numpy _= & copy

本文介绍numpy的矩阵赋值操作和copy操作

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Demo.py

# =的赋值方式会带有关联性
import numpy as np
a = np.arange(4)
# array([0, 1, 2, 3])
b = a
c = a
d = b
#改变a的第一个值，b、c、d的第一个值也会同时改变。
a[0] = 11
print(a)
# array([11,  1,  2,  3])

#确认b、c、d是否与a相同。
b is a  # True
c is a  # True
d is a  # True

#同样更改d的值，a、b、c也会改变。
d[1:3] = [22, 33]   # array([11, 22, 33,  3])
print(a)            # array([11, 22, 33,  3])
print(b)            # array([11, 22, 33,  3])
print(c)            # array([11, 22, 33,  3])

#copy()的赋值方式没有关联性
b = a.copy()    # deep copy
print(b)        # array([11, 22, 33,  3])
a[3] = 44
print(a)        # array([11, 22, 33, 44])
print(b)        # array([11, 22, 33,  3])

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结果：

[11  1  2  3]
[11 22 33  3]
[11 22 33  3]
[11 22 33  3]
[11 22 33  3]
[11 22 33 44]
[11 22 33  3]