python矩阵运算,转置,逆运算,共轭矩阵的用法-创新互联

这篇文章主要讲解了python矩阵运算,转置,逆运算,共轭矩阵的用法，内容清晰明了，对此有兴趣的小伙伴可以学习一下，相信大家阅读完之后会有帮助。

我就废话不多说了，大家还是直接看代码吧！

#先定义两个矩阵
X=np.array([[1,2104,5,1,45],[1,1416,3,2,40],[1,1534,3,2,30],[1,852,2,1,36]])
 
y=np.array([45,40,30,36])
#内积以后发现
c=np.dot(X.T,X)
c
array([[  4, 5906,  13,  6,  151],
  [ 5906, 9510932, 21074, 8856, 228012],
  [  13, 21074,  47,  19,  507],
  [  6, 8856,  19,  10,  221],
  [ 151, 228012,  507,  221, 5821]])
c.I
d=np.dot(c.I,X.T)
Traceback (most recent call last):
 
 File "", line 1, in 
 d=np.dot(c.I,X.T)
 
AttributeError: 'numpy.ndarray' object has no attribute 'I'

#说明array进行内积以后已经不是array对象，成为ndarray对象，不能再进行.I,.T,.M的操作。
#解决方法：把结果转为matrix就可以
a=np.matrix([[  4, 5906,  13,  6,  151],
  [ 5906, 9510932, 21074, 8856, 228012],
  [  13, 21074,  47,  19,  507],
  [  6, 8856,  19,  10,  221],
  [ 151, 228012,  507,  221, 5821]])

a.I
matrix([[ -4.12181049e+13, 1.93633440e+11, -8.76643127e+13,
   -3.06844458e+13, 2.28487459e+12],
  [ 1.93633440e+11, -9.09646601e+08, 4.11827338e+11,
   1.44148665e+11, -1.07338299e+10],
  [ -8.76643127e+13, 4.11827338e+11, -1.86447963e+14,
   -6.52609055e+13, 4.85956259e+12],
  [ -3.06844458e+13, 1.44148665e+11, -6.52609055e+13,
   -2.28427584e+13, 1.70095424e+12],
  [ 2.28487459e+12, -1.07338299e+10, 4.85956259e+12,
   1.70095424e+12, -1.26659193e+11]])