Sample code

xcorr.py

from __future__ import division, print_function
import numpy as np
import matplotlib.pyplot as pp


def xcorr(a, b, mode='same'):
    a = np.asarray(a)
    b = np.asarray(b)
    
    a = a - a.mean()
    b = b - b.mean()

    r = np.correlate(a, b, mode)
    
    r /= np.sqrt(np.correlate(a, a) * np.correlate(b, b))
    
    return r


def xcorr_sl(a, b, k=2):
    sl = k / np.sqrt(min(len(a), len(b))) # min?
    return sl


def xcorr_lags(r):
    lag_max = int(len(r) / 2)
    lags = np.asarray(xrange(-lag_max, lag_max + len(r) % 2))
    return lags


def xcorr_plot(a, b, mode='same', sl_k=2):
    r = xcorr(a, b)
    sl = xcorr_sl(a, b, k=sl_k)
    lags =xcorr_lags(r)
    pp.plot(lags, r)
    pp.plot(lags, np.ones(len(lags)) *  sl, color='r')
    pp.plot(lags, np.ones(len(lags)) * -sl, color='r')
    pp.show()


n = 100
a = np.random.normal(10, 2, n)
#b = np.random.normal(20, 5, n)
xcorr_plot(a, a)