我在python中有一些unixtime数据,值:
[(1301672429, 274), (1301672430, 302), (1301672431, 288)...]
时间不断一步一秒。我如何减少这些数据,以便时间戳每秒,但该值是周围10个值的平均值?
Fancier滚动平均值也会很好,但是这些数据是绘制的,因此主要是为了平滑图表。
在得出结论认为在SQL中尝试这样做是痛苦之路后,(TSQL Rolling Average of Time Groupings)跟进。
答案 0 :(得分:16)
使用http://www.scipy.org/Cookbook/SignalSmooth:
import numpy
def smooth(x,window_len=11,window='hanning'):
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': #moving average
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:-window_len+1]
我得到的结果似乎很好(不是我理解数学):
if form_results['smooth']:
a = numpy.array([x[1] for x in results])
smoothed = smooth(a,window_len=21)
results = zip([x[0] for x in results], smoothed)
答案 1 :(得分:10)
如果您有numpy
的访问权限,可以尝试以下方法: