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對numpy.append()里的axis的用法詳解

 更新時間:2018年06月28日 14:33:37   作者:我愛阿鑫  
今天小編就為大家分享一篇對numpy.append()里的axis的用法詳解,具有很好的參考價值,希望對大家有所幫助。一起跟隨小編過來看看吧

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):

簡答來說,就是arr和values會重新組合成一個新的數(shù)組,做為返回值。而axis是一個可選的值

當axis無定義時,是橫向加成,返回總是為一維數(shù)組!

 Examples
 --------
 >>> np.append([1, 2, 3], [[4, 5, 6], [7, 8, 9]])
 array([1, 2, 3, 4, 5, 6, 7, 8, 9])

當axis有定義的時候,分別為0和1的時候。(注意加載的時候,數(shù)組要設置好,行數(shù)或者列數(shù)要相同。不然會有error:all the input array dimensions except for the concatenation axis must match exactly)

當axis為0時,數(shù)組是加在下面(列數(shù)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.]]

當axis為1時,數(shù)組是加在右邊(行數(shù)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.]]

以上這篇對numpy.append()里的axis的用法詳解就是小編分享給大家的全部內(nèi)容了,希望能給大家一個參考,也希望大家多多支持腳本之家。

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