7.11 Views: Shallow Copies

  • Views “see” the data in other objects, rather than having their own copies of the data
  • Views are shallow copies *array method view returns a new array object with a view of the original array object’s data
In [1]:
import numpy as np
In [2]:
numbers = np.arange(1, 6)
In [3]:
numbers
Out[3]:
array([1, 2, 3, 4, 5])
In [4]:
numbers2 = numbers.view()
In [5]:
numbers2
Out[5]:
array([1, 2, 3, 4, 5])
  • Use built-in id function to see that numbers and numbers2 are different objects
In [6]:
id(numbers)
Out[6]:
4431803056
In [7]:
id(numbers2)
Out[7]:
4430398928
  • Modifying an element in the original array, also modifies the view and vice versa
In [8]:
numbers[1] *= 10
In [9]:
numbers2
Out[9]:
array([ 1, 20,  3,  4,  5])
In [10]:
numbers
Out[10]:
array([ 1, 20,  3,  4,  5])
In [11]:
numbers2[1] /= 10
In [12]:
numbers
Out[12]:
array([1, 2, 3, 4, 5])
In [13]:
numbers2
Out[13]:
array([1, 2, 3, 4, 5])

Slice Views

  • Slices also create views
In [14]:
numbers2 = numbers[0:3]
In [15]:
numbers2
Out[15]:
array([1, 2, 3])
In [16]:
id(numbers)
Out[16]:
4431803056
In [17]:
id(numbers2)
Out[17]:
4451350368
  • Confirm that numbers2 is a view of only first three numbers elements
In [18]:
numbers2[3]

------------------------------------------------------------------------
IndexError                             Traceback (most recent call last)
<ipython-input-18-83bd44fddddf> in <module>
----> 1 numbers2[3]

IndexError: index 3 is out of bounds for axis 0 with size 3
  • Modify an element both arrays share to show both are updated
In [19]:
numbers[1] *= 20
In [20]:
numbers
Out[20]:
array([ 1, 40,  3,  4,  5])
In [21]:
numbers2
Out[21]:
array([ 1, 40,  3])

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