Python中Numpy mat的使用详解

>>> m= np.mat([1,2,3]) #创建矩阵
>>> m
matrix([[1, 2, 3]])

>>> m[0]        #取一行
matrix([[1, 2, 3]])
>>> m[0,1]       #第一行，第2个数据
2
>>> m[0][1]       #注意不能像数组那样取值了
Traceback (most recent call last):
 File "<stdin>", line 1, in <module>
 File "/usr/lib64/python2.7/site-packages/numpy/matrixlib/defmatrix.py", line 305, in __getitem__
  out = N.ndarray.__getitem__(self, index)
IndexError: index 1 is out of bounds for axis 0 with size 1

#将Python的列表转换成NumPy的矩阵
>>> list=[1,2,3]
>>> mat(list)
matrix([[1, 2, 3]])

#Numpy dnarray转换成Numpy矩阵
>>> n = np.array([1,2,3])
>>> n
array([1, 2, 3])
>>> np.mat(n)
matrix([[1, 2, 3]])

#排序
>>> m=np.mat([[2,5,1],[4,6,2]])  #创建2行3列矩阵
>>> m
matrix([[2, 5, 1],
    [4, 6, 2]])
>>> m.sort()          #对每一行进行排序
>>> m
matrix([[1, 2, 5],
    [2, 4, 6]])

>>> m.shape           #获得矩阵的行列数
(2, 3)
>>> m.shape[0]         #获得矩阵的行数
2
>>> m.shape[1]         #获得矩阵的列数
3

#索引取值
>>> m[1,:]           #取得第一行的所有元素
matrix([[2, 4, 6]])
>>> m[1,0:1]          #第一行第0个元素，注意左闭右开
matrix([[2]])
>>> m[1,0:3]
matrix([[2, 4, 6]])
>>> m[1,0:2]
matrix([[2, 4]])

>>> a = np.mat([[1,2,3], [2,3,4]])
>>> b = np.mat([[1,2], [3,4], [5,6]])
>>> a
matrix([[1, 2, 3],
    [2, 3, 4]])
>>> b
matrix([[1, 2],
    [3, 4],
    [5, 6]])
>>> a * b     #方法一
matrix([[22, 28],
    [31, 40]])
>>> np.matmul(a, b)  #方法二
matrix([[22, 28],
    [31, 40]])
>>> np.dot(a, b)   #方法三
matrix([[22, 28],
    [31, 40]])

>>> a = np.mat([[1,2], [3,4]])
>>> b = np.mat([[2,2], [3,3]])
>>> np.multiply(a, b)
matrix([[ 2, 4],
    [ 9, 12]])

>>> a
matrix([[1, 2],
    [3, 4]])
>>> a.T      #方法一，ndarray也行
matrix([[1, 3],
    [2, 4]])
>>> np.transpose(a)  #方法二
matrix([[1, 3],
    [2, 4]])

>>> a
matrix([[1, 2],
    [3, 4]])
>>> a.I
matrix([[-2. , 1. ],
    [ 1.5, -0.5]])