“克隆"行或列向量 [英] "Cloning" row or column vectors

问题描述

有时，将行或列向量克隆"到矩阵很有用.通过克隆，我的意思是转换行向量，例如

Sometimes it is useful to "clone" a row or column vector to a matrix. By cloning I mean converting a row vector such as

[1,2,3]

放入矩阵

[[1,2,3]
 [1,2,3]
 [1,2,3]
]

或列向量(如

[1
 2
 3
]

进入

[[1,1,1]
 [2,2,2]
 [3,3,3]
]

在matlab或八度音阶中，这很容易做到:

In matlab or octave this is done pretty easily:

 x = [1,2,3]
 a = ones(3,1) * x
 a =

    1   2   3
    1   2   3
    1   2   3

 b = (x') * ones(1,3)
 b =

    1   1   1
    2   2   2
    3   3   3

我想以numpy重复此操作，但未成功

I want to repeat this in numpy, but unsuccessfully

In [14]: x = array([1,2,3])
In [14]: ones((3,1)) * x
Out[14]:
array([[ 1.,  2.,  3.],
       [ 1.,  2.,  3.],
       [ 1.,  2.,  3.]])
# so far so good
In [16]: x.transpose() * ones((1,3))
Out[16]: array([[ 1.,  2.,  3.]])
# DAMN
# I end up with 
In [17]: (ones((3,1)) * x).transpose()
Out[17]:
array([[ 1.,  1.,  1.],
       [ 2.,  2.,  2.],
       [ 3.,  3.,  3.]])

为什么第一种方法(In [16])不起作用?有没有办法以更优雅的方式在python中完成此任务?

Why wasn't the first method (In [16]) working? Is there a way to achieve this task in python in a more elegant way?

推荐答案

这是一种优雅的Pythonic方式:

Here's an elegant, Pythonic way to do it:

>>> array([[1,2,3],]*3)
array([[1, 2, 3],
       [1, 2, 3],
       [1, 2, 3]])

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

[16]的问题似乎是转置对数组没有影响.您可能想要一个矩阵:

the problem with [16] seems to be that the transpose has no effect for an array. you're probably wanting a matrix instead:

>>> x = array([1,2,3])
>>> x
array([1, 2, 3])
>>> x.transpose()
array([1, 2, 3])
>>> matrix([1,2,3])
matrix([[1, 2, 3]])
>>> matrix([1,2,3]).transpose()
matrix([[1],
        [2],
        [3]])

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