[SciPy-User] Understanding the cross-correlation function numpy.correlate & how to use it properly with real and synthetic data

[Vincent Schut]

On 12/14/2011 09:14 PM, Rob Newman wrote:
> Hi SciPy gurus,
>
> First up - I am not a physicist, so please be gentle!
>
> I have an array of real data and an array of synthetic data. I am trying to determine the cross-correlation of the two signals and the timeshift that needs to be applied to the real data to best match the synthetic data. I also want to only use the real data later on the script if the cross correlation result is above some level of confidence.
>
> I have read the man page on numpy.correlate, but I am not entirely sure of what that function returns to me, and how I should use it. I have looked at James Battat's website that has a useful script on the discrete correlation function of two functions (https://www.cfa.harvard.edu/~jbattat/computer/python/science/#correlation) but I think his example is more complicated than my needs.
>
> I understand that the correlate function returns an array that is twice the size of both the input arrays minus 1 (when using mode='full'), but what do I need to do to that resulting array to get the correlation value (if there is indeed a value to be returned) and the timeshift that needs to be applied to the real data to match the synthetic data.
>
> Thanks in advance,
> - Rob

Hi,

if you just need to find the time-shift, another approach could be fft 
phase correlation. I have successfully used that to co-register images 
(satellite images) together, but I suppose it would apply in the 1-d 
case as well. Unfortunately I don't have any code ready, but you just 
might want to check some info on the subject on the internet to see if 
it would fit your needs.

Best,
Vincent.