Python 使用 numpy 数组连接列向量
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Concatenating column vectors using numpy arrays
提问by green diod
I'd like to concatenate 'column' vectors using numpy arrays but because numpy sees all arrays as row vectors by default, np.hstackand np.concatenatealong any axis don't help (and neither did np.transposeas expected).
我想使用 numpy 数组连接“列”向量，但因为默认情况下 numpy 将所有数组视为行向量，np.hstack并且np.concatenate沿任何轴都无济于事（并且也没有np.transpose按预期进行）。
a = np.array((0, 1))
b = np.array((2, 1))
c = np.array((-1, -1))
np.hstack((a, b, c))
# array([ 0, 1, 2, 1, -1, -1]) ## Noooooo
np.reshape(np.hstack((a, b, c)), (2, 3))
# array([[ 0, 1, 2], [ 1, -1, -1]]) ## Reshaping won't help
One possibility (but too cumbersome) is
一种可能性（但太麻烦）是
np.hstack((a[:, np.newaxis], b[:, np.newaxis], c[:, np.newaxis]))
# array([[ 0, 2, -1], [ 1, 1, -1]]) ##
Are there better ways?
有更好的方法吗？
采纳答案by abudis
I believe numpy.column_stackshould do what you want. Example:
我相信numpy.column_stack应该做你想做的。例子：
>>> a = np.array((0, 1))
>>> b = np.array((2, 1))
>>> c = np.array((-1, -1))
>>> numpy.column_stack((a,b,c))
array([[ 0, 2, -1],
[ 1, 1, -1]])
It is essentially equal to
它基本上等于
>>> numpy.vstack((a,b,c)).T
though. As it says in the documentation.
尽管。正如文档中所说。
回答by Pavan Yalamanchili
I tried the following. Hope this is good enough for what you are doing ?
我尝试了以下方法。希望这对你正在做的事情足够好？
>>> np.vstack((a,b,c))
array([[ 0, 1],
[ 2, 1],
[-1, -1]])
>>> np.vstack((a,b,c)).T
array([[ 0, 2, -1],
[ 1, 1, -1]])
