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numpy下的flatten()函数用法详解

作者：波比12　　发布时间：2021-08-19 04:27:54　

标签：numpy,flatten

flatten是numpy.ndarray.flatten的一个函数，其官方文档是这样描述的：

ndarray.flatten(order='C')

Return a copy of the array collapsed into one dimension.

Parameters:

	order : {‘C', ‘F', ‘A', ‘K'}, optional ‘C' means to flatten in row-major (C-style) order. ‘F' means to flatten in column-major (Fortran- style) order. ‘A' means to flatten in column-major order if a is Fortran contiguous in memory, row-major order otherwise. ‘K' means to flatten a in the order the elements occur in memory. The default is ‘C'.
Returns:	y : ndarray A copy of the input array, flattened to one dimension.

order : {‘C', ‘F', ‘A', ‘K'}, optional

‘C' means to flatten in row-major (C-style) order. ‘F' means to flatten in column-major (Fortran- style) order. ‘A' means to flatten in column-major order if a is Fortran contiguous in memory, row-major order otherwise. ‘K' means to flatten a in the order the elements occur in memory. The default is ‘C'.

Returns:

y : ndarray

A copy of the input array, flattened to one dimension.

即返回一个折叠成一维的数组。但是该函数只能适用于numpy对象，即array或者mat，普通的list列表是不行的。

例子：

1、用于array对象

from numpy import *

>>>a=array([[1,2],[3,4],[5,6]]) ###此时a是一个array对象
>>>a
array([[1,2],[3,4],[5,6]])
>>>a.flatten()
array([1,2,3,4,5,6])

2、用于mat对象

>>> a=mat([[1,2,3],[4,5,6]])
>>> a
matrix([[1, 2, 3],
[4, 5, 6]])<br>>>> a.flatten()<br>matrix([[1, 2, 3, 4, 5, 6]])<br>

3、但是该方法不能用于list对象

>>> a=[[1,2,3],[4,5,6],['a','b']]
[[1, 2, 3], [4, 5, 6], ['a', 'b']]
>>> a.flatten() ###报错
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AttributeError: 'list' object has no attribute 'flatten'

想要list达到同样的效果可以使用列表表达式：

>>> [y for x in a for y in x]
[1, 2, 3, 4, 5, 6, 'a', 'b']

4、用在矩阵

>>> a = [[1,3],[2,4],[3,5]]
>>> a = mat(a)
>>> y = a.flatten()
>>> y
matrix([[1, 3, 2, 4, 3, 5]])
>>> y = a.flatten().A
>>> y
array([[1, 3, 2, 4, 3, 5]])
>>> shape(y)
(1, 6)
>>> shape(y[0])
(6,)
>>> y = a.flatten().A[0]
>>> y
array([1, 3, 2, 4, 3, 5])

来源：https://www.cnblogs.com/itdyb/p/5796834.html

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numpy下的flatten()函数用法详解

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