def smooth(x, window_len=11, window='flat'):
 if (x.ndim != 1):
  raise ValueError('smooth only accepts 1 dimension arrays.')
 if (x.size < window_len):
  raise ValueError('Input vector needs to be bigger than window size.')
 if (window_len < 3):
  return x
 if (not (window in ['flat', 'hanning', 'hamming', 'bartlett', 'blackman'])):
  raise ValueError("Window is on of 'flat', 'hanning', 'hamming', 'bartlett', 'blackman'")
 s = numpy.r_[(((2 * x[0]) - x[window_len:1:(-1)]), x, ((2 * x[(-1)]) - x[(-1):(- window_len):(-1)]))]
 if (window == 'flat'):
  w = numpy.ones(window_len, 'd')
 else:
  w = eval((('numpy.' + window) + '(window_len)'))
 y = numpy.convolve((w / w.sum()), s, mode='same')
 return y[(window_len - 1):((- window_len) + 1)]

def smooth ( x , window_len = 11 , window = 'flat' ) : if ( x . ndim != 1 ) : raise ValueError ( 'smooth only accepts 1 dimension arrays.' ) if ( x . size < window_len ) : raise ValueError ( 'Input vector needs to be bigger than window size.' ) if ( window_len < 3 ) : return x if ( not ( window in [ 'flat' , 'hanning' , 'hamming' , 'bartlett' , 'blackman' ] ) ) : raise ValueError ( "Window is on of 'flat', 'hanning', 'hamming', 'bartlett', 'blackman'" ) s = numpy . r_ [ ( ( ( 2 * x [ 0 ] ) - x [ window_len : 1 : ( - 1 ) ] ) , x , ( ( 2 * x [ ( - 1 ) ] ) - x [ ( - 1 ) : ( - window_len ) : ( - 1 ) ] ) ) ] if ( window == 'flat' ) : w = numpy . ones ( window_len , 'd' ) else : w = eval ( ( ( 'numpy.' + window ) + '(window_len)' ) ) y = numpy . convolve ( ( w / w . sum ( ) ) , s , mode = 'same' ) return y [ ( window_len - 1 ) : ( ( - window_len ) + 1 ) ]
running smoothed average .