Rotation Correlation Method

The rotation correlation method searches for the rotation and lag which maximises the similarity of pulse shapes and aligns them in time. The method was introduced by Fukao, 1984.

In my testing I have found it is very important to use the normalised correlation coefficient.

Again, continuing with the Real data example, for which we have used the eigenvalue method and the transverse minimisation method plots:

To do the rotation correlation method we use the CrossM class as follows.

m = sw.CrossM(realdata, lags=(2,))
m.plot()