np.array 的 np.array 的深拷贝 [英] Deep copy of a np.array of np.array

问题描述

我有一个由不同 numpy 数组组成的 numpy 数组，我想制作这些数组的深层副本.我发现了以下内容:

I have a numpy array of different numpy arrays and I want to make a deep copy of the arrays. I found out the following:

import numpy as np

pairs = [(2, 3), (3, 4), (4, 5)]
array_of_arrays = np.array([np.arange(a*b).reshape(a,b) for (a, b) in pairs])

a = array_of_arrays[:] # Does not work
b = array_of_arrays[:][:] # Does not work
c = np.array(array_of_arrays, copy=True) # Does not work
d = np.array([np.array(x, copy=True) for x in array_of_arrays])

array_of_arrays[0][0,0] = 100
print a[0][0,0], b[0][0,0], c[0][0,0], d[0][0,0]

d 是最好的方法吗?是否有我错过的深度复制功能?与这个由不同大小数组组成的数组中的每个元素进行交互的最佳方式是什么?

Is d the best way to do this? Is there a deep copy function I missed? And what is the best way to interact with each element in this array of different sized arrays?

推荐答案

import numpy as np
import copy

pairs = [(2, 3), (3, 4), (4, 5)]
array_of_arrays = np.array([np.arange(a*b).reshape(a,b) for (a, b) in pairs])

a = copy.deepcopy(array_of_arrays)

请在此处阅读更多相关信息.

Feel free to read up more about this here.

哦，这是最简单的测试用例:

Oh, here is simplest test case:

a[0][0,0]
print a[0][0,0], array_of_arrays[0][0,0]

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