numpy数组合并

In [3]: import numpy as np
...: a = np.array([[1,2,3],[4,5,6]])
...: b = np.array([[6,5,6],[7,8,9]])
...: np.stack((a,b),axis=0)
...:
Out[3]:
array([[[1, 2, 3],
[4, 5, 6]],

[[6, 5, 6],
[7, 8, 9]]])

In [4]: np.stack((a,b),axis=0).shape
Out[4]: (2, 2, 3)

In [5]: np.stack((a,b),axis=1)
Out[5]:
array([[[1, 2, 3],
[6, 5, 6]],

[[4, 5, 6],
[7, 8, 9]]])

In [6]: np.stack((a,b),axis=1).shape
Out[6]: (2, 2, 3)

In [7]: np.stack((a,b),axis=2)
Out[7]:
array([[[1, 6],
[2, 5],
[3, 6]],

[[4, 7],
[5, 8],
[6, 9]]])

In [8]: np.stack((a,b),axis=2).shape
Out[8]: (2, 3, 2)

In [9]: np.vstack((a,b))
Out[9]:
array([[1, 2, 3],
[4, 5, 6],
[6, 5, 6],
[7, 8, 9]])

In [10]: np.row_stack((a,b))
Out[10]:
array([[1, 2, 3],
[4, 5, 6],
[6, 5, 6],
[7, 8, 9]])

In [11]: np.hstack((a,b))
Out[11]:
array([[1, 2, 3, 6, 5, 6],
[4, 5, 6, 7, 8, 9]])

In [12]: np.column_stack((a,b))
Out[12]:
array([[1, 2, 3, 6, 5, 6],
[4, 5, 6, 7, 8, 9]])