Question about numpy correlate: not giving expected result

user_9693473 0
Viewed 106

I want to make sure I am using numpy's correlate correctly, it is not giving me the answer I expect. Perhaps I am misunderstanding the correlate function. Here is a code snipet with comments:

import numpy as np
ref = np.sin(np.linspace(-2*np.pi, 2*np.pi, 10000)) # make some data
fragment = ref[2149:7022] # create a fragment of data from ref
corr = np.correlate(ref, fragment) # Find the correlation between the two
maxLag = np.argmax(corr) # find the maximum lag, this should be the offset that we chose above, 2149
print(maxLag)
2167 # I expected this to be 2149.

Isn't the index in the corr array where the correlation is maximum the lag between these two datasets? I would think the starting index I chose for the smaller dataset would be the offset with the greatest correlation.

Why is there a discrepancy between what I expect, 2149, and the result, 2167?

Thanks

correlation numpy python
1 Answers

That looks like a precision error to me, cross-correlation is an integral and it will always have problems when being represented in discrete space, I guess the problem arises when the values are close to 0. Maybe if you increase the numbers or increase the precision that difference will disappear but I don't think it is really necessary since you are already dealing with approximation when using the discrete cross-correlation, below is the graph of the correlation for you te see that the values are indeed close:

enter image description here

user_102602430
Related