如何计算numpy中的斜率

>>> from scipy import stats
>>> import numpy as np
>>> x = np.random.random(10)
>>> y = np.random.random(10)
>>> slope,intercept,r_value,p_value,std_err = stats.linregress(x,y)

这会有用吗？

def slope(x,n): 
   if i<len(x)-n: 
        slope = stats.linregress(x[i:i+n],y[i:i+n])[0]
        return slope

但是数组的长度是相同的

@joe :::

xx = [2.0,4,6,8,10,12,14,16,18,20,22,24,26,28,30]
x  = np.asarray(xx,np.float)
s  = np.diff(x[::3])/3

window  = [1,-1]
window2 = [1,-1]
slope   = np.convolve(x,window,mode='same') / (len(window) - 1)
slope2  = np.convolve(x,window2,mode='same') / (len(window2) - 1)

print x
print s

print slope
print slope2

结果…..

[  2.   4.   6.   8.  10.  12.  14.  16.  18.  20.  22.  24.  26.  28.  30.]
[ 2.  2.  2.  2.]
[ 1.5  2.   2.   2.   2.   2.   2.   2.   2.   2.   2.   2.   2.  -6.  -6.5]
[  2.   2.   2.   2.   2.   2.   2.   2.   2.   2.   2.   2.   2.   2. -14.]

斜率和斜率2是Im之后的除了-6,-6.5和-14不是我正在寻找的结果.

这工作…….

window    = [1,-1]
slope     = np.convolve(xx,mode='valid') / float(len(window) - 1)
padlength = len(window) -1
slope     = np.hstack([np.ones(padlength),slope])
print slope