python-数组-求逆，转置等操作

>> from numpy import *
>>> from numpy.linalg import *

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

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

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

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

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

>>> trace(u)  # trace
2.0

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

>>> eig(j)
(array([ 0.+1.j,  0.-1.j]),
array([[ 0.70710678+0.j,  0.70710678+0.j],
       [ 0.00000000-0.70710678j,  0.00000000+0.70710678j]]))
Parameters:
    square matrix

Returns
    The eigenvalues, each repeated according to its multiplicity.

    The normalized (unit "length") eigenvectors, such that the
    column ``v[:,i]`` is the eigenvector corresponding to the
    eigenvalue ``w[i]`` .