Python Program on View vs Copy

In this article, we will explore a Python program that delves into the concepts of copying, referencing, and viewing arrays using the NumPy library. Understanding these concepts is crucial when working with arrays, as it directly impacts how changes to one array affect others. The program showcases different methods of creating copies, views, and references to NumPy arrays, providing insights into their behaviour and memory management.

Prerequisites

• Fundamental Python Knowledge (Variables, Data Types, Syntax)
• Basic Familiarity with the NumPy Library (Numerical Computing, Basic Array Operations)

Topic Explanation

This program initiates by importing the NumPy library as ‘np’ and generates an array using the ‘arange()’ function. It embarks on an exploration of multiple methods for copying arrays, encompassing ‘copy()’, ‘view()’, and straightforward reference assignment.

Within this exploration, the article delves into the distinctions between these copying techniques and elucidates how modifications made to one array can propagate to others. Readers gain a profound understanding of array copying mechanisms and their implications, enabling them to make informed choices when manipulating data using NumPy arrays.

Code:

import numpy as np

# Create an array using numpy.arange with values from 0 to 9
myar = np.arange(0,20, 3)

# Use numpy.logical_not to compute the element-wise logical NOT of the array
newar = np.logical_not(myar)

# Print the result of the logical NOT operation
print(newar)

# Create a copy of the original array using the copy() method
ar = myar.copy()

# Print the IDs of the original and copied arrays
print("Id of myarray ", id(myar))
print("Id of copy  ", id(ar))

# Print the elements of the original and copied arrays
print("Elements of MYarray :", myar)
print("Elements of copied array :", ar)

# Modify an element in the original array
myar[2] = 500

# Print the elements of the arrays after the modification
print("-------------After Change----------")
print("Elements of Myarray :", myar)
print("Elements of copied array :", ar)

# Creates a view `ar` on `myar`
ar = myar.view()

# Print the IDs of the original array and its view
print("Id of myarray ", id(myar))
print("Id of view  ", id(ar))

# Print the elements of the original array and its view
print("Elements of MYarray :", myar)
print("Elements of View :", ar)

# Modify an element in the original array
myar[2] = 500

# Print the elements of the arrays after the modification
print("-------------After Change----------")
print("Elements of MYarray :", myar)
print("Elements of View :", ar)

# Assign the reference of the original array to a new variable
ar = myar

# Modify elements in both the original and referenced arrays
ar[3] = 100
myar[6] = 500

# Print the elements of the arrays after the modification
print("-------------After Change----------")
print("My Array(myar): ", myar)
print("Reference(Ar): ", ar)

# Print the IDs of the original array and the reference
print("Id of myarray ", id(myar))
print("Id of reference ", id(ar))