NumPy copy()
Summary: in this tutorial, you’ll learn how to use the NumPy copy()
method to create a copy of an array rather than a view.
Introduction to the NumPy copy() method
When you slice an array, you get a subarray. The subarray is a view of the original array. In other words, if you change elements in the subarray, the change will be reflected in the original array. For example:
import numpy as npa = np.array([
[1, 2, 3],
[4, 5, 6]
])
b = a[0:, 0:2]
print(b)
b[0, 0] = 0
print(b)
print(a)
Code language: Python (python)
How it works.
First, create a 2D array:
a = np.array([
[1, 2, 3],
[4, 5, 6]
])
Code language: Python (python)
Second, slice the array a and assign the subarray to the variable b:
b = a[0:, 0:2]
Code language: Python (python)
The variable b is:
[[1 2]
[4 5]]
Code language: Python (python)
Third, change the element at index [0,0] in the subarray b to zero and display the variable b:
b[0, 0] = 0
print(b)
Code language: Python (python)
[[0 2]
[4 5]]
Code language: Python (python)
Since b is a view of array a, the change is also reflected in array a:
print(a)
Code language: Python (python)
[[0 2 3]
[4 5 6]]
Code language: Python (python)
The reason numpy creates a view instead of a new array is that it doesn’t have to copy data therefore improving performance.
However, if you want a copy of an array rather than a view, you can use copy()
method. For example:
import numpy as npa = np.array([
[1, 2, 3],
[4, 5, 6]
])
# make a copy
b = a[0:, 0:2].copy()
print(b)
b[0, 0] = 0
print(b)
print(a)
Code language: Python (python)
In this example:
First, call the copy()
method of array a to make a copy of a subarray and assign it to the variable b.
Second, change the element at index [0,0] of the array b, because both arrays are independent, the change doesn’t affect array a.
Summary
- When you slice an array, you’ll get a view of the array.
- Use the
copy()
method to make a copy of an array rather than a view.