numpy:要提取一列，给出一行

问题描述

我从MATLAB转到Python，在处理矩阵时遇到一些问题.

I came from MATLAB to Python and I face some problems dealing with matrices.

因此，我有一个矩阵(实现为np.array)，我想操纵该矩阵的列.

So, I have a matrix (implemented as a np.array) and I want to manipulate columns of that matrix.

所以，我从初始化开始:

So, I begin with an initialization :

x = np.nan * np.ndarray((2,8))
y = np.nan * np.ndarray((2,8))

给出两个

array([[ nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan],
   [ nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan]])

现在，我想在y内放置列向量v以便以后在x内进行计算

Now, I want to put a column vector v inside y to compute something inside x later

v = np.array([[v1, v2]]) # if v = np.array([[v1], [v2]], doesn't compute on next line
y[:,0] = np.copy(v)
x[:,0] = y[:,0] + someRandomVector

它向我返回一个错误:

ValueError: could not broadcast input array from shape (2,2) into shape (2)

我认为问题出在以下事实:x[:,0]没有给出我期望的列向量，而是

I think the problem comes from the fact that x[:,0] does not give a column vector as I expected but rather

>>> x[:,0]
array([ nan,  nan])

有什么想法或提示可能会有所帮助吗?

Any idea or tips that might help?

推荐答案

>>>x[:,0:1]
print x.[:,0:1].shape
(2,1)

在此帖子解释了动机以及如何在numpy中管理数组.

In this post is explained the motivation and how the array is managed in numpy.

如果您想提取具有更多内容的第五列 超过5列，则可以使用X [:，4:5].如果您想查看 第3-4行和第5-7列，则可以执行X [3:5,5:8].希望你能 这个想法.

If you wanted to extract the fifth column of something that had more than 5 total columns, you could use X[:,4:5]. If you wanted a view of rows 3-4 and columns 5-7, you would do X[3:5,5:8]. Hopefully you get the idea.

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