相关疑难解决方法(0)

我正在寻找NumPy计算两个numpy数组(x和y)之间的Mahalanobis距离的方法.以下代码可以使用Scipy的cdist函数正确计算相同的代码.由于此函数在我的情况下计算不必要的matix,我想要更直接的方式使用NumPy计算它.

import numpy as np
from scipy.spatial.distance import cdist

x = np.array([[[1,2,3,4,5],
               [5,6,7,8,5],
               [5,6,7,8,5]],
              [[11,22,23,24,5],
               [25,26,27,28,5],
               [5,6,7,8,5]]])
i,j,k = x.shape

xx = x.reshape(i,j*k).T


y = np.array([[[31,32,33,34,5],
               [35,36,37,38,5],
               [5,6,7,8,5]],
              [[41,42,43,44,5],
               [45,46,47,48,5],
               [5,6,7,8,5]]])


yy = y.reshape(i,j*k).T

results =  cdist(xx,yy,'mahalanobis')
results = np.diag(results)
print results



[ 2.28765854  2.75165028  2.75165028  2.75165028  0.          2.75165028
  2.75165028  2.75165028  2.75165028  0.          0.          0.          0.
  0.          0.        ]

我的试用版:

VI = np.linalg.inv(np.cov(xx,yy))

print np.sqrt(np.dot(np.dot((xx-yy),VI),(xx-yy).T))

任何人都可以纠正这种方法吗？

这是它的公式:

http://docs.scipy.org/doc/scipy-0.14.0/reference/generated/scipy.spatial.distance.mahalanobis.html#scipy.spatial.distance.mahalanobis