线性代数

简单的数组操作

更多信息请参见 numpy 文件夹中的 linalg.py

>>> a = np.array([[1.0, 2.0], [3.0, 4.0]])
>>> print(a)
[[1. 2.]
 [3. 4.]]

>>> a.transpose()
array([[1., 3.],
       [2., 4.]])

>>> np.linalg.inv(a)
array([[-2. ,  1. ],
       [ 1.5, -0.5]])

>>> u = np.eye(2) # unit 2x2 matrix; "eye" represents "I"
>>> u
array([[1., 0.],
       [0., 1.]])
>>> j = np.array([[0.0, -1.0], [1.0, 0.0]])

>>> j @ j        # matrix product
array([[-1.,  0.],
       [ 0., -1.]])

>>> np.trace(u)  # trace
2.0

>>> y = np.array([[5.], [7.]])
>>> np.linalg.solve(a, y)
array([[-3.],
       [ 4.]])

>>> np.linalg.eig(j)
(array([0.+1.j, 0.-1.j]), array([[0.70710678+0.j        , 0.70710678-0.j        ],
       [0.        -0.70710678j, 0.        +0.70710678j]]))