example application of using RunningStats class for running mean calcs

running_stats.py

import numpy as np
import matplotlib.pylab as plt

# generate some data
x = np.random.rand(1000,1)

# get the class
import RunningStats

# get an instance of the class
rs = RunningStats.RunningStats()

# define a window size for the running average
window_size = 10

from itertools import product

# use sliding window_nd from here: http://www.johnvinyard.com/blog/?p=268
xs = sliding_window_nd(np.squeeze(x),window_size,1)

runav = []
for j in xrange(len(xs)):
   for k in xs[j]:
      rs.Push(k)
   runav.append(rs.Mean())
   rs.Clear()

i = np.linspace(1,len(x),len(runav))
plt.plot(x); plt.plot(i,runav,'r'); 

# compute using a larger window size
window_size = 50
xs = sliding_window_nd(np.squeeze(x),window_size,1)

runav = []
for j in xrange(len(xs)):
   for k in xs[j]:
      rs.Push(k)
   runav.append(rs.Mean())
   rs.Clear()

i = np.linspace(1,len(x),len(runav))
plt.plot(i,runav,'k'); 

plt.show()