如何将numpy数组转换为元组 [英] how to convert numpy array into tuple

查看:2184
本文介绍了如何将numpy数组转换为元组的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!

问题描述

我需要像这样转换数组:

I need to convert array like this:

 [[1527 1369   86   86]
  [ 573  590  709  709]
  [1417 1000   68   68]
  [1361 1194   86   86]]

要这样:

    [(726, 1219, 1281, 664),
    (1208, 1440, 1283, 1365), 
    (1006, 1483, 1069, 1421),
    (999, 1414, 1062, 1351),]

我尝试直接将convert转换为元组,但是得到了:

I tried using convert diretly to tuple but got this:

         ( array([1527, 1369,   86,   86], dtype=int32), 
           array([573, 590, 709, 709], dtype=int32),
           array([1417, 1000,   68,   68], dtype=int32), 
           array([1361, 1194,   86,   86], dtype=int32))
           (array([701, 899, 671, 671], dtype=int32),)      

推荐答案

数组方法tolist是将数组转换为列表的简便方法.它可以正确处理多个尺寸:

The array method tolist is a easy and fast way of converting an array to a list. It handles multiple dimensions correctly:

In [92]: arr = np.arange(12).reshape(3,4)
In [93]: arr
Out[93]: 
array([[ 0,  1,  2,  3],
       [ 4,  5,  6,  7],
       [ 8,  9, 10, 11]])
In [94]: arr.tolist()
Out[94]: [[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]]

在大多数情况下,例如列表列表与元组列表或元组列表一样好.它们仅在可变性方面有所不同.

For most purposes such as list of lists is just as good as a list of tuples, or tuple of tuples. They differ only in mutability.

但是如果您必须有一个元组,则列表理解可以很好地进行转换.

But if you must have a tuples, a list comprehension does the conversion nicely.

In [95]: [tuple(x) for x in arr.tolist()]
Out[95]: [(0, 1, 2, 3), (4, 5, 6, 7), (8, 9, 10, 11)]

替代的[tuple(x) for x in arr]有点慢,因为它在数组而不是列表上进行迭代.它也会产生不同的结果-尽管您必须检查元组元素的type才能看到结果.

An alternative [tuple(x) for x in arr] is a bit slower, because it is iterating on the array rather than on a list. It also produces a different result - though you have to examine the type of the tuple elements to see that.

我强烈建议从tolist方法开始,然后再进行任何列表以进行元组转换.

I strongly recommend starting with the tolist method, and doing any list to tuple conversions after.

这篇关于如何将numpy数组转换为元组的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持IT屋!

查看全文
登录 关闭
扫码关注1秒登录
发送“验证码”获取 | 15天全站免登陆