If we have two different datasets from two different observations, we want to know if those two event sets are correlated. We want to cross correlate them and see if they match in any way. We are looking for a pattern of a smaller data sample in a larger data sample. The pattern does not have to be an obvious or simple pattern.
We can use the matplotlib's function from pyplot lab—matplotlib.pyplot.xcorr. These functions can plot correlation between two datasets in such a way that we can see if there is any significant pattern between the plotted values. It is assumed that x and y are of the same length.
If we pass the normed argument as True, we can normalize by cross correlation at 0-th lag (that is, when there is no time delay or time lag).
Behind the scenes, correlation is done using NumPy's numpy.correlate function.
Using the usevlines argument (setting it to True), we can instruct matplotlib to use vlines() instead of plot...