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python机器学习库numpy---13、数组拷贝

一、总结

一句话总结：

numpy的copy方法是浅拷贝，numpy实现深度拷贝，可以用copy库的deepcopy方法

2、浅拷贝

a = np.arange(4)
# b = a.copy()
b = np.copy(a)
print(a)
print(b)
print(id(a))
print(id(b))

[0 1 2 3]
[0 1 2 3]
1937862920512
1937867598384


3、深拷贝

实现深度拷贝，可以用copy库的deepcopy方法

import copy
a = np.array([1, 'm', [2, 3, 4]], dtype=object)
c = copy.deepcopy(a)

二、数组拷贝

博客对应课程的视频位置：13、数组拷贝-范仁义-读书编程笔记
https://www.fanrenyi.com/video/38/356

1、直接赋值方式

In [1]:

import numpy as np
a = np.arange(4)
b = a
print(a)
print(b)

[0 1 2 3]
[0 1 2 3]

In [2]:

a[0] = 199
b[1:3] = [7,8]
print(a)
print(b)

[199   7   8   3]
[199   7   8   3]

In [3]:

print(id(a))
print(id(b))
print(b is a)

1937866698464
1937866698464
True

2、浅拷贝

In [4]:

a = np.arange(4)
# b = a.copy()
b = np.copy(a)
print(a)
print(b)
print(id(a))
print(id(b))

[0 1 2 3]
[0 1 2 3]
1937862920512
1937867598384

In [5]:

a[0] = 199
b[1:3] = [7,8]
print(a)
print(b)

[199   1   2   3]
[0 7 8 3]

数组里面有对象的时候

In [6]:

a = np.array([1, 'm', [2, 3, 4]], dtype=object)
print(a)

[1 'm' list([2, 3, 4])]

In [7]:

b = np.copy(a)
print(a)
print(b)

[1 'm' list([2, 3, 4])]
[1 'm' list([2, 3, 4])]

In [8]:

b[2][0] = 10
print(a)
print(b)

[1 'm' list([10, 3, 4])]
[1 'm' list([10, 3, 4])]

In [9]:

print(id(a[2]))
print(id(b[2]))

1937867498696
1937867498696

3、深拷贝

实现深度拷贝，可以用copy库的deepcopy方法

In [10]:

import copy
a = np.array([1, 'm', [2, 3, 4]], dtype=object)
c = copy.deepcopy(a)
print(a)
print(c)

[1 'm' list([2, 3, 4])]
[1 'm' list([2, 3, 4])]

In [11]:

c[2][0] = 10
print(a)
print(c)

[1 'm' list([2, 3, 4])]
[1 'm' list([10, 3, 4])]

In [12]:

print(id(a[2]))
print(id(c[2]))

1937852899272
1937861691592

In [ ]: