how to smooth a curve in python

ok, I solved.I have used another approach: Savitzky-Golay filter

The code:

def savitzky_golay(y, window_size, order, deriv=0, rate=1):    import numpy as np    from math import factorial    try:        window_size = np.abs(np.int(window_size))        order = np.abs(np.int(order))    except ValueError, msg:        raise ValueError("window_size and order have to be of type int")    if window_size % 2 != 1 or window_size < 1:        raise TypeError("window_size size must be a positive odd number")    if window_size < order + 2:        raise TypeError("window_size is too small for the polynomials order")    order_range = range(order+1)    half_window = (window_size -1) // 2    # precompute coefficients    b = np.mat([[k**i for i in order_range] for k in range(-half_window, half_window+1)])    m = np.linalg.pinv(b).A[deriv] * rate**deriv * factorial(deriv)    # pad the signal at the extremes with    # values taken from the signal itself    firstvals = y[0] - np.abs( y[1:half_window+1][::-1] - y[0] )    lastvals = y[-1] + np.abs(y[-half_window-1:-1][::-1] - y[-1])    y = np.concatenate((firstvals, y, lastvals))    return np.convolve( m[::-1], y, mode='valid')

now, I can type:

entropy = np.array(entropy)entropy = savitzky_golay(entropy, 51, 3) # window size 51, polynomial order 3

the result is this: