Python 在 NumPy 中将行向量转换为列向量
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Convert row vector to column vector in NumPy
提问by siamii
import numpy as np
matrix1 = np.array([[1,2,3],[4,5,6]])
vector1 = matrix1[:,0] # This should have shape (2,1) but actually has (2,)
matrix2 = np.array([[2,3],[5,6]])
np.hstack((vector1, matrix2))
ValueError: all the input arrays must have same number of dimensions
The problem is that when I select the first column of matrix1 and put it in vector1, it gets converted to a row vector, so when I try to concatenate with matrix2, I get a dimension error. I could do this.
问题是，当我选择 matrix1 的第一列并将其放入 vector1 时，它会转换为行向量，因此当我尝试与 matrix2 连接时，出现维度错误。我可以做到这一点。
np.hstack((vector1.reshape(matrix2.shape[0],1), matrix2))
But this looks too ugly for me to do every time I have to concatenate a matrix and a vector. Is there a simpler way to do this?
但是每次我必须连接矩阵和向量时，这对我来说都太难看了。有没有更简单的方法来做到这一点？
回答by ali_m
Here are three other options:
以下是其他三个选项：
You can tidy up your solution a bit by allowing the row dimension of the vector to be set implicitly:
np.hstack((vector1.reshape(-1, 1), matrix2))You can index with
np.newaxis(or equivalently,None) to insert a new axis of size 1:np.hstack((vector1[:, np.newaxis], matrix2)) np.hstack((vector1[:, None], matrix2))You can use
np.matrix, for which indexing a column with an integer always returns a column vector:matrix1 = np.matrix([[1, 2, 3],[4, 5, 6]]) vector1 = matrix1[:, 0] matrix2 = np.matrix([[2, 3], [5, 6]]) np.hstack((vector1, matrix2))
您可以通过允许隐式设置向量的行维度来稍微整理您的解决方案：
np.hstack((vector1.reshape(-1, 1), matrix2))您可以使用
np.newaxis（或等效地None）索引以插入大小为 1 的新轴：np.hstack((vector1[:, np.newaxis], matrix2)) np.hstack((vector1[:, None], matrix2))您可以使用
np.matrix, 用整数索引列总是返回一个列向量：matrix1 = np.matrix([[1, 2, 3],[4, 5, 6]]) vector1 = matrix1[:, 0] matrix2 = np.matrix([[2, 3], [5, 6]]) np.hstack((vector1, matrix2))
回答by David Z
The easier way is
更简单的方法是
vector1 = matrix1[:,0:1]
For the reason, let me refer you to another answer of mine:
出于这个原因，让我向您推荐我的另一个答案：
When you write something like
a[4], that's accessing the fifth element of the array, not giving you a view of some section of the original array. So for instance, if a is an array of numbers, thena[4]will be just a number. Ifais a two-dimensional array, i.e. effectively an array of arrays, thena[4]would be a one-dimensional array. Basically, the operation of accessing an array element returns something with a dimensionality of one less than the original array.
当你写类似的东西时
a[4]，就是访问数组的第五个元素，而不是让你看到原始数组的某些部分。因此，例如，如果 a 是一个数字数组，那么a[4]它将只是一个数字。如果a是二维数组，即有效的数组数组，a[4]则将是一维数组。基本上，访问数组元素的操作会返回维数比原始数组少一的东西。
