Numpy mat 将数组转换为矩阵

import numpy as np
arr = np.array([[1,2],[3,4]])
print("arr",arr)
print("type(arr)",type(arr))

arr [[1 2]
 [3 4]]
type(arr) <class 'numpy.ndarray'>

m = np.mat(arr)
print("m",m)
print("type(m)",type(m))
print(id(arr),id(m))

m [[1 2]
 [3 4]]
type(m) <class 'numpy.matrix'>
139898878402768 139898871385560

'''
class matrix(ndarray)
 |  matrix(data, dtype=None, copy=True)
 |  
 |  .. note:: It is no longer recommended to use this class, even for linear
 |            algebra. Instead use regular arrays. The class may be removed
 |            in the future.
'''
m2 = np.matrix(arr)
print("m2",m2)
print("type(m2)",type(m2))
print(id(arr),id(m2))

m2 [[1 2]
 [3 4]]
type(m2) <class 'numpy.matrix'>
139898878402768 139898871385784

'''
Unlike `matrix`, `asmatrix` does not make a copy if the input is already
    a matrix or an ndarray.  Equivalent to ``matrix(data, copy=False)``.
'''
m3 = np.asmatrix(arr)
print("m3",m3)
print("type(m3)",type(m3))
print(id(arr),id(m3))

m3 [[1 2]
 [3 4]]
type(m3) <class 'numpy.matrix'>
139898878402768 139898871385672

help(np.mat)

Help on function asmatrix in module numpy:

asmatrix(data, dtype=None)
    Interpret the input as a matrix.
    
    Unlike `matrix`, `asmatrix` does not make a copy if the input is already
    a matrix or an ndarray.  Equivalent to ``matrix(data, copy=False)``.
    
    Parameters
    ----------
    data : array_like
        Input data.
    dtype : data-type
       Data-type of the output matrix.
    
    Returns
    -------
    mat : matrix
        `data` interpreted as a matrix.
    
    Examples
    --------
    >>> x = np.array([[1, 2], [3, 4]])
    
    >>> m = np.asmatrix(x)
    
    >>> x[0,0] = 5
    
    >>> m
    matrix([[5, 2],
            [3, 4]])

help(np.matrix)

Help on class matrix in module numpy:

class matrix(ndarray)
 |  matrix(data, dtype=None, copy=True)
 |  
 |  .. note:: It is no longer recommended to use this class, even for linear
 |            algebra. Instead use regular arrays. The class may be removed
 |            in the future.
 |  
 |  Returns a matrix from an array-like object, or from a string of data.
 |  A matrix is a specialized 2-D array that retains its 2-D nature
 |  through operations.  It has certain special operators, such as ``*``
 |  (matrix multiplication) and ``**`` (matrix power).
 |  
 |  Parameters
 |  ----------
 |  data : array_like or string
 |     If `data` is a string, it is interpreted as a matrix with commas
 |     or spaces separating columns, and semicolons separating rows.
 |  dtype : data-type
 |     Data-type of the output matrix.
 |  copy : bool
 |     If `data` is already an `ndarray`, then this flag determines
 |     whether the data is copied (the default), or whether a view is
 |     constructed.
 |  
 |  See Also
 |  --------
 |  array
 |  
 |  Examples
 |  --------
 |  >>> a = np.matrix('1 2; 3 4')
 |  >>> a
 |  matrix([[1, 2],
 |          [3, 4]])
 |  
 |  >>> np.matrix([[1, 2], [3, 4]])
 |  matrix([[1, 2],
 |          [3, 4]])
 |  
 |  Method resolution order:
 |      matrix
 |      ndarray
 |      builtins.object
 |  
 |  Methods defined here:
 ......

help(np.asmatrix)

Help on function asmatrix in module numpy:

asmatrix(data, dtype=None)
    Interpret the input as a matrix.
    
    Unlike `matrix`, `asmatrix` does not make a copy if the input is already
    a matrix or an ndarray.  Equivalent to ``matrix(data, copy=False)``.
    
    Parameters
    ----------
    data : array_like
        Input data.
    dtype : data-type
       Data-type of the output matrix.
    
    Returns
    -------
    mat : matrix
        `data` interpreted as a matrix.
    
    Examples
    --------
    >>> x = np.array([[1, 2], [3, 4]])
    
    >>> m = np.asmatrix(x)
    
    >>> x[0,0] = 5
    
    >>> m
    matrix([[5, 2],
            [3, 4]])