I have a matrix M1 , each row of which is a time-dependent signal.
And I have another matrix, M2, of the same dimensions, each row of which is also a time dependent
not knowing enough of numpy array magic, I'd just pick out the rows, feed each pair individually to corrcoeff
[np.corrcoef(i,j)[0][1] for i,j in zip(a,b)]
for a np.array column output
c, c.shape = np.array([np.corrcoef(i,j)[0][1] for i,j in zip(a,b)]), (a.shape[0], 1)
I'm sure there's better using numpy broadcast/indexing features