Numpy - Reverse elements of large array using For loop and Optimization

Last update on December 21 2024 07:37:12 (UTC/GMT +8 hours)

NumPy: Performance Optimization Exercise-20 with Solution

Write a NumPy program that creates a large NumPy array and write a function to reverse its elements using a for loop. Optimize it using NumPy's slicing operations.

Sample Solution:

Python Code:

import numpy as np

# Generate a large 1D NumPy array with random integers
large_array = np.random.randint(1, 1000000, size=1000000)

# Function to reverse the array using a for loop
def reverse_with_loop(arr):
    reversed_array = np.empty_like(arr)
    for i in range(len(arr)):
        reversed_array[i] = arr[len(arr) - 1 - i]
    return reversed_array

# Reverse the array using the for loop method
reversed_with_loop = reverse_with_loop(large_array)

# Reverse the array using NumPy's slicing operations
reversed_with_numpy = large_array[::-1]

# Display first 10 elements of the reversed arrays to verify
print("First 10 elements of the array reversed using for loop:")
print(reversed_with_loop[:10])

print("First 10 elements of the array reversed using NumPy slicing:")
print(reversed_with_numpy[:10])

Output:

First 10 elements of the array reversed using for loop:
[283195 306928 188280 377498 738210 923196 756211 836406 578638 560676]
First 10 elements of the array reversed using NumPy slicing:
[283195 306928 188280 377498 738210 923196 756211 836406 578638 560676]

Explanation:

Importing numpy: We first import the numpy library for array manipulations.
Generating a large array: A large 1D NumPy array with random integers is generated.
Defining the function: A function reverse_with_loop is defined to reverse the array using a for loop.
Reversing with loop: The array is reversed using the for loop method.
Reversing with numpy: The array is reversed using NumPy's slicing operations.
Displaying results: The first 10 elements of the reversed arrays from both methods are printed out to verify correctness.

Python-Numpy Code Editor: