NumPy 复制和视图
在执行函数时,其中一些函数会返回输入数组的副本,而其他一些函数会返回视图。当内容在另一个位置物理存储时,称为 复制 。另一方面,如果提供了相同内存内容的不同视图,我们称之为 视图 。
无复制
简单的赋值不会创建数组对象的副本。相反,它使用原始数组的相同id()来访问它。id()返回Python对象的通用标识符,类似于C中的指针。
此外,任何一方的更改都会反映在另一方上。例如,一个的形状改变,另一个的形状也会改变。
示例
import numpy as np
a = np.arange(6)
print 'Our array is:'
print a
print 'Applying id() function:'
print id(a)
print 'a is assigned to b:'
b = a
print b
print 'b has same id():'
print id(b)
print 'Change shape of b:'
b.shape = 3,2
print b
print 'Shape of a also gets changed:'
print a
它将产生以下输出-
Our array is:
[0 1 2 3 4 5]
Applying id() function:
139747815479536
a is assigned to b:
[0 1 2 3 4 5]
b has same id():
139747815479536
Change shape of b:
[[0 1]
[2 3]
[4 5]]
Shape of a also gets changed:
[[0 1]
[2 3]
[4 5]]
查看或浅复制
NumPy有一个名为 ndarray.view() 的方法,它是一个查看原始数组相同数据的新数组对象。与之前的情况不同,新数组的维度的变化不会改变原始数组的维度。
示例
import numpy as np
# To begin with, a is 3X2 array
a = np.arange(6).reshape(3,2)
print 'Array a:'
print a
print 'Create view of a:'
b = a.view()
print b
print 'id() for both the arrays are different:'
print 'id() of a:'
print id(a)
print 'id() of b:'
print id(b)
# Change the shape of b. It does not change the shape of a
b.shape = 2,3
print 'Shape of b:'
print b
print 'Shape of a:'
print a
它会产生以下输出 −
Array a:
[[0 1]
[2 3]
[4 5]]
Create view of a:
[[0 1]
[2 3]
[4 5]]
id() for both the arrays are different:
id() of a:
140424307227264
id() of b:
140424151696288
Shape of b:
[[0 1 2]
[3 4 5]]
Shape of a:
[[0 1]
[2 3]
[4 5]]
数组的切片会创建一个视图。
示例
import numpy as np
a = np.array([[10,10], [2,3], [4,5]])
print 'Our array is:'
print a
print 'Create a slice:'
s = a[:, :2]
print s
它将产生以下输出 −
Our array is:
[[10 10]
[ 2 3]
[ 4 5]]
Create a slice:
[[10 10]
[ 2 3]
[ 4 5]]
深拷贝
ndarray.copy()函数创建一个深拷贝。它是数组和其数据的完全复制,并且不与原始数组共享。
示例
import numpy as np
a = np.array([[10,10], [2,3], [4,5]])
print 'Array a is:'
print a
print 'Create a deep copy of a:'
b = a.copy()
print 'Array b is:'
print b
#b does not share any memory of a
print 'Can we write b is a'
print b is a
print 'Change the contents of b:'
b[0,0] = 100
print 'Modified array b:'
print b
print 'a remains unchanged:'
print a
它将产生以下输出−
Array a is:
[[10 10]
[ 2 3]
[ 4 5]]
Create a deep copy of a:
Array b is:
[[10 10]
[ 2 3]
[ 4 5]]
Can we write b is a
False
Change the contents of b:
Modified array b:
[[100 10]
[ 2 3]
[ 4 5]]
a remains unchanged:
[[10 10]
[ 2 3]
[ 4 5]]