【下载文档:  对numpy.append()里的axis的用法详解.txt 】

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对numpy.append()里的axis的用法详解
如下所示：
def append(arr, values, axis=None):
"""
Append values to the end of an array.
Parameters
----------
arr : array_like
Values are appended to a copy of this array.
values : array_like
These values are appended to a copy of `arr`. It must be of the
correct shape (the same shape as `arr`, excluding `axis`). If
`axis` is not specified, `values` can be any shape and will be
flattened before use.
axis : int, optional
The axis along which `values` are appended. If `axis` is not
given, both `arr` and `values` are flattened before use.
Returns
-------
append : ndarray
A copy of `arr` with `values` appended to `axis`. Note that
`append` does not occur in-place: a new array is allocated and
filled. If `axis` is None, `out` is a flattened array.
numpy.append(arr, values, axis=None):
简答来说，就是arr和values会重新组合成一个新的数组，做为返回值。而axis是一个可选的值
当axis无定义时，是横向加成，返回总是为一维数组！
Examples
--------
>>> np.append([1, 2, 3], [[4, 5, 6], [7, 8, 9]])
array([1, 2, 3, 4, 5, 6, 7, 8, 9])
当axis有定义的时候，分别为0和1的时候。（注意加载的时候，数组要设置好，行数或者列数要相同。不然会有error：all the input array dimensions except for the concatenation axis must match exactly）
当axis为0时，数组是加在下面（列数要相同）：
import numpy as np
aa= np.zeros((1,8))
bb=np.ones((3,8))
c = np.append(aa,bb,axis = 0)
print(c)
[[ 0. 0. 0. 0. 0. 0. 0. 0.]
[ 1. 1. 1. 1. 1. 1. 1. 1.]
[ 1. 1. 1. 1. 1. 1. 1. 1.]
[ 1. 1. 1. 1. 1. 1. 1. 1.]]
当axis为1时，数组是加在右边（行数要相同）：
import numpy as np
aa= np.zeros((3,8))
bb=np.ones((3,1))
c = np.append(aa,bb,axis = 1)
print(c)
[[ 0. 0. 0. 0. 0. 0. 0. 0. 1.]
[ 0. 0. 0. 0. 0. 0. 0. 0. 1.]
[ 0. 0. 0. 0. 0. 0. 0. 0. 1.]]
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