垂直连接两个 NumPy 数组

问题描述

我尝试了以下方法:

>>>a = np.array([1,2,3])>>>b = np.array([4,5,6])>>>np.concatenate((a,b),axis=0)数组([1, 2, 3, 4, 5, 6])>>>np.concatenate((a,b),axis=1)数组([1, 2, 3, 4, 5, 6])

但是，我希望至少有一个结果看起来像这样

array([[1, 2, 3],[4, 5, 6]])

为什么不垂直串联?

解决方案

因为 a 和 b 只有一个轴，因为它们的形状是 (3)，axis参数特指要连接的元素的轴.

这个例子应该阐明 concatenate 对轴做了什么.取两个有两个轴的向量，形状为 (2,3):

a = np.array([[1,5,9], [2,6,10]])b = np.array([[3,7,11], [4,8,12]])

沿第 1 个轴连接(第 1 行，然后是第 2 行):

np.concatenate((a,b),axis=0)数组([[ 1, 5, 9],[ 2, 6, 10],[ 3, 7, 11],[ 4, 8, 12]])

沿第二个轴连接(第一个的列，然后是第二个的列):

np.concatenate((a, b), axis=1)数组([[ 1, 5, 9, 3, 7, 11],[ 2, 6, 10, 4, 8, 12]])

要获得您呈现的输出，您可以使用 vstack

a = np.array([1,2,3])b = np.array([4,5,6])np.vstack((a, b))数组([[1, 2, 3],[4, 5, 6]])

你仍然可以用 concatenate 来做，但你需要先重塑它们:

np.concatenate((a.reshape(1,3), b.reshape(1,3)))数组([[1, 2, 3],[4, 5, 6]])

最后，正如评论中所建议的，一种重塑它们的方法是使用 newaxis:

np.concatenate((a[np.newaxis,:], b[np.newaxis,:]))

I tried the following:

>>> a = np.array([1,2,3])
>>> b = np.array([4,5,6])
>>> np.concatenate((a,b), axis=0)
array([1, 2, 3, 4, 5, 6])
>>> np.concatenate((a,b), axis=1)
array([1, 2, 3, 4, 5, 6])

However, I'd expect at least that one result looks like this

array([[1, 2, 3],
       [4, 5, 6]])

Why is it not concatenated vertically?

解决方案

Because both a and b have only one axis, as their shape is (3), and the axis parameter specifically refers to the axis of the elements to concatenate.

this example should clarify what concatenate is doing with axis. Take two vectors with two axis, with shape (2,3):

a = np.array([[1,5,9], [2,6,10]])
b = np.array([[3,7,11], [4,8,12]])

concatenates along the 1st axis (rows of the 1st, then rows of the 2nd):

np.concatenate((a,b), axis=0)
array([[ 1,  5,  9],
       [ 2,  6, 10],
       [ 3,  7, 11],
       [ 4,  8, 12]])

concatenates along the 2nd axis (columns of the 1st, then columns of the 2nd):

np.concatenate((a, b), axis=1)
array([[ 1,  5,  9,  3,  7, 11],
       [ 2,  6, 10,  4,  8, 12]])

to obtain the output you presented, you can use vstack

a = np.array([1,2,3])
b = np.array([4,5,6])
np.vstack((a, b))
array([[1, 2, 3],
       [4, 5, 6]])

You can still do it with concatenate, but you need to reshape them first:

np.concatenate((a.reshape(1,3), b.reshape(1,3)))
array([[1, 2, 3],
       [4, 5, 6]])

Finally, as proposed in the comments, one way to reshape them is to use newaxis:

np.concatenate((a[np.newaxis,:], b[np.newaxis,:]))

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