带有1列的Numpy重塑1d至2d数组

在numpy中，结果数组的尺寸在运行时会有所不同. 一维数组和具有一列的二维数组之间经常会混淆. 在一种情况下，我可以遍历列，而在另一种情况下，我不能.

In numpy the dimensions of the resulting array vary at run time. There is often confusion between a 1d array and a 2d array with 1 column. In one case I can iterate over the columns, in the other case I cannot.

您如何优雅地解决该问题? 为了避免使用if语句检查维数而乱码，我使用以下函数:

How do you solve elegantly that problem? To avoid littering my code with if statements checking for the dimensionality, I use this function:

def reshape_to_vect(ar):
    if len(ar.shape) == 1:
      return ar.reshape(ar.shape[0],1)
    return ar

但是，这感觉不雅且昂贵.有更好的解决方案吗?

However, this feels inelegant and costly. Is there a better solution?