Numpy 简明教程
NumPy - Copies & Views
在执行函数时，其中一些返回输入数组的副本，而另一些返回视图。当内容物理存储在另一个位置时，称为 Copy 。另一方面，如果提供了相同内存内容的不同视图，则我们将其称为 View 。
No Copy
简单赋值不会生成数组对象的副本。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语言中的指针。
此外，一个中的任何更改都会反映在另一个中。例如，改变一个的形状也将改变另一个的形状。
Example
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它将生成如下输出：
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]]View or Shallow Copy
NumPy具有 ndarray.view() 方法，该方法是一个新的数组对象，它查看原始数组的相同数据。与之前的案例不同，新数组尺寸的变化不会改变原始数组的尺寸。
Example
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它将生成如下输出：
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]]数组的分片创建视图。
Deep Copy
ndarray.copy() 函数创建深度副本。它是数组及其数据的完整副本，并且不与原始数组共享。
Example
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它将生成如下输出：
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]]