/wiki/Cross-correlation#Explanation
If I use a real time domain signal like
http://rjs.org/Python/sample.sig
fh = open(r'sample.sig','rb')
s1 = numpy.fromstring(fh.read(), numpy.int32)
fh.close()
an identity like
c=numpy.correlate(s1, s1, mode='same')
plots like noise.
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